Journal of Proteomics & Bioinformatics
Open Access
ISSN: 0974-276X
+44 1223 790975
ISSN: 0974-276X
+44 1223 790975
Keshava K Datta, Arun H Patil, Krishna Patel, Gourav Dey, Anil K Madugundu, Jyothi E Kaviyil, Bharat B Chattoo, Harsha Gowda, Raju Ravikumar and T S Keshava Prasad
Institute of Bioinformatics, India
KIIT University, India
Manipal University, India
Pondicherry University, India
National Institute of Mental Health and Neurosciences, India
The M. S. University of Baroda, India
Yenepo
Posters & Accepted Abstracts: J Proteomics Bioinform
Candida tropicalis is an opportunistic pathogen which causes candidiasis in immune-compromised individuals. It is one of the members of the non-albicans group of Candida that are known to be azole resistant and is frequently seen in individuals being treated for cancers, HIV-infection and bone-marrow transplant. Although the genome of C. tropicalis was sequenced in the year 2009, the genome annotation has not been supported by experimental validation. In the present study, we have carried out indepth proteomic profiling of C. tropicalis using high-resolution Fourier transform mass spectrometry and mapped ~44% of the computationally predicted protein-coding genes with peptide level evidence. In addition to identifying 2,740 proteins in the cell lysate of this yeast, we also analyzed the proteome of the conditioned media of C. tropicalis culture and identified several unique secreted proteins among a total of 780 proteins. By subjecting the mass spectrometry data derived from cell lysate and conditioned media to proteogenomic analysis, we identified 86 novel genes, 12 novel exons and corrected 49 computationally predicted gene models. To our knowledge, this is the first high-throughput proteomic study to refine the genome annotation of C. tropicalis.
Keshava K Datta is currently a PhD student at the Institute of Bioinformatics, India. He has obtained his MSc degree in Biochemistry from Bangalore University.
Email: ravikumarbly@yahoo.co.uk