Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense
Name
Eyford-2013-Identification of Tr.pdf
Size
209.39 KB
Format
Adobe PDF
Checksum (MD5)
2b4cada7e01ce058f357c5394823cdfc
Author(s)
Eyford, Brett A.
Ahmad, Rushdy
Enyaru, John C.
Pearson, Terry W.
Carr, Steven A
Date Issued
August 2013
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Eyford, Brett A., Rushdy Ahmad, John C. Enyaru, Steven A. Carr, and Terry W. Pearson. “Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense.” Edited by Joy Sturtevant. PLoS ONE 8, no. 8 (August 8, 2013): e71463.
Version
Final published version
Abstract
Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a ‘deep-mining” proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification.
MIT Department
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/journal.pone.0071463
