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A protocol for generating a high-quality genome-scale metabolic reconstruction

Abstract

Network reconstructions are a common denominator in systems biology. Bottom–up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

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Figure 1: Overview of the procedure to iteratively reconstruct metabolic networks.
Figure 2: Refinement of reconstruction content.
Figure 3
Figure 4: Examples of network evaluation.
Figure 5: Gene–protein-reaction (GPR) associations.
Figure 6: Growth-associated maintentance (GAM) and non-GAM (NGAM).
Figure 7: Conversion of reconstruction into a condition-specific model.
Figure 8: Gap analysis.
Figure 9: In silico gene essentiality study as network evaluation tool.
Figure 10: Components of the model structure in Matlab.
Figure 11: Flow chart to calculate the fractional contribution of a precursor to the biomass reaction.
Figure 12: Determination of the content of soluble pool.
Figure 13: Determination of growth-associated maintenance (GAM) cost.
Figure 14: Flow chart on debugging network reactions that cannot carry flux.

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Acknowledgements

We would like to acknowledge R.M.T. Fleming, A. Feist and N. Jamshidi for their valuable discussions. We thank M. Abrahams, S.A. Becker and F.-C. Cheng for reading the paper. We also thank S. Burning for preparing the biomass reaction manual, as well as A. Bordbar and R.M.T. Fleming for providing Matlab code. I.T. was supported by National Institutes of Health (NIH) grant R01 GM057089.

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Correspondence to Bernhard Ø Palsson.

Supplementary information

Supplementary Method 1 | Supplemental tables, figures, and sample use of Cobra Toolbox functions presented in the protocol.

The supplemental tables and figures illustrate additional information which can be helpful during the reconstruction process. We also included detailed examples on the use of various Cobra Toolbox commands needed during the network evaluation and debugging phase. Furthermore, the file includes a list of standards that have been commonly used in metabolic reconstructions (e.g., naming conventions). (PDF 701 kb)

Supplementary Method 2 | Extract of a curated reconstruction.

This spreadsheet can be used as a starting point for the manual reconstruction. It contains all necessary columns for reaction and metabolite curation. The order of columns of the metabolite and reaction spreadsheets is important for importing the reconstruction into Matlab using the ‘xls2model’ function (Step 39). The example also highlights which information is obligatory. (XLS 34 kb)

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Thiele, I., Palsson, B. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 5, 93–121 (2010). https://doi.org/10.1038/nprot.2009.203

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