Ebert Birgitta E, Lamprecht Anna-Lena, Steffen Bernhard, Blank Lars M
Institute of Applied Microbiology (iAMB), RWTH Aachen University, Worringer Weg 1 52074 Aachen, Germany.
Service and Software Engineering, University of Potsdam, August-Bebel-Straße 89, 14482 Potsdam, Germany.
Metabolites. 2012 Nov 12;2(4):872-90. doi: 10.3390/metabo2040872.
Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via 13C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in this complex analysis, but requires several steps that have to be carried out manually, hence restricting the use of this software for data interpretation to a rather small number of experiments. In this paper, we present Flux-P as an approach to automate and standardize 13C-based metabolic flux analysis, using the Bio-jETI workflow framework. Exemplarily based on the FiatFlux software, it demonstrates how services can be created that carry out the different analysis steps autonomously and how these can subsequently be assembled into software workflows that perform automated, high-throughput intracellular flux analysis of high quality and reproducibility. Besides significant acceleration and standardization of the data analysis, the agile workflow-based realization supports flexible changes of the analysis workflows on the user level, making it easy to perform custom analyses.
代谢网络中细胞内通量的定量知识对于推断代谢系统行为和生物系统的设计原则非常重要。然而,细胞内反应速率通常无法直接计算,而必须进行估计;例如,通过基于13C的代谢通量分析,即对代谢中间体中稳定碳同位素模式进行基于模型的解释。现有的软件,如FiatFlux、OpenFLUX或13CFLUX,在这种复杂的分析中为专家提供支持,但需要手动执行几个步骤,因此将该软件用于数据解释的实验数量相当有限。在本文中,我们提出了Flux-P,这是一种使用Bio-jETI工作流框架实现基于13C的代谢通量分析自动化和标准化的方法。以FiatFlux软件为例,它展示了如何创建能够自主执行不同分析步骤的服务,以及如何随后将这些服务组装成软件工作流,以执行高质量和可重复性的自动化高通量细胞内通量分析。除了显著加速和标准化数据分析外,基于敏捷工作流的实现还支持在用户层面灵活更改分析工作流,并便于执行定制分析。