An experimentally validated manually curated genome-scale metabolic model of Enterococcus faecium TX0016 reproduces high-throughput phenotyping data
6 affiliations
- 1Postgraduate Program, Faculty of Pharmacy, Cairo University
- 2Department of Microbiology, Faculty of Pharmacy, The British University in Egypt
- 3Department of Bioengineering, University of California, San Diego
- 4Department of Pediatrics, University of California, San Diego
- 5Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University
- 6Bioscience Research Laboratories, MARC for Medical Services and Scientific Research
Abstract
Enterococci are Gram-positive opportunistic pathogens responsible for a wide range of nosocomial infections. One enterococcal species, Enterococcus faecium , is steadily increasing in prevalence and has been listed among major multidrug-resistant ESKAPE pathogens. To gain systems-level insights into its metabolism and support discovery of potential therapeutic targets, we constructed iDR478, a comprehensive manually curated genome-scale metabolic model (GEM) for E. faecium TX0016 (strain DO). The reconstruction was based on extensive homology searches and literature evidence, and was further refined and gap-filled through experimental validation. Phenotypic profiling using Biolog microarrays enabled assessment of carbon source utilization, while amino acid leave-out growth assays allowed the evaluation of auxotrophies. The final model, after phenotypic-based refinement, successfully predicted 100% of amino acid auxotrophy and 85% of growth on sole carbon sources. Discrepancies between model predictions and experimental phenotypes identified specific knowledge gaps across metabolic pathways, including unresolved carbon source utilization phenotypes, e.g., psicose, sorbitol, and palatinose utilization. Those gaps will guide future experimental characterization. Additionally, we conducted gene essentiality analysis to evaluate the predictive capacity of the iDR478 model. Since no experimental gene essentiality data are currently available for E. faecium , model predictions were compared against Tn-seq experimental results from E. faecalis MMH594. Under simulated unconstrained uptake conditions, iDR478 achieved 84.2% positive predictive value of the experimental essentiality results of E. faecalis MMH594. iDR478 thus provides a framework for studying E. faecium , offers insights into its metabolic network, and serves as a source for generating hypotheses for future experimental investigation.
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BibTeX
@article{rasmi2026experimentally,
title = {{An experimentally validated manually curated genome-scale metabolic model of Enterococcus faecium TX0016 reproduces high-throughput phenotyping data}},
author = {Dina Samir Rasmi and Kalpathy Jayanth Krishnan and Yomna A. Hashem and Bernhard O. Palsson and Mona T. Kashef and Jonathan M. Monk and Ramy K. Aziz},
journal = {Frontiers in Microbiology},
year = {2026},
month = oct,
doi = {10.3389/fmicb.2026.1941652},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2026.1941652/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - An experimentally validated manually curated genome-scale metabolic model of Enterococcus faecium TX0016 reproduces high-throughput phenotyping data
AU - Dina Samir Rasmi
AU - Kalpathy Jayanth Krishnan
AU - Yomna A. Hashem
AU - Bernhard O. Palsson
AU - Mona T. Kashef
AU - Jonathan M. Monk
AU - Ramy K. Aziz
PY - 2026
DA - 2026/10/09
JO - Frontiers in Microbiology
DO - 10.3389/fmicb.2026.1941652
UR - https://www.frontiersin.org/articles/10.3389/fmicb.2026.1941652/full
AB - Enterococci are Gram-positive opportunistic pathogens responsible for a wide range of nosocomial infections. One enterococcal species, Enterococcus faecium , is steadily increasing in prevalence and has been listed among major multidrug-resistant ESKAPE pathogens. To gain systems-level insights into its metabolism and support discovery of potential therapeutic targets, we constructed iDR478, a comprehensive manually curated genome-scale metabolic model (GEM) for E. faecium TX0016 (strain DO). The reconstruction was based on extensive homology searches and literature evidence, and was further refined and gap-filled through experimental validation. Phenotypic profiling using Biolog microarrays enabled assessment of carbon source utilization, while amino acid leave-out growth assays allowed the evaluation of auxotrophies. The final model, after phenotypic-based refinement, successfully predicted 100% of amino acid auxotrophy and 85% of growth on sole carbon sources. Discrepancies between model predictions and experimental phenotypes identified specific knowledge gaps across metabolic pathways, including unresolved carbon source utilization phenotypes, e.g., psicose, sorbitol, and palatinose utilization. Those gaps will guide future experimental characterization. Additionally, we conducted gene essentiality analysis to evaluate the predictive capacity of the iDR478 model. Since no experimental gene essentiality data are currently available for E. faecium , model predictions were compared against Tn-seq experimental results from E. faecalis MMH594. Under simulated unconstrained uptake conditions, iDR478 achieved 84.2% positive predictive value of the experimental essentiality results of E. faecalis MMH594. iDR478 thus provides a framework for studying E. faecium , offers insights into its metabolic network, and serves as a source for generating hypotheses for future experimental investigation.
SN - 1664-302X
ER -