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

Clinical Proteomics

Harsha Gowda¹  Akhilesh Pandey²  Bipin Nair⁷  Sneha M Pinto⁵  Lakshmi Dhevi Nagarajha Selvan⁸  Aditi Chatterjee⁵  Praveen Kumar¹  Jyothi Embekkat Kaviyil⁹  Raja Sekhar Nirujogi³  Thottethodi Subrahmanya Keshava Prasad⁶  Anil K Madugundu¹  Tejaswini Subbannayya⁸  Vinuth N Puttamallesh¹  Dhanashree S Kelkar⁸  Babylakshmi Muthusamy³  Nazia Syed⁴  Raju Ravikumar⁹  Aneesha Radhakrishnan⁴  Sartaj Ahmad⁵ 

[1] Institute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, India;McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaDepartment of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaDepartment of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry, IndiaDepartment of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaDepartment of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry, India;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaManipal University, Manipal, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaManipal University, Manipal, IndiaManipal University, Manipal, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaManipal University, Manipal, India;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaManipal University, Manipal, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaManipal University, Manipal, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaManipal University, Manipal, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaManipal University, Manipal, IndiaManipal University, Manipal, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaCentre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, IndiaManipal University, Manipal, India;Amrita School of Biotechnology, Amrita University, Kollam, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaAmrita School of Biotechnology, Amrita University, Kollam, India;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaAmrita School of Biotechnology, Amrita University, Kollam, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaAmrita School of Biotechnology, Amrita University, Kollam, India;Department of Neuromicrobiology, National Institute of Mental Health and Neuro Sciences, Bangalore, IndiaDepartment of Neuromicrobiology, National Institute of Mental Health and Neuro Sciences, Bangalore, IndiaDepartment of Neuromicrobiology, National Institute of Mental Health and Neuro Sciences, Bangalore, India

关键词: Fungal infection;    Fungal genomics;    Antifungal drugs;    Cryptococcal meningitis;    Computational prediction;    Genome annotation;   

DOI  :  10.1186/1559-0275-11-5

来源: Humana Press Inc

【 摘 要 】

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.

【 授权许可】

Unknown