ArticleMetabolomics : Official journal of the Metabolomic Society2025
LC-MS/MS metabolomics unravels the resistant phenotype of carbapenemase-producing Enterobacterales.
Article in Metabolomics : Official journal of the Metabolomic Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Metabolic adaptations in antibiotic-resistantMicrobiology spectrum · 2026Article
- Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.JAC-antimicrobial resistance · 2026Review
- Untargeted metabolomics reveals organism specific biomarkers of carbapenem resistance in Klebsiella pneumoniae and Escherichia coli.NPJ systems biology and applications · 2026Article
- KPC-2 Orchestrates Systemic Metabolic Rewiring to Facilitate Antibiotic Adaptation inMicroorganisms · 2026Article
- From Molecules to Metabolomes, Understanding Symbiosis through Small Molecules.Journal of natural products · 2026Review
- Serum proteomic profiling of sepsis patients reveals a protein-based diagnostic model, with metabolomic insights into carbapenem-resistantFrontiers in immunology · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
introductionThe degree of antimicrobial resistance demonstrated by carbapenemase-producing Enterobacterales (CPE) represents a growing public health challenge. Conventional methods for detecting CPE involve culture-based techniques with lengthy incubation steps. There is a need to develop rapid and accurate methods for the detection of resistance, for implementation into clinical diagnostics.
objectivesWith cellular phenotype closely linked to the metabolome, the acquisition of resistance should result in detectable differences in microbial metabolism. Accordingly, we sought to profile the metabolome of Enterobacterales isolates belonging to both CPE and non-CPE groups to identify metabolites linked to CPE.
methodsWe used liquid chromatography-mass spectrometry to profile the endo- and exometabolome of 32 Klebsiella pneumoniae and Escherichia coli isolates to identify metabolites which could predict CPE in antibiotic-free conditions after 6 h of growth.
resultsUsing supervised machine learning and multivariate analysis algorithms (partial least squares-discriminant analysis, k-nearest neighbour and random forest), we identified 21 metabolite biomarkers which displayed high performance metrics for the prediction of CPE (AUROCs ≥ 0.845). Results revealed a range of alterations between the metabolomes of CPE and non-CPE isolates. Pathway analysis revealed enrichment of microbial pathways including arginine metabolism, ATP-binding cassette transporters, purine metabolism, biotin metabolism, nucleotide metabolism, and biofilm formation, providing mechanistic insight into the resistance phenotype of CPE.
conclusionOur models demonstrate the ability to distinguish CPE from non-CPE in under 7 h using metabolite biomarkers, showing potential for the development of a targeted diagnostic assay.
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