ArticlemSystems2026
Gempipe: a tool for drafting, curating, and analyzing pan and multi-strain genome-scale metabolic models.
Article in mSystems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Genome-scale metabolic models (GSMMs) can mechanistically explain phenotypic differences among closely related bacterial strains. However, high-throughput multi-strain reconstructions of GSMMs are still challenging: reference-based methods inherit curated information while missing new contents; alternatively (universe-based), reference-free methods could cover strain-specific reactions, but they disregard curated information. Ideally, references should be curated pan-GSMMs for species (or genus), but their reconstruction is extremely demanding, making them still rare in the literature. Here, Gempipe is presented, a computational tool streamlining the multi-strain reconstruction and analysis of GSMMs, going through the production of a pan-GSMM. Its reconstruction method is hybrid; as an optional reference, GSMM is automatically expanded with extra reactions taken from a reference-free reconstruction. Gempipe also downloads, filters, and annotates genomes; performs in-depth gene recovery; annotates models' contents; and predicts strain-specific capabilities. The companion programming interface includes functions ranging from the (pan-)GSMMs' curation to the multi-strain analysis. Gempipe was validated using multi-strain data sets, showing improved accuracy when compared with state-of-the-art tools. Moreover, metabolic diversities within
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