New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand; Department of Molecular Biology, Umeå University, Umeå, Sweden
Eric Libby
New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand; Santa Fe Institute, New Mexico, United States; Department of Mathematics, Umeå University, Umeå, Sweden
Jenny Herzog
New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand
New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand; Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany; Ecole Supérieure de Physique et de Chimie Industrielles de la Ville de Paris, ESPCI Paris-Tech, CNRS UMR 8231, PSL Research University, Paris, France
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.