A Model Integration Pipeline for the Improvement of Human Genome-Scale Metabolic Reconstructions

Journal Article · 20 December 2018 · Journal of Integrative Bioinformatics

DOI: https://doi.org/10.1515/jib-2018-0068 · OSTI ID:1629389

Vieira, Vítor  ^[1]; Ferreira, Jorge ^[2]; Rodrigues, Rúben ^[2]; Liu, Filipe ^[3]; Rocha, Miguel  ^[2]

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1. Center of Biological Engineering, University of Minho – Campus de Gualtar, Braga, Portugal; University of Minho – Campus de Gualtar, Portugal
2. Center of Biological Engineering, University of Minho – Campus de Gualtar, Braga, Portugal
3. Argonne National Lab. (ANL), Argonne, IL (United States)

Abstract Metabolism has been a major field of study in the last years, mainly due to its importance in understanding cell physiology and certain disease phenotypes due to its deregulation. Genome-scale metabolic models (GSMMs) have been established as important tools to help achieve a better understanding of human metabolism. Towards this aim, advances in systems biology and bioinformatics have allowed the reconstruction of several human GSMMs, although some limitations and challenges remain, such as the lack of external identifiers for both metabolites and reactions. A pipeline was developed to integrate multiple GSMMs, starting by retrieving information from the main human GSMMs and evaluating the presence of external database identifiers and annotations for both metabolites and reactions. Information from metabolites was included into a graph database with omics data repositories, allowing clustering of metabolites through their similarity regarding database cross-referencing. Metabolite annotation of several older GSMMs was enriched, allowing the identification and integration of common entities. Using this information, as well as other metrics, we successfully integrated reactions from these models. These methods can be leveraged towards the creation of a unified consensus model of human metabolism.

• Research Organization: Argonne National Lab (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC02-06CH11357
• OSTI ID: 1629389
• Journal Information: Journal of Integrative Bioinformatics, Journal Name: Journal of Integrative Bioinformatics Journal Issue: 1 Vol. 16; ISSN 1613-4516
• Publisher: Walter de Gruyter GmbHCopyright Statement
• Country of Publication: United States
• Language: English