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The lack of new antibiotics necessitates the improvement of existing ones, many of which are limited by toxic side effects. Aminoglycosides, antibiotics with excellent activity and low bacterial resistance, are hampered by dose-dependent toxic effects in patients (nephrotoxicity, ototoxicity). High antibiotic concentrations are often required to treat dormant, non-dividing bacteria, though previous studies show that aminoglycosides can be activated against such bacteria by specific metabolites. Here, we employed this mechanism to greatly boost the activity of low concentrations of aminoglycosides against prevalent Gram-negative pathogens (Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae), suggesting that less toxic drug concentrations might be used effectively in patients. We go on to show that this effect improved treatment of biofilms, did not increase aminoglycoside resistance, and was due to the generation of proton-motive force (PMF). By single-cell microscopy, we demonstrate that stationary-phase cells, while non-dividing, actively maintain a growth-arrested state that is not reversed by metabolite addition. Surprisingly, within starved populations, we observed rare cells (3%) that divided without added nutrients. Additionally, we discovered that mannitol could directly protect human kidney cells from aminoglycoside cytotoxicity, independent of the metabolite's effect on bacteria. This work forwards a mechanism-based strategy to improve existing antibiotics by mitigating their toxic side effects.

How metabolic 'helpers' kill persistent pathogens Bacterial cells can enter a dormant 'persister' state that leaves them more resistant to stress conditions, including killing by antibiotics. In a clinical setting, persister formation can lead to incomplete eradication of bacterial pathogens and treatment failure. James Collins and colleagues show that certain metabolic stimuli (including glucose and pyruvate) can increase killing of persister cells by aminoglycoside antibiotics including gentamicin. This raises the prospect that the delivery of metabolites as adjuvants to aminoglycosides could be effective in the treatment of chronic bacterial infections. Bacterial persistence is a state in which a sub-population of dormant cells, or ‘persisters’, tolerates antibiotic treatment 1 , 2 , 3 , 4 . Bacterial persisters have been implicated in biofilms and in chronic and recurrent infections 5 , 6 , 7 . Despite this clinical relevance, there are currently no viable means for eradicating persisters. Here we show that specific metabolic stimuli enable the killing of both Gram-negative ( Escherichia coli ) and Gram-positive ( Staphylococcus aureus ) persisters with aminoglycosides. This potentiation is aminoglycoside-specific, it does not rely on growth resumption and it is effective in both aerobic and anaerobic conditions. It proceeds by the generation of a proton-motive force which facilitates aminoglycoside uptake. Our results demonstrate that persisters, although dormant, are primed for metabolite uptake, central metabolism and respiration. We show that aminoglycosides can be used in combination with specific metabolites to treat E. coli and S. aureus biofilms. Furthermore, we demonstrate that this approach can improve the treatment of chronic infections in a mouse urinary tract infection model. This work establishes a strategy for eradicating bacterial persisters that is based on metabolism, and highlights the importance of the metabolic environment to antibiotic treatment.

Bacteria can survive antibiotics by forming dormant, drug‐tolerant persisters. Persisters can resuscitate from dormancy after treatment and prolong infections. Resuscitation is thought to occur stochastically, but its transient, single‐cell nature makes it difficult to investigate. We tracked the resuscitation of individual persisters by microscopy after ampicillin treatment and, by characterizing their dynamics, discovered that Escherichia coli and Salmonella enterica persisters resuscitate exponentially rather than stochastically. We demonstrated that the key parameters controlling resuscitation map to the ampicillin concentration during treatment and efflux during resuscitation. Consistently, we observed many persister progeny have structural defects and transcriptional responses indicative of cellular damage, for both β‐lactam and quinolone antibiotics. During resuscitation, damaged persisters partition unevenly, generating both healthy daughter cells and defective ones. This persister partitioning phenomenon was observed in S. enterica , Klebsiella pneumoniae , Pseudomonas aeruginosa , and an E. coli urinary tract infection (UTI) isolate. It was also observed in the standard persister assay and after in situ treatment of a clinical UTI sample. This study reveals novel properties of resuscitation and indicates that persister partitioning may be a survival strategy in bacteria that lack genetic resistance. Synopsis Tracking and modelling single‐cell resuscitation dynamics of bacterial persisters shows that it is a drug‐dependent and non‐stochastic process. Persisters can partition cellular damage into healthy and nonviable daughter cells after antibiotic treatment. Persister resuscitation after treatment is exponential rather than stochastic. Persisters follow distinct trajectories during resuscitation: healthy, damaged, and failed. Persisters can partition into healthy and non‐viable daughter cells after treatment to survive. Persister partitioning occurs in E. coli , S. enterica , K. pneumoniae , and P. aeruginosa and in an E. coli in situ urinary tract infection sample. Graphical Abstract Tracking and modelling single‐cell resuscitation dynamics of bacterial persisters shows that it is a drug‐dependent and non‐stochastic process. Persisters can partition cellular damage into healthy and nonviable daughter cells after antibiotic treatment.

Deeper understanding of antibiotic-induced physiological responses is critical to identifying means for enhancing our current antibiotic arsenal. Bactericidal antibiotics with diverse targets have been hypothesized to kill bacteria, in part by inducing production of damaging reactive species. This notion has been supported by many groups but has been challenged recently. Here we robustly test the hypothesis using biochemical, enzymatic, and biophysical assays along with genetic and phenotypic experiments. We first used a novel intracellular H ₂O ₂ sensor, together with a chemically diverse panel of fluorescent dyes sensitive to an array of reactive species to demonstrate that antibiotics broadly induce redox stress. Subsequent gene-expression analyses reveal that complex antibiotic-induced oxidative stress responses are distinct from canonical responses generated by supraphysiological levels of H ₂O ₂. We next developed a method to quantify cellular respiration dynamically and found that bactericidal antibiotics elevate oxygen consumption, indicating significant alterations to bacterial redox physiology. We further show that overexpression of catalase or DNA mismatch repair enzyme, MutS, and antioxidant pretreatment limit antibiotic lethality, indicating that reactive oxygen species causatively contribute to antibiotic killing. Critically, the killing efficacy of antibiotics was diminished under strict anaerobic conditions but could be enhanced by exposure to molecular oxygen or by the addition of alternative electron acceptors, indicating that environmental factors play a role in killing cells physiologically primed for death. This work provides direct evidence that, downstream of their target-specific interactions, bactericidal antibiotics induce complex redox alterations that contribute to cellular damage and death, thus supporting an evolving, expanded model of antibiotic lethality.

Antibiotics save lives but can have unwanted effects on our gut microbes, thereby contributing to disease. A mechanistic understanding of how such microbes respond to antibiotics is hence critical. Recently in , Nilson et al. investigated the metabolite dependence of antibiotic susceptibility in , an abundant and important member of our gut microbiota (R. Nilson, S. Penumutchu, F. S. Pagano, and P. Belenky, mSphere 9:e00103-24, 2024, https://doi.org/10.1128/msphere.00103-24). Their uncovered findings suggest the possibility of potentiating antibiotics with metabolites to reduce post-antibiotic \"blooming\" of and the associated development of gut symbiosis.

Bacterial communication plays an important role in many population-based phenotypes and interspecies interactions, including those in host environments. These interspecies interactions may prove critical to some infectious diseases, and it follows that communication between pathogenic bacteria and commensal bacteria is a subject of growing interest. Recent studies have shown that Escherichia coli uses the signaling molecule indole to increase antibiotic tolerance throughout its population. Here, we show that the intestinal pathogen Salmonella typhimurium increases its antibiotic tolerance in response to indole, even though S. typhimurium does not natively produce indole. Increased antibiotic tolerance can be induced in S. typhimurium by both exogenous indole added to clonal S. typhimurium populations and indole produced by E. coli in mixed-microbial communities. Our data show that indole-induced tolerance in S. typhimurium is mediated primarily by the oxidative stress response and, to a lesser extent, by the phage shock response, which were previously shown to mediate indole-induced tolerance in E. coli . Further, we find that indole signaling by E. coli induces S. typhimurium antibiotic tolerance in a Caenorhabditis elegans model for gastrointestinal infection. These results suggest that the intestinal pathogen S. typhimurium can intercept indole signaling from the commensal bacterium E. coli to enhance its antibiotic tolerance in the host intestine.

Indole, secreted by E. coli , induces oxidative-stress and phage-shock pathway genes to increase persistence, a phenomenon in which dormant bacteria are resistant to antibiotics. Here we show that bacterial communication through indole signaling induces persistence, a phenomenon in which a subset of an isogenic bacterial population tolerates antibiotic treatment. We monitor indole-induced persister formation using microfluidics and identify the role of oxidative-stress and phage-shock pathways in this phenomenon. We propose a model in which indole signaling 'inoculates' a bacterial subpopulation against antibiotics by activating stress responses, leading to persister formation.

This analysis comprehensively compares methods for gene regulatory network inference submitted through the DREAM5 challenge. It demonstrates that integration of predictions from multiple methods shows the most robust performance across data sets. Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli , Staphylococcus aureus , Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus , each comprising ∼1,700 transcriptional interactions at a precision of ∼50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli , of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.