Noise, Information and Fitness in Changing Environments

Pedraza, Juan Manuel; Garcia, David A.; F., Pérez-Ortiz, Muriel

doi:10.3389/fphy.2018.00083

Cited by 4 publications

(3 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Maintaining an internal model that is required to anticipate future internal states can be costly, and the degree to which organisms use feedforward mechanisms depends on the costs and benefits of anticipatory behaviours [113,114]. For example, sensing mechanisms involved in chemotaxis have a metabolic cost, and presumably the cost increases as the accuracy of sensing increases [115]. Learning and memory may entail fitness costs owing to the energy and materials required to acquire and store information [116].…”

Section: Class 3: General Adaptive Systemsmentioning

confidence: 99%

Life in fluctuating environments

Bernhardt

O’Connor

Sunday

et al. 2020

Phil. Trans. R. Soc. B

109

View full text Add to dashboard Cite

Variability in the environment defines the structure and dynamics of all living systems, from organisms to ecosystems. Species have evolved traits and strategies that allow them to detect, exploit and predict the changing environment. These traits allow organisms to maintain steady internal conditions required for physiological functioning through feedback mechanisms that allow internal conditions to remain at or near a set-point despite a fluctuating environment. In addition to feedback, many organisms have evolved feedforward processes, which allow them to adjust in anticipation of an expected future state of the environment. Here we provide a framework describing how feedback and feedforward mechanisms operating within organisms can generate effects across scales of organization, and how they allow living systems to persist in fluctuating environments. Daily, seasonal and multi-year cycles provide cues that organisms use to anticipate changes in physiologically relevant environmental conditions. Using feedforward mechanisms, organisms can exploit correlations in environmental variables to prepare for anticipated future changes. Strategies to obtain, store and act on information about the conditional nature of future events are advantageous and are evidenced in widespread phenotypes such as circadian clocks, social behaviour, diapause and migrations. Humans are altering the ways in which the environment fluctuates, causing correlations between environmental variables to become decoupled, decreasing the reliability of cues. Human-induced environmental change is also altering sensory environments and the ability of organisms to detect cues. Recognizing that living systems combine feedback and feedforward processes is essential to understanding their responses to current and future regimes of environmental fluctuations. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

show abstract

Section: Class 3: General Adaptive Systemsmentioning

confidence: 99%

Life in fluctuating environments

Bernhardt

O’Connor

Sunday

et al. 2020

Phil. Trans. R. Soc. B

109

View full text Add to dashboard Cite

show abstract

“…Cells must regulate transcriptional variation, as both high and low variation have functional consequences. High variation can have benefits, as cells may be more adaptable to changing environments (Pedraza et al, 2018; Wollman, 2018) and more likely to undergo cell fate transitions (Desai et al, 2021; Suderman et al, 2017). Noise may additionally confer the ability of a cell population to produce a diverse output to a single incoming signal (Azpeitia et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Ginley-Hidinger

Abewe

Osborne

et al. 2023

Preprint

View full text Add to dashboard Cite

Cis-Regulatory Elements (CREs) control transcription levels, temporal dynamics, and cell-cell variation — often referred to as transcriptional noise. However, the combination of regulatory proteins and epigenetic features necessary to control different transcription attributes is not fully understood. Here, single-cell RNA-seq (scRNA-seq) is conducted during a time course of estrogen treatment to identify genomic predictors of expression timing and noise. We find that genes associated with multiple active enhancers exhibit faster temporal responses. Synthetic modulation of enhancer activity verifies that activating enhancers accelerates expression responses, while inhibiting enhancers results in a more gradual response. Noise is controlled by a balance of promoter and enhancer activity. Active promoters are found at genes with low noise levels, whereas active enhancers are associated with high noise. Finally, we observe that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise levels. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

show abstract

“…Evolutionary theories about the fitness of phenotypic strategies [1,2,3,4,5,6] have made successful predictions of the outcomes of natural selection in fluctuating environments [3,4,7,8]. In those theories, the (geometric) fitness [4,5,6] is generally maximised.…”

Section: Introductionmentioning

confidence: 99%

Poor sensing maximises microbial fitness when few out of many signals are sensed

Tjalma

Planquè

Bruggeman

2019

Preprint

View full text Add to dashboard Cite

An open problem in biology is to understand when particular phenotypic adaptation strategies of microorganisms are selected during evolution. They range from random, bet-hedging strategies to deterministic, responsive strategies, relying on signalling circuits. We present an evolutionary model that integrates basic statistical physics of molecular circuits with fitness maximisation and information theory. Besides illustrating when bet-hedging strategies are more evolutionarily successful than responsive strategies, it gives new explanations for several puzzling observations on responsive strategies. For instance, the accuracy with which outputs of signalling networks of single cells track external signals can be remarkably low: cells often distinguish only between 2 to 4 concentration ranges, corresponding to 1 or 2 bits of mutual information between the signal and response variable. Why did evolution lead to such low-fidelity signalling systems? Our theory offers an explanation by taking a novel perspective. It considers the fitness benefit of all signals, including those that are not sensed. We introduce a new concept, 'latent information', which captures the mutual information between all nonsensed signals and the optimal response. The theory predicts that it is often evolutionarily optimal to transduce sensed signals noisily, due to latent information. It indicates that fitness can indeed be maximal when the optimal mutual information extracted from sensed signals is not maximal, but rather has a low value of about 1 or 2 bits -even at moderate values of the latent information -in agreement with experimental findings. Cells likely do not sense all signals because of the fitness cost of expressing many idle signalling systems, which consume limited biosynthetic resources otherwise available for growth. Signals should only be sensed at maximal precision when they contain all information about the optimal response. This work contributes to PreprintOctober 9, 2019 a better understanding of the fitness contributions of phenotypic adaptation strategies of microorganisms.

show abstract

Noise, Information and Fitness in Changing Environments

Cited by 4 publications

References 78 publications

Life in fluctuating environments

Life in fluctuating environments

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Poor sensing maximises microbial fitness when few out of many signals are sensed

Contact Info

Product

Resources

About