PNNL

Abstract

Functional traits are characteristics that affect the fitness and metabolic function of a microorganism. There is growing interest to characterize bacterial pathogens based on functional virulence traits by high-throughput methods. Traditional methods that phenotype a single organism for a single virulence trait can be time-consuming and labor intensive. Alternatively, using machine learning of whole-genome sequences (WGS) has shown some success for predicting virulence but relying solely on WGS can miss functional traits particularly for organisms lacking classical virulence factors. We propose that high-throughput assays for functional virulence trait identification should become a prominent method of characterizing bacterial pathogens on a population scale. We discuss six key areas of functional trait testing and how advancement of high-throughput methods could provide a greater understanding of pathogens. This work is critical as we move from compiling lists of bacterial species associated with disease to pathogen agnostic approaches capable of detecting novel microbes.