A mathematical model for adaptive prediction of environmental changes by microorganisms

Abstract

Survival in natural habitats selects for microorganisms that are well-adapted to a wide range of conditions. Recent studies revealed that cells evolved innovative response strategies that extend beyond merely sensing a given stimulus and responding to it on encounter. A diversity of microorganisms, including Escherichia coli, Vibrio cholerae, and several yeast species, were shown to use a predictive regulation strategy that uses the appearance of one stimulus as a cue for the likely arrival of a subsequent one. A better understanding of such a predictive strategy requires elucidating the interplay between key biological and environmental forces. Here, we describe a mathematical framework to address this challenge. We base this framework on experimental systems featuring early preparation to either a stress or an exposure to improvement in the growth medium. Our model calculates the fitness advantage originating under each regulation strategy in a given habitat. We conclude that, although a predictive response strategy might by advantageous under some ecologies, its costs might exceed the benefit in others. The combined theoreticalexperimental treatment presented here helps assess the potential of natural ecologies to support a predictive behavior.adaptation | conditioning | evolution M icroorganisms are constantly faced with environmental stimuli and stresses. Over the years, cellular response to such challenges has been intensively studied in several model organisms (1-5). Prevalent response strategies follow a sense and respond logic: cells continuously monitor their environment and induce a cellular response to cope with a stimulus on encounter with it. Although evolution selects for improved sensing and response mechanisms, adaptation can also extend and result in the emergence of more sophisticated response strategies. For example, under stochastic switching, cells randomly alternate between potential cellular states. In a fluctuating environment that is hard to monitor, such a response strategy might ensure that a portion of the population is always prepared for unpredicted challenge (6-8).Here, we focus on environments that are characterized by a stereotypical temporal order of stimuli. Previous theoretical work has suggested that such ecologies may select for organisms that use information about the natural sequence of events (8). Recent studies have revealed examples of such adaptations in model microorganisms. Tagkopoulos et al. (9) investigated the response of Escherichia coli to temperature elevation that is followed shortly after by a drop in oxygen availability on entry of bacteria to the host digestive tract and observed an associative anticipatory regulation pattern-each signal by itself can invoke response to both stimuli. In another study, we have shown that E. coli has adapted to the sequential order of exposure to different sugars along the mammalian digestive tract. Additionally, we have shown that this conditioned response entails the bacteria with fitness advantages when cells are exposed...

Phenotypic plasticity in evolutionary rescue experiments

“…Experimental evolution over multiple generations has been carried out with Drosophila [85], Caenorhabditis [93], mice [66] and plants [59], for instance, suggesting that insightful ER experiments could also be performed with multicellular organisms, despite their relatively longer generation time, provided that the evolutionary dynamics per generation are relatively rapid. Potential lags between an environmental cue and selection on the expressed plastic trait also may be easier to measure or manipulate in multicellular organisms than in microbes (even though such lags have already been measured precisely with the latter [72]). A caveat is that the larger body size of multicellular eucaryotes implies that fewer individuals can be reared per space unit.…”

“…We are not aware of any quantitative predictions for this evolutionary demographic effect. Evolutionary theory has investigated the role of environmental predictability for the evolution of plasticity, but without demography [11,30,31,72]; Reed et al [15] performed simulations on the interaction of plasticity and population growth in a fluctuating environment, but without evolution, and without changes in patterns of environmental variation. Despite the lack of quantitative predictions, basic qualitative predictions could be tested experimentally.…”

Response of single bacterial cells to stress gives rise to complex history dependence at the population level

“…It has been demonstrated that bacterial populations respond faster to a change of nutrient source when the forthcoming nutrient source has been presented in the recent past (2,3). Similarly, bacterial populations that were exposed to sublethal stress levels showed increased survival of a higher stress level of the same type (4)(5)(6). Theoretical and experimental studies indicate that basing cellular decisions on environmental cues perceived in the past can be advantageous in dynamic environments (3,7,8), suggesting that such history-dependent behavior can be the result of adaptive evolution in dynamic environments.…”

Stress Adaptation

“…Some microbes occupy reasonably predictable niches in which one environmental input is generally followed by a second input. In such cases, fungi that have evolved to anticipate the second input following exposure to the first would have a fitness advantage (206) Domesticated brewing yeasts provide an excellent example of this “adaptive prediction” because, as they ferment sugars, they become exposed to increasing ethanol concentrations (input 1) and then, when the sugars are exhausted, they switch to respiratory metabolism and become exposed to oxidative stress (input 2). Presumably as a consequence of this environmental predictability, S. cerevisiae has evolved to activate oxidative stress genes following exposure to ethanol (207).…”