ArticlemBio2024
Within-species variability of antibiotic interactions in Gram-negative bacteria.
Article in mBio, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Bioactivity-driven prediction of antibacterial synergy using machine learning models.PLoS computational biology · 2026Article
- Case Commentary: When susceptibility is not enough in recurrentAntimicrobial agents and chemotherapy · 2026Article
- Robust antibiotic sensitization of pathogenic Pseudomonas aeruginosa via negative hysteresis in the cell envelope.Nature communications · 2026Article
- Integrated omics reveal a unique antibacterial mechanism of action for the small molecule HSI#6.Current research in microbial sciences · 2026Article
- Antimicrobial and Synergistic Activity of Metformin AgainstThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2026Article
- Fast detection of synergy and antagonism in antifungal combinations used against Candida albicans clinical isolates.Scientific reports · 2025Article
- Epidemiology, Pathogenesis, Clinical Features, and Management of Non-HACEK Gram-Negative Infective Endocarditis.Antibiotics (Basel, Switzerland) · 2025Review
- CombiANT reader: Deep learning-based automatic image processing tool to robustly quantify antibiotic interactions.PLOS digital health · 2025Article
- Antibiotic killing of drug-induced bacteriostatic cells.Antimicrobial agents and chemotherapy · 2025Article
- Common non-antibiotic drugs enhance selection for antimicrobial resistance in mixture with ciprofloxacin.ISME communications · 2025Article
- Characterization of Plant-Growth-Promoting Rhizobacteria for Tea Plant (Plants (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Treatments with antibiotic combinations are becoming increasingly important even though the supposed clinical benefits of combinations are, in many cases, unclear. Here, we systematically examined how several clinically used antibiotics interact and affect the antimicrobial efficacy against five especially problematic Gram-negative pathogens. A total of 232 bacterial isolates were tested against different pairwise antibiotic combinations spanning five classes, and the ability of all combinations in inhibiting growth was quantified. Descriptive statistics, principal component analysis (PCA), and Spearman's rank correlation matrix were used to determine the correlations between the different combinations on interaction outcome. Several important conclusions can be drawn from the 696 examined interactions. Firstly, within a species, the interactions are in general conserved but can be isolate-specific for a given antibiotic combination and can range from antagonistic to synergistic. Secondly, additive and antagonistic interactions are the most common observed across species and antibiotics, with 87.1% of isolate-antibiotic combinations being additive, 11.6% antagonistic, and only 0.3% showing synergy. These findings suggest that to achieve the highest precision and efficacy of combination therapy, not only isolate-specific interaction profiling ought to be routinely performed, in particular to avoid using drug combinations that show antagonistic interaction and an expected associated reduction in efficacy, but also discovering rare and potentially valuable synergistic interactions.IMPORTANCEAntibiotic combinations are often used to treat bacterial infections, which aim to increase treatment efficacy and reduce resistance evolution. Typically, it is assumed that one specific antibiotic combination has the same effect on different isolates of the same species, i.e., the interaction is conserved. Here, we tested this idea by examining how several clinically used antibiotics interact and affect the antimicrobial efficacy against several bacterial pathogens. Our results show that, even though within a species the interactions are often conserved, there are also isolate-specific differences for a given antibiotic combination that can range from antagonistic to synergistic. These findings suggest that isolate-specific interaction profiling ought to be performed in clinical microbiology routine to avoid using antagonistic drug combinations that might reduce treatment efficacy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.