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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Unravelling the Neospora caninum secretome through the secreted fraction (ESA) and quantification of the discharged tachyzoite using high-resolution mass spectrometry-based proteomics

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Pollo-Oliveira, Leticia [1, 2] ; Post, Harm [3, 4, 5] ; Acencio, Marcio Luis [6] ; Lemke, Ney [6] ; van den Toorn, Henk [3, 4, 5] ; Tragante, Vinicius [7, 8] ; Heck, Albert J. R. [3, 4, 5] ; Altelaar, A. F. Maarten [3, 4, 5] ; Yatsuda, Ana Patricia [1, 2]
Total Authors: 9
[1] Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP - Brazil
[2] Univ Sao Paulo, Nucleo Apoio Pesquisa Prod Nat Sintet NPPNS, BR-14040903 Ribeirao Preto, SP - Brazil
[3] Univ Utrecht, Utrecht Inst Pharmaceut Sci, NL-3884 CH Utrecht - Netherlands
[4] Univ Utrecht, Bijvoet Ctr Biomol Res, NL-3884 CH Utrecht - Netherlands
[5] Netherlands Prote Ctr, NL-3884 CH Utrecht - Netherlands
[6] Univ Estadual Paulista, UNESP, Botucatu Inst Biosci, BR-18918970 Botucatu, SP - Brazil
[7] Univ Med Ctr Utrecht, Dept Cardiol, Div Heart & Lungs, Utrecht - Netherlands
[8] Univ Med Ctr Utrecht, Dept Med Genet, Div Biomed Genet, Utrecht - Netherlands
Total Affiliations: 8
Document type: Journal article
Source: PARASITES & VECTORS; v. 6, NOV 23 2013.
Web of Science Citations: 9

Background: The apicomplexan parasite Neospora caninum causes neosporosis, a disease that leads to abortion or stillbirth in cattle, generating an economic impact on the dairy and beef cattle trade. As an obligatory intracellular parasite, N. caninum needs to invade the host cell in an active manner to survive. The increase in parasite cytosolic Ca2+ upon contact with the host cell mediates critical events, including the exocytosis of phylum-specific secretory organelles and the activation of the parasite invasion motor. Because invasion is considered a requirement for pathogen survival and replication within the host, the identification of secreted proteins (secretome) involved in invasion may be useful to reveal interesting targets for therapeutic intervention. Methods: To chart the currently missing N. caninum secretome, we employed mass spectrometry-based proteomics to identify proteins present in the N. caninum tachyzoite using two different approaches. The first approach was identifying the proteins present in the tachyzoite-secreted fraction (ESA). The second approach was determining the relative quantification through peptide stable isotope labelling of the tachyzoites submitted to an ethanol secretion stimulus (discharged tachyzoite), expecting to identify the secreted proteins among the down-regulated group. Results: As a result, 615 proteins were identified at ESA and 2,011 proteins quantified at the discharged tachyzoite. We have analysed the connection between the secreted and the down-regulated proteins and searched for putative regulators of the secretion process among the up-regulated proteins. An interaction network was built by computational prediction involving the up-and down-regulated proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000424. Conclusions: The comparison between the protein abundances in ESA and their measure in the discharged tachyzoite allowed for a more precise identification of the most likely secreted proteins. Information from the network interaction and up-regulated proteins was important to recognise key proteins potentially involved in the metabolic regulation of secretion. Our results may be helpful to guide the selection of targets to be investigated against Neospora caninum and other Apicomplexan organisms. (AU)

FAPESP's process: 10/20684-3 - Development of machine learning approaches based on biological networks for prediction and determination of rules governing the emergence of phenotypes of interest
Grantee:Marcio Luis Acencio
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 13/02018-4 - Machine learning for molecular systems biology (MLMSB) application on synthetic lethality, conditionally essential genes and cooperative transcription
Grantee:Ney Lemke
Support type: Regular Research Grants