Publications

@article{Lind2019,

title = {Predicting mutational routes to new adaptive phenotypes},

author = {Peter A Lind and Eric Libby and Jenny Herzog and Paul B Rainey},

url = {https://elifesciences.org/articles/38822},

doi = {10.7554/eLife.38822},

year  = {2019},

date = {2019-01-08},

journal = {eLife},

number = {38822},

abstract = {Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive ‘wrinkly spreader’ (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.},

keywords = {Libby},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pcbi.1007169,

title = {Syntrophy emerges spontaneously in complex metabolic systems},

author = {Eric Libby and Laurent Hébert-Dufresne and Sayed-Rzgar Hosseini and Andreas Wagner},

url = {https://doi.org/10.1371/journal.pcbi.1007169},

doi = {10.1371/journal.pcbi.1007169},

year  = {2019},

date = {2019-01-01},

journal = {PLOS Computational Biology},

volume = {15},

number = {7},

pages = {1-17},

publisher = {Public Library of Science},

abstract = {Author summary By exchanging resources, the members of a microbial community can survive in environments where individual species cannot. Despite the abundance of such syntrophy, little is known about its evolutionary origin. The predominant hypothesis is that syntrophy arises when originally independent organisms in the same community become interdependent by accumulating mutations. In this view, syntrophy arises when organisms co-evolve. In sharp contrast we find that different metabolism can interact syntrophically without a shared evolutionary history. We show that syntrophy is an inherent and emergent property of the complex chemical reaction networks that constitute metabolism.},

keywords = {Libby},

pubstate = {published},

tppubtype = {article}

}

@article{Libby2019,

title = {Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging},

author = {Eric Libby and William C. Ratcliff},

url = {https://www.journals.uchicago.edu/doi/abs/10.1086/701786},

doi = {10.1086/701786},

journal = {The American Naturalist},

volume = {0},

abstract = {To survive unpredictable environmental change, many organisms adopt bet-hedging strategies that are initially costly but provide a long-term fitness benefit. The temporal extent of these deferred fitness benefits determines whether bet-hedging organisms can survive long enough to realize them. In this article, we examine a model of microbial bet hedging in which there are two paths to extinction: unpredictable environmental change and demographic stochasticity. In temporally correlated environments, these drivers of extinction select for different switching strategies. Rapid phenotype switching ensures survival in the face of unpredictable environmental change, while slower-switching organisms become extinct. However, when both switching strategies are present in the same population, then demographic stochasticity—enforced by a limited population size—leads to extinction of the faster-switching organism. As a result, we find a novel form of evolutionary suicide whereby selection in a fluctuating environment can favor bet-hedging strategies that ultimately increase the risk of extinction. Population structures with multiple subpopulations and dispersal can reduce the risk of extinction from unpredictable environmental change and shift the balance so as to facilitate the evolution of slower-switching organisms.},

keywords = {evolution, extinction, Libby},

pubstate = {forthcoming},

tppubtype = {article}

}