Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type iii secretion systems

Ram Samudrala, Fred Heffron, Jason E. McDermott

    Research output: Contribution to journalArticle

    123 Citations (Scopus)

    Abstract

    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates-effector proteins-are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

    Original languageEnglish (US)
    JournalPLoS Pathogens
    Volume5
    Issue number4
    DOIs
    StatePublished - Apr 2009

    Fingerprint

    Proteins
    Pseudomonas syringae
    Salmonella enterica
    Chlamydia trachomatis
    Base Composition
    Gram-Negative Bacteria
    Virulence
    Bacteria
    Amino Acids
    Sensitivity and Specificity
    Serogroup
    Type III Secretion Systems

    ASJC Scopus subject areas

    • Microbiology
    • Parasitology
    • Virology
    • Immunology
    • Genetics
    • Molecular Biology

    Cite this

    Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type iii secretion systems. / Samudrala, Ram; Heffron, Fred; McDermott, Jason E.

    In: PLoS Pathogens, Vol. 5, No. 4, 04.2009.

    Research output: Contribution to journalArticle

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