bioRxivSystems BiologyPreprint
Quantitative modelling of fate specification in the C. elegans postembryonicM lineage reveals a missing spatiotemporal signal
Benjamin Planterose JiméneziD, Alexander R. BlackwelliD, João Jacob RamalhoiD, Sander van den HeuveliD, Kirsten ten TusscheriD, Erika TsingosiD
Abstract
The invariant lineages of C. elegans provide tractable cell fate models to study how developing organisms robustly integrate spatial signals at the single-cell level via gene regulatory networks. For instance, during postembryonic development, a mesoderm lineage arises through a sequence of oriented cell divisions from a single progenitor. This mesoblast initially gives rise to 18 cells with three distinct fates - 14 body wall muscles (BWMs), 2 coelomocytes (CCs; dorsal), and 2 sex myoblasts (SMs; ventral). The latter cells migrate and then proliferate to contribute 16 smooth muscles to the nematodes reproductive organs. Prior work identified key symmetry breaking cues: i) ventrally restricted activation of the LIN-12 Notch pathway promoting SM over CC fate and ii) asymmetric re-distribution of SYS-1 {beta}-catenin and POP-1 TCF among daughter cells along the anteroposterior (A-P) axis, i.e. the Wnt/{beta}-catenin asymmetry pathway. However, it remains unclear whether these pathways are sufficient to specify all cell fates accordingly or whether additional symmetry breaking cues are necessary. In this study, we use quantitative modelling to better understand fate specification in the postembryonic M lineage. Specifically, we focus on the anteroposterior symmetry break by creating increasingly complex models towards robustly reproducing fate specification in wild type larvae and mutants. This iterative process resulted in two alternative models that explain the experimental observations by either introducing an additional spatial (spatial symmetry break) or temporal cue (temporal symmetry break). Finally, we evaluate their plausibility and propose a series of experiments to provide support for alternative models. Overall, our study highlights how a quantitative examination of mechanistic ideas can identify knowledge gaps and guide experimental follow-up.
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