Proteogenomic analysis of pathogenic yeast cryptococcus neoformans using high resolution mass spectrometry

Lakshmi Dhevi Nagarajha Selvan, Jyothi Embekkat Kaviyil, Raja Sekhar Nirujogi, Babylakshmi Muthusamy, Vinuth N. Puttamallesh, Tejaswini Subbannayya, Nazia Syed, Aneesha Radhakrishnan, Dhanashree S. Kelkar, Sartaj Ahmad, Sneha M. Pinto, Praveen Kumar, Anil K. Madugundu, Bipin Nair, Aditi Chatterjee, Akhilesh Pandey, Raju Ravikumar, Harsha Gowda, Thottethodi Subrahmanya Keshava Prasad

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Cryptococcus neoformans, a basidiomycetous fungus of universal occurrence, is a significant opportunistic human pathogen causing meningitis. Owing to an increase in the number of immunosuppressed individuals along with emergence of drug-resistant strains, C. neoformans is gaining importance as a pathogen. Although, whole genome sequencing of three varieties of C. neoformans has been completed recently, no global proteomic studies have yet been reported. Results: We performed a comprehensive proteomic analysis of C. neoformans var. grubii (Serotype A), which is the most virulent variety, in order to provide protein-level evidence for computationally predicted gene models and to refine the existing annotations. We confirmed the protein-coding potential of 3,674 genes from a total of 6,980 predicted protein-coding genes. We also identified 4 novel genes and corrected 104 predicted gene models. In addition, our studies led to the correction of translational start site, splice junctions and reading frame used for translation in a number of proteins. Finally, we validated a subset of our novel findings by RT-PCR and sequencing. Conclusions: Proteogenomic investigation described here facilitated the validation and refinement of computationally derived gene models in the intron-rich genome of C. neoformans, an important fungal pathogen in humans.

Original languageEnglish (US)
Article number5
JournalClinical Proteomics
Volume11
Issue number1
DOIs
StatePublished - 2014

Keywords

  • Antifungal drugs
  • Computational prediction
  • Cryptococcal meningitis
  • Fungal genomics
  • Fungal infection
  • Genome annotation

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Clinical Biochemistry

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