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. 2023 Jul 20;14:4369. doi: 10.1038/s41467-023-39982-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — a Heatmap with pairwise Jaccard distance values for isolated GEM pairs based on presence or absence of metabolic reactions. b Selected metabolic reactions with the highest statistical significance for differences in presence/absence by sample origin (Fisher exact test, p ≤ 0.05). Presence frequency indicates the fraction of reaction presence over all investigated strain-specific GEMs. c Decision tree optimized for separation of clinical and environmental strain origin. The decision tree is based on absence or presence of metabolic reactions and growth capability on different nutrients for all strain-specific GEMs. d Machine learning-derived mean area under the curve for precision over recall based on 21 reactions identified by the model using biomass-supporting flux ranges for all reactions determined with flux variability analysis to classify clinical vs. environmental origin. Source data for Fig. 3 are provided in the Source Data file.