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Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates

Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relati...

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Autores principales: de Souza, Gustavo A., Fortuin, Suereta, Aguilar, Diana, Pando, Rogelio Hernandez, McEvoy, Christopher R. E., van Helden, Paul D., Koehler, Christian J., Thiede, Bernd, Warren, Robin M., Wiker, Harald G.
Formato: Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2984234/
https://www.ncbi.nlm.nih.gov/pubmed/20190197
http://dx.doi.org/10.1074/mcp.M900422-MCP200
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author de Souza, Gustavo A.
Fortuin, Suereta
Aguilar, Diana
Pando, Rogelio Hernandez
McEvoy, Christopher R. E.
van Helden, Paul D.
Koehler, Christian J.
Thiede, Bernd
Warren, Robin M.
Wiker, Harald G.
author_facet de Souza, Gustavo A.
Fortuin, Suereta
Aguilar, Diana
Pando, Rogelio Hernandez
McEvoy, Christopher R. E.
van Helden, Paul D.
Koehler, Christian J.
Thiede, Bernd
Warren, Robin M.
Wiker, Harald G.
author_sort de Souza, Gustavo A.
collection PubMed
description Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relationship between strains displaying differing virulence in an epidemiological setting and their behavior in animal models has received little attention. The potential causes for variation in virulence between strains, as determined by differential protein expression, have similarly been a neglected area of investigation. In this study, we used a label-free quantitative proteomics approach to estimate differences in protein abundance between two closely related Beijing genotypes that have been shown to be hyper- and hypovirulent on the basis of both epidemiological and mouse model studies. We were able to identify a total of 1668 proteins from both samples, and protein abundance calculations revealed that 48 proteins were over-represented in the hypovirulent isolate, whereas 53 were over-represented in the hypervirulent. Functional classification of these results shows that molecules of cell wall organization and DNA transcription regulatory proteins may have a critical influence in defining the level of virulence. The reduction in the presence of ESAT-6, other Esx-like proteins, and FbpD (MPT51) in the hypervirulent strain indicates that changes in the repertoire of highly immunogenic proteins can be a defensive process undertaken by the virulent cell. In addition, most of the previously well characterized gene targets related to virulence were found to be similarly expressed in our model. Our data support the use of proteomics as a complementary tool for genomic comparisons to understand the biology of M. tuberculosis virulence.
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spelling pubmed-29842342010-12-02 Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates de Souza, Gustavo A. Fortuin, Suereta Aguilar, Diana Pando, Rogelio Hernandez McEvoy, Christopher R. E. van Helden, Paul D. Koehler, Christian J. Thiede, Bernd Warren, Robin M. Wiker, Harald G. Mol Cell Proteomics Research Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relationship between strains displaying differing virulence in an epidemiological setting and their behavior in animal models has received little attention. The potential causes for variation in virulence between strains, as determined by differential protein expression, have similarly been a neglected area of investigation. In this study, we used a label-free quantitative proteomics approach to estimate differences in protein abundance between two closely related Beijing genotypes that have been shown to be hyper- and hypovirulent on the basis of both epidemiological and mouse model studies. We were able to identify a total of 1668 proteins from both samples, and protein abundance calculations revealed that 48 proteins were over-represented in the hypovirulent isolate, whereas 53 were over-represented in the hypervirulent. Functional classification of these results shows that molecules of cell wall organization and DNA transcription regulatory proteins may have a critical influence in defining the level of virulence. The reduction in the presence of ESAT-6, other Esx-like proteins, and FbpD (MPT51) in the hypervirulent strain indicates that changes in the repertoire of highly immunogenic proteins can be a defensive process undertaken by the virulent cell. In addition, most of the previously well characterized gene targets related to virulence were found to be similarly expressed in our model. Our data support the use of proteomics as a complementary tool for genomic comparisons to understand the biology of M. tuberculosis virulence. The American Society for Biochemistry and Molecular Biology 2010-11 2010-02-26 /pmc/articles/PMC2984234/ /pubmed/20190197 http://dx.doi.org/10.1074/mcp.M900422-MCP200 Text en © 2010 by The American Society for Biochemistry and Molecular Biology, Inc. Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) applies to Author Choice Articles
spellingShingle Research
de Souza, Gustavo A.
Fortuin, Suereta
Aguilar, Diana
Pando, Rogelio Hernandez
McEvoy, Christopher R. E.
van Helden, Paul D.
Koehler, Christian J.
Thiede, Bernd
Warren, Robin M.
Wiker, Harald G.
Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title_full Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title_fullStr Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title_full_unstemmed Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title_short Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates
title_sort using a label-free proteomics method to identify differentially abundant proteins in closely related hypo- and hypervirulent clinical mycobacterium tuberculosis beijing isolates
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2984234/
https://www.ncbi.nlm.nih.gov/pubmed/20190197
http://dx.doi.org/10.1074/mcp.M900422-MCP200
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