201
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Single-molecule analysis of nucleic acid biomarkers - A review. Anal Chim Acta 2020; 1115:61-85. [PMID: 32370870 DOI: 10.1016/j.aca.2020.03.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 02/29/2020] [Accepted: 03/02/2020] [Indexed: 12/11/2022]
Abstract
Nucleic acids are important biomarkers for disease detection, monitoring, and treatment. Advances in technologies for nucleic acid analysis have enabled discovery and clinical implementation of nucleic acid biomarkers. However, challenges remain with technologies for nucleic acid analysis, thereby limiting the use of nucleic acid biomarkers in certain contexts. Here, we review single-molecule technologies for nucleic acid analysis that can be used to overcome these challenges. We first discuss the various types of nucleic acid biomarkers important for clinical applications and conventional technologies for nucleic acid analysis. We then discuss technologies for single-molecule in vitro and in situ analysis of nucleic acid biomarkers. Finally, we discuss other ultra-sensitive techniques for nucleic acid biomarker detection.
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202
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Hashemi Gheinani A, Bigger-Allen A, Wacker A, Adam RM. Systems analysis of benign bladder disorders: insights from omics analysis. Am J Physiol Renal Physiol 2020; 318:F901-F910. [PMID: 32116016 DOI: 10.1152/ajprenal.00496.2019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The signaling pathways and effectors that drive the response of the bladder to nonmalignant insults or injury are incompletely defined. Interrogation of biological systems has been revolutionized by the ability to generate high-content data sets that capture information on a variety of biomolecules in cells and tissues, from DNA to RNA to proteins. In oncology, such an approach has led to the identification of cancer subtypes, improved prognostic capability, and has provided a basis for precision treatment of patients. In contrast, systematic molecular characterization of benign bladder disorders has lagged behind, such that our ability to uncover novel therapeutic interventions or increase our mechanistic understanding of such conditions is limited. Here, we discuss existing literature on the application of omics approaches, including transcriptomics and proteomics, to urinary tract conditions characterized by pathological tissue remodeling. We discuss molecular pathways implicated in remodeling, challenges in the field, and aspirations for omics-based research in the future.
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Affiliation(s)
- Ali Hashemi Gheinani
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts.,Department of Surgery, Harvard Medical School, Boston, Massachusetts
| | - Alexander Bigger-Allen
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts.,Biological and Biomedical Sciences PhD Program, Harvard Medical School, Boston, Massachusetts
| | - Amanda Wacker
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts.,Florida State University, Tallahassee, Florida
| | - Rosalyn M Adam
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts.,Department of Surgery, Harvard Medical School, Boston, Massachusetts
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203
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Lähnemann D, Köster J, Szczurek E, McCarthy DJ, Hicks SC, Robinson MD, Vallejos CA, Campbell KR, Beerenwinkel N, Mahfouz A, Pinello L, Skums P, Stamatakis A, Attolini CSO, Aparicio S, Baaijens J, Balvert M, Barbanson BD, Cappuccio A, Corleone G, Dutilh BE, Florescu M, Guryev V, Holmer R, Jahn K, Lobo TJ, Keizer EM, Khatri I, Kielbasa SM, Korbel JO, Kozlov AM, Kuo TH, Lelieveldt BP, Mandoiu II, Marioni JC, Marschall T, Mölder F, Niknejad A, Rączkowska A, Reinders M, Ridder JD, Saliba AE, Somarakis A, Stegle O, Theis FJ, Yang H, Zelikovsky A, McHardy AC, Raphael BJ, Shah SP, Schönhuth A. Eleven grand challenges in single-cell data science. Genome Biol 2020; 21:31. [PMID: 32033589 PMCID: PMC7007675 DOI: 10.1186/s13059-020-1926-6] [Citation(s) in RCA: 574] [Impact Index Per Article: 143.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 01/02/2020] [Indexed: 02/08/2023] Open
Abstract
The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
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Affiliation(s)
- David Lähnemann
- Algorithms for Reproducible Bioinformatics, Genome Informatics, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Department of Paediatric Oncology, Haematology and Immunology, Medical Faculty, Heinrich Heine University, University Hospital, Düsseldorf, Germany
- Computational Biology of Infection Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Johannes Köster
- Algorithms for Reproducible Bioinformatics, Genome Informatics, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, USA
| | - Ewa Szczurek
- Institute of Informatics, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warszawa, Poland
| | - Davis J. McCarthy
- Bioinformatics and Cellular Genomics, St Vincent’s Institute of Medical Research, Fitzroy, Australia
- Melbourne Integrative Genomics, School of BioSciences–School of Mathematics & Statistics, Faculty of Science, University of Melbourne, Melbourne, Australia
| | - Stephanie C. Hicks
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD USA
| | - Mark D. Robinson
- Institute of Molecular Life Sciences and SIB Swiss Institute of Bioinformatics, University of Zürich, Zürich, Switzerland
| | - Catalina A. Vallejos
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- The Alan Turing Institute, British Library, London, UK
| | - Kieran R. Campbell
- Department of Statistics, University of British Columbia, Vancouver, Canada
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, Canada
- Data Science Institute, University of British Columbia, Vancouver, Canada
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ahmed Mahfouz
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Luca Pinello
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Charlestown, USA
- Department of Pathology, Harvard Medical School, Boston, USA
- Broad Institute of Harvard and MIT, Cambridge, MA USA
| | - Pavel Skums
- Department of Computer Science, Georgia State University, Atlanta, USA
| | - Alexandros Stamatakis
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
- Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | | | - Samuel Aparicio
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
| | - Jasmijn Baaijens
- Life Sciences and Health, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
| | - Marleen Balvert
- Life Sciences and Health, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
- Theoretical Biology and Bioinformatics, Science for Life, Utrecht University, Utrecht, The Netherlands
| | - Buys de Barbanson
- Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
- Quantitative biology, Hubrecht Institute, Utrecht, The Netherlands
| | - Antonio Cappuccio
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
| | - Giacomo Corleone
- Department of Surgery and Cancer, The Imperial Centre for Translational and Experimental Medicine, Imperial College London, London, UK
| | - Bas E. Dutilh
- Theoretical Biology and Bioinformatics, Science for Life, Utrecht University, Utrecht, The Netherlands
- Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maria Florescu
- Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
- Quantitative biology, Hubrecht Institute, Utrecht, The Netherlands
| | - Victor Guryev
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rens Holmer
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands
| | - Katharina Jahn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Thamar Jessurun Lobo
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Emma M. Keizer
- Biometris, Wageningen University & Research, Wageningen, The Netherlands
| | - Indu Khatri
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands
| | - Szymon M. Kielbasa
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Jan O. Korbel
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Alexey M. Kozlov
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Tzu-Hao Kuo
- Computational Biology of Infection Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Boudewijn P.F. Lelieveldt
- PRB lab, Delft University of Technology, Delft, The Netherlands
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ion I. Mandoiu
- Computer Science & Engineering Department, University of Connecticut, Storrs, USA
| | - John C. Marioni
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, UK
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Tobias Marschall
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Felix Mölder
- Algorithms for Reproducible Bioinformatics, Genome Informatics, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Amir Niknejad
- Computation molecular design, Zuse Institute Berlin, Berlin, Germany
- Mathematics Department, Mount Saint Vincent, New York, USA
| | - Alicja Rączkowska
- Institute of Informatics, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warszawa, Poland
| | - Marcel Reinders
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Jeroen de Ridder
- Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Antoine-Emmanuel Saliba
- Helmholtz Institute for RNA-based Infection Research, Helmholtz-Center for Infection Research, Würzburg, Germany
| | - Antonios Somarakis
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Oliver Stegle
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center–DKFZ, Heidelberg, Germany
| | - Fabian J. Theis
- Institute of Computational Biology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Huan Yang
- Division of Drug Discovery and Safety, Leiden Academic Center for Drug Research–LACDR–Leiden University, Leiden, The Netherlands
| | - Alex Zelikovsky
- Department of Computer Science, Georgia State University, Atlanta, USA
- The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Alice C. McHardy
- Computational Biology of Infection Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | | | - Sohrab P. Shah
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Alexander Schönhuth
- Life Sciences and Health, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
- Theoretical Biology and Bioinformatics, Science for Life, Utrecht University, Utrecht, The Netherlands
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204
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Elmentaite R, Teichmann S, Madissoon E. Studying immune to non-immune cell cross-talk using single-cell technologies. CURRENT OPINION IN SYSTEMS BIOLOGY 2019; 18:87-94. [PMID: 32984660 PMCID: PMC7493433 DOI: 10.1016/j.coisb.2019.10.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Single-cell RNA-sequencing has uncovered immune heterogeneity, including novel cell types, states and lineages that have expanded our understanding of the immune system as a whole. More recently, studies involving both immune and non-immune cells have demonstrated the importance of immune microenvironment in development, homeostasis and disease. This review focuses on the single-cell studies mapping cell-cell interactions for variety of tissues in development, health and disease. In addition, we address the need to generate a comprehensive interaction map to answer fundamental questions in immunology as well as experimental and computational strategies required for this purpose.
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Affiliation(s)
- R. Elmentaite
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, United Kingdom
| | - S.A. Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, United Kingdom
- Theory of Condensed Matter, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, CB3 0HE, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - E. Madissoon
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
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205
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Nathan A, Baglaenko Y, Fonseka CY, Beynor JI, Raychaudhuri S. Multimodal single-cell approaches shed light on T cell heterogeneity. Curr Opin Immunol 2019; 61:17-25. [PMID: 31430664 PMCID: PMC6901721 DOI: 10.1016/j.coi.2019.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/03/2019] [Accepted: 07/14/2019] [Indexed: 01/13/2023]
Abstract
Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell's function. But, these data sets pose new statistical challenges for integration and joint analysis.
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Affiliation(s)
- Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Chamith Y Fonseka
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jessica I Beynor
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
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206
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Gao H, Zhang K, Teng X, Li J. Rolling circle amplification for single cell analysis and in situ sequencing. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.115700] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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207
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Chevrier N. Decoding the Body Language of Immunity: Tackling the Immune System at the Organism Level. ACTA ACUST UNITED AC 2019; 18:19-26. [PMID: 32490290 DOI: 10.1016/j.coisb.2019.10.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The immune system is a dynamic mesh of molecules, cells and tissues spanning the entire organism. Despite a wealth of knowledge about the components of the immune system, little is known about the general rules governing the organismal circuitry of immunity. Deciphering the immune system at the scale of the whole organism is crucial to understanding fundamental problems in immunobiology and physiology, and to manipulate immunity for maintaining health and preventing disease. Here I discuss the emerging principles of inter-organ communications during immune responses by focusing on three common themes that are the regulation of the (i) composition, (ii) condition and (iii) coordination of communicating organs by molecular and cellular factors. Based on these common principles, I emphasize fundamental gaps in our knowledge of organismal immune processes and the outlook to tackle immunity at the scale of the whole organism.
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Affiliation(s)
- Nicolas Chevrier
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL 60637, USA
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208
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Keller L, Pantel K. Unravelling tumour heterogeneity by single-cell profiling of circulating tumour cells. Nat Rev Cancer 2019; 19:553-567. [PMID: 31455893 DOI: 10.1038/s41568-019-0180-2] [Citation(s) in RCA: 353] [Impact Index Per Article: 70.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/09/2019] [Indexed: 12/17/2022]
Abstract
Single-cell technologies have contributed to unravelling tumour heterogeneity, now considered a hallmark of cancer and one of the main causes of tumour resistance to cancer therapies. Liquid biopsy (LB), defined as the detection and analysis of cells or cell products released by tumours into the blood, offers an appealing minimally invasive approach that allows the characterization and monitoring of tumour heterogeneity in individual patients. Here, we will review and discuss how circulating tumour cell (CTC) analysis at single-cell resolution provides unique insights into tumour heterogeneity that are not revealed by analysis of circulating tumour DNA (ctDNA) derived from LBs. The molecular analysis of CTCs provides complementary information to that of genomic aberrations determined using ctDNA to fully describe many different cellular components (for example, DNA, RNA, proteins and metabolites) that can influence tumour heterogeneity.
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Affiliation(s)
- Laura Keller
- Department of Tumour Biology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Klaus Pantel
- Department of Tumour Biology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
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209
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Duran RCD, Wei H, Kim DH, Wu JQ. Invited Review: Long non-coding RNAs: important regulators in the development, function and disorders of the central nervous system. Neuropathol Appl Neurobiol 2019; 45:538-556. [PMID: 30636336 PMCID: PMC6626588 DOI: 10.1111/nan.12541] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 12/19/2018] [Indexed: 02/06/2023]
Abstract
Genome-wide transcriptional studies have demonstrated that tens of thousands of long non-coding RNAs (lncRNA) genes are expressed in the central nervous system (CNS) and that they exhibit tissue- and cell-type specificity. Their regulated and dynamic expression and their co-expression with protein-coding gene neighbours have led to the study of the functions of lncRNAs in CNS development and disorders. In this review, we describe the general characteristics, localization and classification of lncRNAs. We also elucidate the examples of the molecular mechanisms of nuclear and cytoplasmic lncRNA actions in the CNS and discuss common experimental approaches used to identify and unveil the functions of lncRNAs. Additionally, we provide examples of lncRNA studies of cell differentiation and CNS disorders including CNS injuries and neurodegenerative diseases. Finally, we review novel lncRNA-based therapies. Overall, this review highlights the important biological roles of lncRNAs in CNS functions and disorders.
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Affiliation(s)
- Raquel Cuevas-Diaz Duran
- The Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Stem Cell and Regenerative Medicine, UT Brown Foundation Institute of Molecular Medicine, Houston, TX 77030, USA
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Morones Prieto 3000, Monterrey, N.L., 64710, Mexico
| | - Haichao Wei
- The Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Stem Cell and Regenerative Medicine, UT Brown Foundation Institute of Molecular Medicine, Houston, TX 77030, USA
| | - Dong H. Kim
- The Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Jia Qian Wu
- The Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Stem Cell and Regenerative Medicine, UT Brown Foundation Institute of Molecular Medicine, Houston, TX 77030, USA
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210
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Hoffecker IT, Yang Y, Bernardinelli G, Orponen P, Högberg B. A computational framework for DNA sequencing microscopy. Proc Natl Acad Sci U S A 2019; 116:19282-19287. [PMID: 31484777 PMCID: PMC6765314 DOI: 10.1073/pnas.1821178116] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
We describe a method whereby microscale spatial information such as the relative positions of biomolecules on a surface can be transferred to a sequence-based format and reconstructed into images without conventional optics. Barcoded DNA "polymerase colony" (polony) amplification techniques enable one to distinguish specific locations of a surface by their sequence. Image formation is based on pairwise fusion of uniquely tagged and spatially adjacent polonies. The network of polonies connected by shared borders forms a graph whose topology can be reconstructed from pairs of barcodes fused during a polony cross-linking phase, the sequences of which are determined by recovery from the surface and next-generation (next-gen) sequencing. We developed a mathematical and computational framework for this principle called polony adjacency reconstruction for spatial inference and topology and show that Euclidean spatial data may be stored and transmitted in the form of graph topology. Images are formed by transferring molecular information from a surface of interest, which we demonstrated in silico by reconstructing images formed from stochastic transfer of hypothetical molecular markers. The theory developed here could serve as a basis for an automated, multiplexable, and potentially superresolution imaging method based purely on molecular information.
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Affiliation(s)
- Ian T Hoffecker
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-17177 Stockholm, Sweden
| | - Yunshi Yang
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-17177 Stockholm, Sweden
| | - Giulio Bernardinelli
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-17177 Stockholm, Sweden
| | - Pekka Orponen
- Department of Computer Science, Aalto University, FI-00076 Aalto, Finland
| | - Björn Högberg
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-17177 Stockholm, Sweden;
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211
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Qualifying antibodies for image-based immune profiling and multiplexed tissue imaging. Nat Protoc 2019; 14:2900-2930. [PMID: 31534232 DOI: 10.1038/s41596-019-0206-y] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 06/03/2019] [Indexed: 12/27/2022]
Abstract
Multiplexed tissue imaging enables precise, spatially resolved enumeration and characterization of cell types and states in human resection specimens. A growing number of methods applicable to formalin-fixed, paraffin-embedded (FFPE) tissue sections have been described, the majority of which rely on antibodies for antigen detection and mapping. This protocol provides step-by-step procedures for confirming the selectivity and specificity of antibodies used in fluorescence-based tissue imaging and for the construction and validation of antibody panels. Although the protocol is implemented using tissue-based cyclic immunofluorescence (t-CyCIF) as an imaging platform, these antibody-testing methods are broadly applicable. We demonstrate assembly of a 16-antibody panel for enumerating and localizing T cells and B cells, macrophages, and cells expressing immune checkpoint regulators. The protocol is accessible to individuals with experience in microscopy and immunofluorescence; some experience in computation is required for data analysis. A typical 30-antibody dataset for 20 FFPE slides can be generated within 2 weeks.
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212
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Finotello F, Rieder D, Hackl H, Trajanoski Z. Next-generation computational tools for interrogating cancer immunity. Nat Rev Genet 2019; 20:724-746. [PMID: 31515541 DOI: 10.1038/s41576-019-0166-7] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2019] [Indexed: 12/17/2022]
Abstract
The remarkable success of cancer therapies with immune checkpoint blockers is revolutionizing oncology and has sparked intensive basic and translational research into the mechanisms of cancer-immune cell interactions. In parallel, numerous novel cutting-edge technologies for comprehensive molecular and cellular characterization of cancer immunity have been developed, including single-cell sequencing, mass cytometry and multiplexed spatial cellular phenotyping. In order to process, analyse and visualize multidimensional data sets generated by these technologies, computational methods and software tools are required. Here, we review computational tools for interrogating cancer immunity, discuss advantages and limitations of the various methods and provide guidelines to assist in method selection.
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Affiliation(s)
- Francesca Finotello
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Dietmar Rieder
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Hubert Hackl
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Zlatko Trajanoski
- Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria.
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213
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Van Hul N, Lendahl U, Andersson ER. Mouse Models for Diseases in the Cholangiocyte Lineage. Methods Mol Biol 2019; 1981:203-236. [PMID: 31016657 DOI: 10.1007/978-1-4939-9420-5_14] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Cholangiopathies are an important group of liver diseases affecting the biliary system, and the purpose of this review is to describe how diseases in the biliary system can be studied in mouse models. A particular focus is placed on mouse models for Alagille syndrome, a cholangiopathy with a strong genetic link to dysfunctional Notch signaling. Recently, a number of different genetic mouse models based on various manipulations of the Notch signaling pathway have been generated to study Alagille syndrome, and we discuss the resulting phenotypes, and possible causes for the phenotypic heterogeneity among the various models. In the final section, we provide a more general discussion on how well mouse models can be expected to mimic human liver disease, as well as an outlook toward the need for new technologies that can help us to gain new insights from mouse models for liver disease.
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Affiliation(s)
- Noémi Van Hul
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
| | - Urban Lendahl
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.
| | - Emma R Andersson
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.,Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
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214
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Uzbas F, Opperer F, Sönmezer C, Shaposhnikov D, Sass S, Krendl C, Angerer P, Theis FJ, Mueller NS, Drukker M. BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis. Genome Biol 2019; 20:155. [PMID: 31387612 PMCID: PMC6683345 DOI: 10.1186/s13059-019-1748-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 06/25/2019] [Indexed: 01/22/2023] Open
Abstract
We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/β-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.
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Affiliation(s)
- Fatma Uzbas
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Florian Opperer
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Can Sönmezer
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Dmitry Shaposhnikov
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Steffen Sass
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Christian Krendl
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Philipp Angerer
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Fabian J. Theis
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Department of Mathematics, Technical University Munich, 85748 Garching, Germany
| | - Nikola S. Mueller
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Micha Drukker
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
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215
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Yap EL, Greenberg ME. Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior. Neuron 2019; 100:330-348. [PMID: 30359600 DOI: 10.1016/j.neuron.2018.10.013] [Citation(s) in RCA: 335] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 10/02/2018] [Accepted: 10/05/2018] [Indexed: 12/21/2022]
Abstract
Gene transcription is the process by which the genetic codes of organisms are read and interpreted as a set of instructions for cells to divide, differentiate, migrate, and mature. As cells function in their respective niches, transcription further allows mature cells to interact dynamically with their external environment while reliably retaining fundamental information about past experiences. In this Review, we provide an overview of the field of activity-dependent transcription in the vertebrate brain and highlight contemporary work that ranges from studies of activity-dependent chromatin modifications to plasticity mechanisms underlying adaptive behaviors. We identify key gaps in knowledge and propose integrated approaches toward a deeper understanding of how activity-dependent transcription promotes the refinement and plasticity of neural circuits for cognitive function.
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Affiliation(s)
- Ee-Lynn Yap
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Program in Neuroscience, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Michael E Greenberg
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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216
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Blencowe M, Arneson D, Ding J, Chen YW, Saleem Z, Yang X. Network modeling of single-cell omics data: challenges, opportunities, and progresses. Emerg Top Life Sci 2019; 3:379-398. [PMID: 32270049 PMCID: PMC7141415 DOI: 10.1042/etls20180176] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 06/07/2019] [Accepted: 06/24/2019] [Indexed: 01/07/2023]
Abstract
Single-cell multi-omics technologies are rapidly evolving, prompting both methodological advances and biological discoveries at an unprecedented speed. Gene regulatory network modeling has been used as a powerful approach to elucidate the complex molecular interactions underlying biological processes and systems, yet its application in single-cell omics data modeling has been met with unique challenges and opportunities. In this review, we discuss these challenges and opportunities, and offer an overview of the recent development of network modeling approaches designed to capture dynamic networks, within-cell networks, and cell-cell interaction or communication networks. Finally, we outline the remaining gaps in single-cell gene network modeling and the outlooks of the field moving forward.
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Affiliation(s)
- Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
| | - Douglas Arneson
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
| | - Jessica Ding
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
| | - Yen-Wei Chen
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
- Molecular Toxicology Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
| | - Zara Saleem
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
- Molecular Toxicology Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, U.S.A
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217
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Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Vieira Braga FA, Timens W, Koppelman GH, Budinger GRS, Burgess JK, Waghray A, van den Berge M, Theis FJ, Regev A, Kaminski N, Rajagopal J, Teichmann SA, Misharin AV, Nawijn MC. The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. Am J Respir Cell Mol Biol 2019; 61:31-41. [PMID: 30995076 PMCID: PMC6604220 DOI: 10.1165/rcmb.2018-0416tr] [Citation(s) in RCA: 128] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 04/17/2019] [Indexed: 12/13/2022] Open
Abstract
Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, aging, or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments, including the tissue resident structural and immune cells, the tissue matrix, and the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach, and the expected impact of a Human Lung Cell Atlas.
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Affiliation(s)
- Herbert B. Schiller
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Group Systems Medicine of Chronic Lung Disease, Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Daniel T. Montoro
- Harvard Stem Cell Institute, Cambridge, Massachusetts
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Lukas M. Simon
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany
| | - Emma L. Rawlins
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, United Kingdom
| | | | - Maximilian Strunz
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Group Systems Medicine of Chronic Lung Disease, Member of the German Center for Lung Research (DZL), Munich, Germany
| | | | - Wim Timens
- Department of Pathology and Medical Biology
- Groningen Research Institute for Asthma and COPD at the University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Gerard H. Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children’s Hospital, and
- Groningen Research Institute for Asthma and COPD at the University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - G. R. Scott Budinger
- Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois
| | - Janette K. Burgess
- Department of Pathology and Medical Biology
- Groningen Research Institute for Asthma and COPD at the University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Avinash Waghray
- Harvard Stem Cell Institute, Cambridge, Massachusetts
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Maarten van den Berge
- Department of Pulmonology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Groningen Research Institute for Asthma and COPD at the University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Fabian J. Theis
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany
- Department of Mathematics, Technische Universität München, Munich, Germany
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts
- Department of Biology, Howard Hughes Medical Institute and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; and
| | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Jayaraj Rajagopal
- Harvard Stem Cell Institute, Cambridge, Massachusetts
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | | | - Alexander V. Misharin
- Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois
| | - Martijn C. Nawijn
- Department of Pathology and Medical Biology
- Groningen Research Institute for Asthma and COPD at the University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
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218
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Mayr U, Serra D, Liberali P. Exploring single cells in space and time during tissue development, homeostasis and regeneration. Development 2019; 146:146/12/dev176727. [DOI: 10.1242/dev.176727] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
ABSTRACT
Complex 3D tissues arise during development following tightly organized events in space and time. In particular, gene regulatory networks and local interactions between single cells lead to emergent properties at the tissue and organism levels. To understand the design principles of tissue organization, we need to characterize individual cells at given times, but we also need to consider the collective behavior of multiple cells across different spatial and temporal scales. In recent years, powerful single cell methods have been developed to characterize cells in tissues and to address the challenging questions of how different tissues are formed throughout development, maintained in homeostasis, and repaired after injury and disease. These approaches have led to a massive increase in data pertaining to both mRNA and protein abundances in single cells. As we review here, these new technologies, in combination with in toto live imaging, now allow us to bridge spatial and temporal information quantitatively at the single cell level and generate a mechanistic understanding of tissue development.
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Affiliation(s)
- Urs Mayr
- Department of Quantitative Biology, Friedrich Miescher Institute for Biomedical Research (FMI), Maulbeerstrasse 66, 4058 Basel, Switzerland
- University of Basel, Petersplatz 1, 4001 Basel, Switzerland
| | - Denise Serra
- Department of Quantitative Biology, Friedrich Miescher Institute for Biomedical Research (FMI), Maulbeerstrasse 66, 4058 Basel, Switzerland
- University of Basel, Petersplatz 1, 4001 Basel, Switzerland
| | - Prisca Liberali
- Department of Quantitative Biology, Friedrich Miescher Institute for Biomedical Research (FMI), Maulbeerstrasse 66, 4058 Basel, Switzerland
- University of Basel, Petersplatz 1, 4001 Basel, Switzerland
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219
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Abstract
X chromosome inactivation silences one X chromosome in female mammals. However, this silencing is incomplete, and some genes escape X inactivation. We describe methods to determine the chromosome-wide X inactivation status of genes in tissues or cell lines derived from mice using a combination of skewing of X inactivation and allele-specific analyses of gene expression based on RNA-seq.
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220
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Kebschull JM. DNA sequencing in high-throughput neuroanatomy. J Chem Neuroanat 2019; 100:101653. [PMID: 31173871 DOI: 10.1016/j.jchemneu.2019.101653] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Revised: 03/30/2019] [Accepted: 05/24/2019] [Indexed: 01/15/2023]
Abstract
Mapping brain connectivity at single cell resolution is critical for understanding brain structure. For decades, such mapping has been principally approached with microscopy techniques, aiming to visualize neurons and their connections. However, these techniques are often very labor intensive and do not scale well to the complexity of mammalian brains. We recently leveraged the speed and parallelization of DNA sequencing to map the projections of thousands of single neurons in single experiments, and to map cortical mesoscale connectivity in single mice. Here, I review the state of sequencing-based neuroanatomy, and discuss future directions in synaptic connectivity mapping and comparative connectomics.
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221
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Crow M, Gillis J. Single cell RNA-sequencing: replicability of cell types. Curr Opin Neurobiol 2019; 56:69-77. [PMID: 30654233 PMCID: PMC6551252 DOI: 10.1016/j.conb.2018.12.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 12/03/2018] [Accepted: 12/09/2018] [Indexed: 01/09/2023]
Abstract
Recent technical advances have enabled transcriptomics experiments at an unprecedented scale, and single-cell profiles from neural tissue are accumulating rapidly. There has been considerable effort to use these profiles to understand cell diversity, primarily through unsupervised clustering and differential expression analysis. However, current practices to validate these findings vary. In this review, we describe recent efforts to evaluate clusters from single-cell RNA-sequencing data, and provide a framework for considering current evidence and practices in terms of their capacity to establish principles of cell biology. Single-cell RNA-sequencing has already transformed neuroscience. By facilitating detailed comparative and genetic perturbation analyses, it may provide the tools to uncover fundamental mechanisms of neural diversity throughout the tree of life.
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Affiliation(s)
- Megan Crow
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA
| | - Jesse Gillis
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA.
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222
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Chudnovskiy A, Pasqual G, Victora GD. Studying interactions between dendritic cells and T cells in vivo. Curr Opin Immunol 2019; 58:24-30. [PMID: 30884422 PMCID: PMC6927575 DOI: 10.1016/j.coi.2019.02.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 02/09/2019] [Accepted: 02/14/2019] [Indexed: 12/12/2022]
Abstract
Antigen presentation is the key first step in the establishment of an antigen-specific T cell response. Among professional antigen presenting cells (APCs), dendritic cells (DCs) are the major population responsible for the priming of both CD4+ and CD8+ naïve T cells. This priming requires physical interaction between the DC and the T cell; during which signals are exchanged that determine both the magnitude and the quality of the ensuing response. The nature of these signals varies widely depending on the nature of the antigen, the anatomical site in which they take place, and the phenotype of the antigen-presenting DC, making the study of the dynamics, microanatomical distribution and phenotypic variation of DCs a key part of our understanding of adaptive immunity. Here, we provide a brief survey of how our view of T cell activation by DCs has evolved over recent years as intravital multiphoton microscopy and other emerging technologies have expanded our ability to study these events in vivo.
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Affiliation(s)
- Aleksey Chudnovskiy
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA.
| | - Giulia Pasqual
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA
| | - Gabriel D Victora
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA.
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223
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Xia C, Babcock HP, Moffitt JR, Zhuang X. Multiplexed detection of RNA using MERFISH and branched DNA amplification. Sci Rep 2019; 9:7721. [PMID: 31118500 PMCID: PMC6531529 DOI: 10.1038/s41598-019-43943-8] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 05/02/2019] [Indexed: 01/21/2023] Open
Abstract
Multiplexed error-robust fluorescence in situ hybridization (MERFISH) allows simultaneous imaging of numerous RNA species in their native cellular environment and hence spatially resolved single-cell transcriptomic measurements. However, the relatively modest brightness of signals from single RNA molecules can become limiting in a number of applications, such as increasing the imaging throughput, imaging shorter RNAs, and imaging samples with high degrees of background, such as some tissue samples. Here, we report a branched DNA (bDNA) amplification approach for MERFISH measurements. This approach produces a drastic signal increase in RNA FISH samples without increasing the fluorescent spot size for individual RNAs or increasing the variation in brightness from spot to spot, properties that are important for MERFISH imaging. Using this amplification approach in combination with MERFISH, we demonstrated RNA imaging and profiling with a near 100% detection efficiency. We further demonstrated that signal amplification improves MERFISH performance when fewer FISH probes are used for each RNA species, which should allow shorter RNAs to be imaged. We anticipate that the combination of bDNA amplification with MERFISH should facilitate many other applications and extend the range of biological questions that can be addressed by this technique in both cell culture and tissues.
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Affiliation(s)
- Chenglong Xia
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, and Department of Physics, Harvard University, Cambridge, MA, 02138, USA
| | - Hazen P Babcock
- Center for Advanced Imaging, Harvard University, Cambridge, MA, 02138, USA
| | - Jeffrey R Moffitt
- Program in Cellular and Molecular Medicine, Boston Children's Hospital; Department of Microbiology, Harvard Medical School, Boston, MA, 02115, USA.
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, and Department of Physics, Harvard University, Cambridge, MA, 02138, USA.
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224
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Ye X, Fang X, Li Y, Wang L, Li X, Kong J. Sequence-Specific Probe-Mediated Isothermal Amplification for the Single-Copy Sensitive Detection of Nucleic Acid. Anal Chem 2019; 91:6738-6745. [PMID: 31046251 DOI: 10.1021/acs.analchem.9b00812] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
There is currently the lack of a method for precisely monitoring the progress of isothermal amplification reactions by means of sequence-specific fluorescent probes like the TaqMan probe used in the PCR system. Here, we created a circular fluorescent probe-mediated isothermal amplification (CFPA) method. This novel method uses two circular fluorescent probes and Bst DNA polymerase to construct an overlapping structure that can be cut off by flap structure-specific endonuclease 1, separating the fluorescence and quenching groups on the probes. The results showed single-copy sensitivity, ultrahigh specificity, stability (C.V. < 0.1), and anti-interference ability in detecting nucleic acid samples. A clinical trial demonstrated the perfect effectiveness of this method in the diagnosis of rotavirus infection and consistency with the gold standard method used in the clinic ( p > 0.05). In summary, we present a new, reliable, and precise isothermal amplification approach for applications in biomedical research and the clinical accurate diagnosis of pathogen infections.
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Affiliation(s)
- Xin Ye
- Department of Chemistry and Institutes of Biomedical Sciences , Fudan University , Shanghai 200433 , P. R. China
| | - Xueen Fang
- Department of Chemistry and Institutes of Biomedical Sciences , Fudan University , Shanghai 200433 , P. R. China
| | - Yang Li
- Shanghai Suchuang Diagnostic Products Co., Ltd, Shanghai 201318 , P. R. China.,Shanghai Suxin Biotechnology Co. Ltd, Shanghai 201318 , P. R. China
| | - Lijuan Wang
- Shanghai Suchuang Diagnostic Products Co., Ltd, Shanghai 201318 , P. R. China.,Shanghai Suxin Biotechnology Co. Ltd, Shanghai 201318 , P. R. China
| | - Xinxin Li
- Shanghai Suchuang Diagnostic Products Co., Ltd, Shanghai 201318 , P. R. China.,Shanghai Suxin Biotechnology Co. Ltd, Shanghai 201318 , P. R. China
| | - Jilie Kong
- Department of Chemistry and Institutes of Biomedical Sciences , Fudan University , Shanghai 200433 , P. R. China
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225
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Litman T. Personalized medicine-concepts, technologies, and applications in inflammatory skin diseases. APMIS 2019; 127:386-424. [PMID: 31124204 PMCID: PMC6851586 DOI: 10.1111/apm.12934] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 01/31/2019] [Indexed: 12/19/2022]
Abstract
The current state, tools, and applications of personalized medicine with special emphasis on inflammatory skin diseases like psoriasis and atopic dermatitis are discussed. Inflammatory pathways are outlined as well as potential targets for monoclonal antibodies and small-molecule inhibitors.
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Affiliation(s)
- Thomas Litman
- Department of Immunology and MicrobiologyUniversity of CopenhagenCopenhagenDenmark
- Explorative Biology, Skin ResearchLEO Pharma A/SBallerupDenmark
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226
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Almouemen N, Kelly HM, O'Leary C. Tissue Engineering: Understanding the Role of Biomaterials and Biophysical Forces on Cell Functionality Through Computational and Structural Biotechnology Analytical Methods. Comput Struct Biotechnol J 2019; 17:591-598. [PMID: 31080565 PMCID: PMC6502738 DOI: 10.1016/j.csbj.2019.04.008] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 03/26/2019] [Accepted: 04/13/2019] [Indexed: 12/13/2022] Open
Abstract
Within the past 25 years, tissue engineering (TE) has grown enormously as a science and as an industry. Although classically concerned with the recapitulation of tissue and organ formation in our body for regenerative medicine, the evolution of TE research is intertwined with progress in other fields through the examination of cell function and behaviour in isolated biomimetic microenvironments. As such, TE applications now extend beyond the field of tissue regeneration research, operating as a platform for modifiable, physiologically-representative in vitro models with the potential to improve the translation of novel therapeutics into the clinic through a more informed understanding of the relevant molecular biology, structural biology, anatomy, and physiology. By virtue of their biomimicry, TE constructs incorporate features of extracellular macrostructure, molecular adhesive moieties, and biomechanical properties, converging with computational and structural biotechnology advances. Accordingly, this mini-review serves to contextualise TE for the computational and structural biotechnology reader and provides an outlook on how the disciplines overlap with respect to relevant advanced analytical applications.
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Affiliation(s)
- Nour Almouemen
- School of Pharmacy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
- Tissue Engineering Research Group, Dept. of Anatomy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
- Advanced Materials and Bioengineering Research (AMBER) Centre, Royal College of Surgeons in Ireland and Trinity College Dublin, Dublin 2, Ireland
| | - Helena M. Kelly
- School of Pharmacy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
- Tissue Engineering Research Group, Dept. of Anatomy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
| | - Cian O'Leary
- School of Pharmacy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
- Tissue Engineering Research Group, Dept. of Anatomy, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland
- Advanced Materials and Bioengineering Research (AMBER) Centre, Royal College of Surgeons in Ireland and Trinity College Dublin, Dublin 2, Ireland
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227
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Salmén F, Ståhl PL, Mollbrink A, Navarro JF, Vickovic S, Frisén J, Lundeberg J. Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections. Nat Protoc 2019; 13:2501-2534. [PMID: 30353172 DOI: 10.1038/s41596-018-0045-2] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Spatial resolution of gene expression enables gene expression events to be pinpointed to a specific location in biological tissue. Spatially resolved gene expression in tissue sections is traditionally analyzed using immunohistochemistry (IHC) or in situ hybridization (ISH). These technologies are invaluable tools for pathologists and molecular biologists; however, their throughput is limited to the analysis of only a few genes at a time. Recent advances in RNA sequencing (RNA-seq) have made it possible to obtain unbiased high-throughput gene expression data in bulk. Spatial Transcriptomics combines the benefits of traditional spatially resolved technologies with the massive throughput of RNA-seq. Here, we present a protocol describing how to apply the Spatial Transcriptomics technology to mammalian tissue. This protocol combines histological staining and spatially resolved RNA-seq data from intact tissue sections. Once suitable tissue-specific conditions have been established, library construction and sequencing can be completed in ~5-6 d. Data processing takes a few hours, with the exact timing dependent on the sequencing depth. Our method requires no special instruments and can be performed in any laboratory with access to a cryostat, microscope and next-generation sequencing.
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Affiliation(s)
- Fredrik Salmén
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.,Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, Utrecht, The Netherlands
| | - Patrik L Ståhl
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
| | - Annelie Mollbrink
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - José Fernández Navarro
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Sanja Vickovic
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.,Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonas Frisén
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
| | - Joakim Lundeberg
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
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228
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Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science 2019; 363:1463-1467. [PMID: 30923225 DOI: 10.1126/science.aaw1219] [Citation(s) in RCA: 1129] [Impact Index Per Article: 225.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 02/28/2019] [Indexed: 12/24/2022]
Abstract
Spatial positions of cells in tissues strongly influence function, yet a high-throughput, genome-wide readout of gene expression with cellular resolution is lacking. We developed Slide-seq, a method for transferring RNA from tissue sections onto a surface covered in DNA-barcoded beads with known positions, allowing the locations of the RNA to be inferred by sequencing. Using Slide-seq, we localized cell types identified by single-cell RNA sequencing datasets within the cerebellum and hippocampus, characterized spatial gene expression patterns in the Purkinje layer of mouse cerebellum, and defined the temporal evolution of cell type-specific responses in a mouse model of traumatic brain injury. These studies highlight how Slide-seq provides a scalable method for obtaining spatially resolved gene expression data at resolutions comparable to the sizes of individual cells.
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Affiliation(s)
- Samuel G Rodriques
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Robert R Stickels
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.,Graduate School of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.,Division of Medical Science, Harvard Medical School, Boston, MA 02115, USA
| | | | - Carly A Martin
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Evan Murray
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | | | - Joshua Welch
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Linlin M Chen
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
| | - Evan Z Macosko
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. .,Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
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229
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Paolillo C, Londin E, Fortina P. Single-Cell Genomics. Clin Chem 2019; 65:972-985. [PMID: 30872376 DOI: 10.1373/clinchem.2017.283895] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 01/28/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Single-cell genomics is an approach to investigate cell heterogeneity and to identify new molecular features correlated with clinical outcomes. This approach allows identification of the complexity of cell diversity in a sample without the loss of information that occurs when multicellular or bulk tissue samples are analyzed. CONTENT The first single-cell RNA-sequencing study was published in 2009, and since then many more studies and single-cell sequencing methods have been published. These studies have had a major impact on several fields, including microbiology, neurobiology, cancer, and developmental biology. Recently, improvements in reliability and the development of commercial single-cell isolation platforms are opening the potential of this technology to the clinical laboratory. SUMMARY In this review we provide an overview of the current state of single-cell genomics. We describe opportunities in clinical research and medical applications.
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Affiliation(s)
- Carmela Paolillo
- Division of Precision and Computational Diagnostics, Department of Clinical Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Eric Londin
- Computational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA
| | - Paolo Fortina
- Department of Cancer Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA; .,Department of Molecular Medicine, Sapienza University, Rome, Italy
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230
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Highly Multiplexed Fluorescence in Situ Hybridization for in Situ Genomics. J Mol Diagn 2019; 21:390-407. [PMID: 30862547 DOI: 10.1016/j.jmoldx.2019.01.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 12/16/2018] [Accepted: 01/30/2019] [Indexed: 12/31/2022] Open
Abstract
The quantification of changes in gene copy number is critical to our understanding of tumor biology and for the clinical management of cancer patients. DNA fluorescence in situ hybridization is the gold standard method to detect copy number alterations, but it is limited by the number of genes one can quantify simultaneously. To increase the throughput of this informative technique, a fluorescent bar-code system for the unique labeling of dozens of genes and an automated image analysis algorithm that enabled their simultaneous hybridization for the quantification of gene copy numbers were devised. We demonstrate the reliability of this multiplex approach on normal human lymphocytes, metaphase spreads of transformed cell lines, and cultured circulating tumor cells. It also opens the door to the development of gene panels for more comprehensive analysis of copy number changes in tissue, including the study of heterogeneity and of high-throughput clinical assays that could provide rapid quantification of gene copy numbers in samples with limited cellularity, such as circulating tumor cells.
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231
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Kalisky T, Oriel S, Bar-Lev TH, Ben-Haim N, Trink A, Wineberg Y, Kanter I, Gilad S, Pyne S. A brief review of single-cell transcriptomic technologies. Brief Funct Genomics 2019; 17:64-76. [PMID: 28968725 DOI: 10.1093/bfgp/elx019] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
In recent years, there has been an effort to develop new technologies for measuring gene expression and sequence information from thousands of individual cells. Large data sets that were obtained using these 'single cell' technologies have allowed scientists to address fundamental questions in biomedicine ranging from stems cells and development to cancer and immunology. Here, we provide a brief review of recent developments in single-cell technology. Our intention is to provide a quick background for newcomers to the field as well as a deeper description of some of the leading technologies to date.
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232
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A microfluidic platform towards automated multiplexed in situ sequencing. Sci Rep 2019; 9:3542. [PMID: 30837556 PMCID: PMC6401021 DOI: 10.1038/s41598-019-40026-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 02/08/2019] [Indexed: 01/06/2023] Open
Abstract
Advancements in multiplexed in situ RNA profiling techniques have given unprecedented insight into spatial organization of tissues by enabling single-molecule quantification and sub-micron localization of dozens to thousands of RNA species simultaneously in cells and entire tissue sections. However, the lack of automation of the associated complex experimental procedures represents a potential hurdle towards their routine use in laboratories. Here, we demonstrate an approach towards automated generation and sequencing of barcoded mRNA amplicons in situ, directly in fixed cells. This is achieved through adaptation of a microfluidic tool compatible with standard microscope slides and cover glasses. The adapted tool combines a programmable reagent delivery system with temperature controller and flow cell to perform established in situ sequencing protocols, comprising hybridization and ligation of gene-specific padlock probes, rolling circle amplification of the probes yielding barcoded amplicons and identification of amplicons through barcode sequencing. By adapting assay parameters (e.g. enzyme concentration and temperature), we achieve a near-identical performance in identifying mouse beta-actin transcripts, in comparison with the conventional manual protocol. The technically adapted assay features i) higher detection efficiency, ii) shorter protocol time, iii) lower consumption of oligonucleotide reagents but slightly more enzyme. Such an automated microfluidic tissue processor for in situ sequencing studies would greatly enhance its research potentials especially for cancer diagnostics, thus paving way to rapid and effective therapies.
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233
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Sabri L, Huang Q, Liu JN, Cunningham BT. Design of anapole mode electromagnetic field enhancement structures for biosensing applications. OPTICS EXPRESS 2019; 27:7196-7212. [PMID: 30876288 DOI: 10.1364/oe.27.007196] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 02/18/2019] [Indexed: 06/09/2023]
Abstract
The design of an all-dielectric nanoantenna based on nonradiating "anapole" modes is studied for biosensing applications in an aqueous environment, using FDTD electromagnetic simulation. The strictly confined electromagnetic field within a circular or rectangular opening at the center of a cylindrical silicon disk produces a single point electromagnetic hotspot with up to 6.5x enhancement of |E|, for the 630-650 nm wavelength range, and we can increase the value up to 25x by coupling additional electromagnetic energy from an underlying PEC-backed substrate. We characterize the effects of the substrate design and slot dimensions on the field enhancement magnitude, for devices operating in a water medium.
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234
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Salvador-Martínez I, Grillo M, Averof M, Telford MJ. Is it possible to reconstruct an accurate cell lineage using CRISPR recorders? eLife 2019; 8:e40292. [PMID: 30688650 PMCID: PMC6349403 DOI: 10.7554/elife.40292] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 01/11/2019] [Indexed: 02/02/2023] Open
Abstract
Cell lineages provide the framework for understanding how cell fates are decided during development. Describing cell lineages in most organisms is challenging; even a fruit fly larva has ~50,000 cells and a small mammal has >1 billion cells. Recently, the idea of applying CRISPR to induce mutations during development, to be used as heritable markers for lineage reconstruction, has been proposed by several groups. While an attractive idea, its practical value depends on the accuracy of the cell lineages that can be generated. Here, we use computer simulations to estimate the performance of these approaches under different conditions. We incorporate empirical data on CRISPR-induced mutation frequencies in Drosophila. We show significant impacts from multiple biological and technical parameters - variable cell division rates, skewed mutational outcomes, target dropouts and different sequencing strategies. Our approach reveals the limitations of published CRISPR recorders, and indicates how future implementations can be optimised. Editorial note This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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Affiliation(s)
- Irepan Salvador-Martínez
- Centre for Life’s Origins and Evolution, Department of Genetics Evolution and EnvironmentUniversity College LondonLondonUnited Kingdom
| | - Marco Grillo
- Institut de Génomique Fonctionnelle de Lyon (IGFL)École Normale Supérieure de LyonLyonFrance
- Centre National de la Recherche Scientifique (CNRS)ParisFrance
| | - Michalis Averof
- Institut de Génomique Fonctionnelle de Lyon (IGFL)École Normale Supérieure de LyonLyonFrance
- Centre National de la Recherche Scientifique (CNRS)ParisFrance
| | - Maximilian J Telford
- Centre for Life’s Origins and Evolution, Department of Genetics Evolution and EnvironmentUniversity College LondonLondonUnited Kingdom
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235
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Abstract
The combination of next generation sequencing (NGS) and automated liquid handling platforms has led to a revolution in single-cell genomic studies. However, many molecules that are critical to understanding the functional roles of cells in a complex tissue or organs, are not directly encoded in the genome, and therefore cannot be profiled with NGS. Lipids, for example, play a critical role in many metabolic processes but cannot be detected by sequencing. Recent developments in quantitative imaging, particularly coherent Raman scattering (CRS) techniques, have produced a suite of tools for studying lipid content in single cells. This article reviews CRS imaging and computational image processing techniques for non-destructive profiling of dynamic changes in lipid composition and spatial distribution at the single-cell level. As quantitative CRS imaging progresses synergistically with microfluidic and microscopic platforms for single-cell genomic analysis, we anticipate that these techniques will bring researchers closer towards combined lipidomic and genomic analysis.
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Affiliation(s)
- Anushka Gupta
- UC Berkeley-UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley Graduate Division, Berkeley, California, USA.
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236
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Haimovich G, Gerst JE. Detection of mRNA Transfer Between Mammalian Cells in Coculture by Single-Molecule Fluorescent In Situ Hybridization (smFISH). Methods Mol Biol 2019; 2038:109-129. [PMID: 31407281 DOI: 10.1007/978-1-4939-9674-2_8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In eukaryotic cells, a small percentage of mRNA molecules can undergo transfer from one cell to another. mRNA transfer occurs primarily via membrane nanotubes, which are long thin protrusions that are produced by numerous cell types and can connect cells that can be up to hundreds of microns apart. Potentially, mRNAs might also transfer via extracellular vesicles (EVs). Here we describe a method to detect transferred mRNA in cocultures of two different cell types and to distinguish between nanotube- and EVs-mediated transfer. This method uses single molecule fluorescent in situ hybridization (smFISH) to provide an accurate and quantitative detection of transferred mRNA molecules and their subcellular localization. Following the guidelines presented here will allow the user to investigate mRNA transfer of most transcripts in any co-culture system. In addition, we present modifications that improve nanotube preservation during the smFISH procedure.
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Affiliation(s)
- Gal Haimovich
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
| | - Jeffrey E Gerst
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
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237
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Wang HLV, Chekanova JA. An Overview of Methodologies in Studying lncRNAs in the High-Throughput Era: When Acronyms ATTACK! Methods Mol Biol 2019; 1933:1-30. [PMID: 30945176 PMCID: PMC6684206 DOI: 10.1007/978-1-4939-9045-0_1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The discovery of pervasive transcription in eukaryotic genomes provided one of many surprising (and perhaps most surprising) findings of the genomic era and led to the uncovering of a large number of previously unstudied transcriptional events. This pervasive transcription leads to the production of large numbers of noncoding RNAs (ncRNAs) and thus opened the window to study these diverse, abundant transcripts of unclear relevance and unknown function. Since that discovery, recent advances in high-throughput sequencing technologies have identified a large collection of ncRNAs, from microRNAs to long noncoding RNAs (lncRNAs). Subsequent discoveries have shown that many lncRNAs play important roles in various eukaryotic processes; these discoveries have profoundly altered our understanding of the regulation of eukaryotic gene expression. Although the identification of ncRNAs has become a standard experimental approach, the functional characterization of these diverse ncRNAs remains a major challenge. In this chapter, we highlight recent progress in the methods to identify lncRNAs and the techniques to study the molecular function of these lncRNAs and the application of these techniques to the study of plant lncRNAs.
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Affiliation(s)
- Hsiao-Lin V Wang
- Guangxi Key Laboratory of Sugarcane Biology, Guangxi University, Nanning, Guangxi, China
- Present address: Department of Biology, Emory University, Atlanta, GA, USA
| | - Julia A Chekanova
- Guangxi Key Laboratory of Sugarcane Biology, Guangxi University, Nanning, Guangxi, China.
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238
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Emergence of Bias During the Synthesis and Amplification of cDNA for scRNA-seq. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1068:149-158. [PMID: 29943302 DOI: 10.1007/978-981-13-0502-3_12] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The advent of single-cell omics technology has promoted our understanding of the genomic, epigenomic, and transcriptomic heterogeneity in individual cells. Compared to traditional sequencing studies using bulk cells, single-cell transcriptome technology is naturally more dynamic for in depth analysis of genomic variation resulting from cell division and is useful in unraveling the regulatory mechanisms of gene networks in many diseases. However, there are still some limitations of current single-cell RNA sequencing (scRNA-seq) protocols. Biases that arise during the RNA reverse transcription and cDNA pre-amplification steps are the most common problems and play pivotal roles in limiting the quantitative accuracy of scRNA-seq. In this review, we will describe how these biases emerge and impact scRNA-seq protocols. Moreover, we will introduce several current and convenient modified scRNA-seq methods that allow for bias to be decreased and estimated.
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239
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Abstract
Cellular heterogeneity within and across tumors has been a major obstacle in understanding and treating cancer, and the complex heterogeneity is masked if bulk tumor tissues are used for analysis. The advent of rapidly developing single-cell sequencing technologies, which include methods related to single-cell genome, epigenome, transcriptome, and multi-omics sequencing, have been applied to cancer research and led to exciting new findings in the fields of cancer evolution, metastasis, resistance to therapy, and tumor microenvironment. In this review, we discuss recent advances and limitations of these new technologies and their potential applications in cancer studies.
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Affiliation(s)
- Xianwen Ren
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China.
| | - Boxi Kang
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China
| | - Zemin Zhang
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China.
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240
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Himmel LE, Hackett TA, Moore JL, Adams WR, Thomas G, Novitskaya T, Caprioli RM, Zijlstra A, Mahadevan-Jansen A, Boyd KL. Beyond the H&E: Advanced Technologies for in situ Tissue Biomarker Imaging. ILAR J 2018; 59:51-65. [PMID: 30462242 PMCID: PMC6645175 DOI: 10.1093/ilar/ily004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 04/27/2018] [Accepted: 06/05/2018] [Indexed: 02/07/2023] Open
Abstract
For decades, histopathology with routine hematoxylin and eosin staining has been and remains the gold standard for reaching a morphologic diagnosis in tissue samples from humans and veterinary species. However, within the past decade, there has been exponential growth in advanced techniques for in situ tissue biomarker imaging that bridge the divide between anatomic and molecular pathology. It is now possible to simultaneously observe localization and expression magnitude of multiple protein, nucleic acid, and molecular targets in tissue sections and apply machine learning to synthesize vast, image-derived datasets. As these technologies become more sophisticated and widely available, a team-science approach involving subspecialists with medical, engineering, and physics backgrounds is critical to upholding quality and validity in studies generating these data. The purpose of this manuscript is to detail the scientific premise, tools and training, quality control, and data collection and analysis considerations needed for the most prominent advanced imaging technologies currently applied in tissue sections: immunofluorescence, in situ hybridization, laser capture microdissection, matrix-assisted laser desorption ionization imaging mass spectrometry, and spectroscopic/optical methods. We conclude with a brief overview of future directions for ex vivo and in vivo imaging techniques.
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Affiliation(s)
- Lauren E Himmel
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Troy A Hackett
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Jessica L Moore
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Wilson R Adams
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Giju Thomas
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Tatiana Novitskaya
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Richard M Caprioli
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Andries Zijlstra
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Anita Mahadevan-Jansen
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
| | - Kelli L Boyd
- Lauren E. Himmel, DVM, PhD, is an assistant professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee. Troy A. Hackett, PhD, is a professor in the Department of Hearing and Speech Sciences at Vanderbilt University Medical Center in Nashville, Tennessee. Jessica L. Moore, PhD, is a postdoctoral research fellow in the Mass Spectrometry Research Center at the Vanderbilt University School of Medicine in Nashville, Tennessee. Wilson R. Adams, BS, is graduate student in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Giju Thomas, PhD, is a post-doctoral researcher in the Biophotonics Center and Department of Biomedical Engineering at Vanderbilt University in Nashville, Tennessee. Tatiana Novitskaya, MD, PhD, is a staff scientist in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center. Richard M. Caprioli, PhD, is a professor in the Department of Chemistry at the Vanderbilt University School of Medicine in Nashville, Tennessee. Andries Zijlstra, PhD, is an associate professor in the Department of Pathology, Microbiology and Immunology at Vanderbilt University Medical Center in Nashville, Tennessee. Anita Mahadevan-Jansen, PhD, is a professor in the Department of Biomedical Engineering at the Vanderbilt University School of Engineering and Department of Neurosurgery at Vanderbilt University Medical Center in Nashville, Tennessee. Kelli L. Boyd, DVM, PhD, is a professor and veterinary pathologist in the Division of Comparative Medicine at Vanderbilt University Medical Center in Nashville, Tennessee
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241
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Tumour heterogeneity and metastasis at single-cell resolution. Nat Cell Biol 2018; 20:1349-1360. [PMID: 30482943 DOI: 10.1038/s41556-018-0236-7] [Citation(s) in RCA: 351] [Impact Index Per Article: 58.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 10/24/2018] [Indexed: 02/07/2023]
Abstract
Tumours comprise a heterogeneous collection of cells with distinct genetic and phenotypic properties that can differentially promote progression, metastasis and drug resistance. Emerging single-cell technologies provide a new opportunity to profile individual cells within tumours and investigate what roles they play in these processes. This Review discusses key technological considerations for single-cell studies in cancer, new findings using single-cell technologies and critical open questions for future applications.
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242
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Valdes-Mora F, Handler K, Law AMK, Salomon R, Oakes SR, Ormandy CJ, Gallego-Ortega D. Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology. Front Immunol 2018; 9:2582. [PMID: 30483257 PMCID: PMC6240655 DOI: 10.3389/fimmu.2018.02582] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 10/19/2018] [Indexed: 12/21/2022] Open
Abstract
Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches.
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Affiliation(s)
- Fatima Valdes-Mora
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.,St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Kristina Handler
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Andrew M K Law
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Robert Salomon
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Samantha R Oakes
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.,The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Christopher J Ormandy
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.,The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - David Gallego-Ortega
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.,The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
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243
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Wang J, Kreutz JE, Thompson AM, Qin Y, Sheen AM, Wang J, Wu L, Xu S, Chang M, Raugi DN, Smith RA, Gottlieb GS, Chiu DT. SD-chip enabled quantitative detection of HIV RNA using digital nucleic acid sequence-based amplification (dNASBA). LAB ON A CHIP 2018; 18:3501-3506. [PMID: 30351338 PMCID: PMC6219917 DOI: 10.1039/c8lc00956b] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Quantitative detection of RNA is important in molecular biology and clinical diagnostics. Nucleic acid sequence-based amplification (NASBA), a single-step method to amplify single-stranded RNA, is attractive for use in point-of-care (POC) diagnostics because it is an isothermal technique that is as sensitive as RT-PCR with a shorter reaction time. However, NASBA is limited in its ability to provide accurate quantitative information, such as viral load or RNA copy number. Here we test a digital format of NASBA (dNASBA) using a self-digitization (SD) chip platform, and apply it to quantifying HIV-1 RNA. We demonstrate that dNASBA is more sensitive and accurate than the real-time quantitative NASBA, and can be used to quantify HIV-1 RNA in plasma samples. Digital NASBA is thus a promising POC diagnostics tool for use in resource-limited settings.
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Affiliation(s)
- Jiasi Wang
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA.
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244
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Fluorescence in situ hybridization (FISH): History, limitations and what to expect from micro-scale FISH? MICRO AND NANO ENGINEERING 2018. [DOI: 10.1016/j.mne.2018.10.006] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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245
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Spatial organization of the somatosensory cortex revealed by osmFISH. Nat Methods 2018; 15:932-935. [DOI: 10.1038/s41592-018-0175-z] [Citation(s) in RCA: 237] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Accepted: 08/08/2018] [Indexed: 01/07/2023]
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246
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Ackers-Johnson M, Tan WLW, Foo RSY. Following hearts, one cell at a time: recent applications of single-cell RNA sequencing to the understanding of heart disease. Nat Commun 2018; 9:4434. [PMID: 30375391 PMCID: PMC6207674 DOI: 10.1038/s41467-018-06894-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 09/28/2018] [Indexed: 11/26/2022] Open
Abstract
The mammalian heart contains heterogeneous cell types contributing to pathological changes in cardiac disease. In this Comment, we explore how single-cell transcriptomic approaches are unveiling intricate cellular mechanisms and gene co-expression networks that regulate the workings, and failings, of the heart.
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Affiliation(s)
- Matthew Ackers-Johnson
- Cardiovascular Research Institute, National University Health System, 14 Medical Drive, Singapore, 117599, Singapore
- Genome Institute of Singapore, 60 Biopolis Street, Singapore, 1368672, Singapore
| | - Wilson Lek Wen Tan
- Cardiovascular Research Institute, National University Health System, 14 Medical Drive, Singapore, 117599, Singapore
- Genome Institute of Singapore, 60 Biopolis Street, Singapore, 1368672, Singapore
| | - Roger Sik-Yin Foo
- Cardiovascular Research Institute, National University Health System, 14 Medical Drive, Singapore, 117599, Singapore.
- Genome Institute of Singapore, 60 Biopolis Street, Singapore, 1368672, Singapore.
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247
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George L, Indig FE, Abdelmohsen K, Gorospe M. Intracellular RNA-tracking methods. Open Biol 2018; 8:rsob.180104. [PMID: 30282659 PMCID: PMC6223214 DOI: 10.1098/rsob.180104] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 09/03/2018] [Indexed: 12/26/2022] Open
Abstract
RNA tracking allows researchers to visualize RNA molecules in cells and tissues, providing important spatio-temporal information regarding RNA dynamics and function. Methods such as fluorescent in situ hybridization (FISH) and molecular beacons rely on complementary oligonucleotides to label and view endogenous transcripts. Other methods create artificial chimeric transcripts coupled with bacteriophage-derived coat proteins (e.g. MS2, λN) to tag molecules in live cells. In other approaches, endogenous RNAs are recognized by complementary RNAs complexed with noncatalytic Cas proteins. Each technique has its own set of strengths and limitations that must be considered when planning an experiment. Here, we discuss the mechanisms, advantages, and weaknesses of in situ hybridization, molecular beacons, MS2 tagging and Cas-derived systems, as well as how RNA tracking can be employed to study various aspects of molecular biology.
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Affiliation(s)
- Logan George
- Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA.,Confocal Core Facility, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Fred E Indig
- Confocal Core Facility, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Kotb Abdelmohsen
- Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Myriam Gorospe
- Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
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248
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Dong X, Liao Z, Gritsch D, Hadzhiev Y, Bai Y, Locascio JJ, Guennewig B, Liu G, Blauwendraat C, Wang T, Adler CH, Hedreen JC, Faull RLM, Frosch MP, Nelson PT, Rizzu P, Cooper AA, Heutink P, Beach TG, Mattick JS, Müller F, Scherzer CR. Enhancers active in dopamine neurons are a primary link between genetic variation and neuropsychiatric disease. Nat Neurosci 2018; 21:1482-1492. [PMID: 30224808 PMCID: PMC6334654 DOI: 10.1038/s41593-018-0223-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Accepted: 07/23/2018] [Indexed: 01/07/2023]
Abstract
Enhancers function as DNA logic gates and may control specialized functions of billions of neurons. Here we show a tailored program of noncoding genome elements active in situ in physiologically distinct dopamine neurons of the human brain. We found 71,022 transcribed noncoding elements, many of which were consistent with active enhancers and with regulatory mechanisms in zebrafish and mouse brains. Genetic variants associated with schizophrenia, addiction, and Parkinson's disease were enriched in these elements. Expression quantitative trait locus analysis revealed that Parkinson's disease-associated variants on chromosome 17q21 cis-regulate the expression of an enhancer RNA in dopamine neurons. This study shows that enhancers in dopamine neurons link genetic variation to neuropsychiatric traits.
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Affiliation(s)
- Xianjun Dong
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Zhixiang Liao
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - David Gritsch
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Yavor Hadzhiev
- Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Yunfei Bai
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Joseph J Locascio
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Boris Guennewig
- Sydney Medical School, Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
- Division of Neuroscience, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- St Vincent's Clinical School, UNSW Sydney, Sydney, New South Wales, Australia
| | - Ganqiang Liu
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | | | - Tao Wang
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | | | - John C Hedreen
- Harvard Brain Tissue Resource Center, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Richard L M Faull
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, MA, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
| | - Patrizia Rizzu
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Antony A Cooper
- Division of Neuroscience, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- St Vincent's Clinical School, UNSW Sydney, Sydney, New South Wales, Australia
| | - Peter Heutink
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | | | - John S Mattick
- Division of Neuroscience, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- St Vincent's Clinical School, UNSW Sydney, Sydney, New South Wales, Australia
| | - Ferenc Müller
- Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Clemens R Scherzer
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA.
- Center for Advanced Parkinson's Disease Research of Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, MA, USA.
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA.
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249
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Andreassi C, Crerar H, Riccio A. Post-transcriptional Processing of mRNA in Neurons: The Vestiges of the RNA World Drive Transcriptome Diversity. Front Mol Neurosci 2018; 11:304. [PMID: 30210293 PMCID: PMC6121099 DOI: 10.3389/fnmol.2018.00304] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 08/09/2018] [Indexed: 12/17/2022] Open
Abstract
Neurons are morphologically complex cells that rely on the compartmentalization of protein expression to develop and maintain their extraordinary cytoarchitecture. This formidable task is achieved, at least in part, by targeting mRNA to subcellular compartments where they are rapidly translated. mRNA transcripts are the conveyor of genetic information from DNA to the translational machinery, however, they are also endowed with additional functions linked to both the coding sequence (open reading frame, or ORF) and the flanking 5′ and 3′ untranslated regions (UTRs), that may harbor coding-independent functions. In this review, we will highlight recent evidences supporting new coding-dependent and -independent functions of mRNA and discuss how nuclear and cytoplasmic post-transcriptional modifications of mRNA contribute to localization and translation in mammalian cells with specific emphasis on neurons. We also describe recently developed techniques that can be employed to study RNA dynamics at subcellular level in eukaryotic cells in developing and regenerating neurons.
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Affiliation(s)
- Catia Andreassi
- MRC Laboratory for Molecular Cell Biology, University College London, London, United Kingdom
| | - Hamish Crerar
- MRC Laboratory for Molecular Cell Biology, University College London, London, United Kingdom
| | - Antonella Riccio
- MRC Laboratory for Molecular Cell Biology, University College London, London, United Kingdom
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250
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Jusino S, Fernández-Padín FM, Saavedra HI. Centrosome aberrations and chromosome instability contribute to tumorigenesis and intra-tumor heterogeneity. ACTA ACUST UNITED AC 2018; 4. [PMID: 30381801 PMCID: PMC6205736 DOI: 10.20517/2394-4722.2018.24] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Centrosomes serve as the major microtubule organizing centers in cells and thereby contribute to cell shape, polarity, and motility. Also, centrosomes ensure equal chromosome segregation during mitosis. Centrosome aberrations arise when the centrosome cycle is deregulated, or as a result of cytokinesis failure. A long-standing postulate is that centrosome aberrations are involved in the initiation and progression of cancer. However, this notion has been a subject of controversy because until recently the relationship has been correlative. Recently, it was shown that numerical or structural centrosome aberrations can initiate tumors in certain tissues in mice, as well as invasion. Particularly, we will focus on centrosome amplification and chromosome instability as drivers of intra-tumor heterogeneity and their consequences in cancer. We will also discuss briefly the controversies surrounding this theory to highlight the fact that the role of both centrosome amplification and chromosome instability in cancer is highly context-dependent. Further, we will discuss single-cell sequencing as a novel technique to understand intra-tumor heterogeneity and some therapeutic approaches to target chromosome instability.
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Affiliation(s)
- Shirley Jusino
- Basic Sciences Department, Division of Pharmacology and Toxicology, Ponce Health Sciences University, Ponce Research Institute, Ponce, PR 00732, USA
| | - Fabiola M Fernández-Padín
- Basic Sciences Department, Division of Pharmacology and Toxicology, Ponce Health Sciences University, Ponce Research Institute, Ponce, PR 00732, USA
| | - Harold I Saavedra
- Basic Sciences Department, Division of Pharmacology and Toxicology, Ponce Health Sciences University, Ponce Research Institute, Ponce, PR 00732, USA
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