ArticleSystems and synthetic biology2013
A quantitative study of gene regulatory pathways in Bacillus subtilis for virulence and competence phenotype by quorum sensing.
Article in Systems and synthetic biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Time-resolved analysis of Bacillus subtilis DB104 Spo0A-mutant transcriptome profile and enhancement of recombinant protein release.Journal of microbiology (Seoul, Korea) · 2025Article
- Influence of Oral Administration of Bacillus subtilis on Growth Performance and Physiological Responses in Litopenaeus vannamei Cultured in Low Saline Waters.Probiotics and antimicrobial proteins · 2021Article
- Fungal-bacterial interaction selects for quorum sensing mutants with increased production of natural antifungal compounds.Communications biology · 2020Article
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Authors and funding
2 authors.
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Abstract
Quorum sensing (QS) is a process which allows a population of bacteria to coordinately regulate gene expression of their entire community. Bacillus subtilis is a soil organism which uses QS to alternate between competence for DNA uptake and sporulation. We propose a model to describe the components involved in QS and to analyze reaction species involved in the regulation of QS machinery. We targeted only those QS phenotypes for which the genetic organization and molecular characterization of the components are fully elucidated. We have analyzed simulations for concentration of different species involved in competence as well as sporulation pathways at diverse time period using quantitative methods. It was observed that there is possibility of achieving different measurement from reactions taken place between species by applying irreversible Michaelis-Menten kinetic law. We obtain variation in measurement on changing parameters such as concentrations ranging from 0.3 to 50 μM in stepwise manner by setting end time in the range of 0.1-100 ms. Additionally we observe covariance between different reaction species involved in QS by fluctuating their quantities in real-time simulations. Our model mimics correctly the phenotype for competence and virulence. We concluded that time factor play major role to determine rate kinetics of diverse reaction species as compared to their concentrations and support the hypothesis of getting genetic stability while colonies are in synchronization.
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