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Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets

BACKGROUND: The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to...

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Autores principales: Vashisht, Rohit, Bhat, Ashwini G, Kushwaha, Shreeram, Bhardwaj, Anshu, Consortium, OSDD, Brahmachari, Samir K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201925/
https://www.ncbi.nlm.nih.gov/pubmed/25304862
http://dx.doi.org/10.1186/s12967-014-0263-5
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author Vashisht, Rohit
Bhat, Ashwini G
Kushwaha, Shreeram
Bhardwaj, Anshu
Consortium, OSDD
Brahmachari, Samir K
author_facet Vashisht, Rohit
Bhat, Ashwini G
Kushwaha, Shreeram
Bhardwaj, Anshu
Consortium, OSDD
Brahmachari, Samir K
author_sort Vashisht, Rohit
collection PubMed
description BACKGROUND: The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery. METHODS: The enhanced functional annotations of the Mtb genome, which were previously obtained through a crowd sourcing approach was used to reconstruct the metabolic network of Mtb in a bottom up manner. We represent this information by developing a novel Systems Biology Spindle Map of Metabolism (SBSM) and comprehend its static and dynamic structure using various computational approaches based on simulation and design. RESULTS: The reconstructed metabolism of Mtb encompasses 961 metabolites, involved in 1152 reactions catalyzed by 890 protein coding genes, organized into 50 pathways. By accounting for static and dynamic analysis of SBSM in Mtb we identified various critical proteins required for the growth and survival of bacteria. Further, we assessed the potential of these proteins as putative drug targets that are fast acting and less toxic. Further, we formulate a novel concept of metabolic persister genes (MPGs) and compared our predictions with published in vitro and in vivo experimental evidence. Through such analyses, we report for the first time that de novo biosynthesis of NAD may give rise to bacterial persistence in Mtb under conditions of metabolic stress induced by conventional anti-tuberculosis therapy. We propose such MPG’s as potential combination of drug targets for existing antibiotics that can improve their efficacy and efficiency for drug tolerant bacteria. CONCLUSION: The systems level framework formulated by us to identify potential non-toxic drug targets and strategies to circumvent the issue of bacterial persistence can substantially aid in the process of TB drug discovery and translational research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-014-0263-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-42019252014-10-23 Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets Vashisht, Rohit Bhat, Ashwini G Kushwaha, Shreeram Bhardwaj, Anshu Consortium, OSDD Brahmachari, Samir K J Transl Med Research BACKGROUND: The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery. METHODS: The enhanced functional annotations of the Mtb genome, which were previously obtained through a crowd sourcing approach was used to reconstruct the metabolic network of Mtb in a bottom up manner. We represent this information by developing a novel Systems Biology Spindle Map of Metabolism (SBSM) and comprehend its static and dynamic structure using various computational approaches based on simulation and design. RESULTS: The reconstructed metabolism of Mtb encompasses 961 metabolites, involved in 1152 reactions catalyzed by 890 protein coding genes, organized into 50 pathways. By accounting for static and dynamic analysis of SBSM in Mtb we identified various critical proteins required for the growth and survival of bacteria. Further, we assessed the potential of these proteins as putative drug targets that are fast acting and less toxic. Further, we formulate a novel concept of metabolic persister genes (MPGs) and compared our predictions with published in vitro and in vivo experimental evidence. Through such analyses, we report for the first time that de novo biosynthesis of NAD may give rise to bacterial persistence in Mtb under conditions of metabolic stress induced by conventional anti-tuberculosis therapy. We propose such MPG’s as potential combination of drug targets for existing antibiotics that can improve their efficacy and efficiency for drug tolerant bacteria. CONCLUSION: The systems level framework formulated by us to identify potential non-toxic drug targets and strategies to circumvent the issue of bacterial persistence can substantially aid in the process of TB drug discovery and translational research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-014-0263-5) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-11 /pmc/articles/PMC4201925/ /pubmed/25304862 http://dx.doi.org/10.1186/s12967-014-0263-5 Text en © Vashisht et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Vashisht, Rohit
Bhat, Ashwini G
Kushwaha, Shreeram
Bhardwaj, Anshu
Consortium, OSDD
Brahmachari, Samir K
Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title_full Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title_fullStr Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title_full_unstemmed Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title_short Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets
title_sort systems level mapping of metabolic complexity in mycobacterium tuberculosis to identify high-value drug targets
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201925/
https://www.ncbi.nlm.nih.gov/pubmed/25304862
http://dx.doi.org/10.1186/s12967-014-0263-5
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