SSTAR, a Stand-Alone Easy-To-Use Antimicrobial Resistance Gene Predictor

Abstract

Whole-genome sequencing (WGS) is quickly becoming a routine method for identifying genes associated with antimicrobial resistance (AR). However, for many microbiologists, the use and analysis of WGS data present a substantial challenge. We developed SSTAR, software with a graphical user interface that enables the identification of known AR genes from WGS and has the unique capacity to easily detect new variants of known AR genes, including truncated protein variants. Current software solutions do not notify the user when genes are truncated and, therefore, likely nonfunctional, which makes phenotype predictions less accurate. SSTAR users can apply any AR database of interest as a reference comparator and can manually add genes that impact resistance, even if such genes are not resistance determinants per se (e.g., porins and efflux pumps).