A rticle An Experimentally Informed Evolutionary Model Improves Phylogenetic Fit to Divergent Lactamase Homologs

Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionarymodels that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments havemade it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene’s fitness landscape.Mol Biol Evol. 31:1581–1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35 % divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that exper-imental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence. Key words: phylogenetics, deep mutational scanning, lactamase, protein evolution, substitution model