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Abstract
Background Vibrio parahaemolyticus is a common pathogen infecting humans and marine animals; this pathogen has become a major concern of marine food products and trade. In this study, V. parahaemolyticus isolated from sewage was exposed to different culture conditions and analyzed by isobaric tag for relative and absolute quantitation (iTRAQ) based reversed-phase liquid chromatography-tandem mass spectrometry (LC-MS/MS) technique. Our goal is to gain further insights into the proteomics of V. parahaemolyticus, particularly differentially expressed proteins closely correlated with growth conditions and pathogenicity associated proteins. Results In this study, a total of 2,717 proteins including numerous membrane proteins were significantly identified, and 616 proteins displayed significant differential expression under different conditions. Of them, 12 proteins mainly participating in metabolism showed the most elastic expression differentiation between different culture conditions. Some membrane proteins such as type I secretion outer membrane protein, TolC, lipoprotein, efflux system proteins iron-regulated protein A and putaive Fe-regulated protein B, ferric siderophore receptor homolog and several V. parahaemolyticus virulence-associated proteins were differentially regulated under different conditions. Some differentially regulated proteins were analyzed and confirmed at gene expression level by quantitative real time polymerase chain reaction (qRT-PCR). Conclusions Proteomics analysis results revealed the characteristics of V. parahaemolyticus proteome expression, provided some promising biomarkers related with growth conditions, the results likely advance insights into the mechanism involved in the response of V. parahaemolyticus to different conditions. Some virulence-associated proteins were discovered to be differentially expressed under different conditions. Electronic supplementary material The online version of this article (doi:10.1186/s12953-015-0075-4) contains supplementary material, which is available to authorized users.
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Kumar GSS, Venugopal AK, Mahadevan A, Renuse S, Harsha HC, Sahasrabuddhe NA, Pawar H, Sharma R, Kumar P, Rajagopalan S, Waddell K, Ramachandra YL, Satishchandra P, Chaerkady R, Prasad TSK, Shankar K, Pandey A. Quantitative proteomics for identifying biomarkers for tuberculous meningitis. Clin Proteomics 2012. [PMID: 23198679 DOI: 10.1186/1559-0275-9-12] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
UNLABELLED INTRODUCTION Tuberculous meningitis is a frequent extrapulmonary disease caused by Mycobacterium tuberculosis and is associated with high mortality rates and severe neurological sequelae. In an earlier study employing DNA microarrays, we had identified genes that were differentially expressed at the transcript level in human brain tissue from cases of tuberculous meningitis. In the current study, we used a quantitative proteomics approach to discover protein biomarkers for tuberculous meningitis. METHODS To compare brain tissues from confirmed cased of tuberculous meningitis with uninfected brain tissue, we carried out quantitative protein expression profiling using iTRAQ labeling and LC-MS/MS analysis of SCX fractionated peptides on Agilent's accurate mass QTOF mass spectrometer. RESULTS AND CONCLUSIONS Through this approach, we identified both known and novel differentially regulated molecules. Those described previously included signal-regulatory protein alpha (SIRPA) and protein disulfide isomerase family A, member 6 (PDIA6), which have been shown to be overexpressed at the mRNA level in tuberculous meningitis. The novel overexpressed proteins identified in our study included amphiphysin (AMPH) and neurofascin (NFASC) while ferritin light chain (FTL) was found to be downregulated in TBM. We validated amphiphysin, neurofascin and ferritin light chain using immunohistochemistry which confirmed their differential expression in tuberculous meningitis. Overall, our data provides insights into the host response in tuberculous meningitis at the molecular level in addition to providing candidate diagnostic biomarkers for tuberculous meningitis.
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Prasad TSK, Harsha HC, Keerthikumar S, Sekhar NR, Selvan LDN, Kumar P, Pinto SM, Muthusamy B, Subbannayya Y, Renuse S, Chaerkady R, Mathur PP, Ravikumar R, Pandey A. Proteogenomic Analysis of Candida glabrata using High Resolution Mass Spectrometry. J Proteome Res 2011; 11:247-60. [DOI: 10.1021/pr200827k] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
- T. S. Keshava Prasad
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Centre
of Excellence in Bioinformatics,
Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry -605 014, India
- Manipal University, Madhav Nagar, Manipal, Karnataka 576104; India
- Amrita School of Biotechnology, Amrita University, Kollam -690 525, India
| | - H. C. Harsha
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
| | | | - Nirujogi Raja Sekhar
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Centre
of Excellence in Bioinformatics,
Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry -605 014, India
| | - Lakshmi Dhevi N. Selvan
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Amrita School of Biotechnology, Amrita University, Kollam -690 525, India
| | - Praveen Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Amrita School of Biotechnology, Amrita University, Kollam -690 525, India
| | - Sneha M. Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Manipal University, Madhav Nagar, Manipal, Karnataka 576104; India
| | - Babylakshmi Muthusamy
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Centre
of Excellence in Bioinformatics,
Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry -605 014, India
| | - Yashwanth Subbannayya
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Rajiv Gandhi University of Health Sciences, Jayanagar, Bangalore −560
041, India
| | - Santosh Renuse
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
- Amrita School of Biotechnology, Amrita University, Kollam -690 525, India
| | - Raghothama Chaerkady
- Institute of Bioinformatics, International Technology Park, Bangalore
-560 066, India
| | - Premendu P. Mathur
- Centre
of Excellence in Bioinformatics,
Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry -605 014, India
| | - Raju Ravikumar
- Department of
Neuromicrobiology, National Institute of Mental Health and Neuro Sciences, Bangalore -560029, India
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