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      Emergent Stem Cell Homeostasis in the C. elegans Germline Is Revealed by Hybrid Modeling

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          Abstract

          The establishment of homeostasis among cell growth, differentiation, and apoptosis is of key importance for organogenesis. Stem cells respond to temporally and spatially regulated signals by switching from mitotic proliferation to asymmetric cell division and differentiation. Executable computer models of signaling pathways can accurately reproduce a wide range of biological phenomena by reducing detailed chemical kinetics to a discrete, finite form. Moreover, coordinated cell movements and physical cell-cell interactions are required for the formation of three-dimensional structures that are the building blocks of organs. To capture all these aspects, we have developed a hybrid executable/physical model describing stem cell proliferation, differentiation, and homeostasis in the Caenorhabditis elegans germline. Using this hybrid model, we are able to track cell lineages and dynamic cell movements during germ cell differentiation. We further show how apoptosis regulates germ cell homeostasis in the gonad, and propose a role for intercellular pressure in developmental control. Finally, we use the model to demonstrate how an executable model can be developed from the hybrid system, identifying a mechanism that ensures invariance in fate patterns in the presence of instability.

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          Most cited references40

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          A genetic model for colorectal tumorigenesis.

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            Genetic control of programmed cell death in the Caenorhabditis elegans hermaphrodite germline.

            Development of the nematode Caenorhabditis elegans is highly reproducible and the fate of every somatic cell has been reported. We describe here a previously uncharacterized cell fate in C. elegans: we show that germ cells, which in hermaphrodites can differentiate into sperm and oocytes, also undergo apoptotic cell death. In adult hermaphrodites, over 300 germ cells die, using the same apoptotic execution machinery (ced-3, ced-4 and ced-9) as the previously described 131 somatic cell deaths. However, this machinery is activated by a distinct pathway, as loss of egl-1 function, which inhibits somatic cell death, does not affect germ cell apoptosis. Germ cell death requires ras/MAPK pathway activation and is used to maintain germline homeostasis. We suggest that apoptosis eliminates excess germ cells that acted as nurse cells to provide cytoplasmic components to maturing oocytes.
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              Executable cell biology.

              Computational modeling of biological systems is becoming increasingly important in efforts to better understand complex biological behaviors. In this review, we distinguish between two types of biological models--mathematical and computational--which differ in their representations of biological phenomena. We call the approach of constructing computational models of biological systems 'executable biology', as it focuses on the design of executable computer algorithms that mimic biological phenomena. We survey the main modeling efforts in this direction, emphasize the applicability and benefits of executable models in biological research and highlight some of the challenges that executable biology poses for biology and computer science. We claim that for executable biology to reach its full potential as a mainstream biological technique, formal and algorithmic approaches must be integrated into biological research. This will drive biology toward a more precise engineering discipline.
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                Author and article information

                Contributors
                Journal
                Biophys J
                Biophys. J
                Biophysical Journal
                The Biophysical Society
                0006-3495
                1542-0086
                21 July 2015
                21 July 2015
                : 109
                : 2
                : 428-438
                Affiliations
                [1 ]Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, United Kingdom
                [2 ]Microsoft Research Cambridge, Cambridge, UK
                [3 ]Department of Computer Science, University of Leicester, Leicester, UK
                [4 ]Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
                [5 ]Department of Biochemistry, University of Cambridge, Cambridge, UK
                Author notes
                Article
                S0006-3495(15)00589-5
                10.1016/j.bpj.2015.06.007
                4621618
                26200879
                3cbde25b-1c7e-481f-b051-01710ea2ef3e
                © 2015 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 7 January 2015
                : 5 June 2015
                Categories
                Systems Biophysics

                Biophysics
                Biophysics

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