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Non‐genetic diversity modulates population performance
by
Frankel, Nicholas W
, Johnston, Jessica F
, Dufour, Yann S
, Emonet, Thierry
, Waite, Adam James
, Long, Junjiajia
in
Adaptation, Physiological
/ Bias
/ Biodiversity
/ cellular motility
/ Chemotaxis
/ Data analysis
/ E coli
/ EMBO23
/ EMBO33
/ EMBO37
/ Escherichia coli - genetics
/ Escherichia coli - physiology
/ Escherichia coli Proteins - metabolism
/ Experiments
/ Gene Expression Regulation, Bacterial
/ Genetic diversity
/ Genotype & phenotype
/ Genotypes
/ Jensen's inequality
/ Microfluidic Analytical Techniques - instrumentation
/ Microfluidic devices
/ Microfluidics
/ Models, Biological
/ nonlinear systems
/ non‐genetic diversity
/ Phenotype
/ Phenotypes
/ Population
/ Population genetics
/ Proteins
/ Random variables
/ Swimming
2016
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Non‐genetic diversity modulates population performance
by
Frankel, Nicholas W
, Johnston, Jessica F
, Dufour, Yann S
, Emonet, Thierry
, Waite, Adam James
, Long, Junjiajia
in
Adaptation, Physiological
/ Bias
/ Biodiversity
/ cellular motility
/ Chemotaxis
/ Data analysis
/ E coli
/ EMBO23
/ EMBO33
/ EMBO37
/ Escherichia coli - genetics
/ Escherichia coli - physiology
/ Escherichia coli Proteins - metabolism
/ Experiments
/ Gene Expression Regulation, Bacterial
/ Genetic diversity
/ Genotype & phenotype
/ Genotypes
/ Jensen's inequality
/ Microfluidic Analytical Techniques - instrumentation
/ Microfluidic devices
/ Microfluidics
/ Models, Biological
/ nonlinear systems
/ non‐genetic diversity
/ Phenotype
/ Phenotypes
/ Population
/ Population genetics
/ Proteins
/ Random variables
/ Swimming
2016
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Non‐genetic diversity modulates population performance
by
Frankel, Nicholas W
, Johnston, Jessica F
, Dufour, Yann S
, Emonet, Thierry
, Waite, Adam James
, Long, Junjiajia
in
Adaptation, Physiological
/ Bias
/ Biodiversity
/ cellular motility
/ Chemotaxis
/ Data analysis
/ E coli
/ EMBO23
/ EMBO33
/ EMBO37
/ Escherichia coli - genetics
/ Escherichia coli - physiology
/ Escherichia coli Proteins - metabolism
/ Experiments
/ Gene Expression Regulation, Bacterial
/ Genetic diversity
/ Genotype & phenotype
/ Genotypes
/ Jensen's inequality
/ Microfluidic Analytical Techniques - instrumentation
/ Microfluidic devices
/ Microfluidics
/ Models, Biological
/ nonlinear systems
/ non‐genetic diversity
/ Phenotype
/ Phenotypes
/ Population
/ Population genetics
/ Proteins
/ Random variables
/ Swimming
2016
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Journal Article
Non‐genetic diversity modulates population performance
2016
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Overview
Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non‐genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely swimming
Escherichia coli
as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well‐mixed wild‐type populations due to non‐genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non‐genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype‐to‐performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could act on both during the process of adaptation.
Synopsis
A bacterial “race” in a microfluidic device revealed non‐genetic diversity in behavior and performance of clonal
E. coli
cells. The “shape” of behavioral diversity affected population performance as much as the mean behavior, supporting the hypothesis that this shape is evolvable.
A new microfluidic device was designed and used to track and analyze the trajectories of tens of thousands of individual, freely swimming bacteria climbing a gradient of chemoattractant.
Clonal wild‐type populations featured substantial behavioral diversity, giving rise to differences in performance that caused populations of bacteria to spatially segregate by phenotype as they climbed a gradient of attractant.
Manipulating gene expression of key chemotaxis proteins changed population phenotype and consequently performance, establishing a causal relationship between gene expression, phenotypic distribution, and population performance.
The population outperformed its mean phenotype due to the nonlinear shape of the phenotype‐to‐performance function, which disproportionately amplified the contributions of the tail of the phenotype distribution. Thus, the shape of a phenotypic distribution can be as important in determining population performance as its mean.
Graphical Abstract
A bacterial “race” in a microfluidic device revealed non‐genetic diversity in behavior and performance of clonal
E. coli
cells. The “shape” of behavioral diversity affected population performance as much as the mean behavior, supporting the hypothesis that this shape is evolvable.
Publisher
Nature Publishing Group UK,EMBO Press,John Wiley and Sons Inc,Springer Nature
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