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      Agent-based modeling of morphogenetic systems: Advantages and challenges

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          Abstract

          The complexity of morphogenesis poses a fundamental challenge to understanding the mechanisms governing the formation of biological patterns and structures. Over the past century, numerous processes have been identified as critically contributing to morphogenetic events, but the interplay between the various components and aspects of pattern formation have been much harder to grasp. The combination of traditional biology with mathematical and computational methods has had a profound effect on our current understanding of morphogenesis and led to significant insights and advancements in the field. In particular, the theoretical concepts of reaction–diffusion systems and positional information, proposed by Alan Turing and Lewis Wolpert, respectively, dramatically influenced our general view of morphogenesis, although typically in isolation from one another. In recent years, agent-based modeling has been emerging as a consolidation and implementation of the two theories within a single framework. Agent-based models (ABMs) are unique in their ability to integrate combinations of heterogeneous processes and investigate their respective dynamics, especially in the context of spatial phenomena. In this review, we highlight the benefits and technical challenges associated with ABMs as tools for examining morphogenetic events. These models display unparalleled flexibility for studying various morphogenetic phenomena at multiple levels and have the important advantage of informing future experimental work, including the targeted engineering of tissues and organs.

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          Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells.

          G Martin (1981)
          This report describes the establishment directly from normal preimplantation mouse embryos of a cell line that forms teratocarcinomas when injected into mice. The pluripotency of these embryonic stem cells was demonstrated conclusively by the observation that subclonal cultures, derived from isolated single cells, can differentiate into a wide variety of cell types. Such embryonic stem cells were isolated from inner cell masses of late blastocysts cultured in medium conditioned by an established teratocarcinoma stem cell line. This suggests that such conditioned medium might contain a growth factor that stimulates the proliferation or inhibits the differentiation of normal pluripotent embryonic cells, or both. This method of obtaining embryonic stem cells makes feasible the isolation of pluripotent cells lines from various types of noninbred embryo, including those carrying mutant genes. The availability of such cell lines should made possible new approaches to the study of early mammalian development.
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            Establishment in culture of pluripotential cells from mouse embryos.

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              Formation of pluripotent stem cells in the mammalian embryo depends on the POU transcription factor Oct4.

              Oct4 is a mammalian POU transcription factor expressed by early embryo cells and germ cells. We report that the activity of Oct4 is essential for the identity of the pluripotential founder cell population in the mammalian embryo. Oct4-deficient embryos develop to the blastocyst stage, but the inner cell mass cells are not pluripotent. Instead, they are restricted to differentiation along the extraembryonic trophoblast lineage. Furthermore, in the absence of a true inner cell mass, trophoblast proliferation is not maintained in Oct4-/- embryos. Expansion of trophoblast precursors is restored, however, by an Oct4 target gene product, fibroblast growth factor-4. Therefore, Oct4 also determines paracrine growth factor signaling from stem cells to the trophectoderm.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                28 March 2019
                March 2019
                : 15
                : 3
                : e1006577
                Affiliations
                [001]The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America
                National Research Council of Italy, ITALY
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-3781-8802
                http://orcid.org/0000-0003-1378-3043
                Article
                PCOMPBIOL-D-18-01191
                10.1371/journal.pcbi.1006577
                6438454
                30921323
                8d208139-0771-4081-8462-b3aa413e0786
                © 2019 Glen et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 5, Tables: 0, Pages: 31
                Funding
                The authors gratefully acknowledge funding from NSF Emergent Behaviors of Integrated Cellular Systems Science and Technology Center (CBET 0939511) and NSF-MCB 1517588 (EOV [PI]) and a graduate research fellowship to CMG from the Natural Sciences and Engineering Research Council of Canada. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Review
                Biology and Life Sciences
                Developmental Biology
                Morphogenesis
                Biology and Life Sciences
                Developmental Biology
                Cell Differentiation
                Research and Analysis Methods
                Simulation and Modeling
                Agent-Based Modeling
                Computer and Information Sciences
                Systems Science
                Agent-Based Modeling
                Physical Sciences
                Mathematics
                Systems Science
                Agent-Based Modeling
                Biology and Life Sciences
                Developmental Biology
                Molecular Development
                Morphogens
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cell Cycle and Cell Division
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Stem Cells
                Cell Potency
                Pluripotency
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cell Death
                Apoptosis
                Biology and Life Sciences
                Developmental Biology
                Morphogenesis
                Pattern Formation

                Quantitative & Systems biology
                Quantitative & Systems biology

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