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      Predictive Modeling of Signaling Crosstalk during C. elegans Vulval Development

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          Abstract

          Caenorhabditis elegans vulval development provides an important paradigm for studying the process of cell fate determination and pattern formation during animal development. Although many genes controlling vulval cell fate specification have been identified, how they orchestrate themselves to generate a robust and invariant pattern of cell fates is not yet completely understood. Here, we have developed a dynamic computational model incorporating the current mechanistic understanding of gene interactions during this patterning process. A key feature of our model is the inclusion of multiple modes of crosstalk between the epidermal growth factor receptor (EGFR) and LIN-12/Notch signaling pathways, which together determine the fates of the six vulval precursor cells (VPCs). Computational analysis, using the model-checking technique, provides new biological insights into the regulatory network governing VPC fate specification and predicts novel negative feedback loops. In addition, our analysis shows that most mutations affecting vulval development lead to stable fate patterns in spite of variations in synchronicity between VPCs. Computational searches for the basis of this robustness show that a sequential activation of the EGFR-mediated inductive signaling and LIN-12 / Notch-mediated lateral signaling pathways is key to achieve a stable cell fate pattern. We demonstrate experimentally a time-delay between the activation of the inductive and lateral signaling pathways in wild-type animals and the loss of sequential signaling in mutants showing unstable fate patterns; thus, validating two key predictions provided by our modeling work. The insights gained by our modeling study further substantiate the usefulness of executing and analyzing mechanistic models to investigate complex biological behaviors.

          Author Summary

          Systems biology aims to gain a system-level understanding of living systems. To achieve such an understanding, we need to establish the methodologies and techniques to understand biological systems in their full complexity. One such attempt is to use methods designed for the construction and analysis of complex computerized systems to model biological systems. Describing mechanistic models in biology in a dynamic and executable language offers great advantages for representing time and parallelism, which are important features of biological behavior. In addition, automatic analysis methods can be used to ensure the consistency of computational models with biological data on which they are based. We have developed a dynamic computational model describing the current mechanistic understanding of cell fate determination during C. elegans vulval development, which provides an important paradigm for studying animal development. Our model is realistic, reproduces up-to-date experimental observations, allows in silico experimentation, and is analyzable by automatic tools. Analysis of our model provides new insights into the temporal aspects of the cell fate patterning process and predicts new modes of interaction between the signaling pathways involved. These biological insights, which were also validated experimentally, further substantiate the usefulness of dynamic computational models to investigate complex biological behaviors.

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          Most cited references45

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          Robustness in simple biochemical networks.

          Cells use complex networks of interacting molecular components to transfer and process information. These "computational devices of living cells" are responsible for many important cellular processes, including cell-cycle regulation and signal transduction. Here we address the issue of the sensitivity of the networks to variations in their biochemical parameters. We propose a mechanism for robust adaptation in simple signal transduction networks. We show that this mechanism applies in particular to bacterial chemotaxis. This is demonstrated within a quantitative model which explains, in a unified way, many aspects of chemotaxis, including proper responses to chemical gradients. The adaptation property is a consequence of the network's connectivity and does not require the 'fine-tuning' of parameters. We argue that the key properties of biochemical networks should be robust in order to ensure their proper functioning.
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            The lin-12 locus specifies cell fates in Caenorhabditis elegans.

            We describe two classes of mutations in the lin-12 locus of the nematode Caenorhabditis elegans. Ten semidominant mutations (lin-12[d]) appear to elevate the level of lin-12 activity. Thirty-two recessive alleles (lin-12[0]), including two amber mutations, appear to eliminate gene activity. The lin-12(d) and lin-12(0) mutations result in reciprocal homeotic transformations in the fates of defined cells in several different tissues. Gene dosage studies suggest that a high level of lin-12 activity specifies one cell fate and a low level specifies an alternative fate. Temperature-shift experiments indicate that lin-12 acts at the time cell fate is determined in wild type. We propose that lin-12 functions as a binary switch to control decisions between alternative cell fates during C. elegans development.
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              Crosstalk between the EGFR and LIN-12/Notch pathways in C. elegans vulval development.

              The Caenorhabditis elegans vulva is an important paradigm for cell-cell interactions in animal development. The fates of six vulval precursor cells are patterned through the action of the epidermal growth factor receptor-mitogen-activated protein kinase (EGFR-MAPK) inductive signaling pathway, which specifies the 1 degrees fate, and the LIN-12/Notch lateral signaling pathway, which specifies the 2 degrees fate. Here, we provide evidence that the inductive signal is spatially graded and initially activates the EGFR-MAPK pathway in the prospective 2 degrees cells. Subsequently, this effect is counteracted by the expression of multiple new negative regulators of the EGFR-MAPK pathway, under direct transcriptional control of the LIN-12-mediated lateral signal.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                May 2007
                18 May 2007
                : 3
                : 5
                : e92
                Affiliations
                [1 ] School of Computer and Communication Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
                [2 ] Institute of Zoology, University of Zurich, Zurich, Switzerland
                [3 ] Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, California, United States of America
                The University of Tokyo, Japan
                Author notes
                * To whom correspondence should be addressed. E-mail: jasmin.fisher@ 123456epfl.ch
                Article
                07-PLCB-RA-0010R2 plcb-03-05-10
                10.1371/journal.pcbi.0030092
                1868774
                17511512
                459a90b5-c812-42fc-a6b0-e2eca3e45056
                Copyright: © 2007 Fisher 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
                : 9 January 2007
                : 10 April 2007
                Page count
                Pages: 12
                Categories
                Research Article
                Cell Biology
                Computational Biology
                Developmental Biology
                Developmental Biology
                Caenorhabditis
                Custom metadata
                Fisher J, Piterman N, Hajnal A, Henzinger TA (2007) Predictive modeling of signaling crosstalk during C. elegans vulval development. PLoS Comput Biol 3(5): e92. doi: 10.1371/journal.pcbi.0030092

                Quantitative & Systems biology
                Quantitative & Systems biology

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