title: Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.forename: Rohit
authors.initials: R
authors.lastname: Vashisht
authors.forename: Ashwini G
authors.initials: AG
authors.lastname: Bhat
authors.forename: Shreeram
authors.initials: S
authors.lastname: Kushwaha
authors.forename: Anshu
authors.initials: A
authors.lastname: Bhardwaj
authors.affiliation: CSIR-Open Source Drug Discovery Unit, New Delhi, India. skb@igib.res.in.
authors.forename: Samir K
authors.initials: SK
authors.lastname: Brahmachari
mesh_terms: D000222:Adaptation, Physiological / Q000187:drug effects / Q000235:genetics; D000995:Antitubercular Agents / Q000494:pharmacology* / Q000627:therapeutic use; D005798:Genes, Bacterial; D051188:Knowledge Bases; D064688:Metabolic Flux Analysis; D053858:Metabolic Networks and Pathways / Q000187:drug effects*; D058990:Molecular Targeted Therapy; D009169:Mycobacterium tuberculosis / Q000187:drug effects* / Q000235:genetics / Q000254:growth & development / Q000378:metabolism*; D010641:Phenotype; D049490:Systems Biology / Q000379:methods*
chemical_list: D000995:Antitubercular Agents