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Nitroxoline is a bacteriostatic quinoline antibiotic, known to form complexes with metals. Its clinical indications are limited to uncomplicated urinary tract infections, with a susceptibility breakpoint only available for Escherichia coli . Here, we test > 1000 clinical isolates and demonstrate a much broader activity spectrum and species-specific bactericidal activity, including Gram-negative bacteria for which therapeutic options are limited due to multidrug resistance. By combining genetic and proteomic approaches with direct measurement of intracellular metals, we show that nitroxoline acts as a metallophore, inducing copper and zinc intoxication in bacterial cells. The compound displays additional effects on bacterial physiology, including alteration of outer membrane integrity, which underpins nitroxoline’s synergies with large-scaffold antibiotics and resensitization of colistin-resistant Enterobacteriaceae in vitro and in vivo. Furthermore, we identify conserved resistance mechanisms across bacterial species, often leading to nitroxoline efflux. Nitroxoline is a bacteriostatic quinoline antibiotic, known to form complexes with metals, with few clinical applications. Here, Cacace et al. show that the compound displays a broad activity spectrum, with species-specific bactericidal activity, and acts as a metallophore inducing copper and zinc intoxication in bacterial cells.

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease 1 . Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species 2 . Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for β-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal 3 – 5 and human 6 , 7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota. This study systematically profiles the activity of several classes of antibiotics on gut commensal bacteria and identifies drugs that mitigate their collateral damage on commensal bacteria without compromising their efficacy against pathogens.

Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae . Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus , including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus . All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ). Antibacterial combinations that are potent against Gram-positive bacteria are identified using an automated high-throughput screen.

By acquiring or evolving resistance to one antibiotic, bacteria can become cross-resistant to a second antibiotic, which further limits therapeutic choices. In the opposite scenario, initial resistance leads to collateral sensitivity to a second antibiotic, which can inform cycling or combinatorial treatments. Despite their clinical relevance, our knowledge of both interactions is limited. We used published chemical genetics data of the Escherichia coli single-gene deletion library in 40 antibiotics and devised a metric that discriminates between known cross-resistance and collateral-sensitivity antibiotic interactions. Thereby we inferred 404 cases of cross-resistance and 267 of collateral-sensitivity, expanding the number of known interactions by over threefold. We further validated 64/70 inferred interactions using experimental evolution. By identifying mutants driving these interactions in chemical genetics, we demonstrated that a drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied collateral-sensitive drug pairs in combination to reduce antibiotic-resistance development in vitro. Resistance to one antibiotic can make bacteria resistant or sensitive to another antibiotic, opening paths for combinatorial treatments. This study presents an approach to systematically discover and understand such antibiotic relationships.

By acquiring or evolving resistance to one antibiotic, bacteria can become resistant to a second one, due to shared underlying mechanisms. This is called cross-resistance (XR) and further limits therapeutic choices. The opposite scenario, in which initial resistance leads to sensitivity to a second antibiotic, is termed collateral sensitivity (CS) and can inform cycling or combinatorial treatments. Despite their clinical relevance, our current knowledge of such interactions is limited, mostly due to experimental constraints in their assessment and lack of understanding of the underlying mechanisms. To fill this gap, we used published chemical genetic data on the impact of all Escherichia coli non-essential genes on resistance/sensitivity to 40 antibiotics, and devised a metric that robustly discriminates between known XR and CS antibiotic interactions. This metric, based on chemical genetic profile (dis)similarity between two drugs, allowed us to infer 404 XR and 267 CS interactions, thereby expanding the number of known interactions by more than 3-fold – including reclassifying 116 previously reported interactions. We benchmarked our results by validating 55 out of 59 inferred interactions via experimental evolution. By identifying mutants driving XR and CS interactions in chemical genetics, we recapitulated known and uncovered previously unknown mechanisms, and demonstrated that a given drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied CS drug pairs in combination to reduce antibiotic resistance development in vitro. Altogether, our approach provides a systematic framework to map XR/CS interactions and their mechanisms, paving the way for the development of rationally-designed antibiotic combination treatments.

Serotyping of bacteria using genomic information (in silico serotyping) has increasingly replaced serology. However, the E. coli capsule serotyping system has been largely abandoned since the 1990s, leaving gaps in our knowledge of capsule genetics, diversity, distribution, and epidemiology. To address this, we established a definitive genotype-serotype map for 35 serologically identified and structurally characterized transporter-dependent capsules. We then surveyed >37,000 E. coli genomes, cataloging 85 transporter-dependent capsule types (K-types), including 55 novel ones. We leveraged this catalog to develop an in silico serotyping tool, kTYPr, and applied it to curated sets of >25,000 E. coli genomes and metagenome-assembled genomes spanning diverse environmental and clinical sources. We found novel K-types enriched in under-sampled environments and associated with E. coli disease. This research expands our understanding of E. coli surface structures, supporting efforts for precision targeting with phage therapy or vaccines.

Nitroxoline is a bacteriostatic quinoline antibiotic, considered a metal chelator inhibiting the activity of RNA-polymerase1. Its clinical indications are limited to uncomplicated urinary tract infections (UTIs), with a clinical susceptibility breakpoint only available for Escherichia coli2. By testing > 1,000 clinical isolates, here we demonstrate a much broader activity spectrum and species-specific bactericidal activity, including multidrug-resistant Gram-negative bacteria for which therapeutic options are limited due to resistance. By combining systematic genetic and proteomic approaches with direct measurement of intracellular metals, we dissect nitroxoline perturbation of metal homeostasis and unveil additional effects on bacterial physiology. We show that nitroxoline affects outer membrane integrity, synergizing with large-scaffold antibiotics and resensitizing colistin-resistant Enterobacteriaceae in vitro and in vivo. We further characterise resistance mechanisms across E. coli, Acinetobacter baumannii and Klebsiella pneumoniae, recapitulating known E. coli resistance determinants and uncovering novel and conserved mechanisms across species, demonstrating their common effect on nitroxoline efflux.

Drug combinations present a powerful strategy to tackle antimicrobial resistance, but have not been systematically tested in many bacterial species. Here, we used an automated high-throughput setup to profile ∼ 8000 combinations between 65 antibacterial drugs in three Gram-positive species: the model species, Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulate previously known drug interactions, but also identify ten times more interactions than previously reported in the pathogen S. aureus, including two synergies that were also effective in multi-drug resistant clinical S. aureus isolates in vitro and in vivo. Interactions were largely species-specific and mostly synergistic for drugs targeting the same cellular process, as observed also for Gram-negative species1. Yet, the dominating synergies are clearly distinct between Gram-negative and Gram-positive species, and are driven by different bottlenecks in drug uptake and vulnerabilities of their cell surface structures. To further explore interactions of commonly prescribed non-antibiotic drugs with antibiotics, we tested 2728 of such combinations in S. aureus, detecting a plethora of unexpected antagonisms that could compromise the efficacy of antimicrobial treatments in the age of polypharmacy. We uncovered even more synergies than antagonisms, some of which we could demonstrate as effective combinations in vivo against multi-drug resistant clinical isolates. Among them, we showed that the antiaggregant ticagrelor interferes with purine metabolism and changes the surface charge of S. aureus, leading to strong synergies with cationic antibiotics. Overall, this exemplifies the untapped potential of approved non-antibacterial drugs to be repurposed as antibiotic adjuvants. All data can be browsed through an interactive interface (https://apps.embl.de/combact/).

Antibiotics are used for fighting pathogens, but also target our commensal bacteria as a side effect, disturbing the gut microbiota composition and causing dysbiosis and disease. Despite this well-known collateral damage, the activity spectrum of the different antibiotic classes on gut bacteria remains poorly characterized. Having monitored the activities of >1,000 marketed drugs on 38 representative species of the healthy human gut microbiome, we here characterize further the 144 antibiotics therein, representing all major classes. We determined >800 Minimal Inhibitory Concentrations (MICs) and extended the antibiotic profiling to 10 additional species to validate these results and link to available data on antibiotic breakpoints for gut microbes. Antibiotic classes exhibited distinct inhibition spectra, including generation-dependent effects by quinolones and phylogeny-independence by β-lactams. Macrolides and tetracyclines, two prototypic classes of bacteriostatic protein synthesis inhibitors, inhibited almost all commensals tested. We established that both kill different subsets of prevalent commensal bacteria, and cause cell lysis in specific cases. This species-specific activity challenges the long-standing divide of antibiotics into bactericidal and bacteriostatic, and provides a possible explanation for the strong impact of macrolides on the gut microbiota composition in animals and humans. To mitigate the collateral damage of macrolides and tetracyclines on gut commensals, we exploited the fact that drug combinations have species-specific outcomes in bacteria and sought marketed drugs, which could antagonize the activity of these antibiotics in abundant gut commensal species. By screening >1,000 drugs, we identified several such antidotes capable of protecting gut species from these antibiotics without compromising their activity against relevant pathogens. Altogether, this study broadens our understanding of antibiotic action on gut commensals, uncovers a previously unappreciated and broad bactericidal effect of prototypical bacteriostatic antibiotics on gut bacteria, and opens avenues for preventing the collateral damage caused by antibiotics on human gut commensals.