TY - JOUR
T1 - Comparative proteomic analysis of Candida albicans and Candida glabrata
AU - Prasad, Thottethodi Subrahmanya Keshava
AU - Keerthikumar, Shivakumar
AU - Chaerkady, Raghothama
AU - Kandasamy, Kumaran
AU - Renuse, Santosh
AU - Marimuthu, Arivusudar
AU - Venugopal, Abhilash Karavattu
AU - Thomas, Joji Kurian
AU - Jacob, Harrys K.C.
AU - Goel, Renu
AU - Pawar, Harsh
AU - Sahasrabuddhe, Nandini A.
AU - Krishna, Venkatarangaiah
AU - Nair, Bipin G.
AU - Gucek, Marjan
AU - Cole, Robert N.
AU - Ravikumar, Raju
AU - Harsha, H. C.
AU - Pandey, Akhilesh
N1 - Funding Information:
Acknowledgements We thank the Department of Biotechnology of the Government of India for research support to the Institute of Bioinformatics, Bangalore. TSKP is supported by research grants including a Young Investigator award from the Department of Biotechnology, India. We thank the Council for Scientific and Industrial Research (CSIR), India for the research support to HKCJ, HP, and NP and the University Grants Commission (UGC), India for the research support to SR.
PY - 2010/12
Y1 - 2010/12
N2 - 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.
AB - 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.
KW - Biomarker
KW - Candidemia
KW - Candidiasis
KW - Fungal infection
KW - Medical mycology
KW - Molecular diagnostics
KW - Quantitative proteomics
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U2 - 10.1007/s12014-010-9057-9
DO - 10.1007/s12014-010-9057-9
M3 - Article
AN - SCOPUS:78649700130
SN - 1542-6416
VL - 6
SP - 163
EP - 173
JO - Clinical Proteomics
JF - Clinical Proteomics
IS - 4
ER -