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Simulation of E. coli gene regulation including overlapping cell cycles, growth, division, time delays and noise.

ABSTRACT: Due to the complexity of biological systems, simulation of biological networks is necessary but sometimes complicated. The classic stochastic simulation algorithm (SSA) by Gillespie and its modified versions are widely used to simulate the stochastic dynamics of biochemical reaction systems. However, it has remained a challenge to implement accurate and efficient simulation algorithms for general reaction schemes in growing cells. Here, we present a modeling and simulation tool, called 'GeneCircuits', which is specifically developed to simulate gene-regulation in exponentially growing bacterial cells (such as E. coli) with overlapping cell cycles. Our tool integrates three specific features of these cells that are not generally included in SSA tools: 1) the time delay between the regulation and synthesis of proteins that is due to transcription and translation processes; 2) cell cycle-dependent periodic changes of gene dosage; and 3) variations in the propensities of chemical reactions that have time-dependent reaction rates as a consequence of volume expansion and cell division. We give three biologically relevant examples to illustrate the use of our simulation tool in quantitative studies of systems biology and synthetic biology.

SUBMITTER: Luo R

PROVIDER: S-EPMC3637171 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Simulation of E. coli gene regulation including overlapping cell cycles, growth, division, time delays and noise.

Luo Ruoyu R Ye Lin L Tao Chenyang C Wang Kankan K

PloS one 20130426 4

Due to the complexity of biological systems, simulation of biological networks is necessary but sometimes complicated. The classic stochastic simulation algorithm (SSA) by Gillespie and its modified versions are widely used to simulate the stochastic dynamics of biochemical reaction systems. However, it has remained a challenge to implement accurate and efficient simulation algorithms for general reaction schemes in growing cells. Here, we present a modeling and simulation tool, called 'GeneCirc ...[more]

PMID: 23638057

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Project description:Bacteria either duplicate their chromosome once per cell division or a new round of replication is initiated before the cells divide, thus cell cycles overlap. Here, we show that the opportunistic pathogen Pseudomonas aeruginosa switches from fast growth with overlapping cell cycles to sustained slow growth with only one replication round per cell division when cultivated under standard laboratory conditions. The transition was characterized by fast-paced, sequential changes in transcriptional activity along the ori-ter axis of the chromosome reflecting adaptation to the metabolic needs during both growth phases. Quorum sensing (QS) activity was highest at the onset of the slow growth phase with non-overlapping cell cycles. RNA sequencing of subpopulations of these cultures sorted based on their DNA content, revealed a strong gene dosage effect as well as specific expression patterns for replicating and nonreplicating cells. Expression of flagella and mexE, involved in multidrug efflux was restricted to cells that did not replicate, while those that did showed a high activity of the cell division locus and recombination genes. A possible role of QS in the formation of these subpopulations upon switching to non-overlapping cell cycles could be a subject of further research. IMPORTANCE The coordination of gene expression with the cell cycle has so far been studied only in a few bacteria, the bottleneck being the need for synchronized cultures. Here, we determined replication-associated effects on transcription by comparing Pseudomonas aeruginosa cultures that differ in their growth mode and number of replicating chromosomes. We further show that cell cycle-specific gene regulation can be principally identified by RNA sequencing of subpopulations from cultures that replicate only once per cell division and that are sorted according to their DNA content. Our approach opens the possibility to study asynchronously growing bacteria from a wide phylogenetic range and thereby enhance our understanding of the evolution of cell cycle control on the transcriptional level.

Dataset Information

Simulation of E. coli gene regulation including overlapping cell cycles, growth, division, time delays and noise.

Publications

Simulation of E. coli gene regulation including overlapping cell cycles, growth, division, time delays and noise.

Similar Datasets

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