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Table of contents :
Front Cover
Atomic Force Microscopy for Nanoscale Biophysics
Copyright Page
Contents
About the author
Preface
1 Fundamentals and methods of atomic force microscopy for biophysics
1.1 Background of atomic force microscopy for biophysics
1.2 Atomic force microscopy topographical imaging modes
1.2.1 Basic principles
1.2.2 Contact mode
1.2.3 Noncontact mode
1.2.4 Tapping mode
1.2.5 Peak force tapping mode
1.3 Atomic force microscopy force spectroscopy techniques
1.3.1 Single-cell mechanical measurement
1.3.2 Single-cell force spectroscopy
1.3.3 Single-molecule force spectroscopy
1.4 High-speed atomic force microscopy
1.5 Topography and recognition imaging mode atomic force microcopy
References
2 Imaging and force detection of single deoxyribonucleic acid molecules by atomic force microscopy
2.1 Background
2.2 Sample preparation methods
2.3 Topographical imaging of single DNA molecules and events
2.4 Time-lapse imaging of individual DNA molecular dynamics
2.5 Extracting the persistence length of DNA molecules from atomic force microscopy images
2.6 Mechanically unzipping single DNA molecules by atomic force microscopy force spectroscopy
2.7 Probing individual DNA behaviors on DNA origami nanostructures
2.8 Summary
References
3 High-resolution imaging and force spectroscopy of single membrane proteins by atomic force microscopy
3.1 Background
3.2 Topographical imaging of single native membrane proteins
3.3 Unfolding mechanics of individual native membrane proteins
3.4 Observing the dynamics of single membrane proteins by high-speed atomic force microscopy
3.5 Multiparametric atomic force microscopy imaging of single membrane proteins
3.6 Topography and recognition imaging of single membrane proteins
3.7 Summary
References
4 Characterizing the nanostructures and mechanical properties of hydrogels by atomic force microscopy
4.1 Background
4.2 Nanostructures and nanomechanics of natural plant hydrogels
4.3 Characterizations of biopolymeric hydrogels inspired by carnivorous plant mucilage
4.4 Imaging and mechanical analysis of peptide-assembled nanofibrillar hydrogel
4.5 Probing the mechanical cues in cell–hydrogel interactions
4.6 Summary
References
5 Detecting the behaviors of single viruses by atomic force microscopy
5.1 Background
5.2 Imaging the fine structures of single viruses
5.3 Nanoindentation for mechanical measurements and manipulations of single viruses
5.4 Single-virus force spectroscopy for probing viral binding affinity
5.5 Multiparametric atomic force microscopy imaging of virus–cell interactions
5.6 Visualizing individual viral dynamics by high-speed atomic force microscopy
5.7 Summary
References
6 Imaging and mechanical analysis of single native exosomes by atomic force microscopy
6.1 Background
6.2 Exosome isolation and immobilization
6.3 Imaging single native exosomes in liquid
6.4 Measuring the mechanics of single native exosomes
6.5 Multiparametric imaging of single native exosomes
6.6 Single-molecule force spectroscopy on single exosomes
6.7 Summary
References
7 Nanoscale imaging and force probing of single microbial cells by atomic force microscopy
7.1 Background
7.2 Immobilization methods of living microbial cells for atomic force microscopy imaging
7.3 Visualizing the nanostructures and their dynamics of living microbial cells by atomic force microscopy
7.4 Measuring the mechanical properties of single living microbial cells by atomic force microscopy
7.5 Single-molecule force spectroscopy and single-cell force spectroscopy of microbial adhesion
7.6 Multiparametric atomic force microscopy imaging of single living microbial cells
7.7 Atomic force microscopy cantilever as a nanomechanical sensor for monitoring microbial activities
7.8 Summary
References
8 Investigating the structures and mechanics of single animal cells by atomic force microscopy
8.1 Background
8.2 Imaging the surface structures and their dynamics of single living adherent animal cells
8.3 Measuring the mechanical properties of single living adherent animal cells
8.4 Probing the molecular activities on the surface of single adherent cells
8.5 Visualizing the surface structures and their dynamics of single living suspended animal cells
8.6 Detecting the mechanical cues involved in the activities of lymphoma cells
8.7 Probing the molecular activities on the surface of primary lymphoma cells
8.8 Summary
References
9 Characterizing the extracellular matrix for regulating cell behaviors by atomic force microscopy
9.1 Background
9.2 Detecting the mechanical properties of decellularized extracellular matrix
9.3 Investigating the structures and mechanics of basement membranes
9.4 In situ imaging of cell culture medium-forming nanogranular surface for cell growth
9.5 Hierarchical micro-/nanotopography of extracellular matrix for tuning cellular structures and mechanics
9.6 Summary
References
10 Combining atomic force microscopy with complementary techniques for biophysics
10.1 Background
10.2 Scanning near-field ultrasound holography
10.3 Fluidic force microscopy
10.4 Combining atomic force microscopy with micropipette
10.5 Combining atomic force microscopy with fluidic environment
10.6 Summary
References
11 Future perspectives of atomic force microscopy for biophysics
References
Index
Back Cover
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ATOMIC FORCE MICROSCOPY FOR NANOSCALE BIOPHYSICS

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ATOMIC FORCE MICROSCOPY FOR NANOSCALE BIOPHYSICS From Single Molecules to Living Cells

MI LI Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, P.R. China

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2023 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-95360-3

For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Stacy Masucci Acquisitions Editor: Michelle Fisher Editorial Project Manager: Pat Gonzalez Production Project Manager: Swapna Srinivasan Cover Designer: Mark Rogers Typeset by MPS Limited, Chennai, India

Contents

About the author Preface

ix xi

1. Fundamentals and methods of atomic force microscopy for biophysics

1

1.1 Background of atomic force microscopy for biophysics 1.2 Atomic force microscopy topographical imaging modes 1.3 Atomic force microscopy force spectroscopy techniques 1.4 High-speed atomic force microscopy 1.5 Topography and recognition imaging mode atomic force microcopy References

1 5 19 31 33 35

2. Imaging and force detection of single deoxyribonucleic acid molecules by atomic force microscopy

43

2.1 2.2 2.3 2.4 2.5

Background Sample preparation methods Topographical imaging of single DNA molecules and events Time-lapse imaging of individual DNA molecular dynamics Extracting the persistence length of DNA molecules from atomic force microscopy images 2.6 Mechanically unzipping single DNA molecules by atomic force microscopy force spectroscopy 2.7 Probing individual DNA behaviors on DNA origami nanostructures 2.8 Summary References

58 61 66 68

3. High-resolution imaging and force spectroscopy of single membrane proteins by atomic force microscopy

75

3.1 3.2 3.3 3.4

Background Topographical imaging of single native membrane proteins Unfolding mechanics of individual native membrane proteins Observing the dynamics of single membrane proteins by high-speed atomic force microscopy 3.5 Multiparametric atomic force microscopy imaging of single membrane proteins

v

43 44 47 52 55

75 77 84 88 91

vi

Contents

3.6 Topography and recognition imaging of single membrane proteins 3.7 Summary References

4. Characterizing the nanostructures and mechanical properties of hydrogels by atomic force microscopy 4.1 Background 4.2 Nanostructures and nanomechanics of natural plant hydrogels 4.3 Characterizations of biopolymeric hydrogels inspired by carnivorous plant mucilage 4.4 Imaging and mechanical analysis of peptide-assembled nanofibrillar hydrogel 4.5 Probing the mechanical cues in cellhydrogel interactions 4.6 Summary References

5. Detecting the behaviors of single viruses by atomic force microscopy

94 97 99

105 105 108 116 122 127 130 131

135

5.1 Background 5.2 Imaging the fine structures of single viruses 5.3 Nanoindentation for mechanical measurements and manipulations of single viruses 5.4 Single-virus force spectroscopy for probing viral binding affinity 5.5 Multiparametric atomic force microscopy imaging of viruscell interactions 5.6 Visualizing individual viral dynamics by high-speed atomic force microscopy 5.7 Summary References

143 147 150 153 155 156

6. Imaging and mechanical analysis of single native exosomes by atomic force microscopy

161

6.1 Background 6.2 Exosome isolation and immobilization 6.3 Imaging single native exosomes in liquid 6.4 Measuring the mechanics of single native exosomes 6.5 Multiparametric imaging of single native exosomes 6.6 Single-molecule force spectroscopy on single exosomes 6.7 Summary References

7. Nanoscale imaging and force probing of single microbial cells by atomic force microscopy 7.1 Background 7.2 Immobilization methods of living microbial cells for atomic force microscopy imaging

135 139

161 164 168 172 174 177 179 182

187 187 191

Contents

7.3 Visualizing the nanostructures and their dynamics of living microbial cells by atomic force microscopy 7.4 Measuring the mechanical properties of single living microbial cells by atomic force microscopy 7.5 Single-molecule force spectroscopy and single-cell force spectroscopy of microbial adhesion 7.6 Multiparametric atomic force microscopy imaging of single living microbial cells 7.7 Atomic force microscopy cantilever as a nanomechanical sensor for monitoring microbial activities 7.8 Summary References

8. Investigating the structures and mechanics of single animal cells by atomic force microscopy 8.1 Background 8.2 Imaging the surface structures and their dynamics of single living adherent animal cells 8.3 Measuring the mechanical properties of single living adherent animal cells 8.4 Probing the molecular activities on the surface of single adherent cells 8.5 Visualizing the surface structures and their dynamics of single living suspended animal cells 8.6 Detecting the mechanical cues involved in the activities of lymphoma cells 8.7 Probing the molecular activities on the surface of primary lymphoma cells 8.8 Summary References

9. Characterizing the extracellular matrix for regulating cell behaviors by atomic force microscopy 9.1 9.2 9.3 9.4

Background Detecting the mechanical properties of decellularized extracellular matrix Investigating the structures and mechanics of basement membranes In situ imaging of cell culture medium-forming nanogranular surface for cell growth 9.5 Hierarchical micro-/nanotopography of extracellular matrix for tuning cellular structures and mechanics 9.6 Summary References

10. Combining atomic force microscopy with complementary techniques for biophysics 10.1 Background 10.2 Scanning near-field ultrasound holography 10.3 Fluidic force microscopy

vii 193 200 203 207 210 212 213

219 219 222 229 241 246 248 258 261 262

269 269 272 275 279 281 284 285

289 289 291 293

viii

Contents

10.4 Combining atomic force microscopy with micropipette 10.5 Combining atomic force microscopy with fluidic environment 10.6 Summary References

297 301 305 306

11. Future perspectives of atomic force microscopy for biophysics

309

References

313

Index

315

About the author Mi Li, PhD, is a full professor at Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China. Mi Li received his BE and ME degrees from Huazhong University of Science and Technology, Wuhan, China, in 2006 and 2008, respectively. He received his PhD degree from Shenyang Institute of Automation, Chinese Academy of Sciences in 2015, after which he continues his academic career at Shenyang Institute of Automation, Chinese Academy of Sciences until now. From September 2016 to August 2017, he studied as a visiting scholar at The Ohio State University, Columbus, United States. From October 2020 to March 2021 he studied as a visiting professor at ETH Zurich, Zurich, Switzerland. Since 2009 Mi Li has been engaged in the studies of atomic force microscopy (AFM) and its biomedical applications to reveal the biophysical and biomechanical cues in life activities and pathological processes. Mi Li has published more than 70 peer-reviewed journal papers in the field of AFM as the first or corresponding author. He has also won the National Natural Science Foundation of China for Excellent Young Scholars (2019), the IEEE Senior Member (2020), the Outstanding Doctoral Dissertation Award of Chinese Academy of Sciences (2016), the Outstanding Doctoral Dissertation Award of Chinese Association of Automation (2017), and the Springer Theses (2018).

ix

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Preface Atomic force microscopy (AFM) is a revolutionary and powerful tool for imaging the topographical structures and detecting the mechanical properties of living biological systems in their native states under aqueous conditions with unprecedented spatiotemporal resolution, opening up the door to an exciting new world of biophysics. AFM allows experimental access to characterizing the behaviors and activities of individuals in diverse biological systems ranging from single molecules to living cells as well as tissue and organ specimens, which significantly complements the results obtained by traditional ensemble-averaged assays and offers novel possibilities to understand cellular and molecular heterogeneity. The wide applications of AFM in life sciences considerably improve our understanding of the underlying mechanisms guiding various life activities and pathological processes from the perspective of biomechanics, which promote developing novel methods for detecting, monitoring, and treating diseases and contribute much to the field of mechanobiology. Particularly, AFM has been rapidly evolving since its invention, and the instrumental functions and performances of AFM continue to advance, which make AFM more appealing to researchers and subsequently further benefit the practical applications in biomedicine. Besides, AFM is highly compatible and has been integrated with various complementary techniques to enable investigations of more biological issues, which strikingly helps to decipher the mysteries of life from additional perspectives. The purpose of this book is to summarize the state-of-the-art of AFM in biophysics, to show what AFM can do for life sciences and how AFM can be used to address various biological issues, and explore the limitations and future developments of AFM for biomedical applications. The contents of the book are organized into 11 chapters, going from basic principles and methods to applications in diverse biological systems and future perspectives. In Chapter 1, the fundamentals of AFM techniques for biomedical applications are described. The applications of AFM in characterizing the fine structures and conformational dynamics as well as mechanics of single DNA molecules are presented in Chapter 2. In Chapter 3, the studies of single membrane proteins by AFM high-resolution imaging and force spectroscopy are surveyed. Subsequently, applications of AFM in resolving the nanostructures and mechanics of hydrogels for revealing the underlying mechanisms

xi

xii

Preface

guiding the self-assembly of hydrogels are shown in Chapter 4. In Chapter 5, applications of AFM in the studies of single viruses to promote the field of physical virology are presented. In Chapter 6, utilizing AFM to image the structures and measure the mechanical properties of single native exosomes in liquids is described. Next, applications of AFM in detecting the nanoscale activities of single living microbial cells are shown in Chapter 7. Utilizing AFM to investigate the structures and mechanical properties as well as molecular activities of single animal cells including primary cells isolated from clinical patients are described in Chapter 8. After that, applications of AFM in characterizing the structures and mechanics of extracellular matrix for tuning cellular behaviors are presented in Chapter 9. Combining AFM with complementary techniques for biophysics is shown in Chapter 10, and finally, the future perspectives for AFM-based biophysics are provided in Chapter 11. I wish to sincerely thank Elsevier/Academic Press for giving me the opportunity to write this book, and I hope that this book will interest students and researchers who are engaged in the studies of utilizing AFM to address biological issues and will inspire further activities in the field of AFM-based mechanobiology. I would like to express my sincere gratitude to Shenyang Institute of Automation, Chinese Academy of Sciences, for providing firm and long-term support to my studies. I would like to thank my students (Yaqi Feng, Jiajia Wei, and Yanqi Yang) for preparing the ancillary video materials of AFM experiments. I deeply appreciate the continuous funding from National Natural Science Foundation of China (62273330, 61922081, 61873258, 61503372), and I am also thankful for the supports from the Key Research Program of Frontier Sciences Chinese Academy of Sciences (ZDBS-LY-JSC043) and from the LiaoNing Revitalization Talents Program (XLYC1907072). Finally, I would like to thank my wife, Jing Gao, for her constant and patient supports. Mi Li

C H A P T E R

1 Fundamentals and methods of atomic force microscopy for biophysics

1.1 Background of atomic force microscopy for biophysics Single-cell analysis is an emerging and promising area expected to remarkably benefit unveiling the underlying mechanisms guiding life activities. A cell is the fundamental structural and functional unit of living organisms. The study of the structure, function, and behavior of cells is critical for seeking the answers to the questions of what life is and how it works [1], which has been highlighted long ago by the pioneering cell biologist E. B. Wilson in his famous textbook The Cell in Development and Heredity: “The key to every biological problem must finally be sought in the cell, for every living organism is, or at some time has been, a cell” [2,3]. So far much of our understanding of cellular physiological and pathological activities has come from traditional ensemble-averaged assays [4], which reflect the dominant biological traits in a population and assume that an average response is representative of a typical cell within a population, whereas cell-to-cell differences are usually obscured [5,6]. Heterogeneity between individual cells is an intrinsic feature of dynamic cellular processes, including signaling, transcription, and cell fate [7]. Even for genetically identical cells that have been cultured under the same conditions, cellular heterogeneity can also be observed [8]. The basis of cellular heterogeneity is a field of active investigation, and multiple mechanisms are thought to contribute to this phenomenon, such as stochastic molecular interactions, phenotypic differences, stochastic transcriptional bursting, and so on [911]. Cellular heterogeneity represents one of the greatest challenges in tumor

Atomic Force Microscopy for Nanoscale Biophysics DOI: https://doi.org/10.1016/B978-0-323-95360-3.00009-5

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© 2023 Elsevier Inc. All rights reserved.

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1. Fundamentals and methods of atomic force microscopy for biophysics

therapeutics [12,13]. For tumors, extensive genetic and phenotypic variations have been observed, including intertumoral heterogeneity (variations between tumors of different tissue and cell types), intratumoral heterogeneity (subclonal diversity within a tumor), and intercellular heterogeneity (cellular variations within a subclonal population of tumor cells) [14], which significantly add the complexity of tumors and have been shown to be closely associated with the therapeutic responses and drug resistance as well as disease relapse of tumors [15,16]. Single-cell analysis is therefore essential to understand the causes and consequences of cellular heterogeneity and how it changes during the physiological or pathological processes [17]. In fact, there have been significant advances in the development of single-cell biochemical analysis tools in the past years, which are able to detect diverse components of individual cells, including DNAs, RNAs, proteins and metabolites [1820]. The practical applications of single-cell biochemical analysis methods have significantly promoted our understanding of tumor heterogeneity, including the identification of metastasis-initiating cells [21], single-cell pathology landscape of breast cancer [22], revealing heterogeneity of intratumoral T cell states for cancer immunotherapy [23], discovering novel cell types of tumor microenvironment [24], and so on, showing the great potentials of single-cell analysis in addressing biological issues from the perspective of individual cells. It is increasingly evident in the communities of life sciences that mechanical cues play a fundamental role in regulating cellular activities. Cell life is not only a chemical process but also a mechanical one [25]. Cells generate, transmit and respond to forces through an intricate network of mechanical components, resulting in cell movement and shape change, as well as altered signaling, modulated expression and even genomic damage [26]. The mechanical interactions between the cell and extracellular matrix (ECM) often yield unique biochemical and mechanical properties of the cell [27]. For example, studies have shown that substrates with a stiffness similar to that of the brain (0.11 kPa), muscle (817 kPa), or bone tissues (2540 kPa) guide the stem cells to differentiate into neurons, myoblasts, and osteoblasts, respectively [28]. Particularly, changes in the biomechanical and biophysical properties of cells and subcellular structures influence, and are influenced by, the onset and progression of human diseases such as cancer [29]. Numerous studies have shown that cancerous cells are softer and more deformable than healthy cells due to a disorganized and less filamentous cytoskeletal network, which helps the malignant cells to squeeze through the narrow constrictions of the ECM and the tight endothelial cellcell junctions [3032]. In malaria disease, researchers have shown that progression through the parasite development stages (ring stage, trophozoite stage, schizont stage) leads to a considerable stiffening and decreased deformability of the host red blood

Atomic Force Microscopy for Nanoscale Biophysics

1.1 Background of atomic force microscopy for biophysics

3

cells compared to healthy ones [3335]. The knowledge of cell mechanics, combined with previously known biochemical cues, has greatly advanced our understanding of related diseases [36] and has inspired new therapeutic approaches for practical applications. In recent years researchers have been exploring targeting the mechanical cues involved in diverse human diseases (cancer, fibrosis, and cardiovascular disease) as a therapeutic intervention [37] and various agents that interfere with either the mechanical properties of the tissue or signaling responsive to changes in the tissue mechanics have been developed for preclinical and clinical trials [38], offering new opportunities for treating human diseases. Biointerfaces are surfaces at which tissues, microorganisms, cells, viruses or biomolecules make contact with other natural or synthetic materials, and observing and manipulating the interactions that occur at biointerfaces is critical for understanding the behaviors of biological systems nearly at all levels [39]. We know that in vivo cells are embedded within the fibrous ECM to form tissues and then many tissues are organized together to constitute organs [40]. The ECM provides not only essential physical scaffolding for the cellular constituents but also initiates crucial biochemical and biomechanical cues that are required for tissue morphogenesis, differentiation and homeostasis [41]. The resident cells of each tissue are responsible for and responsive to the ECM in a process referred to as dynamic reciprocity: cells modify their secreted ECM products in response to various stimuli (e.g., mechanical cues, oxygen and nutrient concentration), and in turn, the ECM sends mechanical and biochemical signals to resident cells through the engagement of cell surface receptors (e.g., integrins, ion channels [42]) and the subsequent activation of intracellular signaling cascades and ultimately the changes in gene expression and cell phenotype [43]. Abnormal interactions between cells and ECM are often accompanied by pathological changes in living organisms such as tumors [44] which leverages ECM remodeling to create a microenvironment that promotes tumorigenesis and metastasis [45] (e.g., thickening and linearization of ECM fibers are common in cancers, which facilitate the migration and progression of tumor cells [46]). At the level of individual cells, cells interact with their environments via their surfaces whose functions are mediated by the structurally complex and dynamic assembly of specific carbohydrates, proteins, lipids and other macromolecules distributed on cell surfaces [47]. Cell surface molecules regulate many essential cellular processes, including cell adhesion, tissue development, cellular communication, inflammation, tumor metastasis, and microbial infection [48], and therefore probing the molecular activities and behaviors on the cell surface is of remarkable significance for understanding the underlying mechanisms guiding cellular processes. At the level of individual viruses, in order to gain access to the cell interior to deliver the viral

Atomic Force Microscopy for Nanoscale Biophysics

4

1. Fundamentals and methods of atomic force microscopy for biophysics

genome to the cell cytoplasm, viruses attach to the host cells via the specific binding interactions between molecules on the surface of the virus and receptors (proteins, carbohydrates, or lipids) on the cell surface [49]. Consequently, investigating the structures and properties as well as functions of biointerfaces is particularly meaningful for revealing the underpinnings of life processes. The advent of atomic force microscopy (AFM) provides a revolutionary, powerful, and multifunctional tool for investigating the structures and mechanics of living biological systems at biointerfaces under aqueous conditions with high resolution. AFM uses a sharp tip mounted at the end of a soft cantilever to raster scan the surface of specimens immobilized on stiff substrates, during which a laser beam is used to detect the deflections of the cantilever to sense the interaction forces between tip atoms and specimen surface atoms and a piezoelectric actuator drives the tip move vertically to maintain the interaction forces constant [50], yielding the three-dimensional topographical images of the specimen surface. In essence, the spatial resolution of AFM is determined by the contact area between the AFM tip and sample surface, which typically contains several factors, including probe geometry, tip sharpness, sticking of sample to AFM tip, mobility of the sample (or the substructures on the surface of the sample), mobility of substrate, and so on, and historically the spatial resolution of AFM on biological samples in liquids is about 1 nm at best [51]. Recently, a new technique called localization AFM (LAFM) is developed by Heath et al. [52], which increases the spatial resolution of AFM to 0.1 nm on biomolecules in a buffer solution. AFM is able to not only visualize the native structures of living specimens in near-physiological conditions without the need for chemical treatments (e.g., fixation, staining, labeling) [53], but also can measure the mechanical properties of specimens and quantify the molecular forces at force spectroscopy mode [54,55], making AFM particularly suited for applications in life sciences. Compared with other typical high-resolution imaging and force measurement methods used in molecular and cell biology, AFM has unique advantages. The spatial resolution of conventional optical microscopy is limited to about 200300 nm due to the effect of Abbe diffraction, making it impossible to visualize cellular structures and machineries as well as their assembly dynamics in nanoscopic details [56]. The development of superresolution optical microscopy [e.g., stimulated emission microscopy (STED), photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM)] shatters this limit and achieves the spatial resolution of 20 nm [57], enabling visualization of previously invisible molecular details in biological systems [58]. However, super-resolution optical microscopy requires the fluorescent labeling of target molecules, and strictly speaking the results only reflect the behaviors of the fluorescein, not

Atomic Force Microscopy for Nanoscale Biophysics

1.2 Atomic force microscopy topographical imaging modes

5

of the target molecules. Besides, fluorescent labeling inevitably reduces the fidelity of the target molecules and may affect the physiological activities of molecules and cells [59]. Electron microscopy [including scanning electron microscopy (SEM) and transmission electron microscopy (TEM)] is able to observe single molecules with high spatial resolution, but it requires the dehydration of the samples which can cause damage to samples [60,61]. Though cryo-electron microscopy (cryo-EM) is able to resolve the structures of proteins and macromolecular complexes at near-atomic resolution (,0.4 nm) without the need for crystals [62], it only provides static snapshots of molecules and is unable to capture the dynamics of molecules. Optical tweezers and magnetic tweezers are widely used methods for single-cell and single-molecule force assays [6368], but they cannot obtain the structural information of samples while AFM is able to simultaneously perform topographical imaging and force measurements on samples. The detailed comparisons between AFM and the other techniques described above are summarized in Table 1.1. The excellent merits of AFM have attracted the tremendous attention of researchers from various disciplines (e.g., biology, chemistry, physics, and engineering) to utilize AFM to probe cellular and molecular activities taking place at biointerfaces. In the past decades, AFM has achieved great success in characterizing the structures and mechanical cues of diverse biological systems with the unprecedented spatiotemporal resolution, yielding numerous insights into how mechanical forces regulate physiological and pathological behaviors at the single-cell and single-molecule levels. Particularly, the instrumental performances and functions of AFM have been being improved continuously since its invention, which has considerably promoted the wide applications of AFM, offering novel possibilities for unveiling the underlying mechanisms guiding life processes and human diseases from the perspective of biomechanics and biophysics.

1.2 Atomic force microscopy topographical imaging modes 1.2.1 Basic principles In order to understand the principles of AFM imaging, we need to discard the notions of conventional microscopy (optical microscopy, electron microscopy), since AFM does not have any lenses. Instead, AFM uses a tip mounted on a soft cantilever to feel the sample surface, much like a blind person feels a person’s face with their fingers and then forms a mental image of the person’s face [69]. As shown in Fig. 1.1A, an AFM is commonly composed of five parts, including a soft microcantilever with a sharp tip mounted at its end (the cantilever/tip assembly is often referred to as the probe), a piezoelectric tube actuator, an optical lever system, a

Atomic Force Microscopy for Nanoscale Biophysics

TABLE 1.1 biology.

Comparisons of representative high-resolution imaging and force measurement tools for applications in molecular and cell

Techniques/ features

Atomic force microscopy

General descriptions

The deflection of a cantilever is measured by a laser beam and a position-sensing detector to obtain force and displacement for both topographical imaging and force spectroscopy. For force spectroscopy, ligand molecules are attached to the surface of AFM tip which is then controlled to touch the receptors on the substrate (or cell surface) to form receptorligand pairs and mechanically rupture the molecular pairs.

Spatial resolution

0.11 nm

Super-resolution optical microscopy (STED, PALM, STORM)

Electron microscopy (SEM, TEM, Cryo-EM)

Optical tweezers

Magnetic tweezers

Applying a focused excitation beam with a donut shape to create a region of fluorescent emission much smaller than a typical focal spot of conventional optical microscopy (STED) or stochastically turning on individual molecules within the diffraction-limited volume at different time points (PALM, STORM).

Using electrons to penetrate a thin specimen and then image the transmitted electrons (TEM), or focusing electrons into a small-diameter electron probe to raster scan the specimen and then collect the secondary electrons released from each local region of the specimen (SEM). CryoEM is a type of TEM capable of observing samples at cryogenic temperatures.

An optical trap is created by focusing a laser to a diffractionlimited spot with a high numerical aperture (NA) microscope objective to capture the dielectric particles (Bμm sized beads, bacteria, organelles). Polystyrene or silica beads used as “handles” attached to biological samples permit precise measurements of force and displacement.

A pair of permanent magnets is placed above the sample holder of an inverted microscope outfitted with a charge-coupled device (CCD) camera, applying force and rotation on magnetic beads linked with biological samples. The three-dimensional position of the bead is obtained by video tracking.

2050 nm

0.210 nm

B1 nm

110 nm

Force range

10104 pN

N/A

N/A

0.1100 pN

0.01100 pN

Sample preparation and work environment

Samples immobilized on substrates in physiological conditions (cell growth medium or buffer solution, controllable temperature and CO2).

Fluorescent labeling of target molecules in physiological conditions

Dehydrated specimens on grid in vacuum (TEM); dehydrated and gilding specimens in vacuum (SEM); vitrified specimens at cryogenic temperatures (cryoEM).

Beads on living cells or inside cells by phagocytosis, or beads coated with molecules in physiological conditions.

Magnetic beads on living cells or inside cells by phagocytosis, or beads linked with molecules in physiological conditions.

Advantages

Imaging living samples and observing life dynamics under native conditions without the need of staining, labeling or fixation; simple sample preparation; high signal-to-noise ratio; assessment of multiple physical, chemical and biological parameters.

Access to threedimensional cellular structures; high spatiotemporal resolution; monitoring biomolecular processes in living cells.

Solving atomic structures of proteins; conformational snapshots of proteins and complexes; visualizing molecular structures within the cell; imaging the surfaces of specimens at nanometer resolution.

High precision control of torque and force, parallel processing of multiple beads, and capable of altering the trap position at high frequencies (kHz).

Insensitive to drift and low-frequency noise (,1 Hz), inherently providing ultrastable operation, no need of complex designs, passive force clamp.

Limitations

Restricted to the surface of specimens and unable to detect intracellular structures.

Fluorescent labeling decreases specimen fidelity and could affect life processes.

Providing only static snapshots and incapable of observing life dynamics.

Photodamage and sample heating.

Lower resolution and no 3D trapping.

Information compiled from Refs. [5268].

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FIGURE 1.1 Atomic force microscopy (AFM) configuration. (A) Schematic of AFM principle. (B and C) Actual photographs of commercial AFMs. (B) A commercial Bioscope Catalyst AFM (Bruker, Santa Barbara, CA, USA) is set on an inverted optical and fluorescence microscope. The inset shows the Petri dish. Cells are grown in dishes and the AFM probe is immersed in the medium in the dish to probe the cells under the guidance of optical (fluorescence) microscopy. (C) A commercial Dimension Icon AFM (Bruker, Santa Barbara, CA, USA) which has a lateral optical microscope for visual guidance of moving AFM probe to target areas on the substrates. The inset is the optical image of the working AFM probe in liquids in the dish. Source: (B) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Nanoscale imaging and mechanical analysis of Fc receptormediated macrophage phagocytosis against cancer cells, Langmuir 30(6) (2014) 16091621. Copyright 2014 American Chemical Society. (C) Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, In situ high-resolution AFM imaging and force probing of cell culture mediumforming nanogranular surfaces for cell growth, IEEE Trans. Nanobiosci. 19(3) (2020) 385393. Copyright 2020 IEEE.

signal processing module and a feedback control electronics. The piezoelectric actuator acts as an electromechanical transducer that is able to convert electrical potentials into mechanical movements or vice versa. When a potential difference is applied on the opposite faces of a piezoelectric structure, the shape of the piezoelectric structure changes, and normally the

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expansion coefficient for a single piezoelectric shape is on the order of 0.1 nm/V applied [70]. The piezoelectric materials used in AFM are commonly lead zirconate titanate (PZT). The piezoelectric scanner of AFM integrates independently operated electrodes for X, Y, and Z directions into a single tube, which allows the nanopositioning of the AFM probe in threedimensional directions (XYZ) on the surface of the sample being probed. Notably in the early days of scanning probe microscopy, the shape of the piezoelectric scanner is like a tripod, which has been totally superseded by tubes of piezoelectric ceramic materials now. Piezoelectric tube has many advantages over tripod arrangement and the principal one is that larger scan ranges are possible with the compact and symmetrical geometry of the tube scanner [71]. In essence, the piezoelectric material does not respond linearly to the applied voltage, and there are two prevailing methods in current commercial AFM to address this issue: one is adding XYZ position sensors to monitor the actual movements of the piezoelectric tube and then correcting the nonlinearity through a feedback loop (usually called close loop), and the other one is firstly modeling the nonlinearity and then using nonlinear voltage to drive the tube to obtain linear movements (usually called open loop) [72]. For AFM imaging, the AFM probe is driven by the piezoelectric tube to raster scan the surface of the sample in the horizontal plane (XY directions), during which the piezoelectric tube simultaneously drives the probe to move vertically (Z direction) to maintain the constant interaction forces between tip surface atoms and sample surface atoms. The interaction forces between the AFM probe and sample are sensed by the optical lever system. A laser beam is focused onto the backside of the cantilever and is reflected via a mirror to a fourquadrant position sensitive detector (PSD). Any cantilever deflections caused by the changes of tip-sample interaction forces will result in slight alterations in the direction of the reflected beam, which is tracked by the PSD. The PSD signals are analyzed by the signal processing module and then the feedback system will control the piezoelectric tube to move vertically according to the topography of the sample to maintain the tip-sample interaction forces constant. The displacements in the XYZ directions of the piezoelectric tube are recorded during scanning, which yields a threedimensional topographical image of the specimen being scanned. A computer is linked to the controller to set up AFM imaging parameters and collect data from the controller. In practice, an optical microscopy system is commonly integrated with the commercial AFM to facilitate the manipulator to visually move the AFM probe to the specimens [73,74], as shown in Fig. 1.1B and C. AFM imaging depends on monitoring the interaction forces between tip surface atoms and sample surface atoms. It is now well-known that there are four distinct forces in nature, two of which are the strong and weak interactions that act between neutrons, protons, electrons, and

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other elementary particles and have a very short range of action (less than 1025 nm) [75]. The other two types of forces are the electromagnetic and gravitational interactions that act between atoms and molecules. For the interaction forces between tip surface atoms and sample surface atoms involved in AFM imaging, the gravitational force is completely insignificant compared to electromagnetic force (e.g., the gravitational force between two ions 1 nm apart is 32 orders of magnitude weaker than the electrostatic force) [76]. Electromagnetic forces are the source of all intermolecular interactions which determine the properties of solids, liquids, and gases, the behaviors of particles in solution, chemical reactions, and the organization of biological structures [75]. We know that electrons within an atom are in continual motion and travel extremely fast. For a given atom, it may appear electrically neutral over conventional periods of time, but for a very short period of time (saying a snapshot), the distribution of electric charges due to the electron motions is not perfectly symmetrical and this gives rise to subtle charge imbalances referred to as dipoles. Each molecule, therefore, exhibits a slightly different distribution of charge within a given snapshot and the charge imbalance in one molecule can electrically induce a similar imbalance in a neighbor molecule, causing that the slightly positive end of one molecule will be attracted to the negative end of another neighboring molecule and this is the origin of the van der Waals force [71]. For simplicity, we can consider the interactions between an atom at the tip apex and another atom on the sample surface, which can be characterized by the LennardJones potential function [77]: EðrÞ 5 4ε

   σ 12 σ6 2 r r

(1.1)

where r is the separation between the two atoms, ε is the depth of the potential well (associated with interaction strength), and σ is the interatomic distance where the potential is zero. ε and σ are two constants that depend on the materials and need to be experimentally determined to describe the specific molecular interaction. Normally, σ is approximately equal to the diameter of the atom involved (typically a few Angstroms [77]), and is sometimes called the hard sphere diameter [71]. Plotting the LennardJones function gives the interaction forces between the AFM tip atom and sample surface atom, as shown in Fig. 1.2. When the tip atom is far away from the sample atom, there is no interaction force between the two atoms (stage ①). When the tip atom approaches the sample atom gradually, the van der Waals attractive force arises which pulls the tip atom toward the surface, causing the downward deflection of the AFM cantilever (stage ②). As the tip atom further contacts and compresses the sample atom, repulsive forces

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FIGURE 1.2 Schematic showing the interactions between atomic force microscopy tip atom and sample surface atom modeled by LennardJones function.

due to Pauli exclusion principle and electrostatic (Coulombic) interactions dominate the interaction forces between tip atom and sample atom, causing the upward deflection of the AFM cantilever (stage ③). Depending on the types of interaction forces (attractive force or repulsive force) between the AFM tip and sample sensed by the AFM cantilever, different AFM imaging modes are obtained (as denoted in Fig. 1.2), which will be described in the following paragraphs. It should be noted that the interaction forces between the AFM tip and sample surface are highly complicated and many other types of forces are involved in different imaging environments, for example, meniscus force arises from capillary condensation around the contact sites between the AFM tip and sample surface for AFM imaging under ambient conditions, whereas double-layer and hydrodynamic force emerge when imaging in liquids [78]. Readers are referred to the references [76,78] for more descriptions of the AFM tip-sample interaction forces.

1.2.2 Contact mode Contact mode is the first imaging mode developed for AFM, and it is the basis for AFM techniques. In the contact mode, the AFM probe tip is in continuous physical contact with the sample surface and the repulsive forces between the probe tip and sample surface are sensed by the AFM probe cantilever (Fig. 1.2). For contact mode AFM imaging, the piezoelectric tube drives the probe to raster scan the sample in the horizontal plane, during which the probe is dragged across the sample surface (Fig. 1.3A) and the topographical changes of the sample surface in the vertical direction will result in the alterations of the deflection of

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FIGURE 1.3 Typical types of atomic force microscopy (AFM) imaging modes. (A) Contact mode and tapping mode. (I) Schematic diagram of AFM imaging of biological specimens (an example of a cell membrane is shown) attached on the substrate. (II) Contact mode AFM imaging. In contact mode, AFM tip is scanned over the specimen surface, while the deflection of the cantilever is maintained constant. (III) Tapping mode AFM imaging. In tapping mode, commonly the amplitude of the oscillating cantilever is maintained constant. (B) PFT mode. (I) Schematic diagram of AFM imaging at PFT mode. The vibrating tip indents the specimen in the vertical direction (z) at each sampling point to record force curves during raster scanning (the movement trajectory of the AFM tip is denoted by the dashed yellow line) at the horizontal plane (xy). (II) Schematic diagram of the force curve. Each force curve is composed of two portions, including an approach curve and a retract curve. By analyzing the different parts of the force curve, various mechanical parameters of the specimen are obtained, including Young’s modulus, deformation, adhesion force, and energy dissipation. Young’s modulus and adhesion forces are obtained from the retract curve, deformation is obtained from the approach curve, and the energy dissipation represents the area (orange shaded area) between the approach curve and retract curve.

AFM probe. The AFM signal processing and feedback module then compare the current cantilever deflection (called the feedback parameter) with a preset threshold (called the setpoint). The difference between the current cantilever deflection and the setpoint is called the error signal. If the current cantilever deflection is not equal to the setpoint, specific voltage is then applied to control the piezoelectric tube to move up or down to make

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the error signal back to zero. By recording the movements of the piezoelectric tube in three-dimension directions, we get the three-dimensional topographical image of the sample being scanned. The setpoint of the cantilever deflection in contact mode is preset by the user before AFM scanning and this parameter determines how hard the AFM tip pushes against the surface of the sample (called the scan force), which is important for utilizing contact mode AFM imaging to observe fragile biological samples. Notably, the contact mode AFM imaging described here operates in a way of constant force mode. Constant force mode is by far the most widely used mode, and generally any references to contact mode AFM mean constant force mode [79]. Contact mode can also work in constant height mode, in which the probe maintains a fixed height above the sample and there is no feedback loop in this mode. In constant height mode, the image signal comes entirely from the cantilever deflection and the deflection force on the cantilever is directly used to calculate the separation between the tip and sample surface. Constant height mode is appropriate for quick scans of samples with small height differences (if height differences are large, the tip will very likely crash onto the surface, causing either the tip to be destroyed or the tip to damage the sample) [80] and this mode has specific biomedical applications (e.g., observing the behaviors of biomolecules firmly attached to the smooth substrate with high-speed AFM [81,82]). A notable point for contact mode AFM is the selection of the probe. Normally, there is a contradiction between the force sensitivity and the stability of the probe. A softer cantilever (with a lower spring constant) deforms more under the same load and thus has better force detection sensitivity. However, a softer cantilever is more susceptible to the thermal drift caused by the environmental temperature variation (e.g., the heat generated by the AFM laser or optical microscope illumination often results in significant drift in deflection of the cantilever with a spring constant lower than 0.01 N/m, in the range of a few volts in the PSD output signals [72]), which conversely influences the quality of AFM imaging. In practice, cantilevers with a spring constant between 0.01 and 0.1 N/m are usually good for living cell imaging by contact mode AFM [72]. Besides, commercial AFM probes are commonly fabricated with the use of silicon or silicon nitride. In order to increase the reflectivity, a thin layer of gold is often coated on the backside of the cantilever, or a ferromagnetic coating may be applied if magnetic sensitivity is required [71]. Obviously, due to the fact that the thermal expansion coefficient of the coated material is different from the cantilever material (silicon/silico nitride), coating only one side of the cantilever will lead to a substantial thermal drift of the cantilever in response to the changes of environmental temperature. In 2012, Churnside et al. [83] have shown that even coating AFM cantilevers on both sides has thermal drift effects on the probe, whereas removing the coating layers of

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the AFM probes significantly increases the force stability and precision. As an alternative way, we can perform gold coating only at the end of the probe cantilever for increasing laser reflectivity while the rest of the cantilever is uncoated (this type of probe has been commercially available [72]), which will produce the probe that is insensitive to environmental temperature alterations and at the same time has adequate force detection precision. Since contact mode AFM imaging senses the repulsive forces between AFM tip atoms and sample surface atoms to obtain the topographical image of the sample, and the repulsive forces are highly localized (the repulsive force between the tip atom and a target atom on the sample is not susceptible by the neighbor atoms of the target atom), contact mode has a high spatial resolution. In fact, contact mode has long been used to obtain the high-quality topographical image of single membrane proteins (which will be described in Chapter 3) immobilized on substrates in near-physiological buffer solutions in the past decades [84,85] and so far contact mode AFM is still the preferred method to obtain the high-resolution topography of single native membrane proteins under aqueous conditions [52]. Besides, contact mode is suited for imaging the fine structures of single living cells [86,87], which usually requires applying the adequate scan force on living cells depending on which cellular parts are to be visualized (e.g., cell surface structures, cytoskeletons beneath cell surface, and so on). Applications of AFM topographical imaging on single membrane proteins (Chapter 3) and living cells (Chapters 7 and 8) will be described in detail in the subsequent chapters of the book. Notably, the drawback of contact mode is that the lateral dragging of the probe tip across the sample surface can cause mechanical deformation or even damage to the sample, which is detrimental for observing soft and fragile biological samples which are loosely adsorbed onto the substrate.

1.2.3 Noncontact mode Noncontact AFM (NC-AFM) is the only one AFM mode which is able to detect the behaviors of single atoms (including true atomic resolution, control of atomic forces, measurement of atomic forces, measurement of atomic response, observing atomic defects, mechanical manipulation of individual atoms, and mechanical assembly atom by atom) [88]. Atomic imaging of molecules by NC-AFM is commonly performed in frequency-modulated NC-AFM, in which the cantilever is actively oscillated at constant amplitude at its resonance frequency by a feedback circuit and interaction of the tip with the sample surface causing the resonance frequency to shift by Δf which is the key measurement signal in NC-AFM [89]. In the limit of small

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amplitudes, the frequency shift (Δf) is proportional to the gradient of the interaction force between tip and sample and therefore the tip-sample interaction forces can be measured by monitoring the frequency shift of the cantilever. NC-AFM usually works in constant height mode, in which the tip is scanned in a fixed plane above the sample surface while the frequency shift of the cantilever is recorded (typically, for atomic imaging, the height of the scanning tip above the sample is a few Angstroms [90]). A notable point is that atomic imaging by NC-AFM usually requires the use of a specific sensor called qPlus [91] which is based on the concept of piezoelectric quartz tuning forks similar to those used as timekeeping elements in wristwatches, allowing AFM operation at oscillation amplitudes down to a few Angstrom. A standard qPlus sensor is created by attaching one of the prongs of the tuning fork to a substrate and attaching a tip to the other prong which acts as a probe with the capability of self-sensing. For more descriptions of qPlus sensors, readers are referred to the recent review of literature by Giessibl [91]. An alternative to the self-sensing piezoelectric quartz sensor is the length extensional resonator or the so-called Kolibri sensor and the performance comparison between qPlus and Kolibri sensors is still under debate in the community [90]. Besides, utilizing NC-AFM to visualize the atomic structures of single molecules often requires tip functionalization [92]. For imaging single molecules, the AFM probe tip should be rather inert to prevent the target molecule from being picked up or moved by the tip, whereas the bare metal tips are often with high reactivity which could lead to the picking up of the target molecule before obtaining an atomic image. So far, the most popular functionalization for high-resolution NC-AFM is the CO tip [92], which is made by picking up a CO molecule with a metal tip (often copper [89]). Notably, NC-AFM is mainly applied in the fields of surface chemistry [93] for single molecular characterization with atomic resolution and requires substantial instrumentation as well as the harsh work environments (often in ultra-high vacuum (UHV) conditions [94]), which are uncommon for other applications, particularly for biomedical applications. The purpose of the brief description of NC-AFM here is to help readers understand AFM imaging techniques.

1.2.4 Tapping mode Tapping mode is also known as intermittent contact mode, dynamic force mode, oscillation mode, or AC mode. In tapping mode (Fig. 1.3A), the probe cantilever vibrates near its resonance frequency while raster scanning the sample surface and the probe tip intermittently touches the sample at its downward movement. When the probe is brought to the sample surface, the interactions between the tip and sample cause changes in both cantilever amplitude and resonance frequency. Either amplitude

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or resonance frequency of the cantilever can be used as the feedback parameter for tapping mode imaging, but using the amplitude as feedback is technically simpler because it requires only one feedback loop compared with using frequency as feedback which requires three such loops [61]. Hence, so far tapping mode AFM is commonly based on amplitude modulation. However, it should be noted that compared with amplitude modulation, the resonance frequency shift is more sensitive to the forces acting on the tip at the closest approach to the sample surface during the oscillation cycle [50], and frequency modulation is particularly suited for high-resolution imaging AFM such as in NC-AFM described above. During the raster scanning, the amplitudes of the cantilever are detected by the lock-in amplifier in the AFM controller and the piezoelectric tube drives the probe to move vertically to maintain the constant amplitude of the cantilever, yielding the three-dimensional topography of the sample by recording the XYZ displacements of the piezoelectric tube. The amplitude setpoint defines the amplitude of the cantilever oscillation signal to be maintained by the feedback loop and the setpoint reflects the tapping force exerted on the sample. In practice the amplitude setpoint is often chosen at about 80% of the free cantilever amplitude [72]. However, the adequate setpoint should be determined during experiments and it is associated with various factors, including specimen and probe as well as the imaging conditions. Generally, a larger tapping force often means better imaging quality, but also means more likely to cause tip damage (e.g., tip wear, tip break, and tip contamination) which could influence the life of the tip. A feasible way is starting the scanning with a lower tapping force and then increasing it slowly until the imaging quality does not improve anymore. Since tapping mode eliminates the lateral force between tip and sample, tapping mode is good at imaging loosely adsorbed and soft samples (e.g., biomolecules [50] and cellsurface fine structures [95]) which are often challenging for contact mode AFM. Incidentally, tapping mode AFM achieves great success in imaging DNA molecules, which will be described in Chapter 2. Nevertheless, one drawback of tapping mode is that it is unable to directly measure the interaction forces between tip and sample, as the lock-in amplifier only monitors the amplitude changes of the vibrating cantilever, making users unable to quantitatively characterize the interactions between tip and sample. Tapping mode AFM offers a powerful method for mapping the material and mechanical properties of the sample, which is called phase imaging [96]. Depending on the properties of the surface being probed (e.g., composition, friction, viscoelasticity, and adhesion), in addition to the amplitude changes, the interactions between tip and sample surface will also cause the phase changes of cantilever oscillation (called phase lag or phase shift), which can be recorded by the lock-in amplifier of AFM as well. Therefore, the cantilever’s vibration amplitude is used as

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the feedback parameter to move the piezoelectric tube vertically to generate the topography of the sample while the cantilever’s vibration phase lag is used to simultaneously generate the material properties map of the sample. Phase lag is caused by the energy dissipation during each contact between the tip and sample, which includes several factors (the inelastic deformation of the sample caused by the tip during the approaching stage, the van der Waals attractive force (Fig. 1.2) and adhesion force needing to overcome by the tip during retracting stage) [72] and are associated with the properties of the sample. The dissipated energy due to the inelastic tipsample interactions can be mathematically described as follows [97]: E5

 kω  AA0 sinϕ 2 A2 2Q

(1.2)

where E is the dissipated energy, k is the spring constant of the cantilever, Q is the quality factor, A is the cantilever vibration amplitude during scanning, A0 is the free cantilever vibration amplitude without the tipsample contact, ω is the driving frequency, and ϕ is the phage lag compared to driver. We can see that, since the cantilever vibration amplitude is maintained constant during scanning, the energy dissipation is directly linked to the phase lag and therefore the phage images reflect the mechanical properties of the sample. Tapping mode phase imaging is undoubtedly useful for investigating the material properties and readers are referred to Ref. [96] for more descriptions of the phase imaging theory. Nevertheless, as described above, the force curves are not recorded during tapping mode imaging and thus information on the sample provided by tapping mode phase imaging is limited. Particularly, there has been a new AFM technique called peak force tapping (PFT) mode which provides powerful capabilities to quantitatively characterize the diverse material properties of samples and will be described in the following.

1.2.5 Peak force tapping mode PFT mode originates from the AFM-based force spectroscopy techniques [50,98]. Traditionally, for AFM-based force spectroscopy assays, the AFM tip is controlled to vertically indent the specimens, during which the force curves are recorded. The mechanical properties of the specimens can be extracted from the obtained force curves, which will be described in detail in the following contents. However, traditional force spectroscopy is time-consuming and inefficient with a poor spatiotemporal resolution, and recent developments in AFM techniques allow fast obtaining force curves on each sampling point on the specimen while simultaneously recording

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topographic images of the specimen [61,99,100], and this technique is called PFT. The principle of PFT is shown in Fig. 1.3B. During AFM’s raster scanning along the xy horizontal plane (the movement trajectory of the AFM tip is denoted by the dashed yellow line in Fig. 1.3BI), the vibrating tip performs approachretract cycle in the vertical direction (z) on the specimen at each sampling point (each tiny grid in Fig. 1.3BI is equal to a sampling point). During the approach-retract movement, the changes in the deflection of the cantilever and the vertical displacements of the piezoelectric tube are recorded, which yield the so-called forcedistance curves. The peak force (as shown in Fig. 1.3BII, the peak force is the force from the cantilever at its maximum deflection during approach stage) of the obtained force curve is then used as the feedback parameter for controlling the piezoelectric tube to move vertically to maintain the peak force constant, which subsequently constructs the topography image of the specimen as the tip horizontally raster scans the specimen. As described above, contact mode AFM and tapping mode AFM record the deflection or the oscillation amplitude (frequency) of the cantilever as the feedback parameter during the scanning, which cannot sense the contact processes between the tip and sample during imaging. On the contrary, PFT records the force curves and uses the peak force of the force curves as the feedback parameter for imaging, and thus the tipsample contact processes during imaging are available from the force curves (e.g., the contact point between the tip and sample is discernible from the force curve and can be used to determine when the tip contacts the sample), facilitating integrating AFM with other complementary techniques to realize the simultaneous multimodal probing (such as combining PFT imaging and infrared imaging [101]) with high controllability and precision, which is quite meaningful for comprehensively understanding life activities. PFT imaging is able to display the multiple properties of the sample as colored maps by analyzing the force curves, which are correlated with the topography of the sample. The force curve contains various physical properties of the sample, as shown in Fig. 1.3BII. For example, the adhesion force reflects the adhesive capabilities of the sample surface. When using a bare tip (without functionalization) to perform PFT imaging, the adhesion force map reflects the nonspecific adhesive features of the sample surface. When using the functionalized tip to perform PFT imaging [102], the adhesion force map reflects the specific adhesive interactions between the target molecules on the sample surface and the antibody molecules on the tip surface, which is meaningful for revealing the molecular behaviors of cells. Particularly, viruses can also be directly attached to the surface of the AFM tip via linker molecules [103], which is useful for probing viruscell interactions at the single-virus level. Detailed descriptions of AFM-based force spectroscopy with the use of functionalized tip will be presented in the

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following texts. By fitting the force curve with mechanical models, Young’s modulus of the sample can be obtained. Notably, the commercially AFM produced by Bruker Company (Santa Barbara, CA, USA) uses DerjaguinMullerToporov (DMT) to extract Young’s modulus of samples. Some other theoretical models, such as HertzSneddon model (this mode will be described in detail in the following sections) and JohnsonKendallRoberts (JKR) [78], have also been widely used to analyze the force curves to obtain Young’s modulus of samples. The deformation of the sample can be obtained by analyzing the approach curve after the contact point, and the energy dissipation can be obtained by analyzing the area between the approach curve and the retraction curve. Since multiple properties maps of the specimen are generated simultaneously with the topographical image of the specimen during PFT imaging, PFT-based AFM imaging is also called multiparametric AFM [99,102]. The biomedical applications of PFT-based multiparametric imaging will be included in the subsequent chapters. Notably, for utilizing PFT-based AFM to investigate the mechanical properties of the specimens, we need to use appropriate AFM probes based on the characteristics of the specimens. Stiffer cantilevers can cause larger deformation on the specimen, while softer cantilevers have better detection sensitivity, and thus compromises are required for the specimens being probed. Generally, the cantilever spring constant should be comparable with the stiffness of the specimens being probed [104].

1.3 Atomic force microscopy force spectroscopy techniques 1.3.1 Single-cell mechanical measurement AFM achieves great success in measuring the mechanical properties (e.g., elasticity, viscoelasticity) of single living cells in the past decades and now AFM indentation assay has become a standard method for characterizing the mechanics of cells. Both cellular elasticity and viscoelasticity can be simultaneously measured by applying an AFM probe to vertically perform approach-dwell-retract movements on the cell surface [50]. The process of the AFM approach-dwell-retract cycle is shown in Fig. 1.4A. Firstly, the AFM probe, which is far away from the cell, is controlled by the piezoelectric tube to gradually touch and indent the cell in the vertical direction (stage ①). The contact between the tip and cell will result in the deflection of the AFM cantilever (x) which is detected by the PSD of AFM (Fig. 1.1A). According to Hooke’s law: F 5 kx

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FIGURE 1.4 Measuring cellular viscoelastic properties by atomic force microscopy (AFM) approach-dwell-retract experiments. (A) Schematic diagram of controlling AFM tip to vertically perform approach-dwell-retract movement on the cells. (B) A typical FD curve (I) and FT curve (II) obtained during the approach-dwell-retract process. (I) According to the contact point, the approach curve is converted into the indentation curve and the indentation curve is then fitted by the HertzSneddon model to extract cellular Young’s modulus (the inset). (II) The FT curve is fitted by the two-order Maxwell model to extract the cellular relaxation times (the inset). Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanotopographical surfaces for regulating cellular mechanical behaviors investigated by atomic force microscopy, ACS Biomater. Sci. Eng. 5(10) (2019) 50365050. Copyright 2019 American Chemical Society.

where k is the spring constant of the cantilever and x is the deflection of the cantilever, the interaction force between probe and cell is obtained (also called the loading force of probe cantilever). Notably, in order to exactly obtain the loading force exerted by the cantilever, the spring constant of the cantilever needs to be accurately calibrated in advance. Diverse methods have been developed to calibrate the spring constant of cantilever [105], including the static mass hanging method, reference cantilever method, dynamic mass attachment method, resonant frequency method, and thermal noise method. In practice, commonly, force curves are firstly obtained on the stiff substrate to calibrate the deflection sensitivity of the cantilever, and then the spring constant of the cantilever is calibrated by the thermal noise [106] module of AFM. When the loading force of the cantilever achieves the preset value during the approach process, AFM probe stops approaching and dwells on the cell surface for a period of time (stage ②). The purpose of dwelling is to observe the relaxation process of the cell. Subsequently, the AFM

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probe retracts from the cell surface to its original position (stage ③). During the approach-dwell-retract cycle, the vertical displacements of the AFM piezoelectric tube and the deflections of the AFM cantilever are obtained by AFM, which yields the forcedistance (FD) curve (also called force curve), as shown in Fig. 1.4BI. Each force curve is composed of two portions, an approach curve and a retract curve. Due to the dwelling of the AFM tip on the cell surface, the endpoint of the approach curve does not coincide with the start point of the retract curve. Generally, the approach curve is used for calculating the cellular elastic properties (such as Young’s modulus) [107], whereas the retract curve is used for probing adhesive interactions which usually requires using functionalized tips [47]. By linking an oscilloscope to the output signal of AFM, the PSD signal changes of AFM cantilever versus time are recorded [108,109], which yield the forcetime (FT) curves (also called relaxation curve). The FT curves obtained during the dwelling process of AFM tip on cells reflect the relaxation dynamics of cells, as shown in Fig. 1.4BII. By analyzing the FT curves, cellular viscoelastic properties (such as relaxation time) are obtained. The detailed processes of extracting cellular Young’s modulus from FD curve and relaxation time from FT curve are described in the following, respectively. Cellular Young’s modulus is obtained by fitting the FD curve with theoretical models. Several models have been presented for analyzing the indentation process of AFM tip, including HertzSneddon model, JKR model, DMT model, and OliverPharr model [40]. HertzSneddon model neglects the adhesion forces between the AFM tip and specimen, while JKR and DMT models consider the adhesion forces between the AFM tip and specimen (the JKR model considers the adhesion forces inside the contact area between tip and specimen, while the DMT model considers the adhesion forces outside the contact area) [110]. Thus, strictly speaking, HertzSneddon is applicable when the adhesion force is much smaller than the loading force, the JKR model is applicable in the case of large tips and soft samples with a large adhesion, and the DMT model is applicable in the case of small tips and stiff samples with a small adhesion [78]. The OliverPharr model is mainly used for determining the mechanical properties of thin films [111]. Nevertheless, for practical reasons, the HertzSneddon model is the most widely used one for calculating cellular Young’s modulus from FD curves [104,112114]. Hertz model is applicable to spherical tip and Sneddon extended the Hertz model to conical tip: pffiffiffiffi 4Eδ1:5 R Fspherical 5 (1.4) 3ð1 2 υ2 Þ Fconical 5

2Eδ2 tanθ πð1 2 υ2 Þ

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where υ is the Poisson ratio of cell (cells are often considered as incompressible materials and thus υ 5 0.5), F is the loading force of the AFM probe, δ is the indentation depth, E is the cellular Young’s modulus, θ is the half-opening angle of the conical tip, and R is the radius of the spherical tip. For applying the HertzSneddon model to analyze the FD curves, the FD curve needs to be converted into the indentation curve according to the contact point in the FD curve (the indentation δ is equal to the difference between the vertical displacement change of AFM piezoelectric driver and the deflection of the cantilever). We can imagine that if the specimen being indented is extremely stiff and there is no deformation on the sample during the indentation process, the vertical displacement of the piezoelectric tube is therefore equal to the deflection of the cantilever and the indentation depth is zero. For the soft specimens such as cells, there is a deformation of the specimen during indentation, and therefore the vertical displacement of the piezoelectric tube is the sum of the indentation depth and cantilever deflection. The HertzSneddon model is then used to fit the indentation curve. The inset in Fig. 1.4BI is an example showing the comparison of the HertzSneddon fitting curve and experimental indentation curve. The fitting gives the cellular Young’s modulus E. Notably, the HertzSneddon model assumes that the sample is infinitely thick, but it works well when the indentation into the sample by the tip is less than 10% of the sample thickness [115]. In 2012, Gavara and Chadwick [116] improved the HertzSneddon model to make it applicable for thin samples by introducing a bottom effect correction factor, significantly facilitating probing of the mechanical properties of cellular lamellar structures such as pseudopodia. However, this method requires measuring the thickness of the cell and is more complex than the HertzSneddon model. It should be noted that cellular Young’s modulus measured by AFM is influenced by experimental conditions, such as tip shape, probe loading rate, cellular positions being indented, environmental temperature and measurement medium [117], and thus these conditions should be maintained identical during experiments to eliminate artificial errors and make the results comparable with each other. Besides, cells are highly heterogeneous, and the elastic properties of different intracellular structures are included in the different parts of the recorded force curves. With smaller indentations, the AFM tip senses the stiff cellular cortex which is composed of actin proteins. With larger indentations, the AFM tip senses the softer structures beneath the cellular cortex, such as cytoplasm. When further increasing the loading force to indent the cells, the cell nuclei may be probed by AFM. Another notable point regarding AFM-based cellular mechanical measurement is the geometry of the probe tip. Studies have shown that cellular Young’s modulus measured by the conical tip is significantly larger than that measured by the same cantilever modified with a spherical tip [118], and this is due to the fact that different intracellular

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structures are probed by the different tips. The spherical tip has a much larger contact area than the conical tip. The conical tip primarily probes the stiff cell cortex, whereas the spherical tip probes both the cell cortex and the softer underlying cytoplasm. Cellular relaxation time is obtained by analyzing the FT curves recorded on cells. Young’s modulus only reflects the elastic properties of cells, while in fact living cells are intrinsically viscoelastic materials and the rheological behavior of cells is closely connected to the fundamental functions of cells. Hence, characterizing the viscoelastic properties of cells is quite meaningful for understanding cell behaviors from the perspective of biomechanics. By the way, AFM is a type of active method for characterizing cellular rheological properties, and passive methods (using the thermal fluctuations of embedded colloidal probes to measure cellular rheology) [119] have also been developed to characterize the rheology of cells. Generally, the FT curve can be fitted by a two-order Maxwell spring-dashpot model to obtain cellular relaxation time [108,109]: FðtÞ 5 A0 1 Ai

2 X

e2t=τ i

(1.6)

i51

τi 5

ηi ; i 5 1; 2 Ei

(1.7)

where F is the loading force of the AFM probe, A0 is the instantaneous (purely elastic) response, Ai are the ith force amplitudes, τ i is the ith cellular relaxation time, ηi is the ith cellular viscosity, and Ei is the ith cellular Young’s modulus. The cellular relaxation time (τ) is the ratio of cellular viscosity (η) to cellular Young’s modulus (E), and thus cellular relaxation time indicates the viscoelastic properties of cells. In practice, the one-order Maxwell model often does not fit the FT curve well, while the two-order Maxwell model matches the FT curve well [108,109,120,121]. The inset in Fig. 1.4BII is an example showing the comparison of the two-order Maxwell fitting curve and experimental relaxation curve and we can see that the two curves are considerably consistent with each other. Fitting the relaxation curve with a two-order Maxwell model gives two cellular relaxation times (τ 1 and τ 2). During the AFM indentation process, the AFM tip successively probes the cell membrane and cytoskeleton. The first-order cellular relaxation time τ 1 (the fast relaxation time) originates from the rapid deformations of the cell membrane, while the second-order cellular relaxation time τ 2 (the slow relaxation time) originates from the relatively slow reorganizations of cytoskeletons. A notable point is that cellular relaxation times measured by AFM are dependent on the measurement parameters, such as surface dwell time and ramp rate [122], and thus experimental conditions should be identical to make the obtained results comparable.

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Modifying the AFM cantilever with an individual sphere to form a spherical tip is particularly useful for characterizing cell mechanics since the spherical tip has a defined geometry which facilitates theoretical modeling and the spherical tip could also better represent the mechanical properties of the whole cell compared with a conical tip which only detects the mechanical properties of local areas of cells. We have conveniently fabricated an AFM probe with spherical tips based on AFM micromanipulations [120,121] and the protocol is in the following as a reference to the readers (Fig. 1.5). First, a regular AFM probe is mounted onto the AFM head and the laser signal reflected on the cantilever is adjusted (for some commercial AFMs, such as the Dimension 3100 AFM used here, we need to adjust the laser signal of the cantilever to beyond a certain value and then the AFM head can be moved). Subsequently, a drop of the polystyrene sphere solution (the sphere diameter is B20 μm here and readers can use spheres with different sizes according to their experimental requirements) is placed on a fresh glass slide and a drop of mixed two-part epoxy adhesive (Araldite, USA) is placed on another position of the same glass slide by using a toothpick. The glass slide is then placed onto the specimen stage of AFM. Under the guidance of optical microscopy, the AFM cantilever is controlled to slightly touch the epoxy adhesive and then retract immediately. The AFM cantilever is then moved to contact a single sphere for 10 s and then retract from the glass slide. Fig. 1.5A shows the optical

FIGURE 1.5 Fabricating spherical tip for single-cell mechanical analysis. (A) Under the guidance of optical microscopy, a sphere is glued to the end of the atomic force microscopy (AFM) cantilever. Optical images obtained before (I) and after (II) gluing a sphere to the AFM cantilever. (B and C) SEM images of the fabricated spherical tips. (B) Triangular cantilever glued with a sphere. (C) Rectangular cantilever glued with a sphere. Source: (A) Reprinted with permission from M. Li, L. Liu, X. Xiao, N. Xi, Y. Wang, Effects of methotrexate on the viscoelastic properties of single cells probed by atomic force microscopy, J. Biol. Phys. 42(4) (2016) 551569. Copyright 2016 Springer Nature. (B and C) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Atomic force microscopy studies on cellular elastic and viscoelastic properties, Sci. China Life Sci. 61(1) (2018) 5767. Copyright 2017 Science China Press and Springer-Verlag GmbH Germany.

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images before (Fig. 1.5AI) and after (Fig. 1.5AII) gluing a sphere to the cantilever of the AFM probe. The prepared probes with spherical tips are placed in a probe box for 24 h at room temperature for the hardening of epoxy adhesive and then the probe can be used for single-cell mechanical measurement experiments. Experimental results have shown that either triangular or rectangular cantilevers can be easily modified with spherical tips by this method (Fig. 1.5B and C).

1.3.2 Single-cell force spectroscopy AFM-based single-cell force spectroscopy (SCFS) is able to quantify the adhesive interactions of individual cells. Cell adhesion, commonly defined as the binding of a cell to a substrate (the substrate can be another cell, a surface or an organic matrix), is broadly connected to physiological and pathological processes, including embryonic development, assembly of tissues, cellular communication, inflammation, wound healing, tumor metastasis, cell growth, and viral and bacterial infection [123]. AFM-based SCFS offers novel possibilities for seeking answers to the fundamental issues in cell adhesion. The prerequisite of SCFS is functionalizing the AFM cantilever to allow firmly attachment of individual living cells onto the cantilever to prepare single-cell probe. For single-cell probes, weak adsorption of the cell onto the cantilever may cause the sliding of cells during measurements, which results in the failure of the experiments. Commonly, AFM cantilevers are coated with concanavalin A (ConA) to adsorb single cells [124,125]. For doing so, AFM cantilever is firstly incubated with biotin-conjugated bovine serum albumin (BSA) at 37 C overnight, after which the cantilever is washed with phosphate buffered saline (PBS) to remove the unbound molecules. The cantilever is then incubated in streptavidin solution for 30 min at room temperature. After the incubation, the cantilever is washed with PBS again and then is incubated in biotin-conjugated ConA solution for 30 min at room temperature. After the incubation, the ConAfunctionalized cantilever can be stored in PBS for up to 1 week at 4 C. Individual living cells can be tightly attached to the ConA-functionalized cantilever by AFM micromanipulations for SCFS experiments, as shown in Fig. 1.6A. Under the guidance of optical microscopy, the ConAfunctionalized cantilever is moved to gradually approach individual living cells on the substrate (I in Fig. 1.6A). When the cantilever contacts the cell with adequate forces, the cantilever dwells on the cell for about 30 s to allow the formation of firm binding between the cell and cantilever (II in Fig. 1.6A), after which the cantilever retracts from the cell and usually a single-cell probe is prepared (III in Fig. 1.6A). A notable point is that after attaching the cell to the cantilever, the cell needs to recover for at least 10 min, during which the cell will form firm contacts with the cantilever

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FIGURE 1.6

Atomic force microscopy (AFM)-based single-cell force spectroscopy (SCFS). (A) Attaching single living cell to the ConA-coated cantilever by AFM micromanipulations. (I) The ConA-coated cantilever is approaching a cell on the substrate under the guidance of optical microscopy. (II) The cantilever contacts the cell and dwells on the cell for 30 s to allow the binding of the cell to the cantilever. (III) The cantilever retracts from the substrate and the cell is attached to the cantilever. (IV) Staining the cell probe with CFDA SE confirms the viability of the cell. (B) Schematic of SCFS for measuring the adhesive interactions between cell and surface. The single-cell cantilever is lowered toward the collagen substrate (I) until a preset force is reached (II). After a given contact time, the cantilever is retracted from the surface (III) until cell and substrate are completely separated (IV). (C) A typical FD curve showing steps (I, II, III, IV) corresponding to those outlined in (B). The maximum force required to separate the cell from the surface is referred to the detachment force (F). Source: (A) Reprinted with permission from D. Dang, R. Xiang, B. Liu, X. Liu, M. Li, Quantifying the adhesion forces of lymphoma cells by AFM single-cell force spectroscopy, Prog. Biochem. Biophys. 46(1) (2019) 8998. (B and C) are reprinted with permission from J. Friedrichs, J. Helenius, D. J. Muller, Quantifying cellular adhesion to extracellular matrix components by single-cell force spectroscopy, Nat. Protoc. 5(7) (2010) 13531361. Copyright 2010 Nature America, Inc.

surface [125]. In order to examine the viability of the cell on the cantilever, the live/dead reagent CFSE DA is used to stain the cell on the cantilever, and we can see that cells exhibit bright fluorescence after the staining of CFSE DA (IV in Fig. 1.6A), indicating that the cell on the cantilever is alive. With the use of single-cell probe, the adhesive interactions between cell and substrate can then be probed by controlling the probe to vertically perform approach-retract cycle on the substrate, as shown in Fig. 1.6B. Incidentally, Fig. 1.6B only shows an example of adhesive interactions between cell and surface (collagen), and the surface can be replaced with a cell grown on a substrate and in that case the adhesive interactions between two cells are

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measured. Firstly, the cell probe, which is originally far away from the surface, is controlled to vertically approach the surface. After the cell probe contacts the surface, the probe compresses the surface until the preset force is achieved (II in Fig. 1.6B) and the probe dwells on the surface for a period of time (called the contact time). Subsequently, the cell probe withdraws from the surface, during which the adhesion between the cell and surface could cause the downward deflection of the cantilever (III in Fig. 1.6B). When the pulling force is larger than the adhesion forces between the cell and surface, the cellsurface adhesive bonds rupture and the cell probe return to its original position (IV in Fig. 1.6B). By analyzing the force curves recorded during the approach-retract cycle (Fig. 1.6C) [123,125], the detachment force of the cell (denoted by F in Fig. 1.6C) is obtained. Particularly, studies have shown that two types of smaller unbinding events are often contained in the obtained force curves which are frequently named rupture (denoted by r in Fig. 1.6C) and tether (denoted by t in Fig. 1.6C) events, respectively [126]. In rupture events, the receptor remains anchored in the cell cortex and unbinds as the loading force increases, causing the shrinking of the contact area and subsequently the detaching of the cell body from the substrate. In tether events, receptor anchoring is lost and the membrane tethers are pulled out of the cell, causing the staircase-like manner of the force curve.

1.3.3 Single-molecule force spectroscopy AFM can probe the specific interaction force of single receptorligand pair by the technique called single-molecule force spectroscopy (SMFS). For doing so, ligands are attached to the surface of the AFM tip and then the functionalized tip is controlled to vertically perform approach-retract cycles on the cell surface. The ligands attached to the surface of the AFM tip can specifically bind to the particular receptors on the cell surface. As shown in Fig. 1.7A, the ligandconjugated tip, which is originally far away from the cell, gradually approaches the cell surface (I in Fig. 1.7A). The tip contacts and compresses the cell surface until the loading force achieves the preset maximum value (II in Fig. 1.7A). Subsequently, the tip retracts from the cell surface (III in Fig. 1.7A). If the receptorligand binding occurs during the contact between the AFM tip and cell, the receptorligand pair is stretched by the AFM tip (III in Fig. 1.7A) during the retract process. When the pulling force exerted by the AFM cantilever is larger than the bond strength of the receptorligand pair, the receptorligand pair ruptures and then the AFM tip returns back to its original position (IV in Fig. 1.7A). By analyzing the force curves (Fig. 1.7C) recorded during the approach-retract cycle, the rupture force of the individual

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FIGURE 1.7 Atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS). (A) Schematic diagram of probing single receptors on cell surface by AFM-based SMFS. (I) AFM tip carrying ligands begins approaching cell surface. (II) AFM tip contacts the cell surface, allowing the binding of ligands and receptors. (III) AFM tip retracts from cell surface, which stretches the receptorligand pair. (IV) Receptorligand ruptures when the pulling force exerted by AFM cantilever is larger than the strength of receptorligand bond. (B) Schematic diagram of tip functionalization for SMFS. Not only various biomolecules (I), but also virus (II) can be attached to the AFM tip. (C) A typical force curve recorded during AFM-based SMFS experiments. The denoted steps (I, II, III, IV) correspond to those outlined in (A). Source: (B) Reprinted with permission from D. J. Muller, Y. F. Dufrene, Force nanoscopy of living cells, Curr. Biol. 21(6) (2011) R212R216. Copyright 2011 Elsevier Ltd. (C) is reprinted with permission from M. Li, X. Xiao, L. Liu, N. Xi, Y. Wang, Z. Dong, et al., Nanoscale mapping and organization analysis of target proteins on cancer cells from B-cell lymphoma patients, Exp. Cell Res. 319(18) (2013) 28122821. Copyright 2013 Elsevier Inc.

receptorligand pair is obtained. Fig. 1.7C shows a practical force curve obtained during SMFS experiments [127]. The stretching of the receptorligand pair (III in Fig. 1.7C) yields an unbinding force peak in the retract portion of the curve (denoted by the black arrow in Fig. 1.7C) and the magnitude of this peak is equal to the rupture force of the receptorligand pair. When the density of ligands linked to the AFM tip is adjusted to an appropriate level that only one receptorligand pair is formed between the tip-cell contact area, the unbinding peak then corresponds to single receptorligand pair and thus the unbinding force of single molecular pair is measured. A critical point for AFM-based SMFS is linking biomolecules (which can specifically bind to the target receptors on the cell surface) onto the surface of AFM tips, and this process is commonly called tip functionalization (Fig. 1.7B) [128]. Originally, researchers attach biomolecules

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onto the surface with the use of short rigid linker [129132] (typically avidinbiotin system), and the drawback of this method is that high coverage of ligands increases the risk of probing multiple binding events and increases steric hindrance, which can interfere with the binding process [55]. Besides, ligands linked to the AFM tip have weak conformational mobility. In order to overcome these defects, researchers have used long, flexible and distensible linkers such as polyethylene glycol (PEG) to attach ligands onto AFM tip [133]. For doing so, the PEG linker molecules typically carry two different functional ends. One end of the PEG linker molecule covalently reacts with the amine-functionalized tip surface, and the other end covalently reacts with the ligands. The use of heterobifunctional PEG crosslinker has several advantages. First, the binding strength of covalent bonds (12 nN) is about ten times stronger than typical receptorligand bonds [134], which ensures that the receptorligand pair ruptures during the SMFS process. Second, the ligands at the end of the PEG linker can freely orient in the solution to recognize the receptors on the cell surface, which facilitates the receptorligand binding interactions. Third, during the retract process, stretching the PEG linker will often cause a nonlinear shape of force peak in the force curve (denoted by the green arrow in Fig. 1.7C), which can be used to discriminate the specific receptorligand rupture events and nonspecific rupture events. Hence, so far PEG covalent coupling has been the predominant tip functionalization method for SMFS. Notably, in practice, one end of the PEG linker is commonly NHS, and the other end of the PEG linker is diverse depending on the types of ligands to be attached. In brief, amino-functionalization is firstly performed to coat the AFM probe with a layer of NH2. The NH2 group is able to form covalent bonds with the NHS group of the PEG linker, allowing attachment of the PEG linker to the AFM tip. The last step is attaching ligands to the reactive groups at the other end of the PEG linker, and various strategies (e.g., NHS-PEG-aldehyde, NSH-PEG-maleimide) have been presented to attach a wide range of ligands (e.g., protein, antibody, virus) [135]. Besides, methods based on the affinity between tetravalent nickel and histidine have also been developed for the attachment of His6-tagged ligands, which achieve tip functionalization in a controlled orientation of the ligands. There are several points which should be noted for practical SMFS experiments. Before applying AFM force spectroscopy to probe the target receptors on the cell surface, the expression levels of the receptor on the cell surface need to be confirmed, which can be performed by staining the target receptors with fluorescein and the subsequent recording of the fluorescent images [136]. For AFM force spectroscopy experiments, due to the fact that membrane proteins are often heterogeneously distributed on the cell surface, force curves are commonly recorded at different surface points of multiple cells (at least 10 cells) to

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obtain statistical results and the probability of finding specific molecular unbinding events usually ranges from 10% to 30% [137]. Besides, blocking experiments are often required to demonstrate the specific receptorligand binding interactions, during which free ligands are added to block the receptors on the cell surface and then the functionalized tip is applied to record force curves on the cell surface. For the force curves obtained on cells after blocking, there should be no, or few specific unbinding force peaks. Since receptorligand interactions are closely related to the cell states, one should carefully monitor cell morphology and cell viability during SMFS experiments and only force curves obtained from the same cell morphology/viability can be compared with each other [55]. In addition, the rupture force of receptorligand pair measured by AFM is dependent on the loading rate (retraction velocity multiplied by the spring constant of the cantilever) of the AFM cantilever, which is theoretically described by the BellEvans model [138]:

kB T rxβ ln F5 xβ koff kB T

(1.8)

where F is the rupture force, r is the loading rate, koff is the kinetic dissociation rate at zero force, xβ is the distance to the transition state along the projection of the applied force, kB is the Boltzmann’s constant, and T is the temperature. The formula (1.8) indicates the linear relationship between the measured receptorligand rupture force and the logarithm of the loading rate. Hence, in practice, rupture forces are measured at different pulling velocities to investigate the dissociation dynamics of the molecular interactions and at least 1000 force curves [55] are required to record one pulling velocity. AFM-based SMFS also allows the revealing of the unfolding dynamics of single membrane proteins. Most proteins have to acquire an adequate three-dimensional structure to perform biological functions. The folding of proteins into their compact three-dimensional structures is one of the most fundamental examples of biological self-assembly. Protein misfolding is associated with many human diseases, including neurodegenerative diseases (e.g., Alzheimer’s disease, spongiform encephalopathies, Parkinson’s disease), nonneuropathic systemic amyloidosis (e.g., amyloid A (AA) amyloidosis), and nonneuropathic localized amyloidosis (e.g., type II diabetes) [139]. Hence, understanding the protein folding process significantly benefits understanding the underlying mechanisms guiding protein functions and behaviors. Utilizing AFM-based SMFS to mechanically unfold single proteins provides unique insights into the mechanics of proteins. For doing this, AFM tip does not require tip functionalization. After immobilizing membrane protein patches, either natural membranes containing highly

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ordered proteins (e.g., purple membrane) or artificial membranes containing reconstituted proteins [140], onto the substrate, the AFM tip is moved to above single membrane proteins based on high-resolution AFM imaging of single membrane proteins [141]. AFM tip is then controlled to approach and touch a single membrane protein with a contact force of B0.51 nN for B1 s, which results in firm adsorption of the protein to the AFM tip in about 15% of all cases [85]. Subsequently, the AFM tip retracts from the membrane, which mechanically unfolds the membrane protein. Force curves are recorded during the approach-retract cycle of the tip. Notably, if the polypeptide adsorbed to the AFM tip is the C- or N-terminal end of the protein, the force curves will exhibit a length corresponding to that of the entirely stretched protein. If the protein attaches with a polypeptide loop or slips off the tip before being completely unfolded, the force curves will be shorter and thus difficult to interpret. Therefore, only force curves representing the entirely unfolded and stretched protein should be used for analysis [142]. The force curve with a fully membrane protein unfolding process shows the sawtooth-like pattern of force peaks, each of which corresponds to the unfolding of a segment of membrane protein. The force curve is fitted by the worm-like chain (WLC) model to analyze the unfolding pathway of the protein [55,84]: " #

kB T 1 x 22 x 1 12 1 2 (1.9) FðxÞ 5 lp 4 Lc L0 4 where F(x) is the force, Lc is the contour length of the peptide, lp is the persistence length of the peptide which describes the rigidity of the polymer, x is the extension of peptide, kB is the Boltzmann’s constant, and T is the temperature. Fitting each sawtooth-like peak with WLC model gives the number of amino acids of the stretched segment and thus the unfolding pathway of the protein is generated after fitting all the peaks.

1.4 High-speed atomic force microscopy The developments of high-speed AFM enable capturing the dynamics of biomolecular activities at work with unprecedented temporal resolution. Life is dynamic and the functions of biological systems depend on the dynamic processes that occur in biomolecules, organelles, and cells [143]. Observing the real-time dynamics of single biomolecules at work is considerably meaningful for uncovering the underpinnings of biological processes. AFM is the only technique which is able to visualize the structure of single native biomolecules with nanometer spatial resolution under aqueous conditions. However, the topographical imaging

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speed of AFM has long been slow. It often takes minutes to acquire a topographical image of biological specimens by conventional AFM, which is much greater than the time scale at which dynamic processes usually occur in biology [144]. Therefore, strong demand of AFM for biomedical applications is the ability to rapidly acquire successive high-resolution images of individual biomolecules in action. In 2001, Ando et al. [145] developed a high-speed AFM for studying biomolecules based on tapping mode, which is able to capture a 100 3 100 pixel2 image within 80 Ms and the experimental results exhibit the exciting capabilities of the high-speed AFM to capture the Brownian motions of single myosin V molecules in solution. Since then, highspeed AFM techniques has been continuously advanced and now high-speed AFM is coming of age [146] for biomedical applications. High-speed AFM is able to not only watch single biomolecules in action in real-time [147], but also can visualize the morphological dynamics of single living cells [148], contributing much to molecular and cell biology. High-speed AFM typically operates in tapping mode [149], in which the cantilever is excited to vibrate near its resonance frequency to intermittently contact the sample surface. The highest possible imaging rate of tapping mode AFM is determined by the bandwidth of feedback control to maintain the tapping amplitude constant during scanning as well as by scan parameters and the sample itself [146]. The details of the basic principles of high-speed AFM are beyond the scope of this book and readers are referred to the references [143,146,149] for more descriptions of the quantitative relationship between the feedback bandwidth and the various factors involved in AFM and the scanning conditions. Briefly, in the high-speed AFM system (Fig. 1.8A), various devices, including cantilevers (Fig. 1.8B), electronic circuits, the sample-stage scanner (Fig. 1.8C), and the cantilever deflection detection system, are optimized for achieving highspeed performance [150,151]. For example, cantilevers are miniaturized to achieve high resonant frequencies and small spring constants, while a new feedback control technique capable of maintaining weak tip-sample interactions and active camping techniques to suppress the scanner’s mechanical vibrations have been implemented. Notably, Fig. 1.8C shows a narrow-area scanner for high-speed AFM. Researchers have also developed a wide-area scanner for high-speed AFM [152] which has a maximum XY scan range of 46 3 46 μm2 and is able to capture the dynamic processes of single living bacterial and eukaryotic cells. High-speed AFM has now become an important method for observing the real-time dynamics of life processes and the practical applications of utilizing high-speed AFM to address biological issues will be presented in the subsequent chapters.

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FIGURE 1.8 High-speed atomic force microscopy (AFM). (A) Schematic diagram of the configuration of the high-speed system. (B) SEM image of a small cantilever for highspeed AFM. The inset shows an electron beam deposited amorphous carbon tip grown on the original tip. (C) Structure of a high-speed AFM scanner for narrow area imaging ( , 1 μm 3 4 μm). Source: (A) Reprinted with permission from T. Uchihashi, N. Kodera, T. Ando, Guide to video recording of structure dynamics and dynamic processes of proteins by high-speed atomic force microscopy, Nat. Protoc. 7(6) (2012) 11931206. Copyright 2012 Nature America, Inc. (B and C) Reprinted with permission from T. Ando, High-speed AFM imaging, Curr. Opin. Struct. Biol. 28 (2014) 6368. Copyright 2014 Elsevier Ltd.

1.5 Topography and recognition imaging mode atomic force microcopy The advent of simultaneous topography and recognition imaging (TREC) mode AFM offers novel opportunities for detecting molecular behaviors. Traditionally, in order to apply AFM force spectroscopy techniques to map the spatial distributions of particular receptors on single cells, the functionalized probes are used to obtain arrays of force curves at the small local areas on the cell surface [153]. For an array of force curves, the unbinding force of each force curve is calculated from the force peak in the retract curve (as denoted by the black arrow in Fig. 1.7C). If there are no unbinding force peaks, the unbinding force is set to zero. After normalizing the unbinding forces into gray colors (0255), a force map is constructed by using imaging processing software and the brightness of the pixel reflects the magnitude of unbinding forces. This method is called force volume mode which is time-consuming and inefficient. In 2004, Stroh et al. [154] developed a new molecular recognition mode based on AFM, which is called TREC. TREC is able to simultaneously obtain a topography image and a recognition image on the cell surface and the imaging time is comparable to

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conventional AFM imaging. TREC mode is based on tapping mode AFM imaging. In TREC mode (Fig. 1.9A), the oscillating tip which carries ligands raster scans the cell surface. Both the maxima and minima of the oscillation periods are recorded. During scanning, if the ligand

FIGURE 1.9 Topography and recognition imaging (TREC) mode atomic force microscopy (AFM). (A) Schematic diagram of the principle of detecting cell surface receptors by TREC mode AFM. An oscillating AFM tip tethered with a ligand molecule scans across the cell surface to elucidate the nanoscale organization of receptor molecules. The cantilever oscillation amplitude is split into lower and upper parts, resulting in simultaneously acquired topography and recognition images. The topography image is generated from the lower part and the corresponding recognition map is constructed from the upper part of the oscillation amplitude. The recognition events originate from the PEG linker stretching which results in a damping of the upper part of the oscillation. (B) Amplitude signals of cantilever oscillations. The maxima signals of the cantilever oscillation amplitudes (denoted by red arrows) keep constant when scanning with a bare tip (I). Scanning with a functionalized tip results in significant changes in the maxima signals (denoted by blue arrows) while the topographical information is also contained in the minima signals (II). (C) Topography image (I) and corresponding recognition map (II) of thrombin protein molecules deposited on mica. The circles indicate those protein molecules that were recognized, whereas the square indicates the protein that was not recognized. (D) Topography image (I) and corresponding recognition map (II) of receptors on mica surface. In the recognition map, dark spots indicate the regions where the antibody on the tip is bound to the target receptors on surface. The white arrows indicate the interactions with large aggregates. Source: (A) Reprinted with permission from L.A. Chtcheglova, P. Hinterdorfer, Simultaneous AFM topography and recognition imaging at the plasma membrane of mammalian cells, Semin. Cell Dev. Biol. 73 (2018) 4556. Copyright 2017 Elsevier Ltd. (B) Reprinted with permission from C. M. Stroh, A. Ebner, M. Geretschlager, G. Freudenthaler, F. Kienberger, A. S. M. Kamruzzahan, et al., Simultaneous topography and recognition imaging using force microscopy, Biophys. J. 87(3) (2004) 19811990. Copyright 2004 The Biophysical Society. (C) Reprinted with permission from S. Senapati, S. Manna, S. Lindsay, P. Zhang, Application of catalyst-free click reactions in attaching affinity molecules to tips of atomic force microscopy for detection of protein biomarkers, Langmuir 29(47) (2013) 1462214630. Copyright 2013 American Chemical Society. (D) Reprinted with permission from P. Kaur, Q. Fu, A. Fuhrmann, R. Ros, L.O. Kutner, L.A. Schneeweis, et al., Antibody-unfolding and metastable-state binding in force spectroscopy and recognition imaging, Biophys. J. 100(1) (2011) 243250. Copyright 2011 the Biophysical Society.

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molecules on the tip do not bind to the receptors on the cell surface, the tip vibrates like imaging with a nonfunctionalized tip. When the ligand molecules bind to the receptors on the cell surface, the subsequent unbinding events of receptorligand pairs will result in changes in the upper part of the vibration amplitude signal (maxima) but does not influence the lower part of the vibration amplitude signal (minima) (Fig. 1.9B) [155]. When using a bare tip (nonfunctionalized tip) to scan the surface of specimen, the maxima signals of cantilever oscillations keep constant while the topographical information is contained in the minima of the cantilever oscillations (I in Fig. 1.9B). When using a functionalized tip to perform scanning, not only the topographical information is contained in the minima of the cantilever oscillations, but also the specific molecular unbinding events are contained in the maxima of cantilever oscillations (II in Fig. 1.9B). By using a special electronic circuit called TREC box, the recognition image is generated simultaneously with the topographical image [156], therefore allowing correlating receptor distribution with cell surface structures. For TREC mode AFM, the cantilever oscillation amplitude should be slightly smaller than the extended PEG linker length, so that the ligand remains bound while passing a binding site and the reduction of the maxima of cantilever oscillations is of sufficient significance compared to the thermal noise. With TREC mode AFM, not only the purified biomolecules deposited on the substrate can be recognized [157159] (Fig. 1.9C and D), but also the proteins reconstituted in the artificial lipid bilayer membranes [160] and even the receptors on the cell surface [136,156,161,162] can be recognized, which provide novel insights into the molecular interactions and practical applications of TREC mode AFM will be presented in the subsequent chapters. Notably, TREC does not record force curves during imaging, and thus quantitative force information about molecular binding events is missing.

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[143] T. Ando, T. Uchihashi, T. Fukuma, High-speed atomic force microscopy for nanovisualization of dynamic biomolecular processes, Prog. Surf. Sci. 83 (79) (2008) 337437. [144] D.J. Muller, Y.F. Dufrene, Atomic force microscopy: a nanoscopic window on the cell surface, Trends Cell Biol. 21 (8) (2011) 461469. [145] T. Ando, N. Kodera, E. Takai, D. Maruyama, K. Saito, A. Toda, A high-speed atomic force microscope for studying biological macromolecules, Proc. Natl. Acad. Sci. USA 98 (22) (2001) 1246812472. [146] T. Ando, High-speed atomic force microscopy coming of age, Nanotechnology 23 (6) (2012) 062001. [147] A.J. Katan, C. Dekker, High-speed AFM reveals the dynamics of single biomolecules at the nanometer scale, Cell 147 (5) (2011) 979982. [148] M. Shibata, H. Watanabe, T. Uchihashi, T. Ando, R. Yasuda, High-speed atomic force microscopy imaging of live mammalian cells, Biophys. Physicobiol. 14 (2017) 127135. [149] T. Ando, T. Uchihashi, S. Scheuring, Filming biomolecular processes by high-speed atomic force microscopy, Chem. Rev. 114 (6) (2014) 31203188. [150] T. Uchihashi, N. Kodera, T. Ando, Guide to video recording of structure dynamics and dynamic processes of proteins by high-speed atomic force microscopy, Nat. Protoc. 7 (6) (2012) 11931206. [151] T. Ando, High-speed AFM imaging, Curr. Opin. Struct. Biol. 28 (2014) 6368. [152] H. Watanabe, T. Uchihashi, T. Kobashi, M. Shibata, J. Nishiyama, R. Yasuda, et al., Wide-area scanner for high-speed atomic force microscopy, Rev. Sci. Instrum. 84 (5) (2013) 053702. [153] M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Imaging and measuring the biophysical properties of Fc gamma receptors on single macrophages using atomic force microscopy, Biochem. Biophys. Res. Commun. 438 (4) (2013) 709714. [154] C.M. Stroh, A. Ebner, M. Geretschlager, G. Freudenthaler, F. Kienberger, A.S.M. Kamruzzahan, et al., Simultaneous topography and recognition imaging using force microscopy, Biophys. J. 87 (3) (2004) 19811990. [155] L.A. Chtcheglova, P. Hinterdorfer, Simultaneous AFM topography and recognition imaging at the plasma membrane of mammalian cells, Semin. Cell Dev. Biol. 73 (2018) 4556. [156] S. Senapati, S. Lindsay, Recent progress in molecular recognition imaging using atomic force microscopy, Acc. Chem. Res. 49 (3) (2016) 503510. [157] S. Senapati, S. Manna, S. Lindsay, P. Zhang, Application of catalyst-free click reactions in attaching affinity molecules to tips of atomic force microscopy for detection of protein biomarkers, Langmuir 29 (47) (2013) 1462214630. [158] P. Kaur, Q. Fu, A. Fuhrmann, R. Ros, L.O. Kutner, L.A. Schneeweis, et al., Antibody-unfolding and metastable-state binding in force spectroscopy and recognition imaging, Biophys. J. 100 (1) (2011) 243250. [159] C. Stroh, H. Wang, R. Bash, B. Ashcroft, J. Nelson, H. Gruber, et al., Single-molecule recognition imaging microscopy, Proc. Natl. Acad. Sci. USA 101 (34) (2004) 1250312507. [160] R. Zhu, A. Rupprecht, A. Ebner, T. Haselgrubler, H.J. Gruber, P. Hinterdorfer, et al., Mapping the nucleotide binding site of uncoupling protein 1 using atomic force microscopy, J. Am. Chem. Soc. 135 (9) (2013) 36403646. [161] S. Lee, J. Mandic, K.J. Van Vliet, Chemomechanical mapping of ligand-receptor binding kinetics on cell, Proc. Natl. Acad. Sci. USA 104 (23) (2007) 96099614. [162] M. Duman, M. Pfleger, R. Zhu, C. Rankl, L.A. Chtcheglova, I. Neundlinger, et al., Improved localization of cellular membrane receptors using combined fluorescence microscopy and simultaneous topography and recognition imaging, Nanotechnology 21 (11) (2010) 115504.

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2 Imaging and force detection of single deoxyribonucleic acid molecules by atomic force microscopy A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/9780323953603

2.1 Background It is well known that deoxyribonucleic acid (DNA) plays a vital role in life activities. Life depends on the ability of cells to store, retrieve, and translate the genetic instructions required to make and maintain a living organism, and this hereditary information in every living cell is stored in DNA [1]. A DNA molecule consists of two long polynucleotide chains composed of four types of nucleotide subunits (adenine, cytosine, guanine, and thymine) and each of the chains is called a DNA chain or a DNA strand. DNA guides the production of proteins which are not only the building blocks of cells but also carry out the majority of cellular functions necessary for life. When a cell needs a particular protein, the nucleotide sequence (called a gene) of the appropriate portion of the DNA is first copied into ribonucleic acid (RNA) (a process called transcription), and then the RNA is used as templates to direct the synthesis of the protein (a process called translation). DNA damage can be induced by exogenous physical agents (e.g., UV and other radiation sources, chemicals), by endogenous chemical genotoxic agents that are the products of metabolism, such as reactive oxygen species (ROS), or by spontaneous chemical reactions, such as hydrolysis

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[2]. DNA damage has a range of molecular consequences (e.g., genomic instability, telomere dysfunction, epigenetic alterations, proteostatic stress and compromised mitochondrial function) which can finally have marked consequences on cell fate decisions, particularly when driving cells into senescence [3]. Genomic instability is a key hallmark of cancer that arises owing to defects in the DNA damage response (DDR) and/or increased replication stress and these alterations promote the clonal evolution of cancer cells [4]. In the process of cancer metastasis, circulating tumor cells release cell-free DNA (cfDNA) and cell-free RNA (cfRNA) into the bloodstream [5]. Physical and molecular as well as topological features of cfDNA fragments and the patterns of methylation of these molecules bear information about their tissues of origin [6] and it is increasingly apparent in the communities of biomedicine that liquid biopsies involving cfDNA are becoming an efficient minimally invasive biomarker for the detection and monitoring of various diseases such as cancer and organ transplantation [7]. Consequently, developing novel methods and techniques to better characterize the structures and properties as well as behaviors of DNA molecules considerably benefits revealing the underlying mechanisms guiding life processes and human diseases. Traditionally, single-molecule fluorescence microscopy is widely utilized to probe the behaviors of DNA molecules in living cells [811]. Nevertheless, DNA molecules after fluorescent staining are not native and fluorescent labeling could probably influence the physiological activities of DNA molecules in living cells. Electron microscopy [12] and X-ray crystallography [13] have also been used to visualize the structures of individual DNA molecules, but they require a complex sample preparation process, and the obtained structures are essentially static. Compared with these methods, atomic force microscopy (AFM) has unique advantages. AFM is able to not only visualize the fine structures of single native DNA molecules but also can reveal the real-time structural dynamics of single DNA molecules under aqueous conditions in response to external stimuli. The mechanical properties of single DNA molecules can also be measured by AFM. In the past decades, AFM has been widely applied in characterizing the structures and properties of single DNA molecules [1417], which has yielded numerous novel insights into the behaviors of DNA that are inaccessible by other methods, offering novel possibilities for uncovering the underlying mechanisms guiding DNA activities and contributing much to the field of molecular biology.

2.2 Sample preparation methods The prerequisite of utilizing AFM to image DNA molecules is attaching DNA molecules onto a flat substrate and mica is by far the most

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commonly used substrate. The diameter of the DNA double helix is only 2 nm and is virtually constant along the entire length of the molecule [1]. Therefore, the substrate used for DNA imaging needs to be smooth enough to avoid the influence of substrate asperity on the imaging quality of AFM. Mica belongs to the family of clay minerals, and the crystal structure of mica is typically associated with KAl2(Si3Al) O10(OH)2 [18]. A bulk crystal of mica consists of negatively charged aluminosilicate layers in which the negative charge of the layers arises from a substitution of a quarter of the Si41 ions by Al31 ions. The negatively charged layers are kept together by interlayer potassium (K1) cations which compensate the charge. After cleavage along the layers, potassium cations are distributed on both sides, leaving uncompensated negative charges on both surfaces of mica [19]. Freshly cleaved mica is extremely smooth (the topography roughness is about 0.1 nm [20]) and is negatively charged, which makes it an ideal substrate for utilizing AFM to image positively charged biomolecules. Besides, mica can be easily cut to make a substrate with a desired size and shape [21]. The cleaved mica surface is also highly clean and there is no need for additional cleaning of the surface. These features make mica particularly suited to serve as the substrate for imaging biomolecules by AFM. Notably, since DNA molecules are also negatively charged, DNA molecules cannot naturally adsorb onto the mica surface. Therefore, special pretreatments of mica surfaces are required to attach DNA molecules onto the mica surface. There are two prevailing types of mica surface pretreatments to adsorb DNA molecules for AFM imaging, including divalent cation coating and chemical modification, which are described in the following. The first method of attaching DNA molecules onto mica surface is performing ionic treatment on mica surface. In this approach, cation is used to treat mica surface, which increases the affinity of the mica surface to negatively charged DNA molecules and allows reliable imaging of DNA molecules on the mica surface by AFM [22]. In 1992, Bustamante et al. [23,24] firstly acquired clear AFM topographical images of single circular DNA molecules by treating mica with Mg21. For doing this, freshly cleaved mica is soaked in magnesium acetate overnight to favor the replacement of potassium ions by magnesium in the mica surface so as to provide a stronger binding site with the phosphate groups of DNA molecules. The mica is then sonicated in pure water to remove the excess salts from the surface, after which the mica surface is glow discharged under vacuum to harden the substrate. As soon as the mica is brought up to air, the DNA solution is deposited onto the mica surface, which will result in the firm adsorption of DNA molecules on the mica surface for AFM imaging. This method also allows imaging DNA molecules in propanol and results have shown

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that imaging plasmid DNA in propanol gives a better spatial resolution of the structural details of DNA strands [25]. In 1995, Hansma et al. [26] showed that pretreating mica surface with NiCl2 enables imaging individual DNA molecules and their conformational changes in buffer solution. Further studies revealed that the binding of DNA molecules to mica surface is correlated with the radius of the transition metal cation for imaging DNA molecules in aqueous conditions by AFM [27]. Ni21, ˚ , can effecCo21, and Zn21, which have ionic radii from 0.69 to 0.74 A tively attach DNA molecules to mica for AFM imaging in liquid. For ˚ , DNA binds weakly to mica. For Mn21, whose ionic radius is 0.82 A 21 ˚ ˚ ), Cd (the ionic radius is 0.97 A) and Hg21 (the ionic radius is 1.1 A which have a larger ionic radius, DNA molecules do not bind to mica surface at all. In 2013, Alonso-Sarduy et al. [28] utilized AFM to observe the dynamic changes of single DNA molecules in response to drug molecules in aqueous conditions. For doing this, freshly cleaved mica is firstly treated with NiCl2, and then Na1 and Mg21 are used to adjust the binding strength between DNA molecules and Ni21-treated mica surface to an appropriate level, which enables the adsorption of DNA molecules to mica surface for AFM imaging while simultaneously allowing them to undergo conformational changes. In 2019, Heenan et al. [29] developed a protocol for imaging DNA molecules in liquid by AFM based on ionic treatments, which contains three main steps. First, the freshly cleave mica is treated by Ni21, ant then DNA molecules are deposited onto the Ni21-treated mica at biochemically relevant ionic conditions (Mg21, K1). Finally, the sample is transferred to imaging buffer for AFM imaging. The whole sample preparation process takes about 5 min and the experimental results showed that this sample preparation method allows AFM imaging of DNA molecules with a high signal-to-noise ratio (SNR). The second method of attaching DNA molecules onto mica surface is performing chemical functionalization on mica surface. In 1993, Lyubchenko et al. [30] firstly developed a sample preparation process based on the use of 3-aminopropyltriethoxysilane (APTES), allowing AFM imaging of DNA molecules in air and under water. For doing this, freshly cleaved mica is placed in the APTES atmosphere created by a small pool of APTES in the bottom of a glass desiccator left at ambient temperature for 2 h. Treating mica surface with APTES results in a positively charged surface aminopropyl mica due to the protonation of the surface immobilized amino groups [21]. APTES-treated mica surfaces remain positively charged even at alkali pH values (pKa 5 10.4), allowing attachment of negatively charged DNA molecules onto mica surface in the pH range of the DNA duplex stability [22]. The drawback of APTES-treated mica is that APTES hydrolysis in water complicates the AFM imaging in aqueous solution particularly

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for time-lapse AFM imaging of protein-DNA interactions [14]. In order to address this issue, 1-(3-aminopropyl)silatrane (APS) has been developed to treat mica surface, which is stable and resistant to polymerization in water, allowing AFM imaging for a wide range of protein-DNA complexes [31]. However, APS is not commercially available and needs to be synthesized [22]. The process of APS synthesis, purification, storage, and use is described in the reference [32]. A notable point for real time monitoring of DNA dynamics in aqueous solution is the DNA-mica binding strength and DNA behaviors [16]. If DNA molecules are weakly bound to mica surface, the scanning AFM tip could remove DNA molecules from the surface, which will influence AFM imaging. The stronger binding between DNA molecules and mica surface will produce better spatial resolution of AFM images. However, attaching DNA molecules too strongly to the substrate will compromise DNA functions and inhibit their conformational changes in response to external stimuli. Therefore, a delicate balance between AFM imaging resolution and DNA functions has to be found in practice for experimental purposes.

2.3 Topographical imaging of single DNA molecules and events AFM is able to resolve the exquisite morphological structures of single DNA molecules with unprecedented spatial resolution. The topological properties of DNA molecules, which are defined by how the two complementary single strands are intertwined, influence the mechanical and biochemical interactions of DNA molecules and have been found to play an important role in DNA metabolism and chromatin architecture within the cell [33,34]. With the use of AFM, the diverse supercoiling structures of single DNA molecules can be clearly visualized [22], such as plectonemic supercoiled plasmid DNA (Fig. 2.1A), cruciform plasmid DNA (Fig. 2.1B), intramolecular DNA triplex (H-DNA) (Fig. 2.1C) and so on, showing the exciting capabilities of AFM in revealing local conformational structures within a long DNA molecule. The substructures of DNA double helix can further be obtained by AFM high-resolution imaging techniques in aqueous condition. In 2012, Leung et al. [35] used miniaturized AFM cantilever (the cantilever thickness was 250 nm, and the cantilever length was 11 μm) to reduce the noise when detecting the tip-sample forces, which substantially improved the spatial resolution of AFM imaging of biomolecules and the groove structures of DNA chains were clearly discerned from the AFM images (Fig. 2.1D). In 2013, Ido et al. [36] obtained the clear helix structures of single DNA molecules by using frequency modulation AFM (FM-AFM) which measures the resonance frequency shift of the oscillating cantilever to sense the tip-sample interaction forces. The resonance

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FIGURE 2.1

Visualizing the fine structures of single DNA molecules by atomic force microscopy (AFM). (A)(C) AFM imaging revealing the different types of supercoiling structures of DNA. (A) Supercoiled plasmid DNA. (B) Cruciform plasmid DNA. White arrow indicates the cruciform. (C) H-DNA. White arrow indicates the sharp kink at the base of a thick protrusion. The inset shows the model for H-DNA. Images were obtained in air at tapping mode on APTES/APS-treated mica. (D) AFM images of 3486 bp plasmid DNA. (Top) Large-size scan of the whole DNA. (Bottom) Small-size scan of the double helix of DNA. Green arrows indicate the two strands of the double helix, separated by the minor groove (depth # 0.1 nm). The major groove (depth B0.2 nm) separates the subsequent turns of the double helix. Images were obtained in buffer solution (1 mM NiCl2, 10 mM HEPES, pH 7.0) on Ni21-treated mica. (E and F) FM-AFM images of plasmid DNA. (E) A large-size scan AFM topographical image of plasmid DNA (2686 base pairs). (F) High-resolution image showing the helix structures of single plasmid DNA. Red and blue arrows indicate the positions of major and minor grooves of B-DNA, respectively. Gray arrow indicates the local melting region of the plasmid DNA. The inset shows the molecular structure of B-DNA. Images were obtained in aqueous solution (50 mM NiCl2). (G) AFM image of the double helix structure of DNA molecules acquired using a highly sharp tip. Images were obtained in buffer solution (10 mM NiCl2, 25 mM KCl, 10 mM HEPES, pH 7.5). Sources: (AC) Reprinted with permission from Y.L. Lyubchenko, Preparation of DNA and nucleoprotein samples for AFM imaging, Micron 42(2) (2011) 196206. Copyright 2010 Elsevier Ltd. (D) Reprinted with permission from C. Leung, A. Bestembayeva, R. Thorogate, J. Stinson, A. Pyne, C. Marcovich, et al., Atomic force microscopy with nanoscale cantilevers resolves different structural conformations of the DNA double helix, Nano Lett. 12(7) (2012) 38463850. Copyright 2012 American Chemical Society. (E and F) Reprinted with permission from S. Ido, K. Kimura, N. Oyabu, K. Kobayashi, M. Tsukada, K. Matsushige, et al., Beyond the helix pitch: direct visualization of native DNA in aqueous solution, ACS Nano 7(2) (2013) 18171822. Copyright 2013 American Chemical Society. (G) Reprinted with permission from P.R. Heenan, T.T. Perkins, Imaging DNA equilibrated onto mica in liquid using biochemically relevant deposition conditions, ACS Nano 13(4) (2019) 42204229. Copyright 2019 American Chemical Society.

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frequency shift is sensitive to the forces acting on the probe tip at the closest approach distance to the sample surface during an oscillation cycle, and thus FM-AFM has improved force sensitivity compared with conventional amplitude modulation AFM. From the obtained AFM images, the deep grooves between the sugar-phosphate backbones of DNA are clearly resolved (Fig. 2.1F). Two distinct types of grooves with different widths appeared alternatively, which were attributed to the major and minor grooves of DNA molecules. Notably, a recent study [29] has shown that the clear-cut helix structures of DNA molecules can be obtained in aqueous conditions by using a tip featuring a sharp tip radius (the nominal radius was about 2 nm) (Fig. 2.1G), vividly showing that the tip size of AFM probe is a determinant of the spatial resolution of AFM imaging. These studies remarkably demonstrate that AFM is a powerful tool to image the molecular and structural conformations of single native DNA molecules at the nanoscale under near-physiological conditions, which has important implications for the studies of DNA topology. AFM topographical imaging benefits visually understanding the molecular mechanisms of DNA-targeted drugs. DNA is the target for many anticancer drugs (such as platinum complexes and DNA intercalating agents) and these drugs are viewed as broadly cytotoxic agents [37]. DNA-targeted anticancer drugs are some of the most effective agents in clinical use and have produced significant increases in the survival of cancer patients when used in combination with drugs that have different mechanisms of action [38]. Novel DNA-targeted agents are being developed for cancer therapeutics and the underlying mechanisms of DNA-targeted anticancer drugs are still not fully understood [39]. In addition to itself as a drug target, DNA-related components such as proteins involved in the DDR system have been recently identified as promising avenues for targeted cancer therapeutics [40]. AFM offers a novel way to characterize the detailed behaviors of single DNA molecules in response to DNA-targeted agents, which is extremely meaningful for understanding the actions of anticancer drugs. In 1998, Onoa et al. [41] used AFM to investigate the effects of metal complexes on DNA conformations. Various metal complexes were incubated with DNA for 24 h at 37 C and then the DNA-metal complex solution was deposited on freshly cleaved mica. AFM images of regular DNA molecules and drugtreated DNA molecules were obtained in the air. The experimental results significantly showed the various structural changes of DNA molecules treated by different metal complexes (e.g., cisplatin-induced shortening of DNA molecules, transplatin caused shortening and compaction of DNA molecules, aggregation of DNA strands was observed for platinumfamotidine compound but not for palladium-famotidine compound or the metal-free famotidine), indicating the potentials of AFM in evaluating the molecular effects of therapeutic agents. In 2009, Hou et al. [42] also used

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AFM to visualize the structural changes of single DNA molecules treated by cisplatin and revealed the relationship between DNA conformational changes and cisplatin concentrations. These studies [41,42] were performed on linear DNA molecules. The effects of cisplatin on plasmid DNA have also been investigated [43], as shown in Fig. 2.2. Cisplatin solution and plasmid DNA solution were mixed and incubated for a certain time (30 min, 60 min) at room temperature. Subsequently, the plasmid DNA solution was deposited on APTES-treated mica. AFM images of plasmid DNA molecules were then obtained in the air. We can see that plasmid DNAs curl more and have more supercoiled structures after the treatment of cisplatin (Fig. 2.2B) for 30 min compared with plasmid DNAs without drug stimulation (Fig. 2.2A). Increasing the time of cisplatin treatment further causes the rupture of plasmid DNAs (Fig. 2.2C). The results clearly show the dynamic conformational changes of individual plasmid DNA molecules in response to cisplatin, deepening our understanding of chemotherapy agents.

FIGURE 2.2 Atomic force microscopy topographical images of cisplatin-induced conformational changes of single plasmid DNA molecules. (A) Plasmid DNAs from the control group (without cisplatin). (B and C) Plasmid DNAs after cisplatin treatments. (B) Treatment with 5 ng/μL cisplatin for 30 min. (C) Treatment with 5 ng/μL cisplatin for 60 min. Source: Reprinted with permission from M. Li, L. Liu, X. Xiao, N. Xi, Y. Wang, The dynamic interactions between chemotherapy drugs and plasmid DNA investigated by atomic force microscopy, Sci. China Mater. 60(3) (2017) 269278. Copyright 2017 Science China Press and Springer-Verlag Berlin Heindelberg.

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AFM is also able to visualize the binding events between DNA molecules and protein molecules. The DNA behaviors require the involvement of numerous DNA-binding proteins and the proteinDNA interactions largely dominate the organization of DNA strands into higher-order structures [44]. These DNA-binding proteins have diverse roles and may function as structural proteins making up the nucleosome, enzymes modulating chromatin structure to control gene expression, transcription factors, and also as cofactors [45], which are eventually responsible for the regulation of key biological functions in all cells such as transcription, translation, replication, and recombination [46]. Identifying the specific sequences of DNA molecules that proteins bind can help to elucidate regulatory networks within cells and how genetic variation can cause disruption of normal gene expression, which is often associated with diseases [47]. AFM topographical images of proteinDNA interactions provide protein binding specificity and affinity, protein-induced DNA bending, and protein binding stoichiometry, which improve our understanding of how proteins interact with DNA to recognize their cognate binding sites [48]. In 2006, Lushnikov et al. [49] used AFM to investigate the interactions between SfiI restriction enzyme and DNA molecules under noncleaving reaction conditions (Ca21 instead of Mg21 in the reaction buffer). For doing so, the DNA solution was mixed with SfiI solution in a 1:1 ratio in the reaction buffer containing 2 mM CaCl2 instead of MgCl2 to prevent DNA cleavage, and the mixture was incubated for 15 min at room temperature. After incubation, the mixture was chemically fixed by 0.5% glutaraldehyde to cross-link the complex, which was then purified by filtration. The filtrate was then deposited on APS-treated mica and AFM images of SfiI-DNA complexes were obtained in the air. AFM images clearly reveal the looped morphology with a bright spot at the crossover, indicating the binding of SfiI to DNA. Analysis of the AFM images shows that DNA recognition sites are crossed at an angle of 60 degrees and the two different relative orientations of the recognition sites are equally populated in the SfiI-DNA complexes. In 2008, Tessmer et al. [50] used AFM to investigate the interactions between DNA and MutS which is a mismatched DNA repair protein and the experimental results evidently provide a structural explanation for the mechanisms by which MutS searches for and recognizes mismatches. Notably, these studies [49,50] were performed in the air which is unable to observe the real-time dynamics of proteinDNA interactions. In 2019, Heenan et al. [29] obtained AFM images of proteinDNA complexes in aqueous conditions, as shown in Fig. 2.3. The three-step process of sample preparation for imaging DNA molecules on Ni21-treated mica in liquid by AFM was firstly established (Fig. 2.3A). This method used biochemically relevant deposition condition in which DNA’s configuration was more extended, thus facilitating easier analysis of DNA behaviors from AFM images. With this method, both single DNA molecules and single proteinDNA complexes (Fig. 2.3B, C, D)

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FIGURE 2.3 Imaging protein-DNA complexes by AFM in aqueous conditions. (A) Rapid three-step protocol for preparing DNA for imaging on mica in liquid. (B)(D) AFM images of BspMI (a type of restriction enzyme)-DNA complexes acquired in buffer solution. (B and C) Images showing the binding of BspMI to a long DNA via the single recognition site located on DNA. (D) Image showing two separate DNA molecules bridged via a BspMI complex bound to two recognition sites. Green arrows indicate the binding sites. Source: Reprinted with permission from P.R. Heenan, T.T. Perkins, Imaging DNA equilibrated onto mica in liquid using biochemically relevant deposition conditions, ACS Nano 13 (4) (2019) 42204229. Copyright 2019 American Chemical Society.

could be reliably imaged by AFM in liquid, opening novel possibilities for in situ observation of proteinDNA interactions.

2.4 Time-lapse imaging of individual DNA molecular dynamics Time-lapse AFM topographical imaging of DNA molecules in liquid provides an invaluable tool to understand the dynamics of DNA behaviors. Supercoiling and changes in the supercoiling state are ubiquitous in cellular DNA and affect virtually all genomic processes [51], for example, the interactions between DNA and other biomolecules often cause local changes in DNA structures which subsequently affect DNA and cell functions. Time-lapse AFM imaging provides direct evidence of the dynamics of single DNA molecules during physiological or pathological processes,

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which is of considerable significance for understanding the biology of DNA. In 2013, Alonso-Sarduy et al. [28] used a time-lapse AFM imaging technique to investigate drug-induced DNA conformational changes, as shown in Fig. 2.4A. NiCl2-treated freshly cleaved mica was placed in the

FIGURE 2.4

Visualizing the dynamic processes of individual DNA molecule by time-lapse AFM topographical imaging. (A) AFM images of drug-induced DNA conformational changes. (I, II, III) Representative AFM images of pBR322 plasmid DNA molecules treated with different concentrations of Dau. (I) 0. (II) 2.5 μM. (III) 10 μM. Wr denotes the writhe of DNA. (IV) Consecutive AFM images of the conformational changes of single plasmid DNA induced by 250 μM Dau. (B) Visualizing the structural and dynamic diversity in supercoiled DNA minicircles. (I, II, III) High-resolution AFM images of natively supercoiled DNA minicircles of 339 bp showing their helical structure and disruptions of canonical B-form DNA (denoted by red arrowheads). (IV) Time-lapse AFM images of a natively supercoiled 339 bp DNA minicircle recorded at 3 min per frame. White arrows denote the fast scan direction of AFM imaging. (C) Real-time visualization of DNA wrapping around histone H2A by high-speed AFM. (I) Successive high-speed AFM topographical images showing the dynamics of the interactions between single DNA molecule and single histone H2A. (II) Four distinct interaction patterns observed from AFM images. Sources: (A) Reprinted with permission from L. Alonso-Sarduy, G. Longo, G. Dietler, S. Kasas, Time-lapse AFM imaging of DNA conformation changes induced by daunorubicin, Nano Lett. 13(11) (2013) 56795684. Copyright 2013 American Chemical Society. (B) Reprinted with permission from A.L.B. Pyne, A. Noy, K.H.S. Main, V. Velasco-Berrelleza, M.M. Piperakis, L.A. Mitchenall, et al., Base-pair resolution analysis of the effect of supercoiling on DNA flexibility and major groove recognition by triplex-forming oligonucleotides, Nat. Commun. 12 (2021) 1053. Copyright 2021 The Authors. (C) Reprinted with permission from G. Nishide, K. Lim, M.S. Mohamed, A. Kobayashi, M. Hazawa, T. Watanabe-Nakayama, et al., High-speed atomic force microscopy reveals spatiotemporal dynamics of histone protein H2A involution by DNA inchworming, J. Phys. Chem. Lett. 12(15) (2021) 38373846. Copyright 2021 American Chemical Society.

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solution (10 mM Tris with pH 8.0, 2 mM MgCl2, 10 mM NaCl, and 1 μg/mL pBR322 DNA molecules), and AFM topographical images of DNA molecules were obtained in the same solution. Time-lapse AFM imaging was performed by slowly injecting drug solution into the fluid chamber of AFM via a microfluidic injection system. The injection system had two syringes which were mounted back-to-back and could move simultaneously, such that the quantity of liquid injected into the chamber was equal to the quantity of liquid removed from the chamber to maintain the constant fluid volume in the chamber. The effects of daunorubicin (Dau) on DNA structures were firstly imaged (I, II, III in Fig. 2.4A), and the results showed that Dau caused the relaxation of DNA molecules and the increase of DNA writhe (Wr). Subsequently, time-lapse AFM imaging captured the dynamic changes caused by Dau on a plasmid DNA molecule (IV in Fig. 2.4A), clearly showing that the plasmid DNA proceeded through a series of transitions in which their degree of negative supercoiling decreased and then reversed to positive supercoiling. In 2021, Pyne et al. [52] investigated the structural and dynamic diversity in supercoiled DNA minicircles by time-lapse AFM imaging, as shown in Fig. 2.4B. Highresolution AFM images recorded in liquid showed the individual DNA minicircles with sufficient resolution to resolve the two oligonucleotide strands of the double helix (I, II, III in Fig. 2.4B), allowing observing the local conformational changes such as disruptions of individual plasmid DNA. Time-lapse AFM images (IV in Fig. 2.4B) visualized the dynamic behaviors of single DNA minicircle caused by thermal fluctuations within supercoiled DNA and further, the interactions between DNA minicircle and DNA-binding ligands were revealed, providing mechanistic insight into how DNA supercoiling could affect molecular recognition. High-speed AFM time-lapse imaging brings great breakthroughs in imaging the dynamic activities of single DNA molecule. It takes dozens of seconds [28] or several minutes [52] to acquire an AFM topographical image of single DNA molecules with conventional AFM, which is much slower than that of DNA activities and thus many dynamic events taking place in the process of DNA activities are missing. High-speed AFM records an AFM image at a millisecond time scale, which is much closer to that of DNA activities and thus allows the identification of novel mechanisms regulating DNA behaviors. In 2011, Miyagi et al. [53] applied high-speed AFM to investigate the nucleosome dynamics in aqueous conditions. For doing this, nucleosome solution was dropped onto the APS-mica and incubated for 5 min. Subsequently, after rinsing the mica with imaging buffer (10 mM HEPES with pH 7.5, 4 mM MgCl2), successive AFM imaging was performed in the imaging buffer. The experimental results obtained at the speed of 1 frame per second clearly visualized the dynamic unwrapping process of single nucleosome in less than 1 min and transient states of the unwrapping process

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were further revealed at the elevated scanning speed of high-speed AFM. In 2021, Nishide et al. [54] investigated the dynamic DNA-histone H2A interactions by high-speed AFM, as shown in Fig. 2.4C. High-speed AFM time-lapse images significantly showed the real-time dynamics of the touching-sliding-sandwiching-wrapping of shortlinearized dsDNA on histone H2A. Strong electrostatic attraction between histone H2A and DNA was sufficient to initiate spontaneous wrapping without the necessity of ATP energy sources. After the contact of the DNA strand on the histone H2A due to the electrostatic attraction, the DNA strand was dragged forward and histone H2A slid along the DNA strand. When the two edges of DNA touched histone H2A, the topology changed from sliding to sandwiching. The DNA strand continued to slide along the surface of histone H2A until a protruded segment of the DNA strand was dragged back to histone H2A, which caused the formation of wrapping topology, directly providing dynamic details of DNA-histone interactions. These studies show the potent capabilities of high-speed AFM time-lapse imaging in capturing the rapid and transient dynamics of DNA-protein interactions, which significantly improves our understanding of DNA behaviors.

2.5 Extracting the persistence length of DNA molecules from atomic force microscopy images The persistence length of DNA can be extracted by analyzing the AFM topographical images of DNA molecules. The persistence length of a polymer is equal to half of the Kuhn length of the polymer. The Kuhn length of a polymer is defined as the ratio of the mean-square end-to-end distance and the fully extended size [55]. Therefore, the persistence length reflects the flexibility or stiffness of a polymer chain. The flexibility of polymer chains originates from the covalent bonds linking the units together, which gives polymer products unique properties [56]. Studies have revealed that there is a close relationship between polymer flexibility and the performances of polymer materials [57], and polymer chain stiffness has distinct effects on the polymer chain conformation [58]. Identifying the origin of the local flexibility of polymers has been considered as a promising way to improve the bottom-up design of polymer materials [59]. Hence, developing methods for better characterizing the mechanical properties of polymers is particularly meaningful for understanding the behaviors of polymers. Persistence lengths of polymers can be measured in solution by light-scattering or viscosity assays, but it is increasingly common to calculate them using computerized molecular modeling methods [56]. The flexibility of a polymer changes with temperature because at higher temperatures larger fluctuations of bond angle

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take place and more high-energy conformations occur. The molecular modeling methods are advantageous in that the effective temperature of the polymer can be varied over a much greater range than is available with experimental measurements, whereas knowledge of the variation of the persistence length with temperature is important in understanding the behaviors of polymers. Directly measuring the persistence length of polymers such as DNA molecules from AFM images provides an alternative way to characterize the mechanical properties of polymers. The advantage of AFM-based methodology is that measurements are performed on individual polymer molecules with high precision [60], which benefits the comparison between experimental measurements and theoretical calculation and facilitates a comprehensive understanding of polymer mechanics. In 1996, Rivetti et al. [61] used AFM imaging to investigate the persistence length of DNA molecules. Persistence lengths of DNA molecules were extracted from AFM images of DNA molecules obtained in the air by using the WLC model. The experimental results showed that DNA molecules deposited onto untreated, freshly cleaved mica were able to equilibrate on the surface. When the DNA molecules were deposited on glow-discharged mica or water-treated mica, DNA molecules condensed and did not equilibrate on the surface, revealing the influence of the deposition process on DNA flexibility. In 2006, Wiggins et al. [62] used AFM to investigate the flexibility of DNA molecules on short-length scales and presented a novel model called linear subelastic chain (LSEC). The results showed that LSEC could better characterize the bending behaviors of short DNA molecules than the WLC model. Besides, both LSEC and WLC models could well characterize the bending behaviors of long DNA molecules. In 2010, Liu et al. [63] investigated drug-induced changes in the flexibility of DNA molecules and the experimental results showed that cisplatin treatment caused a significant decrease in the persistence length of DNA molecules, revealing the effects of anticancer drug molecules on DNA mechanics. Notably, these studies [6163] were performed in air, which is different from the aqueous conditions in which traditional bulk methods (such as fluorescence recovery [64] and gel electrophoresis [65]) are used to measure the persistence length of DNA molecules, causing that the obtained results might be different from the results obtained by bulk methods. In 2017, Murugesapillai et al. [66] acquired AFM images of single DNA molecules deposited on APTEStreated mica in liquid and then applied a three-dimensional WLC model to extract the persistence length of DNA molecules. The experimental results showed that the calculated persistence lengths of DNA molecules were quite consistent with that measured by optical tweezers, remarkably demonstrating the effectiveness of the presented procedure based on AFM imaging in aqueous conditions to characterize the accurate flexibility of DNA and DNAprotein molecules.

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The persistence length of DNA molecules is obtained by analyzing the AFM images of DNA molecules with the WLC model. Typically, the persistence length of DNA molecules can be obtained via different measures all derived from WLC mode, and the two prevailing measures are mean-square end-to-end distance and tangent vector correlation [61,6770] (as shown in Fig. 2.5C): 

2P  L 1 2 e22P hR2 ðLÞi2D 5 4PL 1 2 (2.1) L hcosθðLÞi2D 5 e22P L

(2.2)

where L is the contour length along the DNA between two points on DNA, P is the persistence length of DNA, , R2(L) . is the mean-square end-toend distance between two points, and θ is the angle between two tangent vectors (t1, t2) separated by L along the DNA. The above formulas [(2.1) and (2.2)] correspond to the two-dimensional WLC model. In three dimensions, the molecule can also bend in a direction perpendicular to the plane, and the formulas of the three-dimensional WLC model become: 

P L 1 2 e2P hR2 ðLÞi3D 5 2PL 1 2 (2.3) L hcosθðLÞi3D 5 e2P L

(2.4)

FIGURE 2.5 Calculating the persistence length of DNA molecules from AFM images. (A) A typical AFM topographical image of DNA molecules. (B) AFM image is converted into a gray image and DNA molecules in the image are fitted by splines. (C) Illustration of two commonly used measures (mean-square end-to-end distance and tangent vector correlation) for two points on a DNA molecule to calculate the persistence length of DNA molecules. Sources: (A and B) are reprinted with permission from J.P. Peters, L.J. Maher, Approaches for determining DNA persistence length using atomic force microscopy, Methods Mol. Biol. 1837 (2018) 211256. Copyright 2018 Springer Nature. (C) Reprinted with permission from M. Schneider, A. Al-Shaer, N.R. Forde, AutoSmarTrace: Automated chain tracing and flexibility analysis of biological filaments, Biophys. J. 120(13) (2021) 25992608. Copyright 2021 Biophysical Society.

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So far there are several open-source software programs [70,71] which provide user-friendly and efficient tools to determine the persistence lengths of polymer chains from AFM images. With the use of these programs, researchers can easily get the persistence length values of polymer molecules according to the step-by-step instructions. Briefly, after obtaining substantial AFM topographical images of DNA molecules, these images (Fig. 2.5A) are loaded into the software. AFM images are often grayed (Fig. 2.5B) to facilitate analysis with image processing algorithms. For an AFM image, each DNA molecule in the image is fitted by a parametric spline (typically denoted by the red curve in Fig. 2.5B). The spline is then randomly divided into nonoverlapping segments (denoted by the blue dashed lines). For a molecule whose ends are not clear or are in touch with (or crossed over by) other molecules, subsections of the molecule can also be fitted by spline for analysis [68]. For all segments of a given contour length L, the mean and standard error of , R2(L) . and , cosθ(L) . are determined, which are then fitted by the WLC model to give the persistence length of DNA molecules.

2.6 Mechanically unzipping single DNA molecules by atomic force microscopy force spectroscopy AFM is able to manipulate single DNA molecules to sense the mechanical forces of DNA molecules. DNA molecules are often bent, twisted, supercoiled and stretched during their biological processes due to the impacts of different mechanical forces arising from their microenvironments, and a deep insight into the role of mechanical forces in regulating DNA structural transitions has important implications for DNA-based nanotechnological applications, such as rational drug design, programmable molecular machines, and DNA origami [72]. Traditionally, the studies of DNA mechanics are performed in bulk experiments, whereby large numbers of molecules are sampled simultaneously, making it difficult to resolve the detailed mechanical cues that emerge during the biological reactions of single DNA molecules [73]. The developments of single-molecule techniques (such as AFM, optical tweezers, and magnetic tweezers) [74] allow researchers to directly measure the mechanical forces generated during the activities of single DNA molecules and even to exert mechanical forces on individual DNA molecules to alter the fate of these activities, which provide a new perspective of the mechanical properties of the DNA double helix [75], significantly benefiting understanding the underlying relationship between DNA mechanics and DNA structural transitions [76]. For more descriptions of the mechanical studies of single DNA molecules by optical/magnetic tweezers, readers are referred to the literatures [74,77,78]. Here we focus on the utilization of AFM to probe the mechanical forces of single DNA molecules. In 1999, Rief et al. [79] firstly used AFM-based SMFS (the technical details of

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AFM-based SMFS are shown in Chapter 1) to measure sequence-dependent forces of DNA by mechanically stretching single DNA double chains. DNA molecules were adsorbed on a gold surface, and an individual DNA strand was picked up with an AFM tip by applying a contact force of several nanonewtons (nN). Subsequently, the DNA strand was stretched between the gold surface and the AFM tip during the retraction process of the AFM cantilever, resulting in the specific changes of force peaks in the force curves recorded during the SMFS assay. Based on this method, the base-pairing forces were directly measured. The experimental results showed that the base pair-unbinding forces for G-C and A-T were (20 6 3 pN) and (9 6 3 pN), respectively. Also in 1999, Strunz et al. [80] performed AFM dynamic force spectroscopy of single DNA molecules to examine the loading rate dependence of the unbinding forces between complementary DNA strands to get information about the energy profile of the separation path, as shown in Fig. 2.6. For doing so, complementary oligonucleotides were

FIGURE 2.6 Measuring the forces to mechanically separate a DNA chain from its complementary chain by AFM-based SMFS. (A) Schematic diagram of the single DNA force measurements by AFM. The complementary single strands of a DNA are immobilized on an AFM tip and a surface via their 50 -ends by PEG linker molecules. On approach of the surface to AFM tip, a duplex may form which is then stretched in the retract process until an unbinding occurs. (B) A typical force curve obtained during the approach-retract process showing an unbinding event. The inset shows a force curve in which two DNA molecules unbind one after the other. (C) The dependence of the most probable unbinding force on the retract velocity for AFM tip against a substrate linked with different DNA oligomers (10 bp, 20 bp, 30 bp) and linear fits to the respective data sets. The inset shows that the maximum of the unbinding force distribution for the duplex (10 bp) is shifted from 21 to 41 pN (from Gaussian fits) when increasing the retract velocity from 8 to 1600 nm/s. Source: Reprinted with permission from T. Strunz, K. Oroszlan, R. Schafer, H.J. Guntherodt, Dynamic force spectroscopy of single DNA molecules, Proc. Natl. Acad. Sci. USA 96(20) (1999) 1127711282. Copyright 1999 National Academy of Sciences.

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covalently immobilized onto the AFM tip and a substrate via a 30-nm-long PEG cross-linker, respectively (Fig. 2.6A). The use of a PEG cross-linker was to reduce unspecific forces between the AFM tip and substrate. Besides, oligonucleotides containing no self-complementary regions were used to facilitate the interpretation of the data. The unbinding forces between the oligonucleotide and itself were compared with that between the oligonucleotide and its complement to confirm the specificity of the measured unbinding forces. The specific unbinding events were clearly discernible from the obtained force curves (Fig. 2.6B), which often caused the nonlinear elastic behaviors of the PEG linker. The unbinding forces were measured at five or six different values of the retraction velocity in the range between 8 and 2000 nm/s while the approach velocity was kept constant at 100 nm/s. By a linear fit of the measured forces and the logarithm of the loading rate (Fig. 2.6C), the thermal dissociation rates of the DNA duplexes were obtained and a single energy barrier along the mechanical separation path was revealed. These studies give excellent templates for utilizing AFMbased SMFS to investigate the mechanical forces and the thermodynamics involved in the specific binding interactions of DNA molecules and complexes, which provide a novel approach to detect DNA mechanics at the single-molecule level and have general impacts on the studies of DNA behaviors and DNA-based applications. AFM-based SMFS has been utilized to investigate the role of mechanical cues in various DNA-related activities. The conformational changes of DNA molecules are often accompanied by alterations in the mechanical properties of DNA molecules. In 2000, Krautbauer et al. [81] investigated the mechanical changes of single DNA molecules after the stimulation of cisplatin. For doing so, cisplatin solution was added to a DNA-containing solution and incubated to react for 24 h at 37 C in darkness. After the reaction, the DNA molecules were adsorbed onto a gold substrate and dried in air. AFM-based SMFS experiments were then performed on the sample in Tris buffer solution (10 mM, pH 8.0) containing NaCl (150 mM) and EDTA (1 mM). There were significant differences between the force curves obtained on untreated DNA molecules and that obtained on cisplatin-treated DNA molecules, showing that cisplatin inhibited the permanent mechanical separation of the DNA double helix. Further SMFS experiments performed on synthetic DNA molecules with specific base compositions revealed the sequence specificity of the cisplatin. The study shows the great potential of AFM-based SMFS as an analytical tool for obtaining new structural information about DNA and its interaction with binding agents. In 2002, the same group investigated the unzipping dynamics of double-stranded DNA molecules with different sequences [82]. The experimental results showed that the force profiles were remarkably characteristic for each DNA sequence and could be described quantitatively using a thermodynamic equilibrium model, demonstrating

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that DNA base composition could be discriminated in the unzipping force signal with an unprecedented resolution of about 10 base pairs in both synthetic and naturally occurring sequences. In 2015, Aschenbrenner et al. [83] combined AFM with molecular force assay (MFA) to investigate the effects of pyrimidine modifications on the mechanical stability of DNA molecules. AFM-based SMFS was employed to characterize the differences in the mechanical stability of short DNA duplexes with varying numbers of integrated propynyl bases. The experimental results showed that propynyl bases significantly increased the mechanical stability if the DNA molecules were annealed at high temperatures, whereas modified DNA complexes formed at room temperature and short incubation times displayed the same stability as nonfmodified DNA duplexes. The study provides a novel way to correlate DNA structures with DNA thermal and mechanical stability, which benefits the studies where DNA molecules are used as a programmable building block. In 2017, Liang et al. [84] used AFM-based SMFS assay to measure the strength and kinetics of DNAprotein complexes. For doing so, the DNAprotein complexes were adsorbed on a gold substrate and were then imaged in buffer solution by AFM at the PFT mode (the detailed descriptions of PFT mode are shown in Chapter 1). From the AFM images, the position of each point for collecting pulling data was determined and then SMFS assays were applied to the hundreds of positions to obtain the overall distribution of the interaction forces of DNA molecules, providing a novel idea for SMFS assays with high throughput.

2.7 Probing individual DNA behaviors on DNA origami nanostructures The advent of DNA origami technology provides a promising technique for bottom-up fabrication of well-defined nanostructures ranging from tens of nanometers to submicrometers [85]. Molecular self-assembly exists everywhere in the natural world and various molecules (e.g., peptides, proteins, DNA, lipids, organic molecules, and hybridization of metal ions and organic molecules) have been used as self-assembly building blocks to synthesize designer molecular structures or devices to perform desired functions [86]. Among these molecules, DNA is an excellent nanoscale building block because of its specific three-dimensional conformation, chemical addressability and predictable WatsonCrick base-pairing [87]. In 2006, Rothemund [88] presented a versatile and simple “one-pot” method for using numerous short single strands of DNA to direct the folding of a long, single strand of DNA into desired shapes that were roughly 100 nm in diameter and had spatial resolution of about 6 nm, and he termed this method “scaffolded DNA origami.” “Origami” is a Japanese word that means folding of a plain sheet into an arbitrary form having a specific

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dimension [89]. In brief, DNA origami involves raster-filling a designed shape using a long single-stranded scaffold DNA (most commonly the 7.3 kilobase genome of the M13 bacteriophage) with the help of hundreds of short oligonucleotides (typically 2050 nucleotides in length) called staple strands to hold the scaffold in place to form a prescribed shape after rapid heating followed by slow cooling over the course of an hour [90,91] (Fig. 2.7A). DNA origami has several important advantages as compared to traditional tile-based DNA assembly strategies [92,93]. The DNA origami method avoids stoichiometric dependence and thus eliminates the need for purification of the oligonucleotides and reduces the time required for synthesis. Besides, the DNA origami method is able to create more complex shapes and the formed nanostructures have well-defined dimensions and are fully addressable, allowing the attachment of molecules at prescribed positions for various applications. With the use of DNA origami technology, a wide range of nanostructures with user-defined shapes and features have been synthesized, such as two-dimensional planar patterns (Fig. 2.7B) [88], two-dimensional and three-dimensional wireframe nanostructures (Fig. 2.7C) [94], chiral plasmonic nanostructures [95], single-molecule navigator system [96] and so on. Particularly, DNA origami technology has been successfully used to create a nanoscale DNA box (42 3 36 3 36 nm3 in size) with a controllable lid (Fig. 2.7D) which can be opened in the presence of externally supplied DNA “keys” [97]. For doing so, the lid of the box was functionalized with a dual lock-key system composed of DNA duplexes with sticky-end extensions to provide a “toehold” for the displacement by externally added “key” oligonucleotides. Inspired by this study, researchers have used DNA dynamic box as an intelligent drug carrier to deliver therapeutic molecules to cells [98] and even for cancer treatments in vivo (Fig. 2.7E) [99], significantly advancing the studies of nanorobots for biomedical applications [100]. Besides, DNA origami has long been used to create devices in the 10100 nm scale [101] since its invention and this limit is being shattered now. A recent study by Yao et al. [101] has shown that a six-helix bundle DNA origami nanostructure in the submicrometer scale (called meta-DNA) could be used as a magnified analog of single-stranded DNA, which allows creating a range of complex static and dynamic structures in the submicrometer and micrometer scales and will enable new applications of DNA origami technology. Combining AFM with DNA origami technology offers novel possibilities for detecting the behaviors of single DNA molecules. In 2010, Endo et al. [102] combined AFM with DNA origami technology to observe the methylation reactions of single DNA molecules and the effects of tensions of DNAs on DNA methylation were examined, as shown in Fig. 2.8A. For doing so, a DNA scaffold was prepared using the DNA origami technology, which accommodated two different lengths of the double-stranded DNA fragments, a tense 64mer double

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FIGURE 2.7 DNA origami technology. (A) Principle of DNA origami. A long singlestranded scaffold DNA is annealed with multiple short staples (blue). The staples can bring together distant regions of the scaffold via base pairing (pairing sequences are marked red, orange, green and blue, for example), resulting in a prescribed shape. (B) DNA origami planar structures imaged by AFM. (I) Rectangle. (II) Star. (III) Disk with three holes. (IV) Triangle with rectangular domains. (V) Sharp triangle with trapezoidal domains. (C) DNA origami wireframe nanostructures imaged by AFM. (I, II, III) Platonic tiling based on hexagon (I), square (II) and triangle geometries (III), respectively. (IV) Star-shaped pattern without translational symmetry. (V) Three-dimensional wireframe Archimedean cuboctahedron. (D) DNA origami box with a lid. (I) Schematic illustration of the controlled open of the box lid. (II) AFM image of a box. (III) AFM image of a box in which one lid was left open. (E) DNA origami nanorobot for drug delivery. (I, II) AFM images of closed (I) and opened states (II) of DNA origami nanorobot. White circles denote the drug molecules loaded in the nanorobot. Sources: (A) Reprinted with permission from S. Dey, C. Fan, K.V. Gothelf, J. Li, C. Lin, L. Liu, et al., DNA origami, Nat. Rev. Methods Primers 1 (2021) 13. Copyright 2021 Springer Nature. (B) Reprinted with permission from P.W.K. Rothemund, Folding DNA to create nanoscale shapes and patterns, Nature 440(7082) (2006) 297302. Copyright 2006 Nature Publishing Group. (C) Reprinted with permission from F. Zhang, S. Jiang, S. Wu, Y. Li, C. Mao, Y. Liu, et al., Complex wireframe DNA origami nanostructures with multi-arm junction vertices, Nat. Nanotechnol. 10(9) (2015) 779784. Copyright 2015 Macmillan Publishers Limited. (D) Reprinted with permission from E.S. Andersen, M. Dong, M.M. Nielsen, K. Jahn, R. Subramani, W. Mamdouh, et al., Self-assembly of a nanoscale DNA box with a controllable lid, Nature 459(7243) (2009) 7376. Copyright 2009 Macmillan Publishers Limited. (E) Reprinted with permission from S. Li, Q. Jiang, S. Liu, Y. Zhang, Y. Tian, C. Song, et al., A DNA nanorobot functions as a cancer therapeutic in response to a molecular trigger in vivo, Nat. Biotechnol. 36(3) (2018) 258264. Copyright 2018 Nature America, Inc.

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FIGURE 2.8 Visualizing individual DNA molecular reactions by AFM on the scaffold constructed by DNA origami. (A) DNA methylation. (I) Schematic illustration of the incorporation of two different double-stranded DNAs into the DNA origami scaffold by self-assembly using the connection sites. (II) AFM images of self-assembled DNA frame without (left) and with two double-stranded DNAs (right). (III) Successive AFM images of the binding of M. EcoRI to 64mer double-stranded DNA. The white arrow denotes the M. EcoRI. One image was obtained every 1 s. Triangles in (II, III) denote the right-bottom lacking corner of the scaffold. (B) DNA recombination. (I) Schematic illustration of the DNA frame structure for the incorporation of loxP site-containing DNAs. (II) Successive AFM images of the recombination events. The imaging rate was 1 frame per second. Sources: (A) Reprinted with permission from M. Endo, Y. Katsuda, K. Hidaka, H. Sugiyama, Regulation of DNA methylation using different tensions of double strands constructed in a defined DNA nanostructure, J. Am. Chem. Soc. 132(5) (2010) 15921597. Copyright 2010 American Chemical Society. (B) Reprinted with permission from Y. Suzuki, M. Endo, Y. Katsuda, K. Ou, K. Hidaka, H. Sugiyama, DNA origami based visualization system for studying site-specific recombination events, J. Am. Chem. Soc. 136(1) (2014) 211218. Copyright 2013 American Chemical Society.

strand and a relaxed 74mer double strand (I in Fig. 2.8A). The length of the 64mer double-stranded DNA was equal to that of the duplex parallel to the frame (as the tense state of double helices), whereas the 74mer double-stranded DNA allowed bending by 60 degrees at the target sequence (as the relaxed state of double helices). The DNA frame was designed to lack the right bottom corner for identification of the orientation of the frame (denoted by the triangles in Fig. 2.8A). The sample was adsorbed on a freshly cleaved mica and imaged by

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AFM in buffer solution. AFM images clearly showed the two doublestranded DNAs (64mer duplex and 74mer duplex) in the DNA scaffold (II in Fig. 2.8A). With the use of time-lapse AFM imaging, the dynamic movements of the two duplexes in the scaffold without and with the binding of EcoRI methyltransferase (M.EcoRI) (III in Fig. 2.8A) were captured, revealing that the ratios of the M. EcoRI binding for the 64mer and 74mer double strands were 13% and 87%, respectively. The experimental results directly showed that the preferential binding sites of M.EcoRI were the 74mer double strands, indicating the flexibility of DNA on the reactions of methylation. In 2014, the same group used AFM to investigate the site-specific recombination events based on DNA origami technology and examine the effects of the topological state of the substrate on the recombination reactions [103], as shown in Fig. 2.8B. A DNA scaffold was prepared with the use of DNA origami technology, in which two pairs of perpendicular connectors were introduced for the hybridization of the two different loxP-containing double-stranded DNAs (I in Fig. 2.8B). By changing the orientation of the strand between the C-D sites, the two loxP sites could be arranged in parallel or antiparallel orientations in the DNA scaffold. AFM images visualized that the two incorporated DNA strands were separated clearly in the frame, showing that the duplexes were long enough to fit into the connection sites but short enough to prevent the overlapping of the two strands. Time-lapse AFM imaging significantly showed the recombination reactions for antiparallel loxP substrates after the addition of Cre recombinase (II in Fig. 2.8B). The bright spot at the center of the X-shape corresponded to the Cre-loxP synaptic complex. The complex remained until 4 s. The brightness of the spot decreased at 5 s, indicating the destabilization of the recombinant reactions. At 6 s, the complex dissociated and the recombinant strands were seen. Further studies showed that for parallel loxP substrates the two loxP sites could synapse upon binding of Cre but no recombination reactions were observed, indicating the influence of substrate topology on DNA recombinant reactions. These studies impressively show the great potential of combining AFM with DNA origami technology to probe the behaviors of individual DNA molecules which are precisely placed and manipulated in the DNA scaffold, contributing much to the detailed analysis of DNA-related reactions in real-time and at molecular resolution [104]. More recently, in 2018, Roth et al. [105] combined AFM with DNA origami to probe the mechanical properties of single-stranded DNA. Based on DNA origami technology, a special nanostructure composed of two rigid rods with a singlestranded DNA segment between them was fabricated. The rigid rods could exactly identify the ends of DNA and thus allowed accurate determination of the end-to-end distance of the DNA segment for

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calculating the persistence length of the DNA, providing a novel idea for detecting the mechanics of DNA molecules.

2.8 Summary In the past three decades, AFM has been widely applied to probe the structures and properties as well as activities of single DNA molecules. The methodologies of utilizing AFM to characterize DNA behaviors have been largely established due to the great efforts of researchers from diverse disciplines, including sample preparation process of DNA molecules (cation treatment, chemical modification), visualizing the fine structures of single DNA molecules (from DNA supercoiled topological structures to substructures of DNA double helix, from AFM imaging in air to AFM imaging in liquid) (Figs. 2.12.3), capturing the structural and conformational dynamics of single DNA molecules (time-lapse AFM imaging, high-speed AFM imaging, DNA dynamics in response to external stimuli such as drug molecules) (Fig. 2.4), extracting the flexibility (persistence length) of DNA molecules from AFM topographical images (from long DNA molecules to short DNA molecules, from twodimensional measurements to three-dimensional measurements) (Fig. 2.5), mechanically unzipping single DNA molecules and dynamic force spectroscopy (directly measuring the base-pairing unbinding forces, calculating the thermodynamic parameters of the free-energy landscape of DNA molecular binding) (Fig. 2.6), precisely observing individual DNA reactions on DNA origami scaffold (Fig. 2.8), and so on. These outstanding achievements have yielded numerous novel insights into DNA-related processes at the single-molecule level, significantly complementing the traditional bulk studies of DNA and contributing much to molecular biology. Further applications of AFM in DNA-related studies in future will benefit answering fundamental issues in life sciences. So far, studies of DNA by AFM are commonly focused on probing the biophysical properties of DNA molecules (such as fine structures, conformational dynamics, and mechanical properties). An important point is exploring the relationships between AFM-acquired information and the biological functions of DNA inside the cell. Currently, it is increasingly evident in the communities of biomedicine that analyzing the activities of DNA molecules of single cells is a promising way to reshape our understanding of mutational heterogeneity in normal and diseased tissues and enables the identification of novel mechanisms of the pathogenesis of diseases [106108]. Hence, combining AFM with complementary techniques (such as biochemical assays) to simultaneously detect the biophysical and chemical properties of DNA molecules from an individual

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cell will considerably help to correlate DNA biophysics with DNA functions as well as cell states (e.g., healthy cell or diseased cell) for unveiling novel mechanisms regulating cellular activities, and this kind of investigations is still scarce so far. For doing this, one needs to extract the DNA molecules from single cells and then the established methodologies of AFM-based DNA analysis can be applied to detect the DNA molecules. As an alternative way, one may directly utilize AFM to probe the DNA molecules in the cell. In 2016, Koo et al. [109] used AFM-based SMFS to successfully probe the microRNA molecules in the cell with the use of functionalized tips, showing the capabilities of AFM in mapping the spatial resolution of single RNA molecules in the cell. Notably, this method [109] requires the chemical fixation of the cell, meaning that the cell loses biological activities after fixation. Applications of AFM-based DNA analysis in clinical medicine may promote the development of novel methods for disease diagnosis. Currently, an important research direction of oncology is the detection of cfDNA [57]. cfDNA is highly degraded DNA fragments, which are detectable in the peripheral blood of every human [110]. In healthy individuals, the death of normal cells of the hematopoietic lineage is the main contributor of plasma cfDNA [111]. Under certain physiologic or pathologic states, the composition of cfDNA may change [110], for example, the blood of pregnant females contains DNA fragments from the fetus and cancer patients have DNA fragments from the circulating tumor cell. Studies have shown that probing cfDNA has the potential to substantially improve early cancer detection [112]. In 2014, Mouliere et al. [113] firstly used AFM to visualize cfDNA molecules which were isolated from the blood samples of cancer patients and the experimental results revealed the significant differences in cfDNA size between cancerous patients and healthy volunteers, showing the potentials of AFM in the characterizations of cfDNA [114]. Nevertheless, on the whole the studies of cfDNA by AFM are still few. Hence, utilizing the established methodologies of AFM-based DNA analyses to investigate the behaviors of cfDNA will significantly improve our understanding of the biology of cfDNA and may further advance the early cancer detection. For doing so, one needs to isolate cfDNA from the liquid biopsies of clinical patients and then apply AFM to characterize the features of cfDNA molecules and correlate the AFM-acquired information with clinical pathological diagnosis results. Taken together, AFM is now an important tool for the studies of single DNA molecules and offers novel possibilities for understanding the physical and mechanical cues involved in DNA activities. In the future, as more DNA-related biological systems are investigated by AFM alone or combined with other complementary techniques, we will see increasing advancements in the field of genetics and molecular biology.

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C H A P T E R

3 High-resolution imaging and force spectroscopy of single membrane proteins by atomic force microscopy

3.1 Background Membrane proteins are crucial to the life of the cell. For an animal cell, the plasma membrane encloses the cell, defines its boundaries, and maintains the essential differences between the cytosol and the extracellular environment [1]. Inside the cells, the membranes of organelles (e.g., nucleus, endoplasmic reticulum, Golgi apparatus, mitochondria, lysosome, peroxisome) maintain the characteristic differences between the contents of each organelle and the cytosol. All biological membranes have a common general structure: each is a very thin film of lipids and proteins that are associated with noncovalent interactions [2]. Biological membranes, in general, are fluids, and the component proteins and lipids are able to translate laterally in the plane of the membrane [3]. The lipid bilayer (the thickness of the lipid bilayer is about 5 nm [1]) provides the basic fluid structure for the plasma membrane which is under constant remodeling through the action of flippase, vesicle fusion or endocytosis [4]. Notably, for the biological membranes of organelles, some types of organelles (e.g., nucleus, mitochondria, chromatophore, anammoxosome, magnetosome) are surrounded by a lipid bilayer, while some other types of organelles (e.g., endoplasmic reticulum, Golgi apparatus, lysosome, peroxisome, chlorosome, lipid body) are enclosed by a lipid monolayer [5]. Cellular plasma membranes are

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laterally heterogeneous, featuring a variety of distinct subcompartments (called lipid rafts) that differ in their biophysical properties and composition [6]. The lipid bilayer of the plasma membrane is decorated by various types of proteins (as shown in Fig. 3.1) which mediate nearly all of the biological functions of the cell, for example, some membrane proteins (transmembrane ion channels, carriers, and pumps) are responsible for providing the cell with nutrients, controlling internal ion concentration, and establishing a transmembrane electrical potential, some membrane proteins (receptors) mediate interactions of cells with their immediate environment and convert the binding of extracellular signaling molecules (such as hormones and growth factors) into chemical or electrical signals that influence the activity of the cell, and some proteins (adhesion proteins) allow cells to bind specifically to each other or to the extracellular matrix, and so on [7]. Membrane proteins serve as important centers by which we can influence cellular functions to combat pathophysiological states, and unsurprisingly although membrane proteins only account for approximately 25% of the protein-coding genes in all organisms [8] but disproportionately constitute .60% of drug targets [9]. Consequently, investigating the detailed behaviors of membrane proteins is of remarkable significance for understanding the mysteries of life activities, which will have general impacts on drug developments and disease treatments. AFM offers a unique and powerful tool to characterize the structures and mechanics of single membrane proteins in their native states under aqueous conditions. Traditionally, X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryogenic electron microscopy (cryo-EM) are the prevailing techniques that have been used to determine the three-dimensional structure of transmembrane proteins [10]. The process of structural biology analysis of membrane proteins mainly includes three steps, membrane protein expression, membrane protein purification, and membrane protein crystallization, each of which poses great challenges and barriers [11]. Besides, these methods only provide static snapshots of proteins, which are unable to capture the structural dynamics of single membrane proteins at work. Particularly, these methods require extracting membrane proteins from the lipid membranes with the use of detergents, meaning that the extracted membrane proteins are not in their native environments and thus the results may not completely reflect the real situations of membrane proteins in the lipid layer. It is increasingly apparent that rather than being a passive bystander in the function of membrane proteins, the membrane can at times have an essential role in determining the function of these proteins [12], for example, a recent study has shown that lipid bilayer composition modulates the unfolding free energy of membrane protein [13]. A better understanding of the lipid bilayer and its effects on membrane protein folding is not only important for a theoretical understanding

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FIGURE 3.1 Schematic illustration of the structure of an animal cell plasma membrane. The basic structure of the membrane is lipid bilayer which has a hydrophobic interior, causing the plasma membrane is impermeable to ions and most water-soluble molecules and thus forming a barrier between the cytoplasm and the extracellular environment. Membrane proteins span the lipid bilayer to participate in the processes of virtually all cellular functions. The plasma membrane consists of various raft-like and nonraft domains with distinct compositions and properties. Lipid rafts domains are usually defined as small, highly dynamic and transient plasma membrane entities that are enriched in saturated phospholipids, sphingolipids, glycolipids, cholesterol, lapidated proteins and glycosylphosphatidylinositol (GPI)anchored proteins. Source: Reprinted with permission from E. Sezgin, I. Levental, S. Mayor, C. Eggeling, The mystery of membrane organization: composition, regulation and roles of lipid rafts, Nat. Rev. Mol. Cell Biol. 18(6) (2017) 361374. Copyright 2017 Macmillan Publishers Limited.

of the folding processes of membrane proteins but can also have a practical impact on our ability to work with and design membrane proteins [14]. AFM is able to not only directly visualize the surface structures and their dynamics of single native membrane proteins in the lipid bilayer in buffer solution with a lateral resolution of less than 1 nm and a vertical resolution of 0.10.2 nm, but can also reveal the dynamic mechanical forces involved in the unfolding process of membrane proteins [15], significantly complementing structural biology analysis methods. Notably, AFM is limited to nanometer spatial resolution and cannot provide atomic resolution details of single membrane proteins [16]. Nevertheless, AFM has become an invaluable analytical tool for the studies of membrane proteins [1719] and applications of AFM in membrane proteins have strikingly deepened our understanding of the behaviors of membrane proteins.

3.2 Topographical imaging of single native membrane proteins AFM has been broadly used to visualize single bacteriorhodopsin molecules in native purple membranes in liquid. Purple membrane is

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one of the gifts from nature to structural biologists [20]. Purple membrane is a specialized membrane from the extremely halophilic archaebacterium, and a stirring feature of purple membrane is that it consists of native highly ordered trigonal 2D crystals of a membrane protein called bacteriorhodopsin. Bacteriorhodopsin is a small (24 kDa) integral membrane protein, which pumps protons out of cells and provides cells with the energy to live [21,22]. The atomic organizations of single bacteriorhodopsin have been revealed by X-ray crystallography [23,24], which provide the structural basis for understanding the biochemistry and functions of bacteriorhodopsin molecules. Nonetheless, AFM imaging directly and visually provides unique details of the structure and conformation of bacteriorhodopsin molecules. In 1990, Butt et al. [25] firstly applied AFM to image the purple membrane in a buffer solution. For doing so, purple membrane patches were prepared from Halobacterium halobium strain and then the purple membrane solution was dropped onto freshly cleaved mica. Subsequently, AFM imaging was performed on the sample in a buffer solution. Since purple membranes are negatively charged, and freshly cleaved mica surface is also negatively charged, and thus an important step is to find the conditions of the buffer solution in which the membrane purple patches adsorb to mica. The authors found that in the buffer solution containing 2 mM CaCl2, 80 mM KCl, 10 mM KH2PO4, and pH 4.0, the purple membrane could tightly adsorb to mica. Besides, the scan force should be below 1 nN, as a force larger than this value could destroy the surface details of purple membrane. Although the signal-to-noise ratio of the obtained AFM image of purple membrane was rather low, the trimer structures of bacteriorhodopsin molecules on purple membrane were visualized by performing image processes on the original AFM images (Fourier transform was firstly performed on the original AFM image, and then the spots belonging to the hexagonal structure in the Fourier transform image were masked, after which the inverse Fourier transform was performed to yield the filtered AFM image). Since the mid-1990s, Muller et al. [2630] have carried out comprehensive investigations on AFM high-resolution imaging of native purple membranes. The immobilization of purple membranes onto the mica surface was carefully studied, and the experimental results showed that the adsorption of purple membranes onto mica surface could be tuned by adjusting the electrolyte concentration and the pH of the buffer solution [29]. Both monovalent (Li1, Na1, K1) and divalent (Ca21, Ni21, Mg21) electrolytes are able to regulate the adsorption of purple membrane to mica. Besides, their studies revealed that the thickness of purple membrane was about 5.6 nm at pH values above 6, and the thickness of purple membrane became approximately 5.1 nm below pH 6 [26], indicating the influence of buffer solution on the thickness of purple membrane. The pH of the

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buffer solution also has impacts on the orientations of the purple membrane adsorbed on mica (whether the cytoplasmic side or extracellular side of the purple membranes attaches to mica). By immunolabeling techniques (e.g., using antibodies directed against the C-terminus of bacteriorhodopsin), the cytoplasmic and extracellular surface of purple membrane on the mica could be well discriminated [28]. From the acquired AFM topographical images of native purple membranes (Fig. 3.2A), the trimers of bacteriorhodopsin on the purple membrane are clearly visible. The trimers arrange in a trigonal lattice of 6.2 6 0.2 nm side length, and each subunit in the trimer features a particularly pronounced protrusion extending 0.83 6 0.19 nm above the lipid surface [30]. Furthermore, different conformations of individual bacteriorhodopsin molecules have been observed by changing the scanning force of the AFM tip [27] and the fine structures of single bacteriorhodopsin in the AFM image are visually correlated with the secondary structures of the bacteriorhodopsin. These studies impressively give experimental support to the structures of bacteriorhodopsin and also offer a novel approach based on AFM to characterize the behaviors of single native bacteriorhodopsin molecules under aqueous conditions. In addition to purple membrane, researchers have also utilized AFM to image the exquisite structures of some other specific types of natural membranes. In 2003, Fotiadis et al. [31] used AFM to reveal the native arrangement of rhodopsin which formed paracrystalline arrays of dimers in mouse disk membranes, as shown in Fig. 3.2B. Rod outersegment disk membranes were isolated from the mouse retina. After attaching the disk membranes to mica, AFM images were obtained in buffer solution (20 mM TrisHCl, pH 7.8, 150 mM KCl, 25 mM MgCl2). AFM images showed that the surface of disk membrane had a markedly textured topography consisting of densely packed lines (I in Fig. 3.2B). At higher magnification, AFM image clearly revealed rows of rhodopsin pairs densely packed in paracrystalline arrays (II in Fig. 3.2B), in stark contrast to the 30-year-old dogma within the field that considered rhodopsin to occur as a monomer [20]. In 2004, Bahatyrova et al. [32] firstly used AFM to reveal the native architecture of a photosynthetic membrane, as shown in Fig. 3.2C. Native photosynthetic membrane patches of Rhodobacter sphaeroides were isolated and adsorbed onto mica via the use of an adsorption buffer (10 mM TrisHCl, pH 7.5, 150 mM KCl, 25 mM MgCl2). AFM images of photosynthetic membranes were obtained in buffer solution (10 mM TrisHCl, pH 7.5, 150 mM KCl) at tapping mode. The obtained AFM image clearly showed the photosynthetic membrane patches which are composed of linear arrays of dimeric complexes (I in Fig. 3.2C). Small-size scanning of a single photosynthetic membrane patch revealed that the light-harvesting 2 (LH2) complexes were clustered in regions between the rows of the reaction

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FIGURE 3.2 Atomic force microscopy (AFM) topographical imaging visualizing single native membrane proteins in natural membranes in buffer solution. (A) Native purple membrane. (I) AFM image of a purple membrane patch adsorbed on mica. (II, III) Highresolution AFM images of purple membrane showing the trimeric assembly of bacteriorhodopsin. (II) Extracellular surface of the purple membrane. (III) Cytoplasmic surface of the purple membrane. (B) Native eye-disk membrane. (I) AFM deflection image of a disk membrane patch. (II) High-resolution AFM image of the membrane showing rows of rhodopsin dimers. Arrowheads denote occasional rhodopsin monomers and dashed ellipse denotes individual dimers. (C) Native photosynthetic membrane. (I) AFM large-scale imaging of several membrane fragments. (II) Higher-magnification AFM image showing the core complex arrays. The inset at the bottom is a representation of the region denoted by the dashed box in the center. (D) Native outer membrane of Gram-negative bacteria. Encircled is a single porin trimer. The arrow denotes remnant peptidoglycan. The inset shows a threefold symmetrized average (n 5 45). (E) Native surface layer of bacteria. Sources: (A) Reprinted with permission from D.J. Muller, A. Engel, Atomic force microscopy and spectroscopy of native membrane proteins, Nat. Protoc. 2(9) (2007) 21912197. Copyright 2007 Nature Publishing Group. (B) Reprinted with permission from D. Fotiadis, Y. Liang, S. Filipek, D. A. Saperstein, A. Engel, K. Palczewski, Rhodopsin dimers in native disk membranes, Nature 421

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center (RC)-LH1-PufX dimers (II in Fig. 3.2C). Typically, these regions contained 1020 LH2 complexes. The study provides direct evidence of the relative positions and associations of the photosynthetic complexes and uncovers new features of the organization of the photosynthetic complex network. In 2005, Scheuring et al. [33] further investigated how the composition and architecture of photosynthetic membranes of a bacterium change in response to light by high-resolution AFM imaging and the results significantly showed that the structural adaptation of photosynthetic complexes ensured efficient photo capture under low-light conditions and prevented photodamage under high-light conditions. In 2009, Jaroslawski et al. [34] used AFM to investigate the supramolecular structure of the outer membrane of Gram-negative bacteria Roseobacter denitrificans and revealed the densely packed porin trimer structures on the outer membrane, as shown in Fig. 3.2D. The outer membrane patches were attached to mica in the adsorption buffer (10 mM TrisHCl, pH 7.2, 25 mM MgCl2) and AFM images were obtained in the recording buffer (10 mM TrisHCl, pH 7.2, 150 mM KCl) at contact mode. Repetitive scanning of the specimen with slightly increasing loading force allowed the removal of the peptidoglycan layer on the specimen and individual porin molecules were then visualized clearly, showing the trimer structures of porin molecules. Besides the outer membrane, AFM has also been used to reveal the hexagonally packed proteins which make up the outermost cell wall layer of Corynebacterium glutamicum (Fig. 3.2E) [35,36], providing novel insights into understanding the amazing stability of the protective bacterial surface coat. AFM high-resolution imaging allows directly visualizing the conformational changes of single native membrane proteins upon stimulation. Except for a few specific types of membranes (some examples of these membranes are described above) which are composed of only one kind of membrane protein, most plasma membranes are made up of various different membrane proteins and many membrane proteins do not show distinctive morphological features and are indistinguishable from each other in an AFM topographical image [37]. Thus, specific sample preparation procedures are required for utilizing AFM to investigate the (6919) (2003) 127128. Copyright 2003 Nature Publishing Group. (C) Reprinted with permission from S. Bahatyrova, R.N. Frese, C.A. Siebert, J.D. Olsen, K.O. van der Werf, R. van Grondelle, et al., The native architecture of a photosynthetic membrane, Nature 430(7003) (2004)10581062. Copyright 2004 Nature Publishing Group. (D) Reprinted with permission from S. Jaroslawski, K. Duquesne, J.N. Sturgis, S. Scheuring, High-resolution architecture of the outer membrane of the Gram-negative bacteria Roseobacter denitrificans, Mol. Microbiol. 74(5) (2009) 12111222. Copyright 2009 Blackwell Publishing Ltd. (E) Reprinted with permission from S. Scheuring, Y.F. Dufrene, Atomic force microscopy: probing the spatial organization, interactions and elasticity of microbial cell envelopes at molecular resolution, Mol. Microbiol. 75(6) (2010) 13271336. Copyright 2010 Blackwell Publishing Ltd.

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structures and behaviors of these membrane proteins. Commonly, one needs to firstly express high levels of the target membrane proteins on the hosts [38] and then extract the target membrane proteins from hosts and purify the target membrane proteins, which are widely used in the field of structural biology [10]. Subsequently, the purified membrane proteins are reconstituted into artificial lipid bilayers to form densely packed membrane proteins for AFM high-resolution imaging. In 2002, Muller et al. [39] firstly reported the high-resolution AFM topographical images of native connexin 26 gap junction plaques and their conformational changes, as shown in Fig. 3.3A. Gap junction plaques isolated from overexpressing connexin 26 HeLa cells were adsorbed onto mica and then AFM images of the connexon surface were obtained in buffer solution (5 mM Tris, 1 mM EGTA, 1 mM PMSF), clearly showing the hexagonal assembly of individual connexons into microcrystalline patches. When imaging the connexon surface in the Ca21-free buffer, the six subunits were arranged into a donut-shaped structure surrounding a central pore (I in Fig. 3.3A). After adding calcium ion into the imaging buffer (the imaging buffer became 5 mM Tris, 0.5 mM CaCl2, and 1 mM PMSF), AFM images of the same plaques were obtained again and the results showed that the central pore became significantly smaller (II in Fig. 3.3A), providing direct evidence that Ca21 stimulates the gap junctions to close the intercellular channel. AFM has been widely used to visualize the conformational changes of MlotiK1 potassium channel proteins at single-molecule level [4042], as shown in Fig. 3.3B. The MlotiK1 potassium channel belongs to the family of channels that are regulated by cyclic nucleotides and these channels have C-terminal cytoplasmic cyclic nucleotide-binding (CNB) domains. Upon binding of cAMP or cGMP, the CNB domains undergo a conformational change that favors the opening of the gate of the channel. After reconstituting the purified MlotiK1molecules into lipid bilayer membranes, the membranes were adsorbed on mica in buffer solution for AFM imaging. AFM images showed that single MlotiK1 channels had a fourfold symmetric arrangement in the presence of cAMP (I in Fig. 3.3B). After replacing the imaging buffer with cAMP-free buffer, AFM images clearly showed that the characteristic fourfold symmetric structures were lost and each channel became a single protrusion, visually confirming the cAMP-regulated opening of the MlotiK1 channel. The section profile curves (II in Fig. 3.3B) taken along AFM topographical images show a significant decrease in the protein heights after the addition of cAMP, which are consistent with the conformational changes of the proteins. In addition, AFM has also been used to visualize the topography of single β-barrel membrane proteins reconstituted in a lipid bilayer [43,44]. These studies provide vivid examples of utilizing AFM high-resolution topographical imaging to investigate the structure and conformational

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FIGURE 3.3 Visualizing the conformational changes of single native membrane proteins in buffer solution by atomic force microscopy (AFM). (A) Native connexon in gap junction plaque. (I) AFM image of connexon recorded in a Ca21-free buffer solution. (II) Same connexon surface imaged in the presence of 0.5 mM CaCl2. The insets in (I, II) are the corresponding average AFM images. (B) AFM analysis of MloK1 in the presence and absence of cAMP. (I) High-resolution AFM images of MloK1. In the cAMP-bound state (left), each subunit of the tetrameric channels is well resolved on each single molecule. The four CNB domains were arranged in a left-handed windmill. In the cAMP-free state (right), sub-molecular details could not be resolved and the tetramer is contoured as a single protrusion of variable height and appearance. The insets are corresponding average AFM images of single MloK1 molecules. (II) The corresponding section profile curves of MloK1 molecules taken along the dashed lines in (I). Sources: (A) Reprinted with permission from D.J. Muller, G.M. Hand, A. Engel, G.E. Sosinsky, Conformational changes in surface structures of isolated connexin 26 gap junctions, EMBO J. 21(14) (2002) 35983607. Copyright 2002 European Molecular Biology Organization. (B) Reprinted with permission from S.A. Mari, J. Pessoa, S. Altieri, U. Hensen, L. Thomas, J.H. Morais-Cabral, et al., Gating of the MlotiK1 potassium channel involves large rearrangements of the cyclic nucleotide-binding domains, Proc. Natl. Acad. Sci. USA 108(51) (2011) 2080220807. Copyright 2011 National Academy of Sciences. Reprinted with permission from J. Kowal, M. Chami, P. Baumgartner, M. Arheit, P.L. Chiu, M. Rangl, et al., Ligand-induced structural changes in the cyclic nucleotide-modulated potassium channel MloK1, Nat. Commun. 5 (2014) 3106. Copyright 2014 Macmillan Publishers Limited.

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changes of individual membrane proteins in response to chemical stimuli in their native environments, which is meaningful for understanding the behaviors and biological functions of membrane proteins.

3.3 Unfolding mechanics of individual native membrane proteins Besides visualizing the conformations of single native membrane proteins, AFM also allows deciphering the unfolding pathway of single native membrane proteins by measuring the molecular forces via the AFM-based force spectroscopy technique called single-molecule force spectroscopy (SMFS). Molecular interactions drive all processes of life, and particularly for membrane proteins, molecular interactions drive the folding of the polypeptide into the functional state, stabilize the structure, and even lead to protein misfolding [45]. To perform biological functions, membrane proteins should fold into three-dimensional structures in the lipid bilayers, and this process can be divided into two stages: insertion and folding [46]. Each folding stage is driven by a distinct set of molecular forces [47]. In the insertion stage, polypeptide segments insert into the lipid bilayer to form stable transmembrane helices (TMHs), which are mainly driven by the hydrophobic nature of the amino acids of TMHs and the hydrogen bonding in the nonpolar bilayer. In the folding stage, the TMHs fold to form a compact three-dimensional structure, which is driven by van der Waals packing and polar interactions. Uncovering the molecular forces involved in the protein folding process, therefore, benefits understanding the behaviors of membrane protein folding and its quality control [48]. In SMFS, the AFM tip is utilized to mechanically extract single membrane proteins out of the membrane while the changes of forces are simultaneously monitored, which construct the molecular interactions involved in the unfolding process of the protein [49], as shown in Fig. 3.4A. For doing so, commonly, target membrane proteins are reconstituted into lipid bilayers, which are then attached to a support. AFM tip (without the need for functionalization) is controlled to approach and push a single native membrane protein with an adequate force for a period of time, which will result in the adsorption of the protein to the tip with a certain probability [15,50]. Subsequently, the AFM tip is controlled to retract from the protein, which will mechanically extract the protein from the membrane. AFM topographical imaging is often used to assist SMFS experiments on membrane protein. The successful extraction of a membrane protein will leave a vacancy in the position of the membrane protein, which can be visible from the reobtained AFM image of the same area after SMFS experiments [51], as shown in Fig. 3.4B. Force curves are recorded during the approachretract process, and fitting the sawtooth-like peaks in the force curves with

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FIGURE 3.4 Unfolding single membrane proteins by atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS). (A) Principle. AFM tip picks one end of the membrane protein to mechanically unfold the protein. A schematic force curve recording the unfolding process of the membrane protein is shown. Different parts of the force curve are numbered and the corresponding action during the SMFS experiment is shown. At stage ①, AFM tip starts pulling the extracellular end of the membrane protein. At stage ②③④, the stable segments (blue, orange, green) of the membrane are sequentially stretched. At stage ⑤, the protein has been fully extracted out of the membrane by AFM tip. Each force peak represents the mechanical unfolding of a stable structural segment (blue, orange, green). Dashed lines represent fitted WLC model curves, which provide an estimate of the contour length. (B) AFM high-resolution images of the cytoplasmic purple membrane surface. (I) AFM image obtained before performing SMFS experiment on a bacteriorhodopsin. (II) Same area imaged after the SMFS experiment showing the missing of one bacteriorhodopsin (denoted by white circle). (C) A typical force curve obtained during the unfolding process of a bacteriorhodopsin on purple membrane. Blue lines are the WLC fitting curves of the peaks in the force curve. The distance between the first and the forthcoming force peak reveals the polypeptide stretch that has been released, which corresponds to a structural segment of the membrane protein. Sources: (A) Reprinted with permission from A.M. Whited, P.S.H. Park, Atomic force microscopy: a multifaceted tool to study membrane proteins and their interactions with ligands, Biochim. Biophys. Acta 1838 (2014) 5668. Copyright 2013 Elsevier B.V. (B) Reprinted with permission from D.J. Muller, M. Kessler, F. Oesterhelt, C. Moller, D. Oesterhelt, H. Gaub, Stability of bacteriorhodopsin α-helices and loops analyzed by single-molecule force spectroscopy, Biophys. J. 83(6) (2002) 35783588. Copyright 2002 the Biophysical Society. (C) Reprinted with permission from D.J. Muller, A. Engel, Atomic force microscopy and spectroscopy of native membrane proteins, Nat. Protoc. 2(9) (2007) 21912197. Copyright 2007 Nature Publishing Group.

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the WLC model gives the unfolding pathways of the membrane protein, as shown in Fig. 3.4C. More technical details of utilizing SMFS to reveal the unfolding mechanics of individual membrane proteins are shown in Chapter 1. One advantage of SMFS is that the direction along which the membrane protein is extracted in a mechanical unfolding process establishes a well-defined reaction coordinate [52]. Along this privileged spatial resolution, parameters of the reactions such as the distance to the transition state, the height of the energy barrier, and the energy difference between the initial and the final states can be determined, which are quite meaningful for understanding the molecular interactions guiding protein folding. AFM-based SMFS technique has been used to reveal the unfolding pathways of various membrane proteins, yielding novel insights into the mechanics and behaviors of membrane proteins. Bacteriorhodopsin has been the most extensively studied membrane protein for AFMbased SMFS. In 2000, Oesterhelt et al. [50] firstly combined AFM imaging with SMFS to investigate the unfolding process of single bacteriorhodopsin molecules in the native purple membrane. The obtained force curves clearly show three main force peaks when unfolding single bacteriorhodopsin molecules (Fig. 3.4C), which correspond to the stable segments of bacteriorhodopsin. The study reveals a very detailed map of the unfolding pathways and the local interactions within the membrane protein, providing a novel approach to unravel the individualism of the unfolding process of membrane protein. Since then, researchers have investigated various issues of the unfolding behaviors of bacteriorhodopsin by SMFS, including analyzing the stability of bacteriorhodopsin α-helices and loops [51], the dynamic responses during protein unfolding [53], and examining the effects of bacteriorhodopsin assemblies on the unfolding barriers of protein [54]. Further, SMFS studies have shown that there are no significant alterations of unfolding intermediates and unfolding pathways between bacteriorhodopsin in native purple membrane and bacteriorhodopsin reconstituted in lipid nanodiscs [55], indicating that lipid nanodiscs provide a novel approach for the studies of native membrane proteins using SMFS techniques that have been established on water-soluble proteins. Researchers have also investigated the unfolding process of single bacteriorhodopsin molecules coated on a nanoscopic hole and extended the WLC model to the cubic extension model to exactly characterize the unfolding behaviors of a membrane protein from freely spanning membranes [56]. In 2017, Yu et al. [57] used ultrashort cantilevers to extract single bacteriorhodopsin molecules at 300 nm/s and numerous intermediates were detected during the unfolding process of bacteriorhodopsin, sharpening the picture of the mechanical unfolding of membrane proteins and enabling experimental access to previously obscured protein dynamics. Besides bacteriorhodopsin, researchers have utilized SMFS to investigate the unfolding

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process of other types of membrane protein. In 2012, Kawamura et al. [58] used SMFS to characterize the unfolding dynamics of rhodopsin molecules in the disk membranes isolated from the eyes of mice, as shown in Fig. 3.5. Rhodopsin is the light receptor that initiates phototransduction in rod photoreceptor cells of the retina and mutations in rhodopsin often cause retinal diseases including congenital stationary night blindness and retinitis pigmentosa. Wild-type rhodopsin and G90D (A G90D point mutation in rhodopsin results in congenital stationary night blindness) rhodopsin were obtained from regular mice and G90D mice, respectively. After adsorbing the disk membrane patches onto freshly cleaved mica, SMFS experiments were performed on the disk membranes in a dark in buffer solution at room temperature to unfold single rhodopsin molecules in the membrane (Fig. 3.5A). The obtained force curves (Fig. 3.5BD) as well as the WLC fitting results of the force peaks in the force curves showed no significant differences between regular rhodopsin molecules and mutant rhodopsin molecules, indicating that the location of structural

FIGURE 3.5 Utilizing single-molecule force spectroscopy (SMFS) to unfold single rhodopsin molecules in native mouse disk membranes. (A) Schematic illustration of SMFS on rhodopsin in mouse disk membranes. In SMFS, the atomic force microscopy tip is brought in contact with the N-terminal end of rhodopsin and then retracted from the membrane. A white circle denotes the location of the G90D mutation. (B) Examples of force curves obtained from the mechanical unfolding of single wild-type (black) or G90D mutant (blue) rhodopsin. Dashed regions denote the three clusters of force peaks. (C, D) Density maps generated from superimposition of all force curves collected for wild-type (C) and G90D mutant (D) rhodopsin. (E) Stable structural segments of wild-type and G90D mutant rhodopsin detected by SMFS. Source: Reprinted with permission from S. Kawamura, A.T. Colozo, L. Ge, D.J. Muller, P.S.H. Park, Structural, energetic, and mechanical perturbations in rhodopsin mutant that causes congenital stationary night blindness, J. Biol. Chem. 287(26) (2012) 2182621835. Copyright 2012 The American Society for Biochemistry and Molecular Biology.

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segments stabilizing rhodopsin remained unchanged by the G90D mutation. The WLC fitting results also gave the structural segments of wild-type and G90D rhodopsin, as shown in Fig. 3.5E. This study offers a template for utilizing SMFS to investigate the unfolding pathways of membrane proteins. More recently, researchers have utilized SMFS to investigate the bacterial and human transmembrane β-barrel proteins and the effects of translocases and insertases on the folding pathways of membrane proteins [5962], providing mechanistic insights into the biogenesis of membrane proteins.

3.4 Observing the dynamics of single membrane proteins by high-speed atomic force microscopy With the use of high-speed AFM topographical imaging, the conformational dynamics of single membrane proteins in native membranes can be revealed. On the cell membrane, molecular interactions as well as changes of molecular conformations within microdomains (lipid rafts), particularly membrane proteins and their interactions [63], take place all the time during the life of a cell, which have direct impacts on the biological functions of the cell such as cell adhesion, signaling, antigen presentation and cellcell interactions [64]. Hence, observing the instantaneous changes of single membrane proteins in the lipid membrane considerably benefits revealing the underpinnings guiding life activities. Fluorescence-based methods, including fluorescence correlation spectroscopy (FCS), fluorescence recovery after photobleaching (FRAP), fluorescence resonance energy transfer (FRET), fluorescence lifetime imaging microscopy (FLIM), single-particle tracking (SPT), generalized polarization (GP), photo counting histogram (PCH), fluorescence intensity distribution analysis (FIDA), number and brightness analysis (N&B), and so on [65,66], have been broadly used to detect the molecular dynamics in cell membrane. However, fluorescent assays require labeling target membrane proteins with fluorescein and thus membrane proteins are not in their native states, which may influence the real activities of membrane proteins. The developments of high-speed AFM [67] allow us to visualize the dynamics of biological systems with unprecedented temporal resolution. Particularly, membrane patches (either natural membranes such as purple membrane or reconstituted membranes) adsorbed onto mica are quite thin and smooth, which facilitates performing high-speed AFM imaging on them. For detailed descriptions of high-speed AFM, readers are referred to Chapter 1. In 2010, Shibata et al. [68] utilized high-speed AFM to investigate the photoactivated structural dynamics of single bacteriorhodopsin molecules in purple membranes, as shown in Fig. 3.6A. For doing so, purple membranes containing D96N bacteriorhodopsin mutant were isolated from H. salinarum and then

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FIGURE 3.6 High-speed atomic force microscopy (AFM) revealing the conformational and motional dynamics of single native membrane proteins in the lipid membrane. (A) Structural dynamics of single D96N bacteriorhodopsin molecules induced by illumination. (I, II, III, IV) Successive AFM images. A bacteriorhodopsin trimer is denoted by the white triangle. The green bars denote illumination of 532-nm green light at 0.5 μW. (V) Surface maps of the magnified images in the dark (upper panel) and under illumination (bottom panel). White dots denote the position of each trimer center. A monomer in the dark is indicated by a white arrow. The green arrows 1 and 2 indicate the major and minor protrusions formed after illumination, respectively. (B) Motions of OmpF trimers in the membrane. Successive AFM images are shown in the upper panel, and the same AFM images as well as the overlaid outlines of the localization and orientation of each OmpF trimer are shown in the bottom panel. Sources: (A) Reprinted with permission from M. Shibata, H. Yamashita, T. Uchihashi, H. Kandori, T. Ando, High-speed atomic force microscopy shows dynamic molecular processes in photoactivated bacteriorhodopsin, Nat. Nanotechnol. 5(3) (2010) 208212. Copyright 2010 Macmillan Publishers Limited. (B) Reprinted with permission from I. Casuso, J. Khao, M. Chami, P. Paul-Gilloteaux, M. Husain, J.P. Duneau, et al., Characterization of the motion of membrane proteins using high-speed atomic force microscopy, Nat. Nanotechnol. 7(8) (2012) 525529. Copyright 2012 Macmillan Publishers Limited.

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adsorbed onto freshly cleaved mica. High-speed AFM topographical images were obtained at 1 frame per second in buffer solution. Firstly, AFM images were obtained in dark, and bacteriorhodopsin trimers were clearly visible from the images (I, II in Fig. 3.6A). Upon illumination with green light, AFM images showed that bacteriorhodopsin molecules remarkably changed their structures (III, IV in Fig. 3.6A). Further imaging results showed that the bacteriorhodopsin molecules returned to the unphotolyzed state in a few seconds after light-off, indicating the reproducible conformational changes of the bacteriorhodopsin molecules in repeated dark-illustration cycles. In order to quantitatively characterize the conformational changes of bacteriorhodopsin molecules, the positions of mass center of the individual bacteriorhodopsin monomers were analyzed, showing that all of the activated bacteriorhodopsin monomers exhibited displacements (approximately 0.69 6 0.15 nm) of their center of mass. Besides, magnified AFM images obtained before and after illumination showed that the monomer split into two protrusions (V in Fig. 3.6A), which were correlated with the changes of the helix structures of the bacteriorhodopsin by integrating AFM data with the crystal structure of the bacteriorhodopsin. Further experiments were performed to measure the decay of the active state of bacteriorhodopsin after flash illumination at various pH values to ensure that the conformational changes were not caused by artifacts such as tip-induced structural changes. The results clearly showed a strong pH dependence of the decay, which was consistent with the previous results of UV-visible spectroscopy and verified the illumination-induced structural changes of bacteriorhodopsin molecules. High-speed AFM also allows directly visualizing the motions of single native membrane proteins in the lipid membrane under aqueous conditions. Many membrane proteins diffuse in the plane of the membrane, including rotational diffusion (rotating about an axis perpendicular to the plane of the bilayer) and lateral diffusion (moving laterally within the membrane) [1], which plays a determining role in the physiology and biochemical organization of the cell [69]. The lateral diffusion rates of membrane proteins can be measured by FRAP or SPT [1], both of which require labeling individual membrane membranes with antibodies conjugated with fluorescent dyes. In 2012, Casuso et al. [70] demonstrated the capabilities of high-speed AFM in directly revealing the diffusion of single unlabeled native membrane proteins in the lipid bilayer membrane, as shown in Fig. 3.6B. The outer membrane protein F (OmpF) was used in this study. For doing so, OmpF co-purified with natural outer membrane component lipopolysaccharide (LPS) was reconstituted into E. coli lipids. The samples were then adsorbed onto freshly cleaved mica in the buffer solution (10 mM TrisHCl, pH 7.3, 150 mM KCl) and imaged by highspeed AFM. High-speed AFM allowed for acquiring movies of the dynamic motions of the OmpF, which clearly showed the translational and rotational

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dynamics of the unlabeled OmpF molecules in the membrane environment with unprecedented spatiotemporal resolution (upper panel in Fig. 3.6B). Cross-correlation-based algorithms were used to define the location and orientation of each OmpF in the membrane with Angstrom precision and with a time resolution of 477 ms (bottom panel in Fig. 3.6B), which allowed tracing the movements and the areas of single molecules, providing experimental access to the effect of crowding on molecular motions. Quantitative results showed that the majority of OmpF molecules were confined into a small membrane space, while a few molecules were disposed in a free membrane area much larger than the average area. These few molecules actually diffused in the membrane. These studies distinctly exhibit the real-space and real-time visualization of the conformational and motional dynamics of individual membrane proteins at work in native environments obtained with the use of high-speed AFM, providing a straightforward way to in situ elucidate how single native membrane proteins function.

3.5 Multiparametric atomic force microscopy imaging of single membrane proteins Peak force tapping (PFT)-based multiparametric AFM imaging allows imaging single native membrane proteins while simultaneously measuring their mechanical properties. Proteins can have different properties (dimensions) that are either largely physically (e.g., primary sequence, secondary structure, tertiary structure, mass), chemically (e.g., surface hydrophobicity, solubility, charge distribution), or biologically (e.g., abundance, isoforms, localization, interactions, modifications, tissue distribution, turnover, cell cycle) relevant, and therefore understanding protein structurefunction relationships not only requires the identification of proteins but also the detailed analysis of the protein properties that constitute the dimensions of the proteome [71]. PFT-based multiparametric AFM imaging provides a novel approach to image native biological systems in a physiological environment while simultaneously map the systems’ multiple properties at a molecular resolution [72], and the applications of PFT imaging have contributed much to the field of cell and molecular biology [73]. For the principles of PFT-based multiparametric AFM imaging, readers are referred to Chapter 1. In 2011, Rico et al. [74] utilized PFT mode AFM to investigate single bacteriorhodopsin in native purple membranes. Purple membranes adsorbed onto freshly cleaved mica were imaged in buffer solution (10 mM TrisHCl, pH 7.4, 150 mM KCl) at PFT mode. The topographical image and corresponding stiffness map of purple membranes were obtained simultaneously. Quantitative analysis of the magnified topographical and stiffness images revealed the various flexibility of different substructures of single bacteriorhodopsin

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molecules. The interhelical loops of bacteriorhodopsin were compliant structures providing structural flexibility to allow functions involving conformational changes, while protruding α-helices were rigid structures providing molecular stability, providing a new perspective to the relation between structure, function, and mechanics of membrane proteins. Also in 2011, Medalsy et al. [75] investigated the multiple properties of purple membranes at PFT mode and the mechanical properties of the substructures of bacteriorhodopsin were consistent with the results obtained by Rico et al. [74]. Besides, the effects of scanning force on the mechanical stability of membrane proteins were examined. By increasing the trigger force of PFT imaging to an adequate value (e.g., 125 pN), the substructures of bacteriorhodopsin collapsed, which were clearly visible from the multiparametric images, providing a direct way to investigate the conformational dynamics of membrane proteins in response to mechanical stimulation. In 2015, Alsteens et al. [76] imaged single G protein-coupled receptors while simultaneously quantifying their ligand-binding thermodynamics by using functionalized tips at PFT mode, as shown in Fig. 3.7A. The human protease-activated receptor-1 (PAR1) was used in the study. PAR1 was reconstituted in a lipid bilayer and ligands that could specifically bind to PAR1 were linked to AFM tip via PEG spacer (I in Fig. 3.7A). Scanning the PAR1-contained lipid bilayer patches with the functionalized tip at PFT mode allows both contouring of the membrane receptor by the tip and separate the ligand from the receptor while mechanically stretching the linker by withdrawing the cantilever [77], yielding the topographical image (IV in Fig. 3.7A) and corresponding adhesion map (V in Fig. 3.7A). Force curves for each sampling point were recorded during PFT imaging and there were different types of force curves (II in Fig. 3.7A), including no adhesion events, nonspecific adhesion events in the contact region (,45 nm) of tip and sample, and specific adhesion events distant ( . 5 nm) from the contact region. The force curves were used to separate nonspecific interactions from specific interactions. The overlay of topography and adhesion map structurally correlated nonspecific and specific adhesion events (VI in Fig. 3.7A). Since the tip oscillates in a sinusoidal manner during PFT imaging, the ligand-receptor bond can be ruptured at a wide range of loading rates, which provides sufficient data to reconstruct the free-energy landscape of the receptorligand complex [77]. For doing so, a force curve is displayed as a force-time curve, from which the loading rate can be extracted via the slope of the curve just before bond rupture. These studies demonstrate that PFT-based multiparametric AFM imaging is a potent tool for simultaneously and quantitatively characterizing the multidimensional (physical, chemical, and biological) properties of single unlabeled membrane proteins in the native membrane, which are quite meaningful for unraveling the underpinnings of proteins.

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FIGURE 3.7 Imaging single membrane proteins while simultaneously quantifying their specific binding interactions by peak force tapping (PFT)-based multiparametric atomic force microscopy (AFM). (A) Mapping ligand binding to human PAR1 by PFT multiparametric imaging. (I) Schematic illustration of imaging reconstituted PAR1 in lipid membrane at PFT mode using functionalized tips. (II) Representative force curves recorded during PFT imaging. (III) Overview topographical image of PAR1 in lipid membrane. (IV, V) Topographical image (IV) and corresponding adhesion map (V) of the boxed area in (III). (VI) Overlay of adhesive interactions (red) with a representative AFM topographical image (gray). (B) Mapping specific ligand-receptor events between an NTA-functionalized AFM tip and His-tagged bacteriorhodopsin of purple membrane by combining PFT with confocal fluorescence microscopy. (I) Schematic illustration of engineering His-tags to bacteriorhodopsin in purple membrane. (II, III) Confocal image (II) and AFM topography (III) of purple membrane patches adsorbed to mica in buffer solution. (IV) Adhesion map of the purple membranes recorded in the presence of Ni21. (V) Adhesion map obtained with the same AFM tip after blocking the Ni21 in the buffer solution. Sources: (A) Reprinted with permission from D. Alsteens, M. Pfreundschuh, C. Zhang, P.M. Spoerri, S.R. Coughlin, B.K. Kobilka, et al., Imaging G protein-coupled receptors while quantifying their ligand-binding freeenergy landscape, Nat. Methods 12(9) (2015) 845851. Copyright 2015 Nature America, Inc. (B) Reprinted with permission from P.R. Laskowski, M. Pfreundschuh, M. Stauffer, Z. Ucurum, D. Fotiadis, D.J. Muller, High-resolution imaging and multiparametric characterization of native membranes by combining confocal microscopy and an atomic force microscopy-based toolbox, ACS Nano 11(8) (2017) 82928301. Copyright 2017 American Chemical Society.

Combining PFT-based multiparametric AFM imaging with fluorescence microscopy improves the localization and detection of single membrane proteins in native membranes. Though the specific receptorligand interactions can be deduced from the obtained force curves (as shown in the II in Fig. 3.7A), direct verification of the specific

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adhesion events via commonly used biochemical methods is still important and critical for convincingly characterizing the behaviors of single membrane proteins. In 2017, Laskowski et al. [78] combined multiparametric AFM imaging with confocal fluorescence microscopy to investigate the purple membranes, as shown in Fig. 3.7B. For doing so, AFM was mounted on top of an inverted confocal microscope. A His10-tag was engineered to the cytoplasmic C-terminal end of bacteriorhodopsin (I in Fig. 3.7B). The sample was then fluorescently labeled with Ni21-NTA-Atto 488 and imaged by confocal microscopy. It is difficult to determine the exposed surface of purple membrane patches from the obtained AFM topographical images (III in Fig. 3.7B), but the exposed surface of the purple membrane patches could be clearly verified from the fluorescence images. The fluorescent surface means that the membrane patch exposes the cytoplasmic surface while the surface without fluorescence means that the membrane patch exposes the extracellular surface (II in Fig. 3.7B). By imaging purple membranes with a functionalized tip which could specifically bind to the His10-tag on the bacteriorhodopsin, the specific molecular interaction events were visible from the adhesion map (IV in Fig. 3.7B). After adding EDTA to chelate the coordinating Ni21 ions for blocking experiments, the specific unbinding events significantly decreased (V in Fig. 3.7B), further verifying the specific molecular interactions. The study distinctly shows the complementarity between AFM and fluorescence microscopy in biochemically identifying the membrane proteins while simultaneously detecting their binding mechanics, which helps to better probe the behaviors of membrane proteins.

3.6 Topography and recognition imaging of single membrane proteins As described above, except for the few types of natural membranes such as purple membranes, commonly, membrane proteins are reconstituted into lipid bilayers which are then adsorbed onto support for AFM imaging and force spectroscopy of single membrane proteins. A drawback of this experimental strategy is that the artificial lipid bilayer membrane is not the real plasma membrane of cells and thus strictly speaking the membrane proteins in the artificial lipid bilayers are not in their fully native states. From this point, directly probing the membrane proteins in the plasma membranes of cells benefits understanding their activities. Nevertheless, living animal cells have quite soft, rough, and deformable surfaces, making it extremely challenging for applying AFM to directly image the single membrane proteins in plasma membranes on living cells with sufficient spatial resolution. As an alternative way, we can isolate cell membrane patches from living cells and

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then attach these membrane patches onto a flat and stiff substrate, which facilitates AFM detection of the membrane proteins in the membrane patches with high SNR. Since red blood cells (RBCs) are much simpler than other types of cells (RBCs do not have a nucleus and other intracellular organelles [79]), the plasma membranes of RBCs have been largely used as the examples for AFM-based investigations of the structures and functions of the cell membrane [80]. A commonly used method to prepare membranes of RBCs is opening RBCs with a jet stream of hypotonic phosphate buffered saline (PBS) using a micropipette [81], as shown in Fig. 3.8A. For doing so, RBCs are firstly adsorbed to the substrates which are coated with poly-Llysine [82] or 3-aminopropyltriethoxysilane (APTES) [83] in advance to promote the attachment of RBCs to substrates. Then a micropipette or a syringe is used to inject hypotonic buffer (such as 7.5 mM PBS, pH 7.5) to flush the RBC cells on the substrate at an angle of 20 degrees. Shearing RBCs at a fast speed can cause the exposing of the inner membrane on the substrate, while a slow speed of shearing can obtain the outer membrane of RBCs deposited on the substrate. The mechanical stripping method has also been presented to isolate plasma membranes [84], as shown in Fig. 3.8B. In brief, cells are firstly seeded on coverslips (I in Fig. 3.8B). Next, the cell-seeded coverslips are reversed and placed on a clean coverslip (II in Fig. 3.8B). Weighting pieces can be put on the cell-seeded coverslip to increase the pressure. Finally, the cell-seeded coverslip is stripped and the cell membrane patches are left on the lower coverslip for AFM detection (III in Fig. 3.8B). In addition, researchers have also used the ultrasonic-based unroofing technique [85] or trypsin-based digestion [86] to obtain the cell membrane patches for AFM studies, providing additional ideas for isolating the plasma membranes from living cells. Applications of simultaneous topography and recognition imaging (TREC) mode AFM in detecting the plasma membrane patches offer novel possibilities for characterizing the activities of native membrane proteins at molecular resolution. For the principles of TREC mode AFM imaging, readers are referred to Chapter 1. In 2009, Jiang et al. [87] used TREC mode AFM to map the Na, K-ATPase in the quasi-native plasma membrane, as shown in Fig. 3.8C. During the evolution of life, most living cells have established a similar ionic composition of their cytoplasm, including low calcium, low sodium, high potassium, and neutral pH [88]. Na, K-ATPase is an integral membrane protein which mainly functions as an ion pump, hydrolyzing one molecule of ATP to pump three Na1 out of the cell in exchange for two K1 entering the cell per pump cycle [89] to maintain the high K1 and low Na1 concentrations in the cytoplasm for molecular and cellular functions. Na, K-ATPase is ubiquitously expressed in the plasma membrane of all animal cells [90]. After preparing the plasma membranes of RBCs using the shearing open method as described above, AFM imaging was performed on the

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FIGURE 3.8 Mapping membrane proteins in the plasma membrane patches with molecular resolution by simultaneous topography and recognition imaging (TREC) mode atomic force microscopy (AFM). (A) Schematic illustration of preparing cell membrane patches of red blood cells (RBCs) by shearing stream. RBCs are exposed to rapid fluid flow-imposed shear stress and, as a result, the cells are open, exposing their cytoplasmic side of the membrane. (B) Schematic illustration of preparing cell membrane patches by mechanical stripping. (C) Imaging single membrane proteins while simultaneously recognizing their unbinding events by TREC mode AFM. (I) AFM image of the RBC membranes exposing cytoplasmic surfaces. (II, III) Topographical image (II) and corresponding recognition image (III) of local areas on the membranes obtained during TREC mode imaging. (IV) Overlay of topography and recognition (green dots). Sources: (A) Reprinted with permission from H. Schillers, Imaging CFTR in its native environment, Pflug. Arch. Eur. J. Physiol. 456 (1) (2008) 163177. Copyright 2007 Springer-Verlag. (B) Reprinted with permission from C. Marasini, E. Jacchetti, M. Moretti, C. Canale, O. Moran, M. Vassalli, Visualization of single proteins from stripped native cell membranes: a protocol for high-resolution atomic force microscopy, Microsc. Res. Tech. 76(7) (2013) 723732. Copyright 2013 Wiley Periodicals, Inc. (C) Reprinted with permission from J. Jiang, X. Hao, M. Cai, Y. Shan, X. Shang, Z. Tang, et al., Localization of Na 1 -K 1 ATPases in quasi-native cell membranes, Nano Lett. 9(12) (2009) 44894493. Copyright 2009 American Chemical Society.

membrane patches. AFM images clearly showed the well-distributed membranes of RBCs (I in Fig. 3.8C). By using functionalized tips (antibodies which could specifically bind Na, K-ATPase molecules were attached to the surface of AFM tip) to scan the local areas on the membrane patches at TREC mode, topographical image and recognition image were obtained simultaneously. From the topographical image (II in Fig. 3.8C), protein particles are clearly discriminable. From the

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corresponding recognition image (III in Fig. 3.8C), the dark spots (denoted by the arrows) indicate the unbinding events between Na, K-ATPase molecules and antibodies. The spatial distributions of Na, K-ATPase molecules in the membrane proteins are visually revealed from the superimposition of the topographical image and recognition image (denoted by the green dots in IV of Fig. 3.8C). The correctness of the recognition spots in the recognition image was confirmed by the blocking experiments, in which free antibodies were added to bind to the Na, K-ATPase molecules in the membrane and then TREC mode AFM imaging was performed on the membrane. Based on this method, the changes in spatial distributions of membrane proteins in the plasma membrane of RBCs upon chemical treatments were revealed [91]. These studies show that AFM is able to specifically locate individual membrane proteins in the natural complex plasma membranes containing numerous different types of proteins with high spatial resolution as well as detect their functions, which benefits understanding the behaviors of membrane proteins in their really native environments.

3.7 Summary We can see that AFM is now a highly powerful and multifunctional tool to characterize the structures and properties as well as functions of single membrane proteins in their native environments under physiological conditions, including visualizing the fine structures and conformational dynamics of single membrane proteins (Figs. 3.2 and 3.3), revealing the mechanical pathways during the unfolding process of single membrane proteins (Figs. 3.4 and 3.5), capturing the instantaneously conformational and motional changes of single membrane proteins at work in lipid bilayers by high-speed AFM (Fig. 3.6), imaging single membrane protein while simultaneously quantifying their binding thermodynamics by multiparametric AFM (Fig. 3.7), and locating single membrane proteins in the real plasma membrane patches by TREC mode AFM (Fig. 3.8). Applications of AFM in the studies of individual membrane proteins have yielded numerous unique insights into the field of molecular biology and impressively offer a new perspective to understand the biophysics of proteins, which are of great significance for deciphering the mysteries of life at the single-molecule level. Regarding the AFM-based studies of membrane proteins, the different research strategies have their own advantages and are complementary. By reconstituting membrane proteins into the artificial lipid bilayers (Figs. 3.3 and 3.4), the conformations and their dynamics as well as the mechanical unfolding dynamics of single membrane proteins in a membrane environment can be revealed by AFM, which provide

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straightforward details on the activities and functions of single membrane proteins with unprecedented spatiotemporal resolution. In contrast, utilizing AFM to directly detect the membrane proteins in the plasma membranes isolated from living cells (Fig. 3.8) benefits understanding how the membrane proteins function in the real plasma membrane environment. Notably, although different types of methods have been developed to prepare cell membrane patches, utilizing AFM to investigate the behaviors of membrane proteins in plasma membrane patches (particularly in non-RBC cells) is still scarce. In addition, due to the separation from the cell, neither reconstituted lipid membrane nor real plasma membrane patches can be used to examine the impacts of membrane proteins on the activities of living cells. Therefore, combining AFM-based membrane protein studies with cellular studies (such as evaluating the biological functions of cells which are associated with the specific membrane proteins) will promote a comprehensively understanding of the functions of membrane proteins. Further applications of AFM to the studies of membrane proteins in more biological systems will help to improve our understanding of the physiological and pathological processes. It is increasingly evident that there are significant changes in the compositions and structures of plasma membranes during the formation and progression of cancerous cells. For example, normal cells have a short glycocalyx on the cell membrane and the distribution of glycoproteins and adhesion molecules are uniform across the cell membrane, while tumor cells have a larger glycocalyx on the cell membrane which results in the clustering of integrins [92]. Besides, integrins are the main adhesion receptors on the cell surface and altered integrin expression is frequently detected in tumor cells during metastasis [93]. The structures and organizations of plasma membranes, therefore, provide a unique biomarker for indicating the states of cancerous cells. Particularly, studies have shown that the specific makeup and arrangement of the cell membrane can be modulated to help cancer therapy [94]. Hence, applying the established methodologies to locate the specific membrane proteins and detect their changes in the plasma membrane patches isolated from cancerous cells (also from healthy counterparts for the control group) will undoubtedly improve our understanding of oncology. For doing so, one needs to isolate primary cancerous cells from the biopsies of clinical tumor patients and then extract the plasma membrane patches from these cancerous cells for AFM studies. Taken together, AFM significantly expands the biophysical studies of single membrane proteins in their near-native states, which benefits answering the fundamental issues in the field of life sciences. In the future, more membrane protein-related studies performed with AFM, particularly combined with other complementary techniques, will lead

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to further advances in the regulatory role of membrane proteins in physiological and pathological processes.

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C H A P T E R

4 Characterizing the nanostructures and mechanical properties of hydrogels by atomic force microscopy

4.1 Background Hydrogels have emerged as a promising material to recapitulate the microenvironment of cells for biomedical applications. Hydrogels, which are three-dimensional networks composed of cross-linked hydrophilic polymer chains, can be cast into practically any shape, size, or form and can absorb up to thousands of times their dry weight in water [1]. Because of the large water content, hydrogels are quite biocompatible, and can be made with water contents quite similar to those of biological tissues (B70%) or much greater (up to and beyond 99% water) [2]. Hydrogels are formed by cross-linking polymer chains dispersed in an aqueous medium through a myriad of mechanisms, including physical (noncovalent) crosslinking (e.g., thermo condensation, self-assembly, ionic gelation, and electrostatic interaction) and chemical (covalent) crosslinking [3]. A wide and diverse range of polymer compositions has been used to fabricate hydrogels, which can be divided into natural polymers (polysaccharides and proteins), synthetic polymers (polyesters and other polymers containing hydrophilic functional groups), and combinations of the two classes [4]. Since single-network hydrogels have weak mechanical properties and slow response at swelling, multicomponent networks as interpenetrating polymer networks (IPNs) have been designed to enhance the mechanical strength and swelling/deswelling response [5], for example, researchers

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have mixed different types of crosslinked polymers to create highly stretchable, tough, and adhesive hydrogels for biomedical applications [6,7]. An important application of hydrogels is to construct the growth microenvironments of cells. Hydrogel-based three-dimensional cell culture offers novel possibilities to bridge the gap between conventional twodimensional cultures and complex native in vivo environments, as hydrogels mimic salient elements of native extracellular matrices (ECMs) allowing encapsulated cells to interact with their ECMs in three directions, have mechanics similar to those of many soft tissues, and can support cell adhesion and protein sequestration [8], as shown in Fig. 4.1. Users need to understand the properties of the hydrogels for cell culture applications, as they can influence the utility of hydrogels, including mechanics (can influence the stability of hydrogels and also cellular mechanotransduction), swelling (an indicator of the polymer network hydrophilicity and relative crosslinking density), mesh size (can influence nutrient flux throughout the matrix), degradation (can influence mechanics and swelling of hydrogel, which in turn affect cell behaviors such as motility, spreading and traction force generation), and so on [8]. Besides, to recapitulate the dynamic nature of the ECM, many reversible chemistries have been incorporated into hydrogels to regulate cell spreading, biochemical ligand presentation and matrix mechanics [9]. Particularly, studies have demonstrated the feasibility of the controlled addition and release of multiple proteins within a single hydrogel, which move hydrogels to the fourth dimension and are quite

FIGURE 4.1 Three-dimensional hydrogels can be engineered to present a more realistic network microenvironment to cells. Hydrogel design variables are indicated. Physically crosslinked hydrogels have transient network junctions, while chemically crosslinked hydrogels have permanent network junctions due to the covalent bonding between polymer chains. Some hydrogels (such as alginate hydrogels) must be modified with an adhesive ligand such as RGD to enable cell attachment. Hydrolysis of hydrogels occurs with inclusion of hydrolytically unstable bonds. Natural hydrogels like collagen and fibrin degrade by cell-mediated proteases such as matrix metalloproteinases (MMPs). External triggers such as ultraviolet (UV) light have also been used to control degradation of hydrogels. Source: Reprinted with permission from S.R. Caliari, J.A. Burdick, A practical guide to hydrogels for cell culture, Nat. Methods 13(5) (2016) 405414. Copyright 2016 Nature America, Inc.

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meaningful for addressing complex biological questions in threedimensional environments [10]. Hydrogels also significantly promote the studies of regenerative medicine which aims to regenerate damaged or diseased cells/tissues/organs and decrease reliance on transplantations, as advances in hydrogel technologies are allowing researchers to create ex vivo tissue models that replicate native tissues better than ever before [11,12]. Since AFM is able to work in liquids with nanometer spatial resolution, whereas hydrogels are biomaterials with high water content, AFM is an adequate tool for the characterizations of hydrogels. AFM has unique advantages compared with other techniques largely used for the characterizations of hydrogels. SEM has been a commonly used tool to characterize the three-dimensional porous network structures of freeze-dried hydrogels [13,14]. However, the crystalline ice formed during the freezing process can damage the biological specimens [15], which results in a marked disordering of the structures of hydrogels [16], and therefore the images obtained by SEM may not faithfully reflect the real structures of hydrogels. Although cryo-SEM has the potential to offer the most authentic insights into the native three-dimensional structures of hydrogels due to the ability to enable the formation of vitreous ice instead of crystalline ice [17,18], cryo-SEM requires complex sample preparations and substantial instrumentations which are still rarely present in many laboratories. On the contrast, AFM is able to resolve the fine structures of hydrogels in their hydrated states without any pretreatments [19] and the sample preparation process is quite simple. Notably, due to the fact that AFM is essentially a surface characterization instrument, AFM can only give the topographical images of the surface structures of hydrogels in the planar directions and cannot access the interior structures of hydrogels in three dimensions. In addition to topographical imaging, AFM can also measure the mechanical properties of hydrogels by indentation assays. In fact, AFM-based indentation assay is now a standard tool to characterize the local mechanics of hydrogels for applications in cell culture because of the nano/micron-sized tips used to indent the specimens [8,20]. With the use of nano-sized sharp tips, the mechanical properties of hydrogels can be obtained with nanometer spatial resolution to map the local heterogeneous mechanics of hydrogels [2], which is meaningful to examine the delicate mechanical cues in cell-ECM interactions [21]. By attaching individual micron-sized spheres to the AFM cantilever to form spherical tips [22], the mechanical properties of hydrogels at a cellular level can be measured. Hence, AFM is a powerful and multifunctional tool for the studies of hydrogels, and applications of AFM in characterizing the nanostructures and mechanical properties of biopolymeric hydrogels to better understand the nanoscale self-assembly mechanisms during the formation of hydrogels are presented in the remaining of the chapter.

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4.2 Nanostructures and nanomechanics of natural plant hydrogels The natural biomaterials and their delicate structures formed during the evolution of nature over hundreds of millions of years provide a wealth of resources for the research and design of biomimetic materials, and therefore elucidating the molecular mechanisms guiding the formation of these biomaterials’ fine structures extremely benefits the studies of biomaterials for practical applications. In nature, carnivorous plants trap and utilize animals to improve their supply of mineral nutrients, and one strategy for prey capture is the use of adhesive traps, for example, leaves of sundew are able to produce sticky mucilage [23]. Once the insects touch the mucilage, the insects are trapped firmly, which triggers the closure of leaves to ensure the digestion of insects by the transfer of biochemical (auxin) and electrical signals (jasmonic acid) [24]. In order to utilize AFM to characterize the fine structures of the mucilage secreted by sundew, the prerequisite is culturing sundew. The seedlings of carnivorous plants such as sundew are commercially available. For a study of characterizing sundew mucilage by AFM [25,26], the sundew was purchased from Shandong Guixiang Photoelectric Co., Ltd (Weifang, China). The potted sundew (I in Fig. 4.2A) was cultured according to the protocol provided by the supplier. Since the sundew is a type of heliophile, the potted sundew needs to be placed on the windowsill to receive sunshine for growth. Besides, mineral-free water was used for the growth of sundew. In addition, the ambient temperature for sundew growth was in the range 20 C25 C and the environmental humidity for sundew was in the range 50%70%. After about one week of the growth of the potted sundew, the mucilage dewdrops were produced by the leaves of sundew, which were typically denoted by the blue arrows in Fig. 4.2A(II)). The mucilage dewdrop is sticky, which allows the capture of insects on the leaf of sundew, as denoted by the dashed red ellipse in Fig. 4.2A(III). The process of preparing sundew mucilage for AFM characterizations is shown in Fig. 4.2B. In brief, a freshly cleaved mica (approximately 1 3 1 cm), which was attached to a glass slide (Fig. 4.2C), was controlled to gently touch the sundew mucilage to transfer the mucilage to the mica surface. The sample was then directly analyzed by AFM without any pretreatments. On the whole, the size of dewdrops on different tentacles is approximately close to each other. In order to make the procedure of sample preparation reproducible as much as possible, one probable way is placing each dewdrop on a different area of the mica surface to ensure that each dewdrop area on the mica surface has a similar volume of mucilage. AFM topographical imaging visualizes the nanostructures and their organizations of the natural mucilage secreted by sundew, as shown in

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FIGURE 4.2 Sample preparation of utilizing atomic force microscopy (AFM) to observe the natural mucilage secreted by sundew. (A) Mucilage produced by Drosera capensis. (I) Overall optical image of the potted sundew. (II) Optical image of a leaf of sundew. There are many tentacles on the leaf and mucilage dewdrops (typically denoted by the blue arrows) are secreted at the end of each tentacle. (III) An insect (denoted by the dashed red ellipse) captured by the mucilage. (B) Schematic illustration of the procedure of coating sundew mucilage on mica for AFM characterizations. (I, II) Schematic diagram (I) and optical image (II) of a tentacle on a sundew leaf. (III) Mucilage coated on mica is directly observed by AFM without any pretreatments. (C) Optical image of touching sundew mucilage dewdrops with a freshly cleaved mica (the mica is immobilized on a glass slide). Sources: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Composite nanostructures and adhesion analysis of natural plant hydrogels investigated by atomic force microscopy, IEEE Trans. Nanobiosci. 18(3) (2019) 448455. Copyright 2019 IEEE. Reprinted with permission from M. Li, N. Xi, L. Liu, Ultra-microstructures and mechanics of plant mucilage functional interfaces investigated via atomic force microscopy in liquid (in Chinese), Sci. Sin. Tech. 51(5) (2021) 543553.Copyright 2021 Science China Press.

Fig. 4.3. AFM experiments were performed with a commercial AFM called Dimension Icon AFM (Bruker, Santa Barbara, CA, USA) at PFT mode. For imaging in air, the nominal spring constant of the used cantilever is 0.4 N/m, the nominal resonant frequency of the cantilever is 70 kHz, and the tip radius is about 2 nm. For imaging in water, the nominal spring constant of the used cantilever is 0.7 N/m, the nominal resonant frequency of the cantilever is 150 kHz, and tip radius is about 20 nm. When utilizing AFM to image sundew mucilage in air, the porous network structures are remarkably revealed (I and II in Fig. 4.3A). Besides, closely packed nanofibrils are also observed (III in Fig. 4.3A). In order to image the structure of single nanofibrils, the

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FIGURE 4.3 Atomic force microscopy (AFM) topographical images revealing the diverse nanostructures of sundew mucilage in different imaging conditions (in air and in pure water). (A) AFM images recorded in air. (I-IV) AFM topographical images. (V) A longitudinal section profile curve staken along a nanofibril (denoted by the red line in IV). (B) AFM images recorded in pure water. (I-II) AFM topographical images. (III) A section profile curve taken on nanoparticles (denoted by the red line in II). Sources: (A) Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Composite nanostructures and adhesion analysis of natural plant hydrogels investigated by atomic force microscopy, IEEE Trans. Nanobiosci. 18(3) (2019) 448455. Copyright 2019 IEEE. (B) Reprinted with permission from M. Li, N. Xi, L. Liu, Ultra-microstructures and mechanics of plant mucilage functional interfaces investigated via atomic force microscopy in liquid (in Chinese), Sci. Sin. Tech. 51(5) (2021) 543553. Copyright 2021 Science China Press.

mucilage-coated mica was washed by pure water and then AFM imaging was performed on the sample again, showing the distinct topography of individual nanofibrils (IV in Fig. 4.3A). From the longitudinal section curve taken along a nanofibril (denoted by the red line in the IV of Fig. 4.3A), we can see many peaks (denoted by the blue arrows in the V of Fig. 4.3A), indicating that the nanofibril has heterogeneous structures along the longitudinal direction. In fact, the helical substructures of each nanofibril are discriminable from AFM images (IV in Fig. 4.3A).

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When imaging the mucilage-coated sample in pure water, we cannot see the nanofibrous structures in the AFM images but at the same time nanoparticles are significantly observed, as shown in Fig. 4.3B(I, II). The peaks in the section curve (denoted by the green arrows in the III of Fig. 4.3B) correspond to the nanoparticles. It is reasonable to speculate that these nanoparticles may be the products formed due to the degradation of sundew mucilage in pure water. The experimental results (Fig. 4.3) clearly show the diverse nanostructures (porous structure, network structure, nanofibril, nanoparticle) of sundew mucilage in different conditions(in air, or in water) imaged by AFM topographical imaging. Researchers have widely used SEM or AFM to characterize the structures of seed mucilage in air, and nanofibrils have been largely observed [2729]. Notably, these studies were performed in the air (AFM) or in vacuum (SEM), both of which require the air-drying of mucilage specimens. Here, by applying AFM to image sundew mucilage in liquid, nanoparticles were observed, that were previously undiscovered. Further studies are needed to reveal the relationships between nanoparticles and nanofibril networks during the formation of sundew mucilage. Overall, the studies (Fig. 4.3) provide direct evidence of the nanostructures (nanoparticles, nanofibrils) of sundew mucilage, which will benefit understanding the biological functions of sundew mucilage. AFM has also been used to characterize the morphology and mechanical properties of nanostructures of the natural mucilage secreted by another type of carnivorous plant called pinguicula [30]. Fig. 4.4 shows the results of utilizing AFM to reveal the nanostructures of pinguicula mucilage. Similar to sundew, the leaves of pinguicula also produce sticky mucilage for prey capture [23]. Since pinguicula is a type of shade-requiring plant, the purchased potted pinguicula was placed indoors and mineral-free water was used for the growth of pinguicula. Mucilage dewdrops are clearly discriminable from the optical images of the leaves of the pinguicula, as shown in Fig. 4.4A. The sample preparation procedure of pinguicula mucilage for AFM characterizations is the same as that of sundew mucilage. After coating the pinguicula mucilage on freshly cleaved mica, AFM imaging was performed in the air. AFM images of pinguicula mucilage distinctly show nanofibrils and reveal the diverse assembly behaviors of nanofibrils (Fig. 4.4B). Not only nanofibril reticular structures are observed (I, II in Fig. 4.4B), but also individual nanofibrils (III in Fig. 4.4B) and bundled nanofibrils (IV in Fig. 4.4B) are visualized. When imaging pinguicula mucilage in pure water by AFM, nanoparticles are significantly observed, as shown in Fig. 4.4C. We can see that the nanostructures of sundew mucilage (Fig. 4.3) and pinguicula mucilage (Fig. 4.4) are similar to each other, both of which exhibit nanofibrous structures in air and exhibit nanoparticle structures in pure water, indicating that nanofibrils and

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FIGURE 4.4 Atomic force microscopy (AFM) topographical images revealing the nanostructures that constitute the mucilage of pinguicula. (A) Mucilage secreted by Pinguicula esseriana. (I) Overall optical image of the potted pinguicula. (II) Optical image of a leaf of pinguicula. There are numerous dewdrops (mucilage) on the leaf. (III) Magnified image of the dewdrops. (B) AFM images acquired in air. (C) AFM images acquired in pure water. (I) AFM topographical image and the (II) corresponding peak force error image. AFM images were recorded at PFT mode. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanoscale organization and functional analysis of carnivorous plant mucilage by atomic force microscopy, IEEE Trans. Nanotechnol. 19 (2020) 579593. Copyright 2020 IEEE.

nanoparticles are widespread in the mucilage secreted by carnivorous plants which use mucilage to trap insects. Besides resolving the nanostructures of mucilage, AFM can also measure the mechanical properties of single nanofibrils, as shown in Fig. 4.5. With the use of PFT-based multiparametric AFM imaging, various mechanical property maps of nanofibrils are generated simultaneously with the topographical image (I in Fig. 4.5A), including deformation map (II in Fig. 4.5A), Young’s modulus map (III in Fig. 4.5A), and adhesion force map (IV in Fig. 4.5A). The multiparametric AFM images qualitatively correlate the

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FIGURE 4.5 Atomic force microscopy (AFM) mechanical analysis revealing the mechanical properties of single nanofibrils. (A) Imaging individual nanofibrils while simultaneously visualizing their multiple mechanical properties by PFT-based multiparametric AFM imaging. Experiments were performed in air. (I) Topographical image and corresponding (II) deformation image, (III) Young’s modulus image, and (IV) adhesion image of nanofibrils. The section curves taken along the red lines in (I-IV) are shown under each of the AFM images. (B) Quantitatively measuring the mechanical properties of single nanofibrils by AFM indentation assay. (I) A typical force curve obtained on nanofibrils. (II) Fitting the experimental indentation curve with Sneddon model to obtain Young’s modulus of nanofibrils. (III, IV) Statistical histograms (Mean 6 SD) of adhesion force (III) and Young’s modulus (IV) of nanofibrils measured at different loading rates of AFM probe. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanoscale organization and functional analysis of carnivorous plant mucilage by atomic force microscopy, IEEE Trans. Nanotechnol. 19 (2020) 579593. Copyright 2020 IEEE.

mechanical properties (e.g., deformation, Young’s modulus, adhesion force) of single nanofibrils with their structures. The section profile curves (bottom curves under AFM images in Fig. 4.5A) taken along the nanofibrils (denoted by the red lines in Fig. 4.5A) allow comparing

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the mechanical properties of different nanofibrils in the same AFM image. The mechanical properties of single nanofibrils can also be quantitatively measured by AFM indentation assay, during which the AFM tip is controlled to indent single nanofibrils to record force curves. For more technical details of AFM-based indentation assay and force spectroscopy, readers are referred to Chapter 1. A typical force curve obtained on nanofibrils is shown in Fig. 4.5B(I). Analyzing the approach part of a force curve with the HertzSneddon model gives Young’s modulus of nanofibrils (II in Fig. 4.5B), while the adhesion force of nanofibrils is calculated from the retract part (I in Fig. 4.5B). Notably, the adhesion force of nanofibrils does not depend on the loading rates of the AFM probe (III in Fig. 4.5B), whereas Young’s modulus of nanofibrils increases with the loading rates of the AFM probe (IV in Fig. 4.5B). Hence, if one wants to analyze and compare Young’s modulus of different nanofibrils, one needs to confirm that the loading rates of the AFM probe during all measurements are identical to eliminate the effects of measurement parameters on the results. In addition to the sticky mucilage produced by sundew and pinguicula, AFM has also been used to reveal the nanostructures of nectar secreted by trumpet pitchers and Venus flytraps, as shown in Fig. 4.6. The predation mechanisms of trumpet pitchers and Venus flytraps are quite different from that of sundew and pinguicula. The trumpet pitcher uses modified leaves (called pitcher) that form upright, funnel-shaped traps to capture prey [31]. The pitcher opening is surrounded by a smooth, swollen rim called the peristome, and nectar is secreted at the peristome as bait to lure the insects. When the visiting insects climb into the pitcher to consume the nectar, they slip and fall into the bottom of the pitcher, and subsequently, these insects are digested by the digestive enzymes at the bottom of the pitcher to provide the nutrients for the growth of trumpet pitchers. The Venus flytrap uses the trap-forming leaf to capture the prey [32]. The Venus flytrap has mechanically sensitive hairs in the bivalved leaf, and also nectar is secreted to coat the inner surface of the leaf to lure the insects. The visiting insect’s movements in the leaf of the Venus flytrap to consume the nectar can easily trigger these sensitive hairs, which will cause the rapid closure of the Venus flytrap leaf in about 100 ms [33]. The insects are then firmly trapped and digested by the Venus flytrap to provide the nutrients for the growth of the Venus flytrap. We can see that both the trumpet pitcher and Venus flytrap secrete nectar to lure insects, and AFM has been used to reveal the nanostructures of nectar produced by the trumpet pitcher and Venus flytrap [34]. Trumpet pitcher and Venus flytrap are both photophilous plants, and thus both of them were placed on the windowsill to receive sunshine for growth. Deionized water was used for the growth of the trumpet pitcher and Venus flytrap. For the

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FIGURE 4.6 Atomic force microscopy (AFM) topographical imaging and analysis of nectar secreted by Sarracenia rubra and Dionaea muscipula. (A) Nectar secreted by trumpet pitcher. (B) Nectar secreted by Venus flytrap. (I) Optical images of the nectar. (II, III) Typical AFM topographical images of nectar. AFM images were obtained in pure water at PFT mode. (IV) Section profile curves taken along the nanoparticles (denoted by the red lines in III). (V) Statistical histograms of the size of nanoparticles. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, In situ imaging and analysis of the nanostructures in natural hydrogels from carnivorous plants by atomic force microscopy (in Chinese), Sci. Sin. Vitae 50(6) (2020) 650660. Copyright 2020 Science China Press.

trumpet pitcher, we can clearly see the nectar at the rim of the leaf (denoted by the blue arrows in the I of Fig. 4.6A). For the Venus flytrap, the nectar is also distinctly discernible (denoted by the blue arrow in the I of Fig. 4.6B). In experiments, we found that the nectar from the trumpet pitcher or Venus flytrap did not dry in the air, causing it challenging to image the fine structures of nectar by AFM in the air. We therefore directly imaged the nectar-coated specimens in pure water by AFM, and nanoparticles were significantly observed from the obtained AFM images (II and III in Fig. 4.6A and B), showing that nanoparticles are important building blocks of the structures of nectar produced by trumpet pitcher or Venus flytrap. An interesting phenomenon is that the nanoparticles of nectar secreted by trumpet pitcher were significantly smaller than that secreted by Venus flytrap (IV and V in Fig. 4.6A and B), showing the differences between trumpet pitchersecreted nanoparticles and Venus flytrap-secreted nanoparticles. Overall, AFM topographical imaging visually provides direct evidence of the nanostructures of the nectar, which benefits understanding the biological functions of nectar produced by carnivorous plants. Further

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studies are needed to analyze the compositions of these nanoparticles, which will help to reveal the molecular mechanisms guiding the formation of nectar.

4.3 Characterizations of biopolymeric hydrogels inspired by carnivorous plant mucilage Inspired by the mucilage produced by sundew, an alginate-gum arabic biopolymeric hydrogel with tunable structures has been developed, as shown in Fig. 4.7. Studies have revealed the chemical compositions of the mucilage secreted by sundew, showing that sundew mucilage is a viscoelastic, homogeneous, about 4% aqueous solution of a single polysaccharide with a molecular weight over 2 3 106 Da [23]. After hydrolysis of sundew mucilage, the sugars L-arabinose, D-xylose, D-galactose, D-mannose, and L-glucuronic acid are found. The mucilage also contains inorganic cations (Ca21, Mg21, K1, Na1) and ester sulfate. According to the chemical compositions of sundew mucilage, sodium alginate and gum arabic as well as Ca21 were used to mimic the sundew mucilage (Fig. 4.7A) [35]. Alginate is a whole family of linear copolymers containing blocks of (1,4)-linked β-D-mannuronate (M) and α-L-guluronate residues [36]. Gum arabic is one of the most commonly used hydrocolloids in the food industry due to its excellent emulsifying properties, and the major component of gum Arabic is arabinogalactan [37]. Mixing sodium alginate and gum arabic under calcium ion-mediated crosslinking yields the sundew-inspired sticky hydrogel (Fig. 4.7B). The detailed process of preparing the sundew-inspired hydrogel based on sodium alginate and gum arabic under Ca21 crosslinking is following [35] (1) Prepare 1 M Ca21 solution by dissolving 1.47 g of CaCl2 2H2O with 10 mL of pure water. (2) Pipette a certain amount of Ca21 solution into 2 mL of pure water in a vial to prepare Ca21 solution (e.g., 5, 10, 15 mM). (3) Add a certain amount of gum Arabic powder (e.g., for fabricating hydrogels containing 3% (w/v) gum Arabic, 60 mg of gum Arabic powder is added) into the vial, and then stir the solution using a magnetic stirrer until the gum Arabic is fully dissolved. (4) Add a certain amount of sodium alginate (e.g., for hydrogels containing 3% (w/v) sodium alginate, 60 mg of sodium alginate is added) into the vial and then stir for about 1 h to obtain the fabricated hydrogel. (5) Take the magnetic rotor out of the vial and then pour the hydrogels into a centrifuge tube. For simplicity, the prepared sundew-inspired hydrogel containing X% sodium alginate, Y% gum Arabic, and Z mM Ca21 will be abbreviated as hydrogel (XYZ). Fig. 4.7C shows the prepared hydrogel stored in a tube. By coating the prepared hydrogel on a substrate, AFM topographical imaging is applied to visualize the morphology of the prepared bioinspired hydrogel. AFM imaging results clearly show the tunable porous scaffolds of the



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FIGURE 4.7

Fabricating sundew-inspired biopolymeric hydrogels. (A) Schematic illustration of the sundew-inspired hydrogels. (B) Sundew-inspired hydrogels are formed by Ca21-mediated crosslinking of sodium alginate and gum Arabic. (C) Photograph of the prepared sundew-inspired hydrogel. (D) Characterizing the structures of sundew-inspired hydrogels. (I, II) Atomic force microscopy (AFM) images of hydrogel (7425) (I) and hydrogel (3315) (II). (III, IV) SEM images of freeze-dried hydrogel (3315). (E) AFM image (I) and SEM image (II) of hydrogel (0.20.21). Sources: (A and B) Reprinted with permission from M. Li, H. Li, X. Li, H. Zhu, Z. Xu, L. Liu, et al., A bioinspired alginate-gum arabic hydrogel with micro-/nanoscale structures for controlled drug release in chronic wound healing, ACS Appl. Mater. Interfaces 9(27) (2017) 2216022175. Copyright 2017 American Chemical Society. (C and D) Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Tunable hybrid biopolymeric hydrogel scaffolds based on atomic force microscopy characterizations for tissue engineering, IEEE Trans. Nanobiosci. 18(4) (2019) 597610. Copyright 2019 IEEE.

sundew-inspired hydrogel [38]. On the whole, increasing the component concentrations will yield hydrogels with larger pores. For example, AFM images show that the pore size of hydrogel (7425) (I in Fig. 4.7C) is significantly larger than that of hydrogel (3315) (II in Fig. 4.7C). SEM

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images of the freeze-dried hydrogels distinctly show the three-dimensional porous structures of the sundew-inspired hydrogels (III and IV in Fig. 4.7D). When the component concentration is decreased to a low level, such as the hydrogel (0.20.21), both AFM imaging (I in Fig. 4.7E) and SEM imaging (II in Fig. 4.7E) results remarkably show the individual nanofibrils (denoted by the yellow arrows in Fig. 4.7E) in the prepared hydrogels, indicating that the Ca2-mediated crosslinking of sodium alginate and gum Arabic could form nanofibrillar hydrogels. We can see that natural mucilage secreted by sundew or pinguicula considerably contains nanofibrillar structures (Figs. 4.3 and 4.4), and thus the nanofibrillar hydrogels formed by a low level of sodium alginate and gum Arabic are similar to the natural hydrogel to some extent. The adhesion properties of sundew-inspired hydrogels are analyzed by AFM, as shown in Fig. 4.8. Fig. 4.8A(I) is a typical force curve obtained on the hydrogel-coated substrate using the AFM probe with a conical tip (the spring constant of the cantilever is 0.08 N/m), showing that the adhesion force is about 20 nN. By changing the component concentrations (sodium alginate, gum Arabic, Ca21), sundew-inspired hydrogels with different adhesion properties can be obtained. For some hydrogels, the adhesion forces are quite large and exceed the measurement range of the probe with a conical tip. In order to measure the adhesion properties of these hydrogels, a probe with a spherical tip is used. A typical force curve obtained by the probe with a spherical tip (the spring constant of the cantilever is 2.8 N/m) is shown in Fig. 4.8A (II), showing that the adhesion force is about 150 nN. Topography and adhesion map of the hydrogels can be simultaneously acquired at the AFM force volume mode. Fig. 4.8B(I) is a representative topography image and Fig. 4.8B(II) is the corresponding adhesion force map recorded by a conical tip. The AFM force volume imaging was performed in a 35 3 35 μm2 area, during which 32 3 32 force curves were recorded. The adhesion force maps were automatically generated by the AFM software. We can see that porous scaffold structures are clearly discerned in the topographical image (I in Fig. 4.8B), while the adhesion force map (II in Fig. 4.8B) shows that there are no significant differences in the adhesion forces between scaffold areas (denoted by the red asterisks) and nonscaffold areas (denoted by the white asterisks). Fig. 4.8B (III) is the statistical histogram and the Gaussian fitting of the adhesion forces in Fig. 4.8B(II), showing that the adhesion forces are 20 6 1 nN. AFM force volume imaging results with the use of a spherical tip are shown in Fig. 4.8C, also showing the porous scaffold structures of the hydrogel with no significant differences in the adhesion forces between scaffold areas and nonscaffold areas. In order to examine whether hydrogels adhere to the AFM tip surface during AFM force spectroscopy measurements, control experiments were performed, as shown in

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FIGURE 4.8

Characterizing the adhesion properties of sundew-inspired hydrogels by atomic force microscopy (AFM). (A) Typical force curves obtained on the hydrogel-coated glass slides with conical tip (I) and spherical tip (II) respectively. (B and C) AFM force volume mode results obtained with conical tip (B) and spherical tip (C) respectively. (I) Topography images and (II) the corresponding adhesion force maps. (III) Statistical histograms of the adhesion forces in (II). (D) Adhesion force maps obtained on a control substrate (without hydrogel) and on a hydrogel-coated substrate by spherical tip. Adhesion measurements were performed on the control substrate firstly (I) and then on the hydrogel-coated substrate (II) with the same AFM tip. Subsequently, the same AFM tip was used to measure the adhesion forces on the control substrate again (III). Source: Reprinted with permission from M. Li, H. Li, X. Li, H. Zhu, Z. Xu, L. Liu, et al., A bioinspired alginate-gum Arabic hydrogel with micro-/nanoscale structures for controlled drug release in chronic wound healing, ACS Appl. Mater. Interfaces 9(27) (2017) 2216022175. Copyright 2017 American Chemical Society.

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Fig. 4.8D. With the same spherical tip, adhesion force maps were first obtained on a control substrate (without hydrogel) (I in Fig. 4.8D) and then on a hydrogel-coated substrate (II in Fig. 4.8D), showing that the adhesion forces on the hydrogel-coated substrate are significantly larger than that on the control substrate. Then the same tip was used to measure the adhesion forces on the control substrate again (III in Fig. 4.8D), showing that the adhesion forces significantly decrease to the level comparable to the adhesion forces obtained in the first measurement of the control substrate. The experimental results show that the effect of hydrogel attachments to the AFM tip was weak. Overall, the results (Fig. 4.8) show that the sundew-inspired hydrogel is sticky with homogeneous adhesion properties in the scaffold regions and nonscaffold regions. Adhesion properties are an important parameter for hydrogels, as adhesive hydrogels facilitate cell adhesion on them. The mucilage secreted by sundew is a natural sticky hydrogel, and sundew uses the mucilage to trap insects. Here, by using two natural polysaccharides (sodium alginate and gum Arabic) to mimic the chemical compositions of sundew mucilage, tunable sticky hydrogels are formed under the Ca21-mediated crosslinking, showing an example of designing hydrogels inspired by natural products and providing a novel idea to prepare adhesive hydrogels for biomedical applications. AFM has also been used to reveal the structural dynamics during the degradation process of sundew-inspired hydrogels, as shown in Fig. 4.9. The degradation kinetics of hydrogels have been commonly studied by measuring the dried weight of degraded hydrogels or utilizing SEM/optical microscopy to image the morphology of degraded hydrogels [3941]. AFM topographical imaging provides an alternative and convenient way to observe the detailed structural dynamics during the degradation process of hydrogels. For doing so, a drop of pure water was added to the hydrogelcoated substrate and then AFM imaging was performed on the different areas of the specimen. From the dynamic optical images (Fig. 4.9AD) of the specimen after the addition of the water drop, we can clearly see that the porous scaffold structures disappeared when they met the water flow. AFM images of three representative areas on the hydrogel were then acquired. The area (I) was the control area, which was not degraded by the water flow, and the AFM image (Fig. 4.9E) shows the thick, porous scaffold structures of this area. The area (II) was the peripheral area of the degraded hydrogel, and the AFM image (Fig. 4.9F) shows that the thick scaffold structures became thin and began to melt (denoted by the arrow in Fig. 4.9F). Besides, many particles are visible on the scaffold structures of a hydrogel. The area (III) was the central area of the degraded hydrogel, and the AFM image (Fig. 4.9G) shows the compact network patches containing small pores which are clearly visible from the higher resolution image (Fig. 4.9H). In order to further observe the structural changes of the hydrogel after

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FIGURE 4.9 Atomic force microscopy (AFM) topographical imaging revealing the structural dynamics during the degradation of the sundew-inspired. The hydrogel (6420) was used for the study. (AD) Successive optical images of the hydrogel-coated substrate after adding a drop of pure water to the specimen. (EG) AFM topographical images of three typical areas (denoted by the squares in D) on the hydrogel. (E) corresponds to the area I, (F) corresponds to the area II, and (G) corresponds to the area III. (H) Higher resolution AFM topographical image (the scan area is denoted by the square in G). (I and J) AFM topographical images of the degraded hydrogel washed by the second drop of pure water. (K and L) AFM topographical image (K) and the corresponding deflection image (L) of the degraded hydrogel washed by the third drop of pure water. AFM images were obtained at contact mode. Source: Reprinted with permission from M. Li, H. Li, X. Li, H. Zhu, Z. Xu, L. Liu, et al., A bioinspired alginate-gum Arabic hydrogel with micro-/nanoscale structures for controlled drug release in chronic wound healing, ACS Appl. Mater. Interfaces 9(27) (2017) 2216022175. Copyright 2017 American Chemical Society.

degradation, the second drop of pure water was added to the degradation area for about 5 s. After removing the water from the substrate, AFM images were obtained (Fig. 4.9I and J), clearly showing the discrete scaffold structures. Fig. 4.9K and L are the AFM images of the degradation area after being washed by the third drop of water, and we can see that at this time scaffold structures disappeared and only nanoparticles (denoted by the circles in Fig. 4.9K) are visible. The AFM imaging results (Fig. 4.9) distinctly reveal the dynamic structural alterations (thick scaffold structures with large pores- . thin and compact network scaffold patches with small pores. discrete scaffold structures-. nanoparticles) of the sundew-inspired hydrogel during the degradation process. In fact, the degradation process is

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the reverse process of the formation of the sundew-inspired hydrogel, and we can see that the final products of the degradation of the sundewinspired hydrogel are the nanoparticles (Fig. 4.9K and L), indicating that nanoparticles are the fundamental elements of the sundewinspired hydrogels, which are similar to sundew mucilage to some extent (after the degradation of sundew mucilage by pure water, nanoparticles are significantly observed by AFM, as shown in Fig. 4.3B). Overall, AFM offers novel possibilities to visualize the nanoscale details involved in the formation and degradation process of hydrogels, which complements traditional methods for characterizing the formation/degradation process of hydrogels and is meaningful for understanding the self-assembly behaviors of hydrogels.

4.4 Imaging and mechanical analysis of peptide-assembled nanofibrillar hydrogel With the use of AFM topographical imaging, the nanoscale structural details during the formation of peptide-assembled nanofibrillar hydrogel can be revealed. Peptide-based hydrogels derived from naturally occurring amino acids offer key advantages because of the role of polypeptides as structural elements in biological systems, such as biocompatibility, biodegradability, extensive ability for their chemical and biological decoration and functionalization, the facile synthesis of natural and modified peptides, and generally being nonimmunogenic [42,43]. Peptide self-assembly is a spontaneous thermodynamic and kinetic-driven process, based on the synergistic effect of various intermolecular noncovalent interactions, including hydrogen-bonding, ππ stacking, electrostatic, hydrophobic, and van der Waals interactions [44]. Various complementary methods have been applied to characterize the self-assembly process of peptide-based hydrogels, which can be roughly classified as imaging (e.g., AFM, SEM, optical microscopy), spectroscopy (e.g., circular dichroism, nuclear magnetic resonance, Fourier transform infrared spectroscopy), and scattering (small-angle neutron scattering, light scattering) [45]. Fig. 4.10 shows utilizing AFM to reveal the diverse self-assembly behaviors of peptide-based hydrogels [46]. The hydrogel was prepared by fluorenyl-9-methoxycarbonyl (Fmoc)-phenylalanine (Phe)-OH. Briefly, Fmoc-Phe-OH powder (Sigma-Aldrich, St. Louis, MO, USA) was firstly added into a fresh tube, after which pure water was also added into the same tube. Subsequently, NaOH solution was added to the tube to promote the full dissolution of Fmoc-Phe-OH. Finally, D-(1)-gluconic acid δ-lactone powder (Sigma-Aldrich, St. Louis, MO, USA) was added into the tube, which allowed the gelation of peptide-based hydrogels for 10 min at room temperature. After coating a substrate with a drop of peptide hydrogels, AFM imaging was performed. AFM images (Fig. 4.10A)

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FIGURE 4.10 Visualizing the individual nanofibrils of peptide-based hydrogels by atomic force microscopy (AFM). (A) AFM topographical images of a substrate coated with different concentrations of peptide-based hydrogel. (I) High concentrations of hydrogel. (II, III) Low concentrations of hydrogel. (B) AFM imaging revealing the diverse assembly behaviors of nanofibrils during the formation of peptide-based hydrogels. (I, II, III) AFM topographical images of the hydrogels. (IV) Transverse section curves of different nanofibrils taken along the lines in I and III. (V) A longitudinal section curve taken along the nanofibril (denoted by the red rectangle in III). (VI) The statistical histogram of the heights of the different types of nanofibrils. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanoscale multiparametric imaging of peptide-assembled nanofibrillar hydrogels by atomic force microscopy, IEEE Trans. Nanotechnol. 18 (2019) 315328. Copyright 2019 IEEE.

distinctly show the nanofibrillar structures of the hydrogel. When a large amount of hydrogel was coated on the substrate, the dense nanofibrillar network structures were observed (I in Fig. 4.10A). When a very small amount of hydrogel was coated on the substrate, single nanofibrils could be clearly imaged (II and III in Fig. 4.10A). In addition, various self-assembly behaviors of nanofibrils are observed from the AFM images (I-III in Fig. 4.10B), including thin nanofibrils (typically denoted by the white arrows), thick nanofibrils (denoted by the blue arrows), merged nanofibrils (denoted by the purple arrows), branched nanofibrils (denoted by the green arrows), paralleled

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nanofibrils (denoted by red arrows), and tangled nanofibrils (denoted by yellow arrows). From the transverse section profile curves (IV in Fig. 4.10B) taken along AFM topographical images, the heights of nanofibrils can be obtained. When the nanofibrils intertwined, the height of the nanofibrils increased (green line). When the nanofibrils paralleled, the height of nanofibrils did not change (blue and red lines). From the longitudinal section profile curve (V in Fig. 4.10B), many peaks are observed, indicating the heterogeneous structures of the nanofibrils. In fact, AFM imaging has revealed the helical substructures of single nanofibrils (Fig. 4.12), which are consistent with the longitudinal section curve. From the histogram of the heights of nanofibrils (VI in Fig. 4.10B), we can see that the height of single discrete nanofibrils was about 4.36 6 0.1 nm. When the discrete nanofibrils were assembled to bundled nanofibrils, the height of nanofibrils significantly increased. AFM has also been used to characterize the rigidity changes of nanofibrils during the formation of peptide-based hydrogels. The mechanics of the network nanofibrils in the peptide-based hydrogels is an important property, particularly when the peptide-based hydrogels are used to mimic the ECM for cell growth [47,48], as cells sense and correspond to the mechanical properties of ECM and these interactions between cells and ECM can influence the fate of cells. The WLC model has been widely utilized to characterize the rigidity of polymer chains [4951]. By applying the WLC model to analyze the AFM images of nanofibrils of peptide-based hydrogels, the rigidity of individual nanofibrils can be obtained, as shown in Fig. 4.11. For the technical details of analyzing AFM images of polymer molecules by WLC model, readers are referred to Chapter 2 which presents obtaining the rigidity of DNA molecules by analyzing AFM images with the WLC model. Briefly, AFM images (II in Fig. 4.11A) of nanofibrils were grayed (III in Fig. 4.11A) and then fitted by a parametric spline (IV in Fig. 4.11A) to obtain the mean-square end-to-end distance ,R2. as a function of the contour length L along the nanofibrils (I in Fig. 4.11A), which was then fitted by the WLC model to obtain the persistence length (a parameter reflecting the rigidity of the polymer chain) of the nanofibrils. WLC-based analysis was utilized to calculate the persistence length of individual discrete nanofibrils (Fig. 4.11B) and bundled nanofibrils (Fig. 4.11C) respectively. In order to obtain statistical results, 89 discrete nanofibrils (typically denoted by the arrows in the I of Fig. 4.11B) and 73 bundled nanofibrils (typically denoted by the rectangles in the I of Fig. 4.11I) were analyzed, showing that the persistence length of bundled nanofibrils (43309 6 11240 nm) was significantly larger than that of discrete nanofibrils (6802 6 2158 nm). The results indicate that the bundled nanofibrils were much more rigid than discrete individual nanofibrils, consistent with the results [52,53] which show the increased persistence length of β-lactoglobulin fibrils when they are bundled together.

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FIGURE 4.11 Measuring the persistence length of nanofibrils in peptide-based hydrogels. (A) Process of extracting the persistence length of nanofibrils from atocmic force microscopy (AFM) images by WLC model. (I) Schematic illustration of analyzing polymer chain rigidity by WLC model. (II) Original AFM image. (III) Grayed AFM image. (IV) The nanofibril is fitted by a finite set of points. (B) Results of single discrete nanofibrils. (C) Results of bundled nanofibrils. (I) AFM images of nanofibrils. (II) Histograms of contour lengths. (III) The calculated persistence lengths. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanoscale multiparametric imaging of peptide-assembled nanofibrillar hydrogels by atomic force microscopy, IEEE Trans. Nanotechnol. 18 (2019) 315328. Copyright 2019 IEEE.

Notably, the study (Fig. 4.11) was performed in the air on a twodimensional surface and thus the results may not fully reflect the real mechanics of nanofibrils in the three-dimensional hydrogels. Developing methods to directly measure the mechanical properties of individual nanofibrils in their native three-dimensional states will be quite meaningful for understanding the mechanical cues involved in cellECM interactions. PFT-based multiparametric AFM imaging allows visualizing the mechanical properties of the substructures of single nanofibrils in peptide-based hydrogels, as shown in Fig. 4.12. Fig. 4.12A shows the PFT multiparametric imaging results of a single nanofibril in which the multiple mechanical maps (e.g., Young’s modulus, adhesion force, and deformation) of the nanofibril were generated simultaneously with the topography of the nanofibril. The height (denoted by H) of the

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FIGURE 4.12 PFT-based multiparametric imaging revealing the substructures and their mechanical properties of nanofibrils. (A, B) Single nanofibrils. (C, D) Crossed nanofibrils. (I) Topographical images, and corresponding (II) Young’s modulus maps, (III) adhesion force maps, and (IV) deformation maps. H denotes the height of the nanofibril and W denotes the length of the blue line taken along the nanofibril. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, Nanoscale multiparametric imaging of peptide-assembled nanofibrillar hydrogels by atomic force microscopy, IEEE Trans. Nanotechnol. 18 (2019) 315328. Copyright 2019 IEEE.

nanofibril was 5.6 nm and the width (denoted by W) was 20 nm. We can see that the helical structures (denoted by the red arrows) of the nanofibril are remarkably discernible from both the topographical image (I in Fig. 4.12A) and adhesion force map (III in Fig. 4.12A), whereas these helical features are not clear from Young’s modulus map (II in Fig. 4.12A) or deformation map (IV in Fig. 4.12A). Nevertheless, the whole nanofibril could be identified from both Young’s modulus map and the deformation map. Fig. 4.12B shows the PFT multiparametric

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images of a thicker nanofibril and we can see that the substructures (denoted by the red arrows) of the nanofibril are distinguishable from the adhesion force map (III in Fig. 4.12B). The results obtained on crossed and paralleled nanofibrils (Fig. 4.12C and D) also clearly show the substructure features along the nanofibrils, which are consistent with the substructures of the nanofibrils. The experimental results (Fig. 4.12) indicate that the changes of the substructures of the nanofibril are accompanied with the changes of the adhesion, which can be visualized by AFM multiparametric imaging, providing novel insights into the self-assembly behaviors of peptides. Researchers have commonly used AFM indentation assay to probe the mechanical properties of peptide-assembled nanostructures and have revealed the relationship between protein material structures and protein material mechanics [54]. PFT-based multiparametric AFM imaging provides direct and visual evidence to the relationship between structures and mechanics of peptide-assembled nanostructures with improved spatial resolution compared with common AFM indentation assay, which will benefit the designing and characterizations of functional biomaterials based on molecular assembly. Notably, the mechanical maps generated in PFT imaging only show the qualitative mechanical properties of the specimens being detected. If one wants to obtain quantitative results of the mechanical properties of nanomaterials which can be compared with others, AFM indentation assay is still critical. For doing this, one needs to obtain force curves on the specimens with known measurement parameters (such as loading rate of probe) and then analyze these force curves to obtain the mechanical properties of the specimens (as shown in Fig. 4.5).

4.5 Probing the mechanical cues in cellhydrogel interactions AFM is now a standard tool to characterize the stiffness of hydrogels for regulating cellular behaviors. Cells sense and respond to tissue organization and mechanics at subcellular, cellular and multicellular scales through interactions between the plasma membrane and the matrix, which causes transient or permanent alterations on both cells and the matrix, and this process is called mechanotransduction [55]. Hydrogels have been widely utilized to fabricate substrates with varying stiffness to grow cells for examining the effects of substrate stiffness on cellular behaviors [20], during which AFM indentation-based measurements of the local stiffness of hydrogel substrates with cellular/subcellular spatial resolution allow a relatively accurate assessment of the mechanical properties of substrates and their correlations with adhesive spreading [56] and directional cell locomotion [57] of a cell. After coating the gel

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on the substrate, Young’s modulus of the gel can be measured by AFM indentation assay, during which force curves are obtained on the specimen and the HertzSneddon model is applied to analyze the force curves to calculate Young’s modulus of the specimen (for more details of AFM indentation assay, readers are referred to Chapter 1). Notably, though conventional pyramid-tipped cantilevers can be used in AFM indentation assay to measure the stiffness of the hydrogel film [56], the porous structures of hydrogels probably cause the penetration of AFM tip into the hydrogel film, which may result in trouble in the interpretation of the obtained force curves. From this point, using the spherical tip which has a well-defined and larger contact area allows exactly and robustly measuring Young’s modulus of hydrogel film [58,59]. For the preparation of sphere-tipped cantilever, readers are referred to Chapter 1 (Fig. 1.5). In 2006, based on the accurate measurements of hydrogel stiffness by AFM, Engler et al. [60] prepared polyacrylamide gels with various stiffness to mimic the different types of tissues, including brain (0.11 kPa), muscle (817 kPa), and collagenous bone (2540 kPa), which were used to grow mesenchymal stem cells (MSCs). The experimental results distinctly show that the matrix stiffness directs the lineage specification of MSCs. In 2013, the same group [61] revealed the molecular mechanisms guiding the substrate stiffness-directed stem cell differentiation, showing that stem cell differentiation into fat on the soft matrix was enhanced by low lamin-A levels, whereas differentiation into the bone on the stiff matrix was enhanced by high lamin-A levels. Based on AFM measurements of the stiffness of hydrogel substrates, researchers have also fabricated stiffness gradient hydrogels [6264] which were used to investigate the morphology, migration, and differentiation of cells as well as the stiffness-dependent drug efficacy on cells, promoting cellular studies and drug screenings on a substrate with comparable stiffness to the native tissue. AFM is also able to probe the mechanics of cells or cellular organoids embedded in three-dimensional hydrogels. The above studies [6064] were performed on cells which were grown on the surface of hydrogels, and thus these results only reflect the regulatory role of substrate stiffness on cellular behaviors in the two-dimensional environment. In the body, cells are likely to receive signals not just at their ventral surface but in all three dimensions [8]. In 2010, Huebsch et al. [65] firstly revealed that the rigidity of three-dimensional microenvironments had significant effects on clonally derived MSC phenotype, showing that osteogenic commitment occurred primarily at intermediate stiffness of microenvironments (1130 kPa) whereas adipogenic lineage predominated in softer (2.55 kPa) microenvironments. Notably, this study [65] was performed with the use of nondegradable alginate hydrogels which were expected to remain constant over the processes of cells. In fact, the cell-matrix interactions in the body are highly reciprocal: cells are

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constantly depositing, breaking down, or remodeling the matrix, while any changes in the matrix as a result of cellular activities in turn influence cellular behaviors [66]. In 2021, Jowett et al. [67] encapsulated human induced pluripotent stem cell (iPSC)-derived organoids (HIO) in degradable three-dimensional hydrogels and utilized AFM to probe the mechanical interplay between complex tissues and rare cell types within controlled three-dimensional microenvironment, as shown in Fig. 4.13. Notably, utilizing AFM to sense the mechanical changes caused by cellmatrix interactions within the three-dimensional hydrogels is an indirect measure of the cells/organoids embedded in the hydrogels

FIGURE 4.13

Sensing the mechanical changes of cellular organoids embedded within three-dimensional (3D) hydrogels by atomic force microscopy (AFM). (A) Schematic illustration of measuring relative stiffness differences between 3D cell structures encapsulated in 3D hydrogels. As the hydrogel is indented, the AFM probe detects the stiffness of a combination of both the hydrogel and the underlying organoid. As the encapsulated organoids remodel their surrounding environment through matrix degradation (I) or ECM production (II), AFM indentation assay can detect these effects as changes in stiffness. (B) Schematic of AFM-based stiffness mapping of HIO (I) and mixture of HIO and aILC1(II) in 3D degradable hydrogels. (C) Optical bright field images (I) and the corresponding AFM stiffness maps (150 μm 3 150 μm) (II) of the HIO-encapsulated hydrogels with or without aILC1. Source: (A) Reprinted with permission from M.D.A. Norman, S.A. Ferreira, G.M. Jowett, L. Bozec, E. Gentleman, Measuring the elastic modulus of soft culture surfaces and threedimensional hydrogels using atomic force microscopy, Nat. Protoc. 16(5) (2021) 24182449. Copyright 2021 Springer Nature. (B and C) Reprinted with permission from G.M. Jowett, M.D.A. Norman, T.T.L. Yu, P.R. Arevalo, D. Hoogland, S.T. Lust, et al., ILC1 drive intestinal epithelial and matrix remodeling, Nat. Mater. 20(2) (2021) 250259. Copyright 2020 Springer Nature.

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(Fig. 4.13A). AFM indentation assay with a spherical probe will cause deformation many microns deep into the hydrogel, and thus the resulting mechanical response will be a combination of the overlying hydrogel, the cells or organoids themselves, and their surrounding matrix, allowing a relative analysis of the matrix changes due to cellular activities [68]. For doing so, HIO was cocultured with ancillary human intestinal lamina propria type-1 innate lymphoid cells (aILC1) in threedimensional hydrogels. The aILC1 is able to not only secrete transforming growth factor β1 to regulate epithelial activities but also produce matrix metalloproteinase (MMP) to degrade the matrix. AFM force volume assay was then applied to detect the stiffness changes of the threedimensional hydrogels containing HIO and aILC1 (II in Fig. 4.13B). For control, hydrogels containing only HIO were also probed (I in Fig. 4.13B). From the optical images (I in Fig. 4.13C), the epithelial layer (IEC) and surrounding fibroblast region (Fb) were discernible. The corresponding AFM stiffness maps (II in Fig. 4.13C) show the increased heterogeneity and significant difference in the variance of stiffness when coculturing HIO with aILC1, indicating a balance between ILC1derived MMP degradation and ILC1-induced mesenchymal ECM deposition accounts for the quantitative difference in AFM stiffness maps. Overall, the studies show the capabilities of AFM in detecting the mechanical cues of subsurface within three-dimensional hydrogels, which benefit investigating the regulatory role of mechanics in life activities in near-in vivo environments.

4.6 Summary As shown in this chapter, AFM has shown extraordinary capabilities in characterizing the nanostructures and properties of hydrogels with unprecedented spatial resolution. AFM is able to resolve the fine structures of the building elements that constitute the hydrogels at diverse conditions (in air, in liquids), which has been utilized to reveal the significant structure differences of natural hydrogels secreted by carnivorous plants in different environments (Figs. 4.3, 4.4, and 4.6), providing direct evidence to the nanoscale structural dynamics during the formation/degradation process of hydrogels (Fig. 4.9). The rigidity of polymer chains can be obtained by analyzing AFM topographical images of the hydrogel nanofibrils (Fig. 4.11). With the use of PFT-based multiparametric AFM imaging, multiple mechanical properties of the hydrogel nanofibrils (Fig. 4.5) and even the substructures on the nanofibrils (Fig. 4.12) can be qualitatively visualized. With conventional AFM indentation assay, the mechanical properties (Young’s modulus, adhesion force) of individual nanofibrils can be quantitatively measured (Figs. 4.5 and 4.8). In addition, with the use of a sphere-tipped probe, not

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only the local stiffness of hydrogel film can be accurately measured for applications of examining the effect of substrate stiffness on cellular behaviors, but also the mechanical dynamics caused by the activities of cells or organoids embedded within three-dimensional hydrogels can be sensed (Fig. 4.13). The established methods can be directly applied to other hydrogel/biological systems, which will have implications for diverse fields including innovative biomaterials, cell biology, tissue engineering and regenerative medicine. On the one hand, AFM provides unique structural and mechanical properties to hydrogels, which significantly complements the results obtained with other methods and will therefore potentially benefit revealing the underlying mechanisms guiding the assembly behaviors of hydrogels. On the other hand, applications of AFM to the studies of cellhydrogel (matrix) interactions promote revealing the mechanical cues involved in the physiological/pathological process of cells and tissues, which will potentially facilitate developing novel methods for the diagnosis and treatment of diseases.

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5 Detecting the behaviors of single viruses by atomic force microscopy A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/9780323953603

5.1 Background Viruses play an important role in the evolution and biodiversity of global ecosystems and can have beneficial properties for treating diseases. Horizontal gene transfer (HGT), also known as lateral gene transfer, refers to the movements of genetic information across normal mating barriers, between more or less distantly related organisms, and thus stands in distinction to the standard vertical transmission of genes from parent to offspring [1]. HGT has long been recognized as a crucial driving force in the evolution of bacteria and archaea. In recent years, accumulating evidence has exhibited the enduring influence of HGT on the evolution and diversity of all parts of the web of life including eukaryotes [2]. Particularly, viruses serve as basic vectors for gene transfers between host cells [3]. Viruses are biological entities that cannot replicate alone; instead, they must infect cells and use the elements of the host cells to replicate themselves [4]. Often, the infected cell will be killed by the massive proliferation of virus particles inside it; but sometimes, the viral DNA, instead of directly generating virus particles, may persist in its host for many cell generations as a relatively innocuous passenger, either as a separate intracellular fragment of DNA, known as a plasmid or as a sequence inserted into the cell’s regular genome [5]. Besides, viruses can accidentally pick up fragments of DNA from the

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genome of one host cell and ferry them into another cell. Numerous studies have shown that such virus-mediated gene transfer is very common in prokaryotes [6]. More recently, in 2022, Irwin et al. [7] have systematically characterized viral-eukaryotic gene exchange across eukaryotic and viral diversity, distinctly demonstrating that viruses participate in eukaryotic transduction and reinforcing the hypothesis of viruses as critical vectors of HGT in eukaryotes [8]. It is worth mentioning that many viruses have specific tissue tropisms that can be exploited as a starting point for preferential infection and replication within the tumor microenvironment to selectively kill cancerous cells without harming noncancerous cells (these viruses are called oncolytic viruses) [9], and this therapeutic strategy is referred to as virotherapy. Both wild-type and engineered viruses have been used to target and deplete cancerous cells, and increasing studies have shown that virotherapy is an emerging and effective tool in anticancer immunotherapy [10,11]. Despite the great contribution of viruses in ecosystems on Earth, some viruses are detrimental or even lethal to human health. Over the past decades until now, we have been witnessing extreme panic and huge damage caused by various notorious viruses to human life, which pose an unprecedented burden to human society in the world. Ebola virus disease (EVD), so far mainly occurring in Middle and Western Africa, is a severe and frequently lethal disease caused by the Ebola virus (the case-fatality rate of EVD is B40%50% overall) and the main symptoms of EVD include fever, gastrointestinal signs and multiple organ dysfunction syndromes [12]. Zika virus (ZIKV) is a mosquitotransmitted flavivirus that has emerged as a global health threat because of ZIKV’s ability to cause congenital defects in fetuses and infants [13]. Although transmission of ZIKV has declined in the Americas since 2016, outbreaks and infection clusters continue to occur in some regions, such as India and Southeast Asia, where there are large populations of women of childbearing age who are susceptible to the virus [14]. Each year, seasonal influenza viruses infect 5%15% of the human population and cause approximately 500,000 deaths worldwide [15]. Right now, people all over the world are suffering from the ongoing outbreak of the coronavirus disease 2019 (COVID-19) which is caused by a new virus called severe acute respiratory syndrome Coronavirus 2 (SARSCoV-2) [16], and more than 6 million people worldwide have died from this virus (according to the data of World Health Organization). The SARS-CoC-2, together with severe acute respiratory syndrome coronavirus (SARS-CoV, responsible for the pandemic of SARS in 200203) and Middle East respiratory syndrome coronavirus (MERS-CoV, responsible for the pandemic of MERS since 2012), are deadly zoonotic pathogens that can replicate in the lower respiratory tract and cause severe pneumonia in humans [17,18]. Viruses are also closely related to the

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development of human cancers, and so far, seven human viruses have been found to account for 10%15% of human cancers worldwide [19], including Epstein-Barr virus (EBV) for Burkitt’s lymphoma, hepatitis B virus (HBV) and hepatitis C virus (HCV) for hepatocellular carcinomas, human T-lymphotropic virus-I (HTLV-I) for adult T cell leukemia, human papillomavirus (HPV) for cervical cancers and penile cancers, Kaposi’s sarcoma herpesvirus (KSHV) for Kaposi’s sarcoma, and Merkel cell polyomavirus (MCV) for Merkel cell carcinoma. In addition, a recent study has shown the hidden associations between viruses and a variety of human chronic diseases (e.g., Parkinson’s disease, obesity, diabetes, hypertension, atherosclerosis, liver cirrhosis, ankylosing spondylitis, and nonalcoholic fatty liver disease) [20], indicating that viruses may be ubiquitously involved in human diseases. The structures and entry behaviors of viruses are illustrated in Fig. 5.1. Viruses can come in nearly all shapes. Besides the commonly sphereshaped viruses, viruses with other shapes have been identified, including the starfish-shaped giant mimivirus, the lunar-lander-shaped bacteriophage, the filamentous Ebola virus, the rod-shaped tobacco rattle virus, the Acidianus bottle-shaped virus, and so on [21]. Nevertheless, all viruses have two substructures in common: nucleic acid genomes (either RNA or DNA, but not both), and a protein coat (called capsid) encasing the genetic materials. In some viruses, the capsid is covered with another lipid membrane (called envelope) which is generally taken from host cells [22], and this category of the virus is called enveloped viruses. Viruses which do not have the outer lipid membrane are therefore called nonenveloped viruses. Fig. 5.1A shows the structure of a nonenveloped virus called rotavirus, which causes gastroenteritis, particularly for children younger than 5 years of age [23,24]. Fig. 5.1B shows the structure of SARS-CoV-2, which is an enveloped virus [2527]. Generally, the multiplication and propagation of viruses is a cyclic process: an infectious viral particle (called virion) introduces its genome into a host cell, and then new virions are formed in the cell and released, and these virions in turn may infect other host cells [28]. This cycle of viral infection is often called the virus life cycle. During the process of infecting cells, viruses firstly attach to the cellsurface receptors, and then deliver the viral genome into the cell via two main entry routes, including endocytosis and membrane fusion [29], as shown in Fig. 5.1C. For the route of endocytosis, both pinocytosis and phagocytosis can be exploited by viruses to enter cells and in some cases, a virus can use more than one pathway [30]. Membrane fusion is a basic mode of entering cells by enveloped viruses, during which a ligand-triggered, large-scale conformational change in the fusion protein is coupled to the apposition and merger of the two membranes [31]. It is undoubted that investigating the details of viral structures, properties, and behaviors at the single-virus level is of remarkable significance

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FIGURE 5.1 Structures and behaviors of viruses. (A) Rotavirus, a type of nonenveloped virus. (I) Schematic representation of a rotavirus virion. There are six rotavirus structural proteins, which form three concentric layers. The internal layer, which encases the viral genomes, is composed of the scaffolding protein VP2, the RNA-dependent RNA polymerase VP1, and the guanylyltransferase and methyltransferaseVP3. The intermediate layer is made of VP6, which is the major structural protein of rotavirus. The external layer is made up of VP7 (a glycoprotein) and is decorated with VP4 (a spike glycoprotein). (II) A Cryo-EM image of rotavirus. (B) SARS-CoV-2, a type of enveloped virus. (I) Schematic representation of SARS-CoV-2 structure. Only four viral proteins-the spike (S), envelope (E), membrane (M) and nucleocapsid (N) proteins are incorporated into the virion. While the N protein bound to the viral genomic RNA is packed inside the virion, the structural proteins S, E and M are incorporated in the virion membrane. (II) A Cryo-EM image of a SARS-CoV-2. (III) Life cycle of SARS-CoV-2. SARS-CoV-2 firstly attaches to the host cell through binding of the S protein to the angiotensin-converting enzyme 2 (ACE2) receptor, allowing it to enter the cell and release its viral RNA. In the cell, the virus hijacks the machinery of the host cell to synthesize RNA and produce structural proteins, which are used to assemble new viruses that are released from the host cell. (C) Two main virus entry pathways. (I) Endocytosis. (II) Membrane fusion. Sources: (A) (I) Reprinted with permission from J. Angel, M.A. Franco, H.B. Greenberg, Rotavirus vaccines: recent developments and future considerations, Nat. Rev. Microbiol. 5(7) (2007) 529539. Copyright 2007 Springer Nature. (II) Reprinted with permission from S.L. Greig, J.A. Berriman, J.A. O’Brien, J.A. Taylor, A.R. Bellamy, M.J. Yeager, et al., Structural determinants of rotavirus subgroup specificity mapped by cryo-electron microscopy, J. Mol. Biol. 356(1) (2006) 209221. Copyright 2005 Elsevier Ltd. (B) (I) Reprinted with permission from C.B. Jackson, M. Farzan, B. Chen, H. Choe, Mechanisms of SARS-CoV-2 entry into cells, Nat. Rev. Mol. Cell Biol. 23(1) (2022) 320. Copyright 2022 Springer Nature. (II) Reprinted with permission from Z. Ke, J. Oton, K. Qu, M. Cortese, V. Zila, L. McKeane, et al., Structures and distributions of SARS-CoV-2 spike proteins on intact virions, Nature 588(7838) (2020) 498502. Copyright 2020 Springer Nature. (III) Reprinted with permission from Z. Tang, N. Kong, X. Zhang, Y. Liu, P. Hu, S. Mou, et al., A materials-science perspective on tackling COVID-19, Nat. Rev. Mater. 5(11) (2020) 847860. Copyright 2020 Springer Nature. (C) Reprinted with permission from D.S. Dimitrov, Virus entry: molecular mechanisms and biomedical applications, Nat. Rev. Microbiol. 2(2) (2004) 109122. Copyright 2004 Springer Nature.

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for revealing the underlying mechanisms guiding viral infections, and AFM offers novel possibilities for the studies of individual viruses. CryoEM has been one of the main tools for imaging the structures of viruses, as shown in the II of Fig. 5.1A and B. Compared with cryo-EM, AFM has unique advantages. AFM is able to not only visualize the fine structures of single viruses directly under aqueous conditions, but also measure the mechanical properties of single viruses, which significantly promotes understanding of virus particles from the perspective of physical virology [28,32]. Applications of AFM in the characterizations of viruses have yielded numerous new insights into the activities of viruses, which are presented in the remaining of the chapter.

5.2 Imaging the fine structures of single viruses AFM has been broadly used to visualize the detailed structures of single viruses and their dynamics. The prerequisite of utilizing AFM to image viruses is immobilizing viruses onto the stiff substrate. At neutral pH, most viral particles have a net negative charge because they have an isoelectric point below 7 [33], therefore attaching viruses to poly-Llysine-coated substrate has been a commonly used immobilization method for AFM studies [34]. The pioneering studies of utilizing AFM to visualize viruses were performed on the crystalline form of viruses, in which viruses were immobilized on the surface of crystals and therefore were suitable for AFM imaging [35]. In 1995, Malkin et al. [36] firstly imaged the morphological dynamics in the crystal growth of satellite tobacco mosaic virus (STMV) by AFM. The viral crystals were grown on etched silica substrates and the final crystal sizes were in the range of 3050 μm. Individual virus monomers with center-to-center distances of 18 nm were distinctly visualized from the AFM topographical images acquired on the surface of viral crystals. In 2001, Lucas et al. [37] acquired the AFM topographical images of the crystals formed by brome mosaic virus (BMV) in solution, clearly revealing the organization of capsomeres on the surfaces of the BMV particles (I in Fig. 5.2A). Besides, the formation of T 5 1 BMV particles derived from native T 5 3 BMV particles was evidently observed by time-lapse AFM imaging. After the addition of CaCl2, AFM images clearly show the viral particles with decreased diameters, and substantial accumulations of materials were observed in the neighboring area of the particles on the substrate, indicating the transition of viral particles. Besides the viral crystals, AFM has been used to image the fine structures of individual isolated viruses. In 2004, Kuznetsov et al. [38] imaged the Moloney murine leukemia virus (M-MuLV) particles that emerged from the surface of productively infected NIH 3T3 cells by AFM, and AFM topographical

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FIGURE 5.2 AFM topographical imaging revealing the fine structures and their dynamics of single virions. (A) Nanostructures of single virions imaged by AFM. (I) BMV (T 5 3) crystals. (II) M-PMV virions. (III) Mimivirus. (IV) HSV-1 virions. (B) Structural changes of single SARS-CoV-2virions. (I) An AFM topographical image of native infectious SARS-CoV-2virions. (IIV) AFM images of infectious virions from control group (II), virions treated by 1% FA for 30 min at 20 C (III), treated by 2% FA for 30 min at 20 C (IV), or incubated at 58 C for 30 min (V). Sources: (A) (I) Reprinted with permission from R.W. Lucas, Y.G. Kuznetsov, S.B. Larson, A. McPherson, Crystallization of brome mosaic virus and T 5 1 brome mosaic virus particles following a structural transition, Virology 286(2) (2001) 290303. Copyright 2001 Academic Press. (II) Reprinted with permission from Y.G. Kuznetsov, P. Ulbrich, S. Haubova, T. Ruml, A. McPherson, Atomic force microscopy investigation of Mason-Pfizer monkey virus and human immunodeficiency virus type 1 reassembled particles, Virology 360(2) (2007) 434446. Copyright 2006 Elsevier Inc. (III) Reprinted with permission from C. Xiao, Y.G. Kuznetsov, S. Sun, S.L. Hafenstein, V.A. Kostyuchenko, P.R. Chipman, et al., Structural studies of the giant mimivirus, PLoS Biol. 7(4) (2009) e1000092. Copyright 2009 The Authors. (IV) Reprinted with permission from U. Sae-Ueng, D. Li, X. Zuo, J.B. Huffman, F.L. Homa, D. Rau, et al., Solid-to-fluid DNA transition inside HSV-1 capsid close to the temperature of infection, Nat. Chem. Biol. 10(10) (2014) 861867. Copyright 2014 Nature America, Inc. (B) Reprinted with permission from S. Lyonnais, M. Henaut, A. Neyret, P. Merida, C. Cazevieille, N. Gros, et al., Atomic force microscopy analysis of native infectious and inactivated SARS-CoV-2 virions, Sci. Rep. 11(1) (2021) 11885. Copyright 2021 The Authors.

images clearly show the dense arrangements of protein “tufts” whose size was about 1112 nm on the surface of the viruses. In 2007, the same group [39] obtained the fine structures of a single MasonPfizer monkey virus (M-PMV) by AFM (II in Fig. 5.2A). AFM images show that the surface of M-PMV is an assembly of lattice domains composed of protein units which form a regular array of rings with large central holes and the results of length measurements indicate that the center-tocenter distance of the holes is about 8.7 nm. Notably, viruses were chemically fixed by glutaraldehyde in these studies [38,39]. Chemical

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fixation hardens the substructures of viruses and therefore facilitates AFM imaging with higher spatial resolution, but chemical fixation may also cause structural changes in the viruses. In 2009, Xiao et al. [40] investigated the surface structures of single Mimiviruses in their native states without chemical fixation (III in Fig. 5.2A). Mimivirus particles were immobilized onto freshly cleaved mica which was coated with poly-L-lysine, and then AFM images were obtained in a buffer solution. The starfish-shaped feature of the surface of Mimivirus is remarkably discernible from the obtained AFM images. Besides, AFM images of Mimivirus particles missing the starfish-shaped feature clearly show the ejected DNA molecules, indicating that the starfish-shaped feature might be acting as a seal to hold together the five faces associated with the special vertex. In 2014, Sae-Ueng et al. [41] investigated the human Herpes simplex virus type 1 (HSV-1) capsid by AFM (IV in Fig. 5.2A), and individual hexon structures are clearly shown from the obtained AFM topographical images of HSV-1 particles (denoted by the dashed outline). In 2021, Lyonnais et al. [42] used AFM to investigate the structures of native infectious and inactivated SARS-CoV-2 virions (Fig. 5.2B). For doing so, AFM was placed in a level 3 biosafety (BSL3) facility. Virions were attached to the substrate which was coated with poly-L-lysine in advance, and AFM experiments were performed at room temperature in a buffer solution. AFM topographical images distinctly show the spherical or ellipsoidal shapes of the infectious SARSCoV-2 virions (I in Fig. 5.2B). Based on AFM imaging, the effects of formaldehyde (FA) fixation and heat on the inactivation of virions were examined, clearly showing the disrupted shapes of virions treated by 2% FA (IV in Fig. 5.2B) or heating (V in Fig. 5.2B). Besides the protein shells, AFM is also able to probe the encapsulated genome of single virions by mechanically disrupting the protein shells [43]. In 2015, Ortega-Esteban et al. [44] combined AFM with fluorescence microscopy to investigate the genome inside single viruses, as shown in Fig. 5.3A. Human adenovirus was used in this study. The viral genome is protected and condensed as a core within the capsid. During the disassembly process of the adenovirus, the capsid pentons are firstly released, after which the capsid breaks and the viral genome is released into the cell (I in Fig. 5.3A). AFM is used to mechanically induce the dynamic disassembly of single viruses. For doing so, adenovirus particles were attached to the substrate and imaged by AFM in a buffer solution. In order to monitor the genome released by a single virion, the DNA-specific intercalating fluorescent dye, YOYO-1, was also added to the buffer solution. The fluorescent dye could not access the viral DNA of intact virions but could stain the viral DNA of disrupted virions. Individual virions were repeatedly imaged by AFM with a scan force below the capsid rupture force, which is called the

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FIGURE 5.3 Detecting the genomes inside single viruses by atomic force microscopy (AFM). (A) Release of internal genomes from single virions induced by AFM mechanical touching. (I) Schematic illustration of the disassembly process of single viruses. (II) Successive AFM images of a virion. (III) The same images in (I) and structural changes of the virion are denoted. (IV) The corresponding fluorescence images. (B) Imaging single genomes of viruses by AFM. (I) Spherical shape RNA molecules. (II) Extended RNA molecules. Sources: (A) Reprinted with permission from A. Ortega-Esteban, K. Bodensiek, C.S. Martin, M. Suomalainen, U.F. Greber, P.J. de Pablo, et al., Fluorescence tracking of genome release during mechanical unpacking of single viruses, ACS Nano 9(11) (2015) 1057110579. Copyright 2015 American Chemical Society. (B) Reprinted with permission from Y.G. Kuznetsov, S. Daijogo, J. Zhou, B.L. Semler, A. McPherson, Atomic force microscopy analysis of icosahedral virus RNA, J. Mol. Biol. 347(1) (2005) 4152. Copyright 2005 Elsevier Ltd.

mechanical fatigue experiment [45]. From the successive AFM topographical images, the slow disassembly process of single virions could be distinctly observed (II and III in Fig. 5.3A). In the initial stage, AFM images show intact viral morphology, and no fluorescence was observed at this time (IV in Fig. 5.3A). When the pentons were lost (in frame 7), a fluorescent spot appeared. Subsequently, as the gradual disassembly of the virion, the fluorescence became increasingly evident. With the use of AFM topographical imaging, the viral genomes could be clearly visualized. Essentially, utilizing AFM to image viral genomes (DNA/RNA) is the same as that of imaging DNA molecules by AFM which has been presented in Chapter 2 (readers are referred to Chapter 2 for details of detecting DNA molecules by AFM). Fig. 5.3B

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shows the AFM topographical images of individual RNA molecules from poliovirus [46]. For doing so, RNA molecules were firstly extracted from poliovirus, and then the RNA specimens were attached to mica which was pretreated by chemical functionalization for adsorption of RNA molecules onto the substrate. AFM images clearly show the spherical shape of the condensed RNA molecules whose diameters were about 30 nm (I in Fig. 5.3B). The diameter was approximately equal to the inside diameter of the poliovirus capsid. After heating the RNA specimens at 26 C for 30 min or at 65 C for one minute, the compact spheres of condensed RNA molecules transformed into extended chains (II in Fig. 5.3B). Particularly, individual unwound RNA molecules are clearly discernible from the AFM images (denoted by the arrow in Fig. 5.3B). These studies vividly show the excellent capabilities of AFM in mechanically disrupting single virions to release viral genomes and imaging the fine structures of individual genetic molecules in their different states (condensed, relaxed), which significantly benefits investigating viral genomes with unprecedented spatial resolution.

5.3 Nanoindentation for mechanical measurements and manipulations of single viruses The mechanical properties of single viruses can be measured by applying an AFM indentation assay. Viral mechanics plays an important role in regulating viral activities. Intuitively, the viruses should be sufficiently stable to protect their highly stressed genomes inside the extracellular environment (e.g., viruses are known to tolerate wide ranges of pH and salt conditions and to withstand internal pressures as high as 100 atmospheres without rupture [47]), but also be sufficiently unstable that the genomes can be released into the host cells [32]. In fact, the mechanical properties of viruses have been shown to extensively participate in the activities of viruses (e.g., traffic of viral genome, viral entry into host cells, and viral uncoating), and viral mechanics are tuned by the host cells during the replication of viruses [48]. It is therefore of remarkable significance to probe the mechanical properties of viral capsids to examine how their strength depends on the capsid structure [49] and reveal their mechanical stability in response to external stimuli. By controlling the AFM tip to perform an approach-retract cycle on single viruses in the vertical direction (the so-called indentation assay, as schematically illustrated in Fig. 5.4A), the mechanical properties of the virus can be obtained. For more descriptions of AFM-based indentation assay, readers are referred to Chapter 1. Notably, there are subtle differences between the AFM single-cell indentation assay and AFM single-virus indentation assay in the navigation of moving the

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FIGURE 5.4 Atomic force microscopy (AFM) single-virus nanoindentation assay for characterizing viral mechanical properties. (A) Schematic representation of AFM nanoindentation on single viruses. (B) Disassembly of individual TrV particles after indentation. (I and II) Before indentation. (III and IV) After indentation. (I and III) AFM topographical images. (II and IV) Section profile curves taken along the line of the white arrowheads. (C) AFM images of a HSV1 particle before (I) and after (II) indentation. The insets show the section profile curves along the dashed lines. Sources: (A and B) Reprinted with permission from J. Snijder, C. Uetrecht, R.J. Rose, R. Sanchez-Eugenia, G.A. Marti, J. Agirre, et al., Probing the biophysical interplay between a viral genome and its capsid, Nat. Chem. 5(6) (2013) 502509. Copyright 2013 Macmillan Publishers Limited. (C) Reprinted with permission from U. Sae-Ueng, D. Li, X. Zuo, J.B. Huffman, F.L. Homa, D. Rau, et al., Solid-to-fluid DNA transition inside HSV-1 capsid close to the temperature of infection, Nat. Chem. Biol. 10(10) (2014) 861867. Copyright 2014 Nature America, Inc.

AFM tip to the target specimen. When applying AFM indentation assay to probe the mechanical properties of cells, the AFM tip can be easily moved to the target cell under the guidance of optical microscopy. However, since viruses are often invisible from optical microscopy

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images, the AFM tip is moved to the surface of the target virus under the guidance of AFM topographical imaging. After visualized viruses immobilized on the substrate by AFM topographical imaging, the AFM tip can then be moved to the surface of the virus via the interface of AFM manipulation software and then the AFM tip is controlled to vertically approach and indent the virus. In the approach stage, there is zero force with vertical displacement until the AFM tip contacts the virus. As the tip compresses the virus, there is a linear increase in the force [50] from which the elastic properties of the virus (e.g., Young’s modulus [51]) can be obtained. A higher load results in the mechanical failure of the virus, which can be identified from a sharp transition in the force curve and this force is referred to as the breaking force. Sometimes mechanical failure results in the disassembly of the capsid (Fig. 5.4B), while sometimes mechanical failure results in an evident hole in the capsid (Fig. 5.4C) [41,52]. With the utilization of a single-virus AFM indentation assay, the effects of capsid protein mutations, capsid maturation and environmental changes on the viral mechanical properties have been revealed [53]. In 2006, Michel et al. [49] examined the effects of capsid protein mutations on the elasticity and strength of cowpea chlorotic mottle virus (CCMV) by AFM, showing that full capsids were more resistant to indentation than empty capsids and a single point mutation in the capsid protein could cause the changes of the capsid stiffness. Also in 2006, Kol et al. [54] measured the mechanical properties of live mature and immature murine leukemia virus particles by AFM and the experimental results show that the viral shell was twofold stiffer in the immature than the mature form. In 2013, Snijder et al. [50] characterized the effects of pH on viral mechanics, showing that increasing pH could cause the decrease of the spring constant of the picornalike Triatoma virus (TrV) virions but the breaking force was maintained. In 2014, Sae-Ueng et al. [41] examined the effects of ionic conditions on the mechanics of HSV-1 particles, showing that no differences in spring constant were observed for A-, B-, and C-capsids in high-salt buffer, whereas the spring constant of C-capsids was much larger compared to that of A-capsids in low-salt buffer. More recently, in 2022, DominguezZotes et al. [55] showed that the binding of compounds to the viral capsid could cause changes in viral mechanics which were associated with the biochemical activities of viruses. Also in 2022, Evilevitch et al. [56] revealed that viral DNA ejection could cause mechanical transformations of the cell nucleus, which disrupted the integrity of the cell nucleus and facilitated viral replication. These studies provide new insights into physical virology, which are meaningful for elucidating the role of mechanical cues in the viral life cycle as well as the design of antiviral drugs [57].

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AFM indentation-based mechanical manipulations allow the detection of the intermediates during the process of the viral life cycle. Viral capsids are often regarded as inert structural units, but in actuality, they display fascinating and complex dynamics during different stages of their life cycle [58]. Capsid disassembly is a crucial step during viral infection, but the dynamic and transient nature of the disassembly process makes it challenging to isolate intermediates in a temporal, stepwise manner for structural characterization for a long time [59,60]. With the use of AFM, the substructures of single virions can be controllably manipulated. In 2009, Roos et al. [61] combined AFM topographical imaging and nanoindentation to investigate the HSV-1 particles. AFM topographical images of the target virion were recorded before and after indentation. The results clearly show that the capsomeres on the capsid could be displaced or removed after the manipulation of indentation. In 2012, Castellanos et al. [62] used AFM to remove individual capsomers from the minute virus of mice (MVM), as shown in Fig. 5.5. For doing so, individual virions adsorbed on the substrate were firstly located by AFM topographical imaging. Subsequently, a series of high-force (about 1 nN) indentations were performed on the particle. After indentations,

FIGURE 5.5 Mechanically removing a single capsomere from the viral capsid by atomic force microscopy (AFM). Each panel (AD) shows results obtained with a different virion, including AFM three-dimensional topographical images (left), negative images (center) of the same virion before (upper) and after (lower) removal of a single capsomere, and section profile curves (right) taken along the lines indicated in the negative images. Source: Reprinted with permission from M. Castellanos, R. Perez, P.J.P. Carrillo, P.J. de Pablo, M. G. Mateu, Mechanical disassembly of single virus particles reveals kinetic intermediates predicted by theory, Biophys. J. 102(11) (2012) 26152624. Copyright 2012 The Biophysical Society.

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AFM images of the particle were obtained again to confirm whether the capsomeres had been removed. During indentation, the loss of a single capsomere will cause an abrupt force peak in the force curve, whereas the loss of multiple capsomeres will result in multiple force peaks in the force curve. The experimental results (Fig. 5.5) distinctly show that individual specific capsomeres could be mechanically removed from the capsid, leaving a gap at the position it had originally occupied. Not only single capsomere can be exactly removed from the capsid, but also a pentamer of capsomeres can be removed by altering the indentation parameters (e.g., loading force, indentation depth). Particularly, the intermediates revealed by AFM (capsids missing one capsomere, capsids missing one pentamer of capsomere, and free pentamers of capsomeres) were consistent with the results of theoretical prediction [62]. Besides, AFM indentation is able to even induce the collapse of the viral capsid and the subsequent release of the viral genomes [44,50,63], which can be used to investigate the intermediates of the viral life cycle. Overall, AFM indentation-based single-virus mechanical manipulation offers experimental access to the studies of viral dynamics, which will benefit unveiling the underlying mechanisms guiding viral activities.

5.4 Single-virus force spectroscopy for probing viral binding affinity AFM-based single-virus force spectroscopy allows quantitatively measuring the binding affinities of individual viruses. During the life cycle of viruses, the first step is the binding of proteins on the viral surface to the receptors on the host cell, which are responsible for the attachment of the virus to the host cell and the subsequent entry of the virus into the cell [64]. Therefore, the binding affinity between the virus and the host cell is crucial for the viral life cycle, as it determines the accessibility of viruses to host cells [65]. In fact, studies have shown that viral mutations that enhance the binding affinity of the virus to the host cells often promote the entry efficiency of viruses [66]. Consequently, utilizing the AFM force spectroscopy technique to directly measure the binding affinity of a single virus is of great significance for understanding viral behaviors. In 2008, Rankl et al. [67] characterized the binding forces between human rhinovirus (HRV) and their receptor proteins at the single-molecule level by AFM, providing a template for the studies of virus binding affinity, as shown in Fig. 5.6. For doing so, viruses were attached to the tip surface of the AFM probe via a heterobifunctional cross-linker called aldehyde-PEG-NHS (I in Fig. 5.6A). AFM imaging of the virus-functionalized probe distinctly shows the dense packing of virus particles on the cantilever and the diameters of virus

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FIGURE 5.6 Atomic force microscopy (AFM) single-virus force spectroscopy. (A) Linking virus particles to the surface of AFM tip and tethering receptor proteins to the surface of mica. (I) Schematic representation of AFM tip functionalization and substrate preparation. (II) The virus-functionalized cantilever was imaged by AFM. (III) AFM image with higher resolution. (B) Experimental results. (I) A typical force curve showing the specific unbinding of a single virus-receptor bond. The inset is the force curve after inactivating the receptor proteins. (II) A force curve showing the serial rupture of two receptors bound to the virus. (III) Force curves showing simultaneous unbinding of single (red), double (green), triple (blue), and quadruple (cyan) bonds. (IV) Dynamic force spectra of single (solid squares), double (empty squares), and triple (solid circles) bonds. Source: Reprinted with permission from C. Rankl, F. Kienberger, L. Wildling, J. Wruss, H.J. Gruber, D. Blaas, et al., Multiple receptors involved in human rhinovirus attachment to live cells, Proc. Natl. Acad. Sci. U. S. A. 105(46) (2008) 1777817783. Copyright 2008 National Academy of Sciences.

particles were about 30 nm (II and III in Fig. 5.6A). The functionalized probe carrying viruses was then used to perform force spectroscopy experiments on the substrate (the substrate was coated by receptor proteins of host cells in advance) to obtain force curves. The interactions between virus and receptor molecules can then be identified from the force curves. Readers are referred to Chapter 1 for detailed descriptions of AFM-based force spectroscopy techniques. The experimental results show that in most cases single virusreceptor unbinding events were observed (I in Fig. 5.6B), but occasionally rupture events of the bonds between one virus particle and multiple receptor proteins were observed (III in Fig. 5.6B). Also, in rare cases (,10%) the sequential unbinding of receptorvirus bonds was observed (II in Fig. 5.6B). The specificity of the binding events was confirmed by blocking experiments, after which the specific nonlinear force peaks disappeared from the force curves, as shown in the inset of Fig. 5.6B(I). By obtaining force curves at different pulling velocities of the AFM probe to perform dynamic force spectroscopy, the linear relationship between the measured virusreceptor rupture force and the logarithm of the loading

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rate was observed (IV in Fig. 5.6B), which could be used to calculate the energetic and kinetic parameters of the virusreceptor bond. Applications of AFM single-virus force spectroscopy technique in virus-related studies improve our understanding of viral activities. In 2012, Sieben et al. [68] used AFM to investigate the binding interactions between influenza A viruses and their host cells. Two types of influenza A viruses (H3N2 and H1N1) and three types of cell lines (CHO, MDCK, and A549 cells) were used. Virions were covalently attached to the surface of the AFM tip via a PEG linker, and then the functionalized probes were controlled to lower and touch the living cells to detect the unbinding forces. The results show that the unbinding forces between influenza A viruses and host cells were about 1025 pN. In addition, though CHO, MDCK, and A549 cells had different subtypes of receptors for the binding of influenza A virions, no preference for viral binding for one of the three cell lines was observed. Particularly, optical tweezers were also used to measure the unbinding forces between influenza A viruses and host cells, and the results obtained by optical tweezers were consistent with that obtained by AFM, confirming the accuracy of viral unbinding forces measured by AFM. In 2019, Dragovich et al. [69] investigated the binding interactions of Ebola viruses. T-cell immunoglobulin and mucin domain (TIM) family proteins, which are the receptors of the Ebola virus, were immobilized on the substrate. Ebola viruses were tethered to the AFM tip. The results show that the unbinding forces between TIM and Ebola viruses were 40100 pN depending on the loading rates. In 2022, Zhang et al. [70] also applied AFM force spectroscopy to detect the binding interactions of the Ebola virus. The results show that, besides TIM, Ebola viruses could also specifically bind to the C-type lectin dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin receptor (DC-SIGNR). A two-step entry mechanism for the Ebola virus was presented and the dual role of TIM during the entry was found based on the results of AFM. First, the binding of Ebola virions to TIM and DC-SIGNR serves as the initial high-affinity attachment before entry into cells. Second, the TIM specifically binds to the phosphatidylserine on the viral shell to promote membrane fusion. In 2021, Cao et al. [71] probed and compared the binding affinity of SARS-CoV-2/SARS-CoV-1 virions by AFM. The receptorbinding domain (RBD) on the viral surface was attached to the AFM tip, and the angiotensin-converting enzyme 2 (ACE2) receptor was immobilized on the substrate. The results distinctly show that the unbinding forces between SARS-CoV-2 RBD and ACE2 were 70105 pN depending on the loading rates and were 30%40% higher than those of SARS-CoV-1 RBD and ACE2 under similar loading rates, indicating that the binding affinity of viruses to host cells is an important parameter for the infection of viruses. In 2021, Collett et al. [72]

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used the AFM force spectroscopy technique to investigate the binding interactions between virus particles and their receptors in threedimensional cell culture system, which is meaningful for understanding viral behaviors in near-in vivo conditions.

5.5 Multiparametric atomic force microscopy imaging of viruscell interactions PFT-based multiparametric AFM imaging allows visually locating individual virions on the surface of infected cells while simultaneously characterizing the mechanical alterations of the cell infected by the virions, which benefits comprehensively understanding the viral infection interactions at single-virus and single-cell levels. In 2013, Alsteens et al. [73] firstly applied multiparametric AFM imaging to investigate mechanical cues involved in the extrusion of individual bacteriophages from the surface of living bacteria (E. coli), as shown in Fig. 5.7A. For doing so, the bacteriophages were genetically engineered to express His-tags on their tails, and AFM tips were tethered with Ni21-NTA groups (I in Fig. 5.7A). The Ni21-NTA group can specifically bind to the His-tag, which thus allows the AFM tip to specifically bind to the bacteriophages exposed on the surface of bacteria when performing approach-retract cycles during PFT scanning. The stretching of the His-Ni21-NTA bond during the retract process will cause a specific peak in the force curve, and the magnitude of the force peak corresponds to the adhesion force values in the subsequently generated adhesion force map. The bacteriophages can then be identified from the adhesion force map. Readers are referred to Chapter 1 for more descriptions of multiparametric AFM imaging. Using the functionalized probe to scan the surface of single bacteria infected by bacteriophages at multiparametric imaging mode, adhesion force (IV and VI in Fig. 5.7A) and Young’s modulus (V and VII in Fig. 5.7A) maps were obtained simultaneously with the cellular topography (III in Fig. 5.7A). The bright pixels in the adhesion force map correspond to the bacteriophages (IV and VI in Fig. 5.7A). For control, no adhesion events were observed from the adhesion force maps for the noninfected bacteria scanned by the functionalized probe. Besides, no adhesion events were observed after blocking the biochemical specificity of the functionalized probe, confirming that adhesion spots in the adhesion force maps were indeed bacteriophage particles. The results reveal that most adhesion events (bacteriophages) were not randomly distributed but organized into nanodomains located near the septum and the poles of bacteria, indicating the heterogeneous distributions of bacteriophages on the infected cell. Besides, bacteriophages were preferentially detected in soft regions of the bacteria (denoted by the dashed outlines in V and VII in Fig. 5.7A),

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FIGURE 5.7 Imaging viruscell interactions by multiparametric atomic force microscopy (AFM) imaging with functionalized tips. (A) Single bacteriophages extruding from living bacteria. (I) Schematic illustration of detecting single bacteriophages on the surface of bacteria by using biochemically sensitive AFM tips. (II) Low- and (III) high-resolution AFM topographical images of E. coli cells infected by bacteriophages obtained in PBS using functionalized tips. (IV and VI) Adhesion force maps and corresponding (V and VII) Young’s modulus maps of the local areas on infected E. coli cells. (B) Interactions between SARS-CoV-2 RBD and ACE2 receptor. (I) Schematic illustration showing probing the ACE2 on A549 cells by using AFM tips carrying RBD of SARS-CoV-2. Multiparametric imaging results before (II, IV, and VI) and after (III, V, and VII) blocking the RBD on the AFM tip. (II and III) Overlay of fluorescence and optical bright field images. (IV and V) AFM topographical images and (VI and VII) corresponding adhesion force maps recorded in the specified areas in (II and III) denoted by dashed squares. Sources: (A) Reprinted with permission from D. Alsteens, H. Trabelsi, P. Soumillion, Y.F. Dufrene, Multiparametric atomic force microscopy imaging of single bacteriophages extruding from living bacteria, Nat. Commun. 4 (2013) 2926. Copyright 2013 Macmillan Publishers Limited. (B) Reprinted with permission from J. Yang, S.J.L. Petitjean, M. Koehler, Q. Zhang, A.C. Dumitru, W. Chen, et al., Molecular interaction and inhibition of SARS-CoV-2 binding to the ACE2 receptor, Nat. Commun. 11(1) (2020) 4541. Copyright 2020 The Authors.

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showing the correlation between bacteriophage extrusion and bacterial mechanics and facilitating understanding of viral infection from the perspective of mechanics. In recent years, multiparametric AFM imaging has been widely used to detect the interactions between viruses and host cells by using the AFM probe conjugated with virions or viral binding proteins. In 2017, Alsteens et al. [74] combined multiparametric AFM with confocal microscopy to quantify the first viral binding events in animal cells. The rabies virus (RABV) particles were tethered to the surface of the AFM tip via PEG linker. The MDCK cells were engineered to express tumor virus receptor A (TVA) which was the receptor protein of RABV. MDCK-TVA cells were then labeled with fluorescein and co-cultured with wild-type MDCK cells. A trick is that, under the guidance of fluorescence, areas in which both cell types (wild-type MDCK cells and MDCK-TVA cells) were in contact with each another were used. Both cell types were then imaged by the AFM probe carrying virus particles in one AFM image at multiparametric mode, allowing a direct control to evaluate the specific viruscell interactions and unspecific molecular interactions. The experimental results distinctly show numerous adhesion events on MDCK-TVA cells while the adhesion events were rarely observed on wild-type MDCK cells, confirming the specificity of the measured viruscell interactions. By analyzing the force curves recorded at different loading rates during multiparametric AFM imaging, the energetic and kinetic parameters of the virus-cell bond were then extracted, showing that the first bond formed during viral initial attachment had a relatively low lifetime and free energy, but this increased as additional bonds formed rapidly (#1 ms). With this method, the interactions between herpesvirus and living cells were investigated [75], and the results show that the major envelope glycoprotein on the virus functions as a regulator of binding valency during both attachment and release steps. These studies [74,75] were performed with the use of an AFM probe conjugated with virus particles, and thus the results reflect the interactions between single viruses and single host cells. Attaching viral RBD onto the surface of the AFM tip allows the detection of the interactions between viral RBD and the receptors on host cells. In 2020, Yang et al. [76] investigated the mechanisms of the interactions between RBD of SARS-CoV-2 and ACE2 receptors, as shown in Fig. 5.7B. The RBD components of SARS-CoV-2 were tethered to the AFM tip, and A549 cells were engineered to express ACE2 receptors and labeled with fluorescein (I in Fig. 5.7B). A549-ACE2 cells were then co-cultured with wild-type A549 cells and areas containing adjacent A549-ACE2 and A549 cells were selected for AFM imaging. Multiparametric imaging results show that the binding frequency of A549-ACE2 cells (20.1%) was much higher than that of A549 cells

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(13.5%) (VI in Fig. 5.7B) and the binding frequency of A549-ACE2 cells significantly decreased (VII in Fig. 5.7B) after incubating AFM probe with peptide to block the RBD components on AFM tip, confirming the specificity of the molecular interactions. By multiparametric AFM imaging using biochemically sensitive tips, the binding affinities of the designed blocking molecules for inhibiting viral infection can be directly evaluated [77], offering a novel way for the development of therapeutic agents against viruses.

5.6 Visualizing individual viral dynamics by high-speed atomic force microscopy High-speed AFM is able to visualize the binding dynamics of antibody molecules on the surface of single viruses. Antibodies, including neutralizing antibodies and nonneutralizing antibodies, provide an important way for the development of therapeutic interventions for viral infection. Neutralizing antibodies could block viral entry by preventing the viral RBD from binding to host cell receptors or by preventing the conformational changes of the RBD undergoes to mediate membrane fusion [78,79]. Nonneutralizing antibodies that bind to viral proteins but do not neutralize virions also contribute to the immune control of infection through the increased clearance of free viruses or by targeting infected cells for immune clearance [80]. For individuals that successfully control infection, virus-elicited antibodies can provide surveillance and protection from future insults [81]. Hence, investigating the details of the interactions between antibodies and viruses benefits understanding the underlying anti-virus mechanisms. In 2014, Preiner et al. [82] used high-speed AFM to observe the dynamic movements of antibodies on single HRV particles, as shown in Fig. 5.8. Two types of monoclonal IgG1 antibodies were used (8F5, 3B10). For doing so, HRV particles were attached to freshly cleaved mica in buffer solution (50 mM TrisHCl, 5 mM NiCl2, pH 7.6) by cation adsorption for 15 min [83]. After washing the mica surface with the same buffer solution, the buffer solution was changed to 50 mM TrisHCl, 5 mM NiCl2, and 2 mM CaCl2, and then antibodies were added (the final concentration was 10 μg/mL) and incubated for 1 h. Successive high-speed AFM images were then recorded on single HRV particles. The results distinctly show the different movements of the two types of antibodies on the surface of HRV particles, which were stepping (Fig. 5.8A) and wagging (Fig. 5.8B), respectively. For 8F5 antibodies which bind HRV particles with two Fab arms, since the distance between adjacent epitopes is about 6 nm, a center-of-mass (COM) movement of roughly 3 nm was observed (Fig. 5.8A). For 3B10 antibodies (a type of

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FIGURE 5.8 Visualizing dynamic movements of single antibodies on viral surface by high-speed atomic force microscopy (AFM). (A) Time series of AFM images of 8F5 IgG acquired on the surface of a virion. Red arrows indicate a step, and white arrows indicate the dwelling of the antibody between consecutive images. (B) Successive AFM images of 3B10 IgG bound monovalently to the surface of a virion. White arrows indicate dwelling of the antibody between consecutive images. Source: Reprinted with permission from J. Preiner, N. Kodera, J. Tang, A. Ebner, M. Brameshuber, D. Blaas, et al., IgGs are made for walking on bacterial and viral surfaces, Nat. Commun. 5 (2014) 4394. Copyright 2014 Macmillan Publishers Limited.

neutralizing antibody) which only bind HRV particles with one Fab arm, wagging motion was observed (Fig. 5.8B). The study shows that antibodies do not remain stationary on the viral surface but rather exhibit stochastic walking on the viral surface, which significantly complements the results obtained by traditional methods and will inspire the investigations of antibodies for the treatment of viral infection. High-speed AFM has also been used to reveal the self-assembly dynamics of the formation of viral capsids. Self-assembly, a process in which functional nanoscale structures build themselves driven by Brownian motion and interactions between components, was originally coined to describe the formation of a viral capsid [84]. For viruses that encase RNA, capsid self-assembly can occur spontaneously upon mixing protein and nucleic acid, which makes them ideal model systems to study the self-assembly process [85]. Thermodynamic studies have constructed instructive phase diagrams for viral assembly, with pH and ionic strength acting as thermodynamic control parameters [58]. A three-step mechanism has been proposed for the self-assembly process of the viral capsid, including nucleation (a nucleus is defined as the smallest intermediate of assembly with more than 50% probability to grow instead of disassembling), growth (nucleus size increases by sequential addition of protein subunits), and completion (closure of the capsid) [86]. Nevertheless, the underlying mechanisms guiding the

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self-assembly of the viral capsid are still quite elusive. With the use of high-speed AFM, the individual transient intermediates and reaction pathways during the self-assembly of viral capsid can be revealed. In 2020, Valbuena et al. [87] investigated the self-assembly behaviors of the capsid protein (CA) which constitutes the framework of the mature human immunodeficiency virus (HIV) by high-speed AFM. For doing so, AFM imaging was firstly performed on a freshly cleaved mica in PBS, and then the CA solution was gently added to the imaging solution. There are substantial negative charges on the freshly cleaved mica, which can provide a two-dimensional electrostatic mimic of the negatively charged threedimensional ribonucleoprotein (RNP) complex in the mature virion. Thus, once the CA molecules were added to the AFM imaging solution, the selfassembly of CA was triggered by the negative charges on the mica, which could be monitored by high-speed AFM imaging. Successive AFM images distinctly show that CA subunits were incorporated into the growing hexamer in a stochastic process in which both association and dissociation events (separated by variable intervals) were observed, providing direct evidence for stochastic pathways during the self-assembly of CA. In 2021, the same group revealed the self-assembly pathway of HBV capsid by high-speed AFM [88]. HBV mainly forms T 5 4 icosahedral capsids by 120 core protein (Cp) homodimers, and each Cp consists of an assembly domain and a C-terminal domain (CTD). The CTD is unnecessary for the assembly of the capsid, and its role is mainly promoting the interactions between proteins and nucleic acid to form genome-encapsulated capsids. The high-speed AFM imaging results distinctly show that the HBV assembly pathway proceeds by the formation of diamond pentamers and dodecamers, providing novel insights into the intermediates of the self-assembly of HBV capsids.

5.7 Summary AFM has become a highly powerful and multifunctional tool for characterizing the structures and properties of single viruses under physiological conditions with unprecedented spatiotemporal resolution, which contributes much to the field of physical virology. As a native imaging tool, AFM is able to not only resolve the fine structures on the surface of single virions and structural changes in response to external stimuli (Fig. 5.2) in aqueous conditions, but also visualize the single genomic molecules (DNA/RNA) after viral uncoating (Fig. 5.3), providing knowledge that is closer to the in vivo situations than typical structural biology methods. With the use of high-speed AFM imaging, the real-time dynamical activities of single viruses can be captured at the single-molecule level (Fig. 5.8), benefiting revealing the intermediates

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involved in viral activities. As a measurement tool, AFM can not only directly measure the mechanical properties of single virions by indentation assay (Fig. 5.4), but also can quantify the unbinding forces between viruses and their receptors on the host cells by tethering virus particles onto the surface of AFM tip (Fig. 5.6), which are useful for analyzing the structural stability as well as the viral attachment to host cells during the viral life cycle. By multiparametric AFM imaging technique, various mechanical cues taking place during viruscell interactions can be visually uncovered (Fig. 5.7). In addition, AFM can be even used as a manipulation tool to induce stepwise disassembly of single virions (Fig. 5.5) to release genomic materials (Fig. 5.3). Taken together, the applications of AFM in the studies of viruses considerably improve our understanding of viral behaviors, and the established methodology described in this chapter can be directly applied to other viral systems. As more virus-related studies are performed by the AFM toolbox in future, we have much to look forward to in uncovering the mysteries of the astonishing behaviors of viruses.

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[75] M. Delguste, C. Zeippen, B. Machiels, J. Mast, L. Gillet, D. Alsteens, Multivalent binding of herpesvirus to living cells is tightly regulated during infection, Sci. Adv. 4 (8) (2018). eaat1273. [76] J. Yang, S.J.L. Petitjean, M. Koehler, Q. Zhang, A.C. Dumitru, W. Chen, et al., Molecular interaction and inhibition of SARS-CoV-2 binding to the ACE2 receptor, Nat. Commun. 11 (1) (2020) 4541. [77] S.J.L. Petitjean, W. Chen, M. Koehler, R. Jimmidi, J. Yang, D. Mohammed, et al., Multivalent 9-O-acetylated-sialic acid glycoclusters as potent inhibitors for SARSCoV-2 infection, Nat. Commun. 13 (1) (2022) 2564. [78] J. Abraham, Passive antibody therapy in COVID-19, Nat. Rev. Immunol. 20 (7) (2020) 401403. [79] B. Ju, Q. Zhang, J. Ge, R. Wang, J. Sun, X. Ge, et al., Human neutralizing antibodies elicited by SARS-CoV-2 infection, Nature 584 (7819) (2020) 115119. [80] D. Cromer, J.A. Juno, D. Khoury, A. Reynaldi, A.K. Wheatley, S.J. Kent, et al., Prospects for durable immune control of SARS-CoV-2 and prevention of reinfection, Nat. Rev. Immunol. 21 (6) (2021) 395404. [81] C.D. Murin, I.A. Wilson, A.B. Ward, Antibody responses to viral infections: a structural perspective across three different enveloped viruses, Nat. Microbiol. 4 (5) (2019) 734747. [82] J. Preiner, N. Kodera, J. Tang, A. Ebner, M. Brameshuber, D. Blaas, et al., IgGs are made for walking on bacterial and viral surfaces, Nat. Commun. 5 (2014) 4394. [83] F. Kienberger, C. Rankl, V. Pastushenko, R. Zhu, D. Blaas, P. Hinterdorfer, Visualization of single receptor molecules bound to human rhinovirus under physiological conditions, Structure 13 (9) (2005) 12471253. [84] R.F. Garmann, A.M. Goldfain, V.N. Manoharan, Measurements of the self-assembly kinetics of individual viral capsids around their RNA genome, Proc. Natl. Acad. Sci. U. S. A. 116 (45) (2019) 2248522490. [85] J.J. McManus, P. Charbonneau, E. Zaccarelli, N. Asherie, The physics of protein selfassembly, Curr. Opin. Colloid Interface Sci. 22 (2016) 7379. [86] P. Buzon, S. Maity, W.H. Roos, Physical virology: from virus self-assembly to particle mechanics, WIREs Nanomed. Nanobiotechnol. 12 (4) (2020) e1613. [87] A. Valbuena, S. Maity, M.G. Mateu, W.H. Roos, Visualization of single molecules building a viral capsid protein lattice through stochastic pathways, ACS Nano 14 (7) (2020) 87248734. [88] P. Buzon, S. Maity, P. Christodoulis, M.J. Wiertsema, S. Dunkelbarger, C. Kim, et al., Virus self-assembly proceeds through contact-rich energy minima, Sci. Adv. 7 (45) (2021). eabg0811.

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C H A P T E R

6 Imaging and mechanical analysis of single native exosomes by atomic force microscopy A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/ 9780323953603.

6.1 Background Extracellular vesicles (EVs) play an essential role in the physiological and pathological processes of living organisms. In multicellular organisms, distant cells can exchange information by sending out signals composed of single molecules or via complex packets stuffed with a selection of proteins, lipids, and nucleic acids, and these packets are called EVs [1]. All cells, both prokaryotes and eukaryotes, secrete EVs as part of their normal physiology and during acquired abnormalities [2]. EVs are produced and released into virtually all body biofluids, such as serum/plasma, urine, saliva, bile, ascites, semen, synovial fluid, amniotic fluid, cerebrospinal fluid and breast milk [3,4]. The physiological purpose of generating EVs remains poorly understood, and one speculated role is that EVs probably remove excess and/or unnecessary constituents from cells to maintain cellular homeostasis [2]. EVs have been shown to not only participate in numerous normal physiological processes (e.g., blood coagulation, innate and/or acquired immunity and immunomodulation, stem cell differentiation, tissue regeneration and angiogenesis, autophagy, embryo implantation, placental physiology, semen regulatory function, reproductive biology, pregnancy, and development of nervous system), but also are largely involved in various pathological processes (e.g., inflammatory diseases, autoimmune

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disorders, pathogen infections, cardiovascular diseases, metabolic diseases, neurodegenerative diseases, respiratory diseases, renal diseases, hepatic diseases, musculoskeletal diseases, and cancers) [59]. For example, during tumor metastasis, primary tumor cells secrete EVs to modify the distant microenvironment in advance to provide a suitable niche (the modified niche is called premetastatic niche) for the colonization of incoming tumor cells [10,11]. The ability of EVs to transport biomolecules to recipient cells has made them attractive for drug delivery purposes [12], and EVs have been shown to deliver functional cargoes with decreased immune clearance compared with standard delivery methods [13], opening new frontiers for modern drug delivery. The biogenesis and structures of exosomes are illustrated in Fig. 6.1. According to the mechanisms by which EVs are formed, EVs can be

FIGURE 6.1 The formation and structures of exosomes. (A) Biogenesis and secretion of extracellualr vesicles (EVs) (exosomes and ectosomes). Ectosomes are released by the outward budding of the plasma membrane. Exosomes are generated from the inward budding of the late endosomal compartments called multivesicular bodies (MVBs) in which intraluminal vesicles (ILVs) are included. These MVBs can translocate to the lysosome and deliver their cargo for degradation, or travel to and fuse with the plasma membrane to release ILVs into the extracellular milieu and these released ILVs are called exosomes. Mitochondria also produce vesicles called mitochondrial-derived vesicles (MDVs). MDVs can become part of the MVB and be transported to the lysosome for degradation, or can be secreted from the cell as exosomes. (B) The structures of exosomes. The tetraspanins (CD9, CD63, and CD81) and other molecules on the surface of exosomes initiate recipient cell binding of exosomes. Exosomes can contain different types of cell surface proteins, intracellular proteins, RNA, DNA, amino acids, and metabolites [2]. Some proteins (ALIX, syndecan, TSG101, HSP) inside the exosomes have been used to characterize the biogenic origin of exosomes. Sources: (A) Reprinted with permission from A. Safdar, A. Saleem, M.A. Tarnopolsky, The potential of endurance exercisederived exosomes to treat metabolic diseases, Nat. Rev. Endocrinol. 12(9) (2016) 504517. Copyright 2016 Macmillan Publishers Limited. (B) Reprinted with permission from A. Moller, R.J. Lobb, The evolving translational potential of small extracellular vesicles in cancer, Nat. Rev. Cancer 20(12) (2020) 697709. Copyright 2020 Springer Nature Limited.

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broadly divided into two categories, ectosomes and exosomes [2]. Ectosomes, in a size range of approximately 50 nm10 μm [14], comprise diverse types of EVs such as oncosomes and microvesicles that are generated by the direct outward budding of the plasma membrane (Fig. 6.1A). Exosomes originate from the endosomal pathway and are in a size range of approximately 30150 nm (B100 nm on average). The maturation of early endosomal membranes into late endosomes involves the formation of intraluminal vesicles (ILVs) which give rise to a specialized cell compartment called multivesicular bodies (MVBs) [6], and the subsequent fusion of MVB and the plasma membrane causes the release of ILVs as exosomes (Fig. 6.1A). Once released by cells, EVs may directly interact with the extracellular matrix to facilitate the dissemination of EVs, and EVs can also be directly released into biofluids by transcytosis or by passing through breaches of biological barriers to disseminating via the circulation systems [14]. In this chapter, exosomes are used as an example to show the applications of AFM in characterizing the behaviors of individual EVs, and thus we will focus on exosomes in the remaining contents. Exosomes consist of a lipid bilayer membrane which encases the biochemical materials (e.g., DNA, RNA, proteins, lipids), and the diverse biomolecular constituents of exosomes are reflective of their cell of origin [15], as shown in Fig. 6.1B. Many proteins are distributed on the bilayer membrane of exosomes, and some of these proteins have been widely used as markers for the identification of exosomes, including CD63, CD81, CD9, flotillin, and so on [2,16]. Exosomes can be internalized by recipient cells to transfer the encapsulated bioactive materials via different mechanisms, including phagocytosis, macropinocytosis, endocytosis, and direct membrane fusion [7]. Besides, the ligands on the surface of exosomes can directly bind to the specific receptors on the recipient cell, which then triggers the intracellular signaling cascade to regulate the behaviors of the recipient cell [17]. Hence, investigating the behaviors of exosomes is of remarkable significance for unveiling the underlying mechanisms guiding the physiological/pathological processes of life. Currently, exosomes have been widely characterized by SEM or TEM, which require the dehydration of exosomes, and the distorted cup-shaped morphologies of exosomes are commonly observed from the obtained SEM/TEM images [1820]. Cryo-EM allows imaging exosomes in frozen samples without the need for dehydration, and the round morphology of exosomes is commonly observed from cryo-EM images [2123], indicating that the cup-shaped morphology of exosomes visible in SEM/TEM images is in fact an artifact from dehydration [24]. Compared with cryo-EM, AFM can not only visualize the fine structures of single native exosomes under aqueous conditions without any pretreatments but also can measure the mechanical properties of

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exosomes, offering a novel way to characterize the structures and properties of exosomes and applications of AFM in the studies of exosomes provide novel insights into the cell biology.

6.2 Exosome isolation and immobilization The prerequisite of utilizing AFM to detect the behaviors of exosomes is collecting the purified exosomes from biofluids. In recent years, liquid biopsy assays have been an emerging and promising way of detecting and monitoring human diseases such as cancers with clinical translational significance [25]. In oncology, the term liquid biopsy is used in a broad sense to refer to the sampling and analysis of analytes from various biological fluids, mostly blood but also other easily accessible fluids such as urine, ascites or pleural effusions [26]. In theory, pathological changes in the organisms are often accompanied by alterations of the analytes in the biofluid, which can then be captured to track the evolutionary dynamics of diseases. At present, the molecular profiles of solid tumors are established using surgical or biopsy tissue samples, which are subject to sampling bias and cannot be obtained repeatedly [27]. In contrast, owing to their noninvasive nature, liquid biopsies can be scheduled more frequently to provide a personalized snapshot of disease at successive time points [28], and thus liquid biopsy assays promise for the early detection of diseases and will hopefully lead to improvements in patient management and outcomes [29]. Hence, characterizing the behaviors of exosomes isolated from the biofluids significantly benefits the studies of liquid biopsy assay for practical applications in clinical medicine. Various methods have been presented for the isolation of exosomes from biofluids, mainly including differential ultracentrifugation, sizebased isolation, bead-based isolation, and polymer-based precipitation [3032]. Differential ultracentrifugation is currently the gold-standard technique for EV isolation and is widely used to isolate EVs from both cell culture media and body fluids [33,34]. Notably, there is still debate about the best option for exosome isolation methods [35]. Differential ultracentrifugation typically consists of low-speed centrifugation to remove cells and cell debris and high-speed ultracentrifugation (100,000 3 g) to pellet exosomes. Ultracentrifugation can also be combined with a sucrose density gradient to remove protein molecules and improve purity. Size-based isolation methods rely on the use of porous membranes with specified pore size to separate the components based on their size or molecular weight, and various sizebased isolation methods have been developed for isolating exosomes, including ultrafiltration, sequential filtration, size-exclusion chromatography, fractionation, hydrostatic filtration dialysis, and commercially available products such as ExoMir Kit [32]. Many proteins are found to be exclusively expressed on the surface of exosomes, and thus these proteins can be used

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as markers to recognize exosomes (CD9, CD63, and CD81 are the most commonly used markers for exosome isolation) [36,37]. By coating antibodies that can specifically bind to these markers onto beads (magnetic beads are the most conventionally used beads), these beads can be used to specifically adsorb exosomes in the biofluids. Purified exosomes are then obtained by collecting these beads, for example, magnetic beads can be intercepted by a magnetic field, and this method is called bead-based immunocapture. Exosomes can also be isolated by polymer-based precipitation, in which highly hydrophilic polymers (PEG is the most commonly used one) are added into the exosome-containing solution to tie up the water molecules surrounding the exosomes to lower the solubility of the exosomes and therefore allows collecting exosomes by low-speed centrifugation [31]. The detailed comparisons of these exosome isolation methods, including their advantages and limitations, are summarized in Table 6.1. Fig. 6.2 shows the results of isolating exosomes from bone marrow prepared from clinical lymphoma patients by commercial precipitation reagents (Life Technologies, Thermo Fisher Scientific Inc., Waltham, USA) as an example of exosome preparation for AFM studies [38,39]. The procedure of isolating exosomes from the bone marrow was according to the protocol of the manufacturer. First, 1 mL bone marrow aspiration samples (treated with EDTA for anticoagulation, as shown in the I of Fig. 6.2A) were added to a fresh centrifuge tube and centrifuged at 2000 3 g for 20 min at room temperature. After centrifugation, the supernatant was transferred to a new fresh centrifuge tube and 0.4 mL PBS was added into the tube. Subsequently, exosome precipitation reagent solution (0.24 mL) was added into the tube and incubated at room temperature for 10 min. After incubation, the sample was centrifuged at 10000 3 g for 5 min at room temperature. After centrifugation, exosome precipitations were observed at the bottom of the tube (II in Fig. 6.2A). After removing the supernatant, PBS was added into the tube to resuspend the exosomes. The prepared exosome samples can be immediately used for AFM studies or can be stored at 20 C. After obtaining the purified exosomes from biofluids, the next issue is using adequate immobilization methods to attach exosomes onto stiff substrates for AFM characterizations. Like the plasma membrane of cells, the exosome surface is generally negatively charged in neutral buffer solutions [40], and the magnitude of the zeta potential (ZP) of exosomes is dependent on several factors, including surface chemistry, pH, protonated states, presence of H-bonds, ionic strength of the medium, and so on [41]. By coating the substrates with a layer of positively charged biomolecules (such as poly-L-lysine), negatively charged exosomes can then be immobilized onto the substrates via electrostatic adsorption (Fig. 6.2B). Experimental results have distinctly shown that the poly-Llysine-based electrostatic adsorption allows reliable AFM imaging and

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TABLE 6.1 Comparisons of representative exosome isolation methods. Exosome isolation methods

General descriptions

Time

Purity

Yield

Advantages

Limitations

Differential ultracentrifugation

Multiple cycles of centrifugation with progressively stronger centrifugal forces (from 300 3 g to 100,000 3 g) are performed to successively remove cells, cell debris, and large EVs, and finally exosomes are obtained.

518 h

Medium

Medium

Suitable for large volume preparation; reagents are costeffective.

High equipment requirement; potential damage due to highspeed centrifugation; timeconsuming; labor intensive.

Size-based isolation

The biofluids are driven to pass through multiple porous membranes with specified pore sizes based on the size/ molecular weight of the components in biofluids to finally separate the exosomes.

24 h

High

Low

No requirement of special equipment; fast procedure; portable and safe; isolating native exosomes.

Possibility of clogging; potential damage by shear stress; loss of exosomes attached to the membrane.

Bead-based immunocapture

Antibodies that can recognize exosomal surface markers (e.g., CD9, CD63, CD81) are coated on beads, which are then incubated with biofluids to enrich exosomes on the beads.

26 h

High

Low

High purity; isolation of specific exosomes.

Expensive; low yields and processing volume; exosome markers must be optimized; works well only for cell-free samples.

Polymer-based precipitation

High hydrophilic water-excluding polymers (e.g., PEG) are added into the biofluids to lower the solubility of exosomes, which allows collecting exosomes by low-speed centrifugation.

0.512 h

Low

High

Suitable for both small and large sample volume; easy to use; high efficiency.

Potential polymeric, protein aggregates, and other EV contaminants.

Reprinted with permission from J. Wang, P. Ma, D.H. Kim, B.F. Liu, U. Demirci, Towards microfluidic-based exosome isolation and detection for tumor therapy, Nano Today 37 (2021) 101066. Copyright 2020 Elsevier Ltd. Modified according to the information from M. Zhang, K. Jin, L. Gao, Z. Zhang, F. Li, F. Zhou, et al., Methods and technologies for exosome isolation and characterization, Small Methods 2(9) (2018) 1800021 and D. Yang, W. Zhang, H. Zhang, F. Zhang, L. Chen, L. Ma, et al., Progress, opportunity, and perspective on exosome isolation-efforts for efficient exosome-based theranostics, Theranostics 10(8) (2020) 36843707.

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FIGURE 6.2 Exosome isolation and immobilization for atomic force microscopy (AFM) studies. (A) Isolating exosomes from bone marrow. (I) Bone marrow aspiration sample. (II) Exosomes isolated from the bone marrow by the method of polymer-based precipitation. The red arrow denotes the exosomes deposited at the bottom of the tube. (B) Schematic representation of attaching exosomes onto the substrate via electrostatic adsorption. Source: Reprinted and modified with permission from M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Nanostructures and mechanics of living exosomes probed by atomic force microscopy, Prog. Biochem. Biophys. 48(1) (2021) 100110.

force detection of single native exosomes in solution [38,39]. A brief protocol for immobilizing native exosomes onto the substrates by poly-Llysine is following. First, the poly-L-lysine stock solution is diluted 10 times with pure water. The diluted poly-L-lysine solution is then dropped onto a fresh glass slide, and the slide is placed at room temperature for air-drying. After air-drying, the isolated exosome solution is dropped onto the poly-L-lysine-coated slide and incubated for 2 min to establish the firm adsorption between exosomes and the substrate. After incubation, the glass slide is directly placed in a dish containing PBS and then AFM is controlled to detect the exosomes in the PBS.

6.3 Imaging single native exosomes in liquid AFM is able to directly visualize the fine structures of single native exosomes under aqueous conditions. Based on the immobilization method of poly-L-lysine electrostatic adsorption (Fig. 6.2), AFM images of native exosomes isolated from the bone marrow of lymphoma patients without any pretreatments were obtained at PFT mode in PBS, as shown in Fig. 6.3A. Readers are referred to Chapter 1 for the principles of PFT mode AFM imaging. The experiments were performed with a commercial AFM called Dimension Icon AFM (Bruker, Santa Barbara, USA). The AFM probe used here is commercially called ScanAsystFluid (Bruker, Santa Barbara, CA, USA), whose nominal spring constant is 0.7 N/m. Before performing AFM imaging, force curves were firstly

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FIGURE 6.3 Atomic force microscopy (AFM) images of the exosomes isolated from the bone marrow of lymphoma patients. (A) AFM images of the exosomes obtained in PBS. (B) AFM images of the exosomes obtained in the air. (I) Large-size scanning. (II) Small-size scanning. (III) The corresponding section profile curves taken along the red and blue dashed lines in (II). Source: Reprinted and modified with permission from M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Nanostructures and mechanics of living exosomes probed by atomic force microscopy, Prog. Biochem. Biophys. 48(1) (2021) 100110.

obtained on the bare areas of the substrates to calibrate the deflection sensitivity of the probe, which was subsequently used to calculate the exact spring constant of the cantilever by using AFM’s thermal noise module. From the obtained AFM images (I and II in Fig. 6.3A), the round morphology of native exosomes is distinctly observed and exosomes with different sizes are discretely distributed on the substrate. We can see that the morphology of native exosomes revealed by AFM images is comparable with that revealed by cryo-EM [2123], whereas the sample preparation for AFM imaging is far simpler than that for cryo-EM. The height of the exosomes can be obtained from the section curves of the AFM images (III in Fig. 6.3A). The results show that polyL-lysine-based electrostatic adsorption is able to firmly attach exosomes onto the substrate and allows imaging exosomes in their native states (in buffer solution) by AFM. AFM images of exosomes were also obtained in the air, as shown in Fig. 6.3B. The round morphology of exosomes is also observed from the AFM images of exosomes recorded in air, but from the section curves, we can clearly see that the height of exosomes in the air (III in Fig. 6.3B) is much less than that of exosomes in aqueous conditions (III in Fig. 6.3A), showing that air-drying could significantly cause the shrinking of exosomes. AFM has been widely

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utilized to image exosomes, and many of these studies were performed in the air which requires the air-drying of exosomes, including exosomes secreted by MDA-MB-231 cells [42], exosomes in the oral fluids of oral cancer patients [43], exosomes released by HeLa cells [44], and exosomes from raw milk of cows [45]. We know that exosomes are in the biofluids in vivo, and thus the results obtained in the air may not fully reflect the structures and properties of exosomes in the biofluids. Therefore, directly imaging native exosomes in liquids by AFM significantly benefits characterizing the real behaviors of exosomes. With the use of poly-L-lysine electrostatic adsorption, exosomes generated by red blood cells [46] and exosomes from the peripheral blood of healthy volunteers [47] have also been imaged by AFM in liquid. Notably, besides poly-L-lysine electrostatic adsorption, researchers have developed other immobilization methods to attach native exosomes onto the substrates for AFM imaging of exosomes under aqueous conditions, including immobilizing exosomes onto cation-treated mica surface [48] and immobilizing exosomes onto APTES-treated mica surface [49], offering alternative methods for AFM-based imaging of native exosomes. The exact geometric parameters of single native exosomes adsorbed on the substrate in the fluids can be obtained from AFM data. By analyzing the section profile curves of exosomes taken along the acquired AFM topographical images of exosomes, the real radius of exosomes can be calculated [5052], which is based on the reasonable assumption that exosomes form a spherical morphology on the substrate. After imaging single exosomes by AFM (Fig. 6.4A), a section profile curve through the maximum of the exosome can be generated (Fig. 6.4B). Due to the AFM tip-sample convolution effect caused by the geometrical interactions between the AFM tip and surface features during AFM scanning, the lateral broadening of the surface protrusions is often observed from the obtained AFM images [53]. In the case of imaging exosomes by AFM, the broadening effect is particularly evident when the AFM tip scans the side of the exosomes, whereas the broadening effect is very weak when the AFM tip scans the upper part of the exosomes [54], as shown in Fig. 6.4C. Hence, it can be considered that the profile of the upper part of the exosome is quite consistent with the real morphology of the exosome (as denoted by the dotted profile of the upper part of the exosome in Fig. 6.4C), and fits the top circular arc in the section curve gives the estimated radius (Rc) of the exosome (Fig. 6.4B). The section curve also gives the height of the exosome (Fig. 6.4B), but notably, this height value is lower than the real height of the exosome on the substrate due to the compression of the exosome caused by the scanning tip. As shown in Fig. 6.4F, lowering the scanning force results in the increase of the height of the exosome measured from the AFM topographical images. In order to obtain the real height

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FIGURE 6.4 Determining the size and geometry of the exosomes adsorbed on the substrate. (A) Atomic force microscopy (AFM) topographical image of an exosome derived from MCF-10A. (B) The section profile curve taken along the orange line in (A). The red solid line and the black dashed line indicate the fitted circular arc and the estimated shape of the exosome, respectively, under the assumption that the exosome forms spherical caps on the substrate. (C) Schematic illustration of the tip-sample convolution effect for imaging exosomes with AFM. The dotted line indicates the profile morphology of the exosome generated during AFM scanning. (D) A force curve obtained on the exosome to determine the real height of the exosome. (E) The representative shapes of the adsorbed exosomes illustrated in the red dotted box. (F) AFM topographical images of the same exosome under different scanning forces. The insets are the section profile curves taken along the orange lines. Sources: (A, B, D, E, and F) Reprinted with permission from S. Ye, W. Li, H. Wang, L. Zhu, C. Wang, Y. Yang, Quantitative nanomechanical analysis of small extracellular vesicles for tumor malignancy indication, Adv. Sci. 8(18) (2021) 2100825. Copyright 2021 The Authors. (C) is reprinted with permission from W.K. Serem, K.L. Lusker, J.C. Garno, Using scanning probe microscopy to characterize nanoparticles and nanocrystals, in: R.A. Meyers (Ed.), Encyclopedia of analytical chemistry: applications, theory and instrumentation, John Wiley & Sons, Hoboken, 2010, pp. 135. Copyright 2010 John Wiley & Sons, Ltd.

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of the exosome, the AFM tip is controlled to indent the exosome to record force curves (Fig. 6.4D). A notable point is that, in order to exactly obtain the real height of the exosomes, the AFM tip needs to penetrate the upper and lower membranes of the exosome to reach the stiff substrate [5052]. From the obtained force curves, the distance from the zero-force contact point to the maximum indentation is equal to the real height (HFIC) of the exosome (Fig. 6.4D). The geometry of the exosome can then be determined by the value of HFIC/Rc and different geometric shapes of the exosomes on the substrate can then be identified according to the values of HFIC/Rc (Fig. 6.4E).

6.4 Measuring the mechanics of single native exosomes The mechanical properties of single native exosomes can be measured by AFM indentation assay. For doing so, AFM topographical imaging is firstly performed to localize the exosomes on the substrate (Fig. 6.3). After localizing single exosomes by AFM topographical imaging, the AFM tip is positioned on individual exosomes to perform indentation assay to record force curves. By analyzing the force curves with the HertzSneddon model, Young’s modulus of the exosomes being indented can then be calculated. Readers are referred to Chapter 1 for more descriptions of AFM indentation assay. Fig. 6.5A shows the results of measuring Young’s modulus of single native exosomes by AFM. According to the contact point visually determined in the approach curve (I in Fig. 6.5A), the approach curve is converted into the indentation curve (the indentation is obtained by subtracting the deflection of the cantilever from the vertical displacement of the probe). Fitting the indentation curve with the HertzSneddon model gives Young’s modulus of the exosome (II in Fig. 6.5A). Fig. 6.5B shows the results of Young’s modulus measurements of exosomes treated by the chemical fixative. After attaching the isolated exosomes to the polyL-lysine-coated substrate, 4% paraformaldehyde solution was added to chemically fix the exosomes for 30 min. After fixation, the exosomes were rinsed with PBS and detected by AFM in PBS. From the statistical histograms (III in Fig. 6.5A and B), we can clearly see that exosomes become significantly stiffer after chemical fixation, indicating the effects of chemical fixation on the mechanics of exosomes. The mechanical properties of exosomes are closely associated with the structures of exosomes, and the morphological changes of exosomes after chemical fixation could be visualized by AFM. Fig. 6.5C shows the AFM topographical images of native exosomes and paraformaldehyde-treated exosomes respectively. Native exosomes exhibit round morphology (I in Fig. 6.5C), whereas concave structures appear on the exosomes after chemical fixation (II in Fig. 6.5C), indicating that chemical fixation could cause the structural distortion of the

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FIGURE 6.5 Detecting Young’s modulus of exosomes by atomic force microscopy (AFM). (A) Young’s modulus measurements of native exosomes. (B) Young’s modulus measurements of exosomes after chemical fixation. (I) Typical force curves. (II) Experimental indentation curves (black dotted) and corresponding theoretical fitting curves (red). (III) Statistical histograms of Young’s modulus values of exosomes. (C) Typical AFM topographical images of native exosomes (I) and paraformaldehyde-treated exosomes (II). Images were obtained in PFT mode in PBS. The insets are the section profile curves taken along the lines across the exosomes denoted by the red arrows. Source: Reprinted and modified with permission from M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Nanostructures and mechanics of living exosomes probed by atomic force microscopy, Prog. Biochem. Biophys. 48(1) (2021) 100110.

exosomes. For utilizing AFM indentation assay to detect the mechanical properties of exosomes, since Young’s modulus of specimens measured by AFM is dependent on the measurement parameters, a notable point is that the experimental conditions (e.g., the approaching velocity of AFM probe, the buffer solution in which experiments are performed, tip shape and tip size) should be maintained identical to make the results comparable with each other.

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Studies performed with AFM have shown that the mechanical properties of exosomes are indicative of the pathological changes of diseases. In 2018, Vorselen et al. [51] investigated the mechanical properties of red blood cell (RBC) exosomes from healthy volunteers and from patients with hereditary spherocytosis (HS) by AFM. RBCs derived from healthy volunteers or HS patients were treated with a Ca21 ionophore to generate exosomes. The RBC-secreted exosomes were collected by the differential ultracentrifugation method, after which the purified exosomes were attached to the poly-L-lysine-coated glass slides and AFM experiments (topographical imaging and indentation assay) were performed on the exosomes in PBS. The experimental results show that the exosomes from HS patients have a significantly lower (B40%) bending modulus than the exosomes from healthy donors. An interesting phenomenon is that the RBCs from HS patients are stiffer than the RBCs from healthy donors. In 2021, Ye et al. [52] investigated the mechanical properties of exosomes secreted by different types of cancerous cells for tumor malignancy indication with the use of AFM. The normal human mammary epithelial cell line MCF-10A and four human breast cancer cell lines with increasing malignancy (MCF-7, SK-BR-3, MDA-MB-468, MDA-MB-231) were used. Exosomes were collected from the cell culture medium of the five different types of cells by differential ultracentrifugation. The experimental results show that the stiffness of the exosomes decreased with the increasing size of exosomes, and exosomes secreted by invasive cancerous cells were significantly stiffer than the exosomes secreted by indolent cancerous cells. Researchers have shown that primary tumor-derived exosomes facilitate metastasis by increasing the adhesive ability to circulate tumor cells [55]. The rigid feature of exosomes secreted by malignant cancerous cells may facilitate the entry of exosomes into the recipient cells to promote tumor metastasis, but further investigations are needed to establish the associations between exosome mechanics and exosome-cell interactions. Overall, these studies show the evident relationships between exosome mechanics and pathological changes, which will benefit comprehensively understanding human diseases and will have potential impacts on the development of exosome-related biomarkers for disease diagnosis.

6.5 Multiparametric imaging of single native exosomes PFT-based multiparametric AFM imaging allows acquiring the morphology of single native exosomes while simultaneously obtaining the multiple mechanical properties of the exosomes. It is increasingly apparent in the field of life sciences that biological entities at all scales, from molecules and organelles to cells and organs, are both mechanical and

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biochemical systems [56]. For exosomes, the uptake of exosomes by the recipient cell is typically mechanical and biochemical. The first step of the uptake of exosomes is the recognizing and binding of exosomes to the recipient cell, which is dependent on the adhesion proteins (such as integrin), receptors, antigens, and other molecules on the surface of exosomes [57]. These molecules mediate the strength of the binding interactions between exosomes and cell surfaces, which influence the subsequent internalization of the exosomes into the recipient cell to deliver substances encapsulated in the exosomes. In fact, studies have shown that inhibition of integrins on the exosome surface impairs the adhesion and uptake of exosomes [58]. Hence, the adhesive properties of exosomes play an important role in the uptake and biology of the exosomes. Besides, studies have also shown the indicative role of the rigidity of the exosomes in human diseases [51,52]. Therefore, simultaneously imaging the structures of exosomes and detecting the multiple mechanical properties of exosomes significantly benefits comprehensively understanding the regulatory role of mechanical cues in exosome-related activities. Fig. 6.6 shows the multiparametric AFM imaging results of native exosomes adsorbed on a poly-L-lysine-coated substrate in PBS, including the topography images (Fig. 6.6A, B) and corresponding various mechanical images (Fig. 6.6C-F) of three native exosomes. PFT-based multiparametric AFM imaging was performed with a commercial AFM called Dimension Icon AFM (Bruker, Santa Barbara, United States). The driving frequency of the cantilever was 2 kHz, the scan rate was 1 Hz, the scan line was 512, and the sampling point for each scan line was also 512 [39]. Readers are referred to Chapter 1 for more descriptions of PFT-based multiparametric AFM imaging. Force curves for each sampling point on the surface of specimens are recorded during PFT imaging, and analyzing the different parts of the force curves gives the various mechanical properties of the specimens, including Young’s modulus (Fig. 6.6C), adhesion force (Fig. 6.6D), deformation (Fig. 6.6E), and energy dissipation (Fig. 6.6F). In the mechanical maps, the color brightness directly presents the magnitude of the mechanical parameter values. The exosomes are discriminable from the mechanical maps (Fig. 6.6CF), which are correlated with the morphology of exosomes (Fig. 6.6A and B). Native exosomes are much softer (Fig. 6.6C) and more deformable (Fig. 6.6E) than the rigid substrates, whereas the adhesion forces between native exosomes and AFM tip are similar to the adhesion forces between AFM tip and substrates (Fig. 6.6D). Besides, Young’s modulus values in Young’s modulus maps of exosomes (Fig. 6.6C) are consistent with the results obtained from the traditional AFM indentation assay (Fig. 6.5A), confirming the validity of multiparametric AFM imaging results. A notable phenomenon is that there is significantly larger energy

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FIGURE 6.6 Multiparametric atomic force microscopy (AFM) imaging results of native exosomes recorded in PBS. (A) Height image. (B) Deflection image. (C) Young’s modulus image. (D) Adhesion force image. (E) Deformation image. (F) Energy dissipation image. The section profile curves taken along the three exosomes are shown under each type of AFM image. Source: Reprinted and modified with permission from M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Multiparametric atomic force microscopy imaging of single native exosomes, Acta Biochim. Biophys. Sin. 53(3) (2021) 385388. Copyright 2021 The Authors.

dissipation at one side edge of the native exosomes (Fig. 6.6F), indicating the heterogeneous distributions of energy dissipation features on the exosomes. Fig. 6.7 shows the multiparametric AFM imaging results of exosomes treated with 4% paraformaldehyde. We can see that exosomes after chemical treatment are quite indistinguishable from the mechanical maps (Fig. 6.7), whereas the native exosomes without chemical fixation are remarkably distinguishable from the mechanical maps

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FIGURE 6.7 Multiparametric atomic force microscopy (AFM) imaging results of chemically fixed exosomes obtained in PBS. (A) Results of an exosome after chemical fixation. (B) Results of another exosome after chemical fixation. Height images (I), and corresponding deformation images (II), adhesion force images (III), and Young’s modulus images (IV). Source: Reprinted and modified with permission from M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Nanostructures and mechanics of living exosomes probed by atomic force microscopy, Prog. Biochem. Biophys. 48(1) (2021) 100110.

(Fig. 6.6). After chemical fixation, exosomes have decreased deformation (II in Fig. 6.7) and increased stiffness (IV in Fig. 6.7), consistent with the results obtained by AFM indentation assay (Fig. 6.5B). The results (Fig. 6.7) distinctly show the influence of chemical fixation on the multiple mechanical properties of exosomes. Overall, the experimental results (Figs. 6.6 and 6.7) demonstrate the capabilities of multiparametric AFM imaging in resolving the structures and simultaneously visualizing the multiple mechanical properties of single native exosomes in aqueous conditions with high spatial resolution as well as characterizing their dynamics in response to external stimuli, which offer a novel approach to correlate the exosome structures with their mechanics and will be particularly meaningful for understanding the behaviors of exosomes from the perspective of biomechanics and biophysics.

6.6 Single-molecule force spectroscopy on single exosomes With the use of the AFM-based single-molecule force spectroscopy (SMFS) technique, individual protein molecules on the surface of native exosomes can be located and the binding affinities of these molecules can be directly measured. There are various protein molecules on the surface of exosomes (as shown in Fig. 6.1B), which regulate the behaviors of exosomes. Traditional biochemical methods (such as western

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blot analysis and mass spectrometry) for detecting these protein molecules require the lysis of the exosomes to obtain purified proteins from exosomes [5962], after which exosomes are destroyed and lose biological activities. AFM is able to directly detect the single proteins on the surface of exosomes without the requirement of the lysis of exosomes, which is quite meaningful for investigating the molecular interactions of exosome surface proteins in their native states. Readers are referred to Chapter 1 for the principle of SMFS. Briefly, the antibodies that can specifically bind to the protein molecules on the exosome surface are attached to the surface of the AFM tip via linker molecules (such as PEG) (Fig. 6.8A). The functionalized probe is then controlled to perform approach-retract cycles on the exosome. If the antibodies on the AFM tip bind to the receptors on the exosome during the contact between the AFM tip and exosome, the receptor-antibody complexes are stretched until ruptured during the retract process of the AFM probe, which will cause a specific unbinding force peak in the retract portion of the force curve. The magnitude of the force peak corresponds to the unbinding force of the receptor-antibody bond. In 2010, Sharma et al. [63] used AFM-based SMFS to investigate the binding affinity of CD63 molecules on the exosomes, as shown in Fig. 6.8(B and C). Exosomes were isolated from the saliva samples of healthy donors by differential ultracentrifugation. In order to confirm the expression of CD63 on the exosomes, AFM immunobead imaging was performed (Fig. 6.8B). Exosomes were

FIGURE 6.8 Detecting single protein molecules on the surface of exosomes by atomic force microscopy (AFM)-based SMFS. (A) Schematic illustration. Antibodies that can specifically bind to the protein molecules on the exosomes are linked to the surface of the AFM tip and the functionalized probes are used to localize the proteins on exosomes by SMFS experiments. (B) AFM topographical image of the exosomes after being incubated with anti-CD63 antibodies and gold beads coated with secondary antibodies. The inset shows a single exosome with several beads bound on the exosome surface. (C) The histogram of the distribution of the rupture forces. (I, II) Typical force curves with specific unbinding peaks (I) and nonspecific force peaks (II) respectively. Source: (B and C) are reprinted with permission from S. Sharma, H.I. Rasool, V. Palanisamy, C. Mathisen, M. Schmidt, D. T. Wong, et al., Structural-mechanical characterization of nanoparticle exosomes in human saliva, using correlative AFM, FESEM, and force spectroscopy, ACS Nano 4(4) (2010) 19211926. Copyright 2010 American Chemical Society.

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firstly incubated with anti-CD63 antibodies. After incubation, exosomes were incubated with gold beads carrying secondary antibodies. AFM imaging of the exosomes clearly shows the gold beads bound onto the exosomes (Fig. 6.8B), indicating the CD63 molecules on the exosomes. The anti-CD63 antibody-functionalized AFM probes were then used to perform topographical imaging to localize single exosomes. After localizing the exosomes from the obtained topographical images, SMFS experiments were performed on the exosomes to obtain force curves. Big force peaks appeared in the force curves (I in Fig. 6.8C), which reflected the specific unbinding events between CD63 molecules and anti-CD63 antibodies. AFM probes linked with nonspecific antibodies were used for the control group, and only small nonspecific force peaks were observed in the force curves (II in Fig. 6.8C). The statistical histogram shows that the specific unbinding forces of CD63-anti-CD63 antibody are significantly larger than that of nonspecific unbinding forces (Fig. 6.8C). In 2011, the same group used the established methods to investigate the molecular interactions of CD63 on the exosomes of healthy volunteers and from oral cancer patients [64]. The experimental results show that the unbinding forces of CD63 on the normal exosomes were 70 6 15 pN, with 38% of the unbinding events falling between 50 and 100 pN. The unbinding forces of CD63 on the cancerous exosomes were 70 6 15 pN, with 58% unbinding events in the range of 50100 pN, indicating the higher density of CD63 molecules on the cancerous exosomes. These studies not only provide a template to investigate the molecular behaviors of single proteins on native exosomes by AFM-based SMFS technique, but also reveal the changes of the exosome surface proteins during pathological processes, giving novel insights into the indicative role of exosomes in life activities at the singlemolecule level. However, it should be noted that the AFM-based SMFS investigation on exosomes is still a largely unexplored area [65] and more studies of the molecular interactions on native exosome surfaces with AFM-based SMFS will advance our understanding of exosome behaviors.

6.7 Summary AFM offers a multifunctional tool to characterize the structures and properties of individual native exosomes under aqueous conditions, including imaging the fine structures of exosomes (Fig. 6.3), analyzing the geometric features of exosomes adsorbed on the substrates (Fig. 6.4), quantitatively measuring Young’s modulus of exosomes (Fig. 6.5), simultaneous topographical and mechanical imaging to directly correlate exosome structures with their mechanical properties (Figs. 6.6 and

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6.7), and detecting the protein interactions on the surface of exosomes at single-molecule level (Fig. 6.8). Applications of AFM in the studies of exosomes promote our understanding of the behaviors of exosomes from the perspective of biophysics, which yield novel insights into the physiological/pathological processes. The established methodologies described in the chapter can be directly applied to other exosome systems, which will contribute to unveiling the underlying mechanisms regulating life activities and developing methods for the diagnosis and treatment of human diseases with clinical translational significance. Utilizing AFM to investigate the molecular interactions on the surface of exosomes remains poorly explored. Many biomolecules on the surface of exosomes (e.g., lectins, adhesion molecules, fibronectin, phosphatidylserine, and epidermal growth factor), and their interactions with corresponding receptors on the recipient cells have been identified as participants in the uptake of exosomes [66]. Detecting these molecular interactions is crucial for understanding the behaviors of exosomes at the single-molecule level. AFM is a powerful tool for detecting molecular interactions at the nanoscale in near-physiological environments (such as in various biofluids), which has contributed much to the field of mechanobiology [67]. Nevertheless, so far utilizing AFM to probe the molecular interactions on exosomes is surprisingly few. In addition to the traditional AFM-based SMFS assay, in recent years, researchers have broadly utilized multiparametric AFM imaging with biochemically sensitive tips to investigate the molecular interactions between viruses and cells [68], in which the viruses are covalently attached to the AFM tip and the virusconjugated probes are used to sense the interactions between individual viruses and individual host cells (readers are referred to Chapter 5 for more descriptions of applying AFM force spectroscopy techniques to detect viruscell interactions). Since the sizes of viruses are often similar to that of the exosomes, we can learn from the applications of detecting virus behaviors by AFM to probe the exosome behaviors. For example, the exosomes may be attached to the AFM tips via linker molecules, which can then be used to probe the interactions between exosomes and recipient cells in the multiparametric AFM imaging mode or in the conventional SMFS mode. Furthermore, the kinetic parameters of the molecular bonds can be obtained by AFM force spectroscopy experiments [69], which will particularly benefit revealing the regulatory role of molecular interactions in exosome and cell activities. Studies of applying AFM to investigate the cargoes of exosomes are still scarce. Current studies of detecting exosomes by AFM are commonly performed on the surface of exosomes, which cannot access the cargoes inside the exosomes, whereas the cargoes carried by exosomes play a crucial role in the biology, function, and biomedical applications of exosomes [2]. For the studies of viruses, AFM has been successfully

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used to visualize the internal genomes of virus particles after viral uncoating (shown in Fig. 5.3 of Chapter 5), inspiring us that we may use AFM to probe the biomolecules inside the exosomes after disintegrating the exosomes. For example, we may use AFM to investigate the DNA/RNA molecules encapsulated in the exosomes. Applications of AFM in characterizing DNA molecules are presented in Chapter 2, and the methods described in Chapter 2 can be directly used to probe the DNA/RNA molecules of exosomes. Detecting the cargoes derived from exosomes with AFM will potentially provide novel insights into the behaviors of exosomes and will complement traditional methods used for analyzing the cargoes of exosomes. There is still huge room for utilizing AFM to detect the exosomes in a liquid biopsy from clinical patients. Exosomes could reflect the altered physiological and pathological state of their parental cells, and analyzing the circulating exosomes and their derived cargoes have been a new frontier of liquid biopsy for noninvasive cancer early diagnosis and treatment [7072]. Researchers have isolated the exosomes from biofluids (e.g., blood plasma [38,39,47], saliva) [63,64] and used AFM to characterize the structural and mechanical properties of these exosomes. Besides, biochemical assays could also be performed on the exosomes to obtain the chemical properties of the exosomes, which are then correlated with the results obtained by AFM [51], facilitating comprehensively characterizing the properties of exosomes in the biofluids. However, a notable point is that the obtained results reflect the averaged behaviors of the ensemble exosomes from both normal cells and diseased cells in the biofluids, and thus the exact properties of exosomes secreted by diseased cells and their contributions to the ensemble results are unknown, which cause challenges to explore the detailed exosome-mediated mechanisms involved in the pathological changes. In order to examine the properties of exosomes released by diseased cells, we need to specifically recognize these exosomes and then collect them from the biofluids, which is still challenging. As an alternative way, researchers have investigated the exosomes released by cell lines cultured in vitro by AFM [52], in which the biogenesis of the exosomes is determined. Nevertheless, cells cultured in vitro cannot fully reflect the real situations in vivo, and thus the results of the exosomes from cell lines may also not faithfully reflect the real behaviors of the exosomes in the body. Taken together, AFM is a promising tool to characterize the structures and mechanical properties as well as the molecular interactions of single native exosomes under aqueous conditions with unprecedented spatial resolution. In the future, as AFM is utilized to investigate more exosome systems, particularly combined with other complementary techniques, we will see increasing insights into the regulatory role of exosomes in physiological and pathological processes.

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[60] M. Nawaz, M.I. Malik, H. Zhang, I.A. Hassan, J. Cao, Y. Zhou, et al., Proteomic analysis of exosome-like vesicles isolated from saliva of the tick haemaphysalis longicornis, Front. Cell. Infect. Microbiol. 10 (2020) 542319. [61] Y. Risha, Z. Minic, S.M. Ghobadloo, M.V. Berezovski, The proteomic analysis of breast cell line exosomes reveals disease patterns and potential biomarkers, Sci. Rep. 10 (1) (2020) 13572. [62] F.G. Kugeratski, K. Hodge, S. Lilla, K.M. McAndrews, X. Zhou, R.F. Hwang, et al., Quantitative proteomics identifies the core proteome of exosomes with syntenin-1 as the highest abundant protein and a putative universal biomarker, Nat. Cell Biol. 23 (6) (2021) 631641. [63] S. Sharma, H.I. Rasool, V. Palanisamy, C. Mathisen, M. Schmidt, D.T. Wong, et al., Structural-mechanical characterization of nanoparticle exosomes in human saliva, using correlative AFM, FESEM, and force spectroscopy, ACS Nano 4 (4) (2010) 19211926. [64] S. Sharma, B.M. Gillespie, V. Palamisamy, J.K. Gimzewski, Quantitative nanostructural and single-molecule force spectroscopy biomolecular analysis of human-salivaderived exosomes, Langmuir 27 (23) (2011) 1439414400. [65] S. Sharma, M. LeClaire, J.K. Gimzewski, Ascent of atomic force microscopy as a nanoanalytical tool for exosomes and other extracellular vesicles, Nanotechnology 29 (13) (2018) 132001. [66] A. Gonda, J. Kabagwira, G.N. Senthil, N.R. Wall, Internalization of exosomes through receptor-mediated endocytosis, Mol. Cancer Res. 17 (2) (2019) 337347. [67] M. Krieg, G. Flaschner, D. Alsteens, B.M. Gaub, W.H. Roos, G.J.L. Wuite, et al., Atomic force microscopy-based mechanobiology, Nat. Rev. Phys. 1 (1) (2019) 4157. [68] D.J. Muller, A.C. Dumitru, C. Lo Giudice, H.E. Gaub, P. Hinterdorfer, G. Hummer, et al., Atomic force microscopy-based force spectroscopy and multiparametric imaging of biomolecular and cellular systems, Chem. Rev. 121 (19) (2021) 1170111725. [69] A. Viljoen, M. Mathelie-Guinlet, A. Ray, N. Strohmeyer, Y.J. Oh, P. Hinterdorfer, et al., Force spectroscopy of single cells using atomic force microscopy, Nat. Rev. Meth. Prim. 1 (2021) 63. [70] S. Halvaei, S. Daryani, Z. Eslami-S, T. Samadi, N. Jafarbeik-Iravani, T.O. Bakhshayesh, et al., Exosomes in cancer liquid biopsy: a focus on breast cancer, Mol. Ther. Nucleic Acids 10 (2018) 131141. [71] Z. Gao, B. Pang, J. Li, N. Gao, T. Fan, Y. Li, Emerging role of exosomes in liquid biopsy for monitoring prostate cancer invasion and metastasis, Front. Cell Dev. Biol. 9 (2021) 679527. [72] D. Yu, Y. Li, M. Wang, J. Gu, W. Xu, H. Cai, et al., Exosomes as a new frontier of cancer liquid biopsy, Mol. Cancer 21 (1) (2022) 56.

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C H A P T E R

7 Nanoscale imaging and force probing of single microbial cells by atomic force microscopy A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/ 9780323953603

7.1 Background Microbial cells are closely related to human health and diseases. Humans are naturally colonized at birth with microorganisms that mainly inhabit the external and internal surfaces in the human body, including skin, oral cavity, conjunctiva, vagina and gastrointestinal tract [1,2]. The vast majority of these microorganisms live in our distal guts [3], and a recent study has shown that the mass of microbes produced in the body per day is at least 60 g (1 3 1013 cells) [4]. These microorganisms play an important role in human health. For example, the beneficial effects of gut bacteria on human health include supplying essential nutrients, synthesizing vitamin K, aiding in the digestion of cellulose, and promoting angiogenesis and enteric nerve function [5]. Live microorganisms that are thought to have beneficial effects on the host are called probiotics, whereas ingredients that stimulate the growth and/or function of beneficial microorganisms are called prebiotics [6]. The skin is a complex and dynamic ecosystem that is inhabited by many microorganisms, and studies have shown that these microorganisms can promote both innate and adaptive immunity to skin pathogens [7]. Nevertheless, microorganisms are also closely related to human diseases. The altered gut microbiota, owing to dietary shifts, antibiotic use, age or infection, has been shown to be associated with many diseases,

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such as inflammatory bowel disease (IBD), obesity, colorectal cancer, metabolic syndrome and atopy [8,9]. Urinary tract infections (UTIs) are among the most common bacterial infections acquired in the community and in hospitals, and Escherichia coli are the bacteria most frequently implicated in uncomplicated UTI and catheter-associated UTI [10]. Fungi are associated with a wide spectrum of diseases in humans, including respiratory allergy, skin diseases, recurrent vulvovaginal candidiasis, IBD, and invasive fungal disease (IFD) [11]. Notably, IFD is associated with unacceptably high mortality rates (more than 50%), but research into the pathophysiology of human fungal infections significantly lags behind that of diseases caused by other pathogens [12]. Particularly, the emergence of antibiotic resistance in bacteria is resulting in the challenge of recalcitrant infections [13], and it is estimated that the number of deaths caused by antimicrobial-resistant pathogens will exceed those due to cancer by 2050 [14], posing a major threat to human health. Researchers have presented the basic definitions and guidelines for research on antibiotic persistence, which will pave the way for better characterization of antibiotic persistence and for understanding its relevance to clinical outcomes [15]. Microorganisms can be divided into seven types, including algae, protozoa, slime molds, fungi, bacteria, archaea, and viruses [16]. In this chapter, the applications of AFM in characterizing the structures and properties of two types of microbial cells, bacteria and fungi, are represented. Bacteria are small prokaryotic cells, generally of the size of mitochondria (the length of bacteria is in the range of 0.210 μm, and the width of bacterial is in the range of 0.21.5 μm), and the shapes of bacteria can be cocci, rods, spiral, filamentous, or cubes [17]. In 1884 Christian Gram developed a staining procedure, which allowed classifying nearly all bacteria into two groups (one group retain Christian’s stain and is called Gram-positive bacteria, while the other group do not retain the stain and is called Gram-negative bacteria), and the basis for the Gram stain classification lies in the essential structural differences in the cell envelope of bacteria [18]. Gram-negative bacteria have two highly distinct membranes (outer membrane and inner membrane, respectively) that delimit an aqueous cellular compartment called the periplasm [19], as shown in Fig. 7.1A. The outer membrane plays an essential role in the activities of Gram-negative bacteria, mainly including serving as the location of a substantial fraction of environmental sensors, serving as an anchor point for adhesive organelles, serving as a platform for interactions with host immune systems as well as with neighboring bacterial cells, and acting as an important permeability barrier. By contrast, Gram-positive bacteria lack an outer membrane but have a much thicker peptidoglycan cell wall compared with that of Gram-negative bacteria [20], as shown in Fig. 7.1B. Besides, most Gram-positive bacteria possess other protective surface structures, Atomic Force Microscopy for Nanoscale Biophysics

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FIGURE 7.1 Cell surface structures of typical microbes. (A) Gram-negative bacteria. The cytoplasm of all bacterial cells is surrounded by an inner membrane composed of phospholipids and inner membrane proteins. In Gram-negative bacteria, the cell wall resides in the periplasm, an approximately 15-nm-thick aqueous compartment enclosed by the inner and outer membranes. The outer membrane is asymmetrical, composed of phospholipids in the inner leaflet and lipopolysaccharide (LPS) molecules along with outer membrane proteins (OMPs) such as the porin OmpA and lipoproteins such as Braun’s lipoprotein (Lpp), which links the outer membrane and peptidoglycan. (B) Gram-positive bacteria. Gram-positive bacteria have a single lipid membrane surrounded by a cell wall composed of a thick layer of peptidoglycan and lipoteichoic acid, which is anchored to the cell membrane by diacylglycerol. (C) Fungi. A single plasma membrane is also present in fungi, surrounded by a cell wall consisting of various layers of the polysaccharides chitin, β-glucan and mannan (in the form of mannoproteins). Source: (A) Reprinted with permission from J. Sun, S.T. Rutherford, T.J. Silhavy, K.C. Huang, Physical properties of the bacterial outer membrane, Nat. Rev. Microbiol. 20 (4) (2022) 236248. Copyright 2021 Springer Nature Limited. (B and C) Reprinted with permission from L. Brown, J.M. Wolf, R. Prados-Rosales, A. Casadevall, Through the wall: extracellular vesicles in Gram-positive bacteria, mycobacteria and fungi, Nat. Rev. Microbiol. 13 (10) (2015) 620630. Copyright 2015 Macmillan Publishers Limited.

including capsular polysaccharides, S-layer proteins, mycolic acids or combinations of these elements [21]. Fungi are eukaryotic, with a range of internal membrane systems, membrane-bound organelles, and a welldefined cell wall (as shown in Fig. 7.1C) composed of polysaccharides (glucan, mannan) and chitin [22]. Though fungi show considerable variations in size and form, fungi can be generally classified into three main groups, including molds (multicellular filamentous fungi), yeasts Atomic Force Microscopy for Nanoscale Biophysics

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(are predominantly unicellular and oval or round in shape), and dimorphic fungi (are capable of changing their growth to either a mycelial or yeast phase depending on the growth conditions) [22]. Since AFM is essentially a surface tool, the surface structures of typical microbial cells are summarized in Fig. 7.1, which are expected to facilitate understanding of the related contents in this chapter. Microbial cells are often small and have stiff cell surfaces, which facilitate detecting them by AFM. In fact, AFM has achieved unprecedented success in detecting the structures and properties as well as the molecular activities of single

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microbial cells in the past decades, significantly advancing our understanding of the behaviors of microorganisms from the perspective of mechanobiology (which is referred to as mechanomicrobiology) [23] and considerably yielding numerous novel insights into the underlying mechanisms guiding microbial pathogenicity.

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As with imaging other types of specimens by AFM, the prerequisite of imaging microbial cells by AFM is to immobilize microbial cells onto the substrates. Various methods have been developed to attach living microbial cells onto the substrates for AFM imaging [2426], mainly including electrostatic adsorption, porous filter membrane trapping, and fabrication of microstructured substrates. Most bacterial cells possess an overall negative charge at neutral pH due to the presence of peptidoglycan which is rich in carboxyl and amino groups [27]. Besides, the teichoic acids which contain phosphate-rich components also contribute to the negative charge of bacterial cell surfaces. Therefore substrates coated with positively charged biomolecules are able to adsorb the negatively charged microbial cells, and this method is called electrostatic adsorption (I in Fig. 7.2A). FIGURE 7.2 Typical methods to immobilize living microbial cells for atomic force microscopy (AFM) imaging. (A) Electrostatic adsorption. (I) Schematic illustration. Negatively charged cells are attached to the substrate coated with positively charged biomolecules. (II) AFM image of E. coli bacteria immobilized on the poly-L-lysine-coated substrate. AFM image was obtained in buffer solution. (B) Porous membrane trapping. (I) Schematic illustration. Cells are mechanically trapped in the pores of the filter membrane. (II) AFM height image of a living Saccharomyces carlsbergensis trapped in the porous membrane. (C) Silicon substrate with hole arrays fabricated by photolithography. (I) AFM height image of a microstructured silicon substrate. (II) AFM height image of a living S. aureus cell trapped in the silicon hole recorded in buffer solution. (D) Microstructured PDMS stamp trapping. (I) Schematic illustration. PDMS stamps with square patterns are fabricated from the silicon master, and living microbial cells are assembled into the squares of the PDMS stamp by convective and capillary deposition to form cell arrays. (II) Three-dimensional AFM height image of C. albicans cell array trapped by the PDMS stamp obtained in buffer solution. Source: (A) (I) Reprinted with permission from Y.F. Dufrene, Atomic force microscopy and chemical force microscopy of microbial cells, Nat. Protoc. 3 (7) (2008) 11321138. Copyright 2008 Nature Publishing Group. (II) Reprinted with permission from G. Benn, A.L.B. Pyne, M.G. Ryadnov, B.W. Hoogenboom, Imaging live bacteria at the nanoscale: comparison of immobilization strategies, Analyst 144 (23) (2019) 69446952. Copyright 2019 The Royal Society of Chemistry. (B) Reprinted with permission from Y.F. Dufrene, Atomic force microscopy and chemical force microscopy of microbial cells, Nat. Protoc. 3 (7) (2008) 11321138. Copyright 2008 Nature Publishing Group. (C) Reprinted with permission from L. Kailas, E.C. Ratcliffe, E.J. Hayhurst, M.G. Walker, S.J. Foster, J.K. Hobbs, Immobilizing live bacteria for AFM imaging of cellular processes, Ultramicroscopy 109 (7) (2009) 775780. Copyright 2009 Elsevier B.V. (D) Reprinted with permission from C. Formosa, F. Pillet, M. Schiavone, R.E. Duval, L. Ressier, E. Dague, Generation of living cell arrays for atomic force microscopy studies, Nat. Protoc. 10 (1) (2015) 199204. Copyright 2014 Nature America, Inc.

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Various positively charged biomolecules, including poly-L-lysine (II in Fig. 7.2A) [28], polyethylenimine [29], and gelatin [30], have been used to immobilize microbial cells, allowing reliable AFM imaging of living microbial cells in aqueous conditions. The substrate coating procedures of these three reagents (poly-L-lysine, polyethylenimine, gelatin) are similar to each other. Generally, a certain concentration of the reagents is coated on a substrate, after which the substrate is naturally dried. The cell suspension is then directly dropped onto the functionalized substrate and incubated for a certain time to establish firm adsorption between cells and the substrate. The specimen is then placed in a Petri dish containing an imaging solution for AFM imaging. The electrostatic adsorption method based on the chemical functionalization of the substrates is suited for nearly all types of cells. However, it should be noted that immobilizing microbial cells with these positively charged biomolecules could influence the behaviors of microbial cells such as cellular oscillations [31] and may denature cell surface molecules. Hence, strictly speaking, the immobilized cells are not in their native states. Besides, the biomolecules coated on the substrate may contaminate the AFM tip, which could result in artifacts. The second immobilization strategy is mechanically trapping single microbial cells with the use of commercially porous filter membranes. For doing so, a concentrated microbial cell suspension is directly sucked through a porous filter membrane whose pore size is slightly smaller than that of the microbial cells [24]. The cells can then be trapped in the pores of the filter membrane (I in Fig. 7.2B). Next, the porous filter membrane is transferred to a Petri dish containing imaging solution and gently agitated to remove cells that are not trapped in the pores of the filter membrane. Subsequently, the bottom side of the filter membrane is quickly dried by wipes, and the filter membrane is then attached to a hard substrate with adhesive tape. After placing the specimen in a Petri dish containing an imaging solution, AFM imaging is performed to find trapped cells. The porous membrane immobilization method is able to trap individual spherical microbial cells under aqueous conditions for AFM imaging, while minimizing the denaturation of the cellular surface molecules [32,33]. Fig. 7.2B(II) is an AFM image, which clearly shows a living yeast cell trapped in a pore of a filter membrane. The advantage of the porous membrane trapping method is that it does not require any chemical pretreatments on the cells, and thus the trapped cells are in their native states, which facilitates the interpretation of the experimental results. However, the limitation of this method is that it is generally suited for spherical microbes but not for rod-shaped microbes. The third immobilization method is based on the fabrication of microstructured substrates. With the use of photolithography technology, the arrays of holes can be formed on the silicon wafers (I in Fig. 7.2C) [25],

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which can then be used to immobilize microbial cells. A drop of microbial cell suspension is directly deposited onto the microstructured silicon substrate and allowed to settle for 2030 min, which gives the cells time to fill the holes on the substrate [34]. The cells trapped in the holes of the substrate can then be imaged by AFM in aqueous conditions (II in Fig. 7.2C). Based on the fabrication of microstructured silicon substrate, PDMS stamps can also be formed to immobilize microbial cells for AFM imaging. For doing so, the first step is generating a microstructured silicon master presenting the negative geometry desired for the PDMS stamps with the use of photolithography technology (the patterns of the silicon master are squares, and diverse geometrical parameters of the squares can be designed for immobilizing different types of microbial cells) (I in Fig. 7.2D), from which microstructured PDMS stamps can be replicated by molding [26]. The fabricated PDMS stamps are hydrophobic, and need to be made hydrophilic to trap microbial cells. Either treating the PDMS stamps with oxygen plasma or lectin concanavalin A (ConA) can make the PDMS stamps hydrophilic [35]. After that, the microbial cell suspension can be deposited on the PDMS stamps by convective/capillary assembly, during which a coverslip is utilized to drag a droplet of the cell suspension onto the PDMS stamps at a given translation speed for several times. The specimen is then placed in a Petri dish containing imaging solution for AFM imaging. Fig. 7.2D(II) is the result of using this method to immobilize living C. albicans for AFM imaging, clearly showing that each square of the PDMS stamp has a cell. The immobilization based on microstructured substrates enables fabricating microstructure patterns with any specific geometrical properties (such as size, depth) to immobilize microbial cells being detected and allows generating single-cell arrays for high-throughput AFM studies, which benefits improving the efficiency of AFM experiments. However, this method is also mainly suited for spherical microbes, and it requires substantial instrumentation for microfabrication.

7.3 Visualizing the nanostructures and their dynamics of living microbial cells by atomic force microscopy AFM is able to resolve the fine surface structures of single living microbial cells. The yeast S. cerevisiae is a single-celled organism capable of rapid division on a defined medium, and each cell reproduces by budding [36]. The wine and ale beer industries have been dominated by S. cerevisiae, which constitutes 64.8% of the alcoholic beverage market [37]. Based on the immobilization of porous filter membranes, AFM images of single living S. cerevisiae cells have been obtained, showing that the cell surface is very smooth [32,38] (I in Fig. 7.3A). In 2003

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FIGURE 7.3 Atomic force microscopy (AFM) allows imaging the detailed surface structures of individual living microbial cells under aqueous conditions. (A) AFM images of living fungi. (I) Three-dimensional AFM height image of a Saccharomyces cerevisiae yeast cell trapped in a porous membrane. (II) High-resolution AFM deflection image of the surface of Phanerochaete chrysosporium fungal spores immobilized by porous membrane. (B) AFM images of living Gram-positive bacteria. (I) High-pass filtered AFM image of a whole Staphylococcus aureus cell immobilized in microfabricated silicon holes. The blue arrowhead denotes the mesh area, and the while arrow denotes the ring area. The inset shows the unfiltered image of the same area. (II) Higher resolution AFM image of the ring area. The inset shows the raw data. (III) Higher resolution AFM image of the mesh area. The white arrowhead denotes a feature consistent with a single glycan chain, the green dotted arrows are examples of strand convergence, and the blue arrows denote multi-strand fibers. (C) AFM images of living Gram-negative bacteria. (I) AFM phase image of the local surface of Escherichia coli cell with patches denoted by dashed lines. (II) AFM height image of the same area. The white line is the section profile curve taken along the dashed line. The inset shows AFM height image of the whole Escherichia coli cell. (III) Successive AFM phase images of a same area show the dynamics of the patches. Source: (A) Reprinted with permission from Y.F. Dufrene, Using nanotechniques to explore microbial surfaces, Nat. Rev. Microbiol. 2 (6) (2004) 451460. Copyright 2004 Springer Nature. (B) Reprinted with permission from L. Pasquina-Lemonche, J. Burns, R.D. Turner, S. Kumar, R. Tank, N. Mullin, et al., The architecture of the Gram-positive bacterial cell wall, Nature 582 (7811) (2020) 294297. Copyright 2020 Springer Nature. (C) Reprinted with permission from G. Benn, I.V. Mikheyeva, P.G. Inns, J.C. Forster, N. Ojkic, C. Bortolini, et al., Phase separation in the outer membrane of Escherichia coli, Proc. Natl. Acad. Sci. USA 118 (44) (2021) e2112237118. Copyright 2021 National Academy of Sciences.

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Ahimou et al. [39] investigated the surface topography of single living S. cerevisiae cells by time-lapse AFM imaging based on the immobilization of porous membranes. The roughness of the smooth surface of regular S. cerevisiae cells calculated from the AFM height image is about 0.3 nm. Treating S. cerevisiae cells with protease results in the significant increase of cellular surface roughness, and large depressions surrounded by protruding edges (B50 nm in height) are formed on the cell, which are due to the protease-induced erosion of the mannoprotein outer layer of the cell (the cell surface structures of yeast cells are schematically shown in Fig. 7.1C). By contrast, AFM images of living Phanerochaete chrysosporium show that the surface of the P. chrysosporium spores are covered with a regular pattern of rodlets which are several hundred nanometers in length and have a periodicity of 10 nm [40] (II in Fig. 7.3A). In 2010 Andre et al. [41] used AFM to image the surface morphology of single living Lactococcus lactis cells which are Grampositive bacteria. The experimental results show that the cell surface is quite smooth when AFM images are obtained at small scanning forces (B250 pN). Ring-like structures significantly appear when AFM images are recorded at large scanning forces (B5 nN), which reflect the 25-nmwide peptidoglycan periodic bands of the L. lactis cell wall. In 2020 Pasquina-Lemonche [42] revealed the surface architecture of the living Gram-positive bacterial cell wall by AFM, as shown in Fig. 7.3B. Based on the immobilization of microfabricated silicon holes, AFM images of single living Staphylococcus aureus cells were obtained. Large-size scanning of the entire cell clearly shows two types of structures on the surface of S. aureus cells, which are disordered mesh and ordered ring structures, respectively (I in Fig. 7.3B). Small-size scanning of the ring area shows that the ring-like structures are composed of radially corrugated groups of circumferentially oriented individual strands (II in Fig. 7.3B), and AFM imaging of the disordered mesh area shows the diverse assembly behaviors of the peptidoglycan fibrils (III in Fig. 7.3B). In 2021 Benn et al. [43] impressively imaged the detailed surface structures of single living Gram-negative bacterial cell walls by AFM with single-molecule resolution, as shown in Fig. 7.3C. Since Gram-negative bacteria have outer membranes on their surface (Fig. 7.1A), imaging living Gram-negative bacterial by AFM yields the topographical structures of the outer membrane of Gram-negative bacteria. AFM images of E. coli cells were obtained at tapping mode. The experimental results show that, in contrast to the height image, the simultaneously obtained phase image allows better seeing molecular-scale details of the outer membrane, remarkably revealing that the surface of E. coli cells contains a dense packing of pores which are attributed to the trimeric porins on the outer membrane. Besides, AFM images show that, on the cell surface, there are also sparse, pore-free, and smooth patches, which protrude by approximately 0.51 nm above the pores (I and II in Fig. 7.3C). Atomic Force Microscopy for Nanoscale Biophysics

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Time-lapse AFM imaging of the bacterial surface shows that these patches behave as liquid phases in the outer membrane: merging, growing, and splitting apart over long time periods but maintaining their approximate lateral positions at the bacterial surface (III in Fig. 7.3C). Overall, these studies distinctly show the exciting capabilities of AFM in .

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unveiling the nanostructures on the surface of single living microbial cells, which provide unique insights into the surface structures and configurations of microbial cells. With the use of AFM, the detailed structural dynamics taking place during the activities of single living microbial cells can be revealed. In 2007 Plomp et al. [44] utilized AFM to observe the nanoscale cell wall changes during the germination of single Bacillus atrophaeus spores under native conditions, as shown in Fig. 7.4A. For doing so, the bacterial spores were immobilized, and AFM images were obtained in the germinant solution at 37 C. Before germination, the surface of B. atrophaeus spores was composed of a crystalline rodlet array (I in Fig. 7.4A). After the addition of the germinant solution, significant morphological changes on the surface of B. atrophaeus spores took place. At the initial stage of bacterial germination, 2- to 3-nm-wide pits emerged in the rodlet layer of cells (denoted by the arrows in Fig. 7.4AII). These pits then formed fissures which were oriented perpendicular to the rodlet layer direction (III and IV in Fig. 7.4A). As the germination progressed, the disassembly of the rodlet layer was remarkably observed (V and VI in Fig. 7.4A). Disaggregation of the rodlet layer caused the emergence of banded remnants, and these banded remnants were further disrupted into nanofibrils which were also perpendicular to the rodlet direction. Subsequently, small spore coat apertures (60- to 70-nm-deep) were clearly observed (VIIIX in Fig. 7.4A) from the AFM images, which allowed the emergence of vegetative cells. In 2008 Dague et al. [45] visualized the cell surface dynamics of Aspergillus fumigatus conidia during germination by AFM based on porous membrane immobilization, as

FIGURE 7.4 Visualizing the surface structural dynamics of single living microbial spores during the process of germination by atomic force microscopy (AFM). (A) AFM images of single germinating Bacillus atrophaeus spores. (I) The intact rodlet layer of the bacterial spores before germination. (IIIV) AFM successive height images tracking the initial changes of the rodlet layer after 13 min (II), 113 min (III), and 295 min (IV) of exposure to germination solution. (V and VI) AFM height images of the same local area on cell surface showing the rodlet disassembly. Time between images was 45 min. In the circled regions, banded remnants of rodlet structure (V) disassemble into thinner fibrous structures (VI). (VIIIX) Series of AFM height images showing apertures in the rodlet layer (denoted by the arrows in VII) that gradually enlarged to erode the entire spore coat (VIII and IX). (B) High-resolution successive AFM images of the local areas on the surface of single germinating Aspergillus fumigatus spores recorded at different times after the germination of spores. The insets are the corresponding AFM height images of the whole cell. Source: (A) Reprinted with permission from M. Plomp, T.J. Leighton, K.E. Wheeler, H.D. Hill, A. J. Malkin, In vitro high-resolution structural dynamics of single germinating bacterial spores, Proc. Natl. Acad. Sci. USA 104 (23) (2007) 96449649. Copyright 2007 National Academy of Sciences. (B) Reprinted with permission from E. Dague, D. Alsteens, J.P. Latge, Y.F. Dufrene, Highresolution cell surface dynamics of germinating Aspergillus fumigatus conidia, Biophys. J. 94 (2) (2008) 656660. Copyright 2008 The Biophysical Society.

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shown in Fig. 7.4B. AFM images were obtained in culture medium at 37 C. Time-lapse AFM imaging of the whole cell clearly showed the swelling, growing, and protruding of the spore trapped in the pore membrane during the process of germination (the insets in Fig. 7.4B). Small-size scanning of the local area on single A. fumigatus spores remarkably revealed the ultrastructural changes on the cellular surface during germination. At the initial stage (060 min), the spore surface was covered with a layer of crystalline rodlet array. After 2 h germination, significant changes in cell surface structures took place and the rodlet layer changed into a layer of amorphous material. Subsequent experiments of measuring cellular adhesive properties by AFM confirmed that the rodlet layer structure was uniformly hydrophobic, whereas the amorphous material formed during germination was highly hydrophilic, correlating cellular structural changes with cellular adhesive properties. These studies provide direct evidence of the detailed structural dynamics on the surface of individual germinating microbial spores, significantly benefiting understanding of the germination process of microbial cells. High-speed AFM allows capturing the real-time structural dynamics of single living microbial cells. In 2010 Fantner et al. [46] visualized the kinetics of antimicrobial peptide activity on single living E. coli bacterial cells by high-speed AFM, as shown in Fig. 7.5A. E. coli cells were immobilized on poly-L-lysine-coated substrates for AFM imaging. AFM images were obtained every 13 s upon the addition of antimicrobial peptide into the imaging solution, clearly showing that the bacterial surface changed from smooth to corrugated. Besides, the heterogeneity in the cellular responses to the antimicrobial peptide was observed. The bacterium 1 immediately started structural changing upon the addition of the peptide, while bacterium 2 started to change after about 80 s of peptide stimulation (Fig. 7.5A). Transmission electron microscopy (TEM) and super-resolution optical microscopy have been commonly used to investigate the effects of antimicrobial peptides on individual bacterial cells [47]. However, TEM cannot observe living microbial cells, and super-resolution microscopy is limited to spatial resolution. In contrast, high-speed AFM is able to capture the rapid changes of the fine structures on the surface of single living microbial cells in response to antimicrobial peptides with an unprecedented spatiotemporal resolution, which enables uncovering the intermediates of the killing effects of antimicrobial peptides to better understand the actions of antimicrobial drugs. In 2012 Yamashita et al. [48] observed the molecular dynamics on the surface of single living Magnetospirillum magneticum bacterial cells by high-speed AFM, as shown in Fig. 7.5B. Cells were immobilized onto the mica by poly-L-lysine-based electrostatic adsorption and highspeed AFM images were obtained in liquid medium. AFM images

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FIGURE 7.5 Visualizing structural dynamics on the surface of single living bacterial cells by high-speed AFM. (A) Successive high-speed AFM images showing the morphological changes of two Escherichia coli cells in response to antimicrobial peptide. (B) Molecular dynamics on the surface of a Magnetospirillum magneticum cell. (I) AFM image of cell surface at a range of 80 3 80 nm2. (II) AFM image with trajectories of four pore structures. The trajectories were drawn by tracing the movement of each pore. (III) Total trajectories of the two-dimensional diffusion for four pore structures. Source: (A) Reprinted with permission from G.E. Fantner, R.J. Barbero, D.S. Gray, A.M. Belcher, Kinetics of antimicrobial peptide activity measured on individual bacterial cells using high-speed atomic force microscopy, Nat. Nanotechnol. 5 (4) (2010) 280285. Copyright 2010 Macmillan Publishers Limited. (B) Reprinted with permission from H. Yamashita, A. Taoka, T. Uchihashi, T. Asano, T. Ando, Y. Fukumori, Single-molecule imaging on living bacterial cell surface by high-speed AFM, J. Mol. Biol. 422 (2) (2012) 300309. Copyright 2012 Elsevier Ltd.

clearly show the porous structures on the surface of M. magneticum cells. Besides, many particles were observed on the rims of the pore structures (denoted by the arrows in Fig. 7.5BI). The results revealed that these particles diffused rapidly on the cell surface, making it difficult to capture their movements. However, the motional dynamics of the pores on the cell surface could be captured by high-speed AFM successive imaging, showing that the pore structures exhibited random movements on the living cell surface (II and III in Fig. 7.5B). The experimental results demonstrate that high-speed AFM is able to visualize the structural dynamics on single living microbial cells with a molecular resolution, which is particularly meaningful for understanding the living molecular activities taking place on the cell surface.

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7.4 Measuring the mechanical properties of single living microbial cells by atomic force microscopy With the use of AFM indentation assay, the mechanical properties of single living microbial cells can be measured. In recent years, it is increasingly apparent in the communities of microbiology that mechanics play a significant role in the biology of microbial cells, and numerous studies have revealed that bacteria are attuned to mechanical forces and can exploit mechanics to drive adaptive behavior [49]. The study of bacterial mechanics may uncover roles of cell mechanics linked to their cellular function and applications in the infection of eukaryotic hosts, which potentially benefits understanding the problem of widespread drug resistance of bacteria to antibiotics and uncovering new therapeutic targets [50]. AFM provides a powerful tool to characterize the mechanical properties of single living microbial cells. Readers are referred to as Chapter 1 for detailed descriptions of measuring cellular mechanics by AFM indentation assay. Briefly, the AFM tip is positioned on the surface of a living microbial cell under the guidance of optical microscopy/AFM topographical imaging to perform approach-retract cycles in the vertical direction to record force curves. Microbial cells are often small, making it difficult to exactly place the AFM tip on the specific local areas on the cell surface under the guidance of optical microscopy. After obtaining the AFM topographical images of the fine structures of target microbial cells, the AFM tip can be easily moved to the specified locations on the cell surface. By analyzing the force curves acquired on microbial cells, the mechanical properties of the microbial cells can be obtained. Notably, the force curve obtained on microbial cells contains two regimes, including a nonlinear region and a linear region, which reflect the property of the cell wall to deform upon compression under the low force exerted by the AFM probe and the turgor pressure of the cell under the high force exerted by AFM probe, respectively [51,52]. Analyzing the nonlinear part of the force curve with the HertzSneddon model gives Young’s modulus of the cell, and fitting the linear region part of the force curve with Hooke’s law gives the stiffness of the cell [29]. It should be noted that stiffness is a pseudomaterial property of structures because it depends on the geometry of the structures, whereas Young’s modulus is independent of the geometry of the structures [53]. Applications of AFM indentation assay have yielded novel insights into the biological activities of individual microbial cells. In 2003 Touhami et al. [54] investigated the heterogeneous mechanical properties on the different surface areas of single yeast cells by AFM, as shown in Fig. 7.6A. Single living S. cerevisiae cells were immobilized by a

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FIGURE 7.6 Measuring the mechanical properties of single living microbial cells by atomic force microscopy (AFM) indentation assay. (A) Mechanics of single living yeast cells. (I) Three-dimensional AFM height image of a single Saccharomyces cerevisiae cell trapped in a porous membrane, clearly showing a circular bud scar left after detachment of the daughter cell. AFM image was obtained in aqueous solution. (II and IV) Typical force curves obtained on the bud scar (II) and on the surrounding mother cell surface (IV) of the yeast cell, respectively. (III and V) Typical indentation curves converted from the force curves obtained on bud scar (III) and surrounding mother cell surface (V), respectively. The indentation curves were fitted by HertzSneddon model to give the cellular Young’s modulus. (B) Mechanics of single living Gram-negative cells. (I) Typical force curves obtained on living Escherichia coli cells after the treatment of different concentrations of EDTA. (II) Cell stiffness changes versus time after the stimulus of EDTA. (III) Schematic illustration of microfluidics-based bending assay of a single cell. Source: (A) Reprinted with permission from A. Touhami, B. Nysten, Y.F. Dufrene, Nanoscale mapping of the elasticity of microbial cells by atomic force microscopy, Langmuir 19 (11) (2003) 45394543. Copyright 2003 American Chemical Society. (B) Reprinted with permission from E.R. Rojas, G. Billings, P.D. Odermatt, G.K. Auer, L. Zhu, A. Miguel, et al., The outer membrane is an essential load-bearing element in Gram-negative bacteria, Nature 559 (7715) (2018) 617621. Copyright 2018 Springer Nature.

porous membrane, and Fig. 7.6A(I) clearly shows the AFM image of a yeast cell with a bud scar trapped in the porous membrane (I in Fig. 7.6A). Under the guidance of the AFM image of the yeast cell, the AFM tip was moved to the bud scar area and the surrounding cell surface area to record force curves, respectively. The theoretical fitting

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results (II-V in Fig. 7.6A) distinctly show that the bud scar (6.1 6 2.4 MPa) is 10 times stiffer than the surrounding cell wall (0.6 6 0.4 MPa), which reveals the regions of different elasticity at the surface of single microbial cells and is consistent with the traditional studies of the components of the cell surface. Chitin is usually not found in the cell wall, but it accumulates in the very localized region of the cell wall involved in the budding [55], and thus the accumulation of chitin may cause the stiffening of bud scar, revealing the correlation between cell structures and cell mechanics. In 2008 Francius et al. [56] investigated the changes in mechanical properties of individual bacterial cells during cell wall digestion by AFM. Based on the immobilization of the porous membrane, successive AFM imaging was performed on single living S. aureus cells after the addition of lysostaphin. AFM topographical images clearly show the formation of the lysostaphin-induced osmotically fragile cell due to peptidoglycan hydrolysis. The AFM indentation assay results show a significant decrease in both bacterial stiffness and Young’s modulus after the treatment of lysostaphin, demonstrating that structural changes are correlated with major differences in cell wall mechanical properties. In 2009 Das et al. [57] investigated the structural and mechanical changes of Termitomyces clypeatus cell during different growth stages (logarithmic phase, stationary phase, and death phase) by AFM, showing that the changes of the surface ultrastructures during the growth processes are correlated to the corresponding changes in the stiffness and Young’s modulus of the cell wall. In 2018 Rojas et al. [58] showed that the mechanical properties of E. coli cells are largely due to the outer membrane, as shown in Fig. 7.6B. Living bacterial cells were immobilized onto the glass slides by poly-Llysine-based electrostatic adsorption. AFM indentation assays were performed on single cells after the addition of EDTA. EDTA could chelate magnesium, which causes the release of LPS (Fig. 7.1A) from the outer membrane of Gram-negative bacterial cells. The AFM experimental results show that treating cells with EDTA significantly decreased cell stiffness in a concentration-dependent manner (I and II in Fig. 7.6B). Besides, the deformable capability of bacterial cells was measured by a microfluidics-based assay (III in Fig. 7.6B), where a perpendicular fluid force was applied to single filamentous cells and the deflection of the cell was recorded to obtain the bending rigidity of the cell, showing that untreated cells deformed less than did EDTA-treated cells. The experimental results of microfluidics-based bending rigidity measurement were consistent with that of the AFM indentation assay, and independently demonstrated the contribution of LPS to the stiffness of the outer membrane of Gram-negative bacterial cells. In 2020 Odermatt et al. [59] revealed how mechanical forces interact with molecular mechanisms to control bacterial cell division by using a combination of AFM imaging,

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nanomechanical mapping and nanomanipulation. The results show that the emergence of a precleaved furrow in the middle of the cell is accompanied by increasing mechanical stress before rapid cell cleavage. Inhibiting cell wall hydrolysis delays cellular cleavage, and applying mechanical forces can induce instantaneous and premature cleavage. Overall, these studies demonstrate the great potential of AFM to characterize the mechanical properties of single living microbial cells and their unique dynamics in the biological processes of microbes, which will benefit answering a number of important questions in the emerging field of mechanomicrobiology [60].

7.5 Single-molecule force spectroscopy and single-cell force spectroscopy of microbial adhesion The forces involved in the adhesion of microbial cells have been widely investigated by AFM-based single-molecule force spectroscopy (SMFS). Microbes have the ability to form biofilms, which are complex, heterogeneous, multicellular communities that adhere to nearly all natural and artificial surfaces [61,62]. Microbial cells in biofilms live in a self-produced matrix known as a hydrated extracellular polymeric substance (EPS) [63]. The EPS provides the mechanical stability of biofilms, mediates their adhesion to surfaces and forms a cohesive, three-dimensional polymer network that interconnects and transiently immobilizes biofilm cells [63]. The biofilm formed on implant surfaces shelters the bacteria, encourages the persistence of infection, and eludes the host defenses as well as biocides and antibiotic chemotherapies, posing a great burden to medical device-associated infections [64]. The formation of biofilms begins with the attachment of individual microbial cells to the surface, and thus unveiling the underlying mechanisms guiding the adhesion of microbial cells to surfaces is critical not only in microbiology, but also in medicine and biotechnology [65]. With the use of AFM-based SMFS techniques, single adhesion molecules on microbial cells can be detected. For doing so, ligands that can bind to the specific adhesion molecules are conjugated to the surface of the AFM tip via linker molecules, which is called tip functionalization. The tips carrying ligands are then controlled to perform force spectroscopy assays to record force curves. Readers are referred to as Chapter 1 for more descriptions of SMFS. A notable point is the analysis of the recorded force curves. Fig. 7.7A shows a typical force curve with a specific unbinding event obtained during SMFS experiments [66], from which two important parameters reflecting the unbinding of individual adhesion-ligand molecular pairs can be obtained, including adhesion force (determined as the force difference between the minimum of the

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FIGURE 7.7 Sensing individual biomolecules on the microbial cell surface by atomic force microscopy (AFM)-based SMFS assay. (A) A typical force curve. The unbinding force is determined by the force difference between the rupture point and the baseline (red double-headed arrow), the unbinding length by the distance between the contact and the rupture points (blue double-headed arrow). From the thermal noise, the standard deviation of the unbinding force is calculated (yellow double-headed arrow). (B) Formation and propagation of Als5p nanodomains. (I) AFM height images of cells. (II) Adhesion force maps (map 1) recorded on a given target area of the native cell (cells were never subjected to force). Blue and red pixels correspond to forces smaller and larger than 150 pN. (III) Second adhesion force maps recorded on the same target area (map 1’). (IV) Adhesion force maps recorded on remote areas (map 2) localized several hundred nanometers away from each other. (C) Schematic illustration of force-induced formation and propagation of Als5p protein clusters. SMFS, Single-molecule force spectroscopy. Source: (A) Reprinted with permission from A. Viljoen, M. Mathelie-Guinlet, A. Ray, N. Strohmeyer, Y. J. Oh, P. Hinterdorfer, et al., Force spectroscopy of single cells using atomic force microscopy, Nat. Rev. Methods Prim. 1 (2021) 63. Copyright 2021 Springer Nature. (B and C) Reprinted with permission from D. Alsteens, M.C. Garcia, P.N. Lipke, Y.F. Dufrene, Force-induced formation and propagation of adhesion nanodomains in living fungal cells, Proc. Natl. Acad. Sci. USA 107 (48) (2010) 2074420749. Copyright 2010 National Academy of Sciences.

rupture curve and the baseline, denoted by the red double-headed arrow) and rupture length (determined as the distance between the rupture point and the contact point, denoted by the blue double-headed arrow). In 2010 Alsteens et al. [67] revealed the force-induced formation and propagation of adhesion nanodomains in living fungal cells by AFM-based SMFS technique, as shown in Fig. 7.7B and C. The Als5p proteins on the S. cerevisiae cells were tagged with a V5 epitope, and AFM tips were functionalized with anti-V5 antibodies. Cells were immobilized by porous filter membrane (I in Fig. 7.7B), and AFM Atomic Force Microscopy for Nanoscale Biophysics

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functionalized tips were used to obtain arrays of force curves at the local areas (32 3 32 force curves on 1 3 1 μm2 areas) on the cell surface. After calculating the adhesion force of each force curve, an adhesion force map was generated. One can clearly see the evenly distributed Als5p proteins in the adhesion force maps obtained from cells on which force was never applied (II in Fig. 7.7B). Recording second force maps on the same areas shows the clustering of proteins (III in Fig. 7.7B), and force maps obtained on remote areas of the cells also exhibit protein clusters (IV in Fig. 7.7B), revealing that locally applying mechanical stimuli on living yeast cells triggers the formation and propagation of Als5p adhesion nanodomains (Fig. 7.7C). Other biomolecules and structures of microbial cells have also been probed by AFM-based SMFS assay, including heparin-binding haemagglutinin adhesin (HBHA) [68], biofilm adhesin LapA [69], type IV pili [70], and so on, providing novel insights into the adhesive behaviors of microbial cells. AFM-based single-cell force spectroscopy (SCFS) allows quantifying the adhesive behaviors of individual microbes. In 2013 Beaussart et al. [71] presented a versatile platform for reliable SCFS in microbiology, which combines the use of colloidal probe cantilevers and a bioinspired polydopamine wet adhesive, as shown in Fig. 7.8. The detailed protocol of this method is available [72]. The first step (Fig. 7.8A) is to prepare the colloidal probe, in which a microsphere is glued to the AFM cantilever by AFM micromanipulation under the guidance of optical microscopy. The colloidal probe is then immersed in a 10 mM TrisHCl buffer solution (pH 8.5) containing 4 mg/mL dopamine hydrochloride for 1 h to coat the microsphere with polydopamine. The polydopamine-coated colloidal probe is then controlled to contact with an individual microbial cell to attach the cell to the microsphere of the probe, and the prepared single-cell probe can then be used for SCFS assay. Fluorescent microscopy can be used to check the position and vitality of the cell on the probe, showing that single bacterial cells attached to the probes were alive after 60 min measurements (Fig. 7.8B) and thus demonstrating the biocompatibility of the single-cell probe preparation method. As a proof of concept, the single-cell probe was utilized to obtain force curves on substrates coated with ConA (Fig. 7.8C). More molecular unbinding events between cells and substrates were observed when increasing the contact time to 1 s, and the specificity of the molecular interactions was confirmed by blocking experiments. Notably, for yeast cells which are spherical themselves, attaching a microsphere to the AFM cantilever is unnecessary and the other steps are the same as described above. With this method for microbial SCFS, the forces involved in the various adhesive processes of microbial cells have been revealed. In 2015 El-Kirat-Chatel et al. [73] demonstrated the Epa adhesion protein-mediated adhesion of Candida glabrata yeast cells to hydrophobic surfaces. Tipless AFM cantilevers were coated with Atomic Force Microscopy for Nanoscale Biophysics

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FIGURE 7.8 Quantifying the adhesive interactions of individual living microbial cells by atomic force microscopy (AFM)-based single-cell force spectroscopy assay. (A) Singlebacterial cell force spectroscopy, which uses colloidal probe cantilevers combined with polydopamine polymers, contains three steps (attaching a bead to the cantilever to prepare a colloidal probe, attaching single cell to the bead, and force spectroscopy experiments using the single-cell probe). (B) Fluorescent images of bacterial cells on the bead with the use of LIVE/DEAD stain, which were obtained immediately (I) or after 60 min of force measurements (II). (C) Obtain force curves on lectin surfaces with the use of a singlebacterial cell probe. (I and II) Adhesion force (I) and rupture length histograms (II) measured with a contact time of 1 s. The red line on the top curve is a theoretical fitting line by the extended freely jointed chain model. (III and IV) Adhesion force (III) and rupture length histograms (IV) obtained after the addition of blockers. Source: Reprinted with permission from A. Beaussart, S. El-Kirat-Chatel, P. Herman, D. Alsteens, J. Mahillon, P. Hols, et al., Single-cell force spectroscopy of probiotic bacteria, Biophys. J. 104 (9) (2013) 18861892. Copyright 2013 The Biophysical Society.

polydopamine to adsorb single C. glabrata cells, and the single yeast probe was then used to perform force spectroscopy on hydrophobic and hydrophilic substrates, respectively. The results show that there were strong adhesive interactions between yeast cells and hydrophobic substrates, whereas the adhesion between yeast cells and hydrophilic surfaces was quite weak. Besides, yeast cells with impaired expression of Epa proteins exhibited adhesion forces that were much smaller, less frequent and with much shorter extension, compared to wild-type yeast cells, evidencing that hydrophobic interactions of C. glabrata cells were mediated by Epa proteins. Also in 2015, Sullan et al. [74] showed the P1 adhesin-mediated attachment of Streptococcus mutans (a Gram-positive oral bacterium) cells to extracellular matrix proteins (fibronectin and collagen) and hydrophobic surfaces, providing a molecular basis for the multifunctional adhesion properties of C. glabrata cells. In 2018 Prystopiuk et al. [75] investigated the mechanical forces guiding the Atomic Force Microscopy for Nanoscale Biophysics

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S. aureus cellular invasion, showing that the fibronectin (Fn)-binding proteins (FnBPA) mediate bacterial adhesion to soluble fibronectin via strong forces (B1500 pN) and the FnBPA-Fn complex further binds to α5β1 integrins with a strength much higher than that of the classical Fn-integrin bond. Besides, the results reveal that the Fn-dependent adhesion between S. aureus and endothelial cells strengthens with time, offering a molecular foundation for the FnBPA-mediated invasion of S. aureus to host cells. In 2019 the same group investigated the mechanical stability of the FnBPA-mediated binding between S. aureus and endothelial cells [76], and the results show that adhesion forces between single bacteria and integrins are strongly inhibited by the RGD peptide, identifying a potential therapeutic target against S. aureus infections. More recently, in 2021, Mignolet et al. [77] investigated the unique adhesion properties of the Caulobacter type IVc pilus nanomachine and the results reveal that the unipolar Tad pilus exhibits three adhesive behaviors when being pulled away from a hydrophobic surface, which is helpful to better understand the structure-function relationship of bacterial pilus nanomachines.

7.6 Multiparametric atomic force microscopy imaging of single living microbial cells PFT-based multiparametric AFM imaging allows imaging the structures of a single living microbial cell while simultaneously visualizing various mechanical properties of the cell. For the principles of PFTbased multiparametric AFM imaging, readers are referred to as Chapter 1. Conventional AFM indentation and force spectroscopy assays as described above require the operator to collect thousands of force curves on cells, which is often labor-intensive to obtain results with statistical significance. With the use of PFT-based multiparametric AFM imaging, the mechanical properties maps of the cells can be generated simultaneously with the topography of the cells, which significantly helps to qualitatively observe the mechanical changes of cells. In 2015 Dover et al. [78] applied multiparametric AFM imaging to investigate the nanoscale surface architecture and mechanical properties of living Streptococcus cells in different medium osmolarity. A new net-like arrangement of cell-wall peptidoglycan was revealed, which stretched and stiffened in the hypotonic medium. Besides, the results show that cell aging (cells were grown in stationary cultures) did not alter the elasticity of the cell wall but caused changes in cell surface structures. In 2016 Formosa-Dague et al. [79] investigated the zinc-dependent activation of intercellular adhesion of S. aureus cells with the use of multiparametric AFM imaging, as shown in Fig. 7.9A. SasG is a type of cell-wall-anchored protein which mediates cell-cell adhesion. In this Atomic Force Microscopy for Nanoscale Biophysics

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FIGURE 7.9 Multiparametric atomic force microscopy (AFM) imaging of individual living microbial cells. (A) Multiparametric AFM imaging revealing zinc-dependent intercellular adhesion via SasG. AFM topographical images of cells were obtained simultaneously with cellular mechanical images (elasticity, adhesion). (I) Results of two dividing S. aureus cells expressing SasG in TBS buffer imaged successively in the same conditions following the addition of 1 mM ZnCl2, of 1 mM ZnCl2 then 1 mM of EDTA, and following further addition of 1 mM of ZnCl2. (II) Results of control experiments using S. aureus cells without SasG in TBS buffer with or without 1 mM ZnCl2. (B) Multiparametric AFM imaging revealing mechanical cues in the formation of bacterial biofilms. (I) Cells cultured in conditions favoring the production of FnBP. (II) Cells lacking PIA. (III) Cells cultured in conditions favoring the production of PIA. Source: (A) Reprinted with permission from C. Formosa-Dague, P. Speziale, T.J. Foster, J.A. Geoghegan, Y.F. Dufrene, Zinc-dependent mechanical properties of Staphylococcus aureus biofilm-forming surface protein SasG, Proc. Natl. Acad. Sci. USA 113 (2) (2016) 410415. Copyright 2016 National Academy of Sciences. (B) Reprinted with permission from C. Formosa-Dague, C. Feuillie, A. Beaussart, S. Derclaye, S. Kucharikova, I. Lasa, et al., Sticky matrix: adhesion mechanism of the staphylococcal polysaccharide intercellular adhesin, ACS Nano 10 (3) (2016) 34433452. Copyright 2016 American Chemical Society.

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study, S. aureus cells were engineered to express or do not express SasG. First, multiparametric AFM images (topography, Young’s modulus, adhesion force) of the same living bacteria expressing SasG were successively obtained in the same Tris buffer saline (TBS) after the addition of different stimuli (I in Fig. 7.9A), which directly correlate cell structures with cell mechanics. One can clearly see that cells become significantly smoother, stiffer and stickier in the presence of zinc. Next, multiparametric AFM images of living bacteria which did not express SasG were obtained (II in Fig. 7.9A), showing that the addition of zinc did not cause significant changes in bacterial structures and mechanics on the whole. Further, the addition of Ca21 also did not alter the structural and mechanical properties of cells. The experimental results directly and vividly show the zinc-dependent intercellular adhesion via SasG. In 2016 the same group [80] investigated the adhesion mechanisms of bacterial biofilms using multiparametric AFM imaging, as shown in Fig. 7.9B. Polysaccharide intercellular adhesin (PIA), an important component of the EPS of staphylococcal biofilms, plays a fundamental function in mediating intercellular adhesion of bacterial cells for bacterial aggregation [81]. From the multiparametric AFM images of the cells grown in conditions favoring the production of PIA (III in Fig. 7.9B), one can see the PIA matrix surrounding the bacterial cell (denoted by the M). The PIA matrix was quite soft and sticky, which was confirmed by the quantitative measurements of obtaining force curves on native cells and on centrifuged cells (for these cells, the PIA matrix was removed by centrifugation), respectively. Cells lacking PIA (II in Fig. 7.9) and cells grown in conditions favoring the production of FnBP (I in Fig. 7.9B) were then probed, showing that cells exhibited stiff properties. Besides, the adhesion of cells lacking PIA was very weak. The study shows that PIA endows bacterial cells with a soft and sticky surface. In 2020 Liu et al. [82] investigated the correlation between bacterial mechanics and bacterial antibiotic resistance with the use of multiparametric AFM imaging. In the study, 22 clinical isolates of Salmonella, E. coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae, were collected. First, the antimicrobial resistance of these isolates was confirmed by biochemical assays including minimum inhibitory concentration (MIC) and whole-genome sequencing, based on which the isolates were divided into two categories including β-lactam-resistant (BLR) bacteria and β-lactam-susceptible (BLS) bacteria. Next, for each isolate, living cells were immobilized to the poly-L-lysine-coated substrate and imaged at PFT mode to simultaneously obtain the structure image and Young’s modulus map of cells. The experimental results distinctly show that BLR bacteria were about 10 times softer than BLS bacteria, indicating that the acquired antibiotic resistance was accompanied by mechanical changes in cells. Overall, these studies remarkably show the

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indicative role of microbial mechanics in the diverse biological processes of microbes at the single-cell level and also demonstrate the great potential of multiparametric AFM imaging in visualizing the mechanical properties of single living microbial cells.

7.7 Atomic force microscopy cantilever as a nanomechanical sensor for monitoring microbial activities The AFM cantilever can serve as a highly sensitive nanomechanical sensor for monitoring microbial activities. In 2013 Longo et al. [83] realized the rapid detection of bacterial resistance to antibiotics using AFM cantilevers as nanomechanical sensors, as shown in Fig. 7.10A. For doing so, the AFM cantilever was treated with APTES to provide an adequate immobilization of bacteria on the cantilever without remarkably influencing cellular metabolic activities. After inserting the AFM cantilever into the AFM probe holder, the holder was immediately placed in the AFM working medium containing bacteria. Bacteria were immobilized on both sides of the cantilever (I and II in Fig. 7.10A), and then the deflections of the cantilever were monitored by the AFM’s laser lever system. Living bacteria on the cantilever could cause distinct fluctuations in the cantilever deflection due to the bacterial metabolism (III in Fig. 7.10A), but dead bacteria cause only minor fluctuations in the cantilever. Therefore, by monitoring the fluctuations of the cantilever deflections, the biological activities of bacteria and the killing effects of antibiotics on bacteria can be determined. The AFM chamber was linked with an inlet and outlet tubing system for changing the media in the chamber. Fig. 7.10A (IV) shows the time-dependent fluctuations of the cantilever deflection caused by the attached E. coli cells while the AFM chamber was filled successively with PBS, nourishing medium (lysogeny broth, LB), LB containing ampicillin and again LB. One can clearly see that there were remarkable fluctuations of the cantilever deflection for cells in PBS (bacteria in PBS) or in LB (bacteria in LB), whereas the addition of ampicillin significantly decreased the fluctuations of cantilever deflection (ampicillin) even after draining the ampicillin (LB wash), indicating that ampicillin had killed the bacteria. Analysis of the variance of the cantilever deflection further quantitatively confirmed that (bottom panel in the IV of Fig. 7.10A) bacteria in LB had the strongest activities while treatment with ampillin dropped the bacterial activities to a very low level compared with that obtained in PBS without bacteria. In 2014 Lissandrello et al. [84] confirmed detecting bacterial activities by monitoring the cantilever deflections and revealed that bacteria adsorbed on the AFM cantilever did not cause the detectable frequency shift of the cantilever due to the low number of cells adsorbed on the cantilever. It is estimated that at least 104

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FIGURE 7.10 The atomic force microscopy (AFM) cantilever as a highly sensitive nanomechanical sensor for detecting microbial activities in response to antibiotics. (A) Conventional AFM cantilever. (I and II) Schematic illustration (I) and optical image (II) of the AFM cantilever after the adsorption of living bacteria. (III) Schematic illustration of the fluctuations of the AFM cantilever caused by the adsorbed bacteria. (IV) Deflection of the AFM cantilever (top) and corresponding variance (bottom) for E. coli experiment. The traces represent 20 s of recording for “PBS” and 30 s for the other media. The time axis indicates the minute when each recording was started. The “B” line indicates when bacteria were injected, and the “A” line indicates when ampicillin was injected. (B) Microfabricated microchanneled cantilever combined with infrared light to detect the effect of ampicillin on E. coli cells. (I) Schematic illustration of the microchanneled cantilever filled with bacteria. At the bottom, the cantilever is coated with a 300 nm-thick layer of gold, which serves as a second element (mismatched expansion coefficients between the silicon nitride and gold layer facilitate the cantilever deflection as a localized heat is produced). The interior surface of the cantilever is coated with a bacteria-targeted receptor and the cantilever is irradiated with a specific wavelength of tunable infrared light. The inset at the top is the SEM image of an inlet of the microchanneled cantilever. The inset at the bottom is the depiction of the interior of the microchanneled cantilever. (II) SEM image of the microchannel of the cantilever. (III and IV) Fluorescence microscopy images of the bacteria with the use of live/dead stain before (III) and (IV) after the injection of ampicillin. (V) The resonance frequency shift and the nanomechanical deflections as a result of serial steps starting from a blank cantilever to removal of the antibiotics (ampicillin) and re-introduction of LB media. Source: (A) Reprinted with permission from G. Longo, L. Alonso-Sarduy, L.M. Rio, A. Bizzini, A. Trampuz, J. Notz, et al., Rapid detection of bacterial resistance to antibiotics using AFM cantilevers as nanomechanical sensors, Nat. Nanotechnol. 8 (7) (2013) 522526. Copyright 2013 Macmillan Publishers Limited. (B) Reprinted with permission from H. Etayash, M.F. Khan, K. Kaur, T. Thundat, Microfluidic cantilever detects bacteria and measures their susceptibility to antibiotics in small confined volumes, Nat. Commun. 7 (2016) 12947. Copyright 2016 The authors.

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bacteria are needed for generating a measurable frequency-shift signal [84], which exceeds the limit of the number of cells that the AFM cantilever can commonly hold. Furthermore, this method can be used to detect the viability of various living specimens including the microbes in soil and water samples [85], which is meaningful for sensing life activities originating from unknown sources and complements traditional chemical lifedetection assays. In 2016 Etayash et al. [86] used a microchanneled bimaterial cantilever combined with infrared spectroscopy to sense microbial activities in response to antibiotics, as shown in Fig. 7.10B. The cantilever was fabricated using silicon nitride with a layer of gold on one side for enhanced thermal sensitivity, and a microfluidic channel was embedded inside the cantilever (I in Fig. 7.10B). The interior surfaces of the microchanneled cantilever were coated with specific receptors to selectively capture target bacteria. The microchanneled cantilever could work in the air, overcoming the limitations of liquid damping and increasing the resolution of mass sensitivity. The binding of bacteria to the receptors on the interior surface of the cantilever changes the mass of the cantilever, which subsequently causes the changes in the resonance frequency of the cantilever. Besides, the cantilever was illuminated with an infrared light, which could cause additional changes in cantilever bending and allowed acquiring nanomechanical infrared spectrum for cells. Fig. 7.10B(V) represents the time-dependent changes of cantilever deflections and resonance frequency shifts upon the successive injection of different media to examine the effects of antibiotics (ampicillin) on E. coli cells, showing the changes of both cantilever deflection and resonance frequency after the trapping of bacterial cells. In addition, the treatment of ampicillin also caused changes in cantilever deflection and resonance frequency and fluorescence microscopy was used to confirm the vitality of cells before and after the addition of antibiotics (III and IV in Fig. 7.10B), indicating the killing effect of ampicillin on bacteria. These studies show that the AFM cantilever is a powerful nanomechanical sensor to rapidly detect microbial activities, which will benefit the development of novel methods for clinical antibiotic susceptibility testing with translational medicine significance.

7.8 Summary AFM has achieved great success in characterizing the behaviors of individual living microbial cells under aqueous conditions with an unprecedented spatiotemporal resolution, and applications of AFM in microbiology have yielded numerous unique and novel insights into the underpinnings of microbial physiology as well as the pathogenic mechanisms of microbial infections. AFM is able to not only image the

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fine structures of the cell surface (Fig. 7.3) and their dynamics during microbial activities (Figs. 7.4 and 7.5) by topographical imaging, but also can quantitatively measure the mechanical properties of single living microbes (Fig. 7.6) by indentation assay. With the use of AFM-based SMFS in which antibody molecules are linked to the surface of the AFM tip, individual protein molecules on the cell surface can be localized (Fig. 7.7), which allows quantifying the specific intermolecular interaction forces and mapping the nanoscale spatial distribution of proteins on single cells. With the use of AFM-based SCFS in which the AFM tip is replaced with a cell (Fig. 7.8), the adhesive behaviors of single microbes to various surfaces can be precisely measured, allowing revealing the molecular basis guiding microbial processes. Besides, PFTbased multiparametric AFM imaging enables simultaneously acquiring the structures and various mechanical properties of the individual living microbial cell (Fig. 7.9), which significantly benefits understanding the cellular structure-property relationships. In addition, an AFM cantilever can be used as a highly sensitive nanomechanical sensor to rapidly monitor real-time microbial activities such as that in response to antibiotics (Fig. 7.10). Taken together, the methodologies of utilizing AFM to probe microbial behaviors are now highly powerful and multifunctional, and further applications of AFM to more microbial systems in future particularly combining AFM with other complementary techniques will continuously advance our understanding of microbial activities and promote the development of mechanomicrobiology.

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C H A P T E R

8 Investigating the structures and mechanics of single animal cells by atomic force microscopy A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/9780323953603

8.1 Background Animal cells are the structural and functional units of life activities of animals, including human beings. Animal cells are eukaryotic cells, which are encased by the plasma membrane and possess membranebound nuclei and organelles. Animal cells are typically 10 times bigger in linear dimension and 1000 times larger in volume than microbial cells [1]. Besides, due to the lack of a stiff cell wall, animal cells can deform rapidly and are able to engulf other cells and small objects by phagocytosis. The structures of an animal cell commonly include plasma membrane, cytoplasm, nucleus, cytoskeleton, and various organelles. Fig. 8.1A shows the structures of a migrating tumor cell [2]. There are diverse animal cells that vary greatly in structures and functions, and a particular cell may not have all of the structures, for example, mature red blood cells do not have a nucleus and organelles to contain more hemoglobin for carrying more oxygen molecules. Besides, some cells have unique structures to perform specific biological functions, for example, sperm cells have flagellum for motility [3], nerve cells (also called neurons) have axons and dendrites to generate and transmit electrophysiological signals to communicate between neurons and brain regions [4], and cardiomyocytes contain numerous myofibrils composed of adjoining micrometer-sized contractile units called sarcomeres to perform rhythmic beating [5]. Cellular structures are not static

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FIGURE 8.1 Animal cell structures. (A) Schematic illustration of the structures of animal cells. An example of a migrating tumor cell is shown. During migration, tumor cells generate increased protrusive forces and form membrane protrusions, known as lamellipodial protrusions which are flat broad protrusions at the leading edge created from peripheral actin polymerization. Tumor cells also form invadopodia which are finger-like F-actin protrusions associated with the degradation of ECM in cancer invasion. (B) SEM images of adherent animal cells (I and II) and suspended animal cells (III and IV). (I and II) SEM images of a Vero cell (I) and the local area on the cell surface (II). (III and IV) SEM images of a T lymphocyte (III) and the local area (indicated by the yellow square in III) on the cell surface (IV). The yellow arrows typically denote the cilia on the cell surface. Source: (A) Reprinted with permission from D. Vasilaki, A. Bakopoulou, A. Tsouknidas, E. Johnstone, K. Michalakis, Biophysical interactions between components of the tumor microenvironment promote metastasis, Biophys. Rev. 13 (3) (2021) 339357. Copyright 2021 The authors. (B) (I and II) Reprinted with permission from L.A. Caldas, F.A. Carneiro, L.M. Higa, F.L. Monteiro, G.P. da Silva, L.J. da Costa, et al., Ultrastructural analysis of SARS-CoV-2 interactions with the host cell via high resolution scanning electron microscopy, Sci. Rep. 10 (1) (2020) 16099. Copyright 2020 The authors. (III and IV) Reprinted with permission from H.R. Kim, Y. Mun, K.S. Lee, Y.J. Park, J.S. Park, J.H. Park, et al., T cell microvilli constitute immunological synaptosomes that carry messages to antigen-presenting cells, Nat. Commun. 9 (1) (2018) 3630. Copyright 2018 The authors.

but dynamic, and cellular structures change during the life of cells. For example, the nuclear architectures (nuclear lamina, nucleolus, heterochromatin structure, and nuclear speckles) of embryonic stem cells undergo morphological changes during the differentiation process [6], and studies have shown that 36% of active and inactive chromosomal compartments throughout the genome are altered during stem cell differentiation [7].

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Particularly, when a normal cell becomes a diseased cell, dramatical changes in cell structures and properties take place. For example, compared with their normal counterparts, cancerous cells have bulky glycocalyx on the cell surface, which facilitates integrin clustering by funneling active integrins into adhesions and altering the integrin state by applying tension to matrix-bound integrins [8]. For efficient metastasis of cancerous cells, cytoskeletal components like actin, myosin, and intermediate filaments and their associated proteins reorganize in an orderly fashion to form many cellular protrusions-like lamellipodia, filopodia, and invadopodia [9], as shown in Fig. 8.1A. These structural changes often result in the unique mechanical properties of cancerous cells, such as cancerous cells are commonly much softer than normal cells [10]. Consequently, investigating the structures and properties of animal cells is of fundamental significance for revealing the mysteries of life and the underlying mechanisms guiding the pathological processes. AFM offers a unique and multifunctional tool to perform label-free characterizations of the structures and properties of single living animal cells under aqueous conditions with unprecedented spatial resolution. SEM has been broadly used to image the fine structures of animal cells, and the individual cilia on the surface of both adherent animal cells and suspended animal cells can be clearly observed by SEM, as shown in Fig. 8.1B. However, SEM requires substantially destructive pretreatments (e.g., chemical fixation, dehydration, drying, gilding) of cells [11,12] and cannot observe the structures of living cells in their native states. AFM is able to directly image the fine structures of living animal cells without any pretreatments in near-physiological environments (cell growth medium, 37 C, 5% CO2) and reveal the structural dynamics during cellular activities [13], which thus remarkably complement SEM imaging. Particularly, besides topographical imaging, AFM is also able to measure the mechanical properties of single living animal cells and sense the specific single protein molecules on the cell surface as well as quantify molecular interactions via AFM-based force spectroscopy techniques [14], which significantly benefit unveiling the mechanical issues in cellular and molecular activities. In fact, AFM has become an important and standard tool for characterizing the mechanical properties of single cells [1517], and applications of AFM in single-cell mechanical assay have contributed much to the communities of mechanobiology. Notably, according to the growth in the medium, animal cells can be divided into two categories, including adherent cells and suspended cells. Adherent cells are the most common form of animal cells and they need to adhere to a surface to remain viable and proliferate [18], thus these cells are also called anchorage-dependent cells. Suspended cells naturally float in the medium (e.g., blood cells, immune cells, and metastatic cancerous cells in the vascular fluid) and do not require adhesion for

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survival [19], and thus these cells are also called anchorage-independent cells. In the remaining of the chapter, applications of AFM to the structural imaging and mechanical detection of adherent animal cells and suspended animal cells are presented, respectively.

8.2 Imaging the surface structures and their dynamics of single living adherent animal cells AFM is able to image the fine structures of single living adherent animal cells in their native states under aqueous conditions. Since adherent animal cells can naturally attach to and spread on the substrates, no extra immobilization strategies are required to assist AFM imaging of them. Besides, AFM imaging does not require any pretreatments (such as fluorescent labeling used in super-resolution optical microscopy imaging) on the target cells and thus cells are in their native states, providing unique information on the nanostructures of living cells which considerably complements optical microscopy imaging and SEM imaging. In 1992 Henderson et al. [20] first imaged living adherent cells (glial cells) by AFM. The XR1 glial cells (a nonneuronal cell line from Xenopus retinal neuroepithelium) were used. XR1 glial cells were grown on coverslips coated with collagen and then directly imaged by AFM at contact mode in growth media without any pretreatments. The nucleus and filaments of single living XR1 cells were clearly identified from the obtained AFM images. During contact mode imaging, the scan forces exerted by the AFM tip on the cell cause cell indentation, allowing the AFM tip to sense and image the stiff cytoskeletal structures embedded in the cytoplasm [21]. Commonly, the topography of the cell in the obtained AFM image is prone to be smooth and featureless at low scan forces, whereas the underlying cytoskeletal structures start to appear in the AFM image at higher scan forces. A notable point is that the AFM height image (I in Fig. 8.2A and B) provides precise information regarding cell surface topography, and the corresponding AFM deflection error image (II in Fig. 8.2A and B) provides more details of the structures of the cell but lack quantitative height information. Many different types of living adherent cells have been imaged by AFM, including normal rat kidney (NRK) cells [22], fibroblasts [23], human small airway epithelial cells (HSAECs) [24], A549 (human lung cancer cell line) cells (Fig. 8.2A), MCF-7 (human breast cancer cell line) cells, HeLa (human cervical cancer cell line) cells [25], C2C12 (mouse myoblast cell line) cells (Fig. 8.2B) [26], and so on. In 2000 Domke et al. [27] imaged living osteoblast cells by AFM, as shown in Fig. 8.2C. The experimental results show that the linearly patterned actin filaments are clearly visible over all parts of the cell from the AFM height image (I in Fig. 8.2C) and it is possible to resolve structures of about 50 nm width (denoted by the white arrows in the II of Fig. 8.2C). In 2015

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FIGURE 8.2 Atomic force microscopy (AFM) imaging revealing the ultrastructures of single living adherent cells. (A) AFM height image (I) and deflection image (II) of a living A549 cell obtained in cell growth medium at room temperature. (B) AFM height image (I) and deflection image (II) of a living C2C12 cell obtained in a cell growth medium. (C) AFM images of living osteoblast cells. (I) AFM height image of a living osteoblast cell. (II) AFM deflection image of the local area (denoted by the white box in I) of the cell. Structures down to 50 nm (white arrows) of the web-like cytoskeleton are resolved. (D) AFM height images of the nanofiber structures of a living NIH-3T3 fibroblast obtained at PFT mode. (I) Raw image. (II) Magnified image of the region denoted by the white dashed square in (I). (E) AFM images of the individual microvilli on living MDCK cell obtained at PFT mode. (I) Whole-cell (25 3 25 μm2) imaging. (IIIV) Local area (10 3 10 μm2) imaging results obtained with different scan forces. (II) 150250 pN. (III) 100130 pN. (IV) 80100 pN. Source: (A) (II) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells investigated by atomic force microscopy, Sci. China Life Sci. 58 (9) (2015) 889901. Copyright 2015 The authors. (B) Reprinted with permission from M. Li, L. Liu, X. Xiao, N. Xi, Y. Wang, Effects of methotrexate on the viscoelastic properties of single cells probed by atomic force microscopy, J. Biol. Phys. 42 (4) (2016) 551569. Copyright 2016 Springer. (C) Reprinted with permission from J. Domke, S. Dannohl, W.J. Parak, O. Muller, W.K. Aicher, M. Radmacher, Substrate dependent differences in morphology and elasticity of living osteoblasts investigated by atomic force microscopy, Colloids Surf. B Biointerfaces 19 (4) (2000) 367379. Copyright 2000 Elsevier Science B.V. (D) Reprinted with permission from F. Eghiaian, A. Rigato, S. Scheuring, Structural, mechanical, and dynamical variability of the actin cortex in living cells, Biophys. J. 108 (6) (2015) 13301340. Copyright 2015 The Biophysical Society. (E) Reprinted with permission from H. Schillers, I. Medalsy, S. Hu, A.L. Slade, J.E. Shaw, Peakforce tapping resolves individual microvilli on living cells, J. Mol. Recognit. 29 (2) (2016) 95101. Copyright 2015 The authors.

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Eghiaian et al. [28] visualized the actin cortex architectures in living NIH-3T3 fibroblasts with the use of PFT mode AFM imaging, as shown in Fig. 8.2D. A dense filament network was largely observed on most parts of NIH-3T3 cells, and various actin-specific substructures were distinctly revealed from AFM images, including large fibers (Fig. 8.2D), intricate meshwork, and actin asters and stars. Besides the cytoskeleton structures beneath the cytoplasm membrane, AFM can also visualize the cilia structures on the surface of living adherent animal cells. During contact mode imaging, the lateral movement of the AFM tip over the cell surface can easily deform the fragile microvilli (II and IV in Fig. 8.1) on the cell surface, which is thus detrimental to imaging the microvilli on the cell surface. In 2016 Schillers et al. [29] visualized the individual microvilli on living Madin-Darby canine kidney (MDCK) cells by PFT mode AFM imaging, as shown in Fig. 8.2E. For doing so, a specific AFM probe with a 45-μm-long cantilever and a 17-μm-long tip was used. Since the cantilever is far from the cell surface, the effect of hydrodynamic force variation on AFM imaging can be effectively inhibited. When the scan force of PFT imaging was larger than 100 pN, the microvilli on the cell surface could easily be displaced, yielding the waving grain morphology in the obtained image (II and III in Fig. 8.2E). Individual microvilli were clearly visualized when the scan force was reduced to the range of 80100 pN (IV in Fig. 8.2E), since this small peak force could avoid displacement of the microvilli. PFT-based AFM imaging not only eliminates the lateral force but also is able to control the force exerted vertically on the cell surface to a low level (with piconewton sensitivity), allowing visualizing the individual microvilli on the living cell surface [30]. Overall, these studies demonstrate the great capabilities of AFM in noninvasively imaging the ultrastructures (e.g., individual microvilli on the cell surface, cytoskeleton structures beneath cell membrane) of single living adherent cells, significantly benefiting the study of cell structure. Time-lapse AFM imaging allows capturing the structural dynamics during various biological processes of single living adherent cells. Cell migration plays a crucial role in various biological phenomena, including both normal physiology and pathology, for example, leukocytes immigrate into areas of insult to mediate phagocytic functions and immune attacks, fibroblasts and vascular endothelial cells migrate for wound healing, and cancerous cells migrate for tumor invasion and metastasis [31]. Hence, investigating the detailed behaviors of cell migration benefits understanding the mysteries of life and promoting disease therapy. The molecular mechanisms that control single-cell polarization and migration have been extensively studied, including polarized cytoskeletal rearrangements, the polarized organization of membrane trafficking, adhesion regulation, membrane tension, and nuclear mechanics [32,33]. With the use of AFM time-lapse imaging, the nanoscale structural dynamics during the migration of single living adherent cells in their native states can be clearly

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revealed, providing direct and unique evidence for cell locomotion. In 1994 Schoenenberger et al. [34] observed the cellular dynamics of single MDCK cells by time-lase AFM, as shown in Fig. 8.3A. Cells grown on coverslips

FIGURE 8.3 Time-lapse atomic force microscopy (AFM) imaging revealing the structural dynamics of single living adherent cells. (A) Time-lapse AFM images of process movement of a living MDCK cell. (B and C) Successive AFM images of a living MCF-7 cell (B) and a living Neuro-2a cell obtained in cell growth media at room temperature. AFM deflection images are shown. For the MCF-7 cell, AFM images were obtained immediately after taking it from the incubator. For the Neuro-2a cell, the cell sample was removed from the incubator and then placed at room temperature for 1 h, after which AFM images were obtained. (D) Successive high-speed AFM images obtained on a living HeLa cell showing the dynamic process of endocytosis. The imaging rate is 5 s per frame. (E) Sequential high-speed AFM images capturing the dynamic reorganizations of the cytoskeletons on a living COS-7 cell. Source: (A) Reprinted with permission from C.A. Schoenenberger, J.H. Hoh, Slow cellular dynamics in MDCK and R5 cells monitored by time-lapse atomic force microscopy, Biophys. J. 67 (2) (1994) 929936. Copyright 1994 The Biophysical Society. (B and C) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Z. Dong, X. Xiao, et al., Atomic force microscopy imaging of live mammalian cells, Sci. China Life Sci. 56 (9) (2013) 811817. Copyright 2013 The authors. (D) Reprinted with permission from H. Watanabe, T. Uchihashi, T. Kobashi, M. Shibata, J. Nishiyama, R. Yasuda, et al., Widearea scanner for high-speed atomic force microscopy, Rev. Sci. Instrum. 84 (5) (2013) 053702. Copyright 2013 AIP Publishing LLC. (E) Reprinted with permission from A. Yoshida, N. Sakai, Y. Uekusa, K. Deguchi, J.L. Gilmore, M. Kumeta, et al., Probing in vivo dynamics of mitochondria and cortical actin networks using high-speed atomic force/fluorescence microscopy, Genes Cells 20 (2) (2015) 8594. Copyright 2014 The authors.

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were imaged by AFM in PBS. Series of AFM images were recorded at time intervals of 50100 s on the same cells, clearly showing the retraction of cellular lamellipodium as well as the reorganizations of cytoskeletons over tens of minutes. With the use of time-lapse AFM imaging, the dynamic changes of single living MCF-7 cells during the process of retraction have also been revealed [35], as shown in Fig. 8.3B. Successive AFM images of one living MCF-7 cell were recorded immediately in cell growth media at room temperature after taking cell samples out of the CO2 incubator. At the original state (0 min), the cell adhered tightly to the substrate and the cytoskeletons were discriminable from the AFM images. Subsequently, the cell began retracting and the reorganizations of the cell lamellipodia were clearly observed. We can see the formation of several filopodia during cell retraction (denoted by red arrows in Fig. 8.3B), and finally, these filopodia fused into the cell lamellipodium (100 min). Further, time-lapse AFM imaging (at room temperature) of another MCF-7 cell 1 h after taking cell samples out of the CO2 incubator showed no observable changes of cell lamellipodium [35], indicating the potential relationship between cellular retraction and environmental temperature. Fig. 8.3C shows the timelapse AFM images of a living Neuro-2a cell recorded 1 h after taking cell samples out of the incubator. We can see that although the cell did not retract but the reorganizations of the cytoskeleton (particularly the filament structures, denoted by the blue arrow) were clearly observed during serial AFM imaging, indicating the diverse behaviors between different types of cells (MCF-7, Neuro-2a) in response to AFM mechanical stimuli. With the use of time-lapse high-speed AFM imaging, even the transient states during the rapid cellular activities can be observed. In 2013 Watanabe et al. [36] revealed the dynamics of cellular engulfment taking place on the surface of a living HeLa cell by successive high-speed AFM imaging, as shown in Fig. 8.3D. AFM images clearly show the formation of nanoscale pits (denoted by the dashed circles) on the cell surface. Subsequently, these pits were coated by membrane protrusions and finally, these protrusions vanished, indicating the completion of the cell engulfment. In 2015 Yoshida et al. [37] captured the detailed filament organizations and their real-time dynamics on single living COS-7 cells by time-lapse high-speed AFM imaging, as shown in Fig. 8.3E. AFM images show that filaments longer than 4 μm crossed each other to form a network structure with mesh sizes ranging from 1.7 3 104 to 1.4 3 105 nm2. Besides, successive AFM images show the dynamic changes of the actin structures, such as appearance (denoted by white arrowheads) or disappearance (denoted by black arrowheads) of the actin filaments, and the transient invaginations followed by swollen structures (denoted by the black arrow). Overall, these studies show the typical applications of time-lapse (high-speed) AFM imaging in visualizing the dynamics of single living adherent cells in their native states, which are of great significance for understanding the biology of cell behaviors.

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Combining AFM with fluorescence microscopy allows precisely probing the behaviors of subcellular structures of single living adherent cells. From the AFM images of living cells obtained with regular (nonfunctionalized) AFM tips, except those structures which have unique morphology (e.g., cytoskeleton, microvilli, cell lamellipodium, cell filopodium, as shown in Figs. 8.2 and 8.3), commonly the specific components of the cell cannot be identified. Fluorescence labeling is a commonly used method to specifically identify cellular/molecular structures. Therefore these two techniques (AFM and fluorescence microscopy) complement each other, and combining AFM with fluorescence microscopy offers novel possibilities for investigating the behaviors of single living cells. Exocytosis is a process for moving large molecules out of the cell, which includes regulated exocytosis (the cargo of an intracellular vacuole is secreted in response to a specific signal) and constitutive exocytosis (macromolecules are secreted from the cell without having to await a specific signal) [38]. Specialized secretory cells, including neurons and nonneuronal cells, carry out stimulus-induced release of secretory molecules by regulated exocytosis [39]. An example of regulated exocytosis is the release of pulmonary surfactant by alveolar type II (ATII) cells after the stimulation of adenosine-50 -triphosphate (ATP) and phorbol 12-myristate 13-acetate (PMA). In 2012 Hecht et al. [40] visualized the exocytosis process of single living ATII cells by combining AFM with fluorescence microscopy, as shown in Fig. 8.4A. For doing so, the ATII cells isolated from Sprague Dawley rats were seeded on glass coverslips. The cell growth medium was then changed with bath solution in which fluorescein was added to recognize the fusion events. After adding ATP/PMA to stimulate the cells, the fusion events of exocytosis were identified by the fluorescence (I in Fig. 8.4A). AFM images obtained on the cells with fusion events clearly show the vesicle protrusion in cell membrane (II and III in Fig. 8.4A), correlating topographical changes in ATII cells with the exocytosis activities. Further studies show that actin coating and subsequent contraction of the actin coat are essential to facilitate the surfactant secretion [41]. AFM has also been integrated with super-resolution optical microscopy for probing the activities of single living cells. In 2015 Odermatt et al. [42] combined AFM with photoactivated localization microscopy (PALM)-based super-resolution optical microscopy to observe the detailed life activities of single CHO cells, as shown in Fig. 8.4B. Both AFM images and PALM images of single living CHO cells were obtained. AFM images showed the dynamic changes of cellular filopodia (I in Fig. 8.4B), while PALM images showed the dynamic changes of fluorescein-labeled molecular clusters (II in Fig. 8.4B), benefiting correlating cell structure reorganization with molecular dynamics in the physiological/pathological processes of single living cells. Nevertheless, it should be noted that AFM and PALM results were

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FIGURE 8.4 Combining atomic force microscopy (AFM) with fluorescence microscopy to observe the fine activities of single living cells. (A) Observing exocytosis of single living ATII cells by combining AFM with fluorescence microscopy. (I) Overlay of the bright field and fluorescence image 15 min after cells were treated with ATP/PMA. (II, III) AFM height image (II) and deflection image (III) of the cell with fusion events (the scan area is denoted by the square in I). The inset in (II) is the overlay of the fluorescence image (green) with the AFM height image (magenta). The inset in (III) shows the schematic illustration of the exocytosis. (B) Combining AFM with super-resolution optical microscopy to observe single living CHO cells. (I) Time-lapse AFM images of the leading edge of the cell showing the dynamics of filopodia protrusion. The white square in the AFM image denotes the area of subsequent PALM images shown in (II). (II) Successive PALM images show the reorganization of the fluorescein-labeled molecular clusters. Source: (A) Reprinted with permission from E. Hecht, K. Thompson, M. Frick, O.H. Wittekindt, P. Dietl, B. Mizaikoff, et al., Combined atomic force microscopy-fluorescence microscopy: analyzing exocytosis in alveolar type II cells, Anal. Chem. 84 (13) (2012) 57165722. Copyright 2012 American Chemical Society. (B) Reprinted with permission from P.D. Odermatt, A. Shivanandan, H. Deschout, R. Jankele, A.P. Nievergelt, L. Feletti, et al., High-resolution correlative microscopy: bridging the gap between single molecule localization microscopy and atomic force microscopy, Nano Lett. 15 (8) (2015) 48964904 Copyright 2012 American Chemical Society.

recorded in a correlated fashion but not simultaneously, and a better integration of the AFM operating software with the PALM acquisition software would allow for truly simultaneous imaging. Overall, these studies show that a combination of AFM and fluorescence microscopy is a promising tool to capture more details of the cellular activities, allowing correlating cellular activities with molecular dynamics.

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8.3 Measuring the mechanical properties of single living adherent animal cells AFM has been widely applied to measure Young’s modulus of individual living adherent cells. Fig. 8.5A illustrates utilizing AFM indentation to measure the mechanical properties of adherent cells [17]. For more detailed descriptions of AFM indentation assay, readers are referred to as Chapter 1. Briefly, AFM tip is controlled to indent the cell vertically (I in Fig. 8.5A), during which the force curves are recorded. If the cell being indented is rigid, the slope of the obtained force curve after contact point is relatively large, and the slope of the force curve decreases when the cell being indented is softer (II in Fig. 8.5A). Therefore, by analyzing the force curves, the rigidity of the cell can be characterized. Notably, the cellular Young’s modulus measured by AFM indentation assay is dependent on many factors, including tip shape of the AFM probe (Fig. 8.5B), loading rate of probe (Fig. 8.5C), environmental temperature of measurement (Fig. 8.5D), cellular areas being poked (Fig. 8.5E), substrate (Fig. 8.5F), working solution (Fig. 8.5G), cell states (Fig. 8.5H), and so on. Young’s modulus of cell measured by conical tip is often significantly larger than that measured by spherical tip [26], as shown in Fig. 8.5B. This is because of the different cellular structures probed the different AFM tips [16]. The sharp conical tip mainly probes the rigid cellular cortex, while the spherical tip probes both cortex and soft cytoplasm. Besides, increasing the loading rate of the AFM tip will result in the increased cellular Young’s modulus (Fig. 8.5C) [43], which is due to the viscous contributions of the cell to its mechanical response. An interesting phenomenon is that healthy cells are more sensitive to the changes of the loading rate compared with cancerous cells [43,44]. The environmental temperature also influences the measurement results. Studies have shown that Young’s modulus of fibroblast cells gradually increased when the temperature raised from 25 C to 37 C, but the further increase of temperature caused the dropping of cell Young’s modulus [45], as shown in Fig. 8.5D. Studies have also shown that the responses of cells to the changes of environmental temperature are diverse for different types of cells [25]. To obtain results with statistical significance, one needs to obtain a large number of force curves. Studies have shown that prolonged poking at the same point on the cell surface can cause the remodeling of the cytoskeleton, which subsequently results in changes in the cellular Young’s modulus [45], as shown in Fig. 8.5E. This effect can be overcome by obtaining arrays of force curves within a region on the cell surface. The substrate on which cells are grown also influences the measurement results, for example, it has been reported that Young’s modulus of HCV29 cells (nonmalignant cancerous cell of the ureter) grown on the poly-L-lysine-coated glass surface was 1.5 times larger than that of the cells

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FIGURE 8.5 Factors that influence the measurement results of atomic force microscopy (AFM)-based single-cell mechanical assay. (A) Schematic illustrations of AFM-based single-cell mechanical assay. (I) AFM probe is controlled to indent a single cell in the vertical direction. (II) Force curves can be used to discriminate mechanically soft and hard samples. (B) Results of Young’s modulus of four different types of cells (C2C12, L929, A549, HEK293) measured by the conical tip and spherical, respectively (mean 6 SEM, N 5 50). (C) Plot of Young’s modulus against loading rate for MCF-10A and MCF-7 measured at 37 C. (D) Influence of temperature on the elasticity of living fibroblast cells. (E) Young’s modulus of one cell is measured at the same location and within a region of the cell (N denotes the number of consecutive poking). (F) Effects of surface modification on the mechanical properties of HCV29 cells. (G) The medium composition affects the mechanical properties of the cells. (H) Cellular density influences Young’s modulus of cells measured by AFM. Source: (A) Reprinted with permission from P.H. Wu, D.R.B. Aroush, A. Asnacios, W.C. Chen, M.E. Dokukin, B.L. Doss, et al., A comparison of methods to assess cell mechanical properties, Nat. Methods 15 (7) (2018) 491498. Copyright 2018 Nature America Inc. (B) Reprinted with permission from M. Li, L. Liu, X. Xiao, N. Xi, Y. Wang, Effects of methotrexate on the viscoelastic properties of single cells probed by atomic force microscopy, J. Biol. Phys. 42 (4) (2016) 551569. Copyright 2016 Springer. (C) Reprinted with permission from Q.S. Li, G.Y.H. Lee, C.N. Ong, C.T. Lim, AFM indentation study of breast cancer cells, Biochem. Biophys. Res. Commun. 374 (4) (2008) 609613. Copyright 2008 Elsevier Inc. (DH) Reprinted with permission from M. Lekka, Discrimination between normal and cancerous cells using AFM, Bionanoscience 6 (1) (2016) 6580. Copyright 2016 The authors.

grown on the glass surface, as shown in Fig. 8.5F. Modifications of the substrate may change the adhesive interactions between cells and substrates, which can result in subsequent changes in cellular structures and cellular

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mechanical properties. Studies have also shown that the cell growth media in which AFM indentation assays are performed to measure the cellular Young’s modulus also affect the experimental results [46]. Both MCF-10A and MDA-MB-231 cells exhibited decreased Young’s modulus when the concentration of fetal bovine serum (FBS) in the media reduced from 10% to 5% and changing cell growth media from RPMI to DMEM but with the same FBS concentration also caused the slight changes in cellular Young’s modulus, as shown in Fig. 8.5G. The different cell growth media may cause diverse changes in cell structures as well as cell mechanics, which can be verified by performing additional experiments such as fluorescence microscopy of the cytoskeletons. In addition, studies have shown the differences in Young’s modulus among separated cells, clustered cells and monolayer cells (as shown in Fig. 8.5H) [45], indicating that the neighboring cells could influence the mechanical properties of the target cell being probed. An interesting point is that the influence of neighboring cells on the mechanical properties of the target cell is associated with cell types, and some types of cells are insensitive to this effect (Fig. 8.5H). Overall, as summarized in Fig. 8.5, to make the results comparable with each other for AFM-based single-cell mechanical analysis, we need to keep the conditions identical throughout the studies to eliminate the impacts of artificial errors. Nevertheless, concerns arise for the influence of cell growth environment (such as substrate and media) on cell mechanics. We know that the microenvironments of cancerous cells are quite different from that of normal cells in vivo, for example, tumors have an acidic microenvironment because of high metabolic activity and insufficient perfusion [47], whereas under normal physiological conditions the pH of blood and tissue is tightly controlled around pH 7.4 [48]. Hence, to make the results reflect the real cell mechanics as faithful as possible, we need to construct the in vitro cell growth environments that match the real in vivo microenvironments of cells as much as possible for the single-cell mechanical experiments. AFM has also been utilized to simultaneously detect the elastic and viscoelastic properties of single living adherent cells. Young’s modulus only reflects the elastic properties of cells. However, cells are both elastic and viscous, and thus are viscoelastic materials [49]. The viscoelasticity allows living cells to preserve a basic architecture due to their solid-like characteristics, but also at the same time to dynamically reorganize in different shapes and patterns due to their viscous-like characteristics [50]. In fact, the viscosity of a cell significantly affects diffusion in the cytoplasm, which is closely related to various biological processes in living cells, such as protein-protein interactions, signal transduction and transportation of small solutes, macromolecules, and other cellular organelles [51]. Cellular viscosity has also been shown to be relevant to many diseases: abnormalities in red blood cell viscosity have been observed in sickle cell anemia and type II diabetes, whereas changes in the mitochondrial membrane viscosity

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have been reported in numerous neurodegenerative diseases [52]. Hence, detecting the viscoelastic properties of cells is essential for understanding cellular mechanical behaviors. As a viscoelastic material, cell deforms elastically at short time scales and behaves as viscous fluids at long timescales. Hence, when utilizing AFM to probe the viscoelastic properties of cells, the AFM probe needs to stay on the cell for a period of time to observe the viscous behaviors of the cell. The principle of measuring cellular viscoelasticity by AFM is described in Chapter 1. Briefly, the AFM probe is controlled to vertically indent the cell. When the probe achieves the preset loading force, it dwells on the cell for a period of time, during which the deflections of the cantilever versus time (called relaxation curve) are recorded by an oscilloscope. Subsequently, the probe retracts from the cell to its original position in the vertical direction. With the use of AFM, the elastic and viscoelastic properties of MCF-10A and MCF-7 cells have been detected (as shown in Fig. 8.6) [53]. Fig. 8.6A shows the commercial AFM platform for single-cell mechanical assay as well as the oscilloscope which is connected to the AFM. With this platform, the force curves (I in Fig. 8.6B) and relaxation curves (III in Fig. 8.6B) can be obtained simultaneously during the AFM indentation assay. Fitting the force curve with the HertzSneddon model gives Young’s modulus (elasticity) of the cell (II in Fig. 8.6B), and fitting the relaxation curve with two-order Maxwell model gives the relaxation time (viscoelastic property) of the cell (IV in Fig. 8.6B). The statistical histograms of the measurement results of MCF-10A and MCF-7 cells are shown in Fig. 8.6C. We can see that Young’s modulus of MCF-10A cells is significantly larger than that of MCF-7 cells. Besides, the relaxation times of MCF-10A cells are also significantly larger than that of MCF-7 cells. We know that MCF-10A cells are normal breast cells, and MCF-7 cells are cancerous breast cells. Hence, the different elastic and viscoelastic properties between MCF-10A and MCF-7 cells may be associated with the different structures and functions of the two types of cells. So far AFM has been widely used to measure the cellular Young’s modulus as a biomarker for indicating cancer development and metastasis [16,54]. However, studies have also shown that Young’s modulus of cells sometimes fails to serve as a universal indicator for metastatic progression [55]. Hence, simultaneously detecting the elastic and viscoelastic properties of cells benefit comprehensively characterizing the mechanical properties of cells for potentially better indicating cellular behaviors. AFM force volume mode has been used to visualize the heterogeneous mechanical properties of single living cells. In the force volume mode, the AFM probe is controlled to obtain an array of force curves at the specified region on the sample surface. The specified region is divided into many grids and each grid represents a pixel. For each grid, the AFM tip is lowered and pressed against the sample surface until the preset cantilever deflection threshold is achieved, and the vertical

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FIGURE 8.6 Simultaneously measuring the elasticity and viscoelasticity of single living cells by atomic force microscopy (AFM). (A) Actual photographs of the experimental platform. (I) AFM. (II) Oscilloscope. (B) Extracting cellular Young’s modulus and relaxation time from the recorded force curves and relaxation curves, respectively. (I) A typical force curve obtained on a living MCF-10A cell with conical tip. The contact point is denoted by the black arrow. (II) Fitting the indentation curve converted from the approach curve in (I) with the Sneddon model gives the cellular Young’s modulus. (III) A typical relaxation curve obtained on the same MCF-10A cell. (IV) Fitting the relaxation curve with two-order Maxwell model gives the cellular relaxation times. (C) Comparison of the elastic and viscoelastic properties of MCF-10A and MCF-7 cells. (I) Cellular Young’s modulus. (II) Cellular relaxation time τ 1. (III) Cellular relaxation time τ 2. Source: Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Atomic force microscopy studies on cellular elastic and viscoelastic properties, Sci. China Life Sci. 61 (1) (2018) 5767. Copyright 2017 Science China Press and Springer-Verlag GmbH Germany.

position of the AFM piezoelectric tube at this time is recorded as the height of the grid. Subsequently, the AFM tip is controlled to retract from the grid, and a force curve reflecting the approach-retract movement of the AFM tip is recorded. The AFM tip is then moved to the next grid to repeat this process until a force curve is obtained for each grid point. By automatically analyzing the force curves, the various mechanical properties (e.g., elasticity, adhesion) at the grid areas on the sample can be visualized as mechanical maps. Readers are referred to Chapter 1 for detailed descriptions of PFT mode (PFT is essentially a type of AFM force volume mode). Besides, a low spatial resolution height image of the specified region is generated simultaneously with the mechanical maps, which is particularly useful for correlating

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mechanical properties with topographical structures. In 2000 Rotsch et al. [56] investigated the mechanical properties of fibroblasts by AFM force volume mode. Two types of fibroblasts were used, including NIH3T3 cells and NRK cells. Cells were grown on Petri dishes for 13 days and then AFM experiments were performed without changing the solution in physiological conditions (37 C, 5% CO2). AFM force volume mode was performed with a frequency of 10 Hz at a resolution of 64 3 64 force curves, which took about 20 min to obtain a single force map. From the images obtained at contact mode AFM imaging, the filament structures of living NRK cells were clearly observed (I in Fig. 8.7A, denoted by the arrow), mostly parallel to the longer axis of the cell. The filament structures were also discriminable from the height image generated during AFM force volume mode (II in Fig. 8.7A), but the spatial resolution is much lower. From the elasticity map (III in Fig. 8.7A), the heterogeneous distribution of the cellular Young’s modulus was visualized. We can see that the thick areas of the cell had a lower Young’s modulus (denoted by dark colors in Fig. 8.7III) than the peripheral area (denoted by the light colors in Fig. 8.7AIII), which is partially due to the influence of the stiff substrate. Time-lapse force volume mode AFM assays were performed on the single living cells after the stimulation of Cytochalasin B and the results show a remarkable decrease of cellular Young’s modulus within 120 min. For control, timelapse force volume images obtained on the same cells without the addition of drugs show no elasticity changes within 3 h, visually and directly confirming the effects of Cytochalasin B on cell elasticity. In 2015 Wang et al. [57] investigated the mechanical properties of human pulmonary artery endothelial cells (HPAECs) by AFM force volume mode, as shown in Fig. 8.7B. The effects of thrombin on cell mechanics were examined, which were correlated with the structural changes of cells observed by fluorescence microscopy and scanning transmission electron microscopy. These studies provide templates for utilizing AFM force volume mode to characterize the cellular mechanical properties and their dynamics in cellular activities, which can be directly applied to other types of adherent cells for providing novel insights into mechanobiology. PFT-based multiparametric AFM imaging offers novel possibilities for single-cell mechanical characterization. Although powerful, AFM force volume mode has long been limited by its poor spatiotemporal resolution, and advancements in the AFM technology have spawned PFTbased multiparametric AFM imaging which is able to simultaneously obtain the structural image and various mechanical maps of biological systems at the speed of conventional AFM topographical imaging [58]. PFT imaging significantly promotes the spatiotemporal resolution of traditional force volume mode, which helps to explore more details of the

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FIGURE 8.7 Mapping the mechanical properties of single living adherent cells by atomic force microscopy (AFM) force volume mode. (A) Living NRK fibroblasts. (I) AFM deflection image of a living NRK fibroblast recorded at contact mode. The arrow points to fibrous structures. (II and III) Height image (II) and elasticity map (III) of the same region in (I) generated at force volume mode. (B) Living HPAEC endothelial cells. (I) AFM deflection image of the cell. (II and III) Height image (II) and elasticity map (III) of the same region in (I) obtained at force volume mode (32 3 32 force curves were recorded on 70 3 70 μm2 area) with the use of a colloidal probe. Source: (A) Reprinted with permission from C. Rotsch, M. Radmacher, Drug-induced changes of cytoskeletal structure and mechanics in fibroblasts: an atomic force microscopy study, Biophys. J. 78 (1) (2000) 520535. Copyright 2000 The Biophysical Society. (B) Reprinted with permission from X. Wang, R. Bleher, M.E. Brown, J. G.N. Garcia, S.M. Dudek, G.S. Shekhawat, et al., Nano-biomechanical study of spatio-temporal cytoskeleton rearrangements that determine subcellular mechanical properties and endothelial permeability, Sci. Rep. 5 (2015) 11097. Copyright 2015 The authors.

mechanical issues involved in life activities. In 2016 Calzado-Martin et al. [59] utilized PFT imaging to investigate the effect of actin organization on the stiffness of living breast cancerous cells, as shown in Fig. 8.8A. Three types of breast cancer cells with different degrees of malignancy were used, including MCF-10A (healthy), MCF-7 (tumorigenic, noninvasive), and MDA-MB-231 (tumorigenic, invasive). The height images show that MCF-10A cells had long, compact, and well-aligned fibers (I in Fig. 8.8A), whereas the corresponding elasticity images show that these filaments possessed larger values of Young’s modulus (III in Fig. 8.8A). The disorganized cytoskeleton network areas were correlated with lower Young’s modulus. Besides, tumorigenic cells (MCF-7 and MDA-MB-231 cells) showed a much featureless morphology, and no significant correlation between the topographical features of tumorigenic cells and Young’s

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FIGURE 8.8 Visualizing the correlation between cell structures and cell mechanics by PFT-based multiparametric atomic force microscopy (AFM) imaging. Imaging living adherent cells at PFT mode simultaneously gives topographical image and multiple mechanical maps of the cell. (A) Different structures and mechanics between normal breast cells (I, III, and V) and cancerous breast cells (II, IV, and VI) are revealed by PFT imaging. (B) Drug-induced changes in cell structures and mechanics. PFT imaging results of cells from control group (I, III, and V) and glyphosate group (II, IV, and VI) show the remarkable changes in cytoskeletons and cell mechanics after drug stimulation. Source: (A) (IIV) Reprinted with permission from A. Calzado-Martin, M. Encinar, J. Tamayo, M. Calleja, A. San Paulo, Effect of actin organization on the stiffness of living breast cancer cells revealed by peakforce modulation atomic force microscopy, ACS Nano 10 (3) (2016) 33653374. Copyright 2016 American Chemical Society. (V and VI) Reprinted with permission from Q.S. Li, G.Y.H. Lee, C.N. Ong, C.T. Lim, AFM indentation study of breast cancer cells, Biochem. Biophys. Res. Commun. 374 (4) (2008) 609613. Copyright 2008 Elsevier Inc. (B) Reprinted with permission from C. Heu, A. Berquand, C. Elie-Caille, L. Nicod, Glyphosate-induced stiffening of HaCaT keratinocytes, a peak force tapping study on living cells, J. Struct. Biol. 178 (1) (2012) 17. Copyright 2012 Elsevier Inc.

modulus values were observed (II and IV in Fig. 8.8A). Nevertheless, the statistical results showed that the invasive cancerous cells were much softer than indolent cancerous cells. Particularly, the structural differences between normal breast cells and cancerous breast cells observed by AFM were well consistent with the actin labeling fluorescence microscopy results (V and VI in Fig. 8.8A) [43], indicating the important role of actin reorganization in tumor invasion and metastasis. In 2012 Heu et al. [60] investigated drug-induced changes in cellular mechanical properties by PFT-based multiparametric imaging, as shown in Fig. 8.8B. The HaCaT

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keratinocytes were used. Glyphosate is an extensively used herbicide that has been shown to increase the risk of cancer. Living HaCaT cells from the control group (without glyphosate) or treated with glyphosate were imaged in PFT mode. Cells from the control group exhibited membrane surfaces with regular and homogenous protrusions (I in Fig. 8.8B), which were correlated with the homogeneous Young’s modulus map (III in Fig. 8.8B) and deformation map (V in Fig. 8.8B). After the treatment of glyphosate, cells developed a filamentous subcellular network (II in Fig. 8.8B), which was accompanied by an increase in elasticity (IV in Fig. 8.8B) and a decrease in deformation (VI in Fig. 8.8B). Particularly, the filamentous structures were also discriminated from the elasticity and deformation maps. The results distinctly visualized the drug-induced cytoskeleton reorganizations as well as the alterations in cell mechanics, which are useful for evaluating drug actions at the single-cell level. The adhesive properties of single living adherent cells can be precisely measured by AFM-based SCFS assay. The adhesive capabilities of cells (e.g., cell-to-cell adhesion, cell-to-extracellular matrix adhesion) play an important role in the homeostasis of healthy tissues, for example, normal epithelial cells maintain tissue structure by adhering to each other and to the extracellular matrix [61]. There are four major types of cell adhesion molecules (including cadherins, integrins, selectins, and immunoglobulins) on the cell surface which are responsible for the adhesion of the cell to other cells or extracellular matrix, and altered expressions of these adhesion molecules and the corresponding changes in cellular adhesive properties have been linked to many types of cancers [62]. Hence, investigating the adhesive properties of single cells evidently benefits understanding the role of cellular adhesion in regulating cellular physiological and pathological processes, and AFM-based SCFS provides a powerful method to quantify the adhesion of single cells. Readers are referred to Chapter 1 for the principles of AFM-based SCFS. With the use of AFM-based SCFS assay, the adhesive behaviors of tumor cells have been broadly studied. In 2014 Omidvar et al. [63] investigated the cell-cell adhesion forces of three types of cancerous breast cell lines (MCF-7, T47D, and MDA-MB-231) by AFM. The results show that increased contact time resulted in a significant increase in the measured adhesion forces of cells, which might be due to the fact that increased contact time could lead to the formation of more intermolecular connections between cells. Hence, to make the results comparable with each other, the contact time during the SCFS assay should be kept identical. Besides, the results show that the adhesion forces between MCF-7 cells were the highest, indicating the decrease of cellular adhesion forces with the invasive potential. In 2016 Smolyakov et al. [64] also investigated the adhesion forces of breast cancerous cells with different invasive potentials by AFM-based SCFS and the results show that

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the cellular adhesion forces increased with the invasive potentials. We can see that the relationships between cellular adhesion and cellular invasiveness are still under debate [63,64] and more studies are required to reveal the role of cellular adhesion in the metastasis of tumor cells. In 2018 Xie et al. [65] utilized the AFM-based SCFS assay to investigate the adhesive interactions between human breast cancer cells (HBCCs) and human bone marrow endothelium (HBME) cells. The cellular adhesion forces were measured before and after the treatment of antibodies (the antibodies were able to block the specific adhesion molecules on cell surface), and the results show the contribution of several cell adhesion molecules (Thomsen-Friedenreich antigen, galectin-3, integrin-β1, integrin-α3) to the adhesion of HBCC to HBME. More recently, in 2021, Liebsch et al. [66] investigated the adhesion between human nonsmall cell lung cancer cells (A549) and platelets to examine the antimetastatic effect of heparin, as shown in Fig. 8.9. For doing so, the platelets were immobilized on the collagen-coated glass surface, and a layer of activated platelets was formed after 2 h at room temperature. The A549 cell suspension was then added to the platelet buffer, and single living A549 cells were attached to the AFM tipless cantilever under the guidance of optical microscopy (Fig. 8.9B). The single-cell probe was then moved to the activated platelets to perform the SCFS assay (Fig. 8.9A). The results show that the unbinding forces between A549 cells and platelets (Fig. 8.9D) were much larger than that between A549 cells and collagen (Fig. 8.9C). Besides, there are evident molecular unbinding events in the force curve obtained on platelets, whereas the molecular unbinding events are hardly observable in the force curve obtained on collagen, confirming the adhesive interaction between A549 cells and platelets. The results obtained after the addition of heparin clearly show the decrease of cellular adhesion forces. Further, after blocking the P-selectin on the platelets, the addition of heparin further caused the decrease of cellular adhesion forces, demonstrating the antimetastatic effect of heparin. The AFM cantilever can also serve as an ultrasensitive nanomechanical sensor for probing the mechanical properties of single living adherent cells. A typical application is directly measuring the rounding forces of single cells during mitosis. A tipless AFM cantilever is positioned above single living cells, the rounding cell under the AFM cantilever due to mitosis comes in contact with the cantilever and causes the deflections of the cantilever. Hence, by monitoring the changes of the deflections of the cantilever, the rounding force exerted by the mitotic cell can be directly measured. Both regular cantilever (I in Fig. 8.10A) and wedged cantilever (II in Fig. 8.10A) can be used for measuring the rounding force of the cell during mitosis. Standard AFM systems mount the cantilever at an angle of 812 degrees relative to the sample surface, which is prone to cause the lateral sliding of the cell

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FIGURE 8.9 Measuring adhesive interactions between A549 cells and platelets by atomic force microscopy (AFM)-based SCFS. (A) Schematic illustration of the SCFS measurement of the adhesion between A549 cells and platelets. (I) The AFM cantilever with an A549 cell (red sphere) is controlled to approach the layer of activated platelets (green structures). (II) Contact and adhesion between A549 cell and platelets. (III) Retraction of the cantilever causes the rupture of the molecular bonds between A549 cell and platelets. (IV) The cantilever returns to its original position. (B) The cantilever (denoted by the dashed white line) carrying an A549 cell (denoted by the dashed light blue line) is moved to the activated platelets (typically denoted by the dotted dark blue line) for SCFS experiments. (C and D) Representative force curves obtained on collagen (C) and on platelets (D), respectively. The gray double arrows denote the adhesion force. The blue region areas denote the detachment work. Source: Reprinted with permission from A.G. Liebsch, H. Schillers, Quantification of heparin’s antimetastatic effect by single-cell force spectroscopy, J. Mol. Recognit. 34 (1) (2021) e2854. Copyright 2020 The authors.

attached to the cantilever during SCFS assay [67]. Besides, regular cantilever also adds complication to determine the geometrical parameters involved in the SCFS assay such as cell-cantilever contact area, cell surface area, and cell volume. These issues can be well addressed by using wedged cantilevers. The wedged cantilevers can be fabricated by focused ion beam (FIB) ablation on standard AFM cantilevers [68]. In 2011 Stewart et al. [69] have utilized AFM cantilever to reveal the dynamic changes of the rounding forces exerted by individual dividing cell, as shown in Fig. 8.10B. Fluorescence microscopy images of the

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FIGURE 8.10 Atomic force microscopy (AFM) cantilever as an ultrasensitive nanomechanical sensor for detecting the mechanics of single living adherent cells. (A) The shapes of cells are compressed by regular (I) and wedged cantilevers (II). Three-dimensional rendered confocal images of the cells being compressed are shown in the bottom panel. (B) Measuring the rounding force of a mitotic cell. (I and II) Schematic illustrations of the changes of the AFM cantilever before (I) and after cell rounding (II). (III) Dynamical changes of the rounding forces of single cells during mitosis. The corresponding fluorescence microscopy images are shown in the top panel. (C) Measuring the mass of a living cell. (I) Schematic illustration of the principle. (II) Mass dynamics of a fibroblast monitored at 10-Ms time resolution. Source: (A) Reprinted with permission from M.P. Stewart, A.W. Hodel, A. Spielhofer, C.J. Cattin, D.J. Muller, J. Helenius, Wedged AFM-cantilevers for parallel plate cell mechanics, Methods 60 (2) (2013) 186194. Copyright 2013 Elsevier Inc. (B) Reprinted with permission from M.P. Stewart, J. Helenius, Y. Toyoda, S.P. Ramanathan, D.J. Muller, A.A. Hyman, Hydrostatic pressure and the actomyosin cortex drive mitotic cell rounding, Nature 469 (7329) (2011) 226230. Copyright 2011 Macmillan Publishers Limited. (C) Reprinted with permission from D. Martinez-Martin, G. Flaschner, B. Gaub, S. Martin, R. Newton, C. Beerli, et al., Inertial picobalance reveals fast mass fluctuations in mammalian cells, Nature 550 (7677) (2017) 500505. Copyright 2017 Macmillan Publishers Limited.

mitotic cells were simultaneously recorded to confirm the mitotic phases of the cell (III in Fig. 8.10B). From the dynamic deflection changes of the AFM cantilever, one can see that the cellular rounding force increased as the cell progressed through prometaphase and into metaphase. When the cell entered into anaphase, the rounding force rapidly dropped to zero in about 10 min. The rounding pressure can also be obtained by dividing the force by the cross-sectional area of the cell, and the results show that the maximum rounding pressure of the cell during the mitosis was 0.14 6 0.04 nN/μm2. AFM cantilever can also be used to measure the mass of single living cells, allowing capturing the fast and subtle mass fluctuations through the cell cycle. In 2017 Martinez-Martin et al. [70] developed a picobalance based on AFM to measure the mass of single living cells, as shown in Fig. 8.10C. A lowpower intensity-modulated blue laser (405 nm, # 50 μW) is focused at

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the base of the cantilever to generate vary small cantilever oscillations ˚ , and the oscillation amplitude and frein the range of about 115 A quency of the cantilever are detected by reflecting an infrared laser (852 nm, # 250 μW) from the free end of the cantilever (I in Fig. 8.10C). Attaching a cell to the cantilever causes the changes of the effective mass and the resonance frequency of the cantilever, and thus the cell mass can be determined by measuring the resonance frequency of the cantilever before and after attaching a cell. With this method, the measured mass of single HeLa cells and fibroblasts were 2.43 and 2.29 ng, respectively. Besides, successive measurements remarkably reveal that the cells showed fast (about 2 s) and slow (about 18 s) dynamic mass fluctuations during the life cycle (II in Fig. 8.10C). For control, the mass fluctuations were not observed for chemically fixed cells, indicating that the mass fluctuations were due to the biological activities of the living cells.

8.4 Probing the molecular activities on the surface of single adherent cells With the use of AFM-based SFMS assay, the specific molecular interactions on the surface of adherent cells have been broadly probed. There are thousands of different biomolecules (lipids, proteins, and carbohydrates) on the surface of a cell, and the assemblies and interactions of these molecules are associated with most cellular activities [71]. Abnormal behaviors of these biomolecules are often accompanied with diseases, for example, the expression levels of the programmed deathligand 1 (PD-L1) on the cell surface are closely related with various types of cancers [72]. Due to the critical role of cell surface molecules in the cellular physiological and pathological processes, many drugs target these cell surface molecules for treating diseases [73]. Hence, probing the details of these molecular interactions on the cell surface, such as how a cell surface receptor finds its ligand, how and where the ligand binds, and by which mechanism the ligand switches the functional state of its target [74], is of fundamental significance for deciphering the mysteries of life. By linking ligand molecules onto the surface of AFM tip, AFM is able to specifically locate the corresponding receptors on the cell surface and quantify the receptorligand interactions (readers are referred to as Chapter 1 for the principle of AFM-based SMFS), which benefits understanding the behaviors of cell surface molecules in their native states. In 2011 Puntheeranurak et al. [75] utilized AFM-based SMFS to investigate the sodium-glucose cotransporter 1 (SGLT1) on CHO cells. Notably, an important point of AFM-based SCFS on living cells is expressing high levels of target receptors on the cell surface to increase the probability for the ligand to find its cognate receptor, which

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can be realized by cellular transfection and confirmed by immunohistochemistry staining. Under the guidance of optical microscopy, the functionalized probe is moved to the target cell to obtain force curves. The observed probability for finding specific unbinding events between the receptors on cell surface and the ligands on the tip surface was about 10%30% and the specific unbinding events could be clearly discriminated from the shape of the adhesion peak in the force curve (II in Fig. 8.11A). After adding additional ligands to block the receptors on the cell surface, force curves were obtained on the cells again and in

FIGURE 8.11 Probing the molecular activities on single adherent cells by atomic force microscopy (AFM). (A) Measuring the binding affinity and thermodynamic parameters of receptors on cell surface. (I) AFM height image of a CHO cell. (II) A typical force curve (only the retract portion is shown) obtained on living CHO cell showing the specific interaction between SGLT1 and antibody. The inset is the force curve obtained after blocking experiments. (III) The loading rates dependence on the rupture forces of EGF-EGFR in the

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L

this case, the specific unbinding peaks disappeared (the inset in II of Fig. 8.11A), confirming the specific receptor-ligand molecular interactions. In 2013 Zhang et al. [76] investigated the effects of human epidermal growth factor receptor-2 (HER2) antibody drugs on epidermal growth factor (EGF) mediated ligand-receptor interactions on living HEK 293 cells by AFM-based SMFS. Trastuzumab and Pertuzumab are two monoclonal antibodies which target different extracellular domains of HER2 in the practical therapy of cancers. The EGF-conjugated AFM tips were used to detect the interactions between EGF and EGFR on cells with or without HER2 expression. The results clearly show that HER2 could induce a more stable interaction of EGF-EGFR. The addition of antibodies to block the HER2 caused the significant decrease of the interaction forces of EGF-EGFR, showing the inhibition effect of HER2 antibody on EGF-EGFR interactions. Besides, force curves were obtained at different loading rates to obtain the dynamic force spectra of EGF-EGFR (III in Fig. 8.11A), showing the effects of HER antibodies on the energy landscapes of EGF-EGFR complex. The results provide a molecular basis for the HER2-mediated EGF-EGFR interactions on cancer cells. With the use of AFM-based SMFS techniques, various other

presence of HER2 measured on living HEK 293 cells. (B) Mapping the Fc gamma receptors on single macrophages. (I) AFM deflection image of individual macrophages. (II) Force map constructed by obtaining 16 3 16 force curves on 500 3 500 nm2 area of the cell surface. (III) Force map obtained after blocking experiments. (IV) Force map obtained on another cell without blocking experiments using the same AFM functionalized tip. (C) Visualizing the distribution of VEGFR2 receptors on HUVEC by TREC mode AFM imaging. (I) AFM topographical image of the cell. (II) Recognition image of the local area (denoted by the square in I) on the cell surface. Dark spots (circled) indicate the VEGFR2 recognition events. (III and IV) Recognition images obtained after blocking experiments. (D) Correlating molecular activities with cell mechanics by PFT-based multiparametric AFM imaging. (I) Overlay of optical microscopy and fluorescence image of the cocultured cells. (II) Height image, (III) adhesion force image, and (IV) Young’s modulus image of the cells (the scanning area is denoted by the orange square in I) obtained at PFT mode. Source: (A) (I, II) Reprinted with permission from T. Puntheeranurak, I. Neundlinger, R. K. Kinne, P. Hinterdorfer, Single-molecule recognition force spectroscopy of transmembrane transporters on living cells, Nat. Protoc. 6 (9) (2011) 14431452. Copyright 2011 Nature America, Inc. (III) Reprinted with permission from X. Zhang, X. Shi, L. Xu, J. Yuan, X. Fang, Atomic force microscopy study of the effect of HER 2 antibody on EGF mediated ErbB ligand-receptor interaction, Nanomedicine 9 (5) (2013) 627635. Copyright 2013 Elsevier Inc. (B) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Imaging and measuring the biophysical properties of Fc gamma receptors on single macrophages using atomic force microscopy, Biochem. Biophys. Res. Commun. 438 (4) (2013) 709714. Copyright 2013 Elsevier Inc. (C) Reprinted with permission from S. Lee, J. Mandic, K. J. Van Vliet, Chemomechanical mapping of ligand-receptor binding kinetics on cell, Proc. Natl. Acad. Sci. USA 104(23) (2007) 96099614. Copyright 2007 National Academy of Sciences. (D) Reprinted with permission from A.C. Dumitru, D. Mohammed, M. Maja, J. Yang, S. Verstraeten, A. del Campo, et al., Label-free imaging of cholesterol assemblies reveals hidden nanomechanics of breast cancer cells, Adv. Sci. 7(22) (2020) 2002643. Copyright 2020 The authors.

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biomolecules on the surface of adherent cells have also been investigated, such as luteinizing hormone-releasing hormone receptors on HeLa cells [77], tenascin-C on U251 cells [78], integrins on pancreatic cancer cells [79], and so on. In addition to measure the rupture forces of receptorligand molecular pair, by obtaining arrays of the force curves at the local areas on the cell surface at AFM force volume mode, the nanoscale distribution of receptor molecules on cell surface can be visualized [80], as shown in Fig. 8.11B. With the use of functionalized tips, the heterogeneous distributions of Fcγ receptors (FcγR) on the local surface areas of macrophages were mapped (II in Fig. 8.11B, each gray/bright pixel denotes a Fcγ unbinding event). After blocking experiments, the number of gray and bright pixels in the force map significantly decreased (III in Fig. 8.11B), confirming the specificity of the measured molecular interactions. Particularly, specific unbinding events were also largely observed on the cells without blocking using the same AFM tip (IV in Fig. 8.11B), indicating that the functionalized AFM tip was still biologically active. TREC mode AFM has been widely used to investigate the spatial distributions of specific biomolecules on the surface of adherent cells. Readers are referred to Chapter 1 for the principles of TREC mode AFM. In brief, the vibrating tip carrying ligands is controlled to raster scan the cell surface, and the topographical image and recognition image of the cell surface can be generated simultaneously. In 2007 Lee et al. [81] investigated the vascular endothelial growth factor receptor-2 (VEGFR2) on both chemically fixed and living human umbilical vein endothelial cells (HUVECs) by TREC mode AFM, as shown in Fig. 8.11C. The AFM tips functionalized with anti-VEGFR2 antibodies were used to perform TREC mode imaging on HUVECs. From the recognition images (II in Fig. 8.11C), the sites of VEGFR2 on the cell surface were clearly observed, which were denoted by the black pixels (a typical recognition site was circled). After adding antiVEGFR2 antibodies to block the VEGFR2 on cell surface, the recognition events disappeared significantly (III and IV in Fig. 8.11C). Particularly, the number of recognition sites did not decrease after the addition of another type of antibody targeting a different HUVEC receptor, demonstrating that the recognition sites in the recognition images were due to the unbinding interactions between VEGFR2 on HUVEC and anti-VEGFR2 antibody on AFM tip. In 2008 Chtcheglova et al. [82] investigated the potassium channel proteins on HEK 293 cells by TREC mode AFM imaging. The obtained recognition images show that the potassium channel proteins clustered into microdomains with dimensions ranging from 30 to 350 nm on the cell surface. After the addition of ergtoxin 1 which is a type of potassium channel blocker, the recognition sites vanished significantly while no changes were observed in the topographical image, providing direct evidence to the binding of ergtoxin 1 to K1 channel. In 2014 Zhang et al. [83] utilized TREC mode AFM imaging to investigate the human

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gonadotropin-releasing hormone receptor (GnRH-R) on human bladder cancer cells. The recognition images show that the GnRH-R formed nanodomains on the cell surface. To verify the specificity of the recognition spots, successive TREC scanning was performed on the same area of the cell surface and the results show that the recognition spots were stable. Besides, the results obtained after the addition of free GnRH1 molecules show that almost all recognition spots disappeared, confirming that the recognition events were from the unbinding interactions between GnRH-R on cell surface and GnRH1 on AFM tip. Further, statistical analysis results of the recognition images show that the area of the nanodomains formed by GnRH-R was in the range of 10028,000 nm2, improving our understanding of the local distributions of GnRH-R on bladder cancer cells with molecular resolution. The molecular interactions on living adherent cells have also been studied by PFT-based multiparametric AFM imaging to correlate cellular biochemical properties with cellular mechanical properties. In 2020 Dumitru et al. [84] investigated the relationships between membrane compositions and cell mechanics as well as cell functions during tumor progression by PFT-based multiparametric imaging using functionalized tips, as shown in Fig. 8.11D. Three types of MCF10 cell lines with different invasive capabilities were used, including MCF10A (benign), MCF10AT (premalignant, noninvasive), and MCF10CA1a (malignant, invasive). The theta-toxin molecules, which can bind cholesterol molecules exposed at the external leaflet of the plasma membrane of MCF10A cells, were attached to the AFM tip via NHS-PEG-acetal linker molecules. By using the functionalized tips, the molecular interactions between cholesterol on cell surface and theta-toxin on AFM tip can be visualized from the adhesion force image obtained at PFT mode. Besides, MCF10A (fluorescently labeled, green) and MCF10CA1a cells (unlabeled) were cocultured, and fields of view in which both types of cells were adjacent were selected for PFT imaging (I in Fig. 8.11D). Topographical image (II in Fig. 8.11D), adhesion force image (III in Fig. 8.11D) and Young’s modulus image (IV in Fig. 8.11D) of adjacent MCF10A and MCFCA1a cells were obtained simultaneously in the same scanning, providing a direct comparison of the molecular interactions and cell mechanics between normal cells and malignant cells. From Young’s modulus image, we can clearly see that normal cells (MCF10A) were significantly stiffer than malignant cells (MCF10CA1a). From the adhesion force image, we can see that a higher density of adhesion events was observed on cancerous cells, suggesting that there were increased presence of cholesterol-enriched areas on the surface of malignant cells. After treating cells with MβCD to deplete cholesterol, the results show that the cholesterol molecular binding probability and cellular Young’s modulus decreased significantly for all of the three types

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of cells, revealing the relationship between cell membrane component and cell mechanics. The study vividly demonstrates the capabilities of PFT-based multiparametric AFM imaging in directly and visually investigating the correlation between specific molecular behaviors and cellular mechanics on single living cells.

8.5 Visualizing the surface structures and their dynamics of single living suspended animal cells Individual living suspended animal cells have also been imaged by AFM. Since suspended animal cells cannot naturally attach to and spread on the substrate like adherent cells, immobilization strategies are required for utilizing AFM to image suspended animal cells. The porous filter membrane-based mechanical trapping developed for immobilizing microbial cells (readers are referred to Chapter 7 for imaging microbial cells by AFM) is not suitable for suspended animal cells, since suspended animal cells are much larger than the sizes of commercially available porous filter membranes. Coating the substrate with a layer of poly-L-lysine allows attaching suspended animal cells onto the substrate, but this immobilization is weak and the lateral forces exerted by the AFM probe during scanning can easily lead to the movement of the trapped cells. To image the surface structures of living suspended animal cells by AFM, a method combining microfabricated pillar array mechanical trapping and poly-L-lysine electrostatic adsorption has been developed [85,86], as shown in Fig. 8.12. The substrate of the pillar chip is coated by a layer of poly-L-lysine to adsorb the cell in the vertical direction and the pillar arrays surrounding the cell mechanically trap the cell in the horizontal direction, allowing the threedimensional immobilization of suspended animal cells (I in Fig. 8.12A). The pillar array chip was fabricated by photolithography on a silicon substrate and the distance between pillars was close to the to the size of the cell being immobilized. The fabricated pillar array chip can be characterized by SEM (II in Fig. 8.12A), and also AFM can be used to characterize the geometrical features of the pillar arrays (III and IV in Fig. 8.12A). In practice, the geometrical parameters of the fabricated pillar arrays (e.g., pillar height, pillar diameter, the distance between adjacent pillars) need to be optimized according to the size of the cells being investigated. To demonstrate the effectiveness of the method, Raji (a human B lymphoblastoid cell line) cells were used as an example of suspended animal cell. The pillar array chip coated with poly-L-lysine in advance was glued to a glass slide using a small piece of double-sided tape. The Raji cell suspension was dropped onto the pillar array chip and incubated for 1 min, after which the specimen was placed in a Petri dish containing PBS. The Petri dish was then placed onto the sample stage of AFM for imaging experiments. Under the

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FIGURE 8.12 Imaging single living suspended animal cells by atomic force microscopy (AFM) based on the immobilization integrating pillar array mechanical trapping with poly-L-lysine electrostatic adsorption. (A) Immobilizing suspended animal cells for AFM imaging. (I) Schematic illustration of the immobilization method. (II) SEM image of the fabricated pillar array chip. (III) AFM height image of the pillars. (IV) Section profile curve (taken along the dashed line in III) showing the height of the pillars. (B) Results of imaging single living lymphoma Raji cells. (I) AFM height images of the whole cell. (II, III) AFM height image (II) and the corresponding three-dimensional image (III) of the local area on the cell surface. (IV) Section profile curve (taken along the dashed line in I) of the cell trapped in pillars. (C) Results of rituximab-induced topographical changes of Raji cells. (I, II) AFM height images of a Raji cell after the treatment of 0.2 mg/mL rituximab for 2 h. (III, IV) AFM height images of another Raji cell after the treatment of 0.5 mg/mL rituximab for 2 h. Source: (B) (I, II) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Z. Dong, O. Tabata, et al., Imaging and measuring the rituximab-induced changes of mechanical properties in B-lymphoma cells using atomic force microscopy, Biochem. Biophys. Res. Commun. 404 (2) (2011) 689694. Copyright 2010 Elsevier Inc. (C) Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Z. Dong, X. Xiao, et al., Drug-induced changes of topography and elasticity in living B lymphoma cells based on atomic force microscopy, Acta Phys. Chim. Sin. 28 (6) (2012) 15021508. Copyright 2012 Editorial office of Acta Physico-Chimica Sinica.

guidance of optical microscopy, AFM probe was moved to the trapped cells. Notably, the pillar array chip based on silicon was opaque, and thus it was not suitable for the studies of AFM set up on an inverted optical microscope. Pillar array chips fabricated with transparent materials will suit the AFM with an inverted optical microscope. Here a commercial AFM with a lateral view optical microscope was used. The experimental results clearly show that single living Raji cells could be imaged by AFM under

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aqueous conditions at tapping mode based on the immobilization of pillar trapping and poly-L-lysine adsorption (Fig. 8.12B). From the AFM image, the cell immobilized in four pillars was distinctly observed (I in Fig. 8.12B). Besides, the local structures on the living cell were visualized by AFM imaging (II and III in Fig. 8.12B). With the use of this immobilization method, drug-induced topographical changes of living Raji cells were revealed by AFM, as shown in Fig. 8.12C. Rituximab, a chimeric monoclonal antibody (incorporating human immunoglobulin G1 heavy-chain sequences and murine immunoglobulin variable regions) targeting the human CD20 antigen on B cells, is broadly used in the clinical treatment of B-cell lymphomas [87] and here the effects of rituximab on the surface topography of individual living Raji cells were examined. AFM imaging results show that Raji cells became more corrugated after the treatment of 0.2 mg/mL rituximab for 2 h (I and II in Fig. 8.12C). When Raji cells were treated by 0.5 mg/mL rituximab for 2 h, tubercle structures (denoted by the red arrows) appeared on the cell surface (III and IV in Fig. 8.12C), improving our understanding of the effects of rituximab on lymphoma cells. The results demonstrate the capabilities of AFM in imaging the surface structures of single living suspended animal cells based on the threedimensional immobilization, which will benefit investigating the biomechanical issues involved in the physiological and pathological processes of suspended animal cells.

8.6 Detecting the mechanical cues involved in the activities of lymphoma cells AFM single-cell mechanical assay has been used to correlate the mechanical properties of hematologic tumor cells with their invasive capabilities [88], as shown in Fig. 8.13. Four types of hematologic cells were used, including red blood cells (RBCs), Raji cells, Hut 78 cells, and K562 cells. To better characterize the mechanical properties of the whole cells, the AFM cantilever carrying a spherical tip was used. Based on the AFM micromanipulations under the guidance of optical microscopy, a microsphere was glued to the end of a tipless cantilever to prepare the spherical tip (the inset in Fig. 8.13B). AFM imaging results clearly show the bi-concave disk shape of RBCs and the round shapes of the other three types of cells (Fig. 8.13A). After attaching living cells onto the poly-L-lysine-coated glass slides and incubated for 1 min, the samples were placed in a Petri dish containing buffer solution and the AFM spherical probe was moved to the cells to obtain force curves. Although only five cells were measured for each type of cell, the statistical results show that there were significant differences in cellular Young’s modulus among the four types of cells (Fig. 8.13B). Among the four types of

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FIGURE 8.13 Detecting the mechanical properties of RBCs and hematologic tumor cells with different aggressive capabilities by AFM. (A) AFM height images of the four types of cells. Cells were chemically fixed for AFM imaging. (I) RBC. (II) Raji. (III) Hut. (IV) K562. (B) Statistical histogram of Young’s modulus of the four types of cells. The inset is the SEM image of the spherical probe used in the study. Source: Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, Z. Dong, X. Xiao, and et al., Atomic force microscopy imaging and mechanical properties measurement of red blood cells and aggressive cancer cells, Sci. China Life Sci. 55 (11) (2012) 968973. Copyright 2012 The authors.

cells, RBCs had the smallest Young’s modulus (0.10.2 kPa). This may be due to the unique structures of RBCs. We know that mature RBCs do not have nucleus and organelles, which may cause the extreme softness of RBCs. For the remaining three types of cells, the results show that aggressive cells were much softer than indolent cells. Raji cells are from Burkitt’s lymphoma which is a highly aggressive B-cell non-Hodgkin lymphoma and is the fastest-growing human tumor [89], and here we can see that Young’s modulus of Raji cells (0.20.4 kPa) was much smaller than that of Hut (11.4 kPa) and K562 cells (0.60.7 kPa). Hut cells are from cutaneous T-cell lymphoma which is typically a chronic disease that progresses slowly and has an indolent evolution [90], whereas K562 cells are from chronic myelogenous leukemia which is commonly a slow growing leukemia [91]. Hut cells and K562 cells are less aggressive than Raji cells, and Hut cells and K562 cells were stiffer than Raji cells. The study shows the potential relationship between cell mechanics and cell invasiveness. Nevertheless, further studies are required to reveal the underlying mechanisms guiding the alterations of cell mechanics during the pathological processes of hematologic tumor cells. The structural and mechanical alterations of single lymphoma Raji cells taking place during the effect of rituximab-induced complement-dependent cytotoxicity (CDC) have been revealed by AFM [92], as shown in Fig. 8.14. Studies performed in vitro have shown that the binding of rituximab to CD20 results in the depletion of B cells via three main killing mechanisms, including programmed cell death (PCD), complement-dependent

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FIGURE 8.14 Structural and mechanical changes of single lymphoma Raji cells during rituximab-induced CDC effect revealed by AFM. (A) Structural changes during CDC effect. (I and II) AFM height images of a Raji cell from control group. The white arrows denote the microvilli on cell surface. (III and IV) AFM deflection image (III) and height image (IV) of the Raji cell with CDC effect showing the micropores on cell surface (denoted by yellow arrows) as well as the cytoplasm efflux (denoted by red asterisks). (V and VI) AFM height images of Raji cells with CDC effect showing the cellular debris with large micropores (denoted by yellow arrows). (B) Mechanical dynamics of cells during CDC effect. (I) Statistical histogram of the changes in cellular Young’s modulus during CDC effect. (IIIV) Optical/fluorescence microscopy images of moving AFM probe to the cells. (II) Raji cells from control group. (III) Raji cells after treatment but without CDC effect. (IV) Raji cells after treatment with CDC effect. Source: Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Quantitative analysis of drug-induced complement-mediated cytotoxic effect on single tumor cells using atomic force microscopy and fluorescence microscopy, IEEE Trans. Nanobiosci. 14(1) (2015) 8494. Copyright 2014 IEEE.

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cytotoxicity (CDC), and antibody-dependent cellular cytotoxicity (ADCC) [93]. For the effect of CDC, the complement protein C1q binds to the Fc domain of rituximab after the binding of rituximab to CD20 on B cell, which activates the classical complement pathway [94]. The final product of CDC is the generation of membrane attack complex (MAC) on the B cell, through which small molecules such as water molecules and ions can freely enter the cell to cause the death of the cell. For observing the rituximab-induced CDC effect, Raji cells were cultured in RPMI-1640 medium containing rituximab and human serum at 37 C (5% CO2) for 2 h. After incubation, Raji cells were stained with propidium iodide (PI) dye solution and then Raji cells were attached to the poly-L-lysine-coated glass slides. For AFM topographical imaging of Raji cells, cells were fixed by 4% paraformaldehyde for 30 min. For AFM mechanical measurements of Raji cells, cells were not chemically fixed. AFM imaging results (III and IV in Fig. 8.14A) remarkably show the appearance of micropores (typically denoted by the yellow arrows) on the cell surface as well as the cytoplasm efflux from the cell (denoted by the red asterisks). Particularly, AFM images show that some cells lysed and the flat cellular debris with large micropores (typically denoted by the yellow arrows) was observed (V and VI in Fig. 8.14A). Incubating Raji cells with rituximab and human serum could activate the rituximab’s CDC effect to form the MAC on the cell surface, which was responsible for the porous structures on the cell surface as well as the subsequent structural changes of the cell (e.g., cytoplasm efflux, cellular lysis). For control, the surface of Raji cells cultured in RPMI-1640 medium was intact (I and II in Fig. 8.14A). An interesting phenomenon was that the microvilli on Raji cells were observed from the AFM images (typically denoted by the white arrows). Microvilli are found on almost all cell types, particularly on lymphocytes (as shown in Fig. 8.1BIV) [95]. Notably, here the microvilli were observed on chemically fixed Raji cells. In the future, directly imaging the individual microvilli on living lymphocytes by AFM will be quite meaningful for understanding the behaviors of lymphocytes. With the use of AFM indentation assay, the mechanical changes of Raji cells during the rituximab’s CDC effect were revealed, as shown in Fig. 8.14B. For Raji cells incubated with rituximab and human serum, some cells exhibited red PI fluorescence and these cells were with CDC effect, while some cells did not exhibit red PI fluorescence and these cells were without CDC effect. Young’s modulus values of Raji cells from control group (Raji cells cultured in cell growth medium) were also measured. Under the guidance of optical/fluorescence microscopy, AFM probe was moved to the cells to perform indentation assay (IIIV in Fig. 8.14B). The results of AFM measurements (I in Fig. 8.14B) show that, during the rituximab-induced CDC effect, cellular Young’s modulus first decreased (after treatment without CDC) and finally increased (after treatment with CDC) significantly. For the cells after treatment without CDC, though the

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cell surface was intact, rituximab’s PCD effect could cause the structural changes of the cell and might thus cause the mechanical alterations. For the cells with CDC effect, cell structures changed significantly (as shown in Fig. 8.14A), which may cause the changes of cell mechanics. Overall, the results reveal the structural and mechanical dynamics of single lymphoma cells during the rituximab’s CDC effect, providing novel insights into the antibody-dependent immune therapy of tumors. AFM has also been used to reveal the structural and mechanical changes during the rituximab-induced ADCC effect [96], as shown in Fig. 8.15. For rituximab’s ADCC effect, after the binding of rituximab to the CD20 on B cell, the Fc domain of rituximab binds to the Fcγ receptor on the effector cell (such as NK cell and macrophage) to recruit effector cells to kill the B cell [94]. NK cell is able to release cytotoxic granules to kill the B cell, while macrophage can deplete the B cell via phagocytosis. Here AFM was utilized to investigate the rituximab-induced macrophage phagocytosis against B lymphoma Raji cells. Since two different types of cells (lymphoma Raji cell, macrophage) were involved in the rituximab’s ADCC effect, Raji cells were fluorescently stained to facilitate distinguishing the two types of cells. Raji cells were first stained with carboxyfluorescein succinimidyl ester (CFSE) for 10 min at 37 C. After removing the free CFSE by centrifugation, Raji cells were incubated with rituximab for 10 min at 37 C. Subsequently, Raji cells were incubated with RAW 264.7 (a macrophage cell line) cells. The cocultured Raji and macrophage cells were chemically fixed, and then AFM images of the cells were obtained under the guidance of optical and fluorescent microscopy. From the overlay of optical bright field image and CFSE fluorescent image (I and IV in Fig. 8.15A), lymphoma Raji cells could be clearly identified by the fluorescence and macrophages could be identified according to their adherent morphology. AFM images distinctly show the detailed situations between Raji cells and macrophages. Some macrophages were beginning to engulf the Raji cells (II and III in Fig. 8.15A), while some macrophages had engulfed some portions of the Raji cells (V and VI in Fig. 8.15A). Further studies show that though living macrophages could be well imaged by AFM, it was challenging to image living macrophages which were engulfing Raji cells. Due to the weak binding of Raji cells to macrophages, the scanning AFM tip could easily cause the movement of Raji cells on macrophages. Sophisticated immobilizing strategies are required to image living macrophages with lymphoma Raji cells by AFM, such as the pillar array chip as shown in Fig. 8.12. The mechanical changes of macrophages during phagocytosis of Raji cells were then measured with the use of AFM indentation assay. Under the guidance of optical microscopy (the inset in Fig. 8.15B), AFM probe was moved to macrophages engulfing Raji cells to obtain force curves. Force curves were also obtained on macrophages without Raji

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FIGURE 8.15 Cellular structural and mechanical changes during rituximab-induced macrophage phagocytosis against lymphoma Raji cells revealed by atomic force microscopy (AFM). (A) AFM topographical imaging shows the details of structural dynamics during macrophage phagocytosis against Raji cells. (IIII) A macrophage was beginning to engulf a Raji cell. (IV-VI) A macrophage has engulfed some portions of a Raji cell. (I and IV) Overlay of optical bright field and fluorescent images. (II, III, V, and VI) AFM deflection images. (B) AFM indentation assay shows the mechanical alterations of macrophages during phagocytosis against Raji cells. The insets are the optical images of macrophages with or without Raji cells. Source: Reprinted with permission from M. Li, L. Liu, N. Xi, Y. Wang, X. Xiao, W. Zhang, Nanoscale imaging and mechanical analysis of Fc receptor-mediated macrophage phagocytosis against cancer cells, Langmuir 30 (6) (2014) 16091621. Copyright 2014 American Chemical Society.

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cells (the inset in Fig. 8.15B). For each type of macrophage, including macrophage engulfing Raji cell and macrophage without Raji cell, five macrophages were measured. AFM measurement results clearly show that (Fig. 8.15B) macrophages became stiffer when they were engulfing Raji cells, indicating the mechanical changes of macrophages during the phagocytosis. Upon the docking of target cells on macrophages to activate the macrophage phagocytosis, rapid reorganizations of the cytoskeletons of macrophages take place to increase phagocytic receptor diffusion for the phagocytosis of the target cells [97]. Hence, these cytoskeleton changes may cause the stiffening of macrophages during the phagocytosis. Overall, the experimental results reveal the cellular structural and mechanical changes during rituximab-induced macrophage phagocytosis against lymphoma cells, deepening our understanding of the antibody-dependent ADCC effect in immune therapy. The effects of rituximab on chemotherapy of lymphomas have been investigated by AFM in vitro at single-cell level [98], as shown in Fig. 8.16. Since its first approval in 1997, rituximab has revolutionized the treatment of B-cell malignancies and has now become a standard component of first-line therapy for follicular lymphoma, diffuse large B-cell lymphoma, chronic lymphocytic leukemia, and mantle cell lymphoma [99]. A notable point is that rituximab is commonly approved in combination with chemotherapy for the treatment of B-cell malignancies [100]. Despite the unprecedented success of rituximab, clinical applications of rituximab have also shown that some patients do not respond to rituximab and others experience relapse after initial response to therapy [99]. Particularly, the exact mechanisms of action of rituximab in vivo are still unclear [100]. Here, with the use of AFM, the structural and mechanical changes of single lymphoma Raji cells during the synergistic actions of rituximab and chemotherapy drugs were revealed. Two chemotherapy drugs were used, including cisplatin and cytarabine. Raji cells were incubated with different drug combinations and drug concentrations at 37 C (5% CO2), after which Raji cells were attached to the poly-L-lysine-coated glass slides. For AFM topographical imaging, cells were chemically fixed

FIGURE 8.16 Structural and mechanical changes of lymphoma Raji cells after the treatment of different combinations of drugs revealed by atomic force microscopy (AFM). (A) AFM deflection images of Raji cells treated by different drug combinations. (I and II) Cells treated by cisplatin alone. (III and IV) Cells treated by cisplatin and rituximab. (V and VI) Cells treated by cisplatin, cytarabine, and rituximab. The insets in (V and VI) are the AFM images of the whole cell. (B) Typical force curves (only approach curves are shown) obtained after the treatment of different drug combinations as well as Young’s modulus calculation results of the force curves. Source: Reprinted with permission from M. Li, X. Xiao, L. Liu, N. Xi, Y. Wang, Nanoscale quantifying the effects of targeted drug on chemotherapy in lymphoma treatment using atomic force microscopy, IEEE Trans. Biomed. Eng. 63 (10) (2016) 21872199. Copyright 2016 IEEE.

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by 4% paraformaldehyde for 30 min and then AFM images were obtained in PBS. For AFM mechanical assay, Raji cells adsorbed on the glass slides were directly measured without chemical fixation. AFM imaging results show that many micropores appeared on the cell surface after the stimulation of cisplatin alone (I and II in Fig. 8.16A, denoted by the red arrows). After the treatment of the combination of cisplatin and rituximab, many blebs were formed on the cell surface (III and IV in Fig. 8.16A, denoted by the yellow arrows). After the treatment of the combination of cisplatin, cytarabine, and rituximab, clustered blebs were formed on the cell surface (V in Fig. 8.16A). Besides, some cells lysed and the nuclei (denoted by the white asterisk) were exposed (VI in Fig. 8.16A). To quantitatively analyze the effects of the different combinations of drugs on the topographical structures of the cells, the cell surface roughness was calculated from the obtained AFM height images. The statistical roughness results show that cells treated with the combination of rituximab and chemotherapy drugs were rougher than the cells treated by chemotherapy drugs alone. The mechanical alterations of Raji cells after the treatment of different combinations of drugs were then measured. For each situation (different combinations of drugs, different stimulation times, different drug concentrations), approximately 20 cells were measured. Typical force curves obtained on Raji cells after the treatment of different combinations of drugs are shown in Fig. 8.16B. The statistical results show that cells treated by the combination of rituximab and chemotherapy drugs were significantly stiffer than the cells treated by chemotherapy drugs alone. Overall, the experimental results distinctly show that rituximab could enhance the killing effects of chemotherapy drugs at single-cell level, providing a novel approach to investigate the synergistic interactions between drugs on cells in vitro. A method of utilizing AFM to detect the mechanical properties of living primary B lymphocytes has also been developed [101], as shown in Fig. 8.17. So far, the studies of utilizing AFM to measure the mechanical properties of animal cells are commonly performed on cell lines cultured in vitro, whereas it is well known that cell lines cultured in vitro are quite different from the cells in the body. The results obtained on the cell lines may not fully reflect the in vivo behaviors of the cells in the body, and thus directly probing the mechanical properties of the primary cells prepared from the clinical patients significantly benefits understanding the mechanical behaviors of cells under near in vivo conditions. Here, as an example, the peripheral blood (treated with heparin for anticoagulation) extracted from healthy volunteers was used. To isolate the B cells from the blood, the peripheral blood mononuclear cells (PBMCs) were first isolated via density gradient centrifugation. After the density gradient centrifugation, the blood layered and the PBMCs were collected (I in Fig. 8.17A). Subsequently, the B cells in PBMCs were collected by magnetic sorting

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FIGURE 8.17 Detecting the mechanical properties of primary B cells by atomic force microscopy (AFM). (A) The process of isolating B cells from the peripheral blood. (I) Optical microscopy image of the layered blood after density gradient centrifugation. (II) Schematic illustration of isolating B cells from PBMCs based on magnetic sorting. (III) Optical microscopy images of the isolated B cells. (B) Confirming the activity and specificity of the isolated B cells by fluorescence microscopy. (C) Characterizing the morphology and geometrical features of primary B cells by AFM. (D) Measuring the mechanical properties of living primary B cells. (I) Optical images of moving AFM probe to the B cells. (II) Measuring cellular elasticity. Fitting the indentation curve converted from the force curve gives cellular Young’s modulus. (III) Measuring cellular viscoelasticity. Fitting the relaxation curve gives cellular relaxation times. (E) Statistical histograms showing the comparison in cellular mechanics between primary healthy B cells and Raji cells. (I) Cellular Young’s modulus. (II) Cellular relaxation time τ1. (III) Cellular relaxation time τ2. Source: Reprinted with permission from M. Li, L. Liu, X. Xiao, N. Xi, Y. Wang, Viscoelastic properties measurement of human lymphocytes by atomic force microscopy based on magnetic beads cell isolation, IEEE Trans. Nanobiosci. 15 (5) (2016) 398411. Copyright 2016 IEEE.

with the use of magnetic beads coated with anti-CD19 antibodies (II in Fig. 8.17A). The PBMCs were incubated with CD19 magnetic beads. After incubation, the PBMCs were aspirated to a separate column to pass through a magnetic field. Non-B cells could flow out of the magnetic field, while B cells were trapped in the magnetic field. The separation column was then removed from the magnetic field and the trapped B cells (III in Fig. 8.17A) in the column were then collected by pushing the plunger into the column. To verify that the collected cells were B cells, fluorescence experiments were performed, as shown in Fig. 8.17B. The isolated cells did not exhibit fluorescence after the treatment of PI dye and the cells exhibited fluorescence in response to CFSE dye, confirming that the cells were

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alive. Besides, cells exhibited fluorescence after the labeling of fluoresceinconjugated anti-CD20 antibodies (CD20 is a specific cell surface biomarker of B cells), showing that the cells were B cells. AFM imaging was then performed on the isolated B cells, showing the round shape and smooth surface of the primary B cells (I and II in Fig. 8.17C). The geometrical features of cells were then extracted from the obtained AFM height images and the statistical results show that the primary B cells were much smaller than lymphoma Raji cells (III in Fig. 8.17C). Under the guidance of optical microscopy, AFM probe was moved to the living primary B cells attached on the poly-L-lysine-coated glass slides to perform indentation assay (I in Fig. 8.17D) to simultaneously measure the elastic and viscoelastic properties of cells (the process of simultaneously measuring cellular elastic and viscoelastic properties is the same as that in Fig. 8.6). Cellular Young’s modulus was obtained from the force curves (II in Fig. 8.17D), and cellular relaxation time was obtained from the relaxation curves (III in Fig. 8.17D). Statistical results show that Raji cells were significantly softer than primary B cells (I in Fig. 8.17E). Though there were no significant differences in cellular relaxation time τ1 between Raji cells and primary B cells (II in Fig. 8.17E), the cellular relaxation time τ2 of Raji cells was much larger than that of primary B cells. The results show the different mechanical properties between Raji cells and primary B cells. Raji cells are cancerous B cells cultured in vitro, while the primary B cells used here were healthy cells from the peripheral blood of healthy volunteers. The different structures between Raji cells and primary healthy B cells may cause the different cellular mechanical properties. Further studies show that the mechanical behaviors of primary B cells in bone marrow were also different from those in peripheral blood [102]. Overall, the studies demonstrate the capabilities of AFM in detecting the mechanical properties of primary cells, which offers novel possibilities to understand the mechanical cues in life activities.

8.7 Probing the molecular activities on the surface of primary lymphoma cells Utilizing AFM to investigate the specific molecular activities on the surface of primary cancerous cells from clinical lymphoma patients has been explored [103105], as shown in Fig. 8.18. AFM-based single-molecule techniques have become a powerful tool for probing the molecular activities taking place on the cell surface, but so far these studies are commonly performed on the cell lines cultured in vitro. The huge differences between cell lines in vitro and cells in vivo cause that the results obtained on cell lines cannot faithfully reflect the real behaviors of molecules on cells in vivo. Here, AFM-based SMFS was used to probe the molecular activities on the surface of primary cancerous cells from clinical lymphoma patients.

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FIGURE 8.18 Detecting the CD20 molecules on the primary lymphoma cells by atomic force microscopy (AFM). (A) Schematic illustration of detecting the CD20s on malignant B cells based on the ROR1 fluorescent labeling. The inset shows the ROR1 fluorescent labeling of lymphoma Raji cells. (B) Bone marrow specimen obtained from the clinical B lymphoma patients. (C) Optical bright field image (I) and corresponding ROR1 fluorescence image (II) of the bone marrow cells. (D) AFM imaging showing the different structures and geometrical features between tumor cells and healthy cells. (E) Typical force curves obtained on tumor cells (I) and healthy cells (II). (F) Statistical histograms of the molecular unbinding forces measured on tumor cells (I) and healthy cells (II), respectively. (G) Mapping the spatial distributions of CD20s on tumor cells. (I) Comparison of molecular distribution maps between tumor cells and healthy cells. (II) Distribution maps of CD20s on tumor cells obtained before and after blocking experiments. Source: (A, C, D, F, and G) Reprinted with permission from M. Li, X. Xiao, L. Liu, N. Xi, Y. Wang, Z. Dong, et al., Nanoscale mapping and organization analysis of target proteins on cancer cells from B-cell lymphoma patients, Exp. Cell Res. 319 (18) (2013) 28122821. Copyright 2013 Elsevier Inc. (B) Reprinted with permission from M. Li, X. Xiao, W. Zhang, L. Liu, N. Xi, Y. Wang, Nanoscale distribution of CD20 on B-cell lymphoma tumor cells and its potential role in the clinical efficacy of rituximab, J. Microsc. 254 (1) (2014) 1930. Copyright 2014 The authors. (E) Reprinted with permission from M. Li, X. Xiao, L. Liu, N. Xi, Y. Wang, Z. Dong, et al., Atomic force microscopy study of the antigen-antibody binding force on patient cancer cells based on ROR1 fluorescence recognition, J. Mol. Recognit. 26 (9) (2013) 432438. Copyright 2013 John Wiley & Sons, Ltd.

The bone marrow obtained from B-cell lymphoma patients with bone marrow infiltration was used. In the bone marrow, tumor cells were mixed with healthy cells. To probe the molecular activities on tumor cells, we need to first recognize the tumor cells in the bone marrow. Studies have shown that the oncofetal antigen receptor tyrosine kinase orphan receptor 1 (ROR1) is expressed on malignant B cells, but not on normal B cells [106], and hence ROR1 fluorescent labeling was used to specifically recognize the tumor cells in the bone marrow. Under the guidance of ROR1 fluorescence, AFM probe could be moved to the tumor cells to perform SMFS assay to detect the interactions between CD20 on malignant B cells

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and rituximab on AFM tip (Fig. 8.18A). The B lymphoma Raji cells were first examined with ROR1 fluorescent staining. The results clearly show the bright fluorescence of Raji cells after ROR1 staining (the inset in Fig. 8.18A), suggesting that there were ROR1s on Raji cells. The Raji cells with ROR1 fluorescent labeling were further labeled with fluoresceinconjugated anti-CD20 antibodies. The results show that Raji cells exhibited anti-CD20 antibody fluorescence, indicating that the ROR1 labeling did not influence the detection of the CD20 molecules on Raji cells. Subsequently, the bone marrow specimen (Fig. 8.18B) was labeled with fluoresceinconjugated anti-ROR1 antibodies. From the typical optical bright field and ROR1 fluorescence images (Fig. 8.18C), the tumor cells that exhibited fluorescence were clearly identified. For control, ROR1 labeling experiments were performed on the peripheral blood of healthy volunteers and no fluorescence was observed, suggesting that normal cells did not express ROR1. AFM topographical imaging was then applied to characterize the morphology of primary tumor cells (I in Fig. 8.18D). AFM images of healthy cells were also recorded (II in Fig. 8.18D). Statistical results of cellular geometrical features extracted from the AFM height images of tumor cells and healthy cells distinctly show that tumor cells were much larger than healthy cells (III in Fig. 8.18D). Next, the functionalized probes (rituximabs were attached to the surface of AFM tip by PEG linkers) were used to detect the CD20 molecules on tumor cells. There were specific unbinding force peaks in the force curve obtained on tumor cells (I in Fig. 8.18E), while only unspecific force peaks appeared in the force curve obtained on healthy cells (II in Fig. 8.18E). Notably, here RBCs were used as healthy cells, since the bi-concave disk shape of RBCs is unique and RBCs can be visually confirmed from the optical images. The statistical results show that the probability of finding specific molecular unbinding events was about 17% for tumor cells (I in Fig. 8.18F), while the probability of finding unspecific molecular unbinding events on healthy cells was only 3% (II in Fig. 8.18F). Besides, the specific CD20-rituximab unbinding forces (about 54 pN) were significantly larger than the unspecific molecular forces (about 21 pN). By obtaining arrays of force curves at the local areas on cell surface at AFM force volume mode, the spatial distributions of CD20 molecules on the cell surface were mapped (I in Fig. 8.18G). After the addition of free rituximabs to block the CD20s on the cells, the specific molecular unbinding events significantly decreased (II in Fig. 8.18G), confirming that the measured specific molecular unbinding events were due to the interactions between CD20s on malignant B cells and rituximabs on AFM tips. Inspired by the method, the interactions between rituximabs and Fc receptors on primary NK cells prepared from clinical lymphoma patients were also investigated by AFM [107], providing a molecular basis for the rituximab’s ADCC effect for the immune therapy of lymphomas. Besides, with the use of rituximabfunctionalized AFM probes, the spatial distributions of CD20s on primary

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tumor cells were mapped simultaneously with the topography of the cells by PFT-based multiparametric AFM imaging [108], which benefits understanding the relationship between cellular structures and molecular activities directly on primary cells. Overall, the studies demonstrate the capabilities of AFM in detecting the molecular behaviors on the surface of primary tumor cells, which will be of potential significance for developing novel methods to investigate the molecular and cellular pathology of cancers.

8.8 Summary In the past decades, AFM has been broadly utilized to characterize the structures, mechanics, and molecular activities of individual animal cells, providing numerous novel insights into the mechanical cues in physiological and pathological processes and contributing much to the field of mechanobiology. For adherent animal cells, AFM is able to not only resolve the fine and fragile surface structures on living cells with unprecedented spatial resolution (Fig. 8.2), but also capture the dynamics of these structures (Figs. 8.3 and 8.4) during the life activities of living cells. With the use of AFM indentation assay, the elastic and viscoelastic properties of single living cells can be quantitatively measured (Figs. 8.5 and 8.6). AFM force volume mode, including PFT-based multiparametric imaging, allows simultaneously obtaining the topographical image and mechanical maps of living cells (Figs. 8.7 and 8.8). By attaching single living cells onto the AFM cantilever, the adhesive properties of single living cells can be precisely probed with the use of AFM-based SCFS (Fig. 8.9), and the AFM cantilever can be even used as a nanomechanical sensor to monitor the mechanical dynamics of single living cells adsorbed on the cantilever with highly temporal resolution (Fig. 8.10) to reveal the transient states of cells during life processes. With the use of AFM-based SMFS, the binding affinities as well as the nanoscale spatial distributions of specific biomolecules on the living cells can be revealed (Fig. 8.11). For suspended animal cells, AFM has also been used to image the surface structures on living cells (Fig. 8.12) and measure the dynamics of cellular mechanics during life activities (Figs. 8.138.16). Particularly, methods of utilizing AFM to detect the mechanical properties and molecular behaviors of primary cells have been established (Figs. 8.17 and 8.18). The methodologies of utilizing AFM to investigate the behaviors of adherent animal cells are potent now, and we will have much to look forward to as more adherent animal cells are detected by AFM. Nevertheless, studies of utilizing AFM to investigate the behaviors of living suspended animal cells are still relatively scarce. There is significant room for visualizing the fine structures (such as microvilli) of living suspended animal cells, which will

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require elaborate immobilization strategies. Besides, more studies performed on primary cells prepared from clinical patients with the use of AFM toolbox will bring novel insights into the underlying mechanisms guiding disease development.

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9 Characterizing the extracellular matrix for regulating cell behaviors by atomic force microscopy

9.1 Background The extracellular matrix (ECM) plays an important role in regulating the physiological and pathological processes of cells. ECM is the noncellular component present within all tissues and organs, and provides not only essential physical scaffolding for the cellular constituents but also initiates crucial biochemical and biomechanical cues that are required for tissue morphogenesis, differentiation, and homeostasis [1]. There are two main types of ECM that differ with regard to their location and composition, including basement membrane, which separates the epithelium from the surrounding stroma, and interstitial matrix which surrounds cells and encapsulates most tissues [2], as shown in Fig. 9.1A. The ECM is composed of two main classes of macromolecules, which are proteoglycans (PGs) and fibrous proteins [1]. The negative charge of many ECM molecules (particularly the PGs) and the large area that they occupy in tissues facilitate the interactions between ECM molecules and other charged molecules, such as growth factors and chemokines, thus influencing the local concentration or accessibility of these factors to the cells in ECM [3]. Virtually every cell in the body is exposed to ECM proteins, for example, epithelia and endothelia contact the basement membranes, cells in connective tissues are completely surrounded by the ECM, and even cells in the blood are exposed to soluble ECM proteins

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FIGURE 9.1 Histologic structures of extracellular matrix (ECM). (A) Schematic illustration of the mammalian matrisome. The ECM is composed of around 300 proteins, which consists of 43 collagen subunits, 36 proteoglycans (PGs), and approximately 200 complex glycoproteins. There are two main types of ECM: the interstitial connective tissue matrix and the basement membrane. The interstitial matrix surrounds cells and is mainly composed of collagen I and fibronectin, which provide structural scaffolding for tissues. The basement membrane is more compact than the interstitial matrix and mainly consists of collagen IV, laminins, heparan sulfate proteoglycans (HSPGs), and proteins. (B) SEM images of ECM fibrils generated by stromal fibroblasts. (I) After 1 h of culture, fibrils (typically denoted by the black row) appeared. (II) After 1 week of culture, the fibroblastproduced ECM had both individual fibrils (typically denoted by the black arrow) and fibrous mesh-like structures (typically denoted by asterisks). Source: (A) Reprinted with permission from C. Bonnans, J. Chou, Z. Werb, Remodelling the extracellular matrix in development and disease, Nat. Rev. Mol. Cell Biol. 15 (12) (2014) 786801. Copyright 2014 Macmillan Publishers Limited; (B) Reprinted with permission from R.A.B. Crabb, E.P. Chau, D.M. Decoteau, A. Hubel, Microstructural characteristics of extracellular matrix produced by stromal fibroblasts, Ann. Biomed. Eng. 34 (10) (2006) 16151627. Copyright 2006 Biomedical Engineering Society.

such as fibronectins [4]. The macromolecules that constitute the ECM are mainly produced locally by cells in the ECM, and, in most connective tissues, the ECM macromolecules are secreted by fibroblasts [5,6], as shown in Fig. 9.1B. Cells bind to the ECM mainly via the integrins on the cell surface to sense and respond to the biochemical (e.g., composition) and biomechanical cues (e.g., topography, stiffness, viscoelasticity, density,

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porosity, insolubility) of ECM [79]. The cellECM interactions are highly dynamic and reciprocal: on the one hand, cells are constantly creating, breaking down, or otherwise rearranging ECM components to change one or more properties of the ECM; on the other hand, any change in the ECM as a result of cellular activities will in turn influence adjacent cells and modify their behaviors [10]. The cellECM interactions are crucial in embryonic development and adult physiology, and are involved in numerous diseases such as cancer [11]. In cancer, the ECM is altered at the biochemical, biomechanical, architectural, and topographical levels, and the importance of the ECM in solid tumors is increasingly evident [12]. Studies have shown that the stiff tumor microenvironment, caused by tumor-associated ECM remodeling and characterized by increased ECM deposition, fiber alignment and cross-linking, actively promotes tumor progression and malignancy through increased integrin signaling [13]. Besides, circulating tumor cells exploit the flow mechanics (e.g., flow rates, vessel size, shear stress) of blood and lymphatic circulatory systems to successfully seed distant metastases [14]. Consequently, revealing the details involved in the behaviors of ECM will help us to better understand the complexity of life activities and diseases. AFM offers a unique and potent tool to characterize the structures and properties of native ECM at the nanoscale. So far diverse tools have been used to investigate the chemical, mechanical and topographical features of ECM for their influence on cellular behaviors [15]. Optical microscopy techniques have been widely used to observe the various ECM components (e.g., collagen, fibronectin, laminin) [1618], but it requires complex fluorescence staining (e.g., fixation, permeabilization, BSA blocking, primary antibody labeling, and labeling of secondary antibody conjugated with fluorescein) of the specimens which is often time-consuming. The topographical structures of ECM have been largely visualized by SEM or TEM [1921], but electron microscopy techniques require the fixation and dehydration of the specimens which may cause distortion of the ECM structures. Magnetic resonance elastography (MRE) has been broadly used to probe the mechanical properties of ECM in vivo as a diagnostic approach, particularly for the comparison between malignant tumors and normal tissues [2224], but MRE is unable to dissect the contribution of various ECM elements due to the low spatial resolution [25]. Compared with these tools, AFM is able to not only image the nanostructures of native ECM without any pretreatments but also measure the mechanical properties of individual ECM components (e.g., single collagen nanofibril [26]), which significantly provide complementary information on the behaviors of ECM and remarkably benefit revealing the regulatory role of ECM in cellular physiological and pathological processes from the perspective of mechanobiology. In the remaining of the chapter, applications of AFM in characterizing the structures and

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mechanical properties of various ECMs for regulating cellular behaviors are presented.

9.2 Detecting the mechanical properties of decellularized extracellular matrix The mechanical properties of organ-derived decellularized ECM can be detected by AFM with high spatial resolution. For the studies of ECM, the prerequisite is removing cells in the ECM to obtain the decellularized ECM. Decellularization methods have been developed for almost every tissue in the body and the selection of decellularization methods is dependent on the characteristics of the tissue to be decellularized, for example, mechanical delamination and immersion in decellularization agents are often suited for tissues that are small and relatively unstructured (e.g., esophagus, tendon, trachea, skeletal muscle, small intestine, urinary bladder, and dermis), and perfusion of decellularization agents through native vasculature is often used for whole organ (e.g., heart, liver, lung, kidney) decellularization [27]. Alternatively, the whole organ can also be cut into small pieces or slices and then decellularized as small biopsy samples [28]. In 2013 Luque et al. [29] firstly investigated the local mechanical properties of decellularized lung ECM by AFM under aqueous conditions. The whole trachea and lungs (I in Fig. 9.2A) were excised from exsanguinated rats. The decellularized lungs (II in Fig. 9.2A) were obtained after simultaneous tracheal instillation and arterial perfusion of a solution of triton X-100 (0.1%) and sodium dodecyl sulfate (1%). The 7-μm-thick lung sections were cut from the decellularized lungs and placed on positively charged glass slides. The specimens were then rinsed and immersed in PBS for AFM measurements. Under the guidance of optical microscopy, the AFM probe was positioned at different areas (e.g., pleural region, alveolar wall segment, and alveolar junction) of the lung ECM to perform an indentation assay. The results show that there were no significant differences in stiffness between alveolar wall segments and alveolar junctions, but the pleural regions were about threefold stiffer than alveolar walls, revealing the heterogeneous mechanics of the different parts of lung ECM. In 2014 Melo et al. [30] investigated the changes in ECM mechanics during lung diseases by AFM. The lung fibrosis was induced by intratracheal instillation of bleomycin and confirmed by Masson’s trichrome staining. The collagen I of the fibrotic lung ECM slices was fluorescently stained. Under the guidance of optical and fluorescent microscopy (III in Fig. 9.2A), the AFM probe was moved to the highly fibrotic sites (accumulation of collagen and stained with red fluorescence) and the preserved normal areas to perform indentation assay respectively. The results show that the fibrotic areas were significantly stiffer than normal areas (IV in Fig. 9.2A), suggesting that fibrosis

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FIGURE 9.2

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Characterizing the local mechanical properties of decellularized extracellular matrix (ECM) by atomic force microscopy (AFM). (A) Mechanics of decellularized lung ECM. (I, II) Photographic images of a mouse lung before (I) and after (II) decellularization. (III) Moving AFM probe to the fibrotic areas (red staining) and normal areas of the decellularized lung ECM to perform mechanical measurements respectively. (IV) Statistical results showing the different mechanical properties between fibrotic areas and normal areas. (B) Mechanics of decellularized heart ECM. (I) Optical microscopy image showing endocardium (EN) and myocardium regions (M) of the decellularized heart ECM. (II) Correlating ECM mechanics with ECM compositions. The left column shows large-scale fluorescence images. Collagen I and elastin are displayed in red and green, respectively. The middle column is an enlargement of the regions denoted by the squares (40 μm 3 40 μm) in the left column. The right column shows stiffness maps of the regions in the middle column obtained at AFM force volume mode. Source: (A) (I, II) Reprinted with permission from I. Jorba, J.J. Uriarte, N. Campillo, R. Farre, D. Navajas, Probing micromechanical properties of the extracellular matrix of soft tissues by atomic force microscopy, J. Cell. Physiol. 232 (1) (2017) 1926. Copyright 2016 Wiley Periodicals, Inc.; (III, IV) Reprinted with permission from E. Melo, N. Cardenes, E. Garreta, T. Luque, M. Rojas, D. navajas, et al., Inhomogeneity of local stiffness in the extracellular matrix scaffold of fibrotic mouse lungs, J. Mech. Behav. Biomed. Mater. 37 (2014) 186195. Copyright 2014 Elsevier Ltd.; (B) Reprinted with permission from I. Andreu, T. Luque, A. Sancho, B. Pelacho, O. Iglesias-Garcia, E. Melo, et al., Heterogeneous micromechanical properties of the extracellular matrix in healthy and infarcted hearts, Acta Biomater. 10 (7) (2014) 32353242. Copyright 2014 Elsevier Ltd.

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could cause the stiffening of ECM. In 2014 Andreu et al. [31] compared the mechanical properties of ECM in healthy and infarcted hearts with the use of AFM, as shown in Fig. 9.2B. For the modeling of infarcted hearts, the left anterior descending coronary artery of a mouse was ligated. Under the guidance of optical microscopy (I in Fig. 9.2B), the mechanical properties of different parts of the decellularized ECM from healthy hearts were measured by AFM, including endocardium, myocardium, and epicardium. For the infarcted hearts, AFM mechanical measurements were performed in the central area of the myocardium scar. The results show that the ECM of the myocardium scar was significantly stiffer than the ECM of healthy hearts. Particularly, combining AFM force volume mode with fluorescence microscopy allows correlating ECM mechanics with ECM compositions (II in Fig. 9.2B), showing that myocardial infarction scar had a more compact and homogeneous collagen composition which was associated with high stiffness compared with heathy ECM. Overall, these studies show the heterogeneous local mechanics of the ECM and reveal the relationships between ECM mechanics and diseases, providing novel insights into the indicative role of ECM in the physiological and pathological changes of living organisms. AFM has also been widely utilized to detect the mechanical properties of cultured cell-derived decellularized ECM. Cultured cell-derived decellularized ECM provides alternative scaffolds to tissue-/organ-derived decellularized ECM, and cell-derived decellularized ECM has several advantages (e.g., simple preparation process, reducing the risk of pathogen transfer caused by allogenic ECM, eliminating adverse host immune responses induced by xenogeneic ECM, and is easy to be modified) [32]. Several points need to be considered while preparing cultured cell-derived decellularized ECM, including culture medium compositions, initial culture substrates, decellularization methods, modification of the ECM, and cell types [33]. In 2011 Soucy et al. [34] investigated the mechanical properties of lung cellderived ECM by AFM. For doing so, human lung fibroblasts were grown on fibronectin-coated petri dishes for 710 days, after which various reagents (Triton X-100, NH4OH, DNase I) were used to remove the cellular and nuclear materials to obtain decellularized ECM. The mechanical properties of fibroblast-derived decellularized ECM were then measured by AFM indentation assay in PBS. To better characterize the mechanics of the ECM, the AFM cantilever carrying a microsphere was used. The results show that Young’s modulus of fibroblast-derived ECM was 105 6 14 Pa. In 2016 Tello et al. [35] investigated the mechanical properties of ECM generated by different types of fibroblasts by AFM. Two types of fibroblasts were used, including caveolin-1 wild-type mouse embryonic fibroblasts (WT-MEFs) and caveolin-1 knockout mouse embryonic fibroblasts (KO-MEFs). The results distinctly show that the ECM generated by caveolin-1 WT-MEFs was significantly stiffer than that generated by caveolin-1 KO-MEFs, revealing the

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different mechanics of ECM produced by different types of cells. In 2018 Kim et al. [36] revealed the relationship between the mechanical properties of cell-derived ECM and the behaviors of cells grown on the decellularized ECM. Fibroblasts were grown on either plastic dishes or gelatin-coated glass for one week, after which the decellularized ECM was obtained. Genipin is a natural cross-linker, which is able to induce the cross-linking of ECM. The decellularized ECMs were treated with different concentrations of genipin to form ECMs with different stiffness. AFM indentation results show that treating ECM with genipin caused a significant increase of the ECM stiffness and ECM treated by high concentration of genipin was much stiffer than ECM treated by low concentration of genipin. The subsequent results of utilizing the decellularized ECMs with different stiffness to grow human pluripotent stem cells (hPSCs) clearly show that hPSCs exhibited different biological behaviors (adhesion, migration, pluripotency, epithelial-mesenchymal-transition) on the different ECMs with diverse rigidity, suggesting that the ECM stiffness could be a dominant factor in mediating hPSC plasticity. PFT-based multiparametric AFM imaging has also been applied to simultaneously obtain the structural and mechanical images of ECM. In 2019 Mao et al. [37] revealed the different structural and mechanical properties between ECM derived from human articular chondrocytes (AC-ECM) and ECM derived from bone marrow stromal cells (BM-ECM) with the use of PFT-based multiparametric AFM imaging. The results of growing cells show that these two different types of ECMs had differential effects on chondrocytes, identifying AC-ECM as a preferred substrate for in vitro expansion of chondrocytes for cell therapy. Also in 2019, Babu et al. [38] used PFT-based multiparametric AFM imaging to investigate the structures and mechanics of five different types of decellularized ECMs on which normal fibroblasts and pathological fibroblasts were grown, and the results showed that normal fibroblasts softened ECMs more than pathological fibroblasts, deepening our understanding of cellECM interactions. More recently, in 2020, Satyam et al. [39] utilized AFM to measure the stiffness of decellularized fibroblast-derived ECM which was used to grow human immortalized podocytes. Overall, these studies show that AFM has become a standard tool to characterize and evaluate the mechanical properties of cultured cell-derived decellularized ECM, which provides novel insights into the regulatory role of ECM mechanics in cellular behaviors.

9.3 Investigating the structures and mechanics of basement membranes The structural and mechanical changes of basement membranes during tumor invasion and metastasis have been revealed by AFM. The basement membrane is a thin, dense sheet of ECM underlying epithelial

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and endothelial tissues and serves as a structural barrier to cancer cell invasion, intravasation, and extravasation [40]. Epithelial-derived tumors, also called carcinomas, represent about 90% of all cancers [41]. Particularly, metastasis causes greater than 90% of cancer death [42]. During the invasion and metastasis of carcinomas, the first barrier that invading cells breach is the epithelial basement membrane. Besides, the endothelial basement membrane hinders carcinoma cell invasion into (called intravasation) and out of (called extravasation) vascular systems during metastasis [40]. The mechanical properties of basement membranes are essential to their functions, but knowledge of the mechanics of basement membranes has long been poor due to the technical limitations of measurements [43]. In recent years, progress in the characterizations of basement membranes by AFM has substantially improved our understanding of the regulatory role of basement membranes during tumor metastasis from the perspective of mechanobiology. In 2017 Glentis et al. [44] investigated the mechanical cues involved in cancerassociated fibroblast (CAF)-induced cancer cell invasion of the basement membrane with the use of AFM, as shown in Fig. 9.3A. For doing so, the native mesentery was isolated from mice and glued onto the inserts of a transwell, whereas human primary fibroblasts were isolated from fresh colon tumors from clinical patients. On the bottom side of the mesentery, a collagen solution containing fibroblasts was added. Once collagen was polymerized, human colon cancer cells were seeded on the top of the mesentery. Cells were then cocultured for 325 days, after which cells in the mesentery were removed by ammonium hydroxide and the decellularized mesentery was attached to the poly-L-lysinecoated glass slides for AFM characterizations. AFM imaging shows that frequent holes which were often surrounded by big bundles of ECM were observed for the mesentery incubated with CAFs and cancer cells, whereas the mesentery from the control group was more homogeneous (I in Fig. 9.3A), which was consistent with the results obtained by SEM imaging (III in Fig. 9.3A). Quantitative analysis of the AFM topographical images shows that the roughness of mesentery increased significantly after the incubation of CAFs and cancer cells (IV in Fig. 9.3A). AFM mechanical measurements show that the mesentery significantly softened after the coculture of CAFs and cancer cells (II and IV in Fig. 9.3A). AFM results clearly show the structural and mechanical changes of basement membranes remodeled by CAFs and cancer cells for the invasion of cancer cells. Further studies show that CAF-induced invasion of cancer cells was metalloproteinase-independent. Instead, CAFs facilitate cancer cell invasion by applying mechanical forces on the basement membrane to remodel the basement membrane and make it permissive for cancer cell migration. In 2021 Reuten et al. [45] investigated the functional role of basement membrane architecture and

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FIGURE 9.3 Characterizing the structural and mechanical properties of native basement membranes by AFM. (A) Structural and mechanical changes of basement membranes during cancer cell invasion. (I) AFM height images, (II) AFM stiffness maps, and (III) SEM images of nontreated mesentery (Ctrl) and mesentery treated by CAFs and cancer cells (CC 1 CAFs). (IV) Statistical results showing the roughness and stiffness changes of mesentery caused by CAFs and cancer cells. (B) The ECM Net4 protein is associated with the stiffness of the basement membrane for promoting tumor metastasis. (I) Schematic illustration of detecting the mechanics of alveolar basement membrane from Net4 WT and Net4 KO mice by AFM. (II) Typical AFM measurements to determine the stiffness of alveolar basement membrane in Net4 WT and Net4 KO mice. AFM measurements start in one alveolus and go to another, detecting different stiffness patterns corresponding to the alveolar space (S), followed by cell layer (C), followed by the basement membrane (BM), followed by cell layer (C), ending in the opposite alveolar space (S). (III) Statistical results of the stiffness measurements. (IV) Schematic illustration showing the modulation of basement membrane through ECM protein Net4 and how increasing amounts of Net4 reduce the stiffness of a laminin network and thereby of the entire basement membrane. Stiff basement membranes favor metastases formation, whereas soft basement membranes are more antimetastatic. Source: (A) Reprinted with permission from A. Glentis, P. Oertle, P. Mariani, A. Chikina, F.E. Marjou, Y. Attieh, et al., Cancer-associated fibroblasts induce metalloproteaseindependent cancer cell invasion of the basement membrane, Nat. Commun. 8 (1) (2017) 924. Copyright 2017 The authors. (B) Reprinted with permission from R. Reuten, S. Zendehroud, M. Nicolau, L. Fleischhauer, A. Laitala, S. Kiderlen, et al., Basement membrane stiffness determines metastases formation, Nat. Mater. 20 (6) (2021) 892903. Copyright 2021 The authors.

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stiffness in tumor invasion and metastasis by AFM, as shown in Fig. 9.3B. First, 49 genes encoding for basement membrane components were examined, showing that high levels of the ECM protein netrin-4 (Net4) were strongly associated with good prognosis in breast and kidney cancer patients. Next, mouse breast cancer cells were injected into the mammary fat pad of Net4 wild-type (WT) and Net4 knockout (KO) mice. After primary tumors reached their maximum size, the tumors were resected to allow the formation of metastases for 28 days. Subsequently, the lung tissues were isolated and cut into slices for utilizing AFM to characterize the mechanics of alveolar basement membranes (I in Fig. 9.3B).

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The alveolar basement membrane was localized between an epithelial and endothelial cell layer, and the AFM probe was moved across the alveolar space from the epithelial side to the endothelial side to detect the mechanical patterns of the alveolar specimens, allowing the identification of the basement membranes in between the softer cell layers (II in Fig. 9.3B). The statistical results clearly show that the basement membrane was significantly softer in the presence of Net4 (III in Fig. 9.3B). Further studies show that Net4 softened the mechanical properties of native basement membranes by opening laminin node complexes, correlating the basement membrane protein components with basement membrane mechanics as well as tumor metastasis. Overall, these studies vividly show the great potential of AFM in characterizing the structural and mechanical properties of native basement membranes and uncovering the mechanical cues involved in tumor invasion and metastasis, which will have general implications for deciphering the mysteries of cancer.

9.4 In situ imaging of cell culture medium-forming nanogranular surface for cell growth

L

AFM has been used to reveal the cell culture medium-forming nanogranular surface for cell growth [46,47], as shown in Fig. 9.4. It is increasingly apparent that cells respond to the nanotopography of ECM [7]. Recapitulating local architectures that cells encounter during life activities allows elucidating and dissecting of the fundamental signal transduction pathways that control cell behaviors in critical development, physiological, FIGURE 9.4 Visualizing the cell culture medium-forming nanogranular topography for cell growth and detecting the nanogranule-cell adhesive interactions by atomic force microscopy (AFM). (A) AFM imaging revealing the dynamic formation of nanogranular topography on the glass slides incubated in cell culture medium. (IIV) AFM height images of the surface of the glass slides incubated in the cell culture medium for different times. (I) 30 min. (II) 1 h. (III) 12 h. (IV) 24 h. (V) Changes of the roughness (Mean 6 SD) of the cell culture medium-forming nanogranular surfaces. (B) AFM force spectroscopy revealing the adhesive interactions between cell culture medium protein nanogranules and living cells. (I, II) Schematic illustration of the nanogranule-functionalized tip (I) and regular tip (II). (III, IV) Statistical histograms of the molecular unbinding forces obtained with functionalized tips (III) and regular tips (IV). The insets in (III, IV) show the typical force curves obtained with functionalized tips (III) or regular tips (IV). (C) Schematic illustration of the presented mechanisms of cell growth in cell culture medium. Protein nanogranules in the cell culture medium (I) deposit onto the substrate to form nanogranular surface (II). Cells can then bind to the protein nanogranules by the adhesion molecules on the cell surface, which facilitate cell attachment and growth. Source: Reprinted with permission from M. Li, N. Xi, Y. Wang, L. Liu, In situ high-resolution AFM imaging and force probing of cell culture medium-forming nanogranular surfaces for cell growth, IEEE Trans. Nanobiosci. 19 (3) (2020) 385393. Copyright 2020 IEEE.

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and pathological processes [48]. So far, the studies of the interactions between cells and ECM nanotopography commonly focus on fabricating substrates with nanotopographical features (e.g., nanopits, nanopillars, nanogrooves) and utilizing them to grow cells and observe the cellular behaviors and functions [4952]. The cell culture medium is essential for the growth of cells in vitro, but the associations between cell culture medium and ECM nanotopography for cell growth have long been neglected. Here, with the use of AFM, it is found that the cell culture medium could form a nanogranular surface for cell growth. For doing so, fresh glass slides were placed in a cell culture medium (DMEM high glucose containing 10% FBS and 1% penicillinstreptomycin) and incubated at 37 C (5% CO2) for different times (10 min, 30 min, 1 h, 2 h, 12 h, 24 h). After the incubation, the glass slides were washed with pure water for three times and then the glass slides were placed in Petri dishes containing pure water in which AFM images were obtained at PFT mode. AFM imaging results distinctly show the dynamic formation of the nanogranular surface on the glass slides (Fig. 9.4A). Sparse nanogranules were clearly observed for 30 min after the glass slides were incubated in a cell culture medium (typically denoted by the red arrows in I of Fig. 9.4A). About 1 h after the incubation, nanogranule clusters formed on the surface of glass slides (II in Fig. 9.4A). When the incubation time became 12 and 24 h, compact nanogranules were remarkably seen (III and IV in Fig. 9.4A). The roughness of the glass slides was calculated from the obtained AFM height images, showing that on the whole, the glass slides became rougher during the dynamic formation of nanogranular surfaces (V in Fig. 9.4A). For control, glass slides were incubated in PBS at 37 C (5% CO2) for 24 h and then imaged by AFM in pure water. No nanogranules were observed on the glass slides, confirming that the nanogranular structures formed on the glass slides were from the cell culture medium. To examine which components in the cell culture medium contribute to the nanogranular depositions on the glass slides, glass slides were incubated in DMEM solution, 10% FBS solution, or 1% penicillinstreptomycin solution, respectively [47]. After the incubation, AFM images were obtained. AFM imaging results show that nanogranular structures were observed for the glass slides incubated in 10% FBS solution and in DMEM solution. When glass slides were incubated in 1% penicillinstreptomycin solution, no nanogranular structures were observed, suggesting that the components from FBS and DMEM were involved in the nanogranular depositions. To inspect the detailed compositions of the nanogranular structures, fluorescence labeling microscopy experiments with antibodies were performed. Since BSA is a major component of FBS, BSA antibodies were used as an example. The glass slides, which were incubated in the cell culture medium for 24 h, were successively labeled with anti-BSA antibodies and secondary antibodies conjugated with fluorescein. Many fluorescence spots were observed

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on the surface of glass slides, showing that BSA molecules were contained in the nanogranular structures. Notably, there are many ingredients (particularly many different protein molecules) in the FBS and DMEM solution, and thus more studies are needed to identify the components of the nanogranular surfaces. Next, to examine whether these nanogranules deposited on the surface of glass slides promote cell growth, the adhesive interactions between cells and the nanogranules were detected by AFM force spectroscopy, as shown in Fig. 9.4B. By incubating the AFM probe in the cell culture medium for 24 h, the cell culture medium protein nanogranules attached to the surface of the AFM tip and the functionalized probes were prepared (I in Fig. 9.4B). The functionalized probes were then used to obtain force curves on living cells. For control, regular probes were also used to obtain force curves on cells (II in Fig. 9.4B). Statistical results show that there were two force peaks for the unbinding interactions between cells and nanogranules (III in Fig. 9.4B), whereas there was only a single force peak for the unspecific interactions between cells and AFM tip (IV in Fig. 9.4B). In fact, sometimes there were big force peaks in the force curves obtained with functionalized probes (inset of III in Fig. 9.4B), which reflected the parallel unbinding of several molecular bonds, whereas the force peaks in the force curves obtained with regular probes were commonly much weaker (inset of IV in Fig. 9.4B). The AFM force spectroscopy results show the adhesive interactions between nanogranules and cells. Notably, since there are many different types of adhesion molecules on the cell surface, further studies are needed to examine which types of adhesion molecules contribute to the adhesive interactions between cells and cell culture medium protein nanogranules. The study reveals that the cell culture medium proteins can naturally deposit onto the surface of substrates to form nanotopography for promoting cell attachment (as schematically illustrated in Fig. 9.4C), which is previously undiscovered and provides novel insights into the cell growth in vitro. Besides, the study demonstrates that the functional role of cell culture medium in cell growth in vitro is observable and measurable with the use of AFM techniques, offering novel possibilities for uncovering the underlying molecular mechanisms guiding cellular activities.

9.5 Hierarchical micro-/nanotopography of extracellular matrix for tuning cellular structures and mechanics AFM has also been used to investigate the hierarchical micro-/nanotopography of ECM for tuning cellular structures and mechanical properties [53], as shown in Fig. 9.5. In addition to the nanotopography of ECM, studies have also shown that the microtopography of ECM plays an important role in cellular mechanotransduction and subsequent cell fate [54,55].

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FIGURE 9.5 Hierarchical micro-/nanotopography-induced structural and mechanical changes of single cells revealed by atomic force microscopy (AFM). (A) Constructing hierarchical micro-/nanotopography for cell growth. (I) AFM height image of microgroove silicon substrates. (II) Section profile curves taken along the red and blue lines in (I). (III, IV) AFM images of the local areas on the surface of microgroove incubated in PBS (III) or in cell culture medium (IV). The inset in (III) shows the AFM image of the whole microgroove and the red square denotes the local imaging area. (B) Morphological changes of cells induced by hierarchical micro-/nanotopography. (IIV) AFM images of chemically fixed cells grown on regular (I, III) or microgroove (II, IV) substrates. (V, VI) Geometrical changes of NIH-3T3 cells (V) and MCF-7 cells (VI) in response to hierarchical micro-/nanotopography. (C) Mechanical changes of cells in response to hierarchical micro-/nanotopography. (I, II) Optical microscopy images showing moving AFM probes to the individual living cells grown on regular (I) or microgroove (II) substrates. (III) Statistical results showing the changes of cellular Young’s modulus induced by hierarchical micro-/nanotopography. (D) AFM height image of a living NIH-3T3 cell grown on the microgroove substrate. Source: Reprinted with permission from M. Li, N. Xi, L. Liu, Hierarchical micro-/nanotopography for tuning structures and mechanics of cells probed by atomic force microscopy, IEEE Trans. Nanobiosci. 20(4) (2021) 543553. Copyright 2021 IEEE.

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Nevertheless, details of the interactions between cells and hierarchical micro-/nanotopography are still not fully understood. Here, with the use of AFM, the structural and mechanical changes of single living cells grown on hierarchical micro-/nanotopography were revealed. For doing so, the hierarchical micro-/nanotopography was firstly constructed, as shown in Fig. 9.5A. The microgroove silicon substrates were fabricated by photolithography. AFM imaging clearly shows the microgroove structures of the substrates (I in Fig. 9.5A). Section profile curves taken along the AFM topographical images show that the height of the microgrooves is about 400 nm, the width of the microgrooves is about 5 μm, and the distance between adjacent microgrooves is also about 5 μm (II in Fig. 9.5A). According to the results of Fig. 9.4, the microgroove substrates were then incubated in the cell culture medium at 37 C (5% CO2) for 24 h, and AFM imaging distinctly shows the cell culture medium-forming nanogranular topography on the surface of microgroove (IV in Fig. 9.5A). For control, the microgroove substrates incubated in PBS possessed smooth surfaces (III in Fig. 9.5A). The hierarchical micro-/nanotopography, which combines microscale groove structures and nanoscale granular surface, was then used to grow cells. For control, the regular flat silicon substrates without microgroove structures were also used to grow cells. Two types of cells, including NIH-3T3 cells (as an example of a normal cell) and MCF-7 cells (as an example of cancerous cells), were used. For reliable AFM imaging, cells grown on the microgroove/regular substrates were chemically fixed by 4% paraformaldehyde. AFM imaging results show that both NIH-3T3 cells and MCF-7 cells spread along the microgrooves to form long and narrow morphology (II and IV in Fig. 9.5B). In contrast, cells grown on regular substrates had compact morphology (I and III in Fig. 9.5B). To quantitatively analyze the geometrical features of the cells grown on the microgroove/regular substrates, the length (defined as the maximum length of the cell along the direction of microgrooves) and width (defined as the maximum length of the cell along the direction perpendicular to the microgrooves) of the cells were calculated to obtain the cellular aspect ratio (the ratio of length to width), remarkably showing that the cellular aspect ratio significantly increased for both NIH-3T3 and MCF-7 cells grown on microgroove substrates compared with cells grown on regular substrates (V and VI in Fig. 9.5B). Besides, the changes in the cellular aspect ratio of MCF-7 cells were much stronger than that of NIH-3T3 cells, showing the different behaviors between MCF-7 cells and NIH-3T3 cells in response to microgroove topography. AFM images of the local areas of cells grown on microgroove substrates clearly show the cellular filopodia and lamellipodia along the direction of microgrooves or across the valley and ridge of microgrooves, revealing the changes of the cellular fine structures in response to hierarchical micro-/nanotopography. Particularly, sometimes single living cells grown on the microgroove substrates could be successfully imaged by AFM in the cell culture medium, as

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shown in Fig. 9.5D. The filamentous cytoskeletons in the living cells were clearly observed from the AFM image (denoted by the red arrows in Fig. 9.5D). Nevertheless, during the experiments, it is still challenging to obtain high-quality AFM images of the whole living cells grown on the microgroove substrates. Further studies of utilizing AFM to image living cells grown on substrates with micro-/nanotopography, for example, coating poly-L-lysine on the substrates to enhance the adhesion of cells to substrates, will be quite meaningful for investigating the structural dynamics of living cells in response to micro-/nanotopography. Young’s modulus of living cells grown on microgroove/regular substrates was then measured, as shown in Fig. 9.5C. Under the guidance of optical microscopy (I and II in Fig. 9.5C), AFM probes were moved to the individual living cells grown on microgroove or regular substrates to perform indentation assay and force curves were obtained. Statistical results show that cells grown on microgroove substrates were significantly softer than that grown on regular substrates (III in Fig. 9.5C), suggesting the micro-/nanotopography-induced mechanical changes of cells. Notably, further studies, such as observing the cytoskeleton alterations of cells grown on microgroove substrates with fluorescence microscopy, are required to correlate cell mechanical alterations with cellular structural reorganizations. The study shows the capabilities of AFM in characterizing the structural and mechanical properties of single cells in response to ECM with hierarchical micro-/nanotopography, which will benefit deciphering cellECM interactions in their native states.

9.6 Summary AFM has become a powerful tool to characterize the local structures and mechanical properties of various ECMs in their native states for better understanding cellECM interactions and human pathophysiology, including decellularized ECMs (Fig. 9.2), basement membranes (Fig. 9.3), and ECM with hierarchical micro-/nanotopography (Figs. 9.4 and 9.5). Applications of AFM in the studies of ECM have revealed the significant changes in the biophysics of ECM in certain physiological and pathological processes particularly during tumor invasion and metastasis, yielding novel insights into the functional role of ECM in life activities. The established methodologies described in the chapter can be directly applied to the studies of other ECM systems. Notably, due to the highly complex characteristics of native ECMs, each tissue type from each animal species requires specific optimization of the sample preparation process for AFM assay as well as subsequent validation in terms of the maintenance of ECM integrity, which can be rather a time-consuming [56]. Particularly, so far, the studies of utilizing AFM to characterize the behaviors of native ECMs [2831,44,45] are commonly performed on specimens prepared

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from animals, which may not fully reflect the real situations in the human body. Therefore applying AFM to capture the structural and mechanical alterations of the ECMs taken from clinical patients during pathological processes will considerably help to elucidate the functional role of ECM in human diseases. In the future, as the AFM multifunctional toolbox is utilized to address more ECM-associated biomedical issues, particularly combined with other complementary techniques, we will see increasing advancements in the role of ECM in human healthcare, which will not only contribute to the field of mechanobiology but also promote the understanding of human diseases with clinical translational significance.

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10 Combining atomic force microscopy with complementary techniques for biophysics A set of short videos accompanying the book is available in electronic format at https://www.elsevier.com/books-and-journals/book-companion/ 9780323953603

10.1 Background Though atomic force microscopy (AFM) has achieved great success in characterizing the biophysical properties of various biological systems (as described in the previous chapters of the book) in their native states under aqueous conditions with an unprecedented spatiotemporal resolution, AFM has obvious limitations. For example, AFM is essentially a surface characterization tool which is unable to detect the activities taking place inside the specimens, the three-dimensional (3D) manipulation capability of AFM is quite weak, it is challenging for AFM to apply biochemical stimulation on the specimens, and so on. Fortunately, AFM is highly compatible and has been successfully integrated with diverse complementary techniques in the past decades to overcome these limitations, offering novel possibilities for the studies of biophysics in the field of life sciences. Combining AFM with ultrasound technology allows visualizing the internal substructures of the specimens, which is quite useful for exploring the interior life activities of biological systems. Traditionally, by linking biomolecules onto the surface of the AFM needle tip, these biomolecules can be delivered to the interior of a cell once the needle tip has penetrated the cell [1]. However, this method requires the chemical modifications (attaching the biomolecules to the AFM tip) of the target biomolecules to be delivered, which can inevitably reduce the fidelity of the

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FIGURE 10.1

Imaging nanoparticles in cells by scanning near-field ultrasound holography (SNFUH). (A) Schematic illustration of intracellular imaging of aspirated nanoparticles using SNFUH which combines atomic force microscopy (AFM) with ultrasound technology. The cell vibrates at Megahertz frequencies fs and the cantilever independently vibrates at a slightly different frequency fc. The local perturbations in the coupled oscillations of the ultrasonic-driven microcantilever-macrophage system due to the intracellular structures are monitored with the lock-in amplifier using the difference frequency fcfs as reference. By mapping the strength of the coupling in a scanned area of the cell, a phase image that contains information on the buried nanoparticles is generated simultaneously

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biomolecules. Besides, this delivery method is dependent on reversible chemical reactions, which requires specific expertise and thus its applicability is limited. The advent of fluidic force microscopy [2,3], which combines AFM with microchanneled cantilevers connected to a microfluidics system, allows precise delivery of native biomolecules to individual cells and effective 3D manipulation of the cell as well as the detection of cellular electrophysiology, significantly enhancing the capabilities of AFM for biophysics. More recently, AFM has been combined with other complementary techniques (e.g., micropipette, and fluidic environment) for better deciphering the role of mechanical cues in life processes. In the remaining of the chapter, the achievements of combining AFM with complementary techniques for biophysics are presented.

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Combining AFM with ultrasound technology allows simultaneously observing the surface and subsurface structures of biological systems with high spatial resolution, which significantly promotes the nondestructive detection of intracellular activities. In 2005, Shekhawat et al. [4] developed a noninvasive imaging method based on the integration of AFM and ultrasound technology to probe the buried nanostructures in the specimens, which is termed scanning near-field ultrasound holography (SNFUH). In SNFUH, a high-frequency acoustic wave (fs) is launched from the bottom of the specimen, while another acoustic wave (fc) is launched on the AFM cantilever at a slightly different frequency, as shown in Fig. 10.1A. The interference of these two waves results in a surface acoustic standing wave, and the perturbations to the phase of the surface acoustic standing wave caused by the buried features of the specimens are detected by the lock-in approach and a SNFUH electric module. As the sample is scanned point-by-point, a SNFUH phase map, which reflects the elastic properties of the internal structures of the sample, is generated simultaneously with the AFM topographical image of the sample. As an example, individual animal cells were scanned by with AFM topographical image. (B) AFM topographical images (I, III, V) and corresponding SNFUH phase images (II, IV, VI) of RBCs obtained from a mouse sacrificed 24 h after exposure to nanoparticles. (C) AFM topographical image (I) and corresponding SNFUH phase image of RBCs obtained from a control mouse without nanoparticle stimulation. (D) AFM topographical images (I, II, IV, V) and SNFUH phase images (III, VI) of alveolar macrophages obtained from a control mouse (I, II, III) and a mouse sacrificed 7 days after exposure to nanoparticles (IV, V, VI). Source: Reprinted with permission from L. Tetard, A. Passian, K.T. Venmar, R.M. Lynch, B.H. Voy, G. Shekhawat, et al., Imaging nanoparticles in cells by nanomechanical holography, Nat. Nanotechnol. 3 (8) (2008) 501505. Copyright 2008 Macmillan Publishers Limited.

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SNFUH. While the AFM topographical image only shows the outer morphology of the cell, the SNFUH phase image remarkably shows the internal substructure of the cell including the nucleus [5]. The malaria-infected red blood cells (RBCs) were also examined by SNFUH. AFM topographical images show the typical surface morphology of RBCs, whereas SNFUH phase images distinctly show the presence of parasites inside RBCs without any fluorescent labels or sectioning of cells [4]. Particularly, the parasites inside RBCs at the early stage of infection can be clearly captured by SNFUH imaging, which is difficult to confirm by other noninvasive methods such as fluorescent labeling, demonstrating the high sensitivity of SNFUH in detecting the structural alterations inside single cells. Nanomaterials such as nanoparticles with tunable and diverse properties hold tremendous potential in the field of biomedicine, but also their possible adverse effects and toxicity to healthy cells/tissues/organs cause severe concerns for their practical applications [6]. Therefore, methods that can noninvasively detect the nanomaterials inside the cells are quite meaningful for the studies of nanomaterials-based drug delivery and toxicology. In 2008, Tetard et al. [7] investigated the cellular uptake of nanoparticles by SNFUH. For doing so, mice were exposed to single-walled carbon nanoparticles by pharyngeal aspiration. Mice were sacrificed 24 h and 7 days after aspiration. Macrophages were collected from the mice and then imaged by SNFUH, clearly showing the nanoparticles (typically denoted by the green arrows in Fig. 10.1D) in the macrophages. The SNFUH imaging results also evidently show the nanoparticles in RBCs (denoted by the green arrows in Fig. 10.1B) prepared from the peripheral blood samples of mice, which were not present in the RBCs collected from a control mouse without exposure to nanoparticles (Fig. 10.1C). Further, the nanoparticles in the cells were verified by Raman spectroscopy of cells. Notably, the difference in contrast of SNFUH images of nanoparticles between RBCs (appearing in black) and macrophages (appearing in white) was due to the difference in the phase accretion associated with the coupling between the oscillations of cantilever and cell (as illustrated in Fig. 10.1A). In 2017, Shekhawat et al. [8] utilized SNFUH to investigate endothelial cells in response to drug stimulation. AFM topographical images and SNFUH phase images of endothelial cells were obtained under physiological conditions after incubation with thrombin for 30 min. The SNFUH phase images show the stiffening of the cell nucleus after the treatment of thrombin. Besides, the small fibers within the intracellular fiber network are visible from SNFUH images, which are not observed from AFM topographical images, demonstrating the merits of SNFUH in resolving the fine, buried structures of cells. These studies show the striking capabilities of SNFUH in detecting the diverse biological activities taking place inside single cells, which significantly complements conventional AFM topographical imaging and extends the applications of

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AFM for biophysics. Nevertheless, intracellular structures are often highly complex and contain many different types of substructures (e.g., various organelles), and so far, it is still challenging to exactly discriminate these heterogeneous substructures inside cells from the SNFUH phase images, which is mainly due to the relative low vibration frequencies (commonly at a few Megahertz) of the oscillators in the SNFUH. In future, using high-frequency oscillators that vibrate at up to Gigahertz frequencies will allow SFNUH to image features a few nanometers in size that are embedded as deep as several microns into a sample, and theoretical and experimental studies of the quantitative understanding of SFNUH phase measurements will enable determination of subsurface material properties and geometries [9], which will significantly benefit the biophysical studies of intracellular activities.

10.3 Fluidic force microscopy Fluidic force microscopy (FluidFM), which combines AFM with hollow cantilevers, significantly improves the capabilities of AFM to manipulate single cells. In 2009, Meister et al. [10] developed FluidFM. The basic components of FluidFM are the same as AFM, except that FluidFM uses a microchanneled cantilever which is connected to a pressure controller by tubing, as shown in Fig. 10.2A. FluidFM thus has a continuous and closed fluidic channel that can be filled with an arbitrarily chosen liquid, which can be locally dispensed through the nanoscale aperture at the extremity of the cantilever and also can be exploited to perform various manipulations [3]. FluidFM is able to deliver biomolecules in their native states as chemical stimuli to the single selected living cell grown on the substrates. Under the guidance of optical microscopy, the microchanneled probe filled with a particular biomolecule solution is gently approached onto a selected cell and maintained in contact with the cell membrane based on AFM feedback control. Subsequently, by applying positive pressure to the channel of the cantilever, the solution inside the channel can be released to the cell through the aperture at the apex of the tip (I and II in Fig. 10.2B). By using a pyramidal tip with a side-hole preserving the sharpness of the apex, the channeled probe can easily penetrate cell membranes to deliver biomolecules into single cells (III and IV in Fig. 10.2B). Besides biomolecules, even individual virus particles can be delivered to the target cell by FluidFM dispensing [11] (Fig. 10.2C), facilitating observing the dynamics of viral infection on single cells. For adherent cells which can attach to and spread on the substrate, the prerequisite of picking up the cell is removing the molecular anchors between the cell and substrate. With the use of FluidFM, trypsin solution can be loaded in the channel and locally delivered to single adherent cells to detach the target

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FIGURE 10.2 Fluidic force microscopy (FluidFM) allows various manipulations at singlecell level for biomedical applications. (A) Schematic illustration of FluidFM. The microchanneled cantilever is fixed to the drilled atomic force microscopy (AFM) probe holder, which is immersed in liquid on top of an inverted optical/fluorescent microscope. (B) Delivering biomolecules as chemical stimuli to single cells by FluidFM. (I, II) Locally dispensing fluorescent dye molecules to single cells. (I) Schematic. (II) Fluorescent image of the cell after dispensing. (III, IV) Injecting fluorescent dye molecules into single cells. (III) Schematic. (IV) Superposition of the optical image and corresponding fluorescent image of the cell after injection. (C) Delivering individual virus particles to a living cell. (I-IV) Schematic illustration of the procedure of delivering viruses onto the targeted cell. (V) Superposition of the optical image and

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cells from the substrate while the neighboring cells remain adherent [12] (Fig. 10.2D). The detached cell can then be easily adsorbed to the aperture of the AFM tip and moved to specific positions on the substrates by AFM micromanipulations for various applications, for example, collection of specific cells, sorting of different types of cells, formation of special cell patterns, and so on. FluidFM can also be used to extract the intracellular content of single living cells for downstream analyses [13], as shown in Fig. 10.2E. For doing so, the FluidFM probe is firstly aligned on top of the desired location of the cell under the guidance of optical microscopy and controlled to penetrate the cell with a preset force. Once the preset force is achieved, the AFM feedback control system allows maintenance of the tip inside the cell at constant preset force, during which negative pressure is applied through the microchannel to suck the cellular contents into the probe. Subsequently, the tip retracts from the cell and moves to the desired position on a suitable substrate. Finally, the extract inside the probe is released onto the substrate for further analysis by applying positive pressure through the microchannel. With this method, either the nuclear components (I in Fig. 10.2E) or the cytoplasmic components (II in Fig. 10.2E) of single living cells can be precisely extracted. Therefore, one can first probe the properties of single selected living cells and then extract the intracellular components of the selected cell by FluidFM and probe the properties of the intracellular components, which will be quite meaningful for correlating cellular behaviors with intracellular activities at the same cell level. Notably, the microchanneled probe needs to be functionalized with an antifouling coating prior to experiments to avoid

the corresponding fluorescent image of the virus (labeled with fluorescein to yield red fluorescence) deposited on the cell. (VI) Expression of green fluorescent protein detected on cells 11 h after viral infection. (D) Single-cell detachment by controlled trypsin delivery. (I) HeLa cells transfected with fluorescence. (II) The microchanneled probe was positioned above the target cell to release trypsin. (III) The target cell detached in response to trypsin. (E) Extracting internal contents from single living cells. (I, II) Optical images and corresponding fluorescent images showing the successful extraction of nuclear components (0.3 pL of nuclear components was extracted) and cytoplasmic components (1.5 pL of the cell cytoplasm was extracted) from target cells. Source: (A and B) Reprinted with permission from A. Meister, M. Gabi, P. Behr, P. Studer, J. Voros, P. Niedermann, et al., FluidFM: combining atomic force microscopy and nanofluidics in a universal liquid delivery system for single cell applications and beyond, Nano Lett. 9 (6) (2009) 25012507. Copyright 2009 American Chemical Society. (C) Reprinted with permission from P. Stiefel, F.I. Schmidt, P. Dorig, P. Behr, T. Zambelli, J.A. Vorholt, et al., Cooperative vaccinia infection demonstrated at the single-cell level using FluidFM, Nano Lett. 12 (8) (2012) 42194227. Copyright 2012 American Chemical Society. (D) Reprinted with permission from O. Guillaume-Gentil, T. Zambelli, J.A. Vorholt, Isolation of single mammalian cells from adherent cultures by fluidic force microscopy, Lab. Chip 14 (2) (2014) 402414. Copyright 2014 The Royal Society of Chemistry. (E) Reprinted with permission from O. Guillaume-Gentil, R.V. Grindberg, R. Kooger, L. Dorwling-Carter, V. Martinez, D. Ossola, et al., Tunable single-cell extraction for molecular analyses, Cell 166 (2) (2016) 506516. Copyright 2016 Elsevier Inc.

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biofouling and subsequent clogging of the microchannel. Fortunately, an antifouling coating material is now commercially available (http://www. cytosurge.com), facilitating the practical applications of FluidFM. FluidFM also allows simultaneous mechanical detection and patch clamp of single cells [14], as shown in Fig. 10.3. For doing so, an electrode is inserted into the reservoir of the FluidFM probe, and another electrode is placed in the bath solution (I in Fig. 10.3A). The electrodes are connected to a patch clamp amplifier. A cylindrical aperture (the diameter was about 350 nm and the height was about 500 nm) is milled by FIB at the pyramid apex (III and IV in Fig. 10.3A), allowing seal resistance in the order of 150 MΩ which is enough for the recording of whole-cell ionic currents. After selecting a cell on the dish, the FluidFM probe is positioned on top of it under the guidance of optical microscopy and the probe is controlled to approach the membrane of the target cell via the AFM force feedback. By applying a slight underpressure a seal is formed in the cylindrical aperture of around 150 MΩ, after which the mechanical forces and ionic currents of the cell can be

FIGURE 10.3 Fluidic force microscopy (FluidFM) allows force-controlled patch clamp of single cells. (A) Force-controlled whole-cell patch clamp by FluidFM. (I) Schematic illustration of the FluidFM-based whole-cell patch clamp configuration. (II) Scanning electron microscopy (SEM) images of the FluidFM microchanneled cantilever. The inset shows the hollow nature of the cantilever with a section through the pyramid made with FIB. (III) SEM image of the pyramidal tip with an aperture at the apex used for patch clamp. (IV) SEM image showing the profile structure of the aperture in the microchanneled tip based on FIB section. (B) Force and ionic current recording during approach on a contracting cardiomyocyte with enabled force control. The force increases simultaneously with a drop in ionic current as the FluidFM tip contacts the cell (denoted by arrow ①). The arrows without labeling indicate the slight increase of suction force applied through the microchannel inside the FluidFM probe. Source: Reprinted with permission from D. Ossola, M.Y. Amarouch, P. Behr, J. Voros, H. Abriel, T. Zambelli, Force-controlled patch clamp of beating cardiac cells, Nano Lett. 15(3) (2015) 17431750. Copyright 2015 American Chemical Society.

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detected simultaneously. Notably, the contact between the FluidFM tip and the cell is stable due to the automated force feedback control of AFM, whereas the contact is prone to get lost in conventional patch clamping due to vibrations or cell volume changes. Based on the method, the whole-cell ionic currents and the contraction forces of individual mouse adult cardiomyocytes were simultaneously recorded (Fig. 10.3B), clearly showing the rhythmic movements of the cardiomyocyte as well as the changes of whole-cell ionic currents. Since the AFM probe is able to exert mechanical forces on the cell with high force (piconewton) sensitivity, the FluidFM-based patch clamp is particularly suited to quantitatively investigate the behaviors of mechanosensitive ion channels which are activated by mechanical forces for uncovering the underlying mechanisms guiding ion-channel-mediated mechanosensory transduction. FluidFM-based patch clamp can also be used as the scanning nanopore microscopy to sense the ions and biomolecules secreted by the selected cell [15], providing a novel way to detect the molecular activities of single living cells in their native states. Nevertheless, there is still a huge gap between the current seal resistances achieved in FluidFM-based patch clamp and gigaseal, which decreases the measurement quality of patch clamping and therefore optimizing the geometry of the FluidFM probes to achieve higher seal resistances will be quite useful for the advancements of FluidFM-based patch clamp.

10.4 Combining atomic force microscopy with micropipette Combining AFM with micropipette offers a novel way to investigate the mechanical properties of single cells in response to chemical stimuli [16], as shown in Fig. 10.4. Although FluidFM is able to precisely deliver biomolecules to single cells with high precision, the microchanneled configuration of the probe used in FluidFM can inevitably affect the measurement performances of the probe, causing the mechanical sensitivity of the microchanneled probe is not as good as that of the regular solid AFM probe. Micropipette has been widely used for single-cell manipulation including delivering stimuli (e.g., proteins, peptides, DNA/RNA molecules, and drug molecules) onto/into single cells [1719]. Here, the micropipette was integrated with AFM for simultaneous single-cell drug delivery and cell mechanics measurement. The micropipette was used to locally deliver drug molecules to a single selected cell, whereas AFM was used to characterize the mechanical properties of the selected cell (I in Fig. 10.4A). The micropipette-based single-cell microinjection system was built on an inverted fluorescent microscope by using a 3D manipulator, a micropump, a syringe, a PTFE tube and a micropipette (III in Fig. 10.4A). The micropipette was obtained from the glass capillary by using the

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FIGURE 10.4 Single-cell manipulation and detection platform based on the integration of atomic force microscopy (AFM) and micropipette. (A) The configuration of the platform. (I) Schematic illustration of combining AFM with micropipette for simultaneous single-cell drug delivery and cell mechanics measurement. (II, III) Actual photographs of the AFM system (II) and the micropipette system (III). (IV) Micropipette-based single-cell injection under the guidance of optical microscopy. (V, VI) Optical bright field image (V) and SEM image (VI) of a fabricated micropipette. (VII) Moving the AFM probe to the selected cell under the guidance of optical microscopy to perform a mechanical assay. (VIII) Optical image showing the single-cell injection by micropipette. (B) Optical images showing the results of single-cell injection. (I) Optical image of the HEK 293 cell after injection by micropipette with large tip size. (II) Optical image of the NIH-3T3 cell after injection by micropipette with small tip size. (III, IV) Optical images of the MCF-7 cell before (III) and after (IV) the injection. The cells being injected are denoted by the yellow arrows. (C) The dynamic process of injecting PI dye solution into single cells by micropipette. (I) Optical image of the selected NIH-3T3 cell (denoted by the yellow arrow) before injection. (IIVIII) Successive PI fluorescent images recorded during the injection. Source: Reprinted with permission from Y. Feng, P. Yu, J. Shi, M. Li, Combining micropipette and atomic force microscopy for single-cell drug delivery and simultaneous cell mechanics measurement, Prog. Biochem. Biophys. 49(2) (2022) 420430.

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micropipette puller (V and VI in Fig. 10.4A). The prepared micropipette was mounted onto the 3D manipulator and connected with the syringe (the syringe was installed in the micropump) through the PTFE tube. After placing the petri dish in which cells are grown onto the specimen stage of the inverted microscope, micropipette-based drug delivery manipulations were performed on a single selected cell under the guidance of optical microscopy (IV and VIII in Fig. 10.4A). Subsequently, the micropipette was removed from the inverted microscope and the AFM was mounted on the same inverted microscope to perform AFM detection on the selected cell (II and VII in Fig. 10.4A). For the manipulations of micropipette-based single-cell injection, the solution to be injected was loaded into the micropipette by a syringe. After removing the air bubbles in the micropipette, the micropipette was connected to the syringe in the micropump through the PTFE tube and mounted onto the 3D manipulator. The syringe and the PTFE tube were preloaded with PBS, thus forming a sealed liquid environment for the entire injection system. The micropump was then controlled to push the syringe plunger to exert adequate positive pressure, which allowed the release of the solution inside the micropipette. Notably, the size of the micropipette tip is associated with the results of the injection. If the outer diameter of the micropipette tip is larger than 1 μm, the injection process can cause significant changes in cellular morphology due to mechanical damage from the micropipette (I in Fig. 10.4B). If the outer diameter of the micropipette tip is less than 1 μm, cellular morphology remains intact after injection (II in Fig. 10.4B). To examine the performance of the micropipette injection system, blue ink solution was used as an example. The experimental results clearly show that the cell became blue after injection, indicating that the blue ink solution was successfully injected into the cell (III and IV in Fig. 10.4B). Further, the PI dye solution was injected into single cells, and the PI fluorescent images were successively recorded. The results distinctly show the dynamic process of the cell with gradually increasing fluorescence (Fig. 10.4C), indicating that the PI dye solution was successfully injected into the cell. Therefore these experimental results demonstrate the effectiveness of the established micropipette-based single-cell injection system. Based on the integration of AFM and micropipette, the procedures of simultaneously measuring the mechanical properties of single selected cells in response to local drug stimulation were then established, as shown in Fig. 10.5. The PI dye solution was first used as an example for experiments. Under the guidance of optical microscopy, the micropipette was controlled to inject PI dye solution into a selected cell (I in Fig. 10.5A). After injection, the nucleus of the cell exhibited bright red fluorescence (III in Fig. 10.5A), suggesting that PI solution had been

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FIGURE 10.5 Single-cell injection and simultaneous cell mechanics measurement by combining AFM with micropipette. (A) Detecting the mechanical changes of single NIH3T3 cells after being stained with PI dye solution. (I) Optical image of the selected cell (denoted by the yellow arrow) for PI injection. (II, III) Optical image (II) the corresponding PI fluorescent image (III) of the selected cell after injection. (IV) Moving the AFM probe to the cell under the guidance of PI fluorescence. (V) A typical force curve obtained on the cell with PI fluorescence. The black arrow denotes the contact point in the approach curve. (VI) Cellular Young’s modulus was extracted by fitting the indentation curve with Hertz-Sneddon model. (B) Detecting the mechanical changes of single MCF-7 cells after the locally delivery of therapeutic drug (cytarabine). (I) Optical image showing moving AFM probe to the selected cell (denoted by the yellow arrow) to perform indentation assay before drug stimulation. (II) Optical image of injecting cytarabine solution into the selected cell. (III) Optical image showing measuring the mechanical properties of the cell again by AFM after the injection of cytarabine. (IV, V) Typical experimental indentation curves obtained before (IV) and after (V) cytarabine injection. Fitting the indentation curves with Hertz-Sneddon theoretical model gives the cellular Young’s modulus. Source: Reprinted with permission from Y. Feng, P. Yu, J. Shi, M. Li, Combining micropipette and atomic force microscopy for single-cell drug delivery and simultaneous cell mechanics measurement, Prog. Biochem. Biophys. 49 (2) (2022) 420430.

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delivered into the cell. Subsequently, under the guidance of fluorescence, the AFM probe was moved to the target cell with PI solution injection to perform indentation assay (IV in Fig. 10.5A), during which force curves were obtained on the target cell (V in Fig. 10.5A). According to the contact point (denoted by the black arrow in the V of Fig. 10.5A) in the approach part of the force curve, the approach curve was converted into the indentation curve (the blue dotted line in VI of Fig. 10.5A). Fitting the indentation curve Hertz-Sneddon model gave the cellular Young’s modulus (VI in Fig. 10.5A). The results (Fig. 10.5A) show the feasibility of simultaneous AFM measurement of single-cell mechanical properties in response to chemical stimuli. With the established procedure, the mechanical changes of single cells in response to chemotherapeutic drugs (cytarabine was used here as an example of chemotherapeutic drug) were revealed, as shown in Fig. 10.5B. The mechanical properties of single selected cell were first measured by AFM under the guidance of optical microscopy (I in Fig. 10.5B). Subsequently, the cytarabine solution was injected into the selected cell by micropipette under the guidance of optical microscopy (II in Fig. 10.5B). After the injection, the AFM probe was used to measure the mechanical properties of the cell again to monitor Young’s modulus changes of the cell after drug stimulation (III in Fig. 10.5B). Typical force curves as well as the Hertz-Sneddon theoretical fittings are shown in IV and V in Fig. 10.5B and we can see that the theoretical curves are quite consistent with the experimental curves. The mechanical changes of 10 cells before and after cytarabine treatment were measured and the statistical results clearly show that cells softened after the treatment of cytarabine, suggesting the effects of cytarabine on cellular mechanics. So far, studies of combining AFM with micropipette for simultaneous drug delivery and mechanical measurement of single cells are still scarce. Here, the methods of integrating AFM with micropipette for single-cell mechanical monitoring after local chemical stimuli were explored. Nevertheless, it should be noted that, for the procedures established here, AFM measurements and micropipette manipulations are obtained in a correlated fashion but not truly synchronous. In future, integrating AFM with micropipette in the same visual workspace will allow real simultaneous AFM assay and micropipette manipulation, which will be quite meaningful for revealing the intermediates of cellular states taking place during the interactions between cells and chemical stimuli.

10.5 Combining atomic force microscopy with fluidic environment Combining AFM with a fluidic environment offers a novel way to investigate the mechanical properties of single cells in rheological

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conditions. So far, studies of utilizing AFM to detect the mechanical properties of cells are commonly performed in a static liquid environment. Typically, a petri dish in which cells are grown is placed on the sample stage of AFM, and then the mechanical properties of the cells in the static cell culture medium in the dish are measured by AFM. Nevertheless, in many cases, the cells in vivo are not in the static environment but in the fluidic environment. For example, when the primary cancerous cells metastasize to other sites in the body through the vasculature, the cancerous cells are in the fluidic environment of the vasculature. Particularly, the flow mechanics (e.g., flow rate, vessel size, and shear stress) of the blood and lymphatic circulatory systems can influence the behaviors of cancerous cells, and cancerous cells also exploit the underlying physical forces within these fluids to successfully seed distant metastases [20]. Hence, exploring and detecting the mechanical properties of cancerous cells in a fluidic environment is of fundamental significance for revealing the force mechanisms guiding the interactions between cancerous cells and vascular flowing microenvironments during tumor metastasis. Here, the fluidic environment for cell growth was established to be integrated with AFM [21], as shown in Fig. 10.6A. The side-opening petri dish was fabricated by performing perforation on the symmetrical sides of the dish with the use of an electric soldering iron. The petri dish was then connected to an inlet and outlet tubing micropump system via the two holes in the side wall of the dish for changing the cell growth medium in the dish. The injection pump injects the cell growth medium into the petri dish at a certain flow rate, whereas the extraction pump draws the cell growth medium at the same flow rate, thus forming a continuous and stable fluidic environment to simulate the flow conditions cells encounter in vivo. Cells were seeded on coverslips. After the cells had attached tightly to the coverslips, the coverslips were placed in the side-opening petri dish for studies. The fluidic medium device for cell growth was placed on the AFM sample stage (here the commercial Bruker Dimension Icon AFM with a lateral optical microscope was used as an example), thus allowing AFM to detect the mechanics of single cells in the fluidic environment (Fig. 10.6B). The fluidic medium device can also be integrated with the inverted optical microscope which has a heating plate to provide the 37 C environment to observe the growth of cells under the fluidic cell growth medium environment (Fig. 10.6C). To examine the performance of the established fluidic medium device, the black ink solution was loaded into the side-opening petri dish and PBS was loaded into the injection pump. After the start of the injection pump and the extraction pump, the black solution was significantly transferred to the extraction pump, showing the effectiveness of the fluidic medium device in generating the flow environment. Further, the cell-seeded coverslip was placed in the fluidic

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FIGURE 10.6 Experimental platform of measuring cell mechanics in fluidic cell growth medium environment by AFM. (A) Schematic illustration of combining AFM with fluidic environment. (B) Actual photographs of the experimental platform. (I) The whole system. (II) Local area of the system showing the integration of AFM and side-opening petri dish. (III, IV) Optical images showing measuring the mechanical properties of single living MCF-7 cells (III) and HGC-27 cells (IV) by AFM in fluidic environments. (C) The fluidic cell growth medium device can also be mounted on an inverted optical microscope. Source: Reprinted with permission from J. Wei, M. Li, Y. Feng, L. Liu, Measuring the mechanical properties of cancerous cells in fluidic environments by atomic force microscopy, Prog. Biochem. Biophys. 49(10) (2022) 20412053.

medium device and incubated for 8 h in the fluidic environment. For control, cells were grown in a static medium environment for 8 h. The results clearly show that the number of viable cells grown in a fluidic environment was significantly larger than that grown in a static fluidic environment, demonstrating that the fluidic medium environment could better benefit the growth and proliferation of cells. This may be due to the fact that the toxic metabolites produced by cells during cell growth can be timely expelled in a fluidic medium environment and also the fresh cell growth medium is simultaneously provided. Based on the integration of AFM and fluidic medium device, the effects of fluidic medium environment on the mechanical properties of cancerous cells were revealed, as shown in Fig. 10.7. MCF-7 (human breast cancer cell line) cells and HGC-27 (human gastric cancer cell line) cells were used in the study. For doing so, the cell-seeded coverslips were placed in the fluidic medium device and AFM was utilized to

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FIGURE 10.7 AFM indentation assay revealing Young’s modulus changes of MCF-7 cells after growth in fluidic cell culture medium. MCF-7 cells were grown at different flow rates (30, 60, 120 mL/h) of the cell culture medium for different times (1, 2, 3, 4 h). The cellular Young’s modulus values before and after growth in the fluidic cell culture medium were measured. (A) Flow rate 30 mL/h. (B) Flow rate 60 mL/h. (C) Flow rate 120 mL/h. (I) Growing for 1 h. (II) Growing for 2 h. (III) Growing for 3 h. (IV) Growing for 4 h. For each situation, ten cells were measured (*P , .05; **P , .01; ***P , .001; ****P , .0001). Source: Reprinted with permission from J. Wei, M. Li, Y. Feng, L. Liu, Measuring the mechanical properties of cancerous cells in fluidic environments by atomic force microscopy, Prog. Biochem. Biophys., 49(10) (2022) 20412053.

obtain force curves on ten cells to measure the original mechanical properties of these cells (0 h). Subsequently, the injection and extraction pumps were started at a certain flow rate (30, 60, or 120 mL/h) to grow cells for a period of time (1, 2, 3, or 4 h). After the growth, the injection and extraction pumps were stopped, and AFM was utilized to measure the mechanical properties of ten cells. The statistical results (Fig. 10.7) remarkably show that Young’s modulus of MCF-7 cells significantly decreased after growth in the fluidic medium environment. Particularly, when the flow rate increased, Young’s modulus of cells decreased more significantly. For control, Young’s modulus of MCF-7 cells grown on coverslips was measured by AFM. The cells were then cultured in a

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static cell growth medium for a period of time (1, 2, 3, or 4 h), after which the cellular mechanical properties were measured again. The results show that there were no significant changes in Young’s modulus for cells grown in a static medium. Therefore the results demonstrate the effects of the fluidic medium environment on the mechanics of MCF-7 cells. The same results (softening of cells after growth in a fluidic cell culture medium environment) were also observed on the HGC-27 cells, showing that the effects of the fluidic environment on cellular mechanics may be independent of cell types. Nevertheless, more studies are required to perform experiments on other different types of cells to examine whether the effect is universal. Notably, due to the fact that the fluidic cell growth medium significantly disturbs the AFM cantilever, the fluidic medium was turned off when using AFM to detect the mechanical properties of cells here, and thus the AFM measurements are not fully in a fluidic environment. In future, developing methods to allow AFM to directly measure the mechanical properties of cells in a fluidic environment will be quite meaningful for investigating the mechanical behaviors of cells in rheological conditions.

10.6 Summary As shown in this chapter, the integration of AFM and complementary techniques has achieved substantial success in the detection of single cells, offering novel possibilities for unveiling the mysteries of life activities and human diseases. Combining AFM with complementary techniques not only significantly enhances the capability of AFM for single-cell assay, for example, observations of intracellular structures (Fig. 10.1), 3D single-cell manipulations (Fig. 10.2), and single-cell electrophysiology (Fig. 10.3), but also makes it possible to apply AFM to investigate more biological issues in the field of life sciences, for example, mechanical dynamics of single cells in response to local chemical stimuli (Figs. 10.4 and 10.5), and cellular mechanics in fluidic environments (Figs. 10.6 and 10.7). Notably, the complementary techniques described in the chapter are mainly for detecting the biophysical properties of biological systems. AFM has also been widely integrated with chemical techniques to simultaneously obtain the structural, mechanical, and chemical properties of biological specimens, such as compositional imaging based on the integration of AFM and infrared spectroscopy [22], and tip-enhanced Raman spectroscopy based on the integration of AFM and Raman spectroscopy [23], which is particularly meaningful for comprehensively understanding the multidimensional properties (biological, chemical, or physical) of biological systems. Since this book focuses on biophysics, readers are referred to the references [2225] for more descriptions of the combination of AFM and

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chemical techniques. In future, besides cells, applications of the hybrid AFM techniques described in the chapter to more biological systems (such as the various biological systems described in previous chapters of the book) will yield novel insights into physiological and pathological processes. In addition, advances in the combination of AFM with complementary techniques will further promote the studies of biophysics.

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C H A P T E R

11 Future perspectives of atomic force microscopy for biophysics The broad applications of AFM in diverse biological systems ranging from single molecules to living cells as well as tissues (locally) over the past decades have evidently demonstrated the exciting and multifunctional capabilities of AFM to nondestructively characterize the structures and properties of biological specimens under aqueous conditions with an unprecedented spatiotemporal resolution, offering novel opportunities to discover the underlying mechanisms of the regulatory role of biophysics in life activities. With the use of AFM, numerous unique insights into the physiological and pathological processes have been yielded, significantly complementing traditional biochemical methods. Many mechanical biomarkers with translational significance have been identified for indicating cell states and drug actions as well as disease stages, which promote developing novel therapeutic strategies against human diseases. Now AFM has become an important and standard tool for biophysical studies and the achievements of AFM have contributed much to the field of mechanobiology. Nevertheless, for further progressions and better biomedical applications of the AFM-based toolbox, several issues need to be noticed and addressed. There is huge room for the improvement of AFM techniques. The cell membrane of living animal cells is extremely soft and thin (the thickness of the lipid bilayer is about 5 nm [1]), which can be easily deformed by AFM tip during the scanning process of imaging cell surface by AFM. Therefore, the AFM tip often senses the stiff cytoskeletons beneath the cell membrane and the obtained AFM topographical images contain structural features of many different cellular parts. Thus, the surface roughness quantitatively calculated from the AFM topographical images only reflects the comprehensive results of these different cellular structures (e.g., cell membrane, cytoskeleton, and probably some unknown intracellular structures), making it difficult to determine the exact

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contribution of the cell membrane. Studies have shown that AFM imaging with a very small scan force (less than 100 pN) at PFT mode allows visualizing the cell membrane of living animal cells [2], but so far studies of utilizing AFM to explore the role of the topographical feature of living cell membrane in cellular physiological and pathological processes are still scarce. During the process of applying AFM to indent single living cells to measure the mechanical properties of cells, the AFM probe successively contacts with different parts of the cell, such as the cell membrane, cytoskeleton, and cell nucleus, and thus the recorded force curves contain the mechanical properties of these different cellular structures. Analyzing the different parts of the force curves allows extracting the mechanical properties of the different cellular structures [3], but so far determining the indentation ranges of the force curves for different cellular structures is often arbitrary and how to exactly verify the boundaries in the force curves for the contributions of different cellular structures is still challenging. Researchers have developed algorithms to automatically determine the contact points of force curves by analyzing the slope changes of the force curves [4], which may be exploited to assist in accurately determining the indentation ranges in the force curves for different cellular structures. During the experiments of AFM-based SMFS, the lifetime of the molecules attached to the surface of the AFM tip may be very short due to denaturation caused by tip damage or contamination by the loosely bound macromolecules on the biological specimen [5]. However, so far it is difficult to real-timely determine whether the tip has been contaminated or not. To obtain results with statistical significance, one needs to perform experiments with many functionalized probes, which will be quite labor-intensive and time-consuming. Recently, researchers have added photocleavable groups to the linker molecules for tip functionalization [6], which are able to control the release of the ligands attached to the AFM tip to confirm the specificity of the detected molecular interactions and thus significantly benefit improving the efficiency of SMFS experiments. Increasing the throughput of AFM experiments will remarkably make AFM more appealing to researchers. Currently, the AFM indentation experiments to measure the mechanical properties of specimens mainly rely on manual labor. Taking the measurement of cell mechanics as an example, the process includes manually controlling the AFM probe to move to the adequate position to allow the AFM probe to exactly engage the target cell, manually setting instrumental parameters to obtain force curves on the cell, manually moving the AFM sample stage to find appropriate cells, and manually processing the recorded force curves [7]. This procedure results in very low throughput: cells are measured one by one and each cell often requires several minutes [8]. In practice, to obtain

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results with statistical significance, one needs to perform measurements on a large number of cells, causing a high workload. Hence, automating the measurement process as much as possible is quite meaningful for improving the efficiency of the experiments. For example, we can use imaging processing algorithms to recognize the cells and AFM probe from the optical images, which can be exploited to automatically move the AFM probe to the adequate position for engagement. Besides, automating the process of data analysis provides an alternative way to improve the efficiency of AFM experiments. In fact, researchers have used machine learning algorithms to automatically analyze AFM topographical images of cells [9] and the force curves [10], which are useful to bypass the manual and time-consuming analysis of AFM data. Notably, there are built-in algorithms in some AFM manipulation software (such as the Nanoscope software of the commercial AFM produced by Bruker Company, http://www.bruker.com) for automatically analyzing the force curves and real-timely displaying the mechanical maps of specimens (for example the PFT-based multiparametric imaging [11]). However, performing studies to develop algorithms to intelligently analyze the AFM data is still meaningful, as researchers sometimes want to know the detailed situations (e.g., the intermediate results) of the analysis of AFM data rather than just getting the final results. When utilizing AFM to probe specimens with small sizes, such as DNA molecules, membrane proteins, viruses, and exosomes, new problems arise. Since these specimens are invisible from optical images, we need to perform blind engagement of AFM probes for AFM experiments and then identify them from the obtained AFM topographical images. In this case, developing automated algorithms based on the AFM images to increase the throughput of AFM experiments is imperative. Studies of utilizing AFM to investigate the multidimensional cellular and subcellular life activities at the same cell level will allow revealing novel insights into the biophysical cues in physiological and pathological processes. Life activities are highly heterogeneous and are associated with multidimensional (e.g., molecular level, organellar level, cellular level, tissue/organ level) behaviors [12]. So far, AFM has been widely applied to individually probe various biological systems (e.g., DNA molecules, protein molecules, viruses, exosomes, cells, and ECMs), which have been described in the previous chapters of the book. However, these studies are often ensemble-averaged assays without considering the biological heterogeneity. For example, when utilizing AFM to detect the structures and properties of organelles (e.g., mitochondria [13], nuclei [14]), many cells are lysed to collect the organelles and then these organelles are characterized by AFM. The drawback of this research strategy is that we do not know which cell the AFM-probed organelles originate from, and thus we cannot directly

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establish the relationship between cells and their organelles at the same cell level. To eliminate the influence of cellular heterogeneity on the measurement results, we need to firstly probe the selected cell. After that, the selected cell is lysed to collect the organelles and these organelles are then probed by AFM. For doing so, we can directly correlate cell behaviors with organelle behaviors at the same cell level. Studies have shown that it is feasible to extract intracellular contents from single selected living cells by FluidFM manipulations [15], which significantly benefits investigating the cellular and subcellular activities at the same cell level. After extracting the organelles from the selected cell, the established methodologies of utilizing AFM to probe organelles can be directly applied. Besides, since AFM detection is label-free, the biochemical properties of the organelles can be detected by biochemical methods after AFM characterization, which will be quite meaningful for comprehensively understanding cellular and subcellular activities at the same cell level. Characterizing the behaviors of biological systems by the AFM toolbox under conditions closer to the in vivo environments are essential for faithfully understanding the biophysical cues in biological activities. There is still a huge gap between current studies of biological specimens by AFM and real situations in vivo. Taking the measurement of cell mechanics as an example, so far, the studies are commonly performed on cell lines grown in vitro. Due to the remarkable differences between primary cells in vivo and cell lines in vitro, performing AFM mechanical measurements on primary cells in vivo is beneficial to understand the real mechanical behaviors of cells, which requires isolating primary cells from the human body while maximally maintaining the fidelity of the cells. The mechanical properties of cells are closely related to the microenvironment surrounding them [16]. Nevertheless, the microenvironment of the cell lines provided in the current AFM-based mechanical studies is very different from that in the body. For example, cell lines are often seeded in two-dimensional petri dish (or cells are seeded on glass slides and then the glass slides are placed in the petri dish containing the cell growth medium) and then AFM measurements are performed in the static cell growth medium. The two-dimensional environment is obviously unnatural, and, in two-dimensional cultures, many cell types develop different phenotypes and genotypes with respect to what happens in vivo [17]. Researchers have utilized AFM to investigate the mechanical properties of cells grown in a threedimensional microenvironment constructed by hydrogels [18], which allows for better recapitulation of the microenvironment of cells and the subsequent cell mechanics. In the human body, fluidic microenvironments such as blood and lymphatic vessels play an important role in physiological and pathological processes. Particularly, fluidic mechanics

Atomic Force Microscopy for Nanoscale Biophysics

References

313

has been shown to be closely associated with tumor metastasis [19]. A recent study has been performed to reveal the significant effects of a fluidic shearing environment on the mechanical properties of cells by combining AFM with a fluidic medium device [20], which benefits understanding the mechanical cues in fluidic environments. Taken together, AFM opens up the door to an exciting new world for biophysics, which provides substantially novel insights into life activities and human diseases. AFM is also highly compatible with other complementary techniques, offering novel possibilities for mechanobiology. There is still huge room for further advancements in AFM itself and its biomedical applications. In the future, as AFM is exploited to address more biological issues and investigate more biological systems, we have much to look forward to.

References [1] B. Alberts, A. Johnson, J. Lewis, D. Morgan, M. Raff, K. Roberts, et al., Molecular Biology of the Cell, sixth ed., Garland Science, New York, 2014. [2] H. Schillers, I. Medalsy, S. Hu, A.L. Slade, J.E. Shaw, Peakforce tapping resolves individual microvilli on living cells, J. Mol. Recognit. 29 (2) (2016) 95101. [3] C.R. Guerrero, P.D. Garcia, R. Garcia, Subsurface imaging of cell organelles by force microscopy, ACS Nano 13 (8) (2019) 96299637. [4] N. Gavara, Combined strategies for optimal detection of the contact point in AFM force-indentation curves obtained on thin samples and adherent cells, Sci. Rep. 6 (2016) 21267. [5] Y.F. Dufrene, D. Martinez-Martin, I. Medalsy, D. Alsteens, D.J. Muller, Multiparametric imaging of biological systems by force-distance curve-based AFM, Nat. Methods 10 (9) (2013) 847854. [6] M. Koehler, C.L. Giudice, P. Vogl, A. Ebner, P. Hinterdorfer, H.J. Gruber, et al., Control of ligand-binding specificity using photocleavable linkers in AFM force spectroscopy, Nano Lett. 20 (5) (2020) 40384042. [7] M. Li, D. Dang, L. Liu, N. Xi, Y. Wang, Atomic force microscopy in characterizing cell mechanics for biomedical applications: a review, IEEE Trans. Nanobiosci. 16 (6) (2017) 523540. [8] D. Di Carlo, A mechanical biomarker of cell state in medicine, J. Lab. Autom. 17 (1) (2012) 3242. [9] I. Sokolov, M.E. Dukukin, V. Kalaparthi, M. Miljkovic, A. Wang, J.D. Seigne, et al., Noninvasive diagnostic imaging using machine-learning analysis of nanoresolution images of cell surfaces: detection of bladder cancer, Proc. Natl. Acad. Sci. USA 115 (51) (2018) 1292012925. [10] P. Muller, S. Abuhattum, S. Mollmert, E. Ulbricht, A.V. Taubenberger, J. Guck, nanite: using machine learning to assess the quality of atomic force microscopyenabled nano-indentation data, BMC Bioinforma. 20 (1) (2019) 465. [11] M. Li, X. Xu, N. Xi, W. Wang, X. Xing, L. Liu, Multiparametric atomic force microscopy imaging of single native exosomes, Acta Biochim. Biophys. Sin. 53 (3) (2021) 385388. [12] M. Larance, A.I. Lamond, Multidimensional proteomics for cell biology, Nat. Rev. Mol. Cell Biol. 16 (5) (2015) 269280. [13] Y. Tian, J. Li, M. Cai, W. Zhao, H. Xu, Y. Liu, et al., High resolution imaging of mitochondrial membranes by in situ atomic force microscopy, RSC Adv. 3 (2013) 708712.

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[14] Y. Sakiyama, A. Mazur, L.E. Kapinos, R.Y.H. Lim, Spatiotemporal dynamics of the nuclear pore complex transport barrier resolved by high-speed atomic force microscopy, Nat. Nanotechnol. 11 (8) (2016) 719723. [15] O. Guillaume-Gentil, R.V. Grindberg, R. Kooger, L. Dorwling-Carter, V. Martinez, D. Ossola, et al., Tunable single-cell extraction for molecular analyses, Cell 166 (2) (2016) 506516. [16] O. Chaudhuri, J. Cooper-White, P.A. Janmey, D.J. Mooney, V.B. Shenoy, Effects of extracellular matrix viscoelasticity on cellular behavior, Nature 584 (7822) (2020) 535546. [17] J. Nicolas, S. Magli, L. Rabbachin, S. Sampaolesi, F. Nicotr, L. Russo, 3D extracellular matrix mimics: fundamental concepts and role of materials chemistry to influence stem cell fate, Biomacromolecules 21 (6) (2020) 19681994. [18] M.D.A. Norman, S.A. Ferreira, G.M. Jowett, L. Bozec, E. Gentleman, Measuring the elastic modulus of soft culture surfaces and three-dimensional hydrogels using atomic force microscopy, Nat. Protoc. 16 (5) (2021) 24182449. [19] G. Follain, D. Herrmann, S. Harlepp, V. Hyenne, N. Osmani, S.C. Warren, et al., Fluids and their mechanics in tumour transit: shaping metastasis, Nat. Rev. Cancer 20 (2) (2020) 107124. [20] J. Wei, M. Li, Y. Feng, L. Liu, Measuring the mechanical properties of cancerous cells in fluidic environments by atomic force microscopy, Prog. Biochem. Biophys. 49 (10) (2022) 20412053.

Atomic Force Microscopy for Nanoscale Biophysics

Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A A549 (human lung cancer cell line) cells, 149150, 152153, 222224, 237238, 239f A549-ACE2, 152153 Abbe diffraction, 45 AC mode AFM, 1517 Acidianus bottle-shaped virus, 137 Acoustic wave, 291293 Adherent cells, 221226, 246248 Adhesion force, 1819, 2123, 111114, 118120, 119f, 130131, 150152, 174177, 203205, 237238 Adult T cell leukemia, 136137 AFM force spectroscopy, 1731 high-speed atomic force microscopy, 3132, 33f mechanically unzipping single DNA molecules, 5861 single-cell force spectroscopy, 2527, 26f single-cell mechanical measurement, 1925, 20f, 24f single-molecule force spectroscopy, 2731, 28f topography and recognition imaging, 3335, 34f AFM indentation assay, 111114, 128130 AFM-based mechanical studies, 312313 AFM-based SMFS, 309310 Aldehyde-PEG-NHS, 147149 Alginate, 116118 Alveolar type II (ATII) cells, 227228, 228f Amino-functionalization, 2829 1-(3-aminopropyl)silatrane (APS), 4647 3-aminopropyltriethoxysilane (APTES), 4647, 4950, 9495, 210212 Ammonium hydroxide, 275279 Anchorage-dependent cells, 221222 Angiotensin-converting enzyme 2 (ACE2) receptor, 138f, 149150, 151f, 152153 Animal cell structures, 219221, 220f

Antibody-dependent cellular cytotoxicity (ADCC), 249255 Anticancer drugs, 4950 DNA mechanics, 5556 Anti-CD19 antibodies, 256258 Anti-CD20 antibodies, 256261 Approach-dwell-retract cycle, 1921 APTES-treated mica, 4950 Articular chondrocytes (AC-ECM), 274275 Artificial lipid bilayer membrane, 9495 Aspergillus fumigatus, 197198 Atomic force microscopy (AFM) force spectroscopy techniques, 1931 single-cell force spectroscopy, 2527 single-cell mechanical measurement, 1925 single-molecule force spectroscopy, 2731 high-speed atomic force microscopy, 3132 molecular force assay, 6061 topographical imaging modes, 519, 6t basic principles, 511 contact mode, 1114, 12f noncontact mode, 1415 peak force tapping mode, 12f, 1719 tapping mode, 1517

B B cells, 249252, 256258 Bacillus atrophaeus, 197198, 197f Bacteria specific types Bacteriophage, 150152 Bacteriorhodopsin, 7779, 8690, 9394 Basement membrane, 269271, 270f, 275279, 277f B-cell lymphoma, 246248, 255256 B-cell non-Hodgkin lymphoma, 248249 Bead-based immunocapture, 164165, 166t BellEvans model, 2930 β-lactoglobulin, 124125

315

316

Index

Biochemical cues, 23 Biointerfaces, 35 Biological membranes, 7576 Biomedical application, 309, 313 Biophysics, 15 Blood and lymphatic circulatory systems, 269271 Blood and tissue, 229231 Bone marrow stromal cells (BM-ECM), 274275 Bovine serum albumin (BSA), 2527, 271272, 279281 Brome mosaic virus (BMV), 139141, 140f Brownian motion, 3132, 154155 Built-in algorithms, 310311 Burkitt’s lymphoma, 136137, 248249

C C2C12 (mouse myoblast cell line) cells, 222224 Cancer metastasis, 4344 Cancer-associated fibroblast (CAF), 275279, 277f Candida glabrata, 205207 Cantilever oscillations, 3335 Capsid, 137, 141145, 154155 Capsid disassembly, 146147 Capsid protein (CA), 154155 Carboxyfluorescein succinimidyl ester (CFSE), 252258 Carcinomas, 275279 Carnivorous plants, 108 pinguicula, 111114 sundew, 108, 109f Caveolin-1 knockout mouse embryonic fibroblasts (KO-MEFs), 274275 CD19 magnetic beads, 256258 Cell adhesion, defined, 2527 Cell culture medium-forming nanogranular topography, 284285 Cell growth medium, 227228 Cell growth, 279281, 279f Cell mechanics measurement, 297299 Cell membrane, 309310 molecular interactions, 8890 Cell nucleus, 309310 Cell organelles, 7576 Cell states, 229231 CellECM interactions, 269271 Cell-free DNA (cfDNA), 4344, 67 Cell-free RNA (cfRNA), 4344 Cellhydrogel interactions, 127130, 129f

Cell-seeded coverslips, 301305 Cell surface receptors, 34, 34f, 241244 Cell surface structures of typical microbes, 188191, 189f Cellular areas being poked, 229231 Cellular electrophysiology, 289291 Cellular heterogeneity single-cell analysis, 12 tumor therapeutics, 12 Cellular plasma membranes, 7576 Cellular processes, 34 Cellular relaxation time, 23 Cellular structures, 219221 Center-of-mass (COM), 153154 Cervical cancers, 136137 Chemotherapy drugs, 255256 Chitin, 200203 Chronic lymphocytic leukemia, 255256 Cisplatin, 4950, 6061 Close loop, 59 CO2 incubator, 224226 Collagen solution containing fibroblasts, 275279 Colorectal cancer, 187188 Combining atomic force microscopy, 289308 fluidic environment, 301305, 303f, 304f fluidic force microscopy, 293297, 294f, 296f micropipette, 297301, 298f, 300f scanning near-field ultrasound holography, 290f, 291293 Complementary techniques, 289291 Complement-dependent cytotoxicity (CDC), 249252, 250f Concanavalin A (ConA), 2527, 192193, 205207 Conformational dynamics, of single membrane proteins, 8892 Contact mode AFM, 1114, 12f Contact time, 2527, 205207, 206f, 237238 Core protein (Cp), 154155 Coronavirus 2 (SARSCoV-2), 136137, 138f, 139141, 149150, 152153 Coronavirus disease 2019 (COVID-19). See Coronavirus 2 (SARSCoV-2) Corynebacterium glutamicum, 7981 Cowpea chlorotic mottle virus (CCMV), 143145 Cre-loxP synaptic complex, 6266 Cross-correlation-based algorithms, 9091

Index

Cruciform plasmid DNA, 4749 Cryogenic electron microscopy (cryo-EM), 45, 7677, 137139, 163164, 168170 Cryo-SEM, 107 C-terminal domain (CTD), 154155 Cultured cell-derived decellularized ECM, 274275 Cyclic nucleotide-binding (CNB) domains, 8184, 83f Cylindrical aperture, 296297 Cytoplasm, 9597, 189f, 219224, 231232, 250f Cytoskeleton, 23, 229231, 309310 Cytosol, 7576

D 3D manipulator, 297299 Daunorubicin (Dau), 5254 Decellularized extracellular matrix, 272275 Decellularized mesentery, 275279 Deformation, 174177 Degradation process, of hydrogels, 120122 Deionized water, 114116 Dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin receptor (DC-SIGNR), 149150 Dense filament network, 222224 Deoxyribonucleic acid (DNA) molecules, 12, 1516, 4346 extracting persistence length, 5558, 57f probing behaviors by origami method, 6166, 63f, 64f sample preparation, 4447 targeted anticancer drugs, 4950 time-lapse imaging, 5255, 53f topographical imaging, 4752 DerjaguinMullerToporov (DMT) model, 1819, 2123 D-galactose, 116118 Differential ultracentrifugation, 164165, 166t Differentiation, 269271 Dimension Icon AFM, 108, 168170, 174177 D-mannose, 116118 DNA conformational dynamics, 6667 DNA damage response (DDR), 4344, 4950

317

DNA origami technology, 6166, 63f DNA strand, 4344 DNA-binding proteins, 5152 DNAprotein complexes, 6061 Drug resistance, 12, 200 Dynamic force mode AFM, 1517

E Ebola virus, 137, 149150 Ebola virus disease (EVD), 136137 Electron microscopy, 45, 6t, 44, 271272 Electrostatic adsorption, 191192 Endocardium, 272274 Endosomal pathway, 162163 Endothelial basement membrane, 275279 Energy dissipation, 12f, 1619, 174177, 176f Enveloped viruses, 137, 138f Environmental temperature of measurement, 229231 Epicardium, 272274 Epidermal growth factor (EGF), 180, 241244 Epithelial-derived tumors, 275279 Epstein-Barr virus (EBV), 136137 Error signal, 1113 Escherichia coli, 187188 Exocytosis, 227228, 228f ExoMir Kit, 164165 Exosome isolation/immobilization, 164168, 166t, 168f Exosomes, 162165 formation and structures, 162f Extracellular matrix (ECM), 24, 105107, 237238 basement membranes, structures and mechanics, 275279, 277f cell growth, cell culture medium-forming nanogranular surface, 279281, 279f decellularized, mechanical properties, 270f, 272275, 273f tuning cellular structures/mechanics, hierarchical micro-/ nanotopography, 281284 Extracellular polymeric substance (EPS), 203205, 207210 Extracellular vesicles (EVs), 161165, 162f Extravasation, 275279

F Feedback parameter, 1113, 1518

318

Index

Fetal bovine serum (FBS), 229231, 279281 Fibroblasts, 222224, 274275 Fibronectins, 269271 Fibronectin (Fn)-binding proteins (FnBPA), 205207 Fibrous proteins, 269271 Fine structures, 221224 Fluidic cell growth medium environment, 301303 Fluidic environment, 301305, 303f, 304f Fluidic force microscopy (FluidFM), 289291, 293297, 294f, 296f, 311312 Fluidic microenvironments, 312313 Fluorescence correlation spectroscopy (FCS), 8890 Fluorescence intensity distribution analysis (FIDA), 8890 Fluorescence labeling, 227228 Fluorescence lifetime imaging microscopy (FLIM), 8890 Fluorescence microscopy, 210212, 211f, 227231, 238241 Fluorescence recovery after photobleaching (FRAP), 8891 Fluorescence resonance energy transfer (FRET), 8890 Fluorescent microscopy, 205207, 252255, 272274 Focused ion beam (FIB), 238241, 296297, 296f Force curve, 12f, 1721, 2731, 8486 Forcedistance (FD) curves, 1721 Force volume mode, 3335, 232234 Forcetime (FT) curves, 1921, 20f, 23 Freeze-dried hydrogels, 116118 Functionalized probe, 238241 Fungi, 187191, 189f

G Galectin-3, 237238 Gap junction plaques, 8184, 83f Gel electrophoresis, 5556 Gene, 4344 Generalized polarization (GP), 8890 Genomic instability, 4344 Gigahertz frequency, 291293 Glycocalyx, 98 Glycoprotein, 98 Glyphosate, 234237 Golgi apparatus, 7576

Gonadotropin-releasing hormone receptor (GnRH-R), 244245 Gram-negative bacteria, 188191, 193197, 200203 Gram-positive bacteria, 188191 Gum Arabic, 116120

H HaCaT keratinocytes, 234237 Halobacterium halobium strain, 7779 Hard sphere diameter, 911 H-bonds, 165168 HCV29 cells, Young’s modulus, 229231 HEK 293 cells, 244245 HeLa (human cervical cancer cell line) cells, 168170, 222224 Heparin-binding haemagglutinin adhesin (HBHA), 203205 Hepatocellular carcinomas, 136137 Hepatitis B virus (HBV), 136137, 154155 Hepatitis C virus (HCV), 136137 Hereditary spherocytosis (HS), 174 Herpes simplex virus type 1 (HSV-1), 139141, 140f, 143147 HertzSneddon model, 1819, 2123, 111114, 127128, 172173, 200, 299301 Heterobifunctional PEG crosslinker, 2829 HGC-27 (human gastric cancer cell line) cells, 303305 High-frequency acoustic wave, 291293 High-speed AFM time-lapse imaging, 5455 High-speed AFM topographical imaging, 8891 High-speed atomic force microscopy, 3132, 33f Homeostasis, 34, 161162, 237238, 269271 Hooke’s law, 1921, 200 Horizontal gene transfer (HGT), 135136 Human adenovirus, 141143 Human bone marrow endothelium (HBME) cells, 237238 Human breast cancer cells (HBCCs) cells, 237238 Human diseases, 309, 313 Human epidermal growth factor receptor-2 (HER2), 241244, 242f Human immunodeficiency virus (HIV), 154155 Human papillomavirus (HPV), 136137

Index

Human pluripotent stem cells (hPSCs), 274275 Human pulmonary artery endothelial cells (HPAECs), 232234, 235f Human rhinovirus (HRV), 147149, 153154 Human small airway epithelial cells (HSAECs), 222224 Human T-lymphotropic virus-I (HTLV-I), 136137 Human umbilical vein endothelial cells (HUVECs), 242f, 244245 Hut cells, 248249 Hut 78 cells, 248249 Hydrocolloids, 116118 Hydrogels, 105107 degradation process, 120122 natural plant, nanostructures/ nanomechanics, 108116, 109f, 110f, 112f, 113f, 115f characterizations, 116122, 117f, 119f, 121f peptide-assembled nanofibrillar, imaging and mechanical analysis, 122127, 123f, 125f, 126f probing mechanical cues in cellhydrogel interactions, 127130, 129f three-dimensional hydrogels, 106f Hydrolysis, 4344 sundew mucilage, 116118

I Imaging single native exosomes, 168172, 169f, 171f Immobilization strategies, 246248 In vivo environments, 312313 Indentation assay, 143145 Inflammatory bowel disease (IBD), 187188 Injection/extraction pumps, 303305 Intercellular heterogeneity, 12 Intermittent contact mode AFM, 1517 Interpenetrating polymer networks (IPNs), 105107 Intertumoral heterogeneity, 12 Intraluminal vesicles (ILVs), 162163, 162f Intramolecular DNA triplex, 4749 Intratumoral heterogeneity, 12 Intravasation, 275279 Invading cells, 275279

319

Invasive fungal disease (IFD), 187188 Ionic treatment, on mica surface, 4546

J Jasmonic acid, 108 JohnsonKendallRoberts (JKR), 1819, 2123

K K562 cells, 248249 Kaposi’s sarcoma, 136137 Kaposi’s sarcoma herpesvirus (KSHV), 136137 Kolibri sensor, 1415 Kuhn length, 5556

L β-lactam-resistant (BLR) bacteria, 207210 β-lactam-susceptible (BLS) bacteria, 207210 Lactococcus lactis cells, 193197 Lamellipodial protrusions, 220f L-arabinose, 116118 Lateral gene transfer, 135136 Lead zirconate titanate (PZT), 59 LennardJones function, 911, 11f L-glucuronic acid, 116118 Life activities, 311312 Light-harvesting 2 (LH2) complexes, 7981 Light-scattering, 5556 Linear subelastic chain (LSEC), 5556 Linkers, 2829 Lipid rafts, 7576, 77f, 8890 Lipopolysaccharide (LPS), 9091, 189f, 200203 Liquid biopsy, 164165, 181 Living animal cells, cell membrane, 309310 Living COS-7 cells, 224226 Living HaCaT cells, 234237 Living HeLa cell, 224226 Living MCF-7 cells, 224226 Living microbial cells immobilization methods, 191193, 191f multiparametric atomic force microscopy imaging, 207210 visualizing the nanostructures/ dynamics, 193199, 194f, 197f, 199f, 201f Loading force of probe cantilever, 1921 Loading rate of probe, 229231 Localization AFM (LAFM), 4

320

Index

Lung diseases, AFM, 272274 Lung fibrosis, 272274 Lymphoma cells, 248258 Lysosome, 7576, 162f

M Machine learning algorithms, 310311 Macrophages, 241244, 252255, 291293 Madin-Darby canine kidney (MDCK) cells, 149150, 152153, 222224, 223f, 225f Magnetic resonance elastography (MRE), 271272 Magnetic tweezers, 45, 6t, 5860 Malaria, 23 Mantle cell lymphoma, 255256 MasonPfizer monkey virus (M-PMV), 139141, 140f Matrix metalloproteinase (MMP), 106f, 128130 Maxwell model, 23, 231232 MCF-7 (human breast cancer cell line) cells, 222224, 231234, 303305 MCF-10A cells, 172174, 229232, 245246 MCFCA1a cells, 245246 MDA-MB-231 cells, 168170, 229231, 234237 Mechanical fatigue experiment, 141143 Mechanical properties, 219222, 229241, 245246, 248249, 249f, 256258, 257f Mechanobiology, 180, 188191, 221222, 309, 313 Mechanotransduction, 127128 Membrane attack complex (MAC), 249252 Membrane proteins, 7576 biological functions, 8486 Merkel cell carcinoma, 136137 Merkel cell polyomavirus (MCV), 136137 Mesenchymal stem cells (MSCs), 127130 Metabolic syndrome, 187188 Meta-DNA, 6162 Metastasis, 34, 224226, 231232, 234238, 275279 Mica, 4445 APTES-treated, 5556 attaching DNA molecules chemical functionalization, 4647 ionic treatment, 4546 mucilage-coated, 108111 NiCl2-treated, 5254 Rhodobacter sphaeroides patches, 7981

Microbial activities, 210212, 211f Microbial adhesion, 203207 Microchanneled cantilever, 210212, 211f, 289291, 293296, 294f Microchanneled probe, 293299 Microfluidic injection system, 5254 Microgrooves, 281285 Microorganisms, 34, 187191 Micropipette, 297301, 298f, 300f Micropump, 297299, 301303 MicroRNA, 6667 Microvilli, 222224, 249252, 250f Middle East respiratory syndrome coronavirus (MERS-CoV), 136137 Mimivirus, 139141, 140f Minimum inhibitory concentration (MIC), 207210 Minute virus of mice (MVM), 146147 Mitochondria, 7576, 77f, 188191, 311312 Mitochondrial-derived vesicles (MDVs), 162f MlotiK1 potassium channel, 8184, 83f Molecular biology, 44, 9192, 97 Molecular dynamics, 8890, 198199, 199f, 227228 Molecular force assay (MFA), AFM with, 6061 Molecular interactions, 8486, 8890, 152153, 177181, 245246 Molecular modeling methods, 5556 Molecular self-assembly, 6162 Moloney murine leukemia virus (MMuLV), 139141 Mucilage, 108, 109f, 111114, 112f, 116120 Multiparametric AFM, 1819 Multivesicular bodies (MVBs), 162163, 162f Myocardium, 272274 Myocardium scar, 272274

N Nanofibrillar hydrogels, peptideassembled, imaging and mechanical analysis, 122127, 123f, 125f, 126f Nanofibrils, 108111 peptide-based hydrogels, 124125, 125f self-assembly behaviors, 122124 Nanogranular surface, 279281 Nanomaterials, 291293 Nanomaterials-based drug delivery, 291293

Index

Nanoparticles, 108114, 120122, 291293 Native biomolecules, 289291 Natural membranes, 7981, 80f, 9495 Natural plant hydrogels, nanostructures and nanomechanics, 108116, 109f, 110f, 112f, 113f, 115f characterizations, 116122, 117f, 119f, 121f Neurons, 23, 219221, 227228 NHS-PEG-acetal linker molecules, 245246 NIH-3T3 cells, 232234 NK cell, 252255, 258261 Noncontact AFM (NC-AFM), 1416 Nonenveloped viruses, 137 Noninvasive imaging method, 291293 Normal rat kidney (NRK) cells, 222224, 232234 Nuclear magnetic resonance (NMR) spectroscopy, 7677 Number and brightness analysis (N&B), 8890

O Obesity, 136137, 187188 Oligonucleotide, 5862 OliverPharr model, 2123 Oncolytic viruses, 135136 Open loop, 59 Optical microscopy techniques, 271272, 297299 Optical tweezers, 45, 6t Origami method, 6166 Oscillation mode AFM, 1517 Outer membrane protein F (OmpF), 9091

P Patch clamp amplifier, 296297 Pauli exclusion principle, 911 Peak force tapping (PFT) mode, 12f, 1619 Peak force tapping (PFT)-based multiparametric AFM imaging, 9192, 93f fluorescence microscopy, 9394 Penile cancers, 136137 Peptide-assembled nanofibrillar hydrogels, 122124 imaging and mechanical analysis, 122127, 123f, 125f, 126f Peptide-based hydrogels, 125127, 126f Peripheral blood mononuclear cells (PBMCs), 256258, 257f Periplasm, 188191, 189f

321

Peristome, 114116 Persistence length of DNA molecules, 5558 PFT-based multiparametric AFM imaging, 125127, 126f, 310311 pH, 7779 Phase imaging, 1617 Phase lag, 1617 Phase shift, 1617 Phorbol 12-myristate 13-acetate (PMA), 227228, 228f Phosphate buffered saline (PBS), 2527, 9495, 151f, 154155, 165170, 169f, 210212, 255256, 272274, 297299, 301303 Photo counting histogram (PCH), 8890 Photoactivated localization microscopy (PALM), 45, 6t, 227228, 228f Photosynthetic membrane, 7981, 80f Pinguicula mucilage, 111114, 112f Pitcher, 114116 Plasma membrane, 77f, 9598, 96f lipid bilayer, 7576 Plasmid, 135136 Plectonemic supercoiled plasmid DNA, 4749 Poisson ratio, 2123 Polydopamine-coated colloidal probe, 205207 Polyethylene glycol (PEG), 2829 Poly-L-lysine, 139141, 165170, 172174 -based electrostatic adsorption, 168170 Polymer-based precipitation, 166t Polysaccharide intercellular adhesin (PIA), 207210 Position sensitive detector (PSD), 59 Prebiotics, 187188 Primary cell, 256261 Premetastatic niche, 161162 Probe, AFM, 229234 Probing viral binding affinity, Single-virus force spectroscopy, 147150, 148f Probiotics, 187188 Programmed cell death (PCD), 249252 Programmed death-ligand 1 (PD-L1), 241244 Protease-activated receptor-1 (PAR1), 9192 Protein misfolding, 3031 ProteinDNA interactions, 5152 Proteins, 9192 Proteoglycans (PGs), 269271

322

Index

P-selectin, 237238 PTFE tube, 297299 Purple membrane, 7779 bacteriorhodopsin molecules, 8890, 89f immobilization, 7779

Q qPlus, 1415 Quantitative analysis, 9192, 275279

R Rabies virus (RABV), 152153 Raji cells, 246256, 247f, 258261 Raman spectroscopy of cells, 291293 Reaction center (RC)-LH1-PufX dimers, 7981 Reaction coordinate, 8486 Reactive oxygen species (ROS), 4344 Receptor tyrosine kinase orphan receptor 1 (ROR1), 258261 Receptorbinding domain (RBD), 149150, 153154 Red blood cells (RBCs), 9495, 174, 248249, 291293 Relaxation curve, 1921, 231232 Resonance frequency shift, 4749 Resonant frequency method, 1921 Retinitis pigmentosa, 8688 Rhodobacter sphaeroides, 7981 Rhodopsin, 7981, 80f, 8688, 87f Ribonucleic acid (RNA), 4344 Ribonucleoprotein (RNP), 154155 Rituximab, 246256, 258261 Rod-shaped tobacco rattle virus, 137 Roseobacter denitrificans, 7981 Rotavirus, 137

S Sample preparation, 4447 Sarcomeres, 219221 Satellite tobacco mosaic virus (STMV), 139141 Scaffolded DNA origami method, 6162 ScanAsyst Fluid, 168170 Scan force, 1113 Scanning electron microscopy (SEM), 45 Scanning near-field ultrasound holography (SNFUH), 290f, 291293 Self-assembly, 154155 Setpoint, 1113, 1516 Severe acute respiratory syndrome Coronavirus 2 (SARSCoV-2), 136137

SfiI-DNA complexes, 5152 Side-opening petri dish, 301303 Signal-to-noise ratio (SNR), 4546, 9495 Silicon nitride, 1314, 210212, 211f Single D96N bacteriorhodopsin molecules, structural dynamics of, 89f Single exosomes, 177179, 178f Single membrane proteins, high-resolution imaging and force spectroscopy of multiparametric AFM imaging, 9194, 93f observing dynamics by high-speed AFM, 8891 topographical imaging, 7784, 80f topography and recognition imaging, 9497, 96f unfolding mechanics, 8488 Single native exosomes¸ mechanics of, 172177, 173f, 176f, 177f Single viruses fine structures, 139143, 140f, 142f nanoindentation for mechanical measurements/manipulations, 143147, 144f, 146f Single-cell analysis, 12 Single-cell biochemical analysis, 12 Single-cell drug delivery, 297299 Single-cell force spectroscopy (SCFS), 2527, 26f, 203207, 204f, 206f Single-cell injection system, 297299, 298f, 300f Single-cell level, 255256 Single-cell mechanical measurement, 1925, 20f, 24f Single-molecule fluorescence microscopy, 44 Single-molecule force spectroscopy (SMFS), 2731, 28f, 177179, 203207, 204f, 206f AFM-based, 5861 unfolding single membrane proteins, 8488, 85f unfold single rhodopsin molecules, 8688, 87f Single-particle tracking (SPT), 8890 Single-walled carbon nanoparticles, 291293 Size-based isolation, 166t Sodium-glucose cotransporter 1 (SGLT1), 241244 Solid tumors, ECM, 269271 Specimens, 289291, 310311 Sprague Dawley rats, 227228

Index

Staining procedure, 188191 Staphylococcus aureus cells, 193197 Staple strands, 6162 Static mass hanging method, 1921 Stimulated emission microscopy (STED), 45 Stochastic molecular interactions, 12 Stochastic optical reconstruction microscopy (STORM), 45 Streptococcus mutans, 205207 Structural biology, 7677, 8184, 155156 Substrate, 191192, 229231 Sundew mucilage, 108, 109f Sundew-inspired hydrogel adhesion properties, 118120, 119f degradation process, 120122 fabricating, 116118, 117f preparation of, 116118, 117f Supercoiling structure imaging, 4749, 5254 Superresolution optical microscopy, 6t, 198199 Syringe, 297299

T Tapping mode AFM, 1517 T-cell lymphoma, 248249 Termitomyces clypeatus, 200203 Thermal noise method, 1921 Thermodynamic equilibrium model, 6061 Thomsen-Friedenreich antigen, 237238 Three-dimensional (3D) manipulation capability, 289291 Three-dimensional hydrogels, 105107, 106f, 128130, 129f Three-dimensional WLC model, 5758 Time-lapse AFM imaging, 6266 Time-lapse AFM topographical imaging, 5255, 53f Tip functionalization, 2829, 203205, 309310 Tissue morphogenesis, 269271 Topographical imaging degradation process of hydrogels, 120122 of single DNA molecules, 4752 of single native membrane proteins, 7784, 80f Topography and recognition imaging (TREC) mode AFM, 3335, 34f of single membrane proteins, 9497, 96f Touching-sliding-sandwiching-wrapping, 5455

323

Toxicology, 291293 Transcription, 12, 4344, 5152 Translation, 4344 Transmembrane helices (TMHs), 8486 Transmission electron microscopy (TEM), 45, 198199 Triatoma virus (TrV), 143145 Tris buffer saline (TBS), 207210 Trumpet pitchers nectar, 115f predation mechanisms, 114116 Tumor therapeutics, cellular heterogeneity in, 12 Tumor virus receptor A (TVA), 152153 Tumorigenesis, 34 Two-dimensional environment, 128130, 312313 Two-dimensional planar patterns, 6162, 63f Two-dimensional WLC model, 5758

U Ultrasound technology, 289293, 290f Unfolding mechanics, of individual native membrane proteins, 8488, 85f, 87f Urinary tract infections (UTIs), 187188

V van der Waals force, 911 Vascular endothelial growth factor receptor-2 (VEGFR2), 242f, 244245 Venus flytraps nectar secreted by, 115f predation mechanisms, 114116 Vibrating tip carrying ligands, 244245 Viral genome, 137, 138f, 141147 Virion, 137 Virotherapy, 135136 Viruscell interactions, 150153, 151f Virus life cycle, 137 Viruses, structures and behaviors, 138f Virus-mediated gene transfer, 135136 Viscoelasticity, 1617, 1921, 231232, 233f, 269271 Viscosity assays, 5556 Visualizing individual viral dynamics, 153155, 154f

W WatsonCrick base-pairing, 6162 Wild-type mouse embryonic fibroblasts (WT-MEFs), 274275

324 Working solution, 229231 Worm-like chain (WLC) model, 3031, 5558, 8488, 124125

X XR1 glial cells, 222224 X-ray crystallography, 44, 7679

Index

Young’s modulus, 1823, 111114, 127128, 172177, 173f, 200203, 229234, 248249, 256258, 274275, 284285, 299301, 303305, 304f YOYO-1, 141143

Z Y Yeast cells, 188197, 200207

Zeta potential (ZP), 165168 Zika virus (ZIKV), 136137