Steffensen Jon Lund, Dufault-Thompson Keith, Zhang Ying
Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, Rhode Island, United States of America.
PLoS Comput Biol. 2016 Feb 1;12(2):e1004732. doi: 10.1371/journal.pcbi.1004732. eCollection 2016 Feb.
The genome-scale models of metabolic networks have been broadly applied in phenotype prediction, evolutionary reconstruction, community functional analysis, and metabolic engineering. Despite the development of tools that support individual steps along the modeling procedure, it is still difficult to associate mathematical simulation results with the annotation and biological interpretation of metabolic models. In order to solve this problem, here we developed a Portable System for the Analysis of Metabolic Models (PSAMM), a new open-source software package that supports the integration of heterogeneous metadata in model annotations and provides a user-friendly interface for the analysis of metabolic models. PSAMM is independent of paid software environments like MATLAB, and all its dependencies are freely available for academic users. Compared to existing tools, PSAMM significantly reduced the running time of constraint-based analysis and enabled flexible settings of simulation parameters using simple one-line commands. The integration of heterogeneous, model-specific annotation information in PSAMM is achieved with a novel format of YAML-based model representation, which has several advantages, such as providing a modular organization of model components and simulation settings, enabling model version tracking, and permitting the integration of multiple simulation problems. PSAMM also includes a number of quality checking procedures to examine stoichiometric balance and to identify blocked reactions. Applying PSAMM to 57 models collected from current literature, we demonstrated how the software can be used for managing and simulating metabolic models. We identified a number of common inconsistencies in existing models and constructed an updated model repository to document the resolution of these inconsistencies.
代谢网络的基因组规模模型已广泛应用于表型预测、进化重建、群落功能分析和代谢工程。尽管已经开发出支持建模过程中各个步骤的工具,但将数学模拟结果与代谢模型的注释和生物学解释联系起来仍然很困难。为了解决这个问题,我们开发了一个代谢模型分析便携式系统(PSAMM),这是一个新的开源软件包,支持在模型注释中集成异构元数据,并为代谢模型分析提供用户友好的界面。PSAMM独立于MATLAB等付费软件环境,其所有依赖项对学术用户免费提供。与现有工具相比,PSAMM显著减少了基于约束分析的运行时间,并使用简单的单行命令实现了模拟参数的灵活设置。PSAMM中异构的、特定于模型的注释信息的集成是通过一种基于YAML的新颖模型表示格式实现的,这种格式具有几个优点,例如提供模型组件和模拟设置的模块化组织、实现模型版本跟踪以及允许集成多个模拟问题。PSAMM还包括一些质量检查程序,以检查化学计量平衡并识别受阻反应。将PSAMM应用于从当前文献中收集的57个模型,我们展示了该软件如何用于管理和模拟代谢模型。我们在现有模型中发现了一些常见的不一致之处,并构建了一个更新的模型存储库来记录这些不一致之处的解决方法。