<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><volume>9</volume><submitter>Nicolas Le Novère</submitter><journal>Microbial cell factories</journal><pagination>94</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/MODEL1507180031</full_dataset_link><repository>biostudies-other</repository><additional_accession>21092328</additional_accession><pubmed_authors>Nicolas Le Novère</pubmed_authors></additional><is_claimable>false</is_claimable><name>Lee2010 - Genome-scale metabolic network of Zymomonas mobilis (iZmobMBEL601)</name><description>&lt;notes xmlns="http://www.sbml.org/sbml/level3/version1/core">      &lt;body xmlns="http://www.w3.org/1999/xhtml">        &lt;div class="dc:title">Lee2010 - Genome-scale metabolic network ofZymomonas mobilis (iZmobMBEL601)&lt;/div>&lt;div class="dc:bibliographicCitation">  &lt;p>This model is described in the article:&lt;/p>  &lt;div class="bibo:title">    &lt;a href="http://identifiers.org/pubmed/21092328" title="Access to this publication">The genome-scale metabolic    network analysis of Zymomonas mobilis ZM4 explains    physiological features and suggests ethanol and succinic acid    production strategies.&lt;/a>  &lt;/div>  &lt;div class="bibo:authorList">Lee KY, Park JM, Kim TY, Yun H, Lee  SY.&lt;/div>  &lt;div class="bibo:Journal">Microb. Cell Fact. 2010; 9: 94&lt;/div>  &lt;p>Abstract:&lt;/p>  &lt;div class="bibo:abstract">    &lt;p>BACKGROUND: Zymomonas mobilis ZM4 is a Gram-negative    bacterium that can efficiently produce ethanol from various    carbon substrates, including glucose, fructose, and sucrose,    via the Entner-Doudoroff pathway. However, systems metabolic    engineering is required to further enhance its metabolic    performance for industrial application. As an important step    towards this goal, the genome-scale metabolic model of Z.    mobilis is required to systematically analyze in silico the    metabolic characteristics of this bacterium under a wide range    of genotypic and environmental conditions. RESULTS: The    genome-scale metabolic model of Z. mobilis ZM4, ZmoMBEL601, was    reconstructed based on its annotated genes, literature,    physiological and biochemical databases. The metabolic model    comprises 579 metabolites and 601 metabolic reactions (571    biochemical conversion and 30 transport reactions), built upon    extensive search of existing knowledge. Physiological features    of Z. mobilis were then examined using constraints-based flux    analysis in detail as follows. First, the physiological changes    of Z. mobilis as it shifts from anaerobic to aerobic    environments (i.e. aerobic shift) were investigated. Then the    intensities of flux-sum, which is the cluster of either all    ingoing or outgoing fluxes through a metabolite, and the    maximum in silico yields of ethanol for Z. mobilis and    Escherichia coli were compared and analyzed. Furthermore, the    substrate utilization range of Z. mobilis was expanded to    include pentose sugar metabolism by introducing metabolic    pathways to allow Z. mobilis to utilize pentose sugars.    Finally, double gene knock-out simulations were performed to    design a strategy for efficiently producing succinic acid as    another example of application of the genome-scale metabolic    model of Z. mobilis. CONCLUSION: The genome-scale metabolic    model reconstructed in this study was able to successfully    represent the metabolic characteristics of Z. mobilis under    various conditions as validated by experiments and literature    information. This reconstructed metabolic model will allow    better understanding of Z. mobilis metabolism and consequently    designing metabolic engineering strategies for various    biotechnological applications.&lt;/p>  &lt;/div>&lt;/div>&lt;div class="dc:publisher">  &lt;p>This model is hosted on   &lt;a href="http://www.ebi.ac.uk/biomodels/">BioModels Database&lt;/a>  and identified by:   &lt;a href="http://identifiers.org/biomodels.db/MODEL1507180031">MODEL1507180031&lt;/a>.&lt;/p>  &lt;p>To cite BioModels Database, please use:   &lt;a href="http://identifiers.org/pubmed/20587024" title="Latest BioModels Database publication">BioModels Database:  An enhanced, curated and annotated resource for published  quantitative kinetic models&lt;/a>.&lt;/p>&lt;/div>&lt;div class="dc:license">  &lt;p>To the extent possible under law, all copyright and related or  neighbouring rights to this encoded model have been dedicated to  the public domain worldwide. Please refer to   &lt;a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0  Public Domain Dedication&lt;/a> for more information.&lt;/p>&lt;/div>&lt;/body>    &lt;/notes></description><dates><release>2015-07-18T00:00:00Z</release><modification>2025-07-15T09:10:24.664Z</modification><creation>2025-03-30T21:59:09.113Z</creation></dates><accession>MODEL1507180031</accession><cross_references><pubmed>21092328</pubmed><mamo>MAMO_0000009</mamo><unknown>null</unknown></cross_references></HashMap>