1
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Fischer SC, Schardt S, Lilao-Garzón J, Muñoz-Descalzo S. The salt-and-pepper pattern in mouse blastocysts is compatible with signaling beyond the nearest neighbors. iScience 2023; 26:108106. [PMID: 37915595 PMCID: PMC10616410 DOI: 10.1016/j.isci.2023.108106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/03/2023] [Accepted: 09/26/2023] [Indexed: 11/03/2023] Open
Abstract
Embryos develop in a concerted sequence of spatiotemporal arrangements of cells. In the preimplantation mouse embryo, the distribution of the cells in the inner cell mass evolves from a salt-and-pepper pattern to spatial segregation of two distinct cell types. The exact properties of the salt-and-pepper pattern have not been analyzed so far. We investigate the spatiotemporal distribution of NANOG- and GATA6-expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single-cell-based neighborhood analyses. A combination of spatial statistics and agent-based modeling reveals that the cell fate distribution follows a local clustering pattern. Using ordinary differential equations modeling, we show that this pattern can be established by a distance-based signaling mechanism enabling cells to integrate information from the whole inner cell mass into their cell fate decision. Our work highlights the importance of longer-range signaling to ensure coordinated decisions in groups of cells to successfully build embryos.
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Affiliation(s)
- Sabine C. Fischer
- Julius-Maximilians-Universität Würzburg, Faculty of Biology, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, 97074 Würzburg, Germany
| | - Simon Schardt
- Julius-Maximilians-Universität Würzburg, Faculty of Biology, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, 97074 Würzburg, Germany
| | - Joaquín Lilao-Garzón
- Instituto Universitario de Investigaciones Biomédicas y Sanitarias (IUIBS), Universidad Las Palmas de Gran Canaria (ULPGC), Paseo Blas Cabrera Felipe "Físico" 17, Las Palmas de Gran Canaria 35016, Spain
| | - Silvia Muñoz-Descalzo
- Instituto Universitario de Investigaciones Biomédicas y Sanitarias (IUIBS), Universidad Las Palmas de Gran Canaria (ULPGC), Paseo Blas Cabrera Felipe "Físico" 17, Las Palmas de Gran Canaria 35016, Spain
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2
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Dirk R, Fischer JL, Schardt S, Ankenbrand MJ, Fischer SC. Recognition and reconstruction of cell differentiation patterns with deep learning. PLoS Comput Biol 2023; 19:e1011582. [PMID: 37889897 PMCID: PMC10631711 DOI: 10.1371/journal.pcbi.1011582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 11/08/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023] Open
Abstract
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran's index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms.
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Affiliation(s)
- Robin Dirk
- Julius-Maximilians-Universität Würzburg, Fakultät für Biologie, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, Germany
| | - Jonas L. Fischer
- Julius-Maximilians-Universität Würzburg, Fakultät für Biologie, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, Germany
| | - Simon Schardt
- Julius-Maximilians-Universität Würzburg, Fakultät für Biologie, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, Germany
| | - Markus J. Ankenbrand
- Julius-Maximilians-Universität Würzburg, Fakultät für Biologie, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, Germany
| | - Sabine C. Fischer
- Julius-Maximilians-Universität Würzburg, Fakultät für Biologie, Center for Computational and Theoretical Biology, Klara-Oppenheimer-Weg 32, Campus Hubland Nord, Germany
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3
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Fischer SC, Bassel GW, Kollmannsberger P. Tissues as networks of cells: towards generative rules of complex organ development. J R Soc Interface 2023; 20:20230115. [PMID: 37491909 PMCID: PMC10369035 DOI: 10.1098/rsif.2023.0115] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 07/05/2023] [Indexed: 07/27/2023] Open
Abstract
Network analysis is a well-known and powerful tool in molecular biology. More recently, it has been introduced in developmental biology. Tissues can be readily translated into spatial networks such that cells are represented by nodes and intercellular connections by edges. This discretization of cellular organization enables mathematical approaches rooted in network science to be applied towards the understanding of tissue structure and function. Here, we describe how such tissue abstractions can enable the principles that underpin tissue formation and function to be uncovered. We provide an introduction into biologically relevant network measures, then present an overview of different areas of developmental biology where these approaches have been applied. We then summarize the general developmental rules underpinning tissue topology generation. Finally, we discuss how generative models can help to link the developmental rule back to the tissue topologies. Our collection of results points at general mechanisms as to how local developmental rules can give rise to observed topological properties in multicellular systems.
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Affiliation(s)
- Sabine C. Fischer
- Center for Computational and Theoretical Biology, Faculty of Biology, University of Würzburg, Würzburg, Germany
| | - George W. Bassel
- School of Life Sciences, The University of Warwick, Coventry, UK
| | - Philip Kollmannsberger
- Biomedical Physics, Department of Physics, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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4
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Allègre N, Chauveau S, Dennis C, Renaud Y, Meistermann D, Estrella LV, Pouchin P, Cohen-Tannoudji M, David L, Chazaud C. NANOG initiates epiblast fate through the coordination of pluripotency genes expression. Nat Commun 2022; 13:3550. [PMID: 35729116 PMCID: PMC9213552 DOI: 10.1038/s41467-022-30858-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 05/24/2022] [Indexed: 12/20/2022] Open
Abstract
The epiblast is the source of all mammalian embryonic tissues and of pluripotent embryonic stem cells. It differentiates alongside the primitive endoderm in a “salt and pepper” pattern from inner cell mass (ICM) progenitors during the preimplantation stages through the activity of NANOG, GATA6 and the FGF pathway. When and how epiblast lineage specification is initiated is still unclear. Here, we show that the coordinated expression of pluripotency markers defines epiblast identity. Conversely, ICM progenitor cells display random cell-to-cell variability in expression of various pluripotency markers, remarkably dissimilar from the epiblast signature and independently from NANOG, GATA6 and FGF activities. Coordination of pluripotency markers expression fails in Nanog and Gata6 double KO (DKO) embryos. Collectively, our data suggest that NANOG triggers epiblast specification by ensuring the coordinated expression of pluripotency markers in a subset of cells, implying a stochastic mechanism. These features are likely conserved, as suggested by analysis of human embryos. Pluripotent epiblast cells segregate from primitive endoderm in the blastocyst inner cell mass (ICM). Here the authors show that mosaic epiblast differentiation during mouse and human preimplantation development initiates stochastically in ICM progenitors, independently of the FGF pathway, and requires NANOG activity
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Affiliation(s)
- Nicolas Allègre
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France
| | - Sabine Chauveau
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France
| | - Cynthia Dennis
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France
| | - Yoan Renaud
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France.,Byonet, 19 rue du courait, F-63200, Riom, France
| | - Dimitri Meistermann
- Université de Nantes, CHU Nantes, INSERM, CR2TI, UMR 1064, ITUN, F-44000, Nantes, France.,Université de Nantes, CNRS, LS2N, CNRS UMR 6004, F-44000, Nantes, France
| | - Lorena Valverde Estrella
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France
| | - Pierre Pouchin
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France
| | - Michel Cohen-Tannoudji
- Institut Pasteur, Université Paris Cité, CNRS UMR3738, Epigenomics, Proliferation, and the Identity of Cells, Department of Developmental and Stem Cell Biology, F-75015, Paris, France
| | - Laurent David
- Université de Nantes, CHU Nantes, INSERM, CR2TI, UMR 1064, ITUN, F-44000, Nantes, France.,Université de Nantes, CHU Nantes, INSERM, CNRS, UMS Biocore, INSERM UMS 016, CNRS UMS 3556, F-44000, Nantes, France
| | - Claire Chazaud
- Université Clermont Auvergne, CNRS, INSERM, GReD Institute, Faculté de Médecine, F-63000, Clermont-Ferrand, France.
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5
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Malaguti M, Portero Migueles R, Annoh J, Sadurska D, Blin G, Lowell S. SyNPL: Synthetic Notch pluripotent cell lines to monitor and manipulate cell interactions in vitro and in vivo. Development 2022; 149:275525. [PMID: 35616331 PMCID: PMC9270970 DOI: 10.1242/dev.200226] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 05/13/2022] [Indexed: 12/11/2022]
Abstract
Cell-cell interactions govern differentiation and cell competition in pluripotent cells during early development, but the investigation of such processes is hindered by a lack of efficient analysis tools. Here, we introduce SyNPL: clonal pluripotent stem cell lines that employ optimised Synthetic Notch (SynNotch) technology to report cell-cell interactions between engineered ‘sender’ and ‘receiver’ cells in cultured pluripotent cells and chimaeric mouse embryos. A modular design makes it straightforward to adapt the system for programming differentiation decisions non-cell-autonomously in receiver cells in response to direct contact with sender cells. We demonstrate the utility of this system by enforcing neuronal differentiation at the boundary between two cell populations. In summary, we provide a new adaptation of SynNotch technology that could be used to identify cell interactions and to profile changes in gene or protein expression that result from direct cell-cell contact with defined cell populations in culture and in early embryos, and that can be customised to generate synthetic patterning of cell fate decisions. Summary: Optimised Synthetic Notch circuitry in mouse pluripotent stem cells provides a modular tool with which to monitor cell-cell interactions and program synthetic patterning of cell fates in culture and in embryos.
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Affiliation(s)
- Mattias Malaguti
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Rosa Portero Migueles
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Jennifer Annoh
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Daina Sadurska
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Guillaume Blin
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Sally Lowell
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
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6
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Robert C, Prista von Bonhorst F, De Decker Y, Dupont G, Gonze D. Initial source of heterogeneity in a model for cell fate decision in the early mammalian embryo. Interface Focus 2022; 12:20220010. [DOI: 10.1098/rsfs.2022.0010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 05/12/2022] [Indexed: 12/17/2022] Open
Abstract
During development, cells from a population of common progenitors evolve towards different fates characterized by distinct levels of specific transcription factors, a process known as cell differentiation. This evolution is governed by gene regulatory networks modulated by intercellular signalling. In order to evolve towards distinct fates, cells forming the population of common progenitors must display some heterogeneity. We applied a modelling approach to obtain insights into the possible sources of cell-to-cell variability initiating the specification of cells of the inner cell mass into epiblast or primitive endoderm cells in early mammalian embryo. At the single-cell level, these cell fates correspond to three possible steady states of the model. A combination of numerical simulations and bifurcation analyses predicts that the behaviour of the model is preserved with respect to the source of variability and that cell–cell coupling induces the emergence of multiple steady states associated with various cell fate configurations, and to a distribution of the levels of expression of key transcription factors. Statistical analysis of these time-dependent distributions reveals differences in the evolutions of the variance-to-mean ratios of key variables of the system, depending on the simulated source of variability, and, by comparison with experimental data, points to the rate of synthesis of the key transcription factor NANOG as a likely initial source of heterogeneity.
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Affiliation(s)
- Corentin Robert
- Unit of Theoretical Chronobiology and Université Libre de Bruxelles (ULB), Brussels CP 231, Belgium
- Nonlinear Physical Chemistry Unit, Université Libre de Bruxelles (ULB), Brussels CP 231, Belgium
| | | | - Yannick De Decker
- Nonlinear Physical Chemistry Unit, Université Libre de Bruxelles (ULB), Brussels CP 231, Belgium
| | - Geneviève Dupont
- Unit of Theoretical Chronobiology and Université Libre de Bruxelles (ULB), Brussels CP 231, Belgium
| | - Didier Gonze
- Unit of Theoretical Chronobiology and Université Libre de Bruxelles (ULB), Brussels CP 231, Belgium
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7
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Raina D, Bahadori A, Stanoev A, Protzek M, Koseska A, Schröter C. Cell-cell communication through FGF4 generates and maintains robust proportions of differentiated cell types in embryonic stem cells. Development 2021; 148:dev199926. [PMID: 34651174 PMCID: PMC8602943 DOI: 10.1242/dev.199926] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 10/04/2021] [Indexed: 01/20/2023]
Abstract
During embryonic development and tissue homeostasis, reproducible proportions of differentiated cell types are specified from populations of multipotent precursor cells. Molecular mechanisms that enable both robust cell-type proportioning despite variable initial conditions in the precursor cells, and the re-establishment of these proportions upon perturbations in a developing tissue remain to be characterized. Here, we report that the differentiation of robust proportions of epiblast-like and primitive endoderm-like cells in mouse embryonic stem cell cultures emerges at the population level through cell-cell communication via a short-range fibroblast growth factor 4 (FGF4) signal. We characterize the molecular and dynamical properties of the communication mechanism and show how it controls both robust cell-type proportioning from a wide range of experimentally controlled initial conditions, as well as the autonomous re-establishment of these proportions following the isolation of one cell type. The generation and maintenance of reproducible proportions of discrete cell types is a new function for FGF signaling that might operate in a range of developing tissues.
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Affiliation(s)
| | | | | | | | | | - Christian Schröter
- Department of Systemic Cell Biology, Max Planck Institute of Molecular Physiology, 44227 Dortmund, Germany
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8
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Sridhar S, Saha G, Lata S, Mehrotra R. Molecular docking studies of Indian variants of pathophysiological proteins of SARS-CoV-2 with selected drug candidates. J Genet 2021. [PMID: 34553696 PMCID: PMC8435403 DOI: 10.1007/s12041-021-01313-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
SARS-CoV-2 pandemic has recently made the entire world come to a standstill. The number of cases in the world, especially India, have been increasing exponentially. The need of the hour is to assimilate as much data as possible to fast track the pipeline of bringing in new therapeutic tools against this fatal virus. In this brief communication, we aim to throw light on the various variants of the proteins involved heavily in the pathophysiology of COVID-19, namely Spike protein, ACE2, GRP78, TMPRSS2 and NSP-12. We also portray the molecular docking studies of these proteins with specific drugs that are currently being associated with the same. In our brief study, we come across a few key findings. First of all the combinations of the variants of spike protein and ACE2 binding show overall 25% unfavourable ΔΔG. Second, NSP12 is the most mutation prone among all the NSPs of the SARS-CoV-2 genome and the most common mutations are P323L and A97V. Third, we discovered the variants found in the Indian subpopulation that have greater binding with the currently investigated drugs.
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9
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Forsyth JE, Al-Anbaki AH, de la Fuente R, Modare N, Perez-Cortes D, Rivera I, Seaton Kelly R, Cotter S, Plusa B. IVEN: A quantitative tool to describe 3D cell position and neighbourhood reveals architectural changes in FGF4-treated preimplantation embryos. PLoS Biol 2021; 19:e3001345. [PMID: 34310594 PMCID: PMC8341705 DOI: 10.1371/journal.pbio.3001345] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 08/05/2021] [Accepted: 07/01/2021] [Indexed: 11/30/2022] Open
Abstract
Architectural changes at the cellular and organism level are integral and necessary to successful development and growth. During mammalian preimplantation development, cells reduce in size and the architecture of the embryo changes significantly. Such changes must be coordinated correctly to ensure continued development of the embryo and, ultimately, a successful pregnancy. However, the nature of such transformations is poorly defined during mammalian preimplantation development. In order to quantitatively describe changes in cell environment and organism architecture, we designed Internal Versus External Neighbourhood (IVEN). IVEN is a user-interactive, open-source pipeline that classifies cells into different populations based on their position and quantifies the number of neighbours of every cell within a dataset in a 3D environment. Through IVEN-driven analyses, we show how transformations in cell environment, defined here as changes in cell neighbourhood, are related to changes in embryo geometry and major developmental events during preimplantation mammalian development. Moreover, we demonstrate that modulation of the FGF pathway alters spatial relations of inner cells and neighbourhood distributions, leading to overall changes in embryo architecture. In conjunction with IVEN-driven analyses, we uncover differences in the dynamic of cell size changes over the preimplantation period and determine that cells within the mammalian embryo initiate growth phase only at the time of implantation.
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Affiliation(s)
- Jessica E. Forsyth
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
- School of Mathematics, Alan Turing Building, University of Manchester, Manchester, United Kingdom
| | - Ali H. Al-Anbaki
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
| | - Roberto de la Fuente
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
- Department of Experimental Embryology, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, Jastrzębiec, Poland
| | - Nikkinder Modare
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
| | - Diego Perez-Cortes
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
| | - Isabel Rivera
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
| | - Rowena Seaton Kelly
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
| | - Simon Cotter
- School of Mathematics, Alan Turing Building, University of Manchester, Manchester, United Kingdom
| | - Berenika Plusa
- Faculty of Biology, Medicine and Health (FBMH), Division of Developmental Biology & Medicine, Michael Smith Building, University of Manchester, Manchester, United Kingdom
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10
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Stanoev A, Schröter C, Koseska A. Robustness and timing of cellular differentiation through population-based symmetry breaking. Development 2021; 148:dev.197608. [PMID: 33472845 DOI: 10.1242/dev.197608] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 12/24/2020] [Indexed: 01/23/2023]
Abstract
During mammalian development and homeostasis, cells often transition from a multilineage primed state to one of several differentiated cell types that are marked by the expression of mutually exclusive genetic markers. These observations have been classically explained by single-cell multistability as the dynamical basis of differentiation, where robust cell-type proportioning relies on pre-existing cell-to-cell differences. We propose a conceptually different dynamical mechanism in which cell types emerge and are maintained collectively by cell-cell communication as a novel inhomogeneous state of the coupled system. Differentiation can be triggered by cell number increase as the population grows in size, through organisation of the initial homogeneous population before the symmetry-breaking bifurcation point. Robust proportioning and reliable recovery of the differentiated cell types following a perturbation is an inherent feature of the inhomogeneous state that is collectively maintained. This dynamical mechanism is valid for systems with steady-state or oscillatory single-cell dynamics. Therefore, our results suggest that timing and subsequent differentiation in robust cell-type proportions can emerge from the cooperative behaviour of growing cell populations during development.
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Affiliation(s)
- Angel Stanoev
- Department of Systemic Cell Biology, Max Planck Institute of Molecular Physiology, 44227 Dortmund, Germany
| | - Christian Schröter
- Department of Systemic Cell Biology, Max Planck Institute of Molecular Physiology, 44227 Dortmund, Germany
| | - Aneta Koseska
- Department of Systemic Cell Biology, Max Planck Institute of Molecular Physiology, 44227 Dortmund, Germany
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11
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Liebisch T, Drusko A, Mathew B, Stelzer EHK, Fischer SC, Matthäus F. Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach. Sci Rep 2020; 10:22405. [PMID: 33376253 PMCID: PMC7772343 DOI: 10.1038/s41598-020-80141-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 12/17/2020] [Indexed: 01/13/2023] Open
Abstract
During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell-cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.
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Affiliation(s)
- Tim Liebisch
- Faculty of Biological Sciences and Frankfurt Institute for Advanced Studies (FIAS), Goethe Universität Frankfurt am Main, Ruth-Moufang-Straße 1, 60438, Frankfurt, Germany.
| | - Armin Drusko
- Faculty of Biological Sciences and Frankfurt Institute for Advanced Studies (FIAS), Goethe Universität Frankfurt am Main, Ruth-Moufang-Straße 1, 60438, Frankfurt, Germany
| | - Biena Mathew
- Faculty of Biological Sciences and Buchmann Institute for Molecular Life Sciences (BMLS), Goethe Universität Frankfurt am Main, Max-von-Laue Str. 15, 60438, Frankfurt, Germany
| | - Ernst H K Stelzer
- Faculty of Biological Sciences and Buchmann Institute for Molecular Life Sciences (BMLS), Goethe Universität Frankfurt am Main, Max-von-Laue Str. 15, 60438, Frankfurt, Germany
| | - Sabine C Fischer
- Center for Computational and Theoretical Biology (CCTB), Julius-Maximilians-Universität Würzburg, Campus Hubland Nord 32, 97074, Würzburg, Germany
| | - Franziska Matthäus
- Faculty of Biological Sciences and Frankfurt Institute for Advanced Studies (FIAS), Goethe Universität Frankfurt am Main, Ruth-Moufang-Straße 1, 60438, Frankfurt, Germany
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12
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Fiorentino J, Torres-Padilla ME, Scialdone A. Measuring and Modeling Single-Cell Heterogeneity and Fate Decision in Mouse Embryos. Annu Rev Genet 2020; 54:167-187. [PMID: 32867543 DOI: 10.1146/annurev-genet-021920-110200] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cellular heterogeneity is a property of any living system; however, its relationship with cellular fate decision remains an open question. Recent technological advances have enabled valuable insights, especially in complex systems such as the mouse embryo. In this review, we discuss recent studies that characterize cellular heterogeneity at different levels during mouse development, from the two-cell stage up to gastrulation. In addition to key experimental findings, we review mathematical modeling approaches that help researchers interpret these findings. Disentangling the role of heterogeneity in cell fate decision will likely rely on the refined integration of experiments, large-scale omics data, and mathematical modeling, complemented by the use of synthetic embryos and gastruloids as promising in vitro models.
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Affiliation(s)
- Jonathan Fiorentino
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Institute of Functional Epigenetics (IFE) and Institute of Computational Biology (ICB), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
| | - Maria-Elena Torres-Padilla
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Faculty of Biology, Ludwig-Maximilians Universität, D-82152 Planegg-Martinsried, Germany
| | - Antonio Scialdone
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Institute of Functional Epigenetics (IFE) and Institute of Computational Biology (ICB), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
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Saiz N, Mora-Bitria L, Rahman S, George H, Herder JP, Garcia-Ojalvo J, Hadjantonakis AK. Growth-factor-mediated coupling between lineage size and cell fate choice underlies robustness of mammalian development. eLife 2020; 9:e56079. [PMID: 32720894 PMCID: PMC7513828 DOI: 10.7554/elife.56079] [Citation(s) in RCA: 31] [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: 02/16/2020] [Accepted: 07/24/2020] [Indexed: 01/03/2023] Open
Abstract
Precise control and maintenance of population size is fundamental for organismal development and homeostasis. The three cell types of the mammalian blastocyst are generated in precise proportions over a short time, suggesting a mechanism to ensure a reproducible outcome. We developed a minimal mathematical model demonstrating growth factor signaling is sufficient to guarantee this robustness and which anticipates an embryo's response to perturbations in lineage composition. Addition of lineage-restricted cells both in vivo and in silico, causes a shift of the fate of progenitors away from the supernumerary cell type, while eliminating cells using laser ablation biases the specification of progenitors toward the targeted cell type. Finally, FGF4 couples fate decisions to lineage composition through changes in local growth factor concentration, providing a basis for the regulative abilities of the early mammalian embryo whereby fate decisions are coordinated at the population level to robustly generate tissues in the right proportions.
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Affiliation(s)
- Néstor Saiz
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, United States
| | - Laura Mora-Bitria
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
| | - Shahadat Rahman
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, United States
| | - Hannah George
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, United States
| | - Jeremy P Herder
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, United States
| | - Jordi Garcia-Ojalvo
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
| | - Anna-Katerina Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, United States
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