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dc.creatorAshari, Zhila Esna
dc.creatorBrayton, Kelly A.
dc.creatorBroschat, Shira L.
dc.date.accessioned2020-07-13T20:21:29Z
dc.date.available2020-07-13T20:21:29Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/2376/17912
dc.description.abstractType IV secretion systems (T4SS) are used by a number of bacterial pathogens to attack the host cell. The complex protein structure of the T4SS is used to directly translocate effector proteins into host cells, often causing fatal diseases in humans and animals. Identification of effector proteins is the first step in understanding how they function to cause virulence and pathogenicity. Accurate prediction of effector proteins via a machine learning approach can assist in the process of their identification. The main goal of this study is to predict a set of candidate effectors for the tick-borne pathogen Anaplasma phagocytophilum, the causative agent of anaplasmosis in humans. To our knowledge, we present the first computational study for effector prediction with a focus on A. phagocytophilum. In a previous study, we systematically selected a set of optimal features from more than 1,000 possible protein characteristics for predicting T4SS effector candidates. This was followed by a study of the features using the proteome of Legionella pneumophila strain Philadelphia deduced from its complete genome. In this manuscript we introduce the OPT4e software package for Optimal-features Predictor for T4SS Effector proteins. An earlier version of OPT4e was verified using cross-validation tests, accuracy tests, and comparison with previous results for L. pneumophila. We use OPT4e to predict candidate effectors from the proteomes of A. phagocytophilum strains HZ and HGE-1 and predict 48 and 46 candidates, respectively, with 16 and 18 deemed most probable as effectors. These latter include the three known validated effectors for A. phagocytophilum.en_US
dc.languageEnglish
dc.publisherFrontiers in Microbiology
dc.rightsCreative Commons Attribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titlePrediction of T4SS Effector Proteins for Anaplasma phagocytophilum Using OPT4e, A New Software Tool
dc.typeArticle
dc.description.versionPublished copy
dc.description.citationEsna Ashari, Z., K.A. Brayton, and S.L. Broschat. (2019). Prediction of T4SS effector proteins for Anaplasma phagocytophilum using OPT4e, a new software tool. Frontiers in Microbiology, Vol.10. doi:10.3389/fmicb.2019.01391. PMCID: PMC6598457.
dc.description.noteFirst publication by Frontiers Media


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  • Broschat, Shira
    This collection features research and educational materials by Shira Broschat, Professor and Curriculum Coordinator for the School of Electrical Engineering and Computer Science at Washington State University.

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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International