Mining and Statistical Modeling of Natural and Variant Class IIa Bacteriocins Elucidate Activity and Selectivity Profiles across Species

Abstract

Class IIa bacteriocin antimicrobial peptides (AMPs), an alternative to traditional small-molecule antibiotics, are capable of selective activity toward various Gram-positive bacteria, limiting negative side effects associated with broad-spectrum activity. This selective activity is achieved through targeting of the mannose phosphotransferase system (manPTS) of a subset of Gram-positive bacteria, although factors affecting this mechanism are not entirely understood. Peptides identified from genomic data, as well as variants of previously characterized AMPs, can offer insight into how peptide sequence affects activity and selectivity. The experimental methods presented here identify promising potent and selective bacteriocins for further evaluation, highlight the potential of simple computational modeling for prediction of AMP performance, and demonstrate that factors beyond manPTS sequence affect bacterial susceptibility to class IIa bacteriocins.