Reactive metabolic byproducts contribute to antibiotic lethality under anaerobic conditions

Persistent glucose consumption under antibiotic treatment protects bacterial community

Antibiotics typically induce major physiological changes in bacteria. However, their effect on nutrient consumption remains unclear. Here we found that Escherichia coli communities can sustain normal levels of glucose consumption under a broad range of antibiotics. The community-living resulted in a low membrane potential in the bacteria, allowing slow antibiotic accumulation on treatment and better adaptation. Through multi-omics analysis, we identified a prevalent adaptive response characterized by the upregulation of lipid synthesis, which substantially contributes to sustained glucose consumption. The consumption was maintained by the periphery region of the community, thereby restricting glucose penetration into the community interior. The resulting spatial heterogeneity in glucose availability protected the interior from antibiotic accumulation in a membrane potential-dependent manner, ensuring rapid recovery of the community postantibiotic treatment. Our findings unveiled a community-level antibiotic response through spatial regulation of metabolism and suggested new strategies for antibiotic therapies.

The Combination of Membrane Disruption and FtsZ Targeting by a Chemotherapeutic Hydrogel Synergistically Combats Pathogens Infections

The emergence of multidrug-resistant (MDR) bacteria poses a significant challenge to global health. Due to a shortage of antibiotics, alternative therapeutic strategies are urgently needed. Unfortunately, colistin, the last-resort antibiotic, has unavoidable nephrotoxicity and hepatotoxicity, and its single killing mechanism is prone to drug resistance. To address this challenge, a promising combinatorial approach that includes colistin, a membrane-disrupting antimicrobial agent, and chelerythrine (CHE), a FtsZ protein inhibitor is proposed. This approach significantly reduces antibiotic dose and development of resistance, leading to almost complete inactivation of MDR pathogens in vitro. To address solubility issues and ensure transport, the antimicrobial hydrogel system LNP-CHE-CST@hydrogel, which induced reactive oxygen species (ROS) and apoptosis-like cell death by targeting the FtsZ protein, is used. In an in vivo mouse skin infection model, the combination therapy effectively eliminated MDR bacteria within 24 h, as monitored by fluorescence tracking. The findings demonstrate a promising approach for developing multifunctional hydrogels to combat MDR bacterial infections.

Role of RelA-synthesized (p)ppGpp and ROS-induced mutagenesis in de novo acquisition of antibiotic resistance in E. coli

The stringent response of bacteria to starvation and stress also fulfills a role in addressing the threat of antibiotics. Within this stringent response, (p)ppGpp, synthesized by RelA or SpoT, functions as a global alarmone. However, the effect of this (p)ppGpp on resistance development is poorly understood. Here, we show that knockout of relA or rpoS curtails resistance development against bactericidal antibiotics. The emergence of mutated genes associated with starvation and (p)ppGpp, among others, indicates the activation of stringent responses. The growth rate is decreased in ΔrelA-resistant strains due to the reduced ability to synthesize (p)ppGpp and the persistence of deacylated tRNA impeding protein synthesis. Sluggish cellular activity causes decreased production of reactive oxygen species (ROS), thereby reducing oxidative damage, leading to weakened DNA mismatch repair, potentially reducing the generation of mutations. These findings offer new targets for mitigating antibiotic resistance development, potentially achieved through inhibiting (p)ppGpp or ROS synthesis.

Streptococcus pneumoniae favors tolerance via metabolic adaptation over resistance to circumvent fluoroquinolones

Streptococcus pneumoniae is a major human pathogen of global health concern and the rapid emergence of antibiotic resistance poses a serious public health problem worldwide. Fluoroquinolone resistance in S. pneumoniae is an intriguing case because the prevalence of fluoroquinolone resistance does not correlate with increasing usage and has remained rare. Our data indicate that deleterious fitness costs in the mammalian host constrain the emergence of fluoroquinolone resistance both by de novo mutation and recombination. S. pneumoniae was able to circumvent such deleterious fitness costs via the development of antibiotic tolerance through metabolic adaptation that reduced the production of reactive oxygen species, resulting in a fitness benefit during infection of mice treated with fluoroquinolones. These data suggest that the emergence of fluoroquinolone resistance is tightly constrained in S. pneumoniae by fitness tradeoffs and that mutational pathways involving metabolic networks to enable tolerance phenotypes are an important contributor to the evasion of antibiotic-mediated killing.IMPORTANCEThe increasing prevalence of antibiotic resistant bacteria is a major global health concern. While many species have the potential to develop antibiotic resistance, understanding the barriers to resistance emergence in the clinic remains poorly understood. A prime example of this is fluroquinolone resistance in Streptococcus pneumoniae, whereby, despite continued utilization, resistance to this class of antibiotic remains rare. In this study, we found that the predominant pathways for developing resistance to this antibiotic class severely compromised the infectious capacity of the pneumococcus, providing a key impediment for the emergence of resistance. Using in vivo models of experimental evolution, we found that S. pneumoniae responds to repeated fluoroquinolone exposure by modulating key metabolic pathways involved in the generation of redox molecules, which leads to antibiotic treatment failure in the absence of appreciable shifts in resistance levels. These data underscore the complex pathways available to pathogens to evade antibiotic mediating killing via antibiotic tolerance.

Immunometabolic Regulation of Bacterial Infection, Biofilms, and Antibiotic Susceptibility

BACKGROUND

Upon infection, mucosal tissues activate a brisk inflammatory response to clear the pathogen, i.e., resistance to disease. Resistance to disease is orchestrated by tissue-resident macrophages, which undergo profound metabolic reprogramming after sensing the pathogen. These metabolically activated macrophages release many inflammatory factors, which promote their bactericidal function. However, in immunocompetent individuals, pathogens like Pseudomonas aeruginosa, Staphylococcus aureus, and Salmonella evade this type of immunity, generating communities that thrive for the long term.

SUMMARY

These organisms develop features that render them less susceptible to eradication, such as biofilms and increased tolerance to antibiotics. Furthermore, after antibiotic therapy withdrawal, "persister" cells rapidly upsurge, triggering inflammatory relapses that worsen host health. How these pathogens persisted in inflamed tissues replete with activated macrophages remains poorly understood.

KEY MESSAGES

In this review, we discuss recent findings indicating that the ability of P. aeruginosa, S. aureus, and Salmonella to evolve biofilms and antibiotic tolerance is promoted by the similar metabolic routes that regulate macrophage metabolic reprogramming.

Discovery of a structural class of antibiotics with explainable deep learning

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1-9. Deep learning approaches have aided in exploring chemical spaces1,10-15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

Genome-wide screen reveals cellular functions that counteract rifampicin lethality in Escherichia coli

IMPORTANCE

Rifamycins are a group of antibiotics with a wide antibacterial spectrum. Although the binding target of rifamycin has been well characterized, the mechanisms underlying the discrepant killing efficacy between gram-negative and gram-positive bacteria remain poorly understood. Using a high-throughput screen combined with targeted gene knockouts in the gram-negative model organism Escherichia coli, we established that rifampicin efficacy is strongly dependent on several cellular pathways, including iron acquisition, DNA repair, aerobic respiration, and carbon metabolism. In addition, we provide evidence that these pathways modulate rifampicin efficacy in a manner distinct from redox-related killing. Our findings provide insights into the mechanism of rifamycin efficacy and may aid in the development of new antimicrobial adjuvants.

Exposure and resistance to lantibiotics impact microbiota composition and function

The intestinal microbiota is composed of hundreds of distinct microbial species that interact with each other and their mammalian host. Antibiotic exposure dramatically impacts microbiota compositions and leads to acquisition of antibiotic-resistance genes. Lantibiotics are ribosomally synthesized and post-translationally modified peptides produced by some bacterial strains to inhibit the growth of competing bacteria. Nisin A is a lantibiotic produced by Lactococcus lactis that is commonly added to food products to reduce contamination with Gram-positive pathogens. Little is known, however, about lantibiotic-resistance of commensal bacteria inhabiting the human intestine. Herein, we demonstrate that Nisin A administration to mice alters fecal microbiome compositions and the concentration of taurine-conjugated primary bile acids. Lantibiotic Resistance System genes (LRS) are encoded by lantibiotic-producing bacterial strains but, we show, are also prevalent in microbiomes across human cohorts spanning vastly different lifestyles and 5 continents. Bacterial strains encoding LRS have enhanced in vivo fitness upon dietary exposure to Nisin A but reduced fitness in the absence of lantibiotic pressure. Differential binding of host derived, secreted IgA contributes to fitness discordance between bacterial strains encoding or lacking LRS. Although LRS are associated with mobile genetic elements, sequence comparisons of LRS encoded by distinct bacterial species suggest they have been long-term components of their respective genomes. Our study reveals the prevalence, abundance and physiologic significance of an underappreciated subset of antimicrobial resistance genes encoded by commensal bacterial species constituting the human gut microbiome, and provides insights that will guide development of microbiome augmenting strategies.

Reactive oxygen species accelerate de novo acquisition of antibiotic resistance in E. coli

Reactive oxygen species (ROS) produced as a secondary effect of bactericidal antibiotics are hypothesized to play a role in killing bacteria. If correct, ROS may play a role in development of de novo resistance. Here we report that single-gene knockout strains with reduced ROS scavenging exhibited enhanced ROS accumulation and more rapid acquisition of resistance when exposed to sublethal levels of bactericidal antibiotics. Consistent with this observation, the ROS scavenger thiourea in the medium decelerated resistance development. Thiourea downregulated the transcriptional level of error-prone DNA polymerase and DNA glycosylase MutM, which counters the incorporation and accumulation of 8-hydroxy-2'-deoxyguanosine (8-HOdG) in the genome. The level of 8-HOdG significantly increased following incubation with bactericidal antibiotics but decreased after treatment with the ROS scavenger thiourea. These observations suggest that in E. coli sublethal levels of ROS stimulate de novo development of resistance, providing a mechanistic basis for hormetic responses induced by antibiotics.

The influence of oxygen and oxidative stress on de novo acquisition of antibiotic resistance in E. coli and Lactobacillus lactis

BACKGROUND

Bacteria can acquire resistance through DNA mutations in response to exposure to sub-lethal concentrations of antibiotics. According to the radical-based theory, reactive oxygen species (ROS), a byproduct of the respiratory pathway, and oxidative stress caused by reactive metabolic byproducts, play a role in cell death as secondary killing mechanism. In this study we address the question whether ROS also affects development of resistance, in the conditions that the cells is not killed by the antibiotic.

RESULTS

To investigate whether oxygen and ROS affect de novo acquisition of antibiotic resistance, evolution of resistance due to exposure to non-lethal levels of antimicrobials was compared in E. coli wildtype and ΔoxyR strains under aerobic and anaerobic conditions. Since Lactococcus lactis (L. lactis) does not have an active electron transport chain (ETC) even in the presence of oxygen, and thus forms much less ROS, resistance development in L. lactis was used to distinguish between oxygen and ROS. The resistance acquisition in E. coli wildtype under aerobic and anaerobic conditions did not differ much. However, the aerobically grown ΔoxyR strain gained resistance faster than the wildtype or anaerobic ΔoxyR. Inducing an ETC by adding heme increased the rate at which L. lactis acquired resistance. Whole genome sequencing identified specific mutations involved in the acquisition of resistance. These mutations were specific for each antibiotic. The lexA mutation in ΔoxyR strain under aerobic conditions indicated that the SOS response was involved in resistance acquisition.

CONCLUSIONS

The concept of hormesis can explain the beneficial effects of low levels of ROS and reactive metabolic byproducts, while high levels are lethal. DNA repair and mutagenesis may therefore expedite development of resistance. Taken together, the results suggest that oxygen as such barely affects resistance development. Nevertheless, non-lethal levels of ROS stimulate de novo acquisition of antibiotic resistance.

CpxA/R-Controlled Nitroreductase Expression as Target for Combinatorial Therapy against Uropathogens by Promoting Reactive Oxygen Species Generation

The antibiotic resistances emerged in uropathogens lead to accumulative treatment failure and recurrent episodes of urinary tract infection (UTI), necessitating more innovative therapeutics to curb UTI before systematic infection. In the current study, the combination of amikacin and nitrofurantoin is found to synergistically eradicate Gram-negative uropathogens in vitro and in vivo. The mechanistic analysis demonstrates that the amikacin, as an aminoglycoside, induced bacterial envelope stress by introducing mistranslated proteins, thereby constitutively activating the cpxA/R two-component system (Cpx signaling). The activation of Cpx signaling stimulates the expression of bacterial major nitroreductases (nfsA/nfsB) through soxS/marA regulons. As a result, the CpxA/R-dependent nitroreductases overexpression generates considerable quantity of lethal reactive intermediates via nitroreduction and promotes the prodrug activation of nitrofurantoin. As such, these actions together disrupt the bacterial cellular redox balance with excessively-produced reactive oxygen species (ROS) as "Domino effect", accelerating the clearance of uropathogens. Although aminoglycosides are used as proof-of-principle to elucidate the mechanism, the synergy between nitrofurantoin is generally applicable to other Cpx stimuli. To summarize, this study highlights the potential of aminoglycoside-nitrofurantoin combination to replenish the arsenal against recurrent Gram-negative uropathogens and shed light on the Cpx signaling-controlled nitroreductase as a potential target to manipulate the antibiotic susceptibility.

Bacterial metabolism and susceptibility to cell wall-active antibiotics

Bacterial infections are increasingly resistant to antimicrobial therapy. Intense research focus has thus been placed on identifying the mechanisms that bacteria use to resist killing or growth inhibition by antibiotics and the ways in which bacteria share these traits with one another. This work has led to the advancement of new drugs, combination therapy regimens, and a deeper appreciation for the adaptability seen in microorganisms. However, while the primary mechanisms of action of most antibiotics are well understood, the more subtle contributions of bacterial metabolic state to repairing or preventing damage caused by antimicrobials (thereby promoting survival) are still understudied. Here, we review a modern viewpoint on a classical system: examining bacterial metabolism's connection to antibiotic susceptibility. We dive into the relationship between metabolism and antibiotic efficacy through the lens of growth rate, energy state, resource allocation, and the infection environment, focusing on cell wall-active antibiotics.

Understanding Antimicrobial Resistance Using Genome-Scale Metabolic Modeling

The urgent necessity to fight antimicrobial resistance is universally recognized. In the search of new targets and strategies to face this global challenge, a promising approach resides in the study of the cellular response to antimicrobial exposure and on the impact of global cellular reprogramming on antimicrobial drugs' efficacy. The metabolic state of microbial cells has been shown to undergo several antimicrobial-induced modifications and, at the same time, to be a good predictor of the outcome of an antimicrobial treatment. Metabolism is a promising reservoir of potential drug targets/adjuvants that has not been fully exploited to date. One of the main problems in unraveling the metabolic response of cells to the environment resides in the complexity of such metabolic networks. To solve this problem, modeling approaches have been developed, and they are progressively gaining in popularity due to the huge availability of genomic information and the ease at which a genome sequence can be converted into models to run basic phenotype predictions. Here, we review the use of computational modeling to study the relationship between microbial metabolism and antimicrobials and the recent advances in the application of genome-scale metabolic modeling to the study of microbial responses to antimicrobial exposure.

Resistance-resistant antibacterial treatment strategies

Antibiotic resistance is a major danger to public health that threatens to claim the lives of millions of people per year within the next few decades. Years of necessary administration and excessive application of antibiotics have selected for strains that are resistant to many of our currently available treatments. Due to the high costs and difficulty of developing new antibiotics, the emergence of resistant bacteria is outpacing the introduction of new drugs to fight them. To overcome this problem, many researchers are focusing on developing antibacterial therapeutic strategies that are "resistance-resistant"-regimens that slow or stall resistance development in the targeted pathogens. In this mini review, we outline major examples of novel resistance-resistant therapeutic strategies. We discuss the use of compounds that reduce mutagenesis and thereby decrease the likelihood of resistance emergence. Then, we examine the effectiveness of antibiotic cycling and evolutionary steering, in which a bacterial population is forced by one antibiotic toward susceptibility to another antibiotic. We also consider combination therapies that aim to sabotage defensive mechanisms and eliminate potentially resistant pathogens by combining two antibiotics or combining an antibiotic with other therapeutics, such as antibodies or phages. Finally, we highlight promising future directions in this field, including the potential of applying machine learning and personalized medicine to fight antibiotic resistance emergence and out-maneuver adaptive pathogens.