Comparative proteomic analysis of Candida albicans and Candida glabrata

Thottethodi Subrahmanya Keshava Prasad, Shivakumar Keerthikumar, Raghothama Chaerkady, Kumaran Kandasamy, Santosh Renuse, Arivusudar Marimuthu, Abhilash Karavattu Venugopal, Joji Kurian Thomas, Harrys K.C. Jacob, Renu Goel, Harsh Pawar, Nandini A. Sahasrabuddhe, Venkatarangaiah Krishna, Bipin G. Nair, Marjan Gucek, Robert N. Cole, Raju Ravikumar, H. C. Harsha, Akhilesh Pandey*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)163-173
Number of pages11
JournalClinical Proteomics
Issue number4
StatePublished - Dec 2010


  • Biomarker
  • Candidemia
  • Candidiasis
  • Fungal infection
  • Medical mycology
  • Molecular diagnostics
  • Quantitative proteomics

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Clinical Biochemistry


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