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Dataset of the proteome of purified outer membrane vesicles from the human pathogen Aggregatibacter actinomycetemcomintans

The Gram-negative bacterium Aggregatibacter actinomycetemcomitans is an oral and systemic pathogen, which is linked to aggressive forms of periodontitis and can be associated with endocarditis. The outer membrane vesicles (OMVs) of this species contain effector proteins such as cytolethal distending...

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Detalles Bibliográficos
Autores principales: Kieselbach, Thomas, Oscarsson, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5192097/
https://www.ncbi.nlm.nih.gov/pubmed/28050585
http://dx.doi.org/10.1016/j.dib.2016.12.015
Descripción
Sumario:The Gram-negative bacterium Aggregatibacter actinomycetemcomitans is an oral and systemic pathogen, which is linked to aggressive forms of periodontitis and can be associated with endocarditis. The outer membrane vesicles (OMVs) of this species contain effector proteins such as cytolethal distending toxin (CDT) and leukotoxin (LtxA), which they can deliver into human host cells. The OMVs can also activate innate immunity through NOD1- and NOD2-active pathogen-associated molecular patterns. This dataset provides a proteome of highly purified OMVs from A. actinomycetemcomitans serotype e strain 173. The experimental data do not only include the raw data of the LC-MS/MS analysis of four independent preparations of purified OMVs but also the mass lists of the processed data and the Mascot.dat files from the database searches. In total 501 proteins are identified, of which 151 are detected in at least three of four independent preparations. In addition, this dataset contains the COG definitions and the predicted subcellular locations (PSORTb 3.0) for the entire genome of A. actinomycetemcomitans serotype e strain SC1083, which is used for the evaluation of the LC-MS/MS data. These data are deposited in ProteomeXchange in the public dataset PXD002509. In addition, a scientific interpretation of this dataset by Kieselbach et al. (2015) [2] is available at http://dx.doi.org/10.1371/journal.pone.0138591.