Conserved Evolutionary Trajectory Can Be Perturbed to Prevent Resistance Evolution under Norfloxacin Pressure by Forcing Mycobacterium smegmatis on Alternate Evolutionary Paths

Antibiotic resistance is a pressing health issue, with the emergence of resistance in bacteria outcompeting the discovery of novel drug candidates. While many studies have used Adaptive Laboratory Evolution (ALE) to understand the determinants of resistance, the influence of the drug dosing profile on the evolutionary trajectory remains understudied. In this study, we employed ALE on Mycobacterium smegmatis exposed to various concentrations of Norfloxacin using both cyclic constant and stepwise increasing drug dosages to examine their impact on the resistance mechanisms selected. Mutations in an efflux pump regulator, LfrR, were found in all of the evolved populations irrespective of the drug profile and population bottleneck, indicating a conserved efflux-based resistance mechanism. This mutation appeared early in the evolutionary trajectory, providing low-level resistance when present alone, with a further increase in resistance resulting from successive accumulation of other mutations. Notably, drug target mutations, similar to those observed in clinical isolates, were only seen above a threshold of greater than 4× the minimum inhibitory concentration (MIC). A combination of three mutations in the genes, lfrR, MSMEG_1959, and MSMEG_5045, was conserved across multiple lineages, leading to high-level resistance and preceding the appearance of drug target mutations. Interestingly, in populations evolved from parental strains lacking the lfrA efflux pump, the primary target of the lfrR regulator, no lfrR gene mutations are selected. Furthermore, evolutional trajectories originating from the ΔlfrA strain displayed early arrest in some lineages and the absence of target gene mutations in those that evolved, albeit delayed. Thus, blocking or inhibiting the expression of efflux pumps can arrest or delay the fixation of drug target mutations, potentially limiting the maximum attainable resistance levels.

Recent Advances of Engineered Cell Membrane-Based Nanotherapeutics to Combat Inflammatory Diseases

An immune reaction known as inflammation serves as a shield from external danger signals, but an overactive immune system may additionally lead to tissue damage and even a variety of inflammatory disorders. By inheriting biological functionalities and serving as both a therapeutic medication and a drug carrier, cell membrane-based nanotherapeutics offer the potential to treat inflammatory disorders. To further strengthen the anti-inflammatory benefits of natural cell membranes, researchers alter and optimize the membranes using engineering methods. This review focuses on engineered cell membrane-based nanotherapeutics (ECMNs) and their application in treating inflammation-related diseases. Specifically, this article discusses the methods of engineering cell membranes for inflammatory diseases and examines the progress of ECMNs in inflammation-targeted therapy, inflammation-neutralizing therapy, and inflammation-immunomodulatory therapy. Additionally, the article looks into the perspectives and challenges of ECMNs in inflammatory treatment and offers suggestions as well as guidance to encourage further investigations and implementations in this area.

Universal Lineage-Independent Markers of Multidrug Resistance in Mycobacterium tuberculosis

(1) Background: This study was aimed to identify universal genetic markers of multidrug resistance (MDR) in Mycobacterium tuberculosis (Mtb) and establish statistical associations among identified mutations to enhance understanding of MDR in Mtb and inform diagnostic and treatment development. (2) Methods: GWAS analysis and the statistical evaluation of identified polymorphic sites within protein-coding genes of Mtb were performed. Statistical associations between specific mutations and antibiotic resistance were established using attributable risk statistics. (3) Results: Sixty-four polymorphic sites were identified as universal markers of drug resistance, with forty-seven in PE/PPE regions and seventeen in functional genes. Mutations in genes such as cyp123, fadE36, gidB, and ethA showed significant associations with resistance to various antibiotics. Notably, mutations in cyp123 at codon position 279 were linked to resistance to ten antibiotics. The study highlighted the role of PE/PPE and PE_PGRS genes in Mtb's evolution towards a 'mutator phenotype'. The pathways of acquisition of mutations forming the epistatic landscape of MDR were discussed. (4) Conclusions: This research identifies marker mutations across the Mtb genome associated with MDR. The findings provide new insights into the molecular basis of MDR acquisition in Mtb, aiding in the development of more effective diagnostics and treatments targeting these mutations to combat MDR tuberculosis.

Antibiotic resistance: A key microbial survival mechanism that threatens public health

Antibiotic resistance (AMR) is a global public health threat, challenging the effectiveness of antibiotics in combating bacterial infections. AMR also represents one of the most crucial survival traits evolved by bacteria. Antibiotics emerged hundreds of millions of years ago as advantageous secondary metabolites produced by microbes. Consequently, AMR is equally ancient and hardwired into the genetic fabric of bacteria. Human use of antibiotics for disease treatment has created selection pressure that spurs the evolution of new resistance mechanisms and the mobilization of existing ones through bacterial populations in the environment, animals, and humans. This integrated web of resistance elements is genetically complex and mechanistically diverse. Addressing this mode of bacterial survival requires innovation and investment to ensure continued use of antibiotics in the future. Strategies ranging from developing new therapies to applying artificial intelligence in monitoring AMR and discovering new drugs are being applied to manage the growing AMR crisis.

Acquisition of plasmids from Shiga toxin-producing Escherichia coli strains had low or neutral fitness cost on commensal E. coli

Although it has been hypothesized that the acquisition of plasmids-especially those bearing virulence factors and antimicrobial resistance genes-increases the energetic burden and reduces the fitness of a bacterium in general, some results have challenged this view, showing little or no effect on fitness after plasmid acquisition, which may lead to change in the view that there are evolutionary barriers for a wide spread of such plasmids among bacteria. Here, to evaluate the fitness impact of plasmid-encoded antibiotic resistance and virulence genes, plasmids from O26:H11, O111:H8, and O118:H16 Shiga toxin-producing Escherichia coli (STEC) human and bovine isolates were transferred to the non-virulent E. coli HS and K-12 MG1655 strains. Sequencing and PCR were used to characterize plasmids, and to identify the presence of antimicrobial resistance and/or virulence genes. The fitness impact of plasmids encoding virulence and antimicrobial resistance upon bacterial hosts was determined by pairwise growth competition. Plasmid profile analysis showed that STEC strains carried one or more high and low molecular weight plasmids belonging to the B/O, F, I, K, P, Q, and/or X incompatibility groups encoding virulence genes (SPATE-encoding genes) and/or antimicrobial resistance genes (aadA1, strAB, tetA, and/or tetB). Competition experiments demonstrated that the biological cost of carriage of these plasmids by the commensal E. coli strain HS or the laboratory strain E. coli K-12 MG1655 was low or non-existent, ranging from - 4.7 to 5.2% per generation. This suggests that there are few biological barriers-or, alternatively, it suggests that there are biological barriers that we were not able to measure in this competition model-against the spread of plasmid encoding virulence and resistance genes from STEC to other, less pathogenic E. coli strains. Thus, our results, in opposition to a common view, suggest that the acquisition of plasmids does not significantly affect the bacteria fitness and, therefore, the theorized plasmid burden would not be a significant barrier for plasmid spread.

When it rains it pours: An increased prevalence of intestinal carriage of vancomycin-resistant Enterococcus faecium related to higher use of oral vancomycin in a tertiary care Hungarian clinical centre during the years of the COVID-19 pandemic

OBJECTIVES

This study aims to investigate the association between oral vancomycin consumption and intestinal vancomycin-resistant Enterococcus carriage in the pre- and COVID era in the clinical centre of the University of Szeged, Hungary.

METHODS

This retrospective microbiological examination was carried out using electronically collected data, corresponding to the period between 1 January 2018 and 31 December 2022, at the Department of Medical Microbiology. Data included isolated species and the according antimicrobial susceptibility patterns. Annual consumption data for oral vancomycin consumption were exported from the database of the central pharmacy of the clinical centre. As a strain typing procedure, Fourier transform infrared spectroscopy analysis was used.

RESULTS

There was a significant increase in the number of faecal vancomycin-resistant Enterococcus isolates throughout the study. The prevalence increased significantly during the years of the pandemic. The use of orally administered vancomycin in the clinical centre increased significantly. A strong positive correlation existed between the two phenomena. Several strains with different resistance patterns spread in the clinical centre. Two of these occurred in greater numbers, differing in their high-level aminoglycoside resistance. However, the overall resistance of these strains was stagnating. FTIR analysis revealed that 59 of the 62 strains were also divided into 2 large clusters differing partially in their high-level aminoglycoside resistance.

CONCLUSIONS

During the pandemic, intestinal VRE carriage among clinical centre patients increased significantly, linked to increased oral vancomycin use. Different strains spread, with aminoglycoside resistance being the primary distinction. This highlights the negative impact of the pandemic on VRE carriage.

Genetic Characterization and Population Structure of Drug-Resistant Mycobacterium tuberculosis Isolated from Brazilian Patients Using Whole-Genome Sequencing

The present study aimed to determine the genetic diversity of isolates of Mycobacterium tuberculosis (Mtb) from presumed drug-resistant tuberculosis patients from several states of Brazil. The isolates had been submitted to conventional drug susceptibility testing for first- and second-line drugs. Multidrug-resistant (MDR-TB) (54.8%) was the most frequent phenotypic resistance profile, in addition to an important high frequency of pre-extensive resistance (p-XDR-TB) (9.2%). Using whole-genome sequencing (WGS), we characterized 298 Mtb isolates from Brazil. Besides the analysis of genotype distribution and possible correlations between molecular and clinical data, we determined the performance of an in-house WGS pipeline with other online pipelines for Mtb lineages and drug resistance profile definitions. Sub-lineage 4.3 (52%) was the most frequent genotype, and the genomic approach revealed a p-XDR-TB level of 22.5%. We detected twenty novel mutations in three resistance genes, and six of these were observed in eight phenotypically resistant isolates. A cluster analysis of 170 isolates showed that 43.5% of the TB patients belonged to 24 genomic clusters, suggesting considerable ongoing transmission of DR-TB, including two interstate transmissions. The in-house WGS pipeline showed the best overall performance in drug resistance prediction, presenting the best accuracy values for five of the nine drugs tested. Significant associations were observed between suffering from fatal disease and genotypic p-XDR-TB (p = 0.03) and either phenotypic (p = 0.006) or genotypic (p = 0.0007) ethambutol resistance. The use of WGS analysis improved our understanding of the population structure of MTBC in Brazil and the genetic and clinical data correlations and demonstrated its utility for surveillance efforts regarding the spread of DR-TB, hopefully helping to avoid the emergence of even more resistant strains and to reduce TB incidence and mortality rates.

Halicin: A New Horizon in Antibacterial Therapy against Veterinary Pathogens

It is crucial to discover novel antimicrobial drugs to combat resistance. This study investigated the antibacterial properties of halicin (SU3327), an AI-identified anti-diabetic drug, against 13 kinds of common clinical pathogens of animal origin, including multidrug-resistant strains. Employing minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assessments, halicin demonstrated a broad-spectrum antibacterial effect. Time-killing assays revealed its concentration-dependent bactericidal activity against Escherichia coli ATCC 25922 (E. coli ATCC 25922), Staphylococcus aureus ATCC 29213 (S. aureus ATCC 29213), and Actinobacillus pleuropneumoniae S6 (APP S6) after 4 h of treatment at concentrations above the MIC. Halicin exhibited longer post-antibiotic effects (PAEs) and sub-MIC effects (PA-SMEs) for E. coli 25922, S. aureus 29213, and APP S6 compared to ceftiofur and ciprofloxacin, the commonly used veterinary antimicrobial agents, indicating sustained antibacterial action. Additionally, the results of consecutive passaging experiments over 40 d at sub-inhibitory concentrations showed that bacteria exhibited difficulty in developing resistance to halicin. Toxicology studies confirmed that halicin exhibited low acute toxicity, being non-mutagenic, non-reproductive-toxic, and non-genotoxic. Blood biochemical results suggested that halicin has no significant impact on hematological parameters, liver function, and kidney function. Furthermore, halicin effectively treated respiratory A. pleuropneumoniae infections in murine models. These results underscore the potential of halicin as a new antibacterial agent with applications against clinically relevant pathogens in veterinary medicine.

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.

Modeling spatial evolution of multi-drug resistance under drug environmental gradients

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria based on a drug-concentration rescaling approach. We show how the resistance to drugs in space, and the consequent adaptation of growth rate, is governed by a Price equation with diffusion, integrating features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Although in many evolution models, per capita growth rate is a natural surrogate for fitness, in spatially-extended, potentially heterogeneous habitats, fitness is an emergent property that potentially reflects additional complexities, from boundary conditions to the specific spatial variation of growth rates. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical metric for characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem, λ1. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits to the relative advantage of each mutant across the environment. Our approach allows one to predict the precise outcomes of selection among mutants over space, ultimately from comparing their λ1 values, which encode a critical interplay between growth functions, movement traits, habitat size and boundary conditions. Such mathematical understanding opens new avenues for multi-drug therapeutic optimization.

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

Polydopamine-Coated Copper-Doped Co3O4 Nanosheets Rich in Oxygen Vacancy on Titanium and Multimodal Synergistic Antibacterial Study

Medical titanium-based (Ti-based) implants in the human body are prone to infection by pathogenic bacteria, leading to implantation failure. Constructing antibacterial nanocoatings on Ti-based implants is one of the most effective strategies to solve bacterial contamination. However, single antibacterial function was not sufficient to efficiently kill bacteria, and it is necessary to develop multifunctional antibacterial methods. This study modifies medical Ti foils with Cu-doped Co3O4 rich in oxygen vacancies, and improves their biocompatibility by polydopamine (PDA/Cu-Ov-Co3O4). Under near-infrared (NIR) irradiation, nanocoatings can generate •OH and 1O2 due to Cu+ Fenton-like activity and a photodynamic effect of Cu-Ov-Co3O4, and the total reactive oxygen species (ROS) content inside bacteria significantly increases, causing oxidative stress of bacteria. Further experiments prove that the photothermal process enhances the bacterial membrane permeability, allowing the invasion of ROS and metal ions, as well as the protein leakage. Moreover, PDA/Cu-Ov-Co3O4 can downregulate ATP levels and further reduce bacterial metabolic activity after irradiation. This coating exhibits sterilization ability against both Escherichia coli and Staphylococcus aureus with an antibacterial rate of ca. 100%, significantly higher than that of bare medical Ti foils (ca. 0%). Therefore, multifunctional synergistic antibacterial nanocoating will be a promising strategy for preventing bacterial contamination on medical Ti-based implants.

Host defense peptides mitigate the spread of antibiotic resistance in physiologically relevant condition

Antibiotic resistance represents a significant challenge to public health and human safety. The primary driver behind the dissemination of antibiotic resistance is the horizontal transfer of plasmids. Current conjugative transfer assay is generally performed in a standardized manner, ignoring the effect of the host environment. Host defense peptides (HDPs) possess a wide range of biological targets and play an essential role in the innate immune system. Herein, we reveal that sub-minimum inhibitory concentrations of HDPs facilitate the conjugative transfer of RP4-7 plasmid in the Luria Broth medium, and this observation is reversed in the RPMI medium, designed to simulate the host environment. Out of these HDPs, indolicidin (Ind), a cationic tridecapeptide from bovine neutrophils, significantly inhibits the conjugation of multidrug resistance plasmids in a dose-dependent manner, including blaNDM- and tet(X4)-bearing plasmids. We demonstrate that the addition of Ind to RPMI medium as the incubation substrate downregulates the expression of conjugation-related genes. In addition, Ind weakens the tricarboxylic acid cycle, impedes the electron transport chain, and disrupts the proton motive force, consequently diminishing the synthesis of adenosine triphosphate and limiting the energy supply. Our findings highlight the importance of the host-like environments for the development of horizontal transfer inhibitors and demonstrate the potential of HDPs in preventing the spread of resistance plasmids.

Unveiling a novel mechanism for competitive advantage of ciprofloxacin-resistant bacteria in the environment through bacterial membrane vesicles

Ciprofloxacin (CIP) is a prevalent environmental contaminant that poses a high risk of antibiotic resistance. High concentrations of antibiotics can lead to the development of resistant bacteria with high fitness costs, which often face a competitive disadvantage. However, it is unclear whether low-cost resistant bacteria formed by exposure to sub-MIC CIP in the environment can evolve competitive mechanisms against sensitive Escherichia coli (SEN) other than stronger resistance to CIP. Our study exposed E. coli to sub-MIC CIP levels, resulting in the development of CIP-resistant E. coli (CIPr). In antibiotic-free co-culture assays, CIPr outcompeted SEN. This indicates that CIPr is very likely to continue to develop and spread in antibiotic-free environments such as drinking water and affect human health. Further mechanism investigation revealed that bacterial membrane vesicles (BMVs) in CIPr, functioning as substance delivery couriers, mediated a cleavage effect on SEN. Proteomic analysis identified Entericidin B (EcnB) within CIPr-BMVs as a key factor in this competitive interaction. RT-qPCR analysis showed that the transcription of its negative regulator ompR/envZ was down-regulated. Moreover, EcnB plays a crucial role in the development of CIP resistance, and some resistance-related proteins and pathways have also been discovered. Metabolomics analysis highlighted the ability of CIPr-BMVs to acidify SEN, increasing the lytic efficiency of EcnB through cationization. Overall, our study reveals the importance of BMVs in mediating bacterial resistance and competition, suggesting that regulating BMVs production may be a new strategy for controlling the spread of drug-resistant bacteria.

Evaluation of Antimicrobial Stewardship Programs and antibiotic prescribing patterns among physicians in ambulatory care settings in Jordan

OBJECTIVES

Currently, there is an urgent need to implement an Antimicrobial Stewardship Program (ASP) in outpatient settings since nearly half of the antibiotic prescribing is inappropriate or unnecessary. The implementation of ASP should emphasize educational interventions that are more interactive. This study examines the adoption of outpatient ASP by physicians in Jordan.

METHODS

A cross-sectional study was conducted between 2 March 2022 and 20 May 2022 at major hospitals in Jordan. The survey was distributed randomly among (n = 187) Jordanian physicians.

RESULTS

It was found that more than half of the physicians were females (51.9%). The participants who reported not including antibiotic stewardship-related duties in position descriptions were (40.1%). While (46.5%) of participants reported writing and displaying public commitments supporting antibiotic stewardship in ambulatory care settings. Physicians' adoption of (action) core elements of ASPs in ambulatory care settings was positive. Almost (24.6%) reported a lack of self-evaluation of their antibiotic-prescribing practices. It was reported that (69.5%) of physicians used effective communication strategies to educate patients about when antibiotics are necessary.

CONCLUSION

It was fair adoption of the core elements in the ambulatory care settings among Jordanian physicians. Progress necessitates a comprehensive strategy tailored to the needs of the health system.

Predictive Modeling of Phenotypic Antimicrobial Susceptibility of Selected Beta-Lactam Antimicrobials from Beta-Lactamase Resistance Genes

The outcome of bacterial infection management relies on prompt diagnosis and effective treatment, but conventional antimicrobial susceptibility testing can be slow and labor-intensive. Therefore, this study aims to predict phenotypic antimicrobial susceptibility of selected beta-lactam antimicrobials in the bacteria of the family Enterobacteriaceae from different beta-lactamase resistance genotypes. Using human datasets extracted from the Antimicrobial Testing Leadership and Surveillance (ATLAS) program conducted by Pfizer and retail meat datasets from the National Antimicrobial Resistance Monitoring System for Enteric Bacteria (NARMS), we used a robust or weighted least square multivariable linear regression modeling framework to explore the relationship between antimicrobial susceptibility data of beta-lactam antimicrobials and different types of beta-lactamase resistance genes. In humans, in the presence of the blaCTX-M-1, blaCTX-M-2, blaCTX-M-8/25, and blaCTX-M-9 groups, MICs of cephalosporins significantly increased by values between 0.34-3.07 μg/mL, however, the MICs of carbapenem significantly decreased by values between 0.81-0.87 μg/mL. In the presence of carbapenemase genes (blaKPC, blaNDM, blaIMP, and blaVIM), the MICs of cephalosporin antimicrobials significantly increased by values between 1.06-5.77 μg/mL, while the MICs of carbapenem antimicrobials significantly increased by values between 5.39-67.38 μg/mL. In retail meat, MIC of ceftriaxone increased significantly in the presence of blaCMY-2, blaCTX-M-1, blaCTX-M-55, blaCTX-M-65, and blaSHV-2 by 55.16 μg/mL, 222.70 μg/mL, 250.81 μg/mL, 204.89 μg/mL, and 31.51 μg/mL respectively. MIC of cefoxitin increased significantly in the presence of blaCTX-M-65 and blaTEM-1 by 1.57 μg/mL and 1.04 μg/mL respectively. In the presence of blaCMY-2, MIC of cefoxitin increased by an average of 8.66 μg/mL over 17 years. Compared to E. coli isolates, MIC of cefoxitin in Salmonella enterica isolates decreased significantly by 0.67 μg/mL. On the other hand, MIC of ceftiofur increased in the presence of blaCTX-M-1, blaCTX-M-65, blaSHV-2, and blaTEM-1 by 8.82 μg/mL, 9.11 μg/mL, 8.18 μg/mL, and 1.04 μg/mL respectively. In the presence of blaCMY-2, MIC of ceftiofur increased by an average of 10.20 μg/mL over 14 years. The ability to predict antimicrobial susceptibility of beta-lactam antimicrobials directly from beta-lactamase resistance genes may help reduce the reliance on routine phenotypic testing with higher turnaround times in diagnostic, therapeutic, and surveillance of antimicrobial-resistant bacteria of the family Enterobacteriaceae.

A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest

BACKGROUND

In recent years, the extensive use of drugs and antibiotics has led to increasing microbial resistance. Therefore, it becomes crucial to explore deep connections between drugs and microbes. However, traditional biological experiments are very expensive and time-consuming. Therefore, it is meaningful to develop efficient computational models to forecast potential microbe-drug associations.

RESULTS

In this manuscript, we proposed a novel prediction model called GARFMDA by combining graph attention networks and bilayer random forest to infer probable microbe-drug correlations. In GARFMDA, through integrating different microbe-drug-disease correlation indices, we constructed two different microbe-drug networks first. And then, based on multiple measures of similarity, we constructed a unique feature matrix for drugs and microbes respectively. Next, we fed these newly-obtained microbe-drug networks together with feature matrices into the graph attention network to extract the low-dimensional feature representations for drugs and microbes separately. Thereafter, these low-dimensional feature representations, along with the feature matrices, would be further inputted into the first layer of the Bilayer random forest model to obtain the contribution values of all features. And then, after removing features with low contribution values, these contribution values would be fed into the second layer of the Bilayer random forest to detect potential links between microbes and drugs.

CONCLUSIONS

Experimental results and case studies show that GARFMDA can achieve better prediction performance than state-of-the-art approaches, which means that GARFMDA may be a useful tool in the field of microbe-drug association prediction in the future. Besides, the source code of GARFMDA is available at https://github.com/KuangHaiYue/GARFMDA.git.

Bioactive VS4-based sonosensitizer for robust chemodynamic, sonodynamic and osteogenic therapy of infected bone defects

BACKGROUND

Most bone defects caused by bone disease or trauma are accompanied by infection, and there is a high risk of infection spread and defect expansion. Traditional clinical treatment plans often fail due to issues like antibiotic resistance and non-union of bones. Therefore, the treatment of infected bone defects requires a strategy that simultaneously achieves high antibacterial efficiency and promotes bone regeneration.

RESULTS

In this study, an ultrasound responsive vanadium tetrasulfide-loaded MXene (VSM) Schottky junction is constructed for rapid methicillin-resistant staphylococcus aureus (MRSA) clearance and bone regeneration. Due to the peroxidase (POD)-like activity of VS4 and the abundant Schottky junctions, VSM has high electron-hole separation efficiency and a decreased band gap, exhibiting a strong chemodynamic and sonodynamic antibacterial efficiency of 94.03%. Under the stimulation of medical dose ultrasound, the steady release of vanadium element promotes the osteogenic differentiation of human bone marrow mesenchymal stem cells (hBMSCs). The in vivo application of VSM in infected tibial plateau bone defects of rats also has a great therapeutic effect, eliminating MRSA infection, then inhibiting inflammation and improving bone regeneration.

CONCLUSION

The present work successfully develops an ultrasound responsive VS4-based versatile sonosensitizer for robust effective antibacterial and osteogenic therapy of infected bone defects.

The Pseudomonas aeruginosa Resistome: Permanent and Transient Antibiotic Resistance, an Overview

One of the most concerning characteristics of Pseudomonas aeruginosa is its low susceptibility to several antibiotics of common use in clinics, as well as its facility to acquire increased resistance levels. Consequently, the study of the antibiotic resistance mechanisms of this bacterium is of relevance for human health. For such a study, different types of resistance should be distinguished. The intrinsic resistome is composed of a set of genes, present in the core genome of P. aeruginosa, which contributes to its characteristic, species-specific, phenotype of susceptibility to antibiotics. Acquired resistance refers to those genetic events, such as the acquisition of mutations or antibiotic resistance genes that reduce antibiotic susceptibility. Finally, antibiotic resistance can be transiently acquired in the presence of specific compounds or under some growing conditions. The current article provides information on methods currently used to analyze intrinsic, mutation-driven, and transient antibiotic resistance in P. aeruginosa.

Modeling spatial evolution of multi-drug resistance under drug environmental gradients

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria, based on a rescaling approach (Gjini and Wood, 2021). We show how the resistance to drugs in space, and the consequent adaptation of growth rate is governed by a Price equation with diffusion. The covariance terms in this equation integrate features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits, to the relative advantage of each mutant across the environment. Such a mathematical understanding allows to predict the precise outcomes of selection over space, ultimately from the fundamental balance between growth and movement traits, and their diversity in a population.

Epigenetic effects of ceftriaxone-resistant Neisseria gonorrhoeae FC428 mosaic-like sequences found in PenA sequences unique to Neisseria subflava and related species

OBJECTIVES

The aim of this study was to explore the origin of the PenA mosaic amino acid sequence in the ceftriaxone-resistant Neisseria gonorrhoeae FC428 clone.

METHODS

The penA sequences of 27 Neisseria subflava pharyngeal isolates were determined by the Sanger method and penA sequences of 52 isolates from nine Neisseria species were obtained from the NCBI database. Comparative analysis of each PenA sequence was performed by multiple sequence alignment using ClustalW. In vitro resistance acquisition experiments were conducted to investigate the possibility of selection pressure by cefixime-induced amino acid substitution mutations in PenA.

RESULTS

All N. subflava strains, including two with low susceptibility to expanded-spectrum cephalosporins (ESCs), possessed the majority of the PenA FC428 sequence. Furthermore, a number of strains, but not all, of closely related species of N. subflava showed similar results. PenA FC428 sequences were also found in some strains of distantly related species. No new mutations in the penA sequence were observed in colonies with increased MIC in in vitro resistance acquisition experiments.

CONCLUSIONS

This study provides strong evidence that the FC428 PenA mosaic sequence originated from N. subflava and related species among oral commensal Neisseria species. The results of in vitro resistance acquisition experiments also suggested that one of the PenA FC428-like sequence gene polymorphisms resulted in the expression of ESC resistance. Furthermore, many of the PenA FC428 mosaic sequences were thought to be involved in the so-called epistasis effect that regulates the expression of resistance, without directly contributing to the resistance level itself.

Promotion of plasmid maintenance by heterogeneous partitioning of microbial communities

Transferable plasmids play a critical role in shaping the functions of microbial communities. Previous studies suggested multiple mechanisms underlying plasmid persistence and abundance. Here, we focus on the interplay between heterogeneous community partitioning and plasmid fates. Natural microbiomes often experience partitioning that creates heterogeneous local communities with reduced population sizes and biodiversity. Little is known about how population partitioning affects the plasmid fate through the modulation of community structure. By modeling and experiments, we show that heterogeneous community partitioning can paradoxically promote the persistence of a plasmid that would otherwise not persist in a global community. Among the local communities created by partitioning, a minority will primarily consist of members able to transfer the plasmid fast enough to support its maintenance by serving as a local plasmid haven. Our results provide insights into plasmid maintenance and suggest a generalizable approach to modulate plasmid persistence for engineering and medical applications.

Chance Favors the Prepared Genomes: Horizontal Transfer Shapes the Emergence of Antibiotic Resistance Mutations in Core Genes

Bacterial lineages acquire novel traits at diverse rates in part because the genetic background impacts the successful acquisition of novel genes by horizontal transfer. Yet, how horizontal transfer affects the subsequent evolution of core genes remains poorly understood. Here, we studied the evolution of resistance to quinolones in Escherichia coli accounting for population structure. We found 60 groups of genes whose gain or loss induced an increase in the probability of subsequently becoming resistant to quinolones by point mutations in the gyrase and topoisomerase genes. These groups include functions known to be associated with direct mitigation of the effect of quinolones, with metal uptake, cell growth inhibition, biofilm formation, and sugar metabolism. Many of them are encoded in phages or plasmids. Although some of the chronologies may reflect epidemiological trends, many of these groups encoded functions providing latent phenotypes of antibiotic low-level resistance, tolerance, or persistence under quinolone treatment. The mutations providing resistance were frequent and accumulated very quickly. Their emergence was found to increase the rate of acquisition of other antibiotic resistances setting the path for multidrug resistance. Hence, our findings show that horizontal gene transfer shapes the subsequent emergence of adaptive mutations in core genes. In turn, these mutations further affect the subsequent evolution of resistance by horizontal gene transfer. Given the substantial gene flow within bacterial genomes, interactions between horizontal transfer and point mutations in core genes may be a key to the success of adaptation processes.

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.

Interkingdom interactions between Pseudomonas aeruginosa and Candida albicans affect clinical outcomes and antimicrobial responses

Infections that involve interkingdom microbial communities, such as those between bacteria and yeast pathogens, are difficult to treat, associated with worse patient outcomes, and may be a source of antimicrobial resistance. In this review, we address co-occurrence and co-infections of Candida albicans and Pseudomonas aeruginosa, two pathogens that occupy multiple infection niches in the human body, especially in immunocompromised patients. The interaction between the pathogen species influences microbe-host interactions, the effectiveness of antimicrobials and even infection outcomes, and may thus require adapted treatment strategies. However, the molecular details of bacteria-fungal interactions both inside and outside the infection sites, are insufficiently characterised. We argue that comprehensively understanding the P. aeruginosa-C. albicans interaction network through integrated systems biology approaches will capture the highly dynamic and complex nature of these polymicrobial infections and lead to a more comprehensive understanding of clinical observations such as reshaped immune defences and low antimicrobial treatment efficacy.

Selective Pressure by Rifampicin Modulates Mutation Rates and Evolutionary Trajectories of Mycobacterial Genomes

Resistance to the frontline antibiotic rifampicin constitutes a challenge to the treatment and control of tuberculosis. Here, we analyzed the mutational landscape of Mycobacterium smegmatis during long-term evolution with increasing concentrations of rifampicin, using a mutation accumulation assay combined with whole-genome sequencing. Antibiotic treatment enhanced the acquisition of mutations, doubling the genome-wide mutation rate of the wild-type cells. While antibiotic exposure led to extinction of almost all wild-type lines, the hypermutable phenotype of the ΔnucS mutant strain (noncanonical mismatch repair deficient) provided an efficient response to the antibiotic, leading to high rates of survival. This adaptative advantage resulted in the emergence of higher levels of rifampicin resistance, an accelerated acquisition of drug resistance mutations in rpoB (β RNA polymerase), and a wider diversity of evolutionary pathways that led to drug resistance. Finally, this approach revealed a subset of adaptive genes under positive selection with rifampicin that could be associated with the development of antibiotic resistance. IMPORTANCE Rifampicin is the most important first-line antibiotic against mycobacterial infections, including tuberculosis, one of the top causes of death worldwide. Acquisition of rifampicin resistance constitutes a major global public health problem that makes the control of the disease challenging. Here, we performed an experimental evolution assay under antibiotic selection to analyze the response and adaptation of mycobacteria, leading to the acquisition of rifampicin resistance. This approach explored the total number of mutations that arose in the mycobacterial genomes under long-term rifampicin exposure, using whole-genome sequencing. Our results revealed the effect of rifampicin at a genomic level, identifying different mechanisms and multiple pathways leading to rifampicin resistance in mycobacteria. Moreover, this study detected that an increase in the rate of mutations led to enhanced levels of drug resistance and survival. In summary, all of these results could be useful to understand and prevent the emergence of drug-resistant isolates in mycobacterial infections.

Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients

Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that mixed strain populations are common in the opportunistic pathogen P. aeruginosa. Crucially, resistance evolves rapidly in patients colonized by multiple strains through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by single strains due to selection for novel resistance mutations. However, strong trade-offs between resistance and growth rate occur in mixed strain populations, suggesting that within-host diversity can also drive the loss of resistance in the absence of antibiotic treatment. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment.

Antimicrobial Activity of Psidium guajava Aqueous Extract against Sensitive and Resistant Bacterial Strains

The inappropriate use of antimicrobials, along with environmental conditions, can lead to the emergence of resistant microorganisms. The use of phytopharmaceuticals and herbal medicines has a positive impact and represents a promising alternative. Psidium guajava extracts have been widely reported to have antimicrobial potential; however, studies reporting their activity against resistant bacterial strains are scarce. Because of the emerging resistance, the aim of this study was to analyze the antimicrobial capacity of the aqueous extract of guava leaves against wild-type and resistant bacterial strains. The aqueous extract obtained from the leaves of P. guajava was evaluated by HPLC for the content of total phenolics and tannins, antioxidant activity, and chemical composition. The antimicrobial activity of the extracts was analyzed by the disk diffusion and broth microdilution methods. The results of the chemical analysis of the extracts showed total phenolics content of 17.02 ± 6.87 mg/g of dry extract, total tannin content of 14.09 ± 1.20 mg of tannic acid equivalents/g of dry extract, and moderate antioxidant capacity with an EC₅₀ value of 140 µg/mL. Flavonoids are the major compounds (rutin, hesperidin, and quercetin), followed by phenolic acids. Disk diffusion test results showed the presence of inhibition halos for Gram-positive bacteria (Staphylococcus aureus, sensitive and resistant; Staphylococcus pseudintermedius, sensitive and resistant; and Streptococcus spp., beta-hemolytic), while for Gram-negative bacteria (Escherichia coli, sensitive and resistant), there was no inhibition in the tested concentration range. The Minimal Inhibitory Concentration was 6.8 mg/mL for all Gram-positive strains evaluated. The present study demonstrated the antimicrobial activity of the aqueous extract of P. guajava against sensitive and resistant Gram-positive bacteria. The better antimicrobial activity found in the present study compared with previously reported activity should be highlighted and may be related to the higher concentration of total phenolics present in the tested extract. Moreover, the content of tannins found suggests a species with high quality that produces tannins. These new findings suggest an innovative profile regarding therapeutic resources that can be adopted to combat resistant microbial strains.

The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.

Characterization and evaluation of the cholesterol-lowering ability of Lactiplantibacillus plantarum HJ-S2 isolated from the intestine of Mesoplodon densirostris

In this study, ten strains of lactic acid bacteria were isolated from the intestine of Blainville's beaked whale (Mesoplodon densirostris),and their cholesterol-lowering activities in vitro and in vivo were investigated. The among these strains, HJ-S2 strain, which identified as Lactiplantibacillus plantarum, showed a high in vitro cholesterol-lowering rate (48.82%). Strain HJ-S2 was resistant to acid and bile salts, with a gastrointestinal survival rate of more than 80%, but was sensitive to antibiotics. Strain HJ-S2 was found to be able to adhere to HT-29 cells in an adhesion test. The number of cell adhesion was 132.52. In addition, we also performed the cholesterol-lowering activities in vivo using high-fat diet feed mouse models. Our results indicated that HJ-S2 reduced total cholesterol (TC), total glycerol (TG), and low-density lipoprotein cholesterol (LDLC) levels while increasing the high-density lipoprotein cholesterol (HDLC) level. It also alleviated the lipid accumulation in high-fat diet feed mouse liver and pancreas. Hence, HJ-S2 demonstrated appropriate cholesterol-lowering ability and has the potential to be used as a probiotic in functional foods.

The evolution of colistin resistance increases bacterial resistance to host antimicrobial peptides and virulence

Antimicrobial peptides (AMPs) offer a promising solution to the antibiotic resistance crisis. However, an unresolved serious concern is that the evolution of resistance to therapeutic AMPs may generate cross-resistance to host AMPs, compromising a cornerstone of the innate immune response. We systematically tested this hypothesis using globally disseminated mobile colistin resistance (MCR) that has been selected by the use of colistin in agriculture and medicine. Here, we show that MCR provides a selective advantage to Escherichia coli in the presence of key AMPs from humans and agricultural animals by increasing AMP resistance. Moreover, MCR promotes bacterial growth in human serum and increases virulence in a Galleria mellonella infection model. Our study shows how the anthropogenic use of AMPs can drive the accidental evolution of resistance to the innate immune system of humans and animals. These findings have major implications for the design and use of therapeutic AMPs and suggest that MCR may be difficult to eradicate, even if colistin use is withdrawn.

Interspecies interaction reduces selection for antibiotic resistance in Escherichia coli

Evolution of microbial traits depends on the interaction of a species with its environment as well as with other coinhabiting species. However, our understanding of the evolution of specific microbial traits, such as antibiotic resistance in complex environments is limited. Here, we determine the role of interspecies interactions on the dynamics of nitrofurantoin (NIT) resistance selection among Escherichia coli. We created a synthetic two-species community comprised of two variants of E. coli (NIT susceptible and resistant) and Bacillus subtilis in minimal media with glucose as the sole carbon source. We show that the presence of B. subtilis significantly slows down the selection for the resistant E. coli mutant when NIT is present and that this slowdown is not due to competition for resources. Instead, the dampening of NIT resistance enrichment is largely mediated by extracellular compounds produced by B. subtilis with the peptide YydF playing a significant role. Our results not only demonstrate the impact of interspecies interactions on the evolution of microbial traits but also show the importance of using synthetic microbial systems in unravelling relevant interactions and mechanisms affecting the evolution of antibiotic resistance. This finding implies that interspecies interactions should be considered to better understand and predict resistance evolution in the clinic as well as in nature.

Colistin- and amikacin-loaded lipid-based drug delivery systems for resistant gram-negative lung and wound bacterial infections

Antimicrobial resistance (AMR) is a global health issue, which needs to be tackled without further delay. The World Health Organization(WHO) has classified three gram-negative bacteria, Pseudomonas aeruginosa, Klebsiella pneumonia and Acinetobacter baumannii, as the principal responsible for AMR, mainly causing difficult to treat nosocomial lung and wound infections. In this regard, the need for colistin and amikacin, the re-emerged antibiotics of choice for resistant gram-negative infections, will be examined as well as their associated toxicity. Thus, current but ineffective clinical strategies designed to prevent toxicity related to colistin and amikacin will be reported, highlighting the importance of lipid-based drug delivery systems (LBDDSs), such as liposomes, solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs), as efficient delivery strategies for reducing antibiotic toxicity. This review reveals that colistin- and amikacin-NLCs are promising carriers with greater potential than liposomes and SLNs to safely tackle AMR, especially for lung and wound infections.

Ecology, more than antibiotics consumption, is the major predictor for the global distribution of aminoglycoside-modifying enzymes

Antibiotic consumption and its abuses have been historically and repeatedly pointed out as the major driver of antibiotic resistance emergence and propagation. However, several examples show that resistance may persist despite substantial reductions in antibiotic use, and that other factors are at stake. Here, we study the temporal, spatial, and ecological distribution patterns of aminoglycoside resistance, by screening more than 160,000 publicly available genomes for 27 clusters of genes encoding aminoglycoside-modifying enzymes (AME genes). We find that AME genes display a very ubiquitous pattern: about 25% of sequenced bacteria carry AME genes. These bacteria were sequenced from all the continents (except Antarctica) and terrestrial biomes, and belong to a wide number of phyla. By focusing on European countries between 1997 and 2018, we show that aminoglycoside consumption has little impact on the prevalence of AME-gene-carrying bacteria, whereas most variation in prevalence is observed among biomes. We further analyze the resemblance of resistome compositions across biomes: soil, wildlife, and human samples appear to be central to understand the exchanges of AME genes between different ecological contexts. Together, these results support the idea that interventional strategies based on reducing antibiotic use should be complemented by a stronger control of exchanges, especially between ecosystems.

Factors associated with plasmid antibiotic resistance gene carriage revealed using large-scale multivariable analysis

Plasmids are major vectors of bacterial antibiotic resistance, but understanding of factors associated with plasmid antibiotic resistance gene (ARG) carriage is limited. We curated > 14,000 publicly available plasmid genomes and associated metadata. Duplicate and replicate plasmids were excluded; where possible, sample metadata was validated externally (BacDive database). Using Generalised Additive Models (GAMs) we assessed the influence of 12 biotic/abiotic factors (e.g. plasmid genetic factors, isolation source, collection date) on ARG carriage, modelled as a binary outcome. Separate GAMs were built for 10 major ARG types. Multivariable analysis indicated that plasmid ARG carriage patterns across time (collection years), isolation sources (human/livestock) and host bacterial taxa were consistent with antibiotic selection pressure as a driver of plasmid-mediated antibiotic resistance. Only 0.42% livestock plasmids carried carbapenem resistance (compared with 12% human plasmids); conversely, tetracycline resistance was enriched in livestock vs human plasmids, reflecting known prescribing practices. Interpreting results using a timeline of ARG type acquisition (determined by literature review) yielded additional novel insights. More recently acquired ARG types (e.g. colistin and carbapenem) showed increases in plasmid carriage during the date range analysed (1994-2019), potentially reflecting recent onset of selection pressure; they also co-occurred less commonly with ARGs of other types, and virulence genes. Overall, this suggests that following acquisition, plasmid ARGs tend to accumulate under antibiotic selection pressure and co-associate with other adaptive genes (other ARG types, virulence genes), potentially re-enforcing plasmid ARG carriage through co-selection.

Comparative selective pressure potential of antibiotics in the environment

To guide both environmental and public health policy, it is important to assess the degree of antibiotic resistance selection pressure under measured environmental concentrations (MECs), and to compare the efficacy of different mitigation strategies to minimize the spread of resistance. To this end, the resistance selection and enrichment potential due to antibiotic emissions into the environment must be analysed from a life cycle perspective, for a wide range of antibiotics, and considering variations in the underlying fitness costs between different resistance mutations and genes. The aim of this study is to consistently derive fitness cost-dependent minimum selective concentrations (MSCs) from readily available bacterial inhibition data and to build MSC-based species sensitivity distributions (SSDs). These are then used to determine antibiotic-specific resistance selection concentrations predicted to promote resistance in 5% of exposed bacterial species (RSC₅). Using a previously developed competition model, we provide estimated MSC₁₀ endpoints for 2,984 antibiotic and bacterial species combinations; the largest set of modelled MSCs available to date. Based on constructed SSDs, we derive RSC₅ for 128 antibiotics with four orders of magnitude difference in their 'selective pressure potential' in the environment. By comparing our RSC₅ to MECs, we highlight specific environmental compartments (e.g. hospital and wastewater effluents, lakes and rivers), as well as several antibiotics (e.g. ciprofloxacin, norfloxacin, enrofloxacin, and tetracycline), to be scrutinized for their potential role in resistance selection and dissemination. In addition to enabling comparative risk screening of the selective pressure potential of multiple antibiotics, our SSD-derived RSC₅ provide the point of departure for calculating new life cycle-based characterization factors for antibiotics to compare mitigation strategies, thereby contributing towards a 'One-Health' approach to tackling the global antibiotic resistance crisis.

Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations

Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.

Bioaccumulation of antibiotics and resistance genes in lettuce following cattle manure and digestate fertilization and their effects on soil and phyllosphere microbial communities

The degradation and bioaccumulation of selected antibiotics such as the sulfonamide sulfamethoxazole (SMX) and the fluoroquinolones enrofloxacin (ENR) and ciprofloxacin (CIP) were investigated in soil microcosm experiments where Lactuca sativa was grown with manure or digestate (1%) and spiked with a mixture of the three antibiotics (7.5 mg/kg each). The soil, rhizosphere and leaf phyllosphere were sampled (at 0 and 46 days) from each microcosm to analyze the antibiotic concentrations, main resistance genes (sul1, sul2, qnrS, aac-(6')-Ib-crand qepA), the intI1and tnpA mobile genetic elements and the microbial community structure.Overall results showed that SMX and CIP decreased (70-85% and 55-79%, respectively), and ENR was quite persistent during the 46-day experiment. In plant presence, CIP and ENR were partially up-taken from soil to plant. In fact the bioaccumulation factors were > 1, with higher values in manure than digestate amended soils. The most abundant gene in soil was sul2 in digestate- and aac-(6')-Ib-cr in the manure-amended microcosms. In soil, neither sulfamethoxazole-resistance (sul1 and sul2), nor fluoroquinolone-resistance (aac-(6')-Ib-cr, qepA and qnrS) gene abundances were correlated with any antibiotic concentration. On the contrary, in lettuce leaves, the aac-(6')-Ib-cr gene was the most abundant, in accordance with the fluoroquinolone bioaccumulation. Finally, digestate stimulated a higher soil microbial biodiversity, introducing and promoting more bacterial genera associated with antibiotic degradation and involved in soil fertility and decreased fluoroquinolone bioaccumulation.

Diversity and emergence of multi-resistant Staphylococcus spp. isolated from subclinical mastitis in cows in of the state of Piauí, Brazil

This research aimed to identify the diversity of bacterial species of the genus Staphylococcus spp. in subclinical mastitis in dairy herds in the state of Piauí, Northeastern Brazil, and to evaluate the phenotypic and genotypic resistance profile. Samples were obtained from a total of 17 dairy farms, amounting to 321 positive samples in the California Mastitis Test. Staphylococcus spp. were identified by matrix-assisted laser desorption ionization time-of-flight mass spectroscopy. Subsequently, an antibiogram was performed, and a polymerase chain reaction was carried out to screen for resistance genes in the isolates. Among all the isolates, 59.45% (110/185) belonged to the Staphylococcus genus. Moreover, the following Staphylococcus spp. were identified Staphylococcus aureus, 68.1% (75/110); Staphylococcus chromogenes, 12.7% (14/110); Staphylococcus epidermidis, 5.4% (6/110); Staphylococcus sciuri, 4.5% (5/110); Staphylococcus warneri, 2.7% (3/110); Staphylococcus haemolyticus, 1.8% (2/110); Staphylococcus hominis, 1.8% (2/110); Staphylococcus arlettae, 0.9% (1/110); Staphylococcus capitis, 0.9% (1/110); and Staphylococcus gallinarum, 0.9% (1/110). The antibiogram showed a high frequency of resistance to penicillin and ampicillin, 70.0% (77/110) and 61.8% (68/110), respectively, and a low frequency of resistance to gentamicin and vancomycin, 10.9% (12/110) and 11.8% (13/110), respectively. In the genotypic tests for the different species of Staphylococcus spp., the occurrence of the blaZ gene was observed in 60.9% (67/110) of the isolates, followed by tetL and tetM, both with 20.0% (22/110) each, and the mecA and vanB genes were detected in 0.9% (1/110) of the samples. The identification of all Staphylococcus species isolated from subclinical mastitis cases and the phenotypic and genotypic resistance characterization in these isolates is of great importance for dairy farming in the state of Piauí, as well as for public health.

The Extent of Antimicrobial Resistance Due to Efflux Pump Regulation

A key mechanism driving antimicrobial resistance (AMR) stems from the ability of bacteria to up-regulate efflux pumps upon exposure to drugs. The resistance gained by this up-regulation is pliable because of the tight regulation of efflux pump levels. This leads to temporary enhancement in survivability of bacteria due to higher efflux pump levels in the presence of antibiotics, which can be reversed when the cells are no longer exposed to the drug. Knowledge of the extent of resistance thus gained would inform intervention strategies aimed at mitigating AMR. Here, we combine mathematical modeling and experiments to quantify the maximum extent of resistance that efflux pump up-regulation can confer via phenotypic induction in the presence of drugs and genotypic abrogation of regulation. Our model describes the dynamics of drug transport in and out of cells coupled with the associated regulation of efflux pump levels and predicts the increase in the minimum inhibitory concentration (MIC) of drugs due to such regulation. To test the model, we measured the uptake and efflux as well as the MIC of the compound ethidium bromide (EtBr), a substrate of the efflux pump LfrA, in wild-type Mycobacterium smegmatis mc²155, as well as in two laboratory-generated strains. Our model captured the observed EtBr levels and MIC fold-changes quantitatively. Further, the model identified key parameters associated with the resulting resistance, variations in which could underlie the extent to which such resistance arises across different drug-bacteria combinations, potentially offering tunable handles to optimize interventions aimed at minimizing AMR.

The evolving biology of Mycobacterium tuberculosis drug resistance

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb) is an ancient disease that has remained a leading cause of infectious death. Mtb has evolved drug resistance to every antibiotic regimen ever introduced, greatly complicating treatment, lowering rates of cure and menacing TB control in parts of the world. As technology has advanced, our understanding of antimicrobial resistance has improved, and our models of the phenomenon have evolved. In this review, we focus on recent research progress that supports an updated model for the evolution of drug resistance in Mtb. We highlight the contribution of drug tolerance on the path to resistance, and the influence of heterogeneity on tolerance. Resistance is likely to remain an issue for as long as drugs are needed to treat TB. However, with technology driving new insights and careful management of newly developed resources, antimicrobial resistance need not continue to threaten global progress against TB, as it has done for decades.

Genomic analysis of plasmid content in food isolates of E. coli strongly supports its role as a reservoir for the horizontal transfer of virulence and antibiotic resistance genes

The link between E. coli strains contaminating foods and human disease is unclear, with some reports supporting a direct transmission of pathogenic strains via food and others highlighting their role as reservoirs for resistance and virulence genes. Here we take a genomics approach, analyzing a large set of fully-assembled genomic sequences from E. coli available in GenBank. Most of the strains isolated in food are more closely related to each other than to clinical strains, arguing against a frequent direct transmission of pathogenic strains from food to the clinic. We also provide strong evidence of genetic exchanges between food and clinical strains that are facilitated by plasmids. This is based on an overlapped representation of virulence and resistance genes in plasmids isolated from these two sources. We identify clusters of phylogenetically-related plasmids that are largely responsible for the observed overlap and see evidence of specialization, with some food plasmid clusters preferentially transferring virulence factors over resistance genes. Consistent with these observations, food plasmids have a high mobilization potential based on their plasmid taxonomic unit classification and on an analysis of mobilization gene content. We report antibiotic resistance genes of high clinical relevance and their specific incompatibility group associations. Finally, we also report a striking enrichment for adhesins in food plasmids and their association with specific IncF replicon subtypes. The identification of food plasmids with specific markers (Inc and PTU combinations) as mediators of horizontal transfer between food and clinical strains opens new research avenues and should assist with the design of surveillance strategies.

Molecular Evolution of the Pseudomonas aeruginosa DNA Gyrase gyrA Gene

DNA gyrase plays important roles in genome replication in various bacteria, including Pseudomonasaeruginosa. The gyrA gene encodes the gyrase subunit A protein (GyrA). Mutations in GyrA are associated with resistance to quinolone-based antibiotics. We performed a detailed molecular evolutionary analyses of the gyrA gene and associated resistance to the quinolone drug, ciprofloxacin, using bioinformatics techniques. We produced an evolutionary phylogenetic tree using the Bayesian Markov Chain Monte Carlo (MCMC) method. This tree indicated that a common ancestor of the gene was present over 760 years ago, and the offspring formed multiple clusters. Quinolone drug-resistance-associated amino-acid substitutions in GyrA, including T83I and D87N, emerged after the drug was used clinically. These substitutions appeared to be positive selection sites. The molecular affinity between ciprofloxacin and the GyrA protein containing T83I and/or D87N decreased significantly compared to that between the drug and GyrA protein, with no substitutions. The rate of evolution of the gene before quinolone drugs were first used in the clinic, in 1962, was significantly lower than that after the drug was used. These results suggest that the gyrA gene evolved to permit the bacterium to overcome quinolone treatment.

Metagenomic Characterization of Resistance Genes in Deception Island and Their Association with Mobile Genetic Elements

Antibiotic resistance genes (ARGs) are undergoing a remarkably rapid geographic expansion in various ecosystems, including pristine environments such as Antarctica. The study of ARGs and environmental resistance genes (ERGs) mechanisms could provide a better understanding of their origin, evolution, and dissemination in these pristine environments. Here, we describe the diversity of ARGs and ERGs and the importance of mobile genetic elements as a possible mechanism for the dissemination of resistance genes in Antarctica. We analyzed five soil metagenomes from Deception Island in Antarctica. Results showed that detected ARGs are associated with mechanisms such as antibiotic efflux, antibiotic inactivation, and target alteration. On the other hand, resistance to metals, surfactants, and aromatic hydrocarbons were the dominant ERGs. The taxonomy of ARGs showed that Pseudomonas, Psychrobacter, and Staphylococcus could be key taxa for studying antibiotic resistance and environmental resistance to stress in Deception Island. In addition, results showed that ARGs are mainly associated with phage-type mobile elements suggesting a potential role in their dissemination and prevalence. Finally, these results provide valuable information regarding the ARGs and ERGs in Deception Island including the potential contribution of mobile genetic elements to the spread of ARGs and ERGs in one of the least studied Antarctic ecosystems to date.

Evolutionary Instability of Collateral Susceptibility Networks in Ciprofloxacin-Resistant Clinical Escherichia coli Strains

Collateral sensitivity and resistance occur when resistance development toward one antimicrobial either potentiates or deteriorates the effect of others. Previous reports on collateral effects on susceptibility focus on newly acquired resistance determinants and propose that novel treatment guidelines informed by collateral networks may reduce the evolution, selection, and spread of antimicrobial resistance. In this study, we investigate the evolutionary stability of collateral networks in five ciprofloxacin-resistant, clinical Escherichia coli strains. After 300 generations of experimental evolution without antimicrobials, we show complete fitness restoration in four of five genetic backgrounds and demonstrate evolutionary instability in collateral networks of newly acquired resistance determinants. We show that compensatory mutations reducing efflux expression are the main drivers destabilizing initial collateral networks and identify rpoS as a putative target for compensatory evolution. Our results add another layer of complexity to future predictions and clinical application of collateral networks.

Evolution of Habitat-Dependent Antibiotic Resistance in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic human pathogen that usually causes difficult-to-treat infections due to its low intrinsic antibiotic susceptibility and outstanding capacity for becoming resistant to antibiotics. In addition, it has a remarkable metabolic versatility, being able to grow in different habitats, from natural niches to different and changing inpatient environments. Study of the environmental conditions that shape genetic and phenotypic changes of P. aeruginosa toward antibiotic resistance supposes a novelty, since experimental evolution assays are usually performed with well-defined antibiotics in regular laboratory growth media. Therefore, in this work we address the extent to which the nutrients’ availability may constrain the evolution of antibiotic resistance. We determined that P. aeruginosa genetic trajectories toward resistance to tobramycin, ceftazidime, and ceftazidime-avibactam are different when evolving in laboratory rich medium, urine, or synthetic sputum. Furthermore, our study, linking genotype with phenotype, showed a clear impact of each analyzed environment on both the fitness and resistance level associated with particular resistance mutations. This indicates that the phenotype associated with specific resistance mutations is variable and dependent on the bacterial metabolic state in each particular habitat. Our results support that the design of evolution-based strategies to tackle P. aeruginosa infections should be based on robust patterns of evolution identified within each particular infection and body location.

IMPORTANCE Predicting evolution toward antibiotic resistance (AR) and its associated trade-offs, such as collateral sensitivity, is important to design evolution-based strategies to tackle AR. However, the effect of nutrients' availability on such evolution, particularly those that can be found under in vivo infection conditions, has been barely addressed. We analyzed the evolutionary patterns of P. aeruginosa in the presence of antibiotics in different media, including urine and synthetic sputum, whose compositions are similar to the ones in infections, finding that AR evolution differs, depending on growth conditions. Furthermore, the representative mutants isolated under each condition tested render different AR levels and fitness costs, depending on nutrients’ availability, supporting the idea that environmental constraints shape the phenotypes associated with specific AR mutations. Consequently, the selection of AR mutations that render similar phenotypes is environment dependent. The analysis of evolution patterns toward AR requires studying growth conditions mimicking those that bacteria face during in vivo evolution.

Localized pmrB hypermutation drives the evolution of colistin heteroresistance

Colistin has emerged as an important last line of defense for the treatment of infections caused by antibiotic-resistant gram-negative pathogens, but colistin resistance remains poorly understood. Here, we investigate the responses of ≈1,000 populations of a multi-drug-resistant (MDR) strain of P. aeruginosa to a high dose of colistin. Colistin exposure causes rapid cell death, but some populations eventually recover due to the growth of sub-populations of heteroresistant cells. Heteroresistance is unstable, and resistance is rapidly lost under culture in colistin-free medium. The evolution of heteroresistance is primarily driven by selection for heteroresistance at two hotspot sites in the PmrAB regulatory system. Localized hypermutation of pmrB generates colistin resistance at 10³–10⁴ times the background resistance mutation rate (≈2 × 10^-5 per cell division). PmrAB provides resistance to antimicrobial peptides that are involved in host immunity, suggesting that this pathogen may have evolved a highly mutable pmrB as an adaptation to host immunity.

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Pseudomonas populations recover from colistin due to the growth of heteroresistant cells

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Heteroresistance is driven by pre-existing mutations in the PmrAB regulatory system

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pmrB mutations arise at 10³–10⁴ times the background mutation rate

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Heteroresistance is unstable and is rapidly lost in the absence of colistin

Empirical estimates of the mutation rate for an alphabaculovirus

Mutation rates are of key importance for understanding evolutionary processes and predicting their outcomes. Empirical mutation rate estimates are available for a number of RNA viruses, but few are available for DNA viruses, which tend to have larger genomes. Whilst some viruses have very high mutation rates, lower mutation rates are expected for viruses with large genomes to ensure genome integrity. Alphabaculoviruses are insect viruses with large genomes and often have high levels of polymorphism, suggesting high mutation rates despite evidence of proofreading activity by the replication machinery. Here, we report an empirical estimate of the mutation rate per base per strand copying (s/n/r) of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). To avoid biases due to selection, we analyzed mutations that occurred in a stable, non-functional genomic insert after five serial passages in Spodoptera exigua larvae. Our results highlight that viral demography and the stringency of mutation calling affect mutation rate estimates, and that using a population genetic simulation model to make inferences can mitigate the impact of these processes on estimates of mutation rate. We estimated a mutation rate of μ = 1×10⁻⁷ s/n/r when applying the most stringent criteria for mutation calling, and estimates of up to μ = 5×10⁻⁷ s/n/r when relaxing these criteria. The rates at which different classes of mutations accumulate provide good evidence for neutrality of mutations occurring within the inserted region. We therefore present a robust approach for mutation rate estimation for viruses with stable genomes, and strong evidence of a much lower alphabaculovirus mutation rate than supposed based on the high levels of polymorphism observed.

Virus populations can evolve rapidly, driven by the large number of mutations that occur during virus replication. It is challenging to measure mutation rates because selection will affect which mutations are observed: beneficial mutations are overrepresented in virus populations, while deleterious mutations are selected against and therefore underrepresented. Few mutation rates have been estimated for viruses with large DNA genomes, and there are no estimates for any insect virus. Here, we estimate the mutation rate for an alphabaculovirus, a virus that infects caterpillars and has a large, 134 kilobase pair DNA genome. To ensure that selection did not bias our estimate of mutation rate, we studied which mutations occurred in a large artificial region inserted into the virus genome, where mutations did not affect viral fitness. We deep sequenced evolved virus populations, and compared the distribution of observed mutants to predictions from a simulation model to estimate mutation rate. We found evidence for a relatively low mutation rate, of one mutation in every 10 million bases replicated. This estimate is in line with expectations for a DNA virus with self-correcting replication machinery and a large genome.

Evolved resistance to a novel cationic peptide antibiotic requires high mutation supply

Background and Objectives

A key strategy for resolving the antibiotic resistance crisis is the development of new drugs with antimicrobial properties. The engineered cationic antimicrobial peptide WLBU2 (also known as PLG0206) is a promising broad-spectrum antimicrobial compound that has completed Phase I clinical studies. It has activity against Gram-negative and Gram-positive bacteria including infections associated with biofilm. No definitive mechanisms of resistance to WLBU2 have been identified.

Methodology

Here, we used experimental evolution under different levels of mutation supply and whole genome sequencing (WGS) to detect the genetic pathways and probable mechanisms of resistance to this peptide. We propagated populations of wild-type and hypermutator Pseudomonas aeruginosa in the presence of WLBU2 and performed WGS of evolved populations and clones.

Results

Populations that survived WLBU2 treatment acquired a minimum of two mutations, making the acquisition of resistance more difficult than for most antibiotics, which can be tolerated by mutation of a single target. Major targets of resistance to WLBU2 included the orfN and pmrB genes, previously described to confer resistance to other cationic peptides. More surprisingly, mutations that increase aggregation such as the wsp pathway were also selected despite the ability of WLBU2 to kill cells growing in a biofilm.

Conclusions and implications

The results show how experimental evolution and WGS can identify genetic targets and actions of new antimicrobial compounds and predict pathways to resistance of new antibiotics in clinical practice.

A Microfluidic Chip for Studies of the Dynamics of Antibiotic Resistance Selection in Bacterial Biofilms

Biofilms are arguably the most important mode of growth of bacteria, but how antibiotic resistance emerges and is selected in biofilms remains poorly understood. Several models to study evolution of antibiotic resistance have been developed, however, their usability varies depending on the nature of the biological question. Here, we developed and validated a microfluidic chip (Brimor) for studying the dynamics of enrichment of antibiotic-resistant bacteria in biofilms using real-time monitoring with confocal microscopy. In situ extracellular cellulose staining and physical disruption of the biomass confirmed Escherichia coli growth as biofilms in the chip. We showed that seven generations of growth occur in 16 h when biofilms were established in the growth chambers of Brimor, and that bacterial death and growth rates could be estimated under these conditions using a plasmid with a conditional replication origin. Additionally, competition experiments between antibiotic-susceptible and -resistant bacteria at sub-inhibitory concentrations demonstrated that the antibiotic ciprofloxacin selected for antibiotic resistance in bacterial biofilms at concentrations 17-fold below the minimal inhibitory concentration of susceptible planktonic bacteria. Overall, the microfluidic chip is easy to use and a relevant model for studying the dynamics of selection of antibiotic resistance in bacterial biofilms and we anticipate that the Brimor chip will facilitate basic research in this area.