2015
DOI: 10.1128/iai.02855-14
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Identification of ElpA, a Coxiella burnetii Pathotype-Specific Dot/Icm Type IV Secretion System Substrate

Abstract: Coxiella burnetii causes human Q fever, a zoonotic disease that presents with acute flu-like symptoms and can result in chronic life-threatening endocarditis. In human alveolar macrophages, C. burnetii uses a Dot/Icm type IV secretion system (T4SS) to generate a phagolysosome-like parasitophorous vacuole (PV) in which to replicate. The T4SS translocates effector proteins, or substrates, into the host cytosol, where they mediate critical cellular events, including interaction with autophagosomes, PV formation, … Show more

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Cited by 21 publications
(25 citation statements)
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“…Effectors have consequently evolved to contain ELFs in the form of domains or motifs that functionally mimic eukaryotic host cell proteins [113]. The higher frequency of ELFs in bacterial effectors versus noneffectors provides a powerful predictive tool for assembling candidate effector lists [73,88,[90][91][92][94][95][96]107,113]. Indeed, recognition of a cohort of Coxiella genes encoding 33 amino acid ankyrin repeat domains (ARDs) resulted in identification of the first class of Coxiella Dot/Icm effectors [90,92].…”
Section: Mining For Effectorsmentioning
confidence: 99%
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“…Effectors have consequently evolved to contain ELFs in the form of domains or motifs that functionally mimic eukaryotic host cell proteins [113]. The higher frequency of ELFs in bacterial effectors versus noneffectors provides a powerful predictive tool for assembling candidate effector lists [73,88,[90][91][92][94][95][96]107,113]. Indeed, recognition of a cohort of Coxiella genes encoding 33 amino acid ankyrin repeat domains (ARDs) resulted in identification of the first class of Coxiella Dot/Icm effectors [90,92].…”
Section: Mining For Effectorsmentioning
confidence: 99%
“…Eukaryotic-like features (ELF), a C-terminal Dot/Icm translocation signal and similarity to known Coxiella effectors are strong predictors of effector proteins. Indicators of effector genes are upstream PmrA regulatory motifs and genomic location [73,[87][88][89][90][91][92][94][95][96]107]. When assembling candidate effector gene lists, the predictive power of these features is amplified when multiple criteria are combined in machine learning [95] and manual approaches [88,94].…”
Section: Mining For Effectorsmentioning
confidence: 99%
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