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An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana
- Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis withQuantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.…
Author details: | Sebastian HußORCiD, Rika Siedah Judd, Kaan Koper, Hiroshi A. MaedaORCiD, Zoran NikoloskiORCiDGND |
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DOI: | https://doi.org/10.1111/tpj.15903 |
ISSN: | 0960-7412 |
ISSN: | 1365-313X |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/35819300 |
Title of parent work (English): | The plant journal |
Publisher: | Wiley-Blackwell |
Place of publishing: | Oxford [u.a.] |
Publication type: | Article |
Language: | English |
Date of first publication: | 2022/07/12 |
Publication year: | 2022 |
Release date: | 2024/04/25 |
Tag: | atom mapping; flux analysis; genome-scale metabolic model; isotopic labeling; metabolic; technical advance |
Volume: | 111 |
Issue: | 5 |
Number of pages: | 15 |
First page: | 1486 |
Last Page: | 1500 |
Funding institution: | U.S. Department of Energy, Office of Science, Office of Biological and; Environmental Research, Genomic Science Program [DE-SC0020390]; Projekt; DEAL |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 58 Pflanzen (Botanik) / 580 Pflanzen (Botanik) |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | CC-BY-NC - Namensnennung, nicht kommerziell 4.0 International |