Phylogenetic profiling, an untapped resource for the prediction of secreted proteins and its complementation with sequence-based classifiers in bacterial type III, IV and VI secretion systems

Andrés Zalguizuri, Gustavo Caetano-Anollés, Viviana Claudia Lepek

Research output: Contribution to journalArticle

Abstract

In the establishment and maintenance of the interaction between pathogenic or symbiotic bacteria with a eukaryotic organism, protein substrates of specialized bacterial secretion systems called effectors play a critical role once translocated into the host cell. Proteins are also secreted to the extracellular medium by free-living bacteria or directly injected into other competing organisms to hinder or kill. In this work, we explore an approach based on the evolutionary dependence that most of the effectors maintain with their specific secretion system that analyzes the co-occurrence of any orthologous protein group and their corresponding secretion system across multiple genomes. We compared and complemented our methodology with sequence-based machine learning prediction tools for the type III, IV and VI secretion systems. Finally, we provide the predictive results for the three secretion systems in 1606 complete genomes at http://www.iib.unsam.edu.ar/orgsissec/.

Original languageEnglish (US)
Pages (from-to)1395-1402
Number of pages8
JournalBriefings in bioinformatics
Volume20
Issue number4
DOIs
StatePublished - Mar 27 2018

Keywords

  • T3SS
  • T4SS
  • T6SS
  • machine learning
  • phylogenetic profile
  • protein secretion prediction

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology

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