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Cited by 79Microbial Metabolic Engineering and BioproductionBacterial Genetics and BiotechnologyComputational Drug Discovery Methods

Metabolomics-Driven Exploration of the Chemical Drug Space to Predict Combination Antimicrobial Therapies

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Campos, Adrian I., Zampieri, Mattia·2019·Molecular Cell
DOI 10.1016/j.molcel.2019.04.001PMC PMC6591011
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Abstract

Alternative to the conventional search for single-target, single-compound treatments, combination therapies can open entirely new opportunities to fight antibiotic resistance. However, combinatorial complexity prohibits experimental testing of drug combinations on a large scale, and methods to rationally design combination therapies are lagging behind. Here, we developed a combined experimental-computational approach to predict drug-drug interactions using high-throughput metabolomics. The approach was tested on 1,279 pharmacologically diverse drugs applied to the gram-negative bacterium Escherichia coli. Combining our metabolic profiling of drug response with previously generated metabolic and chemogenomic profiles of 3,807 single-gene deletion strains revealed an unexpectedly large space of inhibited gene functions and enabled rational design of drug combinations. This approach is applicable to other therapeutic areas and can unveil unprecedented insights into drug tolerance, side effects, and repurposing. The compendium of drug-associated metabolome profiles is available at https://zampierigroup.shinyapps.io/EcoPrestMet, providing a valuable resource for the microbiological and pharmacological communities.

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  • Exogenous glutathione raises minimal inhibitory concentrations 2-fold for DIS, explaining its limited activity against thiol-rich Gram-negatives versus Gram-positives.

    “Exogenous glutathione raises minimal inhibitory concentrations 2-fold for DIS,100 explaining its limited activity against thiol-rich Gram-negatives versus Gram-positives.100,103,104,105,106,107,108”

    From Off-label and repurposed use of disulfiram beyond alcohol dependence: A systematic review of clinical and preclinical evidence (2026) · cites this paper as [104]

    The Results section, “From Drug Metabolic Fingerprint to Drug-Gene Associations” (page unavailable), reports disulfiram’s inhibition of purified isocitrate dehydrogenase, not a glutathione-supplemented susceptibility test. Searches for glutathione, a twofold increase in disulfiram MIC, and a Gram-negative versus Gram-positive comparison found no passage addressing the claim. (LLM, conf=0.77)

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Authors
Campos, A. I., & Zampieri, M.
Affiliations
ETH Zurich (CH)
Corresponding author
Zampieri, Mattia
ORCID
Zampieri, Mattia
Venue
Molecular Cell
Publisher
Elsevier BV
Published
2019-06
Volume
74
Issue
6
Pages
1291-1303.e6
ISSN
1097-2765 (ISSN-L)
DOI
10.1016/j.molcel.2019.04.001
PMC
PMC6591011
OpenAlex
W2943226553
Cited by
79
References
87
Citations by year
2026: 6 · 2025: 7 · 2024: 14 · 2023: 9 · 2022: 15 · 2021: 15 · 2020: 11 · 2019: 2
FWCI
3.56
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Cell (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by-nc-nd)
  • ETH Zürich Research Collection
Funders
  • Worldwide Cancer Research (WCR-15-1058)
  • UNAM-DGECI
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Keywords
combination therapy, drug-drug interactions, antimicrobial resistance, Escherichia coli, metabolomics, chemogenomics, rational drug design, drug repurposing, drug tolerance
MeSH terms
Cheminformatics, Anti-Bacterial Agents, Drug Combinations, Drug Interactions, Escherichia coli, Genome, Bacterial, Gene Deletion, Internet, Drug Resistance, Multiple, Bacterial, Metabolic Networks and Pathways, Metabolomics, Prescription Drugs, Drug Repositioning

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