A mathematical model for adaptive prediction of environmental changes by microorganisms

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 theoretical-experimental treatment presented here helps assess the potential of natural ecologies to support a predictive behavior.