A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.
A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.
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DOI：
10.1186/1752-0509-8-79
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发表时间：
2014-06-30
影响因子：
--
通讯作者：
Karp PD
中科院分区：
文献类型：
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作者：
Weaver DS;Keseler IM;Mackie A;Paulsen IT;Karp PD
大肠杆菌代谢通量的约束模型在基因组尺度的细胞代谢计算研究中发挥了关键作用。我们试图开发下一代基于约束的E。大肠杆菌模型，实现了提高表型预测精度，同时经常更新，易于使用。我们还试图将模型预测与实验数据进行比较，以突出E. coli biology.我们提出了EcoCyc-18.0-GEM，一个基因组规模的E. coli K-12 MG 1655代谢网络。该模型是使用MetaFlux软件从EcoCyc的当前状态自动生成的，每年可以发布多个模型更新。EcoCyc-18.0-GEM包含1445个基因，2286个独特的代谢反应和1453个独特的代谢产物。我们展示了一个三部分的验证模型，在广度和准确性方面开辟了新的天地：（i）在有氧和厌氧葡萄糖培养模拟生长与恒化器培养的实验结果和E. coli建模文献。(ii)对模型中的1445个基因进行了预测，其中EcoCyc-18.0-GEM在预测实验性基因敲除的生长表型方面实现了95.2%的准确性提高。(iii)在431种不同的介质条件下，该模型实现了80.7%的总体准确度的养分利用预测。该模型源自EcoCyc，可通过EcoCyc网站进行查询和可视化，便于模型重用和检查验证。我们提出了一个广泛的调查之间的分歧EcoCyc-18.0-GEM预测和实验数据，以突出感兴趣的领域，E。大肠杆菌建模者和实验者，包括70个不正确的预测的基因重要性的葡萄糖，80个不正确的预测的基因重要性的甘油，和83个不正确的预测的营养利用。模式生物数据库和以MetaFlux为代表的通量平衡建模相结合，可以获得显著的优势。将EcoCyc数据库解释为通量平衡模型导致高度准确的代谢模型，并为存储在数据库中的信息提供严格的一致性检查。
Constraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology. We present EcoCyc–18.0–GEM, a genome-scale model of the E. coli K–12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc–18.0–GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc–18.0–GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model’s derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc–18.0–GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization. Significant advantages can be derived from the combination of model organism databases and flux balance modeling represented by MetaFlux. Interpretation of the EcoCyc database as a flux balance model results in a highly accurate metabolic model and provides a rigorous consistency check for information stored in the database.
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影响因子：
4.3
作者：
Borisov, Vitaliy B.;Gennis, Robert B.;Hemp, James;Verkhovsky, Michael I.
通讯作者：
Verkhovsky, Michael I.
影响因子：
4.8
作者：
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通讯作者：
Anjum, Muna F.
影响因子：
3.2
作者：
CHANG, YY;CRONAN, JE
通讯作者：
CRONAN, JE
影响因子：
4.3
作者：
Brochado, Ana Rita;Andrejev, Sergej;Patil, Kiran R.
通讯作者：
Patil, Kiran R.
大肠杆菌K-12的构造框架，单基因敲除突变体：Keio Collection。
影响因子：
9.9
作者：
通讯作者：
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