Send to

Choose Destination
Sci Rep. 2016 Oct 7;6:34516. doi: 10.1038/srep34516.

Computational prediction shines light on type III secretion origins.

Author information

Department of Informatics, Bioinformatics &Computational Biology - I12, TUM, Garching, Germany.
Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), TUM, Garching, Germany.
Institute for Advanced Study (TUM-IAS), Garching, Germany.
Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.
Department of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, USA.


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

[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center