ArticleJournal of translational medicine2014
Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.
Article in Journal of translational medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 32 citations in OpenAlex.
- Quantitative metabolic fluxes regulated by trans-omic networks.The Biochemical journal · 2022Review
- Mechanisms of Drug-Induced Tolerance in Mycobacterium tuberculosis.Clinical microbiology reviews · 2020Review
- A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks.PLoS computational biology · 2020Article
- Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens.Frontiers in cell and developmental biology · 2020Review
- Metformin as Host-Directed Therapy for TB Treatment: Scoping Review.Frontiers in microbiology · 2020Article
- Current status and applications of genome-scale metabolic models.Genome biology · 2019Review
- Modeling Host-Pathogen Interaction to Elucidate the Metabolic Drug Response of IntracellularFrontiers in cellular and infection microbiology · 2019Article
- Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions.BMC systems biology · 2018Article
- Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.Journal of translational medicine · 2017Article
- Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection.BMC systems biology · 2017Article
- Data Intensive Genome Level Analysis for Identifying Novel, Non-Toxic Drug Targets for Multi Drug Resistant Mycobacterium tuberculosis.Scientific reports · 2017Article
- Comparative Proteomic Analyses of Avirulent, Virulent, and Clinical Strains of Mycobacterium tuberculosis Identify Strain-specific Patterns.The Journal of biological chemistry · 2016Article
- Metformin as a potential combination therapy with existing front-line antibiotics for Tuberculosis.Journal of translational medicine · 2015Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsThe 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.
resultsThe 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.
conclusionThe 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.
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