Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit
Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on e...
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Published in | Molecular systems biology Vol. 17; no. 7; pp. e9832 - n/a |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
01.07.2021
EMBO Press John Wiley and Sons Inc Springer Nature |
Subjects | |
Online Access | Get full text |
ISSN | 1744-4292 1744-4292 |
DOI | 10.15252/msb.20209832 |
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Abstract | Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σ
V
circuit in
Bacillus subtilis
generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single‐cell time‐lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σ
V
under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the
sigV
operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma‐anti‐sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.
SYNOPSIS
A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history.
The time to activate the alternative sigma factor σ
V
in
Bacillus
subtilis
is found to be heterogeneous under lysozyme stress.
This phenotypic variability can be tuned by stress levels, previous stress applications, and genetic perturbations.
Modelling and experiments show that this tunability can be explained by the structure of the
sigV
operon, which consists of a ‘mixed’ positive and negative feedback loop.
Graphical Abstract
A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history. |
---|---|
AbstractList | Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σ
V
circuit in
Bacillus subtilis
generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single‐cell time‐lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σ
V
under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the
sigV
operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma‐anti‐sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.
SYNOPSIS
A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history.
The time to activate the alternative sigma factor σ
V
in
Bacillus
subtilis
is found to be heterogeneous under lysozyme stress.
This phenotypic variability can be tuned by stress levels, previous stress applications, and genetic perturbations.
Modelling and experiments show that this tunability can be explained by the structure of the
sigV
operon, which consists of a ‘mixed’ positive and negative feedback loop.
Graphical Abstract
A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history. Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σ circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σ under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single‐cell time‐lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma‐anti‐sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history. Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single‐cell time‐lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma‐anti‐sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. SYNOPSIS A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history. The time to activate the alternative sigma factor σV in Bacillus subtilis is found to be heterogeneous under lysozyme stress. This phenotypic variability can be tuned by stress levels, previous stress applications, and genetic perturbations. Modelling and experiments show that this tunability can be explained by the structure of the sigV operon, which consists of a ‘mixed’ positive and negative feedback loop. A combination of single‐cell imaging and mathematical modelling reveals a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment and environmental history. Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. Abstract Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single‐cell time‐lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma‐anti‐sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment. |
Author | Loman, Torkel E Schwall, Christian P Saez, Teresa Martins, Bruno M C Villava, Casandra Kusmartsev, Vassili Locke, James C W Livesey, Toby Cortijo, Sandra |
AuthorAffiliation | 2 School of Life Sciences University of Warwick Coventry UK 1 Sainsbury Laboratory University of Cambridge Cambridge UK |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34286912$$D View this record in MEDLINE/PubMed https://hal.inrae.fr/hal-03379751$$DView record in HAL |
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Keywords | microbial systems biology stochastic gene expression stress priming single‐cell time‐lapse microscopy single-cell time-lapse microscopy Bacillus subtilis Virology & Host Pathogen Interaction stress priming Subject Category Microbiology stress primingphenoty |
Language | English |
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Snippet | Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by... Abstract Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for... |
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SubjectTerms | Bacillus subtilis Bacillus subtilis - genetics Bacteria Bacterial Proteins - genetics Bacterial Proteins - metabolism Biological Variation, Population Circuits EMBO23 Environmental conditions Environmental history Gene expression Gene Expression Regulation, Bacterial Genetic variability Heterogeneity Homeostasis Humans Iterative methods Life Sciences Lysozyme microbial systems biology Microfluidics Microscopy Operon - genetics Perturbation Populations Proteins RNA polymerase Sigma factor Sigma Factor - genetics Sigma Factor - metabolism Signal transduction single‐cell time‐lapse microscopy stochastic gene expression Stress stress priming Transcription Variability |
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Title | Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit |
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