ゲノム情報科学研究教育機構  アブストラクト
Date Nov 30, 2016
Speaker Jiangning Song, Biomedicine Discovery Institute, Monash University, Australia
Title Systematic identification of secreted effector proteins of bacterial secretion system IV: a bioinformatics study
Abstract In the course of infection of their hosts, pathogenic bacteria secrete numerous effector proteins: bacterial proteins that pervert host cell biology. Many Gram-negative bacteria, including human pathogens such as Helicobacter pylori and Legionella pneumophila, use a type IV secretion system (T4SS) to translocate effectors directly into the cytosol of host cells. A number of type IV secreted effectors (T4SEs) have been experimentally identified, all of which play crucial roles in virulence by manipulating host cell gene expression and other processes. Effects include changes of cellular morphology, actin rearrangements, dysregulation of cell death pathways and activation of pro-inflammatory responses. Consequently, the identification and characterization of effector proteins is an important step in increased understanding of host-pathogen interactions and bacterial pathogenesis. In this context, we have recently developed a new bioinformatics method termed Bastion4 (Bacterial secretion effector predictor for type IV secretion system) to predict T4SEs from genome sequence data. In my talk, I will discuss the methodological details of Bastion4, effective strategies of how to combine different but complementary features to improve the predictive performance of T4SEs, as well as how machine learning can be harnessed to improve our understanding of the bacterial effector secretion.
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