The data set contains genome-scale metabolic network reconstructions for 5414 microbial genomes from the Human Reference Gut Microbiome (HRGM) collection (doi: 10.1186/s13073-021-00950-7). Reconstructions were made using gapseq (development version 1.1, commit: 564668f). When using the models, please cite: Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). DOI: 10.1186/s13073-021-00950-7 Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). DOI: 10.1186/s13059-021-02295-1 The models were reconstructed using the following workflow. # Reaction & Pathway prediction ./gapseq find -b 200 -v 1 -p all -k -t <Bacteria|Archaea> <genomeID>.fna.gz # Transporter prediction ./gapseq find-transport -b 200 -k <genomeID>.fna.gz # Draft network reconstruction ./gapseq draft -r <genomeID>-all-Reactions.tbl -t <genomeID>-Transporter.tbl -b <Bacteria|Archaea> -c <genomeID>.fna.gz -p <genomeID>-all-Pathways.tbl -u 200 -l 100 # gapfill/growth medium prediction ./gapseq medium -m <genomeID>-draft.RDS -p <genomeID>-all-Pathways.tbl -c "cpd00007:0" # Gap-filling # (If H2 is part of the medium) ./gapseq fill -m <genomeID>-draft.RDS -n <genomeID>-medium.csv -c <genomeID>-rxnWeights.RDS -g <genomeID>-rxnXgenes.RDS -b 100 -e highH2 # (If H2 is not part of the medium) ./gapseq fill -m <genomeID>-draft.RDS -n <genomeID>-medium.csv -c <genomeID>-rxnWeights.RDS -g <genomeID>-rxnXgenes.RDS -b 100

{"references": ["Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1", "Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). https://doi.org/10.1186/s13073-021-00950-7"]}