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Existing models and analyses of\n                      <jats:italic>M. tuberculosis<\/jats:italic>\n                      metabolic networks are able to reproduce experimentally measured cellular growth rates and identify genes required for growth in a range of different\n                      <jats:italic>in vitro<\/jats:italic>\n                      media. However, these models, under\n                      <jats:italic>in vitro<\/jats:italic>\n                      conditions, do not provide an adequate description of the metabolic processes required by the pathogen to infect and persist in a host.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      To better account for the metabolic activity of\n                      <jats:italic>M. tuberculosis<\/jats:italic>\n                      in the host environment, we developed a set of procedures to systematically modify an existing\n                      <jats:italic>in vitro<\/jats:italic>\n                      metabolic network by enhancing the agreement between calculated and\n                      <jats:italic>in vivo-<\/jats:italic>\n                      measured gene essentiality data. After our modifications, the new\n                      <jats:italic>in vivo<\/jats:italic>\n                      network contained 663 genes, 838 metabolites, and 1,049 reactions and had a significantly increased sensitivity (0.81) in predicted gene essentiality than the\n                      <jats:italic>in vitro<\/jats:italic>\n                      network (0.31). We verified the modifications generated from the purely computational analysis through a review of the literature and found, for example, that, as the analysis suggested, lipids are used as the main source for carbon metabolism and oxygen must be available for the pathogen under\n                      <jats:italic>in vivo<\/jats:italic>\n                      conditions. Moreover, we used the developed\n                      <jats:italic>in vivo<\/jats:italic>\n                      network to predict the effects of double-gene deletions on\n                      <jats:italic>M. tuberculosis<\/jats:italic>\n                      growth in the host environment, explore metabolic adaptations to life in an acidic environment, highlight the importance of different enzymes in the tricarboxylic acid-cycle under different limiting nutrient conditions, investigate the effects of inhibiting multiple reactions, and look at the importance of both aerobic and anaerobic cellular respiration during infection.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      The network modifications we implemented suggest a distinctive set of metabolic conditions and requirements faced by\n                      <jats:italic>M. tuberculosis<\/jats:italic>\n                      during host infection compared with\n                      <jats:italic>in vitro<\/jats:italic>\n                      growth. Likewise, the double-gene deletion calculations highlight the importance of specific metabolic pathways used by the pathogen in the host environment. The newly constructed network provides a quantitative model to study the metabolism and associated drug targets of\n                      <jats:italic>M. tuberculosis<\/jats:italic>\n                      under\n                      <jats:italic>in vivo<\/jats:italic>\n                      conditions.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/1752-0509-4-160","type":"journal-article","created":{"date-parts":[[2010,11,23]],"date-time":"2010-11-23T14:16:03Z","timestamp":1290521763000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Development and analysis of an in vivo-compatible metabolic network of Mycobacterium tuberculosis"],"prefix":"10.1186","volume":"4","author":[{"given":"Xin","family":"Fang","sequence":"first","affiliation":[]},{"given":"Anders","family":"Wallqvist","sequence":"additional","affiliation":[]},{"given":"Jaques","family":"Reifman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,11,23]]},"reference":[{"key":"571_CR1","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1042\/BST0351317","volume":"35","author":"SH Gillespie","year":"2007","unstructured":"Gillespie SH: Tuberculosis: evolution in millennia and minutes. 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