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Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis

Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA), Apa, Malate Synthase of M. tuberculosis have been id...

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Autores principales: Kumar, Sanjiv, Puniya, Bhanwar Lal, Parween, Shahila, Nahar, Pradip, Ramachandran, Srinivasan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726780/
https://www.ncbi.nlm.nih.gov/pubmed/23922800
http://dx.doi.org/10.1371/journal.pone.0069790
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author Kumar, Sanjiv
Puniya, Bhanwar Lal
Parween, Shahila
Nahar, Pradip
Ramachandran, Srinivasan
author_facet Kumar, Sanjiv
Puniya, Bhanwar Lal
Parween, Shahila
Nahar, Pradip
Ramachandran, Srinivasan
author_sort Kumar, Sanjiv
collection PubMed
description Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA), Apa, Malate Synthase of M. tuberculosis have been identified using specific experimental interaction models based on the biological knowledge of the pathogen. In the present work, we carried out computational screening for adhesins of M. tuberculosis. We used an integrated computational approach using SPAAN for predicting adhesins, PSORTb, SubLoc and LocTree for extracellular localization, and BLAST for verifying non-similarity to human proteins. These steps are among the first of reverse vaccinology. Multiple claims and attacks from different algorithms were processed through argumentative approach. Additional filtration criteria included selection for proteins with low molecular weights and absence of literature reports. We examined binding potential of the selected proteins using an image based ELISA. The protein Rv2599 (membrane protein) binds to human fibronectin, laminin and collagen. Rv3717 (N-acetylmuramoyl-L-alanine amidase) and Rv0309 (L,D-transpeptidase) bind to fibronectin and laminin. We report Rv2599 (membrane protein), Rv0309 and Rv3717 as novel adhesins of M. tuberculosis H37Rv. Our results expand the number of known adhesins of M. tuberculosis and suggest their regulated expression in different stages.
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spelling pubmed-37267802013-08-06 Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis Kumar, Sanjiv Puniya, Bhanwar Lal Parween, Shahila Nahar, Pradip Ramachandran, Srinivasan PLoS One Research Article Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA), Apa, Malate Synthase of M. tuberculosis have been identified using specific experimental interaction models based on the biological knowledge of the pathogen. In the present work, we carried out computational screening for adhesins of M. tuberculosis. We used an integrated computational approach using SPAAN for predicting adhesins, PSORTb, SubLoc and LocTree for extracellular localization, and BLAST for verifying non-similarity to human proteins. These steps are among the first of reverse vaccinology. Multiple claims and attacks from different algorithms were processed through argumentative approach. Additional filtration criteria included selection for proteins with low molecular weights and absence of literature reports. We examined binding potential of the selected proteins using an image based ELISA. The protein Rv2599 (membrane protein) binds to human fibronectin, laminin and collagen. Rv3717 (N-acetylmuramoyl-L-alanine amidase) and Rv0309 (L,D-transpeptidase) bind to fibronectin and laminin. We report Rv2599 (membrane protein), Rv0309 and Rv3717 as novel adhesins of M. tuberculosis H37Rv. Our results expand the number of known adhesins of M. tuberculosis and suggest their regulated expression in different stages. Public Library of Science 2013-07-29 /pmc/articles/PMC3726780/ /pubmed/23922800 http://dx.doi.org/10.1371/journal.pone.0069790 Text en © 2013 Kumar et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kumar, Sanjiv
Puniya, Bhanwar Lal
Parween, Shahila
Nahar, Pradip
Ramachandran, Srinivasan
Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title_full Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title_fullStr Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title_full_unstemmed Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title_short Identification of Novel Adhesins of M. tuberculosis H37Rv Using Integrated Approach of Multiple Computational Algorithms and Experimental Analysis
title_sort identification of novel adhesins of m. tuberculosis h37rv using integrated approach of multiple computational algorithms and experimental analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726780/
https://www.ncbi.nlm.nih.gov/pubmed/23922800
http://dx.doi.org/10.1371/journal.pone.0069790
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