Publication Type : Journal Article
Publisher : Clinical Proteomics
Source : Clinical Proteomics, Volume 6, Number 4, p.163-173 (2010)
Keywords : article, bioinformatics, Candida albicans, Candida glabrata, cell free system, cell labeling, controlled study, data base, enolase, fructose bisphosphate aldolase, liquid chromatography, nonhuman, orthology, priority journal, protein, protein analysis, protein expression, proteomics, pyruvate carboxylase, pyruvate kinase, quadrupole mass spectrometry, species difference
Campus : Amritapuri
School : School of Biotechnology
Department : biotechnology
Year : 2010
Abstract : Introduction: Candida albicans and Candida glabrata are the two most common opportunistic pathogens which are part of the normal flora in humans. Clinical diagnosis of infection by these organisms is still largely based on culturing of these organisms. In order to identify species-specific protein expression patterns, we carried out a comparative proteomic analysis of C. albicans and C. glabrata. Methods: We used isobaric tag for relative and absolute quantitation (iTRAQ) labeling of cell homogenates of C. albicans and C. glabrata followed by LC-MS/MS analysis using a quadrupole time-of-flight mass spectrometer. The MS/MS data was searched against a protein database comprised of known and predicted proteins reported from these two organisms. Subsequently, we carried out a bioinformatics analysis to group orthologous proteins across C. albicans and C. glabrata and calculated protein abundance changes between the two species. Results and Conclusions: We identified 500 proteins from these organisms, the large majority of which corresponded to predicted transcripts. A number of proteins were observed to be significantly differentially expressed between the two species including enolase (Eno1), fructose-bisphosphate aldolase (Fba1), CCT ring complex subunit (Cct2), pyruvate kinase (Cdc19), and pyruvate carboxylase (Pyc2). This study illustrates a strategy for investigating protein expression patterns across closely related organisms by combining orthology information with quantitative proteomics.
Cite this Research Publication : T. S. K. Prasad, S. Keerthikumar, R. Chaerkady, K. Kandasamy, S. Renuse, A. Marimuthu, A. K. Venugopal, J. K. Thomas, H. K. C. Jacob, R. Goel, H. Pawar, N. A. Sahasrabuddhe, V. Krishna, Dr. Bipin G. Nair, M. Gucek, R. N. Cole, R. Ravikumar, H. C. Harsha, and A. Pandey, “Comparative proteomic analysis of Candida albicans and Candida glabrata”, Clinical Proteomics, vol. 6, pp. 163-173, 2010