1
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Garcia-Alonso L, Handfield LF, Roberts K, Nikolakopoulou K, Fernando RC, Gardner L, Woodhams B, Arutyunyan A, Polanski K, Hoo R, Sancho-Serra C, Li T, Kwakwa K, Tuck E, Lorenzi V, Massalha H, Prete M, Kleshchevnikov V, Tarkowska A, Porter T, Mazzeo CI, van Dongen S, Dabrowska M, Vaskivskyi V, Mahbubani KT, Park JE, Jimenez-Linan M, Campos L, Kiselev VY, Lindskog C, Ayuk P, Prigmore E, Stratton MR, Saeb-Parsy K, Moffett A, Moore L, Bayraktar OA, Teichmann SA, Turco MY, Vento-Tormo R. Author Correction: Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro. Nat Genet 2023; 55:165. [PMID: 36539619 PMCID: PMC9839447 DOI: 10.1038/s41588-022-01287-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Luz Garcia-Alonso
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Kenny Roberts
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Konstantina Nikolakopoulou
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Ridma C. Fernando
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Lucy Gardner
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK
| | - Benjamin Woodhams
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Anna Arutyunyan
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
| | - Krzysztof Polanski
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Regina Hoo
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
| | | | - Tong Li
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Elizabeth Tuck
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Valentina Lorenzi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Hassan Massalha
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK
| | - Martin Prete
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | | | - Tarryn Porter
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Stijn van Dongen
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Monika Dabrowska
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Vasyl Vaskivskyi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Krishnaa T. Mahbubani
- grid.5335.00000000121885934Department of Haematology, University of Cambridge, Cambridge, UK ,grid.454369.9Cambridge Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Jong-eun Park
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Mercedes Jimenez-Linan
- grid.24029.3d0000 0004 0383 8386Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Campos
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Cecilia Lindskog
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Paul Ayuk
- grid.420004.20000 0004 0444 2244Department of Women’s Services, Newcastle-upon-Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Elena Prigmore
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Kourosh Saeb-Parsy
- grid.454369.9Cambridge Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK ,grid.5335.00000000121885934Department of Surgery, University of Cambridge, Cambridge, UK
| | - Ashley Moffett
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK
| | - Luiza Moore
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Omer A. Bayraktar
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Sarah A. Teichmann
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK
| | - Margherita Y. Turco
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Roser Vento-Tormo
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
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2
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Garcia-Alonso L, Lorenzi V, Mazzeo CI, Alves-Lopes JP, Roberts K, Sancho-Serra C, Engelbert J, Marečková M, Gruhn WH, Botting RA, Li T, Crespo B, van Dongen S, Kiselev VY, Prigmore E, Herbert M, Moffett A, Chédotal A, Bayraktar OA, Surani A, Haniffa M, Vento-Tormo R. Single-cell roadmap of human gonadal development. Nature 2022; 607:540-547. [PMID: 35794482 PMCID: PMC9300467 DOI: 10.1038/s41586-022-04918-4] [Citation(s) in RCA: 74] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 05/30/2022] [Indexed: 01/09/2023]
Abstract
Gonadal development is a complex process that involves sex determination followed by divergent maturation into either testes or ovaries1. Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal-mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15+ and TREM2+ fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.
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Affiliation(s)
| | | | | | - João Pedro Alves-Lopes
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
- Physiology, Development and Neuroscience Department, University of Cambridge, Cambridge, UK
| | | | | | - Justin Engelbert
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Magda Marečková
- Wellcome Sanger Institute, Cambridge, UK
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | - Wolfram H Gruhn
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
- Physiology, Development and Neuroscience Department, University of Cambridge, Cambridge, UK
| | - Rachel A Botting
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Tong Li
- Wellcome Sanger Institute, Cambridge, UK
| | - Berta Crespo
- Great Ormond Street Institute of Child Health, University College London, London, UK
| | | | | | | | - Mary Herbert
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Ashley Moffett
- University of Cambridge Centre for Trophoblast Research, Department of Pathology, University of Cambridge, Cambridge, UK
| | - Alain Chédotal
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | | | - Azim Surani
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
- Physiology, Development and Neuroscience Department, University of Cambridge, Cambridge, UK
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Muzlifah Haniffa
- Wellcome Sanger Institute, Cambridge, UK
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
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3
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Chazarra-Gil R, van Dongen S, Kiselev VY, Hemberg M. Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench. Nucleic Acids Res 2021; 49:e42. [PMID: 33524142 PMCID: PMC8053088 DOI: 10.1093/nar/gkab004] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 12/11/2020] [Accepted: 01/29/2021] [Indexed: 01/02/2023] Open
Abstract
As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.
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Affiliation(s)
| | - Stijn van Dongen
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | | | - Martin Hemberg
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
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4
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Stephenson E, Reynolds G, Botting RA, Calero-Nieto FJ, Morgan MD, Tuong ZK, Bach K, Sungnak W, Worlock KB, Yoshida M, Kumasaka N, Kania K, Engelbert J, Olabi B, Spegarova JS, Wilson NK, Mende N, Jardine L, Gardner LCS, Goh I, Horsfall D, McGrath J, Webb S, Mather MW, Lindeboom RGH, Dann E, Huang N, Polanski K, Prigmore E, Gothe F, Scott J, Payne RP, Baker KF, Hanrath AT, Schim van der Loeff ICD, Barr AS, Sanchez-Gonzalez A, Bergamaschi L, Mescia F, Barnes JL, Kilich E, de Wilton A, Saigal A, Saleh A, Janes SM, Smith CM, Gopee N, Wilson C, Coupland P, Coxhead JM, Kiselev VY, van Dongen S, Bacardit J, King HW, Rostron AJ, Simpson AJ, Hambleton S, Laurenti E, Lyons PA, Meyer KB, Nikolić MZ, Duncan CJA, Smith KGC, Teichmann SA, Clatworthy MR, Marioni JC, Göttgens B, Haniffa M. Single-cell multi-omics analysis of the immune response in COVID-19. Nat Med 2021; 27:904-916. [PMID: 33879890 PMCID: PMC8121667 DOI: 10.1038/s41591-021-01329-2] [Citation(s) in RCA: 321] [Impact Index Per Article: 107.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/23/2021] [Indexed: 02/07/2023]
Abstract
Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy.
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Affiliation(s)
- Emily Stephenson
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Gary Reynolds
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Rachel A Botting
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Michael D Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Zewen Kelvin Tuong
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Karsten Bach
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Waradon Sungnak
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Kaylee B Worlock
- UCL Respiratory, Division of Medicine, University College London, London, UK
| | - Masahiro Yoshida
- UCL Respiratory, Division of Medicine, University College London, London, UK
| | | | - Katarzyna Kania
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Justin Engelbert
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Bayanne Olabi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Nicola K Wilson
- Wellcome - MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Nicole Mende
- Wellcome - MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Laura Jardine
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Louis C S Gardner
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Issac Goh
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Dave Horsfall
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jim McGrath
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Simone Webb
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Michael W Mather
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Emma Dann
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Ni Huang
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Elena Prigmore
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Florian Gothe
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, Ludwig-Maximilians-Universität Munich, Munich, Germany
| | - Jonathan Scott
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Rebecca P Payne
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Kenneth F Baker
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Aidan T Hanrath
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Department of Infection and Tropical Medicine, Newcastle upon Tyne Hospitals NHS Foundation, Newcastle upon Tyne, UK
| | | | - Andrew S Barr
- Department of Infection and Tropical Medicine, Newcastle upon Tyne Hospitals NHS Foundation, Newcastle upon Tyne, UK
| | - Amada Sanchez-Gonzalez
- Department of Infection and Tropical Medicine, Newcastle upon Tyne Hospitals NHS Foundation, Newcastle upon Tyne, UK
| | - Laura Bergamaschi
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Federica Mescia
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Josephine L Barnes
- UCL Respiratory, Division of Medicine, University College London, London, UK
| | - Eliz Kilich
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Angus de Wilton
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Anita Saigal
- Royal Free Hospital NHS Foundation Trust, London, UK
| | - Aarash Saleh
- Royal Free Hospital NHS Foundation Trust, London, UK
| | - Sam M Janes
- UCL Respiratory, Division of Medicine, University College London, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Claire M Smith
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Nusayhah Gopee
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
- Department of Dermatology, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Caroline Wilson
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
- The Innovation Lab Integrated COVID Hub North East, Newcastle Upon Tyne, UK
| | - Paul Coupland
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | | | | | - Stijn van Dongen
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Jaume Bacardit
- School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Hamish W King
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
- Centre for Immunobiology, Blizard Institute, Queen Mary University of London, London, UK
| | - Anthony J Rostron
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Integrated Critical Care Unit, Sunderland Royal Hospital, South Tyneside and Sunderland NHS Foundation Trust, Sunderland, UK
| | - A John Simpson
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Sophie Hambleton
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Elisa Laurenti
- Wellcome - MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Paul A Lyons
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Kerstin B Meyer
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Marko Z Nikolić
- UCL Respiratory, Division of Medicine, University College London, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Christopher J A Duncan
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Department of Infection and Tropical Medicine, Newcastle upon Tyne Hospitals NHS Foundation, Newcastle upon Tyne, UK
| | - Kenneth G C Smith
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Sarah A Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
- Theory of Condensed Matter Group, Cavendish Laboratory/Department of Physics, University of Cambridge, Cambridge, UK.
| | - Menna R Clatworthy
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, Cambridge Biomedical Campus, Cambridge, UK.
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK.
| | - John C Marioni
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK.
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - Berthold Göttgens
- Wellcome - MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
| | - Muzlifah Haniffa
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
- NIHR Newcastle Biomedical Research Centre, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
- Department of Dermatology, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
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5
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Abstract
Single-cell technologies have made it possible to profile millions of cells, but for these resources to be useful they must be easy to query and access. To facilitate interactive and intuitive access to single-cell data we have developed scfind, a single-cell analysis tool that facilitates fast search of biologically or clinically relevant marker genes in cell atlases. Using transcriptome data from six mouse cell atlases, we show how scfind can be used to evaluate marker genes, perform in silico gating, and identify both cell-type-specific and housekeeping genes. Moreover, we have developed a subquery optimization routine to ensure that long and complex queries return meaningful results. To make scfind more user friendly, we use indices of PubMed abstracts and techniques from natural language processing to allow for arbitrary queries. Finally, we show how scfind can be used for multi-omics analyses by combining single-cell ATAC-seq data with transcriptome data.
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Affiliation(s)
| | - Nikolaos Patikas
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- UK Dementia Research Institute, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Martin Hemberg
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
- Evergrande Center for Immunologic Disease, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA.
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6
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Garcia-Alonso L, Handfield LF, Roberts K, Nikolakopoulou K, Fernando RC, Gardner L, Woodhams B, Arutyunyan A, Polanski K, Hoo R, Sancho-Serra C, Li T, Kwakwa K, Tuck E, Lorenzi V, Massalha H, Prete M, Kleshchevnikov V, Tarkowska A, Porter T, Mazzeo CI, van Dongen S, Dabrowska M, Vaskivskyi V, Mahbubani KT, Park JE, Jimenez-Linan M, Campos L, Kiselev VY, Lindskog C, Ayuk P, Prigmore E, Stratton MR, Saeb-Parsy K, Moffett A, Moore L, Bayraktar OA, Teichmann SA, Turco MY, Vento-Tormo R. Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro. Nat Genet 2021; 53:1698-1711. [PMID: 34857954 PMCID: PMC8648563 DOI: 10.1038/s41588-021-00972-2] [Citation(s) in RCA: 173] [Impact Index Per Article: 57.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 10/18/2021] [Indexed: 12/24/2022]
Abstract
The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated dense single-cell and spatial reference maps of the human uterus and three-dimensional endometrial organoid cultures. We dissect the signaling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids reveals the pathways and cell states regulating differentiation of the secretory and ciliated lineages both in vivo and in vitro. In vitro downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. We utilize our cellular maps to deconvolute bulk data from endometrial cancers and endometriotic lesions, illuminating the cell types dominating in each of these disorders. These mechanistic insights provide a platform for future development of treatments for common conditions including endometriosis and endometrial carcinoma.
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Affiliation(s)
- Luz Garcia-Alonso
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Kenny Roberts
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Konstantina Nikolakopoulou
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Ridma C. Fernando
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Lucy Gardner
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK
| | - Benjamin Woodhams
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Anna Arutyunyan
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
| | - Krzysztof Polanski
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Regina Hoo
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
| | | | - Tong Li
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Elizabeth Tuck
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Valentina Lorenzi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Hassan Massalha
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK
| | - Martin Prete
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | | | - Tarryn Porter
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Stijn van Dongen
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Monika Dabrowska
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Vasyl Vaskivskyi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Krishnaa T. Mahbubani
- grid.5335.00000000121885934Department of Haematology, University of Cambridge, Cambridge, UK ,grid.454369.9Cambridge Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Jong-eun Park
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Mercedes Jimenez-Linan
- grid.24029.3d0000 0004 0383 8386Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Campos
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Cecilia Lindskog
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Paul Ayuk
- grid.420004.20000 0004 0444 2244Department of Women’s Services, Newcastle-upon-Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Elena Prigmore
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | | | - Kourosh Saeb-Parsy
- grid.454369.9Cambridge Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK ,grid.5335.00000000121885934Department of Surgery, University of Cambridge, Cambridge, UK
| | - Ashley Moffett
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK
| | - Luiza Moore
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Omer A. Bayraktar
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK
| | - Sarah A. Teichmann
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK
| | - Margherita Y. Turco
- grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK ,grid.5335.00000000121885934Department of Pathology, University of Cambridge, Cambridge, UK ,grid.482245.d0000 0001 2110 3787Present Address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Roser Vento-Tormo
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
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Andrews TS, Kiselev VY, McCarthy D, Hemberg M. Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data. Nat Protoc 2020; 16:1-9. [PMID: 33288955 DOI: 10.1038/s41596-020-00409-w] [Citation(s) in RCA: 130] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 09/08/2020] [Indexed: 01/01/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows you to profile the whole transcriptome of a large number of individual cells. However, the analysis of the large volumes of data generated from these experiments requires specialized statistical and computational methods. Here we present an overview of the computational workflow involved in processing scRNA-seq data. We discuss some of the most common tasks and the tools available for addressing central biological questions. In this article and our companion website ( https://scrnaseq-course.cog.sanger.ac.uk/website/index.html ), we provide guidelines regarding best practices for performing computational analyses. This tutorial provides a hands-on guide for experimentalists interested in analyzing their data as well as an overview for bioinformaticians seeking to develop new computational methods.
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Affiliation(s)
| | | | - Davis McCarthy
- Bioinformatics and Cellular Genomics, St Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Melbourne Integrative Genomics, Faculty of Science, University of Melbourne, Melbourne, Victoria, Australia
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8
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Snyder MP, Lin S, Posgai A, Atkinson M, Regev A, Rood J, Rozenblatt-Rosen O, Gaffney L, Hupalowska A, Satija R, Gehlenborg N, Shendure J, Laskin J, Harbury P, Nystrom NA, Silverstein JC, Bar-Joseph Z, Zhang K, Börner K, Lin Y, Conroy R, Procaccini D, Roy AL, Pillai A, Brown M, Galis ZS, Cai L, Shendure J, Trapnell C, Lin S, Jackson D, Snyder MP, Nolan G, Greenleaf WJ, Lin Y, Plevritis S, Ahadi S, Nevins SA, Lee H, Schuerch CM, Black S, Venkataraaman VG, Esplin E, Horning A, Bahmani A, Zhang K, Sun X, Jain S, Hagood J, Pryhuber G, Kharchenko P, Atkinson M, Bodenmiller B, Brusko T, Clare-Salzler M, Nick H, Otto K, Posgai A, Wasserfall C, Jorgensen M, Brusko M, Maffioletti S, Caprioli RM, Spraggins JM, Gutierrez D, Patterson NH, Neumann EK, Harris R, deCaestecker M, Fogo AB, van de Plas R, Lau K, Cai L, Yuan GC, Zhu Q, Dries R, Yin P, Saka SK, Kishi JY, Wang Y, Goldaracena I, Laskin J, Ye D, Burnum-Johnson KE, Piehowski PD, Ansong C, Zhu Y, Harbury P, Desai T, Mulye J, Chou P, Nagendran M, Bar-Joseph Z, Teichmann SA, Paten B, Murphy RF, Ma J, Kiselev VY, Kingsford C, Ricarte A, Keays M, Akoju SA, Ruffalo M, Gehlenborg N, Kharchenko P, Vella M, McCallum C, Börner K, Cross LE, Friedman SH, Heiland R, Herr B, Macklin P, Quardokus EM, Record L, Sluka JP, Weber GM, Nystrom NA, Silverstein JC, Blood PD, Ropelewski AJ, Shirey WE, Scibek RM, Mabee P, Lenhardt WC, Robasky K, Michailidis S, Satija R, Marioni J, Regev A, Butler A, Stuart T, Fisher E, Ghazanfar S, Rood J, Gaffney L, Eraslan G, Biancalani T, Vaishnav ED, Conroy R, Procaccini D, Roy A, Pillai A, Brown M, Galis Z, Srinivas P, Pawlyk A, Sechi S, Wilder E, Anderson J. The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature 2019; 574:187-192. [PMID: 31597973 PMCID: PMC6800388 DOI: 10.1038/s41586-019-1629-x] [Citation(s) in RCA: 272] [Impact Index Per Article: 54.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 09/09/2019] [Indexed: 12/12/2022]
Abstract
Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.
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10
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Díaz-Muñoz MD, Kiselev VY, Le Novère N, Curk T, Ule J, Turner M. Tia1 dependent regulation of mRNA subcellular location and translation controls p53 expression in B cells. Nat Commun 2017; 8:530. [PMID: 28904350 PMCID: PMC5597594 DOI: 10.1038/s41467-017-00454-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Accepted: 06/30/2017] [Indexed: 11/24/2022] Open
Abstract
Post-transcriptional regulation of cellular mRNA is essential for protein synthesis. Here we describe the importance of mRNA translational repression and mRNA subcellular location for protein expression during B lymphocyte activation and the DNA damage response. Cytoplasmic RNA granules are formed upon cell activation with mitogens, including stress granules that contain the RNA binding protein Tia1. Tia1 binds to a subset of transcripts involved in cell stress, including p53 mRNA, and controls translational silencing and RNA granule localization. DNA damage promotes mRNA relocation and translation in part due to dissociation of Tia1 from its mRNA targets. Upon DNA damage, p53 mRNA is released from stress granules and associates with polyribosomes to increase protein synthesis in a CAP-independent manner. Global analysis of cellular mRNA abundance and translation indicates that this is an extended ATM-dependent mechanism to increase protein expression of key modulators of the DNA damage response.Sequestering mRNA in cytoplasmic stress granules is a mechanism for translational repression. Here the authors find that p53 mRNA, present in stress granules in activated B lymphocytes, is released upon DNA damage and is translated in a CAP-independent manner.
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Affiliation(s)
- Manuel D Díaz-Muñoz
- Laboratory of Lymphocyte Signalling and Development, The Babraham Institute, Cambridge, CB22 3AT, UK.
- Centre de Physiopathologie Toulouse-Purpan, INSERM UMR1043 / CNRS U5282, Toulouse, 31300, France.
| | - Vladimir Yu Kiselev
- Laboratory of Signalling, The Babraham Institute, Cambridge, CB22 3AT, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Nicolas Le Novère
- Laboratory of Signalling, The Babraham Institute, Cambridge, CB22 3AT, UK
| | - Tomaz Curk
- University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia
| | - Jernej Ule
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- The Crick Institute, 1 Midland Road, London, NW1 1AT, UK
| | - Martin Turner
- Laboratory of Lymphocyte Signalling and Development, The Babraham Institute, Cambridge, CB22 3AT, UK
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11
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Kiselev VY, Kirschner K, Schaub MT, Andrews T, Yiu A, Chandra T, Natarajan KN, Reik W, Barahona M, Green AR, Hemberg M. SC3: consensus clustering of single-cell RNA-seq data. Nat Methods 2017; 14:483-486. [PMID: 28346451 PMCID: PMC5410170 DOI: 10.1038/nmeth.4236] [Citation(s) in RCA: 794] [Impact Index Per Article: 113.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 03/01/2017] [Indexed: 01/22/2023]
Abstract
Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (http://bioconductor.org/packages/SC3). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.
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Affiliation(s)
| | - Kristina Kirschner
- Cambridge Institute for Medical Research, Wellcome Trust/MRC Stem Cell Institute and Department of Haematology, University of Cambridge, Hills Road, Cambridge, UK
| | - Michael T. Schaub
- Department of Mathematics and naXys, University of Namur, Belgium
- ICTEAM, Université catholique de Louvain, Belgium
| | | | - Andrew Yiu
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Tamir Chandra
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Kedar N Natarajan
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
- EMBL-European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Wolf Reik
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
- Epigenetics Programme, The Babraham Institute, Babraham, Cambridge, UK
- Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
| | | | - Anthony R Green
- Cambridge Institute for Medical Research, Wellcome Trust/MRC Stem Cell Institute and Department of Haematology, University of Cambridge, Hills Road, Cambridge, UK
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12
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Kiselev VY, Juvin V, Malek M, Luscombe N, Hawkins P, Le Novère N, Stephens L. Perturbations of PIP3 signalling trigger a global remodelling of mRNA landscape and reveal a transcriptional feedback loop. Nucleic Acids Res 2015; 43:9663-79. [PMID: 26464442 PMCID: PMC4787766 DOI: 10.1093/nar/gkv1015] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 09/24/2015] [Indexed: 01/10/2023] Open
Abstract
PIP3 is synthesized by the Class I PI3Ks and regulates complex cell responses, such as growth and migration. Signals that drive long-term reshaping of cell phenotypes are difficult to resolve because of complex feedback networks that operate over extended times. PIP3-dependent modulation of mRNA accumulation is clearly important in this process but is poorly understood. We have quantified the genome-wide mRNA-landscape of non-transformed, breast epithelium-derived MCF10a cells and its response to acute regulation by EGF, in the presence or absence of a PI3Kα inhibitor, compare it to chronic activation of PI3K signalling by cancer-relevant mutations (isogenic cells expressing an oncomutant PI3Kα allele or lacking the PIP3-phosphatase/tumour-suppressor, PTEN). Our results show that whilst many mRNAs are changed by long-term genetic perturbation of PIP3 signalling ('butterfly effect'), a much smaller number do so in a coherent fashion with the different PIP3 perturbations. This suggests a subset of more directly regulated mRNAs. We show that mRNAs respond differently to given aspects of PIP3 regulation. Some PIP3-sensitive mRNAs encode PI3K pathway components, thus suggesting a transcriptional feedback loop. We identify the transcription factor binding motifs SRF and PRDM1 as important regulators of PIP3-sensitive mRNAs involved in cell movement.
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Affiliation(s)
| | - Veronique Juvin
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK
| | - Mouhannad Malek
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK
| | | | - Phillip Hawkins
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK
| | - Nicolas Le Novère
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK EMBL-European Bioinformatics Institute, Hinxton, CB10 1SD, UK
| | - Len Stephens
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK
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13
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Kiselev VY, Leda M, Lobanov AI, Marenduzzo D, Goryachev AB. Lateral dynamics of charged lipids and peripheral proteins in spatially heterogeneous membranes: comparison of continuous and Monte Carlo approaches. J Chem Phys 2012; 135:155103. [PMID: 22029337 DOI: 10.1063/1.3652958] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Biological membranes are complex environments whose physico-chemical properties are of utmost importance for the understanding of many crucial biological processes. Much attention has been given in the literature to the description of membranes along the z-axis perpendicular to the membrane. Here, we instead consider the lateral dynamics of lipids and peripheral proteins due to their electrostatic interaction. Previously, we constructed a Monte Carlo automaton capable of simulating mutual diffusive dynamics of charged lipids and associated positively charged peptides. Here, we derive and numerically analyze a system of Poisson-Boltzmann-Nernst-Planck (PBNP) equations that provide a mean-field approximation compatible with our Monte Carlo model. The thorough comparison between the mean-field PBNP equations and Monte Carlo simulations demonstrates that both the approaches are in a good qualitative agreement in all tested scenarios. We find that the two methods quantitatively deviate when the local charge density is high, presumably because the Poisson-Boltzmann formalism is applicable in the so-called weak coupling limit, whose validity is restricted to low charge densities. Nevertheless, we conclude that the mean-field PBNP approach provides a good approximation for the considerably more detailed Monte Carlo model at only a fraction of the associated computational cost and allows simulation of the membrane lateral dynamics on the space and time scales relevant for the realistic biological problems.
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Affiliation(s)
- Vladimir Yu Kiselev
- Centre for Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, United Kingdom
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14
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Kiselev VY, Marenduzzo D, Goryachev AB. Lateral dynamics of proteins with polybasic domain on anionic membranes: a dynamic Monte-Carlo study. Biophys J 2011; 100:1261-70. [PMID: 21354399 DOI: 10.1016/j.bpj.2011.01.025] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2010] [Accepted: 01/13/2011] [Indexed: 10/18/2022] Open
Abstract
Positively charged polybasic domains are essential for recruiting multiple signaling proteins, such as Ras GTPases and Src kinase, to the negatively charged cellular membranes. Much less, however, is known about the influence of electrostatic interactions on the lateral dynamics of these proteins. We developed a dynamic Monte-Carlo automaton that faithfully simulates lateral diffusion of the adsorbed positively charged oligopeptides as well as the dynamics of mono- (phosphatidylserine) and polyvalent (PIP(2)) anionic lipids within the bilayer. In agreement with earlier results, our simulations reveal lipid demixing that leads to the formation of a lipid shell associated with the peptide. The computed association times and average numbers of bound lipids demonstrate that tetravalent PIP(2) interacts with the peptide much more strongly than monovalent lipid. On the spatially homogeneous membrane, the lipid shell affects the behavior of the peptide only by weakly reducing its lateral mobility. However, spatially heterogeneous distributions of monovalent lipids are found to produce peptide drift, the velocity of which is determined by the total charge of the peptide-lipid complex. We hypothesize that this predicted phenomenon may affect the spatial distribution of proteins with polybasic domains in the context of cell-signaling events that alter the local density of monovalent anionic lipids.
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Affiliation(s)
- Vladimir Yu Kiselev
- Centre for Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
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