Literature DB >> 22486982

Proteomic analysis of sputum in patients with active pulmonary tuberculosis.

Y R Fu1, Z J Yi, S Z Guan, S Y Zhang, M Li.   

Abstract

The protein composition of sputum most faithfully reflects the state of the lungs. The aim of this study was to determine whether relative qualitative and quantitative differences in protein expression of sputum could be related to active pulmonary tuberculosis. Sputum samples were collected from 65 patients with active pulmonary tuberculosis and 38 healthy controls. Comprehensive proteomic approaches were used to profile the proteome changes of host sputum in response to Mycobacterium tuberculosis infection using two-dimensional electrophoresis in combination with matrix-assisted laser desorption ionization time-of-flight/time-of-flight mass spectrometry. Mascot software was used to identify proteins from protein databases. Enzyme-linked immunosorbent assay was used to confirm the proteomic results. A total of 62 differentially expressed proteins were identified, among which, 15 proteins were up-regulated and 47 proteins were down-regulated in the tuberculosis sputum compared with the controls. Bacterial protein UqhC was the most increased protein, whereas serum albumin was the most decreased protein in the tuberculosis sputum compared with the controls. The enzyme-linked immunosorbent assay analysis was consistent with proteomic data. Bioinformatics analysis suggested that multiple host cell pathways were involved in the tuberculosis infection processes, including acute phase response, signal transduction, cytoskeleton structure, immune response and so on. In all, for the first time, our results revealed that a number of proteins were differentially expressed during active pulmonary tuberculosis infection. These data will provide valuable clues for further investigation of tuberculosis pathogenesis and biomarkers for detection of active pulmonary tuberculosis infection.
© 2012 The Authors. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.

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Year:  2012        PMID: 22486982     DOI: 10.1111/j.1469-0691.2012.03824.x

Source DB:  PubMed          Journal:  Clin Microbiol Infect        ISSN: 1198-743X            Impact factor:   8.067


  8 in total

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Journal:  J Microbiol       Date:  2016-10-29       Impact factor: 3.422

Review 2.  Antibodies and tuberculosis.

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Journal:  Tuberculosis (Edinb)       Date:  2016-08-26       Impact factor: 3.131

Review 3.  Proteomics in Biomarker Discovery for Tuberculosis: Current Status and Future Perspectives.

Authors:  Jiubiao Guo; Ximeng Zhang; Xinchun Chen; Yi Cai
Journal:  Front Microbiol       Date:  2022-04-26       Impact factor: 5.640

4.  Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis.

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Journal:  BMC Infect Dis       Date:  2022-08-25       Impact factor: 3.667

Review 5.  Applications of MALDI-MS/MS-Based Proteomics in Biomedical Research.

Authors:  Laura Darie-Ion; Danielle Whitham; Madhuri Jayathirtha; Yashveen Rai; Anca-Narcisa Neagu; Costel C Darie; Brînduşa Alina Petre
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6.  Differential Levels of Alpha-2-Macroglobulin, Haptoglobin and Sero-Transferrin as Adjunct Markers for TB Diagnosis and Disease Progression in the Malnourished Tribal Population of Melghat, India.

Authors:  Prachi R Bapat; Ashish R Satav; Aliabbas A Husain; Seema D Shekhawat; Anuja P Kawle; Justin J Chu; Hemant J Purohit; Hatim F Daginawala; Girdhar M Taori; Rajpal S Kashyap
Journal:  PLoS One       Date:  2015-08-04       Impact factor: 3.240

7.  Transcriptomic signatures in cartilage ageing.

Authors:  Mandy Peffers; Xuan Liu; Peter Clegg
Journal:  Arthritis Res Ther       Date:  2013-08-23       Impact factor: 5.156

8.  Sputum Proteomics Reveals a Shift in Vitamin D-binding Protein and Antimicrobial Protein Axis in Tuberculosis Patients.

Authors:  Subasa C Bishwal; Mrinal K Das; Vinod K Badireddy; Deepti Dabral; Aleena Das; Alok R Mahapatra; Sukanya Sahu; Dipankar Malakar; I Ibungo Singh; Himanghsu Mazumdar; Saurav J Patgiri; Trinayan Deka; Wetetsho Kapfo; Kevideme Liegise; Rukuwe-U Kupa; Sanjita Debnath; Rajesh Bhowmik; Rahul Debnath; Rajendra K Behera; Manoj G Pillai; Pranjal Deuri; Reema Nath; K Pewezo Khalo; W Asoka Sing; Bhaswati Pandit; Anjan Das; Sibabrata Bhattacharya; Digambar Behera; Lahari Saikia; Vinotsole Khamo; Ranjan K Nanda
Journal:  Sci Rep       Date:  2019-01-31       Impact factor: 4.379

  8 in total

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