Computational prediction shines light on type III secretion origins

Abstract

Type III secretion system is a key bacterial symbiosis and pathogenicity mechanism responsible for a variety of infectious diseases, ranging from food-borne illnesses to the bubonic plague. In many Gram-negative bacteria, the type III secretion system transports effector proteins into host cells, converting resources to bacterial advantage. Here we introduce a computational method that identifies type III effectors by combining homology-based inference with de novo predictions, reaching up to 3-fold higher performance than existing tools. Our work reveals that signals for recognition and transport of effectors are distributed over the entire protein sequence instead of being confined to the N-terminus, as was previously thought. Our scan of hundreds of prokaryotic genomes identified previously unknown effectors, suggesting that type III secretion may have evolved prior to the archaea/bacteria split. Crucially, our method performs well for short sequence fragments, facilitating evaluation of microbial communities and rapid identification of bacterial pathogenicity - no genome assembly required. pEffect and its data sets are available at http://services.bromberglab.org/peffect.

Publication
Scientific Reports
Tatyana Goldberg
Tatyana Goldberg
PhD Student

I am a proud former scholar of the Ernst Ludwig Ehrlich Studienwerk and also a guest editor of the F1000Research BioJS channel

Yana Bromberg
Yana Bromberg
Principal Investigator - Professor of Bioinformatics

My research focuses on deciphering the DNA blueprints of life’s molecular machinery