Collective antibiotic resistance: mechanisms and implications

Quorum sensing inhibitors (QSIs): a patent review (2019-2023)

INTRODUCTION

The collective behavior of bacteria is regulated by Quorum Sensing (QS), in which bacteria release chemical signals and express virulence genes in a cell density-dependent manner. Quorum Sensing inhibitors (QSIs) are a large class of natural and synthetic compounds that have the potential to competitively inhibit the Quorum Sensing (QS) systems of several pathogens blocking their virulence mechanisms. They are considered promising compounds to deal with antimicrobial resistance, providing an opportunity to develop new drugs against these targets.

AREAS COVERED

The present review represents a comprehensive analysis of patents and patent applications available on Espacenet and Google Patent, from 2019 to 2023 referring to the therapeutic use of Quorum Sensing inhibitors.

EXPERT OPINION

Unlike classical antibiotics, which target the basic cellular metabolic processes, QSIs provide a promising alternative to attenuating virulence and pathogenicity without putting selective pressure on bacteria. The general belief is that QSIs pose no or little selective pressure on bacteria since these do not affect their growth. To date, QSIs are seen as the most promising alternative to traditional antibiotics. The next big step in this area of research is its succession to the clinical stage.

Understanding the bovine mastitis co-infections: Coexistence with Enterobacter alters S. aureus antibiotic susceptibility and virulence phenotype

The World Health Organization recently reported an alarming evolution and spread of antibiotic resistance, a global risk factor recognized as a One Health challenge. In veterinary, the general lack of clear treatment guidelines often leads to antibiotic misuse. Bovine mastitis is responsible for major economic losses and the main cause of antibiotic administration in the dairy industry, favoring the emergence of multi-resistant phenotypes. The complexity of inter-microbial and host-pathogen interactions in the mammary gland, demonstrated by culture-independent techniques, not only complicates the prediction of antibiotic treatment outcomes but also underscores the urgent need for further research in this field. This work evaluated the interactions between S. aureus L33 and Enterobacter sp. L34 obtained from an intramammary co-infection. The behavior of the dual-species culture resembled that of the Enterobacter monoculture in all the evaluated contexts. Most of the selected S. aureus virulence factors and the antibiotic susceptibility were altered by coexisting with Enterobacter. Under the protection of Enterobacter, S. aureus was able to survive upon exposure to concentrations of cloxacillin and other antibiotics that would be bactericidal for the monoculture. This could have serious implications for bacterial clearance of mastitis originating from the underestimated co-infections. These findings highlight the importance of broadening our knowledge of how microbial interactions in intramammary infections could contribute to antibiotic treatments failures. Moreover, they open new perspectives for the design of bovine mastitis therapies that consider the ecological context in order to optimize the antibiotic usage, improve the success rates and reduce antibiotic resistance.

Spatial population dynamics of bacterial colonies with social antibiotic resistance

Bacteria frequently inhabit surface-attached communities where rich "social" interactions can significantly alter their population-level behavior, including their response to antibiotics. Understanding these collective effects in spatially heterogeneous communities is an ongoing challenge. Here, we investigated the spatial organization that emerges from antibiotic exposure in initially randomly distributed communities containing antibiotic-resistant and -sensitive strains of Enterococcus faecalis, an opportunistic pathogen. We identified that a range of complex spatial structures emerged in the population homeland-the inoculated region that microbes inhabit prior to range expansion-which depended on initial colony composition and antibiotic concentration. We found that these arrangements were explained by cooperative interactions between resistant and sensitive subpopulations with a variable spatial scale, the result of dynamic zones of protection afforded to sensitive cells by growing populations of enzyme-producing resistant neighbors. Using a combination of experiments and mathematical models, we explored the complex spatiotemporal interaction dynamics that create these patterns, and predicted spatial arrangements of sensitive and resistant subpopulations under new conditions. We illustrated how spatial population dynamics in the homeland affect subsequent range expansion, both because they modulate the composition of the initial expanding front, and through long-range cooperation between the homeland and the expanding region. Finally, we showed that these spatial constraints resulted in populations whose size and composition differed markedly from matched populations in well-stirred (planktonic) cultures. These findings underscore the importance of spatial structure and cooperation, long-studied features in theoretical ecology, for determining the fate of bacterial communities under antibiotic exposure.

Pooled Antibiotic Susceptibility Testing for Polymicrobial UTI Performs Within CLSI Validation Standards

BACKGROUND/OBJECTIVES

Urinary tract infections (UTIs) pose an increasing risk of antimicrobial resistance, and novel diagnostic tests have been developed to address the limitations of standard urine culture in these cases. It is important that these novel tests be validated for agreement and error rates against the standard antibiotic susceptibility testing (AST) methods.

METHODS

Polymicrobial (≥two non-fastidious microorganisms) consecutive clinical urine specimens submitted for UTI diagnostic testing were included in this analysis. Specimens were tested with Pooled Antibiotic Susceptibility Testing (P-AST) and with broth microdilution/disk diffusion (BMD/DD) in parallel. Performance characteristics, such as essential agreement (EA%), very major errors (VMEs), and major errors (MEs), were assessed using Clinical and Laboratory Standards Institute (CLSI) standards. Specimens with P-AST-resistant and BMD/DD consensus-sensitive results were assessed for heteroresistance. Real-world clinical sample data were used to assess associations between increasing organism counts and average "sensitive" antibiotic count per sample.

RESULTS

The essential agreement between P-AST and standard isolate AST was ≥90%, VMEs were <2.0%, and MEs were <3.0%, meeting the CLSI guidelines for AST verification and validation studies. When heteroresistance was accounted for, overall VMEs and MEs were both <1.5%. The presence of additional non-fastidious organisms dropped the number of average "sensitive" antibiotics from 9.8 with one organism to 2.5 with five or more organisms. The presence of fastidious organisms did not have any meaningful impact.

CONCLUSIONS

P-AST, a component of the Guidance® UTI assay (Pathnostics, Irvine, CA, USA), performed within CLSI standards for AST in polymicrobial UTI diagnostic urine specimens.

Habitat fragmentation enhances microbial collective defence

Microbes often inhabit complex, spatially partitioned environments such as host tissue or soil, but the effects of habitat fragmentation on microbial ecology and infection dynamics are poorly understood. Here, we investigate how habitat fragmentation impacts a prevalent microbial collective defence mechanism: enzymatic degradation of an environmental toxin. Using a theoretical model, we predict that habitat fragmentation can strongly enhance the collective benefits of enzymatic toxin degradation. For the example of [Formula: see text]-lactamase-producing bacteria that mount a collective defence by degrading a [Formula: see text]-lactam antibiotic, we find that realistic levels of habitat fragmentation can allow a population to survive antibiotic doses that greatly exceed those required to kill a non-fragmented population. This 'habitat-fragmentation rescue' is a stochastic effect that originates from variation in bacterial density among different subpopulations and demographic noise. We also study the contrasting case of collective enzymatic foraging, where enzyme activity releases nutrients from the environment; here we find that increasing habitat fragmentation decreases the lag time for population growth but does not change the ecological outcome. Taken together, this work predicts that stochastic effects arising from habitat fragmentation can greatly enhance the effectiveness of microbial collective defence via enzymatic toxin degradation.

Clinical considerations on antimicrobial resistance potential of complex microbiological samples

Antimicrobial resistance (AMR) is one of our greatest public health challenges. Targeted use of antibiotics (ABs) can reduce the occurrence and spread of AMR and boost the effectiveness of treatment. This requires knowledge of the AB susceptibility of the pathogens involved in the disease. Therapeutic recommendations based on classical AB susceptibility testing (AST) are based on the analysis of only a fraction of the bacteria present in the disease process. Next and third generation sequencing technologies allow the identification of antimicrobial resistance genes (ARGs) present in a bacterial community. Using this metagenomic approach, we can map the antimicrobial resistance potential (AMRP) of a complex, multi-bacterial microbial sample. To understand the interpretiveness of AMRP, the concordance between phenotypic AMR properties and ARGs was investigated by analyzing data from 574 Escherichia coli strains of five different studies. The overall results show that for 44% of the studied ABs, phenotypically resistant strains are genotypically associated with a 90% probability of resistance, while for 92% of the ABs, the phenotypically susceptible strains are genotypically susceptible with a 90% probability. ARG detection showed a phenotypic prediction with at least 90% confidence in 67% of ABs. The probability of detecting a phenotypically susceptible strain as resistant based on genotype is below 5% for 92% of ABs. While the probability of detecting a phenotypically resistant strain as susceptible based on genotype is below 5% for 44% of ABs. We can assume that these strain-by-strain concordance results are also true for bacteria in complex microbial samples, and conclude that AMRP obtained from metagenomic ARG analysis can help choose efficient ABs. This is illustrated using AMRP by a canine external otitis sample.

Pooled Antibiotic Susceptibility Testing Performs Within CLSI Standards for Validation When Measured Against Broth Microdilution and Disk Diffusion Antibiotic Susceptibility Testing of Cultured Isolates

Background/Objectives: While new methods for measuring antimicrobial susceptibility have been associated with improved patient outcomes, they should also be validated using standard protocols for error rates and other test metrics. The objective of this study was to validate a novel susceptibility assay for complicated and recurrent urinary tract infections (UTIs): pooled antibiotic susceptibility testing (P-AST). This assay was compared to broth microdilution (BMD) and disk diffusion (DD), following Clinical and Laboratory Standards Institute (CLSI) guidelines for assessment of error rates and agreement. Methods: This study analyzed consecutive fresh clinical urine specimens submitted for UTI diagnostic testing. Upon receipt, the urine samples were subjected in parallel to standard urine culture and multiplex polymerase chain reaction (M-PCR) for microbial identification and quantification. Specimens with the same monomicrobial non-fastidious bacteria detected by both M-PCR and standard urine culture (SUC) underwent standard antibiotic susceptibility testing (AST) and P-AST antibiotic susceptibility testing. Analysis was also undertaken to assess the presence of heteroresistance for specimens with P-AST-resistant and BMD/DD consensus-susceptible results. Results: The performance measures without correction for heteroresistance showed essential agreement (EA%) of ≥90%, very major errors (VMEs) of <1.5%, and major errors (MEs) of <3.0% for P-AST, all meeting the threshold guidelines established by CLSI for AST. The categorical agreement (CA%) also met acceptable criteria (>88%), as the majority of the errors were minor (mEs) with essential agreement. The very major and major error rates for P-AST decreased to <1.0% when heteroresistance was accounted for. Conclusions: The P-AST assay methodology is validated within acceptable parameters when compared to broth microdilution and disk diffusion using CLSI criteria.

Spatial population dynamics of bacterial colonies with social antibiotic resistance

Bacteria frequently inhabit surface-attached communities where rich "social" interactions can significantly alter their population-level behavior, including their response to antibiotics. Understanding these collective effects in spatially heterogeneous communities is an ongoing challenge. Here, we investigated the spatial organization that emerges from antibiotic exposure in initially randomly distributed communities containing antibiotic-resistant and -sensitive strains of E. faecalis , an opportunistic pathogen. We identified that a range of complex spatial structures emerged in the population homeland-the inoculated region that microbes inhabit prior to range expansion-, which depended on initial colony composition and antibiotic concentration. We found that these arrangements were explained by cooperative interactions between resistant and sensitive subpopulations with a variable spatial scale, the result of dynamic zones of protection afforded to sensitive cells by growing populations of enzyme-producing resistant neighbors. Using a combination of experiments and mathematical models, we explored the complex spatiotemporal interaction dynamics that create these patterns, and predicted spatial arrangements of sensitive and resistant subpopulations under new conditions. We illustrated how spatial population dynamics in the homeland affect subsequent range expansion, both because they modulate the composition of the initial expanding front, and through long-range cooperation between the homeland and the expanding region. Finally, we showed that these spatial constraints resulted in populations whose size and composition differed markedly from matched populations in well-stirred (planktonic) cultures. These findings underscore the importance of spatial structure and cooperation, long-studied features in theoretical ecology, for determining the fate of bacterial communities under antibiotic exposure.

Significance

Interactions between bacteria are common, particularly in the crowded surface-associated communities that occur anywhere from natural ecosystems to the human body to medical devices. Antibiotic resistance can be influenced by these "social" interactions, making it difficult to predict how spatial communities respond to antibiotic. Here, we show that complex spatial arrangements emerge when initially randomly distributed populations of antibiotic-resistant and -sensitive E. faecalis , a microbial pathogen, are exposed to antibiotic. Using mathematical models and experiments, we show how local competition and dynamic-range cross-protection drive pattern formation. As a result, these spatially structured populations respond differently to antibiotics than well-mixed communities. Our findings elucidate how "social" antibiotic resistance affects spatially structured bacterial communities, a step towards predicting and controlling resistance.

From Petri Dishes to Patients to Populations: Scales and Evolutionary Mechanisms Driving Antibiotic Resistance

Tackling the challenge created by antibiotic resistance requires understanding the mechanisms behind its evolution. Like any evolutionary process, the evolution of antimicrobial resistance (AMR) is driven by the underlying variation in a bacterial population and the selective pressures acting upon it. Importantly, both selection and variation will depend on the scale at which resistance evolution is considered (from evolution within a single patient to the host population level). While laboratory experiments have generated fundamental insights into the mechanisms underlying antibiotic resistance evolution, the technological advances in whole genome sequencing now allow us to probe antibiotic resistance evolution beyond the lab and directly record it in individual patients and host populations. Here we review the evolutionary forces driving antibiotic resistance at each of these scales, highlight gaps in our current understanding of AMR evolution, and discuss future steps toward evolution-guided interventions.

Klebsiella in Wildlife: Clonal Dynamics and Antibiotic Resistance Profiles, a Systematic Review

Klebsiella spp. are a genus of Gram-negative, opportunistic bacteria frequently found in the flora of the mucosal membranes of healthy animals and humans, and in the environment. Species of this group can cause serious infections (meningitis, sepsis, bacteraemia, urinary tract infections, liver damage) and possible death in immunocompromised organisms (and even in immunocompetent ones in the case of hypervirulent K. pneumoniae) that are exposed to them. K. pneumoniae is part of the ESKAPE organisms, and so it is important to understand this genus in terms of multidrug-resistant bacteria and as a carrier of antibiotic resistance mechanisms. As it is a durable bacterium, it survives well even in hostile environments, making it possible to colonize all kinds of habitats, even the mucosal flora of wildlife. This systematic review explores the prevalence of Klebsiella spp. bacteria in wild animals, and the possibility of transmission to humans according to the One Health perspective. The isolates found in this review proved to be resistant to betalactams (blaTEM, blaOXA-48…), aminoglycosides (strAB, aadA2…), fosfomycin, tetracyclines, sulphonamides, trimethoprim, phenicols (catB4), and polymyxins (mcr4).

Advances in Bioreceptor Layer Engineering in Nanomaterial-based Sensing of Pseudomonas Aeruginosa and its Metabolites

Pseudomonas aeruginosa is a pathogen that infects wounds and burns and causes severe infections in immunocompromised humans. The high virulence, the rise of antibiotic-resistant strains, and the easy transmissibility of P. aeruginosa necessitate its fast detection and control. The gold standard for detecting P. aeruginosa, the plate culture method, though reliable, takes several days to complete. Therefore, developing accurate, rapid, and easy-to-use diagnostic tools for P. aeruginosa is highly desirable. Nanomaterial-based biosensors are at the forefront of detecting P. aeruginosa and its secondary metabolites. This review summarises the biorecognition elements, biomarkers, immobilisation strategies, and current state-of-the-art biosensors for P. aeruginosa. The review highlights the underlying principles of bioreceptor layer engineering and the design of optical, electrochemical, mass-based, and thermal biosensors based on nanomaterials. The advantages and disadvantages of these biosensors and their future point-of-care applications are also discussed. This review outlines significant advancements in biosensors and sensors for detecting P. aeruginosa and its metabolites. Research efforts have identified biorecognition elements specific and selective towards P. aeruginosa. The stability, ease of preparation, cost-effectiveness, and integration of these biorecognition elements onto transducers are pivotal for their application in biosensors and sensors. At the same time, when developing sensors for clinically significant analytes such as P. aeruginosa, virulence factors need to be addressed, such as the sensor's sensitivity, reliability, and response time in samples obtained from patients. The point-of-care applicability of the developed sensor may be an added advantage since it enables onsite determination. In this context, optical methods developed for P. aeruginosa offer promising potential.

Trehalose catalytic shift is an intrinsic factor in Mycobacterium tuberculosis that enhances phenotypic heterogeneity and multidrug resistance

Drug-resistance (DR) in many bacterial pathogens often arises from the repetitive formation of drug-tolerant bacilli, known as persisters. However, it is unclear whether Mycobacterium tuberculosis (Mtb), the bacterium that causes tuberculosis (TB), undergoes a similar phenotypic transition. Recent metabolomics studies have identified that a change in trehalose metabolism is necessary for Mtb to develop persisters and plays a crucial role in metabolic networks of DR-TB strains. The present study used Mtb mutants lacking the trehalose catalytic shift and showed that the mutants exhibited a significantly lower frequency of the emergence of DR mutants compared to wildtype, due to reduced persister formation. The trehalose catalytic shift enables Mtb persisters to survive under bactericidal antibiotics by increasing metabolic heterogeneity and drug tolerance, ultimately leading to development of DR. Intriguingly, rifampicin (RIF)-resistant bacilli exhibit cross-resistance to a second antibiotic, due to a high trehalose catalytic shift activity. This phenomenon explains how the development of multidrug resistance (MDR) is facilitated by the acquisition of RIF resistance. In this context, the heightened risk of MDR-TB in the lineage 4 HN878 W-Beijing strain can be attributed to its greater trehalose catalytic shift. Genetic and pharmacological inactivation of the trehalose catalytic shift significantly reduced persister formation, subsequently decreasing the incidence of MDR-TB in HN878 W-Beijing strain. Collectively, the trehalose catalytic shift serves as an intrinsic factor of Mtb responsible for persister formation, cross-resistance to multiple antibiotics, and the emergence of MDR-TB. This study aids in the discovery of new TB therapeutics by targeting the trehalose catalytic shift of Mtb.

Disruption of bacterial interactions and community assembly in Babesia-infected Haemaphysalis longicornis following antibiotic treatment

BACKGROUND

A previous study highlighted the role of antibiotic-induced dysbiosis in the tick microbiota, facilitating the transstadial transmission of Babesia microti from nymph to adult in Haemaphysalis longicornis. This study builds on previous findings by analyzing sequence data from an earlier study to investigate bacterial interactions that could be linked to enhanced transstadial transmission of Babesia in ticks. The study employed antibiotic-treated (AT) and control-treated (CT) Haemaphysalis longicornis ticks to investigate shifts in microbial community assembly. Network analysis techniques were utilized to assess bacterial interactions, comparing network centrality measures between AT and CT groups, alongside studying network robustness and connectivity loss. Additionally, functional profiling was conducted to evaluate metabolic diversity in response to antibiotic treatment.

RESULTS

The analysis revealed notable changes in microbial community assembly in response to antibiotic treatment. Antibiotic-treated (AT) ticks displayed a greater number of connected nodes but fewer correlations compared to control-treated (CT) ticks, indicating a less interactive yet more connected microbial community. Network centrality measures such as degree, betweenness, closeness, and eigenvector centrality, differed significantly between AT and CT groups, suggesting alterations in local network dynamics due to antibiotic intervention. Coxiella and Acinetobacter exhibited disrupted connectivity and roles, with the former showing reduced interactions in AT group and the latter displaying a loss of connected nodes, emphasizing their crucial roles in microbial network stability. Robustness tests against node removal showed decreased stability in AT networks, particularly under directed attacks, confirming a susceptibility of the microbial community to disturbances. Functional profile analysis further indicated a higher diversity and richness in metabolic capabilities in the AT group, reflecting potential shifts in microbial metabolism as a consequence of antimicrobial treatment.

CONCLUSIONS

Our findings support that bacterial interaction traits boosting the transstadial transmission of Babesia could be associated with reduced colonization resistance. The disrupted microbial interactions and decreased network robustness in AT ticks suggest critical vulnerabilities that could be targeted for managing tick-borne diseases.

Mechanism of antibacterial resistance, strategies and next-generation antimicrobials to contain antimicrobial resistance: a review

Antibacterial drug resistance poses a significant challenge to modern healthcare systems, threatening our ability to effectively treat bacterial infections. This review aims to provide a comprehensive overview of the types and mechanisms of antibacterial drug resistance. To achieve this aim, a thorough literature search was conducted to identify key studies and reviews on antibacterial resistance mechanisms, strategies and next-generation antimicrobials to contain antimicrobial resistance. In this review, types of resistance and major mechanisms of antibacterial resistance with examples including target site modifications, decreased influx, increased efflux pumps, and enzymatic inactivation of antibacterials has been discussed. Moreover, biofilm formation, and horizontal gene transfer methods has also been included. Furthermore, measures (interventions) taken to control antimicrobial resistance and next-generation antimicrobials have been discussed in detail. Overall, this review provides valuable insights into the diverse mechanisms employed by bacteria to resist the effects of antibacterial drugs, with the aim of informing future research and guiding antimicrobial stewardship efforts.

A 'rich-get-richer' mechanism drives patchy dynamics and resistance evolution in antibiotic-treated bacteria

Bacteria in nature often form surface-attached communities that initially comprise distinct subpopulations, or patches. For pathogens, these patches can form at infection sites, persist during antibiotic treatment, and develop into mature biofilms. Evidence suggests that patches can emerge due to heterogeneity in the growth environment and bacterial seeding, as well as cell-cell signaling. However, it is unclear how these factors contribute to patch formation and how patch formation might affect bacterial survival and evolution. Here, we demonstrate that a 'rich-get-richer' mechanism drives patch formation in bacteria exhibiting collective survival (CS) during antibiotic treatment. Modeling predicts that the seeding heterogeneity of these bacteria is amplified by local CS and global resource competition, leading to patch formation. Increasing the dose of a non-eradicating antibiotic treatment increases the degree of patchiness. Experimentally, we first demonstrated the mechanism using engineered Escherichia coli and then demonstrated its applicability to a pathogen, Pseudomonas aeruginosa. We further showed that the formation of P. aeruginosa patches promoted the evolution of antibiotic resistance. Our work provides new insights into population dynamics and resistance evolution during surface-attached bacterial growth.

Preserving the efficacy of antibiotics to tackle antibiotic resistance

Different international agencies recognize that antibiotic resistance is one of the most severe human health problems that humankind is facing. Traditionally, the introduction of new antibiotics solved this problem but various scientific and economic reasons have led to a shortage of novel antibiotics at the pipeline. This situation makes mandatory the implementation of approaches to preserve the efficacy of current antibiotics. The concept is not novel, but the only action taken for such preservation had been the 'prudent' use of antibiotics, trying to reduce the selection pressure by reducing the amount of antibiotics. However, even if antibiotics are used only when needed, this will be insufficient because resistance is the inescapable outcome of antibiotics' use. A deeper understanding of the alterations in the bacterial physiology upon acquisition of resistance and during infection will help to design improved strategies to treat bacterial infections. In this article, we discuss the interconnection between antibiotic resistance (and antibiotic activity) and bacterial metabolism, particularly in vivo, when bacteria are causing infection. We discuss as well how understanding evolutionary trade-offs, as collateral sensitivity, associated with the acquisition of resistance may help to define evolution-based therapeutic strategies to fight antibiotic resistance and to preserve currently used antibiotics.

The collapse of cooperation during range expansion of Pseudomonas aeruginosa

Cooperation is commonly believed to be favourable in spatially structured environments, as these systems promote genetic relatedness that reduces the likelihood of exploitation by cheaters. Here we show that a Pseudomonas aeruginosa population that exhibited cooperative swarming was invaded by cheaters when subjected to experimental evolution through cycles of range expansion on solid media, but not in well-mixed liquid cultures. Our results suggest that cooperation is disfavoured in a more structured environment, which is the opposite of the prevailing view. We show that spatial expansion of the population prolongs cooperative swarming, which was vulnerable to cheating. Our findings reveal a mechanism by which spatial structures can suppress cooperation through modulation of the quantitative traits of cooperation, a process that leads to population divergence towards distinct colonization strategies.

Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

The antibiotic crisis: On the search for novel antibiotics and resistance mechanisms

In the relentless battle for human health, the proliferation of antibiotic-resistant bacteria has emerged as an impending catastrophe of unprecedented magnitude, potentially driving humanity towards the brink of an unparalleled healthcare crisis. The unyielding advance of antibiotic resistance looms as the foremost threat of the 21st century in clinical, agricultural and environmental arenas. Antibiotic resistance is projected to be the genesis of the next global pandemic, with grim estimations of tens of millions of lives lost annually by 2050. Amidst this impending calamity, our capacity to unearth novel antibiotics has languished, with the past four decades marred by a disheartening 'antibiotic discovery void'. With nearly 80% of our current antibiotics originating from natural or semi-synthetic sources, our responsibility is to cast our investigative nets into uncharted ecological niches teeming with microbial strife, the so-called 'microbial oases of interactions'. Within these oases of interactions, where microorganisms intensively compete for space and nutrients, a dynamic and ever-evolving microbial 'arms race' is constantly in place. Such a continuous cycle of adaptation and counter-adaptation is a fundamental aspect of microbial ecology and evolution, as well as the secrets to unique, undiscovered antibiotics, our last bastion against the relentless tide of resistance. In this context, it is imperative to invest in research to explore the competitive realms, like the plant rhizosphere, biological soil crusts, deep sea hydrothermal vents, marine snow and the most modern plastisphere, in which competitive interactions are at the base of the microorganisms' struggle for survival and dominance in their ecosystems: identify novel antibiotic by targeting microbial oases of interactions could represent a 'missing piece of the puzzle' in our fight against antibiotic resistance.

Protist predation promotes antimicrobial resistance spread through antagonistic microbiome interactions

Antibiotic resistance has grown into a major public health threat. In this study, we reveal predation by protists as an overlooked driver of antibiotic resistance dissemination in the soil microbiome. While previous studies have primarily focused on the distribution of antibiotic resistance genes, our work sheds light on the pivotal role of soil protists in shaping antibiotic resistance dynamics. Using a combination of metagenomics and controlled experiments in this study, we demonstrate that protists cause an increase in antibiotic resistance. We mechanistically link this increase to a fostering of antimicrobial activity in the microbiome. Protist predation gives a competitive edge to bacteria capable of producing antagonistic secondary metabolites, which secondary metabolites promote in turn antibiotic-resistant bacteria. This study provides insights into the complex interplay between protists and soil microbiomes in regulating antibiotic resistance dynamics. This study highlights the importance of top-down control on the spread of antibiotic resistance and directly connects it to cross-kingdom interactions within the microbiome. Managing protist communities may become an important tool to control outbreaks of antibiotic resistance in the environment.

Population dynamics of cross-protection against β-lactam antibiotics in droplet microreactors

Introduction

Bacterial strains that are resistant to antibiotics may protect not only themselves, but also sensitive bacteria nearby if resistance involves antibiotic degradation. Such cross-protection poses a challenge to effective antibiotic therapy by enhancing the long-term survival of bacterial infections, however, the current understanding is limited.

Methods

In this study, we utilize an automated nanoliter droplet analyzer to study the interactions between Escherichia coli strains expressing a β-lactamase (resistant) and those not expressing it (sensitive) when exposed to the β-lactam antibiotic cefotaxime (CTX), with the aim to define criteria contributing to cross-protection.

Results

We observed a cross-protection window of CTX concentrations for the sensitive strain, extending up to approximately 100 times its minimal inhibitory concentration (MIC). Through both microscopy and enzyme activity analyses, we demonstrate that bacterial filaments, triggered by antibiotic stress, contribute to cross-protection.

Discussion

The antibiotic concentration window for cross-protection depends on the difference in β-lactamase activity between co-cultured strains: larger differences shift the 'cross-protection window' toward higher CTX concentrations. Our findings highlight the dependence of opportunities for cross-protection on the relative resistance levels of the strains involved and suggest a possible specific role for filamentation.

Antibiotics and Antibiotic Resistance-Mur Ligases as an Antibacterial Target

The emergence of Multidrug Resistance (MDR) strains of bacteria has accelerated the search for new antibacterials. The specific bacterial peptidoglycan biosynthetic pathway represents opportunities for the development of novel antibacterial agents. Among the enzymes involved, Mur ligases, described herein, and especially the amide ligases MurC-F are key targets for the discovery of multi-inhibitors, as they share common active sites and structural features.

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.

Origin of Antibiotics and Antibiotic Resistance, and Their Impacts on Drug Development: A Narrative Review

Antibiotics have revolutionized medicine, saving countless lives since their discovery in the early 20th century. However, the origin of antibiotics is now overshadowed by the alarming rise in antibiotic resistance. This global crisis stems from the relentless adaptability of microorganisms, driven by misuse and overuse of antibiotics. This article explores the origin of antibiotics and the subsequent emergence of antibiotic resistance. It delves into the mechanisms employed by bacteria to develop resistance, highlighting the dire consequences of drug resistance, including compromised patient care, increased mortality rates, and escalating healthcare costs. The article elucidates the latest strategies against drug-resistant microorganisms, encompassing innovative approaches such as phage therapy, CRISPR-Cas9 technology, and the exploration of natural compounds. Moreover, it examines the profound impact of antibiotic resistance on drug development, rendering the pursuit of new antibiotics economically challenging. The limitations and challenges in developing novel antibiotics are discussed, along with hurdles in the regulatory process that hinder progress in this critical field. Proposals for modifying the regulatory process to facilitate antibiotic development are presented. The withdrawal of major pharmaceutical firms from antibiotic research is examined, along with potential strategies to re-engage their interest. The article also outlines initiatives to overcome economic challenges and incentivize antibiotic development, emphasizing international collaborations and partnerships. Finally, the article sheds light on government-led initiatives against antibiotic resistance, with a specific focus on the Middle East. It discusses the proactive measures taken by governments in the region, such as Saudi Arabia and the United Arab Emirates, to combat this global threat. In the face of antibiotic resistance, a multifaceted approach is imperative. This article provides valuable insights into the complex landscape of antibiotic development, regulatory challenges, and collaborative efforts required to ensure a future where antibiotics remain effective tools in safeguarding public health.

Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance

There is a pressing need to better understand how microbial populations respond to antimicrobial drugs, and to find mechanisms to possibly eradicate antimicrobial-resistant cells. The inactivation of antimicrobials by resistant microbes can often be viewed as a cooperative behaviour leading to the coexistence of resistant and sensitive cells in large populations and static environments. This picture is, however, greatly altered by the fluctuations arising in volatile environments, in which microbial communities commonly evolve. Here, we study the eco-evolutionary dynamics of a population consisting of an antimicrobial-resistant strain and microbes sensitive to antimicrobial drugs in a time-fluctuating environment, modelled by a carrying capacity randomly switching between states of abundance and scarcity. We assume that antimicrobial resistance (AMR) is a shared public good when the number of resistant cells exceeds a certain threshold. Eco-evolutionary dynamics is thus characterised by demographic noise (birth and death events) coupled to environmental fluctuations which can cause population bottlenecks. By combining analytical and computational means, we determine the environmental conditions for the long-lived coexistence and fixation of both strains, and characterise a fluctuation-driven AMR eradication mechanism, where resistant microbes experience bottlenecks leading to extinction. We also discuss the possible applications of our findings to laboratory-controlled experiments.

The carbapenem inoculum effect provides insight into the molecular mechanisms underlying carbapenem resistance in Enterobacterales

Carbapenem-resistant Enterobacterales (CRE) are important pathogens that can develop resistance via multiple molecular mechanisms, including hydrolysis or reduced antibiotic influx. Identifying these mechanisms can improve pathogen surveillance, infection control, and patient care. We investigated how resistance mechanisms influence the carbapenem inoculum effect (IE), a phenomenon where inoculum size affects antimicrobial susceptibility testing (AST). We demonstrated that seven different carbapenemases impart a meropenem IE in Escherichia coli. Across 110 clinical CRE isolates, the carbapenem IE strictly depended on resistance mechanism: all carbapenemase-producing CRE (CP-CRE) exhibited a strong IE, whereas porin-deficient CRE displayed none. Concerningly, 50% and 24% of CP-CRE isolates changed susceptibility classification to meropenem and ertapenem, respectively, across the allowable inoculum range in clinical guidelines. The meropenem IE, and the ratio of ertapenem to meropenem minimal inhibitory concentration (MIC) at standard inoculum, reliably identified CP-CRE. Understanding how resistance mechanisms affect AST could improve diagnosis and guide therapies for CRE infections.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

QbD-Engineered Development and Validation of a RP-HPLC Method for Simultaneous Estimation of Rutin and Ciprofloxacin HCl in Bilosomal Nanoformulation

In the given study, a new reverse-phase high-performance liquid chromatography (RP-HPLC) method has been reported for the simultaneous estimation of ciprofloxacin hydrochloride (CPX) and rutin (RUT) using quality by design (QbD) approach. The analysis was carried out by applying the Box-Behnken design having fewer design points and less experimental runs. It relates between factors and responses and gives statistically significant values, along with enhancing the quality of the analysis. CPX and RUT were separated on the Kromasil C₁₈ column (4.6 × 150 mm, 5 μm) using an isocratic mobile phase combination of phosphoric acid buffer (pH 3.0) and acetonitrile with the ratio of 87:13% v/v at a flow rate of 1.0 mL/min. CPX and RUT were detected at their respective wavelengths of 278 and 368 nm using a photodiode array detector. The developed method was validated according to guideline ICH Q2 R (1). The validation parameters taken were linearity, system suitability, accuracy, precision, robustness, sensitivity, and solution stability which were in the acceptable range. The findings suggest that the developed RP-HPLC method can be successfully applied to analyze novel CPX-RUT-loaded bilosomal nanoformulation prepared by thin-film hydration technique.

Reduced Antibiotic Resistance in the Rhizosphere of Lupinus albus in Mercury-Contaminated Soil Mediated by the Addition of PGPB

The emergence of antibiotic resistance (AR) poses a threat to the "One Health" approach. Likewise, mercury (Hg) pollution is a serious environmental and public health problem. Its ability to biomagnify through trophic levels induces numerous pathologies in humans. As well, it is known that Hg-resistance genes and AR genes are co-selected. The use of plant-growth-promoting bacteria (PGPB) can improve plant adaptation, decontamination of toxic compounds and control of AR dispersal. The cenoantibiogram, a technique that allows estimating the minimum inhibitory concentration (MIC) of a microbial community, has been postulated as a tool to effectively evaluate the evolution of a soil. The present study uses the metagenomics of 16S rRNA gene amplicons to understand the distribution of the microbial soil community prior to bacterial inoculation, and the cenoantibiogram technique to evaluate the ability of four PGPB and their consortia to minimize antibiotic resistance in the rhizosphere of Lupinus albus var. Orden Dorado grown in Hg-contaminated soils. Results showed that the addition of A1 strain (Brevibacterium frigoritolerans) and its consortia with A2, B1 and B2 strains reduced the edaphic community´s MIC against cephalosporins, ertapenem and tigecycline. The metagenomic study revealed that the high MIC of non-inoculated soils could be explained by the bacteria which belong to the detected taxa,. showing a high prevalence of Proteobacteria, Cyanobacteria and Actinobacteria.

Reduced selection for antibiotic resistance in community context is maintained despite pressure by additional antibiotics

Selection for antibiotic resistance at very low antibiotic concentrations has been demonstrated for individual antibiotics in single species experiments. Furthermore, selection in these focal strains is reduced when taking place in complex microbial community context. However, in the environment, bacteria are rarely exposed to single, but rather complex mixtures of selective agents. Here, we explored how the presence of a second selective agent affects selection dynamics between isogenic pairs of focal E. coli strains, differing exclusively in a single resistance determinant, in the absence and presence of a model wastewater community across a gradient of antibiotics. An additional antibiotic that exclusively affects the model wastewater community, but to which the focal strains are resistant to, was chosen as the second selective agent. This allowed exploring how inhibition alters the community's ability to reduce selection. In the presence of the community, the selection coefficient at specific antibiotic concentrations was consistently decreased compared to the absence of the community. While pressure through the second antibiotic significantly decreased the activity and diversity of the community, its ability to reduce selection was consistently maintained at levels comparable to those recorded in absence of the second antibiotic. This indicates that the observed effects of community context on selection dynamics are rather based on competitive or protective effects between the focal strains and a small proportion of bacteria within the community, than on general competition for nutrients. These findings have implications for our understanding of the evolution and selection for multi-drug resistant strains.

The Role of Coagulase-Negative Staphylococci Biofilms on Late-Onset Sepsis: Current Challenges and Emerging Diagnostics and Therapies

Infections are one of the most significant complications of neonates, especially those born preterm, with sepsis as one of the principal causes of mortality. Coagulase-negative staphylococci (CoNS), a group of staphylococcal species that naturally inhabit healthy human skin and mucosa, are the most common cause of late-onset sepsis, especially in preterms. One of the risk factors for the development of CoNS infections is the presence of implanted biomedical devices, which are frequently used for medications and/or nutrient delivery, as they serve as a scaffold for biofilm formation. The major concerns related to CoNS infections have to do with the increasing resistance to multiple antibiotics observed among this bacterial group and biofilm cells’ increased tolerance to antibiotics. As such, the treatment of CoNS biofilm-associated infections with antibiotics is increasingly challenging and considering that antibiotics remain the primary form of treatment, this issue will likely persist in upcoming years. For that reason, the development of innovative and efficient therapeutic measures is of utmost importance. This narrative review assesses the current challenges and emerging diagnostic tools and therapies for the treatment of CoNS biofilm-associated infections, with a special focus on late-onset sepsis.

Usage of antibiotics in aquaculture and the impact on coastal waters

For decades, coastal marine ecosystems have been threatened by a wide range of anthropogenic pollutants. Recently, there has been increasing concern about the accumulation and impacts of antibiotic compounds on marine ecosystems. However, information regarding the accumulation of antibiotics and the impacts they may have on microbial communities in coastal water bodies and on human health is sparse in literature. Antibiotics from aquacultures are constantly discharged into marine environments via rivers. Large rivers transport tons of antibiotics every year into coastal waters, e.g., 12 tons of sulfonamide by the river Mekong. Here, we discuss a potential influence of such imported antibiotics on bacterial communities in coastal waters. Potential accumulation of antibiotics in the uppermost surface layer of aquatic ecosystems, the so-called sea surface microlayer (SML), is of interest. Because of the ability of the SML to accumulate anthropogenic pollutants, it may serve as a pool for antibiotics and correspondingly also for resistant organisms. Also, due to its biofilm-like structure, the SML could serve as a hotspot for horizontal gene transfer, speeding up the spread of antibiotic resistant strains to encompassing marine environments. The emergence of antibiotic resistant bacteria is a global threat and scientists projected that it could pave the way for the next pandemic that could ravage the world in the next decades. For this reason, it is time to focus research on understanding and minimizing the impact of antibiotics on the sustainability of coastal waters and on the health of humans who depend on coastal resources for food and recreational purposes. Also, knowledge about antibiotics in the SML is necessary to understand the effects they are likely to have on bacterial abundance, diversity, and metabolic activities in coastal water bodies.

AtbFinder Diagnostic Test System Improves Optimal Selection of Antibiotic Therapy in Persons with Cystic Fibrosis

Cystic fibrosis (CF) is characterized by mutations of CFTR that lead to increased viscous secretions, bacterial colonization, and recurrent infections. Chronic Pseudomonas aeruginosa infection in persons with CF is associated with progressive and accelerated lung function decline despite aggressive antibiotic treatment. We report the management of respiratory infections in persons with CF with antibiotic therapy that was based on the recommendations of AtbFinder, a novel, rapid, culture-based diagnostic test system that employs a novel paradigm of antibiotic selection. AtbFinder mimics bacterial interactions with antibiotics at concentrations that can be achieved in affected tissues or organs and models conditions of interbacterial interactions within polymicrobial biofilms. This open-label, single-arm, investigator-initiated clinical study was designed to identify the efficacy of antibiotics selected using AtbFinder in persons with CF. Microbiological and clinical parameters were assessed following the change of antibiotic therapy to antibiotics selected with AtbFinder between January 2016 and December 2018 and retrospectively compared with clinical data collected between January 2013 and December 2015. We enrolled 35 persons with CF (33 with chronic P. aeruginosa colonization). Antibiotics selected using AtbFinder resulted in clearance of P. aeruginosa in 81.8% of subsequent cultures, decreased pulmonary exacerbations from 1.21 per patient per annum to 0, and an increase in predicted percent predicted forced expiratory volume in 1 s up to 28.4% from baseline. The number of systemic antibiotic courses used in patients after switching to the AtbFinder-selected therapy was reduced from 355 to 178. These findings describe the superiority of antibiotic regimens selected with AtbFinder compared with routine antimicrobial susceptibility testing.

DNase I and chitosan enhance efficacy of ceftazidime to eradicate Burkholderia pseudomallei biofilm cells

Biofilm-associated Burkholderia pseudomallei infection contributes to antibiotic resistance and relapse of melioidosis. Burkholderia pseudomallei biofilm matrix contains extracellular DNA (eDNA) that is crucial for biofilm establishment. However, the contribution of eDNA to antibiotic resistance by B. pseudomallei remains unclear. In this study, we first demonstrated in vitro that DNase I with the administration of ceftazidime (CAZ) at 24 h considerably inhibited the 2-day biofilm formation and reduced the number of viable biofilm cells of clinical B. pseudomallei isolates compared to biofilm treated with CAZ alone. A 3-4 log reduction in numbers of viable cells embedded in the 2-day biofilm was observed when CAZ was combined with DNase I. Confocal laser-scanning microscope visualization emphasized the competence of DNase I followed by CAZ supplementation to significantly limit B. pseudomallei biofilm development and to eradicate viable embedded B. pseudomallei biofilm cells. Furthermore, DNase I supplemented with chitosan (CS) linked with CAZ (CS/CAZ) significantly eradicated shedding planktonic and biofilm cells. These findings indicated that DNase I effectively degraded eDNA leading to biofilm inhibition and dispersion, subsequently allowing CAZ and CS/CAZ to eradicate both shedding planktonic and embedded biofilm cells. These findings provide efficient strategies to interrupt biofilm formation and improve antibiotic susceptibility of biofilm-associated infections.

Treatment of chronic relapsing urinary tract infection with antibiotics selected by AtbFinder

We report the case of a 46-year-old patient who, after renal cancer surgery, developed a recurrent urinary tract infection that lasted for more than 2 years. Despite repeated antibiotic courses, including broad-spectrum drugs chosen using conventional antibiotic susceptibility testing, multiple reinfections followed. The patient was successfully treated once antibiotics were selected with AtbFinder. Unlike routine antimicrobial susceptibility methods, which select antibiotics effective only against a "lead bacterial pathogen," AtbFinder identifies antibiotics that target the mixture of bacteria at the infection site. This case demonstrates the ability of AtbFinder to successfully select antibiotics for the treatment of relapsing urinary tract infections.

Overcoming Antibiotic Resistance with Novel Paradigms of Antibiotic Selection

Conventional antimicrobial susceptibility tests, including phenotypic and genotypic methods, are insufficiently accurate and frequently fail to identify effective antibiotics. These methods predominantly select therapies based on the antibiotic response of only the lead bacterial pathogen within pure bacterial culture. However, this neglects the fact that, in the majority of human infections, the lead bacterial pathogens are present as a part of multispecies communities that modulate the response of these lead pathogens to antibiotics and that multiple pathogens can contribute to the infection simultaneously. This discrepancy is a major cause of the failure of antimicrobial susceptibility tests to detect antibiotics that are effective in vivo. This review article provides a comprehensive overview of the factors that are missed by conventional antimicrobial susceptibility tests and it explains how accounting for these methods can aid the development of novel diagnostic approaches.

Predicting the re-distribution of antibiotic molecules caused by inter-species interactions in microbial communities

Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that neighbouring species enforce the re-distribution of carbon and antimicrobial molecules, predictably changing drug efficacy with respect to standard laboratory assays. A simple mathematical model, validated experimentally using pairwise competition assays, suggests that differences in drug sensitivity between the competing species causes the re-distribution of drug molecules without affecting carbon uptake. The re-distribution of drug is even when species have similar drug sensitivity, reducing drug efficacy. But when their sensitivities differ the re-distribution is uneven: The most sensitive species accumulates more drug molecules, increasing efficacy against it. Drug efficacy tests relying on samples with multiple species are considered unreliable and unpredictable, but study demonstrates that efficacy in these cases can be qualitatively predicted. It also suggests that living in communities can be beneficial even when all species compete for a single carbon source, as the relationship between cell density and drug required to inhibit their growth may be more complex than previously thought.

The Mechanism of Bacterial Resistance and Potential Bacteriostatic Strategies

Bacterial drug resistance is rapidly developing as one of the greatest threats to human health. Bacteria will adopt corresponding strategies to crack the inhibitory effect of antibiotics according to the antibacterial mechanism of antibiotics, involving the mutation of drug target, secreting hydrolase, and discharging antibiotics out of cells through an efflux pump, etc. In recent years, bacteria are found to constantly evolve new resistance mechanisms to antibiotics, including target protective protein, changes in cell morphology, and so on, endowing them with multiple defense systems against antibiotics, leading to the emergence of multi-drug resistant (MDR) bacteria and the unavailability of drugs in clinics. Correspondingly, researchers attempt to uncover the mystery of bacterial resistance to develop more convenient and effective antibacterial strategies. Although traditional antibiotics still play a significant role in the treatment of diseases caused by sensitive pathogenic bacteria, they gradually lose efficacy in the MDR bacteria. Therefore, highly effective antibacterial compounds, such as phage therapy and CRISPER-Cas precision therapy, are gaining an increasing amount of attention, and are considered to be the treatments with the moist potential with regard to resistance against MDR in the future. In this review, nine identified drug resistance mechanisms are summarized, which enhance the retention rate of bacteria under the action of antibiotics and promote the distribution of drug-resistant bacteria (DRB) in the population. Afterwards, three kinds of potential antibacterial methods are introduced, in which new antibacterial compounds exhibit broad application prospects with different action mechanisms, the phage therapy has been successfully applied to infectious diseases caused by super bacteria, and the CRISPER-Cas precision therapy as a new technology can edit drug-resistant genes in pathogenic bacteria at the gene level, with high accuracy and flexibility. These antibacterial methods will provide more options for clinical treatment, and will greatly alleviate the current drug-resistant crisis.

Colistin-degrading proteases confer collective resistance to microbial communities during polymicrobial infections

BACKGROUND

The increasing prevalence of resistance against the last-resort antibiotic colistin is a significant threat to global public health. Here, we discovered a novel colistin resistance mechanism via enzymatic inactivation of the drug and proposed its clinical importance in microbial communities during polymicrobial infections.

RESULTS

A bacterial strain of the Gram-negative opportunistic pathogen Stenotrophomonas maltophilia capable of degrading colistin and exhibiting a high-level colistin resistance was isolated from the soil environment. A colistin-degrading protease (Cdp) was identified in this strain, and its contribution to colistin resistance was demonstrated by growth inhibition experiments using knock-out (Δcdp) and complemented (Δcdp::cdp) mutants. Coculture and coinfection experiments revealed that S. maltophilia carrying the cdp gene could inactivate colistin and protect otherwise susceptible Pseudomonas aeruginosa, which may seriously affect the clinical efficacy of the drug for the treatment of cystic fibrosis patients with polymicrobial infection.

CONCLUSIONS

Our results suggest that Cdp should be recognized as a colistin resistance determinant that confers collective resistance at the microbial community level. Our study will provide vital information for successful clinical outcomes during the treatment of complex polymicrobial infections, particularly including S. maltophilia and other colistin-susceptible Gram-negative pathogens such as P. aeruginosa. Video abstract.

Optimal dose of lactoferrin reduces the resilience of in vitro Staphylococcus aureus colonies

The rise in antibiotic resistance has stimulated research into adjuvants that can improve the efficacy of broad-spectrum antibiotics. Lactoferrin is a candidate adjuvant; it is a multifunctional iron-binding protein with antimicrobial properties. It is known to show dose-dependent antimicrobial activity against Staphylococcus aureus through iron sequestration and repression of β-lactamase expression. However, S. aureus can extract iron from lactoferrin through siderophores for their growth, which confounds the resolution of lactoferrin's method of action. We measured the minimum inhibitory concentration (MIC) for a range of lactoferrin/ β-lactam antibiotic dose combinations and observed that at low doses (< 0.39 μM), lactoferrin contributes to increased S. aureus growth, but at higher doses (> 6.25 μM), iron-depleted native lactoferrin reduced bacterial growth and reduced the MIC of the β-lactam-antibiotic cefazolin. This differential behaviour points to a bacterial population response to the lactoferrin/ β-lactam dose combination. Here, with the aid of a mathematical model, we show that lactoferrin stratifies the bacterial population, and the resulting population heterogeneity is at the basis of the dose dependent response seen. Further, lactoferrin disables a sub-population from β-lactam-induced production of β-lactamase, which when sufficiently large reduces the population's ability to recover after being treated by an antibiotic. Our analysis shows that an optimal dose of lactoferrin acts as a suitable adjuvant to eliminate S. aureus colonies using β-lactams, but sub-inhibitory doses of lactoferrin reduces the efficacy of β-lactams.

Strategies to Improve the Potency of Oxazolidinones towards Bacterial Biofilms

Biofilms are part of the natural lifecycle of bacteria and are known to cause chronic infections that are difficult to treat. Most antibiotics are developed and tested against bacteria in the planktonic state and are ineffective against bacterial biofilms. The oxazolidinones, including the last resort drug linezolid, are one of the main classes of synthetic antibiotics progressed to clinical use in the last 50 years. They have a unique mechanism of action and only develop low levels of resistance in the clinical setting. With the aim of providing insight into strategies to design more potent antibiotic compounds with activity against bacterial biofilms, we review the biofilm activity of clinically approved oxazolidinones and report on structural modifications to oxazolidinones and their delivery systems which lead to enhanced anti-biofilm activity.

Towards understanding mechanisms and functional consequences of bacterial interactions with members of various kingdoms in complex biofilms that abound in nature

The microbial world represents a phenomenal diversity of microorganisms from different kingdoms of life which occupy an impressive set of ecological niches. Most, if not all, microorganisms once colonise a surface develop architecturally complex surface-adhered communities which we refer to as biofilms. They are embedded in polymeric structural scaffolds serve as a dynamic milieu for intercellular communication through physical and chemical signalling. Deciphering microbial ecology of biofilms in various natural or engineered settings has revealed co-existence of microorganisms from all domains of life, including Bacteria, Archaea and Eukarya. The coexistence of these dynamic microbes is not arbitrary, as a highly coordinated architectural setup and physiological complexity show ecological interdependence and myriads of underlying interactions. In this review, we describe how species from different kingdoms interact in biofilms and discuss the functional consequences of such interactions. We highlight metabolic advances of collaboration among species from different kingdoms, and advocate that these interactions are of great importance and need to be addressed in future research. Since trans-kingdom biofilms impact diverse contexts, ranging from complicated infections to efficient growth of plants, future knowledge within this field will be beneficial for medical microbiology, biotechnology, and our general understanding of microbial life in nature.

Gut Microbiome as a Mediator of Stress Resilience: A Reactive Scope Model Framework

Stress resilience is defined as the ability to rebound to a homeostatic state after exposure to a perturbation. Organisms modulate various physiological mediators to respond to unpredictable changes in their environment. The gut microbiome is a key example of a physiological mediator that coordinates a myriad of host functions including counteracting stressors. Here, we highlight the gut microbiome as a mediator of host stress resilience in the framework of the reactive scope model. The reactive scope model integrates physiological mediators with unpredictable environmental changes to predict how animals respond to stressors. We provide examples of how the gut microbiome responds to stressors within the four ranges of the reactive scope model (i.e., predictive homeostasis, reactive homeostasis, homeostatic overload, and homeostatic failure). We identify measurable metrics of the gut microbiome that could be used to infer the degree to which the host is experiencing chronic stress, including microbial diversity, flexibility, and gene richness. The goal of this perspective piece is to highlight the underutilized potential of measuring the gut microbiome as a mediator of stress resilience in wild animal hosts.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics

SignificanceAntibiotic exposure stands among the most used interventions to drive microbial communities away from undesired states. How the ecology of microbial communities shapes their recovery-e.g., posttreatment shifts toward Clostridioides difficile infections in the gut-after antibiotic exposure is poorly understood. We study community response to antibiotics using a model community that can reach two alternative states. Guided by theory, our experiments show that microbial growth following antibiotic exposure can counteract antibiotic susceptibility in driving transitions between alternative community states. This makes it possible to reverse the outcome of antibiotic exposure through modifying growth dynamics, including cooperative growth, of community members. Our research highlights the relevance of simple ecological models to better understand the long-term effects of antibiotic treatment.

Inter-species interactions alter antibiotic efficacy in bacterial communities

The efficacy of antibiotic treatments targeting polymicrobial communities is not well predicted by conventional in vitro susceptibility testing based on determining minimum inhibitory concentration (MIC) in monocultures. One reason for this is that inter-species interactions can alter the community members' susceptibility to antibiotics. Here we quantify, and identify mechanisms for, community-modulated changes of efficacy for clinically relevant antibiotics against the pathogen Pseudomonas aeruginosa in model cystic fibrosis (CF) lung communities derived from clinical samples. We demonstrate that multi-drug resistant Stenotrophomonas maltophilia can provide high levels of antibiotic protection to otherwise sensitive P. aeruginosa. Exposure protection to imipenem was provided by chromosomally encoded metallo-β-lactamase that detoxified the environment; protection was dependent upon S. maltophilia cell density and was provided by S. maltophilia strains isolated from CF sputum, increasing the MIC of P. aeruginosa by up to 16-fold. In contrast, the presence of S. maltophilia provided no protection against meropenem, another routinely used carbapenem. Mathematical ordinary differential equation modelling shows that the level of exposure protection provided against different carbapenems can be explained by differences in antibiotic efficacy and inactivation rate. Together, these findings reveal that exploitation of pre-occurring antimicrobial resistance, and inter-specific competition, can have large impacts on pathogen antibiotic susceptibility, highlighting the importance of microbial ecology for designing successful antibiotic treatments for multispecies communities.

Environmental contamination in a high-income country (France) by antibiotics, antibiotic-resistant bacteria, and antibiotic resistance genes: Status and possible causes

Antimicrobial resistance (AMR) is a major global public health concern, shared by a large number of human and animal health actors. Within the framework of a One Health approach, actions should be implemented in the environmental realm, as well as the human and animal realms. The Government of France commissioned a report to provide policy and decision makers with an evidential basis for recommending or taking future actions to mitigate AMR in the environment. We first examined the mechanisms that underlie the emergence and persistence of antimicrobial resistance in the environment. This report drew up an inventory of the contamination of aquatic and terrestrial environments by AMR and antibiotics, anticipating that the findings will be representative of some other high-income countries. Effluents of wastewater treatment plants were identified as the major source of contamination on French territory, with spreading of organic waste products as a more diffuse and incidental contamination of aquatic environments. A limitation of this review is the heterogeneity of available data in space and time, as well as the lack of data for certain sources. Comparing the French Measured Environmental Concentrations (MECs) with predicted no effect concentrations (PNECs), fluoroquinolones and trimethoprim were identified as representing high and medium risk of favoring the selection of resistant bacteria in treated wastewater and in the most contaminated rivers. All other antibiotic molecules analyzed (erythromycin, clarithromycin, azithromycin, tetracycline) were at low risk of resistance selection in those environments. However, the heterogeneity of the data available impairs their full exploitation. Consequently, we listed indicators to survey AMR and antibiotics in the environment and recommended the harmonization of sampling strategies and endpoints for analyses. Finally, the objectives and methods used for the present work could comprise a useful example for how national authorities of countries sharing common socio-geographic characteristics with France could seek to better understand and define the environmental dimension of AMR in their particular settings.

Social selection within aggregative multicellular development drives morphological evolution

Aggregative multicellular development is a social process involving complex forms of cooperation among unicellular organisms. In some aggregative systems, development culminates in the construction of spore-packed fruiting bodies and often unfolds within genetically and behaviourally diverse conspecific cellular environments. Here, we use the bacterium Myxococcus xanthus to test whether the character of the cellular environment during aggregative development shapes its morphological evolution. We manipulated the cellular composition of Myxococcus development in an experiment in which evolving populations initiated from a single ancestor repeatedly co-developed with one of several non-evolving partners-a cooperator, three cheaters and three antagonists. Fruiting body morphology was found to diversify not only as a function of partner genotype but more broadly as a function of partner social character, with antagonistic partners selecting for greater fruiting body formation than cheaters or the cooperator. Yet even small degrees of genetic divergence between distinct cheater partners sufficed to drive treatment-level morphological divergence. Co-developmental partners also determined the magnitude and dynamics of stochastic morphological diversification and subsequent convergence. In summary, we find that even just a few genetic differences affecting developmental and social features can greatly impact morphological evolution of multicellular bodies and experimentally demonstrate that microbial warfare can promote cooperation.

Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. In this work, we investigate the spatiotemporal dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen Enterococcus faecalis with plasmid-encoded β-lactamase, we track colony expansion dynamics and visualize spatial patterns in fluorescently labeled populations exposed to antibiotics. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells at otherwise lethal concentrations. The populations exhibit a diverse range of spatial segregation patterns that depend on drug concentration and initial conditions. Mathematical models indicate that the observed dynamics are consistent with global cooperation, despite the fact that β-lactamase remains cell-associated. Experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony, and populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of the drug. While biophysical models of drug degradation suggest that individual resistant cells offer only short-range protection to neighboring cells, we show that long-range protection may arise from synergistic effects of multiple resistant cells, providing surprisingly large protection zones even at small population fractions.

Engineering biomaterials to prevent post-operative infection and fibrosis

Implantable biomaterials are essential surgical devices, extending and improving the quality of life of millions of people globally. Advances in materials science, manufacturing, and in our understanding of the biological response to medical device implantation over several decades have resulted in improved safety and functionality of biomaterials. However, post-operative infection and immune responses remain significant challenges that interfere with biomaterial functionality and host healing processes. The objectives of this review is to provide an overview of the biology of post-operative infection and the physiological response to implanted biomaterials and to discuss emerging strategies utilizing local drug delivery and surface modification to improve the long-term safety and efficacy of biomaterials.

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.