The physiology and genetics of bacterial responses to antibiotic combinations

Multiplicity of type 6 secretion system toxins limits the evolution of resistance

The bacterial type 6 secretion system (T6SS) is a toxin-injecting nanoweapon that mediates competition in plant- and animal-associated microbial communities. Bacteria can evolve de novo resistance against T6SS attacks, but resistance is far from universal in natural communities, suggesting key features of T6SS weaponry may act to limit its evolution. Here, we combine ecoevolutionary modeling and experimental evolution to examine how toxin type and multiplicity in Acinetobacter baylyi attackers shape resistance evolution in susceptible Escherichia coli competitors. In both our models and experiments, we find that combinations of multiple distinct toxins limit resistance evolution by creating genetic bottlenecks, driving resistant lineages extinct before they can reach high frequency. We also show that, paradoxically, single-toxin attackers can drive the evolution of cross-resistance, protecting bacteria against unfamiliar toxin combinations, even though such evolutionary pathways were inaccessible against multitoxin attackers. Our findings indicate that, comparable to antimicrobial and anticancer combination therapies, multitoxin T6SS arsenals function to limit resistance evolution in competing microbes. This helps us to understand why T6SSs remain widespread and effective weapons in microbial communities, and why many T6SS-armed bacteria encode functionally diverse anticompetitor toxins.

High-Throughput Shotgun Metagenomics of Microbial Footprints Uncovers a Cocktail of Noxious Antibiotic Resistance Genes in the Winam Gulf of Lake Victoria, Kenya

Background: A diverse range of pollutants, including heavy metals, agrochemicals, pharmaceutical residues, illicit drugs, personal care products, and other anthropogenic contaminants, pose a significant threat to aquatic ecosystems. The Winam Gulf of Lake Victoria, heavily impacted by surrounding human activities, faces potential contamination from these pollutants. However, studies exploring the presence of antibiotic resistance genes (ARGs) in the lake remain limited. In the current study, a shotgun metagenomics approach was employed to identify ARGs and related pathways. Genomic DNA was extracted from water and sediment samples and sequenced using the high-throughput Illumina NovaSeq platform. Additionally, phenotypic antibiotic resistance was assessed using the disk diffusion method with commonly used antibiotics. Results: The analysis of metagenomes sequences from the Gulf ecosystem and Comprehensive Antibiotic Resistance Database (CARD) revealed worrying levels of ARGs in the lake. The study reported nine ARGs from the 37 high-risk resistant gene families previously documented by the World Health Organization (WHO). Proteobacteria had the highest relative abundance of antibiotic resistance (53%), Bacteriodes (4%), Verrucomicrobia (2%), Planctomycetes Chloroflexi, Firmicutes (2%), and other unclassified bacteria (39%). Genes that target protection, replacement, change, and antibiotic-resistant efflux were listed in order of dominance. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed antibiotic resistance to beta-lactamase and vancomycin. Phenotypic resistance to vancomycin, tetracycline, sulfamethoxazole, erythromycin, trimethoprim, tetracycline, and penicillin was reported through the zone of inhibition. Conclusions: This study highlights that the Winam Gulf of Lake Victoria in Kenya harbors a diverse array of antibiotic-resistant genes, including those conferring multidrug resistance. These findings suggest that the Gulf could be serving as a reservoir for more antibiotic-resistant genes, posing potential risks to both human health and aquatic biodiversity. The insights gained from this research can guide policy development for managing antibiotic resistance in Kenya.

The effect of combining antibiotics on resistance: A systematic review and meta-analysis

Background

Under which conditions antibiotic combination therapy decelerates rather than accelerates resistance evolution is not well understood. We examined the effect of combining antibiotics on within-patient resistance development across various bacterial pathogens and antibiotics.

Methods

We searched CENTRAL, EMBASE, and PubMed for (quasi)-randomised controlled trials (RCTs) published from database inception to 24 November 2022. Trials comparing antibiotic treatments with different numbers of antibiotics were included. Patients were considered to have acquired resistance if, at the follow-up culture, a resistant bacterium (as defined by the study authors) was detected that had not been present in the baseline culture. We combined results using a random effects model and performed meta-regression and stratified analyses. The trials' risk of bias was assessed with the Cochrane tool.

Results

42 trials were eligible and 29, including 5054 patients, qualified for statistical analysis. In most trials, resistance development was not the primary outcome and studies lacked power. The combined odds ratio for the acquisition of resistance comparing the group with the higher number of antibiotics with the comparison group was 1.23 (95% CI 0.68-2.25), with substantial between-study heterogeneity (I2=77%). We identified tentative evidence for potential beneficial or detrimental effects of antibiotic combination therapy for specific pathogens or medical conditions.

Conclusions

The evidence for combining a higher number of antibiotics compared to fewer from RCTs is scarce and overall compatible with both benefit or harm. Trials powered to detect differences in resistance development or well-designed observational studies are required to clarify the impact of combination therapy on resistance.

Funding

Support from the Swiss National Science Foundation (grant 310030B_176401 (SB, BS, CW), grant 32FP30-174281 (ME), grant 324730_207957 (RDK)) and from the National Institute of Allergy and Infectious Diseases (NIAID, cooperative agreement AI069924 (ME)) is gratefully acknowledged.

Toward better cures for Mycobacterium abscessus lung disease

SUMMARYThe opportunistic pathogen Mycobacterium abscessus (Mab) causes fatal lung infections that bear similarities-and notable differences-with tuberculosis (TB) pulmonary disease. In contrast to TB, no antibiotic is formally approved to treat Mab disease, there is no reliable cure, and the discovery and development pipeline is incredibly thin. Here, we discuss the factors behind the unsatisfactory cure rates of Mab disease, namely intrinsic resistance and persistence of the pathogen, and the use of underperforming, often parenteral and toxic, repurposed drugs. We propose preclinical strategies to build injectable-free sterilizing and safe regimens: (i) prioritize oral bactericidal antibiotic classes, with an initial focus on approved agents or advanced clinical candidates to provide immediate options for desperate patients, (ii) test drug combinations early, (iii) optimize novel leads specifically for M. abscessus, and (iv) consider pharmacokinetic-pharmacodynamic targets at the site of disease, the lung lesions in which drug tolerant bacterial populations reside. Knowledge and tool gaps in the preclinical drug discovery process are identified, including validated mouse models and computational platforms to enable in vitro mouse-human translation. We briefly discuss recent advances in clinical development, the need for readouts and biomarkers that correlate with cure, and clinical trial concepts adapted to the uniqueness of Mab patient populations for new regimen development. In an era when most pharmaceutical firms have withdrawn from antimicrobial drug discovery, the breakthroughs needed to fill the regimen development pipeline will likely come from partnerships between academia, biotech, pharma, non-profit organizations, and governments, with incentives that reward cooperation.

Predicting the evolution of antibiotic resistance

Predicting the evolution of antibiotic resistance is critical for realizing precision antibiotic therapies. How exactly to achieve such predictions is a theoretical challenge. Insights from mathematical models that reflect future behavior of microbes under antibiotic stress can inform intervention protocols. However, this requires going beyond heuristic approaches by modeling ecological and evolutionary responses linked to metabolic pathways and cellular functions. Developing such models is now becoming possible due to increasing data availability from systematic experiments with microbial systems. Here, I review recent theoretical advances promising building blocks to piece together a predictive theory of antibiotic resistance evolution. I focus on the conceptual framework of eco-evolutionary response models grounded on quantitative laws of bacterial physiology. These forward-looking models can predict previously unknown behavior of bacteria upon antibiotic exposure. With current developments covering mostly the case of ribosome-targeting antibiotics, I write this Opinion piece as an invitation to generalize the principles discussed here to a broader range of drugs and context dependencies.

Ultra-high-throughput screening of antimicrobial combination therapies using a two-stage transparent machine learning model

Here, we present M2D2, a two-stage machine learning (ML) pipeline that identifies promising antimicrobial drug combinations, which are crucial for combating drug resistance. M2D2 addresses key challenges in drug combination discovery by predicting drug synergies using computationally generated drug-protein interaction data, thereby circumventing the need for expensive omics data. The model improves the accuracy of drug target identification using high-throughput experimental and computational methods via feedback between ML stages. M2D2's transparent framework provides mechanistic insights into drug interactions and was benchmarked against chemogenomics, transcriptomics, and metabolomics datasets. We experimentally validated M2D2 using high-throughput screening of 946 combinations of Food and Drug Administration (FDA)- approved drugs and antibiotics against Escherichia coli . We discovered synergy between a cerebrovascular drug and a widely used penicillin antibiotic and validated predicted mechanisms of action using genome-wide CRISPR inhibition screens. M2D2 offers a transparent ML tool for rapidly designing combination therapies and guides repurposing efforts while providing mechanistic insights.

Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli

Lineages of rod-shaped bacteria such as Escherichia coli exhibit a temporal decline in elongation rate in a manner comparable to cellular or biological aging. The effect results from the production of asymmetrical daughters, one with a lower elongation rate, by the division of a mother cell. The slower daughter compared to the faster daughter, denoted respectively as the old and new daughters, has more aggregates of damaged proteins and fewer expressed gene products. We have examined further the degree of asymmetry by measuring the density of ribosomes between old and new daughters and between their poles. We found that ribosomes were denser in the new daughter and also in the new pole of the daughters. These ribosome patterns match the ones we previously found for expressed gene products. This outcome suggests that the asymmetry is not likely to result from properties unique to the gene expressed in our previous study, but rather from a more fundamental upstream process affecting the distribution of ribosomal abundance. Because damage aggregates and ribosomes are both more abundant at the poles of E. coli cells, we suggest that competition for space between the two could explain the reduced ribosomal density in old daughters. Using published values for aggregate sizes and the relationship between ribosomal number and elongation rates, we show that the aggregate volumes could in principle displace quantitatively the amount of ribosomes needed to reduce the elongation rate of the old daughters.

High level non-carbapenemase carbapenem resistance by overlaying mutations of mexR, oprD, and ftsI in Pseudomonas aeruginosa

Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global threat, but the mechanism of non-carbapenemase carbapenem resistance is still unclear. In the current study, we investigated the contributions of point mutations in mexR, oprD, and ftsI to carbapenem resistance in P. aeruginosa during in vivo evolution studies with consecutive clinical isolates. Real-time qPCR and Electrophoretic Mobility Shift Assay demonstrated that MexR (Gln55Pro) mutation increased MexAB efflux pump genes expression by altering MexR's binding capacity, leading to a four- to eight-fold increase in meropenem MIC in the Pae d1 Green ∆mexR and PAO1∆mexR mutants. The OprD (Trp415*) truncation affected porin structure, and the constructed mutant Pae d1 Green oprD Trp415* increased meropenem MIC by 16-fold (from 0.25 to 4 µg/mL). The contribution of ftsI mutation to meropenem resistance was confirmed by clinical linkage analysis and was estimated to cause a two-fold increase in meropenem MIC by comparing the resistant clinical isolate with the Pae d1 Green oprD Trp415*∆mexR double mutant. The study found that the oprD Trp415* allele alone accounts for the imipenem MIC in clinical isolates, while the ∆mexR and ftsI Arg504Cys alleles do not contribute to imipenem resistance. In conclusion, we identified and explored the contributions of mexR, oprD, and ftsI mutations to high level non-carbapenemase carbapenem resistance in P. aeruginosa. These findings highlight the interplay of different mutations in causing non-carbapenemase carbapenem-resistance in P. aeruginosa.

IMPORTANCE

The emergence of carbapenem-resistant Pseudomonas aeruginosa (CRPA) poses a significant global health threat, complicating treatment options for infections caused by this pathogen. Understanding the mechanisms behind non-carbapenemase carbapenem resistance is critical for developing effective therapeutic strategies. This study provides crucial insights into how specific point mutations in key genes-mexR, oprD, and ftsI-contribute to carbapenem resistance, particularly the MexR (Gln55Pro) mutation's effect on efflux pump expression and the OprD (Trp415*) truncation's impact on porin structure. The findings elucidate the complex interplay of these mutations, highlighting their roles in conferring high-level resistance, and underscore the imperative for continued research to inform therapeutic strategies against CRPA infections.

Tetracycline and Oxacillin Act Synergistically on Biofilms and Display Increased Efficacy In Vivo Against Staphylococcus aureus

Oxacillin (bactericidal) and tetracycline (bacteriostatic) are clinically relevant antibiotics that are routinely prescribed to treat Staphylococcus aureus infections but not conventionally used in combination. There is an urgent need for treatment regimens that can act upon biofilms during infection, associated with chronic infections on indwelling devices, as well as acute planktonic (systemic) infection. Here we show that in an in vitro model oxacillin and tetracycline act synergistically against S. aureus UAMS-1 biofilms, reducing the concentration of both antibiotics necessary to eradicate an established biofilm. Using an in vivo zebrafish larval infection model with S. aureus NewHG, they display improved bacterial clearance compared to each drug alone and can counteract a loss of host phagocytes, an important innate defence against S. aureus. In these cases, the bacteriostatic nature of tetracycline enhances rather than dampens the bactericidal action of oxacillin, although an exact mechanism remains to be elucidated. We suggest a dual therapy could be of clinical use against biofilm-forming S. aureus and has a potential use in patients with a compromised immune system.

Source elimination of antibiotic resistance risk in aquaculture water by VUV/sulfite pretreatment

Antibiotic resistance risk in the aquaculture industry is increasing with the excessive consumption of antibiotics. Although various efficient technologies for the degradation of antibiotics are available, the potential risk from antibiotic resistance in treated waters is often overlooked. This study compared the risks of antibiotic resistance in anaerobic sludge fed with pretreated florfenicol (FLO) containing wastewater after four UV or vacuum UV (VUV)-driven ((V)UV-driven) pretreatments, and established the VUV/sulfite recirculating water system to validate the effect of controlling the antibiotic resistance risk in the actual aquaculture water. Metagenomics sequencing revealed that a remarkable decrease in the abundance of antibiotic resistance genes (ARGs) was observed in four different pretreated groups, and results among the four pretreated groups were sorted in descending order based on ARG abundance: UV > VUV > UV/sulfite > VUV/sulfite. The low abundance of ARGs from VUV/sulfite group was close to that in the CK group (wastewater without FLO and without any pretreatments), which was 0.41 copies/cell. From the perspective of the temporal changes in the relative abundance of floR, the abundance in VUV/sulfite group remained lower than 11.67 ± 0.73 during the cultivation time. Additionally, microbial diversity analysis found that Proteobacteria and Firmicutes were major carriers of ARGs. Two species from Burkholderiaceae and Rhodocyclales were identified as potential co-hosts to spread by the correlation analysis of the abundances between floR or intI1 and the top 50 genera. Finally, the abundances of ARGs and MGEs in the VUV/sulfite recirculating water system with actual aquaculture water were reduced by 39.15% and 46.04%, respectively, compared to that in the blank group without any pretreatment. This study verified that VUV/sulfite pretreatment system could effectively control the antibiotic resistance risk of ARGs proliferation and transfer in aquaculture water. Furthermore, the study demonstrated that the reduction of antibiotic antibacterial activity plays an important role in the source control of resistance risk.

Global hierarchical meta-analysis to identify the factors for controlling effects of antibiotics on soil microbiota

It is widely known that antibiotics can affect the structure and function of soil microbial communities, but the specific degree of impact and controlled factors on different indicators remain inconclusive. We conducted a multiple hierarchical mixed effects meta-analysis on 2564 observations that were extracted from 60 publications, to comprehensively assess the impact of antibiotics on soil microbiota. The results showed that antibiotics had significant negative effects on soil microbial biomass, α-diversity and soil enzyme activity. Under neutral initial soil, when soil was derived from agricultural land or had a fine-textured, the negative impacts of antibiotics on soil microbial community were exacerbated. Both single and mixed additions of antibiotics had significant inhibitory effects on soil microbial enzyme activities. The Random Forest model predicted the following key moderators involved in the effects of antibiotics on the soil microbiome, and antibiotics type, soil texture were key moderators on the severity of soil microbial biomass changes. Soil texture, temperature and single or combined application constitute of antibiotics were the main drivers of effects on soil enzyme activities. The reported results can be helpful to assess the ecological risk of antibiotics in a soil environment and provides a scientific basis for the rational of antibiotics use in the soil environment.

Salmonella Typhimurium alters galactitol metabolism under ciprofloxacin treatment to balance resistance and virulence

Ciprofloxacin-resistant Salmonella Typhimurium (S. Typhimurium) causes a significant health burden worldwide. A wealth of studies has been published on the contributions of different mechanisms to ciprofloxacin resistance in Salmonella spp. But we still lack a deep understanding of the physiological responses and genetic changes that underlie ciprofloxacin exposure. This study aims to know how phenotypic and genotypic characteristics are impacted by ciprofloxacin exposure, from ciprofloxacin-susceptible to ciprofloxacin-resistant strains in vitro. Here, we investigated the multistep evolution of resistance in replicate populations of S. Typhimurium during 24 days of continuously increasing ciprofloxacin exposure and assessed how ciprofloxacin impacts physiology and genetics. Numerous studies have demonstrated that RamA is a global transcriptional regulator that prominently perturbs the transcriptional landscape of S. Typhimurium, resulting in a ciprofloxacin-resistant phenotype appearing first; the quinolone resistance-determining region mutation site can only be detected later. Comparing the microbial physiological changes and RNA sequencing (RNA-Seq) results of ancestral and selectable mutant strains, the selectable mutant strains had some fitness costs, such as decreased virulence, an increase of biofilm-forming ability, a change of "collateral" sensitivity to other drugs, and inability to utilize galactitol. Importantly, in the ciprofloxacin induced, RamA directly binds and activates the gatR gene responsible for the utilization of galactitol, but RamA deletion strains could not activate gatR. The elevated levels of RamA, which inhibit the galactitol metabolic pathway through the activation of gatR, can lead to a reduction in the growth rate, adhesion, and colonization resistance of S. Typhimurium. This finding is supported by studies conducted in M9 medium as well as in vivo infection models.

IMPORTANCE

Treatment of antibiotic resistance can significantly benefit from a deeper understanding of the interactions between drugs and genetics. The physiological responses and genetic mechanisms in antibiotic-exposed bacteria are not well understood. Traditional resistance studies, often retrospective, fail to capture the entire resistance development process and typically exhibit unpredictable dynamics. To explore how clinical isolates of S. Typhimurium respond to ciprofloxacin, we analyzed their adaptive responses. We found that S. Typhimurium RamA-mediated regulation disrupts microbial metabolism under ciprofloxacin exposure, affecting genes in the galactitol metabolic pathways. This disruption facilitates adaptive responses to drug therapy and enhances the efficiency of intracellular survival. A more comprehensive and integrated understanding of these physiological and genetic changes is crucial for improving treatment outcomes.

Emergence of antibiotic-specific Mycobacterium tuberculosis phenotypes during prolonged treatment of mice

A major challenge in tuberculosis (TB) therapeutics is that antibiotic exposure leads to changes in the physiologic state of M. tuberculosis (Mtb) which may enable the pathogen to withstand treatment. While antibiotic-treated Mtb have been evaluated in short-term in vitro experiments, it is unclear if and how long-term in vivo treatment with diverse antibiotics with varying treatment-shortening activity (sterilizing activity) affect Mtb physiologic states differently. Here, we used SEARCH-TB, a pathogen-targeted RNA-sequencing platform, to characterize the Mtb transcriptome in the BALB/c high-dose aerosol infection mouse model following 4-week treatment with three sterilizing and three non-sterilizing antibiotics. Certain transcriptional changes were concordant among most antibiotics, including decreased expression of genes associated with protein synthesis and metabolism, and the induction of certain genes associated with stress responses. However, the magnitude of this concordant response differed between antibiotics. Sterilizing antibiotics rifampin, pyrazinamide, and bedaquiline generated a more quiescent Mtb state than did non-sterilizing antibiotics isoniazid, ethambutol, and streptomycin, as indicated by decreased expression of genes associated with translation, transcription, secretion of immunogenic proteins, metabolism, and cell wall synthesis. Additionally, we identified distinguishing transcriptional effects specific to each antibiotic, indicating that different mechanisms of action induce distinct patterns of cellular injury. In addition to elucidating Mtb physiologic changes associated with antibiotic stress, this study demonstrates the value of SEARCH-TB as a highly granular pharmacodynamic assay that reveals antibiotic effects that are not apparent based on culture alone.

Probiotics functionalized with a gallium-polyphenol network modulate the intratumor microbiota and promote anti-tumor immune responses in pancreatic cancer

The intratumor microbiome imbalance in pancreatic cancer promotes a tolerogenic immune response and triggers immunotherapy resistance. Here we show that Lactobacillus rhamnosus GG probiotics, outfitted with a gallium-polyphenol network (LGG@Ga-poly), bolster immunotherapy in pancreatic cancer by modulating microbiota-immune interactions. Upon oral administration, LGG@Ga-poly targets pancreatic tumors specifically, and selectively eradicates tumor-promoting Proteobacteria and microbiota-derived lipopolysaccharides through a gallium-facilitated disruption of bacterial iron respiration. This elimination of intratumor microbiota impedes the activation of tumoral Toll-like receptors, thus reducing immunosuppressive PD-L1 and interleukin-1β expression by tumor cells, diminishing immunotolerant myeloid populations, and improving the infiltration of cytotoxic T lymphocytes in tumors. Moreover, LGG@Ga-poly hampers pancreatic tumor growth in both preventive and therapeutic contexts, and amplifies the antitumor efficacy of immune checkpoint blockade in preclinical cancer models in female mice. Overall, we offer evidence that thoughtfully designed biomaterials targeting intratumor microbiota can efficaciously augment immunotherapy for the challenging pancreatic cancer.

The many dimensions of combination therapy: How to combine antibiotics to limit resistance evolution

In combination therapy, bacteria are challenged with two or more antibiotics simultaneously. Ideally, separate mutations are required to adapt to each of them, which is a priori expected to hinder the evolution of full resistance. Yet, the success of this strategy ultimately depends on how well the combination controls the growth of bacteria with and without resistance mutations. To design a combination treatment, we need to choose drugs and their doses and decide how many drugs get mixed. Which combinations are good? To answer this question, we set up a stochastic pharmacodynamic model and determine the probability to successfully eradicate a bacterial population. We consider bacteriostatic and two types of bactericidal drugs-those that kill independent of replication and those that kill during replication. To establish results for a null model, we consider non-interacting drugs and implement the two most common models for drug independence-Loewe additivity and Bliss independence. Our results show that combination therapy is almost always better in limiting the evolution of resistance than administering just one drug, even though we keep the total drug dose constant for a 'fair' comparison. Yet, exceptions exist for drugs with steep dose-response curves. Combining a bacteriostatic and a bactericidal drug which can kill non-replicating cells is particularly beneficial. Our results suggest that a 50:50 drug ratio-even if not always optimal-is usually a good and safe choice. Applying three or four drugs is beneficial for treatment of strains with large mutation rates but adding more drugs otherwise only provides a marginal benefit or even a disadvantage. By systematically addressing key elements of treatment design, our study provides a basis for future models which take further factors into account. It also highlights conceptual challenges with translating the traditional concepts of drug independence to the single-cell level.

Gram-negative bacteria recognition and photodynamic elimination by Zn-DPA based sensitizers

The abuse and overuse of antibiotics let drug-resistant bacteria emerges. Antibacterial photodynamic therapy (APDT) has shown outstanding merits to eliminate the drug-resistant bacteria via cytotoxic reactive oxygen species produced by irradiating photosensitizer. However, most of photosensitizers are not effective for Gram-negative bacteria elimination. Herein conjugates of NBS, a photosensitizer, linked with one (NBS-DPA-Zn) or two (NBS-2DPA-Zn) equivalents of zinc-dipicolylamine (Zn-DPA) have been designed to achieve the functional recognition of different bacteria. Due to the cationic character of NBS and metal transfer channel effect of Zn-DPA, NBS-DPA-Zn exhibited the first regent to distinguish P. aeruginosa from other Gram-negative bacteria. Whereas NBS-2DPA-Zn showed broad-spectrum antibacterial effect because the two arm of double Zn-DPA enhanced interactions with anionic membranes of bacteria, led the bacteria aggregation and thus provided the efficacy of APDT to bacteria and corresponding biofilm. In combination with a hydrogel of Pluronic, NBS-2DPA-Zn@gel shows promising clinical application in mixed bacterial diabetic mouse model infection. This might propose a new method that can realize functional identification and elimination of bacteria through intelligent regulation of Zn-DPA, and shows excellent potential for antibacterial application.

The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures

The prevalence of antibiotic-resistant pathogens has become a major threat to public health, requiring swift initiatives for discovering new strategies to control bacterial infections. Hence, antibiotic stewardship and rapid diagnostics, but also the development, and prudent use, of novel effective antimicrobial agents are paramount. Ideally, these agents should be less likely to select for resistance in pathogens than currently available conventional antimicrobials. The usage of antimicrobial peptides (AMPs), key components of the innate immune response, and combination therapies, have been proposed as strategies to diminish the emergence of resistance. Herein, we investigated whether newly developed random antimicrobial peptide mixtures (RPMs) can significantly reduce the risk of resistance evolution in vitro to that of single sequence AMPs, using the ESKAPE pathogen Pseudomonas aeruginosa (P. aeruginosa) as a model gram-negative bacterium. Infections of this pathogen are difficult to treat due the inherent resistance to many drug classes, enhanced by the capacity to form biofilms. P. aeruginosa was experimentally evolved in the presence of AMPs or RPMs, subsequentially assessing the extent of resistance evolution and cross-resistance/collateral sensitivity between treatments. Furthermore, the fitness costs of resistance on bacterial growth were studied and whole-genome sequencing used to investigate which mutations could be candidates for causing resistant phenotypes. Lastly, changes in the pharmacodynamics of the evolved bacterial strains were examined. Our findings suggest that using RPMs bears a much lower risk of resistance evolution compared to AMPs and mostly prevents cross-resistance development to other treatments, while maintaining (or even improving) drug sensitivity. This strengthens the case for using random cocktails of AMPs in favour of single AMPs, against which resistance evolved in vitro, providing an alternative to classic antibiotics worth pursuing.

Joint effects about antibiotics combined using with antibiotics or phytochemicals on Aeromonas hydrophila

Aeromonas hydrophila is highly prevalent in aquaculture animals and aquaculture environment. Due to the abuse of antibiotics, A. hydrophila can change the antibiotic resistance spectrum directly and affect human health indirectly. The use of combined drugs replacement therapy and the long-term coexistence with drug-resistant bacteria are the reality that human beings have to face in dealing with the problem of antibiotic resistance in the future. This study showed the characteristics and trends through abundant results of combined effects related with the combinations of antibiotic and the combinations of antibiotic and phytochemical on A. hydrophila, and revealed the antagonism probability of combinations of antibiotic and phytochemical is significantly higher than that of the combinations of antibiotic. Meanwhile, the combinations of antibiotic and phytochemical could protect the host cells which also achieved the same effectiveness as combination of antibiotics, and the enrichment pathway was proved to be relatively discrete. In addition, the possible mechanism about the reverse "U" shape of the combined effect curve on wild/antibiotic-resistant bacteria was clarified, and it was confirmed that the antagonism for the combinations of antibiotic and phytochemical might has the significance in inhibiting the evolution of bacterial resistance mutations. This study was aims to provide theoretical basis and some clues for the antibiotic resistance control associated with A. hydrophila.

The effect of combining antibiotics on resistance: A systematic review and meta-analysis

When and under which conditions antibiotic combination therapy decelerates rather than accelerates resistance evolution is not well understood. We examined the effect of combining antibiotics on within-patient resistance development across various bacterial pathogens and antibiotics. We searched CENTRAL, EMBASE and PubMed for (quasi)-randomised controlled trials (RCTs) published from database inception to November 24th, 2022. Trials comparing antibiotic treatments with different numbers of antibiotics were included. A patient was considered to have acquired resistance if, at the follow-up culture, a resistant bacterium (as defined by the study authors) was detected that had not been present in the baseline culture. We combined results using a random effects model and performed meta-regression and stratified analyses. The trials' risk of bias was assessed with the Cochrane tool. 42 trials were eligible and 29, including 5054 patients, were qualified for statistical analysis. In most trials, resistance development was not the primary outcome and studies lacked power. The combined odds ratio (OR) for the acquisition of resistance comparing the group with the higher number of antibiotics with the comparison group was 1.23 (95% CI 0.68-2.25), with substantial between-study heterogeneity (I 2 =77%). We identified tentative evidence for potential beneficial or detrimental effects of antibiotic combination therapy for specific pathogens or medical conditions. The evidence for combining a higher number of antibiotics compared to fewer from RCTs is scarce and overall, is compatible with both benefit or harm. Trials powered to detect differences in resistance development or well-designed observational studies are required to clarify the impact of combination therapy on resistance.

Phage-induced efflux down-regulation boosts antibiotic efficacy

The interactions between a virus and its host vary in space and time and are affected by the presence of molecules that alter the physiology of either the host or the virus. Determining the molecular mechanisms at the basis of these interactions is paramount for predicting the fate of bacterial and phage populations and for designing rational phage-antibiotic therapies. We study the interactions between stationary phase Burkholderia thailandensis and the phage ΦBp-AMP1. Although heterogeneous genetic resistance to phage rapidly emerges in B. thailandensis, the presence of phage enhances the efficacy of three major antibiotic classes, the quinolones, the beta-lactams and the tetracyclines, but antagonizes tetrahydrofolate synthesis inhibitors. We discovered that enhanced antibiotic efficacy is facilitated by reduced antibiotic efflux in the presence of phage. This new phage-antibiotic therapy allows for eradication of stationary phase bacteria, whilst requiring reduced antibiotic concentrations, which is crucial for treating infections in sites where it is difficult to achieve high antibiotic concentrations.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Therapeutic developments for tuberculosis and nontuberculous mycobacterial lung disease

Tuberculosis (TB) drug discovery and development has undergone nothing short of a revolution over the past 20 years. Successful public-private partnerships and sustained funding have delivered a much-improved understanding of mycobacterial disease biology and pharmacology and a healthy pipeline that can tolerate inevitable attrition. Preclinical and clinical development has evolved from decade-old concepts to adaptive designs that permit rapid evaluation of regimens that might greatly shorten treatment duration over the next decade. But the past 20 years also saw the rise of a fatal and difficult-to-cure lung disease caused by nontuberculous mycobacteria (NTM), for which the drug development pipeline is nearly empty. Here, we discuss the similarities and differences between TB and NTM lung diseases, compare the preclinical and clinical advances, and identify major knowledge gaps and areas of cross-fertilization. We argue that applying paradigms and networks that have proved successful for TB, from basic research to clinical trials, will help to populate the pipeline and accelerate curative regimen development for NTM disease.

Within-species variability of antibiotic interactions in Gram-negative bacteria

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.

The Biofilm Lifestyle Shapes the Evolution of β-Lactamases

The evolutionary relationship between the biofilm lifestyle and antibiotic resistance enzymes remains a subject of limited understanding. Here, we investigate how β-lactamases affect biofilm formation in Vibrio cholerae and how selection for a biofilm lifestyle impacts the evolution of these enzymes. Genetically diverse β-lactamases expressed in V. cholerae displayed a strong inhibitory effect on biofilm production. To understand how natural evolution affects this antagonistic pleiotropy, we randomly mutagenized a β-lactamase and selected for elevated biofilm formation. Our results revealed that biofilm evolution selects for β-lactamase variants able to hydrolyze β-lactams without inhibiting biofilms. Mutational analysis of evolved variants demonstrated that restoration of biofilm development was achieved either independently of enzymatic function or by actively leveraging enzymatic activity. Taken together, the biofilm lifestyle can impose a profound selective pressure on antimicrobial resistance enzymes. Shedding light on such evolutionary interplays is of importance to understand the factors driving antimicrobial resistance.

Strategies to Promote the Journey of Nanoparticles Against Biofilm-Associated Infections

Biofilm-associated infections are one of the most challenging healthcare threats for humans, accounting for 80% of bacterial infections, leading to persistent and chronic infections. The conventional antibiotics still face their dilemma of poor therapeutic effects due to the high tolerance and resistance led by bacterial biofilm barriers. Nanotechnology-based antimicrobials, nanoparticles (NPs), are paid attention extensively and considered as promising alternative. This review focuses on the whole journey of NPs against biofilm-associated infections, and to clarify it clearly, the journey is divided into four processes in sequence as 1) Targeting biofilms, 2) Penetrating biofilm barrier, 3) Attaching to bacterial cells, and 4) Translocating through bacterial cell envelope. Through outlining the compositions and properties of biofilms and bacteria cells, recent advances and present the strategies of each process are comprehensively discussed to combat biofilm-associated infections, as well as the combined strategies against these infections with drug resistance, aiming to guide the rational design and facilitate wide application of NPs in biofilm-associated infections.

Antimicrobial Agent Functional Gold Nanocluster-Mediated Multichannel Sensor Array for Bacteria Sensing

Urinary tract infections (UTIs) have greatly affected human health in recent years. Accurate and rapid diagnosis of UTIs can enable a more effective treatment. Herein, we developed a multichannel sensor array for efficient identification of bacteria based on three antimicrobial agents (vancomycin, lysozyme, and bacitracin) functional gold nanoclusters (AuNCs). In this sensor, the fluorescence intensity of the three AuNCs was quenched to varying degrees by the bacterial species, providing a unique fingerprint for different bacteria. With this sensing platform, seven pathogenic bacteria, different concentrations of the same bacteria, and even bacterial mixtures were successfully differentiated. Furthermore, UTIs can be accurately identified with our sensors in ∼30 min with 100% classification accuracy. The proposed sensing systems offer a rapid, high-throughput, and reliable sensing platform for the diagnosis of UTIs.

Gene expression tradeoffs determine bacterial survival and adaptation to antibiotic stress

To optimize their fitness, cells face the crucial task of efficiently responding to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and division. The fundamental principles governing these tradeoffs is an outstanding challenge in the physics of living systems. In this study, we introduce a coarse-grained theoretical framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the Minimum Inhibitory Concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed theoretical model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Gene Expression Tradeoffs Determine Bacterial Survival and Adaptation to Antibiotic Stress

To optimize their fitness, cells face the crucial task of efficiently responding to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and division. The fundamental principles governing these tradeoffs is an outstanding challenge in the physics of living systems. In this study, we introduce a coarse-grained theoretical framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the minimum inhibitory concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed theoretical model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC, and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Aminoglycoside uptake, stress, and potentiation in Gram-negative bacteria: new therapies with old molecules

SUMMARYAminoglycosides (AGs) are long-known molecules successfully used against Gram-negative pathogens. While their use declined with the discovery of new antibiotics, they are now classified as critically important molecules because of their effectiveness against multidrug-resistant bacteria. While they can efficiently cross the Gram-negative envelope, the mechanism of AG entry is still incompletely understood, although this comprehension is essential for the development of new therapies in the face of the alarming increase in antibiotic resistance. Increasing antibiotic uptake in bacteria is one strategy to enhance effective treatments. This review aims, first, to consolidate old and recent knowledge about AG uptake; second, to explore the connection between AG-dependent bacterial stress and drug uptake; and finally, to present new strategies of potentiation of AG uptake for more efficient antibiotic therapies. In particular, we emphasize on the connection between sugar transport and AG potentiation.

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotic effectiveness depends on a variety of factors. While many mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. A common observation is that death rate in antibiotics rises linearly with growth rate; however, it remains unclear how other factors, such as environmental conditions and whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Growth under stress lowers death rate compared to nonstressed environments with similar growth rate. To understand stress's role, we developed a mathematical model of bacterial death based on resource allocation that includes a stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the minimal inhibitory concentration (MIC) with zero free parameters across a wide range of growth conditions. The model also quantitatively predicts death and MIC when sectors are experimentally modulated using cyclic adenosine monophosphate (cAMP), including protection from death at very low cAMP levels. The present study shows that different conditions with equal growth rate can have different death rates and establishes a quantitative relation between growth, death, and MIC that suggests approaches to improve antibiotic efficacy.

Azithromycin induces neurotoxicity in zebrafish by interfering with the VEGF/Notch signaling pathway

Azithromycin (AZM) is a widely used antibiotic in both human and veterinary medicine, and its use has significantly increased during the COVID-19 pandemic. However, potential adverse effects of AZM on aquatic organisms have not been well studied. In this study, we explored the neurotoxicity of AZM in zebrafish and delved into its underlying mechanisms. Our results showed that AZM exposure resulted in a spectrum of detrimental effects in zebrafish, encompassing abnormal behaviors, damaged neuronal development, aberrant lateral line nervous system development, vascular malformations and perturbed expression of genes related to neural development. Moreover, we observed a concentration-dependent exacerbation of these neurotoxic manifestations with increasing AZM concentrations. Notably, AZM induced excessive cell apoptosis and oxidative stress damage. In addition, alterations in the expression levels of the genes involved in the VEGF/Notch signaling pathway were evident in AZM-exposed zebrafish. Consequently, we hypothesize that AZM may induce neurotoxicity by influencing the VEGF/Notch signaling pathway. To validate this hypothesis, we introduced a VEGF signaling inhibitor, axitinib, and a Notch signaling agonist, valproic acid, alongside AZM exposure. Remarkably, the administration of these rescue compounds significantly mitigated the neurotoxic effects induced by AZM. This dual verification provides compelling evidence that AZM indeed induces neurotoxicity during the early developmental stages of zebrafish, primarily through its interference with the VEGF/Notch pathway. Innovatively, our study reveals the molecular mechanism of AZM-induced neurotoxicity from the perspective of the close connection between blood vessels and nervous system. These findings provide new insights into the potential mechanisms underlying the neurotoxic effect of antibiotics and highlight the need for further investigation into the ecotoxicological effects of antibiotics on aquatic organisms and the potential risks to human health.

Steering and controlling evolution - from bioengineering to fighting pathogens

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Key genes of electron transfer, the nitrogen cycle and tetracycline removal in bioelectrochemical systems

BACKGROUND

Soil microbial fuel cells (MFCs) can remove antibiotics and antibiotic resistance genes (ARGs) simultaneously, but their removal mechanism is unclear. In this study, metagenomic analysis was employed to reveal the functional genes involved in degradation, electron transfer and the nitrogen cycle in the soil MFC.

RESULTS

The results showed that the soil MFC effectively removed tetracycline in the overlapping area of the cathode and anode, which was 64% higher than that of the control. The ARGs abundance increased by 14% after tetracycline was added (54% of the amplified ARGs belonged to efflux pump genes), while the abundance decreased by 17% in the soil MFC. Five potential degraders of tetracycline were identified, especially the species Phenylobacterium zucineum, which could secrete the 4-hydroxyacetophenone monooxygenase encoded by EC 1.14.13.84 to catalyse deacylation or decarboxylation. Bacillus, Geobacter, Anaerolinea, Gemmatirosa kalamazoonesis and Steroidobacter denitrificans since ubiquinone reductase (encoded by EC 1.6.5.3), succinate dehydrogenase (EC 1.3.5.1), Coenzyme Q-cytochrome c reductase (EC 1.10.2.2), cytochrome-c oxidase (EC 1.9.3.1) and electron transfer flavoprotein-ubiquinone oxidoreductase (EC 1.5.5.1) served as complexes I, II, III, IV and ubiquinone, respectively, to accelerate electron transfer. Additionally, nitrogen metabolism-related gene abundance increased by 16% to support the microbial efficacy in the soil MFC, and especially EC 1.7.5.1, and coding the mutual conversion between nitrite and nitrate was obviously improved.

CONCLUSIONS

The soil MFC promoted functional bacterial growth, increased functional gene abundance (including nitrogen cycling, electron transfer, and biodegradation), and facilitated antibiotic and ARG removal. Therefore, soil MFCs have expansive prospects in the remediation of antibiotic-contaminated soil. This study provides insight into the biodegradation mechanism at the gene level in soil bioelectrochemical remediation.

Systematic analysis of drug combinations against Gram-positive bacteria

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/ ).

A photoactivatable and phenylboronic acid-functionalized nanoassembly for combating multidrug-resistant gram-negative bacteria and their biofilms

Background

Multidrug-resistant (MDR) gram-negative bacteria-related infectious diseases have caused an increase in the public health burden and mortality. Moreover, the formation of biofilms makes these bacteria difficult to control. Therefore, developing novel interventions to combat MDR gram-negative bacteria and their biofilms-related infections are urgently needed. The purpose of this study was to develop a multifunctional nanoassembly (IRNB) based on IR-780 and N, N'-di-sec-butyl-N, N'- dinitroso-1,4-phenylenediamine (BNN6) for synergistic effect on the infected wounds and subcutaneous abscesses caused by gram-negative bacteria.

Methods

The characterization and bacteria-targeting ability of IRNB were investigated. The bactericidal efficacy of IRNB against gram-negative bacteria and their biofilms was demonstrated by crystal violet staining assay, plate counting method and live/dead staining in vitro. The antibacterial efficiency of IRNB was examined on a subcutaneous abscess and cutaneous infected wound model in vivo. A cell counting kit-8 assay, Calcein/PI cytotoxicity assay, hemolysis assay and intravenous injection assay were performed to detect the biocompatibility of IRNB in vitro and in vivo.

Results

Herein, we successfully developed a multifunctional nanoassembly IRNB based on IR-780 and BNN6 for synergistic photothermal therapy (PTT), photodynamic therapy (PDT) and nitric oxide (NO) effect triggered by an 808 nm laser. This nanoassembly could accumulate specifically at the infected sites of MDR gram-negative bacteria and their biofilms via the covalent coupling effect. Upon irradiation with an 808 nm laser, IRNB was activated and produced both reactive oxygen species (ROS) and hyperthermia. The local hyperthermia could induce NO generation, which further reacted with ROS to generate ONOO-, leading to the enhancement of bactericidal efficacy. Furthermore, NO and ONOO- could disrupt the cell membrane, which converts bacteria to an extremely susceptible state and further enhances the photothermal effect. In this study, IRNB showed a superior photothermal-photodynamic-chemo (NO) synergistic therapeutic effect on the infected wounds and subcutaneous abscesses caused by gram-negative bacteria. This resulted in effective control of associated infections, relief of inflammation, promotion of re-epithelization and collagen deposition, and regulation of angiogenesis during wound healing. Moreover, IRNB exhibited excellent biocompatibility, both in vitro and in vivo.

Conclusions

The present research suggests that IRNB can be considered a promising alternative for treating infections caused by MDR gram-negative bacteria and their biofilms.

Strategies for applying probiotics in the antibiotic management of Clostridioides difficile infection

The vital role of probiotics in the food field has been widely recognized, and at the same time, probiotics are gradually exhibiting surprising effects in the field of nutraceuticals, especially in regulating gut inflammation and the nutritional environment. As a dietary supplement in clinical nutrition, the coadministration of probiotics with antibiotics model has been applied to prevent intestinal infections caused by Clostridioides difficile. However, the mechanism behind this "bacteria-drug combination" model remains unclear. In particular, the selection of specific probiotic strains, the order of probiotics or antibiotics, and the time interval of coadministration are key issues that need to be further explored and clarified. Here, we focus on the issues mentioned above and give reasonable opinions, mainly including: (1) probiotics are safer and more effective when they intervene after antibiotics have been used; (2) the choice of the time interval between coadministration should be based on the metabolism of antibiotics in the host, differences in probiotic strains, the baseline ecological environment of the host's intestine, and the host immune level; in addition, the selection of the coadministration regime should also take into account factors such as the antibiotic sensitivity of probiotics and dosage of probiotics; and (3) by encapsulating probiotics, combining probiotics with prebiotics, and developing next-generation probiotics (NGPs) and postbiotic formulations, we can provide a more reasonable reference for this type of "bacteria-drug combination" model, and also provide targeted guidance for the application of probiotic dietary supplements in the antibiotic management of C. difficile infection.

Translating eco-evolutionary biology into therapy to tackle antibiotic resistance

Antibiotic resistance is currently one of the most important public health problems. The golden age of antibiotic discovery ended decades ago, and new approaches are urgently needed. Therefore, preserving the efficacy of the antibiotics currently in use and developing compounds and strategies that specifically target antibiotic-resistant pathogens is critical. The identification of robust trends of antibiotic resistance evolution and of its associated trade-offs, such as collateral sensitivity or fitness costs, is invaluable for the design of rational evolution-based, ecology-based treatment approaches. In this Review, we discuss these evolutionary trade-offs and how such knowledge can aid in informing combination or alternating antibiotic therapies against bacterial infections. In addition, we discuss how targeting bacterial metabolism can enhance drug activity and impair antibiotic resistance evolution. Finally, we explore how an improved understanding of the original physiological function of antibiotic resistance determinants, which have evolved to reach clinical resistance after a process of historical contingency, may help to tackle antibiotic resistance.

Comparative De Novo and Pan-Genome Analysis of MDR Nosocomial Bacteria Isolated from Hospitals in Jeddah, Saudi Arabia

Multidrug-resistant (MDR) bacteria are one of the most serious threats to public health, and one of the most important types of MDR bacteria are those that are acquired in a hospital, known as nosocomial. This study aimed to isolate and identify MDR bacteria from selected hospitals in Jeddah and analyze their antibiotic-resistant genes. Bacteria were collected from different sources and wards of hospitals in Jeddah City. Phoenix BD was used to identify the strains and perform susceptibility testing. Identification of selected isolates showing MDR to more than three classes on antibiotics was based on 16S rRNA gene and whole genome sequencing. Genes conferring resistance were characterized using de novo and pan-genome analyses. In total, we isolated 108 bacterial strains, of which 75 (69.44%) were found to be MDR. Taxonomic identification revealed that 24 (32%) isolates were identified as Escherichia coli, 19 (25.3%) corresponded to Klebsiella pneumoniae, and 17 (22.67%) were methicillin-resistant Staphylococcus aureus (MRSA). Among the Gram-negative bacteria, K. pneumoniae isolates showed the highest resistance levels to most antibiotics. Of the Gram-positive bacteria, S. aureus (MRSA) strains were noticed to exhibit the uppermost degree of resistance to the tested antibiotics, which is higher than that observed for K. pneumoniae isolates. Taken together, our results illustrated that MDR Gram-negative bacteria are the most common cause of nosocomial infections, while MDR Gram-positive bacteria are characterized by a wider antibiotic resistance spectrum. Whole genome sequencing found the appearance of antibiotic resistance genes, including SHV, OXA, CTX-M, TEM-1, NDM-1, VIM-1, ere(A), ermA, ermB, ermC, msrA, qacA, qacB, and qacC.

Murepavadin induces envelope stress response and enhances the killing efficacies of β-lactam antibiotics by impairing the outer membrane integrity of Pseudomonas aeruginosa

Pseudomonas aeruginosa is a ubiquitous opportunistic pathogen that can cause a variety of acute and chronic infections. The bacterium is highly resistant to numerous antibiotics. Murepavadin is a peptidomimetic antibiotic that blocks the function of P. aeruginosa lipopolysaccharide (LPS) transport protein D (LptD), thus inhibiting the insertion of LPS into the outer membrane. In this study, we demonstrated that sublethal concentrations of murepavadin enhance the bacterial outer membrane permeability. Proteomic analyses revealed the alteration of protein composition in bacterial inner and outer membranes following murepavadin treatment. The antisigma factor MucA was upregulated by murepavadin. In addition, the expression of the sigma E factor gene algU and the alginate synthesis gene algD was induced by murepavadin. Deletion of the algU gene reduces bacterial survival following murepavadin treatment, indicating a role of the envelope stress response in bacterial tolerance. We further demonstrated that murepavadin enhances the bactericidal activities of β-lactam antibiotics by promoting drug influx across the outer membrane. In a mouse model of acute pneumonia, the murepavadin-ceftazidime/avibactam combination showed synergistic therapeutic effect against P. aeruginosa infection. In addition, the combination of murepavadin with ceftazidime/avibactam slowed down the resistance development. In conclusion, our results reveal the response mechanism of P. aeruginosa to murepavadin and provide a promising antibiotic combination for the treatment of P. aeruginosa infections.IMPORTANCEThe ever increasing resistance of bacteria to antibiotics poses a serious threat to global public health. Novel antibiotics and treatment strategies are urgently needed. Murepavadin is a novel antibiotic that blocks the assembly of lipopolysaccharide (LPS) into the Pseudomonas aeruginosa outer membrane by inhibiting LPS transport protein D (LptD). Here, we demonstrated that murepavadin impairs bacterial outer membrane integrity, which induces the envelope stress response. We further found that the impaired outer membrane integrity increases the influx of β-lactam antibiotics, resulting in enhanced bactericidal effects. In addition, the combination of murepavadin and a β-lactam/β-lactamase inhibitor mixture (ceftazidime/avibactam) slowed down the resistance development of P. aeruginosa. Overall, this study demonstrates the bacterial response to murepavadin and provides a new combination strategy for effective treatment.

Recent Progress of Photothermal Therapy Based on Conjugated Nanomaterials in Combating Microbial Infections

Photothermal therapy has the advantages of non-invasiveness, low toxicity, simple operation, a broad spectrum of antibacterial ability, and non-proneness to developing drug resistance, which provide it with irreplaceable superiority in fighting against microbial infection. The effect of photothermal therapy is closely related to the choice of photothermal agent. Conjugated nanomaterials are potential candidates for photothermal agents because of their easy modification, excellent photothermal conversion efficiency, good photostability, and biodegradability. In this paper, the application of photothermal agents based on conjugated nanomaterials in photothermal antimicrobial treatment is reviewed, including conjugated small molecules, conjugated oligomers, conjugated polymers, and pseudo-conjugated polymers. At the same time, the application of conjugated nanomaterials in the combination of photothermal therapy (PTT) and photodynamic therapy (PDT) is briefly introduced. Finally, the research status, limitations, and prospects of photothermal therapy using conjugated nanomaterials as photothermal agents are discussed.

A comprehensive and global evaluation of residual antibiotics in agricultural soils: Accumulation, potential ecological risks, and attenuation strategies

The occurrence of antibiotics in agricultural soils has raised concerns due to their potential risks to ecosystems and human health. However, a comprehensive understanding of antibiotic accumulation, distribution, and potential risks to terrestrial ecosystems on a global scale is still limited. Therefore, in this study, we evaluated the accumulation of antibiotics and their potential risks to soil microorganisms and plants, and highlighted the driving factors of antibiotic accumulation in agricultural soils based on 134 peer-reviewed studies (between 2000 and 2022). The results indicated that 56 types of antibiotics were detected at least once in agricultural soils with concentrations ranging from undetectable to over 7000 µg/kg. Doxycycline, tylosin, sulfamethoxazole, and enrofloxacin, belonging to the tetracyclines, macrolides, sulfonamides, and fluoroquinolones, respectively, were the most accumulated antibiotics in agricultural soil. The accumulation of TCs, SAs, and FQs was found to pose greater risks to soil microorganisms (average at 29.3%, 15.4%, and 21.8%) and plants (42.4%, 26.0%, and 38.7%) than other antibiotics. East China was identified as a hot spot for antibiotic contamination due to high levels of antibiotic concentration and ecological risk to soil microorganisms and plants. Antibiotic accumulation was found to be higher in vegetable fields (245.5 µg/kg) and orchards (212.4 µg/kg) compared to croplands (137.2 µg/kg). Furthermore, direct land application of manure resulted in a greater accumulation of TCs, SAs, and FQs accumulation in soils than compost fertilization. The level of antibiotics decreased with increasing soil pH and organic matter content, attributed to decreasing adsorption and enhancing degradation of antibiotics. In conclusion, this study highlights the need for further research on the impacts of antibiotics on soil ecological function in agricultural fields and their interaction mechanisms. Additionally, a whole-chain approach, consisting of antibiotic consumption reduction, manure management strategies, and remediation technology for soil contaminated with antibiotics, is needed to eliminate the potential environmental risks of antibiotics for sustainable and green agriculture.

Insights into the central role of N-acetyl-glucosamine-1-phosphate uridyltransferase (GlmU) in peptidoglycan metabolism and its potential as a therapeutic target

Several decades after the discovery of the first antibiotic (penicillin) microbes have evolved novel mechanisms of resistance; endangering not only our abilities to combat future bacterial pandemics but many other clinical challenges such as acquired infections during surgeries. Antimicrobial resistance (AMR) is attributed to the mismanagement and overuse of these medications and is complicated by a slower rate of the discovery of novel drugs and targets. Bacterial peptidoglycan (PG), a three-dimensional mesh of glycan units, is the foundation of the cell wall that protects bacteria against environmental insults. A significant percentage of drugs target PG, however, these have been rendered ineffective due to growing drug resistance. Identifying novel druggable targets is, therefore, imperative. Uridine diphosphate N-acetylglucosamine (UDP-GlcNAc) is one of the key building blocks in PG production, biosynthesized by the bifunctional enzyme N-acetyl-glucosamine-1-phosphate uridyltransferase (GlmU). UDP-GlcNAc metabolism has been studied in many organisms, but it holds some distinctive features in bacteria, especially regarding the bacterial GlmU enzyme. In this review, we provide an overview of different steps in PG biogenesis, discuss the biochemistry of GlmU, and summarize the characteristic structural elements of bacterial GlmU vital to its catalytic function. Finally, we will discuss various studies on the development of GlmU inhibitors and their significance in aiding future drug discoveries.

Mutators can drive the evolution of multi-resistance to antibiotics

Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with 'mutators', organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic-under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.

New antifungal strategies: drug combination and co-delivery

The growing occurrence of invasive fungal infections and the mounting rates of drug resistance constitute a significant menace to human health. Antifungal drug combinations have garnered substantial interest for their potential to improve therapeutic efficacy, reduce drug doses, reverse, or ameliorate drug resistance. A thorough understanding of the molecular mechanisms underlying antifungal drug resistance and drug combination is key to developing new drug combinations. Here we discuss the mechanisms of antifungal drug resistance and elucidate how to discover potent drug combinations to surmount resistance. We also examine the challenges encountered in developing such combinations and discuss prospects, including advanced drug delivery strategies.

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.

Collateral Sensitivity to Fosfomycin of Tobramycin-Resistant Mutants of Pseudomonas aeruginosa Is Contingent on Bacterial Genomic Background

Understanding the consequences in bacterial physiology of the acquisition of drug resistance is needed to identify and exploit the weaknesses derived from it. One of them is collateral sensitivity, a potentially exploitable phenotype that, unfortunately, is not always conserved among different isolates. The identification of robust, conserved collateral sensitivity patterns is then relevant for the translation of this knowledge into clinical practice. We have previously identified a robust fosfomycin collateral sensitivity pattern of Pseudomonas aeruginosa that emerged in different tobramycin-resistant clones. To go one step further, here, we studied if the acquisition of resistance to tobramycin is associated with robust collateral sensitivity to fosfomycin among P. aeruginosa isolates. To that aim, we analyzed, using adaptive laboratory evolution approaches, 23 different clinical isolates of P. aeruginosa presenting diverse mutational resistomes. Nine of them showed collateral sensitivity to fosfomycin, indicating that this phenotype is contingent on the genetic background. Interestingly, collateral sensitivity to fosfomycin was linked to a larger increase in tobramycin minimal inhibitory concentration. Further, we unveiled that fosA low expression, rendering a higher intracellular accumulation of fosfomycin, and a reduction in the expression of the P. aeruginosa alternative peptidoglycan-recycling pathway enzymes, might be on the basis of the collateral sensitivity phenotype.

Constructed wetlands as hotspots of antibiotic resistance genes and pathogens: Evidence from metagenomic analysis in Chinese rural areas

In rural China, many constructed wetlands (CWs) have been developed to treat rural wastewater sustainably. However, due to the scarce information on those rural CWs, it is difficult to analyze the biological contaminants within those systems, such as antibiotic resistance genes (ARGs) and pathogens. Based on the data collected from two pilot-scale, one-year-observed CWs, for the first time, this study explored the accumulation of ARGs and pathogens using the metagenomic sequencing approach and SourceTracker analysis under different hydraulic loading rates. The Shannon index of ARGs in the effluent surpassed the level found in the influent. The DESeq2 analysis showed that up to 21.49% of the total pathogen species had increased relative abundance in the effluent compared with the influent. By combining the contribution of substrate and rhizosphere, the CW became a more influencing factor for ARGs and pathogens contamination than the influent. The network analysis revealed a critical but latent fact that the development of antibiotic-resistant pathogens is highly likely to be triggered by the co-occurrence of ARGs and pathogens. Collectively, from the aspect of biological risk, our study showed that CWs alone might not be an ideal solution for improving wastewater treatment in rural China.

Heterogeneous Distribution of Proton Motive Force in Nonheritable Antibiotic Resistance

Bacterial infections that are difficult to eradicate are often treated by sequentially exposing the bacteria to different antibiotics. Although effective, this approach can give rise to epigenetic or other phenomena that may help some cells adapt to and tolerate the antibiotics. Characteristics of such adapted cells are dormancy and low energy levels, which promote survival without lending long-term genetic resistance against antibiotics. In this work, we quantified motility in cells of Escherichia coli that adapted and survived sequential exposure to lethal doses of antibiotics. In populations that adapted to transcriptional inhibition by rifampicin, we observed that ~1 of 3 cells continued swimming for several hours in the presence of lethal concentrations of ampicillin. As motility is powered by proton motive force (PMF), our results suggested that many adapted cells retained a high PMF. Single-cell growth assays revealed that the high-PMF cells resuscitated and divided upon the removal of ampicillin, just as the low-PMF cells did, a behavior reminiscent of persister cells. Our results are consistent with the notion that cells in a clonal population may employ multiple different mechanisms to adapt to antibiotic stresses. Variable PMF is likely a feature of a bet-hedging strategy: a fraction of the adapted cell population lies dormant while the other fraction retains high PMF to be able to swim out of the deleterious environment. IMPORTANCE Bacterial cells with low PMF may survive antibiotic stress due to dormancy, which favors nonheritable resistance without genetic mutations or acquisitions. On the other hand, cells with high PMF are less tolerant, as PMF helps in the uptake of certain antibiotics. Here, we quantified flagellar motility as an indirect measure of the PMF in cells of Escherichia coli that had adapted to ampicillin. Despite the disadvantage of maintaining a high PMF in the presence of antibiotics, we observed high PMF in ~30% of the cells, as evidenced by their ability to swim rapidly for several hours. These and other results were consistent with the idea that antibiotic tolerance can arise via different mechanisms in a clonal population.

Chemical Basis of Combination Therapy to Combat Antibiotic Resistance

The antimicrobial resistance crisis is a global health issue requiring discovery and development of novel therapeutics. However, conventional screening of natural products or synthetic chemical libraries is uncertain. Combination therapy using approved antibiotics with inhibitors targeting innate resistance mechanisms provides an alternative strategy to develop potent therapeutics. This review discusses the chemical structures of effective β-lactamase inhibitors, outer membrane permeabilizers, and efflux pump inhibitors that act as adjuvant molecules of classical antibiotics. Rational design of the chemical structures of adjuvants will provide methods to impart or restore efficacy to classical antibiotics for inherently antibiotic-resistant bacteria. As many bacteria have multiple resistance pathways, adjuvant molecules simultaneously targeting multiple pathways are promising approaches to combat multidrug-resistant bacterial infections.