ArticlePLoS computational biology2020
Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Article
- Stress-Induced Constraint on Expression Noise of Essential Genes in E. coli.Journal of molecular evolution · 2024Article
- Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision.Science advances · 2023Article
- Transcription factor expression levels and environmental signals constrain transcription factor innovation.Microbiology (Reading, England) · 2023Article
- Characterizing the landscape of gene expression variance in humans.PLoS genetics · 2023Article
- A Selective Bottleneck During Host Entry Drives the Evolution of New Legume Symbionts.Molecular biology and evolution · 2023Article
- Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2023Article
- Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level.PLoS computational biology · 2022Article
- Bidirectional Genetic Control of Phenotypic Heterogeneity and Its Implication for Cancer Drug Resistance.Molecular biology and evolution · 2021Article
- Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution.Frontiers in oncology · 2021Article
- Capturing and Understanding the Dynamics and Heterogeneity of Gene Expression in the Living Cell.International journal of molecular sciences · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments where available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele that increases the fraction of a population initiating growth on acetate. Additionally, noise can protect this allele from extinction, accelerate its spread, and increase its likelihood of going to fixation. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks, particularly in environments that fluctuate periodically. Because such bottlenecks are frequent in fluctuating environments, and because periodically fluctuating environments themselves are common, this principle may apply to a broad range of environments and organisms.
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