Cerebral Cavernous Malformations (CCM) : Methods and Protocols [1st ed.] 9781071606391, 9781071606407

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Methods in Molecular Biology 2152

Lorenza Trabalzini Federica Finetti Saverio Francesco Retta Editors

Cerebral Cavernous Malformations (CCM) 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.

Cerebral Cavernous Malformations (CCM) Methods and Protocols

Edited by

Lorenza Trabalzini Department of Biotechnology, Chemistry and Pharmacy, University of Siena, SIENA, Italy

Federica Finetti Department of Biotechnology, Chemistry and Pharmacy, University of Siena, SIENA, Italy

Saverio Francesco Retta Department of Clinical and Biological Sciences, School of Medicine and Surgery, University of Torino, ORBASSANO (TORINO), Italy

Editors Lorenza Trabalzini Department of Biotechnology, Chemistry and Pharmacy University of Siena SIENA, Italy

Federica Finetti Department of Biotechnology, Chemistry and Pharmacy University of Siena SIENA, Italy

Saverio Francesco Retta Department of Clinical and Biological Sciences, School of Medicine and Surgery University of Torino ORBASSANO (TORINO), Italy

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-0639-1 ISBN 978-1-0716-0640-7 (eBook) https://doi.org/10.1007/978-1-0716-0640-7 © Springer Science+Business Media, LLC, part of Springer Nature 2020 This work is subject to copyright. All rights are reserved 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. Cover Illustration Caption: Schematic representation of the major experimental approaches used for understanding the pathobiology of CCM disease, including genetics and molecular and structural biology research; studies on cellular models and blood vessels; biological and biomedical research in animal models of distinct species, such nematode worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), zebrafish (Danio rerio), and mouse (Mus musculus); and clinical and research studies in human beings. The artwork was conceived by Saverio Francesco Retta and realized by the graphic designer Fabio Zanchetta. 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 Cerebral Cavernous Malformation (CCM) is a major cerebrovascular disease of proven genetic origin consisting of closely clustered, abnormally dilated and leaky capillary channels (caverns) lined by a thin endothelial layer. CCM disease may arise sporadically or is inherited as an autosomal dominant condition with incomplete penetrance and highly variable expressivity. The familial form has been linked to loss-of-function mutations in any of three known CCM genes, CCM1/KRIT1, CCM2 and CCM3/PDCD10. CCM lesions exhibit a range of different phenotypes, including wide inter-individual differences in lesion number, size, and susceptibility to intracerebral hemorrhage. Lesions may remain asymptomatic or result in pathological conditions of various type and severity at any age, with symptoms ranging from recurrent headaches to severe neurological deficits, seizures, and stroke. Although significant advances have been made toward understanding the natural history and pathogenic mechanisms of CCM disease, the clinical behavior in individual patients is highly unpredictable. Identification of modifiable risk factors of prognostic value associated with clinical severity of CCM disease is therefore needed to ultimately provide better options for disease prevention and treatment. In addition, novel pharmacological strategies are particularly needed to limit disease progression and severity and prevent de novo formation of CCM lesions in susceptible individuals, as to date there are no direct therapeutic approaches besides the neurosurgical excision of symptomatic and accessible lesions. Useful insights into innovative approaches for CCM disease prevention and treatment are emerging from a growing understanding of the biological functions of the three known CCM proteins, CCM1/KRIT1, CCM2 and CCM3/PDCD10. In particular, accumulating evidence indicates that these proteins play major roles in distinct signaling pathways, including those involved in cellular responses to oxidative stress, inflammation and angiogenesis, pointing to pathophysiological mechanisms whereby the function of CCM proteins may be relevant in preventing vascular dysfunctions triggered by these events. Prepared for non-specialists as well as experienced researchers that may be interested in a multidisciplinary approach to study CCM disease, the book focuses on multidisciplinary experimental approaches aimed at addressing the multiple aspects of this cerebrovascular disease, including its clinicoepidemiological, neuroradiological, neurosurgical, histopathological, genetic, molecular and therapeutic features. The volume is divided into four sections. Part I provides a general overview of the natural history, epidemiology, and pathogenetic mechanisms of CCM disease. Part II describes methods currently used for its diagnosis and treatment. Part III describes the production and analysis of distinct cellular and animal models of the disease. Part IV describes different methodological approaches to study the structure and physiopathological functions of CCM proteins, and the mechanisms of CCM disease onset and progression. Each chapter is organized to include an introductory overview, a list of the materials and reagents needed to perform the experiment, a step-by-step, readily reproducible laboratory protocol, and a helpful notes section offering tips on troubleshooting and avoiding known pitfalls.

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Besides constituting a comprehensive collection of multidisciplinary experimental procedures used in the CCM field and answering the need for standardized protocols, this detailed volume brings together for the first time articles of many of the leading researchers who have contributed significantly to the advancement of scientific knowledge on clinical, genetic and molecular aspects of CCM disease, including epidemiologists, neuroradiologists, neurosurgeons, geneticists, and molecular, cellular and developmental biologists. This authoritative and practical book may therefore serve as a valuable resource for experienced researchers in distinct but complementary clinical and basic research disciplines, but also for future investigators and young students starting to study this complex disease and its pathophysiologic correlates. Siena, Italy Siena, Italy Orbassano (Torino), Italy

Lorenza Trabalzini Federica Finetti Saverio Francesco Retta

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

PART I

OVERVIEW OF CEREBRAL CAVERNOUS MALFORMATIONS

1 From Genes and Mechanisms to Molecular-Targeted Therapies: The Long Climb to the Cure of Cerebral Cavernous Malformation (CCM) Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saverio Francesco Retta, Andrea Perrelli, Lorenza Trabalzini, and Federica Finetti 2 Incidence, Prevalence, and Clinical Presentation of Cerebral Cavernous Malformations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kelly D. Flemming 3 Natural History, Clinical, and Surgical Management of Cavernous Malformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Giovanni G. Vercelli, Fabio Cofano, Filippo Veneziani Santonio, Francesca Vincitorio, Francesco Zenga, and Diego Garbossa

PART II

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DIAGNOSIS AND TREATMENT OF CEREBRAL CAVERNOUS MALFORMATIONS

4 Molecular Genetic Screening of CCM Patients: An Overview . . . . . . . . . . . . . . . . 49 Elisabeth Tournier-Lasserve 5 Next Generation Sequencing (NGS) Strategies for Genetic Testing of Cerebral Cavernous Malformation (CCM) Disease . . . . . . . . . . . . . . . . 59 Valerio Benedetti, Elisa Pellegrino, Alfredo Brusco, Roberto Piva, and Saverio Francesco Retta 6 Genome-wide Genotyping of Cerebral Cavernous Malformation Type 1 Individuals to Identify Genetic Modifiers of Disease Severity . . . . . . . . . . 77 He´le`ne Choquet and Helen Kim 7 Clinical Imaging of Cerebral Cavernous Malformations: Computed Tomography and Magnetic Resonance Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Marc Mabray and Blaine Hart 8 Neuroradiology: Differential Diagnosis, Follow-Up, and Reporting . . . . . . . . . . . 97 Alessandra Splendiani, Federico Bruno, and Alfonso Cerase 9 Surgical Management of Brain Cavernous Malformations . . . . . . . . . . . . . . . . . . . . 109 Marco M. Fontanella, Luca Zanin, Alessandro Fiorindi, Giannantonio Spena, Federico Nicolosi, Francesco Belotti, Pierpaolo Panciani, Claudio Cornali, and Francesco Doglietto

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PART III ANIMAL MALFORMATIONS 10

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MODELS

CAVERNOUS

Generation of CCM Phenotype by a Human Microvascular Endothelial Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Simona Delle Monache and Saverio Francesco Retta Isolation and Purification of Mouse Brain Endothelial Cells to Study Cerebral Cavernous Malformation Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preston Hale, Shady Ibrahim Soliman, Hao Sun, and Miguel Alejandro Lopez-Ramirez Production of KRIT1-knockout and KRIT1-knockin Mouse Embryonic Fibroblasts as Cellular Models of CCM Disease . . . . . . . . . . . . . . . . . . Luca Goitre, Claudia Fornelli, Alessia Zotta, Andrea Perrelli, and Saverio Francesco Retta CRISPR/Cas9-mediated Generation of Human Endothelial Cell Knockout Models of CCM Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Konrad Schwefel, Stefanie Spiegler, Christiane D. Much, Ute Felbor, and Matthias Rath Dissection of the Role of CCM Genes in Tubulogenesis Using the Drosophila Tracheal System as a Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alondra B. Schweizer Burguete and Amin S. Ghabrial Generation and Analysis of CCM Phenotypes in C. elegans . . . . . . . . . . . . . . . . . . Evelyn Popiel and William Brent Derry Generation of Transgenic Lines of Zebrafish Expressing Fluorescently Tagged CCM Proteins to Study Their Function and Subcellular Localization Within the Vasculature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stefan Donat and Salim Abdelilah-Seyfried Vertebrate Models to Investigate CCM Pathogenesis: The Zebrafish and Mouse Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Johnathan Abou-Fadel and Jun Zhang Generation of Cerebral Cavernous Malformation in Neonatal Mouse Models Using Inducible Cre-LoxP Strategy . . . . . . . . . . . . . . . . . . . . . . . . . Jaesung P. Choi and Xiangjian Zheng Isolation of Cerebral Endothelial Cells from CCM1/KRIT1 Null Mouse Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nicholas Nobiletti and Angela J. Glading

PART IV CELLULAR AND MOLECULAR MECHANISMS MALFORMATIONS 20

CEREBRAL

OF

OF

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CEREBRAL CAVERNOUS

Identification of the KRIT1 Protein by LexA-Based Yeast Two-Hybrid System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Ilya G. Serebriiskii, Mohamed Elmekawy, and Erica A. Golemis

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Crystallographic Studies of the Cerebral Cavernous Malformations Proteins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Oriana S. Fisher, Xiaofeng Li, Weizhi Liu, Rong Zhang, and Titus J. Boggon Microscopy Techniques to Investigate CCM Pathogenesis . . . . . . . . . . . . . . . . . . . Johnathan Abou-Fadel and Jun Zhang Preparation and Analysis of Protein Extracts to Investigate CCM Pathogenesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Johnathan Abou-Fadel and Jun Zhang Systems Wide Analysis of CCM Signaling Complex Alterations in CCM-Deficient Models Using Omics Approaches . . . . . . . . . . . . . . . . . . . . . . . . Johnathan Abou-Fadel and Jun Zhang Study of Molecular Interactions of CCM Proteins by Using a GAL4-Based Yeast Two-Hybrid Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Federica Finetti and Lorenza Trabalzini Study of CCM Microvascular Endothelial Phenotype by an In Vitro Tubule Differentiation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Simona Delle Monache and Saverio Francesco Retta Bidimentional In Vitro Angiogenic Assays to Study CCM Pathogenesis: Endothelial Cell Proliferation and Migration . . . . . . . . . . . . . . . . . . Federica Finetti and Lorenza Trabalzini Measurement of Endothelial Barrier Function in Mouse Models of Cerebral Cavernous Malformations Using Intravital Microscopy . . . . . . . . . . . Angela J. Glading Immunofluorescence of Cell–Cell and Cell–Extracellular Matrix Adhesive Defects in In Vitro Endothelial CCM Model: Juxtacrine Role of Mutant Extracellular Matrix on Wild-Type Endothelial Cells. . . . . . . . . . Sandra Manet, Daphne´ Vannier, Anne-Pascale Bouin, Justyna Lisowska, Corinne Albiges-Rizo, and Eva Faurobert Detection of p62/SQSTM1 Aggregates in Cellular Models of CCM Disease by Immunofluorescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saverio Marchi, Saverio Francesco Retta, and Paolo Pinton Notch Signaling in Familial Cerebral Cavernous Malformations and Immunohistochemical Detection of Cleaved Notch1 Intracellular Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sana S. Hasan and Andreas Fischer Measuring the Kinase Activity of GCKIII Proteins In Vitro . . . . . . . . . . . . . . . . . . Juan Zalvide, Cristina Almenglo, Sara Va´zquez, Mar Garcı´a-Colomer, Miriam Sartages, and Celia M. Pombo Spectrophotometric Method for Determining Glyoxalase 1 Activity in Cerebral Cavernous Malformation (CCM) Disease . . . . . . . . . . . . . . . . Cinzia Antognelli, Vincenzo Nicola Talesa, and Saverio Francesco Retta Fluorescence Analysis of Reactive Oxygen Species (ROS) in Cellular Models of Cerebral Cavernous Malformation Disease . . . . . . . . . . . . . Andrea Perrelli and Saverio Francesco Retta

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Contents

Library Preparation for Small RNA Transcriptome Sequencing in Patients Affected by Cerebral Cavernous Malformations. . . . . . . . . . . . . . . . . . . 467 Souvik Kar, Robert Geffers, Amir Samii, and Helmut Bertalanffy Affinity Purification and Preparation of Peptides for Mass Spectrometry from C. elegans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Evelyn Popiel and William Brent Derry

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

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Contributors SALIM ABDELILAH-SEYFRIED • Institute of Biochemistry and Biology, Potsdam University, Potsdam, Germany; Institute of Molecular Biology, Hannover Medical School, Hannover, Germany JOHNATHAN ABOU-FADEL • Department of Molecular and Translational Medicine, Texas Tech University Health Science Center El Paso, El Paso, TX, USA CORINNE ALBIGES-RIZO • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France CRISTINA ALMENGLO´ • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun˜a, Spain; Instituto de Investigacion Sanitaria, Complexo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain CINZIA ANTOGNELLI • Department of Experimental Medicine, University of Perugia, Perugia, Italy FRANCESCO BELOTTI • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy VALERIO BENEDETTI • Department of Clinical and Biological Sciences, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy HELMUT BERTALANFFY • International Neuroscience Institute, Hannover, Germany TITUS J. BOGGON • Department of Pharmacology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA ANNE-PASCALE BOUIN • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France FEDERICO BRUNO • Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy ALFREDO BRUSCO • Departmentof Medical Sciences, University of Torino, Torino, Italy; ` Della Salute e della Scienza University Hospital, Torino, Italy Medical Genetics Unit, Citta ALFONSO CERASE • Unit of Neuroimaging (Diagnostic and Functional Neuroradiology), Department of Neurological and Motor Sciences, “Santa Maria alle Scotte” NHS & University Hospital, Siena, Italy JAESUNG P. CHOI • Centre for Inflammation, Centenary Institute, and Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia; Laboratory of Cardiovascular Signalling, Centenary Institute, and Sydney Medical School, University of Sydney, Sydney, NSW, Australia HE´LE`NE CHOQUET • Division of Research, Kaiser Permanente Northern California (KPNC), Oakland, CA, USA FABIO COFANO • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy CLAUDIO CORNALI • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy SIMONA DELLE MONACHE • Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy; StemTeCh Group, Chieti, Italy

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Contributors

WILLIAM BRENT DERRY • Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada FRANCESCO DOGLIETTO • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy STEFAN DONAT • Institute of Biochemistry and Biology, Potsdam University, Potsdam, Germany; Institute of Molecular Biology, Hannover Medical School, Hannover, Germany MOHAMED ELMEKAWY • Molecular Therapeutics Program, Fox Chase Cancer Center, Philadelphia, PA, USA; Moscow Institute of Physics and Technology, Moscow Region, Russia EVA FAUROBERT • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France UTE FELBOR • Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany FEDERICA FINETTI • Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy; CCM Italia Research Network, Torino, Italy ALESSANDRO FIORINDI • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy ANDREAS FISCHER • Division Vascular Signaling and Cancer (A270), German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Medicine I and Clinical Chemistry, University Hospital of Heidelberg, Heidelberg, Germany; European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany ORIANA S. FISHER • Department of Pharmacology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Department of Chemistry, Lehigh University, Bethlehem, PA, USA KELLY D. FLEMMING • Department of Neurology, Mayo Clinic, Rochester, MN, USA MARCO M. FONTANELLA • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy CLAUDIA FORNELLI • Department of Clinical and Biological Science, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy DIEGO GARBOSSA • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy MAR GARCI´A-COLOMER • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun ˜ a, Spain ROBERT GEFFERS • Genome Analytics Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany AMIN S. GHABRIAL • The Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA ANGELA J. GLADING • Department of Pharmacology & Physiology, University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, NY, USA LUCA GOITRE • Department of Clinical and Biological Science, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy ERICA A. GOLEMIS • Molecular Therapeutics Program, Fox Chase Cancer Center, Philadelphia, PA, USA PRESTON HALE • Department of Medicine and Pharmacology, University of California, San Diego, CA, USA BLAINE HART • Department of Radiology, University of New Mexico School of Medicine, Albuquerque, NM, USA

Contributors

xiii

SANA S. HASAN • Division Vascular Signaling and Cancer (A270), German Cancer Research Center (DKFZ), Heidelberg, Germany SOUVIK KAR • Department of Neurosurgery, International Neuroscience Institute, Hannover, Germany HELEN KIM • Department of Anesthesia and Perioperative Care, School of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA; Institute for Human Genetics, UCSF, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, UCSF, San Francisco, CA, USA XIAOFENG LI • Department of Pharmacology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Abcam Inc., Branford, CT, USA JUSTYNA LISOWSKA • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France WEIZHI LIU • Department of Pharmacology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China; Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China MIGUEL ALEJANDRO LOPEZ-RAMIREZ • Department of Medicine and Pharmacology, University of California, San Diego, CA, USA MARC MABRAY • Department of Radiology, University of New Mexico School of Medicine, Albuquerque, NM, USA SANDRA MANET • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France SAVERIO MARCHI • Department of Clinical and Molecular Sciences, Marche Polytechnic University, Ancona, Italy CHRISTIANE D. MUCH • Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany FEDERICO NICOLOSI • Neurosurgery, Humanitas Research Hospital, Milano, Italy NICHOLAS NOBILETTI • Department of Pharmacology & Physiology, University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, NY, USA PIERPAOLO PANCIANI • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy ELISA PELLEGRINO • Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy ANDREA PERRELLI • Department of Clinical and Biological Science, School of Medicine and Surgery, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy PAOLO PINTON • Department of Medical Sciences, Laboratory for Technologies of Advanced Therapies (LTTA), University of Ferrara, Ferrara, Italy; Maria Cecilia Hospital, GVM Care & Research, Cotignola, Ravenna, Italy ROBERTO PIVA • Department of Molecular Biotechnology and Health Sciences, University of ` Della Salute e della Scienza University Torino, Torino, Italy; Medical Genetics Unit, Citta Hospital, Torino, Italy CELIA M. POMBO • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun˜a, Spain

xiv

Contributors

EVELYN POPIEL • Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada MATTHIAS RATH • Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany SAVERIO FRANCESCO RETTA • Department of Clinical and Biological Science, School of Medicine and Surgery, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy AMIR SAMII • International Neuroscience Institute, Hannover, Germany MIRIAM SARTAGES • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun˜a, Spain KONRAD SCHWEFEL • Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany ALONDRA B. SCHWEIZER BURGUETE • The Taub Institute, New York, NY, USA ILYA G. SEREBRIISKII • Molecular Therapeutics Program, Fox Chase Cancer Center, Philadelphia, PA, USA; Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan, Russia SHADY IBRAHIM SOLIMAN • Department of Medicine and Pharmacology, University of California, San Diego, CA, USA GIANNANTONIO SPENA • Neurosurgery, Alessandro Manzoni Hospital, Lecco, Italy STEFANIE SPIEGLER • Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany ALESSANDRA SPLENDIANI • Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy HAO SUN • Department of Medicine and Pharmacology, University of California, San Diego, CA, USA VINCENZO NICOLA TALESA • Department of Experimental Medicine, University of Perugia, Perugia, Italy ELISABETH TOURNIER-LASSERVE • INSERM U1141, Assistance Publique Hoˆpitaux de Paris, Paris University, Paris, France LORENZA TRABALZINI • Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy; CCM Italia Research Network, Torino, Italy DAPHNE´ VANNIER • Institute for Advanced Biosciences, University Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France SARA VA´ZQUEZ • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun˜a, Spain FILIPPO VENEZIANI SANTONIO • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy GIOVANNI G. VERCELLI • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy FRANCESCA VINCITORIO • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy JUAN ZALVIDE • Departamento de Fisiologı´a and CiMUS, Universidade de Santiago de Compostela, Santiago de Compostela, A Corun˜a, Spain

Contributors

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LUCA ZANIN • Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy FRANCESCO ZENGA • Neurosurgery Unit, Department of Neuroscience, University of Torino, Torino, Italy JUN ZHANG • Department of Molecular and Translational Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, USA RONG ZHANG • Department of Pharmacology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA XIANGJIAN ZHENG • Laboratory of Cardiovascular Signalling, Centenary Institute, and Sydney Medical School, University of Sydney, University of Sydney, Sydney, NSW, Australia; Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China ALESSIA ZOTTA • Department of Clinical and Biological Science, University of Torino, Orbassano (Torino), Italy; CCM Italia Research Network, Torino, Italy

Part I Overview of Cerebral Cavernous Malformations

Chapter 1 From Genes and Mechanisms to Molecular-Targeted Therapies: The Long Climb to the Cure of Cerebral Cavernous Malformation (CCM) Disease Saverio Francesco Retta, Andrea Perrelli, Lorenza Trabalzini, and Federica Finetti Abstract Cerebral cavernous malformation (CCM) is a rare cerebrovascular disorder of genetic origin consisting of closely clustered, abnormally dilated and leaky capillaries (CCM lesions), which occur predominantly in the central nervous system. CCM lesions can be single or multiple and may result in severe clinical symptoms, including focal neurological deficits, seizures, and intracerebral hemorrhage. Early human genetic studies demonstrated that CCM disease is linked to three chromosomal loci and can be inherited as autosomal dominant condition with incomplete penetrance and highly variable expressivity, eventually leading to the identification of three disease genes, CCM1/KRIT1, CCM2, and CCM3/PDCD10, which encode for structurally unrelated intracellular proteins that lack catalytic domains. Biochemical, molecular, and cellular studies then showed that these proteins are involved in endothelial cell-cell junction and blood–brain barrier stability maintenance through the regulation of major cellular structures and mechanisms, including endothelial cell-cell and cell-matrix adhesion, actin cytoskeleton dynamics, autophagy, and endothelial-tomesenchymal transition, suggesting that they act as pleiotropic regulators of cellular homeostasis, and opening novel therapeutic perspectives. Indeed, accumulated evidence in cellular and animal models has eventually revealed that the emerged pleiotropic functions of CCM proteins are mainly due to their ability to modulate redox-sensitive pathways and mechanisms involved in adaptive responses to oxidative stress and inflammation, thus contributing to the preservation of cellular homeostasis and stress defenses. In this introductory review, we present a general overview of 20 years of amazing progress in the identification of genetic culprits and molecular mechanisms underlying CCM disease pathogenesis, and the development of targeted therapeutic strategies. Key words Cerebrovascular diseases, Cerebral cavernous malformation (CCM), Genetic disease, CCM genes, KRIT1/CCM1, CCM2, CCM3/PDCD10, Genetic modifiers, Oxidative stress, Inflammation, Angiogenesis

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Introduction Cerebral Cavernous Malformation (CCM), also known as cavernous angioma or cavernoma, is a major vascular dysplasia with a prevalence of 0.5% in the general population, thus affecting

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_1, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Fig. 1 MRI appearance of a cerebral cavernous malformation. Axial T2-weighted fast spin-echo (FSE) MRI of a CCM lesion in an affected patient. (Image courtesy of Dr. Maria Consuelo Valentini, “Citta` della Salute e della Scienza” University Hospital of Torino, Italy) (from [12])

approximately 35 million people worldwide [1–3] (see Chap. 2 of this volume). It consists of closely clustered, abnormally dilated and leaky sinusoidal capillaries (caverns) lined by a thin endothelium and devoid of normal vessel structural components, such as pericytes and astrocyte foot processes, which on gross histopathological inspection appear as multilobate “mulberry-like” vascular lesions [4, 5]. Diagnosis is commonly made by standard spin-echo magnetic resonance imaging (MRI) at 1.5-, 3-, or 7-Tesla, which can effectively detect well-circumscribed CCM lesions (Fig. 1); however, the unmasking of small lesions is far more likely via gradientecho (GRE) or susceptibility-weighted imaging (SWI) [6–8] (see Chaps. 7 and 8 of this volume). Notably, the incidence of incidentally detected CCM has recently increased substantially due to the widespread use of MRI [9]. CCM lesions are predominantly found in the central nervous system (CNS), including brain and spinal cord, but are also known to affect retina, skin, and liver. Within the brain, CCM can occur as single or multiple lesions (even hundreds), ranging in size from a few millimeters to a few centimeters, which can remain clinically silent for a lifetime or unpredictably give rise to clinical symptoms of various type and severity at any age, including recurrent headaches, focal neurological deficits, seizures, stroke, and intracerebral hemorrhage (ICH) [1–3, 10] (see Chap. 2 of this volume). Indeed, despite the high prevalence of CCM lesions, only approximately 30% of affected people will eventually develop clinical symptoms, which are extremely variable and

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highly unpredictable, suggesting that CCM disease onset and severity may depend on the combinatorial contribution of multiple genetic and environmental risk factors [3, 11, 12]. CCM is a disease of proven genetic origin (OMIM 116860) that may arise sporadically or is inherited as an autosomal dominant condition with incomplete penetrance and variable expressivity [13, 14]. The sporadic form (sCCM) accounts for up to 80% of cases and is characterized by a lack of family history of the disease and the general presence of a single lesion on MRI. On the other hand, the familial form (fCCM) accounts for at least 20% of cases and is often characterized by the presence multiple CCM lesions in the brain, which may show progression in both number and size over time and are sometimes associated with cutaneous and retinal cavernous malformations [14, 15]. Notably, while in sCCM cases a CCM lesion is frequently observed in close association with a developmental venous anomaly (DVA), such association has never been observed in fCCM cases, suggesting the possibility of a different developmental mechanism [16–18]. Human genetic studies have so far identified three genes whose heterozygous loss-of-function mutations are linked to CCM disease: CCM1 (KRIT1), CCM2 (MGC4607), and CCM3 (PDCD10) [14] (see Chap. 4 of this volume). Nevertheless, accumulated evidence in endothelial-specific conditional knockout (cKO) mouse models has clearly demonstrated that even the homozygous loss of CCM genes is not per se sufficient to cause the formation of CCM lesions [19], thus confirming the necessary contribution of additional determinants, including environmental risk factors and genetic modifiers of vascular sensitivity to stressful conditions [11, 12] (see Chap. 6 of this volume). Currently, there are no direct therapeutic approaches for CCM disease, besides the neurosurgical removal of accessible CCM lesions in patients with recurrent hemorrhage or intractable seizures [20–22] (see Chaps. 3 and 9 of this volume). However, based on the great multidisciplinary research advances in the identification of pathobiological mechanisms of CCM disease made in the last decade, some imaging and plasma biomarkers of prognostic value and distinct promising pharmacological strategies for preventing or limiting symptomatic disease onset and severity in susceptible individuals have been recently proposed and tested in animal models and pilot small clinical trials [12, 22, 23]. In this introductory chapter of the MiMB volume focused on CCM disease, which includes articles from major scientists that contributed with complementary expertise to this biomedical field over the past 20 years, we present an historical overview of the main discoveries that have significantly constellated the long multidisciplinary research climb to the cure of CCM disease, allowing the identification and characterization of its genetic bases and pathogenetic mechanisms, and the development of new targeted pharmacological approaches for prevention and treatment.

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The Genetic Basis of CCM Disease The autosomal dominant inheritance and genetic underpinnings of CCM disease have been originally demonstrated since 1995 through genetic linkage analysis by several groups studying large families with multiple affected relatives, which discovered 3 chromosomal loci linked to CCM disease, including the locus CCM1 at 7q21-q22, CCM2 at 7p15-p13, and CCM3 at 3q25.2-q27 [14]. CCM genes were subsequently identified starting from 1999, when the CCM1 gene was first discovered on chromosome 7q using physical mapping and positional cloning strategies [24, 25], and shown to correspond to the KRIT1 (Krev Interaction Trapped 1) gene identified 2 years earlier in a yeast two-hybrid screening for new proteins interacting with Rap1A (also known as Krev1) [26] (see Chap. 20 of this volume), a member of the Ras family of small GTPases that plays a pivotal role in the crosstalk between cadherins and integrins [27–30]. The identification of the CCM2 and CCM3 genes then followed in the years 2003–2005 [31–33]. Molecular screening of these 3 CCM genes in distinct series of consecutive patients led to the identification of a causative germline heterozygous mutation in up to 95% of familial cases and 60% of sporadic cases with multiple lesions. In particular, mutations of CCM1, CCM2, and CCM3 have been involved in about 60–65%, 20%, and 10% of fCCM cases, respectively, while the remaining 5–10% of these cases have been attributed either to other so far undetected genetic alterations in the 3 known CCM genes or to mutations of yet unidentified additional genes [14, 34–36] (see Chap. 4 of this volume). Most of the hundreds of distinct mutations identified so far in the 3 known CCM genes lead to a premature stop codon regardless of the gene and mechanism, including either non-sense mutations, small insertions/deletions, or mutations leading to abnormal splicing and frameshift, resulting in loss-of-function effects [14, 36, 37]. A combination of diagnostic methods, including sequencing and copy number analysis of germline DNA extracted from blood and cDNA analysis, is therefore required to ensure the best screening sensitivity in a diagnostic context [36] (see Chaps. 4 and 5 of this volume). A very strong founder effect has been reported in the HispanoAmerican CCM population of the southwestern United States and northern Mexico states, which mostly shares the Q455X stop codon mutation in CCM1/KRIT1 (also known as the common Hispanic mutation, CHM). Today, it accounts for the largest population of fCCM worldwide, with thousands of affected patients and varying degrees of clinical severity [15, 24, 38], which has facilitated the identification of genetic and environmental risk factors associated with CCM disease onset and progression [38–40].

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Indeed, despite the apparent higher disease severity in fCCM cases, up to 70% of mutation carriers remain asymptomatic or minimally symptomatic throughout life. Moreover, a large variability of disease severity is observed even among family members of similar ages carrying the same disease-associated genetic defect, including wide inter-individual differences in lesion number, size and susceptibility to ICH, suggesting that additional factors other than the diseasecausing mutation can contribute to CCM disease pathogenesis [3, 11, 12] (see Chap. 2 of this volume). Consistently, recent genome-wide association studies (GWAS) based mainly on large and homogeneous cohorts of Hispano-American CCM patients carrying the CCM1/KRIT1 Q455X CHM have identified genetic modifiers of CCM disease, including genetic susceptibility factors related to differences in vascular sensitivity to oxidative stress and inflammation, showing that they may contribute significantly to inter-individual differences in CCM disease susceptibility and severity [19, 39, 40] (see Chap. 6 of this volume).

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Structural Studies of CCM Proteins Structural studies have contributed significantly to shed new light on CCM protein functions, broadening the understanding of CCM-related biology and disease mechanisms. The CCM1/KRIT1 gene has 16 coding exons that encode for KRIT1, a 736 amino-acid scaffold protein (ffi 84 kD MW) containing a N-terminal Nudix domain, three NPxY/F motifs, three ankyrin repeats (ANK), and a C-terminal FERM (band 4.1, ezrin, radixin, and moesin) domain, which mediate both intramolecular and intermolecular interactions [41–43] (see Chap. 21 of this volume). Moreover, it has been reported the identification of a KRIT1 isoform (KRIT1B) characterized by the in-frame alternative splicing of the 15th coding exon, which encodes for the 39-amino acid distal beta-sheet of the F3/PTB-like subdomain of the FERM domain, demonstrating that the absence of a functional PTB binding pocket affects both intramolecular and intermolecular interactions and nucleocytoplasmic shuttling of the protein [41, 44]. CCM2/MGC4607, a 10 coding exons gene, encodes for CCM2 (also known as malcavernin or OSM/osmosensing scaffold for MEKK3), a 444 amino-acid protein (ffi 49 kD MW) that contains a phosphotyrosine binding (PTB) domain at its N-terminus and a C-terminal harmonin homology domain (HHD) (see Chap. 21 of this volume). CCM3/PDCD10 includes seven coding exons encoding for PDCD10 (programmed cell death 10), a 212 amino-acid protein (ffi 25 kD MW) that contains a dimerization domain at the N-terminus and a focal adhesion targeting (FAT)-homology domain at the C-terminus (see Chap. 21 of this volume).

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Many of the roles of the distinct domains of the three CCM proteins have been revealed by structure-guided studies, which showed that the CCM proteins can directly interact with one another to form a either dimeric (KRIT1/CCM2) or trimeric (KRIT1/CCM2/CCM3) scaffold complex that functions in distinct signal transduction pathways by interacting with a range of other binding partners, including ICAP1, RAP1, and MEKK3 [45–48] (see Chaps. 21 and 25 of this volume). Moreover, such studies showed also that CCM3 can independently heterodimerize with proteins of the GCKIII (germinal center kinase III) family of Sterile 20 (Ste20)-like serine/threonine kinases, including MST3/ STK24, SOK1/STK25, and MST4/STK26, forming a stable complex that may function in a separate pathway from the KRIT1/ CCM2 complex, suggesting additional independent roles for CCM3 [49–53] (see Chap. 32 of this volume). Accordingly, CCM3 has been described as residing in the STRiatin-Interacting Phosphatase And Kinase (STRIPAK) complex, which contains STK25 and MST4, but not CCM1 or CCM2 [54–56].

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Cellular and Animal Models of CCM Disease Over the 20 years since the identification of the first CCM gene (CCM1/KRIT1) [24, 25], multiple cellular and animal models of CCM disease have been produced and proved decisive for the identification of CCM gene functions and CCM disease mechanisms. Among cellular models, KRIT1-knockout mouse embryonic fibroblast (MEF) and either human umbilical vein endothelial cells (HUVEC) or human brain microvascular endothelial cells (hBMEC) knockout or silenced for a specific CCM gene have been used extensively, allowing the identification of new molecules and mechanisms involved in physiopathological functions of CCM proteins, and opening novel therapeutic perspectives for CCM disease [57–70] (see Chaps. 10–13, 18, 19, and 26–30 of this volume). Among animal models, the most commonly used has been the murine model Mus musculus [71]. Indeed, constitutive or tissuespecific KO of any of the CCM genes in mice allowed to establish the crucial role of CCM gene expression in endothelial cells for proper embryonic angiogenesis and the maintenance of vascular homeostasis and BBB stability in the adult [64, 72–77] (see Chaps. 18, 19 and 28 of this volume). However, mice with heterozygous knockout of a CCM gene, which mimics the genetic status of CCM patients affected by the familiar form of the disease, do not show any apparent phenotype [57, 64, 71], suggesting that the heterozygous deficiency of a CCM gene is not sufficient to cause CCM disease but requires additional triggers. Consistently, we have

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recently demonstrated that heterozygous KRIT1-KO mice are characterized by an enhanced susceptibility to vascular dysfunctions triggered by pro-oxidant and pro-inflammatory stimuli, including decreased microvessel barrier function and increased vascular permeability [64] and enhanced susceptibility to develop atherosclerotic lesions [70]. Besides the mouse, 3 tiny model organisms have also been used effectively to elucidate the in vivo biological functions of CCM genes, including the fish Danio rerio [50, 71, 78–80] (see Chaps. 16 and 17 of this volume), the nematode Caenorhabditis elegans [54, 81, 82] (see Chaps. 15 and 36 of this volume), and the fruit fly Drosophila melanogaster [83] (see Chap. 14 of this volume).

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Physiological Functions of CCM Proteins and Pathogenetic Mechanisms It has been suggested that CCM lesion genesis requires homozygous loss-of-function mutations in a CCM gene by a Knudsonian two-hit mechanism, whereby an inactivating germline mutation in one allele (first hit) is accompanied by a somatic mutation in the other (second hit) [84–88]. However, the somatic second-hit lossof-heterozygosity mutation was detected only in a subset of the endothelial cells lining cavernous vessels with germline CCM gene mutations [85], which appears antithetical to the Knudson’s two-hit model of CCM pathogenesis. On the other hand, as a plausible refutation of this apparent discrepancy it has been recently reported that CCM lesions may develop through clonal expansion of mutant endothelial cells accompanied by an incorporation in the growing malformation of normal non-mutated endothelial cells [89–91]. Nonetheless, the proposed genetic two-hit mechanism is in sharp contrast with some other observations and findings in tissue-specific cKO mouse models of CCM disease, which have clearly indicated that the biallelic inactivation of a CCM gene is not sufficient to cause the formation of CCM lesions. Indeed, the development of CCM lesions occurs only if endothelial cell-specific conditional deletions of CCM genes are induced immediately after birth (P1) but not in the adult phase [92], and is always spatially restricted despite the homozygous pan-endothelial deletion of CCM genes [61, 92–94]. Furthermore, more recent evidence has unequivocally demonstrated that homozygous loss of CCM genes is indeed not fully sufficient to cause CCM lesion formation and disease progression in the absence of additional critical stimulants, including a pro-inflammatory gut microbiota [19]. Consistently, clinical features of CCM disease, including lesion number and size, rate of recurrent bleeding, age-of-onset, and severity of symptoms, vary greatly even between family members carrying the same causative gene mutation, suggesting that CCM disease onset and progression is determined by a combination of multiple factors,

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including disease-associated mutations, microenvironmental stressors, and inter-individual genetic differences in stress response [11, 40]. Accordingly, it has been reported that severe astrocytosis may play a role in CCM lesion formation through cellnonautonomous mechanisms [95]. Comprehensive molecular genetic studies of CCM disease conducted during the 20 years since the discovery of the first CCM gene have shown that causative mutations are almost always loss-offunction mutations, suggesting that the functions of the 3 known CCM genes need to be severely impaired for pathogenesis [14, 36, 37, 96]. Indeed, the large variety of multidisciplinary experimental approaches used over the past 20 years, including integrated molecular and cellular biology studies in vitro, in vivo, and in silico (see Chaps. 17, and 22–34 of this volume), provided clear evidence that these genes encode for proteins that are crucially involved in the maintenance of endothelial cell-cell junction stability and BBB integrity by regulating major cell structures and signaling mechanisms involved in cellular homeostasis and responses to various physiopathological stressors [12, 97]. Among others, CCM proteins have been shown to regulate cadherin-mediated cell-cell junctions [98, 99], integrin-mediated cell-matrix adhesion [4, 100– 102] (see Chap. 29 of this volume), Rho GTPase-mediated cytoskeleton dynamics [73, 103–106], Notch signaling [70, 107–111] (see Chap. 31 of this volume), vascular endothelial growth factor (VEGF) signaling [112, 113], MAPK/ERK signaling [48, 114– 116], TGF-β-driven endothelial-to-mesenchymal transition (EndMT) [76], endothelial exocytosis of angiopoietin 2 (ANGPT2) [117], and mechanotransduction pathways mediated by blood flow-sensitive transcription factors of the Kru¨ppel-like factor (KLF) family [79, 94, 115, 118]. Furthermore, there is also evidence for bidirectional functional relationships between CCM proteins and miRNAs [119, 120] (see Chap. 35 of this volume). Although the identification of this multitude of molecular functions of CCM proteins has provided significant insights into CCM disease pathogenesis and treatment, the mechanistic interconnection and causal prioritization between these multiple functions have almost never been considered comprehensively in the context of the natural history of CCM disease, and often remained quite elusive or ambiguous [12, 97]. A plausible integrative mechanistic explanation for the involvement of such a plethora of distinct molecules and signaling pathways has been originally provided by the discovery that loss of function of CCM proteins exerts pleiotropic effects by affecting redox homeostasis and signaling [57]. Subsequent findings then confirmed this original discovery, demonstrating that CCM proteins play indeed a major role in controlling redox-sensitive mechanisms involved in normal cell physiology and adaptive responses to oxidative stress and inflammation, which in turn are tightly linked to angiogenic responses,

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thus shedding new light on the wide variety of pathogenetic mechanisms and risk factors correlated with CCM disease onset and progression, and opening new perspectives for disease prevention and treatment [12, 97]. In particular, CCM proteins have been implicated in redox homeostasis and signaling [57, 59, 67–70, 121, 122] (see Chaps. 33 and 34 of this volume), autophagy [60, 66, 97, 123] (see Chap. 30 of this volume), and antioxidant and antiinflammatory defenses [19, 57, 59, 61, 64, 67, 68, 70, 124, 125]. Consistent with this emerging integrated landscape of CCM protein functions in regulating major redox-dependent mechanisms, virtually all the multiple molecular mechanisms that have hitherto been implicated in the pathogenesis of CCM disease are redox-sensitive and may occur downstream of altered redox homeostasis and signaling [12, 97, 121]. Furthermore, growing evidence in animal models suggests that oxidative stress and inflammation are indeed tightly linked to the pathogenesis of CCM disease, and may play even more critical roles than previously described due to systemic effects [19, 61, 64, 70, 124]. Conversely, accumulating data in cellular and animal models indicate that limiting ROS accumulation and oxidative stress via distinct approaches may contribute significantly in preventing or reversing CCM disease phenotypes [57, 60–64, 66–70]. Taken together, the emerged multiple physiological roles of CCM proteins and the growing pleiotropic effects of their loss of function have raised the intriguing possibility that these proteins promote the maintenance of BBB integrity by orchestrating the redox-dependent signaling crosstalk between major regulators of vascular homeostasis and defense against oxidative, inflammatory, and angiogenic insults, including cadherins, integrins, and small GTPases of the Ras superfamily [12, 59, 126, 127]. Consistently, whereas the small GTPase Rap1, a major KRIT1 binding protein [26, 98], has been reported to play a pivotal role in the functional crosstalk between cadherins and integrins [27, 28], there is clear evidence that this and other GTPases of the Ras superfamily involved in CCM protein functions and disease pathogenesis, such as RhoA and Cdc42 [73, 103–106, 128], can act as both regulators and effectors of redox signaling [126, 127, 129].

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Therapeutic Targets and Strategies A recurring theme dominating the CCM scientific literature is the causal link between loss of function of CCM proteins and hyperactivation of the small GTPase RhoA and its effector Rho kinase (ROCK). RhoA activation increases cellular contractility and destabilizes endothelial adherens junctions, thereby reducing endothelial barrier function and increasing vascular permeability [73, 103– 106]. Indeed, the identification of this mechanism has suggested a

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potential therapy for CCM disease based on inhibitors of the RhoA-ROCK signaling, including statins (simvastatin, fluvastatin, and atorvastatin) [73, 130–132], fasudil [105, 132–134], and BA-1049, a ROCK2-selective kinase inhibitor [135]. Moreover, various additional putative therapeutic compounds and strategies have been also proposed with the potentiality to be effective at least in limiting CCM disease severity, including sulindac sulfide and its analogs, which have been shown to inhibit the β-catenin and TGF-β pathways [136]; distinct angiogenesis inhibitors, such as sorafenib [107], semaxanib [112], 3TSR, an anti-angiogenic thrombospondin1 (TSP1) fragment [65], ANGPT2-neutralizing antibodies [117], and ponatinib, an inhibitor of MEKK3-KLF signaling with anti-angiogenic effects [137]; B-cell depletion by anti-BR3 antibodies [138]; Toll-like receptor 4 (TLR4) antagonists and alteration of microbiome [19]; blocking antibodies against the anticoagulant endothelial receptors thrombomodulin (TM) and endothelial protein C receptor (EPCR) [139]; and propranolol, a non-selective beta-blocker used as first-line treatment for infantile hemangiomas [140–144]. Nevertheless, while a need for more rigorous set of mammalian studies to investigate the putative molecular mechanisms and potential side effects of these candidate drugs in CCM pathology has been highlighted [12, 97, 123, 145], more preclinical and clinical data from both retrospective and prospective studies are also required for weighing potential benefits against risks [145–147]. In this regard, the cases of statins and propranolol are quite emblematic. In fact, while statins have been shown to significantly enhance vascular stability and reduce the prevalence of CCM lesions in distinct mouse models of CCM disease [73, 131, 132], leading to an exploratory clinical trial [148], several outstanding questions have been raised about the efficacy and specificity of statins as therapeutic agents to improve CCM outcome [145]. Moreover, there is evidence that administration of statins may correlate with increased risk of intracerebral hemorrhage [149, 150]; hence, more researches should be done before the application of statin in CCM therapy. On the other hand, whereas treatment with the unselective β-blocker propranolol has been presumed to stabilize and eventually lead to CCM size regression in a few cases of adult patients with progressive multiple CCMs and symptomatic hemorrhage [143, 144], the underlying mechanism remains unclear [143] and evidence for this effect in a retrospective cohort study has been not conclusive or even controversial [146], suggesting that additional studies and prospective trials are needed to confirm these findings [147]. Remarkably, whereas accumulated evidence points to oxidative stress and inflammation as driving forces in CCM pathogenesis, there is also clear evidence that all of the different therapeutic candidates for CCM disease proposed so far are endowed with either antioxidant or autophagy-inducing properties or both,

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suggesting that their reported effectiveness may be directly or indirectly related to the modulation of the tight crosstalk between autophagy and redox homeostasis and signaling [12, 97]. Consistently, among the other major potential therapeutic candidates shown to be even more effective than statins in decreasing lesion burden in mouse models of CCM disease there are Tempol, a SOD-mimetic ROS scavenger, and cholecalciferol (vitamin D3), a steroid hormone with established autophagy-inducing and antioxidant properties [12, 61]. Moreover, N-acetylcysteine (NAC), a potent antioxidant compound that acts as glutathione precursor, two of the main autophagy inducers, such as the mTOR inhibitors Rapamycin and Torin 1, and avenanthramides, phenolic compounds present in oats that exhibit antioxidant and antiinflammatory activity, have been shown to counteract major CCM disease phenotypes linked to oxidative stress, including actin stress fiber formation, adherens junction weakening, endothelial barrier dysfunction, and inflammatory responses [12, 66, 70, 151]. Taken together with the emerged evidence that the interplay between defective autophagy and redox imbalance may be integral to the development and progression of CCM lesions by sensitizing endothelial cells to local oxidative stress and inflammatory events [12, 97, 121], these findings suggest that a combination therapy approach based on both antioxidants and autophagy inducers might represent a novel option for the pharmacological treatment of CCM disease [12, 66].

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Concluding Remarks Multidisciplinary studies performed over the last 20 years have led to a great progress towards a comprehensive understanding of the natural history, genetic bases, and molecular mechanisms of CCM disease pathogenesis, revealing a stunning complexity. Nevertheless, original discoveries made over the last decade have demonstrated that this complexity is related to major pleiotropic functions of CCM proteins in modulating redox-sensitive signaling pathways and mechanisms involved in endothelial cell homeostasis and adaptive responses to oxidative stress, inflammation, and angiogenesis, including antioxidant and anti-inflammatory pathways and autophagy, as well as to genetic modifiers of individual susceptibility to stressful conditions [12]. Indeed, these original findings have pointed towards a novel unifying mechanistic scenario based on the fine-tuned crosstalk between autophagy and redox homeostasis and signaling, which accommodates all the different molecular pathways and potential therapeutic compounds so far associated with CCM disease pathogenesis and treatment (Table 1). In turn, this novel mechanistic landscape has provided a novel framework for the ongoing development of novel targeted, safe and effective

[4, 79, 100, 101] [59]

Inhibitors of TGF-β pathway (sulindac sulfide and its analogs) Angiogenesis inhibitors (semaxanib, ponatinib, bevacizumab, propranolol) ANGPT2-neutralizing antibodies TSP-1 replacement (3TSR) TM and EPCR inhibitors Anti-BR3 antibody (B-cell depletion); Avenanthramide; Toll-like receptor 4 (TLR4) antagonists; alteration of microbiome

CCM1, CCM3

CCM1, CCM3

CCM3

CCM1

CCM1, CCM3

CCM3

CCM1, CCM2

CCM1

Endothelial-to-mesenchymal transition (EndMT)

Angiogenesis and VEGF

ANGPT2

TSP-1

TM and EPCR

Inflammation

β1 integrin adhesion

JNK/c-Jun

Antioxidant compounds (N-acetylcysteine)

[60, 66, 97, 123]

mTOR inhibitors (Rapamycin, Torin 1)

CCM1, CCM2, CCM3

Autophagy

[19, 64, 138]

[139]

[65]

[117]

[112, 137, 143, 147]

[76, 118, 136]

[76, 92, 98, 99, 118, 136]

CCM1, CCM2, CCM3

References

Adherens junctions

Pharmacological approach

Mutated gene

Molecular pathway

Table 1 Candidate therapies in CCM based on molecular pathways altered by loss of function of CCM genes

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Antioxidant compounds (N-acetylcysteine, Avenanthramide) Nox inhibitors; Avenanthramide Ponatinib (inhibitor of MEKK3-KLF signaling with anti-angiogenic effects) Ponatinib (inhibitor of MEKK3-KLF signaling with anti-angiogenic effects) Sorafenib (multikinase inhibitor) Inhibitors of Rho signaling and multitarget compounds (Statins, Fasudil, Tempol, Vitamin D3) Antioxidant compounds and autophagy inducers (N-acetylcysteine, Avenanthramide, Tempol, Vitamin D3, Torin 1, Pt NPs)

CCM1, CCM2

CCM1

CCM1, CCM2, CCM3

CCM1, CCM2, CCM3

CCM1, CCM3

CCM1, CCM2, CCM3

CCM1, CCM2, CCM3

CCM3

FoxO1

NADPH oxidase (Nox4)

KLF2/KLF4

MEKK3

Notch

RhoA/ROCK

Reactive Oxygen Species (ROS)

STRIPAK

[49, 53–55, 78, 93]

[57, 59–62, 67, 69, 151]

[61, 73, 78, 93, 103–106, 132, 133, 135, 148]

[107–109]

[48, 114–116, 137]

[79, 94, 115, 116, 118, 137]

[64]

[57, 61, 62]

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therapeutic strategies to counteract CCM disease onset and severity, including synergistic drug combination and personalized medicine approaches tailored to high-risk individuals [12, 66]. Consistently, advances from distinct in vitro and in vivo studies support an important role for either oxidative stress, inflammation, or angiogenesis in CCM disease onset and progression, arguing that the established interplay between these potential determinants should be considered and examined using an integrative systemic approach in order to comprehensively and effectively understand CCM disease pathogenesis and define the best treatment options [12]. Overall, the 20-year long climb towards the treatment of CCM disease by multidisciplinary approaches has been outstanding and produced spectacular results, which have eventually allowed the achievement of the last fundamental step of this arduous but fascinating climbing: the testing of putative drugs through human clinical trials (Fig. 2). On the other hand, these great multidisciplinary efforts have also opened up new avenues for future research aimed at the characterization of the emerging functions of CCM genes in physiological and pathological contexts not limited to the cerebral vasculature. In fact, given that CCM genes are ubiquitously expressed in all major cell types, including neurons and epithelial cells, and considering that the molecular mechanisms in which they are involved also concern other human diseases

Fig. 2 The twenty-year long (1999-2019) climb of multidisciplinary research towards the treatment of CCM disease. (The image, including the 3D rendering and the central clipart representing “scientists climbing a DNA ladder”, is an artwork of Dr. Nicola Retta)

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associated with oxidative stress and inflammation, including atherosclerosis [70] and cancer [119], it is possible to envisage and glimpse new exciting perspectives for future research climbing.

Acknowledgements This work was supported by the Telethon Foundation (grant GGP15219 to SFR and LT), and the MIUR (Progetto Dipartimento di Eccellenza 2018-2022 to LT and FF). The authors are grateful to CCM Italia, the Italian Research Network for Cerebral Cavernous Malformation (https://www. ccmitalia.unito.it), and the Associazione Italiana Angiomi Cavernosi (AIAC) Onlus (https://www.aiac.unito.it), including its president Massimo Chiesa, for fundamental collaboration and support. Special thanks also go to Santina Barbaro and Nicola Retta for their invaluable help. This chapter and the book are dedicated to the memory of Rosa Giunta, Fortunato Barbaro, and Adelia Frison. References 1. Rigamonti D (2011) Cavernous malformations of the nervous system. Cambridge University Press, Cambridge, United Kingdom 2. Fontanella M (2015) Cerebral cavernous malformations (CCM). Minerva Medica, Torino, Italy 3. Flemming KD (2017) Clinical management of cavernous malformations. Curr Cardiol Rep 19:122 4. Zhang J, Clatterbuck RE, Rigamonti D, Chang DD, Dietz HC (2001) Interaction between krit1 and icap1alpha infers perturbation of integrin beta1-mediated angiogenesis in the pathogenesis of cerebral cavernous malformation. Hum Mol Genet 10:2953–2960 5. Tanriover G, Sozen B, Seker A, Kilic T, Gunel M, Demir N (2013) Ultrastructural analysis of vascular features in cerebral cavernous malformations. Clin Neurol Neurosurg 115:438–444 6. de Souza JM, Domingues RC, Cruz LC, Domingues FS, Iasbeck T, Gasparetto EL (2008) Susceptibility-weighted imaging for the evaluation of patients with familial cerebral cavernous malformations: a comparison with t2-weighted fast spin-echo and gradientecho sequences. AJNR Am J Neuroradiol 29:154–158 7. Cooper AD, Campeau NG, Meissner I (2008) Susceptibility-weighted imaging in

familial cerebral cavernous malformations. Neurology 71:382 8. Campbell PG, Jabbour P, Yadla S, Awad IA (2010) Emerging clinical imaging techniques for cerebral cavernous malformations: a systematic review. Neurosurg Focus 29:E6 9. Moore SA, Brown RD, Christianson TJ, Flemming KD (2014) Long-term natural history of incidentally discovered cavernous malformations in a single-center cohort. J Neurosurg 120:1188–1192 10. Batra S, Lin D, Recinos PF, Zhang J, Rigamonti D (2009) Cavernous malformations: natural history, diagnosis and treatment. Nat Rev Neurol 5:659–670 11. Trapani E, Retta SF (2015) Cerebral cavernous malformation (CCM) disease: from monogenic forms to genetic susceptibility factors. J Neurosurg Sci 59:201–209 12. Retta SF, Glading AJ (2016) Oxidative stress and inflammation in cerebral cavernous malformation disease pathogenesis: Two sides of the same coin. Int J Biochem Cell Biol 81:254–270 13. Cavalcanti DD, Kalani MY, Martirosyan NL, Eales J, Spetzler RF, Preul MC (2012) Cerebral cavernous malformations: from genes to proteins to disease. J Neurosurg 116:122–132

18

Saverio Francesco Retta et al.

14. Choquet H, Pawlikowska L, Lawton MT, Kim H (2015) Genetics of cerebral cavernous malformations: current status and future prospects. J Neurosurg Sci 59:211–220 15. Zafar A, Quadri SA, Farooqui M, Ikram A, Robinson M, Hart BL, Mabray MC, Vigil C, Tang AT, Kahn ML, Yonas H, Lawton MT, Kim H, Morrison L (2019) Familial cerebral cavernous malformations. Stroke 50:1294–1301 16. Petersen TA, Morrison LA, Schrader RM, Hart BL (2010) Familial versus sporadic cavernous malformations: differences in developmental venous anomaly association and lesion phenotype. AJNR Am J Neuroradiol 31:377–382 17. Meng G, Bai C, Yu T, Wu Z, Liu X, Zhang J, Zhao J (2014) The association between cerebral developmental venous anomaly and concomitant cavernous malformation: an observational study using magnetic resonance imaging. BMC Neurol 14:50 18. Brinjikji W, El-Masri AE, Wald JT, Flemming KD, Lanzino G (2017) Prevalence of cerebral cavernous malformations associated with developmental venous anomalies increases with age. Childs Nerv Syst 33:1539–1543 19. Tang AT, Choi JP, Kotzin JJ, Yang Y, Hong CC, Hobson N, Girard R, Zeineddine HA, Lightle R, Moore T, Cao Y, Shenkar R, Chen M, Mericko P, Yang J, Li L, Tanes C, ˜ sa U, Whitehead KJ, Li DY, Kobuley D, Vo Franke L, Hart B, Schwaninger M, HenaoMejia J, Morrison L, Kim H, Awad IA, Zheng X, Kahn ML (2017) Endothelial TLR4 and the microbiome drive cerebral cavernous malformations. Nature 545:305–310 20. Fontanella MM, Panciani PP, Spena G, Roca E, Migliorati K, Ambrosi C, Sturiale CL, Retta SF (2015) Professional athletes and cerebral cavernomas: an obstacle to overcome. J Sports Med Phys Fitness 55:1046–1047 21. Fontanella M, Bacigaluppi S (2015) Treatment of cerebral cavernous malformations: where do we stand? J Neurosurg Sci 59:199–200 22. Awad IA, Polster SP (2019) Cavernous angiomas: deconstructing a neurosurgical disease. J Neurosurg 131:1–13 23. Mabray MC, Caprihan A, Nelson J, McCulloch CE, Zafar A, Kim H, Hart BL, Morrison L (2019) Effect of simvastatin on permeability in cerebral cavernous malformation type 1 patients: results from a pilot small randomized controlled clinical trial. Transl Stroke Res

24. Sahoo T, Johnson EW, Thomas JW, Kuehl PM, Jones TL, Dokken CG, Touchman JW, Gallione CJ, Lee-Lin SQ, Kosofsky B, Kurth JH, Louis DN, Mettler G, Morrison L, Gil-Nagel A, Rich SS, Zabramski JM, Boguski MS, Green ED, Marchuk DA (1999) Mutations in the gene encoding KRIT1, a Krev-1/ rap1a binding protein, cause cerebral cavernous malformations (CCM1). Hum Mol Genet 8:2325–2333 25. Laberge-le Couteulx S, Jung HH, Labauge P, Houtteville JP, Lescoat C, Cecillon M, Marechal E, Joutel A, Bach JF, TournierLasserve E (1999) Truncating mutations in CCM1, encoding KRIT1, cause hereditary cavernous angiomas. Nat Genet 23:189–193 26. Serebriiskii I, Estojak J, Sonoda G, Testa JR, Golemis EA (1997) Association of Krev-1/ rap1a with Krit1, a novel ankyrin repeatcontaining protein encoded by a gene mapping to 7q21-22. Oncogene 15:1043–1049 27. Balzac F, Avolio M, Degani S, Kaverina I, Torti M, Silengo L, Small JV, Retta SF (2005) E-cadherin endocytosis regulates the activity of Rap1: a traffic light GTPase at the crossroads between cadherin and integrin function. J Cell Sci 118:4765–4783 28. Retta SF, Balzac F, Avolio M (2006) Rap1: a turnabout for the crosstalk between cadherins and integrins. Eur J Cell Biol 85:283–293 29. Goitre L, Cutano V, Retta SF (2014) Fluorescence microscopy study of Rap1 subcellular localization. Methods Mol Biol 1120:197–205 30. Goitre L, Retta SF (2014) Combined pulldown and time-lapse microscopy studies for determining the role of Rap1 in the crosstalk between integrins and cadherins. Methods Mol Biol 1120:177–195 31. Liquori CL, Berg MJ, Siegel AM, Huang E, Zawistowski JS, Stoffer T, Verlaan D, Balogun F, Hughes L, Leedom TP, Plummer NW, Cannella M, Maglione V, Squitieri F, Johnson EW, Rouleau GA, Ptacek L, Marchuk DA (2003) Mutations in a gene encoding a novel protein containing a phosphotyrosinebinding domain cause type 2 cerebral cavernous malformations. Am J Hum Genet 73:1459–1464 32. Denier C, Goutagny S, Labauge P, Krivosic V, Arnoult M, Cousin A, Benabid AL, Comoy J, Frerebeau P, Gilbert B, Houtteville JP, Jan M, Lapierre F, Loiseau H, Menei P, Mercier P, Moreau JJ, Nivelon-Chevallier A, Parker F, Redondo AM, Scarabin JM, Tremoulet M, Zerah M, Maciazek J, Tournier-Lasserve E, S. F. d. Neurochirurgie (2004) Mutations

The Long Climb to the Cure of CCM Disease within the MGC4607 gene cause cerebral cavernous malformations. Am J Hum Genet 74:326–337 33. Bergametti F, Denier C, Labauge P, Arnoult M, Boetto S, Clanet M, Coubes P, Echenne B, Ibrahim R, Irthum B, Jacquet G, Lonjon M, Moreau JJ, Neau JP, Parker F, Tremoulet M, Tournier-Lasserve E, S. F. d. Neurochirurgie (2005) Mutations within the programmed cell death 10 gene cause cerebral cavernous malformations. Am J Hum Genet 76:42–51 34. Denier C, Labauge P, Bergametti F, Marchelli F, Riant F, Arnoult M, Maciazek J, Vicaut E, Brunereau L, Tournier-Lasserve E, S. F. d. Neurochirurgie (2006) Genotypephenotype correlations in cerebral cavernous malformations patients. Ann Neurol 60:550–556 35. D’Angelo R, Marini V, Rinaldi C, Origone P, Dorcaratto A, Avolio M, Goitre L, Forni M, Capra V, Alafaci C, Mareni C, Garre` C, Bramanti P, Sidoti A, Retta SF, Amato A (2011) Mutation analysis of CCM1, CCM2 and CCM3 genes in a cohort of Italian patients with cerebral cavernous malformation. Brain Pathol 21:215–224 36. Spiegler S, Rath M, Paperlein C, Felbor U (2018) Cerebral cavernous malformations: an update on prevalence, molecular genetic analyses, and genetic counselling. Mol Syndromol 9:60–69 37. Riant F, Bergametti F, Ayrignac X, Boulday G, Tournier-Lasserve E (2010) Recent insights into cerebral cavernous malformations: the molecular genetics of CCM. FEBS J 277:1070–1075 38. Choquet H, Nelson J, Pawlikowska L, McCulloch CE, Akers A, Baca B, Khan Y, Hart B, Morrison L, Kim H (2014) Association of cardiovascular risk factors with disease severity in cerebral cavernous malformation type 1 subjects with the common Hispanic mutation. Cerebrovasc Dis 37:57–63 39. Choquet H, Pawlikowska L, Nelson J, McCulloch CE, Akers A, Baca B, Khan Y, Hart B, Morrison L, Kim H, B. V. M. C. B. Study (2014) Polymorphisms in inflammatory and immune response genes associated with cerebral cavernous malformation type 1 severity. Cerebrovasc Dis 38:433–440 40. Choquet H, Trapani E, Goitre L, Trabalzini L, Akers A, Fontanella M, Hart BL, Morrison LA, Pawlikowska L, Kim H, Retta SF (2016) Cytochrome P450 and matrix metalloproteinase genetic modifiers of disease severity in cerebral cavernous

19

malformation type 1. Free Radic Biol Med 92:100–109 41. Francalanci F, Avolio M, De Luca E, Longo D, Menchise V, Guazzi P, Sgro` F, Marino M, Goitre L, Balzac F, Trabalzini L, Retta SF (2009) Structural and functional differences between KRIT1A and KRIT1B isoforms: a framework for understanding CCM pathogenesis. Exp Cell Res 315:285–303 42. Gingras AR, Liu JJ, Ginsberg MH (2012) Structural basis of the junctional anchorage of the cerebral cavernous malformations complex. J Cell Biol 199:39–48 43. Li X, Zhang R, Draheim KM, Liu W, Calderwood DA, Boggon TJ (2012) Structural basis for small G protein effector interaction of Ras-related protein 1 (Rap1) and adaptor protein Krev interaction trapped 1 (KRIT1). J Biol Chem 287:22317–22327 44. Retta SF, Avolio M, Francalanci F, Procida S, Balzac F, Degani S, Tarone G, Silengo L (2004) Identification of Krit1B: a novel alternative splicing isoform of cerebral cavernous malformation gene-1. Gene 325:63–78 45. Draheim KM, Fisher OS, Boggon TJ, Calderwood DA (2014) Cerebral cavernous malformation proteins at a glance. J Cell Sci 127:701–707 46. Fisher OS, Boggon TJ (2014) Signaling pathways and the cerebral cavernous malformations proteins: lessons from structural biology. Cell Mol Life Sci 71:1881–1892 47. Draheim KM, Li X, Zhang R, Fisher OS, Villari G, Boggon TJ, Calderwood DA (2015) CCM2-CCM3 interaction stabilizes their protein expression and permits endothelial network formation. J Cell Biol 208:987–1001 48. Fisher OS, Deng H, Liu D, Zhang Y, Wei R, Deng Y, Zhang F, Louvi A, Turk BE, Boggon TJ, Su B (2015) Structure and vascular function of MEKK3-cerebral cavernous malformations 2 complex. Nat Commun 6:7937 49. Fidalgo M, Fraile M, Pires A, Force T, Pombo C, Zalvide J (2010) CCM3/ PDCD10 stabilizes GCKIII proteins to promote Golgi assembly and cell orientation. J Cell Sci 123:1274–1284 50. Yoruk B, Gillers BS, Chi NC, Scott IC (2012) Ccm3 functions in a manner distinct from Ccm1 and Ccm2 in a zebrafish model of CCM vascular disease. Dev Biol 362:121–131 51. Zalvide J, Fidalgo M, Fraile M, Guerrero A, Iglesias C, Floridia E, Pombo CM (2013) The CCM3-GCKIII partnership. Histol Histopathol 28:1265–1272

20

Saverio Francesco Retta et al.

52. Zhang M, Dong L, Shi Z, Jiao S, Zhang Z, Zhang W, Liu G, Chen C, Feng M, Hao Q, Wang W, Yin M, Zhao Y, Zhang L, Zhou Z (2013) Structural mechanism of CCM3 heterodimerization with GCKIII kinases. Structure 21:680–688 53. Voss K, Stahl S, Schleider E, Ullrich S, Nickel J, Mueller TD, Felbor U (2007) CCM3 interacts with CCM2 indicating common pathogenesis for cerebral cavernous malformations. Neurogenetics 8:249–256 54. Lant B, Yu B, Goudreault M, Holmyard D, Knight JD, Xu P, Zhao L, Chin K, Wallace E, Zhen M, Gingras AC, Derry WB (2015) CCM-3/STRIPAK promotes seamless tube extension through endocytic recycling. Nat Commun 6:6449 55. Pal S, Lant B, Yu B, Tian R, Tong J, Krieger JR, Moran MF, Gingras AC, Derry WB (2017) CCM-3 promotes C. elegans germline development by regulating vesicle trafficking cytokinesis and polarity. Curr Biol 27:868–876 56. Goudreault M, D’Ambrosio LM, Kean MJ, Mullin MJ, Larsen BG, Sanchez A, Chaudhry S, Chen GI, Sicheri F, Nesvizhskii AI, Aebersold R, Raught B, Gingras AC (2009) A PP2A phosphatase high density interaction network identifies a novel striatin-interacting phosphatase and kinase complex linked to the cerebral cavernous malformation 3 (CCM3) protein. Mol Cell Proteomics 8:157–171 57. Goitre L, Balzac F, Degani S, Degan P, Marchi S, Pinton P, Retta SF (2010) KRIT1 regulates the homeostasis of intracellular reactive oxygen species. PLoS One 5:e11786 58. Guazzi P, Goitre L, Ferro E, Cutano V, Martino C, Trabalzini L, Retta SF (2012) Identification of the Kelch family protein Nd1-L as a novel molecular interactor of KRIT1. PLoS One 7:e44705 59. Goitre L, De Luca E, Braggion S, Trapani E, Guglielmotto M, Biasi F, Forni M, Moglia A, Trabalzini L, Retta SF (2014) KRIT1 loss of function causes a ROS-dependent upregulation of c-Jun. Free Radic Biol Med 68:134–147 60. Marchi S, Corricelli M, Trapani E, Bravi L, Pittaro A, Delle Monache S, Ferroni L, Patergnani S, Missiroli S, Goitre L, Trabalzini L, Rimessi A, Giorgi C, Zavan B, Cassoni P, Dejana E, Retta SF, Pinton P (2015) Defective autophagy is a key feature of cerebral cavernous malformations. EMBO Mol Med 7:1403–1417 61. Gibson CC, Zhu W, Davis CT, BowmanKirigin JA, Chan AC, Ling J, Walker AE,

Goitre L, Delle Monache S, Retta SF, Shiu YT, Grossmann AH, Thomas KR, Donato AJ, Lesniewski LA, Whitehead KJ, Li DY (2015) Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131:289–299 62. Moglia A, Goitre L, Gianoglio S, Baldini E, Trapani E, Genre A, Scattina A, Dondo G, Trabalzini L, Beekwilder J, Retta SF (2015) Evaluation of the bioactive properties of avenanthramide analogs produced in recombinant yeast. Biofactors 41:15–27 63. Moglianetti M, De Luca E, Pedone D, Marotta R, Catelani T, Sartori B, Amenitsch H, Retta SF, Pompa PP (2016) Platinum nanozymes recover cellular ROS homeostasis in an oxidative stress-mediated disease model. Nanoscale 8:3739–3752 64. Goitre L, DiStefano PV, Moglia A, Nobiletti N, Baldini E, Trabalzini L, Keubel J, Trapani E, Shuvaev VV, Muzykantov VR, Sarelius IH, Retta SF, Glading AJ (2017) Up-regulation of NADPH oxidasemediated redox signaling contributes to the loss of barrier function in KRIT1 deficient endothelium. Sci Rep 7:8296 65. Lopez-Ramirez MA, Fonseca G, Zeineddine HA, Girard R, Moore T, Pham A, Cao Y, Shenkar R, de Kreuk BJ, Lagarrigue F, Lawler J, Glass CK, Awad IA, Ginsberg MH (2017) Thrombospondin1 (TSP1) replacement prevents cerebral cavernous malformations. J Exp Med 214:3331–3346 66. De Luca E, Pedone D, Moglianetti M, Pulcini D, Perrelli A, Retta SF, Pompa PP (2018) Multifunctional platinum@BSArapamycin nanocarriers for the combinatorial therapy of cerebral cavernous malformation. ACS Omega 3:15389–15398 67. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Daga M, Pizzimenti S, Barrera G, Cassoni P, Angelucci A, Trabalzini L, Talesa VN, Goitre L, Retta SF (2018) KRIT1 lossof-function induces a chronic Nrf2-mediated adaptive homeostasis that sensitizes cells to oxidative stress: implication for cerebral cavernous malformation disease. Free Radic Biol Med 115:202–218 68. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Fornelli C, Retta F, Cassoni P, Talesa VN, Retta SF (2018) Data in support of sustained upregulation of adaptive redox homeostasis mechanisms caused by KRIT1 loss-of-function. Data Brief 16:929–938 69. Cianfruglia L, Perrelli A, Fornelli C, Magini A, Gorbi S, Salzano AM, Antognelli C, Retta F, Benedetti V, Cassoni P, Emiliani C, Principato G,

The Long Climb to the Cure of CCM Disease Scaloni A, Armeni T, Retta SF (2019) KRIT1 loss-of-function associated with cerebral cavernous malformation disease leads to enhanced. Antioxidants (Basel) 8:E27 70. Vieceli Dalla Sega F, Mastrocola R, Aquila G, Fortini F, Fornelli C, Zotta A, Cento AS, Perrelli A, Boda E, Pannuti A, Marchi S, Pinton P, Ferrari R, Rizzo P, Retta SF (2019) KRIT1 deficiency promotes aortic endothelial dysfunction. Int J Mol Sci 20 71. Chan AC, Li DY, Berg MJ, Whitehead KJ (2010) Recent insights into cerebral cavernous malformations: animal models of CCM and the human phenotype. FEBS J 277:1076–1083 72. Whitehead KJ, Plummer NW, Adams JA, Marchuk DA, Li DY (2004) Ccm1 is required for arterial morphogenesis: implications for the etiology of human cavernous malformations. Development 131:1437–1448 73. Whitehead KJ, Chan AC, Navankasattusas S, Koh W, London NR, Ling J, Mayo AH, Drakos SG, Jones CA, Zhu W, Marchuk DA, Davis GE, Li DY (2009) The cerebral cavernous malformation signaling pathway promotes vascular integrity via Rho GTPases. Nat Med 15:177–184 74. Boulday G, Ble´con A, Petit N, Chareyre F, Garcia LA, Niwa-Kawakita M, Giovannini M, Tournier-Lasserve E (2009) Tissue-specific conditional CCM2 knockout mice establish the essential role of endothelial CCM2 in angiogenesis: implications for human cerebral cavernous malformations. Dis Model Mech 2:168–177 75. He Y, Zhang H, Yu L, Gunel M, Boggon TJ, Chen H, Min W (2010) Stabilization of VEGFR2 signaling by cerebral cavernous malformation 3 is critical for vascular development. Sci Sig 3:ra26 76. Maddaluno L, Rudini N, Cuttano R, Bravi L, Giampietro C, Corada M, Ferrarini L, Orsenigo F, Papa E, Boulday G, TournierLasserve E, Chapon F, Richichi C, Retta SF, Lampugnani MG, Dejana E (2013) EndMT contributes to the onset and progression of cerebral cavernous malformations. Nature 498:492–496 77. Choi JP, Yang X, Foley M, Wang X, Zheng X (2017) Induction and micro-CT imaging of cerebral cavernous malformations in mouse model. J Vis Exp 78. Zheng X, Xu C, Di Lorenzo A, Kleaveland B, Zou Z, Seiler C, Chen M, Cheng L, Xiao J, He J, Pack MA, Sessa WC, Kahn ML (2010) CCM3 signaling through sterile 20-like kinases plays an essential role during zebrafish cardiovascular development and cerebral

21

cavernous malformations. J Clin Invest 120:2795–2804 79. Renz M, Otten C, Faurobert E, Rudolph F, Zhu Y, Boulday G, Duchene J, Mickoleit M, Dietrich AC, Ramspacher C, Steed E, ManetDupe´ S, Benz A, Hassel D, Vermot J, Huisken J, Tournier-Lasserve E, Felbor U, Sure U, Albiges-Rizo C, Abdelilah-Seyfried S (2015) Regulation of β1 integrin-Klf2mediated angiogenesis by CCM proteins. Dev Cell 32:181–190 80. Otten C, Knox J, Boulday G, Eymery M, Haniszewski M, Neuenschwander M, Radetzki S, Vogt I, H€ahn K, De Luca C, Cardoso C, Hamad S, Igual Gil C, Roy P, Albiges-Rizo C, Faurobert E, von Kries JP, Campillos M, Tournier-Lasserve E, Derry WB, Abdelilah-Seyfried S (2018) Systematic pharmacological screens uncover novel pathways involved in cerebral cavernous malformations. EMBO Mol Med 10:e9155 81. Ito S, Greiss S, Gartner A, Derry WB (2010) Cell-nonautonomous regulation of C. elegans germ cell death by kri-1. Curr Biol 20:333–338 82. Chapman EM, Lant B, Ohashi Y, Yu B, Schertzberg M, Go C, Dogra D, Koskim€aki J, Girard R, Li Y, Fraser AG, Awad IA, Abdelilah-Seyfried S, Gingras AC, Derry WB (2019) A conserved CCM complex promotes apoptosis non-autonomously by regulating zinc homeostasis. Nat Commun 10:1791 83. Song Y, Eng M, Ghabrial AS (2013) Focal defects in single-celled tubes mutant for Cerebral cavernous malformation 3, GCKIII, or NSF2. Dev Cell 25:507–519 84. Gault J, Shenkar R, Recksiek P, Awad IA (2005) Biallelic somatic and germ line CCM1 truncating mutations in a cerebral cavernous malformation lesion. Stroke 36:872–874 85. Akers AL, Johnson E, Steinberg GK, Zabramski JM, Marchuk DA (2009) Biallelic somatic and germline mutations in cerebral cavernous malformations (CCMs): evidence for a two-hit mechanism of CCM pathogenesis. Hum Mol Genet 18:919–930 86. Pagenstecher A, Stahl S, Sure U, Felbor U (2009) A two-hit mechanism causes cerebral cavernous malformations: complete inactivation of CCM1, CCM2 or CCM3 in affected endothelial cells. Hum Mol Genet 18:911–918 87. McDonald DA, Shenkar R, Shi C, Stockton RA, Akers AL, Kucherlapati MH, Kucherlapati R, Brainer J, Ginsberg MH, Awad IA, Marchuk DA (2011) A novel

22

Saverio Francesco Retta et al.

mouse model of cerebral cavernous malformations based on the two-hit mutation hypothesis recapitulates the human disease. Hum Mol Genet 20:211–222 88. McDonald DA, Shi C, Shenkar R, Gallione CJ, Akers AL, Li S, De Castro N, Berg MJ, Corcoran DL, Awad IA, Marchuk DA (2014) Lesions from patients with sporadic cerebral cavernous malformations harbor somatic mutations in the CCM genes: evidence for a common biochemical pathway for CCM pathogenesis. Hum Mol Genet 23:4357–4370 89. Detter MR, Snellings DA, Marchuk DA (2018) Cerebral cavernous malformations develop through clonal expansion of mutant endothelial cells. Circ Res 123:1143–1151 90. Rath M, Pagenstecher A, Hoischen A, Felbor U (2020) Postzygotic mosaicism in cerebral cavernous malformation. J Med Genet 57 (3):212–216 91. Malinverno M, Maderna C, Abu Taha A, Corada M, Orsenigo F, Valentino M, Pisati F, Fusco C, Graziano P, Giannotta M, Yu QC, Zeng YA, Lampugnani MG, Magnusson PU, Dejana E (2019) Endothelial cell clonal expansion in the development of cerebral cavernous malformations. Nat Commun 10:2761 92. Boulday G, Rudini N, Maddaluno L, Ble´con A, Arnould M, Gaudric A, Chapon F, Adams RH, Dejana E, Tournier-Lasserve E (2011) Developmental timing of CCM2 loss influences cerebral cavernous malformations in mice. J Exp Med 208:1835–1847 93. Chan AC, Drakos SG, Ruiz OE, Smith AC, Gibson CC, Ling J, Passi SF, Stratman AN, Sacharidou A, Revelo MP, Grossmann AH, Diakos NA, Davis GE, Metzstein MM, Whitehead KJ, Li DY (2011) Mutations in 2 distinct genetic pathways result in cerebral cavernous malformations in mice. J Clin Invest 121:1871–1881 94. Zhou Z, Tang AT, Wong WY, Bamezai S, Goddard LM, Shenkar R, Zhou S, Yang J, Wright AC, Foley M, Arthur JS, Whitehead KJ, Awad IA, Li DY, Zheng X, Kahn ML (2016) Cerebral cavernous malformations arise from endothelial gain of MEKK3KLF2/4 signalling. Nature 532:122–126 95. Louvi A, Chen L, Two AM, Zhang H, Min W, Gu¨nel M (2011) Loss of cerebral cavernous malformation 3 (Ccm3) in neuroglia leads to CCM and vascular pathology. Proc Natl Acad Sci U S A 108:3737–3742 96. Bacigaluppi S, Retta SF, Pileggi S, Fontanella M, Goitre L, Tassi L, La Camera A, Citterio A, Patrosso MC, Tredici G, Penco S (2013) Genetic and

cellular basis of cerebral cavernous malformations: implications for clinical management. Clin Genet 83:7–14 97. Marchi S, Trapani E, Corricelli M, Goitre L, Pinton P, Retta SF (2016) Beyond multiple mechanisms and a unique drug: defective autophagy as pivotal player in cerebral cavernous malformation pathogenesis and implications for targeted therapies. Rare Dis 4: e1142640 98. Glading A, Han J, Stockton RA, Ginsberg MH (2007) KRIT-1/CCM1 is a Rap1 effector that regulates endothelial cell cell junctions. J Cell Biol 179:247–254 99. Glading AJ, Ginsberg MH (2010) Rap1 and its effector KRIT1/CCM1 regulate betacatenin signaling. Dis Model Mech 3:73–83 100. Liu W, Draheim KM, Zhang R, Calderwood DA, Boggon TJ (2013) Mechanism for KRIT1 release of ICAP1-mediated suppression of integrin activation. Mol Cell 49:719–729 101. Faurobert E, Rome C, Lisowska J, ManetDupe´ S, Boulday G, Malbouyres M, Balland M, Bouin AP, Ke´ramidas M, Bouvard D, Coll JL, Ruggiero F, TournierLasserve E, Albiges-Rizo C (2013) CCM1ICAP-1 complex controls β1 integrindependent endothelial contractility and fibronectin remodeling. J Cell Biol 202:545–561 102. Macek Jilkova Z, Lisowska J, Manet S, Verdier C, Deplano V, Geindreau C, Faurobert E, Albige`s-Rizo C, Duperray A (2014) CCM proteins control endothelial β1 integrin dependent response to shear stress. Biol Open 3:1228–1235 103. Crose LE, Hilder TL, Sciaky N, Johnson GL (2009) Cerebral cavernous malformation 2 protein promotes smad ubiquitin regulatory factor 1-mediated RhoA degradation in endothelial cells. J Biol Chem 284:13301–13305 104. Borikova AL, Dibble CF, Sciaky N, Welch CM, Abell AN, Bencharit S, Johnson GL (2010) Rho kinase inhibition rescues the endothelial cell cerebral cavernous malformation phenotype. J Biol Chem 285:11760–11764 105. Stockton RA, Shenkar R, Awad IA, Ginsberg MH (2010) Cerebral cavernous malformations proteins inhibit Rho kinase to stabilize vascular integrity. J Exp Med 207:881–896 106. Richardson BT, Dibble CF, Borikova AL, Johnson GL (2013) Cerebral cavernous malformation is a vascular disease associated with activated RhoA signaling. Biol Chem 394:35–42

The Long Climb to the Cure of CCM Disease 107. Wu¨stehube J, Bartol A, Liebler SS, Bru¨tsch R, Zhu Y, Felbor U, Sure U, Augustin HG, Fischer A (2010) Cerebral cavernous malformation protein CCM1 inhibits sprouting angiogenesis by activating DELTA-NOTCH signaling. Proc Natl Acad Sci U S A 107:12640–12645 108. You C, Sandalcioglu IE, Dammann P, Felbor U, Sure U, Zhu Y (2013) Loss of CCM3 impairs DLL4-Notch signalling: implication in endothelial angiogenesis and in inherited cerebral cavernous malformations. J Cell Mol Med 17:407–418 109. Schulz GB, Wieland E, Wu¨stehube-Lausch J, Boulday G, Moll I, Tournier-Lasserve E, Fischer A (2015) Cerebral cavernous malformation-1 protein controls DLL4Notch3 signaling between the endothelium and pericytes. Stroke 46:1337–1343 110. Kar S, Baisantry A, Nabavi A, Bertalanffy H (2016) Role of delta-notch signaling in cerebral cavernous malformations. Neurosurg Rev 39:581–589 111. You C, Zhao K, Dammann P, Keyvani K, Kreitschmann-Andermahr I, Sure U, Zhu Y (2017) EphB4 forward signalling mediates angiogenesis caused by CCM3/PDCD10ablation. J Cell Mol Med 21:1848–1858 112. DiStefano PV, Kuebel JM, Sarelius IH, Glading AJ (2014) KRIT1 protein depletion modifies endothelial cell behavior via increased vascular endothelial growth factor (VEGF) signaling. J Biol Chem 289:33054–33065 113. Kar S, Samii A, Bertalanffy H (2015) PTEN/ PI3K/Akt/VEGF signaling and the cross talk to KRIT1, CCM2, and PDCD10 proteins in cerebral cavernous malformations. Neurosurg Rev 38:229–236; discussion 236–227 114. Cullere X, Plovie E, Bennett PM, MacRae CA, Mayadas TN (2015) The cerebral cavernous malformation proteins CCM2L and CCM2 prevent the activation of the MAP kinase MEKK3. Proc Natl Acad Sci U S A 112:14284–14289 115. Zhou Z, Rawnsley DR, Goddard LM, Pan W, Cao XJ, Jakus Z, Zheng H, Yang J, Arthur JS, Whitehead KJ, Li D, Zhou B, Garcia BA, Zheng X, Kahn ML (2015) The cerebral cavernous malformation pathway controls cardiac development via regulation of endocardial MEKK3 signaling and KLF expression. Dev Cell 32:168–180 116. Choi JP, Foley M, Zhou Z, Wong WY, Gokoolparsadh N, Arthur JS, Li DY, Zheng X (2016) Micro-CT imaging reveals Mekk3 heterozygosity prevents cerebral cavernous

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malformations in Ccm2-deficient mice. PLoS One 11:e0160833 117. Jenny Zhou H, Qin L, Zhang H, Tang W, Ji W, He Y, Liang X, Wang Z, Yuan Q, Vortmeyer A, Toomre D, Fuh G, Yan M, Kluger MS, Wu D, Min W (2016) Endothelial exocytosis of angiopoietin-2 resulting from CCM3 deficiency contributes to cerebral cavernous malformation. Nat Med 22:1033–1042 118. Cuttano R, Rudini N, Bravi L, Corada M, Giampietro C, Papa E, Morini MF, Maddaluno L, Baeyens N, Adams RH, Jain MK, Owens GK, Schwartz M, Lampugnani MG, Dejana E (2016) KLF4 is a key determinant in the development and progression of cerebral cavernous malformations. EMBO Mol Med 8:6–24 119. Orso F, Balzac F, Marino M, Lembo A, Retta SF, Taverna D (2013) miR-21 coordinates tumor growth and modulates KRIT1 levels. Biochem Biophys Res Commun 438:90–96 120. Kar S, Bali KK, Baisantry A, Geffers R, Samii A, Bertalanffy H (2017) Genome-wide sequencing reveals microRNAs downregulated in cerebral cavernous malformations. J Mol Neurosci 61:178–188 121. Antognelli C, Perrelli A, Armeni T, Talesa VN, Retta SF, (2020) Dicarbonyl Stress and S-Glutathionylation in Cerebrovascular Diseases: A Focus on Cerebral Cavernous Malformations. Antioxidants 9 (2):124 122. Finetti F, Schiavo I, Ercoli J, Zotta A, Boda E, Retta SF, Trabalzini L, (2020) KRIT1 lossmediated upregulation of NOX1 in stromal cells promotes paracrine pro-angiogenic responses. Cellular Signalling 68:109527 123. Marchi S, Retta SF, Pinton P (2016) Cellular processes underlying cerebral cavernous malformations: autophagy as another point of view. Autophagy 12:424–425 124. Corr M, Lerman I, Keubel JM, Ronacher L, Misra R, Lund F, Sarelius IH, Glading AJ (2012) Decreased Krev interaction-trapped 1 expression leads to increased vascular permeability and modifies inflammatory responses in vivo. Arterioscler Thromb Vasc Biol 32:2702–2710 125. Fidalgo M, Guerrero A, Fraile M, Iglesias C, Pombo CM, Zalvide J (2012) Adaptor protein cerebral cavernous malformation 3 (CCM3) mediates phosphorylation of the cytoskeletal proteins ezrin/radixin/moesin by mammalian Ste20-4 to protect cells from oxidative stress. J Biol Chem 287:11556–11565

24

Saverio Francesco Retta et al.

126. Goitre L, Pergolizzi B, Ferro E, Trabalzini L, Retta SF (2012) Molecular crosstalk between integrins and cadherins: do reactive oxygen species set the talk? J Sig Transduct 2012:807682 127. Ferro E, Goitre L, Baldini E, Retta SF, Trabalzini L (2014) Ras GTPases are both regulators and effectors of redox agents. Methods Mol Biol 1120:55–74 ´ lvarez-Aznar ˜a B, Ando K, A 128. Castro M, Lavin A, Abu Taha A, Brakebusch C, Dejana E, Betsholtz C, Gaengel K (2019) CDC42 Deletion Elicits Cerebral Vascular Malformations via Increased MEKK3-Dependent KLF4 Expression. Circulation Research 124 (8):1240–1252 129. Aaron Hobbs G, Zhou B, Cox AD, Campbell SL (2014) Rho GTPases, oxidation, and cell redox control. Small GTPases 5(2):e28579 130. Li DY, Whitehead KJ (2010) Evaluating strategies for the treatment of cerebral cavernous malformations. Stroke 41:S92–S94 131. Nishimura S, Mishra-Gorur K, Park J, Surovtseva YV, Sebti SM, Levchenko A, Louvi A, Gunel M (2017) Combined HMG-COA reductase and prenylation inhibition in treatment of CCM. Proc Natl Acad Sci U S A 114:5503–5508 132. Shenkar R, Peiper A, Pardo H, Moore T, Lightle R, Girard R, Hobson N, Polster SP, Koskim€aki J, Zhang D, Lyne SB, Cao Y, Chaudagar K, Saadat L, Gallione C, Pytel P, Liao JK, Marchuk D, Awad IA (2019) Rho kinase inhibition blunts lesion development and hemorrhage in murine models of aggressive Pdcd10/Ccm3 disease. Stroke 50:738–744 133. McDonald DA, Shi C, Shenkar R, Stockton RA, Liu F, Ginsberg MH, Marchuk DA, Awad IA (2012) Fasudil decreases lesion burden in a murine model of cerebral cavernous malformation disease. Stroke 43:571–574 134. Shenkar R, Shi C, Austin C, Moore T, Lightle R, Cao Y, Zhang L, Wu M, Zeineddine HA, Girard R, McDonald DA, Rorrer A, Gallione C, Pytel P, Liao JK, Marchuk DA, Awad IA (2017) RhoA kinase inhibition with fasudil versus simvastatin in murine models of cerebral cavernous malformations. Stroke 48:187–194 135. McKerracher L, Shenkar R, Abbinanti M, Cao Y, Peiper A, Liao JK, Lightle R, Moore T, Hobson N, Gallione C, Ruschel J, Koskim€aki J, Girard R, Rosen K, Marchuk DA, Awad IA (2019) A brain-targeted orally available ROCK2 inhibitor benefits mild and aggressive cavernous angioma disease. Transl Stroke Res

136. Bravi L, Rudini N, Cuttano R, Giampietro C, Maddaluno L, Ferrarini L, Adams RH, Corada M, Boulday G, Tournier-Lasserve E, Dejana E, Lampugnani MG (2015) Sulindac metabolites decrease cerebrovascular malformations in CCM3-knockout mice. Proc Natl Acad Sci U S A 112:8421–8426 137. Choi JP, Wang R, Yang X, Wang X, Wang L, Ting KK, Foley M, Cogger V, Yang Z, Liu F, Han Z, Liu R, Baell J, Zheng X (2018) Ponatinib (AP24534) inhibits MEKK3-KLF signaling and prevents formation and progression of cerebral cavernous malformations. Sci Adv 4:eaau0731 138. Shi C, Shenkar R, Zeineddine HA, Girard R, Fam MD, Austin C, Moore T, Lightle R, Zhang L, Wu M, Cao Y, Gunel M, Louvi A, Rorrer A, Gallione C, Marchuk DA, Awad IA (2016) B-cell depletion reduces the maturation of cerebral cavernous malformations in murine models. J Neuroimmune Pharmacol 11:369–377 139. Lopez-Ramirez MA, Pham A, Girard R, Wyseure T, Hale P, Yamashita A, Koskim€aki J, Polster S, Saadat L, Romero IA, Esmon CT, Lagarrigue F, Awad IA, Mosnier LO, Ginsberg MH (2019) Cerebral cavernous malformations form an anticoagulant vascular domain in humans and mice. Blood 133:193–204 140. Moschovi M, Alexiou GA, Stefanaki K, Tourkantoni N, Prodromou N (2010) Propranolol treatment for a giant infantile brain cavernoma. J Child Neurol 25:653–655 141. Filippidis AS, Fountas KN, Kalani MY, Zabramski JM, Spetzler RF (2011) Letter by Filippidis et al regarding article, “Evaluating strategies for the treatment of cerebral cavernous malformations”. Stroke 42:e373 142. Berti I, Marchetti F, Skabar A, Zennaro F, Zanon D, Ventura A (2014) Propranolol for cerebral cavernous angiomatosis: a magic bullet. Clin Pediatr (Phila) 53:189–190 143. Zabramski JM, Kalani MYS, Filippidis AS, Spetzler RF (2016) Propranolol treatment of cavernous malformations with symptomatic hemorrhage. World Neurosurg 88:631–639 144. Reinhard M, Schuchardt F, Meckel S, Heinz J, Felbor U, Sure U, Geisen U (2016) Propranolol stops progressive multiple cerebral cavernoma in an adult patient. J Neurol Sci 367:15–17 145. Eisa-Beygi S, Wen XY, Macdonald RL (2014) A call for rigorous study of statins in resolution of cerebral cavernous malformation pathology. Stroke 45:1859–1861

The Long Climb to the Cure of CCM Disease 146. Goldberg J, Jaeggi C, Schoeni D, Mordasini P, Raabe A, Bervini D (2018) Bleeding risk of cerebral cavernous malformations in patients on β-blocker medication: a cohort study. J Neurosurg:1–6 147. Apra C, Dumot C, Bourdillon P, PelissouGuyotat I (2019) Could propranolol be beneficial in adult cerebral cavernous malformations? Neurosurg Rev 42:403–408 148. Polster SP, Stadnik A, Akers AL, Cao Y, Christoforidis GA, Fam MD, Flemming KD, Girard R, Hobson N, Koenig JI, Koskim€aki J, Lane K, Liao JK, Lee C, Lyne SB, McBee N, Morrison L, Piedad K, Shenkar R, Sorrentino M, Thompson RE, Whitehead KJ, Zeineddine HA, Hanley DF, Awad IA (2018) Atorvastatin treatment of cavernous angiomas with symptomatic

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hemorrhage exploratory proof of concept (AT CASH EPOC) trial. Neurosurgery 149. Westover MB, Bianchi MT, Eckman MH, Greenberg SM (2011) Statin use following intracerebral hemorrhage: a decision analysis. Arch Neurol 68:573–579 150. Goldstein LB (2011) Statins after intracerebral hemorrhage: to treat or not to treat. Arch Neurol 68:565–566 151. Perrelli A, Goitre L, Salzano AM, Moglia A, Scaloni A, Retta SF (2018) Biological activities, health benefits, and therapeutic properties of avenanthramides: from skin protection to prevention and treatment of cerebrovascular diseases. Oxidative Med Cell Longev 2018:6015351

Chapter 2 Incidence, Prevalence, and Clinical Presentation of Cerebral Cavernous Malformations Kelly D. Flemming Abstract The incidence, prevalence, and mode of presentation of cavernous malformations is important to better understand the disease, educate patients and practitioners, aid in treatment decisions, and to design clinical trials. Prior to the advent of MRI, cavernous malformations were often diagnosed only when a catastrophic event occurred and/or the lesion was removed. With the more frequent diagnostic use of MRI, it has become clear that cavernous malformations are more prevalent than previously thought and many are identified incidentally. The remainder may present to clinical attention with intracerebral hemorrhage, seizure without hemorrhage, or focal neurologic deficit without overt hemorrhage. The precise reason why some cavernous malformations become symptomatic and others remain asymptomatic is not clear. However, evolving data suggests that brainstem location, estrogen use in women, and low vitamin D may play a role in hemorrhagic presentation. Key words Cavernous malformation, Epidemiology, Prevalence, Incidence, Clinical presentation

1

Introduction The incidence, prevalence, and mode of presentation of disease is important to understand the disease, educate patients and practitioners, make treatment decisions, and design clinical trials. Prior to MRI, cavernous malformations (CM) were often diagnosed at the time of a symptomatic event leading to the erroneous conclusion that most CM were dangerous lesions with a high rate of bleeding. As MRI use has become more frequent since the late 1980s, it has become clear that both symptomatic and asymptomatic diseases exist. Herein we describe the current state of knowledge of incidence and prevalence of CM as well as how patients first present to medical attention.

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_2, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Incidence Incidence refers to the number of new diagnoses of a disease within a defined period of time. The exact incidence of CM is unknown as many patients are asymptomatic and MRI is generally required for the diagnosis. One population-based study, performed largely before the common use of MRI (1965–1992), reported the age and sex adjusted detection rate of CM was 0.17 per 100,000 people per year [1]. This study likely underestimated the number of asymptomatic patients who would require MRI for diagnosis. A second population-based study evaluating patients between 1999 and 2000 found an annual detection rate of 0.56 per 100,000 per year for adults over age 16 years [2].

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Prevalence Prevalence refers to the proportion of people living with a disease (whether newly diagnosed or previously diagnosed) within a given time period. The prevalence of CM has been estimated in autopsy series, clinical series, and in non-clinical MRI studies. Despite the differences and biases in the studies, the prevalence of CM is estimated between 0.2 and 0.9% of the population [3–6]. Autopsy studies may be biased by sampling limitations, low rates of autopsy, and referral bias. Despite limitations, autopsy studies estimate CM prevalence between 0.2 and 0.5% [3, 4]. Up to 90% of patients with CM diagnosed at autopsy were asymptomatic. Estimates of CM prevalence from clinical MRI studies range between 0.39 and 0.9% [5, 7, 8]. Because patients are undergoing a clinical MRI, these studies may overestimate symptomatic disease and underestimate incidental CM. In clinical series, 40–80% of patients may have associated symptoms. In addition, clinically based studies often suffer from referral bias. Patients in the general population may differ from those seeking medical attention for symptoms. Several studies have estimated CM prevalence in patients undergoing MRI for non-clinical purposes. These studies reduce the potential for referral bias and symptomatic disease. The estimated prevalence from these studies is approximately 0.16–0.7% [9–11]. These studies can be limited by lack of clinical data regarding symptomatology and radiologic data. In one population-based study of patients 50–89 years of age, MRI scans were performed in a subset of patients participating in the Mayo Clinic Study of Aging [6]. Using propensity-based analysis, the age and sex adjusted prevalence was 0.46% of the population. The frequency of symptoms associated with CM was only 0.037%. This study improved on

Epidemiology of Cavernous Malformations

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the prevalence data regarding symptomatic vs. asymptomatic CM, but this study was limited to patients over 50 years of age. From our prospective cohort [12], the average age of symptomatic patients is 41.8 years compared to 46.5 years for those found incidentally. Thus such a study evaluating only CM patients over 50 might underestimate the prevalence of symptomatic disease. The prevalence of men and women in these studies combined is not significantly different [5–8]. CM may be sporadic or familial. Sporadic CMs often have a single lesion with an associated developmental venous anomaly (DVA). The familial form is commonly characterized by multiple lesions, generally without DVA and may be due to 1 of 3 genetic mutations. The exact prevalence of each form is not clear. However, general estimates from large clinical cohorts suggest that approximately 20% of patients with CM have the genetic form and 80% are sporadic [13–16]. One study assessed the prevalence of an associated CM with DVA in 1689 patients with a radiologically diagnosed DVA [17]. They found that with each decade of life, the prevalence of an associated CM increased. The prevalence of CM with a DVA was 11.6% for those patients over 70 years compared to just 0.8% of DVA associated with a CM in those patients under 10. This suggests that the prevalence of the sporadic form increases with age.

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Clinical Presentation Patients with CM may come to first clinical attention due to hemorrhage from a CM, seizure without hemorrhage, focal neurologic deficit without hemorrhage or the lesion may be an incidental finding. Many clinical cohorts have been published with wide ranging proportions of patients in each group (Table 1) [6, 12, 13, 18– 21]. The cohorts vary in the proportion of familial form, the number of brainstem locations included, and how clinical information was obtained. Referral bias is common in tertiary care cohorts and/or surgical cohorts. The only population-based study showed an incidental rate of detection as high as 47%. In that study, 12% presented with hemorrhage, 15% with focal neurologic deficits not associated with hemorrhage, and 25% with seizures [13]. Little is known about the risk factors for presentation with hemorrhage or other symptoms. In a prospective study by Flemming and colleagues [12] detailed information was collected about CM patients including demographic data, clinical comorbidities, medications, and radiologic data on 202 patients. In this cohort, 58.4% were female and the average age of diagnosis was 43.7  16.5 years. CM was an incidental finding in 40.6% of patients. 37.1%, 6.5%, and 14.8% of patients present with hemorrhage, focal neurologic deficit, and seizures, respectively. In this

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Kelly D. Flemming

Table 1 First clinical presentation in patients with CM from selected cohorts

Cohort

N (patients)

Incidental (%)

Hemorrhage (%)

Seizure (%)

Focal neurologic deficit (%)

Aiba (1995) [18]

110

20.9%

56.3%

22.7%

0

Al Shahi Salman (2012) [13]

139

47%

12%

25%

15%

Flemming Retrospective [14]

292

37.6%

25.3%

26.0%

11.1%

Flemming (2020) [12]

202

40.6%

37.1%

14.8%

6.5%

1620

28.4%

35.5%

20.8%

15.2%

a

12.5%

47.5%

30.0%

10.0%

12%

25%

36%

20%

Horne (Meta-analysis) [19] LaBauge (2000) [20]

40

Porter (1997) [21]

173

In alphabetic order a Familial only

cohort, brainstem location, estrogen use by women, and low 25-hydroxy vitamin D levels were more commonly associated with presentation with hemorrhage compared to the group that did not present with hemorrhage [12, 22, 23]. It was further noted that patients taking daily aspirin or NSAIDS were less likely to present with hemorrhage. While numbers were small, the influence of estrogen and aspirin were predominantly noted in the sporadic group and thus there may be important differences in the sporadic versus familial groups. In the same cohort, when looking at any symptomatic presentation (seizure, focal neurologic deficit, or hemorrhage) compared to incidental CM, the main risk factor was brainstem location and younger age. Factors more commonly present in the asymptomatic group and potentially protective compared to the symptomatic group included: chronic inflammatory disease, vitamin D supplementation, aspirin, NSAIDS, and statin use (Flemming et al., unpublished data). From a retrospective cohort of patients diagnosed between 1989 and 1999, Flemming and colleagues reported a seasonal variation in hemorrhagic presentation in patients with cavernous malformation [24]. In that cohort, patients were more likely to present with hemorrhage during fall or winter months compared to spring or summer months. Authors proposed a possible role for seasonal variation of vitamin D levels with the lowest levels occurring in the fall or winter months or a potential relationship to the flu season resulting in increased inflammation. However, the same group did not find similar seasonal variation in their prospective cohort of patients between 2015 and 2018 (Flemming et al.,

Epidemiology of Cavernous Malformations

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unpublished). Authors suggest that nearly 30% of patients in the prospective cohort were taking vitamin D supplementation and the use of supplements was distinctly less common in the 1980s and early 1990s [25]. Thus the difference in seasonal variation between the two cohorts could relate to vitamin D supplementation or have been a spurious finding.

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Conclusions The incidence of CM is approximately 0.56 per 100,000 people per year [13]. Approximately 1 in 200 people has a CM, but only about 1 in 2000 patients may be symptomatic. In order of most to least prevalent, patients may present to medical attention for the first time because of symptoms not related to the CM (12–47%), hemorrhage (12–56.3%), seizure (20.8–36.0%), or focal neurologic deficit (6.5–15.2%). Risk factors for presentation with hemorrhage include: brainstem location, low 25-hydroxy vitamin D, and potentially the use of estrogen in select women. Possible protective factors might include aspirin. Further studies are needed to assess whether these risk factors predict future disease activities after presentation. This epidemiologic information may be important in educating patients and in particular, reassuring asymptomatic patients. With new medication options as an alternative to surgery on the horizon [22, 23], epidemiologic data can help determine the prevalence of disease and therefore the number of possible participants for clinical trials with symptomatic disease. This information can be useful to analyze power calculations and determining the sample size required and the number of centers required to enroll enough patients.

References 1. Brown RD, Wiebers DO, Torner J, O’Fallon WM (1996) Incidence and prevalence of intracranial vascular malformations in Olmsted County, Minnesota, 1965-1992. Neurology 46:949–952 2. Al-Shahi Salman R, Bhattacharya JJ, Currie DG, Papanastassiou V, Ritchie V, Roberts RC, Sellar RJ, Warlow CP (2003) Prospective, population-based detection of intracranial vascular malformations in adults: the Scottish intracranial vascular malformation study (SIVMS). Stroke 34:1163–1169. https://doi. org/10.1161/01.str.0000069018.90456.c9

3. Courville CB (1950) Pathology of the central nervous system, 3rd edn. Pacific Press Publishing Association, Mountain View, CA 4. Otten P, Pizzolato GP, Rilliet B, Berney J (1989) 131 cases of cavernous angioma (cavernomas) of the CNS, discovered by retrospective analysis of 24,535 autopsies. Neuro-Chirurgie 35:128–131 5. Al-Holou WN, O’Lynnger TM, Pandey AS, Gemmete JJ, Thompson BG, Muraszko KM, Garton HJ, Maher CO (2012) Natural history and imaging prevalence of cavernous malformations in children and young adults. J Neurosurg Pediatr 9:198–205. https://doi.org/ 10.3171/2011.11.peds11390

32

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6. Flemming KD, Graff-Radford J, Aakre J, Lanzino G, Brown RD Jr, Mielke MM, Roberts RO, Kremers W, Knopman DS, Petersen RC, Jack CR Jr (2017) Population-based prevalence of cerebral cavernous malformations in older adults: mayo clinic study of aging. JAMA Neurol 74:801–805 7. DelCurling O Jr, Kelly DL Jr, Elster AD, Craven TE (1991) An analysis of the natural history of cavernous angiomas. J Neurosurg 75:702–708 8. Sage MR, Brophy BP, Sweeney C, Phipps S, Perrett LV, Sandhu A, Albertyn LE (1993) Cavernous haemangiomas (angiomas) of the brain: clinically significant lesions. Australas Radiol 37:147–155 9. Vernooij MW, Ikram MA, Tanghe HL, Vincent AJPE, Hofman A, Krestin GP, Niessen WJ, MMB B, van der Lugt A (2007) Incidental findings on brain MRI in the general population. N Engl J Med 357:1821–1828 10. Morris Z, Whiteley WN, Longstreth WT Jr, Weber F, Lee YC, Tsushima Y, Alphs H, Ladd SC, Warlow C, Wardlaw JM, Al-Shahi Salman R (2009) Incidental findings on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 339:b3016. https://doi. org/10.1136/bmj.b3016 11. Bos D, Poels MM, Adams HH, Akoudad S, Cremers LG, Zonneveld HI, Hoogendam YY, Verhaaren BF, Verlinden VJ, Verbruggen JG, Peymani A, Hofman A, Krestin GP, Vincent AJ, Feelders RA, Koudstaal PJ, van der Lugt A, Ikram MA, Vernooij MW (2016) Prevalence, clinical management, and natural course of incidental findings on brain MR images: the population-based Rotterdam scan study. Radiology 281:507–515. https://doi. org/10.1148/radiol.2016160218 12. Flemming KD, Kumar S, Brown, RD, Lanzino, G (2020) Predictors of Initial Clinical Presentation of Hemorrhage in Patients with Cavernous Malformation, World Neurosurgery, 133: e767–773 13. Al-Shahi Salman R, Hall JM, Horne MA, Moultrie F, Josephson CB, Bhattacharya JJ, Counsell CE, Murray GD, Papanastassiou V, Ritchie V, Roberts RC, Sellar RJ, Warlow CP, Scottish Audit of Intracranial Vascular Malformations collaborators (2012) Untreated clinical course of cerebral cavernous malformations: a prospective, population-based cohort study. Lancet Neurol 11:217–224. https://doi.org/ 10.1016/S1474-4422(12)70004-2

14. Flemming KD, Link MJ, Christianson TJ, Brown RD Jr (2012) The prospective hemorrhage risk of intracerebral cavernous malformations. Neurology 78:632–636 15. Akers A, Al-Shahi Salman R, Awad I, Dahlem K, Flemming KD, Hart B, Kim H, Jusue-Torres I, Kondziolka D, Lee C, Morrison L, Rigamonti D, Rebeiz T, Tournier-Lasserve E, Waggoner D, Whitehead K (2017) Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the angioma alliance scientific advisory board clinical experts panel. Neurosurgery 80:665–680 16. Morrison L, Akers A (2003) Cerebral Cavernous malformation, familial. University of Washington, Seattle; 1993-2019. https:// www.ncbi.nlm.nih.gov/books/NBK1293/. Accessed 30 Jul 2019 17. Brinjikji W, El-Masri AE, Wald JT, Flemming KD, Lanzino G (2017) Prevalence of cerebral cavernous malformations associated with developmental venous anomalies increases with age. Child Nerv Syst June, vol 33, p 1539 18. Aiba T, Tanaka R, Koike T, Kameyama S, Takeda N, Komata T (1995) Natural history of intracranial cavernous malformations. J Neurosurg 83:56–59 19. Horne MA, Flemming KD, Su IC, Stapf C, Jeon JP, Li D, Maxwell SS, White P, Christianson TJ, Agid R, Cho WS, Oh CW, Wu Z, Zhang JT, Kim JE, Ter Brugge K, Willinsky R, Brown RD Jr, Murray GD, Al-Shahi Salman R, Cerebral Cavernous Malformations Individual Patient Data Metaanalysis Collaborators (2016) Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data. Lancet Neurol 15:166–173. https://doi.org/10. 1016/S1474-4422(15)00303-8 20. Labauge P, Brunereau L, Le´vy C, Laberge S, Houtteville JP (2000) The natural history of familial cerebral cavernomas: a retrospective MRI study of 40 patients. Neuroradiology 42:327–332 21. Porter PJ, Willinsky RA, Harper W, Wallace MC (1997) Cerebral cavernous malformations: natural history and prognosis after clinical deterioration with or without hemorrhage. J Neurosurg 87:190–197 22. Awad IA, Polster SP (2019) Cavernous angiomas: deconstructing a neurosurgical disease. J Neurosurg 131:1–13. https://doi.org/10. 3171/2019.3.JNS181724

Epidemiology of Cavernous Malformations 23. Chohan MO, Marchio S, Morrison LA, Sidman RL, Cavenee WK, Dejana E, Yonas H, Pasqualini R, Arap W (2018) Emerging pharmacologic targets in cerebral cavernous malformation and potential strategies to Alter the natural history of a difficult disease: a review. JAMA Neurol 76:492. https://doi.org/10. 1001/jamaneurol.2018.3634 24. Flemming KD, Brown RD, Link MJ (2015) Seasonal variation in hemorrhage and focal

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neurologic deficit due to intracerebral cavernous malformations. J Clin Neurosci 22:969–971. https://doi.org/10.1016/j. jocn.2015.01.007 25. NIH State-of-the-Science Conference Statement on Multivitamin/Mineral Supplements and Chronic Disease Prevention (2006) NIH consensus and state-of-the-science statements. NIH Consens State Sci Statements 23:1–30

Chapter 3 Natural History, Clinical, and Surgical Management of Cavernous Malformations Giovanni G. Vercelli, Fabio Cofano, Filippo Veneziani Santonio, Francesca Vincitorio, Francesco Zenga, and Diego Garbossa Abstract We describe Natural history, clinical and surgical management of cavernous malformation of the brain and spinal cord. Decision-making for treatment of cavernous malformations cannot ignore their natural history and risk of bleeding, which is different depending on the location. Surgical morbidity also depends on the position of the lesion. We performed a review of hemorrhage risk and clinical assessment of superficial and deep supratentorial, brainstem and intramedullary cavernous malformations. Key words Cavernous malformations, Angioma, Hemorrhage risk, Microsurgical management, Natural history

1

Introduction The first successful removal of a brainstem CM was performed by Walter Dandy in 1934. With the advent of MRI in the 1990s, CM diagnoses began to increase. In this chapter, we will review the natural history, risk of hemorrhage and rehemorrhage, and clinical presentation of cavernous malformations (CMs). The former features are discussed in separate paragraphs, based on the different locations of the CM. When considering surgical treatment, the risk of hemorrhage and therefore clinical onset, or worsening, should be considered and compared to the surgical morbidity. Peri-operative risk varies in relation to the location of the lesion.

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_3, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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1.1 Supratentorial Cavernous Malformations 1.1.1 Epidemiology

1.2 Clinical Presentation

The distribution of sporadic CM throughout the central nervous system is approximately proportionate to its various components. The supratentorial compartment is involved in nearly 80% of the cases [1]. These lesions can be found as single entities or with concomitant venous angiomas or telangiectasias. Developmental venous anomaly (DVA) has been reported in about 2–30% of patients with cavernous malformations. There is still considerable controversy in cited rates and risk factors for bleeding. CMs predisposition to rupture is possibly influenced by different factors including location, history of previous rupture, female sex, size, and presence of an associated DVA. The factor most consistently associated with increased risk for rupture is location [2]. The hemorrhage rate of supratentorial lesions may be 30 times lower than that of lesions in the infratentorial compartment. It is estimated that the incidence of symptomatic hemorrhages in supratentorial CMs is approximately 0.5% per patient-year [3]. However, evaluation of the hemorrhagic risk in the supratentorial compartment is somewhat difficult since many lesions are located in areas with low sensitivity to bleeding. Thus hemorrhage might be undetected due to lack of symptoms. After one hemorrhage the risk of a subsequent bleeding is substantially increased. With each hemorrhagic event, symptoms tend to worsen and then improve. Nevertheless a stepwise progression towards clinical worsening is usually described [3, 4]. Regardless of the clinical picture, evidence of previous hemorrhage is a constant feature of supratentorial CMs, as in any other location. Repeated small hemorrhages and thrombosis within the lesion result in size increase. Organization within the hemorrhagic/ thrombotic cavities creates the potential for further growth. Rarely, these lesions rupture outside their capsule and produce wide hemorrhages into the adjacent brain tissue. Compared to other locations, supratentorial CMs are responsible for the onset of epileptic seizures in 40–70% of the patients. Seizures are medically intractable in 35–40% of the cases and these patients are affected by the so-called supratentorial cerebral cavernous malformation associated epilepsy (SCCMAE). Few data are available regarding the annual risk for the onset of seizures and reported rates for new onset of seizures of 1–2.5% per person-year [5]. The onset or exacerbation of seizure activity in these patients is often associated with MRI evidence of acute/subacute hemorrhage. Since CMs are low-flow and low-pressure lesions, supratentorial hemorrhagic events have usually a relatively benign course. Even extra-capsular overt hemorrhage usually displaces and compresses the surrounding neural tissue rather than destroying it.

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The presence of symptoms is due to previous hemorrhage from the lesion, regardless of whether the clinical onset is insidious or apoplectic. These events are represented mainly by repeated microhemorrhages that cause hemosiderin to accumulate in the surrounding brain giving rise to seizures. Other less frequent scenarios are important bleedings that manifest as apoplectic events. Rarely in the supratentorial compartment, progressive CM growth from repeated intralesional hemorrhage brings mass effect in eloquent areas. The signs and symptoms of patients with cerebral CMs are highly variable. Clinical onset is frequently subtle. The most common clinical presentations in patients affected by sporadic supratentorial CMs are seizures, followed by hemorrhage, focal neurological deficit without documented hemorrhage and headache alone. About 15–20% of supratentorial CMs are diagnosed incidentally. Seizures account for 40–80% of the initial symptoms [5]. Frontal, temporal, or perilimbic location may be at highest risk. The exact mechanism that leads to the seizure activity in these lesions is unknown. CMs are not considered intrinsically epileptogenic: the abnormal epileptic activity is believed to be induced on the surrounding brain tissue through to gliosis, deposits of blood breakdown products, ischemia, venous hypertension, and inflammatory reactions. The hemosiderin rim usually surrounding the lesion is heavily infiltrated with macrophages and iron, which has wellknown epileptogenic activity. 1.3

Management

Despite years of neurosurgical experience, current evidence supports recommendations for management of supratentorial CMs but with generally low classes and levels of evidence [6]. The natural history must be compared to the risk of surgery every time surgical treatment is in question. CM location, its proximity to the brain surface, and the expertise of the surgeon determine the risk of surgery [7]. In asymptomatic patients, especially with lesions in eloquent areas, resection of the CM is generally not recommended because of the benign natural history and the risk of post-operative complications. An exception considers CMs located in proximity to the ventricular system. These lesions have a higher risk of intraventricular hemorrhage since the ventricles do not provide sufficient tissue pressure to tamponade eventual bleeding. Moreover, because of psychological burden, expensive and time-consuming follow-ups or in patients who might need to be on anticoagulation, easily accessible solitary CMs in non-eloquent areas may be surgically treated. In symptomatic patients with easily accessible lesions, surgical removal of the CM is usually indicated since the risk of ulterior

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hemorrhages exceeds that of post-operative complications and sequelae. As for supratentorial CMs in eloquent regions, surgery should be considered only in front of recurrent hemorrhages or significant and/or worsening neurological deficits. The risk for new neurological sequelae after surgery for supratentorial non-eloquent CMs is equivalent to living with the CM for 2 years after a first hemorrhage. On the other hand, surgery in eloquent locations is associated with higher risk, equivalent to living with the CM for 5–10 years after a first bleed [6]. For lesions causing SCCMAE, the risk of recurrent seizures is up to 94% after a first unprovoked seizure. Surgery is usually indicated to reduce or eliminate the seizures as well as the risk of hemorrhage. When CM location allows it, the surrounding hemosiderin rim should be removed. Seizure control after resection of CM is obtained in approximately 80% of such patients. Success is higher if the preoperative duration of seizures is less than 1 year [5, 6]. It is advisable to perform surgery in a subacute phase 2–4 weeks after bleeding. The hemosiderin rim is likely to aid lesion identification and provides a cleavage plane, facilitating surgical dissection [6, 7]. Conflicting behavior regarding resection of DVAs associated with the CM has been described. Many authors advocate avoiding DVA dissection to prevent complications such as edema, hemorrhage, and venous infarcts [6]. Technical adjuncts including intraoperative image guidance, neurophysiologic monitoring, and laser-assisted technique are nowadays important tools in improving post-operative outcome, particularly when treating lesions located in eloquent areas. Although stereotactic radiosurgery (SRS) has been suggested as an alternative treatment for CMs, it is not recommended for asymptomatic supratentorial CMs nor for those that are surgically accessible due to radiation-associated morbidity. SRS may be considered in CMs located in eloquent areas with a history of repeated bleeding and high surgical risk. There is concern about ex novo CM genesis related to SRS in familial CMs [7, 8].

2

Deep-Seated Cavernous Malformations Deep-seated CMs represent a subgroup of lesions located in the thalamus, basal ganglia, insular region, periventricular area, and ventricular system. Because of the critical neurologic functions of these small and vulnerable cerebral regions, surgeons have to face significant challenges during resection of these CMs.

Cavernous Malformations: Clinical Assessment

2.1

Epidemiology

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Thalamic and basal ganglia CMs have been considered to occur infrequently, and their clinical significance is not well known. The incidence of the deep-seated CMs is 3.2/1,000,000 per year for symptomatic lesions and 0.8/1,000,000 per year for incidental lesions. A female preponderance has been noted, particularly among symptomatic lesions in thalamic and basal ganglia CMs. The age range at diagnosis varies between 5 and 54 years; most lesions however are diagnosed in the third and fourth decades of life [9].

2.2 Clinical Presentation

Symptoms and signs at presentation are closely related to the location of the lesion. Acute motor and/or sensory symptoms and signs with or without headache represent the most common presentation of thalamic CMs. Lesions located in the medial thalamus or protruding towards the third ventricle can cause hydrocephalus [10]. Hydrocephalus as presenting symptom can occur in up to 15% of thalamic CMs. Extrapyramidal symptoms, dystonia or hemichorea may also be related to deep-seated CMs. Seizures are not common in these lesions, unlike in superficial ones [9]. The rate of recurrent symptomatic hemorrhage is higher in deep-seated CMs compared to superficial lesions (4.1% per patient-year vs. 0% per patient-year) [9]. CMs in critical eloquent areas such as the thalamus become symptomatic with minimal volumetric increase. The overall risk of first hemorrhage from a thalamic or basal ganglia CM ranges between 0.7% and 5% per year. In patients with prior history of hemorrhage, the reported annual subsequent bleeding rate varies between 4.5% and 30% [11]. Familial and sporadic cases present no significant difference in the annual bleeding rate [4].

2.3

The clinical benefit of surgery for treatment of deep-seated cerebral CMs is still a matter of debate. Although the surgical removal of CMs is feasible, the benefits of reducing the rate of hemorrhage must be balanced against the risk of peri-operative morbidity. A recent meta-analysis, published in 2015, demonstrates postsurgical hemorrhage rate and complications related to surgeries on deep-seated CMs [12]. The post-surgical hemorrhage rate was low with a relatively high rate of post-operative complications. Surgical indication refers to symptomatic patients who suffered prior hemorrhage. A 3–4 weeks waiting to permit neurologic recovery and stabilization of the lesion is advisable. During the subacute phase (2–3 weeks), hemosiderin may be easily used as a trace to identify the cleavage plane during dissection of the lesion. DVAs are frequently associated with deep CMs. As for other locations, removal of the DVA is still at debate [6]. Some authors claim sparing these DVAs is key for successful surgery because they often contribute to the normal venous drainage from the thalamus, deep nuclei, and internal capsule [9, 13].

Management

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Patients with deep-seated and surgically inaccessible CM with prior history of multiple bleeding might benefit from SRS. A reduction of annual hemorrhage rate occurred in the first 2 years and 2 years after, despite several cases that suffer from negative side effects of radiation [14]. The benefit in treating CMs with a single bleed remains less clear. However, repeated hemorrhages carry a significant risk of increased morbidity which is far in excess of any radiosurgery-related morbidity. This finding seems to justify the early active management of deep-seated CMs [15].

3 3.1

Brainstem Cavernous Malformations Epidemiology

Brainstem CMs represent 4–35% of all the CMs of the central nervous system [16]. Most lesions become symptomatic in the fourth decade of life, with important repercussions on the quality of life of patients and their families [10]. The brainstem is a restricted anatomical area with a high concentration of eloquent nuclei and neural tracts. Therefore, CMs in this location are more prone to become symptomatic than supratentorial lesions. For the same reasons, sequelae for patients can be very serious. A meta-analysis of 25 studies on the natural history of CMs concluded that the annual rate of hemorrhage and rehemorrhage for brainstem cavernomas was respectively 2.8% (95% IC, 2.5–3.3%) and 32.3% (95% IN, 19.8–52.7%) per person-year [17]. The median time of rehemorrhage was of 10.5 months. The risk of symptomatic rehemorrhage decreases after 2 years. Complete recovery after hemorrhage was about 40% and no or minimal disability after hemorrhage was about 80%. Most of the studies that have estimated the risk of bleeding have assumed that all cavernomas were congenital, not evaluating ex novo formation of some CM. Therefore these studies probably underestimated the risk of bleeding. Brainstem cavernous malformations appear to be more likely to bleed than other CNS cavernomas. As said, probably this difference is explained by the sensitivity of the brainstem to even minor bleeding. In this region, hemorrhages might more easily cause symptoms compared to other less eloquent areas [10]. In 2016, Horne et al. estimated the risk of hemorrhage and rehemorrhage for CMs during untreated follow-up in an individual patient data meta-analysis. They considered only prospective cohort studies. The 5-year estimated risk of hemorrhage during untreated follow-up was 8.0% (0.1–15.9) for 80 people with brainstem CMs and the 5-year estimated risk of rehemorrhage was 30.8% (26.3–35.2) for 495 people with brainstem CM [18].

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3.2 Clinical Presentation

Signs and symptoms of brainstem CMs are due to mass effect on adjacent cranial nerves nuclei and ascending and descending neural tracts. The clinical onset can be acute if an important hemorrhagic episode occurs. On the other hand, symptoms can arise insidiously as consequence to multiple minor bleeding and thus slow growth of the cavernous malformation. Hemorrhagic events can be followed by partial or full remission of symptoms [10]. The features of clinical presentation depend on the location of the malformation within the brainstem. Approximately 15% are located in the medulla, 25% in the mesencephalon, and 60% in the pons. In a series of 100 patients, multiple presenting signs were common and included cranial nerves palsy (69%), ataxia or dysmetria (43%), sensory deficits (39%), motor deficits (38%), speech difficulty (12%), and an altered level of consciousness (6%). The most common subjective symptoms were headache (36%), vertigo or dizziness (24%), nausea and vomiting (16%), and trigeminal neuralgia (4%) [19].

3.3

The first clinical series were published at the beginning of the 1990s [20]. Initially, only symptomatic patients with multiple bleeding and lesions protruding from the pial or ependymal surface underwent surgery. The goal was to achieve a complete resection of the CM with minimal damage to the surrounding cerebral tissue. At the beginning simple concepts like the “two-point method” were used to select the best surgical approach [21]. With the evolution of microsurgical techniques and the discovery of “safe entry zones” in the brainstem [22], the surgical indications for brainstem CMs were expanded. Lesions appearing at the pial or ependymal level can be recognized for their blackish appearance or for the yellowish perilesional gliosis. If the lesion does not surface, the entry point into the parenchyma should be created with blunt dissection. The entry point must be the smallest possible and the major axis must follow the direction of the neural tracts. Neurophysiological monitoring and neuro-navigation can help in identifying the entry point. The objective is the complete resection of the CM with preservation of the possible DVA [19] and efforts should be made to keep the surrounding hemosiderin-laden gliotic parenchyma intact [22]. In a series of 397 patients, 125 (31.5%) underwent surgery within 6 weeks from hemorrhage. In the univariate analysis, mean GOS scores at last follow-up had improved for 88 of 125 patients (70.4%), compared with 165 of 272 patients (60.7%) who underwent surgery after 6 weeks (P ¼ 0.06). In the multivariate analysis, intervention within 6 weeks was a significant predictor of improved GOS on last follow-up (P ¼ 0.03, OR ¼ 1.73, 95% CI ¼ 1.06–2.83). Smaller lesion size was also a significant predictor of improved outcomes in the multivariate analysis [23]. Garcia et al. reported surgical outcome of 104 operated brainstem

Management

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CM. Favorable outcomes after resection were observed in 83 of 104 patients (mRS score 0–2, 79.8). Most patients (89.4%) showed relative improvements (54.8%) or were unchanged from their preoperative neurological baseline (34.6%) [24].

4 4.1

Intramedullary Cavernous Malformations Epidemiology

4.2 Clinical Presentation

The first description of surgical removal of a medullary CM was made by Schultze in 1912 [25]. Spinal locations have been considered very rare until the Magnetic Resonance Imaging (MRI) became widespread available. Since then, only anecdotal cases were reported in the literature. After the first series of McCormick et al. [26] and Cosgrove et al. [27] in 1988, several contributions have been added and CMs are now a well-recognized cause of myelopathy [10]. Intramedullary CMs constitute a considerable part of the angiomatous lesions involving the spine (5–12%) [28– 30], among the common vertebral body hemangioma and the rare extra-medullary extradural locations [31]. These lesions represent a fascinating challenge for neurosurgeons since the therapeutic strategy and its timing are still under debate. CMs occur mainly in the cervical and thoracic tracts, while cauda equina and conus medullaris are less common locations [10, 32]. A careful family history and brain MRI screening is recommended in patients with intramedullary CMs because of the risk of multiple lesions of the neuraxis [33]. Sensory and motor symptoms appear to be the most common presentation. In a systematic review with meta-analysis, Badhiwala et al. described that sensory and motor involvement was found in 60% of patients, while bladder or bowel disturbances in 23.6% of patients. Pain occurred in 33.8% of patients [34]. Other than the quality of clinical presentation, the clinical course is often unpredictable. Differently from intracranial locations, the natural history of intramedullary CMs is not well known, since these patients often prefer to undergo surgery to avoid spinal cord deficits. Intramedullar CMs are rarely asymptomatic [35]. Based on literature reports [26, 27, 36, 37], three patterns of presentation have been described by Lanzino and Spetzler [10]. An acute onset is usually related to a hemorrhage within or/and around the cord, as testified by the intraoperative findings of recent blood within the lesion [38–40]. In this case, patients complain a neurological deficit and/or the sudden onset of localized pain. Subarachnoid hemorrhage could be a rare clinical presentation in lesions located on the spinal cord surface or of the cauda equina [41, 42]. There is absence of evidence that the acute pattern is associated with pregnancy, history of trauma or physical efforts [10]. The pattern of episodic worsening could resemble that

Cavernous Malformations: Clinical Assessment

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of other non-surgical conditions, like multiple sclerosis and other demyelinating diseases, infective diseases, or vasculitis. The experience of a slight clinical improvement between the episodes, typical of demyelinating pathologies, could sometimes support the distinction between vascular and non-vascular causes. This clinical presentation of CMs represents the result of the deposit of hemosiderin after multiple episodic bleeding. The last pattern is that of a progressive neurologic impairment. The underlying mechanism of this behavior is unknown and based only on expert opinion. The enlargement of the CM could play a key role in causing a progressive myelopathy [26, 36, 38]. Other hypothesis involves the impairment of the microcirculation around the lesion and the toxic effect of hemosiderin on the surrounding parenchyma. Hydrocephalus is a very rare, but described clinical presentation in CMs of the cauda equina [43]. 4.3

Management

With the introduction of MRI, the interval between clinical presentation and diagnosis was shortened in the last decades. In the case series of Li et al. reported in 2018 with 82 patients, the median duration of symptoms was 5 months [32], significantly shorter than that described by Zevgaridisi et al. in 1999 [36]. Computed Tomography (CT), together with myelography, was the procedure of choice before the MRI. CT scan could maintain a role in order to detect the presence of a hemorrhage in an acute onset or calcifications. To plan the surgical procedure, MRI is the gold standard. CMs present the typical appearance of multilobulated and circumscribed lesions with a compartmentalized core of heterogeneous signal intensity [35]. On T2-weighted image, the hypo-intense signal reveals the hemosiderin ring like in intracranial CMs. Methemoglobin and thrombosis are responsible for high-intensity signal [44]. Enhancement with gadolinium is usually only hinted or absent. A false-positive rate has been described in detecting the reaching of the pial surface [45]. Since CMs are not the results of a high-flow shunt, they are angiographically occult and therefore a spinal angiography is usually not recommended. An angiographic study could be advisable when to rule out the suspect of a high-flow malformation. Small AVMs may not be easily recognized and distinguished from CMs. In the rare case of an asymptomatic patient, the therapeutic strategy is controversial. A close observation is probably a wise recommendation given the risk of surgery and the absence of evidence about the natural history of this pathology. If minor symptoms have occurred, surgical treatment could be considered since the clinical scenario of hemorrhagic CMs often predicts a progressive impairment of symptoms. Other factors should be considered, such as the age of the patient, his quality of life and

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daily routine, the position of the lesion within the spinal cord (the closer to the surface, especially posteriorly, the easier to approach without risks), the presence of comorbidities or other lesions. In patients with active symptoms, surgical removal is warranted when possible, to prevent further bleeding and the progression of symptoms. Unlike intracranial CMs, the small size of the spinal cord could not tolerate, for a long time, repeated bleedings or volume expansion. In case of lesions located near or on the surface of the spinal cord, surgical removal could be considered the treatment of choice in symptomatic patients. The average rate of bleeding has been estimated by Zevgaridis et al. [35] to be about 1.4% per lesion per year, given the presence of CMs since birth. Some reports described, however, the possibility to acquire the lesion in life [41, 46, 47].

5

Conclusions This review confirms how CMs should be considered from a surgical point of view as “different” pathologies depending on the location. Symptoms and possible surgical morbidities are closely linked to the localization of CMs. MRI increased the number of CMs diagnoses. The surgical techniques evolved in time to allow resection of CMs in brainstem and spinal cord. Furthermore, many technologies are improving the feasibility and safety of CMs surgery and we can look to the future with optimism.

References 1. Goldstein HE, Solomon RA (2017) Epidemiology of cavernous malformations. In: Handbook of clinical neurology, vol 143. Elsevier, Amsterdam, pp 241–247 2. Gross BA, Du R (2017) Hemorrhage from cerebral cavernous malformations: a systematic pooled analysis. JNS 126(4):1079–1087 3. Dammann P, Jabbarli R, Wittek P et al (2016) Solitary sporadic cerebral cavernous malformations: risk factors of first or recurrent symptomatic hemorrhage and associated functional impairment. World Neurosurg 91:73–80 4. Porter PJ, Willinsky RA, Harper W et al (1997) Cerebral cavernous malformations: natural history and prognosis after clinical deterioration with or without hemorrhage. J Neurosurg 87 (2):190–197 5. He K, Jiang S, Song J et al (2017) Long-term outcomes of surgical treatment in 181 patients with supratentorial cerebral cavernous malformation–associated epilepsy. World Neurosurg 108:869–875

6. Akers A, Al-Shahi Salman R, A Awad I et al (2017) Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the angioma alliance scientific advisory board clinical experts panel. Neurosurgery 80(5):665–680 7. Flemming KD (2017) Clinical Management of Cavernous Malformations. Curr Cardiol Rep 19(12):122 8. Jacobs R, Kano H, Gross BA et al (2019) Defining long-term clinical outcomes and risks of stereotactic radiosurgery for brainstem cavernous malformations. World Neurosurg 124:e58–e64 9. Pozzati E (2000) Thalamic cavernous malformations. Surg Neurol 53:30–40 10. Lanzino G, Spetzler R (2007) Cavernous malformations of the brain and spinal cord. Thieme, New York

Cavernous Malformations: Clinical Assessment 11. Porter R, Zabramski JM, Lanzino G et al (2002) Surgical treatment of brain stem cavernous malformations. Oper Tech Neurosurg 5 (3):185–190 12. Qiao N (2015) A systematic review and metaanalysis of surgeries performed for treating deep-seated cerebral cavernous malformations. Br J Neurosurg 29:493–499 13. Heffez DS (1997) Stereotactic transsylvian, transinsular approach for deepseated lesions. Surg Neurol 48:113–124 14. Wen R (2019) The efficacy of gamma knife radiosurgery for cavernous malformations: a meta-analysis and review. World Neurosurg Mar 123:371–377 15. Nagy G (2010) Stereotactic radiosurgery for deep-seated cavernous malformations: a move toward more active, early intervention. Clinical article. J Neurosurg 113:691–699 16. Xie MG, Li D, Guo FZ et al (2018) Brainstem cavernous malformations: surgical indications based on natural history and surgical outcomes. World Neurosurg 110:55–63 17. Taslimi S, Modabbernia A, Amin-Hanjani S et al (2016) Natural history of cavernous malformation: systematic review and meta-analysis of 25 studies. Neurology 89(21):1984–1991 18. Horne MA, Flemming KD, Su IC et al (2016) Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data. Lancet Neurol 15(2):166–173 19. Porter RW, Detwiler PW, Spetzler RF et al (1999) Cavernous malformations of the brainstem: experience with 100 patients. J Neurosurg 90(1):50–58 20. Zimmerman RS, Spetzler RF, Lee KS et al (1991) Cavernous malformations of the brain stem. J Neurosurg 75:32–39 21. Bertalanffy H, Benes L, Miyazawa T et al (2002) Cerebral cavernomas in the adult. Review of the literature and analysis of 72 surgically treated patients. Neurosurg Rev 25 (1–2):1–53 22. Abla AA, Clark AJ, Lawton MT (2014) Resection of pontine cavernous malformation through the pontomedullary sulcus. Neurosurg Focus 36(1 Suppl):1 23. Zaidi HA, Mooney MA, Levitt MR et al (2017) Impact of timing of intervention among 397 consecutively treated brainstem cavernous malformations. Neurosurgery 81:620–626 24. Garcia RM, Ivan ME, Lawton MT (2015) Brainstem cavernous malformations: surgical results in 104 patients and a proposed grading system to predict neurological outcomes. Neurosurgery 76:265–278

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25. Schultze F (1912) Weiterer Beitrag zur Diagnose und operativen Behandlung 21. von Geschwulstender Ruckenmarkshaute und des Ruckenmarks: Erfolgreiche Operation eines intramedullaren Tumors. Dtsch Med Wochenschr 38:1676–1167 26. McCormick PC, Michelsen WJ, Post KD et al (1988) Cavernous malformations of the spinal cord. Neurosurgery 23:459–463 27. Cosgrove GR, Bertrand G, Fontaine S et al (1988) Cavernous angiomas of the spinal cord. J Neurosurg 68:31–36 28. Slon V, Stein D, Cohen H et al (2015) Vertebral hemangiomas: their demographical characteristics, location along the spine and position within the vertebral body. Eur Spine J 24(10):2189–2195 29. Gross BA, Du R, Popp AJ et al (2010) Intramedullary spinal cord cavernous malformations. Neurosurg Focus 29:E14 30. Jellinger K (1975) The morphology of centrally-situated angiomas. In: Pia HW, JRW G, Grote E, Zierski J (eds) Cerebral angiomas: advances in diagnosis and therapy, vol 1975. Springer-Verlag, New York, pp 9–20 31. Cofano F, Marengo N, Pecoraro F et al (2019) Spinal epidural capillary hemangioma: case report and review of the literature. Br J Neurosurg 4:1–4 32. Li J, Chen G, Gu S et al (2018) Surgical outcomes of spinal cord intramedullary cavernous malformation: a retrospective study of 83 patients in a single center over a 12-year period. World Neurosurg 118:e105–e114 33. Vishteh AG, Zabramski JM, Spetzler RF (1999) Patients with spinal cord cav- 36. Ernous malformations are at an increased risk for multiple neuraxis cavernous malformations. Neurosurgery 45:30–32 34. Badhiwala JH, Farrokhyar F, Alhazzani W et al (2014) Surgical outcomes and natural history of intramedullary spinal cord cavernous malformations: a single- center series and metaanalysis of individual patient data. J Neurosurg Spine 21:662–676 35. Clark AJ, Wang, DD, Lawton MT (2017) Spinal cavernous malformations. Arteriovenous and cavernous malformations. Handbook of clinical neurology, vol.143 (3rd series). pp 303–308 36. Zevgaridis D, Medele RJ, Hamburger C et al (1999) Cavernous haemangiomas of the spinal cord. A review of 117 cases. Acta Neurochir 141:237–245 37. Cantore G, Delfini R, Cervoni L et al (1995) Intramedullary cavernous angiomas of the

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spinal cord: report of six cases. Surg Neurol 43:448–452 38. Ogilvy CS, Louis DN, Ojemann RG (1992) Intramedullary cavernous angiomas of the spinal cord: clinical presentation, pathological features, and surgical management. Neurosurgery 31:219–229 39. Lee KS, Spetzler RF (1990) Spinal cord cavernous malformation in a patient with familial intracranial cavernous malformations. Neurosurgery 26:877–880 40. Lopate G, Black JT, Grubb RL (1990) Cavernous hemangioma of the spinal cord: report of two unusual cases. Neurology 40:1791–1793 41. Canavero S, Pagni CA, Duca S et al (1994) Spinal intramedullary cavernous angiomas: a literature meta-analysis. Surg Neurol 41:381–388 42. Bruni P, Massari A, Greco R et al (1994) Subarachnoid hemorrhage from cavernous angioma of the cauda equina: case report. Surg Neurol 41:226–229

43. Ramos F, de Toffol B, Aesch B et al (1990) Hydrocephalus and cavernoma of the cauda equina. Neurosurgery 27:139–142 44. Hegde A, Mohan S, Tan KK et al (2012) Spinal cavernous malformations: magnetic resonance imaging and associated findings. Singap Med J 53:582–586 45. Vishteh AG, Sankhla S, Anson JA et al (1997) Surgical re- section of intramedullary spinal cord cavernous malfomations: delayed complications, long-term outcomes, and association with cryptic venous malformations. Neurosurgery 41:1094–1101 46. Maraire JN, Abdulrauf SI, Berger S, Knisely J, Awad IA (1999) De novo develop- ment of a cavernous malformation of the spinal cord following spinal axis radiation. Case report. J Neurosurg 90:234–238 47. Pozzati E, Aciarri N, Tognetti F, Marliani F, Giangaspero F (1996) Growth, subsequent bleeding, and de novo appearance of cerebral cavernous angiomas. Neurosurgery 38:662–670

Part II Diagnosis and Treatment of Cerebral Cavernous Malformations

Chapter 4 Molecular Genetic Screening of CCM Patients: An Overview Elisabeth Tournier-Lasserve Abstract Cerebral Cavernous Malformations (CCMs) are vascular lesions which can occur as a sporadic (80% of the cases) or a familial autosomal dominant disease (20%), the latter being characterized by the presence of multiple lesions. Three CCM genes have been identified in the last 10 years. More than 95% of familial cases and 60% of sporadic cases with multiple lesions harbor a germline heterozygous loss of function mutation in one of these 3 genes. Most mutations lead to a premature stop codon whatever the mechanism, including nonsense mutations, deletions, insertions and intronic mutations leading to abnormal splicing and frameshift. A combination of analyses, including sequencing and copy number analysis of germline DNA extracted from blood and cDNA analysis, are therefore required to ensure the best diagnostic sensitivity. Additional causative rare structural CCM gene anomalies have been identified in a research context, as well as rare causative missense mutations. These mutations are rarely searched for in a diagnostic context and explain part of the negative cases, in addition to germline mosaicism which occurs in some sporadic cases with multiple lesions. On top of germline mutations, somatic mutations occur on the wild-type allele in endothelial cells lining CCM lesions. These data established both the role of a double hit in the pathophysiology of CCM lesions and the heterogeneity of endothelial cells lining these lesions. Key words CCM1, KRIT1, CCM2, Malcavernin, CCM3, PDCD10, Molecular screening

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Introduction Cerebral cavernous malformations (CCM/OMIM 116860), also called cavernous angioma or cavernoma, are vascular lesions histologically characterized by abnormally enlarged capillary cavities without intervening brain parenchyma. Most of them are located within the central nervous system (CNS) but they sometimes affect the retina or the skin. CCMs occur as a sporadic or familial, autosomal dominant, condition [1]. Most sporadic cases show a single lesion on cerebral magnetic resonance imaging (MRI) and do not carry germline mutations in any CCM gene. Familial cases present most often with multiple lesions [2, 3]. The proportion of familial cases is close to 20% in Caucasian patients.

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_4, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Three CCM genes have been identified in the last 10 years: KRIT1/CCM1, CCM2/malcavernin, PDCD10/CCM3 [4– 7]. These molecular genetics data provided very useful information for patients’ clinical management and genetic counseling. This was also an important step towards the characterization of the CCM signaling pathways and mechanisms of this disorder as well as the development of highly relevant mouse models. This chapter will summarize the available molecular genetics data and molecular genetics methods which are required to ensure the best sensitivity and specificity to evidence a mutation in those genes.

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Screening of Familial CCM Cases for CCM Germline Mutations Three CCM loci have been mapped to chromosome 7q (CCM1), 7p (CCM2), and 3q (CCM3), most families being linked to the CCM1 locus [8]. The three genes located at these loci have been identified. The KRIT1/CCM1 gene has 16 coding exons which encode for KRIT1, a 736 amino-acid protein containing three ankyrin and one FERM domains. CCM2/MGC4607, a 10 coding exons gene, encodes for malcavernin, a protein which contains a phosphotyrosine binding (PTB) domain. PDCD10/CCM3 includes seven coding exons that encode for programmed cell death 10 protein. Molecular screening of these 3 CCM genes in a series of 163 consecutive patients led to the identification of the causative mutation in 94% of familial CCM cases. CCM1 was involved in 72% of multiplex families, whereas CCM2 and CCM3 were involved in 18% and 10% of these cases [9]. These data were confirmed in additional consecutive cohorts [10]. A very strong founder effect has been reported in the Hispano-American CCM population, in which most CCM patients share the Q455X stop codon mutation in CCM1 [11]. Recurrent mutations have also been identified in a few additional populations [12]. However, in most cases despite their highly stereotyped consequences, germline CCM mutations are “private” mutations present in only one or very few families. Most mutations, regardless of the gene, lead to a premature stop codon, including either nonsense mutations, small insertions/ deletions, copy number alterations, splicing mutational events, or to a deletion of one entire CCM gene or the absence of expression of one CCM allele due to promoter alterations [9, 13–15]. In order to ensure the best screening sensitivity in a diagnostic context, several methods have therefore to be used. The first method to be used is sequencing of all coding exons and exon/ intron boundaries of all 3 CCM genes, to be conducted on genomic DNA extracted from blood (Fig. 1). Both Sanger sequencing and Next Generation Sequencing (NGS) have a very high

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Blood genomic DNA extraction NGS sequencing qPCR, QMPSF, MLPA

Loss of function mutation

No mutation detected or Variant of Unknown significance

RNA extraction Reverse transcription

cDNA Sanger sequencing

Loss of function mutation

No mutation detected (WGS to search for structural anomalies)

Loss of function mutation

No mutation detected

Fig. 1 Screening algorithm of CCM genes in familial CCM index patients and sporadic CCM cases with multiple lesions. As a first step, sequencing of all exons and intron/exon boundaries of the 3 CCM genes is performed on genomic DNA extracted from blood, using Next Generation Sequencing (NGS). In addition, search for exon copy number alterations is performed using quantitative PCR (qPCR, QMPSF, or MLPA). If negative, RNA extracted from blood is reverse transcribed and sequenced with CCM specific oligonucleotides using Sanger sequencing. These approaches are routinely performed in diagnostic labs. If negative, at this step whole genome sequencing can be performed (usually in a research context) to search for structural anomalies

sensitivity for point mutations detection, the latter method being faster and more cost-effective since it allows to screen all 3 CCM genes together [15]. Quantitative analysis of exon copy number using either Quantitative Multiplex PCR Short Fragments (QMPSF) method or Multiplex Ligation-dependent Probe Amplification (MLPA) method allows to detect both deletions or duplications affecting one or multiple exons [9]. Both methods are highly sensitive and specific. NGS data can also be used to search for copy number alterations with algorithms based on sequencing reads depth analysis; however, this approach is in our experience currently less sensitive and less specific than quantitative polymerase chain reaction methods.

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This combination of genomic DNA sequencing and copy number analysis allows to detect the vast majority of CCM germline mutations in familial CCM cases. However, in a minority of patients showing multiple typical CCM lesions and having an affected relative, this screening does not detect a mutation. In those cases, cDNA analysis is indicated. It can reveal either a splicing anomaly caused by a deep intronic mutation, undetectable by exonic sequencing, or a loss of heterozygosity establishing the absence of expression of one of the CCM alleles. CCM genes are expressed in leukocytes. Therefore, messenger RNA (mRNA) can be easily extracted from a blood sample, reverse transcribed and analyzed with CCM1–3 specific oligonucleotides (Fig. 1). Several CCM deep intronic mutations have been identified with this method [16, 17]. Rare structural anomalies leading to an absence of expression of one CCM allele can also be detected when they lead to a loss of heterozygosity. Those rare structural anomalies, such as inversions, can also be detected with whole genome sequencing, as recently shown for a 24 Kb inversion including exon 1 of CCM2 [18]; however, this approach is not currently used in most diagnostic laboratories. The pathogenic feature of a CCM gene mutation is easy to establish when it leads to a premature stop codon. Intragenic in-frame deletions have also been reported, including deletions affecting exons 17 and 18 of CCM1, exon 2 of CCM2, and exon 5 of CCM3 [9, 13]. In some rare cases, missense mutations can also be pathogenic. Some of them activate cryptic splice sites and led to an aberrant splicing of CCM mRNA and a frameshift with a premature stop codon [13]. cDNA analysis is needed to establish the causality of these “missense” variants of unknown significance (VUS). Others may abolish CCM1–CCM2 or CCM2–CCM3 interactions and the formation and stability of the cytosolic CCM complex [19]. Immunoprecipitation analyses of co-transfected mutant alleles, conducted in a research context, have indeed shown that some mutations located in the PTB domain of CCM2 abolish the interaction with either CCM1 or CCM3 [19– 21]. These missense mutations which are affecting CCM1– CCM2 or CCM2–CCM3 interactions are pathogenic.

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Screening of Sporadic CCM Cases with Multiple Lesions Despite the use of the same methodological approaches, the mutation detection rate is much lower (close to 60%) in sporadic cases with multiple lesions [9, 15]. Several hypotheses may be raised to explain this negativity, including (i) mosaic de novo mutations which occurred during gestation and are not detectable in DNA extracted from peripheral blood cells [22], (ii) undetected regulatory mutations located far away from coding exons, (iii)

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epigenetic silencing events and/or (iv) additional yet unknown CCM genes. This will be important to solve in the future since it is of major interest for genetic counseling of sporadic cases with multiple lesions.

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Screening of Sporadic CCM Cases with a Unique Lesion T2∗ gradient echo MRI is the most sensitive sequence to detect CCM lesions. With regard to sporadic CCM cases with a unique lesion on T2∗ cerebral MRI sequences, no causative germline mutation is detected in most patients. Indeed, in a series of 244 mutation carriers, only 8 carriers presented with a unique lesion on both T2 and T2∗ sequences [9]. These data strongly suggest that sporadic cases with a unique lesion on T2∗ brain MRI sequences who harbor a germline mutation are most likely very rare. Therefore, molecular screening is usually not indicated in these cases.

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Are there Additional CCM Genes? The existence of possible additional and yet unidentified genes has been suspected but no novel gene has been confirmed so far. Previous linkage data suggested that the three CCM loci on 7p, 7q, and 3q would most likely account for all CCM families. However, despite extensive screening of exonic sequences for point mutations and deletions, no mutation is detected in around 5% of familial CCM cases and 40% of sporadic cases with multiple lesions. As mentioned above, the existence of a possible fourth CCM gene can be raised to explain those negative cases. ZPLD1 (zona pellucida-like domain containing 1) has been reported to be disrupted in a CCM patient harboring a balanced translocation between chromosome X and chromosome 3q, centromeric to CCM3/PDCD10 [23]. The expression of ZPLD1 mRNA in lymphoblastoid cell lines of the patient was shown to be significantly decreased, suggesting that the interruption of this gene may be causal. However, these data have not been confirmed in any additional patient, suggesting that either this gene is involved in a very small proportion of CCM patients or that its interruption does not cause CCM but that the translocation present in this patient deregulated the expression of a gene that is still unidentified. The tremendous progress in high throughput sequencing technologies should help to resolve this question in the very near future.

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Interestingly, a phenotype very similar to the ones observed in CCM1-CCM3 ablated mice has recently been reported in CDC42 endothelial specific knockout mice [24, 25]. Screening of this gene in patients whose CCM1-CCM3 mutation screening is negative would be of interest.

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Genetic Screening Applications, Penetrance, Expressivity, and Genetic Counseling Familial CCM pattern of inheritance is autosomal dominant with an incomplete clinical and neuroradiological penetrance [1]. The identification of CCM loci and genes allowed the identification of mutation carriers and helped to estimate the penetrance of this disorder. In a genetic linkage analysis conducted on 20 families, CCM penetrance was estimated to be close to 89% in CCM1 linked families, 100% in CCM2 and 63% in CCM3 linked families [8]. An analysis of 64 consecutive CCM1-mutated families showed a clinical penetrance close to 45% [6]. Additional studies conducted on large series of CCM2 and CCM3 families are needed to estimate precisely the penetrance in those families. Due to incomplete clinical penetrance, CCM patients who carry a mutation in one of the three CCM genes might present as sporadic cases. A clinical and neuroradiological analysis conducted prior to CCM gene identification in a series of 22 consecutive sporadic cases with multiple lesions showed that 75% of them were indeed affected with a hereditary form of the disease since one of their two asymptomatic parents showed CCM lesions on MRI [3]. With regard to the remaining 25% of patients, some of them are true genetic cases harboring a de novo mutation in one of the 3 CCM genes. Their offspring has therefore a 50% risk of inheriting the mutated gene. In some other sporadic cases with multiple lesions, the search for point mutations and copy number variations (CNV) is negative (see above). Part of them may harbor mosaic de novo mutations undetectable in genomic DNA extracted from blood. Depending on the proportion of mutated cells in their gonads, the risk of transmitting the disease to their offspring might be lower than 50%. This is important for genetic counseling. Expressivity of CCM is variable depending on the nature of the CCM gene which is mutated. CCM3 mutations are associated with a higher severity, an earlier age at onset, and a higher propensity to hemorrhages [9]. An association with meningiomas has also been reported which is highly specific for CCM3 [26]. It is detected in 5–10% of CCM3 patients and is not associated with a specific mutation.

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Biallelic, Somatic and Germline, Mutations in Endothelial Cells from CCM Lesions The autosomal dominant pattern of inheritance of CCM and the presence of multiple lesions in familial CCM, contrasting with the detection of a single lesion in non-hereditary cavernous angiomas, strongly suggested a “two-hit” hypothesis in CCM pathophysiology, as reported previously in other conditions such as retinoblastoma or other vascular malformations. According to this hypothesis, the complete loss within an endothelial cell of the two alleles of a given CCM gene would lead to a CCM lesion. Loss of the first allele (first hit) would be the result of a germline mutation and loss of the second allele (second hit) will occur somatically. Direct sequencing of the DNA extracted from a few CCM lesions was initially used to screen CCM lesions from both sporadic and a few familial patients. Two CCM1 missense mutations, F97S and K569E, were detected in the CCM lesion of one sporadic case and were shown to be absent in the blood of the patient. However, these data were difficult to interpret due to the nature of the mutations; they were not truncating mutations (a possible aberrant splicing effect of these two mutations was not investigated) and the biallelism of these mutations was not explored. The first biallelic, germline and somatic, mutations within a CCM lesion were reported in 2005 in a CCM1-mutated patient [27]. This work strongly supported the “two-hit” mechanism in the formation of lesions at least in CCM1 patients. Biallelic mutations in each of the three CCM genes were then reported using a cloning approach [28]. These data convincingly established the presence of biallelic, somatic and germline, deleterious mutations in two CCM1, one CCM2, and one CCM3 lesions from four unrelated patients. None of these mutations was detected through direct sequencing of lesions’ DNA, emphasizing the lack of sensitivity of direct sequencing. Using microdissection laser capture, they showed that the somatic mutation occurred in endothelial cells and not in the intervening neural tissue. The proportion of endothelial cells that harbor the somatic mutation was estimated in a few lesions and shown to be highly variable from 1 to 30%. Those data were confirmed by several groups for familial and sporadic cases [29, 30], suggesting shared mechanisms. Very importantly, 2 groups demonstrated recently in CCM mouse models that CCM lesions are the result of a clonal expansion of few CCM null endothelial cells that attract surrounding wildtype endothelial cells [31, 32]. Altogether these data are consistent with the clonal expansion, in human CCM, of a few endothelial cells carrying a germline and a somatic mutation which then attract endothelial cells which carry only a germline mutation. These data do not have clinical care applications so far but are of utmost importance for the understanding of CCM pathophysiology.

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In summary, since the identification of the first multiple cases CCM families, tremendous progress has been made in the last 20 years in the molecular characterization of this condition, mainly thanks to the use of constantly improving molecular screening methods. This progress provided important information for clinical care and genetic counseling and paved the way for a better understanding of CCM pathophysiology. References 1. Labauge P, Denier C, Bergametti F et al (2007) Genetics of cavernous angiomas. Lancet Neurol 6:237–244 2. Rigamonti D, Hadley MN, Drayer BP et al (1988) Cerebral cavernous malformations. Incidence and familial occurrence. N Engl J Med 319:343–347 3. Labauge P, Laberge S, Brunereau L et al (1998) Hereditary cerebral cavernous angiomas: clinical and genetic features in 57 French families. Socie´te´ Franc¸aise de Neurochirurgie. Lancet 352:1892–1897 4. Laberge-le Couteulx S, Jung HH, Labauge P et al (1999) Truncating mutations in CCM1, encoding KRIT1, cause hereditary cavernous angiomas. Nat Genet 23:189–193 5. Liquori CL, Berg MJ, Siegel AM et al (2003) Mutations in a gene encoding a novel protein containing a phosphotyrosine-binding domain cause type 2 cerebral cavernous malformations. Am J Hum Genet 73:1459–1464 6. Denier C, Labauge P, Brunereau L et al (2004) Clinical features of cerebral cavernous malformations patients with KRIT1 mutations. Ann Neurol 55:213–220 7. Bergametti F, Denier C, Labauge P et al (2005) Mutations within the programmed cell death 10 gene cause cerebral cavernous malformations. Am J Hum Genet 76:42–51 8. Craig HD, Gu¨nel M, Cepeda O et al (1998) Multilocus linkage identifies two new loci for a mendelian form of stroke, cerebral cavernous malformation, at 7p15-13 and 3q25.2-27. Hum Mol Genet 7:1851–1858 9. Denier C, Labauge P, Bergametti F et al (2006) Genotype-phenotype correlations in cerebral cavernous malformations patients. Ann Neurol 60:550–556 10. Spiegler S, Najm J, Liu J et al (2014) High mutation detection rates in cerebral cavernous malformation upon stringent inclusion criteria: one-third of probands are minors. Mol Genet Genomic Med 2:176–185 11. Gunel M, Awad IA, Finberg K et al (1996) A founder mutation as a cause of cerebral

cavernous malformation in Hispanic Americans. N Engl J Med 334:946–951 12. Ortiz L, Costa AF, Bellido ML et al (2007) Study of cerebral cavernous malformation in Spain and Portugal: high prevalence of a 14 bp deletion in exon 5 of MGC4607 (CCM2 gene). J Neurol 254:322–326 13. Cave´-Riant F, Denier C, Labauge P et al (2002) Spectrum and expression analysis of KRIT1 mutations in 121 consecutive and unrelated patients with cerebral cavernous malformations. Eur J Hum Genet 10:733–740 14. Stahl S, Gaetzner S, Voss K et al (2008) Novel CCM1, CCM2, and CCM3 mutations in patients with cerebral cavernous malformations: in-frame deletion in CCM2 prevents formation of a CCM1/CCM2/CCM3 protein complex. Hum Mutat 29:709–717 15. Spiegler S, Rath M, Paperlein C et al (2018) Cerebral cavernous malformations: an update on prevalence, molecular genetic analyses, and genetic counselling. Mol Syndromol 9:60–69 16. Riant F, Odent S, Cecillon M et al (2014) Deep intronic KRIT1 mutation in a family with clinically silent multiple cerebral cavernous malformations. Clin Genet 86:585–588 17. Rath M, Jenssen SE, Schwefel K et al (2017) High-throughput sequencing of the entire genomic regions of CCM1/KRIT1, CCM2 and CCM3/PDCD10 to search for pathogenic deep-intronic splice mutations in cerebral cavernous malformations. Eur J Med Genet 60:479–484 18. Spiegler S, Rath M, Hoffjan S et al (2018) First large genomic inversion in familial cerebral cavernous malformation identified by whole genome sequencing. Neurogenetics 19:55–59 19. Zawistowski JS, Stalheim L, Uhlik MT et al (2005) CCM1 and CCM2 protein interactions in cell signaling: implications for cerebral cavernous malformations pathogenesis. Hum Mol Genet 14:2521–2531 20. Fisher OS, Liu W, Zhang R et al (2015) Structural basis for the disruption of the cerebral cavernous malformations 2 (CCM2)

CCM Molecular Screening interaction with Krev interaction trapped 1 (KRIT1) by disease-associated mutations. J Biol Chem 290:2842–2853 21. Draheim KM, Li X, Zhang R et al (2015) CCM2-CCM3 interaction stabilizes their protein expression and permits endothelial network formation. J Cell Biol 208:987–1001 22. Rath M, Spiegler S, Nath N et al (2017) Constitutional de novo and postzygotic mutations in isolated cases of cerebral cavernous malformations. Mol Genet Genomic Med 5:21–27 23. Gianfrancesco F, Esposito T, Penco S et al (2008) ZPLD1 gene is disrupted in a patient with balanced translocation that exhibits cerebral cavernous malformations. Neuroscience 155:345–349 ˜ a B, Castro M, Niaudet C et al (2018) 24. Lavin Defective endothelial cell migration in the absence of Cdc42 leads to capillary-venous malformations. Development 145:dev161182 ˜ a B, Ando K et al (2019) 25. Castro M, Lavin CDC42 deletion elicits cerebral vascular malformations via increased MEKK3-dependent KLF4 expression. Circ Res 124:1240–1252 26. Riant F, Bergametti F, Fournier H-D et al (2013) CCM3 mutations are associated with early-onset cerebral hemorrhage and multiple meningiomas. Mol Syndromol 4:165–172

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27. Gault J, Shenkar R, Recksiek P et al (2005) Biallelic somatic and germ line CCM1 truncating mutations in a cerebral cavernous malformation lesion. Stroke 36:872–874 28. Akers AL, Johnson E, Steinberg GK et al (2009) Biallelic somatic and germline mutations in cerebral cavernous malformations (CCMs): evidence for a two-hit mechanism of CCM pathogenesis. Hum Mol Genet 18:919–930 29. Pagenstecher A, Stahl S, Sure U et al (2009) A two-hit mechanism causes cerebral cavernous malformations: complete inactivation of CCM1, CCM2 or CCM3 in affected endothelial cells. Hum Mol Genet 18:911–918 30. McDonald DA, Shi C, Shenkar R et al (2014) Lesions from patients with sporadic cerebral cavernous malformations harbor somatic mutations in the CCM genes: evidence for a common biochemical pathway for CCM pathogenesis. Hum Mol Genet 23:4357–4370 31. Detter MR, Snellings DA, Marchuk DA (2018) Cerebral cavernous malformations develop through clonal expansion of mutant endothelial cells. Circ Res 123:1143–1151 32. Malinverno M, Maderna C, Abu Taha A et al (2019) Endothelial cell clonal expansion in the development of cerebral cavernous malformations. Nat Commun 10:2761

Chapter 5 Next Generation Sequencing (NGS) Strategies for Genetic Testing of Cerebral Cavernous Malformation (CCM) Disease Valerio Benedetti, Elisa Pellegrino, Alfredo Brusco, Roberto Piva, and Saverio Francesco Retta Abstract The application of next generation sequencing (NGS) technique has a great impact on complex disease studies. Indeed, genetic heterogeneity, phenotypic variability, and disease rarity are all factors that make the traditional diagnostic approach to genetic disorders, whereby a specific gene is selected for sequencing based on the clinical phenotype, very challenging and obsolete. Exome sequencing, which sequences the protein-coding region of the genome, has been rapidly applied to variant discovery in research settings. Recent coverage and accuracy improvements have accelerated the development of clinical exome sequencing (CES) platforms targeting disease-related genes and enabling variant identification in patients with suspected genetic diseases. Nowadays, CES is rapidly becoming the diagnostic test of choice in patients with suspected Mendelian diseases, especially for those with heterogeneous etiology and clinical presentation. Reporting large CES series can improve guidelines on best practices for test utilization, and a better variant interpretation through clinically oriented data sharing. Herein, we suggest a feasible CES procedure for the genetic testing of Cerebral Cavernous Malformation (CCM) disease, including proband identification, library preparation, data analysis, and variant interpretation. Key words Cerebral cavernous malformation (CCM) disease, CCM genes: KRIT1/CCM1, CCM2, CCM3, Familial cerebral cavernous malformation (fCCM), Next generation sequencing (NGS), Clinical exome sequencing (CES)

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Introduction Exponential advances in next-generation sequencing (NGS) technologies, whereby entire gene panels and even whole genomes can be analyzed in a single run for the detection of clinically deleterious variants, have changed the scenario of genetic testing in rare diseases as well as common complex disorders, including cardiovascular diseases, and are transforming clinical practice, enabling precision medicine approaches and reducing unnecessary healthcare costs [1]. Indeed, the growing adoption of the NGS technology in medicine is improving the accurancy and rapidity of genetic

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_5, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Valerio Benedetti et al. Patient(s) identification Whole blood sample DNA extraction DNA quantification NGS library preparation NGS hybridization capture NGS sequencing Data analysis Mutation validation Diagnosis

Fig. 1 Flow chart of the NGS-based genetic testing procedure designed for Cerebral Cavernous Malformation (CCM) disease

diagnosis, increasing the speed and reducing the cost of DNA sequencing by orders of magnitude as compared to the traditional Sanger method [1]. In this chapter, we describe the main steps of a NGS-based genetic testing procedure designed for the high-throughput analysis of hereditary cerebrovascular disorders, including Cerebral Cavernous Malformation (CCM) disease (Fig. 1). 1.1 Cerebral Cavernous Malformation

Cerebral Cavernous Malformation (CCM) is a major cerebrovascular disease of proven genetic origin (OMIM 116860). It has been estimated to affect between 0.3% and 0.5% of the human population and can occur in either sporadic (sCCM) or familial (fCCM) forms. The latter can be inherited as an autosomal-dominant condition with incomplete penetrance and highly variable expressivity. CCM lesions consist of abnormally dilated vascular sinusoids that can be detected unequivocally only by magnetic resonance imaging (MRI), showing a characteristic appearance [2–4]. CCMs are usually found intracranially, although such lesions can also affect the spinal cord and the retina. Individuals with CCMs can present with epilepsy and focal neurological deficits or acute intracerebral hemorrhage (ICH); however, CCMs are often clinically quiescent lesions. Indeed, neuroradiological series revealed that up to 70% of individuals with such malformations are asymptomatic [2–4]. On the other hand, there are currently no direct therapies other than surgical removal of accessible lesions [5, 6].

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Hereditary forms of CCM are caused by loss-of-function mutations in one of three known genes: KRIT1 (CCM1), CCM2, and PDCD10 (CCM3) [7–11]. However, CCM patients carrying the same mutation can manifest different phenotypes and symptoms due to the emerged pleiotropic redox-sensitive mechanisms of CCM disease pathogenesis [12–25], and the inter-individual heterogeneity of susceptibility to local oxidative stress and inflammatory events caused by distinct genetic modifiers of endothelial cell responses to such microenvironmental stress factors, including single-nucleotide polymorphisms (SNPs) of distinct members of the CYP and MMP gene families, which may eventually impact the severity of CCM disease [26, 27]. Remarkably, whereas these evidences prompt complementary diagnostic approaches for the identification of genetic risk factors that may allow an effective risk stratification of patients with enhanced susceptibility to develop the most severe phenotypes of CCM disease, including ICH [26, 27], they are also providing a fundamental framework for the development of preventive and therapeutic approaches [17–19, 28–33]. 1.2 Genetic Diagnosis of the Familial Form of CCM Disease (fCCM)

Sporadic cases of CCM are characterized by a lack of family history of the disease and usually the presence of a single lesion on MRI. In contrast, familial cases mostly exhibit multiple lesions that show progression in both number and size over time.Genetic studies conducted over the past 20 years have identified a wide spectrum of pathogenic mutation types and distribution within the three known CCM genes, including distinct nonsense, frameshift, missense, and splice site mutations as well as large deletions and insertions [11, 34, 35]. Moreover, there is also evidence for the existence of some alternative splicing variants that may eventually generate protein isoforms with specific subcellular compartmentation and distinct expression patterns among various tissues and cells, suggesting that they abnormal expression may also contribute to CCM disease pathogenesis [36, 37]. On the other hand, although most familial cases of CCM have been clearly linked to heterozygous loss-of-function mutations in any of the three known CCM genes, no mutation in either of these genes were found in 5–15% of all CCM cases with a positive family history, suggesting the existence of additional CCM genes [11, 35]. Furthermore, whereas an incomplete penetrance and no clear genotypephenotype correlations have been observed so far, the wide variability in phenotypes seen among carriers of the same CCM gene mutation suggests the influence of additional genetic and/or environmental modifiers [11, 26, 27]. Indeed, the clinical behavior in individual patients, including the development of numerous and large lesions, and the risk of serious complications, such as ICH, remain highly unpredictable even among family members of similar ages carrying the same disease-associated genetic defect

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Patient / Proband

Study of pedigree

No Are there family members with symptoms or signs of disease? Yes MRI analysis

single Possible sporadic case

CCM lesion(s) multiple Possible familiar case carrying a germinal mutation (fCCM)

Proband NGS analysis

No Possible somatic mutation (sCCM)

CCM mutation?

No CCM as secondary disease

Yes Confirmation by Sanger sequencing (or MLPA – RT-PCR analysis)

Clinical Report

Mutationanalysis infamily members

Final diagnosis of fCCM. Clinical Report

Fig. 2 Flow chart for the identification of a proband and related family members affected by CCM disease. fCCM, familial cerebral cavernous malformation; sCCM, sporadic cerebral cavernous malformation; MRI, magnetic resonance imaging; NGS, next generation sequencing; CCM, cerebral cavernous malformation

[26, 27]. Therefore, while the detection of a pathogenic variant in CCM genes is essential to confirm the diagnosis of hereditary CCM and to guide genetic counselling for at-risk family members, the identification of genetic modifiers that affect CCM disease penetrance, expressivity and severity may have an important prognostic value and guide clinical management of CCM patients. The procedure for identification of a proband affected by the inherited form of CCM disease (fCCM) is shown in a schematic flow chart (Fig. 2), which contains guidelines to discriminate sCCM from fCCM and possible analysis extension to all family members. Magnetic resonance imaging (MRI) is established as the gold standard for identifying family members carrying both silent and symptomatic CCM lesions, whereas next generation sequencing (NGS) can be adopted as a gold standard for genetic testing aimed at an unbiased highthroughput identification of genetic variants of diagnostic or prognostic value implicated in CCM disease pathogenesis and severity.

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1.3 Proband and Pedigree Study

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Proband study is divided into the following phases: 1. Identification of symptomatic patients with suspected CCM disease. Clinical signs and symptoms: seizures; focal neurologic deficits; recurrent headaches; signs and symptoms of intracerebral hemorrhage (ICH). CCM disease may become symptomatic at any age, but most typically between the second and fifth decades. 2. Patient’s brain MRI analysis by either spin echo (T1- and T2-weighted), gradient echo (GRE) or susceptibility-weighted imaging (SWI), which may identify characteristic CCM lesions with different sensitivity [38, 39]. 3. Investigation of patient for multiple lesions and family history of CCM disease to confirm a possible fCCM. Individuals with a single CCM and no family history are likely sporadic cases that do not carry germline mutations of CCM genes, despite de novo germline mutation may seldom occur in some of such cases. For these patients, genetic testing is generally not recommended. On the other hand, germline mutations of CCM genes are usually carried by individuals with multiple CCM lesions and/or a family history of CCM disease. For these patients, genetic testing is therefore recommended. 4. CES of the proband using NGS technology. 5. NGS data and low frequency/rare variants analysis. 6. Classification and interpretation of variants. 7. Validation of pathological variants by Sanger sequencing, multiplex ligation-dependent probe amplification (MLPA), and real-time quantitative reverse transcription polymerase chain reaction (real-time qRT-PCR) for gene dosage are the best options to validate structural variations identified by NGS, including large copy number variations (CNVs). 8. Segregation analysis to the proband family members.

1.3.1 Who Should Be Tested?

Whole genome or whole exome sequencing (WGS/WES) are nowadays the most used strategies to identify novel disease genes or approach highly heterogenous genetic diseases. WGS/WES is usually performed in a trio to maximize the possibility to identify de novo variants by excluding the many heterozygous rare variants observed both in the affected individual and in an unaffected parent. Even though these approaches are considered the gold standard with the highest diagnostic yield, their high costs limit the application to research projects. Recently, diagnostic-oriented tools able to cover the coding regions (5 bp of intronic regions) of several thousands of disease-associated genes (e.g., 5000–7000) have been introduced by several companies, and globally named clinical exome sequencing (CES). This approach is considered more cost-effective than

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WGS/WES to provide a quick and cost-effective identification of pathogenic variants in diseases with a limited heterogeneity, including single nucleotide variations (SNVs), small insertions/deletions (INDELs) and copy number variations (CNVs). Furthermore, they allow the Medical Genetics Units to have a unique method to analyze a wide spectrum of genetic diseases. Proband CES followed by parental testing of candidate variants for segregation analysis could represent a cost-effective approach for the etiological diagnosis of rare Mendelian disorders. Probandonly genetic testing is indicated for individuals with multiple CCMs that are not associated with a developmental venous anomaly (DVA) or a history of focal brain radiation, and for those with a positive family history [34]. However, it is not indicated for patients with sporadic disease who present with a solitary CCM, as the sporadic form is generally not caused by a germline mutation. Furthermore, proband-only genetic testing is the best way to screen at-risk family members, including potential asymptomatic mutation carriers. Proband-only and trio genetic testing of asymptomatic at-risk individuals (particularly children) could allow a correct personalized follow-up despite there is currently no curative therapy for those testing positive. However, the absence of a known pathogenic mutation in an at-risk subject can completely exclude the onset of the disease and the risk of having affected children. Genetic counseling is always recommended prior to perform any genetic test. Prenatal and pre-implantation tests are also available for interested individuals with known pathogenic variants.

2

Materials 1. Commercially available DNA extraction and CES kits optimized for sensitive, effective, and reliable NGS analyses. 2. Hybridization buffer: 8.5 μL of 2 Hybridization Buffer + 3.4 μL of Hybridization Buffer Enhancer + 1.1 μL of nuclease-free water. 3. 80% Ethanol solution in nuclease-free water. 4. IDTE: 10 mM Tris, 0.1 mM EDTA, pH 8.0.

3

Methods

3.1 Nucleic Acid Extraction

For any NGS platform, accuracy of sequencing depends largely on using high-quality starting DNA that is quantified accurately (see Note 1). Nucleic acids were extracted using Maxwell® 16 Blood DNA Purification Kit and all technical literature is available at: www.promega.com/protocols/ (see Notes 2 and 3). A flow chart of the DNA extraction process is shown (Fig. 3).

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Whole blood samples Washing

Deionized water

Whole blood samples Digesting Proteinase Klysisbuffer Cell Lysate Cell Lysate and magnetic microsphere Genomic DNA ligation on magnetic microsphere Washing PEG washing buffer Genomic DNA ligation on magnetic microsphere Washing 80%

isopropyl alcohol

Genomic DNA ligation on magnetic microsphere Eluting TE

buffer

Genomic DNA ligation on magnetic microsphere

Genomic DNA

Fig. 3 Flow chart of DNA extraction 3.1.1 Genomic DNA (gDNA) Extraction

Whole Blood Sample Processing and Manual DNA Extraction

Genomic DNA was extracted from whole blood samples using the automated Maxwell® 16 DNA Purification Kits set to the LEV (low elution volume) configuration. DNA samples were purified using paramagnetic particles (PMPs), which provide a mobile solid phase that optimizes gDNA capture, washing and elution (see Notes 1 and 4). 1. Centrifuge whole blood samples (e.g. 2.5 mL of whole blood in a Vacutainer® tube) at 2000  g for 20 min. This results in separation of the material into three layers: a bottom layer containing mainly red blood cells, a top plasma layer and a thin white layer at the interface that is enriched for white blood cells. 2. Use a 1 mL pipette (e.g. Pipetman p1000) to carefully collect the enriched white cells (buffy coat) from the interface (see Notes 1 and 5). 3. Add 250 μL of buffy coat sample to a Maxwell® 16 elution tube containing MagneSil® particles, and perform cell lysis by adding 200 μL of lysis buffer. 4. Wash four times with 500 μL of washing buffer, and elute the DNA from the magnetic particles by adding 300 μL of elution buffer.

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5. After elution of concentrated genomic DNA, residual magnetic spheres can be removed by performing a second clearing using the magnetic elution rack or by centrifuging the eluted material and removing the supernatant to a fresh tube. 6. Concentration of the purified DNA should be measured by absorbance at 260 nm (see Note 7). Automated Purification

1. Set extraction program. 2. Transfer tubes containing samples and plungers from the cartridge preparation rack onto the support. 3. Place one blue elution tube for each cartridge into the elution tube slots at the front of the platform. 4. Add 300 μL of elution buffer to each blue elution tube. 5. Run extraction program. 6. Remove the elution tubes from the platform-heated elution tube slots and place them into the magnetic elution tube rack. 7. Transfer the eluted samples into the storage tube by pipetting. Purification kit is designed to purify genomic DNA from up to 400 μL of whole blood, assuming an average number of white blood cells in the range of 4.2  106 to 1.2  107/mL whole blood (values for a normal healthy adult).

3.2 NGS Library Preparation, Hybridization Capture, and Sequencing 3.2.1 Library Preparation

Individual libraries were prepared using the DNA Library Prep Kit by SOPHiA GENETICS (Saint-Sulpice, Switzerland) as well as AMPure XP® beads and individual adapters provided as part of the Custom Solution kit by SOPHiA GENETICS (Saint-Sulpice, Switzerland) according to the manufacturer’s recommendations. 1. A 200 ng sample of gDNA was enzymatically digested in a total volume of 50 μL for 5 min at 32  C followed by end repair and A-tailing for 30 min at 65  C, and was then immediately placed on ice. 2. Illumina-compatible index adapters were then ligated for 15 min at 20  C in a total volume of 100 μL. 3. Enzymes, buffer, and PCR primers were removed from the ligation reactions using 80 μL AMPure XP beads followed by clean-up with 80% ethanol and elution with 105 μL of IDTE buffer (see Note 8). 4. After magnetic separation, 100 μL of the post-ligation clean-up reaction was transferred to a new tube. Dual size selection of 300–700 bp DNA fragments was performed in two steps. 5. To remove fragments larger than 700 bp, 60 μL AMPure XP beads were added to 100 μL of post-ligation clean-up reaction, and 140 μL supernatant was retained after magnetic separation.

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6. Then, to remove fragments shorter than 300 bp, this supernatant was mixed with 20 μL fresh AMPure XP beads, cleaned with 80% ethanol and eluted with 23.5 μL of IDTE buffer (see Note 8). 7. The adapter-ligated and size-selected libraries were amplified in a volume of 50 μL for 8 PCR cycles: 98  C for 20 s, 60  C for 30 s, and 72  C for 30 s. 8. Finally, the libraries were purified using 50 μL AMPure XP beads followed by 80% ethanol (see Note 8) clean-up and elution to 20 μL with nuclease-free water. 9. Individual libraries were quantified using a Qubit dsDNA HS Assay Kit on a Qubit 2.0 fluorometer (Invitrogen, Thermo Fisher Scientific). 10. The library size was verified using capillary electrophoresis (2200 TapeStation, Agilent Technologies, Santa Clara, USA) according to the manufacturer’s guidelines. 11. Before capture enrichment, 150 ng of each individual library was pooled to obtain 8 tubes, each containing 12 individual libraries (1.8 μg DNA per tube). 12. To prevent nonspecific binding of the probes, Cot-1 DNA and blocking oligos were also added to the libraries, and the solution was dried using a vacuum DNA concentrator until mix is completely lyophilized (45–50  C). 13. Safe stopping point at 3.2.2 Hybridization Capture Using xGenR LockdownR Probes

20  C.

1. Dried pooled libraries were dissolved in 13 μL hybridization buffer and denatured at 95  C for 10 min. 2. The libraries were then hybridized at 65  C for 4 h by the addition of 4 μL HPD_v1 biotinylated probes (SOPHiA GENETICS). The probes target genomic regions associated to human diseases with genetic origin or influence. 3. 17 μL of each pool of libraries hybridized to biotin probes was bound for 45 min at 65  C with 100 μL cleaned streptavidin beads. 4. After the binding step, unbound and nonspecific DNA was removed using two stringent washes at 65  C followed by several washes at room temperature, and the beads were resuspended in 20 μL nuclease-free water in accordance with the manufacturer’s recommendations. 5. The post-capture pooled libraries were amplified for 14 cycles (98  C for 15 s, 60  C for 30 s, and 72  C for 30 s) using KAPA HiFi HotStart ReadyMix and Illumina-compatible library amplification primer mix (Kapa/Roche, Basel, Switzerland) in a total volume of 50 μL.

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6. After PCR amplification, the pooled libraries were purified using 50 μL AMPure XP beads (Beckman Coulter) and washed using 200 μL 80% ethanol (see Note 8). 7. The libraries were then quantified using the Qubit dsDNA HS Assay Kit on the Qubit 2.0 fluorometer (Invitrogen, Thermo Fisher Scientific). 8. The size of the captured libraries was analyzed using capillary electrophoresis (2200 TapeStation, Agilent Technologies, Santa Clara, USA) according to the manufacturer’s guidelines. Library DNA fragments should have a size distribution between 300 bp and 700 bp. 3.2.3 Sequencing

9. Each pooled library was diluted to a final concentration of 4 nM and denatured with 0.2 N NaOH (see Note 8). 10. Equimolar concentrations of the 8 pools of the 12 individual libraries were diluted and mixed to a final concentration of 10 pM (see Note 8). 11. The pooled libraries were combined with 1% PhiX Control before loading onto a NextSeq 500 instrument (Illumina, San Diego, USA). 12. Sequencing was performed with a 300 cycle mid-output kit v2.

3.2.4 Data Analysis

Raw sequence ∗.bcl files generated by the NextSeq 500 instrument were converted to ∗.fastQ files using the bcl2fastq module provided by Illumina. This online computer module works in the Windows environment, MacOS and Linux were supported. Sequence alignments were performed with the PEPPER variant calling technology provided by SOPHiA DDM. Single-nucleotide variations (SNVs), small insertions/deletions (INDELs), and copy number variants (CNVs) were identified using the ILL1XG1G2_CNV/v5.3.5/GEN1GN1GN1FSQ2 pipeline, which was optimized by SOPHiA GENETICS for analyzing germline samples using the HPD-v1 kit (SOPHiA GENETICS). Variant calling was performed with reference to the human genome version hg19/GRCh37 and using associated databases (see Note 9) from ANNOVAR to be included as annotations: RefSeq [40], dbSNP138 [41], the Exome Aggregation Consortium (ExAC) [42], the National Heart, Lung, and Blood Institute Exome Sequencing Project from approximately 5400 exomes (ESP 5400) (Exome Variant Server, NHLBI GO Exome Sequencing Project http://evs.gs.washington.edu/EVS/2017), the 1000 Genomes Project European Cohort (1KGP) [43], ClinVar [44], Combined Annotation Dependent Depletion (CADD) [45], Sorting Intolerant from Tolerant (SIFT) [46], and PolyPhen-2 [47]. A low-coverage warning is provided when fewer than 50 reads align

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over the target sequences. A minimum depth of 30 reads is required to trigger variant detection, with a minimum of 10 reads containing high-quality (Phred >20) alternate bases at the affected position. Query disease mutation databases determine if variants have been previously associated with disease, with reasonable evidence, considering any variants that have not been previously reported as a novel variant. ANNOVAR annotations from ClinVar were assessed, such that the disease-associated variants include any classified as likely pathogenic or pathogenic. Classify variants based on the American College of Medical Genetics (ACMG) Pathogenicity Guidelines [48], assigning each variant a classification as one of the following: (1) pathogenic; (2) likely pathogenic; (3) variant of uncertain significance; (4) likely benign; or (5) benign. The pathogenic mutation was confirmed by both PCR amplification and Sanger sequencing and was analyzed on an ABI PRISM 3130xl instrument (Applied Biosystems, Thermo Fisher, Waltham, USA). Sequence variations were annotated using SOPHiA’s PEPPER and MOKA technologies, which include annotations following the recommendations of the Human Genome Variation Society, i.e., nucleotide position +1 corresponds to the A of the ATG translation initiation codon in coding cDNA reference sequences (GenBank, https://www.ncbi.nlm.nih.gov/gene). 3.2.5 Example of a CNV Output generated by SOPHiA DDM® Software

Case study: Identification of a CCM disease-associated copy number variation (CNV) in a symptomatic 46-year-old patient. Using the experimental procedure described above, we identified distinct germline genetic variations of pathogenic significance in DNA samples from Italian patients with multiple CCM lesions on MRI examination and/or a positive family history of CCM disease. As an example, here we briefly report a result of NGS analysis carried out in a 46-year-old female patient with symptomatic CCM disease and earlier negative Sanger sequencing results for pathogenic mutations. A detailed description of the outcomes of clinical and genetic analyses will be reported elsewhere. Genomic DNA samples isolated from whole blood samples of 16 CCM patients were run on the NextSeq 500 instrument using a clinical exome sequencing (CES) panel. The DNA sample from the case study displayed a mean coverage of 82, with 99.44% of the target regions covered at least 25. After performing variant calling and annotation with the custom bioinformatics analysis workflow, the patient was found to harbor a CNV of a genomic segment on chromosome 7 containing the KRIT1 gene. Specifically, the identified CNV consisted of a large heterozygous deletion involving the entire KRIT1 gene and part of the neighboring gene AKAP9, including coding exons from 38 to 50 (Fig. 4). The CNV mutation was confirmed by real-time qRT-PCR.

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Fig. 4 CNV report from the CCM case study generated by SOPHiA DDM® software. The outputs (panels a-c) show a CNV of a genomic segment on chromosome 7 involving two neighboring genes, KRIT1 and AKAP9, including heterozygous deletion of all the 16 coding exons of KRIT1 (b) and the last 13 coding exons (from 38 to 50) of AKAP9 (c)

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Notes 1. The total yield of genomic DNA from whole blood samples depends on the sample volume and number of white blood cells/mL. Whole blood samples collected in EDTA, ACD or heparin can be used. These samples may be either fresh or frozen. Frozen samples should be thawed and mixed before processing. Samples with little available DNA must be extracted using a method that maximizes the amount of DNA recovered but elutes in a small volume. The Maxwell® 16 LEV method has been optimized to process samples in a low elution volume (LEV) automated format to address these concerns. The magnetic particle-based methodology avoids common problems such as clogged tips or partial reagent transfers that result in suboptimal purification processing by other commonly used automated systems. A Maxwell® 16 Blood DNA Purification Kit is sufficient for 48 automated isolations from whole blood samples and must be stored at 15–30  C. For detailed information, please refer to the Promega Technical Manual available at: www.promega.com/protocols. 2. U.S. Pat. Nos. 6,027,945, 6,368,800 and 6,673,631, European Pat. Nos. 0895546, 1367137 and 1204741, Japanese Pat. Nos. 3253638 and 4425513. 3. A Maxwell® 16 Blood DNA Purification Kit includes: 48 Maxwell® 16 Blood DNA cartridges, 50 purification plungers, 50 elution tubes, and 20 mL elution buffer. The reagent cartridges contain potentially hazardous chemicals. Wear gloves or other personal protective equipment when handling the reagent cartridges. Follow your institutional guidelines for disposal. 4. Genomic DNA samples stored at 20  C can be used for NGS analysis; however, DNA fragmentation and concentration should be evaluated before library preparation. 5. A volume of 250 μL of buffy coat (obtained from 2.5 mL of whole blood) can be processed using the Maxwell® 16 Blood DNA Cartridge and the buffy coat method supplied on the Maxwell® 16 Instrument. 6. Optional RNase Treatment: In some cases, total RNA may copurify with genomic DNA from cell samples. To remove copurified total RNA, perform an RNase treatment. Add 5 μL of RNase A per milliliter of elution buffer. 7. DNA purity should be confirmed by agarose gel electrophoresis and by measuring the A260/A280 ratio, which is typically >1.7. Specifically, the quantity and quality of human genomic DNA extracted from whole blood can be measured by reading

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the whole absorption spectrum (220–750 nm) with NanoDrop (e.g., NanoDrop ND-2000) and calculating DNA concentration and absorbance ratio at both 260/280 and 230/260 nm. Samples of 1 μl volume are measured without the need for cuvettes or capillaries.Each sample can be then quantified with the Qubit® fluorometer. This is a quantitation system relying on dyes that only fluoresce when bound to specific molecules, such as dsDNA, ssDNA or RNA. 8. Dilute stock solutions using nuclease-free water. 9. Use the most up to date available versions of databases.

Acknowledgements This work was supported by grants from the Telethon Foundation (grant GGP15219) and the Fondazione CRT (project “CerebroNGS.TO”) to SFR. The authors are grateful to CCM Italia, the Italian Research Network for Cerebral Cavernous Malformation (https://www. ccmitalia.unito.it), and the Associazione Italiana Angiomi Cavernosi (AIAC) Onlus (https://www.aiac.unito.it), including its president Massimo Chiesa, and Santina Barbaro for fundamental support. We also thank Lorenza Trabalzini for helpful cooperation in reviewing and editing the manuscript. This chapter is dedicated to the memory of Rosa Giunta, Fortunato Barbaro, and Adelia Frison. References 1. Parikh VN, Ashley EA (2017) Next-generation sequencing in cardiovascular disease. Circulation 135(5):406–409 2. Batra S, Lin D, Recinos PF, Zhang J, Rigamonti D (2009) Cavernous malformations: natural history, diagnosis and treatment. Nat Rev Neurol 5:659–670 3. Rigamonti D (2011) Cavernous malformations of the nervous system 4. Fontanella M (2015) Cerebral cavernous malformations. Edizioni Minerva Medica 5. Fontanella MM, Panciani PP, Spena G, Roca E, Migliorati K, Ambrosi C, Sturiale CL, Retta SF (2015) Professional athletes and cerebral cavernomas: an obstacle to overcome. J Sports Med Phys Fitness 55(9):1046–1047 6. Fontanella M, Bacigaluppi S (2015) Treatment of cerebral cavernous malformations: where do we stand? J Neurosurg Sci 59(3):199–200 7. Laberge-le Couteulx S, Jung HH, Labauge P, Houtteville JP, Lescoat C, Cecillon M,

Marechal E, Joutel A, Bach JF, Tournier-Lasserve E (1999) Truncating mutations in CCM1, encoding KRIT1, cause hereditary cavernous angiomas. Nat Genet 23:189–193 8. Sahoo T, Johnson EW, Thomas JW, Kuehl PM, Jones TL, Dokken CG, Touchman JW, Gallione CJ, Lee-Lin SQ, Kosofsky B, Kurth JH, Louis DN, Mettler G, Morrison L, Gil-Nagel A, Rich SS, Zabramski JM, Boguski MS, Green ED, Marchuk DA (1999) Mutations in the gene encoding KRIT1, a Krev-1/rap1a binding protein, cause cerebral cavernous malformations (CCM1). Hum Mol Genet 8:2325–2333 9. Liquori CL, Berg MJ, Siegel AM, Huang E, Zawistowski JS, Stoffer T, Verlaan D, Balogun F, Hughes L, Leedom TP, Plummer NW, Cannella M, Maglione V, Squitieri F, Johnson EW, Rouleau GA, Ptacek L, Marchuk DA (2003) Mutations in a gene encoding a novel protein containing a phosphotyrosine-binding domain

NGS Strategies for Genetic Studies of CCM Disease cause type 2 cerebral cavernous malformations. Am J Hum Genet 73:1459–1464 10. Bergametti F, Denier C, Labauge P, Arnoult M, Boetto S, Clanet M, Coubes P, Echenne B, Ibrahim R, Irthum B, Jacquet G, Lonjon M, Moreau JJ, Neau JP, Parker F, Tremoulet M, Tournier-Lasserve E, Socie´te´ Franc¸aise de Neurochirurgie (2005) Mutations within the programmed cell death 10 gene cause cerebral cavernous malformations. Am J Hum Genet 76:42–51 11. Choquet H, Pawlikowska L, Lawton MT, Kim H (2015) Genetics of cerebral cavernous malformations: current status and future prospects. J Neurosurg Sci 59:211–220 12. Goitre L, Balzac F, Degani S, Degan P, Marchi S, Pinton P, Retta SF (2010) KRIT1 regulates the homeostasis of intracellular reactive oxygen species. PLoS One 5:e11786 13. Guazzi P, Goitre L, Ferro E, Cutano V, Martino C, Trabalzini L, Retta SF (2012) Identification of the Kelch family protein Nd1-L as a novel molecular interactor of KRIT1. PLoS One 7:e44705 14. Goitre L, De Luca E, Braggion S, Trapani E, Guglielmotto M, Biasi F, Forni M, Moglia A, Trabalzini L, Retta SF (2014) KRIT1 loss of function causes a ROS-dependent upregulation of c-Jun. Free Radic Biol Med 68:134–147 15. Marchi S, Corricelli M, Trapani E, Bravi L, Pittaro A, Delle Monache S, Ferroni L, Patergnani S, Missiroli S, Goitre L, Trabalzini L, Rimessi A, Giorgi C, Zavan B, Cassoni P, Dejana E, Retta SF, Pinton P (2015) Defective autophagy is a key feature of cerebral cavernous malformations. EMBO Mol Med 7:1403–1417 16. Marchi S, Retta SF, Pinton P (2016) Cellular processes underlying cerebral cavernous malformations: autophagy as another point of view. Autophagy 12:424–425 17. Marchi S, Trapani E, Corricelli M, Goitre L, Pinton P, Retta SF (2016) Beyond multiple mechanisms and a unique drug: defective autophagy as pivotal player in cerebral cavernous malformation pathogenesis and implications for targeted therapies. Rare Dis 4: e1142640 18. Retta SF, Glading AJ (2016) Oxidative stress and inflammation in cerebral cavernous malformation disease pathogenesis: two sides of the same coin. Int J Biochem Cell Biol 81:254–270 19. Goitre L, DiStefano PV, Moglia A, Nobiletti N, Baldini E, Trabalzini L, Keubel J, Trapani E,

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Shuvaev VV, Muzykantov VR, Sarelius IH, Retta SF, Glading AJ (2017) Up-regulation of NADPH oxidase-mediated redox signaling contributes to the loss of barrier function in KRIT1 deficient endothelium. Sci Rep 7:8296 20. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Daga M, Pizzimenti S, Barrera G, Cassoni P, Angelucci A, Trabalzini L, Talesa VN, Goitre L, Retta SF (2018) KRIT1 lossof-function induces a chronic Nrf2-mediated adaptive homeostasis that sensitizes cells to oxidative stress: implication for cerebral cavernous malformation disease. Free Radic Biol Med 115:202–218 21. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Fornelli C, Retta F, Cassoni P, Talesa VN, Retta SF (2018) Data in support of sustained upregulation of adaptive redox homeostasis mechanisms caused by KRIT1 loss-offunction. Data Brief 16:929–938 22. Cianfruglia L, Perrelli A, Fornelli C, Magini A, Gorbi S, Salzano AM, Antognelli C, Retta F, Benedetti V, Cassoni P, Emiliani C, Principato G, Scaloni A, Armeni T, Retta SF (2019) KRIT1 loss-of-function associated with cerebral cavernous malformation disease leads to enhanced. Antioxidants (Basel) 8:E27 23. Antognelli C, Perrelli A, Armeni T, Nicola Talesa V, Retta SF (2020) Dicarbonyl stress and S-glutathionylation in cerebrovascular diseases: a focus on cerebral cavernous malformations. Antioxidants 9(2):124 24. Vieceli Dalla Sega F, Mastrocola R, Aquila G, Fortini F, Fornelli C, Zotta A, Cento AS, Perrelli A, Boda E, Pannuti A, Marchi S, Pinton P, Ferrari R, Rizzo P, Retta SF (2019) KRIT1 deficiency promotes aortic endothelial dysfunction. Int J Mol Sci 20(19):4930 25. Finetti F, Schiavo I, Ercoli J, Zotta A, Boda E, Retta SF, Trabalzini L (2020) KRIT1 lossmediated upregulation of NOX1 in stromal cells promotes paracrine pro-angiogenic responses. Cell Signal 68:109527 26. Trapani E, Retta SF (2015) Cerebral cavernous malformation (CCM) disease: from monogenic forms to genetic susceptibility factors. J Neurosurg Sci 59:201–209 27. Choquet H, Trapani E, Goitre L, Trabalzini L, Akers A, Fontanella M, Hart BL, Morrison LA, Pawlikowska L, Kim H, Retta SF (2016) Cytochrome P450 and matrix metalloproteinase genetic modifiers of disease severity in cerebral cavernous malformation type 1. Free Radic Biol Med 92:100–109 28. Gibson CC, Zhu W, Davis CT, Bowman-Kirigin JA, Chan AC, Ling J, Walker AE, Goitre L, Delle Monache S, Retta SF, Shiu YT,

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Grossmann AH, Thomas KR, Donato AJ, Lesniewski LA, Whitehead KJ, Li DY (2015) Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131:289–299 29. Moglia A, Goitre L, Gianoglio S, Baldini E, Trapani E, Genre A, Scattina A, Dondo G, Trabalzini L, Beekwilder J, Retta SF (2015) Evaluation of the bioactive properties of avenanthramide analogs produced in recombinant yeast. Biofactors 41:15–27 30. Moglianetti M, De Luca E, Pedone D, Marotta R, Catelani T, Sartori B, Amenitsch H, Retta SF, Pompa PP (2016) Platinum nanozymes recover cellular ROS homeostasis in an oxidative stress-mediated disease model. Nanoscale 8:3739–3752 31. De Luca E, Pedone D, Moglianetti M, Pulcini D, Perrelli A, Retta SF, Pompa PP (2018) Multifunctional Platinum@BSA-Rapamycin nanocarriers for the combinatorial therapy of cerebral cavernous malformation. ACS Omega 3:15389–15398 32. Perrelli A, Goitre L, Salzano AM, Moglia A, Scaloni A, Retta SF (2018) Biological activities, health benefits, and therapeutic properties of avenanthramides: from skin protection to prevention and treatment of cerebrovascular diseases. Oxidative Med Cell Longev 2018:6015351 33. Moglianetti M, Pedone D, Udayan G, Retta SF, Debellis D, Marotta R, Turco A, Rella S, Malitesta C, Bonacucina G, De Luca E, Pompa PP (2020) Intracellular antioxidant activity of biocompatible citrate-capped palladium nanozymes. Nanomaterials 10(1):99 34. Spiegler S, Najm J, Liu J, Gkalympoudis S, Schro¨der W, Borck G, Brockmann K, Elbracht M, Fauth C, Ferbert A, Freudenberg L, Grasshoff U, Hellenbroich Y, Henn W, Hoffjan S, Hu¨ning I, Korenke GC, Kroisel PM, Kunstmann E, Mair M, Munk-Schulenburg S, Nikoubashman O, Pauli S, Rudnik-Scho¨neborn S, Sudholt I, Sure U, Tinschert S, Wiednig M, Zoll B, Ginsberg MH, Felbor U (2014) High mutation detection rates in cerebral cavernous malformation upon stringent inclusion criteria: one-third of probands are minors. Mol Genet Genomic Med 2:176–185 35. Spiegler S, Rath M, Paperlein C, Felbor U (2018) Cerebral cavernous malformations: an update on prevalence, molecular genetic analyses, and genetic counselling. Mol Syndromol 9(2):60–69 36. Retta SF, Avolio M, Francalanci F, Procida S, Balzac F, Degani S, Tarone G, Silengo L (2004) Identification of Krit1B: a novel

alternative splicing isoform of cerebral cavernous malformation gene-1. Gene 325:63–78 37. Jiang X, Padarti A, Qu Y, Sheng S, Abou-Fadel J, Badr A, Zhang J (2019) Alternatively spliced isoforms reveal a novel type of PTB domain in CCM2 protein. Scientific Rep 9(1). https:// doi.org/10.1038/s41598-019-52386-0 38. Bulut HT, Sarica MA, Baykan AH (2014) The value of susceptibility weighted magnetic resonance imaging in evaluation of patients with familial cerebral cavernous angioma. Int J Clin Exp Med 7:5296–5302 39. Rigamonti D, Drayer BP, Johnson PC, Hadley MN, Zabramski J, Spetzler RF (1987) The MRI appearance of cavernous malformations (angiomas). J Neurosurg 67:518–524 40. O’Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R, Rajput B, Robbertse B, Smith-White B, Ako-Adjei D, Astashyn A, Badretdin A, Bao Y, Blinkova O, Brover V, Chetvernin V, Choi J, Cox E, Ermolaeva O, Farrell CM, Goldfarb T, Gupta T, Haft D, Hatcher E, Hlavina W, Joardar VS, Kodali VK, Li W, Maglott D, Masterson P, McGarvey KM, Murphy MR, O’Neill K, Pujar S, Rangwala SH, Rausch D, Riddick LD, Schoch C, Shkeda A, Storz SS, Sun H, Thibaud-Nissen F, Tolstoy I, Tully RE, Vatsan AR, Wallin C, Webb D, Wu W, Landrum MJ, Kimchi A, Tatusova T, DiCuccio M, Kitts P, Murphy TD, Pruitt KD (2016) Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 44:D733–D745 41. Kitts A, Phan L, Ward M, Bradley Holmes J (2013) The database of short genetic variation (dbSNP). The NCBI handbook 42. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, O’Donnell-Luria AH, Ware JS, Hill AJ, Cummings BB, Tukiainen T, Birnbaum DP, Kosmicki JA, Duncan LE, Estrada K, Zhao F, Zou J, Pierce-Hoffman E, Berghout J, Cooper DN, Deflaux N, DePristo M, Do R, Flannick J, Fromer M, Gauthier L, Goldstein J, Gupta N, Howrigan D, Kiezun A, Kurki MI, Moonshine AL, Natarajan P, Orozco L, Peloso GM, Poplin R, Rivas MA, RuanoRubio V, Rose SA, Ruderfer DM, Shakir K, Stenson PD, Stevens C, Thomas BP, Tiao G, Tusie-Luna MT, Weisburd B, Won HH, Yu D, Altshuler DM, Ardissino D, Boehnke M, Danesh J, Donnelly S, Elosua R, Florez JC, Gabriel SB, Getz G, Glatt SJ, Hultman CM, Kathiresan S, Laakso M, McCarroll S, McCarthy MI, McGovern D, McPherson R, Neale BM, Palotie A, Purcell SM, Saleheen D, Scharf JM, Sklar P, Sullivan PF, Tuomilehto J, Tsuang MT, Watkins HC, Wilson JG, Daly MJ,

NGS Strategies for Genetic Studies of CCM Disease MacArthur DG, Consortium EA (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:285–291 43. Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR, Genomes Project Consortium (2015) A global reference for human genetic variation. Nature 526:68–74 44. Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Hoover J, Jang W, Katz K, Ovetsky M, Riley G, Sethi A, Tully R, Villamarin-Salomon R, Rubinstein W, Maglott DR (2016) ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res 44: D862–D868 45. Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative

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pathogenicity of human genetic variants. Nat Genet 46:310–315 46. Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4:1073–1081 47. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR (2010) A method and server for predicting damaging missense mutations. Nat Methods 7:248–249 48. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, Committee ALQA (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17:405–424

Chapter 6 Genome-wide Genotyping of Cerebral Cavernous Malformation Type 1 Individuals to Identify Genetic Modifiers of Disease Severity He´le`ne Choquet and Helen Kim Abstract Familial cerebral cavernous malformation type 1 (CCM1) is an autosomal dominant disease caused by mutations in the Krev Interaction Trapped 1 (KRIT1/CCM1) gene, and characterized by brain lesions that can cause hemorrhagic strokes, seizures, and neurological deficits. Carriers of the same genetic mutation can present with variable symptoms and severity of disease, suggesting the influence of modifier factors. Genetic modifiers of CCM1 disease severity have been recently identified and included common genetic variants in inflammatory, immune response, and oxidative stress genes and pathways. Here, we describe the genotyping of CCM1 patients with the same gene mutation (Q455X) using a high-throughput genotyping array optimized for individuals of Hispanic/Latino ancestry. We then review the quality control steps following the genome-wide genotyping. Genome-wide genotyping of larger cohorts of CCM1 patients might reveal additional genetic variants contributing to the disease severity of CCM1. Key words Cerebral cavernous malformation type 1, Disease severity, DNA, Genome-wide genotyping, Microarray, Single nucleotide polymorphism, Genetic modifiers

1

Introduction Familial cerebral cavernous malformation type 1 (CCM1) is an autosomal dominant disease caused by mutations in the Krev Interaction Trapped 1 (KRIT1/CCM1) gene, and characterized by brain lesions that can cause hemorrhagic strokes, seizures, and neurological deficits. As patients present with a wide range of symptoms, even among carriers of the same genetic mutation for undetermined reasons, it is of particular interest to examine genetic modifiers in CCM1 disease severity [1]. Over the last decade, the development of high-throughput genotyping microarrays has been facilitated by the establishment of the human genome single-nucleotide polymorphism (SNP) map through the International HapMap Project [2]. A SNP is the most common form of variation in the human genome, in which a single

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_6, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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DNA base pair differs between two copies of the genome. Common variants are typically defined as those variants that have a minor allele frequency (MAF) greater than 1%. The development of high-throughput genotyping platforms assaying hundreds of thousands to a million SNPs has offered a wide range of applications for human disease research. These include genome-wide association studies (GWAS) and candidate-gene association, among others. These genome-wide genotyping applications have considerably facilitated a wide range of discoveries in human genetics, illuminating the biological basis of numerous diseases and complex traits, and opening the doors to new targeted therapies [3, 4]. Recently, we investigated genetic modifiers of CCM1 disease severity in a well-characterized cohort of familial Hispanic CCM1 patients, all carriers of a founder mutation in KRIT1 named the “common Hispanic mutation” (c.1363 C>T or Q455X, rs267607203) [5, 6]. Genomic DNA (gDNA) samples from these CCM1 patients were first genome-wide genotyped using the Affymetrix Axiom® Genome-Wide LAT 1 array that includes 817,810 genetic markers (i.e., 813,551 SNPs and 4259 insertion/ deletions) [7]. Using a candidate-gene approach, we then assessed the associations between selected genes/biological pathways and the risk of intracerebral hemorrhage, the number of large lesions, or the total number of lesions, reflecting CCM1 disease severity [5, 6]. We demonstrated that common genetic factors in inflammation and immune response [5] and oxidative stress [6] genes and pathways contribute to the disease severity of CCM1. Here, we describe genome-wide genotyping of these samples using the Affymetrix Axiom® Genome-Wide LAT 1 Human Array. We also review the quality control and data analysis steps following genome-wide genotyping. Future investigations might expand our understanding of the genetic architecture of CCM1 by identifying additional genetic modifiers of CCM1 disease severity, which will help to explain the significant phenotypic heterogeneity of the disease.

2

Materials

2.1 DNA Sample Collection and Preparation

1. QIAamp DNA Blood Mini/Midi/Maxi Kits (Qiagen) to isolate gDNA from fresh and frozen whole blood or buffy coat samples. 2. Oragene® collection kit (DNA Genotek) to collect human genomic DNA (gDNA) from saliva samples and Oragene prepIT® reagent (DNA Genotek). 3. Quantus™ Fluorometer (Promega) in combination with the Quant-iT™ PicoGreen® double-stranded DNA (dsDNA) Assay Kit (Promega) for DNA quantitation.

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4. Low EDTA TE buffer: 10 mM Tris–HCl, pH 8.0, 0.1 mM EDTA for DNA suspension and storage. 5. Hard Shell 96-well plate. 2.2 Genome-wide Genotyping

1. GeneTitan™ Multi-Channel (MC) Instrument (Affymetrix). 2. Axiom® Genome-Wide LAT 1 Array (Affymetrix). 3. Axiom® GeneTitan® Consumables Kit (Affymetrix). 4. Axiom® 2.0 Reagent Kit (Affymetrix).

2.3 Post-genotyping Quality Control

1. Genotyping Console™ Software (Affymetrix) to perform genotype calling, quality control (QC) analysis, and sample or SNP filtering prior to downstream analysis. 2. PLINK software [8, 9]: free, open-source whole genome association analysis toolset (www.cog-genomics.org/plink/) to perform additional QC and downstream association analyses.

3

Methods

3.1 DNA Samples Collection and Preparation

1. Extract gDNA samples from whole blood or buffy coat specimens using QIAamp DNA Blood Mini/Midi/Maxi Kits (Qiagen) or from saliva specimens collected in Oragene® collection kits (DNA Genotek) using prepIT® reagent according to manufacturer’s standard protocols. 2. Determine gDNA concentration by the PicoGreen method (see Notes 1–2). The Quant-iT™ PicoGreen® dsDNA assay quantitates dsDNA in solution at a final assay concentration of 1 ng/ μL–250 pg/mL of dsDNA. 3. Verify the quality of the gDNA (i.e., presence of high molecular weight DNA) by taking 10 ng of gDNA from each sample and running them on a 1% agarose gel (see Note 3). 4. Prepare 600 ng of gDNA at 10 ng/μL (60 μL total) in low EDTA TE buffer. 5. Plate the gDNA samples into a hard shell 96-well plate (see Notes 4–5). Leave one well open (a different well to identify each plate) for the Affymetrix Reference DNA control (see Note 6). Place the gDNA samples in a random pattern in terms of males and females, so that each plate has a different pattern. This will prevent plate mix-ups. Verify that at least 29 females or no females are on each plate for the genotyping algorithm to work (see Note 7). 6. Fill out a 96-well plate layout template for each plate to identify the sample’s location.

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3.2 Genome-wide Genotyping

1. Load the arrays (see Note 8), prepared gDNA samples, and reagents into the GeneTitan™ MC instrument. 2. Press start on the GeneTitan™ MC instrument (see Note 9). 3. View preliminary analysis on the GeneTitan™ MC instrument. Primary analysis can be completed automatically to rapidly assess the quality of each experimental study.

3.3 Post-genotyping Quality Control

1. Generate quality control (QC) metrics and genotype calls (plate by plate) using the Affymetrix Genotyping Console™ (GTC) software through the best practices axiom analysis workflow (see Note 10). 2. Review the QC report including the Dish QC (DQC) scores (see Note 11) and genotype call rates (see Note 12). 3. Exclude samples (individuals) with a DQC value 1.5 (see Note 15). 5. Transfer a suitable volume of overnight culture to a flask containing 300 mL of YPD to obtain an OD600 of 0.2–0.3. 6. Incubate at 30
C for 3 h with shaking (250 rpm) or until OD600 0.4–0.6 (see Note 16). 7. Place cells in 50 mL tubes and centrifuge at 1000  g for 5 min at room temperature. 8. Discard the supernatant and thoroughly resuspend the cell pellet in sterile TE or distilled H2O. Pool the cells into one tube (final volume 25–50 mL). 9. Centrifuge at 1000  g for 5 min at room temperature. 10. Decant the supernatant. 11. Resuspend the cell pellet in 1.5 mL of freshly prepared, sterile 1 TE/1 LiAc. You have prepared competent yeast cells ready to be transformed. 12. Add 0.4–0.6 μg plasmid DNA and 0.1 mg of carrier DNA to a fresh 1.5-mL tube and mix. 13. Add 0.1 mL of yeast competent cells to each tube and mix well by vortexing. 14. Add 0.6 mL of sterile PEG/LiAc solution to each tube and vortex to mix. 15. Incubate at 30
C for 30 min with shaking at 200 rpm. 16. Add 70 μL of DMSO. Mix well by gentle inversion. Do not vortex. 17. Heat shock for 15 min in a 42
C water bath. 18. Chill cells on ice for 1–2 min. 19. Centrifuge cells for 30 s in a microfuge at the maximum speed at room temperature. Remove the supernatant. Resuspend cells in 0.5 mL of sterile 1 TE buffer and centrifuge for 30 s as above (see Note 17).

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Table 1 Two-hybrid vectors provided by the MatchmakerTM GAL4 two-hybrid system 3 (Clontech) Fusion

Epitope

Yeast selection

Bacterial selection

pGBKT7

DNA-BD/BAIT

c-Myc

TRP1

Kanamycin

pGADT7

AD/Library or AD/PREY

HA

LEU2

Ampicillin

pGBKT7-53

DNA-BD/p53

c-Myc

TRP1

Kanamycin

pGADT7-T

AD/T-antigen

HA

LEU2

Ampicillin

pCL1

GAL4

LEU2

Ampicillin

Cloning vectors

Control vectors

The table reports the two-hybrid vectors provided by the commercial kit mentioned in this chapter Cloning vectors: pGABKT7, expresses proteins as fusion products with the GAL4 DNA-BD domain. Contains the Kanr gene for selection in E. coli and the nutritional marker TRP1 for selection in yeast. pGADT7, expresses proteins as fusion products with the GAL4 AD domain. Contains the Ampr gene for selection in E. coli and the nutritional marker LEU2 for selection in yeast Control vectors: pGBKT7-53 and pGADT7-T encode a DNA-BD/murine p53 fusion protein and an AD/SV40 large T-antigen fusion protein, respectively. As the two proteins show a strong interaction in a Y2H assay, they are generally used as positive controls for the interaction [15] pCL1 encodes the full-length, wild-type GAL4 protein and provides a positive control for α-galactosidase and β-galactosidase assays HA hemagglutinin

20. Discard super and resuspend in 0.2 mL of TE 1 buffer. 21. Plate 100 μL of cell suspension on 100 mm SD selective plates (SD/-Trp for DNA-BD constructs and SD/-Leu for AD constructs). 22. Incubate plates at 30
C until colonies appear (generally, 2–4 days). 3.6 Library Screening: Mating Protocol

3.6.1 Determination of the Library Titer (See Note 18)

The protocol described here is suitable for the screening of a cDNA library cloned in the pGADT7 vector and already transformed in the Y187 (MATα) yeast strain, which can be mated with the AH109 (MATa) yeast strain pretransformed with the BAIT (see Note 2 and Table 1) as described in Subheading 3.5. 1. Transfer a 10 μL aliquot of the pretrasformed library to complete medium and plate five appropriate dilutions of this suspension on 10 mm SD/-Leu plates. 2. Incubate plates at 30
C until colonies appear (3–5 days). 3. Calculate the library titer as follows:


N colonies ¼ cfu=mL Plating volume ðmLÞ  dilution factor

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Federica Finetti and Lorenza Trabalzini Transform a MATa yeast strain with BAIT

Prepare liquid culture of the pretrasformed BAIT strain

Mate the pretrasformed BAIT and the pretrasformed library (in a MAT yeast strain)

Plate mating culture and controls on appropriate SD selection media

[Optional] Perform -gal assay

[Optional] Streak selected transformants on X- -Gal selection plates to assay for -galactosidase

Isolate positive clones

Fig. 3 Y2H screening using a pretrasformed cDNA library and mating. Overview of the procedure 3.6.2 Mating (Fig. 3)

1. Inoculate one fresh, large colony of your bait strain (AH109 transformed with the BAIT) into 50 mL of SD/-Trp liquid medium. Incubate shaking (250–270 rpm) at 30
C until the OD600 reaches 0.8 (16–20 h). 2. Centrifuge to pellet the cells (1000  g for 5 min), discard the supernatant. 3. Resuspend the pellet to a cell density of >1  108 cells per mL in 4–5 mL of SD/-Trp. 4. Combine 1 mL of Library strain with the 5 mL of Bait strain in a sterile 2 L flask. Add 45 mL of 2 YPDA liquid medium with 50 mg/mL kanamycin. 5. Incubate at 30
C for 20–24 h, slowly shaking (30–50 rpm) (see Note 19). 6. Centrifuge to pellet the cells at 1000  g for 10 min at room temperature. 7. Meanwhile rinse the 2 L flask twice with 50 mL of 0.5  YPDA with 50 μg/mL kanamycin, combine the rinses and use them to resuspend the pelleted cells.

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8. Centrifuge to pellet the cells at 1000  g for 10 min at room temperature and discard the supernatant. 9. Resuspend cells in 10 mL of 0.5 YPDA/Kan. Measure the total volume of cells + medium. 10. To calculate the number of clones screened, prepare 1/10, 1/100, 1/1000, 1/10,000 dilutions of the cell suspension and spread 100 μL of each dilution on the following 100 mm selective plates and incubate at 30
C for 3–5 days. SD/-Trp (negative control) SD/-Leu (negative control) SD/-Trp/-Leu (diploids cells containing both DNA-BD and AD constructs will grow on this plate) 11. Plate 200 μL aliquots of the remainder of the culture, on 150 mm SD/-Trp/-Leu/-His plates (you will need 50–55 plates). Incubate at 30
C for 3–8 days. Ignore small pale colonies that may appear after 2 days but never grow to >1 mm in diameter. True His+ colonies are robust and can grow to >2 mm. They will be tested for expression of the other reporter genes. 12. Calculate the number of screened clones (diploids) by counting the colonies from the SD/-Leu/-Trp plates (step 10) after 3–5 days. Number of Screened Clones ¼ cfu=mL of diploids  resuspension volume ðmLÞ: It is imperative that at least 1 million diploids are screened. A lower amount will result in a lower chance of detecting genuine interactions (see Note 20). 13. Peak Trp+Leu+His+ colonies with a plastic loop and streak on 100 mm selective SD/-Trp/-Leu/-His/-Ade to test the activation of the ADE2 reporter gene. Let them grow at 30
C. 14. Streak Trp+Leu+His+Ade+ colonies on 100 mm SD/-Trp/Leu/-His/X-α-GAL plates to test the activation of the MEL1 reporter gene (colonies turning blue) (see Note 21). Clones able to grow in the absence of His and Ade and expressing α-galactosidase activity may be considered true positives of the screening and further analyzed. If the number of true positives is very high, the clones can be further selected by verifying activation of the LACZ reporter gene (β-galactosidase filter assay). 3.7 β-Galactosidase Filter Assay

1. For best results, use fresh colonies grown on SD/-Trp/-Leu/His plates (see Note 22). 2. For each plate, presoak a sterile filter by placing it in 2.5–5 mL of Z buffer/X-gal solution in a clean 100-mm diameter plate.

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3. Using forceps, place a clean, dry filter over the surface of the plate of colonies to be assayed. Gently rub the filter with the side of the forceps to help colonies cling to the filter. 4. Carefully lift the filter off the agar plate with forceps and transfer it (colonies facing up) to a pool of liquid nitrogen. Using the forceps, completely submerge the filters in the liquid nitrogen. 5. After the filter has frozen completely (~10 s), remove it from the liquid nitrogen and allow it to thaw at room temperature. This freeze/thaw treatment permeabilizes the cells. 6. Carefully place the filter, colony side up, on the presoaked filter (from step 2). Avoid trapping air bubbles under or between the filters. 7. Incubate the filters at room temperature and check periodically for the appearance of blue colonies (see Note 23). 8. Identify the β-galactosidase-producing colonies. Pick the corresponding positive colonies from the original plates to fresh medium and keep them for further analysis. 3.8 Analysis of Positive Clones (Fig. 4)

3.8.1 Extraction of Plasmid DNA from Yeast Cells (See Note 24)

This phase of the screening is aimed to isolate and identify the AD construct contained in each positive clone and encoding putative interactors of the bait protein. To accomplish this aim, total plasmid DNA is first extracted from yeast cells and then used to transform bacterial cells. AD constructs are finally rescued by bacterial cells by taking advantage of the different selection markers of DNA-BD and AD vectors. 1. For each positive clone, pick the colony, inoculate into 2 mL of SD/-Leu/-Trp medium, and incubate overnight at 30
C with shaking. 2. Pellet the cells in a 1.5-mL microcentrifuge tube and remove the supernatant. 3. Add 200 μL of YLS and gently resuspend the cell pellet with a micropipette tip. 4. Add 400 μL of glass beads and 200 μL of phenol/chloroform/ isoamyl alcohol. 5. Vortex vigorously for 2 min and centrifuge in microfuge at maximum speed for 1 min. 6. Transfer the aqueous phase to a fresh tube and precipitate the nucleic acids by adding 20 μL of sodium acetate and 500 μL of 95% ethanol. 7. Collect the precipitate by centrifugation at maximum speed for 5 min and wash the nucleic acid pellet once with 500 μL of 70% ethanol.

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Isolate plasmids from yeast

[Optional] Eliminate colonies bearing the same AD/library plasmid by PCR

Transform plasmids into E.coli and rescue AD/library plasmids

Conferm interactions in yeast by small scale Y2H

Sequence cDNA inserts

Confirm protein interactions by In vitro binding assays GST-pull down assay ELISA format binding assay etc.

Confirm protein interactions in mammalian cells In vivo co-IP of tagged overexpressed proteins In vivo co-IP of endogenous proteins

Additional Y2H tests Site-specific mutation/deletions

Fig. 4 Analysis of positive clones. Overview of the general strategy

8. Air-dry the pellet for 5 min at room temperature. 9. Dissolve the pellet in 25 μL of TE buffer. 10. Use this DNA extract to transform E. coli cells. 3.8.2 Selection of Plasmids in Bacterial Cells (See Note 25)

1. For each positive clone, add 5 μL of the plasmid DNA extract to competent bacterial cells and incubate in ice for 30 min. 2. Heat shock cells by incubating at 42
C for 45 s and then in ice for 3 min. 3. Add 900 μL of SOC medium and incubate at 37
C for 1 h under shaking. 4. Pellet cells in the microfuge, remove most of the supernatant, leave 150–200 μL. 5. Resuspend cells, plate on LB-Amp and incubate overnight at 37
C to select bacterial clones containing the AD constructs.

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3.8.3 Extraction of AD Constructs from Bacterial Cells

3.8.4 Analysis of AD Constructs

1. For each positive clone, inoculate one amp+ colony into 5 mL on LB/amp and incubate overnight at 37
C with shaking. 2. Purify the AD construct from transformed bacterial cellular suspension using any standard mini-prep DNA purification protocol or kit. 1. Verify the presence and the size of the insert in AD constructs isolated from positive clones by enzymatic digestion and analysis by agarose gel electrophoresis. 2. If the number of positive clones is high, you may need to amplify AD/library inserts by PCR and characterize PCR products by digesting with a frequent cutter restriction enzyme, such as AluI or HaeIII. Analyze fragment size by agarose gel electrophoresis to check for multiple AD/library plasmids and eliminate multiple copies.

3.8.5 Bait Dependency Test

Use each AD vector containing an insert in a small-scale two-hybrid assay to verify the interaction with the bait protein. For each AD construct, cotransform AH109 cells with the following couples of plasmids: BD bait/AD library insert Empty BD vector/AD library insert Only the AD/library insert Cotransform also with the following couples of plasmids as controls: empty BD vector/empty AD vector (negative control) pGBKT7-53/pGADT7-T (positive control)

1. Perform cotransformation as described in Subheading 3.5 using 0.4–0.6 μg of each plasmid DNA. 2. Plate cotransformed cells onto SD/-Trp/-Leu plates and incubate at 30
C until colonies appear. 3. Streak Trp+/Leu+ transformants on SD/-Trp/-Leu/-His and SD/-Trp/-Leu/-His/X-α-GAL and incubate at 30
C. 4. Select clones that exhibit a bait-dependent His3/Mel1-positive phenotype (Table 2) and sequence by using a GAL4AD sequencing primer. 5. Identify putative interacting clones by using bioinformatics tools.

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Table 2 Bait dependency test Plasmid 1 (DNA-BD)

Plasmid 2 (AD)

Expected Y2H results for a true positive

None

AD/library insert

Negative

DNA-BD only (empty vector)

AD/library insert

Negative

DNA-BD/BAIT

AD/library insert

Positive

AH109 cells are cotransformed with combinations of DNA-BD and AD plasmid as indicated and plated on SD/-Trp/Leu selective plates. Protein–protein interactions are verified on the basis of the ability of Trp+/Leu+ transformants to grow on SD/-Trp/-Leu/-His plates (activation of HIS3 reporter gene) and to turn blue on SD/-Trp/-Leu/-His/ X-α-GAL plates (activation of MEL1 reporter gene). The table shows expected results for bait-dependent interactions

3.8.6 Follow-up

1. Validate protein–protein interaction isolated by Y2H screening by using alternative techniques, in non-yeast-based assays. Approaches conventionally used include in vitro binding assays, in vitro “pull-down” assay, co-immunoprecipitation of endogenous proteins, co-immunolocalization. 2. You may further characterize the isolated interaction by generating site-specific mutations and/or deletions of the binding partners and using them in small-scale Y2H assays in order to map regions or residues critical for the interaction.

4

Notes 1. It is not necessary to handle yeast under laminar flood, but take care to work always in “clean” environment because bacterial contaminations are worst enemies for this assay. 2. Here we will refer to the components of the MatchmakerTM GAL4 two-Hybrid System 3 (Clontech) kit as this is the version that we used. As other systems commercially available, this system contains the GAL4 DNA-BD and GAL4 AD cloning vectors and DNA-BD and AD constructs to be used as positive and negative controls. The ones that will be mentioned in this chapter are summarized in Table 1. The vectors contain c-Myc and HA tags to facilitate detection of fusion proteins, and distinct bacterial selection markers (AD-Ampr, DNA-BDKanr) to facilitate selective rescue of plasmids from bacterial cells. The kit provides also suitable yeast strains, and in particular the AH109 yeast strain, MATa, auxotroph for Trp and Leu, and containing four genes under the control of distinct GAL4 UASs and TATA boxes: ADE2, HIS3, MEL1, and LACZ. This strain can be used as the host strain both for the screening of an AD/library and for small-scale assays. Protein–protein interaction may be deduced by the activation of any of these reporter

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genes. It can be mated with MATα strains (such as Y187) pretransformed with cDNA libraries. The Y187 yeast strain is auxotroph for Trp and Leu and contains the LACZ reporter gene under the control of GAL4. It can be used to test for an interaction between two known proteins or as a mating partner to verify protein interactions. In addition to cloning vectors, control plasmids, and yeast strains, commercial kits may contain additional components like oligos to be used as sequence primers in sequence analysis of clones; primary antibodies specific for DNA-BD, AD, or the different tags contained in the Y2H vectors, for detection of fusion proteins. A detailed user manual is generally enclosed to the kit or in alternative it can be downloaded by the website of the company. 3. Yeast strains can be stored indefinitely in YPD medium with 25% glycerol at 70
C. Transformed yeast strains are best stored in the appropriate SD dropout medium to keep selective pressure on the plasmid. A small amount of frozen cells can be scraped from the stock with a loop and streaked onto YPD plates (or SD selective plates) to recover the strain. 4. Due to the high concentration of dextrose, solubilization may be difficult at room temperature. Put about half of the volume of water in a beaker with a magnetic anchor, warm up to 45–50
C and add slowly the glucose keeping stirring until complete solubilization. Add water to 1 liter. 5. It is fundamental to carefully check the pH of media used for yeasts. The pH 5.8 is the optimal value for yeast growth. Small variations in the pH may affect the growth; in addition, very small increase in the pH strongly favor bacterial contaminations. 6. Solubilize in water by adding each component one-by-one under stirring. It may be necessary to slightly warm the water up to improve solubilization. 7. Use only high-quality carrier DNA; nicked calf thymus DNA is not recommended. 8. Yeast cells are protected by rigid cell walls, which are hard to break. Thus one of the challenges regarding the preparation of protein extracts from yeast is the efficiency of the procedure. There are different protocols available; the results (i.e., protein yield and quality) will vary depending on the protein and may be more successful with one protocol than with the other. The protocol described here (Urea/SDS method) is the one we have been used in our lab. The two most challenging aspects of isolating proteins from yeast are disrupting yeast cell walls and inhibiting the many endogenous yeast proteases. Yeast cell walls are tough and must be disrupted by a combination of physical and chemical means. Endogenous proteases must be

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counteracted with a cocktail of strong protease inhibitors. If you know your protein of interest is susceptible to a protease not inhibited by the cocktail described here, add the appropriate inhibitor before using the mixture. You may also wish to add other inhibitors such as sodium fluoride to prevent dephosphorylation, if that is appropriate for your protein. Currently ready-to-use protease inhibitors cocktails are commercially available. If you choose to use any of these, make sure they contain an appropriate number and type of inhibitors. 9. Caution: PMSF is hazardous. Wear gloves. Handle with care and read label precautions. 10. As PMSF has a short half-life (~7 min) in aqueous solutions, you may need to add additional aliquots of PMSF during the preparation of protein extracts. 11. Use classic protocols for DNA cloning [16]. You can easily generate a fusion gene if compatible restriction sites are present in the test gene and the corresponding vector. If not, generate the gene fragment by PCR with useful restriction sites incorporated into the primers. Briefly: (a) purify the gene fragment, whether generated by restriction digestion or PCR; (b) digest the DNA-BD and/or the AD vector with the appropriate restriction enzyme(s), treat with phosphatase when necessary, and purify; (c) ligate the appropriate vector and the insert; (d) transform ligation mix into E. coli; (e) identify insert-containing plasmids by restriction analysis; (f) check orientation and reading frame of the junctions by using appropriate sequencing primers. Sequence the entire insert if produced by PCR. 12. It is fundamental to stop cell culture growth when the OD600 is 0.4–0.6. During late log phase, the ADH1 promoter shuts down and the level of endogenous yeast proteases increases. 13. This initial incubation at 70
C is important because frees membrane-associated proteins. If you skip this step, membrane-associated proteins will be removed from the sample at step 6 (high-speed centrifugation). 14. It is important to use young colonies. Some yeast strains, like AH109 and Y187, carry the ade2-101 mutation and when they become old their color turns to dark pink. You should not pick these colonies. 15. Shake well the flask before measuring the OD600 because yeast cells can stick on the bottom of the flask. 16. If the cell suspension takes more than 3 h to reach an OD600¼0.4–0.6, something is wrong with the culture. It is advisable to stop the experiment and start again with a fresh culture.

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17. This washing step is important. It can be noted that after the second centrifugation, pellets have a different color and look. If the pellet is too sticky and it is difficult to resuspend, there is something wrong (possible bacterial contamination). 18. The titer of pretransformed libraries is generally around 5  107 cfu/mL, while the number of independent clones is guaranteed to be at least 1  106. Before to start the screening, it is worthy to determine the titer of the transformed cDNA library and he number of independent clones that will be analyzed in the screening. 19. A low shaking speed prevents the cells from settling on the base of the flask. Vigorous shaking can reduce the mating efficiency. 20. Example of calculation: Resuspension volume ¼ 11.5 mL. Plating volume ¼ 100 μL. 50 colonies grew on the 1/1000 dilution on SD/-Trp/Leu plates. Number of clones screened ¼ 50  11.5  10  1000 ¼ 5.75 millions. 21. Steps 13 and 14: it is not necessary to remove the whole colony, just pick a small amount of it and streak it on the new plate. Streaking a big amount of cell may produce aspecific growth generating a false positive. Draw a grid on the bottom of each plate in order to streak several colonies in the same plate. Number colonies to trace them during selection (Fig. 5). 22. Streak His+Ade+Mel+ transformants on SD/-Trp/-Leu/-His plates and let them grow at 30
C for 3–5 days. Streak yeast cotransformed with pGBKT7-53 and pGADT7-T as positive control and yeast cotransformed with pGBKT7 and pGADT7 empty vectors as negative control. In this experiment, the age of the colonies is crucial: colonies need to be big enough to be lifted but still metabolically active, thus do not let them get too old. 23. The time it takes colonies expressing β-galactosidase to turn blue typically varies from 30 min to 8 h in a library screening (see Fig. 6 for a typical positive to β-gal assay). Prolonged incubation (>10 h) may give false positives. After 12 h of incubation, all the colonies, including the negative control, turn to a greenish color. Most yeast reporter strains cotransformed with the positive controls for a two-hybrid interaction give a positive blue signal within 60 min. If the controls do not behave as expected, check the reagents and repeat the assay. 24. The plasmid DNA isolated from each positive yeast colony will be a mixture of the DNA-BD/BAIT plasmid and at least one type of the AD/library plasmid. The extraction of plasmid DNA from yeast cells is not trivial, primarily because of the

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Fig. 5 Selection of transformants. In the example showed in the figure AH109 yeast cells have been cotransformed with different combinations of DNA-BD and AD constructs. Cotransformants have been streaked both on a SD/-Trp/-Leu (a) and on a SD/-Trp/-Leu/-His (b) selective plate. A grid has been drawn on the bottom of each plate in order to streak several colonies in the same plate. The colonies have been numbered to trace them during selection. Colonies growing on plate A contain both the DNA-BD (trp1) and the AD (leu2) constructs, while colonies growing on plate B activate the HIS3 reporter gene, indicating interaction between the DNA-BD and AD fusion proteins. Clones #1, 2, and 10 express interacting partners

Fig. 6 β-Galactosidase filter assay. Blue colonies in the filter, expressing β-galactosidase activity, bear putative interacting partners and may be further analyzed

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tough cell wall. Furthermore, the relatively large size (>6 kb) and low copy number of some yeast plasmids result in very low DNA yields, regardless of the plasmid isolation method used. Besides, plasmid DNA isolated from yeast is often contaminated by genomic DNA because yeast contains ~3 as much genomic DNA as E. coli and the isolation method breaks the yeast chromosomes and releases them from cellular material. There are several yeast plasmid isolation procedures currently in use. The various protocols differ primarily in the method used to break the cell walls. The protocol described here is the one that we use in our lab and is suitable to recover AD plasmids from the positive clones isolated by Y2H screening. 25. It is recommended to use bacterial cells able to yield a transformation efficiency of at least 107 cfu/μg. The strong contamination by yeast genomic DNA in the plasmid DNA extracted from yeast cells strongly reduce the transformation efficiency.

Acknowledgments This work was supported by the Telethon Foundation (grant GGP15219) to LT and MIUR (Progetto Dipartimento di Eccellenza 2018–2022) to LT and FF. References 1. Fields S, Song O (1989) A novel genetic system to detect protein-protein interactions. Nature 340:245–246 2. Uetz P.H., Hughes R.E., Fields S. (1998). The two hybrid system: finding likely partners for lonely protein. FOCUS. 363 Vol. 20. 3. Vidal M, Legrain P (1999) Yeast forward and reverse ‘n’-hybrid systems. Nucl. Acid Res 27:919–929 4. Vidalain P, Boxem M, Ge H et al (2004) Increasing specificity in high-throughput yeast two-hybrid experiments. Methods 32:363–370 5. Fields S (2005) High-throughput two-hybrid analysis. The promise and the peril. FEBS J 272:5391–5399 6. Chevray P, Nathans D (1992) Protein interaction cloning in yeast: identification of mammalian proteins that react with the leucine zipper of Jun. Proc Natl Acad Sci U S A 89:5789–5793 7. Serebriiskii I, Estojak J, Sonoda G, Testa JR, Golemis EA (1997) Association of Krev-1/ rap1a with Krit1, a novel ankyrin repeatcontaining protein encoded by a gene mapping to 7q21-22. Oncogene 15:1043–1049

8. Zhang J, Clatterbuck RE, Rigamonti D, Chang DD, Dietz HC (2001) Interaction between krit1 and icap1alpha infers perturbation of integrin beta1-mediated angiogenesis in the pathogenesis of cerebral cavernous malformation. Hum Mol Genet 10:2953–2960 9. Zawistowski JS, Serebriiskii IG, Lee MF, Golemis EA, Marchuk DA (2002) KRIT1 association with the integrin-binding protein ICAP-1: a new direction in the elucidation of cerebral cavernous malformations (CCM1) pathogenesis. Hum Mol Genet 11:389–396 10. Zhang J, Rigamonti D, Dietz HC, Clatterbuck RE (2007) Interaction between krit1 and malcavernin: implications for the pathogenesis of cerebral cavernous malformations. Neurosurgery 60:353–359 11. Czubayko M, Knauth P, Schlu¨ter T, Florian V, Bohnensack R (2006) Sorting nexin 17, a nonself-assembling and a PtdIns(3)P high class affinity protein, interacts with the cerebral cavernous malformation related protein KRIT1. Biochem Biophys Res Commun 345:1264–1272

Molecular Interactions of CCM Proteins by GAL4 Yeast Two-Hybrid 12. Guazzi P, Goitre L, Ferro E, Cutano V, Martino C, Trabalzini L, Retta SF (2012) Identification of the Kelch family protein Nd1-L as a novel molecular interactor of KRIT1. PLoS One 7(9):e44705 13. Francalanci F, Avolio M, De Luca E, Longo D, Menchise V, Guazzi P, Sgro` F, Marino M, Goitre L, Balzac F, Trabalzini L, Retta SF (2009) Structural and functional differences between KRIT1A and KRIT1B isoforms: a framework for understanding CCM pathogenesis. Exp Cell Res. 315:285–303

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14. Stephens DJ, Banting G (2000) The use of yeast two-hybrid screens in studies of protein: protein interactions involved in trafficking. Traffic 1:763–768 15. Li B, Fields S (1993) Identification of mutations in p53 that affect its binding to SV40 T antigen by using the yeast two hybrid system. FASEB J 7:957–963 16. Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY

Chapter 26 Study of CCM Microvascular Endothelial Phenotype by an In Vitro Tubule Differentiation Model Simona Delle Monache and Saverio Francesco Retta Abstract Cerebral cavernous malformation (CCM) proteins play critical roles for endothelial cell functions, including cytoskeletal remodeling, cell–cell interactions, cell polarity, tube formation, and angiogenesis. It has been shown that the mutation of even one of the CCM genes involved in CCMs can determine an alteration in the angiogenesis process, but the precise mechanism is yet to be clarified. Here using a model of cerebral microvascular endothelial cells (hBMEC) transiently silenced by CCM1, we tried to mimic the physiological conditions that occur in the presence of CCM1 gene know-down evaluating their ability to form tube structures through an in vitro angiogenesis assay. Key words Cerebral cavernous malformations (CCMs), Angiogenesis, Endothelial cells interactions

1

Introduction It is well known that cerebral cavernous malformations (CCMs), also known as cavernous angioma, are common vascular abnormalities predominantly localized in the brain and determined by mutations in one of the CCM genes, CCM1 (Krit 1), CCM2, and/or CCM3. The three CCM protein products seem to be crucial for destabilization of newly formed vascular tubes during development [1]. By investigating the mechanism of blood vessels destabilization, it has been demonstrated that each single CCM protein product could be involved in different key steps of tube formation process. For example, CCM1 (also known as KRIT1) has been identified as a stabilizer of endothelial junctions so that its depletion increases vascular permeability and actin stress fiber formation [2]. It has also been demonstrated that CCM1 inhibits endothelial cell proliferation, apoptosis, migration, lumen formation, and sprouting angiogenesis in primary human endothelial cells [3, 4]. Moreover, as reported by Wustenube et al., the reduction or loss of CCM1 in an endothelial cell model would make it very susceptible to initiate angiogenesis [4]. In view of that, CCM1

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_26, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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could be considered a fundamental regulator during vessel formation acting like an anti-angiogenic protein. Liu et al. demonstrated definitively that the loss of CCM1 leads to marked increase in apoptosis in vascular endothelium at the end stage of microvascular angiogenesis through decreased activation of the integrin-linked kinase survival signaling pathway [5]. In addition, they conclude suggesting that an absence of CCM1 dramatically increases apoptosis in the angiogenic cord network after failed angiogenesis leading to vessel regression. For these reasons, it is interesting to investigate on the pathogenic mechanism of CCMs performing functional in vitro studies related to angiogenesis process. To this end, evaluation of tubule formation capacities using cerebral endothelial cells (hBMEC) silenced with siRNA procedure for CCM genes could represent an easy and useful method to mimic physio-pathological condition of CCM phenotype.

2 2.1

Materials Cell Culture

1. Normal human brain microvascular endothelial cells (hBMECs) (P10361) (Innoprot; http://www.innoprot.com/en). 2. hBMECs silenced for CCM1. 3. Microvascular endothelial cell growth medium-2 bullet kit (EGM™-2 MV)(CC-3202) containing endothelial cells EBM™-2 Basal Medium (CC-3156) and EGM™-2 MV SingleQuots™ supplements (CC-4147) (Lonza). 4. Dulbecco’s phosphate-buffered saline (D-PBS) without calcium and magnesium. 5. Trypsin/EDTA solution, 1
in PBS without calcium and magnesium. 6. Tissue culture flasks. 7. Haemocytometer. 8. Centrifuge tubes.

2.2 Preparation of EC Matrix and Coating of Micro-Slides

1. EC Matrix™(ECM 625) (Merk, Millipore).

2.3 Tube Formation Assay

1. 37  CO2 incubator.

2. 15 μ-Slides Angiogenesis (ct. 81,506) (IBIDI). 3. Multichannel pipettes and tips.

2. Haemocytometer. 3. Multichannel pipettes and tips. 4. Inverted light microscope.

In vitro CCM Microvascular Phenotype

2.4 Quantitation of Tubule Formation

3

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1. Inverted microscope connected to a digital camera (Nikon). 2. ImageJ analysis software.

Methods Some precautions are required to prepare hBMECs for in vitro tubule formation assay. The cells should be used at third or fourth passage during exponential growth. The critical points are as follows: (a) starvation of cells (silenced and not silenced cells). Cells should be maintained for 3–4 h in serum-free medium before to begin the tubule formation assay (as described in steps 1 and 2 of Subheading 3.2); (b) warming of complete EGM-2 medium at 37  C before detach cells (as described in step 4 of Subheading 3.2); (c) re-suspension of cells in the μ-slides previously coated at a density of 500,000 cells/mL (as described in steps 10 and 11 of Subheading 3.2).

3.1 Preparation of EC Matrix (See Note 1)

1. Place ECMatrix™ Solution and Diluent Buffer on ice or 0  C water bath and leave for 2–3 h to thaw slowly (see Notes 2, 3, and 4). 2. Add 100 μL of 10
diluent buffer to 900 μL of EC Matrix solution in a sterile microcentrifuge tube. 3. Mix very slowly with a pipette and dispense avoiding the formation of bubbles. 4. Transfer 10 μL of matrix mixture to each well of precooled μ-slides. 5. Place the μ-slide in the incubator at 37  C for 30 min to allow polymerization of matrix.

3.2 Cell Starvation and Preparation for Tubule Formation Assay

1. Replace CCM1-silenced cells (see Note 5) and those of control with fresh medium without serum but in the presence of antibiotics to allow starvation of cells (see Note 6). 2. After 3–4 h start detaching the cells with trypsin. 3. PBS and trypsin should be heated to 37  C for about 10 min. 4. Prepare and heat the complete medium. 5. For T75 add about 3 mL of trypsin. 6. Wait a minute and observe, helping the detachment mechanically.

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7. Neutralize with complete medium and thoroughly mix with a pipette the content of the flask. 8. Centrifuge at 8000
g for 10 min. 9. Discard the medium and re-suspend the cells in the complete medium, previously warmed. 10. Count the cells with the use of an hematocytometer and dilute the suspension at a concentration of 500,000 cells/mL. 11. The final volume of cell suspension to be placed in the μ-slide wells is 40 μL/well. 12. The minimum number of replicates is three. 13. The μ-slide must be placed in the incubator for 16–18 h and tube structures observed under a microscope. 14. The images captured under the microscope will be used to calculate the branch index by a plugin for angiogenesis analysis developed and available from the angiogenesis update site within ImageJ. 3.3 Quantitation of Tubule Formation

1. Open an image from ImageJ program. 2. Extract Angiogenesis analyzer from the menu bar and launch the analysis selecting “Analyze HUVEC phase contrast.” 3. The next picture shows the results: green ¼ branches; cyan ¼ twigs; magenta ¼ segments; orange ¼ master segments; blue sky ¼ meshes; red surrounded by blue ¼ nodes etc. as described in tutorial of Angiogenesis Analyzer for ImageJ by Gilles Carpentier Research website. 4. There is the possibility to select the parameters that are used to better discriminate the image. We find that the best option to use is Branching index.

4

Notes 1. The preparation of the matrix must be done about 15 min before starting to detach the cells. 2. The preparation and seeding of the matrix are done under sterile conditions. Undiluted EC Matrix is highly viscous, so it might be necessary to cut off the tip of pipette tip with a sterile knife. 3. The two solutions (buffer and matrix) must be thawed very slowly at 0  C to avoid polymerization, beginning 3 or 4 h before the experiment. Keep vials containing EC Matrix on ice all the time. 4. Also the μ-slides and the tips must be kept in the fridge for a couple of hours before starting the experiment.

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5. CCM-1-silenced cells must be used within 48 h after silencing. 6. The starvation is necessary because when the growth factors are re-added to the medium, the cells undergo a greater stimulus. References 1. Bacigaluppi S, Retta SF, Pileggi S, Fontanella M, Goitre L, Tassi L, La Camera A, Citterio A, Patrosso MC, Tredici G, Penco S (2013) Genetic and cellular basis of cerebral cavernous malformations: implications for clinical management. Clin Genet 83:7–14 2. Yadla S, Jabbour PM, Shenkar R, Shi C, Campbell PG, Awad IA (2010) Cerebral cavernous malformations as a disease of vascular permeability: from bench to bedside with caution. Neurosurg Focus 29:E4 3. Glading A, Han J, Stockton RA, Ginsberg MH (2007) KRIT-1/CCM1 is a Rap1 effector that

regulates endothelial cell cell junctions. J Cell Biol 179:247–254 4. Wustehube J, Bartol A, Liebler SS, Brutsch R, Zhu Y, Felbor U, Sure U, Augustin HG, Fischer A (2010) Cerebral cavernous malformation protein CCM1 inhibits sprouting angiogenesis by activating DELTA-NOTCH signaling. Proc Natl Acad Sci U S A 107:12640–12645 5. Liu JK, Lu Y, Raslan AM, Gultekin SH, Delashaw JB Jr (2010) Cavernous malformations of the optic pathway and hypothalamus: analysis of 65 cases in the literature. Neurosurg Focus 29: E17

Chapter 27 Bidimentional In Vitro Angiogenic Assays to Study CCM Pathogenesis: Endothelial Cell Proliferation and Migration Federica Finetti and Lorenza Trabalzini Abstract Cerebral cavernous malformation (CCM) is a cerebrovascular disorder of proven genetic origin characterized by abnormally dilated and leaky capillaries occurring mainly in the central nervous system, with a prevalence of 0.3–0.5% in the general population. Genetic studies have identified three genes associated to CCMs: KRIT1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3), which account for about 50%, 20%, and 10% of the cases, respectively. The great advances in the knowledge of the physiopathological functions of CCM genes, such as their involvement in the angiogenic process, have allowed to propose distinct putative therapeutic compounds, which showed to be effective at least in limiting some pathological phenotypes in cellular and animal models of the disease. However, despite numerous efforts, targeted pharmacological therapies that improve the outcome of CCM disease are currently lacking. Here we describe simply and low-cost assays as in vitro endothelial cell proliferation and migration assays that can be used to better understand the role of CCM genes on endothelial cell functions and to screen potential new compounds for CCM therapy. Key words Cerebral Cavernous Malformations, Angiogenesis, Endothelial cells, Proliferation, Migration, MTT assay, Scratch assay, Boyden chamber assay

1

Introduction Cerebral cavernous malformations (CCM) are major cerebrovascular lesions consisting of closely clustered, abnormally dilated, and leaky capillary channels (caverns) lined by a thin endothelium layer devoid of normal vessel structural components [1]. Genetic studies have identified three genes associated to CCMs: KRIT1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3); among the three genes, KRIT1/CCM1 is the most involved in CCM pathogenesis. Loss of KRIT1 drives the stable, quiescent endothelium toward an active pro-angiogenic state marked by loss of barrier function and adherens junction integrity both in vitro [2, 3] and in vivo [4, 5]. In addition, a close relationship between KRIT1 and CCM3 proteins and vascular endothelial growth factor (VEGF) signaling

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_27, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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has been reported [6–9]. In particular, KRIT1 loss is able to induce the switch of endothelial cells from quiescent to active state and is linked to an upregulation of VEGF/VEGFR-2 system. Recent reports describe also an altered VEGF expression in CCM patients [10–13] and KRIT1 / mice [5]. Angiogenesis, the new vessels formation from the existing one, is a complex process that plays a pivotal role in many physiological and pathological conditions. During angiogenesis, endothelial cells modify their state from quiescent to active, undergoing multiple distinct steps that can be individually evaluated and quantified by a large number of bioassays. Currently, the angiogenic assays can be summarized into three major groups: the in vitro, ex vivo, and in vivo assays, and a combination of these assays is often necessary to acquire a large amount of information regarding the entire process. The simplest bidimensional in vitro angiogenic assays are proliferation and migration of endothelial cells that recapitulate the first steps of the angiogenic cascade. For example, VEGF, as the best studied angiogenic growth factor, induces in vitro endothelial cell proliferation and migration [14]. In CCM disease, the cell proliferation assays can be used both to evaluate the consequence of the lack of CCM proteins and to screen new therapeutically active compounds [15]. Proliferation assays often provide the fastest and easiest results to interpret, but they do not measure every vital step in the angiogenesis process. Many different approach to address cell proliferation have been developed with different limitations and challenges. For endothelial cells proliferation, cell counting, colorimetric assays, and DNA synthesis measurement are the options. Each of these approaches has advantages and disadvantages; however, cell counting is considered the gold standard [16]. The simplest technique used to measure the proliferation of endothelial cells is a direct cell count. In this method, endothelial cells are harvested and grown in culture before being treated with potential pro- or anti-angiogenic agents. Although this method approximates proliferation, it only requires counting of endothelial cells by using a light microscope after a nuclear and cytoplasmatic staining, or a hemocytometer or an automated cell counter after cell trypsinization. Colorimetric assays are metabolic assays that take advantage of the natural processes of cell metabolism and represent a viability assay. The most commonly used colorimetric assay utilizes the biomolecule 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, known as MTT, which is metabolized by mitochondrial dehydrogenase in living cells. MTT is widely used in colorimetric assays because it is yellow before it is broken down into a purple formazan. The formazan dye produced by the endothelial cells is dissolved in a solvent system that is then tested for

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Table 1 Proliferation assays: advantages and disadvantages Techniques Advantages

Disadvantages

Cell counting

– Low cost

– High human error – Requires multiple counts to achieve accuracy – Time-consuming

Colorimetric

– Low cost, easy to use, minimal handling, and infrastructure – High reproducibility. – Used to determine both cell viability and cytotoxicity – Used to perform screening of high number of compounds

– Metabolic process can be affected by testing substances

DNA synthesis

– Accuracy

– High cost of immunohistochemical techniques – Time-consuming

absorbance with a spectrophotometer. As the amount of converting enzyme is highly stable in a given cell population, the generation of formazan (and hence color intensity) is proportional to the number of living cells. Both endothelial cell proliferation assays described here could be used in parallel [17, 18], although with some limitation (see Table 1). In addition to the proliferation process, during angiogenesis endothelial cells degrade the basement membrane and migrate away from their origin to form new vessels. To obtain sufficient information by in vitro analysis of new angiogenic signaling pathways modulated by CCM proteins, endothelial cell proliferation assay should be used in parallel with that of migration [16, 19]. The most applied migratory assays for endothelial cells are the wound healing assay and the Boyden Chamber assay. Wound healing is one of the best, yet simplest examples of angiogenesis, and the cell culture wound closure assay is one of the basic readouts for characterizing the migratory activity of cells. In this assay, endothelial cells are grown in culture until they have formed a confluent monolayer. Then, a “wound” is created on the monolayer with a pipet tip, and nearby endothelial cells will begin to proliferate and migrate to heal the wound. However, proliferative effects must be eliminated by adding a proliferation inhibitor (Fig. 1). Although this method is mostly qualitative, data such as how far the cells move, how fast the cells move, and the area traveled through migration can all be evaluated quantitatively [20]. This assay is relatively simple compared to other migration-

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Fig. 1 Wound healing assay. In the example, wound healing assay was performed in HUVEC silenced for KRIT1 expression and exposed to 1% serum for 18 h. Pictures represent cells at time 0 and after 18 h

Fig. 2 The Boyden chamber assay. A schematic representation of Boyden chamber assay

based assays, but presents some reproducibility problems linked to inconsistencies in endothelial cell confluency and to difficulty to perform accurate measurements. The Boyden chamber assay was introduced by Steve Boyden in 1960 [21] and at the present a large range of Boyden chamber device are commercially available. This assay is based on a chamber with two medium filled compartments separated by a microporous membrane of defined pore size (Fig. 2). In an effort to model migration through the extracellular matrix, the porous filter is often coated with collagen, fibronectin, gelatin, or matrigel that allow to reproduce the in vivo condition of endothelial cell migration. Briefly, endothelial cells are placed in the upper compartment and are allowed to migrate through the pores of the membrane into the lower compartment. The chemotactic agent of interest is present in the lower compartment. The membrane between the fluidfilled compartments is harvested, fixed, and the number of cells that have migrated to the bottom side of the membrane is determined by staining and subsequent microscopic counting [22]. As for the proliferation assays, both migration assays here proposed present some advantages or disadvantages that are summarized in Table 2.

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Table 2 Migration assays: advantages and disadvantages Techniques

Advantages

Disadvantages

Wound healing

– Simple compared to other migration assays – Evaluate migration of adherent confluent cells

– Low reproducibility and sensitivity – Inconsistencies in confluency and data – Difficult to interpret results accurately.

Boyden chamber

– Low cost – Fast – Sensitive

– Requires multiple counts to achieve accuracy – Requires experience in handling

2

Materials All media and solutions must be sterile (see Note 1). General Use Materials

1. Endothelial cells transiently or stably silenced for CCM protein of interest (KRIT1, CCM2, PCDC10) (see Note 2) or CCM KO endothelial cells isolated from patients or mice (see Note 3). 2. Sterile tubes. 3. Sterile graduated pipettes. 4. 100-mm Petri plates for cell culture. 5. Culture medium. 6. 1 Trypsin/EDTA solution. 7. Serum. 2.1 Proliferation Assay: Cell Counting

1. Sterile 96-well cell cultures plates. 2. Commercial staining kit used to rapidly fix and stain endothelial cells. 3. Microscope with 20 magnification.

2.2 Proliferation Assay: MTT Assay (See Note 4)

1. Sterile 96-well cell cultures plates.

2.3 Migration Assay: Boyden Chamber

1. Boyden chamber (48-well microchemotaxis chambers).

2. MTT, dimethyl sulfoxide (DMSO). 3. Microplate reader (absorbance at 570 nm).

2. Polycarbonate filter, 8-μm pore size. 3. Type I collagen (100 μg/mL). 4. Human plasma fibronectin (10 μg/mL).

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5. Commercial staining kit used to rapidly fix and stain endothelial cells. 6. Mounting medium in xylene for histology. 7. Microscope slides and cover glasses. 8. Optical microscope with 40 magnification. 2.4 Migration Assay: Scratch Assay

1. Sterile 24-well cell culture plates. 2. Cytosine arabinoside (AraC). 3. Commercial staining kit used to rapidly fix and stain endothelial cells. 4. Optical microscope with camera and 10 magnification.

3

Methods

3.1 Proliferation Assay: Cell Counting

1. Take the plate of confluent wt and CCM KO endothelial cells and remove the medium. 2. Wash with 2 mL of trypsin/EDTA (see Note 5). 3. Add 2 mL of trypsin/EDTA and place the plate in incubator. 4. Prepare for each of plates 15 mL tubes with 700 μL of serum. 5. Put the trypsin suspension of the cells in the tube. 6. Wash the plates two times with 3 mL of medium and add to the tube. 7. Centrifuge the cell suspension for 6 min at 800  g. 8. Resuspend the pellet with 4 mL of medium. 9. Count the cells to obtain the number of cells/mL. 10. In a 96-well plate, put 1500 cells/well in 100 μL medium (10% serum). Prepare at least three wells for each cell lines under investigation (see Note 6). 11. After 24 h, replace the medium with fresh medium containing 0.1% serum. 12. 24 h later, treat endothelial cells with 100 μL of medium 1% serum (see Note 7). 13. After 48 h, stop the experiment. Remove the medium from each well and fix the cells by adding 50 μL of fixing solution. 14. Stain the cells. 15. Count the number of cells in five fields for each well.

3.2 Proliferation Assay: MTT Assay

1. Follow steps 1–12 of Subheading 3.1. 2. After 48 h, remove the medium and replace with 100 μL of the same medium without phenol red and containing 0.05 mg/ mL of MTT.

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3. Incubate for 4 h. 4. Remove the medium and add 50 μL of DMSO. 5. Read the plate at 570 nm. 3.3 Migration Assay: Boyden Chamber

1. Follow steps 1–9 of Subheading 3.1. 2. Prepare the coating of the filter by firstly adding 1 mL of collagen, letting dry, and then adding 1 mL of fibronectin (see Note 8). 3. Wash the filter with fresh medium and air dry. 4. Prepare an endothelial cell suspension with 250,000 cells/mL. 5. Mount the Boyden chamber as follows: add 28 μL of medium (1% serum) in the bottom wells of the chamber; place the filter; close the chamber (see Note 7). 6. Put the 50 μL of cell suspension in the upper side of the chamber. 7. Incubate for 6 h (see Note 9). 8. Put the filter in the fixing solution. 9. Stain the cells on the filter. 10. Remove the cells in the upper side of the filter by using a gauze. 11. Cut the filter and mount the pieces by using the mounting medium, microscope slides, and cover glasses. 12. When the mounting is dry, count the cells in five random fields at 40 magnification.

3.4 Migration Assay: Scratch Assay

1. Follow steps 1–9 of Subheading 3.1. 2. Seed 80,000 cells for well in a 24-well plate and add 1 mL of medium (10% serum). 3. Wait up the cells will be confluent. 4. Scrape the cell monolayer in a straight line to create a “scratch” with a p200 pipet tip. 5. Wash the cells with fresh medium (two time) to remove detached endothelial cells. 6. Add 500 μL of fresh medium containing 1% serum and 5 μg/ mL of AraC to avoid cell proliferation. 7. Photograph at 10 magnification each well at time 0 and after 18 h. 8. Calculate the percent of area covered by the cells after 18 h by using an imaging software (ImageJ) (see Note 10).

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Notes 1. It is necessary to handle endothelial cells under laminar flood and to take care to work always in “clean” environment. 2. The choice of endothelial cells to perform the experiments appears to be the limiting factor. In fact, endothelial cells from different vascular beds possess organ-specific characteristics associated with the specialized functions of the tissue. CCM is a CNS disease and human endothelial cells from brain (i.e., human brain microvascular endothelial cells, HCMEC/D) appear to be the best cellular model to perform in vitro angiogenic assays. 3. Primary isolated endothelial cells must be used until 4/5 passages. 4. The MTT assay is the best choice for testing the activity of chemical or natural compounds against the hyperproliferative effects induced by CCM gene loss. 5. Media and trypsin should be heated to 37  C for about 10 min. 6. It is very important to plate endothelial cells in each well in a homogeneous way since low or high density of cells alter the experimental results. 7. This assay could be used also for screening the anti-proliferative activity of new drugs with a potential activity on CCM disease. In this case, a concentration–response curve may be made by adding the drugs in 1% serum medium. 8. A cut in an established angle of the filter may help to identify the right positioning of the treatments. 9. The incubation time will be different depending on the endothelial cells used. It was empirically determined. 10. The percentage of the area covered by the cells will be inversely proportional to the migratory rate.

Acknowledgments This work was supported by the Telethon Foundation (grant GGP15219) to LT and MIUR (Progetto Dipartimento di Eccellenza 2018–2022) to LT and FF.

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References 1. Gault J, Sarin H, Awadallah NA et al (2004) Pathobiology of human cerebrovascular malformations: basic mechanisms and clinical relevance. Neurosurgery 55(1):1–16 2. Glading A, Han J, Stockton RA et al (2007) KRIT-1/CCM1 is a Rap1 effector that regulates endothelial cell cell junctions. J Cell Biol 179(2):247–254 3. Glading AJ, Ginsberg MH (2010) Rap1 and its effector KRIT1/CCM1 regulate beta-catenin signaling. Dis Model Mech 3(1–2):73–83 4. Stockton RA, Shenkar R, Awad IA et al (2010) Cerebral cavernous malformations proteins inhibit Rho kinase to stabilize vascular integrity. J Exp Med 207(4):881–896 5. Corr M, Lerman I, Keubel JM et al (2012) Decreased Krev interaction-trapped 1 expression leads to increased vascular permeability and modifies inflammatory responses in vivo. Arterioscler Thromb Vasc Biol 32 (11):2702–2710 6. DiStefano PV, Kuebel JM, Sarelius IH et al (2014) KRIT1 protein depletion modifies endothelial cell behavior via increased vascular endothelial growth factor (VEGF) signaling. J Biol Chem 289(47):33054–33065 7. You C, Sandalcioglu IE, Dammann P et al (2013) Loss of CCM3 impairs DLL4-Notch signalling: implication in endothelial angiogenesis and in inherited cerebral cavernous malformations. J Cell Mol Med 17(3):407–418 8. Wu¨stehube J, Bartol A, Liebler SS et al (2010) Cerebral cavernous malformation protein CCM1 inhibits sprouting angiogenesis by activating DELTA-NOTCH signaling. Proc Natl Acad Sci U S A 107(28):12640–12645 9. Zhu Y, Wu Q, Xu JF et al (2010) Differential angiogenesis function of CCM2 and CCM3 in cerebral cavernous malformations. Neurosurg Focus 29(3):E1 10. Jung KH, Chu K, Jeong SW et al (2003) Cerebral cavernous malformations with dynamic and progressive course: correlation study with vascular endothelial growth factor. Arch Neurol 60(11):1613–1618 11. Abe T, Morishige M, Ooba H et al (2009) The association between high VEGF levels and multiple probable punctuate cavernous malformations. Acta Neurochir 151(7):855–859

12. Park SJ, Park SH (2016) Systemic expression of vascular endothelial growth factor in patients with cerebral cavernous malformation treated by stereotactic radiosurgery. J Korean Neurosurg Soc 59(5):442–448 13. Girard R, Zeineddine HA, Fam MD et al (2018) Plasma biomarkers of inflammation reflect seizures and hemorrhagic activity of cerebral cavernous malformations. Transl Stroke Res 9(1):34–43 14. Fallah A, Sadeghinia A, Kahroba H et al (2019) Therapeutic targeting of angiogenesis molecular pathways in angiogenesis-dependent diseases. Biomed Pharmacother 110:775–785 15. Louvi A, Chen L, Two AM et al (2011) Loss of cerebral cavernous malformation 3 (Ccm3) in neuroglia leads to CCM and vascular pathology. Proc Natl Acad Sci U S A 108 (9):3737–3742 16. Nowak-Sliwinska P, Alitalo K, Allen E et al (2018) Consensus guidelines for the use and interpretation of angiogenesis assays. Angiogenesis 21(3):425–532 17. Finetti F, Terzuoli E, Donnini S et al (2016) Monitoring endothelial and tissue responses to cobalt ferrite nanoparticles and hybrid hydrogels. PLoS One 11(12):e0168727 18. De Rosa L, Finetti F, Diana D et al (2016) Miniaturizing VEGF: peptides mimicking the discontinuous VEGF receptor-binding site modulate the angiogenic response. Sci Rep 6:31295 19. Stryker ZI, Rajabi M, Davis PJ et al (2019) Evaluation of angiogenesis assays. Biomedicines 7(2). pii: E37 20. Finetti F, Basile A, Capasso D et al (2012) Functional and pharmacological characterization of a VEGF mimetic peptide on reparative angiogenesis. Biochem Pharmacol 84 (3):303–311 21. Boyden S (1962) The chemotactic effect of mixtures of antibody and antigen on polymorphonuclear leucocytes. J Exp Med 115:453–466 22. Finetti F, Solito R, Morbidelli L et al (2008) Prostaglandin E2 regulates angiogenesis via activation of fibroblast growth factor receptor1. J Biol Chem 283(4):2139–2146

Chapter 28 Measurement of Endothelial Barrier Function in Mouse Models of Cerebral Cavernous Malformations Using Intravital Microscopy Angela J. Glading Abstract Vascular permeability is a major function of the microvasculature that is regulated by multiple factors including blood pressure, blood viscosity, and endothelial barrier function. Intravital microscopy has been used to directly assess vascular permeability in vivo, which allows for the accurate measurement of endothelial barrier function in a truly physiological hemodynamic context. Here, we describe the procedure for measuring endothelial barrier function in mouse models of cerebral cavernous malformations, including micropipette preparation, anesthesia, tracheotomy, jugular catheterization, cremaster dissection, imaging, and data analysis. These animals exhibit an increase in microvessel permeability and abnormal vessel morphology, which require special consideration. Key words Permeability, Endothelial barrier, CCM, Microvessel, Intravital microscopy, Cremaster

1

Introduction Cerebral cavernous malformations (CCMs) are identified as a class of angioma arising predominantly in the central nervous system [1]. CCMs are clinically identified by observation of a characteristic density of hemosiderin during imaging; these iron-rich deposits, caused by extravascular degradation of red blood cells, lead to a characteristic dark appearance on MRI [2]. Thus, the diagnostic definition of CCM highlights the contribution of vascular leak, or vascular permeability, to this disease. Vascular permeability is a native function of capillaries and postcapillary venules that facilitates the exchange of proteins and fluid between the blood and interstitial fluid. This exchange is tightly regulated under normal conditions, and loss of endothelial barrier function, such as during acute inflammation, is accompanied by increased permeability and the development of edema [3]. Increased vascular permeability is a hallmark of several human

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_28, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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pathologies, including chronic inflammatory disease [4], neurodegenerative disorders [5], and cancer [6]. The contribution of vascular permeability to CCM is still under investigation; however, increased vascular permeability is thought to contribute to the symptoms and severity of the disease. Indeed, the severity of individual cases of cerebral cavernous malformations correlate with the rate and extent to which lesions bleed [7]. Initially, cell culture models (Transwell™, Electrical Cell Impedance Sensing (ECIS), etc.) were utilized to show that the proteins mutated in the hereditary cases of CCM (KRIT1, CCM2, and PDCD10) are critical to the stability of the endothelial monolayer and serve to regulate the permeability of the endothelial barrier [8]. Following the development of animal models, several classic methods were used to measure in vitro permeability in CCM protein-deficient animals, including the Miles assay [9, 10]. This assay is based on the intravenous injection (i.v.) of Evans Blue, a dye that covalently binds serum albumin. Thus, the Miles assay describes the permeability of the vascular barrier to molecules of approximately 66 kDa. Other dye-based methods have also been used, including i.v. injection of sodium fluorescein, a small molecule specifically used to probe the tighter barrier of the brain [11]. More recently, we demonstrated that KRIT1-deficient mice exhibit increased microvessel permeability in vivo using intravital microscopy [12]. While loss of one KRIT1 allele doubles basal permeability, induced loss of both endothelial KRIT1 alleles increases vessel permeability >8-fold. Intravital microscopy is widely used to assess physiological vessel permeability in live animals [13]. This approach has the advantage of using an intact vascular network comprising a true hemodynamic context, is amenable to tracers of varying molecular weights, and allows for changes in permeability to be measured in functionally distinct vessels (i.e., arterial, venous, or microvascular). The main limitation of the approach is that imaging is limited to thin, relatively transparent tissues (ear, mesentery, cremaster muscle) due to the requirement for high-intensity, low-magnification imaging parameters. These limitations raise the question of how accurately measurements of permeability in peripheral tissues such as the cremaster reflect changes in permeability in the brain. Brain tissue, however, has been relatively intransigent to intravital measurement of vascular permeability. While two-photon microscopy has been adapted for intravital measurement of permeability in the brain, this modality has not yet been widely adopted, and anatomical and technical limitations remain. Notably, comparisons between changes in brain vascular barrier function vs peripheral vascular barrier function suggest that these vary in magnitude, but not direction, of response to inputs such as inflammatory stimuli or genetic intervention [14–16]. Therefore, measurement of vascular permeability in peripheral tissues is thought to correlate with changes in permeability in the brain.

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In this protocol, we describe a method for measurement of vascular permeability in the cremaster muscle of male mice, including information on micropipette preparation, anesthesia, tracheotomy, jugular catheterization, cremaster dissection, imaging, and data analysis. The cremaster is a skeletal muscle which wraps around the testes and facilitates the withdrawal of the testes into the body cavity in rodents. Its narrow thickness and easy accessibility make it an ideal tissue for intravital microscopy. Interestingly, the cremaster vasculature develops toward the end of gestation at a time when vasculogenesis has completed in most major organs, with the notable exception of the brain [17, 18]. In mouse models of CCM, the cremaster muscle is unique among skeletal muscles as it demonstrates changes in vascular morphology akin to those seen in the brain. Thus, it is an excellent model to investigate how changes in permeability affect vascular structure in KRIT1, CCM2, or PDCD10-deficient mice.

2

Materials Prepare all solutions using double-distilled H2O (ddH2O) unless otherwise specified. Reusable plastic/metal items can be washed using a dilute soap solution, followed by three warm tap water rinses (more if necessary) and three deionized water rinses. Due to the sensitivity of the vasculature to pH and osmolarity, all glassware should be washed in dilute soap solution, followed by three warm tap water rinses (more if necessary), one dilute HCl rinse (5% HCl in ddH2O), and three deionized water rinses.

2.1 Micropipette Preparation

1. Equipment: micropipette puller, micropipette beveler. 2. Capillary tubes. Clean capillary tubes by soaking them overnight in 50% nitric acid diluted in ddH2O. For arterial cannulation, we recommend thin wall tubes with filament and an external diameter of 1.5 mm (internal diameter 1.12 mm) After cleaning, rinse tubes well with ddH2O at least three times, shaking pipettes each time to release trapped fluid. Dry at 50
C. 3. Siliconizing reagent, i.e., Sigmacote®.

2.2

Anesthesia

1. Sterile saline: 0.85% NaCl in ddH2O. 2. Diluted sodium pentobarbital: 7.5 mg/mL in saline. Mix 0.15 mL of 50 mg/mL sodium pentobarbital with 0.85 mL sterile saline. Draw mixture into 1 mL syringe with 25 ga needle. Remove any air bubbles that remain in syringe (see Note 1).

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Fig. 1 Materials for tracheotomy and jugular vein catheterization. Top, jugular vein catheter; bottom, tracheotomy tube. Ruler (cm) is shown for scale 2.3

Tracheotomy

1. Surgical tools: Dissection microscope; Knapp scissors, curved; extra-fine microdissecting straight scissors; No. 7 Dumont forceps; 4-0 silk suture, Vannas curved scissors, Kimwipes, or other low lint laboratory tissues. 2. Saline: 0.85% NaCl in ddH2O. 3. Tracheal tube: Cut a 12–20 mm segment of 1.27OD polyethylene tubing (i.e., BD Intramedic PE90, ID 0.86 mm, OD 1.27 mm). Using a razor blade, bevel one end of the tube at a 45
angle (see Note 2) (Fig. 1).

2.4 Jugular Cannulation

1. Jugular Catheter: Cut a one-foot length of 0.965 mmOD polyethylene tubing (i.e., BD Intramedic PE50 tubing, ID 0.58 mm, OD 0.965 mm). Working over a Bunsen burner, heat the center of this length of tubing for ~5 s while pulling evenly on each end of the tubing. Do not pull completely apart. Using scissors, cut the two pieces apart, then bevel the narrow ends at ~45
. Attach non-beveled end of tubing to a blunt 25 ga needle. Final OD of catheter should be ~0.5 mmOD (Fig. 1). 2. Surgical tools: No. 7 Dumont forceps, 4-0 silk suture, tissue retractor (see Note 3).

2.5 Cremaster Dissection and Preparation

1. Imaging platform: A transparent Plexiglas platform (500 wide  6.2500 long  0.500 thick) is made to fit on the stage of the microscope. The platform is where the anesthetized mouse is secured during surgical preparation of the cremaster muscle and imaging, and has been molded to accommodate glass warming tubes and a vacuum line for suffusate fluid removal. 2. Silicone-quartz tissue pedestal: The pedestal is prepared by embedding a 10  0.5 mm polished quartz disc in silicone encapsulate, i.e., Sylgard184. Silicone encapsulant should be prepared according to the manufacturer’s instructions. A 15-mm thick  50-mm diameter disposable Petri dish is used as a mold to hold the encapsulant around the quartz disc (see Note 4).

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3. 20 Sodium carbonate solution: 22 mM NaHCO3 in ddH2O (see Note 5). 4. 20 Salt solution: 2.638 M NaCl, 94 mM KCl, 40 mM CaCl2∙2H2O, 23.4 mM MgSO4∙7H2O in ddH2O (see Note 5). 5. Physiological suffusate solution (PSS): 131.9 mM NaCl, 4.7 mM KCl, 2 mM CaCl2, 1.2 mM MgSO4, and 30 mM NaHCO3. Make fresh for each prep. Add 200 mL doubledistilled water to 50 mL of 20 Salt solution. Next add 50 mL of 20 sodium bicarbonate solution, then bring total volume to 1 L (see Note 5). Prior to starting cremaster preparation, warm PSS to 37
C and equilibrate with 5% CO2–95% N2 to maintain pH 7.4  0.05 and superfusate PO2 below 15 Torr. 4. Surgical tools: Knapp scissors, curved; extra-fine microdissecting straight scissors; No. 7 Dumont forceps; 4-0 silk suture, 4-0 Ethilon nylon suture, Vannas curved scissors, Kimwipes, or other low lint laboratory tissue. 6. Animal warming apparatus. 7. Pressure sensitive tape. 8. To secure the cremaster muscle on the pedestal, pins are prepared from 0.15-mm insect pins that have been cut in half and bent into an “L” shape.

3

Methods All procedures must be approved by the appropriate institutional body prior to initiating experiments.

3.1 Micropipette Preparation

1. Glass micropipettes for in vivo cannulation should be prepared at least 24 h prior to intravital imaging (see Note 6). 2. After pulling the micropipette, triple-beveled the tip; first bevel 23–24
, second and third bevels 29–30
, beveler is set at 63 rpm. 3. Following beveling, coat the pipette tips with a siliconizing reagent to reduce clogging. Using a 10-mL syringe connected to the micropipette via a small piece of rubber tubing, draw the siliconizing reagent into the pipette, then expel as much as possible using air from the syringe. Repeat 3. 4. Pipettes should be partially dried using a heating element, then allowed dry completely overnight.

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Anesthesia

1. Animals should be acclimated to the lab environment for 15–30 min prior to administering anesthesia (see Note 7). 2. Administer anesthesia at the appropriate dose by weight. Return mouse to clean cage and observe for distress. Sedation should be complete within 10 min (see Note 8).

3.3 Tracheotomy and Intubation

1. Prior to beginning surgery, check that the mouse is in the correct anesthetic plane using an appropriate test (i.e., toe pinch). 2. Place mouse ventral side up on Kimwipe-covered dissection pad. Using Knapp-curved scissors, trim hair from (1) throat and upper chest and (2) on mouse’s right side between thigh and penis, down to end of scrotum, including long hair on back of rear leg. Using a moistened swab or Kimwipe, remove any stray hairs from trimmed areas. 3. Lay mouse on dissection pad with head toward you. Adjust light sources and dissection scope as needed (we begin at 17 magnification). 4. Using straight scissors cut an approximate 1 cm midline incision through the skin over the throat area. 5. Use forceps to pull incision open, separating connective tissue along midline. Observe the natural opening in the submaxillary gland over the trachea, and continue to separate the left and right sides using the forceps to gently pull the tissue apart. 6. Once to the muscle layer, observe the natural division in the muscle (often appearing as a faint white line). Use forceps to separate muscle using that division. 7. Once the trachea is exposed, use the forceps to loosen connective tissue around and under trachea. Once connective tissue is loosened, cut 15 cm of suture silk. Push left forceps under the trachea and grab silk, pulling it under trachea. Tie silk loosely and push toward body as needed to move silk above (toward body) where you will insert trach tube (see Note 9). 8. Using Vannas scissors, cut between cartilage rings of the trachea. 9. Use forceps to hold trachea in place as you slide polyethylene trachea tube into trachea until the exposed end of tube is level with the back of the mouse’s throat. 10. Tighten suture, knot again, and trim ends (see Note 10).

3.4 Jugular Catheter for Supplemental Anesthesia

1. Using tissue retractor (see Note 3), pull skin on the right side of the throat incision (from your perspective) further to the right. 2. Use forceps or scissors to loosen connective tissue to the armpit. Gently move the glandular and fat pad structures until external jugular vein is exposed (see Note 11) (Fig. 2).

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Fig. 2 Anatomical location of jugular vein catheter. Diagram of mouse neck anatomy is shown. Black bars indicate placement of sutures described in 3.4–4 (long bar) and 3.4–6. The catheter is inserted into the vein between these sutures. Purple dotted square indicates placement of tracheotomy tube (external portion only)

3. Once connective tissue is loosened, cut two lengths (~15 cm) of suture silk. 4. Push left forceps under the jugular and grab first silk strand, pulling it under vein gently. Tie off using a square knot, as far toward the head as possible (Fig. 2). 5. Use tape to put tension on this suture, taping down next to the muzzle. 6. Thread through second silk piece, positioning above (posterior) the area of vessel you intend to cut (Fig. 2). Make a loose tie. 7. Moisten tissue with saline and increase magnification to 25. 8. Position catheter next to vein in correct orientation. Make sure the catheter and syringe are free of air bubbles. 9. Using forceps, grab venule (fat pads are handy for this) and make a nick in vein with Vannas scissors, making sure you do not cut through vessel. 10. Use one set of forceps to hold vein while using the other to slide catheter into vessel. Push catheter in until bleeding starts, then tighten upper suture and knot. 11. Using extra silk from bottom suture, tie around catheter tube using square knot. 12. Suture through lip and tie around catheter tubing to secure further. 13. Close incision with a single suture.

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Fig. 3 Representative images of cremaster preparation. (a) Orientation of mouse to imaging pedestal. Dotted line denotes midline of mouse. Double-ended arrow indicates orientation of the long axis of the platform. (1) Quartz imaging disc embedded in silicone. Note pins affixing imaging pedestal to base. (2) Reservoir for collection of PSS. PSS is dripped onto the prep from above (not shown), drawn down into the reservoir, and then aspirated by vacuum. (3) Mouse right leg and tail (just out of field of view) are taped to the platform for stability. (4) Suture silk is tied around the penis to introduce tension to the tissue preparation. This is taped to the platform to the right of the head (not shown). (b) Cremaster muscle after dissection. (1) Skin is tucked between the imaging platform and the body and secured with pins. (2) Note that two pins were used to initially secure the cremaster directly across from the attachment to the body. (3) Here, you see the larger pins used to secure the imaging pedestal to the platform. (4) Bubbles can become trapped beneath the tissue. They can be removed, if necessary, but gentle pressure on top of the tissue with a blunt instrument or moist swab. It is not necessary to remove the bubbles seen here as they are outside of the imaging area. (5) A strip (0.5 cm  0.3 cm) of Kimwipe is used to wick PSS from the top of the imaging pedestal to the reservoir 3.5

Cremaster Prep

1. Attach silicone-quartz imaging pedestal securely to imaging platform using insect pins (Fig. 3). 2. Transfer mouse to imaging platform and connect warming apparatus as needed. Mouse body temperature should be maintained at 36.5  0.5
C. 3. Position mouse with tail on right side of imaging pedestal and right leg on the left side. Tape down tail and leg so that the right flank is snug to the imaging pedestal. Mouse’s midline should be at a 50–60
angle (Fig. 3). 4. To generate tension in the tissue, first tie suture filament around penis, then tape ends of suture to the right of mouse’s head (Fig. 3). 5. Using Ethilon nylon suture filament and attached needle, pierce through skin of scrotum and pull down along midline, taping end of suture to platform (see Note 12).

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6. Using straight scissors, cut an incision through the skin from right above scrotum suture to ~5 mm to the left of the penis (see Note 13). 7. Open incision using forceps, and separate connective tissue until skin is free. 8. Remove suture in scrotum and pin skin to either side on silicone pedestal. 9. Using your finger, exert downward pressure on abdomen just above the penis to descend testicle. Using Vannas scissors, free testicle from connective tissue until it can move freely. 10. Reposition the skin by folding it, hair side down, behind pedestal and re-pinning (Fig. 3). 11. Start superfusion of tissue with warm PSS at this time. During the following dissection, a steady drip of warm PSS over the tissue should be maintained. 12. Note the cremaster muscle encapsulating the testicle. Using forceps, grasp the lower end of the cremaster and pull across the quartz disc, aligning tip with midline, and pin in place. 13. Using Vannas scissors, trim any connective tissue from cremaster exterior (see Note 14). 14. Using Vannas scissors, make an incision in the cremaster close to the terminal pin, cut gently in a straight line up over the epididymis and testicle, exposing them completely. 15. Use forceps to lift epididymis and find vascular connections, pinch these closed for 15 s, then tear apart using two pairs of forceps. Continue to cut the connective tissue under the epididymis and testicle until they freely move. 16. Using Knapp scissors as a guide, push the testicle and epididymis back into abdominal cavity. 17. Pinning alternately on the left and right, pin out the cremaster over the quartz disc, orienting the pinheads away from the muscle (Fig. 3). If necessary, press gently to remove air bubbles under muscle. 18. Transfer the completed preparation to the stage of an intravital microscope, superfuse continuously (3–5 mL/min, 34
C) and equilibrate for 30 min. Supplemental anesthesia (0.2 mL) can be administered through the catheter as needed. 3.6

Data Acquisition

1. Fill the micropipette with tracer solution (see Note 15). We use 10 mg/mL BSA in PSS in which 10% (1 mg/mL) is BSA conjugated with Alexa 488. 2. Position the micropipette in a micromanipulator connected to a pressure reservoir or other low-pressure injection system. 3. Cannulate an arteriole (diameter range 30–100 μm) that feeds a region of the microvasculature (see Note 16).

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4. Visualize the target vessel using bright-field/confocal fluorescence imaging and record video (30 fps) continuously for 10–30 s (baseline) before perfusion of the BSA-488. 5. Perfuse the intact network (both arterioles and venules) by raising the pressure in the pressure reservoir, then use a second hydraulic manipulator to position a blunted glass microoccluding rod as needed to prevent blood entering the perfused region from elsewhere in the network (see Note 17). 6. Continue to record for approximately 1 min. 7. Before stopping perfusion, acquire a bright-field image of the target vessel for measurement of the microvessel diameter. 8. Continue recording for 10–20 s after stopping perfusion and reestablishing blood flow by lifting the occluding rod. 3.7

Data Analysis

1. Identify a region of interest (ROI) for each microvessel by positioning on the video field, a rectangle that encompasses both vessel and tissue and is 3 times the vessel diameter in width and 6–8 times the vessel diameters in length. 2. Measure the total fluorescence intensity (grayscale range: 0–255; 0 ¼ black, 255 ¼ white) for the ROI in each of the sequence of acquired fields, starting with baseline images of the ROI acquired with blood perfusing the vessel before initiation of BSA-488 perfusion and continuing for at least 1 min during perfusion of the micropipette contents (see Note 18) (Fig. 4). 3. Calculate intensity of the ROI before perfusion of the fluorescent probe; this is the background measurement. 4. Use the fluorescence intensity (If) from the selected microvessel and surrounding tissue to calculate solute flux (Js) per unit surface area (S) and constant concentration gradient (ΔC) (Js/ SΔC, cm/s) from the relationship. P s ¼ J s =SΔC ¼ 1=ΔI 0 ðdI f =dt Þi ðD=4Þ: where ΔI0 is the fluorescence intensity of the test solute filling the vessel lumen, (dIf/dt)i is the initial change in fluorescence intensity as solute moves across the vessel wall, and D is the diameter of the microvessel, which is assumed to have circular cross section (Fig. 4).

4

Notes 1. Sodium pentobarbital is a controlled substance. Follow all applicable state and local record-keeping and safety policies. Other anesthetics can be substituted, which may also preclude the need for jugular catheterization. However, all anesthetics can affect cardiovascular function, therefore all experiments should be performed using the same anesthetic.

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32.5 30.0 27.5 25.0 22.5 -10 0 10 20 30 40 50 60 70 Time (sec)

Fig. 4 Representative fluorescence intensity data. (a) Representative trace of total fluorescent intensity in a single ROI over time. (b) Parameters used to calculate Ps. t ¼ 0 is start of perfusion with fluorescent tracer; I0—initial fluorescence intensity; ΔI0—intensity change at t ¼ 0; dI/dt ~Js—rate of intensity change

2. Tracheotomy tubes and jugular catheters can be cleaned and sterilized with 70% ethanol for reuse. 3. We use a “homemade” tissue retractor that is formed using the end of an Ethilon 4-0 monofilament with integrated suture needle tied to a push pin. 4. Silicone (Sylgard or similar) should be poured level with the top of the quartz disc. We recommend positioning the quartz disc to one side of the Petri dish, ~2 mm from to the edge. After pouring the silicone into the Petri dish, degassing in a vacuum chamber for an hour removes air bubbles and improves clarity. Following degassing, curing time is shortened by placing the dish in a laboratory oven at 50
C for several hours. 5. When making concentrated solutions, add each component one at a time and allow to dissolve completely between additions. If any precipitate or floating particles are/become visible, the solution should be discarded and remade. 6. Micropipette dimensions should take into consideration the dimensions of the experimental setup as well as the dimensions of the vessels to be cannulated. Micropipette tip diameter of 1.3–1.5 mm is appropriate for cannulation of small venules within the cremaster muscle of an adult mouse (25–30 g). 7. Make sure animal has access to food and water during this period. 8. In our laboratory, sodium pentobarbital is initially administered intraperitoneally; maintenance is administered via jugular catheter. We have observed that PDGFB-iCreERT2 KRIT1ECKO (KRIT1 null) mice are more sensitive to anesthetic overdose than their wildtype littermates, particularly animals over 8 weeks of age, likely due to their increased accumulation of abdominal fat. Care should be taken to avoid over administering anesthetic. After administering the initial dose, disconnect needle and attach jugular vein catheter to the syringe.

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9. Avoid cutting or crushing the cluster of blood vessels on top of the trachea. 10. Make sure the end of the trachea tube is resting just above the level of the chest, to prevent aspiration of fluid. If you make the incision in the neck too large, or the animal is particularly large, you can limit the chance of aspiration by inserting a small (0.500 ) square of Kimwipe or other absorbent material underneath the end of the tube. 11. The jugular vein here has several branches, any of which can be cannulated. Several nerves also run through this area. In particular, a nerve tract crosses the vein, and can appear to be a thick band of connective tissue. Care should be taken to avoid cutting or tearing this “strap,” and it should not be inside the sutures placed around the vessel. 12. Tissue tension is required for the initial incision of the scrotum. Be careful to only suture through the skin as the cremaster muscle can be immediately beneath this area if the testicle is descended. 13. The area near the penis contains a large number of subdermal blood vessels, which should be avoided. 14. The more connective tissue is removed, the better the imaging will be. However, when removing the gel-like connective tissue, take care not to cut or pull the muscle; injury will release inflammatory and metabolic signals which render the prep unusable. The vasculature of PDGFB-iCreERT2 KRIT1ECKO mice is extremely delicate, and extra care should be taken to avoid rupturing any vessels. Excessive blood loss into the superfusate should be considered an imaging failure. 15. A number of fluorescent tracer molecules have been used for intravital microscopy. We use 10% BSA in PSS to approximate the osmotic character of blood. Low amounts of fluorescent BSA are added to prevent artificially increasing permeability due to high tracer concentration. 16. We suggest cannulating an arteriole near the top of the cremaster (close to the body), to increase the number of microvessels available to visualize in step 4. We have observed abnormal capillaries and venules in the PDGFB-iCreERT2 KRIT1ECKO cremaster, which exhibit higher rates of imaging failure due to incomplete perfusion, thus making it necessary to repeat the cannulation in the same animal. 17. This ensures that the selected vessels downstream in the network are completely filled with perfusate from the micropipette during the measurement of Ps.

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18. During perfusion of the targeted microvascular region with BSA-488 from the micropipette, the rest of the microvasculature remains blood perfused, thus it is possible that small variations in pressure drop across regions of the intact network might occur and therefore result in blood contamination of the target vessel during the permeability measurement. To control for this, quantify the intensity in the vessel itself, and if the vessel intensity decreases with time, or oscillates during the measurement period, discard the measurement. References 1. Kim J (2016) Introduction to cerebral cavernous malformation: a brief review. BMB Rep 49 (5):255–262 2. Mokin M, Agazzi S, Dawson L, Primiani CT (2017) Neuroimaging of cavernous malformations. Curr Pain Headache Rep 21(12):47. https://doi.org/10.1007/s11916-017-0649-1 3. Lampugnani MG, Caveda L, Breviario F, Del Maschio A, Dejana E (1993) Endothelial cellto-cell junctions. Structural characteristics and functional role in the regulation of vascular permeability and leukocyte extravasation. Baillieres Clin Haematol 6(3):539–558 4. Reglero-Real N, Colom B, Bodkin JV, Nourshargh S (2016) Endothelial cell junctional adhesion molecules: role and regulation of expression in inflammation. Arterioscler Thromb Vasc Biol 36(10):2048–2057. https://doi.org/10.1161/ATVBAHA.116. 307610 5. Zlokovic BV (2011) Neurovascular pathways to neurodegeneration in Alzheimer’s disease and other disorders. Nat Rev Neurosci 12 (12):723–738. https://doi.org/10.1038/ nrn3114 6. Park-Windhol C, D’Amore PA (2016) Disorders of vascular permeability. Annu Rev Pathol 11:251–281. https://doi.org/10.1146/ annurev-pathol-012615-044506 7. Akers A, Al-Shahi Salman R, A Awad I, Dahlem K, Flemming K, Hart B, Kim H, Jusue-Torres I, Kondziolka D, Lee C, Morrison L, Rigamonti D, Rebeiz T, Tournier-Lasserve E, Waggoner D, Whitehead K (2017) Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the angioma alliance scientific advisory board clinical experts panel. Neurosurgery 80(5):665–680. https:// doi.org/10.1093/neuros/nyx091 8. Glading A, Han J, Stockton RA, Ginsberg MH (2007) KRIT-1/CCM1 is a Rap1 effector that

regulates endothelial cell cell junctions. J Cell Biol 179(2):247–254 9. Stockton RA, Shenkar R, Awad IA, Ginsberg MH (2010) Cerebral cavernous malformations proteins inhibit Rho kinase to stabilize vascular integrity. J Exp Med 207(4):881–896. https:// doi.org/10.1084/jem.20091258. jem.20091258 [pii] 10. Whitehead KJ, Chan AC, Navankasattusas S, Koh W, London NR, Ling J, Mayo AH, Drakos SG, Marchuk DA, Davis GE, Li DY (2009) The cerebral cavernous malformation signaling pathway promotes vascular integrity via Rho GTPases. Nat Med 11. Kaya M, Ahishali B (2011) Assessment of permeability in barrier type of endothelium in brain using tracers: evans blue, sodium fluorescein, and horseradish peroxidase. Methods Mol Biol 763:369–382. https://doi.org/10.1007/ 978-1-61,779-191-8_25 12. Corr M, Lerman I, Keubel JM, Ronacher L, Misra R, Lund F, Sarelius IH, Glading AJ (2012) Decreased Krev interaction-trapped 1 expression leads to increased vascular permeability and modifies inflammatory responses in vivo. Arterioscler Thromb Vasc Biol 32 (11):2702–2710. https://doi.org/10.1161/ ATVBAHA.112.300115 13. Sarelius IH, Kuebel JM, Wang J, Huxley VH (2006) Macromolecule permeability of in situ and excised rodent skeletal muscle arterioles and venules. Am J Physiol Heart Circ Physiol 290(1): H474–H480. https://doi.org/10.1152/ ajpheart.00655.2005. 00655.2005 [pii] 14. Daneman R, Prat A (2015) The blood-brain barrier. Cold Spring Harb Perspect Biol 7(1): a020412. https://doi.org/10.1101/ cshperspect.a020412 15. Daneman R, Rescigno M (2009) The gut immune barrier and the blood-brain barrier: are they so different? Immunity 31 (5):722–735. https://doi.org/10.1016/j. immuni.2009.09.012

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16. Varatharaj A, Galea I (2017) The blood-brain barrier in systemic inflammation. Brain Behav Immun 60:1–12. https://doi.org/10.1016/j. bbi.2016.03.010 17. Wang DB, Blocher NC, Spence ME, Rovainen CM, Woolsey TA (1992) Development and remodeling of cerebral blood vessels and their flow in postnatal mice observed with in vivo

videomicroscopy. J Cereb Blood Flow Metab 12(6):935–946. https://doi.org/10.1038/ jcbfm.1992.130 18. Carmeliet P, Moons L, Collen D (1998) Mouse models of angiogenesis, arterial stenosis, atherosclerosis and hemostasis. Cardiovasc Res 39(1):8–33. https://doi.org/10.1016/ s0008-6363(98)00108-4

Chapter 29 Immunofluorescence of Cell–Cell and Cell–Extracellular Matrix Adhesive Defects in In Vitro Endothelial CCM Model: Juxtacrine Role of Mutant Extracellular Matrix on Wild-Type Endothelial Cells Sandra Manet, Daphne´ Vannier, Anne-Pascale Bouin, Justyna Lisowska, Corinne Albiges-Rizo, and Eva Faurobert Abstract Endothelial cells lining cerebral cavernous malformations (CCM) present strong adhesive and mechanical defects. Increased cell contractility is a driver to the onset and the expansion of the CCM lesions. 2D in vitro endothelial models have been developed from either endothelial cells isolated from ccm1-3 knock-out mice or CCM1-3-silenced primary endothelial cells. These in vitro models faithfully recapitulate the adhesive and contractile defects of the CCM-deficient endothelial cells such as increased cell–extracellular matrix (ECM) adhesion through β1 integrin-anchored actin stress fibers, abnormal remodeling of the ECM, and destabilized VE-cadherin-dependent cell–cell junctions. Using such 2D in vitro CCM models, we have shown that the ECM remodeled by CCM-depleted endothelial cells can propagate CCM-like adhesive defects to wild-type endothelial cells, a process potentially pertinent to CCM lesion expansion. Here, we detail methods for studying the morphology of focal adhesions, actomyosin cytoskeleton, and VE-cadherindependent Adherens junctions by immunofluorescence and morphometric analyses. Moreover, we detail the protocols to produce and purify remodeled ECM and to test its effect on endothelial cell adhesion. Key words Integrins, VE-cadherin, Actomyosin cytoskeleton, CCM, Focal adhesion, Adherens junctions, Contractility, Mechanotransduction, Extracellular matrix

1

Introduction Changes in the morphology of the endothelial cells lining cerebral cavernous malformations and their underlying extracellular matrix (ECM) were reported since the very first ultrastructural analyses of human lesions [1–3]. Intercellular gaps are observed from where blood has leaked. The basal lamina can be focally multilaminar and is directly embedded in a dense collagenous matrix. No ensheathing mural cells are present. Immunohistochemistry has revealed that endothelial cells in human CCM lesions express higher levels

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_29, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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of phosphorylated myosin light chain (pMLC), a marker of actomyosin contractility, compared to normal blood vessels in the periphery [4]. These morphological defects were later observed in the zebrafish and mouse CCM animal models [5–8]. In parallel, 2D in vitro models of CCM-deficient endothelial cells have been elaborated from either endothelial cells isolated from CCM-mutant animals or CCM1-3-silenced primary endothelial cells. These in vitro models faithfully recapitulate the CCM morphological defects [4, 9–11]. CCM-deficient endothelial cells present numerous transversal actin stress fibers decorated with phosphorylated myosin. They spread and elongate on plastic much more than their wild-type counterparts and present increased cell–ECM focal adhesions and disrupted cell–cell junctions (Fig. 1) [10]. By recapitulating the in vivo morphological defects, these in vitro models are very precious for in-depth molecular analyses that are difficult to perform in in vivo models. For these reasons and because they allow large throughput experiments, they have also been successfully used for therapeutic drug screenings [12, 13]. Beyond being simple markers of the disease, we and others have started to show that the cell adhesion and contractility defects are indeed drivers of the CCM pathology. Inhibition of the cell contractility through inhibition of the phosphorylation of the myosin light chain is sufficient to block the formation of lesions and their expansion in mouse CCM model [14–16]. In normal blood vessels, the tension within the endothelium equilibrates with the forces

Fig. 1 Immunostainings of β1 integrin-dependent focal adhesions, actomyosin cytoskeleton, and VE-cadherindependent junctions in 2D in vitro CCM model. (a) β1 integrin and merged β1 integrin/F-actin stainings of CTand CCM2-silenced HUVEC spread for 1 h on FN-coated glass (0.3 μg/cm2). Scale bar: 2 μm. (b) Merged pMLC and F-actin stainings of CT- and CCM2-silenced HUVEC spread for 4 h on FN-coated glass (0.3 μg/cm2). Scale bar: 5 μm (c) Merged VE-cadherin and F-actin stainings and βcatenin staining of CT- and CCM2-silenced HUVEC cultured for 48 h on FN-coated glass (6 μg/cm2). Scale bar: 10 μm

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generated by the blood flow on its luminal side and by the stiffness of the extracellular matrix on its basal side [17, 18]. Obviously, this tensional homeostasis is lost in cerebral cavernous malformations. Ballooning of the lumen strongly slows down the blood flow lowering the associated shear stress while paradoxically endothelial cells become highly contractile and the ECM most likely stiffens [10]. Molecular analyses further suggested that CCM proteins allow the mechanical adaptation of the endothelial cells to these external forces, preserving the physical integrity of the endothelium [10, 19–21]. Endothelial cells sense external mechanical signals via adhesive structures localized at cell–cell junctions and at the interface with the ECM through VE-cadherin and integrin clusters, respectively [22]. These transmembrane receptors connect intracellularly to the contractile actomyosin cytoskeleton and coordinately organize it to equilibrate tensions between cell–cell and cell–ECM junctions [23]. CCM1-3 proteins associate to form a molecular scaffold downstream of Rap1 [24, 25], a small GTPase regulating the cross-talk between integrins and cadherins [26]. This CCM complex stabilizes cell–cell junctions by recruiting βcatenin, Rac, and the Rho kinase ROCK2 to VE-cadherin [27–29], and it limits cell– ECM adhesions by stabilizing ICAP-1, a negative regulator of β1 integrin activation, and inhibiting RhoA [9, 10, 30]. When the CCM complex is lost, Rac and ROCK2 are delocalized from VE-cadherin, while β1 integrin, RhoA, and its downstream effector the Rho kinase ROCK1 get overactivated [9, 10, 29]. This results in the polymerization of numerous β1 integrin-anchored actomyosin stress fibers that tear the cell–cell junctions apart [29]. Subsequently to their increased contractility and integrindependent adhesions, CCM-depleted endothelial cells remodel ECM very differently than control cells. By firmly pulling on extracellular globular fibronectin (FN), they provoke its polymerization in straight and parallel fibers (Fig. 3a) [10]. This organization is reminiscent of that of cancer stroma and is a distinctive feature of stiff tissues [31]. We proposed that stiffening of the ECM feeds back onto cell contractility, maintaining a positive feedback loop between cell and ECM rigidity (Fig. 2) [10]. Remarkably, we showed that this abnormally remodeled ECM is able to confer a CCM-like contractile phenotype to naı¨ve endothelial cells cultured on it as evidenced by their increased stress fibers (Fig. 3b), destabilized VE-cadherin junctions and impaired barrier function [10]. We thus proposed the existence of a mid-range propagation mechanism in which a newly mutated cell would transmit defects through the ECM to adjacent wild-type cells, which in turn would propagate the defects to their neighbors. This model was recently comforted by two publications showing that CCM lesions correspond to mosaics of mutant and wild-type endothelial cells [32, 33]. Moreover, elegant experiments showed that transplanted

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Fig. 2 β1 activation upon loss in CCM1 or 2 drives a loop between endothelial cell contractility and ECM with deleterious effect on cell–cell junctions. In a quiescent vessel, ICAP-1 maintains low β1 integrin activation. Endothelial cells are well joined, and VE-cadherin adherens junctions are stabilized by a cytoplasmic adaptor complex that recruits junctional actomyosin cytoskeleton. Upon CCM1 or CCM2 depletion, ICAP-1 protein is destabilized and lost. β1 integrin is activated and activates in turn RhoA/ROCK-dependent actin stress fiber formation. Increased β1 integrin activation and cell contractility result in aberrant remodeling of ECM in linear and parallel fibers onto which cells spread and flatten. A self-sustaining mechanical loop is initiated that increases intra- and external tensions destabilizing cell–cell junctions. (Permission from Faurobert et al., JCB 2013; doi/10.1083/jcb.20130304)

ccm / endothelial cells in ccm+/+ animals could attract endothelial cells of the host to form abnormal vessels suggesting that CCM lesions could result from the attraction of wild-type cells by mutant ones [33]. The purpose of this methodological review is twofold. We will describe technics to study the following: (1) the effect of silencing CCM proteins or any other related signaling protein on ECM remodeling, cell–ECM, and cell–cell adhesions; (2) the effect of remodeled mutant ECM on the adhesion of endothelial cells. We first describe how to prepare silenced HUVEC and decellularized remodeled mutant ECM. Then we describe how to culture cells and perform immunofluorescence stainings of ECM proteins,

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Fig. 3 Juxtacrine effect of remodeled ECM from CCM2-depleted HUVEC on naı¨ve endothelial cell adhesion. (a) Immunostainings of FN and collagen IV of decellularized ECM remodeled by CT- or CCM2-depleted HUVEC. Scale bar: 2 μm. (b) pMLC and F-actin stainings of naı¨ve HUVEC spread for 4 h on decellularized ECM remodeled by CT- or CCM2-depleted HUVEC and stained for FN. Scale bar: 5 μm

integrin-dependent focal adhesions, actin cytoskeleton, and VE-cadherin junctions. Finally, we detail how to proceed to the morphometric analyses of the images. The procedure of culturing naı¨ve endothelial cells on decellularized mutant ECM opens the way to the identification of components presented by the ECM, such as growth factors or cytokines, which contribute to the paracrine effect of CCM-mutant endothelial cells on wild-type ones.

2 2.1

Materials HUVEC Culture

1. T75 plastic cell culture-treated flask. 2. Coating solution: Collagen Type I rat tail. Prepare a collagen solution at 100 μg/mL in sterile water for cell culture pyrogenfree, mycoplasma-free, calcium-free, magnesium-free. Store at 4  C for several weeks.

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3. HUVEC (human umbilical vein endothelial cells) from Lonza supplier (500,000 cells, pooled human umbilical vein endothelial cells). 4. Endothelial cell growth medium (EGM-2 BulletKit, Lonza). 5. Endothelial cell growth basal medium (EBM-2, Lonza). 6. Freezing media: 95% bovine calf serum, 5% anhydrous dimethyl sulfoxide (DMSO). 7. Phosphate buffer saline PBS: (PBS calcium-free, magnesiumfree). 8. 100 μg/mL penicillin 9. 100 μg/mL streptomycin. 10. Trypsin-EDTA solution: 10 Trypsin and 0.5 M EDTA in sterile PBS. 2.2 Transient Transfection of siRNA

1. siRNA duplexes for CT (ON-TARGET plus Non-targeting siRNA #1, Dharmacon), CCM1 (siRNA silencer inventoried CCM1, Ambion), and CCM2 (SMARTpool: ON-TARGETplus CCM2 siRNA, Dharmacon). 2. Lipofectamine RNAiMAX Transfection Reagent—Delivery of siRNA (Invitrogen). 3. Opti-MEM I Reduced Serum Media (Invitrogen).

2.3 Production of Remodeled ECM

1. 24-well plate, tissue culture-treated. 2. Round glass coverslips (12 or 14 mm diameter). 3. Coating solution: 20 μg/mL fibronectin from human plasma in PBS. Store until one week at 4  C. 4. 0.5% (v/v) Triton X-100 in H20. 5. 50 mM ammonium hydroxide (NH4OH) in H20.

2.4 Cell Spreading and Culture on FNCoated Glass or Remodeled ECM

1. Trypsin inhibitor: 1 mg/mL in PBS.

2.5 Reagents for Immunostaining

1. 0.2 M phosphate buffer: 140 mM Na2HPO4, 60 mM NaH2PO4, pH 7.3.

2. 1% Bovine serum albumin in EGM-2. 3. EGM-2 medium containing 5% FN-depleted bovine calf serum. To deplete serum from FN, first heat at 56  C for 1 h, incubate in batch with Gelatin-Sepharose 4B beads by rotation on a wheel at 4  C (5 mL of beads for 100 mL of serum) for 4 h, centrifuge at 2500  g for 10 min, and recover the supernatant. Make aliquots and store at 20  C.

2. Fixation solution: 4% or 8% (w/v) paraformaldehyde: Weight 20 g (4%) or 40 g (8%) of paraformaldehyde in 250 mL of H2O, dissolve at 60  C (no more than 65  C), add 1 mL of

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0.1 M NaOH, and stir 30 min more. Then add 250 mL of 0.2 M phosphate buffer. Store at 4  C. 3. Permeabilization buffer: 0.3% (v/v) Triton X-100 in PBS. Store at 4  C. 4. Blocking solution: 10% goat serum (v/v) in PBS. Prepare fresh. 5. Primary antibodies: Rabbit anti-human fibronectin (SigmaAldrich, 1/200), rabbit anti-human collagen type IV (Novotec, 1/80), mouse anti-β3 integrin clone 23C6 (BD Biosciences 1/200), rat anti-activated β1 integrin clone 9EG7 (BD Biosciences, 1/200), rabbit anti-pMLC Ser19 (Cell Signaling, 1/50), mouse anti-zyxin (Synaptic system, 1/100), mouse anti-VE-cadherin clone BV9 (Millipore, 1/200), mouse anti-βcatenin clone 6F9 (Sigma-Aldrich, 1/500) antibodies. 6. Secondary antibodies: Goat anti-mouse and anti-rabbit IgG (H +L) highly cross-adsorbed secondary antibody, Alexa Fluor conjugated AF 488, AF 546, AF 647 (Invitrogen, 1/1000). 7. Phalloidin conjugates with AlexaFluor 488 (Invitrogen, 1/5000) and Atto 647 (Sigma, 1/2000). 8. Wash solution (PBT): 3% BSA and 0.05% Tween 20 in PBS. Store at 20  C. 9. Mounting medium: 24% glycerol (w/v), 10% Mowiol (w/v) in 10 mM Tris–HCl (pH 8.5) and 10 μg/mL DAPI. 2.6 Morphometric Analysis

3

Most of the analysis described in this chapter are performed with FIJI (https://imagej.net/Fiji) [34], a flavor of ImageJ, and can easily be automated by macros. Some codes described below are available upon request.

Methods

3.1 Amplification and Storage of HUVEC

1. Add 5 ml of collagen solution in 3 T75 tissue culture flasks for 30 min at 37  C. Wash with PBS. Flasks can be stored at 4  C up to a week. 2. At reception, split HUVEC from cryopreserved vial directly in the three coated T75 flasks containing 10 mL of EGM-2 (see Note 1). 3. Place the flasks in an incubator at 37  C, 3% O2, 5% CO2 (see Note 2). 4. On the next day, change media with 10 mL of fresh EGM-2 to remove traces of anhydrous dimethyl sulfoxide. Let cells grow and change media every other day. 5. At confluency, wash cells with sterile PBS and add 1 mL of trypsin-EDTA solution for few minutes at 37  C in 5% CO2 incubator. Tap the plate to detach completely the cells. When

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cells are detached, neutralize trypsin by addition of 9 mL of EGM-2. At this stage, the cells are at passage p1. Freeze aliquots in freezing media (see Note 3). 6. Seed 2.5  105 cells p1 per flask in 5 T75 flasks and grow them at 37  C, 3% O2, 5% CO2 in EGM-2. 7. At confluency, tripsinize HUVEC p1 and freeze the maximum of cells p2 as described in step 5 of Subheading 3.1. From passage 2, cultivate HUVEC in regular conditions (37  C, 5% CO2, and atmospheric % O2) and humidified chamber according to the manufacturer’s instructions (see Note 4). 3.2 Silencing of CCM Genes by RNA Interference

1. Start from confluent HUVEC at passage 2. Trypsinize to detach and neutralize with EGM-2. Count and directly seed 1.5  106 cells in collagen I-coated T75 flask in 10 mL EGM-2 without antibiotics. Incubate in 5% CO2 at 37  C (see Note 5). 2. The next morning, prepare a mix for RNAi transfection: in one conical 15-mL polypropylene tube, add 22.5 μL of lipofectamine RNAi max to 1.125 mL of Opti-MEM, and in a second 15-mL tube, prepare 2.7 μL of siRNA (100 μM stock) in 1.125 mL of Opti-MEM. Add the lipofectamine mix to the siRNA mix, gently tap the tube with your fingers. Snap centrifuge to pellet drops at the bottom of the tube. Incubate for 15 min at room temperature. During this time, replace medium over cells with 7.5 mL fresh EGM-2 without antibiotics. After the 15 min of incubation, add the siRNA/liposomes mix drop by drop onto the cells and incubate at 37  C, 5% CO2. 3. Remove media 4 h later and add 7.5 mL of complete EGM-2 without antibiotics. 4. On the next day, repeat a second round of transfection as in step 2 (see Note 6).

3.3 Production and Purification of Remodeled ECM

1. Sterilize glass coverslips by dipping into 100% ethanol and insert the coverslips into the wells of a sterile 24-well plate. Rinse with PBS. 2. Prepare a FN solution at 20 μg/mL in PBS. Add 0.5 mL of FN solution into the wells of the 24-well plate. Incubate plate for 1 h at 37  C or overnight at 4  C. Wash coated coverslips twice with sterile PBS. 3. Trypsinize silenced HUVEC with trypsin-EDTA, count cells, neutralize trypsin with 1 mg/mL trypsin inhibitor, and seed 2  105 HUVECs in 2 mL EGM-2 per well of the 24-well plate on the layer of fibronectin for 48 h at 37  C, 3% O2, 5% CO2 (see Note 7). 4. Lyse cells with 0.5% Triton X-100 for 15 min on ice.

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5. Remove nuclei by incubating with 50 mM NH4OH for 15 min on ice (see Note 8). 6. Wash three times with PBS at room temperature. 7. To check for FN remodeling, fix some coverslips with 4% PFA for 10 min at 37  C and wash twice in PBS. Store at 4  C. 8. The rest of the coverslips is kept at 4  C up to 5 days. 3.4 Study of Adhesion of Silenced HUVEC on FN or of Naive HUVEC on Remodeled ECM

1. Trypsinize silenced or naı¨ve HUVEC at passage 3 and neutralize trypsin with 1 mg/mL trypsin inhibitor. Count, pellet, and resuspend cells in serum-free EGM-2 with 1% BSA at 6  105 cells/mL. Incubate cells in suspension for 30 min at 37  C in a water bath (see Notes 9 and 10).

3.4.1 Early Spreading of Sparse HUVEC on FNCoated Glass or Remodeled ECM

2. To achieve a sparse density, plate 3  104 cells (50 μL) on either FN-coated (silenced HUVEC) or remodeled ECM (naı¨ve HUVEC) coverslips in 0.5 mL EGM-2 containing 5% FN-depleted serum (see Note 11).

Study of Focal Adhesions

3. Let cells spread in a 5% CO2, 37  C incubator for 1 h. 4. Aspirate media and directly fix cells with 4% PFA for 10 min at RT. 5. Wash twice in PBS. Store at 4  C in PBS.

Study of Actomyosin Cytoskeleton

1. Incubate silenced or naı¨ve HUVEC at passage 3 in EGM-2 containing 1% BSA for 30 min at 37  C as in step 1 of “Study of focal adhesions.” 2. Plate 3  104 cells in EGM-2 depleted in FN on either FN-coated (silenced HUVEC) or remodeled ECM (naı¨ve HUVEC) coverslips in 0.5 mL EGM-2 containing 5% FN-depleted serum. 3. Let the cells spread for 4 h. 4. Aspirate media and directly fix cells with 4% PFA 10 min at RT. 5. Wash twice in PBS. Store at 4  C in PBS.

3.4.2 Culture of Confluent HUVEC on FNCoated Glass or Remodeled ECM to Study VE-Cadherin Junctions

1. Trypsinize silenced HUVEC or naı¨ve HUVEC at passage 3 and resuspend them at 2.5  105 cells/mL in complete EGM-2. 2. Plate 2.5  105 cells on either FN-coated (20 μg/mL) (silenced HUVEC) or remodeled ECM (naı¨ve HUVEC) coverslips. 3. Remove medium when cells are adherent and replace with 2 mL of complete EGM-2. 4. Cultivate in 5% CO2 at 37  C for 48 h. 5. Remove 1 mL of media from each well and put back to the incubator to reequilibrate the temperature in the plate. 6. Add 1 mL of prewarmed 8% PFA to each well and incubate for 10 min at 37  C. Store at 4  C in PBS (see Note 12).

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3.5 Immunofluorescence Studies 3.5.1 General Protocol of Immunofluorescence

This protocol is used to stain FN, collagen IV, Zyxin, VE-cadherin, βcatenin. 1. Permeabilize cells on coverslips with permeabilization solution for 10 min at room temperature. 2. Wash once with PBS. 3. Block for 30 min at 37  C in 150 μL of blocking solution. 4. Aspirate blocking solution and add 150 μL of primary antibodies diluted in blocking solution and incubate for 1 h at 37  C. 5. Wash twice with PBT and incubate for 5 min at room temperature. 6. Remove PBT and add diluted secondary antibodies and phalloidin in blocking solution for 45 min at 37  C. 7. Wash twice with PBT and incubate for 5 min in PBT at room temperature in the dark. Remove last wash of PBT. 8. Wash in PBS to remove detergent and let it on coverslips until mounting. 9. Mount coverslips on glass slides by inverting them on a drop of mounting medium. 10. Dry glass slides in the dark overnight before visualization under the microscope. The mounting media hardens overnight (see Note 13).

3.5.2 Immunofluorescence of β Integrins

For immunostaining of β integrins, permeabilization in step 1 of Subheading 3.5.1 is omitted to reduce intracellular background. If intracellular proteins are co-stained, first incubate in blocking solution for 30 min at 37  C, then add β integrins antibodies diluted in blocking solution for 1 h at 37  C. Wash twice with PBT. After these steps, proceed to step 1 of Subheading 3.5.1 for the staining of intracellular antigens. At step 6 of Subheading 3.5.1, add all the secondary antibodies.

3.5.3 Immunofluorescence of pMLC

Permeabilize with 0.3% triton in blocking solution containing 5% goat serum for 1 h at room temperature. At step 4 of Subheading 3.5.1, incubate pMLC (ser19) primary antibody at 1/50 in PBS containing 0.3% triton overnight at 4  C into a humidified chamber (see Note 14). Wash three times with PBS for 5 min and wash once with 0.4 M NaCl in PBS. Continue immunostaining at step 6 of Subheading 3.5.1 with secondary antibodies and washes with PBT before mounting.

3.6 Morphometric Analyses of Cell Shape and Immunostainings

The quality of the images will be determinant for the analysis. It is necessary to acquire images in native or Tiff format and with as less background as possible. Confocal or SD images are usually preferable.

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Create masks and analyze area and morphology of isolated cells from images of actin, membrane protein, or cytosolic protein staining: 1. Set image type: Image > Type > 8-bits. 2. Set scale (Analyze > Set Scale). 3. Create mask (Image > Adjust > Threshold or plugin GDSC > thresholding > Edge Mask or plugin morphoLibJ > Segmentation) and save mask (File > Save As > Tiff) and ROI (File > Save As > XY Coordinates). 4. Set measurements: area, shape descriptors, perimeter, center of mass (Analyze > Set Measurements. . .). 5. Measure (Analyze > Measure).

3.6.2 Analysis of Focal Adhesions

1. Set scale (Analyze > Set Scale). 2. If necessary denoising of image (Process > Filters > Unsharp Mask, Process > Substract Background, Process > Noise > Despeckle, Plugin TopHatfilter. . .). 3. Segmentation: threshold the image (Image > Adjust > Threshold or AutoThreshold). 4. Separate adjacent FA by Watershed algorithm (Process > Binary > Watershed or Plugins > Irregular Watershed). 5. Set measurements: area, shape descriptors, perimeter, center of mass (Analyze > Set Measurements. . .). 6. Detect FA: Analyze > Analyze Particles. . . with options Display Results and Clear Results (see Notes 15 and 16).

3.6.3 Analysis of Stress Fibers

1. Set scale (Analyze > Set Scale). 2. If necessary denoising of image (Process > Filters > Unsharp Mask, Process > Substract Background, Process > Noise > Despeckle, Plugin TopHatfilter. . .). 3. Apply Laplacian filter (Plugin FeatureJ Laplacian or plugin Mexican Hat Filter). 4. Set image type: Image > Type > 8-bits. 5. Create mask (Image > Adjust > Threshold or Auto Threshold and Process > Binary > Convert to Mask). 6. Use the Plugin “Ridge Detection” to detect and measure the fibers. Anisotropy can be calculated after denoising the image using the Plugin OrientationJ or the macro FibrilTool [35].

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3.6.4 Analysis of Junction Thickness (see Note 17)

1. Set image type: Image > Type > 8-bit. 2. Denoise the image (Process > Filters > Unsharp Mask, Process > Substract Background, Process > Noise > Despeckle, Plugin TopHatfilter. . .). 3. Segmentation: threshold the image (Image > Adjust > Threshold or AutoThreshold). 4. Duplicate image (Image > Duplicate). 5. On the first image, measure the length of the junctions: (a) Use gaussian or median filter to smooth irregularities (Process > Filters > Gaussian Blur or Median). (b) Create binary image (Process > Binary > Make binary). (c) Reduce objects to 1 pixel wide (Process > Binary > Skeletonize).

representations

(d) Select the resulting skeleton (Edit > Selection > Create selection). (e) Set measurement: area (Analyze > Set Measurements. . .). (f) Measure the length of junctions (Analyze > Measure). 6. On the second image: (a) Create binary image (Process > Binary > Make binary). (b) If necessary, fill holes to reduce nonspecific spots (Process > Binary > Fill Holes). (c) Select the resulting mask of junctions (Edit > Selection > Create selection). (d) Set measurement: area (Analyze > Set Measurements. . .). (e) Measure the area of junctions (Analyze > Measure). Divide area of the second image (area of junctions) by area of the first, skeletonized image (length of junction).

4

Notes 1. Do not centrifuge cells before seeding. It leads to a high rate of cell death. 2. 3% O2 creates a physiological oxygen environment. Cells cultured in 3% O2 grow faster, live longer, and show lower stress than at atmospheric O2 (20% O2). If no 5% CO2–3% O2 incubator is available, cultivate in regular 5% CO2 incubator. 3. HUVEC can be stored at 80  C for 1 year. For longer storage, it is recommended to keep them in liquid nitrogen.

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4. Amplification and storage of primary cells are made at early passages to avoid cell dedifferentiation. All experiments are done with HUVEC of less than four passages. 5. Only use EGM-2 from Lonza for siRNA transfection of HUVEC. We have had no success with other endothelial cell media from other companies. 6. Two rounds of siRNA transfection are required to silence efficiently the CCM proteins. Silenced HUVEC can be used 24 h after the second round of transfection and up to 72 h after. 7. Do not let the cells remodel the FN for too long (maximum 48 h) to avoid the formation of FN clots on the coverslip. If no 5% CO2 3% O2 incubator is available, use a standard 5% CO2 incubator. 8. Check the removal of the nuclei under microscope. If needed, aspirate and add again NH4OH for 15 min on ice to remove completely the nuclei. 9. Incubation of the cell suspension in BSA allows the detachment of trypsinized ECM fragments from integrins resetting the level of occupied integrins to zero. 10. For FN-coated coverslips, coat coverslips with FN as in step 2 of Subheading 3.3. A range of FN concentrations from 1 (0.3 μg/cm2) to 10 μg/mL (3 μg/cm2) is recommended to better document the differences in focal adhesions and actomyosin fibers between CT- and CCM-silenced HUVEC. 11. FN is depleted from media to avoid its deposition onto the remodeled ECM or the FN-coated coverslip. 12. Cell–cell junctions are sensitive to changes in temperature during the fixation. Work quickly. Do not aspirate the media but instead dilute twice the prewarmed 8% PFA in the well. The plate can be placed on a polystyrene holder to avoid contact with the hood. 13. To mount a coverslip on a glass slide, bend a long syringe needle at 90 . Scratch the bottom of the well at the periphery on the coverglass with the needle tip until it catches and lifts the cover slip a bit. Then carefully grab the coverslip with tweezers. 14. To limit the consumption of anti-pMLC antibody, coverslips can be incubated upside down on 50 μL drops of diluted antibody on parafilm overnight in a humidified chamber. 15. In order to optimize the detection, combine different masks with different settings: for example, a first detection of small and elongated FA, a second detection of medium FA with higher circularity, and a third detection of big elongated FA. Create masks of all detections and combine them with the Image Calculator “OR” function (Process > Image Calculator).

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16. Alternatively, the website “Focal Adhesion Analysis Server” (https://faas.bme.unc.edu/), in particular for time-lapse images analysis, can be used. 17. For segmentation and analysis of confluent cells, CellBorderTracker (https://www.medizin.uni-muenster.de/anatomie2/ forschung/cellbordertracker/) [36] can be used.

Acknowledgments This work was supported by CNRS, INSERM, the French agency for scientific research (ANR), Ligue Nationale contre le Cancer, Association pour la Recherche sur le Cancer, Fondation pour la Recherche Me´dicale, and Espoir Ise`re Cancer. References 1. Wong JH, Awad IA, Kim JH (2000) Ultrastructural pathological features of cerebrovascular malformations: a preliminary report. Neurosurgery 46:1454–1459 2. Clatterbuck RE, Eberhart CG, Crain BJ, Rigamonti D (2001) Ultrastructural and immunocytochemical evidence that an incompetent blood-brain barrier is related to the pathophysiology of cavernous malformations. J Neurol Neurosurg Psychiatry 71:188–192 3. Tanriover G, Sozen B, Seker A, Kilic T, Gunel M, Demir N (2013) Ultrastructural analysis of vascular features in cerebral cavernous malformations. Clin Neurol Neurosurg 115:438–444. https://doi.org/10.1016/j. clineuro.2012.06.023 4. Stockton RA, Shenkar R, Awad IA, Ginsberg MH (2010) Cerebral cavernous malformations proteins inhibit Rho kinase to stabilize vascular integrity. J Exp Med 207:881–896 5. Hogan BM, Bussmann J, Wolburg H, SchulteMerker S (2008) ccm1 cell autonomously regulates endothelial cellular morphogenesis and vascular tubulogenesis in zebrafish. Hum Mol Genet 17:2424–2432 6. Chan AC, Drakos SG, Ruiz OE, Smith AC, Gibson CC, Ling J, Passi SF, Stratman AN, Sacharidou A, Revelo MP, Grossmann AH, Diakos NA, Davis GE, Metzstein MM, Whitehead KJ, Li DY (2011) Mutations in 2 distinct genetic pathways result in cerebral cavernous malformations in mice. J Clin Invest 121:1871–1881 7. Boulday G, Rudini N, Maddaluno L, Blecon A, Arnould M, Gaudric A, Chapon F, Adams RH, Dejana E, Tournier-Lasserve E (2011)

Developmental timing of CCM2 loss influences cerebral cavernous malformations in mice. J Exp Med 208:1835–1847 8. McDonald DA, Shenkar R, Shi C, Stockton RA, Akers AL, Kucherlapati MH, Kucherlapati R, Brainer J, Ginsberg MH, Awad IA, Marchuk DA (2011) A novel mouse model of cerebral cavernous malformations based on the two-hit mutation hypothesis recapitulates the human disease. Hum Mol Genet 20:211–222 9. Whitehead KJ, Chan AC, Navankasattusas S, Koh W, London NR, Ling J, Mayo AH, Drakos SG, Jones CA, Zhu W, Marchuk DA, Davis GE, Li DY (2009) The cerebral cavernous malformation signaling pathway promotes vascular integrity via Rho GTPases. Nat Med 15:177–184 10. Faurobert E, Rome C, Lisowska J, ManetDupe´ S, Boulday G, Malbouyres M, Balland M, Bouin AP, Ke´ramidas M, Bouvard D, Coll JL, Ruggiero F, TournierLasserve E, Albiges-Rizo C, Manet-Dupe S, Boulday G, Malbouyres M, Balland M, Bouin AP, Keramidas M, Bouvard D, Coll JL, Ruggiero F, Tournier-Lasserve E, AlbigesRizo C (2013) CCM1-ICAP-1 complex controls beta1 integrin-dependent endothelial contractility and fibronectin remodeling. J Cell Biol 202:545–561. https://doi.org/10. 1083/jcb.201303044 11. Zheng X, Xu C, Di Lorenzo A, Kleaveland B, Zou Z, Seiler C, Chen M, Cheng L, Xiao J, He J, Pack MA, Sessa WC, Kahn ML (2010) CCM3 signaling through sterile 20–like kinases plays an essential role during zebrafish cardiovascular development and cerebral

Studying Cell Adhesion in in vitro Endothelial CCM Model cavernous malformations. J Clin Invest 120:2795–2804. https://doi.org/10.1172/ JCI39679 12. Gibson CC, Zhu W, Davis CT, BowmanKirigin JA, Chan AC, Ling J, Walker AE, Goitre L, Delle Monache S, Retta SF, Shiu Y-TE, Grossmann AH, Thomas KR, Donato AJ, Lesniewski LA, Whitehead KJ, Li DY (2015) Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131:289–299. https://doi.org/10.1161/ CIRCULATIONAHA.114.010403 13. Otten C, Knox J, Boulday G, Eymery M, Haniszewski M, Neuenschwander M, Radetzki S, Vogt I, H€ahn K, De Luca C, Cardoso C, Hamad S, Igual Gil C, Roy P, Albiges-Rizo C, Faurobert E, von Kries JP, Campillos M, Tournier-Lasserve E, Derry WB, Abdelilah-Seyfried S (2018) Systematic pharmacological screens uncover novel pathways involved in cerebral cavernous malformations. EMBO Mol Med 10:e9155. https://doi. org/10.15252/emmm.201809155 14. McDonald DA, Shi C, Shenkar R, Stockton RA, Liu F, Ginsberg MH, Marchuk DA, Awad IA (2012) Fasudil decreases lesion burden in a murine model of cerebral cavernous malformation disease. Stroke 43:571–574. https://doi.org/10.1161/STROKEAHA. 111.625467 15. Shenkar R, Shi C, Austin C, Moore T, Lightle R, Cao Y, Zhang L, Wu M, Zeineddine HA, Girard R, McDonald DA, Rorrer A, Gallione C, Pytel P, Liao JK, Marchuk DA, Awad IA (2017) RhoA kinase inhibition with fasudil versus simvastatin in murine models of cerebral cavernous malformations. Stroke 48:187–194. https://doi.org/10.1161/ STROKEAHA.116.015013 16. Shenkar R, Peiper A, Pardo H, Moore T, Lightle R, Girard R, Hobson N, Polster SP, Koskim€aki J, Zhang D, Lyne SB, Cao Y, Chaudagar K, Saadat L, Gallione C, Pytel P, Liao JK, Marchuk D, Awad IA (2019) Rho kinase inhibition blunts lesion development and hemorrhage in murine models of aggressive Pdcd10/Ccm3 disease. Stroke 50:738–744. https://doi.org/10.1161/ STROKEAHA.118.024058 17. Huveneers S, Daemen MJAP, Hordijk PL (2015) Between Rho(k) and a hard place: the relation between vessel wall stiffness, endothelial contractility, and cardiovascular disease. Circ Res 116:895–908. https://doi.org/10. 1161/CIRCRESAHA.116.305720 18. Baeyens N, Bandyopadhyay C, Coon BG, Yun S, Schwartz MA (2016) Endothelial fluid

415

shear stress sensing in vascular health and disease. J Clin Invest 126:821–828. https://doi. org/10.1172/JCI83083 19. Jilkova ZM, Lisowska J, Manet S, Verdier C, Deplano V, Geindreau C, Faurobert E, Albige`s-Rizo C, Duperray AD (2014) CCM proteins control endothelial β1 integrin dependent response to shear stress. Biol Open 3. pii: bio.201410132. https://doi.org/10.1242/ bio.201410132 20. Donat S, Lourenc¸o M, Paolini A, Otten C, Renz M, Abdelilah-Seyfried S (2018) Heg1 and Ccm1/2 proteins control endocardial mechanosensitivity during zebrafish valvulogenesis. elife 7. https://doi.org/10.7554/ eLife.28939 21. Li J, Zhao Y, Coleman P, Chen J, Ting KK, Choi JP, Zheng X, Vadas MA, Gamble JR (2019) Low fluid shear stress conditions contribute to activation of cerebral cavernous malformation signalling pathways. Biochim Biophys Acta Mol basis Dis 1865:165519. https://doi.org/10.1016/j.bbadis.2019.07. 013 22. Mui KL, Chen CS, Assoian RK (2016) The mechanical regulation of integrin-cadherin crosstalk organizes cells, signaling and forces. J Cell Sci. https://doi.org/10.1242/jcs. 183699 23. Han MKL, de Rooij J (2016) Converging and unique mechanisms of mechanotransduction at adhesion sites. Trends Cell Biol. https://doi. org/10.1016/j.tcb.2016.03.005 24. Glading A, Han J, Stockton RA, Ginsberg MH (2007) KRIT-1/CCM1 is a Rap1 effector that regulates endothelial cell cell junctions. J Cell Biol 179:247–254 25. Beraud-Dufour S, Gautier R, Albiges-Rizo C, Chardin P, Faurobert E (2007) Krit 1 interactions with microtubules and membranes are regulated by Rap1 and integrin cytoplasmic domain associated protein-1. FEBS J 274:5518–5532 26. Retta S, Balzac F, Avolio M (2006) Rap1: a turnabout for the crosstalk between cadherins and integrins. Eur J Cell Biol 85:283–293. https://doi.org/10.1016/j.ejcb.2005.09.007 27. Glading AJ, Ginsberg MH (2010) Rap1 and its effector KRIT1/CCM1 regulate beta-catenin signaling. Dis Model Mech 3:73–83. https:// doi.org/10.1242/dmm.003293 28. Uhlik MT, Abell AN, Johnson NL, Sun W, Cuevas BD, Lobel-Rice KE, Horne EA, Dell’Acqua ML, Johnson GL (2003) Rac-MEKK3-MKK3 scaffolding for p38 MAPK activation during hyperosmotic shock. Nat

416

Sandra Manet et al.

Cell Biol 5:1104–1110. https://doi.org/10. 1038/ncb1071 29. Lisowska J, Ro¨del CJ, Manet S, Miroshnikova YA, Boyault C, Planus E, De Mets R, Lee H-H, Destaing O, Mertani H, Boulday G, TournierLasserve E, Balland M, Abdelilah-Seyfried S, Albiges-Rizo C, Faurobert E (2018) The CCM1–CCM2 complex controls complementary functions of ROCK1 and ROCK2 that are required for endothelial integrity. J Cell Sci 131:jcs216093. https://doi.org/10.1242/ jcs.216093 30. Borikova AL, Dibble CF, Sciaky N, Welch CM, Abell AN, Bencharit S, Johnson GL (2010) Rho kinase inhibition rescues the endothelial cell cerebral cavernous malformation phenotype. J Biol Chem 285:11760–11764 31. Goetz JG, Minguet S, Navarro-Le´rida I, Lazcano JJ, Samaniego R, Calvo E, Tello M, ˜ ez T, Pellinen T, Echarri A, Osteso-Iba´n Cerezo A, Klein-Szanto AJP, Garcia R, Keely PJ, Sa´nchez-Mateos P, Cukierman E, Del Pozo MA (2011) Biomechanical remodeling of the microenvironment by stromal Caveolin-1 favors tumor invasion and metastasis. Cell 146:148–163. https://doi.org/10.1016/j. cell.2011.05.040 32. Detter MR, Snellings DA, Marchuk DA (2018) Cerebral cavernous malformations develop through clonal expansion of mutant endothelial cells. Circ Res 123:1143–1151.

https://doi.org/10.1161/CIRCRESAHA. 118.313970 33. Malinverno M, Maderna C, Abu Taha A, Corada M, Orsenigo F, Valentino M, Pisati F, Fusco C, Graziano P, Giannotta M, Yu QC, Zeng YA, Lampugnani MG, Magnusson PU, Dejana E (2019) Endothelial cell clonal expansion in the development of cerebral cavernous malformations. Nat Commun 10:2761. https://doi.org/10.1038/s41467-01910707-x 34. Schindelin J, Arganda-carreras I, Frise E, Kaynig V, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez J, White DJ, Hartenstein V, Tomancak P, Cardona A (2019) Fiji—an Open Source platform for biological image analysis 9. https://doi.org/ 10.1038/nmeth.2019.Fiji 35. Uyttewaal M, Wrzalik R, Boudaoud A, Burian A, Borowska-wykre D, Kwiatkowska D, Hamant O (2014) FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images 9. https://doi. org/10.1038/nprot.2014.024 36. Seebach J, Abu A, Janine T, Nico L (2015) The CellBorderTracker, a novel tool to quantitatively analyze spatiotemporal endothelial junction dynamics at the subcellular level. Histochem Cell Biol 144:517–532. https:// doi.org/10.1007/s00418-015-1357-8

Chapter 30 Detection of p62/SQSTM1 Aggregates in Cellular Models of CCM Disease by Immunofluorescence Saverio Marchi, Saverio Francesco Retta, and Paolo Pinton Abstract Cerebral cavernous malformations (CCM) is a familial or sporadic rare disorder that is characterized by capillary vascular lesions with a mulberry-like appearance on MRI scans. Three distinct genes have been associated to CCM disease, known as CCM1/KRIT1, CCM2/MGC4607, and CCM3/PDCD10. Loss-offunctions mutations on these genes lead to deregulation in multiple signaling pathways, thereby resulting in disturbed vessel organization and function. Insufficient autophagy has been observed upon downregulation of all three CCM genes, both in cells and human patient tissues, revealed as aberrant accumulation of the autophagy receptor p62/SQSTM1. The autophagic process is conceived as an adaptive response to stress and is essential for the maintenance of cellular homeostasis. The aim of this review is to briefly summarize the current knowledge on the role of autophagy in CCM disease and to furnish a detailed protocol for detecting and measuring p62/SQSTM1 cytoplasmic aggregates through immunofluorescence technique. Key words Cerebral cavernous malformations, p62/SQSMT1, Autophagy, mTORC1 signaling, Protein aggregates

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Introduction Cerebral cavernous malformations (CCMs) are common vascular malformations that occur frequently in the central nervous system. CCM lesions have a prevalence of about 0.1–0.5% in the general population [1, 2]. Usually, the symptomatology includes weakness, numbness, vision changes, or severe headache. Occasionally, seizures also can occur, as well as CCMs rupture, leading to hemorrhagic stroke or death. Although CCMs mostly occur as a single formation, about 20% of affected people have a familial (inherited) form of the disease. Indeed, CCMs have been linked to loss-offunction mutations in three distinct genes, named CCM1 (KRIT1), CCM2 (MGC4607), and CCM3 (PDCD10) [3, 4]. The last 10 years of research on the molecular mechanisms underlie CCM disorder unequivocally revealed the pleiotropy of CCM genes since their inactivation leads to deregulation of

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_30, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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different cellular processes, including angiogenesis, redox homeostasis, endothelial-to-mesenchymal transition, and autophagy [5, 6]. 1.1 The Autophagic Process: The Role of p62/SQSTM1

Macroautophagy (herein referred to as autophagy) and the ubiquitin-proteasome system (UPS) are the two major quality control pathways responsible for cellular homeostasis [7, 8]. Although UPS is deputed for the degradation of the majority of proteins, large intracellular structures, including damaged organelles (i.e., mitochondria), intracellular bacteria, or protein aggregates, are exclusively degraded by the autophagic route [9, 10]. At first, the selected cargos are sequestered into double-membrane vesicles, called autophagosomes, and after autophagosomes-lysosomes fusion, their degradation is mediated by lysosomal enzymes [11]. This occurs through the activity of specific elements, which are able to recognize selected substrates and designate them to autophagic degradation [12]. The class of proteins known as autophagic receptors include the p62/SQSTM1 (sequestosome-1) [13], NBR1 (neighbor of BRCA1) [14], NDP52 (nuclear dot protein 52 kDa) [15], Tax1BP [16], and Optineurin [17]. They share the capacity to identify degradation signals on cargo substrates and also interact with ATG8s, a family of proteins located in the inner surface of the forming autophagosome. In mammals, the prevailing autophagy-targeting label is ubiquitin, a small (8.6 kDa) signaling molecule that is bound to lysine residues by a sequential cascade that involves ubiquitin-activating (E1s) and -conjugating (E2s) enzymes, as well as ubiquitin ligases (E3s) [18]. The role of p62/SQSTM1 as an autophagy receptor mainly depends on three essential features: (1) p62/SQSTM1 employs its C-terminal UBA domain to bind to poly-ubiquitinated targets, although in some cases, the interaction occurs in an ubiquitinindependent manner; (2) it interacts with ATG8s through its LC3-interacting region (LIR); (3) p62/SQSTM1 polymerizes and co-aggregates with the target substrates, facilitating the conjugation of the complex with ATG8s in the forming autophagosome. This imply that p62/SQSTM1 aggregates are degraded together with the cargos by autophagy. In multiple autophagy-deficient contexts, as well as in various neurodegenerative diseases or liver diseases, p62/SQSTM1 accumulates in cytoplasmic and nuclear ubiquitinated inclusions [19–21]. Moreover, p62/SQSTM1 levels increase upon multiple stress signals, including oxidative stress, through a molecular route that involves the transcription factor NRF2 [22], or inflammation, via the NF-κB pathway [23]. Under resting conditions, the amounts of autophagy receptors are kept low by continuous degradation. Conversely, during different stressful scenarios, p62/SQSTM1 production is rapidly boosted, reasonably to prevent the toxic accumulation of damaged/ubiquitinated structures. However, if there is no compensation by an adequate

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autophagic response, such as in some chronic disorders, aberrant p62/SQSTM1 aggregates are formed inside the cytoplasm, thus representing a distinct pathological signature that could contribute to the progression of the disease. 1.2 Role of Autophagy in CCM

Our group recently showed a defect in the normal autophagic flux in cells depleted for CCM1, CCM2, or CCM3 genes. We observed accumulation of p62/SQSTM1 clusters in CCM cells, leading to the formation of large intracellular aggregates, especially in the perinuclear area [24]. The insufficient autophagy is ascribed to higher activation of the mTORC1 (mechanistic Target of Rapamycin Complex 1) kinase, a master regulator of the autophagic process. Under nutrient-rich conditions, mTORC1 phosphorylates the ULK1/2 complex, thus inhibiting autophagy at early events by limiting the formation of autophagosomes [25]. Moreover, mTORC1 could affect autophagy by acting at the later stages of the process, through inhibition of lysosomal functions. Pharmacological inhibition of mTOR, using Rapamycin analogues, restores normal autophagic levels and mitigates other molecular derangements associated to CCMs, such as ROS (reactive oxygen species) overproduction and endothelial-to-mesenchymal transition [24]. The crucial role of mTOR-dependent autophagy inhibition in the pathogenesis of CCM is supported by other correlative observations, including vessel abnormalities in autophagy-deficient endothelial cells [26], the low autophagy levels in CCM3-depleted senescent cells [27], or overactive endothelial mTORC1 signaling in human arteriovenous malformations [28]. mTOR inhibitors are extensively used for the treatment of vascular anomalies [29], and different therapeutic approaches that have been proposed for CCM, such as Vitamin D3, statins, or sulindac sulfate, also trigger autophagy through mTOR inhibition [30]. Importantly, a recent pharmacological screening aimed to uncover novel molecules for the treatment of familial forms of CCM identified ridaforolimus as one of the few compounds able to induce some degree of rescue in multiple CCM models [31]. The non-prodrug, rapamycin analogue ridaforolimus acts as a potent mTOR inhibitor, showing a strong in vivo stability and antitumor activity [32]. Overall, there are several lines of evidence that deregulation of the mTOR signaling, with consequent suppression of the autophagic process, is one of the key events that arises from CCM genes loss-of-function, therefore contributing to CCM pathogenesis. Here, we describe an immunofluorescence-based technique aimed to visualize and quantify p62/SQSTM1 aggregates in endothelial cell models of CCM. This method could be used to valuate autophagy impairment in different pathological scenarios (not only CCM) or upon stimuli of various nature.

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Materials

2.1 Cell Culture and Transfections

1. Human umbilical vein endothelial cells (HUVEC). 2. Medium 200. 3. Low serum growth supplement (LSGS). 4. 6-well and 24-well plates. 5. Lipofectamine™ RNAiMAX Transfection Reagent (Thermo Fisher Scientific, Cat. no. 13778150). 6. siRNA CCM1 (Thermo Fisher Scientific, Cat. no. AM51331, ID 15469). 7. siRNA CCM2 (Thermo Fisher Scientific, Cat. no. AM16708, ID 147904-05-06). 8. siRNA CCM3 (Thermo Fisher Scientific, Cat. no. AM16708, ID 136322-23-24). 9. Silencer™ Negative Control No. 1 siRNA (Thermo Fisher Scientific, Cat. no. AM4611).

2.2 Immunofluorescence

1. Glass coverslips (13 mm). 2. Parafilm M. 3. 1
Phosphate buffered saline (PBS). 4. 4% Paraformaldehyde (PFA) solution. For 500 mL of 4% PFA, add 400 mL of 1
PBS to a glass beaker on a stir plate in a ventilated hood. Heat while stirring to approximately 50–55  C. Pay attention that the solution does not boil. Add 20 g of PFA powder to the heated PBS and dissolve it overnight. Do not add NaOH. Adjust the volume to 500 mL with 1
PBS. The solution can be aliquoted and frozen at 20  C. 5. Triton X-100 solution. 6. PBST or permeabilization solution: PBS + 0.05% Triton X-100. 7. Blocker Non-Fat Dry Milk. 8. PBSTM or blocking solution: PBST +5% Non-Fat Dry Milk. 9. Anti-p62/SQSTM1 antibody produced in rabbit (SigmaAldrich, Cat. no. P0067). 10. Goat anti-Rabbit IgG (H + L) Secondary Antibody, DyLight 594 (Thermo Fisher Scientific, Cat. no. 35560). 11. Microscope slides. 12. ProLong™ Diamond Antifade Mountant (Thermo Fisher Scientific, Cat. no. P36965).

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3

Equipment Setup

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p62 accumulation/aggregation could be imaged and recorded by using a confocal microscope, equipped with the appropriate filter set. Typically, correct sampling can be achieved by using 60
lens or higher with numerical aperture (N.A.) >1.3, and highresolution CCD or CMOS cameras (with pixel size 75 has been achieved (see Note 3).

3.2 Fixation, Permeabilization, and Blocking

1. Discard the medium and rinse quickly with PBS. 2. Place the 24-well plate on the top of ice and add 500 μL of cold 4% PFA solution for each well. Incubate for 10 min at 4  C (see Note 4). 3. Wash three times with PBS for 10 min each under gentle shacking at room temperature (RT). 4. During incubation with PBS, prepare the PBST solution (see Note 5). 5. Add 500 μL of PBST and incubate for 10 min at RT. 6. Prepare the PBSTM solution (see Note 6). 7. Wash two times with PBS. 8. Add 1 mL of PBSTM. Incubate for 1 h at RT.

3.3 Antibodies Incubation

1. For the primary antibody incubation, firstly prepare a wet chamber. Use a Petri dish (150 mm in diameter) and cover it completely with tinfoil. On the bottom of the Petri, apply a layer of parafilm and fix it to avoid wrinkles or irregularities.

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Fig. 1 Image of a wet chamber for immunofluorescence. The primary antibody is diluted in PBS + 0.05% Triton X-100 + 5% non-fat dry milk (PBSTM)

2. Dilute the p62/SQSTM1 primary antibody in PBSTM [dilution 1:50–1:75] (see Note 7). 3. For each sample, put 30 μL of diluted antibody on the top of the parafilm (Fig. 1), paying attention to avoid bubbles formation. 4. Carefully remove the coverslips from the 24-well plate, gently drain them on clean paper and put on the wet chamber, ensuring that the cells are in direct contact with the antibody. 5. Add a piece of wet paper inside the chamber (Fig. 1) and incubate overnight at 4  C. 6. Carefully place the coverslips in a new 24-well plate, and wash three times with PBS for 10 min each under gentle shacking at RT. 7. Dilute the Goat anti-Rabbit IgG (H + L) Secondary Antibody, DyLight 594 in PBSTM [dilution 1:500–1:1000] and protect it from light (see Note 8). 8. Add 1 mL of diluted secondary antibody per well and gently shake for 1 h at RT, protected from light. 9. Wash three times with PBS for 10 min each, under gentle shacking at RT, protected from light. 10. For each sample, put a drop of ProLong™ Diamond Antifade Mountant on a microscope slides. 11. Carefully remove the coverslips from the 24-well plate, gently drain them on clean paper and put on the microscope slide, ensuring that the cells are in direct contact with the Prolong. 12. Allow to dry for 2–3 h at RT (or overnight at 4  C), protected from light (see Note 9).

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Fig. 2 Immunofluorescence images of HUVEC, silenced with the indicated siRNAs and stained for p62/SQSTM1. Note the numerous p62/SQSTM1 aggregates in CCM1-, CCM2-, and CCM3-silenced cells. Magnification in insets. Scale bar, 10 μm. Images were acquired with confocal microscope Zeiss LSM510 3.4 Microscope Acquisition of Images and Analysis

1. Add the immersion oil on the objective. 2. Place the slide on the microscope stage. 3. For high-resolution imaging, use the standard binning mode 1
1 (each logical pixel is equal to one physical pixel). 4. Acquire multiple images in manual mode or by using motorized stage, if the microscope is equipped. Use the same camera and microscope settings among the different conditions (see Note 10) (Fig. 2). 5. Open Fiji software [33] and load the files output. 6. Remove the background, setting the rolling ball to a size of approximately 1 μm (Menu Process ! Subtract Background). 7. Threshold image to isolate p62/SQSTM1 dots from background (Menu Image ! Adjust ! Threshold). Choose the most appropriate thresholding algorithms. 8. Measure/count p62/SQSTM1 dots using the “Analyze particles” tool (Menu Analyze ! Analyze particles). Set a minimum filter size to 2, check the “Pixel units” and “Display results” options (see Note 11).

4

Notes 1. HUVEC should be used at low passages number (2–6) to increase transfection efficacy. 2. If transfection induces massive cell death, discard the medium, wash two times with PBS, and add 2 mL fresh medium per well. Alternatively, increase the number of cells (up to 600–700.000 cells per well). 3. For CCM1 silencing, transfection with a single siRNA (ID 15469) is sufficient to induce depletion of more than 90%.

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4. To obtain a good p62/SQSTM1 staining, the 4% PFA solution has to be cool. If the solution was previously frozen, put it at 4  C for 5–6 h (or the day before), allowing a slow defrost. 5. The amount of Triton X-100 can be increased up to 0.1%. 6. 5% Bovine serum albumin (BSA) can be used instead of non-fat dry milk. 7. It is important to prepare a negative control (without primary antibody) to recognize the non-specific signals that might derive from fluorescent dyes. 8. Other fluorescent-conjugated secondary antibodies (depending on the microscope filter set) can be used. We obtained good results with Goat anti-Rabbit IgG (H + L) Secondary Antibody, DyLight 488 (Cat. no. 35552). 9. To keep the coverslips in place, it could be useful to paint around the edges with nail varnish. 10. In order to obtain statistical significance, collect a number of at least 20 images per sample. Each condition should be prepared in triplicate and at least three independent experiments should be performed. 11. If the image contains multiple cells, divide the p62/SQSTM1 aggregates for the number of cells.

Acknowledgments PP is grateful to Camilla degli Scrovegni for continuous support. This work was supported by the Italian Ministry of Health (GR-2016-02364602) and local funds from Marche Polytechnic University to SM; Telethon (GGP15219/B), the Italian Association for Cancer Research (AIRC: IG-23670), Progetti di Rilevante Interesse Nazionale (PRIN, 2017 E5L5P3) and local funds from the University of Ferrara to PP; Telethon (GGP15219/A) and local funds from the University of Torino to SFR. References 1. Ene C, Kaul A, Kim L (2017) Natural history of cerebral cavernous malformations. Handb Clin Neurol 143:227–232. https://doi.org/ 10.1016/B978-0-444-63640-9.00021-7 2. Whitehead KJ, Smith MC, Li DY (2013) Arteriovenous malformations and other vascular malformation syndromes. Cold Spring Harb Perspect Med 3(2):a006635. https://doi. org/10.1101/cshperspect.a006635 3. Fischer A, Zalvide J, Faurobert E, AlbigesRizo C, Tournier-Lasserve E (2013) Cerebral

cavernous malformations: from CCM genes to endothelial cell homeostasis. Trends Mol Med 19(5):302–308. https://doi.org/10.1016/j. molmed.2013.02.004 4. Choquet H, Pawlikowska L, Lawton MT, Kim H (2015) Genetics of cerebral cavernous malformations: current status and future prospects. J Neurosurg Sci 59(3):211–220 5. Retta SF, Glading AJ (2016) Oxidative stress and inflammation in cerebral cavernous malformation disease pathogenesis: two sides of the

p62/SQSTM1 Aggregation in CCM same coin. Int J Biochem Cell Biol 81 (Pt B):254–270. https://doi.org/10.1016/j. biocel.2016.09.011 6. Lampugnani MG, Malinverno M, Dejana E, Rudini N (2017) Endothelial cell disease: emerging knowledge from cerebral cavernous malformations. Curr Opin Hematol 24 (3):256–264. https://doi.org/10.1097/ MOH.0000000000000338 7. Zientara-Rytter K, Subramani S (2019) The roles of ubiquitin-binding protein shuttles in the degradative fate of ubiquitinated proteins in the ubiquitin-proteasome system and autophagy. Cell 8(1). https://doi.org/10.3390/ cells8010040 8. Dikic I (2017) Proteasomal and autophagic degradation systems. Annu Rev Biochem 86:193–224. https://doi.org/10.1146/ annurev-biochem-061516-044908 9. Danieli A, Martens S (2018) p62-mediated phase separation at the intersection of the ubiquitin-proteasome system and autophagy. J Cell Sci 131(19). https://doi.org/10.1242/ jcs.214304 10. Janssen AFJ, Katrukha EA, van Straaten W, Verlhac P, Reggiori F, Kapitein LC (2018) Probing aggrephagy using chemically-induced protein aggregates. Nat Commun 9(1):4245. https://doi.org/10.1038/s41467-01806674-4 11. Lamb CA, Yoshimori T, Tooze SA (2013) The autophagosome: origins unknown, biogenesis complex. Nat Rev Mol Cell Biol 14 (12):759–774. https://doi.org/10.1038/ nrm3696 12. Lamark T, Svenning S, Johansen T (2017) Regulation of selective autophagy: the p62/SQSTM1 paradigm. Essays Biochem 61 (6):609–624. https://doi.org/10.1042/ EBC20170035 13. Bjorkoy G, Lamark T, Brech A, Outzen H, Perander M, Overvatn A, Stenmark H, Johansen T (2005) p62/SQSTM1 forms protein aggregates degraded by autophagy and has a protective effect on huntingtin-induced cell death. J Cell Biol 171(4):603–614. https:// doi.org/10.1083/jcb.200507002 14. Kirkin V, Lamark T, Sou YS, Bjorkoy G, Nunn JL, Bruun JA, Shvets E, McEwan DG, Clausen TH, Wild P, Bilusic I, Theurillat JP, Overvatn A, Ishii T, Elazar Z, Komatsu M, Dikic I, Johansen T (2009) A role for NBR1 in autophagosomal degradation of ubiquitinated substrates. Mol Cell 33(4):505–516. https://doi.org/10.1016/j.molcel.2009.01. 020

425

15. Thurston TL, Ryzhakov G, Bloor S, von Muhlinen N, Randow F (2009) The TBK1 adaptor and autophagy receptor NDP52 restricts the proliferation of ubiquitin-coated bacteria. Nat Immunol 10(11):1215–1221. https://doi.org/10.1038/ni.1800 16. Newman AC, Scholefield CL, Kemp AJ, Newman M, McIver EG, Kamal A, Wilkinson S (2012) TBK1 kinase addiction in lung cancer cells is mediated via autophagy of Tax1bp1/ Ndp52 and non-canonical NF-kappaB signalling. PLoS One 7(11):e50672. https://doi. org/10.1371/journal.pone.0050672 17. Wild P, Farhan H, McEwan DG, Wagner S, Rogov VV, Brady NR, Richter B, Korac J, Waidmann O, Choudhary C, Dotsch V, Bumann D, Dikic I (2011) Phosphorylation of the autophagy receptor optineurin restricts Salmonella growth. Science 333 (6039):228–233. https://doi.org/10.1126/ science.1205405 18. Kwon YT, Ciechanover A (2017) The ubiquitin code in the ubiquitin-proteasome system and autophagy. Trends Biochem Sci 42 (11):873–886. https://doi.org/10.1016/j. tibs.2017.09.002 19. Kuusisto E, Kauppinen T, Alafuzoff I (2008) Use of p62/SQSTM1 antibodies for neuropathological diagnosis. Neuropathol Appl Neurobiol 34(2):169–180. https://doi.org/ 10.1111/j.1365-2990.2007.00884.x 20. Olive M, van Leeuwen FW, Janue A, Moreno D, Torrejon-Escribano B, Ferrer I (2008) Expression of mutant ubiquitin (UBB +1) and p62 in myotilinopathies and desminopathies. Neuropathol Appl Neurobiol 34 (1):76–87. https://doi.org/10.1111/j.13652990.2007.00864.x 21. Del Grosso A, Angella L, Tonazzini I, Moscardini A, Giordano N, Caleo M, Rocchiccioli S, Cecchini M (2019) Dysregulated autophagy as a new aspect of the molecular pathogenesis of Krabbe disease. Neurobiol Dis 129:195–207. https://doi.org/10.1016/ j.nbd.2019.05.011 22. Komatsu M, Kurokawa H, Waguri S, Taguchi K, Kobayashi A, Ichimura Y, Sou YS, Ueno I, Sakamoto A, Tong KI, Kim M, Nishito Y, Iemura S, Natsume T, Ueno T, Kominami E, Motohashi H, Tanaka K, Yamamoto M (2010) The selective autophagy substrate p62 activates the stress responsive transcription factor Nrf2 through inactivation of Keap1. Nat Cell Biol 12(3):213–223. https://doi.org/10.1038/ncb2021

426

Saverio Marchi et al.

23. Ling J, Kang Y, Zhao R, Xia Q, Lee DF, Chang Z, Li J, Peng B, Fleming JB, Wang H, Liu J, Lemischka IR, Hung MC, Chiao PJ (2012) KrasG12D-induced IKK2/beta/NFkappaB activation by IL-1alpha and p62 feedforward loops is required for development of pancreatic ductal adenocarcinoma. Cancer Cell 21(1):105–120. https://doi.org/10.1016/j. ccr.2011.12.006 24. Marchi S, Corricelli M, Trapani E, Bravi L, Pittaro A, Delle Monache S, Ferroni L, Patergnani S, Missiroli S, Goitre L, Trabalzini L, Rimessi A, Giorgi C, Zavan B, Cassoni P, Dejana E, Retta SF, Pinton P (2015) Defective autophagy is a key feature of cerebral cavernous malformations. EMBO Mol Med 7(11):1403–1417. https://doi.org/10. 15252/emmm.201505316 25. Noda T (2017) Regulation of autophagy through TORC1 and mTORC1. Biomol Ther 7(3). https://doi.org/10.3390/ biom7030052 26. Maes H, Kuchnio A, Peric A, Moens S, Nys K, De Bock K, Quaegebeur A, Schoors S, Georgiadou M, Wouters J, Vinckier S, Vankelecom H, Garmyn M, Vion AC, Radtke F, Boulanger C, Gerhardt H, Dejana E, Dewerchin M, Ghesquiere B, Annaert W, Agostinis P, Carmeliet P (2014) Tumor vessel normalization by chloroquine independent of autophagy. Cancer Cell 26 (2):190–206. https://doi.org/10.1016/j.ccr. 2014.06.025 27. Guerrero A, Iglesias C, Raguz S, Floridia E, Gil J, Pombo CM, Zalvide J (2015) The cerebral cavernous malformation 3 gene is necessary for senescence induction. Aging Cell 14 (2):274–283. https://doi.org/10.1111/acel. 12316

28. Kawasaki J, Aegerter S, Fevurly RD, Mammoto A, Mammoto T, Sahin M, Mably JD, Fishman SJ, Chan J (2014) RASA1 functions in EPHB4 signaling pathway to suppress endothelial mTORC1 activity. J Clin Invest 124(6):2774–2784. https://doi.org/10. 1172/JCI67084 29. Nadal M, Giraudeau B, Tavernier E, JonvilleBera AP, Lorette G, Maruani A (2016) Efficacy and safety of mammalian target of rapamycin inhibitors in vascular anomalies: a systematic review. Acta Derm Venereol 96(4):448–452. https://doi.org/10.2340/00015555-2300 30. Marchi S, Retta SF, Pinton P (2016) Cellular processes underlying cerebral cavernous malformations: Autophagy as another point of view. Autophagy 12(2):424–425. https://doi. org/10.1080/15548627.2015.1125073 31. Otten C, Knox J, Boulday G, Eymery M, Haniszewski M, Neuenschwander M, Radetzki S, Vogt I, Hahn K, De Luca C, Cardoso C, Hamad S, Igual Gil C, Roy P, Albiges-Rizo C, Faurobert E, von Kries JP, Campillos M, Tournier-Lasserve E, Derry WB, Abdelilah-Seyfried S (2018) Systematic pharmacological screens uncover novel pathways involved in cerebral cavernous malformations. EMBO Mol Med 10(10). https://doi. org/10.15252/emmm.201809155 32. Ridaforolimus (2010) Drugs in. R&D 10 (3):165–178. https://doi.org/10.2165/ 11586010-000000000-00000 33. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A (2012) Fiji: an opensource platform for biological-image analysis. Nat Methods 9(7):676–682. https://doi.org/ 10.1038/nmeth.2019

Chapter 31 Notch Signaling in Familial Cerebral Cavernous Malformations and Immunohistochemical Detection of Cleaved Notch1 Intracellular Domain Sana S. Hasan and Andreas Fischer Abstract Cerebral cavernous malformations (CCM) or cavernomas are slow-flow capillary vascular malformations with a mulberry-like appearance, which are predominantly located in the central nervous system. CCM can occur in a sporadic or a familial form. The latter is inherited in an autosomal dominant manner, and in the majority of the fragile lesions, mutations in the genes CCM1 (KRIT1), CCM2 (OSM), or CCM3 (PDCD10) can be detected. Loss of these genes leads to numerous alterations in endothelial cell signaling resulting in a disturbed vessel architecture and function. Lower activity of Notch signaling occurs upon loss of CCM1, CCM3, or the CCM1-interacting protein ICAP1 in cell culture and animal models. Notch signaling in endothelial cells is an essential regulator of angiogenesis, arterial-venous differentiation, vascular permeability and stability, mural cell recruitment, and flux of metabolites across the vessel wall. The purpose of this chapter is to briefly summarize the current understanding of Notch signaling in familial CCM and to provide a protocol for detecting cleaved Notch1 receptor proteins on paraformaldehyde-fixed paraffin-embedded mouse tissue. Key words Cerebral cavernous malformation, Notch signaling, Angiogenesis, Endothelial cells, Pericytes

1

Introduction CCM are among the most frequent vascular malformations in the central nervous system affecting up to 0.5% of the human population. CCM are characterized by enlarged endothelial channels without intervening brain parenchyma. Loss of the CCM1– CCM3 proteins, which form several protein–protein complexes, leads to the formation of fragile vessel structures that are prone to hemorrhage [1, 2]. Re-activation of angiogenesis or endothelial-tomesenchymal transition (EndMT) appears to underlie CCM formation. Loss of a CCM protein leads to disturbance of multiple signaling pathways in endothelial cells. In particular, mitogen-activated protein kinase kinase kinase 3 (MEKK3) signaling, bone

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_31, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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morphogenic protein (BMP) signaling, TGF-β signaling, integrin signaling, KLF2 and KLF4 signaling, Rho kinase, reactive oxygen production, and several others are affected [1, 2]. 1.1 Notch Signaling: An Overview

Whitehead et al. reported the earliest association between CCM gene and Notch signaling activity already in 2004. The authors deleted the Ccm1 gene in mice and observed vascular defects including lower levels of Dll4 and Notch1 expression. As both the Notch ligand Dll4 and the receptor Notch1 are preferentially expressed on arterial vessels, the authors concluded that Ccm1 is needed for proper arterial fate differentiation [3]. Notch signaling is an evolutionary conserved pathway, which regulates numerous cell differentiation steps during development [4]. In blood vessels, Notch controls angiogenesis in a complex interplay with vascular endothelial growth factor (VEGF) signaling. Notch limits sensitivity toward VEGF, tip cell formation, vessel branching, and endothelial cell proliferation [5]. In addition, Notch is a master regulator for differentiation into arterial fate [6], and it is involved in vessel stabilization by controlling mural cell (pericytes and smooth muscle cells) recruitment and adhesion to the endothelial cells [7]. Furthermore, there is evidence that DLL4-Notch signaling plays a role in brain arteriovenous malformations [8, 9]. Recent findings by our group indicate that Notch signaling activity is also required in quiescent blood vessels to coordinate flux of fatty acids as well as to prevent re-activation of angiogenesis [10]. The Delta-Notch pathway is a remarkably simple signaling transduction system. Notch signaling is mediated via protein interactions between one of four Notch receptors (Notch1–4) and its ligands (Delta-like 1 (DLL1), DLL3-4, and Jagged1-2) leading to conformational changes and subsequent cleavage of the receptor. The short-lived Notch intracellular domain (NICD) translocates to the nucleus, where it interacts with the DNA-binding protein Rbp-jk and several transcriptional co-activators in order to induce gene expression. Since there are no signal amplification steps in the pathway, Notch signaling is mainly regulated by differential expression and modification, e.g., glycosylation or ubiquitination of Notch ligands and receptors to alter their binding affinity. In addition, the Notch nuclear complexes are further modified by chromatin remodeling proteins [4]. In summary, this makes the outcome of Notch signaling highly context and tissue-specific. As a general principle for analyzing Notch signaling activity, one can either detect cleaved Notch receptors by Western blotting or immunohistochemistry as outlined below (Fig. 1), or determine mRNA or protein levels of Hes and Hey basic–helix–loop–helix transcription factors [11] as some of the Hes (Hes1–Hes7) and Hey (Hey1, Hey2, HeyL) genes are directly induced by NICD. Since the Hes and Hey proteins act as transcriptional repressors [12], Notch

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Fig. 1 Immunohistochemical staining for active Notch1 signaling in endothelial cells. Serial sections of mouse brown adipose tissue (BAT) stained for (a) CD31, marker for endothelial cells and (b) cleaved Notch1 intracellular domain (N1ICD). Note the nuclear staining of cleaved N1ICD (black arrowheads) compared to cytoplasmic staining of CD31. Staining was performed on 2.5-μm-thick brown adipose tissue sections from a 10-week-old male C57BL/6J mouse. Images were acquired with Zeiss Axio Scan.Z1 (Motorized Widefield Slide Scanner). Scale bar 50 μm

is also able to repress the expression of certain genes as it has been shown for certain VEGF receptors during angiogenesis [5]. However, the induction of Hes and Hey gene expression needs to be interpreted cautiously as some other signaling pathways, in particular, BMP9-ALK1-SMAD signaling can also lead to induction of Hes and Hey gene transcription [13, 14]. 1.2 Notch Signaling Acts Downstream of CCM1 and CCM3

There are several reports indicating that loss of CCM1, CCM3, or the CCM1 interacting protein integrin cytoplasmic domainassociated protein-1 (ICAP1) leads to lower Notch signaling activity in endothelial cells [15]. After the first report by Whitehead et al. [3], our group showed that CCM1 acts as an anti-angiogenic protein which is keeping the endothelium in a quiescent state. CCM1 expression in primary human umbilical vein endothelial cells inhibited endothelial proliferation, apoptosis, migration, and sprouting angiogenesis. This was, at least in part, executed by increased DLL4-mediated Notch1 signaling. Consistently, silencing of CCM1 led to increased angiogenesis, also upon xenotransplantation of such endothelial cells into mice. In this setting, the multikinase inhibitor Sorafenib could ameliorate loss of CCM1induced excessive microvascular growth and reduced the microvessel density to levels of normal wild-type endothelial cells [16]. We had also obtained similar findings by manipulating the expression of the CCM1-interacting protein ICAP1. This protein inhibited Rho kinase activity as well as ERK (extracellular signal-regulated kinase) phosphorylation and induced the expression of the cell cycle inhibitors p21 and p27. Furthermore, this work revealed that blockage of Notch receptor cleavage using a γ-secretase inhibitor rescued endothelial cells from ICAP1-induced defects and led to normal sprouting, suggesting that Notch might act downstream of ICAP1 to suppress angiogenesis [17].

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Importantly, it has been shown that the endothelial-specific loss of CCM genes in mice during the neonatal period causes EndMT. In this context, Elisabetta Dejana’s group demonstrated not only critical signaling components (BMP6 and TGF-β) mediating EndMT in CCM but also showed diminished Notch signaling activity (less Hey1 and Hey2) in endothelial cells of the vascular malformations. These authors concluded that (1) loss of CCM1 mediates Notch inhibition; (2) notch inhibition upregulates BMP6 expression in the brain endothelium; and (3) autocrine BMP6 activity strongly contributes to the observed EndMT [18]. As such, this study provides a strong functional link how Notch signaling is needed downstream of CCM1 to prevent EndMT. In summary, the above-mentioned publications present a scenario in which Notch signaling acts downstream of CCM1 to prevent EndMT and re-activation of the angiogenesis program. CCM lesions are accompanied by decreased number of pericytes, which are needed to stabilize capillaries and prevent angiogenic sprouting [7]. Our group showed that DLL4 expression on endothelial cells is diminished upon loss of CCM1. Furthermore, silencing of CCM1 expression in endothelial cells led to lower Notch3 expression in co-cultured pericytes, and activation of Notch3 receptors in these pericytes promoted adhesion to endothelial cells, which reduced angiogenic potential [19]. Since Jagged1 levels were not altered in CCM1-silenced endothelial cells, we could propose that endothelial DLL4 may signal through Notch3 receptors present on pericytes to maintain vessel integrity. The role of CCM3 to inhibit angiogenesis had been documented [20, 21], but the role of CCM3 in regulating DLL4-Notch signaling was first reported by the Sure group in 2012 [22]. The authors showed that silencing CCM3 gene in cultured endothelial cells increased endothelial cell proliferation, migration, and sprouting angiogenesis. Lower expression levels of the Notch signaling components DLL4, Notch4, HEY2, and HES1 accompanied this. Consistently, treatment with recombinant DLL4 protein restored expression levels of Notch components, which prevented excessive angiogenesis of CCM3-silenced endothelial cells [22]. In summary, several lines of evidence suggest that Notch signaling acts downstream of the CCM protein complex to inhibit EndMT and angiogenesis and therefore contributes to CCM pathogenesis. A detailed methodology for detecting cleaved Notch1 intracellular domain (N1ICD) in paraformaldehyde-fixed paraffinembedded mouse tissue is described below.

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Materials

2.1 Fixation, Embedding, and Sectioning

1. Histology cassettes. 2. Acid-free phosphate-buffered paraformaldehyde (PFA) solution 4%. 3. Tissue Processing Centre (MEDITE). 4. Paraffin Embedding Station (MEDITE). 5. Microtome. 6. Thermoscientific™ Superfrost Plus™ Adhesion slides.

2.2 Deparaffinization and Antigen Retrieval

1. Xylene. 2. Ethanol (100%, 96%, 90% and 70%). 3. Steamer. 4. HIER citrate buffer pH 6 (Zytomed # ZUC028).

2.3 Immunohistochemistry and Mounting

1. Hydrophobic pen. 2. Casein blocking buffer: 25% Casein, 15 mM sodium azide and 0.1% BSA in 50 mM Tris–HCl, pH 7.6. 3. Tris-buffered saline (TBS; 10): 1.5 M NaCl, 0.1 M Tris–HCl, pH 7.6. 4. 1 TBS containing 0.025% Triton X-100 (TBST). 5. Primary antibody: Cleaved Notch1 Antibody (abcam # ab8925). 6. 0.3% Hydrogen peroxide (H202) in TBST. 7. Secondary antibody: Goat anti-rabbit HRP. 8. DAB Substrate. 9. Signal Stain Antibody Diluent (Cell Signaling # 8112). 10. Hematoxylin solution. 11. Mounting medium.

3

Methods

3.1 Fixation, Embedding, and Sectioning

Carry out all procedures at room temperature (RT) unless otherwise specified. 1. Dissect tissue, place it in a histology cassette and fix it in 4% PFA at 4  C for 24 h (see Notes 1 and 2). 2. Rinse cassette in running tap water for 1 h to remove residual PFA.

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3. Dehydrate and clear tissue by placing cassette in an automated Tissue Processing Centre that would perform serial dehydration with (70%, 90%, 95%, and 100%) ethanol, followed by tissue clearing in xylene and paraffin infiltration in tissues. 4. Remove tissue from cassette and embed it in molten Paraffin at a Paraffin Embedding station. Allow the paraffin blocks to cool down and solidify. 5. Use a microtome to cut 2.5 μm thin tissue sections and collect them on an adhesion slide in a water bath. Allow the slides to dry overnight at 37  C (see Notes 3, 4, and 5). 3.2 Deparaffinization and Antigen Retrieval

1. Incubate slides in three washes of xylene for 10 min each. 2. Incubate slides in two washes of 100% ethanol for 5 min each. 3. Transfer slides to 96%, 90%, and 70% ethanol for 2 min each. 4. Rinse slides with deionized water (dH2O) for 2 min. 5. Preheat steamer for 10 min. 6. Fill a plastic slide chamber with HIER citrate buffer and place it in the steamer for 20 min to preheat (see Note 6). 7. Place slides in the preheated citrate buffer and incubate in the steamer for 45 min (see Note 7). 8. Remove the slide chamber from the steamer and let it cool down at RT for 20 min (see Note 8).

3.3 Immunohistochemistry

1. Wash slides with dH20 for 5 min. 2. Place the slides in a humidified chamber (see Note 9). 3. Use a hydrophobic pen to draw a boundary on the slide around the section (see Notes 10 and 11). 4. Equilibrate sections with TBS followed by permeabilization with TBST for 2–5 min. 5. Remove TBST and block each section with 50–100 μL casein blocking buffer for 1 h at RT. 6. Rinse sections quickly with TBST. 7. Dilute primary antibody 1:100 in casein blocking buffer. 8. Add 50–100 μL primary antibody to each section and incubate overnight at 4  C. 9. Wash sections three times with TBST for 5 min each. 10. Quench endogenous peroxidase activity by adding 50–100 μL 0.3% H2O2/TBST to each section for 10 min. 11. Wash sections three times with TBST for 5 min each. 12. Dilute secondary antibody 1:200 in signal stain antibody diluent.

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13. Add 50–100 μL secondary antibody to each section and incubate for 1 h at RT. 14. Wash sections three times with TBST for 5 min each. 15. Add 50–100 μL DAB substrate to each section for 5 min followed by a quick rinse with TBST. 16. Add the DAB substrate again and incubate for 15 min (see Note 12). 17. Wash sections with TBST for 2 min. 18. Wash sections three times with dH20 for 2 min each. 3.4 Counterstaining, Dehydration, and Mounting

1. Counterstain with hematoxylin for 3 s to visualize nuclei. 2. Rinse sections under running tap water for 5 min. 3. Dehydrate sections by transferring slides to 70%, 90%, 96% ethanol for 2 min each. 4. Incubate slides in three washes of 100% ethanol for 5 min each. 5. Incubate slides in three washes of xylene for 10 min each. 6. Mount sections with coverslips using mounting medium. 7. Allow the mounting medium to set and visualize the slides under a microscope.

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Notes 1. Use adequate fixative volume depending upon tissue size. Around 10–20 volumes of PFA/weight of tissue is sufficient. 2. Certain tissues might require cardiac perfusion of PFA. Adapt protocol accordingly. 3. Paraffin blocks can be stored at RT for extended periods. However, before cutting place them at 4  C overnight followed by 1 h at 20  C. This makes the blocks easier to section. 4. Section thickness would depend on the tissue of interest. 5. Make sure no water is trapped under the paraffin sections on slides. Otherwise, leave them at 37  C until the slides are completely dry. 6. It is important to maintain high temperature (95–98  C) during antigen retrieval with citrate buffer. 7. Use plastic slide chambers for the antigen retrieval step as glass chambers might break at high temperatures. 8. Do not discard the entire citrate buffer at once. Equilibrate slowly with dH20 as this prevents quick drying of sections. 9. Make sure that the slides are always wet as drying of sections leads to non-specific binding.

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10. Hydrophobic pen limit small amount of solutions within the boundary, thus making it easier to work with small amount of reagents. 11. Make sure when using small amount of reagent that it covers the tissue section entirely. 12. Observe sections under microscope to determine incubation time with DAB.

Acknowledgments This work was supported by Deutsche Forschungsgemeinschaft (DFG) SFB1366 project C4 to A.F. We thank Iris Moll for establishing the staining method and Leonie Uhl for providing the images presented in this article. References 1. Fischer A, Zalvide J, Faurobert E, AlbigesRizo C, Tournier-Lasserve E (2013) Cerebral cavernous malformations: from CCM genes to endothelial cell homeostasis. Trends Mol Med 19(5):302–308 2. Zafar A, Quadri SA, Farooqui M, Ikram A, Robinson M, Hart BL et al (2019) Familial cerebral cavernous malformations. Stroke 50 (5):1294–1301 3. Whitehead KJ, Plummer NW, Adams JA, Marchuk DA, Li DY (2004) Ccm1 is required for arterial morphogenesis: implications for the etiology of human cavernous malformations. Development 131(6):1437–1448 4. Bray SJ (2016) Notch signalling in context. Nat Rev Mol Cell Biol 17(11):722–735 5. Potente M, Gerhardt H, Carmeliet P (2011) Basic and therapeutic aspects of angiogenesis. Cell 146(6):873–887 6. Red-Horse K, Siekmann AF (2019) Veins and arteries build hierarchical branching patterns differently: bottom-up versus top-down. BioEssays 41(3):e1800198 7. Gaengel K, Genove G, Armulik A, Betsholtz C (2009) Endothelial-mural cell signaling in vascular development and angiogenesis. Arterioscler Thromb Vasc Biol 29(5):630–638 8. Hill-Felberg S, Wu HH, Toms SA, Dehdashti AR (2015) Notch receptor expression in human brain arteriovenous malformations. J Cell Mol Med 19(8):1986–1993 9. Murphy PA, Kim TN, Huang L, Nielsen CM, Lawton MT, Adams RH et al (2014) Constitutively active Notch4 receptor elicits brain

arteriovenous malformations through enlargement of capillary-like vessels. Proc Natl Acad Sci U S A 111(50):18007–18012 10. Jabs M, Rose AJ, Lehmann LH, Taylor J, Moll I, Sijmonsma TP et al (2018) Inhibition of endothelial notch signaling impairs fatty acid transport and leads to metabolic and vascular remodeling of the adult heart. Circulation 137 (24):2592–2608 11. Wieland E, Rodriguez-Vita J, Liebler SS, Mogler C, Moll I, Herberich SE et al (2017) Endothelial Notch1 activity facilitates metastasis. Cancer Cell 31(3):355–367 12. Fischer A, Gessler M (2007) Delta-Notch--and then? Protein interactions and proposed modes of repression by Hes and Hey bHLH factors. Nucleic Acids Res 35(14):4583–4596 13. Itoh F, Itoh S, Goumans MJ, Valdimarsdottir G, Iso T, Dotto GP et al (2004) Synergy and antagonism between Notch and BMP receptor signaling pathways in endothelial cells. EMBO J 23(3):541–551 14. Woltje K, Jabs M, Fischer A (2015) Serum induces transcription of Hey1 and Hey2 genes by Alk1 but not Notch signaling in endothelial cells. PLoS One 10(3):e0120547 15. Kar S, Baisantry A, Nabavi A, Bertalanffy H (2016) Role of Delta-Notch signaling in cerebral cavernous malformations. Neurosurg Rev 39(4):581–589 16. Wustehube J, Bartol A, Liebler SS, Brutsch R, Zhu Y, Felbor U et al (2010) Cerebral cavernous malformation protein CCM1 inhibits sprouting angiogenesis by activating DELTA-

Analysis of Notch Signaling NOTCH signaling. Proc Natl Acad Sci U S A 107(28):12640–12645 17. Brutsch R, Liebler SS, Wustehube J, Bartol A, Herberich SE, Adam MG et al (2010) Integrin cytoplasmic domain-associated protein-1 attenuates sprouting angiogenesis. Circ Res 107(5):592–601 18. Maddaluno L, Rudini N, Cuttano R, Bravi L, Giampietro C, Corada M et al (2013) EndMT contributes to the onset and progression of cerebral cavernous malformations. Nature 498 (7455):492–496 19. Schulz GB, Wieland E, Wustehube-Lausch J, Boulday G, Moll I, Tournier-Lasserve E et al (2015) Cerebral cavernous Malformation-1 protein controls DLL4-Notch3 signaling between the endothelium and pericytes. Stroke 46(5):1337–1343

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20. He Y, Zhang H, Yu L, Gunel M, Boggon TJ, Chen H et al (2010) Stabilization of VEGFR2 signaling by cerebral cavernous malformation 3 is critical for vascular development. Sci Signal 3(116):ra26 21. Schleider E, Stahl S, Wustehube J, Walter U, Fischer A, Felbor U (2011) Evidence for antiangiogenic and pro-survival functions of the cerebral cavernous malformation protein 3. Neurogenetics 12(1):83–86 22. You C, Sandalcioglu IE, Dammann P, Felbor U, Sure U, Zhu Y (2013) Loss of CCM3 impairs DLL4-Notch signalling: implication in endothelial angiogenesis and in inherited cerebral cavernous malformations. J Cell Mol Med 17(3):407–418

Chapter 32 Measuring the Kinase Activity of GCKIII Proteins In Vitro Juan Zalvide, Cristina Almenglo´, Sara Va´zquez, Mar Garcı´a-Colomer, Miriam Sartages, and Celia M. Pombo Abstract One of the CCM genes, CCM3/PDCD10, binds to the protein kinase family GCKIII, which comprises MST3/STK24, SOK1/STK25, and MST4/STK26. These proteins have been shown to have the same effect as CCM3, both in endothelial cells and in animal models such as zebrafish and are most likely involved in CCM pathogenesis. We describe here an in vitro kinase assay of GCKIII proteins which can be used to study their regulation in endothelial and other cells under different circumstances. Key words GCKIII, CCM3, Cellular stress

1

Introduction Familial cavernomatosis is the result of mutations in one of the three CCM genes: CCM1, CCM2, or CCM3, and their study has shed light on the pathogenesis of these important and prevalent lesions. Besides the three CCM genes, other proteins may play a role in the development of cerebral cavernomas, among them the GCKIII proteins, a subfamily of Ste20 kinases composed of MST3/STK24, SOK1/STK25, and MST4/STK26. They have a catalytic domain which is very similar to the GCKII subfamily (comprising the hippo-related MST1 and MST2), and a regulatory C-terminal domain which binds to CCM3 [1–4]. The first function proposed for GCKIII proteins was response to stress and induction of cell death under certain circumstances [5–7]. A role in cell polarity and cytoskeletal organization was later discovered [8–10], and in the last years, roles in metabolic regulation have also been uncovered [11–21]. Importantly, GCKIII proteins are most likely also involved in the pathogenesis of cerebral cavernoma. Their deficiency in zebrafish results in cardiovascular phenotypes similar to CCM-deficient animals. Further, inhibition of these kinases enhances cell permeability and Rho activity in endothelial cells, an effect also seen upon

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_32, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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CCM gene inhibition [22]. These effects are consistent with the mentioned functions of the kinases in response to stress, cytoskeletal organization, and cell polarity. Thus, study of their kinase activity may be an important tool in the study of the events that lead endothelial cells to develop into cavernous malformations. Control of the kinase activity of GCKIII proteins is complex. They can be regulated by cellular stress and caspase cleavage [7, 23]. Cellular localization has also been proposed to regulate their function. Kinases would be inactive while bound to the STRIPAK complex or the Golgi apparatus, while their binding to CCM3 would both activate and relocate them to their place of action [8, 24–26]. Here, we describe how to measure the kinase activity of GCKIII proteins, both in endothelial and non-endothelial cells. The main issue in our hands is to avoid autophosphorylation of the kinases, which is attained by limiting incubation time. Also, not all antibodies work for immunoprecipitating an active kinase. Mst3 particularly has been proposed to prefer Mn2+ rather than Mg2+ in the incubation reaction. However, we have seen no difference in the regulation of this kinase depending of the ion used [27].

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Materials 1. Cells (see Notes 1 and 2). 2. SAPK buffer: 20 mM HEPES, pH 7.4, 2 mM EGTA, 1 mM Na3VO4, 1% Triton X-100, 10% glycerol, 50 mM β-glycerophosphate, 1 mM DTT, 2 μM leupeptin, 400 μM phenylmethylsulfonyl fluoride (PMSF), 2.3 μg/mL aprotinin (see Note 3). 3. LiCl buffer: 500 mM LiCl, 10 mM Tris–HCl pH 7.6, 0.1% Triton X-100, 1 mM dithiotreitol (DTT) (see Note 4). 4. Assay buffer: 20 mM MOPS pH 7.2, 2 mM EGTA, 10 mM MnCl2, 0.1% Triton X-100, 1 mM dithiotreitol (DTT)S (see Note 5). 5. 10 mM ATP. 6. Anti-GCKIII antibody (see Note 6 and Fig. 1). 7. Myelin Basic Protein (see Notes 7 and 8). 8. γ-32P-ATP. We use ATP, [γ-32P]-3000 Ci/mmol 10 mCi/ mL, catalog number NEG502A from Perkin Elmer. 9. Materials for SDS-PAGE. 10. Gel dryer. 11. Typhoon (see Note 9).

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Fig. 1 Immunoprecipitation of MST3 with various antibodies. MST3 was immunoprecipitated with Novus NB100-1582 antibody (1 and 2), Abcam ab51137 antibody (3), or Bethyl Laboratories A300-564A-M antibody (4). Only NB100 antibody immunoprecipitated MST3 quantitatively

3

Methods 1. Place plates on ice, wash with PBS at 4  C, and add 400 μL SAPK buffer with inhibitors per p90 plate. Downsize according to the plate surface if using other plates. 2. Scrap cells, pipette to an Eppendorf tube, and lyse cells for 20 min on ice, vortexing every 5 min. 3. Spin at 4  C 20 min at 13,000  g and collect supernatants (see Note 10). 4. Quantify proteins. 5. Add 1 mg proteins in 500 μL SAPK buffer to an Eppendorf tube for immunoprecipitation (see Note 11). 6. Add antibody. Incubate at 4  C for 1 h. 7. Add protein G agarose pre-equilibrated with SAPK buffer. We routinely use 20 μL of a 1:1 suspension of protein G agarose per immunoprecipitation. 8. Incubate 2 h at 4  C (see Note 12). 9. Wash with SAPK buffer 3. 10. Wash with LiCl buffer 3. 11. Wash with assay buffer 2. 12. Spin down any remaining drops and aspirate using an insulin needle. 13. Add assay buffer containing 100 μM ATP, plus 5 μg MBP and 0.5 μL γ-32P-ATP per assay. Add approximately the same volume of assay buffer as of packed beads (10 μL of assay buffer per 20 μL 1:1 beads) (see Note 13). 14. Incubate at 30  C for 5 min (see Note 14).

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Fig. 2 Kinase activity of MST3. Liver cells were treated in KRH or KRH and H2O2 for 1 h. Kinase activity was determined as specified in the protocol. Note the higher activity in response to H2O2 treatment

15. Add SDS loading buffer and run in an SDS-PAGE. 16. Dry the gel and expose in typhoon scanner (Fig. 2).

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Notes 1. The choice of cells depends on your experiment. To study the pathogenesis of CCMs, use preferentially brain-derived endothelial cells. Remember that GCKIII proteins have also been shown to be involved in non-endothelial biology, at least in stress response, cytoskeletal regulation, and metabolism. The protocol described here can be used for these other roles of the kinases using different cellular and animal models. 2. The number of cells, degree of confluence, and other culture conditions will depend on your experiment. 3. SAPK buffer was initially developed to make extracts to measure JNK1/2 activity [28]. GCKIII kinases are soluble in this low ionic strength buffer. It has been suggested that lysis buffers containing Triton X-100 inhibit MST3 kinase activity [29]. However, we have seen no evidence of such inhibition. 4. We find that a high concentration of LiCl results in a cleaner immunoprecipitation of these kinases. 5. MST3 has been shown to use Mn2+ as a cofactor rather than Mg2+ [27]. We find that the kinase activity of MST3 upon Mg2 + addition is also detectable and modulated by different stimuli, most prominently oxidative stress, and have found no difference in the regulation of MST3 depending on the cation used. However, it is still possible that under specific circumstances, MST3 behaves different depending on whether Mg2+ or Mn2+ is used, and care should be taken in this respect. 6. Not all antibodies immunoprecipitate MST3 in a catalytically active form. We routinely use Novus NB100-1582 as we have seen it immunoprecipitates MST3 quantitatively. Neither abcam ab51137 antibody nor cell signaling cst 3723 antibody (in this last case as stated in their web page) immunoprecipitate MST3. Bethyl A300-56YA does so only partially (Fig. 1).

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7. We have always used the unspecific substrate Myelin Basic Protein (MBP). MST3 and other GCKIII kinases have been shown to phosphorylate other substrates, such as 14-3-3, Nuclear Dbf2-Related Kinase 1 (NDR1, STK38), ProteinTyrosine Phosphatase 1B (PTP1B, PTPN1), or Ezrin/ radixin/Moesin (ERM) proteins. 8. We use dephosphorylated MBP, from Merck, catalog number 13-110. 9. If a typhoon scanner is not available, gel can be exposed on film and kinase activity quantified in a beta counter after band excision. Beware of the lack of lineal response of traditional films. 10. Samples can be flash-frozen in a dry ice–ethanol bath and stored at 80  C at this point. 11. We routinely use 1 mg of protein if sufficient extract is available to get a reproducible level of kinase activity. 12. We routinely incubate antibody for a total of at least 3 h for immunoprecipitation. It is not necessary to leave this incubation overnight. 13. We have only been successful with GCKIII kinase experiments using 32P. Although there are purportedly specific phosphoMBP antibodies, we have found that they have a very high background and are not useful for kinase experiments, at least for GCKIII kinases. 14. Kinase activity has to be carried out for a limited period of time (5 min in our hands). Otherwise, the kinase will autophosphorylate [6].

Acknowledgments This work was supported by grants to CMP and JZ from FEDER/ Ministerio de Ciencia, Innovacio´n y Universidades-Agencia Estatal de Investigacio´n of Spain (SAF2017-87691-R), and Xunta de Galicia (ED431C 2019/13). MS is a predoctoral fellow from Xunta de Galicia. References 1. Dan I, Watanabe NM, Kusumi A (2001) The Ste20 group kinases as regulators of MAP kinase cascades. Trends Cell Biol 11:220–230 2. Thompson BJ, Sahai E (2015) MST kinases in development and disease. J Cell Biol 210:871–882 3. Pombo CM, Force T, Kyriakis J, Nogueira E, Fidalgo M, Zalvide J (2007) The GCK II and

III subfamilies of the STE20 group kinases. Front Biosci 12(3):850–859 4. Sugden PH, McGuffin LJ, Clerk A (2013) SOcK, MiSTs, MASK and STicKs: the GCKIII (germinal centre kinase III) kinases and their heterologous protein-protein interactions. Biochem J 454:13–30

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5. Huang H, Wu W, Zhang L, Liu XY (2013) Drosophila Ste-20 family protein kinase, Hippo, modulates fat cell proliferation. PLoS One 8(4) 6. Pombo CM, Bonventre JV, Molnar A, Kyriakis J, Force T (1996) Activation of a human Ste20-like kinase by oxidant stress defines a novel stress response pathway. EMBO J 15:4537–4546 7. Huang C-YF, Wu Y-M, Hsu C-Y, Lee W-S, Lai M-D, Lu T-J, Huang C-L, Leu T-H, Shih H-M, Fang H-I et al (2002) Caspase activation of mammalian sterile 20-like Kinase 3 (Mst3). J Biol Chem 277:34367–34374 8. Preisinger C, Short B, De Corte V, Bruyneel E, Haas A, Kopajtich R, Gettemans J, Barr FA (2004) YSK1 is activated by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate 14-3-3zeta. J Cell Biol 164:1009–1020 9. ten Klooster JP, Jansen M, Yuan J, Oorschot V, Begthel H, Di Giacomo V, Colland F, de Koning J, Maurice MM, Hornbeck P et al (2009) Mst4 and Ezrin induce brush borders downstream of the Lkb1/Strad/Mo25 polarization complex. Dev Cell 16:551–562 10. Lu T-J, Lai W-Y, Huang C-YF, Hsieh W-J, Yu J-S, Hsieh Y-J, Chang W-T, Leu T-H, Chang W-C, Chuang W-J et al (2006) Inhibition of cell migration by autophosphorylated mammalian sterile 20-like kinase 3 (MST3) involves paxillin and protein-tyrosine phosphatasePEST. J Biol Chem 281:38405–38417 11. Nerstedt A, Cansby E, Andersson CX, Laakso M, Stancakova A, Bluher M, Smith U, Mahlapuu M (2012) Serine/threonine protein kinase 25 (STK25): a novel negative regulator of lipid and glucose metabolism in rodent and human skeletal muscle. Diabetologia 55:1797–1807 ˜ ez-dur E, 12. Amrutkar M, Cansby E, Nun Pirazzi C, St M, Stenfeldt E, Smith U, Bor J, Mahlapuu M (2015) Protein kinase STK25 regulates hepatic lipid partitioning and progression of liver steatosis and NASH. FASEB J 29(4):1–13 ˜ ez13. Amrutkar M, Cansby E, Chursa U, Nun Dura´n E, Chanclo´n B, Sta˚hlman M, Fride´n V, Mannera˚s-Holm L, Wickman A, Smith U et al (2015) Genetic disruption of protein kinase STK25 ameliorates metabolic defects in a diet-induced type 2 diabetes model. Diabetes 64:2791–2804 14. Cansby E, Amrutkar M, Mannera˚s Holm L, Nerstedt A, Reyahi A, Stenfeldt E, Bore´n J, Carlsson P, Smith U, Zierath JR et al (2013) Increased expression of STK25 leads to impaired glucose utilization and insulin

sensitivity in mice challenged with a high-fat diet. FASEB J 27:3660–3671 15. Amrutkar M, Chursa U, Kern M, NunezDuran E, Stahlman M, Sutt S, Boren J, Johansson BR, Marschall H-U, Bluher M et al (2016) STK25 is a critical determinant in nonalcoholic steatohepatitis. FASEB J 30:3628–3643 ˜ ez-Dura´n E, Cansby E, 16. Chursa U, Nun Amrutkar M, Su¨tt S, Sta˚hlman M, Olsson B-M, Bore´n J, Johansson ME, B€ackhed F et al (2017) Overexpression of protein kinase STK25 in mice exacerbates ectopic lipid accumulation, mitochondrial dysfunction and insulin resistance in skeletal muscle. Diabetologia 60(3):553–567 ˜ ez-Dura´n E, Aghajan M, Amrutkar M, 17. Nun Su¨tt S, Cansby E, Booten SL, Watt A, Sta˚hlman M, Stefan N, H€aring H-U et al (2017) Serine/threonine protein kinase 25 antisense oligonucleotide treatment reverses glucose intolerance, insulin resistance, and nonalcoholic fatty liver disease in mice. Hepatol Commun 2:69–83 ˜ ez-Dura´n E, Chanclo´n B, Su¨tt S, Real J, 18. Nun Marschall HU, Asterholm IW, Cansby E, Mahlapuu M (2017) Protein kinase STK25 aggravates the severity of non-alcoholic fatty pancreas disease in mice. J Endocrinol 234:15–27 ˜ ez19. Su¨tt S, Cansby E, Paul A, Amrutkar M, Nun Dura´n E, Kulkarni NM, Sta˚hlman M, Bore´n J, Laurencikiene J, Howell BW et al (2018) STK25 regulates oxidative capacity and metabolic efficiency in adipose tissue. J Endocrinol 238:187–202 ˜ ez-Dura´n E, Magnusson E, 20. Cansby E, Nun Amrutkar M, Booten SL, Kulkarni NM, Svensson LT, Bore´n J, Marschall HU, Aghajan M et al (2019) Targeted delivery of Stk25 antisense oligonucleotides to hepatocytes protects mice against nonalcoholic fatty liver disease. Cell Mol Gastroenterol Hepatol 7:597–618 ˜ ez-dura´n E, Magnusson E, 21. Cansby E, Nun Amrutkar M, Booten L, Kulkarni NM, Svensson LT, Bore´n J, Aghajan M, Mahlapuu MSC (2019) Cell Mol Gastroenterol Hepatol 22. Uispvhi T, Zheng X, Xu C, Di Lorenzo A, Kleaveland B, Zou Z, Seiler C, Chen M, Cheng L, Xiao J et al (2010) CCM3 signaling through sterile 20–like kinases plays an essential role during zebrafish cardiovascular development and cerebral cavernous malformations. J Clin Invest 120:2795–2804 23. Nogueira E, Fidalgo M, Molnar A, Kyriakis J, Force T, Zalvide J, Pombo CM (2008) SOK1 translocates from the Golgi to the nucleus upon chemical anoxia and induces apoptotic cell death. J Biol Chem 283:16248–16258

Kinase Activity of GCKIII Proteins 24. Kean MJ, Ceccarelli DF, Goudreault M, Sanches M, Tate S, Larsen B, Gibson LCD, Derry WB, Scott IC, Pelletier L et al (2011) Structure-function analysis of core STRIPAK proteins. J Biol Chem 286:25065–25075 25. Madsen CD, Hooper S, Tozluoglu M, Bruckbauer A, Fletcher G, Erler JT, Bates PA, Thompson B, Sahai E (2015) STRIPAK components determine mode of cancer cell migration and metastasis. Nat Cell Biol 17:68–80 26. Zalvide J, Fidalgo M, Fraile M, Guerrero A, Iglesias C, Floridia E, Pombo CM (2013) The CCM3-GCKIII partnership. Histol Histopathol 28 27. Schinkmann K, Blenis J (1997) Cloning and characterization of a human STE20-like

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protein kinase with unusual cofactor requirements∗. J Biol Chem 272:28695–28703 28. Pombo CM, Bonventre JV, Avruch J, Woodgett JR, Kyriakis JM, Force T (1994) The stress-activated protein kinases are major c-Jun amino terminal kinases activated by ischemia and reperfusion. J Biol Chem 269:26546–26551 29. Kan W-C, Lu T-L, Ling P, Lee T-H, Cho C-Y, Huang C-YF, Jeng W-Y, Weng Y-P, Chiang C-Y, Wu JB, Lu TJ (2016) Pervanadate induces M ammalian St e20 Kinase 3 (MST3) tyrosine phosphorylation but not activation. J Inorg Biochem 160:33–39

Chapter 33 Spectrophotometric Method for Determining Glyoxalase 1 Activity in Cerebral Cavernous Malformation (CCM) Disease Cinzia Antognelli, Vincenzo Nicola Talesa, and Saverio Francesco Retta Abstract Glyoxalase 1 (Glo1) is a glutathione (GSH)-dependent enzyme that catalyzes the isomerization of the hemithioacetal formed non-enzymatically from methylglyoxal (MG) and GSH to S-D-lactoylglutathione (SLG). The activity of Glo1 is measured spectrophotometrically by following the increase of absorbance at 240 nm and 25
C, attributable to the formation of SLG. The hemithioacetal is preformed by incubation of 2 mM MG and 1 mM GSH in 0.1 M sodium phosphate buffer (PBS) pH 7.2, at 25
C for 10 min. The cell extract is then added, and the A240 is monitored over 5-min incubation against correction for blank. Glo1 activity is given in units per mg of protein where one unit activity is defined as 1 μmole of SLG produced per min under assay conditions. Here, we describe measurement of Glo1 activity in established cellular models of cerebral cavernous malformation (CCM) disease, including KRIT1-knockout mouse embryonic fibroblast (MEF) and KRIT1-silenced human brain microvascular endothelial (hBMEC) cells. Key words Glyoxalase 1, Methylglyoxal, Glutathione, Enzyme activity, S-D-lactoylglutathione, CCM

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Introduction Glyoxalase 1 (Glo1) (EC4.4.1.5) is a cytosolic enzyme that plays an important role in cellular defense against glycation since it is able to catalyze the detoxification of methylglyoxal (MG), a potent glycating agent [1], into the corresponding α-hydroxyacid, using glutathione (GSH) as a cofactor. In particular, Glo1 catalyzes the formation of S-D-lactoylglutathione (SLG) from the hemithioacetal that is formed through the non-enzymatic conjugation of MG and GSH [2]. The activity of Glo1 is assayed by an established spectrophotometric method [3, 4]. Briefly, the assay solution contains 0.1 M sodium phosphate buffer (PBS), pH 7.2, 2 mM MG, and 1 mM GSH, which are preincubated at 25
C for 10 min to allow the formation of the hemithioacetal, substrate of Glo1. Then the cell extract is added, and the reaction is monitored by following the increase in absorbance at 240 nm due to the formation of SLG.

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_33, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Glo1 activity is calculated from Beer’s law with molar absorption coefficient at 240 nm Δε240 ¼ 2.86 mM1 cm1, against the reagent blank. Glo1 activity is expressed in units per mg of protein where one unit activity is defined as 1 μmole of SLG produced per min under assay conditions. Here, we describe measurement of Glo1 activity in established cellular models of cerebral cavernous malformation (CCM) disease, including KRIT1 knockout mouse embryonic fibroblast (MEF) and KRIT1-silenced human brain microvascular endothelial (hBMEC) cells.

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Materials Prepare all solutions using double distilled water and analyticalgrade reagents. Prepare and store all reagents at room temperature (unless otherwise indicated). Diligently follow all waste disposal procedures.

2.1

Apparatus

1. Shimadzu UV-visible recording spectrophotometer Biospecmini using 1-cm quartz cells equipped with a kinetic program or equivalent instruments. 2. pH meter type Mettler Toledo FE20-ATC Kit FiveEasy™ Benchtop.

2.2

Cells

1. KRIT1/ and KRIT1+/+ mouse embryonic fibroblast (MEF) cells, established from KRIT1/ and KRIT1+/+ E8.5 mouse embryos, respectively, and KRIT1 9/6 MEFs, obtained by infecting KRIT1/ cells with a lentiviral vector encoding KRIT1 [4, 5], cultured at 37
C and 5% CO2 in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal calf serum (FCS), 2 mM glutamine, and 100 U/ mL penicillin/streptomycin. 2. The human brain microvascular endothelial cells (hBMEC), from ScienCell Research Laboratory (Carlsbad, CA) cultured at 37
C and 5% CO2 on cell culture dishes coated with rat tail collagen type-I and containing EGM-2MV medium.

2.3 Buffers and Solutions

1. Sodium phosphate buffer (PBS) (see Note 1) Prepare the appropriate volume of 0.1 M sodium phosphate buffer, pH 7.2, taking into account the number of assays you want to perform. For 100 mL of 0.1 M sodium phosphate buffer, prepare as follows: – Start with 80 mL of distilled water. – Add 1.379 of NaH2PO4.H2O. – Adjust the pH to 7.2 with HCl. – Add distilled water to a total volume of 100 mL.

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2. MG solution Prepare the appropriate volume of 100 mM MG from a 1 M stock solution. For 100 mL of 100 mM MG, prepare as follows: – Start with 90 mL of distilled water. – Add 10 mL of 1 M MG. 3. GSH solution Prepare the appropriate volume of 100 mM GSH, taking into account the number of assays you want to perform. For 10 mL of 100 mM GSH, prepare as follows: – Start with 8 mL of distilled water: – Add 0.307 g of GSH. – Add distilled water to a total volume of 10 mL. 4. Hemithioacetal solution (see Note 1). – Prepare the appropriate volume of 0.1 M sodium phosphate buffer, pH 7.2, taking into account the number of assays you want to perform. For 10 mL of 0.1 M sodium phosphate buffer, pH 7.2, prepare as follows: – Start with 9.7 mL of 0.1 M sodium phosphate buffer, pH 7. – Add 0.2 mL of 100 mM MG solution (final concentration 2 mM MG). – Add 0.1 mL of 100 mM GSH solution (final concentration 1 mM GSH). Incubate at 25
C for 10 min on a magnetic stirrer.

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Methods

3.1 Preparation of Cell Lysates

1. Harvest sub-confluent MEF or hBMEC cells and wash them three times with phosphate buffered saline (PBS). 2. Suspend in 10 mM phosphate buffer, pH 7.0, containing 1 mM DTT and 0.1 mM phenylmethanesulphonyl fluoride (PMSF). 3. Homogenize cell homogenizer.

suspensions

with

a

Potter-Elvehjem

4. Centrifuge at 13,000  g for 30 min. 5. Use the resulting cell lysates for enzymatic activities and protein content measurements. 3.2 Total Protein Measurement

Determine protein concentration in cell extracts by using the BCA protein assay or equivalent methods and express it in mg/mL (or equivalent).

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3.3 Glo1 Activity Assay

Carry out all procedures at 25
C and perform Glo1 activity measurements at least in triplicate. All the following procedures are valid for a single assay. Please, multiply accordingly for the number of assays you want to consider. 1. Place in a 1-cm quartz cell 1000 μL (final volume of the assay) of the hemithioacetal previously prepared, this will be your blank. 2. Place this blank cuvette into the spectrophotometer set at 240 nm wave length (λ) and use it to blank the spectrophotometer reader. 3. Place in another 1-cm quartz cell 990 μL of the hemithioacetal previously prepared. 4. Place this cuvette into the spectrophotometer and add 10 μL of cell lysate previously obtained to reach a final volume of 1000 μL (see Note 2). 5. Gently mix by pipetting several times and start recording the increase of absorbance at 240 nm, due to the ongoing formation of LSG, over a period of 5 min.

3.4 Glo1 Activity Calculation (Use Δε240 ¼ 2.86 mM1 cm1)

3.5 Glo1 Specific Activity Calculation

4

1. ΔAbs min1 ¼ (Abs5 min  Abs0 min)/5 min ! (a). 2. μmol min1 ¼ (a)/2.86 mM1 cm1 ! (b). 3. Glo1 activity (μmol min1 mL1) ¼ (b). 100 (dilution factor, DF). 1. Glo1 specific activity (μmol min1/mg protein) ¼ Glo1 activity/protein content ¼ (μmol min1 mL1)/mg/mL.

Notes 1. Make sure that all the solutions have been prepared properly and have the appropriate pH value. 2. In case you do not detect Glo1 activity using a volume of 10 μL, try with 20 μL up to 50 μL. Important: if with a volume of cell lysate ¼ 50 μL, the value of Glo1 activity is zero, then there is not activity at all or it is very very low in the cell lysate. When calculating Glo1 activity, remember to multiply for 50 or 20 (DF), respectively. If using a volume different from those indicated here, remember: DF ¼ 1000 μL/volume of the cell lysate employed.

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References 1. Antognelli C, Cecchetti R, Riuzzi F, Peirce MJ, Talesa VN (2018) Glyoxalase 1 sustains the metastatic phenotype of prostate cancer cells via EMT control. J Cell Mol Med 22:2865–2883. https://doi.org/10.1111/jcmm.13581 2. Antognelli C, Gambelunghe A, Muzi G, Talesa VN (2015) Peroxynitrite-mediated glyoxalase I epigenetic inhibition drives apoptosis in airway epithelial cells exposed to crystalline silica via a novel mechanism involving argpyrimidinemodified Hsp70, JNK, and NF-κB. Free Radic Biol Med 84:128–141. https://doi.org/10. 1016/j.freeradbiomed.2015.03.026 3. Antognelli C, Gambelunghe A, Muzi G, Talesa VN (2016) Glyoxalase I drives epithelial-tomesenchymal transition via argpyrimidinemodified Hsp70, miR-21 and SMAD signalling in human bronchial cells BEAS-2B chronically exposed to crystalline silica Min-U-Sil 5: Transformation into a neoplastic-like phenotype. Free

Radic Biol Med 92:110–125. https://doi.org/ 10.1016/j.freeradbiomed.2016.01.009 4. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Daga M, Pizzimenti S, Barrera G, Cassoni P, Angelucci A, Trabalzini L, Talesa VN, Goitre L, Retta SF (2018) KRIT1 loss-offunction induces a chronic Nrf2-mediated adaptive homeostasis that sensitizes cells to oxidative stress: implication for cerebral cavernous malformation disease. Free Radic Biol Med 115:202–218. https://doi.org/10.1016/j.fre eradbiomed.2017.11.014 5. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Fornelli C, Retta F, Cassoni P, Talesa VN, Retta SF (2017) Data in support of sustained upregulation of adaptive redox homeostasis mechanisms caused by KRIT1 loss-offunction. Data Brief 16:929–938. https://doi. org/10.1016/j.dib.2017.12.026

Chapter 34 Fluorescence Analysis of Reactive Oxygen Species (ROS) in Cellular Models of Cerebral Cavernous Malformation Disease Andrea Perrelli and Saverio Francesco Retta Abstract Cerebral cavernous malformation (CCM) is a vascular disease of proven genetic origin, which may arise sporadically or can be inherited as an autosomal dominant condition with incomplete penetrance and highly variable expressivity. CCM disease exhibits a range of different phenotypes, including wide interindividual differences in lesion number, size, and susceptibility to intracerebral hemorrhage (ICH). Mutations of the KRIT1 gene account for over 50% of familial cases. Previously, we demonstrated that KRIT1 loss-offunction is associated with altered homeostasis of intracellular reactive oxygen species (ROS) and abnormal activation of redox-sensitive transcription factors, which collectively result in pro-oxidative, pro-inflammatory, and pro-angiogenic effects, suggesting a novel pathogenic mechanism for CCM disease. Consistently, these original discoveries have been confirmed and extended by subsequent findings showing mechanistic relationships between pleiotropic redox-dependent effects of KRIT1 loss-of-function and enhanced cell sensitivity to oxidative stress, which may eventually lead to cellular dysfunctions and CCM disease pathogenesis. In this chapter, we describe few basic methods used for qualitative and quantitative analysis of intracellular ROS in cellular models of CCM disease. Key words Cerebral cavernous malformation (CCM), CCM1/KRIT1, Oxidative stress Reactive oxygen species (ROS), Selective ROS detection, Dichlorofluorescin diacetate (DCFDA), Dihydroethidium (DHE), Amplex® Red hydrogen peroxide/peroxidase assay, MitoSOX Red, Flow cytometry, Fluorometric measurement

1

Introduction Reactive oxygen species (ROS) are chemically reactive oxygen radicals as well as non-radical derivatives of molecular oxygen (O2) that are generated constitutively as common by-products of cellular oxidative metabolism, or in response to the activation of several oxidative enzyme complexes [1, 2]. The main types of ROS are superoxide anion (O2˙
) and hydrogen peroxide (H2O2), both of which may exert either beneficial or detrimental effects on cell functions, depending mainly on specific threshold levels and cell

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols , Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_34, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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context. Despite its short half-life, O2˙
is the key determinant of overall ROS effects. Indeed, it is the precursor of all other major ROS found in biological systems, including H2O2 and the powerful oxidants hydroxyl radical (˙OH) and peroxynitrite (OONO
) [1, 2]. It is generated by a number of sources located throughout the cell via the incomplete, one-electron reduction of O2. Specifically, under physiological conditions, the redox complexes I (NADH/ubiquinone oxidoreductase) and III (ubiquinol/cytochrome c oxidoreductase) of the mitochondrial electron transport chain (ETC) are the major constitutive source, converting up to 5% of O2 to O2˙
. In addition, O2˙
is produced by multiple oxidative enzymes acting at specific intracellular sites, including NADPH oxidase, xanthine oxidase, cytochrome p450, uncoupled NO synthase (NOS), myeloperoxidase, lipoxygenase, and cyclooxygenase. These ROS-producing enzymes can be selectively induced by a variety of chemical and physical stimuli, including growth factors, G-protein coupled receptor agonists, cytokines, neurotransmitters, metabolic factors, shear stress, ischemia/reperfusion, chemotherapeutics, and ionizing radiations, as well as aging [1, 2]. Conversely, O2˙
is rapidly removed by distinct superoxide dismutase (SOD) enzymes, which catalyze the dismutation of O2˙
into H2O2 and O2. Specifically, there are three SOD isoforms (SOD1, SOD2 and SOD3), which differ in cellular localization and in the metal ion cofactor necessary for activity: SOD1 (Cu/Zn SOD) is localized mainly in the cytosol but also in the mitochondrial intermembrane space, SOD2 (MnSOD) is confined in the mitochondrial matrix, and SOD3 (Cu/Zn SOD) is localized in the extracellular space. In turn, H2O2 can act as a second messenger to propagate intracellular signaling, and is eventually reduced to H2O by catalase and glutathione peroxidase enzymes. In addition, O2˙
can be converted to hydroxyl radical (·OH) by the Fenton or Haber-Weiss reactions, or to peroxynitrite (OONO
) by reacting with nitric oxide (NO) [1, 2]. It is now clearly established that ROS and redox-dependent mechanisms affect almost all aspects of life both positively and negatively [2, 3]. Indeed, whereas physiological production of ROS, termed “oxidative eustress,” is essential for governing life processes through redox signaling, supraphysiological oxidative challenge, known as “oxidative stress,” leads to disrupted redox signaling and/or oxidative damage to biomolecules [4, 5]. The maintenance of highly regulated enzymatic and transcriptional mechanisms for spatiotemporal control of intracellular ROS levels and redox homeostasis is therefore essential for normal cell physiology and proper response to environmental stimuli. Specifically, the essential signaling properties of physiologic concentrations of ROS are mainly attributable to the reversible oxidation of redoxsensitive molecular targets, such as redox-sensitive cysteine, methionine, proline, histidine, and tryptophan amino acid side chains in

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proteins [6, 7], thereby influencing the structure-function relationship of important structural and signaling molecules. Accordingly, it has been clearly demonstrated that ROS are involved in the redox-dependent regulation of multiple signal transduction pathways to fulfill a wide range of essential biological processes, including cell adhesion, migration, proliferation, differentiation, and survival [1, 2]. However, at high levels, ROS can cause extensive oxidative damage to most cellular components, including proteins, lipids, and DNA, and may have pathophysiological consequences. This oxidative stress is caused by an imbalance between the production of ROS and the ability of cellular antioxidant mechanisms to readily detoxify reactive intermediates and prevent oxidative damage to biomolecules. Consistent with its potential detrimental effects on most cell types and tissues, it is now well established that oxidative stress contributes significantly to the pathogenesis of multiple human diseases, including cerebrovascular diseases [8–10]. In particular, accumulating evidence demonstrates that oxidative stress may represent an important environmental “second hit” involved in the onset and progression of cerebral cavernous malformation (CCM) disease. This is a major vascular disorder of genetic origin that affects mainly brain capillaries and predisposes to a large variety of clinical symptoms, including headaches, neurological deficits, seizures, stroke, and intracerebral hemorrhage (ICH) [11, 12]. Three disease genes have been identified, CCM1/KRIT1, CCM2, and CCM3/PDCD10 [13], showing that their loss-of-function mutations lead to endothelial cell-cell junction weakening and enhanced microvascular permeability. Among CCM genes, KRIT1 has been shown to play important pleiotropic functions due to its ability to regulate cellular redox homeostasis and defenses against oxidative stress [10, 14–25]. In particular, a central antioxidant and cytoprotective role has been associated with KRIT1-dependent maintenance of mitochondrial homeostasis and modulation of master regulators of cell responses to oxidative stress. These regulators include the transcriptional factor FoxO1, its downstream target and major cellular antioxidant enzyme SOD2, and Sirt1 [14], as well as autophagy [20, 22, 23], pro-oxidant and pro-inflammatory pathways, including JNK/c-Jun [15] and NF-kB [19] redoxdependent signaling, and consequent adaptive responses mediated by major antioxidant transcription factors, such as Nrf2 [16, 17]. Intriguingly, these mechanisms result eventually in a chronic adaptive redox homeostasis that sensitizes cells to additional stressful events [16, 17, 26]. Furthermore and importantly, distinct studies have suggested innovative promising preventive and therapeutic options based on several available repurposed drugs endowed with antioxidant and/or anti-inflammatory properties, such as Tempol [27], Tiron [16, 17, 20], cholecalciferol (vitamin D3) [27], and avenanthramides [19, 28, 29], as well as

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nanotechnology-based combination drug delivery approaches [30, 31]. In this chapter, we describe materials and methods used for ROS detection and analysis in cellular models of CCM disease. In particular, among the several analytical approaches used to detect and characterize intracellular ROS, we will refer mainly to the fastest, easiest, and most accessible methods for monitoring ROS production based on the use of cell permeable ROS-sensitive fluorescent probes, such as 20 ,70 -dichlorofluorescin diacetate (DCFH-DA), dihydroethidium (DHE), MitoSOX™ Red, and Amplex® Red fluorigenic dyes. These probes are all oxidized to form intermediate probe-derived radicals that are successively oxidized to generate the corresponding fluorescent products [32]. Despite some criticisms and limitations reported in the literature [32, 33], these probes show reactivity toward reactive oxygen species produced in different cellular compartments, including cytosolic and mitochondrial superoxide and hydrogen peroxide, and are useful for experiments aimed at measuring general aspects of intracellular redox status and oxidative stress. For more specific analyses, additional analytical methods should be applied, such as HPLC and mass spectrometry [34]. Specifically, DCFH-DA is a nonfluorescent probe that freely permeates the plasma membrane and is de-esterified and oxidized in the cytosol to form the highly fluorescent dichlorofluorescein (DCF) product, which is maximally excited at 495 nm and emits at 520 nm [33]. Despite it is often referred to as “hydrogen peroxidedetecting probe for the measurement of hydrogen peroxide in intact cells”, the range of ROS detected by this probe is much broader [32, 33]. DHE is the reduced form of the widely used DNA dye ethidium bromide, and is commonly used to detect cytosolic superoxide. Indeed, upon its reaction with the superoxide anion, DHE forms a red fluorescent product, 2-hydroxyethidium, which exhibits red fluorescence with maximum excitation and emission peaks at 500 and 580 nm, respectively. However, apart from superoxidemediated oxidation to 2-hydroxyethidium, DHE can also undergo unspecific oxidation by OONO
and ·OH into ethidium, which should be taken into account when interpreting the results [34, 35]. MitoSOX™ Red is a cationic derivative of DHE that is rapidly targeted to the mitochondria, due to the positive charge of the cationic triphenylphosphonium substituent, and is used to measure superoxide production in the mitochondrial matrix. Indeed, it is oxidized by mitochondrial superoxide to form the red fluorescent product 2-hydroxymitoethidium, which is maximally excited at 510 nm and emits at 580 nm [34]. Amplex® Red (10-acetyl-3,7-dihydroxyphenoxazine) is a colorless nonfluorescent derivative of dihydroresorufin that reacts with H2O2 at a stoichiometry of 1:1 in a reaction catalyzed by

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horseradish peroxidase (HRP) to generate the red-fluorescent oxidation product resorufin (7-hydroxy-3H-phenoxazin-3-one). Specifically, HRP catalyzes the decomposition of H2O2 to the hydroxyl radical, which is then reduced to water as a result of irreversible chemical oxidation of Amplex Red, thereby generating the highly fluorescent resorufin (excitation/emission maxima ¼ 563/ 587 nm) [16, 36]. The assay based on this reaction is highly selective and sensitive, allowing measurement of H2O2 at concentrations as low as 50 nM, and has been instrumental to gaining insights into the mechanism of mitochondrial ROS production [37].

2

Materials

2.1 Cell Culture and Treatment

1. 6-well plates for cell cultures. 2. Cell lines of interest, e.g., KRIT1-KO (K
/
) and KRIT1overexpressing (K9/6) MEF cells [14]. 3. Complete cell culture medium (DMEM, Dulbecco’s Modified Eagle Medium), supplemented with 10% fetal bovine serum (FBS) and 100 U/mL penicillin/streptomycin. 4. PBS buffer: 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4, pH 7.4. 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 H2O. Adjust the pH to 7.4 with HCl. Add H2O to 1 L. Sterilize by autoclaving on liquid cycle. Store at room temperature. 5. 0.5% Trypsin-EDTA, 10 solution. 6. 0.5% Trypsin, 1 solution, diluted in sterile PBS buffer, starting from Trypsin 10 solution. Store at 4  C.

2.2 Coverslips for Cell Culture and Fluorescence Microscopy

1. Coverslips of 15 mm diameter.

2.3 Fixation and Fluorescence Staining of Cells on Glass Coverslips

1. NH4Cl Stock solution: 1 M in PBS; working solution: 50 mM in PBS.

2. Acid solution for cleaning coverslips: two parts of nitric acid (HNO3), one part of chloridric acid (HCl). Make up the solution in a glass beaker. Operate under chemical hood.

2. 4% Paraformaldehyde (PFA): dissolve the appropriate amount of PFA in PBS in a glass beaker with a stir bar (see Note 1). Heat in a hot plate in the hood at 60  C. Cool down to 20  C, and adjust pH to 7.4. Store at 4  C or at
20  C for longer time. 3. PBS—0.5% Triton-X 100. 4. PBS—1% bovine serum albumin (BSA).

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5. Mounting reagents: some mounting reagents are supplied with fluorescent probes and antifade reagents and are ready to use. 6. 40 ,6-Diamidino-2-phenylindole (DAPI) or Hoechst for nuclear staining: not necessary if you use a mounting reagent supplied with DAPI (see Note 2). 2.4 Qualitative, Quantitative, and Semiquantitative Detection of ROS

1. Cell permeable ROS-sensitive fluorogenic probes 20 ,70 -dichlorofluorescin diacetate (DCFH-DA) and dihydroethidium (DHE). 2. MitoSOX™ Red fluorigenic dye [3,8-phenanthridinediamine, 5-(60 -triphenylphosphoniumhexyl)-5,6 dihydro-6-phenyl, Invitrogen, Carlsbad, California, USA] (see Note 3). 3. 5 mM (final concentration) Hank’s Buffered Salt Solution, containing calcium and magnesium (HBSS). 4. Blue fluorescent nuclear dye (Hoechst 34580).

2.5 Measurement of Cellular H2O2 Levels

1. Amplex® Red reagent (10-acetyl-3,7-dihydroxyphenoxazine, A22188, Invitrogen), a selective and highly sensitive fluorogenic probe that reacts with H2O2. 2. Horseradish peroxidase (HRP) to generate the red-fluorescent oxidation product resorufin (7-hydroxy-3H-phenoxazin-3one). 3. RIPA Buffer: 100 μM phenyl methyl sulfonyl fluoride (PMSF), 5 M NaCl, 1 M Tris–HCl pH 8, 10% SDS, 1 μM NP4O, 100 mM sodium pyrophosphate, 500 mM EDTA pH 8, 1 M Na3VO4, 1 M NaF, 400 mM protease inhibitors, 10 μM sodium deoxycholate in 5.3 mL of distilled H2O. 4. Reaction buffer: 50 mM sodium phosphate buffer, adjust the pH to 7.4 with HCl. 5. 1 M H2O2 starting solution, diluted in PBS 1. 6. 5 Bradford reagent for protein quantification in cell extracts. 7. 96-well microplates. 8. Antioxidant reagents (e.g., Tiron powder reagent). 9. 1 M Tiron stock solution diluted in distilled H2O; store at 4  C and preserve from light.

3

Methods Qualitative and quantitative analysis of intracellular ROS levels is performed using a well-established method based on the cell permeable ROS-sensitive fluorogenic probes 20 ,70 -dichlorofluorescin diacetate (DCFH-DA) and dihydroethidium (DHE), which have a sensitivity for various ROS/RNS and superoxide anions (O2˙
),

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respectively. Furthermore, the total amount of intracellular H2O2 levels is analyzed by a colorimetric method. 3.1 Cleaning Coverslips for Cell Culture and Fluorescence Microscopy

1. Place coverslips (a few at a time, see Note 4) into the acid solution (300 mL), and allow them to sit for 2 h with occasional swirling. 2. Decant the acid carefully into an adequate waste receptacle. 3. Wash the coverslips extensively in running tap water until the pH of the wash water is back to 5.5–6.0 (see Note 5). 4. Store the coverslips in a covered container suitable to be sterilized in a hot air oven. 5. Sterilize the coverslips in a hot air oven at 180  C for 3 h. You can use a sterilization indicator to check sterility (see Note 6). 6. Put coverslips into 6-well cell culture plates. You can use a Pasteur pipette connected with a vacuum pump to grab coverslips.

3.2 Cell Growth and Treatment

1. Plate cells onto coverslips distributed in 6-well plates. Use different plates for K
/
and K9/6 cells. 2. Grow cells until confluence. K
/
and K9/6 cells must be cultured in complete DMEM at 37  C and 5% CO2 atmosphere. 3. Wash cells twice with PBS. 4. Incubate cells with the ROS-sensitive fluorogenic probes DCFH-DA or DHE at a final concentration of 5 mM in PBS at 37  C for 20 min (see Note 7).

3.3 Cell Fixation and Fluorescence Microscopy Analyses

1. Rinse cells twice with PBS. 2. Fix cells with 4% PFA for 10 min (see Note 8). 3. Rinse 3 times with PBS. 4. Quench with 50 mM NH4Cl for 20 min. This step is crucial in reducing nonspecific background. 5. Rinse 3 times with PBS. 6. Permeabilize cells with PBS–0.5% Triton-X 100 for 1 min. 7. Rinse 3 times with PBS. 8. Soak coverslips briefly in H2O to remove salts. 9. Eliminate excess water from coverslip by carefully touching the edges of the cover slip with a piece of paper. 10. Mount coverslips with cells down on a drop (20 μL) of mounting medium supplied with nuclear staining on a clean microscope slide. Gently lower the coverslips onto the mounting medium, cell side down, so that no air bubbles become trapped.

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Fig. 1 Qualitative detection of the steady-state levels of intracellular ROS by fluorescence microscopy. Wild-type (WT), KRIT1
/
(KRIT1
/
), and KRIT1transduced (Lv-KRIT1 9/6) MEFs grown under standard conditions were analyzed by fluorescence microscopy 20 min after the addition of the cellpermeable redox-sensitive fluorogenic probe DCFH-DA (A) or DHE (B). The images were taken with a fixed short exposure time and a high fluorescence intensity threshold value to avoid saturation, and are representative of several independent experiments. Notice that KRIT1
/
cells (panels b) showed significantly more intense fluorescent signals than WT cells (panels a), indicating that they contained higher levels of ROS. Conversely, ROS levels in KRIT1
/
cells were reduced to near WT levels upon KRIT1 re-expression by lentiviral infection (panels c). Scale bar represents 50 μm. Notice that KRIT1
/
cells displayed the highest content of intracellular ROS, whereas the re-expression of KRIT1 caused a significant, expression level-dependent decrease in intracellular ROS levels [14]

11. Gently remove excess liquid and allow to dry overnight at room temperature in the dark to obtain a hard mount. 12. Analyze samples by confocal fluorescence microscopy. 13. Store samples at 4  C and preserve them from light.

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3.4 Qualitative Fluorescence Microscopy Analysis of Intracellular ROS

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1. Examine fluorescent cell samples on a fluorescence microscope equipped with a cooled CCD camera (e.g., Zeiss Axiovert 200 M fluorescence microscope equipped with a MicroMAX:512BFT cooled CCD camera; Princeton Instruments, Trenton, New Jersey, USA). 2. Acquire images using a microscopy automation and image analysis software (e.g., MetaMorph® Microscopy Automation & Image Analysis Software from Molecular Devices LLC; San Jose, CA, USA). Take the images with a fixed short exposure time and a high fluorescence intensity threshold value to avoid saturation (Fig. 1).

3.5 Quantitative Flow Cytometry Analysis of Intracellular ROS

1. After treatment with ROS-sensitive fluorogenic probes, resuspend cells by incubation with trypsin (1 in PBS) for 5 min in a CO2 incubator. 2. Wash suspended cells twice with PBS. 3. Immediately analyze suspended cells on a FACScan flow cytometer (e.g., Becton Dickinson, Franklin Lakes, New Jersey, USA). Intracellular ROS levels are assessed as the mean fluorescence intensity (M.F.I.) of 20 ,70 -dichlorofluorescin (DCFH) and ethidium (Eth), the oxidation products of DCFH-DA and DHE, respectively (see Note 9). 4. Analyze the DCFH green fluorescence (FL1-H channel) and Eth red fluorescence (FL2-H channel) of 10,000 cells using the Cell Quest software (Becton Dickinson) (Fig. 2).

3.6 Semiquantitative Detection of Mitochondrial Superoxide

1. Growth cells until 50–80% confluence onto coverslips distributed in 6-well plates. 2. Add the Hank’s Buffered Salt Solution and incubate for 15 min at 37  C in a CO2 incubator. 3. Wash cells twice with HBSS. 4. Counterstain with a blue fluorescent nuclear dye (Hoechst 34580). 5. Fix cells with 3.7% paraformaldehyde (see Note 10). 6. Mount glass coverslips on microscope slides with ProLongH Gold antifade reagent (Molecular Probes™, Invitrogen) before imaging. 7. Use confocal microscopy imaging and a PlanApo 63/1.40 oil immersion objective, an Ar 100 mW, 514 nm excitation laser, and a 580  30 nm fluorescence detection range (see Note 11).

3.7 Measurement of Cellular H2O2 Levels

1. Grow cells to confluence in complete medium. 2. Whenever requested, treat cells with the antioxidant Tiron at a final concentration of 5 mM for 24 h. In parallel, replace the culture medium in cells left untreated.

Andrea Perrelli and Saverio Francesco Retta

A

B

150

Counts

120 90

Key Name Ctr K-/WT

90

100 75 % M.F.I.

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K-/WT * P < 0.001; n=5

D

120 90 60

Key Name Ctr K-/K2/7 K10/6 K9/6

100 75 % M.F.I.

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Counts

0

101 102 103 104 DCFH - Fluorescence Intensity (FL1 channel)

C

0 100

*

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* *

25

30

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101 102 103 104 DCFH - Fluorescence Intensity (FL1 channel)

K-/- K2/7 K10/6 K9/6 * P < 0.001; n=5

F

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Key Name Ctr K-/WT K9/6

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35

* *

50 25

30 0 100

100

% M.F.I.

E

Counts

*

50

0

101 102 103 104 DCHF - Fluorescence Intensity (FL2 channel)

K-/WT K9/6 * P < 0.001; n=12

Fig. 2 Quantitative determination of the steady-state levels of intracellular ROS by FACS analysis. Wild-type (WT), KRIT1
/
(K
/
), and three distinct KRIT1
/
cell populations re-expressing KRIT1 at low, medium, and high levels, respectively, Lv-KRIT1 2/7 (K2/7), 10/6 (K10/6), and 9/6 (K9/6), were grown under standard conditions and analyzed by FACS 20 min after the addition of the DCFH-DA (a–d) or DHE (e, f) probes. Representative flow cytometry profiles (a, c, e) and quantitative histograms of the mean fluorescence intensity (M.F.I.) values (b, d, f) of n  5 independent FACS experiments are shown. M.F.I. values were normalized to spontaneous fluorescence of control cells untreated with the fluorogenic probes (Ctr) and expressed as percentage of KRIT1
/
(K
/
) cells (SD). ∗P < 0.001 versus KRIT1
/
cells. Notice that KRIT1
/
cells displayed the highest content of intracellular ROS, whereas the re-expression of KRIT1 caused a significant, expression level-dependent decrease in intracellular ROS levels [14]

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Fig. 3 KRIT1 silencing results in increased H2O2 levels both in MEF and in hBMEC cells. (a) H2O2 levels in wildtype (K+/+), KRIT1
/
(K
/
), and KRIT1
/
re-expressing KRIT1 (K9/6) MEF cells left untreated or treated with the antioxidant Tiron (Tir; 5 mM for 24 h). (b) H2O2 levels in human brain microvascular endothelial cells (hBMEC) transfected with either KRIT1-targeting siRNA (siKRIT1) or a scrambled control (siCTR). Cell extracts containing equal amounts of proteins were analyzed by the Amplex® Red Hydrogen Peroxide/Peroxidase Assay Kit for assessment of H2O2 levels. Fluorescence intensities of the resorufin oxidation product, measured by a microplate reader 30 min after the initiation of the reaction, were expressed in arbitrary units and referred to as H2O2 levels relative to the average value of either K9/6 MEF or siCTR hBMEC control cells. Notice that KRIT1 silencing led to a significant increase in H2O2 levels both in MEF and in hBMEC cells [16]

3. Remove medium and wash the cells twice with 1 PBS. 4. Lyse cells in 250 μL of RIPA buffer for 30 min, then scrape the cell lysate and collect it in a centrifuge tube. 5. Centrifuge the cell lysate at 13,000  g for 20 min in a centrifuge refrigerated at 4  C, then collect the supernatants. 6. Quantify total protein extracts in the cell supernatants using the Bradford reagent 1 diluted in distilled H2O, mixing 5 μL of extract and 995 μL of Bradford 1 for each sample. 7. In 96-well microplates, add cell extracts supernatants containing an equal amount of proteins (35 μg) according to quantification. 8. Add 100 μM Amplex® Red reagent and 0.2 U/mL HRP in 1X reaction buffer to each well of 96-well microplates containing protein extract. 9. Incubate 96-well microplates for 30 min at room temperature to run the H2O2 assay. 10. Measure the fluorescence intensity of the oxidation product, resofurin, with a microplate reader (BioTek Instruments, Inc., USA) using excitation at 530 nm and fluorescence detection at 595 nm (Fig. 3, see Note 12).

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Notes 1. PFA should always be handled under a chemical fume hood! PFA solutions can emit formaldehyde gas, a known human carcinogen, and can irritate the eyes and skin. 2. If you mount samples using reagents that are not supplied with DAPI or Hoechst, before mounting you have to perform the nuclear staining according to the manufacturer’s instruction. Generally, DAPI or Hoechst are diluted in PBS, and you have to stain the cells with the selected solution, and wash the cells with PBS after some minutes. 3. More specific measurements of mitochondrial O2˙
and H2O2 levels in the cellular models can be performed using the superoxide indicator MitoSOX™ Red and the H2O2 sensor pHyPerdMito (mt-HyPer probe) [20]. 4. Pay attention to separate individual coverslips from one another before placing them into a glass containing the acid solution. It is important that the coverslips are not sticking together. This helps cells and coatings stick to glass. It also improves your images by reducing spots on the glass. 5. It is very important that coverslips used in fluorescence microscopy are very clean. Although they look clean, they may have a thin film of grease that will prevent culture cells to adhere well and will affect fluorescent images. 6. You may alternatively sterilize coverslips using autoclave, and then let them dry before using, or flame them with Bunsen burner under laminar flow hood (in this case, you have to be careful not to break the coverslips with the flame). 7. As alternative methods, you can also incubate cells with H2DCF-DA at a final concentration of 5 μM in PBS at 37  C for 30 min, and then analyze by image-based cytometry with a Tali® Image-Based Cytometer (Invitrogen, California, USA). Therefore, you have to process obtained raw data using Flowing software (v.2.5.0, by Purttu Terho) [16, 17]. 8. It would be better to fix samples for 10 min on ice than at room temperature, and the PFA have to cover completely the cells. All work with PFA solutions must be done in a chemical fume hood. 9. Following cleavage of the acetate groups by intracellular esterases, the resultant dichlorofluorescin is trapped intracellularly due to its hydrophilicity, and oxidized by various ROS/RNS to form the highly fluorescent 20 ,70 -dichlorofluorescein, which serves as an effective indicator of generalized cellular oxidative stress.

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10. As an alternative to cell fixation, you can analyze living cells plated on glass bottom multiwell plates suitable for optical imaging, and immediately acquiring images. 11. Instrument parameters for sequential image acquisition, including pinhole diameter, laser intensity, exposure time, PMT gain, and offset, were set and held constant to minimize autofluorescence and for comparison between samples. 12. When you perform the Amplex® Red reagent assay to analyze cellular H2O2 levels, you have to subtract the background fluorescence, determined for a no-HRP control reaction, from each value.

Acknowledgments This work was supported by the Telethon Foundation (grant GGP15219/Coordinator to S.F.R.), the Fondazione CRT (project grant “Cerebro-NGS.TO” to S.F.R.), and the Universita` degli Studi di Torino (Local Research Funding 2016-19 to S.F.R.). The authors wish to gratefully acknowledge the Italian Research Network for Cerebral Cavernous Malformation (CCM Italia, https://www.ccmitalia.unito.it), the Associazione Italiana Angiomi Cavernosi (AIAC) Onlus, including its president Massimo Chiesa, and Santina Barbaro and Paola Neri for fundamental collaboration and assistance. This chapter is dedicated to the memory of Rosa Giunta, Fortunato Barbaro and Adelia Frison. References 1. Goitre L, Pergolizzi B, Ferro E, Trabalzini L, Retta SF (2012) Molecular crosstalk between integrins and cadherins: do reactive oxygen species set the talk? J Signal Transduct 2012:807682 2. Ferro E, Goitre L, Baldini E, Retta SF, Trabalzini L (2014) Ras GTPases are both regulators and effectors of redox agents. Methods Mol Biol 1120:55–74 3. Retta SF, Chiarugi P, Trabalzini L, Pinton P, Belkin AM (2012) Reactive oxygen species: friends and foes of signal transduction. J Signal Transduct 2012:534029 4. Sies H (2017) Hydrogen peroxide as a central redox signaling molecule in physiological oxidative stress: oxidative eustress. Redox Biol 11:613–619 5. Sies H, Berndt C, Jones DP (2017) Oxidative Stress. Annu Rev Biochem 86:715–748 6. Yamakura F, Ikeda K (2006) Modification of tryptophan and tryptophan residues in proteins by reactive nitrogen species. Nitric Oxide 14:152–161

7. Hancock JT (2009) The role of redox mechanisms in cell signalling. Mol Biotechnol 43:162–166 8. Chrissobolis S, Faraci FM (2008) The role of oxidative stress and NADPH oxidase in cerebrovascular disease. Trends Mol Med 14:495–502 9. Valko M, Leibfritz D, Moncol J, Cronin MT, Mazur M, Telser J (2007) Free radicals and antioxidants in normal physiological functions and human disease. Int J Biochem Cell Biol 39:44–84 10. Retta SF, Glading AJ (2016) Oxidative stress and inflammation in cerebral cavernous malformation disease pathogenesis: two sides of the same coin. Int J Biochem Cell Biol 81:254–270 11. Batra S, Lin D, Recinos PF, Zhang J, Rigamonti D (2009) Cavernous malformations: natural history, diagnosis and treatment. Nat Rev Neurol 5:659–670 12. Gault J, Sarin H, Awadallah NA, Shenkar R, Awad IA (2004) Pathobiology of human

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cerebrovascular malformations: basic mechanisms and clinical relevance. Neurosurgery 55:1–16. discussion 16–17 13. Choquet H, Pawlikowska L, Lawton MT, Kim H (2015) Genetics of cerebral cavernous malformations: current status and future prospects. J Neurosurg Sci 59:211–220 14. Goitre L, Balzac F, Degani S, Degan P, Marchi S, Pinton P, Retta SF (2010) KRIT1 regulates the homeostasis of intracellular reactive oxygen species. PLoS One 5:e11786 15. Goitre L, De Luca E, Braggion S, Trapani E, Guglielmotto M, Biasi F, Forni M, Moglia A, Trabalzini L, Retta SF (2014) KRIT1 loss of function causes a ROS-dependent upregulation of c-Jun. Free Radic Biol Med 68:134–147 16. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Fornelli C, Retta F, Cassoni P, Talesa VN, Retta SF (2018) Data in support of sustained upregulation of adaptive redox homeostasis mechanisms caused by KRIT1 loss-offunction. Data Brief 16:929–938 17. Antognelli C, Trapani E, Delle Monache S, Perrelli A, Daga M, Pizzimenti S, Barrera G, Cassoni P, Angelucci A, Trabalzini L, Talesa VN, Goitre L, Retta SF (2018) KRIT1 lossof-function induces a chronic Nrf2-mediated adaptive homeostasis that sensitizes cells to oxidative stress: implication for cerebral cavernous malformation disease. Free Radic Biol Med 115:202–218 18. Choquet H, Trapani E, Goitre L, Trabalzini L, Akers A, Fontanella M, Hart BL, Morrison LA, Pawlikowska L, Kim H, Retta SF (2016) Cytochrome P450 and matrix metalloproteinase genetic modifiers of disease severity in Cerebral Cavernous Malformation type 1. Free Radic Biol Med 92:100–109 19. Goitre L, DiStefano PV, Moglia A, Nobiletti N, Baldini E, Trabalzini L, Keubel J, Trapani E, Shuvaev VV, Muzykantov VR, Sarelius IH, Retta SF, Glading AJ (2017) Up-regulation of NADPH oxidase-mediated redox signaling contributes to the loss of barrier function in KRIT1 deficient endothelium. Sci Rep 7:8296 20. Marchi S, Corricelli M, Trapani E, Bravi L, Pittaro A, Delle Monache S, Ferroni L, Patergnani S, Missiroli S, Goitre L, Trabalzini L, Rimessi A, Giorgi C, Zavan B, Cassoni P, Dejana E, Retta SF, Pinton P (2015) Defective autophagy is a key feature of cerebral cavernous malformations. EMBO Mol Med 7:1403–1417 21. Trapani E, Retta SF (2015) Cerebral cavernous malformation (CCM) disease: from monogenic forms to genetic susceptibility factors. J Neurosurg Sci 59:201–209

22. Marchi S, Trapani E, Corricelli M, Goitre L, Pinton P, Retta SF (2016) Beyond multiple mechanisms and a unique drug: defective autophagy as pivotal player in cerebral cavernous malformation pathogenesis and implications for targeted therapies. Rare Dis 4: e1142640 23. Marchi S, Retta SF, Pinton P (2016) Cellular processes underlying cerebral cavernous malformations: autophagy as another point of view. Autophagy 12:424–425 24. Cianfruglia L, Perrelli A, Fornelli C, Magini A, Gorbi S, Salzano AM, Antognelli C, Retta F, Benedetti V, Cassoni P, Emiliani C, Principato G, Scaloni A, Armeni T, Retta SF (2019) KRIT1 Loss-of-function associated with cerebral cavernous malformation disease leads to enhanced. Antioxidants (Basel) 8 25. Vieceli Dalla Sega F, Mastrocola R, Aquila G, Fortini F, Fornelli C, Zotta A, Cento AS, Perrelli A, Boda E, Pannuti A, Marchi S, Pinton P, Ferrari R, Rizzo P, Retta SF (2019) KRIT1 deficiency promotes aortic endothelial dysfunction. Int J Mol Sci 20(19) 26. Antognelli C, Perrelli A, Armeni T, Talesa VN, Retta SF (2020) Dicarbonyl stress and S-Glutathionylation in cerebrovascular diseases: A focus on cerebral cavernous malformations. Antioxidants 9(2):124 27. Gibson CC, Zhu W, Davis CT, BowmanKirigin JA, Chan AC, Ling J, Walker AE, Goitre L, Delle Monache S, Retta SF, Shiu YT, Grossmann AH, Thomas KR, Donato AJ, Lesniewski LA, Whitehead KJ, Li DY (2015) Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131:289–299 28. Moglia A, Goitre L, Gianoglio S, Baldini E, Trapani E, Genre A, Scattina A, Dondo G, Trabalzini L, Beekwilder J, Retta SF (2015) Evaluation of the bioactive properties of avenanthramide analogs produced in recombinant yeast. Biofactors 41:15–27 29. Perrelli A, Goitre L, Salzano AM, Moglia A, Scaloni A, Retta SF (2018) Biological activities, health benefits, and therapeutic properties of avenanthramides: from skin protection to prevention and treatment of cerebrovascular diseases. Oxidative Med Cell Longev 2018:6015351 30. De Luca E, Pedone D, Moglianetti M, Pulcini D, Perrelli A, Retta SF, Pompa PP (2018) Multifunctional platinum@BSA–rapamycin nanocarriers for the combinatorial therapy of cerebral cavernous malformation. ACS Omega 3(11):15389–15398 31. Moglianetti M, Pedone D, Udayan G, Retta SF, Debellis D, Marotta R, Turco A, Rella S,

Detecting ROS in Cellular Models of CCM Disease Malitesta C, Bonacucina G, De Luca E, Pompa PP (2020) Intracellular antioxidant activity of biocompatible citrate-capped palladium nanozymes. Nanomaterials 10(1):99 32. Winterbourn CC (2014) The challenges of using fluorescent probes to detect and quantify specific reactive oxygen species in living cells. Biochim Biophys Acta 1840:730–738 33. Kalyanaraman B, Darley-Usmar V, Davies KJ, Dennery PA, Forman HJ, Grisham MB, Mann GE, Moore K, Roberts LJ, Ischiropoulos H (2012) Measuring reactive oxygen and nitrogen species with fluorescent probes: challenges and limitations. Free Radic Biol Med 52:1–6 34. Zielonka J, Vasquez-Vivar J, Kalyanaraman B (2008) Detection of 2-hydroxyethidium in

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cellular systems: a unique marker product of superoxide and hydroethidine. Nat Protoc 3:8–21 35. Gomes A, Fernandes E, Lima JL (2005) Fluorescence probes used for detection of reactive oxygen species. J Biochem Biophys Methods 65:45–80 36. Rhee SG, Chang TS, Jeong W, Kang D (2010) Methods for detection and measurement of hydrogen peroxide inside and outside of cells. Mol Cells 29:539–549 37. Miwa S, Treumann A, Bell A, Vistoli G, Nelson G, Hay S, von Zglinicki T (2016) Carboxylesterase converts Amplex red to resorufin: implications for mitochondrial H2O2 release assays. Free Radic Biol Med 90:173–183

Chapter 35 Library Preparation for Small RNA Transcriptome Sequencing in Patients Affected by Cerebral Cavernous Malformations Souvik Kar, Robert Geffers, Amir Samii, and Helmut Bertalanffy Abstract Small RNA sequencing by Illumina’s Next Generation technology has revolutionized the transcriptome analysis by facilitating massive parallel sequencing of RNA molecules at low cost. Illumina’s Next Generation RNA sequencing is ideal for profiling small RNA (microRNAs, snoRNAs, and piRNAs) libraries in the identification of novel biomarkers for better clinical diagnosis. This method offers significant advantages when compared to microarray analysis with the ability to identify novel transcripts, higher sensitivity, specificity, and detection of rare and low-abundance transcripts. Small RNAs, including microRNAs and snoRNAs, belong to the class of small non-coding RNAs with 50–200 nucleotides in length and are involved in post-transcriptional regulation of gene expression. Executing Illumina’s Next Generation Sequencing technology, we have recently deciphered microRNAs and snoRNAs expressed in cerebral cavernous malformations (CCMs). Small RNA library preparation is a prerequisite step prior to RNA sequencing for the identification of microRNAs and snoRNAs. Here, we describe stepwise small RNA library preparation starting from total RNA isolated from CCMs patient until library validation using the Illumina® TruSeq® Small RNA Sample preparation kit. We believe this method will shed light into the functional identification of other novel small non-coding RNAs in CCMs that awaits discovery. Key words Cerebral cavernous malformations, Small RNAs, Illumina, Next generation sequencing

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Introduction Cerebral cavernous malformations (CCMs) are low-flow vascular malformations affecting 0.5% of the general population [1, 2]. They comprise clusters of blood-filled sinuses (caverns) with poorly developed tight junction and adherens junction proteins [3]. CCMs patients are often clinically predisposed to severe headaches, seizures, and hemorrhages [4, 5]. Current treatment options for CCMs patients rely solely on microsurgical intervention. Therefore, alternative non-invasive treatment modalities are of utmost need.

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_35, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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Small non-coding RNAs, such as microRNAs and snoRNAs, are 8]). Also a DNase digestion step along with the RNA isolation protocol is recommended. 2. It is recommended to place the RNA 30 Adapter on ice following performing the 70  C incubation to avoid secondary structure formation. 3. The reaction buffer supplied with the T4 RNA Ligase 2 and Deletion Mutant must not be used to avoid its enzymatic activity in the ligation buffer. 4. It is recommended to place the RNA 50 Adapter on ice following performing the 70  C incubation to avoid secondary structure formation. Perform all the pipetting steps on ice. 5. Freeze the remaining 50 and 30 adapter-ligated RNA at 80  C for up to 1 week. 6. For each individual reaction, only one of the 48 RNA PCR Primer indexes is used during the PCR amplification step. 7. Depending on the quantity of RNA input, type of tissue, and species, the amplification products may vary. As this protocol is validated with 1 μg of total RNA from mouse and human brain, in case of formation of indistinct bands, the PCR cycle number can be adjusted to a maximum of 15 cycles.

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8. Generally, the bands 147 nt and 157 nt are placed in a single slice and are deep sequenced; however, the gel can be analyzed for a better resolution of sequencing results. 9. The precipitation mix can be stored for a maximum of 30 min at 80  C, if required. 10. If the pellet becomes loose, then centrifuge once again at 20,000  g at room temperature for 2 min. 11. To carry out clustering, use the total of all the molarities of the peaks that is generated from the Agilent Bioanalyzer 2100. For example, if there are three peaks, add the molarities of the three peaks together. References 1. Fisher OS, Zhang R, Li X, Murphy JW, Demeler B, Boggon TJ (2013) Structural studies of cerebral cavernous malformations 2 (CCM2) reveal a folded helical domain at its C-terminus. FEBS Lett 587(3):272–277 2. Kar S, Bali KK, Baisantry A, Geffers R, Samii A, Bertalanffy H (2017) Genome-wide sequencing reveals microRNAs downregulated in cerebral cavernous malformations. J Mol Neurosci 61(2):178–188 3. Schneider H, Errede M, Ulrich NH, Virgintino D, Frei K, Bertalanffy H (2011) Impairment of tight junctions and glucose transport in endothelial cells of human cerebral cavernous malformations. J Neuropathol Exp Neurol 70(6):417–429 4. Kar S, Bali KK, Baisantry A, Geffers R, Hartmann C, Samii A, Bertalanffy H (2018) Genome-wide sequencing reveals small nucleolar RNAs downregulated in cerebral cavernous malformations. Cell Mol Neurobiol 38 (7):1369–1382 5. Koskimaki J, Girard R, Li Y, Saadat L, Zeineddine HA, Lightle R, Moore T, Lyne S, Avner K, Shenkar R, Cao Y, Shi C, Polster SP, Zhang D, Carrion-Penagos J, Romanos S, Fonseca G, Lopez-Ramirez MA, Chapman EM, Popiel E, Tang AT, Akers A, Faber P, Andrade J, Ginsberg M, Derry WB, Kahn ML, Marchuk DA, Awad IA (2019) Comprehensive transcriptome analysis of cerebral cavernous malformation across multiple species and genotypes. JCI Insight 4(3) 6. Bai Y, Zhang Z, Jin L, Kang H, Zhu Y, Zhang L, Li X, Ma F, Zhao L, Shi B, Li J, McManus DP, Zhang W, Wang S (2014) Genome-wide sequencing of small RNAs reveals a tissue-specific loss of conserved

microRNA families in Echinococcus granulosus. BMC Genomics 15:736 7. Shore S, Henderson JM, Lebedev A, Salcedo MP, Zon G, McCaffrey AP, Paul N, Hogrefe RI (2016) Small RNA library preparation method for next-generation sequencing using chemical modifications to prevent adapter dimer formation. PLoS One 11(11):e0167009 8. Moore LM, Kivinen V, Liu Y, Annala M, Cogdell D, Liu X, Liu CG, Sawaya R, Yli-Harja O, Shmulevich I, Fuller GN, Zhang W, Nykter M (2013) Transcriptome and small RNA deep sequencing reveals deregulation of miRNA biogenesis in human glioma. J Pathol 229(3):449–459 9. Li P, Shen M, Gao F, Wu J, Zhang J, Teng F, Zhang C (2017) An Antagomir to microRNA106b-5p Ameliorates cerebral ischemia and reperfusion injury in rats via inhibiting apoptosis and oxidative stress. Mol Neurobiol 54 (4):2901–2921 10. Ferreira R, Santos T, Amar A, Tahara SM, Chen TC, Giannotta SL, Hofman FM (2014) MicroRNA-18a improves human cerebral arteriovenous malformation endothelial cell function. Stroke 45(1):293–297 11. Orso F, Balzac F, Marino M, Lembo A, Retta SF, Taverna D (2013) miR-21 coordinates tumor growth and modulates KRIT1 levels. Biochem Biophys Res Commun 438(1):90–96 12. Yeri A, Courtright A, Danielson K, Hutchins E, Alsop E, Carlson E, Hsieh M, Ziegler O, Das A, Shah RV, Rozowsky J, Das S, Van Keuren-Jensen K (2018) Evaluation of commercially available small RNASeq library preparation kits using low input RNA. BMC Genomics 19(1):331

Chapter 36 Affinity Purification and Preparation of Peptides for Mass Spectrometry from C. elegans Evelyn Popiel and William Brent Derry Abstract Affinity purification of a target protein followed by mass spectrometry of the purified peptides can be used to identify physical interactors of the protein of interest. Using this biochemical approach on proteins from whole organisms such as C. elegans can reveal novel in vivo protein interactions that cannot be identified using homology-based predictions or in vitro approaches. Here we describe affinity purification of a GFP-tagged target protein from whole worm lysates, digestion of the purified proteins into peptides, and preparation of the peptides for analysis by mass spectrometry. This protocol has been optimized for ChromoTek GFP-Trap® Magnetic Agarose beads, but it may be used with other tags and antibodyconjugated beads. Key words Affinity purification, Coimmunoprecipitation, Mass spectrometry, Protein interactions, Physical interactions, Peptide sequencing, C. elegans

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Introduction Affinity purification of a protein of interest followed by mass spectrometry is an unbiased approach to identify its physical interactors. The ease of adding fluorescent protein or epitope tag sequences at any gene locus through CRISPR/Cas9 genome editing allows for the immunoprecipitation of a protein even if antibodies to it are not available. Many systems for the purification of GFP- and FLAGtagged proteins are commercially available. Before performing any experiments with a tagged protein, it is important to validate that the addition of the tag has not interfered with the function of the protein. Performing affinity purification of a target protein using whole worm lysates can identify protein-protein interactions in their in vivo context, which may be more biologically relevant than interactions identified using in vitro or computational methods. By expressing the tagged protein of interest in specific tissues it

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7_36, © Springer Science+Business Media, LLC, part of Springer Nature 2020

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may also be possible to identify protein-protein interactions in a tissue-specific manner. The limitations of affinity purification should also be considered before using this technique to identify binding partners of a specific protein. Affinity purification is often unable to identify binding partners with transient or weak interactions with the target protein. For interactions of this nature a proximity-based assay such as BioID/TurboID followed by mass spectrometry are more suitable [1]. For target proteins of low abundance, it may not be possible to isolate enough protein from worm lysates for analysis by mass spectrometry. For these proteins it may be necessary to use a more appropriate in vitro approach such as overexpression in cell culture to identify binding partners using affinity purification followed by mass spectrometry.

2

Materials

2.1 Growing Worm Population for Affinity Purification

Prepare all solutions using ultrapure water (resistivity of 18.2 MΩ cm at 25  C) and sterile technique. 1. M9 buffer: Combine 3 g of KH2HPO4, 6 g of Na2HPO4, and 5 g of NaCl in 1 L H2O. Autoclave for 20 min. Add 1 mL of 1 M MgSO4. 2. Terrific broth (TB): Combine 47.6 g of TB powder and 4 mL of glycerol in H2O to 1 L. Autoclave for 30 min. 3. LB: Combine 10 g of tryptone, 5 g of yeast extract, 10 g of NaCl, and H2O to 1 L. Autoclave for 30 min. 4. Nematode Growth Medium (NGM) agar plates seeded with OP50 strain E. coli: Combine 3 g of NaCl, 2.5 g of peptone, 20 g of agar, and H2O to 1 L. Autoclave for 1 h. Let cool for 1 h in a 55  C water bath. Add 1 mL of cholesterol (5 mg/mL in ethanol), 1 mL of 1 M CaCl2, 1 mL of 1 M MgSO4, and 25 mL of 1 M KPO4 buffer pH 6.0, mixing after each addition. Using an automated plate pourer, pour NGM into sterile plastic plates to set. Keep NGM on a hot plate with a rotating magnetic stir bar to prevent it from solidifying while pouring. Allow plates to set at room temperature. Seed each plate with 1 mL of OP50 E. coli culture using a glass pipette and spread with a glass spreader. Allow bacterial lawn to dry at room temperature. Store plates at 4  C for up to 1 month. 5. OP50 E. coli culture: Inoculate 500 mL of LB with OP50 strain E. coli using sterile technique. Incubate at 37  C overnight. 6. Concentrated OP50 E. coli culture: Inoculate 50 mL of LB with OP50 strain E. coli and grow at 37  C on an orbital shaker at 1  g overnight. Inoculate 500 mL of TB with 50 mL of

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OP50 culture in LB and grow at 37  C on an orbital shaker at 1  g overnight. Centrifuge 500 mL of OP50 culture at 3220  g for 10 min at 4  C. Discard supernatant and dissolve the pellet in 5 volume of M9 buffer. 7. Bleaching solution: Mix 2.5 mL of 100% bleach, 4 mL of 1 M NaOH, and 13.5 mL of H2O. Prepare fresh for each use. 2.2 Affinity Purification with Magnetic Antibody Conjugated Beads

1. Droso base buffer: 30 mM HEPES, 100 mM potassium acetate, 2 mM magnesium acetate. Filter sterilize and store at 4  C. 2. Droso base buffer + NP-40 + DTT: Droso base buffer, 0.1% NP-40 (or IGEPAL), 2 mM dithiothreitol (DTT). Make the day of affinity purification and keep on ice. 3. Complete Droso buffer: Droso base buffer + NP-40 + DTT, 1 tablet/5 mL protease inhibitor (Roche), 1:100 Sigma Phosphatase Inhibitor 2, 1:100 Sigma Phosphatase Inhibitor 3. Make the day of affinity purification and keep on ice. 4. Dounce homogenizer. 5. RNase away (or other surface decontaminant to eliminate RNases). 6. ChromoTek GFP-Trap® Magnetic Agarose beads (other commercially available affinity purification systems can be used) and a magnetic separation rack.

2.3 Elution of Proteins

1. 0.5 M Ammonium hydroxide (pH > 10): Prepare solution the day of the experiment. 200 μL of solution is needed per sample. 2. Vacuum dryer apparatus.

2.4 Denaturation and Digestion of Proteins

1. 50 mM Triethyl ammonium bicarbonate (TEAB) buffer: Prepare solution the same day as the experiment. Make 44 μL per sample and keep on ice. 2. 0.5 M Tris(2-carboxyethyl) phosphine hydrochloride (TCEPHCl): Prepare solution the day of the experiment. Make 1 μL per sample and keep on ice. 3. 1 mg/mL Trypsin: Dissolve trypsin in 1 mM HCl. Keep on ice. Solution can be stored at 80  C. 4. 100 mM iodoacetamide: Prepare solution the day of the experiment. Aliquot a small amount of iodoacetamide powder into a pre-weighed Eppendorf tube (iodoacetamide is very light sensitive, so cover tube with foil immediately after weighing). Calculate the amount of RNase-free H2O that will need to be added for a concentration of 100 mM (19 mg/mL), keeping in mind that 5 μL of 100 mM iodoacetamide will be needed for each sample. Make 100 mM iodoacetamide after the 30-min incubation of samples in TEAB buffer and TCEP-HCl at 55  C (step 2 in Subheading 3.4).

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2.5 Concentrating and Purifying Digested Peptides

1. 100% Acetonitrile (ACN). 2. 1% Trifluoroacetic acid (TFA). 3. 50% ACN + 1% TFA. 4. Millipore® ZipTips C18 (or other commercially available pipette tip columns for protein concentration and purification).

3

Methods

3.1 Preparing Worm Pellet Samples

1. Grow synchronized worms on 4 large (10 cm diameter) NGM plates seeded with OP50. When the worms on the 4 large NGM plates reach gravid adult stage and many eggs have been laid on the plate, add 3 mL of bleaching solution to each plate so the worms are completely immersed and use a glass scraper to ensure that all the eggs are freed from the bacterial lawn. Incubate worms in bleach solution for 3 min at room temperature. Pipette the worms and eggs in solution into a Falcon tube, scraping the plate with a glass pipette to ensure that eggs are not left behind. Centrifuge Falcon tubes at 367  g for 1 min. The bleaching solution will dissolve the bodies of larvae and adult worms but will not dissolve the eggs. Aspirate the supernatant, taking care to not disturb the pelleted worms and eggs. Add 3 mL bleaching solution and shake or vortex the tube for 1 min to dissolve any remaining adults. Centrifuge the tubes at 367  g for 1 min, then aspirate the supernatant to remove as much of the bleaching solution as possible without disturbing the pelleted eggs. Add 3 mL of M9 buffer. Centrifuge the tubes at 367  g for 1 min, then aspirate the supernatant taking care to not disturb the pelleted eggs. Repeat this washing with M9 buffer 2–5 times to remove all traces of the bleaching solution and remaining worm carcasses. Resuspend the embryos in 3 mL of M9 and put the Falcon tubes on a rocker or rotator at room temperature overnight to allow the embryos to hatch. Pipette ~12,000 L1s/plate onto large NGM plates with concentrated OP50 E. coli. 2. When this population reaches young adult stage, wash the worms off the plates using M9 buffer and transfer to a Falcon tube. To maximize the number of worms collected, use the tip of a glass pipette to scrape the plates and filtered pipette tips to collect the worms. 3. Wash the worms to remove E. coli by adding 10 mL M9 buffer to the Falcon tube and place on a rocker at room temperature for 30 min. Next, centrifuge at 805  g for 2 min and remove the supernatant (see Note 1). Repeat the wash with M9 buffer at least once more, until the sample is no longer cloudy.

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4. Wash the sample twice in autoclaved distilled H2O to remove the salts left behind by the M9 buffer. Remove as much liquid from the sample as possible; the final worm pellet should be at least 1 mL (~10 mg of protein for mass spectrometry). 5. Flash freeze the sample in dry ice and ethanol or liquid nitrogen. Store at 80  C. 3.2 Affinity Purification with Magnetic Antibody Conjugated Beads

1. Clean Dounce homogenizer thoroughly with soap, RNAse Away, and H2O. Chill on ice. 2. Thaw the worm pellet on ice. Add an equal volume of precooled complete Droso buffer to the thawed worm pellet. 3. Pipette the dissolved worm pellet in complete Droso buffer into the cooled Dounce homogenizer and homogenize on ice. After every 25–50 Dounce cycles check 1 μL of the sample on a slide using a compound light microscope to check the consistency. Continue to homogenize sample until no worm fragments or embryos remain (see Note 2). After Douncing, transfer the sample to a chilled Eppendorf tube, keeping sample on ice. 4. Spin the homogenized lysate at 10,000  g for 30 min at 4  C. Save the supernatant in a new chilled Eppendorf tube. Check supernatant protein concentration using a microplate reader or other equipment. 5. Wash 50 μL GFP-trap magnetic beads per sample 3 times in complete Droso buffer to equilibrate them, keeping the beads in buffer after final wash to prevent them from drying out. Incubate 50 μL equilibrated GFP-Trap Magnetic Agarose beads with 10 mg of protein for each sample in a volume of about 500 μL (volume can be adjusted by adding complete Droso buffer). Place samples on rocker at 4  C for 2 h. 6. Wash the beads 5 times, each time for 3 min at 4  C on rocker. Wash 1–2 times with complete Droso buffer. Next wash 2–3 times with Droso base buffer + NP-40 + DDT. Perform final wash with Droso base duffer (without NP-40 + DTT; these detergents are not compatible with mass spectrometry analysis, so they must be removed by the final wash). Take care to not lose any beads during these washes. At this step the sample cannot be stored; the proteins must be eluted first.

3.3 Elution of Proteins

1. Centrifuge samples at 92  g for 30 seconds to collect all the sample in the bottom of the Eppendorf tube. 2. Elute proteins from beads by adding 50 μL 0.5 M ammonium hydroxide to the sample and incubate at room temperature for 5 min in a shaker at 112  g. Transfer the eluent to a fresh Eppendorf tube. Repeat the elution 3 times with new 50 μL volumes of 0.5 M ammonium hydroxide. The final volume of

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eluted sample will be 200 μL (see Note 3). Samples may be stored at – 20  C for a few days at this step, but the sample is more stable for storage after vacuum drying. 3. Desiccate protein samples using a vacuum dryer. Use a manual setting with the temperature set to 35  C and check samples after 1 h (do not allow sample to over dry as this can damage the sample). The dry protein samples can be stored at – 80  C. 3.4 Denaturation and Digestion of Proteins

1. Add 44 μL of 50 mM TEAB buffer and 1 μL of 0.5 M TCEPHCl on ice to each sample and vortex quickly. 2. Determine pH of samples using a pH meter; optimal pH for trypsin digest is 9. If the pH is too low, adjust by adding TRISbase. Incubate samples on shaker at 55  g at 55  C for 30 min. While the samples are incubating, weigh out iodoacetamide powder (see item 4 of Subheading 2.4). 3. After the 30 min incubation of samples in TEAB buffer and TCEP-HCl at 55  C, allow the samples to cool to room temperature. Once samples have cooled, add RNase-free H2O to iodoacetamide powder to make 100 mM iodoacetamide. Add 5 μL 100 mM iodoacetamide solution to each sample and incubate at room temperature in the dark for 30 min, on a rotator if possible. 4. Expose samples to light for 30 min at room temperature to breakdown the iodoacetamide. 5. Add 1 μL 1 mg/mL trypsin to samples to digest proteins into peptides. Place samples on shaker at 1  g at 37  C overnight.

3.5 Concentrating and Purifying Digested Peptides

This step uses commercially available Millipore® ZipTips C18. Other methods of concentrating and purifying samples for mass spectrometry are also available. Set aside 8 μL per sample of 50% ACN (acetonitrile) + 1% TFA for elution in individual Eppendorf tubes. 1. To equilibrate a ZipTip aspirate 10 μL 100% ACN (wetting solution) with ZipTip. Repeat twice, dispensing waste between washes. Next aspirate 10 μL 50% + 1% TFA (wetting/equilibration solution) with ZipTip. Repeat twice, dispensing waste between washes. Finally, aspirate 10 μL 1% TFA (washing solution) with ZipTip. Repeat twice, dispensing waste between washes. 2. To bind peptides and wash the samples aspirate 10 μL of sample into ZipTip and dispense into the cap of a new Eppendorf tube. Repeat 3 times, dispensing into the bottom of tube after third time. Repeat this process for entire sample. Pipette the entire sample 20 times to ensure all the peptides are bound to

Affinity Purification and Preparation of Peptides from C. elegans

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the ZipTip. Wash the bound peptides by aspirating and dispensing 10 μL of 1% TFA. Repeat twice. 3. To elute the purified peptides, take an 8 μL aliquot of 50% ACN + 1% TFA and pipette up and down in the ZipTip ten times. 4. Once eluted, vacuum dry the sample (see step 3 of Subheading 3.3). At the end of this protocol the peptide samples are prepared for mass spectrometry. Theory and methods for peptide sequencing by mass spectrometry have been comprehensively reviewed [2, 3].

4

Notes 1. If the sample contains many L1s and embryos, allow it to settle for 5 min and remove supernatant instead of centrifuging (L1s and embryos will remain in supernatant while adults sink to the bottom). 2. While Dounce homogenizing sample, rest every 50 repetitions to prevent it from heating up. Optimal consistency is usually achieved after 100–150 repetitions. Between samples, thoroughly clean the homogenizer using cold water and liquid soap. After cleaning, rinse with reverse osmosis water and dry. Ensure homogenizer is chilled on ice before next use. 3. After elution, 10 μL of sample can be saved for western blotting. Add 10 μL 2 SDS-PAGE buffer to sample and boil at 95  C for 5 min before storing sample at 20  C. Repeat boiling at 95  C for 5 min before running sample on gel.

References 1. Branon TC, Bosch JA, Sanchez AD et al (2018) Efficient proximity labeling in living cells and organisms with TurboID. Nat Biotech 36:880–887 2. Steen H, Mann M (2004) The abc’s (and xyz’s) of peptide sequencing. Nat Rev Mol Cell Biol 5:699–711

3. Hesketh GG, Youn JY, Samavarchi-Tehrani P et al (2017) Parallel exploration of interaction space by BioID and affinity purification coupled to mass spectrometry. In: Comai L, Katz J, Mallick P (eds) Proteomics. MIMB vol 1550. Humana Press, New York

INDEX A Activated protein C (APC) ........................................... 140 Actomyosin cytoskeleton .............................402–404, 409 Acute hemorrhage........................................................... 90 Acute neurologic symptoms ........................................... 85 Adherens junctions ....................................................... 404 Affinity protein chromatography......................... 313, 319 Affinity purification ....................................................... 479 Affymetrix Axiom® .......................................................... 78 Alt-R CRISPR/Cas9-mediated genome editing ........ 172 Amplex® Red hydrogen peroxide/peroxidase assay .............................................................. 461 Angiogenesis................................... 12, 16, 235, 427–430 Angiogenesis process .................................................... 378 Angiogenic assays .......................................................... 378 Ankyrin repeat domain (ARD)..................................... 292 ANNOVAR annotations................................................. 69 Anterior interhemispheric approach ............................ 118 Anteroinferior basal ganglia SCIF......................................................................... 120 Aortic ring assay ................................................... 236, 237 Apoptosis ....................................................................... 246 Apparent diffusion coefficient (ADC) ........................... 89 ApproachViewer software ............................................. 114 Arterial hypertensive ....................................................... 99 Autophagosomes........................................................... 418 Autopsy studies ............................................................... 28

B Bait dependency test ..................................................... 362 Bait protein expression ................................................. 281 Beer’s law....................................................................... 446 Blood–brain barrier (BBB) ......................... 228, 234, 259 Bone morphogenetic protein 6 (BMP6) ..................... 275 Bone morphogenic protein (BMP) signaling.............. 427 Bovine serum albumin (BSA).............144, 145, 147, 262 Boyden chamber assay ......................................... 379, 380 Brain microvascular endothelial cells (BMEC) CCM genes.............................................................. 145 cell passage solutions .............................................. 143 experiments .................................................... 143–144 general materials...................................................... 142 isolation ................................................. 141, 142, 144 Krit1 and Pdcd10 mRNA expression ........... 145–147 loxP-flanked Krit1 exon 5 ...................................... 141

loxP-flanked Pdcd10 exon 4 and 5........................ 141 media and reagents ................................................. 143 medium.................................................................... 143 purification ..................................................... 140, 141 time-controlled genetic inactivation ............ 140, 141, 145, 147 tissue homogenization ................................... 144–145 Brainstem extended retrosigmoid approach............................ 121 medial transpetrosal approach ................................ 122 retromastoid craniotomy ........................................ 123 SCIT approach ........................................................ 120 TCTC approach ...................................................... 121 transsylvian .............................................................. 120 Brainstem CMs clinical series .............................................................. 41 GOS ........................................................................... 41 hemorrhage and rehemorrhage................................ 40 meta-analysis.............................................................. 40 signs and symptoms .................................................. 41 Branching index ............................................................ 374

C Caenorhabditis elegans CRISPR-Cas9 gene editing .................................... 192 CRISPR method ..................................................... 192 EMS mutagenesis.................................................... 193 genetic screens......................................................... 193 high-throughput screening .................................... 193 invertebrate organisms............................................ 191 materials EMS ................................................................... 195 excretory canal................................................... 194 L1 survival ......................................................... 194 RNP ................................................................... 194 methods dominant mutations.......................................... 200 EMS .......................................................... 199, 200 L1 worms.................................................. 196, 197 L4 stage ............................................................. 197 pharmacological suppression ............................ 200 recessive mutations............................................ 200 tracrRNA and crRNAs ...................................... 198 phenotypes............................................................... 192 RNAi screens ........................................................... 193

Lorenza Trabalzini et al. (eds.), Cerebral Cavernous Malformations (CCM): Methods and Protocols, Methods in Molecular Biology, vol. 2152, https://doi.org/10.1007/978-1-0716-0640-7, © Springer Science+Business Media, LLC, part of Springer Nature 2020

487

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS

488 Index

Candidate-gene approach ............................................... 78 Capillary telangiectasia (CTe)......................................... 99 Carboxy-terminal region .............................................. 272 Cardiovascular system ................................................... 215 Caspace-3 active fragment immunostaining................ 247 Caspase cleavage............................................................ 438 Cavernoma ........................................................... 151, 253 Cavernous angioma.............................................. 151, 371 Cavernous malformations (CM) ....................... 27, 35, 86 clinical cohorts .......................................................... 29 clinical presentation .................................................. 30 eloquent regions........................................................ 38 incidence .................................................................... 28 prevalence .................................................................. 28 retrospective cohort .................................................. 30 risk factors.................................................................. 29 signs and symptoms .................................................. 37 vitamin D supplementation ...................................... 31 CCM genes.................................................................... 152 CCM signaling complex (CSC) ................................... 226 bioinformatics processing ..................... 334, 340, 341 ChIP-seq data.......................................................... 333 ChIP-seq data, interactomes .................................. 328 genomics.................................................................. 326 HBMVEC................................................................ 327 HBMVEC cells, zebrafish embryos, and mouse tissue, protein extraction.................... 329, 336 HURI database ....................................................... 335 LC-MS/MS.................................................... 331, 337 pathogenesis ............................................................ 325 peptides........................................................... 329, 336 Proteomics............................................................... 326 Proteomics data, protein interactomes ................. 331, 339, 341 RNA extraction, HBMVEC cells .................. 328, 331 RNA-seg analysis, extract RNA.............................. 328 RNA-seq ................................................ 326, 329, 334 RNA-seq data, interactomes.......................... 328, 333 zebrafish embryos and mouse tissue ............. 328, 332 CCM1 ............................................................................ 191 CCM1/KRIT1 .............................................................. 453 CCM2........................................................................52, 61 CCM2 HHD crystals........................................... 297, 298 CCM2 HHD domain .......................................... 297, 298 CCM2 HHD-MEKK3 co-crystals ............................... 298 CCM2 PTB domain crystals cryoprotect .............................................................. 297 human ...................................................................... 296 ccm-2/CCM2 ................................................................ 191 ccm-3 .............................................................191–193, 198 CCM3 crystals cryoprotect .............................................................. 296 dehydrate tetragonal crystals .................................. 296 LD motif peptides ................................................... 296

AND

PROTOCOLS

orthorhombic crystals ............................................. 296 tetragonal crystals........................................... 295, 296 CCM3 crystals and co-crystals ..................................... 295 CCM-deficient cells and tissues ................................... 306 Cell–cell junctions ........................................402–404, 413 Cell contractility ................................................... 402–404 Cell culture instruments ............................................... 305 Cell culture studies........................................................ 208 Cell–ECM junctions ..................................................... 403 Cell Lysates.................................................................... 447 Cell proliferation assays................................................. 378 Cellular stress................................................................. 438 Central nervous system (CNS)................. 4, 49, 131, 151 Cerebral amyloid angiopathy (CAA) ............................. 99 Cerebral arteriovenous malformations (CAVMSs)...................................................... 99 Cerebral cavernous malformations (CCM) ..................... 3 additional ................................................................... 53 affinity protein chromatography ................... 313, 319 alleles.......................................................................... 52 autosomal dominant pattern .................................... 55 blood and cDNA analysis ........................................... 6 candidate therapies.................................................... 14 CCM3/PDCD10 ......................................................... 7 cellular and animal models ......................................... 8 chromosomal loci ........................................................ 6 clinical penetrance ..................................................... 54 Co-IP ....................................................................... 320 cytoplasmic protein lysate extractions................... 313, 318, 319 deficiencies............................................................... 311 DNA sequencing....................................................... 52 expressivity................................................................. 54 familial........................................................................ 54 families ....................................................................... 50 fCCM........................................................................... 7 gene mutations............................................................ 9 germline mutation ....................................... 49, 53, 55 immunoprecipitation ................................................ 52 label-free measurement, Protein–Protein interactions .................................314, 320–322 lesions ........................................................................ 55 mechanisms ............................................................. 311 microdissection laser capture.................................... 55 MiMB volume ............................................................. 5 mitochondria protein lysate extractions........................................... 313, 318 molecular genetic studies.......................................... 10 molecular screening .................................................. 53 mouse models............................................................ 55 MRI ............................................................................. 4 multiplex protein–lipid binding assay..................................................... 314, 321 murine model .............................................................. 8

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS mutation detection rate ............................................ 52 mutations................................................................... 50 nuclear protein lysate extractions........................................... 313, 318 PDCD10 ................................................................... 50 phenotypes................................................................. 61 physiological roles ..................................................... 11 prevalence .................................................................... 4 pro-inflammatory gut microbiota .............................. 9 protein lysates .......................................................... 312 protein–protein interactions ................................... 312 proteins .....................................................10, 311, 314 RIPA buffer ............................................................. 323 screening algorithm .................................................. 51 screening sensitivity................................................... 50 signaling..................................................................... 50 simulation point ...................................................... 111 skin ............................................................................. 49 sporadic cases............................................................. 53 structural anomalies .................................................. 52 structural studies ......................................................... 7 subcortical ............................................................... 111 surgical approach..................................................... 110 surgical indication ................................................... 111 TBST buffer or PBST buffer .................................. 323 therapeutic approaches ............................................... 5 Western blot ...........................................315–317, 321 whole cell protein lysate extractions........................................... 312, 316 Cerebral cavernous malformations type 1 (CCM1) ......................................................... 77 disease severity........................................................... 77 genetic modifiers .................................................77, 78 Cerebral cavernous malformations type 2 (CCM2) ....................................................... 292 Cerebral endothelial cells BBB .......................................................................... 259 brain tissue dissection ............................................. 263 cell culture ...................................................... 262, 264 cell isolation............................................................. 262 cell selection ............................................................ 262 cerebral microvascular endothelial cells...................................................... 263, 264 cerebrovascular diseases .......................................... 259 matrix-coated tissue culture plates ......................... 262 molecular mechanism of CCM .............................. 260 murine model .......................................................... 259 puromycin................................................................ 260 Cerebrovascular diseases ............................................... 259 Cervicomedullary junction ........................................... 117 Chemotactic agent ........................................................ 380 Chloroform assay .......................................................... 280 Clinical exome sequencing (CES).................................. 63 Clinical imaging methods

AND

PROTOCOLS Index 489

CT ........................................................................87, 89 DWI ........................................................................... 92 modalities and techniques ........................................ 86 MRI ........................................................................... 88 susceptibility sensitive sequences.............................. 91 syndrome ................................................................... 85 T1- and T2-weighted ............................................... 90 T2∗ GRE .................................................................. 91 Colorimetric assays........................................................ 378 Computed tomography (CT) ........................... 85, 87, 98 Confocal microscopy .................................................... 305 Convexity cerebellar CCMs transcortical ............................................................. 118 transvermian ............................................................ 119 Copy number variations (CNV) .................................... 54 Craniotomy ................................................................... 122 Cremaster muscle .......................................................... 388 Cremaster preparation .................................................. 394 CRISPR associated protein 9 (Cas9) ........................... 170 CRISPR-based genome editing ................................... 192 CRISPR/Cas9 genome editing ................................... 173 Cryopreserve crystals .................................................... 299 Cryoprotect CCM2 PTB domain crystals ................... 297 Crystallographic studies................................................ 292 C-terminal FERM domain ........................................... 292 Custom RNA ladder (CRL) ......................................... 469 Cytoplasmic domain-associated protein (ICAP-1) ...................................................... 273

D Dechorionate transgenic embryos ............................... 243 Deep-seated CMs lesions ........................................................................ 38 management .............................................................. 40 meta-analysis.............................................................. 39 symptoms and signs .................................................. 39 thalamic and basal ganglia ........................................ 39 Dehydrate tetragonal crystals ....................................... 296 Developing imaging research techniques ...................... 93 Developmental venous anomaly (DVA).............................. 5, 29, 36, 64, 91, 99 Diagnostic-oriented tools ............................................... 63 Dichlorofluorescein (DCF) product ............................ 454 20 ,70 -Dichlorofluorescin diacetate (DCFH-DA) ...............................454, 456–460 Diffuse axonal injury (DAI) ........................................... 99 Diffusion tensor imaging (DTI) ........................... 92, 112 Diffusion weighted imaging (DWI) .............................. 92 Dihydroethidium (DHE) .................................... 454, 456 Dimethyl sulfoxide (DMSO)........................................ 154 DLL4-Notch signaling ................................................. 428 DNA extraction............................................................... 65 DNA sample collection and preparation .................78, 79 Double-distilled H2O (ddH2O) .................................. 389

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS

490 Index

Drosophila Larvae materials immunofluorescent ........................................... 183 methods immunofluorescent ........................................... 185 Dulbecco’s Modified Eagle Medium (DMEM)...................143, 154, 262, 455, 457 Dulbecco’s phosphate-buffered saline (D-PBS) .............................................. 132, 372

E ECMatrix™ Solution..................................................... 373 EGFP-Krit1 protein levels ............................................ 209 Embryo preparation...................................................... 246 Embryonic fibroblast (MEF) cells................................ 157 EMS mutagenesis screen .............................................. 195 Endothelial barrier brain tissue............................................................... 388 cell culture models .................................................. 388 cremaster.................................................................. 389 intravital microscopy ............................................... 388 materials anesthesis ........................................................... 389 cremaster muscle and imaging ......................... 390 equipment.......................................................... 389 Jugular Catheter................................................ 390 plastic/metal items............................................ 389 tracheotomy....................................................... 390 methods anesthesia ........................................................... 392 cremaster preparation ....................................... 394 data acquisition ................................................. 395 data analysis ....................................................... 396 jugular catheter ................................................. 392 micropipettes ..................................................... 391 tracheotomy and intubation............................. 392 micropipette puller.................................................. 389 permeability ............................................................. 388 Endothelial Cell Growth Basal Medium-2 (EBM-2) ...................................................... 143 Endothelial cell proliferation assays ............................. 379 Endothelial cells (ECs) ................................................. 332 Endothelial protein C receptor (EPCR)...................... 140 Endothelial-specific tamoxifen-regulated Cre recombinase (Pdgfb-iCreERT2) .................... 141, 144, 148 Endothelial-to-mesenchymal transition (EndoMT) .......................................... 275, 427 Endothelium.................................................................. 208 Enhanced green fluorescent protein (EGFP)......................................................... 162 Enzymatic Digestion Solution ..................................... 144 Epidemiologic information ............................................ 31 Ethanol Precipitation .................................................... 476

AND

PROTOCOLS

Ethylenediaminetetraacetic acid (EDTA) solution ........................................................ 143 Extended retrosigmoid approach................................. 121 Extracellular matrix (ECM).............. 401, 403–406, 408, 409, 413 Ezrin/radixin/Moesin (ERM) proteins ...................... 441

F Familial cerebral cavernous malformation (fCCM) hereditary forms ........................................................ 61 Familial form (fCCM)....................................................... 5 Far lateral approach....................................................... 124 FAT-homology (FAT-H) domain ................................ 293 Fetal bovine serum (FBS) ............................................. 154 Flip Recombinase Target (FRT) .................................. 181 Flow cytometry ............................................................. 315 Fluorescence in situ hybridization (FISH) embryos ................................................................... 246 in situ hybridization ....................................... 247–249 in vitro transcription ...................................... 245, 246 RNA Probe .............................................................. 245 Fluorescence intensity data........................................... 397 Focal adhesion targeting (FAT) ................................... 293 Focal adhesion targeting homology (FAT-H) ............ 311 Formazan dye ................................................................ 378 Functional MRI (fMRI) ................................................. 92

G Gadolinium-based contrast ............................................ 89 GCKIII proteins............................................................ 180 CCM genes.............................................................. 437 CCM1...................................................................... 437 CCM2...................................................................... 437 CCM3............................................................. 437, 438 endothelial cells ....................................................... 438 kinase activity......................................... 438, 440, 441 materials................................................................... 438 methods .......................................................... 439–440 non-endothelial cells ............................................... 438 Gel electrophoresis............................................... 474, 475 Genemania..................................................................... 341 Generate quality control (QC)....................................... 80 Genetic counseling....................................................54, 64 Genetic inactivation ............................140, 141, 145, 147 Genetic modifiers ........................................................7, 13 Genetic mosaicism ........................................................ 180 Genetic testing ................................................................ 63 Genome-wide association studies (GWAS) ...............7, 78 Genome-wide genotyping ........................................78–80 genetic modifiers ....................................................... 78 Genome-Wide LAT 1 array ............................................ 78 Genomic DNA (gDNA) ...........................................65, 78 automated purification.............................................. 66

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS Genomics ....................................................................... 326 Genotyping Console™ Software .................................... 79 Glyoxalase 1 (Glo1) ...................................................... 445 activity...................................................................... 445 activity calculation ................................................... 448 activity measurements ............................................. 448 apparatus.................................................................. 446 cells........................................................................... 446 GSH ......................................................................... 447 hemithioacetal solution........................................... 447 KRIT1 knockout ..................................................... 446 materials................................................................... 446 MG........................................................................... 447 PBS........................................................................... 446 sodium phosphate buffer ........................................ 446 specific activity......................................................... 448 Gradient echo (GE) ............................................... 98, 103 Gradient recalled echo (GRE)........................................ 89

H Hank’s Balanced Salt Solution (HBSS) ....................... 143 Harmonin homology domain (HHD) ........................ 293 Harvest mice organs ..................................................... 235 Hemorrhagic metastases (HMs) .................................... 99 Heterozygous KRIT1-KO mice .................................. 153 High-resolution ladder (HRL) .................................... 469 High-throughput genotyping microarrays .................... 77 Homodimerization ....................................................... 293 Homozygous mutant animals ...................................... 180 Horseradish peroxidase (HRP) .................................... 454 Human brain microvascular endothelial cells (hBMECs)................................. 132–134, 136, 152, 327, 446 Human cerebral cavernous malformations .................. 208 Human embryonic kidney (HEK) ...................... 155, 160 Human endothelial cell knockout models editing methods ...................................................... 169 genetic disorders ..................................................... 169 materials cell cultivation ................................................... 170 endonuclease digestion ..................................... 171 RNP transfection............................................... 170 methods genome editing efficiency ................................. 173 knockout cells.................................................... 173 sterile conditions ............................................... 172 Human microvascular endothelial model CCM genes .............................................................. 132 cell culture ...................................................... 132–134 cell transfection ....................................................... 133 hBMECs (see Human brain microvascular endothelial cells (hBMECs)) Krit1 knockdown RT-PCR ............................................................. 136 Western blotting analysis ..........................135–136

AND

PROTOCOLS Index 491

RT-PCR ................................................................... 133 siRNA transfection ......................................... 134–135 Western blotting analysis ........................................ 133 Human umbilical vein endothelial cells (HUVEC) ............................. 8, 402, 404–409, 412, 413, 420, 421, 423 Hydrocephalus ................................................................ 39 4-Hydroxy-tamoxifen solution...........141, 143, 145, 148

I IDEAL paradigm .......................................................... 112 Illumina HiSeq2500 sequencing ................................. 477 ImageJ program ............................................................ 374 Immunofluorescent analysis ......................................... 182 In situ hybridization ..................................................... 231 In vitro “pull-down” assay ........................................... 363 In vitro endothelial models CCM proteins ....................................... 403, 404, 413 cell shape and immunostainings.................... 410–412 fibronectin (FN)...................................................... 409 FN-coated glass ....................................................... 406 focal adhesions ..................... 402, 405, 409, 411, 413 HUVEC.......................................................... 407–408 HUVEC culture ............................................. 405, 406 immunofluorescence ............................................... 410 immunostaining ............................................. 406, 407 morphometric analysis ............................................ 407 mutant and wild-type endothelial cells .................. 403 pMLC (see Phosphorylated myosin light chain (pMLC)) remodeled ECM.................................... 406, 408, 409 RNA interference .................................................... 408 siRNA ...................................................................... 406 VE-cadherin................................... 402–405, 409, 410 In vitro knockout models ............................................. 169 In vitro tubule formation assay .................................... 373 In vivo mouse angiogenesis model ..................... 229, 235 aorta ......................................................................... 236 ear skin ..................................................................... 236 In vivo mouse care ........................................................ 233 In vivo zebrafish angiogenesis model .......................... 230 3-D angiogenesis assay ........................................... 242 GFP imaging ........................................................... 238 Inferomedial occipital CCMs STIO ........................................................................ 117 Inflammation ..................................................................... 7 Institutional Biosafety Committee (IBC)........... 312, 328 Integrin signaling .......................................................... 428 Interaction trap positives ..................................... 280, 285 Interaction Trap reagents ............................................. 276 International HapMap Project ....................................... 77 Intracerebral hemorrhage (ICH) ...................... 4, 60, 453 Intramedullary CMs clinical presentation and diagnosis ........................... 43 sensory and motor symptoms .................................. 42

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS

492 Index

Intramedullary CMs (cont.) spinal locations .......................................................... 42 therapeutic strategy ................................................... 42 Intravital microscopy ........................................... 388, 389 Iscove’s modified Dulbecco’s medium (IMDM).............................................. 155, 160 Isothermal titration calorimetry (ITC)........................ 314

J Jugular vein catheter ..................................................... 393

K KLF2 and KLF4 signaling ............................................ 428 Krev interaction trapped protein 1 (KRIT1) ............... 207 Krev/Rap1 interacting trapped 1(KRIT1).................. 291 KREV1 interaction trapped (KRIT1) .......................... 270 amino acids .............................................................. 273 bacterial protein LexA............................................. 272 biological function .................................................. 274 deficient cells ........................................................... 275 equipment................................................................ 277 functionality............................................................. 273 functions .................................................................. 270 interaction mating approach................................... 273 with KREV1 and ICAP1 ........................................ 274 malcavernin complex............................................... 274 microtubules............................................................ 275 NADPH oxidase ..................................................... 270 NAPDH oxidase ..................................................... 275 plasmids and yeast strains ....................................... 275 publication............................................................... 273 RAS .......................................................................... 270 TAD ......................................................................... 272 tumor suppressor .................................................... 270 Y2H.......................................................................... 276 Y2H paradigm ......................................................... 272 Y2H screening......................................................... 272 kri and ccm-3 phenotypes............................................. 192 kri-1 ............................................................................... 191 krit1 ...................................................................... 211, 214 KRIT1 (CCM1) .............................................................. 61 KRIT1 ARD-FERM domain crystals .......................... 299 KRIT1 FERM domain co-crystals ............................... 299 KRIT1 Nudix domain .................................................. 298 KRIT1/ MEF cells homozygous KRIT1-KO mouse embryos ........... 154, 157–159 recombinant lentivirus encoding KRIT1.............. 155, 160–161 KRIT1/CCM1 .................................. 131–133, 152–155, 157, 158, 160, 161, 163, 164 KRIT1/CCM1 gene ...................................................... 50

AND

PROTOCOLS

KRIT1-knockout MEF cells......................................... 152 KRIT1-KO mice ............................................................... 9 krit1ty219c mutant .......................................................... 209 Kru¨ppel-like factor (KLF) family........................... 10, 152 Kruppel-like factor 4 (KLF4) ....................................... 275 Krypton-Argon laser ..................................................... 308

L Larval fillets preparation ..................................................... 184, 185 Larval instar animal ....................................................... 185 Laser capture microdissection (LCM) ......................... 244 Lenticulostriate vessels.................................................. 120 Leukemia inhibitory factor (LIF)................................. 162 LexA fusion sequences.................................................. 276 Lipofection approach .................................................... 170 Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) ..................................... 331, 337 Low serum growth supplement (LSGS)...................... 420

M Magnetic resonance imaging (MRI)...................... 42, 62, 88, 98 Malcavernin ..................................................................... 50 MARCM system............................................................ 180 mating protocol............................................................. 347 Maxwell® ......................................................................... 64 Medial occipital CCMs occipital lobe ........................................................... 118 posterior interhemispheric approach ..................... 118 Medial temporal CCMs SCTT approach ....................................................... 117 skin incision ............................................................. 116 subfrontal approach ................................................ 116 subtemporal approach............................................. 116 TSTI......................................................................... 115 Medial transpetrosal approach...................................... 122 Medulla far lateral approach .................................................. 124 resigmoid approach................................................. 125 suboccipital approach.............................................. 124 TPMS approach ...................................................... 124 Mendelian disorders........................................................ 64 Methylglyoxal (MG) ..................................................... 445 Mice strains.................................................................... 234 Microangiography ......................................................... 243 Microscope visualization............................................... 116 Microscopy techniques, pathogenesis cellular mechanisms ................................................ 303 materials cell culture ......................................................... 304 plasmid cell transfections .................................. 304 RNAi .................................................................. 304

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS methods cell culture ......................................................... 306 plasmids ............................................................. 307 procedures ......................................................... 306 siRNA ................................................................ 307 subcellular localization and fluorescence microscopy................................................... 307 protocols .................................................................. 304 RNAi treatment....................................................... 303 Microvascular endothelial phenotype angiogenesis............................................................. 371 angiogenesis process ............................................... 372 angiogenic cord network ........................................ 372 cavernous angioma.................................................. 371 cell culture ............................................................... 372 EC matrix ................................................................ 372 endothelial junctions............................................... 371 materials cell culture ......................................................... 372 EC matrix .......................................................... 372 tube formation .................................................. 373 tube formation assay ......................................... 372 methods ECMatrix™ solution ......................................... 373 tubule formation assay ............................. 373, 374 physio-pathological condition ................................ 372 Microvessel permeability............................................... 388 Migration assay advantages and disadvantages................................. 381 Boyden chamber ..................................................... 381 materials scratch assay ....................................................... 382 methods Boyden chamber ............................................... 383 scratch assay ....................................................... 383 Miles assay ..................................................................... 388 Minor allele frequency (MAF) ....................................... 78 Mitogen-activated protein kinase (MAPK) .............................................. 325, 427 MitoSOX™ Red........................................... 454, 456, 462 Mitotic recombination......................................... 180, 181 Mixed vascular malformation ......................................... 99 Monoclinic crystals .............................................. 299, 300 Morpholino analysis ............................................. 230, 238 Morpholino-mediated knockdown .............................. 209 Morpholinos (MOs) ..................................................... 238 Mosaic Analysis with a Repressible Cell Marker (MARCM) ................................................... 180 Mosaic animals .............................................................. 180 Mosaic larvae materials generation.......................................................... 182 methods generation.......................................................... 183

AND

PROTOCOLS Index 493

Mosaic trachea............................................................... 181 Mouse ears models........................................................ 236 Mouse embryonic fibroblast (MEF) ................... 152, 162 Murine model................................................................ 259 Myelin Basic Protein (MBP) ........................................ 441

N N-2-hydroxyethylpiperazine-N-2-ethane sulfonic acid (HEPES) buffer solution ............................ 143 N-acetylcysteine (NAC).................................................. 13 Nematode growth medium (NGM) ................... 194, 196 Neonatal mouse models CCM lesion .................................................... 256, 257 CCM2 ...................................................................... 253 CCM3 ...................................................................... 253 genotyping protocol CCM1................................................................ 255 CCM2 ................................................................ 256 LCdh5CreERT2 ............................................... 255 KRIT1/CCM1 .............................................. 253, 254 sample collection ............................................ 256, 257 vascular malformation ............................................. 254 Neuronavigation ........................................................... 117 Neuroradiological reports .............................................. 98 Neuroradiology CAA ........................................................................... 99 CAVMs ...................................................................... 99 CCMs......................................................................... 97 CT .............................................................................. 98 CTe ............................................................................ 99 DVA ........................................................................... 99 follow-up .......................................................... 98, 104 GE .............................................................................. 98 MRI ........................................................................... 98 neuroradiological diagnostic .................................... 98 report ......................................................................... 99 standards .................................................................. 104 Next generation sequencing (NGS) hybridization capture ................................................ 67 library preparation..................................................... 66 Nikon EclipseTi confocal microscope.......................... 308 Non-yeast-based techniques......................................... 348 Notch signaling angiogenesis (see Angiogenesis) antigen retrieval.............................................. 431, 432 CCM1 and CCM3......................................... 429–430 counterstaining........................................................ 433 dehydration ............................................................. 433 deparaffinization............................................. 431, 432 embedding............................................................... 431 endothelial cells .............................................. 427–430 fixation ..................................................................... 431 immunohistochemistry .................................. 431–433 mounting ........................................................ 431, 433

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS

494 Index

Notch signaling (cont.) pericytes .......................................................... 428, 430 protein–protein complexes ..................................... 427 sectioning................................................................. 431 Notch1 intracellular domain (N1ICD) .............. 429, 430 Nuclear Dbf2-Related Kinase 1 (NDR1) .................... 441 Nucleic acid extraction ................................................... 64 Nudix domain ............................................................... 292

O Oligonucleotide primers ............................................... 277 Open book larval fillets materials preparation ........................................................ 183 Open reading frame (ORF).......................................... 272 Orthorhombic crystals ......................................... 296, 299 Oxidative stress.................... 7, 10, 11, 78, 452–454, 462 and inflammation ...................................................... 11

P p62/SQSTM1 aggregates ............................................ 424 antibody incubation ....................................... 421–422 autophagic process ......................................... 418–419 autophagy ................................................................ 419 blocking ................................................................... 421 cell culture and transfections ......................... 420, 421 equipment setup...................................................... 421 fixation ..................................................................... 421 immunofluorescence ...................................... 420, 422 microscope acquisition............................................ 423 permeabilization...................................................... 421 Paraformaldehyde (PFA) ..................................... 255, 420 Paramagnetic particles (PMPs) ...................................... 65 PDCD10 ...................................................................50, 61 Peptide sequencing affinity purification ......................................... 481, 483 concentrating and purifying digested peptides ...................................... 482, 484, 485 denaturation and digestion of proteins........................................... 481, 484 elution of proteins................................. 481, 483, 484 mass spectrometry..................................479, 483–485 protein-protein interactions ................................... 479 worm pellet samples....................................... 482, 483 worm population............................................ 480, 481 Permeability.......................................................... 388, 398 Pharmacological suppression........................................ 195 Phenylmethylsulfonyl fluoride (PMSF) ....................... 438 Phenylmethyl-sulfonyl fluoride (PMSF) stock solution ........................................................ 352 Phosphate buffered saline (PBS) .......................................... 154, 255, 420 Phosphoglycerate kinase gene (PGKpr) ...................... 162

AND

PROTOCOLS

Phosphorylated myosin light chain (pMLC)...................................... 402, 405, 410 Physical interactions ...................................................... 479 Physical simulation set .................................................. 113 Plasmid-based systems .................................................. 192 Plasmid transfections .................................................... 303 Polymerase chain reaction (PCR) ................................ 255 Pontomedullary sulcus.................................................. 124 Posterior interhemispheric approach ........................... 118 Post-genotyping quality control ..............................79, 80 Post-surgical hemorrhage rate........................................ 39 Proband CES................................................................... 64 Proband-only genetic testing ......................................... 64 Proliferation assay advantages and disadvantages................................. 379 materials cell counting ...................................................... 381 methods cell counting ...................................................... 382 MTT .................................................................. 382 MTT ........................................................................ 381 Proper waste disposal regulations ................................ 304 Protein concentrations......................................... 295, 447 Protein-Tyrosine Phosphatase 1B (PTP1B) ....................................................... 441 Proteomics..................................................................... 326 Proton density axial....................................................... 100 Pseudonudix domain .................................................... 292 Purification kit ................................................................. 66 Puromycin ..................................................................... 260

Q Q-Exactive Plus system................................................. 339 Quantitative Multiplex PCR Short Fragments (QMPSF)..................................... 51 Quantitative susceptibility mapping (QSM).................. 93 QuickExtract™ DNA Extraction Solution .................. 172

R Rap1............................................................................... 295 Reactive oxygen species (ROS) ........................... 275, 419 cell culture and fluorescence microscopy .......................................... 455, 457 cell fixation ..................................................... 457, 458 cell growth and treatment ............................. 455, 457 cellular H2O2 levels................................456, 459–461 detection ......................................................... 454, 456 fixation and fluorescence staining ................. 455, 456 flow cytometry analysis ........................................... 459 fluorescence microscopy analysis ................... 457–459 HPLC and mass spectrometry ............................... 454 hydrogen peroxide (H2O2) .................................... 451 mitochondrial superoxide ....................................... 459

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS oxidative stress (see Oxidative stress) redox-sensitive molecular targets ........................... 452 superoxide anion (O2) .......................................... 451 Reagents CCM2 HHD and MEKK3 PB1 domain .............. 294 CCM2 HHD domain ............................................. 294 CCM2 PTB domain ............................................... 294 CCM3 crystals......................................................... 294 general ..................................................................... 294 KRIT1 FERM domain............................................ 295 Nudix and ICAP1 ................................................... 294 Region of interest (ROI) .............................................. 396 Resigmoid approach ..................................................... 125 Retromastoid craniotomy ............................................. 123 RhoA activation............................................................... 11 RhoA-ROCK signaling................................................... 12 Ribonucleoproteins (RNP) ................................. 170, 194 RNP CRISPR genome ................................................. 192

S Sanger sequencing........................................................... 51 Screening algorithm ........................................................ 51 S-D-lactoylglutathione (SLG) ...................................... 445 Segregation analysis ........................................................ 63 Simian virus 40 (SV40)................................................. 161 Simulating neurosurgical approaches........................... 111 Single-nucleotide polymorphisms (SNPs)..................... 61 Single-nucleotide variation (SNV) ................................. 68 Small RNA library preparation 30 adapter ligation ................................. 468, 469, 471 50 adapter ligation ................................. 468, 469, 472 CCM ........................................................................ 467 cDNA construct .....................................469, 474–476 DNA template storage ............................................ 477 ethanol precipitation ............................................... 469 library validation ..................................................... 477 microRNAs ..................................................... 468, 475 PCR amplification ..................................469, 472–474 positive control........................................................ 470 reverse transcription .............................. 469, 472, 473 snoRNAs.................................................................. 468 Sodium dodecyl sulfate poly acrylamide gel electrophoresis (SDS-PAGE) ...................... 316 Spectrophotometric method ........................................ 445 Sporadic form (sCCM) ..................................................... 5 Standard PCR approach ............................................... 174 Standard subcloning techniques .................................. 278 Subcellular localization and fluorescence microscopy ................................................... 305 Suboccipital approach ................................................... 124 Suboccipital-telovelar approach .......................... 123, 125 Suboccipital-transventricular approach ........................ 125 Supracarotid-infrafrontal approach .............................. 120

AND

PROTOCOLS Index 495

Supracerebellar-infratentorial approach (SCIT) .......... 120 Supratentorial convexity CCM ....................................................... 113 temporal CCMs....................................................... 115 Supratentorial cavernous malformations epidemiology ............................................................. 36 hemorrhage rate ........................................................ 36 Supratentorial cerebral cavernous malformation associated epilepsy (SCCMAE) .................... 36 Supratentorial-infraoccipital approach ......................... 117 Susceptibility sensitive sequences ................................... 91 Susceptibility weighted imaging (SWI) ......................... 89 Symptomatic disease ....................................................... 31

T T1- and T2-weighted sequences.................................... 90 T1-based quantitative perfusion technique ................... 93 T7EI digestion .............................................................. 175 Tamoxifen-inducible endothelial cell-specific Cre line (Cdh5-CreERT2) ................................ 254, 255 Tetragonal crystals ............................................... 295, 296 TGF-β signaling ............................................................ 428 Thermal cycler program ............................................... 174 Thrombomodulin (TM) ........................................ 12, 140 Time-consuming tasks .................................................... 93 Tosyl-L-lysine chloromethyl ketone hydrochloride (TLCK) ........................................................ 143 Tracheotomy and jugular vein catheterization............ 390 Transactivation domain (AD)....................................... 345 Transcallosal-transventricular approach ....................... 119 Transcriptional activation domain (TAD) ................... 270 Transpontomedullary sulcus approach (TPMS) ......... 124 Transsylvian ................................................................... 120 Transsylvian-transinsular approach (TSTI).................. 115 Transvermian ................................................................. 119 Transverse Sinus (TS) junction .................................... 124 Trizol ............................................................................. 327 Tube formation assay .................................................... 372 Tubule formation ................................................. 373, 374 Tubule formation assay cell starvation and preparation ............................... 373 Two-photon microscopy .............................................. 388 Type II chronic cavernous malformation ...................... 86

U UAS/GAL4/GAL80 system ....................................... 180 Ubiquitin-proteasome system (UPS) .......................... 418 Upsim physical simulation model ................................ 113

V Vagoaccessory triangle .................................................. 124 Vapor diffusion method................................................ 295

CEREBRAL CAVERNOUS MALFORMATIONS (CCM): METHODS

496 Index

AND

PROTOCOLS

β-galactosidase filter assay ................................. 360 library titer, determination .......................357–359 non-yeast-based techniques.................................... 348 nutritional markers.................................................. 346 plasmid DNA........................................................... 351 plasmids and yeast strains .............................. 349, 350 positive clones, analysis AD constructs.................................................... 362 bacterial cells............................................. 361, 362 bait dependency test ......................................... 362 plasmid DNA extraction ................................... 360 protein extracts preparation.................................... 352 putative interacting proteins................................... 346 small scale yeast transformation ............................. 356 stock plates .............................................................. 353 test autonomous reporter ....................................... 354 titer........................................................................... 366 verify protein expression protein extracts.................................................. 355 yeast cultures ..................................................... 354 yeast selection .......................................................... 350 yeast strains .............................................................. 364 yeast transformation................................................ 351

Vascular endothelial growth factor (VEGF) ...................................... 325, 377, 428 Vascular lesions.............................................................. 179 Vascular malformation .................................................. 254 Vascular permeability .................................................... 387 Vasculitis .......................................................................... 99 Vertebral body hemangioma .......................................... 42 Vertebrate models animal protocols ...................................................... 226 BBB integrity........................................................... 226 in vivo mouse care and maintenance ..................... 227 IP.............................................................................. 227 mouse model ........................................................... 226 mouse organs .......................................................... 228 zebrafish models...................................................... 225

W Whole genome or whole exome sequencing (WGS/WES) ................................................. 63 Whole-mount immunofluorescent staining ................ 230 imaging and microangiography.............................. 243 zebrafish................................................................... 245 Wound healing assay ............................................ 379, 380

X

Z

X-ray data collection ..................................................... 299 X-ray-induced mosaicism.............................................. 180

Zebrafish models .................................................. 225, 226 cardiovascular system .............................................. 208 Ccm mutant ................................................... 215–217 Ccm protein ............................................................ 208 cDNA Synthesis ...................................................... 210 cell-stage zebrafish embryos ................................... 215 clones and destination vectors................................ 210 expression clone ...................................................... 211 functional antibodies............................................... 208 gateway cloning..................................... 210, 213, 214 generation................................................................ 212 generation and maintenance ......................... 229, 237 genomic DNA and genotyping PCR.............................................................. 212 in situ hybridizations............................................... 208 in vitro studies ......................................................... 208 krit1ty219c mutation ................................................. 212 microinjections ............................................... 211, 212 mRNA...................................................................... 210 PCR primer ............................................................. 217 stable transgenic ............................................. 216, 218 tagged Ccm protein ................................................ 215

Y Yeast library transformation ......................................... 281 Yeast lysis solution (YLS).............................................. 351 Yeast transformation ..................................................... 278 Yeast two-hybrid (Y2H) interaction ............................ 271 Yeast two-hybrid (Y2H) system .......................... 270, 345 advantages................................................................ 347 CCM ........................................................................ 348 cDNA libraries................................................ 346, 348 construct fusion genes ............................................ 353 cotransformation screens ........................................ 347 DNA-BD/BAIT plasmid ....................................... 366 E. coli transformation.............................................. 352 general use materials ............................................... 349 growth and maintenance, yeast .............................. 350 KRIT1 protein ............................................... 348, 349 LexA DNA-binding domains ................................. 349 library proteins ........................................................ 348 mating protocol....................................................... 347