ArticlePloS one2014
Dynamical modeling of the cell cycle and cell fate emergence in Caulobacter crescentus.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- Intracellular signaling in proto-eukaryotes evolves to alleviate regulatory conflicts of endosymbiosis.PLoS computational biology · 2024Article
- Obligate endosymbiosis enables genome expansion during eukaryogenesis.Communications biology · 2023Article
- Evolution of Complex Regulation for Cell-Cycle Control.Genome biology and evolution · 2022Article
- Reciprocal control of motility and biofilm formation by the PdhS2 two-component sensor kinase of Agrobacterium tumefaciens.Microbiology (Reading, England) · 2019Article
- Dynamical Patterning Modules, Biogeneric Materials, and the Evolution of Multicellular Plants.Frontiers in plant science · 2018Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The division of Caulobacter crescentus, a model organism for studying cell cycle and differentiation in bacteria, generates two cell types: swarmer and stalked. To complete its cycle, C. crescentus must first differentiate from the swarmer to the stalked phenotype. An important regulator involved in this process is CtrA, which operates in a gene regulatory network and coordinates many of the interactions associated to the generation of cellular asymmetry. Gaining insight into how such a differentiation phenomenon arises and how network components interact to bring about cellular behavior and function demands mathematical models and simulations. In this work, we present a dynamical model based on a generalization of the Boolean abstraction of gene expression for a minimal network controlling the cell cycle and asymmetric cell division in C. crescentus. This network was constructed from data obtained from an exhaustive search in the literature. The results of the simulations based on our model show a cyclic attractor whose configurations can be made to correspond with the current knowledge of the activity of the regulators participating in the gene network during the cell cycle. Additionally, we found two point attractors that can be interpreted in terms of the network configurations directing the two cell types. The entire network is shown to be operating close to the critical regime, which means that it is robust enough to perturbations on dynamics of the network, but adaptable to environmental changes.
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