Epigenetic Ratchet: Spontaneous Adaptation via Stochastic Gene Expression (original) (raw)

Stochastic Gene Expression in Bacterial Pathogens: A Mechanism for Persistence?

Systems Biology of Tuberculosis, 2012

Recent experiments have shown the relevance of stochastic fl uctuations to numerous biological phenomena. Intrinsic and extrinsic sources of noise existing at the subcellular level are capable of in fl uencing the population dynamics and are believed to be responsible for the appearance of different phenotypes in clonal bacterial populations. Single cell level phenotypic diversity is a likely key factor in the emergence of persistence in Mycobacterium tuberculosis . Stochastic phenomena in molecular interaction networks have been fi rst postulated in theoretical studies and later con fi rmed by experimental observations of individual cells and molecules. Here, we shall review the main modeling tools that can be used in this context, namely stochastic differential equations (Langevin equations) and Master Equations and their simulational counterparts, such as the Gillespie algorithm. We will distinguish between intrinsic and extrinsic noise in subcellular networks, highlighting in particular the unexpected and sometimes counterintuitive behaviors induced by extrinsic noise. We will discuss the dependence of prokaryotic gene expression noise on transcription and translation rates, as emerged from theoretical and experimental studies of stochasticity in biochemical processes. These fi ndings have direct consequences for understanding more complex gene regulatory networks, such as catabolic repression and two-component systems. Finally we will discuss the insights into the emergence of persistence of M. tuberculosis resulting from our understanding of stochastic gene expression, and delineate directions of future research.

Positive feedback circuits and adaptive regulations in bacteria

Acta biotheoretica, 2001

The mechanisms by which bacteria adapt to changes in their environment involve transcriptional regulation in which a transcriptional regulator responds to signal(s) from the environment and regulates (positively or negatively) the expression of several genes or operons. Some of these regulators exert a positive feedback on their own expression. This is a necessary (although not sufficient) condition for the occurrence of multistationarity. One biological consequence of multistationarity may be epigenetic modifications, a hypothesis unusual to microbiologists, in spite of some well-known epigenetic modifications in bacteria. We propose here that the occurrence of mucoidy in the opportunistic pathogen Pseudomonas aeruginosa, which is currently attributed to mutations only, may also be an epigenetic modification. A theoretical approach using a generalised logical analysis lends credit to this hypothesis and suggests experiments to ascertain it.

Adaptable Functionality of Transcriptional Feedback in Bacterial Two-Component Systems

A widespread mechanism of bacterial signaling occurs through two-component systems, comprised of a sensor histidine kinase (SHK) and a transcriptional response regulator (RR). The SHK activates RR by phosphorylation. The most common two-component system structure involves expression from a single operon, the transcription of which is activated by its own phosphorylated RR. The role of this feedback is poorly understood, but it has been associated with an overshooting kinetic response and with fast recovery of previous interrupted signaling events in different systems. Mathematical models show that overshoot is only attainable with negative feedback that also improves response time. Our models also predict that fast recovery of previous interrupted signaling depends on high accumulation of SHK and RR, which is more likely in a positive feedback regime. We use Monte Carlo sampling of the parameter space to explore the range of attainable model behaviors. The model predicts that the effective feedback sign can change from negative to positive depending on the signal level. Variations in two-component system architectures and parameters may therefore have evolved to optimize responses in different bacterial lifestyles. We propose a conceptual model where low signal conditions result in a responsive system with effectively negative feedback while high signal conditions with positive feedback favor persistence of system output.

Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences

Cell, 2008

Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.

Gene amplification as a form of population-level gene expression regulation

Nature Ecology & Evolution, 2020

Organisms cope with change by employing transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. We ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. By real-time monitoring of gene copy number mutations in E. coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy number, and hence expression level, polymorphism. This 'amplification-mediated gene expression tuning' occurs on timescales similar to canonical gene regulation and can deal with rapid environmental changes. Mathematical modeling shows that amplifications also tune gene expression in stochastic environments where transcription factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune expression of any gene, without leaving any genomic signature. Main Natural environments change periodically or stochastically with frequent or very rare fluctuations and life crucially depends on the ability to respond to such changes. Gene regulatory networks have evolved into an elaborate mechanism for such adjustments as populations were repeatedly required to cope with specific environmental changes 1-3. Gene regulation requires many dedicated components-transcription factors and promoter sequences on the DNA-for information processing to occur. However, due to low single base-pair mutation rates, complex promoters cannot easily evolve on ecological time scales 4,5. Gene copy number mutations might provide a fundamentally different adaptation strategy, which neither depends on existing regulation nor requires regulation to evolve. Gene

Escherichia coli can survive stress by noisy growth modulation

Nature Communications

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these strategies. Here, we show how noisy expression of a key stress-response regulator, RpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. We reveal a dynamic positive feedback loop between RpoS and growth rate that produces multi-generation RpoS pulses. We do so experimentally using single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Next, we demonstrate that E. coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by the RpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability.

Pre-Disposition and Epigenetics Govern Variation in Bacterial Survival upon Stress

PLoS Genetics, 2012

Bacteria suffer various stresses in their unpredictable environment. In response, clonal populations may exhibit cell-to-cell variation, hypothetically to maximize their survival. The origins, propagation, and consequences of this variability remain poorly understood. Variability persists through cell division events, yet detailed lineage information for individual stressresponse phenotypes is scarce. This work combines time-lapse microscopy and microfluidics to uniformly manipulate the environmental changes experienced by clonal bacteria. We quantify the growth rates and RpoH-driven heat-shock responses of individual Escherichia coli within their lineage context, stressed by low streptomycin concentrations. We observe an increased variation in phenotypes, as different as survival from death, that can be traced to asymmetric division events occurring prior to stress induction. Epigenetic inheritance contributes to the propagation of the observed phenotypic variation, resulting in three-fold increase of the RpoH-driven expression autocorrelation time following stress induction. We propose that the increased permeability of streptomycin-stressed cells serves as a positive feedback loop underlying this epigenetic effect. Our results suggest that stochasticity, pre-disposition, and epigenetic effects are at the source of stress-induced variability. Unlike in a bet-hedging strategy, we observe that cells with a higher investment in maintenance, measured as the basal RpoH transcriptional activity prior to antibiotic treatment, are more likely to give rise to stressed, frail progeny.

A Generic Mechanism for Adaptive Growth Rate Regulation

PLoS Computational Biology, 2008

How can a microorganism adapt to a variety of environmental conditions despite the existence of a limited number of signal transduction mechanisms? We show that for any growing cells whose gene expression fluctuate stochastically, the adaptive cellular state is inevitably selected by noise, even without a specific signal transduction network for it. In general, changes in protein concentration in a cell are given by its synthesis minus dilution and degradation, both of which are proportional to the rate of cell growth. In an adaptive state with a higher growth speed, both terms are large and balanced. Under the presence of noise in gene expression, the adaptive state is less affected by stochasticity since both the synthesis and dilution terms are large, while for a nonadaptive state both the terms are smaller so that cells are easily kicked out of the original state by noise. Hence, escape time from a cellular state and the cellular growth rate are negatively correlated. This leads to a selection of adaptive states with higher growth rates, and model simulations confirm this selection to take place in general. The results suggest a general form of adaptation that has never been brought to light-a process that requires no specific mechanisms for sensory adaptation. The present scheme may help explain a wide range of cellular adaptive responses including the metabolic flux optimization for maximal cell growth.

Epigenetic Feedback Regulation Accelerates Adaptation and Evolution

PLoS ONE, 2013

A simple cell model consisting of a gene regulatory network with epigenetic feedback regulation is studied to evaluate the effect of epigenetic dynamics on adaptation and evolution. We find that, the type of epigenetic dynamics considered enables a cell to adapt to unfamiliar environmental changes, for which no regulatory program has been prepared, through noise-driven selection of a cellular state with a high growth rate. Furthermore, we demonstrate that the inclusion of epigenetic regulation promotes evolutionary development of a regulatory network that can respond to environmental changes in a fast and precise manner. These results strongly suggest that epigenetic feedback regulation in gene expression dynamics provides a significant increase in fitness by engendering an increase in cellular plasticity during adaptation and evolution.