bioRxivSystems BiologyPreprint
ModelSEED v2: High-throughput genome-scale metabolic model reconstruction with enhanced energy biosynthesis pathway prediction
José P. FariaiD, Filipe LiuiD, Janaka N. EdirisingheiD, Nidhi GuptaiD, Samuel M. D. SeaveriD, Andrew FreiburgeriD, Vibhav SetluriD, Qizhi ZhangiD, Pamela B. WeisenhorniD, Neal R. ConradiD, Raphy ZareckiiD, Hyun‐Seob SongiD, Matthew DeJonghiD, Aaron A. BestiD, Robert W. CottinghamiD, Adam P. ArkiniD, Christopher S. HenryiD
Abstract
Since the release of ModelSEED in 2010, the systems biology research community has used the ModelSEED genome-scale metabolic model reconstruction pipeline to build over 200,000 draft metabolic reconstructions that support hundreds of publications. Here we describe the first comprehensive update to this reconstruction tool, with new features such as (i) a dramatically improved representation of energy metabolism, which ensures that models produce accurate amounts of ATP per mol of nutrient consumed; (ii) a new template for Archaea model reconstruction; and (iii) a significantly improved curation of all metabolic pathways with mappings to RAST subsystems annotations. We applied the improved pipeline to build and analyze core and genome-scale models for Archaea and Bacteria genomes in KEGG. The new ModelSEED pipeline generates larger models that possess more reactions and genes and require fewer gap-filled reactions. In addition, we see conserved patterns in the ATP biosynthesis mechanism across phylogeny, and identify clades where our understanding of energy biosynthesis is still poor. ModelSEED v2 is available through KBase and the ModelSEED website (https://modelseed.org/), which supports reconstruction, gap-filling, flux balance analysis and model export through a modern web interface.
- organism: bacteria (other)
- organism: virus
- assay: whole-genome sequencing
- research focus: database / resource
- approach: statistical model
- Citations
- 24
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