Natural Killer (NK) Cells: Methods and Protocols (Methods in Molecular Biology, 2463) [1st ed. 2022] 9781071621592, 9781071621608, 1071621599

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Methods in Molecular Biology 2463

Noriko Shimasaki Editor

Natural Killer (NK) Cells Methods and Protocols

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Natural Killer (NK) Cells Methods and Protocols

Edited by

Noriko Shimasaki Centre for Translational Medicine, National University of Singapore, Singapore, Singapore

Editor Noriko Shimasaki Centre for Translational Medicine National University of Singapore Singapore, Singapore

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-2159-2 ISBN 978-1-0716-2160-8 (eBook) https://doi.org/10.1007/978-1-0716-2160-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface Natural killer (NK) cells are a subpopulation of lymphocytes that can recognize and lyse unhealthy cells, such as virus-infected cells and cancer cells without prior sensitization. NK cells form a network with other immune cells and regulate immune responses. NK cells have been considered to be a part of the innate immune system, but recently memory-like NK cells were identified as a subpopulation of NK cells that have a potential to promote adaptive immune responses. NK cells developed from hematopoietic progenitors circulate in the peripheral bloodstream or reside in tissues. They distinguish unhealthy cells from healthy cells based on a balance of signaling from the activating and inhibitory receptors. Cells identified as being unhealthy are lysed by NK cells. In addition to the cell contact, NK cells also respond to cytokines such as interleukin (IL)-15, IL-12, and IL-18 secreted by other cells. The activated NK cells produce cytokines such as interferon γ, which recruit other immune cells. Through these responses, NK cells also act as immunoregulators. Since their identification, NK cells have been investigated, and their characteristics have been reported. However, the diversity and specific functions of the various NK cell subtypes remain unclear. Rapid technological developments promotes the investigation of the characteristics or functions of individual cells. Furthermore, NK cells became enabled to expand and be genetically modified ex vivo, which made NK cells an attractive source of cell therapy for cancer. This edition provides a broad collection of methodologies for NK cell research. The first part describes methods of isolation of NK cells and differentiating into NK cells. It also discusses methods for labeling individual NK cells and tracking their mobilization. The second part presents methodologies for functional tests, such as cytotoxicity, viral infection, and metabolism assays. The third part discusses the clinical applications of NK cells, including a review for selecting an allogeneic donor based on killer-cell immunoglobulinlike receptor genotyping, while also presenting a clinically applicable protocol for engineering genetically modified NK cells. I would like to express my gratitude to all the authors who have taken the time to prepare a chapter and share their knowledge and experiences for this edition. I hope that the chapters in this edition will be helpful for readers investigating NK cells. May their new findings contribute to the further development of the basic and clinical NK cell research. Singapore, Singapore

Noriko Shimasaki

v

Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

v ix

NK CELL SPECIFICATION

1 Isolation of Innate Lymphoid Cells from Murine Intestinal Lamina Propria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Ao Mei, Elaheh Hashemi, Mohamed Khalil, Dandan Wang, and Subramaniam Malarkannan 2 Purification of Primary Decidual Natural Killer Cells for Functional Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 ˆ ngela C. Crespo, Aria Alexander, and Tamara Tilburgs A 3 In Vitro Development of Mouse and Human NK Cells from Hematopoietic Progenitor Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Ines Ullmo, Nahide Koksal, Heather Y. K. Ang, and Hugh J. M. Brady 4 Induction of Human Natural Killer Cells Under Defined Conditions by Seamless Transition from Maintenance Culture of Pluripotent Stem Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Akira Niwa and Megumu K. Saito 5 Development of Humanized Mouse Models for Studying Human NK Cells in Health and Disease. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Liang Shan, Richard A. Flavell, and Dietmar Herndler-Brandstetter 6 Antibody–Oligonucleotide Conjugation Using a SPAAC Copper-Free Method Compatible with 10 Genomics’ Single-Cell RNA-Seq. . . . . . . . . . . . . . 67 Dominic Paul Lee, Wang Jiehao Ray, Tan Pee Mei, Shawn Hoon, Jonathan Scolnick, and Gene W. Yeo 7 Methods to Analyze the Developmental Trajectory of Human Primary NK Cells Using Monocle and SCENIC Analyses. . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Dandan Wang, Robert Burns, Mohamed Khalil, Ao Mei, Elaheh Hashemi, and Subramaniam Malarkannan 8 Methods for Isolating and Defining Single-Cell Transcriptomes of Tissue-Resident Human NK Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Elaheh Hashemi, Ao Mei, Dandan Wang, Mohamed Khalil, and Subramaniam Malarkannan 9 Retrogenic Color-Barcoding for Fate Mapping of Single Innate Lymphocytes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Simon Grassmann, Joseph C. Sun, and Veit R. Buchholz 10 Quantifying Human Natural Killer Cell Migration by Imaging and Image Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Amera L. Martinez, Michael J. Shannon, Shira E. Eisman, Everardo Hegewisch-Solloa, Aneeza N. Asif, Tasneem A. M. Ebrahim, and Emily M. Mace

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Contents

Tracking of NK Cells by Positron Emission Tomography Using 89Zr-Oxine Ex Vivo Cell Labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Noriko Sato, Lawrence P. Szajek, and Peter L. Choyke

PART II 12

13

14

15

16

17

18

19

Assessing Changes in Human Natural Killer Cell Metabolism Using the Seahorse Extracellular Flux Analyzer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Javier Traba and Olga M. Anto n Determining Activation Status of Natural Killer Cells Following Stimulation via Cytokines and Surface Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . Lizeth G. Meza Guzman and Sandra E. Nicholson Method to Study Adaptive NK Cells Following MCMV Infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohamed Khalil, Ao Mei, Elaheh Hashemi, Dandan Wang, Megan Schumacher, Scott Terhune, and Subramaniam Malarkannan Assessing the Response of Human NK Cell Subsets to Infection by Clinically Isolated Virus Strains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nobuyo Yawata and Makoto Yawata NK Cell Isolation and Cytotoxicity by Radioactive Chromium Release Assay and DELFIA-EuTDA Cytotoxicity Assay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Casey W. Buller and Stephen O. Mathew Organoid Co-culture Methods to Capture Cancer Cell–Natural Killer Cell Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Isaac S. Chan and Andrew J. Ewald In Vitro Visualization of Cell-to-Cell Interactions Between Natural Killer Cells and Sensory Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hyoung Woo Kim, Alexander J. Davies, and Seog Bae Oh CRISPR Screen to Identify Factors that Render Tumor Cells Sensitive or Resistant to Killing by NK Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaoxuan Zhuang and Eric O. Long

PART III 20

21

NK CELL FUNCTIONAL ASSAYS 165

181

195

205

221

235

251

269

CLINICAL APPLICATION

Practical Considerations and Workflow in Utilizing KIR Genotyping in Transplantation Medicine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 Makoto Yawata and Nobuyo Yawata Gene Transduction of Natural Killer Cells for Clinical Application. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Noriko Shimasaki

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

329

Contributors ARIA ALEXANDER • Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Immunobiology, Center for Inflammation and Tolerance, Cincinnati Children’s Hospital, Cincinnati, OH, USA HEATHER Y. K. ANG • Department of Life Sciences, Imperial College London, London, UK OLGA M. ANTO´N • Department for Molecular Biology, Center for Molecular Biology Severo Ochoa, Spanish National Research Council-Autonomous University of Madrid (CSICUAM), Madrid, Spain; Lymphoid Malignancies Branch, Center for Cancer Research, National Cancer Institute (NIH), Bethesda, MD, USA ANEEZA N. ASIF • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA; Department of Biology, Barnard College, New York, NY, USA HUGH J. M. BRADY • Department of Life Sciences, Imperial College London, London, UK VEIT R. BUCHHOLZ • Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich (TUM), Munich, Germany CASEY W. BULLER • Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA ROBERT BURNS • Bioinformatics Core, Blood Research Institute, Versiti, Milwaukee, WI, USA ISAAC S. CHAN • Department of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA PETER L. CHOYKE • Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA ˆ NGELA C. CRESPO • Program in Cellular and Molecular Medicine, Boston Children’s A Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA ALEXANDER J. DAVIES • Nuffield Department of Clinical Neurosciences, Level 6 West Wing, John Radcliffe Hospital, Oxford, UK TASNEEM A. M. EBRAHIM • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA; Department of Cell, Developmental, and Regenerative Biology, Icahn School of Medicine at Mt. Sinai, New York, NY, USA SHIRA E. EISMAN • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA ANDREW J. EWALD • Department of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA RICHARD A. FLAVELL • Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA; Howard Hughes Medical Institute, Yale University, New Haven, CT, USA SIMON GRASSMANN • Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

ix

x

Contributors

ELAHEH HASHEMI • Laboratory of Molecular Immunology and Immunotherapy, Blood Research Institute, Versiti, Milwaukee, WI, USA; Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA EVERARDO HEGEWISCH-SOLLOA • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA DIETMAR HERNDLER-BRANDSTETTER • Institute of Cancer Research, Department of Medicine I, Medical University of Vienna, Vienna, Austria; Comprehensive Cancer Center Vienna, Medical University of Vienna, Vienna, Austria SHAWN HOON • Molecular Engineering Laboratory, Institute of Molecular and Cell Biology (IMCB), Singapore, Singapore MOHAMED KHALIL • Laboratory of Molecular Immunology and Immunotherapy, Blood Research Institute, Versiti, Milwaukee, WI, USA; Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA HYOUNG WOO KIM • Department of Neurobiology and Physiology, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, Republic of Korea NAHIDE KOKSAL • Department of Life Sciences, Imperial College London, London, UK DOMINIC PAUL LEE • Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore ERIC O. LONG • Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA EMILY M. MACE • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA SUBRAMANIAM MALARKANNAN • Laboratory of Molecular Immunology and Immunotherapy, Blood Research Institute, Versiti, Milwaukee, WI, USA; Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA AMERA L. MARTINEZ • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA STEPHEN O. MATHEW • Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA AO MEI • Laboratory of Molecular Immunology and Immunotherapy, Blood Research Institute, Versiti, Milwaukee, WI, USA; Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA TAN PEE MEI • Molecular Engineering Laboratory, Institute of Molecular and Cell Biology (IMCB), Singapore, Singapore LIZETH G. MEZA GUZMAN • The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia SANDRA E. NICHOLSON • The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia AKIRA NIWA • Department of Clinical Application, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan SEOG BAE OH • Department of Neurobiology and Physiology, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, Republic of Korea

Contributors

xi

WANG JIEHAO RAY • Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore MEGUMU K. SAITO • Department of Clinical Application, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan NORIKO SATO • Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA MEGAN SCHUMACHER • Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA JONATHAN SCOLNICK • Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore LIANG SHAN • Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, Saint Louis, MO, USA; Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA MICHAEL J. SHANNON • Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA NORIKO SHIMASAKI • Departments of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore JOSEPH C. SUN • Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Immunology and Microbial Pathogenesis, Weill Cornell Medical College, New York, NY, USA LAWRENCE P. SZAJEK • PET Department, Clinical Center, National Institutes of Health, Bethesda, MD, USA SCOTT TERHUNE • Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA TAMARA TILBURGS • Division of Immunobiology, Center for Inflammation and Tolerance, Cincinnati Children’s Hospital, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA JAVIER TRABA • Department for Molecular Biology, Center for Molecular Biology Severo Ochoa, Spanish National Research Council-Autonomous University of Madrid (CSICUAM), Madrid, Spain INES ULLMO • Department of Life Sciences, Imperial College London, London, UK DANDAN WANG • Laboratory of Molecular Immunology and Immunotherapy, Blood Research Institute, Versiti, Milwaukee, WI, USA; Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI, USA MAKOTO YAWATA • Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; National University Health System, Singapore, Singapore; Immunology Programme, Life Sciences Institute, National University of Singapore, Singapore, Singapore; NUSMED Immunology Translational Research Programme, National University of Singapore, Singapore, Singapore; Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore; International Research Center for Medical Sciences, Kumamoto University, Kumamoto, Japan NOBUYO YAWATA • Department of Ocular Pathology and Imaging Science, Kyushu University, Fukuoka, Japan; Singapore Eye Research Institute, Singapore, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore

xii

Contributors

GENE W. YEO • Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA XIAOXUAN ZHUANG • Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA

Part I NK Cell Specification

Chapter 1 Isolation of Innate Lymphoid Cells from Murine Intestinal Lamina Propria Ao Mei, Elaheh Hashemi, Mohamed Khalil, Dandan Wang, and Subramaniam Malarkannan Abstract Natural killer (NK) cells are innate cytotoxic immune cells essential for mediating first-line defense against various environmental antigens. With the discoveries of other subsets of innate lymphocytes over the last decade, NK cells are categorized as innate lymphoid cells (ILC) and as the innate counterparts of cytotoxic T cells. Besides NK cells, ILCs are classified into three groups distinguished by their dependence on distinct transcription factors for development and unique effector functions. Subsets of ILCs share many surface proteins that, however, have initially been identified as NK cell markers, making them hard to be distinguished for detailed investigations. Here, we describe a method to identify and individually isolate subsets of innate lymphoid cells from gut lamina propria using cell surface markers. Key words Mucosa, Innate lymphocytes, Lamina propria, Epithelial cells, Development of ILCs

1

Introduction Natural killer (NK) cells are innate lymphocytes capable of mediating cytotoxicity and producing pro-inflammatory cytokines to protect the host from environmental antigens and transformed malignant cells [1]. From studies over the last decade, more types of innate lymphocytes are discovered and categorized. With the new nomenclature formed, NK cells are classified as innate lymphoid cells (ILCs) [2]. ILCs belong to the lineage of lymphocytes lacking antigen-specific receptors expressed by adaptive lymphocytes, including T and B cells. ILCs are enriched at the mucosal surface of physical barriers, sensing the shift of the environmental signals to initiate local cellular response immediately and facilitate the development of adaptive immune response [3]. ILCs are further classified into three groups based on their distinct usage of transcription factors and cellular functions.

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Group 1 ILCs containing NK cells and ILC1s depend on T-bet for IFN-γ production to mediate type 1 immunity [4, 5]. Group 2 ILCs containing only ILC2s use GATA3 and RORα to produce IL-4, IL-5, and IL-13 for type 2 immunity [6–8]. Group 3 ILCs containing ILC3s and lymphoid tissue inducer (LTi) are dependent on RORγt and Ahr to produce IL-17, IL-22, and GM-CSF for type 3 immunity [9, 10]. ILCs are indispensable for maintaining tissue homeostasis at barrier sites such as the gastrointestinal tract and skin. In murine disease models, ILCs play crucial roles in autoimmune, allergic, and inflammatory diseases [11]. In the murine graft-versus-host disease (GvHD) model, IL-22 produced by lamina propria ILC3s protects intestinal stem cells from GvHD induced inflammatory damage [12]. Besides interacting with host cells, lamina propria ILCs also regulate the commensal microbiome to maintain tissue homeostasis. Recently it was found that IL-17D from intestinal epithelial cells regulated the production of IL-22 in ILC3s to sustain intestine and microbiota homeostasis through IL-22 dependent antimicrobial peptides [13]. However, due to the phenotypic similarities within ILC subsets and between ILCs and T cells, a lack of mouse model deficient in specific ILC subsets makes it challenging to study how the individual subset of ILCs is involved in tissue homeostasis and immune response initiation. Therefore, ex vivo and in vitro methods become principal investigation strategies. Identifying and live-sorting specific subsets of ILCs provide an essential control of quality for downstream examination of ILCs. Although distinguished by their functions, subsets of ILCs share many surface proteins previously identified as NK cell markers, including NKp46, NK1.1, and NKG2D [2]. Current fluorescent-based methods in discriminating ILC populations require fluorescent conjugated ILC signature transcription factors or cell membrane permeabilization for intracellular staining. Those methods are either limited to specific mouse strains or unable to keep cells alive for fluorescent activated cell sorting (FACS). Here we present the latest fluorescent-based method to determine and isolate subsets of ILCs alive from mouse lamina propria.

2

Materials

2.1 General Supplies/Reagents

1. Phosphate-buffered saline (PBS). 2. Hank’s balanced salt solution (HBSS) without calcium and magnesium. 3. Curved-tip forceps (see Note 1). 4. Surgical scissor. 5. Syringe.

Isolation of ILCs

5

6. 15 and 50 mL polystyrene conical tubes. 7. 100 μm cell strainer. 8. Percoll. 9. Dissociation solution: HBSS, 5% heat-inactivated fetal bovine serum (FBS), 5 mM ethylenediaminetetraacetic acid (EDTA), 10 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer, 1 mM dithiothreitol (DTT). 10. Digestion solution: HBSS, 2% FBS, 10 mM HEPES buffer, 0.5 mg/mL collagenase D, 0.5 mg/mL DNase I, 1 mg/mL Dispase (see Note 2). 11. FACS buffer: PBS, 2% FBS or 1% bovine serum albumin (BSA), filter sterilized. 12. Sorting buffer: PBS, 1% BSA, 25 mM HEPES buffer, 1 mM EDTA. 13. Collection buffer: PBS, 50% FBS. 2.2

Mice

2.3 Antibodies (See Note 3)

1. C57BL/6 mice: Obtained from Jackson Laboratory and maintained in pathogen-free condition. Mice age between 6 and 12 weeks. 1. Lineage marker antibodies mix (CD3ε, Gr-1, TER-119, CD19)-Pacific Blue (1/200). 2. CD45-PE (1/200). 3. CD127-PE/Cyanine5 (1/200). 4. KLRG1-PE/Cyanine7 (1/200). 5. NK1.1-FITC (1/200).

3

Methods

3.1 Prepare SingleCell Suspension from Intestinal Lamina Propria

1. Euthanize mouse per facility instruction and cut open the abdominal cavity. Cut the connective mesentery and gently pull out the intestine. 2. For the preparation of the small intestine, cut between the pancreas and the cecum; for the preparation of the colon, cut between the cecum and anus. Put each dissected segment in a petri dish containing ice-cold HBSS. 3. Clean fecal content by inserting syringe tip into the intestine and flush with HBSS. 4. Carefully remove remaining connective tissue and Peyer’s patch on the small intestine and colonic patch on the large intestine by cutting out whitish nodes without impairing the intestine (see Note 4).

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5. Open intestine longitudinally, wash off the remaining fecal content, and then cut into small pieces of about 0.5 cm. 6. Transfer intestine pieces into a 50 mL tube containing 20 mL dissociation solution. 7. Incubate sample at 37  C for 20 min with slow rotation (see Note 5). 8. After incubation, vortex for 10–20 s. Remove supernatant by passing the sample through a 100 μm filter. The supernatant containing intraepithelial lymphocytes can be collected for other experiments. 9. Repeat steps 6–8. 10. Wash intestine segments with HBSS. 11. Transfer remaining intestine pieces into a 50 mL tube containing 10 mL pre-warmed digestion solution. 12. Incubate sample at 37  C for 40 min with slow rotation. Vortex for 10 s every 10 min. 13. After incubation, centrifuge briefly to collect all solution at the tube bottom, then add 20 mL ice-cold FACS buffer and resuspend. 14. Pass the cell suspension through a 100 μm cell strainer into a 50 mL tube. Lamina propria lymphocytes are collected in the tube. 15. Briefly wash the cell strainer with HBSS. 16. Centrifuge at 1000  g for 2 min at room temperature. 17. Aspirate supernatant thoroughly and resuspend the cell pellet with 10 mL 40% Percoll (see Note 6). 18. Slowly transfer 10 mL 80% Percoll to the bottom of the cell suspension in 40% Percoll. 19. Centrifuge at 400  g for 20 min at room temperature without brake. 20. Remove the top layer without disrupting lymphocytes between 40% and 80% Percoll. 21. Carefully collect the white layer of lymphocytes with a transfer pipette. 22. Wash cell pellet with 10 mL FACS buffer and centrifuge at 300  g for 5 min. 23. Aspirate supernatant. Resuspend cell pellet with FACS buffer and keep on ice. Cells are ready for staining procedure. 3.2 Surface Staining Procedure to Isolate Subsets of ILCs

1. Spin cells down at 300  g for 5 min. 2. Resuspend cell pellet in ice-cold FACS buffer containing 1:200 antibodies listed in Table 1.

Isolation of ILCs

7

Table 1 Expression of surface antigens on ILC cells Surface antigen

ILC subset expression

CD3ε, Gr-1, TER-119, CD19

Negative

CD45

All ILCs

CD127

ILC1, ILC2, ILC3, LTi

KLRG1

NK, ILC2

NK1.1

NK, ILC1

3. Incubate on ice for 30 min in dark condition. 4. Centrifuge at 300  g for 5 min at 4  C. 5. Decant supernatant and wash cell pellet with FACS buffer. 6. Centrifuge at 300  g for 5 min at 4  C. 7. Decant supernatant and resuspend the cell pellet with sorting buffer. Cells are ready for running in FACS machine with collection tubes containing collection buffer. 3.3 Flow Analysis to Identify ILC Subsets

1. Compensate fluorescent color with single-staining samples automatically by FACS software to correct overlapping fluorescent emission from different colors. 2. Identify lamina propria lymphocytes in the FSC-A and SSC-A window as cells with relatively smaller size and low granularity. 3. Identify ILCs as Lin and CD45+ populations in the identified lamina propria lymphocytes. 4. Identify NK cells as CD127 KLRG1+ NK1.1+; ILC1s as CD127+ KLRG1 NK1.1+; ILC2s as CD127+ KLRG1+ NK1.1 ; ILC3s as CD127+ KLRG1 NK1.1 (Fig. 1).

4

Notes 1. Compared to regular forceps, curved-tip forceps facilitate the handling of intestinal segments and removal of connective and lymphoid tissue. 2. In preparation of dissociation solution, DTT should be added freshly on the day of the experiment and keep at room temperature. In preparation of digestion solution, collagenase D, DNase I, and dispase should be added and kept at 37  C before the digestion step. 3. Fluorescent color and concentration of antibodies should be adjusted for different FACS machines. The antibodies are selected based on the cell type (Table 1).

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WT spleen 250K

5 10

5 10

4 10

4 10

ILC2

5 10

100K

3 10

3 10

0

50K

-10

0 0

50K

100K

150K

200K

3 10

0

3

-10 3 -10

250K

FSC-A

4 10

CD127

CD127

150K

Lin

SSC-A

200K

0

3 10

CD45

4 10

5 10

ILC3

0

NK

3 3 -10

0

3 10

KLRG1

4 10

-10

ILC1

45.5

53.4

3

5 10

3 -10

0

3 10

NK1.1

4 10

5 10

4 10

5 10

WT small intestine 250K

5 10

5 10

4 10

4 10

ILC2

22.6

22.2

5 10

3 10

-10

0 0

50K

100K

150K

FSC-A

200K

250K

3 10

3 10

0

50K

CD127

Lin

150K

100K

4 10

CD127

SSC-A

200K

0

0

3

-10 3 -10

0

3 10

CD45

4 10

5 10

3

NK

49.6 3 -10

5.57 0

3 10

KLRG1

4 10

5 10

ILC3

ILC1

72.8

-10

25.2

3 3 -10

0

3 10

NK1.1

Fig. 1 Gating strategy for wild-type mice splenic and intestinal innate lymphoid cell subsets. The gating strategy to sort each subset of innate lymphoid cells (ILCs) from spleen (top panel) and small intestine (bottom panel) from a wild-type (WT) mouse. ILCs are identified as lineage (Ln: CD3ε, Gr-1, TER-119, CD19) negative and CD45 positive lymphocytes. The four subsets of ILCs are further separated based on their expression of CD127, KLRG1, and NK1.1. Natural killer (NK) cell population is indicated in dark blue color as CD127 KLRG1+; ILC1 population is indicated in light blue color as CD127+ KLRG1 NK1.1+; ILC2 population is indicated in green color as CD127+ KLRG1+; ILC3 population is indicated in red color as CD127+ KLRG1 NK1.1

4. Intestine segment can be placed on a Kimwipe when performing connective tissue removal. Connective tissue tends to attach to Kimwipe, which aids the removal process. But do not let the intestine dry. The remaining fat and connective tissue will impede lamina propria digestion. 5. For incubation on rotation, laterally place the tubes to maximize the mechanical effect. 6. Steps 17–21 are optional. It is recommended to perform these steps for enrichment of leukocytes and better antibody staining efficiency. Enrichment of ILCs will be desirable if additional manipulation of ILCs is required before isolation of ILCs. However, performing Percoll gradient may decrease the amount of lymphocytes harvested and impair the viability of lamina propria lymphocytes, which are sensitive to environmental changes.

Isolation of ILCs

9

Acknowledgements We dedicate this work to our inspiring colleague Dr. Mathew Riese MD, Ph.D., who passed away young. This work was supported in part by NIH R01 AI102893; NCI R01 CA179363 (S.M.); HRHM Program of MACC Fund (S.M.), Nicholas Family Foundation (S.M.); Gardetto Family (S.M.); MCW-Cancer CenterLarge Seed Grant (S.M.); MACC Fund (S.M.); Ann’s Hope Melanoma Foundation (S.M.); and Advancing Healthier Wisconsin (S.M.). References 1. Abel AM et al (2018) Natural killer cells: development, maturation, and clinical utilization. Front Immunol 9:1869 2. Vivier E et al (2018) Innate lymphoid cells: 10 years on. Cell 174(5):1054–1066 3. Diefenbach A, Colonna M, Koyasu S (2014) Development, differentiation, and diversity of innate lymphoid cells. Immunity 41(3): 354–365 4. Bernink JH et al (2013) Human type 1 innate lymphoid cells accumulate in inflamed mucosal tissues. Nat Immunol 14(3):221–229 5. Fuchs A et al (2013) Intraepithelial type 1 innate lymphoid cells are a unique subset of IL-12- and IL-15-responsive IFN-gamma-producing cells. Immunity 38(4):769–781 6. Mjosberg JM et al (2011) Human IL-25- and IL-33-responsive type 2 innate lymphoid cells are defined by expression of CRTH2 and CD161. Nat Immunol 12(11):1055–1062 7. Moro K et al (2010) Innate production of T (H)2 cytokines by adipose tissue-associated c-Kit(+)Sca-1(+) lymphoid cells. Nature 463(7280):540–544

8. Neill DR et al (2010) Nuocytes represent a new innate effector leukocyte that mediates type2 immunity. Nature 464(7293):1367–1370 9. Cella M et al (2009) A human natural killer cell subset provides an innate source of IL-22 for mucosal immunity. Nature 457(7230): 722–725 10. Satoh-Takayama N et al (2008) Microbial flora drives interleukin 22 production in intestinal NKp46+ cells that provide innate mucosal immune defense. Immunity 29(6):958–970 11. Klose CS, Artis D (2016) Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis. Nat Immunol 17(7): 765–774 12. Hanash AM et al (2012) Interleukin-22 protects intestinal stem cells from immunemediated tissue damage and regulates sensitivity to graft versus host disease. Immunity 37(2):339–350 13. Huang J et al (2021) Interleukin-17D regulates group 3 innate lymphoid cell function through its receptor CD93. Immunity 54(4): 673–686 e4

Chapter 2 Purification of Primary Decidual Natural Killer Cells for Functional Analysis Aˆngela C. Crespo , Aria Alexander , and Tamara Tilburgs Abstract Decidual NK cells (dNK) are a unique type of NK cells found at the maternal–fetal interface during pregnancy. dNK play a key role in placental development, trophoblast invasion, and immunity to viral and bacterial infection of the placenta. dNK are the predominant leukocyte population in first trimester placental tissues and comprise around 70% of the total CD45+ leukocytes. dNK remain present throughout pregnancy but their proportion decreases to 20–40% of term placenta decidual tissue leukocytes. Investigation of dNK function throughout pregnancy is of high clinical relevance for understanding the development of placental inflammatory disorders as well as maternal-to-fetal transmission of pathogens. In this chapter, we describe in detail the methods we developed to purify dNK from first trimester and term pregnancy placental tissues. These methods are suitable to assess their protein and gene expression profiles as well as their function. Key words Human, Placenta, Decidua, Natural killer cells, KIR, KIR2DS1, CD107a, Degranulation, IFNγ, TNFα

1

Introduction Decidual natural killer cells (dNK) form a distinct NK cell population that has many differences in gene expression, cytokine secretion, and cell surface receptors compared to peripheral blood NK cells (pNK) [1, 2]. Initially, dNK were characterized as poorly cytotoxic lymphocytes and major cytokine and growth factor producers. Based on this and other studies, their key role was established as cells that facilitate implantation, trophoblast invasion, and other processes that are of key importance for placental development [1, 3]. More recently, the role of dNK in clearance of viral infections, a main function of pNK, was established [4–7]. dNK were shown to clear human cytomegalovirus (HCMV)-infected cells and this ability depended on the presence or absence of the activating NK

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_2, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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receptor killer-immunoglobulin-like receptor (KIR)-2DS1 [6]. More recently, we also established a role for dNK in controlling bacterial infections; here, decidual NK cells transfer the antimicrobial peptide granulysin into trophoblasts and selectively kill bacteria without killing the trophoblasts [8]. While much of the knowledge on dNK is based on dNK obtained from first trimester placental samples, dNK remain present in high proportions in decidual tissues throughout pregnancy and profound differences in gene expression, cytolytic activity, and response to HCMV were observed between first trimester and term pregnancy dNK [9]. Understanding dNK function throughout pregnancy is of high clinical relevance for studies aiming to prevent placental inflammatory disorders as well as maternal-to-fetal transmission of pathogens. In this chapter, we describe in detail the methods we developed to purify dNK from first trimester and term pregnancy placental tissues, which are suitable to assess their cytolytic capacity and cytokine secretion profiles in response to various infected and uninfected maternal and placental target cells.

2 2.1

Materials dNK Purification

2.1.1 Reagents

1. Sterile phosphate buffered saline (PBS). 2. RPMI 1640 medium. 3. Wash medium A: RPMI 1640, 10% fetal bovine serum (FBS), 1
Penicillin (Pen), 1
Streptomycin (Strep). 4. Wash medium B: RPMI 1640, 10% FBS, 1
Pen/Strep, 2% DNase I. 5. dNK culture medium A: X-VIVO 10 (Lonza), 5% human AB serum, 2.5 ng/mL Interleukin-15 (IL-15). 6. Percoll 100% solution: 9 parts Percoll + 1 part 10
PBS. 7. Percoll 70% solution: 7 parts Percoll 100% solution + 3 parts RPMI 1640. 8. Percoll 50% solution: 1 parts Percoll 100% solution + 1 parts RPMI 1640. 9. Percoll 45% solution: 4.5 parts Percoll 100% solution + 5.5 parts PBS. 10. Enzyme cocktail: RPMI 1640, 1 mg/collagenase IV, 0.1 mg/ mL DNase I (see Note 1). 11. Antibodies for cell sorting (see Table 1).

2.1.2 Tools and Disposables

1. Sterile tweezers. 2. Sterile 6 ½00 scissors.

Purification of Decidual NK Cells for Functional Analysis

13

Table 1 List of antibodies

a

Antigen

Conjugatea

Clone

Concentration

Use

CD45

Pacific Orange

HI30

1:200

Cell sorting and phenotyping

CD14

PE/Cy7

HCD14

1:100

Cell sorting

CD56

AF488

HCD56

1:50

Cell sorting and phenotyping

CD56

AF700

HCD56

1:50

Cell sorting and phenotyping

CD8

AF700

SK1

1:100

Cell sorting

CD4

PE

SK3

1:50

Cell sorting

CD107a

Percp/Cy5.5

H4A3

250 ng/mL

Degranulation assay

IgG1

Percp/Cy5.5

MOPC-21

250 ng/mL

Degranulation assay

KIR2DL1

APC

143,211

1:5

Phenotyping

KIR2DL1/S1

PE/Cy7

EB6

1:200

Phenotyping

IFNɣ

PE

B27

1:50

Cytokine assay

TNFα

Pacific Blue

MAb11

1:50

Cytokine assay

Perforin

Pacific Blue

dG9

1:50

Phenotyping

Granzyme B

PE-TxRED

GB11

1:50

Phenotyping

Granulysin 9 kDA

PE

DH2

1:50

Phenotyping

Granulysin

A488

RB1

1:50

Phenotyping

Other conjugates can be used to fit the flow cytometer configuration

3. Large metal 230–250 μm.

cell

dissociation

sieves

with

mesh

size

4. 100, 70, and 40 μm cell strainers. 5. Disposable sterile 5, 10, and 25 mL pipettes. 6. Disposable sterile 5 mL bulb transfer pipettes. 7. Disposable sterile 5 mL FACS tubes with cap. 8. Disposable sterile 15 and 50 mL conical tubes. 9. Disposable sterile 15 cm Petri dishes. 10. Absorbent pads. 11. Parafilm. 2.1.3 Equipment

1. Biosafety cabinet which can accommodate biosafety level (BSL)-2. 2. Bench top centrifuge with capacity for 15 and 50 mL conical tubes. 3. Shaking water bath.

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Aˆngela C. Crespo et al.

4. Fluorescence activated cell sorter (FACS) able to detect four or more fluorescent parameters. 2.2 Preparation of (Infected) Target Cells and dNK Stimulation

1. Target cells, for example, 721.221, K562, JEG3, decidual stromal cells (DSC), or extravillous trophoblasts (EVT). 2. General culture medium: RPMI 1640, 10% FBS, 1
Pen/Strep. 3. DSC culture medium: OPTI-MEM, 3% FBS, 50 μg/mL gentamycin. 4. EVT culture medium: DMEM/F12, 10% newborn calf serum (NCS), 1
Pen/Strep, 1
insulin, transferrin, selenium, 5 ng/ mL epidermal growth factor (EGF), 400 units human chorionic gonadotropin (hCG). 5. Listeria monocytogenes (Lm) culture medium: Sterile H2O, 37 g/L brain heart infusion powder medium, 50 μg/mL streptomycin. 6. Listeria monocytogenes (Lm) cultures (see Note 2). 7. Phorbol 12-myristate 13-acetate and Ionomycin (PMA/I). 8. 96 well U-bottom and flat bottom culture plates. 9. 48 well culture plates. 10. Fibronectin.

2.2.1 Equipment

1. 37  C 5% CO2 mammalian cell incubator. 2. 37  C shaking bacterial culture incubator. 3. Plate reader or Nanodrop.

2.3 dNK Functional Testing

1. dNK culture medium A: X-VIVO 10 (Lonza), 5% human AB serum, 2.5 ng/mL IL-15.

2.3.1 Reagents

2. dNK culture medium B: X-VIVO 10 without gentamycin (Lonza), 5% human AB serum, 2.5 ng/mL IL-15. 3. FACS buffer: PBS, 1% FBS. 4. Streptomycin. 5. Gentamycin. 6. Monensin. 7. Fixation buffer: PBS, 1% FBS, 4% paraformaldehyde. 8. Permeabilization buffer: PBS, 1% FBS, 0.1% Saponin. 9. Antibodies listed in Table 1.

2.3.2 Equipment

1. Multi-parameter flow cytometer able to detect six or more fluorescent parameters.

Purification of Decidual NK Cells for Functional Analysis

3 3.1

15

Methods dNK Purification

3.1.1 Tissue Dissection

1. Place the placenta or placental tissues in wash medium A directly after delivery and keep placenta at room temperature (see Notes 3–7). 2. For term placenta decidua basalis, carefully cut approximately 2
1 cm thin pieces from the maternal part of the placenta with scissors. Avoid necrotic or inflamed-looking tissue. Carefully remove villi from decidua basalis with scissors (Fig. 1a–e). Collect 20–50 mL of tissue in a 50 mL conical tube and add PBS to fill the tube (see Note 8). 3. For term placenta decidua parietalis, remove amnion and then remove decidua parietalis by gently scraping decidua from the chorion (Fig. 1f–h). Avoid necrotic or inflamed-looking tissue. Collect 20–50 mL of tissue in a 50 mL conical tube and add PBS to fill the tube (see Note 8). 4. For first trimester decidual tissue, macroscopically separate decidual tissue. Avoid necrotic or inflamed-looking tissue. Collect 10–30 mL of tissue in a 50 mL conical tube and add PBS to fill the tube. 5. Process decidua basalis and decidua parietalis tissues separately.

3.1.2 Tissue Digestion

1. Wash tissues without centrifugation by adding sterile PBS, waiting until the tissue settles in the lower half of the tube (for approximately 2 min) and discarding the supernatant by pouring or with serological pipettes (see Note 9). Fill up the tubes with PBS again. Wash all tissues until fluid is clear and no blood is visible. If more than 20 mL tissue was collected in Subheading 3.1.1, use 2 or more 50 mL tubes for washing (see Note 10). 2. Cut decidua with scissors inside the 50 mL tube into very small pieces of approximately 1–2 mm2. 3. Wash tissue thoroughly with PBS until fluid is clear as described in (Subheading 3.1.2, step 1). 4. After the last wash step, let tissue settle for approximately 2 min in the bottom of 50 mL tube until no debris are visible in the PBS supernatant and measure tissue volume (see Note 8). 5. Carefully discard supernatant. Divide tissue into 10–20 mL tissue per conical tube (see Note 10), fill tubes with serumfree RPMI 1640 and spin tissue for 1 min at 200
g. 6. Carefully discard supernatant (see Note 9). Add enzyme cocktail and serum-free RPMI to obtain a concentration of 0.5 mg/ mL collagenase IV and 0.05 mg/mL DNase for term placenta decidual tissues or 0.25 mg/mL collagenase IV and 0.025 mg/

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Fig. 1 Placental tissue dissection. (a) Approximately 2
1 cm thin pieces of decidua basalis are carefully cut from the maternal part of the placenta with scissors. (b) Each piece of decidua basalis tissue is placed with villi facing upwards to (c) carefully remove villi from decidua basalis with scissors, until (d, e) decidua basalis looks like a clean membrane devoid of villi. (f) First, the amnion is manually separated from the choriodecidual membrane. (g) A piece of chorio-decidual membrane is placed with decidua facing upwards to (h) carefully

Purification of Decidual NK Cells for Functional Analysis

17

mL DNase for first trimester decidual tissues. Resuspend decidual tissues to a volume that is double the volume of tissue measured in Subheading 3.1.2, step 4 (see Note 11). 7. Wrap tube caps with parafilm and place tubes horizontally in shaking water bath at 50 RPM and 37  C for 75–90 min. 3.1.3 Cell Filtration and Separation

1. Remove tubes from water bath, remove parafilm, and fill up tube with wash medium B. 2. Let undigested tissue settle in the bottom of the tube for approximately 2 min and pour supernatant into a metal dissociation sieve placed in a 15 cm petri dish. Gently stir with back of transfer pipet to strain supernatant into the Petri dish (see Note 12). 3. Fill up tube with wash medium B to resuspend the remaining tissue and repeat Subheading 3.1.3, step 2 once. 4. Transfer remaining tissue into dissociation sieves, add 10–30 mL wash medium B and gently stir with back of a bulb transfer pipet until all fluid is strained. Discard remaining tissue fragments (see Note 12). 5. Filter all supernatants through 100, 70, and 40 μm cell strainers into 50 mL conical tubes. 6. Spin cells down at 650
g for 8 min, discard supernatant, and carefully resuspend cell pellets in remaining medium by flicking the tubes. 7. Resuspend cell pellets in RPMI 1640 without supplements in a volume equal to the tissue volume measured in Subheading 3.1.2, step 4. Add the same volume of Percoll 50% solution to the cell suspension to achieve a final 25% Percoll concentration. 8. Load Percoll gradients using 10 mL Percoll 70%, 15 mL Percoll 45%, 20 mL Percoll 25% containing cells and 5 mL PBS as described in Fig. 2 (see Note 13). 9. Carefully place gradients in centrifuge and spin 30 min at 800
g without brake. 10. Remove debris and macrophage layers first with serological pipettes. Then carefully harvest lymphocyte rings with bulb pipettes and transfer all cells to 50 mL conical tubes. Transfer a max of 20 mL of cells into one 50 mL conical tube and fill up tubes with wash medium A (see Note 14).

ä Fig. 1 (continued) remove decidua parietalis from the chorion with tweezers. (i) Approximately 2
4 cm pieces of placental membranes are cut and placed on a petri dish with decidual tissue facing upwards. (j) Placental membrane pieces are rolled around a syringe needle and (k) tied with suture tread before placing the rolls in fixative

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Fig. 2 Percoll gradient. (a) The Percoll gradient is loaded by making layers of 10 mL 70% Percoll (1.082 g/mL), 15 mL 45% Percoll (1.053 g/mL), 20 mL 25% Percoll (1.029 g/mL) with the isolated cell fractions in suspension, and 5 mL PBS. (b) After density gradient centrifugation, the lymphocyte enriched fraction is collected from the 1.082/1.053 g/mL interface and macrophage enriched fractions from the 1.053/1.029 g/mL interface. The pellet and the proteins, fats, and debris are discarded

11. Centrifuge cells at 650
g for 8 min, discard supernatant, and carefully resuspend cell pellets in 0.5–1 mL wash medium A. 12. Add anti-CD45, CD14, CD56, CD8, and CD4 antibodies at the concentrations listed (Table 1) for 30 min on ice and in the dark. 13. Add 10 mL wash medium A and centrifuge cells at 650
g for 8 min. Discard supernatant and carefully resuspend cell pellets in 0.5–1 mL wash medium A. 14. Filter cells through a 40 μm cell strainer and transfer to a 5 mL sterile FACS tube with cap. 15. Sort CD45+CD14CD56+ single dNK cells according to the gating strategy depicted in Fig. 3. First select live cells in the FSC-A/SSC-A plot (Fig. 3a) and exclude doublets (Fig. 3b, c). Next, select CD45+CD14 lymphocytes (Fig. 3d) and subsequently CD45+CD14CD56+ dNK (sort population I) (Fig. 3e) (see Notes 15 and 16). 16. Centrifuge cells at 650
g for 8 min, discard supernatant, and resuspend CD45+CD14CD56+ dNK in dNK cell culture medium A for functional testing or for overnight culture at 37  C and 5% CO2 if the experiment is not done immediately after isolation (see Note 17).

Purification of Decidual NK Cells for Functional Analysis

19

Fig. 3 Gating strategy for cell sorting. Gating strategy of a representative term placenta decidua basalis sample is shown. (a) First, live cells are selected by gate R1 in the FSC-A/SSC-A plot. Second, doublets are excluded by (b) gate R2 in the FSC-A/FSC-H plot and (c) R3 in the SSC-A/SSC-H plot. (d) Next, CD45 and CD14 are plotted to select CD45+CD14 lymphocytes (R4). (e) Lymphocytes (R4) are plotted for CD45 and CD56 to select CD45+CD56+ dNK (sort population I) and CD45+CD56 lymphocytes (R5). (f) CD45+CD56 lymphocytes (R5) are plotted for CD8 and CD4 to select CD45+CD56CD4CD8+ and CD45+CD56CD8CD4+ T cells (sort populations II and III). Here, CD3 and TCR staining are not used during live cell sorting to avoid T cell activation

3.2 Preparation of (Infected) Target Cells and dNK Stimulation Solutions (See Note 18)

1. Unstimulated controls: Add 100 μL (96 well U-bottom) or 200 μL (48 well) dNK culture medium A per well.

3.2.1 Preparation of Unstimulated Controls 3.2.2 Preparation of PMA/I Stimulation

1. PMA/I stimulation: Add 100 μL (96 well U-bottom) or 200 μL (48 well) dNK culture medium A, supplemented with 2 μg/mL PMA and 2 μg/mL Ionomycin per well (see Note 19).

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Aˆngela C. Crespo et al.

3.2.3 Preparation of Target Cell Lines

1. Add 2.25
105 target cell line (e.g., 721.221 or K562 cells) resuspended in 100 μL (96 well) or 4.5
105 cells resuspended in 200 μL (48 well) dNK culture medium A per well.

3.2.4 Preparation of Human Cytomegalovirus (HCMV) Infected Decidual Stromal Cells (DSC) (See Note 20)

1. 72 h before dNK purification, seed 2–5
105 DSC in 48 well plates in DSC culture medium. The cells will adhere overnight and stay adherent throughout infection and dNK co-culture (see Note 21). 2. 48 h before dNK purification, infect DSC with HCMV at a multiplicity of infection (MOI) 0.5–1. 3. Thaw the HCMV viral stock and dilute it in serum-free DSC culture medium to obtain an MOI of 0.5–1 in 100 μL (this will be the viral inoculum). 4. Aspirate medium from DSC and add the viral inoculum. To the uninfected wells, add 100 μL of serum-free DSC culture medium. 5. Incubate cells with inoculum for 1 h for viral adsorption at 37  C and 5% CO2 and gently shake the culture plate every 15 min. 6. Aspirate the inoculum and add fresh complete DSC culture medium. 7. Aspirate the DSC culture medium of both the uninfected and infected DSC cultures. Culture for 48 h at 37  C and 5% CO2. Add 200 μL dNK culture medium A just before adding dNK for functional testing (Subheading 3.3).

3.2.5 Preparation of HCMV-Infected JEG3 Cells (See Note 20)

1. 72 h before dNK purification, seed 2–5
105 JEG3 cells in 48 well plates in general culture medium. The JEG3 cells will adhere overnight and stay adherent throughout infection and dNK co-culture (see Note 21). 2. 48 h before dNK purification, infect JEG3 cells by spinoculation with MOI 3–4 in 100 μL of viral inoculum (use serum-free JEG3 culture medium to dilute virus stock if necessary). 3. Aspirate general culture medium from JEG3 cells. Add the viral inoculum (or serum-free culture medium for uninfected cells) to the cells and cover the plate with a lid and wrap in parafilm. Centrifuge the plate at 2100
g for 1 h at 37  C. 4. Remove the parafilm and incubate plates for 12 h at 37  C and 5% CO2 (do not remove the inoculum or add medium). 5. Repeat steps 3–4 twice for the second and third round of spinoculation. 6. Remove the viral inoculum, add 200 μL general culture medium, and incubate at 37  C and 5% CO2 for another 12 h. Replace culture medium with dNK culture medium A just before adding dNK for functional testing (Subheading 3.3).

Purification of Decidual NK Cells for Functional Analysis 3.2.6 HCMV Infection of Primary EVT (See Note 20)

21

1. Coat 48-well plate with fibronectin by adding 100 μL 20 ng/ mL fibronectin in PBS to the plate and incubating for 45 min at room temperature. After incubation remove and discard fibronectin solution and add 200 μL EVT culture medium. Keep at 37  C and 5% CO2 until EVT are ready to plate. 2. Add 5
104 freshly isolated EVT to the fibronectin-coated 48-well plate, incubate 2 h at 37  C and 5% CO2. Wash away non-adherent cells with EVT medium (see Note 22). 3. Infect EVT with HCMV at an MOI 0.5–4 with one round of spinoculation as described in Subheading 3.2.5 (see Note 23). 4. Remove the viral inoculum, add 200 μL EVT culture medium, and incubate for another 12 h at 37  C and 5% CO2. Replace culture medium with 200 μL EVT medium supplemented with 2.5 ng/mL IL-15 just before adding dNK for functional testing (Subheading 3.3) (see Notes 24 and 25).

3.2.7 Listeria monocytogenes Infection (See Note 26)

1. 24 h before dNK purification, seed target cells (e. g. JEG3, EVT, DSC, or others) in 48 well plates in antibiotic-free cell culture medium. Target cells will adhere overnight and stay adherent throughout infection and dNK co-culture. Calculate the number of cells to be plated to obtain a confluent well the next day (see Note 21). For EVT, plate 5
104 cells on fibronectin-coated wells (as described in Subheading 3.2.6). Also prepare the Listeria monocytogenes (Lm) culture to grow overnight (see Note 2). 2. Wash all cell cultures with antibiotic-free cell culture medium at least twice before infection by aspirating culture medium, adding the wash medium, incubating for 5 min at room temperature and aspirating it. 3. Infect cells with an MOI between 5 and 20 in 200 μL antibiotic-free target cell culture medium for 30 min at 37  C and 5% CO2 in an incubator [8] (see Note 27). 4. Remove excess bacteria by washing all wells twice with 200 μL antibiotic-free target cell culture medium. After the second wash add 200 μL target cell culture medium without pen/strep and with 50 μg/mL gentamycin. Incubate cells for 15 min at 37  C and 5% CO2. 5. Wash the cells twice more with antibiotic-free target cell culture medium and add 200 μL of dNK culture medium B (except for EVT cultures: add 200 μL EVT medium without pen/strep and supplemented with 2.5 ng/mL IL-15) (see Notes 24 and 28).

3.3 dNK Functional Testing

1. Once all stimulations (Subheading 3.2) are ready, dNK can be prepared. dNK can be used immediately after isolation, or after overnight culture. Resuspend dNK at 7.5
105 dNK/mL in culture medium A. If bacterial infection will be used as

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Aˆngela C. Crespo et al.

stimulation, wash dNK twice by resuspending dNK in culture medium B and spinning at 650
g for 8 min. After the final wash resuspend dNK in culture medium B. 2. Add 7.5
104 dNK in 100 μL or 1.5
105 dNK in 200 μL to each well of the 96 or 48 well plates, respectively, with the target cells or stimulations. 3. To each culture, add anti-CD107a PerCP/Cy5.5 or IgG2a PerCP/Cy5.5 control antibodies at a final concentration of 250 ng/mL as described [6, 10] (see Note 29). 4. To each culture, add 1
monensin according to manufacturer’s instructions (see Note 30). 5. Spin the plates at 700
g for 1 min to bring the dNK closer to the target cells. 6. Incubate dNK for 4–16 h at 37  C and 5% CO2. 7. Collect and transfer NK cells to 5 mL FACS tubes and rinse wells with FACS buffer to collect all NK cells. 8. Centrifuge cells at 650
g for 8 min, discard supernatant by pouring and then carefully resuspend cell pellets in the remaining FACS buffer. 9. Place tubes on ice and add 1 mL 4% PFA/PBS solution or equivalent commercial fixation buffer for 30 min. 10. Add 2 mL FACS buffer, centrifuge cells at 650
g for 8 min, discard supernatant by pouring, and then carefully resuspend cell pellets in remaining FACS buffer (approximately 100 μL). 11. Add cell surface antibodies using concentrations listed in Table 1, incubate 30 min on ice in the dark (see Note 31). 12. Add 2 mL FACS buffer per tube, centrifuge cells at 650
g for 8 min, discard supernatant by pouring, and then carefully resuspend cell pellets in remaining FACS buffer (approximately 100 μL). 13. Add 2 mL permeabilization buffer, directly centrifuge cells at 650
g for 8 min, discard supernatant by pouring, and then carefully resuspend cell pellets in remaining permeabilization buffer (approximately 100 μL). 14. Add intracellular antibodies (e.g., anti-IFNγ and anti-TNFα) and incubate cells 20 min on ice in the dark. 15. Add 2 mL permeabilization buffer, centrifuge cells at 650
g for 8 min, discard supernatant by pouring, and then carefully resuspend cell pellets in remaining permeabilization buffer (approximately 100 μL). 16. Add 2 mL FACS buffer per tube, centrifuge cells at 650
g for 8 min, discard supernatant by pouring, and then carefully resuspend cell pellets in remaining FACS buffer (approximately 100 μL).

Purification of Decidual NK Cells for Functional Analysis

23

Fig. 4 Functional analysis of dNK. (a) Representative dot plots of (a) CD107a, (b) IFNγ, and (c) TNFα expression on unstimulated (left panels) and PMA/I stimulated (right panels) CD56+ dNK cells. (d) Dot plots of CD107a and IFNγ and (e) IFNγ and TNFα expression in dNK identify polyfunctional dNK upon PMA/I stimulation. (f) Representative dot plots of CD107a expression on CD56+ dNK cells stimulated with 721.221 cells, DSC and HCMV-infected DSC compared to unstimulated controls

17. Add 200–300 μL FACS buffer per tube and acquire cells on flow cytometer (see Note 32). 18. Analyze dNK for CD107a dependent degranulation and cytokine expression according to the gating strategy depicted in Fig. 4. First, select CD45+CD14CD56+ single dNK cells as described in Subheading 3.1.3, step 15 and Fig. 3a–e. Next, display CD56 in a dot plot with CD107a, IFNγ, or TNFα. The unstimulated control is used to determine the threshold (gate)

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to determine the percentages of CD107a, IFNγ, and TNFα-positive dNK after PMA/I stimulation (Fig. 4a). The percentage of polyfunctional dNK can be identified by displaying CD45+CD14CD56+ single dNK cells in dot plots for expression of CD107a and IFNγ or IFNγ and TNFα (Fig. 4b). Similarly, CD45+CD14CD56+ dNK cells can be assessed for their CD107a degranulation response and cytokine production (not shown) in response to target cells (Fig. 4c), including 721.221, K562, DSC, JEG3, EVT, or HCMV or Listeria-infected DSC (DSC-HCMV/Lm) or JEG3, or EVT (see Note 33). 19. To determine how CD107a degranulation relates to the expression of NK cell receptors, for example, KIR2DS1 and KIR2DL1. First select CD45+CD14CD56+ NK cells as described in Subheading 3.1.3, step 15 and Fig. 3a–e and display NK cells in a dot plot for KIR2DS1 and KIR2DL1 expression (Fig. 5a). Four dNK populations are selected (L1S1; L1+S1; L1S1+; L1+S1+) and subsequently depicted for CD107a expression (Fig. 5b). CD107a expression is compared to an IgG control or unstimulated cells to determine the percentages of CD107a (Fig. 5c) (see Notes 33 and 34).

Fig. 5 Analysis of the specific function of dNK subtypes defined by expression of NK receptors. (a) Representative dot plot depicting the separation of the four dNK subtypes expressing different combinations of the inhibitory KIR2DL1 and activating KIR2DS1 receptors [6, 10]. (b) Separate analysis of KIR2DL1 and KIR2DS1 expressing dNK subtypes shows that KIR2DS1+ single positive (L1S1+) dNK have higher levels of CD107a dependent degranulation in response to HLA-C2-expressing 721.221 target cells. (c) IgG controls are used to detect non-specific background staining

Purification of Decidual NK Cells for Functional Analysis

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Notes 1. Freeze 10 mL aliquots of RPMI 1640 with 1 mg/mL collagenase IV and 0.1 mg/mL DNase I at 20  C until use. 2. For Listeria monocytogenes cultures, pick a colony from a Petri dish with a micropipette tip and dip into 3 mL of culture medium to grow overnight at 37  C, shaking at 200 RPM (leave the tip inside the tube containing the culture medium). Make sure to pick the colony using BSL2+ practices as described in see Notes 20 and 26. Measure the bacteria concentration by OD600 before infection in a plate reader or Nanodrop. 3. Working with human blood, cells, and tissues and infectious agents requires institutionally approved institutional review board (IRB) and biosafety protocols. Inquire at your IRB and committee for biosafety how to obtain required approvals and do not start work before approvals have been obtained. 4. Work with human cells and tissues should be done within BSL2 biosafety cabinets using BSL2 or BSL2+ practices. BSL2/2+ practices include but are not limited to wearing appropriate personal protective equipment including double gloves and disposable gowns, safe disposal of contaminated fluids in 10% bleach for 20 min and disposal of contaminated plastics in biohazard bag and/or containers that are closed inside the biosafety cabinet before removal. 5. Start processing the placental materials within 5 h after delivery or termination for maximum cell yield and cell viability. 6. Optional: Store tissue for DNA isolation and HLA and/or KIR typing. For first trimester store approximately 0.5 cm3 large pieces of decidual (maternal) and villous (fetal) tissue. For term pregnancy placenta, harvest 0.5–1 mL fetal cord blood, and collect ~1 mL maternal peripheral blood. If maternal peripheral blood is not available, 1
0.5 cm pieces of decidual parietalis tissue can be used. Store all tissues in 1.7 mL Eppendorf tubes at 80  C until DNA isolation. 7. Optional: Store tissues for immunohistopathology analysis and determination of placental inflammatory state. For first trimester collect two or more 0.5 cm3 pieces of decidual (maternal) and villous (fetal) tissue. For term pregnancy decidua basalis collect two or more 0.5 cm3 pieces. For term pregnancy decidua parietalis collect two or more 2
4 cm pieces, rolled around a syringe needle (Fig. 1f–h). Store tissues at 4  C in fixative.

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8. To measure tissue volume, let the tissue settle in the lower half of the tube for approximately 2 min and measure the volume the tissue occupies. 9. Carefully discard supernatant by using a pipette or by carefully pouring it out into a beaker containing a disinfectant (e.g., 10% bleach). 10. Tissue can be divided over multiple 50 mL tubes by filling up the tissue containing conical tube with PBS, gently shaking the tube to resuspend the tissue in PBS and then carefully pouring fractions of the tissue/PBS into (an) additional tube(s). 11. Enzyme concentration should be decreased if loss of CD56 or other lymphocytes markers is observed by the end of the isolation protocol (while sorting in the FACS instrument). Enzyme concentration can be increased if tissue digestion is incomplete and cell yields are low. Well digested tissues generate a viscous solution with few visible pieces of tissue left. 12. The purpose here is to stir tissue and facilitate straining of liquid. Do not attempt to grind remaining tissue through the filter as this will result in impurities. 13. Tip: Practice to make Percoll gradients with perfectly separated layers; fuzzy layers result in diminished cell yields. Use 10 mL serological pipettes or bulb transfer pipettes to carefully layer the different concentrations of Percoll on top of one another without mixing. Touching the tip of the pipette to the wall of the tube helps to control the loading. Loading Percoll gradients using 4  C Percoll solutions generates better results. 14. With the transfer of cells, some Percoll from the gradient is transferred to the 50 mL conical tube. Not sufficiently diluting this Percoll with wash medium will result in excessive cell loss, as cells will not deposit properly. After centrifuging the cells, take care to notice if there are cells attached to the walls of the tube and make sure to collect them in the bottom of the tube while resuspending. 15. Optional: Peripheral blood NK cells (pNK) can be purified and analyzed simultaneously. Purification of CD56+ pNK can be done using RosetteSep™ Human NK Cell Enrichment Cocktail and Ficoll gradient centrifugation or by Ficoll gradient centrifugation and FACS sort following the gating strategy depicted in Fig. 3. 16. Optional: In addition to CD45+CD14CD56+ dNK, other cell types including CD8+ and CD4+ T cells can be obtained from the same placental tissues and used for functional testing [11, 12]. Here CD45+CD14CD56 lymphocytes can be plotted to sort CD45+CD56CD8+CD4 and CD45+CD56CD8CD4+ T cells (Fig. 3f, sort populations II and

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III) from the same placental sample. Here CD3 and TCR staining are not used during live cell sorting to avoid T cell activation. 17. We recommend functional testing directly after isolation or at least within 12 h to ensure dNK viability or a maximum of 24 h if HCMV-infected EVT from the same placental preparation as dNK will be used as a stimulation (as 24 h are needed to obtain a productive infection of EVT). 18. Some of the stimulations used to test dNK activity, such as viral and bacterial infections, require preparation of (infected) target cells in advance. 19. 2 μg/mL PMA and 2 μg/mL Ionomycin per well is a 2
concentration making a final concentration of 1 μg/mL PMA and 1 μg/mL Ionomycin after addition of the NK cells. 20. Working using pathogens including HCMV and listeria monocytogenes requires institutionally approved biosafety protocols. These include working in BSL2 biosafety cabinets using BSL2 or BSL2+ practices. These BSL2/2+ practices include wearing appropriate personal protective equipment including disposable gowns and double gloves, safe disposal of contaminated fluids in 10% bleach for 20 min, and disposal of contaminated plastics in biohazard bag and/or containers that are closed inside the biosafety cabinet before removal. 21. Calculate the number of cells to be plated in order to obtain a confluent culture well the day of the experiment. Numbers can vary based on variable cell growth curves. 22. Optional: Isolation and purification of HLA-G positive EVT for cell culture is further described in [13, 14]. 23. A second round of spinoculation as described in Subheading 3.2.5 can be used to infect EVT and obtain higher infection levels. After the second round of spinoculation, remove viral inoculum from the cells after 10 h of incubation at 37  C and replenish with fresh EVT medium for the last 2 h 24. EVT cannot be grown in pure dNK medium. For optimal viability of dNK and EVT, dNK and EVT medium can be mixed 1:1 with a final concentration of 2.5 ng/mL IL-15. Hence the addition of 2.5 ng/mL IL-15 to the EVT medium here [6, 14]. 25. If EVT and dNK from the same placenta are used for functional testing, keep dNK in dNK medium A at 37  C and 5% CO2 until EVT are ready [6]. 26. Working with Listeria monocytogenes (Lm) requires BSL-2+ practices, including wearing disposable gowns and double gloves. All plastic material in contact with Lm should be decontaminated in 1% Vesphene overnight, and any infected liquid

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should be aspirated into a bottle with 1% Vesphene. All biohazard waste should be autoclaved before being removed from the BSL-2+ lab. 27. Titrate Lm infection for each target cell type to determine optimal MOI for each cell type [8]. 28. If EVT and dNK from the same placental are used for functional testing, keep dNK in dNK medium B at 37  C and 5% CO2 until EVT are ready. 29. CD107a transiently appears on the cell surface during degranulation and is used as measure of cellular cytotoxicity. By stimulating NK cells in the presence of fluorescently labeled CD107a antibodies, degranulating cells are identified [10]. 30. Monensin is used to prevent secretion and to retain cytokines in the cytoplasm of cells, allowing detection of intracellular cytokine storage upon stimulation. Monensin also prevents degradation of internalized CD107a antibody-associated fluorochromes. 31. For KIR2DL1/S1 staining, first add KIR2DL1 antibody for 20 min, then add KIR2DS1 antibody and the remaining cell surface antibodies for an additional 30 min [6, 10]. 32. Acquire the cells on the flow cytometer the same day or within 24 h for best results. 33. Optional assays: This method can also be used to determine the transfer of cytolytic molecules (e.g., granulysin, granzyme B, and perforin) from dNK to target cells, CFU assays to detect bacterial killing as a result of the co-culture with NK cells or plaque assays to detect viral load and to detect viral killing as a result of the co-culture with NK cells as described previously [8, 15]. 34. Optional: Other NK cell receptors and or NK cell markers can be used to determine how their expression relates to the capacity to degranulate or produce cytokines [6]. References 1. King A, Wellings V, Gardner L et al (1989) Immunocytochemical characterization of the unusual large granular lymphocytes in human endometrium throughout the menstrual cycle. Hum Immunol 24:195–205 2. Koopman LA, Kopcow HD, Rybalov B et al (2003) Human decidual natural killer cells are a unique NK cell subset with immunomodulatory potential. J Exp Med 198:1201–1212 3. Hanna J, Goldman-Wohl D, Hamani Y et al (2006) Decidual NK cells regulate key

developmental processes at the human fetalmaternal interface. Nat Med 12:1065–1074 4. Siewiera J, El Costa H, Tabiasco J et al (2013) Human cytomegalovirus infection elicits new decidual natural killer cell effector functions. PLoS Pathog 9:e1003257 5. Tilburgs T, Evans JH, Crespo AC et al (2015) The HLA-G cycle provides for both NK tolerance and immunity at the maternal-fetal interface. Proc Natl Acad Sci U S A 112:13312– 13317

Purification of Decidual NK Cells for Functional Analysis 6. Crespo AC, Strominger JL, Tilburgs T (2016) Expression of KIR2DS1 by decidual natural killer cells increases their ability to control placental HCMV infection. Proc Natl Acad Sci U S A 113:15072–15077 7. Crespo AC, van der Zwan A, Ramalho-Santos J et al (2017) Cytotoxic potential of decidual NK cells and CD8+ T cells awakened by infections. J Reprod Immunol 119:85–90 8. Crespo AC, Mulik S, Dotiwala F et al (2020) Decidual NK cells transfer granulysin to selectively kill bacteria in trophoblasts. Cell 182: 1125–1139 9. de Mendonca VR, Meagher A, Crespo AC et al (2020) Human term pregnancy decidual NK cells generate distinct cytotoxic responses. J Immunol 204:3149–3159 10. Fauriat C, Ivarsson MA, Ljunggren HG et al (2010) Education of human natural killer cells by activating killer cell immunoglobulin-like receptors. Blood 115:1166–1174 11. van der Zwan A, Bi K, Norwitz ER et al (2018) Mixed signature of activation and dysfunction

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allows human decidual CD8(+) T cells to provide both tolerance and immunity. Proc Natl Acad Sci U S A 115:385–390 12. Salvany-Celades M, van der Zwan A, Benner M et al (2019) Three types of functional regulatory T cells control T cell responses at the human maternal-fetal interface. Cell Rep 27: 2537–2547 13. Papuchova H, Kshirsagar S, Xu L, Bougleux Gomes HA et al (2020) Three types of HLA-G+ extravillous trophoblasts that have distinct immune regulatory properties. Proc Natl Acad Sci U S A 117:15772–15777 14. Tilburgs T, Crespo AC, van der Zwan A et al (2015) Human HLA-G+ extravillous trophoblasts: immune-activating cells that interact with decidual leukocytes. Proc Natl Acad Sci U S A 112:7219–7224 15. Sen P, Wilkie AR, Ji F et al (2020) Linking indirect effects of cytomegalovirus in transplantation to modulation of monocyte innate immune function. Sci Adv 6:eaax9856

Chapter 3 In Vitro Development of Mouse and Human NK Cells from Hematopoietic Progenitor Cells Ines Ullmo, Nahide Koksal, Heather Y. K. Ang, and Hugh J. M. Brady Abstract Natural killer (NK) cells are lymphocytes that play an important role at clearing virally infected or cancer cells. Their potential and role in cancer immunotherapy have generated great interest, given the promising results of NK cell adoptive transfer clinical trials. The remaining challenge to bring emerging NK cell immunotherapies to the clinic is to enhance the production of large numbers of functionally competent NK cells ex vivo. Here, we describe two in vitro NK cell development assays using hematopoietic progenitor cells (HPCs), one for human NK cells and one for mouse NK cells. These protocols describe two robust methods that can be utilized for investigation of NK cell development and function. Key words Natural killer cell, NK cell differentiation, Hematopoietic progenitor cell, In vitro, Umbilical cord blood

1

Introduction Natural killer (NK) cells are innate lymphocytes that are crucial for anti-viral and anti-tumor immune responses, without the need for prior antigen sensitization. Both mouse and human NK cells express a vast array of activating and inhibiting receptors on the cell surface that modulate effector responses while maintaining tolerance to healthy cells. NK cells exhibit cytotoxic responses against target cells directly, by release of perforin and granzyme to lyse the target cell membrane or through apoptotic surface receptors such as TRAIL or FasL. Additionally, degranulation and release of cytotoxic proteins is triggered by antibody interaction with CD16 receptors, termed antibody dependent cellular cytotoxicity (ADCC). NK cells can also generate large quantities of cytokines such as IFNγ and TNFα, which help medium the adaptive immune response [1]. While there are similarities in the

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_3, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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overall differentiation pathway in mouse and human, time and cytokine requirements are the main differences that impose a need for the development of unique differentiation protocols. In humans, NK cells develop from hematopoietic stem cells (HSCs) residing within the bone marrow. Transition of HSC toward common lymphoid progenitors (CLPs), followed by NK cell progenitors (NKPs) is marked by an upregulation in CD122 expression and a requirement for IL-15 signaling [2]. The presence of IL-15 at the NKP stage is crucial for differentiation into immature NK cells (iNK), after which these cells can migrate to peripheral secondary lymphoid organs to mature [3]. When IL-15 is maintained, iNK cells mature into CD56brightCD16 NK cells, known for their ability to release cytokines upon activation, and CD56dimCD16+ NK cells, which exhibit strong cytotoxic responses via their CD16 receptor initiating ADCC [4]. There are multiple sources of progenitor cells available to differentiate NK cells in vitro. Traditional sources of CD34+ hematopoietic progenitor cells (HPCs) include the bone marrow, peripheral blood, or umbilical cord blood (UCB). Alternatively, NK cells can be differentiated from human embryonic stem cells (hESC) or induced pluripotent stem cells (iPSCs) [5]. Here, we describe NK cell differentiation using CD34+ HPCs from UCB. These cells are relatively easy to obtain in large numbers and can be cryopreserved for use as required. In addition, UCB-derived HPCs exhibit high proliferative potential when compared to peripheral or bone marrow progenitors [6, 7], allowing for generation of large quantities of human NK cells for downstream applications. NK cell differentiation from CD34+ HPCs can be achieved either in the absence or presence of feeder cells. Options for feeder cells include murine OP9 [8], MS-5 bone marrow stroma [9], EL08-1D2 embryonic liver stroma [10], or ATF024 fetal liver fibroblasts [11]. Feeder co-cultures can generate NK cells by 10–14 days of culture and require lower starting populations of CD34+ HPCs, with EL08-1D2 feeder cells exhibiting a 2852-fold NK cell production by 14 days of culture [10]. Feeder-free approaches can generate approximately 109 GMP grade NK cells at the end of a 5-week culture starting from 1  104 to 1  106 CD34+ HPCs. These methods commonly include the use of cytokines (IL-2, IL-7, IL-15, Flt3L, and SCF), as well as additional compounds (Heparin, Hydrocortisone, and StemRegenin1) to enhance NK cell maturation toward cytotoxic effector cells [12– 14]. The advantage of feeder co-cultures lies in the shorter duration of growth required, lower seeding numbers, and medium components, making it the favored approach for experimental use. For this reason, we describe how we generate NK cells using EL08-1D2 feeder cells, as this approach permits generation clonal populations of genetically modified NK cells from low starting populations.

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Murine NK cells derive from HSCs residing in the bone marrow, where they differentiate into CLP and CD122+ NKPs. In the presence of IL-15, NKPs differentiate into iNK cells and eventually CD3 NK1.1+ NKp46+ mature NK cells [15]. While murine NK cells are commonly identified by expression of NK1.1 or NKp46, this group can be further characterized as cytokine producing CD27+CD11b+ NK cells and cytotoxic CD27 CD11b+ NK cells [16]. In vitro differentiation of murine NK cells is a more rapid procedure than for human, production of mature murine NK cells from bone marrow HPCs can be achieved after a week of culture on OP9 bone marrow feeder cells with IL-15 [17, 18]. While generation of NK cells is possible without a feeder layer [19], there is still a requirement for OP9 conditioning supernatant. Here, we will also describe how we generated murine NK cells from lineage negative (Lin ) cells isolated from mouse bone marrow, using a OP9-GFP stroma cell line. In vitro differentiation of NK cells has been well established, with the existence of several different methods to achieve functional NK cell production. Here, we describe robust methods for generating human and mouse NK cells through the use of a feeder layer co-culture, resulting in functionally mature NK cells available for use in downstream assays.

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Materials

2.1 Human NK Cell Development 2.1.1 Isolation of UCB CD34+ HPCs

1. Transport buffer: Phosphate-buffered saline (PBS), 0.05 μM β-mercaptoethanol (β-Me), 0.63% w/v trisodium citrate. 2. MACS buffer: PBS, 1% BSA, 2 mM EDTA. 3. AB labeling buffer: MACS buffer, 20% human AB serum. 4. Human CD34 Microbead kit (Miltenyi). 5. Ficoll® Paque Plus (GE Healthcare Life Sciences). 6. ACK lysing buffer. 7. QuadroMACS separator (Miltenyi). 8. LS Columns (Miltenyi). 9. RMPI-1640. 10. Antibodies for the CD34+ purity check via flow cytometry: Anti-CD34 (clone 4H11), anti-CD45 (clone H130), and live/dead fixable dye.

2.1.2 EL08-1D2 Cell Culture and Irradiation

1. EL08-1D2 mouse stromal cell line (RRID:CVCL_VV34). 2. EL08-1D2 complete medium: ɑ-MEM, 50% Myelocult, 20% “conditioned” EL08-1D2 medium (see Note 4), 7.5% embryonic stem cell fetal bovine serum (FBS) qualified (ES-FBS), 1%

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1% Penicillin + Streptomycin (P/S), 50 μM β-mercaptoethanol (β-Me), 1 μM hydrocortisone (see Note 3).

L-glutamine,

3. EmbryoMax 0.1% gelatin solution. 4. Trypsin-EDTA. 5. Cell culture flasks (surface area 75 or 175 cm2). 6. 24 well cell culture plates. 7. Cell irradiator (Gamma Irradiator). 2.1.3 NK Cell Differentiation from UCB CD34+ Cells

1. CD34+ undifferentiation medium: Stemspan, 1% L-glutamine, 1% P/S, 10 ng/mL GM-SCF, 100 ng/mL SCF, 100 ng/mL TPO, 100 ng/mL Flt3L, 10 ng/mL IL-3, 10 ng/mL IL-6. 2. Human NK cell basal medium: ɑ-MEM, 50 μM β-Me, 5 ng/ mL sodium selenite, 50 μM ethanolamine. 3. Human NK cell complete medium: Human NK cell basal medium, 20% human AB serum, 20 μg/mL ascorbic acid, 5 ng/mL human IL-3 (for the first week of culture only), 20 ng/mL human IL-7, 20 ng/mL human SCF, 10 ng/mL human Flt3L, 10 ng/mL human IL-15. 4. 24 well cell culture plates. 5. Human NK cell antibody master mix: Anti-CD3 (clone UCHT1), anti-CD45 (clone HI30), anti-CD56 (clone CMSSB), anti-CD16 (clone 3G8), and DAPI.

2.2 Mouse NK Cell Development 2.2.1 OP9-GFP Cell Culture 2.2.2 Isolation of Bone Marrow Lin HPCs

1. OP9 culture medium: IMDM, 20% heat-inactivated FBS, 1% P/S. 2. Trypsin-EDTA. 3. 10 cm tissue culture plates. 1. MACS buffer: PBS, 2 mM EDTA, 0.5% BSA. 2. Lin complete cytokine medium: DMEM, 10% ES-FBS, 1% P/S, 50 μM β-Me, 10 ng/mL mouse Flt3L, 10 ng/mL mouse IL-7, 100 ng/mL mouse SCF. 3. Lin PE antibody cocktail: 2 mL MACS buffer, 20 μL B220PE (clone RA3/6B2), 20 μL CD2-PE (clone RM2–5), 20 μL TER119-PE (clone TER119), 20 μL NK1.1-PE (clone PK136), 5 μL Mac-1-PE (clone M1/70), 5 μL Gr-1-PE (clone RB6-8c5). 4. Anti-PE microbeads ultrapure (Miltenyi). 5. ACK lysing buffer. 6. Mortar and pestle. 7. 40 μM strainer. 8. Scalpel and forceps.

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9. QuadroMACS separator (Miltenyi). 10. LD columns (Miltenyi). 11. 24 well cell culture plates. 2.2.3 NK Cell Differentiation from Lin HPCs

1. Mouse NK culture medium: ɑ-MEM, 20% ES-FBS, 1% P/S, 50 μM β-Me, 30 ng/mL mouse IL-15. 2. Mouse NK cell antibody master mix: Anti-CD3 (clone 17A2), anti-NK1.1 (clone PK136), anti-NKp46 (clone 29A1.4), live/ dead dye. 3. 24 well plates. 4. 6 well plates.

3

Methods All centrifugation steps are carried out with a brake unless otherwise stated.

3.1 Human NK Cell Development 3.1.1 Selection of CD34+ HPCs from Umbilical Cord Blood

1. Dilute whole blood 1:1 with room temperature transport medium and swirl, and wait until the mixture is at room temperature (see Note 1). 2. Add 15 mL of room temperature Ficoll into clean 50 mL Falcon tubes, avoiding droplets. 3. Once at room temperature, mix the cord blood and transport medium with a stripette a few times. Pick up 35 mL and gently layer the blood on top of the Ficoll. The ratio of Ficoll:blood/ transport medium is 1:3. Do not allow the blood and Ficoll layer to mix. 4. Centrifuge at 400  g for 30 min, 20–21  C with the brake off. 5. After the centrifugation, you should see three distinct layers: serum, buffy coat containing the peripheral blood mononuclear cells (PBMCs), and a pellet of red blood cells. Gently remove the top layer of serum using a stripette, try not to disturb the buffy coat layer. Leave 5–10 mL of serum above the buffy coat layer. 6. Using a Pasteur pipette, carefully remove the buffy coat layer and transfer into a clean 50 mL Falcon. Begin extraction from the middle, gradually moving outwards in a circular motion. Continue until there is no more visible buffy coat layer remaining. Avoid collecting excess Ficoll. 7. Divide the collected buffy coat layers into 50 mL Falcon tubes, with no more than 15 mL in each. Top up to 40 mL with room temperature RPMI in order to dilute and wash off the serum or residual Ficoll. 8. Centrifuge at 225  g for 10 min.

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9. Discard the supernatant. Resuspend and combine 2 Falcon tube pellets in 1 mL of ACK lysing buffer (for a total of 6 Falcon tubes and therefore 6 pellets combine the cells and resuspend in a total of 3 mL). Incubate in lysis buffer at 37  C for 1 min. After incubation, add 40 mL of RPMI to wash. Take a sample to count and for the flow cytometry “pre-selection” purity analysis. The unstained control for flow cytometry can also be taken from this sample. 10. Centrifuge at 145  g for 10 min. Discard the supernatant. The lysis step (step 9) can be repeated if the color of the pellet remains red. 11. Resuspend the cell pellet with 300 μL of ice-cold AB labeling buffer per 108 PBMCs counted. 12. Using the Human CD34 Microbead kit, add 100 μL of FcR blocking reagent and 100 μL of microbeads per 108 PBMCs. 13. Incubate for 30 min at 4  C. 14. Wash with 10 mL of ice-cold MACS buffer. 15. Maintain MACS buffer on ice during the following steps. 16. Centrifuge at 225  g for 10 min at 4  C. 17. Resuspend the pellet in 500 μL cold MACS buffer per 108 PBMCs. 18. Place the LS selection column (1 column for up to 2  109 total PBMCs) in the magnet of the MACS separator. Place an opened 15 mL Falcon underneath the column. Equilibrate the column with 3 mL of cold MACS buffer and discard the flowthrough. Place a new 50 mL Falcon underneath. 19. Apply the 500 μL cell suspension onto the column. Collect the flow-through as the CD34 cell fraction. 20. Wash the column four times with 3 mL of cold MACS buffer, allowing the column to stop dripping before continuing with the next wash. 21. Remove the column from the magnetic separator and place onto a clean 15 mL Falcon. 22. Elute and collect the CD34+ cells with 5 mL of cold MACS buffer, allowing the column to stop dripping. 23. Repeat elution with another 5 mL of cold MACS buffer, using the plunger supplied with the column to collect residual cells (see Note 2). 24. Centrifuge at 225  g for 7 min, 4  C. Discard the supernatant. 25. Resuspend the pellet with 300 μL of ice-cold AB labeling buffer, irrespective of cell number. 26. Using the Human CD34 Microbead kit, add 25 μL FcR blocking reagent and 25 μL microbeads to the cells.

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27. Incubate for 15 min at 4  C. 28. Wash with 4 mL of cold MACS buffer. 29. Centrifuge at 225  g for 5 min, 4  C. Discard the supernatant. 30. Resuspend the cell pellet in 500 μL cold MACS buffer. 31. Place a new LS column in the magnet of the MACS separator. Place a 50 mL Falcon under the column and rinse the column with 3 mL of cold MACS buffer. 32. Apply the cell suspension onto the tube and collect the flowthrough as the CD34 fraction. 33. Wash the column four times with 3 mL cold MACS buffer, letting the rinse go through completely each time. 34. Remove the column away from the magnetic separator and place onto a clean 15 mL Falcon. 35. Elute and collect the CD34+ cells with 5 mL of cold MACS buffer, allowing the column to stop dripping. 36. Repeat elution with another 5 mL of cold MACS buffer, using the plunger supplied with the column to collect residual cells (see Note 2). 37. Take a sample out to count and for the flow cytometry postselection purity analysis. 38. Centrifuge at 225  g for 7 min, 4  C. Discard the supernatant. 39. Resuspend the pellet in 500 μL–1 mL human freezing medium for cryopreservation or proceed with the following protocol to begin in vitro NK cell development. 40. With the pre-selection and post-selection samples, stain with anti-CD34 and anti-CD45 antibodies and a live/dead dye and analyze with flow cytometry for purity (Fig. 1).

Fig. 1 Purity of UCB CD34+ cells after isolation

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3.1.2 EL08-1D2 Thaw and Maintenance Culture

1. Gelatinize 75 cm2 flasks (T75) before plating out EL08-1D2 cells to promote adherence. For each 75 cm2 flask, coat the slanted side of the flask with 5–7 mL 0.1% gelatin solution and incubate at 37  C for 15 min. 2. Remove 0.1% gelatin solution and wash the 75 cm2 with 7 mL PBS. 3. Thaw EL08-1D2 cells in EL08-1D2 complete medium (see Note 3). 4. Spin down at 300  g for 10 min. 5. Resuspend in EL08-1D2 complete medium and count the cells. 6. Plate 4  105 cells per 75 cm2 flask in 13–15 mL EL08-1D2 medium, culture at 32  C, 5% CO2 for 3 days. 7. EL08-1D2 cells can be split every 3–4 days once they have reached 80–90% cell confluency. 8. To split the cells, harvest EL08-1D2 medium and filter it using a 0.2 μm filter. This “conditioned” medium can be stored at 80  C to make new EL08-1D2 complete medium when needed (see Note 4). 9. Wash the flask with 7 mL PBS and discard. 10. Add 7 mL of trypsin and incubate for 5 min at 37  C. 11. Once cells have detached from the growth surface, add 7 mL of EL08-1D2 complete medium and collect cells in a Falcon tube. 12. Spin at 300  g for 10 min. 13. Resuspend the pellet in EL08-1D2 complete medium and count. 14. Passage the cells by seeding at 4  105 cells per 75 cm2 into a new cell culture flask.

3.1.3 Irradiation of EL08-1D2 Cells

1. Harvest the cells with trypsin as mentioned above. 2. Irradiate the cells at 25 Gy. 3. After irradiation, spin the cells at 300  g for 10 min at 4  C. 4. Resuspend the pellet in EL08-1D2 complete medium. Count and seed 3–4  104 cells/cm2 into previously gelatinized plates for NK cell differentiation. Culture at 37  C, 5% CO2 (see Note 5).

3.1.4 NK Cell Differentiation from UCB CD34+ Cells

1. Thaw a 1 mL CD34+ cell cryovial in 10 mL α-MEM and 10% human Ab serum and spin at 300  g for 8 min. 2. Resuspend the pellet in 500 μL undifferentiation medium and count.

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3. Seed CD34+ cells at 1  106 cells/mL in undifferentiation medium for an overnight recovery at 37  C, 5% CO2 (plate 5  105 cells in 500 μL in a 24 well). 4. On the same day, thaw irradiated EL08-1D2 and seed onto previously gelatinized tissue culture plates at 3–5  104/cm2. Incubate at 37  C, 5% CO2. Day 0–6 of differentiation 5. After overnight recovery, harvest the CD34+ cells and count.

6. Spin the cells at 300  g for 8 min and resuspend in human NK cell complete medium (with IL-3) at a concentration of 6  103 cells/mL (see Note 6). 7. Aspirate medium from the 24 well plate containing irradiated EL08-1D2 (seeded the day before) and seed the recovered CD34+ cells in that 24 well plate (500 μL/well, for 3  103 cells/well). 8. This is day 0 of differentiation. Culture the cells for 7 days at 37  C, 5% CO2. 9. Perform a half-medium change at day 3 or 4 with the same volume of fresh 2 human NK cell complete medium (with IL-3; see Note 7). Day 7–21 of differentiation 10. On day 7 of differentiation, perform a half-medium change with the same volume of fresh 2 human NK cell complete medium (without IL-3; see Note 7).

11. Perform a half-medium change every 3–4 days. Proliferating cell populations can be transferred into larger sized wells for further expansion (see Note 8). 12. For optimal NK cell production, differentiating cells should be maintained on irradiated EL08-1D2 culture up until day 21–24. After this point, NK cells can be maintained in the absence of stroma and with 50 ng/mL IL-15 alone. 13. Cultures can be analyzed for CD56+ NK cells by day 17 of culture. 3.1.5 NK Cell Surface Marker Staining

1. Harvest cells for flow cytometry and collect into an FACS tube. 2. Wash with 1 mL of PBS 2% FBS. 3. Spin 500  g for 5 min and discard the supernatant. 4. Stain with the human NK cell antibody master mix and leave at 4  C for 20 min in the dark. 5. Wash with 1 mL of PBS 2% FBS and spin 500  g for 5 min. 6. Discard the supernatant and resuspend in 300 μL of PBS 2% FBS.

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Fig. 2 Human CD34+ derived NK cell flow cytometry analysis. (a) Gating strategy to analyze human NK cells. (b) Time course of human NK cell development from UCB CD34+ HPCs, days 14, 17, and 20 after the start of differentiation

7. Run the samples on the flow cytometer and look for NK cell purity by gating on live CD3 , CD45+, CD56+CD16 , or CD56+CD16+ (Fig. 2). 3.2 Mouse NK Cell Development

1. Cell cultures are split at 70–80% confluency, with medium changes every 2–3 days.

3.2.1 OP9-GFP Cell Maintenance Culture

2. To split OP9-GFP cells, aspirate medium from the 10 cm plate and wash with 1 PBS. 3. Add 5 mL of trypsin and incubate at 37  C for 3–5 min.

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4. Once cells have detached from the growth surface, collect the cells and quench the trypsin with 5 mL of OP9 culture medium. 5. Spin at 500  g for 5 min. 6. Aspirate the supernatant and resuspend in 10 mL of OP9 culture medium. 7. Plate 1 mL of cells into a new 10 cm plate. 3.2.2 Bone Marrow Harvest and Lin Cell Isolation

1. Dissect both hindlimbs and hips from the euthanized mouse. 2. Place the bones onto a clean 10 cm plate lid. Using the scalpel and forceps, remove all soft tissue from the femurs, tibias, and hips. 3. Place clean bones into the mortar with 2 mL of PBS 2% FBS, and gently crush with the pestle to isolate bone marrow. Avoid grinding the bones to reduce cell loss. 4. Transfer the bone marrow into a Falcon tube, passing the cell suspension through a 40 μm filter. 5. Repeat step 3 until fragments are no longer pink (see Note 9). 6. Spin the bone marrow suspension at 500  g for 5 min. 7. Remove the supernatant and resuspend the cells in 2 mL ACK lysis buffer, incubate at room temperature for up to 5 min. 8. Wash with 10 mL of PBS 2% FBS and spin at 500  g for 5 min. Take a 50 μL sample prior to spinning for use as the unstained control on flow cytometry for purity testing. 9. Resuspend the pellet in 2 ml Lin PE antibody cocktail and incubate for 5 min at 4  C. 10. Wash with 20 mL of PBS 2% FBS, and spin at 500  g for 5 min. Take a 50 μL sample prior to spinning, as the pre-depleted control for purity testing. 11. Resuspend pellet in 800 μL of PBS 2% FBS buffer. 12. Add 200 μL of anti-PE microbeads and incubate for 15 min at 4  C. 13. While cells are incubating, place one LD column onto the magnetic field separator and a 15 mL Falcon underneath. Equilibrate the column with 3 mL PBS and discard the flowthrough. Place a new 15 mL Falcon underneath. 14. Wash the cells with 20 mL PBS and spin at 500  g for 5 min. 15. Resuspend cells in 500 μL PBS and load onto the LD column by passing through a 40 μm filter, collect the flow-through as the Lin fraction. 16. Wash the column three times with 2 mL of PBS, allowing the column to stop dripping before continuing with the next wash.

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Fig. 3 Purity analysis of mouse bone marrow Lin cells post-depletion. Mouse BM Lin cells post-depletion (open histogram) and pre-depletion (solid histogram). Lin cells usually constitute >95% cells following depletion

17. After the three washes, take 50 μL out as the post-depletion sample for purity testing and take 10 μL to count the cells obtained. 18. Spin the Lin cells obtained at 500  g for 5 min and discard the supernatant. 19. Resuspend the cell pellet in Lin complete cytokine medium at a concentration of 1  106 cells/mL. Plate the cells on a 24 well plate and incubate at 37  C, 5% CO2 for an overnight recovery. 20. Purity analysis: Using flow cytometry, set the PE+ gate using the pre-depleted sample and unstained controls. Determine the purity of the post-depleted Lin sample. Include livedead dye for accurate analysis of the purity post-depletion (Fig. 3). 3.2.3 OP9-GFP Cell Co-culture and Mouse NK Cell Differentiation

1. On the day of bone marrow harvest and Lin cell depletion, harvest OP9-GFP cells using trypsin (see Subheading 3.2.1) and centrifuge at 500  g for 5 min. 2. Resuspend the pellet in OP9 culture medium and plate 3  103 cells/well OP9-GFP cells in 24 well plates and leave to settle overnight. 3. The next day, harvest the Lin cells and count. 4. Spin the cells at 500  g for 5 min and resuspend at 6  104 cells/mL in mouse NK differentiation medium. 5. Aspirate the OP9 culture medium from the 24 well plates with OP9-GFP cells and add 500 μL of the Lin cells on top.

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Fig. 4 Mouse NK cell development after day 9 of differentiation. Gating strategy to analyze mouse NK cells after 9 days of differentiation in vitro

6. Incubate the cells at 37  C, 5% CO2. 7. Perform half-medium changes every 2–3 days with fresh mouse NK differentiation medium (see Note 7). 8. After 7–9 days of culture, the wells can be analyzed for NK cell development (Fig. 4).

4

Notes 1. Cord blood should be processed on the same day; however, it can be processed within 24 h if necessary. 2. To maximize cell recovery and health, do not use too much force when using the plunger. Aim to see 2–3 droplets forming every second. 3. EL08-1D2 medium (without hydrocortisone) can be stored at 4  C for up to 1 month. Hydrocortisone must be added to the medium fresh before use. 4. “Conditioned” medium refers to supernatant from a confluent EL08-1D2 culture, which has been filtered for sterility and stored at 80  C for long-term storage.

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5. Irradiated EL08-1D2 cells can be maintained at 37  C and cultured in EL08-1D2 complete medium for up to 1 week. These cells can also be cryopreserved for future use. 6. Human NK cell basal medium can be stored at 4  C for 1 month. Human NK cell complete medium must be made fresh before use. 7. When performing half-medium changes, carefully remove half the supernatant from the top of the well, taking care to not disturb the suspension cells. Replace with fresh medium by allowing the medium to flow down the well wall in order to not disrupt the adherent layer. 8. Under bright-field microscopy, CD34+ derived cells have a circular, bright, and refractory appearance. Wells that are approximately 80–90% confluent should be split 1:2–1:3 for expansion. We have found that the minimum confluency that can withstand a 1:2 split is 40–50%. Cells should be split onto adhered irradiated EL08-1D2 stroma. To split the wells, a pipette can be used to detach any stroma and developing NK cells from the growth surface. 9. This generally takes no more than three rounds. The bone marrow suspension should be fairly clear by the last round. References 1. Abel AM, Yang C, Thakar MS, Malarkannan S (2018) Natural killer cells: development, maturation, and clinical utilization. Front Immunol 9:1869. https://doi.org/10.3389/fimmu. 2018.01869 2. Freud AG, Caligiuri MA (2006) Human natural killer cell development. Immunol Rev 214: 5 6 – 7 2 . h t t p s : // d o i . o r g / 1 0 . 1 1 1 1 / j . 1600-065X.2006.00451.x 3. Montaldo E, Del Zotto G, Della Chiesa M, Mingari MC, Moretta A, De Maria A, Moretta L (2013) Human NK cell receptors/markers: a tool to analyze NK cell development, subsets and function. Cytometry A 83:702–713. https://doi.org/10.1002/cyto.a.22302 4. Wu Y, Tian Z, Wei H (2017) Developmental and functional control of natural killer cells by cytokines. Front Immunol 8:930. https://doi. org/10.3389/fimmu.2017.00930 5. Zhu H, Kaufman DS (2019) An improved method to produce clinical-scale natural killer cells from human pluripotent stem cells. Methods Mol Biol 2048:107–119. https://doi.org/ 10.1007/978-1-4939-9728-2_12 6. Domogala A, Blundell M, Thrasher A, Lowdell MW, Madrigal JA, Saudemont A (2017) Natural killer cells differentiated in vitro from cord

blood CD34+ cells are more advantageous for use as an immunotherapy than peripheral blood and cord blood natural killer cells. Cytotherapy 19:710–720. https://doi.org/ 10.1016/j.jcyt.2017.03.068 7. Hordyjewska A, Popiołek Ł, Horecka A (2015) Characteristics of hematopoietic stem cells of umbilical cord blood. Cytotechnology 67: 387–396. https://doi.org/10.1007/s10616014-9796-y ´, 8. Herrera L, Salcedo JM, Santos S, Vesga MA Borrego F, Eguizabal C (2017) OP9 feeder cells are superior to M2-10B4 cells for the generation of mature and functional natural killer cells from umbilical cord hematopoietic progenitors. Front Immunol 8:755. https:// doi.org/10.3389/fimmu.2017.00755 9. Haddad R, Guardiola P, Izac B, Thibault C, Radich J, Delezoide A-L, Baillou C, Lemoine FM, Gluckman JC, Pflumio F, Canque B (2004) Molecular characterization of early human T/NK and B-lymphoid progenitor cells in umbilical cord blood. Blood 104: 3918–3926. https://doi.org/10.1182/ blood-2004-05-1845 10. Grzywacz B, Kataria N, Sikora M, Oostendorp RA, Dzierzak EA, Blazar BR, Miller JS,

Human and Mouse NK cell Development in vitro Verneris MR (2006) Coordinated acquisition of inhibitory and activating receptors and functional properties by developing human natural killer cells. Blood 108:3824–3833. https:// doi.org/10.1182/blood-2006-04-020198 11. McCullar V, Oostendorp R, PanoskaltsisMortari A, Yung G, Lutz CT, Wagner JE, Miller JS (2008) Mouse fetal and embryonic liver cells differentiate human umbilical cord blood (UCB) progenitors into CD56 negative NK cell precursors in the absence of IL-15. Exp Hematol 36:598–608. https://doi.org/10. 1016/j.exphem.2008.01.001 12. Hoogstad-van Evert JS, Cany J, van den Brand D, Oudenampsen M, Brock R, Torensma R, Bekkers RL, Jansen JH, Massuger LF, Dolstra H (2017) Umbilical cord blood CD34+ progenitor-derived NK cells efficiently kill ovarian cancer spheroids and intraperitoneal tumors in NOD/SCID/IL2Rgnull mice. Onco Targets Ther 6:e1320630. https://doi. org/10.1080/2162402X.2017.1320630 13. Perez SA, Mahaira LG, Demirtzoglou FJ, Sotiropoulou PA, Ioannidis P, Iliopoulou EG, Gritzapis AD, Sotiriadou NN, Baxevanis CN, Papamichail M (2005) A potential role for hydrocortisone in the positive regulation of IL-15-activated NK-cell proliferation and survival. Blood 106:158–166. https://doi.org/ 10.1182/blood-2004-08-3232 14. Spanholtz J, Tordoir M, Eissens D, Preijers F, van der Meer A, Joosten I, Schaap N, de Witte TM, Dolstra H (2010) High log-scale

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expansion of functional human natural killer cells from umbilical cord blood CD34-positive cells for adoptive cancer immunotherapy. PLoS One 5:e9221. https://doi.org/10.1371/jour nal.pone.0009221 15. Yu J, Freud AG, Caligiuri MA (2013) Location and cellular stages of natural killer cell development. Trends Immunol 34:573–582. https:// doi.org/10.1016/j.it.2013.07.005 16. Chiossone L, Chaix J, Fuseri N, Roth C, Vivier E, Walzer T (2009) Maturation of mouse NK cells is a 4-stage developmental program. Blood 113:5488–5496. https://doi. org/10.1182/blood-2008-10-187179 17. Carotta S, Pang SHM, Nutt SL, Belz GT (2011) Identification of the earliest NK-cell precursor in the mouse BM. Blood 117: 5449–5452. https://doi.org/10.1182/ blood-2010-11-318956 18. Male V, Nisoli I, Kostrzewski T, Allan DSJ, Carlyle JR, Lord GM, Wack A, Brady HJM (2014) The transcription factor E4bp4/Nfil3 controls commitment to the NK lineage and directly regulates Eomes and Id2 expression. J Exp Med 211:635–642. https://doi.org/10. 1084/jem.20132398 19. Tang PM-K, Tang PC-T, Chung JY-F, Hung JSC, Wang Q-M, Lian G-Y, Sheng J, Huang X-R, To K-F, Lan H-Y (2018) A novel feederfree system for mass production of murine natural killer cells in vitro. J Vis Exp (131):56785. https://doi.org/10.3791/56785

Chapter 4 Induction of Human Natural Killer Cells Under Defined Conditions by Seamless Transition from Maintenance Culture of Pluripotent Stem Cells Akira Niwa and Megumu K. Saito Abstract The use of pluripotent stem cells (PSCs) as a source of natural killer cells (NK cells) can improve reproducibility in the analysis of the pathogenesis of NK cell-associated diseases and in the production of off-the-shelf cellular medicines. We have developed a method for the differentiation of NK cells from human PSCs under serum-free and two-dimensional condition. Our method enables the seamless transition from maintenance of PSCs to differentiation of NK cells, without the use of any techniques other than medium exchange and whole culture passage. Key words Natural killer cells, Pluripotent stem cells, Monolayer culture, Serum-free culture, Stepwise differentiation

1

Introduction Unlike T cells, natural killer (NK) cells are not restricted by human leukocyte antigen (HLA) and have a broad spectrum of activity against a variety of antigenic cells [1]. The use of pluripotent stem cells (PSCs) as a source of NK cells is expected to be advantageous in terms of reproducibility for pathological analysis and regenerative medicine. Here, we introduce an easy way to generate highly pure NK cells from human PSCs [2]. This method is a part of a series of two-dimensional serum-free differentiation cultures that we have been reporting on [3–6]. Using this method, NK cells can be induced directly on the dishes in which undifferentiated PSCs are cultured. The only procedures required are medium exchange and floating cell passage.

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_4, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Materials 1. Human pluripotent stem cells (PSCs): Human embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs) (see Note 1). 2. Multi-well cell culture plate. 3. Micro-fabricated plastic vessel: EZSPHERE SP Spheroid Culture Plate 96 well (AGC TECHNO GLASS, Tokyo, Japan). 4. P1000 micropipette. 5. StemFit AK02N medium (Ajinomoto, Tokyo, Japan). 6. PSC medium-A: StemFit AK02N medium, 10 μM ROCK inhibitor Y-27632 (Stemcell Technologies, Vancouver, Canada), 625 ng/mL recombinant laminin-511 E8 fragment, iMatrix-511 (Nippi, Tokyo, Japan) (see Note 2). 7. PSC medium-B: StemFit AK02N medium, 10 μM ROCK inhibitor Y-27632. 8. PSC medium-C: StemFit AK02N medium, 625 ng/mL recombinant laminin-511 E8 fragment, iMatrix-511 (see Note 2). 9. Differentiation medium-A: Essential 8 Medium (Thermo Fisher Scientific, Waltham, MA), 2 μM Glycogen Synthase Kinase 3 (GSK-3) inhibitor CHIR-99021, 80 ng/mL recombinant human bone morphogenetic protein 4 (BMP4), 80 ng/ mL recombinant human vascular endothelial growth factor 165 (VEGF165), store at 4  C. 10. Differentiation medium-B: Essential 6 Medium (Thermo Fisher Scientific), 2 μM TGF-β receptor type I receptor kinase (ALK5) inhibitor, SB431542, 80 ng/mL VEGF165, 50 ng/mL recombinant human stem cell factor (SCF), store at 4  C. 11. Differentiation medium-C: Stemline II Hematopoietic Stem Cell Expansion Medium (Sigma-Aldrich, St. Louis, MO), 50 ng/mL recombinant human SCF, 50 ng/mL recombinant human FMS-like tyrosine kinase 3 (FLT3) ligand, store at 4  C. 12. Differentiation medium-D: Stemline II hematopoietic stem cell expansion medium, 50 ng/mL SCF, 50 ng/mL FLT3 ligand, 50 ng/mL recombinant human interleukin (IL)-7, 50 ng/mL recombinant human IL-15, store at 4  C.

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Methods

3.1 PSC Colony Preparation

1. Seed human PSCs suspended in PSC medium-A at 1000 PSCs in 1.5 mL per well of a 6-well plate (see Notes 1, 3, and 4). 2. Incubate the cells at 37  C in 5% CO2. 3. Next day, aspirate the culture medium and add 1.5 mL of StemFit AK02N medium. 4. Culture the cells at 37  C in 5% CO2, until the colonies grow to a diameter of 750–1000 μm (see Notes 5 and 6).

3.2 A Simple Way to Uniformly Form PSC Colonies Appropriate in Size and Density for Differentiation (See Note 7)

1. Suspend 20,000 PSCs in 100 μL of PSC medium-B. 2. Seed the cells to one well of EZSPHERE SP Spheroid Culture Plate 96 well. 3. Incubate the cells at 37  C in 5% CO2 overnight. 4. Collect the spheroids in a 15 mL conical tube by gentle pipetting using P1000 micropipettes (see Note 8). 5. Leave the spheroids to stand at room temperature for 2 min to precipitate by gravity and then aspirate the supernatant. 6. Suspend the spheroids in PSC medium-C and dispense the suspension into a new cell culture plate at 5–10 spheroids per 10 cm2 (equivalent to one well of 6-well cell culture plate) (see Note 9). 7. Incubate at 37  C in 5% CO2 until the colonies grow to a diameter of 750–1000 μm (see Notes 5 and 10).

3.3 NK Cell Differentiation

1. On the initiation date of differentiation (day 0), remove the culture medium in step 4 of Subheading 3.1 or step 7 of Subheading 3.2, and add 1.5 mL of differentiation mediumA (see Note 11). 2. Incubate the cells at 37  C in 5% CO2 for 2 days. 3. On day 2 of differentiation, remove the medium and add 1.5 mL of differentiation medium-B (see Note 12). 4. Incubate the cells for 2 more days. 5. On day 4 of differentiation, remove the medium and add 1.5 mL of differentiation medium-C (see Note 13). 6. Incubate the cells for 4 days. 7. On day 8 of differentiation, add 1.5 mL of fresh differentiation medium-C. The total volume of medium at this step will be 3.0 mL per well. 8. Incubate the cells for 4 additional days.

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Fig. 1 Orderly emergence of mesodermal and hemogenic endothelial progenitor cells from PSCs. Flow dot plots show the emergence of kinase insert domain receptor (KDR, vascular endothelial growth factor receptor 2 (VEGFR2)) positive cells, followed by CD34 positive cells. On the initiation date of differentiation (Day 0), the cells do not express either KDR or CD34. After 2 days of differentiation, KDR positive mesoderm differentiation cells appear. On day 4, KDR positive CD34 positive hematopoietic endothelial cells emerge

9. On day 12 of differentiation, collect the floating cells together with medium into a conical tube. Centrifuge at 1000  g for 1 min and discard the supernatant. Suspend the cells in 1.5 mL of differentiation medium-D and then back into the original wells (see Note 14). 10. Incubate the cells for 2 days. 11. On day 14 of differentiation, add 1.5 mL of fresh differentiation medium-D. The total volume of medium at this step will be 3.0 mL per well. 12. Incubate the cells for 4–5 additional weeks. During this period, carefully remove 1.5 mL of medium and replace with 1.5 mL of fresh differentiation medium-D every 4–6 days (see Note 15). 13. On day 48 of differentiation, pipette up and down and collect floating cells into a conical tube (Fig. 1, see Note 16).

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Notes 1. This protocol is applicable for both ESCs and iPSCs. 2. The standard concentration of recombinant laminin-511 E8 fragment, iMatrix-511 is 625 ng/mL, but the optimal concentration for colony formation varies by line (range 625–1250 ng/mL). 3. When you use frozen PSCs, it is recommended to culture them for 1–2 passages in the undifferentiated state before use for differentiation.

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4. The appropriate cell number for seeding depends on lines. 5. It usually takes 5–7 days. The colony size can be determined using a microscope. 6. Typically, 5–10 colonies will be produced from 1000 PSCs. If the number of colonies is more than 10, it is recommended to scrape off excess colonies with the tip of the pipette to reduce the colonies. For the differentiation to NK cells, proceed with Subheading 3.3. 7. In this culture system, once differentiation is initiated, no work other than medium change is required at all until NK cells are obtained. In other words, the density of undifferentiated colonies at the start of differentiation is almost the only factor that determines the result. The optional procedure described in Subheading 3.2 is a convenient and efficient way to prepare homogeneous PSC colonies in large quantities to improve the reproducibility in differentiation [7]. 8. The spheroids are very loose at this point, so handle them carefully so as not to break it. 9. The spheroids will quickly adhere to the plate. 10. Typically, you can get 80–100 spheroids evenly consisting of 200 cells by plating 20,000 cells per well. Appropriate cell numbers for seeding depend on lines. 11. This will initiate the differentiation of undifferentiated PSCs into mesodermal cells. The differentiation can be assessed by flow cytometry (FCM) analysis on day 2 (Fig. 1). 12. This will initiate the differentiation into hemogenic endothelial cells. The differentiation can be assessed by FCM analysis on day 4 (Fig. 1). 13. This will induce the early hematopoietic progenitor cells from the hemogenic endothelial cells. 14. This will initiate the differentiation into NK cells. 15. Carefully remove the upper layer of medium without pipetting to avoid the loss of cells. 16. The differentiation from PSCs into NK cells can be assessed by sequential FCM analysis through day 24–48 (Fig. 2) [2]. Generally, CD56 positive NK cells appear on day 24 of differentiation and increase thereafter. On day 48 of differentiation, CD56 positive NK cells reach around 80%.

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Fig. 2 Differentiation to NK cells. Flow dot plots show CD56 positive cells on 24, 36, and 48 days after differentiation (upper panels). Overlay histograms show expression of killer-cell immunoglobulin-like receptor (KIR) and other NK cell receptors (NKR) in CD56+NKp44+ cells on day 48 of differentiation (lower panels). The cells were stained with isotype control (open histogram) or antibodies against the respective receptors (filled histogram)

References 1. Vivier E, Raulet DH, Moretta A, Caligiuri MA, Zitvogel L, Lanier LL et al (2011) Innate or adaptive immunity? The example of natural killer cells. Science 331(6013):44–49 2. Matsubara H, Niwa A, Nakahata T, Saito MK (2019) Induction of human pluripotent stem cell-derived natural killer cells for immunotherapy under chemically defined conditions. Biochem Biophys Res Commun 515(1):1–8 3. Niwa A, Heike T, Umeda K, Oshima K, Kato I, Sakai H et al (2011) A novel serum-free monolayer culture for orderly hematopoietic differentiation of human pluripotent cells via mesodermal progenitors. PLoS One 6(7): e22261 4. Yanagimachi MD, Niwa A, Tanaka T, HondaOzaki F, Nishimoto S, Murata Y et al (2013) Robust and highly-efficient differentiation of functional Monocytic cells from human

pluripotent stem cells under serum- and feeder cell-free conditions. PLoS One 8(4):1–9 5. Morishima T, Watanabe K-I, Niwa A, Hirai H, Saida S, Tanaka T et al (2014) Genetic correction of HAX1 in induced pluripotent stem cells from a patient with severe congenital neutropenia improves defective granulopoiesis. Haematologica 99(1):19–27 6. Nishinaka-Arai Y, Niwa A, Matsuo S, Kazuki Y, Yakura Y, Hiroma T et al (2021) Down syndrome-related transient abnormal myelopoiesis is attributed to a specific erythromegakaryocytic subpopulation with GATA1 mutation. Haematologica 106(2):635–640 7. Ohta R, Sugimura R, Niwa A, Saito MK (2019) Hemogenic endothelium differentiation from human pluripotent stem cells in a feeder- and xeno-free defined condition. J Vis Exp (148)

Chapter 5 Development of Humanized Mouse Models for Studying Human NK Cells in Health and Disease Liang Shan, Richard A. Flavell, and Dietmar Herndler-Brandstetter Abstract Humanized mice, which we define as immunodeficient mice that have been reconstituted with a human immune system, represent promising preclinical models for translational research and precision medicine as they allow modeling and therapy of human diseases in vivo. The first generation of humanized mice showed insufficient development, diversity and function of human immune cells, in particular human natural killer (NK) cells and type 1 innate lymphoid cells (ILC1). This limited the applicability of humanized mice for studying ILC1 and NK cells in the context of human cancers and immunotherapeutic manipulation. However, since 2014, several next-generation humanized mouse models have been developed that express human IL-15 either as a transgene or knock-in (NOG-IL15, NSG-IL15, NSG-IL7-IL15, SRG-15) or show improved development of human myeloid cells, which express human IL-15 and thereby promote human NK cell development (NSG-SGM3, MISTRG, BRGSF). Here we compare the various nextgeneration humanized mouse models and describe the methodological procedures for creating mice with a functioning human immune system and how they can be used to study and manipulate human NK cells in health and disease. Key words Humanized mice, NK cells, Innate lymphoid cells, Hematopoietic stem cells, Preclinical model, Cancer immunotherapy, Immuno-oncology, Translational research, Precision medicine

1

Introduction Natural killer (NK) cells are cytotoxic lymphocytes that are able to kill virus-infected cells and tumor cells by lysis or by inducing apoptosis. Together with type 1 innate lymphoid cells (ILC1), NK cells belong to group 1 ILCs [1]. Although long been considered as a homogeneous population of innate lymphocytes, recent studies revealed subpopulations among NK cells that exhibit diverse phenotypic and functional characteristics, in part influenced by factors such as tissue localization and viral infections [2]. Recently, NK cells and ILC1 have also received much attention regarding the role they play in anti-tumor immunity and cancer immunotherapy [3, 4].

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The cytokine interleukin 15 (IL-15) has been shown to be necessary for the proper development, maturation, and function of NK cells, tissue-resident NK cells and ILC1, CD8αα intraepithelial lymphocytes, and memory CD8+ T cells [5]. IL-15 has also been shown to be essential for functional anti-tumor responses of NK and T cells in cancer immunotherapy. Yet, there is poor interspecies cross-reactivity of IL-15, with only 65% of amino acids being identical between humans and mice [6]. Since 2014, several next-generation humanized mouse models have been generated, which showed improved development and/or function of human NK cells (Table 1). These humanized mice expressed human IL-15 either as a transgene or knock-in (NOG-IL15, NSG-IL15, NSG-IL7-IL15, SRG-15) or showed improved development of human myeloid cells, which expressed human IL-15 and thereby promoted human NK cell development (NSG-SGM3, MISTRG, BRGSF). These next-generation humanized mice can therefore be used as preclinical in vivo models to study human NK cells in health and disease. More details about these humanized mice, in particular their applicability for studying human ILC1 and NK cell subsets (circulating and/or tissueresident) and their function (tumor cell killing, ADCC) in vivo, are listed in Table 1. In this chapter we focus on protocols in SRG-15 humanized mice. In our study we intercrossed RG mice with Sh/hRG-15h/ h mice to obtain experimental mice that have a heterogeneous expression of SIRPA and IL-15 (Sh/mRG-15h/m; h ¼ human, m ¼ mouse; see Note 1) [11]. Knock-in replacement of the mouse IL15 coding sequence by the human IL15 coding sequence had the advantage of proper expression of physiological levels of IL-15 in a tissue- and cell-specific manner [11]. SRG-15 mice reconstituted with human CD34+ HSPCs promoted efficient development of circulating and tissue-resident NK cell subsets. Mass cytometric analysis further confirmed phenotypic and functional heterogeneity similar to NK cells in human peripheral blood (Herndler-Brandstetter et al., Fig. 4) [11]. SRG-15 humanized mice also enabled NK cell-mediated killing of MHC class I-deficient tumor cells (K562) as well as NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC) of Burkitt’s lymphoma cells in vivo [11]. Next-generation humanized mice such as SRG-15 can therefore facilitate translational research by enabling the study of human ILC1 and NK cells and by facilitating the development/testing of novel human ILC1/NK cell-based therapeutic approaches that target infections and malignancies.

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Table 1 Humanized mouse models to study human NK cells Name

Full name /

NSG

NOD SCID Il2rg

NOG-IL2

NOD SCID Il2rgnull hIL2 tg

Description/applicability

References

Human NK cell subsets develop but these NK cells need pre-stimulation with IL-15 to kill K562 or exert ADCC

[7]

Improved development and function of human NK cell subsets (compared to NSG); NK cells killed K562 and exerted ADCC of CCR4+ Hodgkin’s lymphoma cells in vivo

[8]

NOG-IL15 NOD SCID Il2rgnull hIL15 tg

[9] Mice were not engrafted with CD34+ cells. Instead, NK cells were isolated from human PBMC and transferred into NOG-IL15 mice. Transferred NK cells killed K562 in vivo. In vitroexpanded NK cells exerted ADCC of gastric carcinoma cells (NCI-N87)

NSG-IL15 NOD SCID Il2rg/ hIL15 tg

Mouse strain available at The Jackson Laboratory (JAX): https://www.jax. org/strain/030890; no published data available yet

–

[10]

NSG-IL7IL15

NOD SCID Il2rg/ hIL7 KI hIL15 KI

Improved development of human NK cell subsets, including tissue-resident CXCR6+ NK cells (compared to NSG); improved NK cell cytotoxicity toward K562 (in vitro)

SRG-15

Balb/c x 129 Rag2/ Il2rg/ hSIRPA KI hIL15 KI

Improved development of human ILC1 [11] and NK cell subsets, including tissueresident ILC1 and NK cells; mass cytometry revealed similar phenotypic and functional diversity between NK cells in SRG-15 and humans; NK cells killed K562 and exerted ADCC of CD20+ Burkitt’s lymphoma cells in vivo

NSGSGM3

NOD SCID Il2rg/ hIL3/ hGMCSF tg hSCF tg

[12, 13] Improved development of human myeloid cells (compared to NSG), which produce hIL-15 and thereby improve development of human NK cells; no data available about NK cellmediated killing of tumor cells

MISTRG

Balb/c x 129 Rag2/ Il2rg/ Improved development of functional human myeloid cells (compared to hMCSF KI hIL3/hGMCSF KI NSG), which produce hIL-15 and hSIRPA KI hTHPO KI thereby improve development of

[14]

(continued)

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Table 1 (continued) Name

Full name

Description/applicability

References

functional human NK cells; NK cells killed an MHC class I-deficient B cell line LCL721.221 in vivo BRGSF

Balb/c Rag2/ Il2rg/ SIRPANOD Flk2/

Flt3L treatment necessary (6 injections [15] with 5 μg human Flt3L-Fc) to improve development of human myeloid cells, which produce hIL-15 and thereby improve development of human NK cells and ILC1; poly(I:C) i.p. induces IFN-γ and CD107a in NK cells; no data available about NK cell-mediated killing of tumor cells

NOG: nonobese diabetic (NOD), severe combined immunodeficient (SCID), interleukin 2 receptor gamma (Il2rg) null; NSG: NOD, SCID, Il2rg knockout; SRG-15: Rag2 knockout, Il2rg knockout, human Sirpa knock-in, human Il15 knock-in; MISTRG: Rag2 knockout, Il2rg knockout, human Sirpa knock-in, human Thpo knock-in, human Il3/Csf2 knock-in, human Csf1 knock-in; BRGSF: Rag2 knockout, Il2rg knockout, SirpaNOD, Flk2 knockout

2

Materials

2.1 Isolation of Human CD34+ Hematopoietic Stem and Progenitor Cells (HSPCs)

1. Human cord blood. 2. 50 mL conical centrifuge tubes. 3. Ficoll-Paque PLUS density gradient media. 4. 10 mL serological pipette. 5. 3 mL Pasteur Pipette. 6. EasySep Human Cord Blood CD34 Positive Selection Kit II (STEMCELL Technologies, #17896): RosetteSep cord blood CD34 pre-enrichment cocktail II, EasySep Human CD34 positive selection cocktail, EasySep Dextran RapidSpheres 50100. 7. EasySep Magnet (STEMCELL Technologies, #18000). 8. Cold FACS buffer: Phosphate-buffered saline (PBS), 1–2% fetal bovine serum (FBS), 1 mM ethylenediaminetetraacetic acid (EDTA). 9. 5 mL FACS tubes with cap (sterile). 10. Fluorochrome-conjugated anti-human CD34 antibody, clone 561 (BioLegend). 11. 7-AAD Viability Staining Solution (BioLegend). 12. Flow cytometer (e.g., LSR Fortessa). 13. Cold freezing medium: 90% FBS, 10% dimethyl sulfoxide (DMSO). 14. Pre-cooled 1.5–2 mL cryovials.

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15. Pre-cooled cell freezing container (Mr. Frosty™ filled with isopropanol or isopropanol-free Corning™ CoolCell™; all Thermo Fisher Scientific). Change the isopropanol in Mr. Frosty™ freezing containers after five freeze-thaw cycles. 2.2 Intrahepatic Injection of Human CD34+ HSPCs

1. Water bath. 2. 10 cm2 Petri dish. 3. 50 mL conical centrifuge tubes. 4. Cell culture medium: RPMI 1640 and 10% FBS. 5. Sterile PBS. 6. 70% ethanol. 7. Sterile Eppendorf tubes. 8. X-RAD 320 or another X-ray irradiator. 9. 100 μL Hamilton syringe with a 26 G Hamilton needle. 10. Newborn (2–5 day old) humanized mice are used for engraftment (see Table 1 and Note 2).

2.3 Analysis of Engraftment

1. EDTA-coated tubes or 5 mL round-bottom FACS tubes with heparin (1000 USP units per mL; Sigma-Aldrich). 2. Red blood cell (RBC) lysis buffer (BioLegend). 3. Cold FACS buffer: PBS, 1–2% FBS, 1 mM EDTA. 4. Fluorochrome-conjugated antibodies as listed in Table 3.

2.4 Tumor Xenografts

1. Isoflurane vaporizer with isoflurane and oxygen. 2. Small electric hair clipper. 3. PBS. 4. 70% ethanol. 5. Cold FACS buffer. 6. 1 mL 27 G or 30 G insulin syringe. 7. Raji cells (Burkitt’s lymphoma cells, CCL-86, ATCC). 8. Rituxan (Rituximab, Genentech/Roche). 9. Forceps. 10. Surgical scissors. 11. Disposable scalpel. 12. 70 μm cell strainer. 13. Digest medium: RPMI 1640, 10% FBS, 1 mg/mL Collagenase D (Sigma-Aldrich). 14. Cell culture medium: RPMI 1640 and 10% FBS.

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Methods

3.1 Isolation of Human CD34+ HSPCs

The isolation of human cord blood CD34+ hematopoietic stem and progenitor cells (HSPCs) is performed using the EasySep Human Cord Blood CD34 Positive Selection Kit II (STEMCELL Technologies, #17896). See Note 3 for the isolation of human CD34+ cells from other samples, such as fresh or frozen G-CSF mobilized peripheral blood or bone marrow mononuclear cells, or from frozen cord blood mononuclear cells. See Note 4 for the isolation of human CD34+ cells using the MicroBead Kit from Miltenyi Biotec or the MojoSort Kit from BioLegend. 1. Transfer human cord blood into a 50 mL conical centrifuge tube, add RosetteSep Cocktail (part of the EasySep Human Cord Blood CD34 Positive Selection Kit II) at a concentration of 5 μL/mL cord blood. 2. Mix and incubate for 20 min at room temperature. 3. Dilute cord blood sample with FACS buffer (room temperature) up to a total volume of 15 mL. 4. Add 15 mL Ficoll-Paque PLUS (room temperature) to a new 50 mL conical centrifuge tube. 5. Slowly layer 15 mL of the diluted cord blood sample on top of the Ficoll-Paque PLUS (1:1 volume ratio) using a 10 mL serological pipette. Be careful not to mix the cord blood sample with the Ficoll-Paque PLUS. 6. Centrifuge at 500–1200  g for 20–30 min at room temperature, brake OFF. 7. Harvest the white layer consisting of cord blood mononuclear cells at the interface between the yellowish plasma (top layer) and the whitish Ficoll-Paque PLUS (intermediate layer) using a 3 mL Pasteur pipette (or a 10 mL serological pipette) (see Note 5). 8. Transfer the mononuclear cells into a new 50 mL tube and top up with FACS buffer. 9. Centrifuge at 300  g for 10 min at room temperature. 10. Carefully discard supernatant and resuspend cells in 0.5 mL FACS buffer. 11. Transfer cells to a 5 mL FACS tube and add 100 μL/mL of sample EasySep Human CD34 positive selection cocktail. 12. Mix and incubate for 10 min at room temperature. 13. Vortex EasySep Dextran RapidSpheres 50100 for 30 s so that they are evenly dispersed. 14. Add 50 μL/mL of sample EasySep Dextran RapidSpheres 50100, mix and incubate for 1 min at room temperature.

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15. Top up with FACS buffer to 2.5 mL and mix by gently pipetting up and down 2–3 times. 16. Place the FACS tube (without lid) into the magnet and incubate for 3 min at room temperature. 17. Carefully discard the supernatant by picking up the magnet, and in one continuous motion invert the magnet and the tube, pouring off the supernatant. 18. Remove the tube from the magnet and repeat steps 15–17 three more times. 19. Remove the tube from the magnet (the tube contains the isolated CD34+ cells) and top up with FACS buffer. 20. Centrifuge at 300  g for 10 min at room temperature. 21. Carefully discard supernatant and resuspend the isolated human CD34+ HSPCs in desired medium. 22. Determine the number of live cells by using a hemocytometer and trypan blue. 23. To check purity and viability of isolated human CD34+ HSPCs by flow cytometry, transfer a small aliquot into a 5 mL FACS tube and add 50 μL cold FACS buffer. 24. Add fluorochrome-conjugated anti-human CD34, clone 561 and 7-AAD viability staining solution and incubate cells for 20 min on ice and protected from light. 25. Add 1 mL cold FACS buffer, spin cells at 300  g for 10 min, and discard supernatant. 26. Resuspend cell pellet in 150–200 μL cold FACS buffer and analyze on a flow cytometer. 27. To cryopreserve purified human CD34+ cells, spin CD34+ cells at 300  g for 10 min and discard supernatant (see Note 6). 28. Resuspend cells at 1  106 cells/mL in cold freezing medium. Dispense cell suspension aliquots (max. 1 mL per tube) into pre-cooled 1.5–2 mL cryovials and place the cryovials inside a pre-cooled cell freezing container. 29. Place the freezing container in a 80  C freezer overnight and transfer to liquid nitrogen the following day. 3.2 Intrahepatic Injection of Human CD34+ HSPCs

Human cord blood CD34+ cells are thawed and immune cell reconstitution in humanized mice is performed by transcutaneous injection of CD34+ cells into the liver of newborn mice. 1. Remove cryovials with human cord blood CD34+ cells from storage and immediately thaw in a water bath at 37  C for 2 min. 2. Add 48 mL of cold cell culture medium to a new 50 mL conical centrifuge tube.

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3. Gently transfer thawed cells into the pre-filled 50 mL conical centrifuge tube. 4. Rinse the cyrovial with 1 mL cell culture medium and add to the pre-filled 50 mL conical centrifuge tube. 5. Centrifuge at 300  g for 10 min at 4  C. 6. Resuspend human CD34+ cells at desired concentration (the injection volume is 20 μL) in cold sterile PBS. Transfer cells into a pre-cooled Eppendorf tube and maintain on ice. 7. Place newborn mice in a 10 cm2 petri dish for sublethal X-ray irradiation with an X-RAD 320 or another irradiator. 8. Irradiate the mice at the optimal dose shown in Table 2 (see Note 7). 9. After the irradiation, place the cage into a laminar hood. 10. To perform intrahepatic injection of CD34+ cells into newborn mice, disinfect the Hamilton syringe (including a 26 G Hamilton needle) using 70% ethanol. Rinse syringe and needle with sterile PBS afterwards.

Table 2 Engraftment details for different humanized mice to study human NK cells

a

Strains

IR dose (cGy)

Number of hCD34+ cells

Time to reconstitution

Functional NK cell development

NSG

80

100k

12 weeks

No

NOG-IL2

250

50k

4 weeks

Yesa

NOG-IL15

Unknown

Unknown

Unknown

Unknown

NSG-IL15

80

100k

12 weeks

Unknown

NSG-IL7IL15

150

2.5k–26k

12 weeks

Yes

SRG

360

100k

12 weeks

No

SRG-15

360

100k

12 weeks

Yesa

NSG-SGM3

80

50k

7–8 weeks

Unknown

MISTRG

80 or none

10–50k

7–8 weeks

Yesa

BRGSF

300

200k

8–9 weeks

Yes

Studies with these three next-generation humanized mouse stains demonstrated NK cell-mediated killing of tumor cells in vivo (MHC class I-deficient tumor cells and/or ADCC)

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11. Penetrate the skin below the rib cage and above the stomach (usually a white milk spot is visible) and place the needle tip into the center of the liver (the dark red liver is visible through the skin). Gently inject 20 μL of the human CD34+ cell suspension into the liver of the newborn mouse. Wait a few seconds before withdrawing the needle to reduce bleeding and loss of CD34+ cells. 12. Place pups back in the cage with their mothers (see Note 8). 3.3 Analysis of Engraftment

Analysis of human immune cell engraftment is performed between 7 and 14 weeks post-injection. The time to optimal reconstitution of a human immune system varies among humanized mouse strains (Table 2). Blood can be obtained via retro-orbital plexus, facial veins or mandibular veins, and tail veins. 1. Collect 50–100 μL of blood into EDTA-coated tubes or 5 mL round-bottom flow cytometry tubes pre-filled with 10–20 μL heparin (1000 USP units per mL). 2. Resuspend blood in 2–3 mL RBC lysis buffer, vortex thoroughly and incubate at room temperature for 5 min. Vortex again, spin at 300  g for 10 min, and discard supernatant. 3. Repeat step 2. 4. Resuspend cell pellet containing white blood cells in 50 μL cold FACS buffer. 5. Add fluorochrome-conjugated anti-human (h) and anti-mouse (m) antibodies to determine overall human immune cell engraftment, including human NK cell reconstitution. Incubate for 20–30 min on ice in the dark. Three different staining panels are provided in Table 3 (overall engraftment, NK cell development, NK cell maturation). 6. Add 1 mL cold FACS buffer, spin cells at 300  g for 10 min and discard supernatant. 7. Resuspend cell pellet in 150–200 μL cold FACS buffer and analyze on a flow cytometer (e.g., LSR Fortessa).

3.4 Tumor Xenografts

NK cells can kill MHC class I-deficient tumor cells (e.g., K562 tumor cells) but they can also kill tumor cells, which have been labeled with a tumor-opsonizing antibody via antibody-dependent cellular cytotoxicity (ADCC). The latter one has been utilized for cancer immunotherapy. Mice reconstituted with a human immune system can be used to study and manipulate immune responses to tumors. Here we describe a protocol to study ADCC using a human CD20-expressing Burkitt’s lymphoma xenograft model and Rituximab, a clinically approved anti-human CD20 monoclonal antibody.

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Table 3 Analysis of human NK cell differentiation and function in the bone marrow of humanized mice Panel

Antibody

Clone

Vendor

Overall engraftment

mCD45 hCD45 hCD3 hCD33 hCD19 hNKp46 hCD56

30-F11 HI30 SK7 or UCHT1 WM53 HIB19 9E2 HCD56

BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend

NK cell development

hCD45 hCD34 hCD10 hCD45RA hNKp46 hCD56 hCD16 hCD94 hCD117 hCD3

HI30 561 HI10a HI100 9E2 HCD56 3G8 HP-3D9 104D2 SK7 or UCHT1

BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend

NK cell maturation

hCD45 hNKp46 hCD56 hCD16 hCD158 hCD158b hCD158e1 hCD3 hCXCR6

HI30 9E2 HCD56 3G8 HP-MA4 Dx27 DX9 SK7 or UCHT1 K041E5

BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend BioLegend

To analyze human NK cell differentiation in the bone marrow of humanized mice, the following markers are used: ProNK cells: CD34+ CD10+ CD45RA+ CD117; Pre-NK cells: CD34 CD10 CD45RA+ CD117+; immature NK cells: CD56+ CD117+ CD94 CD16 CD10 CD34; mature NK cells: CD94+ CD56bright CD16 (CD56bright NK cell subset) and CD94+ CD56dim CD16+ (CD56dim NK cell subset)

1. Resuspend Burkitt’s lymphoma cells line, Raji cells at desired concentration in sterile PBS and maintain cells on ice. 2. Place the humanized mouse (7–14 weeks post engraftment with hCD34+ cells) into an inhalational anesthesia chamber with a properly calibrated vaporizer for longer than 1 min. Adjust the oxygen flowmeter to 0.8–1.5 L/min. Adjust the isoflurane vaporizer to 3–5%. 3. For subcutaneous injection of tumor cells [16], shave the implantation site (right flank) of the mouse using an electric hair clipper. 4. Draw 5  106 Raji cells in 100 μL PBS into a 1 mL 27 G or 30 G insulin syringe.

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5. Clean the injection site with 70% ethanol. Grasp and lift the skin on the right flank with forceps (or with thumb and index finger) and insert the needle between the skin and the underlying muscles (insert needle 5–10 mm subcutaneously), and gently inject 5  106 Raji cells in 100 μL PBS (see Note 9). 6. Tumor is usually visible/palpable 5–10 days post-injection (see Note 10). 7. Inject 100 μL PBS or 100 μL rituximab (4 mg/kg) intraperitoneal (i.p.) every third day for up to five injections. 8. Measure tumor volume every 1–3 days for up to 2 weeks by caliper measurement according to the following formula: Tumor volume (mm3) ¼ 0.5  (length  width2) (see Note 11). 9. At the endpoint, euthanize the mouse and surgically remove the tumor xenograft underneath the skin using forceps and surgical scissors. Measure the tumor weight. 10. To analyze tumor-infiltrating immune cells, cut the tumor xenograft into small pieces and transfer the pieces to a 50 mL conical centrifuge tube. 11. Add 5 mL digest medium and put the tube in a shaker for 45 min at 37  C. 12. Pour the tumor pieces and cells into a 70 μm cell strainer and thoroughly squash the tumor pieces and filter the cell suspension through the 70 μm cell strainer by adding another 10 mL cell culture medium. 13. Top up with cell culture medium. 14. Spin cells at 300  g for 10 min and discard supernatant. 15. Resuspend cell pellet in 50 μL cold FACS buffer and add fluorochrome-conjugated antibodies. Use the overall engraftment staining panel listed in Table 3. 16. Incubate for 20–30 min on ice in the dark. 17. Add 1 mL cold FACS buffer, spin cells at 300  g for 10 min, and discard supernatant. 18. Resuspend cell pellet in 150–200 μL cold FACS buffer and analyze on a flow cytometer (e.g., LSR Fortessa).

4

Notes 1. We use Sh/mRG mice (heterogeneous expression of SIRPα), since engraftment levels are significantly lower in Sh/hRG compared to Sh/mRG mice (Herndler-Brandstetter et al., Fig. 1d) [11]. The reason is that Sh/hRG mice do not express mouse

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SIRPα and lack of mouse CD47/SIRPα signaling results in bone cell loss and therefore impairs human immune cell engraftment in the mouse BM niche [17]. 2. Humanized mouse strains, including SRG-15 and MISTRG, are severely immunodeficient and therefore susceptible to infections. They should be housed in specific pathogen-free (SPF) animal facilities and handled using a laminar airflow hood and aseptic techniques. A broad-spectrum antibiotic such as Baytril may be necessary to prevent infections. Investigators should consult with the responsible veterinarian. All animal work and procedures must be approved by the local Institutional Animal Care and Use Committee and/or federal authorities. 3. The isolation of human CD34+ cells from other samples, such as fresh or frozen G-CSF mobilized peripheral blood or bone marrow mononuclear cells, or from frozen cord blood mononuclear cells, should be performed using the EasySep Human CD34 Positive Selection Kit II (STEMCELL Technologies, #17856). 4. The isolation of human CD34+ cells can also be performed using isolation kits from other companies, such as Miltenyi Biotec (CD34+ MicroBead Kit, LS column, MACS Separator) and BioLegend (MojoSort Human Hematopoietic Progenitor Cell Isolation Kit, MojoSort Magnet). 5. To minimize platelet contamination, remove and discard the top third of the plasma layer before collecting the cells at the Ficoll-Paque PLUS—plasma interface. Erythrocytes and granulocytes are at the bottom of the tube. 6. Isolated cells can also be injected directly without freezing. 7. The efficacy of human immune cell reconstitution in the peripheral blood of humanized mice following human CD34+ HSPC engraftment is shown as % human CD45+ cells of total CD45+ cells (human and mouse CD45+ cells). In irradiated SRG-15 and MISTRG mice, 85% of engrafted mice show a hCD45+ cell reconstitution level of >10% [11, 14]. In non-irradiated MISTRG mice, only about 50–60% of engrafted MISTRG show a hCD45+ cell reconstitution level of >10%, despite injection of a high number of CD34+ cells (2  105) and analysis of human immune cell reconstitution levels 12 weeks post engraftment (instead of 7–8 weeks) [14]. If MISTRG mice are used, it is therefore recommended to still perform sublethal irradiation because a very low number of CD34+ cells (1–5  104) can be used to achieve a high rate of human immune cell reconstitution. 8. Post-injection survival rate of the newborn mice should be higher than 90%.

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9. For subcutaneous tumor experiments, a consistent injection technique is extremely important. Each mouse should show a clearly visible “bleb” upon injection and up to 2 min postinjection. The needle/syringe can be reused for up to five mice within the same cage. 10. For any new tumor type, test its growth using 1  104–5  106 tumor cells/mouse. 11. The lengths of horizontal and sagittal axes of the tumor are determined using caliper measurement. The horizontal and sagittal axes of the tumor need to be at an angle of 90 to each other. The “length” in the formula always refers to the largest value, no matter whether it was the horizontal axis or the sagittal axis of the tumor.

Acknowledgements This work was supported by the NIH R01AI155162 (L.S.), the Howard Hughes Medical Institute (R.A.F.), and the Austrian Science Fund (DOC59-B33 and J3220-B19; D.H.-B.). References 1. Spits H, Artis D, Colonna M, Diefenbach A, Di Santo JP, Eberl G, Koyasu S, Locksley RM, McKenzie AN, Mebius RE, Powrie F, Vivier E (2013) Innate lymphoid cells--a proposal for uniform nomenclature. Nat Rev Immunol 13:145–149. https://doi.org/10.1038/ nri3365 2. Bjorkstrom NK, Ljunggren HG, Michaelsson J (2016) Emerging insights into natural killer cells in human peripheral tissues. Nat Rev Immunol 16:310–320. https://doi.org/10. 1038/nri.2016.34 3. Chiossone L, Dumas PY, Vienne M, Vivier E (2018) Natural killer cells and other innate lymphoid cells in cancer. Nat Rev Immunol 18:671–688. https://doi.org/10.1038/ s41577-018-0061-z 4. Gao Y, Souza-Fonseca-Guimaraes F, Bald T, Ng SS, Young A et al (2017) Tumor immunoevasion by the conversion of effector NK cells into type 1 innate lymphoid cells. Nat Immunol 18:1004–1015. https://doi.org/ 10.1038/ni.3800 5. Kennedy MK, Glaccum M, Brown SN, Butz EA, Viney JL, Embers M, Matsuki N, Charrier K, Sedger L, Willis CR, Brasel K, Morrissey PJ, Stocking K, Schuh JC, Joyce S, Peschon JJ (2000) Reversible defects in natural killer and memory CD8 T cell lineages in

interleukin 15-deficient mice. J Exp Med 191: 771–780 6. Rongvaux A, Takizawa H, Strowig T, Willinger T, Eynon EE, Flavell RA, Manz MG (2013) Human hemato-lymphoid system mice: current use and future potential for medicine. Annu Rev Immunol 31: 635–674. https://doi.org/10.1146/annurevimmunol-032712-095921 7. Ishikawa F, Yasukawa M, Lyons B, Yoshida S, Miyamoto T, Yoshimoto G, Watanabe T, Akashi K, Shultz LD, Harada M (2005) Development of functional human blood and immune systems in NOD/SCID/IL2 receptor {gamma} chain(null) mice. Blood 106: 1565–1573. https://doi.org/10.1182/ blood-2005-02-0516 8. Katano I, Takahashi T, Ito R, Kamisako T, Mizusawa T, Ka Y, Ogura T, Suemizu H, Kawakami Y, Ito M (2015) Predominant development of mature and functional human NK cells in a novel human IL-2-producing transgenic NOG mouse. J Immunol 194: 3513–3525. https://doi.org/10.4049/ jimmunol.1401323 9. Katano I, Nishime C, Ito R, Kamisako T, Mizusawa T, Ka Y, Ogura T, Suemizu H, Kawakami Y, Ito M, Takahashi T (2017) Long-term maintenance of peripheral blood

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derived human NK cells in a novel human IL-15- transgenic NOG mouse. Sci Rep 7: 17230. https://doi.org/10.1038/s41598017-17442-7 10. Matsuda M, Ono R, Iyoda T, Endo T, Iwasaki M et al (2019) Human NK cell development in hIL-7 and hIL-15 knockin NOD/SCID/ IL2rgKO mice. Life Sci Alliance 2: e201800195. https://doi.org/10.26508/lsa. 201800195 11. Herndler-Brandstetter D, Shan L, Yao Y, Stecher C, Plajer V, Lietzenmayer M, Strowig T, de Zoete MR, Palm NW, Chen J, Blish CA, Frleta D, Gurer C, Macdonald LE, Murphy AJ, Yancopoulos GD, Montgomery RR, Flavell RA (2017) Humanized mouse model supports development, function, and tissue residency of human natural killer cells. Proc Natl Acad Sci U S A 114:E9626–E9634. https://doi.org/10.1073/pnas.1705301114 12. Sippel TR, Radtke S, Olsen TM, Kiem HP, Rongvaux A (2019) Human hematopoietic stem cell maintenance and myeloid cell development in next-generation humanized mouse models. Blood Adv 3:268–274. https://doi. org/10.1182/bloodadvances.2018023887 13. Wunderlich M, Chou FS, Sexton C, Presicce P, Chougnet CA, Aliberti J, Mulloy JC (2018) Improved multilineage human hematopoietic reconstitution and function in NSGS mice.

PLoS One 13:e0209034. https://doi.org/10. 1371/journal.pone.0209034 14. Rongvaux A, Willinger T, Martinek J, Strowig T, Gearty SV, Teichmann LL, Saito Y, Marches F, Halene S, Palucka AK, Manz MG, Flavell RA (2014) Development and function of human innate immune cells in a humanized mouse model. Nat Biotechnol 32:364–372. https://doi.org/10.1038/nbt.2858 15. Lopez-Lastra S, Masse-Ranson G, Fiquet O, Darche S, Serafini N, Li Y, Dusseaux M, Strick-Marchand H, Di Santo JP (2017) A functional DC cross talk promotes human ILC homeostasis in humanized mice. Blood Adv 1:601–614. https://doi.org/10.1182/ bloodadvances.2017004358 16. Yao LC, Aryee KE, Cheng M, Kaur P, Keck JG, Brehm MA (2019) Creation of PDX-bearing humanized mice to study immuno-oncology. Methods Mol Biol 1953:241–252. https:// doi.org/10.1007/978-1-4939-9145-7_15 17. Koskinen C, Persson E, Baldock P, Stenberg A, Bostrom I, Matozaki T, Oldenborg PA, Lundberg P (2013) Lack of CD47 impairs bone cell differentiation and results in an osteopenic phenotype in vivo due to impaired signal regulatory protein alpha (SIRPalpha) signaling. J Biol Chem 288:29333–29344. https://doi. org/10.1074/jbc.M113.494591

Chapter 6 Antibody–Oligonucleotide Conjugation Using a SPAAC Copper-Free Method Compatible with 10
Genomics’ Single-Cell RNA-Seq Dominic Paul Lee, Wang Jiehao Ray, Tan Pee Mei, Shawn Hoon, Jonathan Scolnick, and Gene W. Yeo Abstract Recent advances in multimodal approaches toward single-cell analyses present valuable data points that can complement standard flow cytometry data. In particular, the overlay of cell-surface proteome data with gene expression analysis presents a necessary advancement, particularly in the field of immunology. Here we describe a copper-free click chemistry method for the generation of antibody-oligonucleotide complexes and present the steps for its employment in the context of the 10
genomics droplet-based single-cell RNA-seq workflow, providing a method for coupling proteomic and transcriptomic analyses in an efficient and cost-effect manner. Key words Antibody conjugation, SPAAC, 10
Genomics, Multi-omics, Single-cell RNA-seq, Single-cell proteomics

1

Introduction Maturation of the single-cell RNA-sequencing (sc-RNA-seq) techniques has led to recent multimodal approaches to simultaneously detect protein and transcript abundance, allowing the overlaying of the two molecular datasets [1–3]. The biological insights brought about by these approaches are many; mRNA transcript levels detected through sc-RNA-seq do not always have a direct correlation with their corresponding protein levels. This is because tight regulation of mRNA translation is important for many biological processes. For instance, to enable a poised cell to halt mRNA translation and to only initiate protein production on cue from external stimuli and stressors. Next, differences in both transcript and protein degradation processes can also affect protein and mRNA level discrepancies [4–6]. In addition, RNA-only analyses

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_6, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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can face challenges when low transcript abundances result in transcript dropout events, a challenge that the sensitivity of protein detection can allay [7, 8]. The quantification of cell-surface protein markers is particularly useful for the characterizing of immune cells. Based on instructive differences in cell-surface markers, and backed by decades of flow cytometry research, protein profiling of immune cells facilitates cell-type identification, distinguishes cell linage relationships and functional meaning that may not be reflected at the mRNA level [9–11]. The multimodal single-cell RNA and proteome technique has shown to benefit from the shared strength of both approaches in identification and discovery of cell types and transcripts [2, 3, 12]. Through conjugation of DNA oligonucleotides with target antibodies [13–16], the immuno-PCR method enables the direct transfer of protein signal readout to a DNA level, also known as antibody-derived tags (ADTs), suitable for single-cell sequencing strategies. Although commercial kits are available for the production of antibody–oligonucleotide conjugates (AOCs), such kits can be costly, have chemistry not amenable to further optimization or not ideal for production of AOCs in a massive multiplex manner. We describe here a covalent method of DNA–antibody conjugation that can be employed with established antibodies used in flow cytometry, for use in complement with 10
Genomics 30 Reagent Kits. The method uses strain-promoted azide-alkyne cycloaddition (SPAAC) that is both efficient and cost-effective for DNA–antibody conjugation [17–19]. An additional advantage of the SPAAC method is that the conjugation of the antibody and oligonucleotide consists of two sequential crosslinking steps: (1) the functionalization of the antibody with a dibenzocyclooctyne (DBCO) moiety; and (2) the crosslinking of the functionalized antibody with an oligonucleotide via a copper-free click chemistry reaction. Thus, pre-functionalized antibodies with crosslinkers could be prepared and be used sequentially with different oligonucleotide sequences.

2

Materials

2.1 Buffers (See Note 1)

1. Antibody dilution buffer (ADB): Phosphate-buffered solution (PBS), 10 mM EDTA. 2. Phosphate-buffered saline: 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4. Dissolve 8 g of NaCl, 0.2 g of KCl, 1.44 g of Na2HPO4, and 0.24 g of KH2PO4 in 800 mL of distilled water. Adjust pH to 7.4 with HCl. Adjust the volume to 1 L with the addition of distilled water. 3. Equilibration buffer: 100 mM Sodium phosphate, 0.05% TWEEN 20, pH 7.4.

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4. Wash buffer: 100 mM Sodium phosphate, 300 mM NaCl, 0.05% TWEEN 20, pH 7.4. 5. Elution buffer: 100 mM Sodium phosphate, 300 mM NaCl, 250 mM imidazole, pH 7.4. 6. Cell blocking buffer (CBB): Phosphate-buffered solution (PBS), 2% bovine serum albumin (BSA), 1 mg/mL salmon sperm DNA, 0.03% sodium azide, 5% TruStain FcX (BioLegend). 7. Cell wash buffer (CWB): PBS, 2% BSA, 0.03% sodium azide. 8. Buffer EB: 10 mM Tris-HCl, pH 8.5. 2.2

Equipment

1. Thermomixer (Eppendorf, 5382000015). 2. NanoDrop 2000/2000c Spectrophotometer (Thermo Fisher Scientific, ND-2000/ND-2000C). 3. End-over-end mixer. 4. Countess 3 Automated Cell Counter (Thermo Fisher Scientific, AMQAX2000). 5. Qubit 4 Fluorometer (Thermo Fisher Scientific, Q33238). 6. Real-time qPCR machine. 7. Thermocycler. 8. Magnetic tube holder.

2.3

Other Materials

1. Flow cytometry-grade antibodies. 2. Ultracentrifugation spin columns (Amicon): 10 kDa Molecular weight cut-off (MWCO) (Merck Millipore, Burlington, MA, 0.5 mL-UFC501024, 4 mL-UFC801024). 3. 4 mM Tris(2-carboxyethyl) phosphine hydrochloride (TCEP): Obtained by diluting stock 0.5 M TCEP solution with ADB (see Note 2). 4. DNA LoBind® Tubes: 1.5 mL (Eppendorf, 0030108051). 5. 1.5 and 2 mL microcentrifuge tubes. 6. 10 mM Dibenzocyclooctyne-PEG4-maleimide (DBCOPEG4-Mal): Dissolve DBCO-PEG4-Mal in anhydrous dimethylformamide (DMF) to a final concentration of 10 mM (see Note 3). 7. 7K MWCO Zeba™ Spin Desalting Columns: 0.5 mL (Thermo Fisher Scientific, 89882). 8. 100 μM Azide-modified oligonucleotides (Integrated DNA Technologies). 9. Zn SepFast MAG: Magnetic immobilized metal affinity chromatography (IMAC) resin (Biotoolomics, 190104). 10. Qubit Protein Assay Kit (Thermo Fisher, Q33212).

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11. Single-cell suspensions (e.g., NK cells, peripheral blood mononuclear cells). 12. C-Chip Disposable DHC-N01).

Hemocytometer

(NanoEntek,

13. PCR 8-tube strips (Eppendorf, EP0030124359). 14. DynaMag™-96 Bottom Magnet (Thermo Fisher Scientific). 15. 80% Ethanol (EtOH). 16. SPRIselect reagent (Beckman Coulter, B23319). 17. KAPA HiFi HotStart Readymix (2
) (KAPA Biosystems, KK2600). 18. EvaGreen Dye (20
) (Biotium, #31000).

3

Methods All procedures are carried out at room temperature unless otherwise specified.

3.1 Preparing Antibody

1. Dilute 100 μg of antibody in ADB to a final volume of 4 mL. Pipette well to mix (see Note 4). 2. Transfer the diluted antibodies to an Amicon 4 mL 10 kDa ultracentrifugation spin column. Centrifuge at 5000
g for 22 min and discard the flow-through. Repeat the wash step by adding another 4 mL of ADB to the spin column and centrifuge at 5000
g for another 22 min (see Note 5). 3. Transfer the concentrated Eppendorf tube.

3.2 Antibody Disulfide Bond Cleavage

antibody

to

a

1.5

mL

1. Add equal volume of freshly prepared 4 mM TCEP to concentrated antibody and pipette to mix well (see Notes 6 and 7). 2. Incubate the reaction at 37  C for 30 min in a thermomixer at 600 rpm (see Note 8). Perform a brief centrifugal spin to remove liquid from the lid. 3. Dilute the TCEP treated antibody further in ADB to a final volume of 450 μL and pipette well to mix. 4. Apply the diluted antibody to an Amicon 0.5 mL 10 kDa ultracentrifugation spin column at 14,000
g at 4  C or 5 min. Discard flow-through. 5. Add 350 μL of ADB to the column and centrifuge at 14,000
g at 4  C for 5 min to wash the antibody from residual TCEP. Perform this wash step twice. 6. Transfer the column to a clean 2 mL tube and centrifuge at 1000
g at 4  C for 1 min to remove excess buffer.

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7. Discard flow-through and transfer washed Ab from the column to a clean 1.5 mL DNA LoBind microcentrifuge tube. The washed antibody should be about 50–100 μL (see Note 9). 3.3 Antibody-Crosslinker Conjugation

1. Add 3.0 μL of 10 mM DBCO-PEG4-Mal to the entire volume of washed antibody from step 7 in Subheading 3.2 (see Note 10). 2. Mix and incubate for 2 h at 37  C with mild agitation. 3. During the incubation, prepare a 0.5 mL 7 kDa MWCO Zebaspin desalting column by placing the spin column in a 1.5 mL Eppendorf tube and spin at 1500
g for 1 min to clear the storage solution. Discard the flow-through and add 300 μL of PBS to the column and centrifuge the column at 1500
g for 2 min. Repeat this step once. 4. Add the antibodies from step 2 into the washed column from step 3. Place the column in a clean 1.5 mL Eppendorf tube. 5. Centrifuge the column at 1500
g for 2 min to elute DBCOPEG4-Mal conjugated antibodies. 6. Determine antibody concentration by NanoDrop spectrometer at 280 nm (see Note 11).

3.4 Antibody–Oligonucleotide Conjugation

1. Add 10 μL of 100 μM azide-modified oligonucleotides to the washed antibodies from step 5 in Subheading 3.3 (see Fig. 1 and Table 1). Incubate overnight at 4  C with end-over-end rotation for antibody–oligonucleotide conjugate (AOC) formation (see Note 12).

3.5 Antibody–Oligonucleotide Purification

1. Prepare Zn SepFast MAG resin beads (hereafter referred to as “beads”) by first pipetting beads well to resuspend and transfer 150 μL into a 1.5 mL DNA loBind tube. Add 750 μL equilibrium buffer to the beads and pipette to mix well. Perform a brief centrifuge spin and place the tube in a magnetic tube holder for 1 min. Discard the supernatant. Repeat this washing step for a total of three times. 2. Separately, add 150 μL equilibrium buffer to the AOCs from step 1 in Subheading 3.4. Pipette to mix well and add to the washed beads. 3. Allow binding to occur at 4  C for 2 h with gentle end-overend rotating. 4. Pulse centrifuge to collect any beads of the lid of the tube and place the tube on a magnetic tube holder for 1 min and discard the supernatant. 5. Resuspend beads containing bound AOCs in 500 μL of wash buffer and place the tube on gentle end-over-end rotation for 5 min. Pulse centrifuge to collect any resin beads of the lid of

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O

O

O

N

O N

SH

N3 O

N H

O 3

DBCO

O

Maleimide

Azide-modified Oligonucleotide

DBCO-PEG4-Mal crosslinker

Antibody

N

O

S

O

O O 3

N

N

O N

N

N H

O

O

Stable Antibody-Oligo conjugate

Fig. 1 Production of stable ADTs based on strain-promoted azide-alkyne cycloaddition (SPAAC) reaction. TCEP reduction of disulfide bonds produces reactive sulfhydryls (-SH) for alkylation with reactive maleimide on DBCO-PEG4-Mal crosslinker to produce the functionalized antibody. The addition of 50 azide-modified oligonucleotides with functionalized antibody crossed links with DBCO moiety to form a stable antibodyoligo conjugate Table 1 Modified oligonucleotide and primer sequences Oligos and primers Azide-modified oligo 50 -/5AzideN/ GACTGGAGTTCAGACGTGTGCTCTTCCGATCT -NNNNNNNN-BAAAAAAAAAAAAAAAAAAAAAAAAAAA-30 Forward ADT qPCR GACTGGAGTTCAGACGTGTGCTCTTC primer Reverse ADT qPCR primer

AATGATACGGCGACCACCGAGATCTACAC

ADT P5 primer

TCTTTCCCTACACGACGCTCTTCCGAT*C*T

ADT P7 primer

50 -CAAGCAGAAGACGGCATACGAGAT - index - GTGACTGGAGTTCA GACGTGTGCTCTTC-30

“-NNNNNNNN-” denotes 8-basepair ADT specific barcode “B” denotes C or G or T nucleotide “*” denotes phosphorothioate bond modification “/5azideN/” denotes 50 azide modification

the tube. Place the tube on a magnetic holder for 1 min and discard the supernatant. 6. Repeat step 5 two more times for a total of 3 washes.

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7. Resuspend beads, now containing bound AOCs, in 150 μL of elution buffer and place on a gentle end-over-end rotator for 1 h to elute. Pulse centrifuge to collect any beads of the lid of the tube. 8. Place the tube to a magnetic holder and transfer the supernatant containing the AOCs to a new tube. 9. Prepare a pre-equilibrated 0.5 mL 7 kDa Zebaspin desalting column according to step 3 in Subheading 3.3. 10. Add the eluted AOCs from step 9 to the prepared column and centrifuge at 1500
g for 2 min. 11. The elute contains purified AOCs and can be stored at 4  C (see Note 13). 12. Measure conjugated antibodies concentration using a protein assay kit (see Note 14). 3.6 Cell Labeling with AOCs

1. Prepare 20–100 ng of AOCs in 50 μL of CBB and pipette to mix well (see Note 15). 2. Separately, prepare about one million single cells in suspension and wash in PBS twice by centrifugation at 250
g for 5 min. 3. Remove the supernatant and resuspend the cells in 50 μL of CBB (see Note 16). 4. Add 50 μL of prepared AOCs from step 1 to 50 μL of resuspend cells and pipette gently to mix. Incubate cell suspension on ice for 30 min. 5. Collect cells using centrifugation at 250
g for 5 min at 4  C and wash cells 3 times with 300 μL chilled cell wash buffer. 6. Resuspend the cells in 500 μL of chilled PBS. Verify cell count again with a hemocytometer. 7. At this point, the DNA-barcoded cells are brought to the 10
Genomics scRNA-seq platform for droplet-based single-cell barcode generation (see Fig. 2, see Note 17).

3.7 ADT Library Generation

1. Add 60 μL of SPRIselect reagent to 100 μL of the amplified cDNA in an 8-tube strip and pipette to mix well (see Note 18). 2. After incubating for 5 min, place the tube on a Dynamag until the solution clears. Do not discard the supernatant. Transfer 120 μL of supernatant containing ADT-derived cDNA to a new DNA loBind tube (see Note 19). 3. Add 140 μL of SPRIselect reagent to the tube and mix well. 4. After incubating for 5 min, place the tube on a magnetic separation rack.

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Fig. 2 ADT sequences and library workflow in conjunction with 10
Genomics 30 RNA-seq. Azide-modified oligos contain Poly(dA) tail for hybridization to poly(dT) on Gel Bead Primers, antibody specific nucleotide barcodes, and Illumina Truseq Read 2 sequences for subsequent library amplification. Gel bead primers contain Illumina Truseq Read 1 sequences, 16 bp bead specific 10
barcodes, 12 bp Unique Molecular Identifiers (UMI) for the identification of unique mRNA/ADT molecules, and a 30 bp 30 Poly(dT) sequence for capture. Subsequent to cell lysis is reverse transcription (RT) of the captured ADT and endogenous polyadenylated mRNA (highlighted in Box). 0.6
SPRI bead clean-up of the generated cDNA fragments separates single cell barcoded ADTs that are less than 300 bp from full length mRNA cDNA fragments captured in SPRI bead pellet

Table 2 qPCR mixture Reagent

Amount per sample (μL)

KAPA HiFi Readymix (2
)

5

Forward ADT qPCR primer (10 μM) (Table 1)

0.2

Reverse P5 ADT qPCR primer (10 μM) (Table 1)

0.2

EvaGreen (20
)

0.5

Water

3.1

ADT library

1

Total

10

5. Discard the supernatant and add 100 μL of 80% EtOH to the tube. After 30 s of incubation, discard the 80% EtOH (see Note 20). 6. Repeat step 5 twice. 7. Air dry to remove residual ethanol for 5 min (see Note 21).

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Table 3 qPCR program Temp ( C)

Time

1

95

3 min

2

98

20 s

3

65

15 s

4

72 (READ)

15 s

5

Go to step 2 for a total of 42 cycles

Fig. 3 Cycle threshold readout of ADT libraries. Maximum qPCR cycles required are inferred from amplification plateau, indicated here in red arrows. We deduct 4 cycles from the plateau number as an optimum number for the final library

8. Elute the ADT-derived cDNA in 25 μL of buffer EB. 9. Mix 5 μL of 2
KAPA HiFi Readymix, 0.2 μL of 10 μM ADT qPCR primer, 0.2 μL of 10 μM ADT qPCR Rev primer, 0.5 μL of 20
EvaGreen, 3.1 μL of PCR grade water, 1 μL of ADT library (Table 2). 10. Set up the mixture on a real-time qPCR machine with the program shown in Table 3 to determine adequate PCR cycles for the ADT library (see Note 22 and Fig. 3). 3.8 Final ADT Library Amplification and Clean-Up

1. Mix 25 μL of KAPA HiFi Readymix, 1 μL of 10 μM ADT P5 primer, 1 μL of 10 μM ADT P7 primer, 23 μL of the ADT library from step 3 of Subheading 3.7 (Table 4). 2. Set up the mixture on a thermocycler with the program shown in Table 5 with the number of PCR cycles as determined in step 4 in Subheading 3.7.

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Table 4 ADT library PCR mixture Reagent

Amount per sample (μL)

KAPA HiFi Readymix (2
)

25

ADT P5 primer (10 μM)

1

ADT P7 primer (10 μM) (Table 1)

1

ADT library

23

Total

50

Table 5 ADT library PCR program Step

Temp ( C)

Time

1

95

3 min

2

98

20 s

3

65

15 s

4

72

15 s

5

Go to step 2

6

72

1 min

7

4

Infinite hold

3. Add 80 μL of SPRIselect reagent to the 50 μL of PCR reaction (1.6
SPRI:sample ratio). Pipette to mix well and incubate reaction for 5 min and place the tube on a magnetic separation rack. 4. Perform steps 5–7 in Subheading 3.7 to perform SPRIselect bead clean-up. 5. Elute the library in 20 μL of buffer EB.

4

Notes 1. All buffers are prepared with ultrapure nuclease-free water and reagents. 2. 4 mM TCEP solution is prepared by diluting 8 μL of 0.5 M TCEP with 992 μL of ADB. 3. Inclusion of Peg-4 in the crosslinker increases water solubility of the DBCO-PEG4-Mal molecule to aid functionalization of the antibody.

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Table 6 Recommended flow cytometry antibody clones CD3e

UCHT1

CD38

HIT2

CD56

REA196

CD62L

DREG-56

CD7

CD7-6B7

CD16

3G8

CD94

HP-3D9

CD45

HI30

4. Although signal acquisition method is different between ADT and flow cytometry, the guiding principles of antibody choice are similar. We recommend the use of monoclonal antibodies that have been validated for use in flow cytometry where possible. We recommend the antibody clones for NK cells shown in Table 6. 5. The antibody has to be purified of any contaminants such as sodium azide that may affect downstream conjugations using molecular weight-based centrifugation spin columns. 6. To prepare the antibody for SPAAC conjugation, TCEP is added as a reducing agent for the selective cleavage of disulfide bonds. 7. For utilization of LEAF (Low Endotoxin, Azide-Free) antibodies from Biolegend, concentration of antibodies may be skipped. Prior to TCEP treatment, add 2 μL of 0.5 M EDTA to 100 μL (100 μg) of LEAF antibodies, followed by the addition of equal volume 4 nM TCEP. 8. Be careful not to exceed incubation time here. 9. The TCEP treated, reduced antibodies should be washed and brought to antibody-crosslinker conjugation immediately to avoid –SH bond oxidation. 10. DBCO-PEG4-Mal is antibody here.

added

in molar excess

to the

11. Antibody concentrations are calculated using the mass extinction coefficient of 14 at 280 nm for a 1% (i.e., 10 mg/mL) IgG solution. The mass extinction coefficient value is the A280 of a 10 mg/mL solution in a 1-cm path. Most mammalian antibodies have mass extinction coefficients (percentage) of 12–15. The concentration of the antibody can be determined as follows: Concentration (mg/mL) ¼ (Absorbance value at 280 nm)/Protein extinction coefficient (%)
10 mg/mL.

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12. Functionalized antibodies are conjugated to azide-modified oligos with the latter added in saturation. 13. The antibodies can be supplemented with sodium azide (0.05%) and BSA (1 μg/μL) for stable storage at 4  C until ready to use. 14. Various methods are suitable for this step of quantification of the AOC concentration, including Bradford assay and NanoDrop. We find that the Qubit Fluorometer Protein Assay Kit to be an accurate and quick method. 15. Similar to the use of fluorochrome conjugated antibodies in flow cytometry, successful employment of AOCs to target cells is sensitive to epitope expression level, cell composition, and number of cells used [12, 20]. As such, optimal antibody concentration of AOCs is highly analogous to concentrations used for flow cytometry for the same antibody clone. In addition, as a general rule, we find that using antibody concentrations 10-fold lesser for ADT cell labeling than antibody concentrations used for flow cytometry can reduce “noise” caused by unspecific binding while retaining signal intensity. 16. If working with adherent cells, we recommend usage of 40 μm cell strainers to filter cell clumps before cell counting and incubation with antibodies. 17. At this point, cells are brought to the 10
Genomics scRNAseq platform for droplet-based single-cell barcode generation according to manufacturer’s instructions. In brief, Gel Beadsin-emulsion (GEMs) results in droplet formation containing single cells with Gel Bead primers. Cells are lysed in individual droplets. The gel bead primers containing Poly(dT) and unique molecular identifier (UMI) barcodes amplify both polyadenylated mRNA and ADTs, enabling single-cell specific barcode labeling and identification. 18. After cDNA amplification step, the cDNA contains both mRNA-derived cDNA and ADT-derived cDNAs. This SPRIselect reagent step separates ADT-derived cDNA (300 bp) for separate amplification. 19. Amplified mRNA-derived cDNA is bound to the SPRI beads. 20. Do not resuspend beads in 80% EtOH when washing the beads. Keep beads on magnetic rack and carefully apply EtOH to the opposite face of the tube from the beads. 21. Ensure EtOH is removed completely. To do so, after removing the EtOH with a 200 μL pipette tip, perform a brief centrifugal spin, apply the beads to the magnetic rack again and use a 10 μL laboratory pipette to remove residual EtOH that may be present at the bottom of the 8-tube strip.

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22. Deduct “4” cycles from that number to determine the optimum number of cycles required to amplify each sample at the subsequent PCR step, Subheading 3.8, step 1.

Acknowledgments As a Visiting Professor at the National University of Singapore, G. W.Y. is supported by the Singapore National Research Foundation and G.W.Y.’s interest has been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies S.H. is supported by Singapore’s A*STAR Industry Alignment Fund (IAF-PP H17/01/a0/012). Illustrations created with BioRender.com References 1. Lee J, Hyeon DY, Hwang D (2020) Single-cell multiomics: technologies and data analysis methods. Exp Mol Med 52:1428–1442. https://doi.org/10.1038/s12276-0200420-2 2. Peterson VM, Zhang KX, Kumar N et al (2017) Multiplexed quantification of proteins and transcripts in single cells. Nat Biotechnol 35:936–939. https://doi.org/10.1038/nbt. 3973 3. Stoeckius M, Hafemeister C, Stephenson W et al (2017) Simultaneous epitope and transcriptome measurement in single cells. Nat Methods 14:865–868. https://doi.org/10. 1038/nmeth.4380 4. Hershey JWB, Sonenberg N, Mathews MB (2012) Principles of translational control: an overview. Cold Spring Harb Perspect Biol 4: a011528–a011528. https://doi.org/10. 1101/cshperspect.a011528 5. Truitt ML, Ruggero D (2016) New frontiers in translational control of the cancer genome. Nat Rev Cancer 16:288–304. https://doi.org/10. 1038/nrc.2016.27 6. Istomine R, Pavey N, Piccirillo CA (2016) Posttranscriptional and translational control of gene regulation in CD4 + T cell subsets. J Immunol 196:533–540. https://doi.org/10. 4049/jimmunol.1501337 7. Qiu P (2020) Embracing the dropouts in single-cell RNA-seq analysis. Nat Commun 11:1169. https://doi.org/10.1038/s41467020-14976-9 8. Mair F, Erickson JR, Voillet V et al (2020) A targeted multi-omic analysis approach measures protein expression and low-abundance transcripts on the single-cell level. Cell Rep

31:107499. https://doi.org/10.1016/j.cel rep.2020.03.063 9. McKinnon KM (2018) Flow cytometry: an overview. Curr Protoc Immunol 120:5.1.1. https://doi.org/10.1002/cpim.40 10. Landhuis E (2018) Single-cell approaches to immune profiling. Nature 557:595–597. https://doi.org/10.1038/d41586-01805214-w 11. Gibellini L, De Biasi S, Porta C et al (2020) Single-cell approaches to profile the response to immune checkpoint inhibitors. Front Immunol 11:490. https://doi.org/10.3389/ fimmu.2020.00490 12. Stoeckius M, Zheng S, Houck-Loomis B et al (2018) Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics. Genome Biol 19:224. https://doi.org/10.1186/s13059-0181603-1 13. Sano T, Smith C, Cantor C (1992) ImmunoPCR: very sensitive antigen detection by means of specific antibody-DNA conjugates. Science 258:120–122. https://doi.org/10.1126/sci ence.1439758 14. Becer CR, Hoogenboom R, Schubert US (2009) Click chemistry beyond metalcatalyzed cycloaddition. Angew Chem Int Ed 48:4900–4908. https://doi.org/10.1002/ anie.200900755 15. Dugal-Tessier J, Thirumalairajan S, Jain N (2021) Antibody-oligonucleotide conjugates: a twist to antibody-drug conjugates. J Clin Med 10:838. https://doi.org/10.3390/ jcm10040838

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16. Adler M, Wacker R, Niemeyer CM (2008) Sensitivity by combination: immuno-PCR and related technologies. Analyst 133:702. https://doi.org/10.1039/b718587c 17. Manova RK, Pujari SP, Weijers CAGM et al (2012) Copper-free click biofunctionalization of silicon nitride surfaces via strain-promoted alkyne–azide cycloaddition reactions. Langmuir 28:8651–8663. https://doi.org/10. 1021/la300921e 18. van Hest JCM, van Delft FL (2011) Protein modification by strain-promoted alkyne-azide

cycloaddition. ChemBioChem 12:1309–1312. https://doi.org/10.1002/cbic.201100206 19. Gong H, Holcomb I, Ooi A et al (2016) Simple method to prepare oligonucleotideconjugated antibodies and its application in multiplex protein detection in single cells. Bioconjug Chem 27:217–225. https://doi.org/ 10.1021/acs.bioconjchem.5b00613 20. Buus TB, Herrera A, Ivanova E et al (2021) Improving oligo-conjugated antibody signal in multimodal single-cell analysis. elife 10: e61973. https://doi.org/10.7554/eLife. 61973

Chapter 7 Methods to Analyze the Developmental Trajectory of Human Primary NK Cells Using Monocle and SCENIC Analyses Dandan Wang, Robert Burns, Mohamed Khalil, Ao Mei, Elaheh Hashemi, and Subramaniam Malarkannan Abstract Development of novel cellular therapies based on primary human NK cells is under active investigation. Human NK cells are comprised of distinct subsets with high transcriptomic heterogeneity. Unique methodologies are being developed to determine the transcriptomic profiles of human NK cells. NK cells account for 10–20% of total lymphocytes in the human peripheral blood, which mediates anti-tumor and anti-viral effector functions. Therapeutic success in the clinic depends on a better understanding of the single-cell transcriptome of human NK cell subsets. Moreover, a better understanding of the transcriptional network that regulates NK cell development, subset specification, and terminal maturation is obligatory for their in vitro generation and expansion toward clinical utilization. Here, we describe the procedure for single-cell RNA-sequencing of human NK cells and strategies for bioinformatic analyses. This protocol provides a data analysis roadmap for investigators who work on the basic biology and therapeutic applications of human NK cells. Key words Human NK cells, scRNAseq, Development, Trajectory, Regulon

1

Introduction Natural killer (NK) cells are the major lymphocytes of the innate immune system, which mediates cytotoxicity and produces proinflammatory cytokines without prior sensitization [1, 2]. Although cell surface markers have been widely used to define the developmental stages of NK cells [3], there are inherent limitations associated with them. Cell surface markers-based analyses of NK cell development do not provide the associated molecular mechanisms and do not fully explain the spectrum of developmental heterogeneity. Use of cytometry by time of flight (CyTOF), which combines flow cytometry and mass-spectrometry, predicted 6000–30,000 distinct NK cell phenotypes based on 35 different cell surface antigens [4]. While this finding is exceptional, the transcriptional

Noriko Shimasaki (ed.), Natural Killer (NK) Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2463, https://doi.org/10.1007/978-1-0716-2160-8_7, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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mechanisms that govern the generation of such a divergent heterogeneity of NK cells are not understood. A recent technological breakthrough, single-cell RNA-sequencing (scRNA-seq), provides a revolutionized transcriptomic profile for an individual cell, allowing scientists to study the cellular heterogeneity, development, and activation states in unprecedently high resolution [5–7]. Transcriptomic profiling offers a more reliable definition of cell identities based on the expression of thousands of transcripts at a single-cell level. Work from our laboratory defined the human NK cell heterogeneity based on their transcriptomic profiles [5]. The bioinformatics methods to analyze the scRNA-seq data are being developed in multiple platforms with different scripting languages. The widely used toolkits include Seurat [8] (https://www.biorxiv.org/con tent/10.1101/2020.10.12.335331v1) and Scanpy [9], which are applied to control the quality, pre-process, visualize, and cluster the scRNA-seq data based on the gene expression profiles. Seurat was developed as a simple workflow to begin the bioinformatic analyses using the computational language of R. Scanpy, a Python-based scalable toolkit, is able to analyze the large dataset, for instance, more than one million cells. Further sophisticated analyses are being developed to help scientists define inter-cell transcriptomic and transcriptional relationships in terms of developmental continuity and cell–cell interactions. For example, to understand the development trajectory, unique algorithms are being used to infer the stage-specific and inter-stage specific transcriptomes based on scRNA-seq data, including Monocle [10], RNA Velocity [11], partition-based graph abstraction (PAGA) [12], and URD [13]. To predict the interaction of transcription factors with their target genes and their transcriptional regulons from scRNA-seq data, SCENIC (single-cell regulatory network inference and clustering) [14] is used to build the gene regulatory network, identify regulons, and score the regulon activity. The knowledge gap between biological and bioinformatic analyses hinders researchers to better perform and understand these data. Recent developments in various computing languages, platforms, and program packages help to understand the biological processes of distinct datasets. Here, we will summarize the workflow for scRNA-seq analyses with R-based Seurat, Monocle, and SCENIC for investigators who work on immune cells, including NK cells.

2

Materials

2.1 General Supplies/Reagents

1. 1
Phosphate-buffered saline (1
PBS). 2. Ficoll (Lymphoprep, GE life science). 3. Fetal bovine serum (FBS).

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83

4. Fluorescence-activated cell sorting (FACS) buffer: 1
PBS, 1% FBS. 5. 0.2N sodium hydroxide (NaOH). 6. 200 mM Tris-HCl, pH 7.0. 7. 70 μm cellular filters. 2.2 Human Peripheral Blood Mononuclear Cells for scRNA-seq Library Generation

1. Human buffy coat obtained from IRB-approved sources. 2. Cell sorter (e.g., BD FACSAria III sorter (BD Biosciences, San Jose, CA)). 3. Chromium Single-cell 30 Reagent Kit (10
genomics, Pleasanton, CA). 4. KAPA SYBR FAST qPCR Kits: KAPA SYBR FAST qPCR Kits Master Mix, Primer Premix, KAPA SYBR FAST ROX Low (Roche, Basel, Switzerland). 5. NextSeq 500/550 High Output Kit v2.5 (150 Cycles) (Illumina, San Diego, CA), which provides hybridization buffer (HT1). 6. 10 mM Tris-HCl (pH 8.2). 7. Thermal cycler. 8. QuantStudio™ 7 Flex Real-Time PCR System. 9. Illumina NextSeq 550.

2.3 Human Antibodies (FACS Buffer as Dilution Buffer)

1. Anti-human CD3ε-Pacific blue. 2. Anti-human CD34-Pacific blue. 3. Anti-human CD14-Pacific blue. 4. Anti-human CD19-Pacific blue. 5. Anti-human CD20-Pacific blue. 6. Anti-human CD45-PE. 7. Anti-human CD7-APC.

2.4 Bioinformatic Software

1. Align the human scRNA-seq data with GRCH38 as the reference based on cell ranger (cell ranger version 3.0.2) (https:// support.10xgenomics.com/single-cell-gene-expression/soft ware/pipelines/latest/what-is-cell-ranger). 2. Download and install R (see Note 1). 3. Download and install R-studio (see Note 1). 4. Install package of “BiocManager” (see Supplement 1). 5. Install package of “dplyr,” which is a grammar of data manipulation for R language (https://www.rdocumentation.org/ packages/dplyr/versions/0.7.8) (see Supplement 1).

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6. Install the proper version of “Seurat” packages (https:// satijalab.org/seurat/articles/install.html) (see Supplement 1). We are using version 3.2.2. 7. Seurat workflow to start the quality control, pre-processing, visualization, and clustering (https://satijalab.org/seurat/ articles/pbmc3k_tutorial.html) (also see Supplement 1). 8. Install package of Clustree (https://github.com/lazappi/ clustree) (see Supplement 1). 9. Install package of Monocle (http://cole-trapnell-lab.github. io/monocle-release/docs/) (see Supplement 1). 10. Install package of SCENIC (https://github.com/aertslab/ SCENIC) and its related packages (see Supplement 1).

3

Methods

3.1 Cell Preparation, scRNA-seq Library Generation, Sequencing, and Data Alignment

1. Dilute the buffy coat of healthy human donors with PBS as 1:1. Load 20 mL of Ficoll for every 20–25 mL diluted buffy coat. Spin down at 300
g, 20 min without break. 2. Collect peripheral blood mononuclear cells (PBMCs) and wash the cells. 3. Stain the PBMCs with anti-CD3ε, anti-CD34, anti-CD14, anti-CD19, anti-CD20, anti-CD45, and anti-CD7 antibodies (diluted in 1:200 with FACS buffer, 2 μg/mL for each as final) at 4  C for 20 min. Wash twice with FACS buffer and sort CD3εCD34CD14CD19CD20CD45+CD7+ population from a lymphocyte using a cell sorter. Collect the sorted cells into 1.5 mL Eppendorf tube with 200 μL of pure FBS to keep good cell viability. 4. Generate 30 single-cell RNA-seq library using Chromium Single-cell 30 Reagent Kit. 5. Add 1 mL of Primer Premix (10
) to the 5 mL of KAPA SYBR FAST qPCR Kits Master Mix (2
) in KAPA SYBR FAST qPCR Kits and mix thoroughly. Mix 12 μL of the KAPA SYBR FAST qPCR Master Mix with Primer Premix, 0.4 μL of ROX Low, 3.6 μL of PCR-grade water, and 4 μL of each sample or standard. The concentration range of six standards provided by this library quantification kit ranges from 0.2 fM to 20 pM. Run qPCR assay in a real-time Thermal Cycler and calculate the sample concentration based on the standard curve. 6. Dilute the sample to 4 nM with the 10 mM Tris-HCl (pH 8.2). Pool 5 μL of each 4 nM sample in a 1.5 mL tube. 7. Denature the pooled sample with 5 μL of 0.2N NaOH for each sample for 5 min. Add 5 μL of 200 mM Tris-HCl pH 7, vortex, and briefly centrifuge.

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8. Dilute the denatured 4 nM libraries with 985 μL of prechilled hybridization buffer (HT1) to a final concentration of 20 pM. 9. Further dilute 117 μL of the denatured 20 pM libraries with 1183 μL of prechilled HT1 buffer to a final concentration of 1.8 pM. 10. Sequence the cDNA library via Illumina NextSeq 550 and acquire FASTQ files from Base Space account. 11. Align the sequence data based on Cell Range version 3.0.2 through the terminal command. Here is the example we used: cellranger count --transcriptome¼/path/to/ReferenceGenome/ refdata-cellranger-GRCh38-3.0.0 --id¼sample_ID --fastqs¼/ path/to/this/sample/fastq/file --sample¼sample_name --expectcells¼5000 --localmem¼96 --localcores¼the_computer_cores. Find the file named by the “filtered_feature_bc_matrix” from the each aligned sample files, which is the data read and analyzed by Seurat. 3.2 Data Analyses Using Seurat

Quality control, normalization, visualization, and clustering of the scRNA-seq data based on the gene expression profile (see Supplement 2 for the detailed code). 1. Load the library of “dplyr” and “Seurat.” Import the data to the R-Studio. 2. Following the standard workflow of the Seurat guided clustering tutorial (see step 5 in Subheading 3.2), filter cells that expressed gene numbers 2500 and remove cells that have >5% of mitochondrial transcripts. 3. Log normalize and scale the gene expression values for each cell by a factor of 10,000. 4. Scale and regress the gene expression values based on the number of genes in each cell (nFeautre_RNA), number of UMIs (unique molecular indexes) per cell (nCount_RNA), and the cell mitochondrial transcript content (“percent.mt”) to eliminate the bias from cellular library size or mitochondrial genes (see Note 2). Also, scale the donor IDs to minimize the inherent variance among individuals. 5. Identify highly variable features by conducting the function of FindVariableFeatures. Under this function, choose top variable features from vst, mean.var.plot, or dispersion (see Note 3) as selection.method. 6. Conduct linear dimensional reduction and pick a certain number of principal components (PCs) as the dimensionality of the dataset for the clustering analyses. Choose the number when the number of PCs reached the baseline of the standard deviation in the Elbow plot.

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7. Decide the cluster resolution where a higher number results in more clusters (see Note 4). 8. Perform non-linear dimensional reduction by RunUMAP (UMAP, uniform manifold approximation, and projection for dimension reduction) to visualize the clustering result. 3.3 Data Analyses Using Monocle 2

To determine the trajectory of NK cell development (see Supplement 3 for the detailed code). 1. Load the required libraries “Seurat,” “dplyr,” “monocle,” and “reshape2” (see Note 5). 2. Following the monocle 2 tutorial from Cole Trapnell lab, import the processed data from Subheading 3.2, convert the data to the format fitting in the Monocle, and filter low-quality cells by undergoing the function of newimport, estimateSizeFactors, estimateDispersions, and detectGenes. 3. Pick up the ordering genes for the cell clustering in the trajectory (see Note 6). The method we used is to conduct the function of FindAllMarkers and use the significant differential expression genes (see Note 6) from each cluster as the ordering genes. Filter the replicated genes from different clusters by the function of unique. The picked genes can be visualized as Fig. 1a. 4. Order cells using the selected genes under the function of setOrderingFilter. The function of plot_ordering_genes helps to visualize the amount and location of the picked genes. 5. Click the function line of reduceDimension where the object is with reduction_method ¼ “DDRTree.” Conduct the orderCells function. 6. Plot the trajectory of the cells under the function of plot_cell_trajectory. We can separate the figures with the option of color_by ¼ “seurat_clusters” or “orig.ident” or “Pseudotime.” The cell cluster based and cell state based trajectory figures are shown in Fig. 1b, c.

3.4 Data Analyses by Using SCENIC

The cis-regulated regulons (see Supplement 4 for the detailed code). 1. Load the required libraries: “Seurat,” “SCENIC,” “AUCell,” “RcisTarget,” “scales,” and “feather.” 2. Extract the gene expression matrix and associate each cell group with each color. 3. Set up the organism and directory of the cisTarget databases in SCENIC and initialize with these settings under the function of “initializeScenic” to keep the environment consistent in multiple steps (see Note 7).

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Fig. 1 Single-cell trajectory analysis on human peripheral blood NK cells. (a) The highlight dots mark the genes that are used to cluster cells and set up the trajectory. These genes are chosen by setting up the cutoff of p_val_adj 0.25 under the function of FindAllMarkers. (b) Cells are ordered along the trajectory based on DEGs from each cluster. (c) The cell trajectory is separated into five cell states by two branch points, 1 and 2

4. Filter genes expressed in low levels or in few cells by the function of geneFiltering, which includes the total number of reads per gene (the reads are >3 in 1% of the cells) and the number of cells expressed the gene (the genes are detected in >1% of the cells). 5. To deduce the TFs based on the expression of their targets, the co-expression network is conducted under the function of runGenie3 (take more computer cores and time to run). The co-expression modules are created by conducting the function of runSCENIC_1_coexNetwork2modules with the output of the runGenie3. 6. Conduct the function of runSCENIC_2_createRegulons and runSCENIC_3_scoreCells on the co-expression modules to build and score the regulons (GRN).

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Fig. 2 SCENIC results from single-cell SCENIC analysis on human peripheral blood NK cells. (a) Regulon activity is calculated by the “Area Under the Curve” (AUC). The higher value (the red color) indicates more genes in the regulon are expressed in that cell. (b) Binary regulon activity matrix is generated based on the normalized AUC value. Cluster labels are from clustering result of Seurat analyses. Black square indicates the active regulons, and white stands for the inactive regulons

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7. Set up Area Under the Curve (AUC) threshold to determine which regulon is active in a specific cell state. The possible threshold is automatically calculated by AUCell. This threshold is recommended to be manually adjusted before proceeding to the binarization. The threshold to get regulon on/off to cluster cells is based on the GRN activity. The AUC activity is shown in Fig. 2a. 8. Visualize cell states and GRN activity by tsneAUC. Different options can be used to evaluate the stability of the cell states (e.g., choose all the regulons or only high-confidence regulons by onlyHighConf ¼ TRUE). 9. Binarize the AUC by conducting runSCENIC_4_aucell_binarize and generate binary heatmaps for different cell states by the function of pheatmap. (Require the loading of the library of pheatmap. Correlated regulon, all regulons, or 1% regulons can be chosen to draw the heatmap.) The binary heatmap is shown in Fig. 2b.

4

Notes 1. Download the R based on the computer operation system from the website: https://cran.r-project.org/ and follow the instruction; download the R-studio from https://www. rstudio.com/products/rstudio/ following the instruction. 2. nFeature_RNA means the number of genes in each cell. percent.mt is the percentage of mitochondria genes in each cell. nCount_RNA stands for the total number of molecules detected within a cell. 3. Three selection methods, vst, mean.var.plot, and dispersion, use different ways to calculate variances. A detailed explanation can be found under the function of FindVariableFeatures. 4. Clustree package [15] is helpful to decide on the resolution. Usually, choose the one that a higher resolution did not cause increasing clusters. The result of clustering trees shows the interactions of different clusters under multiple resolutions. This helps to visualize how cells move as the cluster number increases, and decide the resolution. 5. “reshape2” library helps import and manipulate data. 6. There are multiple ways to pick up ordering genes that significantly affect the trajectory, including picking up all genes that pass a given threshold or the top 1000 most significant genes by adjusted p-value. We pick up significant differential expression genes from each Seurat cluster by setting up the cutoff of p_val_adj 0.25 under the function of FindAllMarkers.

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7. The initialization step takes more computer cores to run. Different organisms require the correct database as a reference. The currently available databases are for humans (hgnc), mice (mgi), and drosophila melanogaster (dmel). cisTarget databases can be downloaded from https://resources.aertslab. org/cistarget/, and the database we used is hg19-500b*pupstream-7species.mc8nr, and hg19-tss-centered-5kb-7species. mc8nr.

Acknowledgements We dedicate this work to our inspiring colleague Dr. Mathew Riese MD, Ph.D., who passed away young. This work was supported in part by NIH R01 AI102893; NCI R01 CA179363 (S.M.); HRHM Program of MACC Fund (S.M.), Nicholas Family Foundation (S.M.); Gardetto Family (S.M.); MCW-Cancer CenterLarge Seed Grant (S.M.); MACC Fund (S.M.); Ann’s Hope Melanoma Foundation (S.M.); and Advancing Healthier Wisconsin (S.M.).

Supplements Supplement 1 Packages Installation

##These packages only need to be installed for once. ##Install the bioconductor in R. install.packages("BiocManager") ##Install the library if there is no these libraries in the computer install.packages( "dplyr" ) ##Choose the seurat version as needed, either version 3.2.2 or the newest version 4. remotes::install_version("Seurat" , version = "3.2.2") #install.packages(’Seurat’) install.packages("clustree") ##Install the package of pheatmap to visualize the heatmap install.packages("pheatmap") ##Install the package for monocle 2 BiocManager::install("monocle") ## Install packages for SCENIC BiocManager::install("AUCell") BiocManager::install("RcisTarget") BiocManager::install("GENIE3") install.packages("scales") install.packages("feather") ## Ready to install the package of SCENIC

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if (!requireNamespace("devtools", quietly = TRUE)) install. packages("devtools") devtools::install_github( "aertslab/SCENIC" ) packageVersion("SCENIC")

Supplement 2 Seurat Workflow

##Load the library library(Seurat) library(dplyr) ##Load the sequencing data which aligned by GRCH38 Ctrl_25yF_NK.data