The fitness costs of antibiotic resistance mutations

Growth fitness, virulence, and heat tolerance of Salmonella Typhimurium variants resistant to food preservation methods

To study potential ramifications of antimicrobial resistance, we carried out adaptive laboratory evolution assays (ALE) to isolate three resistant variants (RVs) of Salmonella enterica Typhimurium, employing three different types of food preservation methods: 1) an emergent technology, plasma-activated water (PAW), leading to variant RV-PAW; a traditional method, heat, leading to variant RV-HT, and a natural antimicrobial compound, carvacrol, leading to variant RV-CAR. The variant resistant to plasma-activated water, RV-PAW, had mutations in rpoA and rpoD; it showed increased tolerance to heat in orange juice but ultimately did not pose a significant threat, as it exhibited a fitness cost at refrigeration temperature (8 °C), whereas its virulence against Caenorhabditis elegans decreased. The variant resistant to heat, RV-HT, had mutations in flhC, dnaJ: it exhibited a fitness cost at high growth temperatures (43 °C) and induced morphofunctional alterations in C. elegans. The variant resistant to carvacrol, RV-CAR, had mutations in sseG, flhA, wbaV, lon; this variant not only exhibited significantly higher thermotolerance in both laboratory media and food models but also effectively increased its growth fitness at refrigeration temperatures while retaining its virulence, evidenced by the highest percentage of Smurf phenotype in C. elegans. To address these challenges, we applied a process combining thermal treatment with citral, with the aim of leveraging the sublethal damage caused in RVs by heat treatments in orange juice. This approach achieves enhanced microbial inactivation without having to escalate the intensity of the thermal treatment. The result was particularly encouraging in the case of RV-CAR, the most challenging strain, for which we improved lethality by up to 3 log10 inactivation cycles.

Clinically relevant mutations in regulatory regions of metabolic genes facilitate early adaptation to ciprofloxacin in Escherichia coli

The genomic landscape associated with early adaptation to ciprofloxacin is poorly understood. Although the interplay between core metabolism and antimicrobial resistance is being increasingly recognized, mutations in metabolic genes and their biological role remain elusive. Here, we exposed Escherichia coli to increasing gradients of ciprofloxacin with intermittent transfer-bottlenecking and identified mutations in three non-canonical targets linked to metabolism including a deletion (tRNA-ArgΔ414-bp) and point mutations in the regulatory regions of argI (ARG box) and narU. Our findings suggest that these mutations modulate arginine and carbohydrate metabolism, facilitate anaerobiosis and increased ATP production during ciprofloxacin stress. Furthermore, mutations in the regulatory regions of argI and narU were detected in over 70% of sequences from clinical E. coli isolates and were overrepresented among ciprofloxacin-resistant isolates. In sum, we have identified clinically relevant mutations in the regulatory regions of metabolic genes as a central theme that drives physiological changes necessary for adaptation to ciprofloxacin stress.

A birth-death model to understand bacterial antimicrobial heteroresistance from time-kill curves

Antimicrobial heteroresistance refers to the presence of different subpopulations with heterogeneous antimicrobial responses within the same bacterial isolate, so they show reduced susceptibility compared with the main population. Though it is widely accepted that heteroresistance can play a crucial role in the outcome of antimicrobial treatments, predictive Antimicrobial Resistance (AMR) models accounting for bacterial heteroresistance are still scarce and need to be refined as the techniques to measure heteroresistance become standardised and consistent conclusions are drawn from data. In this work, we propose a multivariate Birth-Death (BD) model of bacterial heteroresistance and analyse its properties in detail. Stochasticity in the population dynamics is considered since heteroresistance is often characterised by low initial frequencies of the less susceptible subpopulations, those mediating AMR transmission and potentially leading to treatment failure. We also discuss the utility of the heteroresistance model for practical applications and calibration under realistic conditions, demonstrating that it is possible to infer the model parameters and heteroresistance distribution from time-kill data, i.e., by measuring total cell counts alone and without performing any heteroresistance test.

Insights into macrolide resistance in Arcobacter butzleri: potential resistance mechanisms and impact on bacterial fitness and virulence

BACKGROUND

Macrolides are recommended for treating the emerging enteropathogen Arcobacter butzleri; nonetheless, this bacterium often exhibits highly variable resistance rates, and the mechanisms behind this resistance phenotype remain largely unexplored.

OBJECTIVES

To understand the phenotypic and genotypic consequences associated with the acquisition of erythromycin resistance in A. butzleri, as well as the effects on the fitness of this species.

METHODS

Resistant strains resulting from spontaneous mutations and adaptive laboratory evolution under increasing erythromycin concentrations were examined regarding their cross-resistance and collateral susceptibility profiles. Genetic causes of phenotypic antibiotic resistance were analysed by sequencing and bioinformatics, with functional correlation through ethidium bromide accumulation assays. Growth profiles in the presence and absence of erythromycin, motility and biofilm formation abilities were assessed to detect potential changes in fitness and virulence.

RESULTS

Clones from spontaneous mutation rate evolution demonstrated decreased susceptibility to erythromycin and other classes of antibiotics, associated with mutations in the transcriptional repressor areR, causing overexpression of the AreABC efflux pump. In turn, WGS analysis of the evolved strain showed additional mutations in the ribosomal proteins L4 and L22 and in the areR gene. Furthermore, the acquisition of macrolide resistance altered A. butzleri virulence and entailed a high biological cost.

CONCLUSIONS

The findings of this study have proved that efflux activity contributes synergistically with mutations in the ribosomal proteins L4 and L22 to A. butzleri's high-level macrolide resistance. The results further suggest an impact on the bacterial physiology and virulence, with the increased fitness cost justifying the low worldwide prevalence of high-level resistant circulating strains.

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.

Impact of multidrug resistance on the virulence and fitness of Pseudomonas aeruginosa: a microbiological and clinical perspective

Pseudomonas aeruginosa is one of the most common nosocomial pathogens and part of the top emergent species associated with antimicrobial resistance that has become one of the greatest threat to public health in the twenty-first century. This bacterium is provided with a wide set of virulence factors that contribute to pathogenesis in acute and chronic infections. This review aims to summarize the impact of multidrug resistance on the virulence and fitness of P. aeruginosa. Although it is generally assumed that acquisition of resistant determinants is associated with a fitness cost, several studies support that resistance mutations may not be associated with a decrease in virulence and/or that certain compensatory mutations may allow multidrug resistance strains to recover their initial fitness. We discuss the interplay between resistance profiles and virulence from a microbiological perspective but also the clinical consequences in outcomes and the economic impact.

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

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

Resistance or tolerance? Highlighting the need for precise terminology in the field of disinfection

The terms 'resistance' and 'tolerance' are well defined in the context of antibiotic research. However, in the field of disinfection, these terms are often used synonymously, which creates ambiguity and can lead to misunderstandings and misconceptions. In addition, this inconsistency in terminology makes it difficult to assess the risk of a disinfectant resistance. This general review aims to discuss existing definitions of the terms 'adaptation', 'susceptibility', 'tolerance', 'persistence' and 'resistance' in the light of disinfectants. The most ambiguity is found between tolerance and resistance. Whereas the former describes the not necessarily heritable survival of transient exposure to usually lethal concentrations, resistance is the strictly heritable ability to survive otherwise lethal concentrations of an antimicrobial agent, regardless of exposure time. A simple transfer of experience from antibiotic research is not recommended when assessing the risk of resistance to disinfectants, as there are important differences between antibiotics and disinfectants, although both are antimicrobials: (i) disinfectants are usually applied at concentrations that exceed the minimum inhibitory concentration by orders of magnitude, (ii) the exposure times of disinfectants are in the range of seconds, minutes, or a few hours, (iii) the mode of action of disinfectants is less specific, and (iv) disinfectants often contain more than one active agent with additive or synergistic effects. It is important to recognize that disinfectants, like other antimicrobial agents such as antibiotics, have a dualistic nature and should be used correctly and with caution.

Quantitative Microbial Risk Assessment of Antibiotic-Resistant E. coli, Legionella pneumophila, and Mycobacteria in Nonpotable Wastewater Reuse Applications

Antibiotic-resistant bacteria (ARB) have become a major threat to public health and modern medicine. A simple death kinetics-based dose-response model (SD-DRM) was incorporated into a quantitative microbial risk assessment (QMRA) to assess the risks of exposure to reclaimed wastewater harboring antibiotic-resistant E. coli, Legionella pneumophila, and Mycobacterium avium for multiple exposure scenarios. The fractions of ARB and trace antibiotics present in the body were incorporated to demonstrate their impact on infection risks. Both ARB and antibiotic susceptible bacteria, ASB, are assumed to have the same dose-response in the absence of antibiotics but behave differently in the presence of residual antibiotics in the body. Annual risk of L. pneumophila infection exceeded the EPA 10-4 pppy (per person per year) benchmark at concentrations in reclaimed water greater than 103-104 CFU/L, depending on parameter variation. Enteropathogenic E. coli infection risks meet the EPA annual benchmark at concentrations around 105-106 total E. coli. The results illustrated that an increase in residual antibiotics from 0 to 40% of the minimum inhibitory concentration (MIC) reduced the risk by about 1 order of magnitude for E. coli but was more likely to result in an untreatable infection.

The effect of antibiotic selection on collateral effects and evolvability of uropathogenic Escherichia coli

Trimethoprim is recommended as a first-line treatment of urinary tract infections (UTIs) in the UK. In 2018, 31.4% of Escherichia coli isolated from UTIs in England were trimethoprim-resistant, leading to overreliance on other first and second-line antibiotics. Here, we assessed whether, in principle, prior selection with trimethoprim results in collateral effects to other antibiotics recommended for the treatment of UTIs. As collateral effects, we considered changes in susceptibility, mutation-selection window and population establishment probability. We selected 10 trimethoprim-resistant derivatives from three clinical isolates of uropathogenic Escherichia coli. We found that mutations conferring trimethoprim resistance did not have any collateral effects on fosfomycin. In contrast, resistance to trimethoprim resulted in decreased susceptibility (collateral resistance) to nitrofurantoin, below the clinical breakpoint and narrowed the mutation-selection window, thereby reducing the maximum concentration for selection of nitrofurantoin resistance mutations. Our analyses demonstrate that multiple collateral responses should be accounted for when predicting and optimising antibiotic use, limiting future antimicrobial resistance emergence.

The atypical antipsychotic aripiprazole alters the outcome of disseminated Candida albicans infections

Invasive fungal infections impose an enormous clinical, social, and economic burden on humankind. One of the most common species responsible for invasive fungal infections is Candida albicans. More than 30% of patients with disseminated candidiasis fail therapy with existing antifungal drugs, including the widely used azole class. We previously identified a collection of 13 medications that antagonize the activity of the azoles on C. albicans. Although gain-of-function mutations responsible for antifungal resistance are often associated with reduced fitness and virulence, it is currently unknown how exposure to azole antagonistic drugs impacts C. albicans physiology, fitness, or virulence. In this study, we examined how exposure to seven azole antagonists affects C. albicans phenotype and capacity to cause disease. Most of the azole antagonists appear to have little impact on fungal growth, morphology, stress tolerance, or gene transcription. However, aripiprazole had a modest impact on C. albicans hyphal growth and increased cell wall chitin content. It also aggravated the disseminated C. albicans infections in mice. This effect was abrogated in immunosuppressed mice, indicating that it is at least in part dependent upon host immune responses. Collectively, these data provide proof of principle that unanticipated drug-fungus interactions have the potential to influence the incidence and outcomes of invasive fungal disease.

Modeling the transmission of antibiotic-resistant Enterobacterales in the community: A systematic review

BACKGROUND

Antibiotic-resistant Enterobacterales (ARE) are a public health threat worldwide. Dissemination of these opportunistic pathogens has been largely studied in hospitals. Despite high prevalence of asymptomatic colonization in the community in some regions of the world, less is known about ARE acquisition and spread in this setting. As explaining the community ARE dynamics has not been straightforward, mathematical models can be key to explore underlying phenomena and further evaluate the impact of interventions to curb ARE circulation outside of hospitals.

METHODS

We conducted a systematic review of mathematical modeling studies focusing on the transmission of AR-E in the community, excluding models only specific to hospitals. We extracted model features (population, setting), formalism (compartmental, individual-based), biological hypotheses (transmission, infection, antibiotic impact, resistant strain specificities) and main findings. We discussed additional mechanisms to be considered, open scientific questions, and most pressing data needs.

RESULTS

We identified 18 modeling studies focusing on the human transmission of ARE in the community (n=11) or in both community and hospital (n=7). Models aimed at (i) understanding mechanisms driving resistance dynamics; (ii) identifying and quantifying transmission routes; or (iii) evaluating public health interventions to reduce resistance. To overcome the difficulty of reproducing observed ARE dynamics in the community using the classical two-strains competition model, studies proposed to include mechanisms such as within-host strain competition or a strong host population structure. Studies inferring model parameters from longitudinal carriage data were mostly based on models considering the ARE strain only. They showed differences in ARE carriage duration depending on the acquisition mode: returning travelers have a significantly shorter carriage duration than discharged hospitalized patient or healthy individuals. Interestingly, predictions across models regarding the success of public health interventions to reduce ARE rates depended on pathogens, settings, and antibiotic resistance mechanisms. For E. coli, reducing person-to-person transmission in the community had a stronger effect than reducing antibiotic use in the community. For Klebsiella pneumoniae, reducing antibiotic use in hospitals was more efficient than reducing community use.

CONCLUSIONS

This study raises the limited number of modeling studies specifically addressing the transmission of ARE in the community. It highlights the need for model development and community-based data collection especially in low- and middle-income countries to better understand acquisition routes and their relative contribution to observed ARE levels. Such modeling will be critical to correctly design and evaluate public health interventions to control ARE transmission in the community and further reduce the associated infection burden.

What makes Candida auris pan-drug resistant? Integrative insights from genomic, transcriptomic, and phenomic analysis of clinical strains resistant to all four major classes of antifungal drugs

The global epidemic of drug-resistant Candida auris continues unabated. We do not know what caused the unprecedented appearance of pan-drug resistant (PDR) Candida auris strains in a hospitalized patient in New York; the initial report highlighted both known and unique mutations in the prominent gene targets of azoles, amphotericin B, echinocandins, and flucytosine antifungal drugs. However, the factors that allow C. auris to acquire multi-drug resistance and pan-drug resistance are not known. Therefore, we conducted a comprehensive genomic, transcriptomic, and phenomic analysis to better understand PDR C. auris . Among 1,570 genetic variants in drug-resistant C. auris , 299 were unique to PDR strains. The whole genome sequencing results suggested perturbations in genes associated with nucleotide biosynthesis, mRNA processing, and nuclear export of mRNA. Whole transcriptome sequencing of PDR C. auris revealed two genes to be significantly differentially expressed - a DNA repair protein and DNA replication-dependent chromatin assembly factor 1. Of 59 novel transcripts, 12 candidate transcripts had no known homology among expressed transcripts found in other organisms. We observed no fitness defects among multi-drug resistant (MDR) and PDR C. auris strains grown in nutrient-deficient or - enriched media at different temperatures. Phenotypic profiling revealed wider adaptability to nitrogenous nutrients with an uptick in the utilization of substrates critical in upper glycolysis and tricarboxylic acid cycle. Structural modelling of 33-amino acid deletion in the gene for uracil phosphoribosyl transferase suggested an alternate route in C. auris to generate uracil monophosphate that does not accommodate 5-fluorouracil as a substrate. Overall, we find evidence of metabolic adaptations in MDR and PDR C. auris in response to antifungal drug lethality without deleterious fitness costs.

The limit to evolutionary rescue depends on ploidy in yeast exposed to nystatin

The number of copies of each chromosome, or ploidy, of an organism is a major genomic factor affecting adaptation. We set out to determine how ploidy can impact the outcome of evolution, as well as the likelihood of evolutionary rescue, using short-term experiments with yeast (Saccharomyces cerevisiae) in a high concentration of the fungicide nystatin. In similar experiments using haploid yeast, the genetic changes underlying evolutionary rescue were highly repeatable, with all rescued lines containing a single mutation in the ergosterol biosynthetic pathway. All of these beneficial mutations were recessive, which led to the expectation that diploids would find alternative genetic routes to adaptation. To test this, we repeated the experiment using both haploid and diploid strains and found that diploid populations did not evolve resistance. Although diploids are able to adapt at the same rate as haploids to a lower, not fully inhibitory, concentration of nystatin, the present study suggests that diploids are limited in their ability to adapt to an inhibitory concentration of nystatin, while haploids may undergo evolutionary rescue. These results demonstrate that ploidy can tip the balance between adaptation and extinction when organisms face an extreme environmental change.

Reversion to sensitivity explains limited transmission of resistance in a hospital pathogen

Bacterial pathogens that are successful in hospital environments must survive times of intense antibiotic exposure and times of no antibiotic exposure. When these organisms are closely associated with human hosts, they must also transmit from one patient to another for the resistance to spread. The resulting evolutionary dynamics have, in some settings, led to rising levels of resistance in hospitals. Here, we focus on an important but understudied aspect of this dynamic: the loss of resistance when the resistant organisms evolve in environments where the antibiotic pressure is removed. Based on prior data, we hypothesize that resistance arising in the context of strong selection may carry a high cost and revert to sensitivity quickly once the selective pressure is removed. Conversely, resistant isolates that persist through times of no antibiotic pressure should carry a lower cost and revert less quickly. To test this hypothesis, we utilize a genetically diverse set of patient-derived, daptomycin-resistant Enterococcus faecium isolates that include cases of both de novo emergence of resistance within patients and putatively transmitted resistance. Both of these sets of strains have survived periods of antibiotic exposure, but only putatively transmitted resistant strains have survived extended periods without antibiotic exposure. These strains were then allowed to evolve in antibiotic free laboratory conditions. We find that putatively transmitted resistant strains tended to have lower level resistance but that evolution in antibiotic-free conditions resulted in minimal loss of resistance. In contrast, resistance that arose de novo within patients was higher level but exhibited greater declines in resistance in vitro. Sequencing of the experimentally evolved isolates revealed that reversal of high level resistance resulted from evolutionary pathways that were frequently genetically associated with the unique resistance mutations of that strain. Thus, the rapid reversal of high-level resistance was associated with accessible evolutionary pathways where an increase in fitness is associated with decreased resistance. We describe how this rapid loss of resistance may limit the spread of resistance within the hospital and shape the diversity of resistance phenotypes across patients.

Drug resistance and epidemiological success of modern Mycobacterium tuberculosis lineages in western India

BACKGROUND

Transmission is contributing to the slow decline of tuberculosis (TB) incidence globally. Drivers of TB transmission in India, the country estimated to carry a quarter of the World's burden, are not well studied. We conducted a genomic epidemiology study to compare epidemiological success, host factors and drug resistance (DR) among the four major Mycobacterium tuberculosis (Mtb) lineages (L1-4) circulating in Pune, India.

METHODS

We performed whole-genome sequencing (WGS) of Mtb sputum culture-positive isolates from participants in two prospective cohort studies and predicted genotypic susceptibility using a validated random forest model. We used maximum likelihood estimation to build phylogenies. We compared lineage specific phylogenetic and time-scaled metrics to assess epidemiological success.

RESULTS

Of the 642 isolates that underwent WGS, 612 met sequence quality criteria. Most isolates belonged to L3 (44.6%). The majority (61.1%) of multidrug-resistant isolates belonged to L2 (P < 0.001). In molecular dating, L2 demonstrated a higher rate and more recent resistance acquisition. We measured higher clustering, and time-scaled haplotypic density (THD) for L4 and L2 compared to L3 and/or L1 suggesting higher epidemiological success. L4 demonstrated higher THD and clustering (OR 5.1 (95% CI 2.3-12.3) in multivariate models controlling for host factors and DR.

CONCLUSION

L2 shows a higher frequency of DR and both L2 and L4 demonstrate evidence of higher epidemiological success than L3 or L1 in the study setting. Our findings highlight the need for contact tracing around TB cases, and heightened surveillance of TB DR in India.

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.

Antibiotic resistance begets more resistance: chromosomal resistance mutations mitigate fitness costs conferred by multi-resistant clinical plasmids

Plasmids are the primary vectors of horizontal transfer of antibiotic resistance genes among bacteria. Previous studies have shown that the spread and maintenance of plasmids among bacterial populations depend on the genetic makeup of both the plasmid and the host bacterium. Antibiotic resistance can also be acquired through mutations in the bacterial chromosome, which not only confer resistance but also result in changes in bacterial physiology and typically a reduction in fitness. However, it is unclear whether chromosomal resistance mutations affect the interaction between plasmids and the host bacteria. To address this question, we introduced 13 clinical plasmids into a susceptible Escherichia coli strain and three different congenic mutants that were resistant to nitrofurantoin (ΔnfsAB), ciprofloxacin (gyrA, S83L), and streptomycin (rpsL, K42N) and determined how the plasmids affected the exponential growth rates of the host in glucose minimal media. We find that though plasmids confer costs on the susceptible strains, those costs are fully mitigated in the three resistant mutants. In several cases, this results in a competitive advantage of the resistant strains over the susceptible strain when both carry the same plasmid and are grown in the absence of antibiotics. Our results suggest that bacteria carrying chromosomal mutations for antibiotic resistance could be a better reservoir for resistance plasmids, thereby driving the evolution of multi-drug resistance.IMPORTANCEPlasmids have led to the rampant spread of antibiotic resistance genes globally. Plasmids often carry antibiotic resistance genes and other genes needed for its maintenance and spread, which typically confer a fitness cost on the host cell observed as a reduced growth rate. Resistance is also acquired via chromosomal mutations, and similar to plasmids they also reduce bacterial fitness. However, we do not know whether resistance mutations affect the bacterial ability to carry plasmids. Here, we introduced 13 multi-resistant clinical plasmids into a susceptible and three different resistant E. coli strains and found that most of these plasmids do confer fitness cost on susceptible cells, but these costs disappear in the resistant strains which often lead to fitness advantage for the resistant strains in the absence of antibiotic selection. Our results imply that already resistant bacteria are a more favorable reservoir for multi-resistant plasmids, promoting the ascendance of multi-resistant bacteria.

Sustainable strategies: Nature-based solutions to tackle antibiotic resistance gene proliferation and improve agricultural productivity and soil quality

The issue of antibiotic resistance is now recognized by the World Health Organisation (WHO) as one of the major problems in human health. Although its effects are evident in the healthcare settings, the root cause should be traced back to the One Health link, extending from animals to the environment. In fact, the use of organic fertilizers in agroecosystems represents one, if not the primary, cause of the introduction of antibiotics and antibiotic-resistant bacteria into the soil. Since the concentrations of antibiotics introduced into the soil are residual, the agroecosystem has become a perfect environment for the selection and proliferation of antibiotic resistance genes (ARGs). The continuous influx of these emerging contaminants (i.e., antibiotics) into the agroecosystem results in the selection and accumulation of ARGs in soil bacteria, occasionally giving rise to multi-resistant bacteria. These bacteria may harbour ARGs related to various antibiotics on their plasmids. In this context, these bacteria can potentially enter the human sphere when individuals consume food from contaminated agroecosystems, leading to the acquisition of multi-resistant bacteria. Once introduced into the nosocomial environment, these bacteria pose a significant threat to human health. In this review, we analyse how the use of digestate as an organic fertilizer can mitigate the spread of ARGs in agroecosystems. Furthermore, we highlight how, according to European guidelines, digestate can be considered a Nature-Based Solution (NBS). This NBS not only has the ability to mitigate the spread of ARGs in agroecosystems but also offers the opportunity to further improve Microbial-Based Solutions (MBS), with the aim of enhancing soil quality and productivity.

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.

Grow now, pay later: When should a bacterium go into debt?

Microbes grow in a wide variety of environments and must balance growth and stress resistance. Despite the prevalence of such trade-offs, understanding of their role in nonsteady environments is limited. In this study, we introduce a mathematical model of "growth debt," where microbes grow rapidly initially, paying later with slower growth or heightened mortality. We first compare our model to a classical chemostat experiment, validating our proposed dynamics and quantifying Escherichia coli's stress resistance dynamics. Extending the chemostat theory to include serial-dilution cultures, we derive phase diagrams for the persistence of "debtor" microbes. We find that debtors cannot coexist with nondebtors if "payment" is increased mortality but can coexist if it lowers enzyme affinity. Surprisingly, weak noise considerably extends the persistence of resistance elements, pertinent for antibiotic resistance management. Our microbial debt theory, broadly applicable across many environments, bridges the gap between chemostat and serial dilution systems.

Effect of wheat crops on the persistence and attenuation of antibiotic resistance genes in soil after swine wastewater application

Swine wastewater (SW) application introduces antibiotic resistance genes (ARGs) into farmland soils. However, ARG attenuation in SW-fertigated soils, especially those influenced by staple crops and soil type, remains unclear. This study investigated twelve soil ARGs and one mobile genetic element (MGE) in sandy loam, loam, and silt loam soils before and after SW application in wheat-planted and unplanted soils. The results revealed an immediate increase in the abundance of ARGs in soil by two orders of magnitude above background levels following SW application. After SW application, the soil total ARG abundance was attenuated, reaching background levels at 54 days; However, more individual ARGs were detected above the detection limit than pre-application. Among the 13 genes, acc(6')-lb, tetM, and tetO tended to persist in the soil during wheat harvest. ARG half-lives were up to four times longer in wheat-planted soils than in bare soils. Wheat planting decreased the persistence of acc(6')-lb, ermB, ermF, and intI2 but increased the persistence of others such as sul1 and sul2. Soil type had no significant impact on ARG and MGE fates. Our findings emphasize the need for strategic SW application and the consideration of crop cultivation effects to mitigate ARG accumulation in farmland soils.

Transmission rates of veterinary and clinically important antibiotic resistant Escherichia coli: A meta- ANALYSIS

The transmission rate per hour between hosts is a key parameter for simulating transmission dynamics of antibiotic-resistant bacteria, and might differ for antibiotic resistance genes, animal species, and antibiotic usage. We conducted a Bayesian meta-analysis of resistant Escherichia coli (E. coli) transmission in broilers and piglets to obtain insight in factors determining the transmission rate, infectious period, and reproduction ratio. We included blaCTX-M-1, blaCTX-M-2, blaOXA-162, catA1, mcr-1, and fluoroquinolone resistant E. coli. The Maximum a Posteriori (MAP) transmission rate in broilers without antibiotic treatment ranged from 0.4∙10-3 to 2.5∙10-3 depending on type of broiler (SPF vs conventional) and inoculation strains. For piglets, the MAP in groups without antibiotic treatment were between 0.7∙10-3 and 0.8∙10-3, increasing to 0.9∙10-3 in the group with antibiotic treatment. In groups without antibiotic treatment, the transmission rate of resistant E. coli in broilers was almost twice the transmission rate in piglets. Amoxicillin increased the transmission rate of E. coli carrying blaCTX-M-2 by three-fold. The MAP infectious period of resistant E. coli in piglets with and without antibiotics is between 971 and 1065 hours (40 - 43 days). The MAP infectious period of resistant E. coli in broiler without antibiotics is between 475 and 2306 hours (20 - 96 days). The MAP infectious period of resistant E. coli in broiler with antibiotics is between 2702 and 3462 hours (113 - 144 days) which means a lifelong colonization. The MAP basic reproduction ratio in piglets of infection with resistant E. coli when using antibiotics is 27.70, which is higher than MAP in piglets without antibiotics between 15.65 and 18.19. The MAP basic reproduction ratio in broilers ranges between 3.46 and 92.38. We consider three possible explanations for our finding that in the absence of antibiotics the transmission rate is higher among broilers than among piglets: i) due to the gut microbiome of animals, ii) fitness costs of bacteria, and iii) differences in experimental set-up between the studies. Regarding infectious period and reproduction ratio, the effect of the resistance gene, antibiotic treatment, and animal species are inconclusive due to limited data.

Unraveling resistance mechanisms in combination therapy: A comprehensive review of recent advances and future directions

Antimicrobial resistance is a global health threat. Misuse and overuse of antimicrobials are the main drivers in developing drug-resistant bacteria. The emergence of the rapid global spread of multi-resistant bacteria requires urgent multisectoral action to generate novel treatment alternatives. Combination therapy offers the potential to exploit synergistic effects for enhanced antibacterial efficacy of drugs. Understanding the complex dynamics and kinetics of drug interactions in combination therapy is crucial. Therefore, this review outlines the current advances in antibiotic resistance's evolutionary and genetic dynamics in combination therapies-exposed bacteria. Moreover, we also discussed four pivotal future research areas to comprehend better the development of antibiotic resistance in bacteria treated with combination strategies.

Inactivation of antibiotic resistant bacteria by Fe3O4 @MoS2 activated persulfate and control of antibiotic resistance dissemination risk

Antibiotic resistance poses a global environmental challenge that jeopardizes human health and ecosystem stability. Antibiotic resistant bacteria (ARB) significantly promote the spreading and diffusion of antibiotic resistance. This study investigated the efficiency and mechanism of inactivating tetracycline-resistant Escherichia coli (TR E. coli) using Fe3O4 @MoS2 activated persulfate (Fe3O4 @MoS2/PS). Under optimized conditions (200 mg/L Fe3O4 @MoS2, 4 mM PS, 35 °C), TR E. coli (∼7.5 log CFU/mL) could be fully inactivated within 20 min. The primary reactive oxygen species (ROS) responsible for TR E. coli inactivation in the Fe3O4 @MoS2/PS system were hydroxyl radicals (•OH) and superoxide radicals (•O2-). Remarkably, the efflux pump protein was targeted and damaged by the generated ROS during the inactivation process, resulting in cell membrane rupture and efflux of cell content. Additionally, the horizontal transmission ability of residual antibiotic resistance genes (ARGs) harboring in the TR E. coli was also reduced after the inactivation treatment. This study offers an efficient approach for TR E. coli inactivation and substantial mitigation of antibiotic resistance dissemination risk.

Frequency-dependent ecological interactions increase the prevalence, and shape the distribution, of pre-existing drug resistance

The evolution of resistance remains one of the primary challenges for modern medicine from infectious diseases to cancers. Many of these resistance-conferring mutations often carry a substantial fitness cost in the absence of treatment. As a result, we would expect these mutants to undergo purifying selection and be rapidly driven to extinction. Nevertheless, pre-existing resistance is frequently observed from drug-resistant malaria to targeted cancer therapies in non-small cell lung cancer (NSCLC) and melanoma. Solutions to this apparent paradox have taken several forms from spatial rescue to simple mutation supply arguments. Recently, in an evolved resistant NSCLC cell line, we found that frequency-dependent ecological interactions between ancestor and resistant mutant ameliorate the cost of resistance in the absence of treatment. Here, we hypothesize that frequency-dependent ecological interactions in general play a major role in the prevalence of pre-existing resistance. We combine numerical simulations with robust analytical approximations to provide a rigorous mathematical framework for studying the effects of frequency-dependent ecological interactions on the evolutionary dynamics of pre-existing resistance. First, we find that ecological interactions significantly expand the parameter regime under which we expect to observe pre-existing resistance. Next, even when positive ecological interactions between mutants and ancestors are rare, these resistant clones provide the primary mode of evolved resistance because even weak positive interaction leads to significantly longer extinction times. We then find that even in the case where mutation supply alone is sufficient to predict pre-existing resistance, frequency-dependent ecological forces still contribute a strong evolutionary pressure that selects for increasingly positive ecological effects (negative frequency-dependent selection). Finally, we genetically engineer several of the most common clinically observed resistance mechanisms to targeted therapies in NSCLC, a treatment notorious for pre-existing resistance. We find that each engineered mutant displays a positive ecological interaction with their ancestor. As a whole, these results suggest that frequency-dependent ecological effects can play a crucial role in shaping the evolutionary dynamics of pre-existing resistance.

Combinatorial in vivo genome editing identifies widespread epistasis during lung tumorigenesis

Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable tumorigenesis in vivo , largely due to a lack of methods for investigating genetic interactions in a high-throughput and multiplexed manner. Here, we employed a novel platform to generate tumors with all pairwise inactivation of ten tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including dramatically synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. This approach has the potential to expand the scope of genetic interactions that may be functionally characterized in vivo , which could lead to a better understanding of how complex tumor genotypes impact each step of carcinogenesis.

Exploring factors shaping antibiotic resistance patterns in Streptococcus pneumoniae during the 2020 COVID-19 pandemic

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

Impact of zinc supplementation on phenotypic antimicrobial resistance of fecal commensal bacteria from pre-weaned dairy calves

The objective of this study was to evaluate the impact of dietary zinc supplementation in pre-weaned dairy calves on the phenotypic antimicrobial resistance (AMR) of fecal commensal bacteria. A repository of fecal specimens from a random sample of calves block-randomized into placebo (n = 39) and zinc sulfate (n = 28) groups collected over a zinc supplementation clinical trial at the onset of calf diarrhea, calf diarrheal cure, and the last day of 14 cumulative days of zinc or placebo treatment were analyzed. Antimicrobial susceptibility testing was conducted for Enterococcus spp. (n = 167) and E. coli (n = 44), with one representative isolate of each commensal bacteria tested per sample. Parametric survival interval regression models were constructed to evaluate the association between zinc treatment and phenotypic AMR, with exponentiated accelerated failure time (AFT) coefficients adapted for MIC instead of time representing the degree of change in AMR (MIC Ratio, MR). Findings from our study indicated that zinc supplementation did not significantly alter the MIC in Enterococcus spp. for 13 drugs: gentamicin, vancomycin, ciprofloxacin, erythromycin, penicillin, nitrofurantoin, linezolid, quinupristin/dalfopristin, tylosin tartrate, streptomycin, daptomycin, chloramphenicol, and tigecycline (MR = 0.96-2.94, p > 0.05). In E. coli, zinc supplementation was not associated with resistance to azithromycin (MR = 0.80, p > 0.05) and ceftriaxone (MR = 0.95, p > 0.05). However, a significant reduction in E. coli MIC values was observed for ciprofloxacin (MR = 0.17, 95% CI 0.03-0.97) and nalidixic acid (MR = 0.28, 95% CI 0.15-0.53) for zinc-treated compared to placebo-treated calves. Alongside predictions of MIC values generated from these 17 AFT models, findings from this study corroborate the influence of age and antimicrobial exposure on phenotypic AMR.

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

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

The atypical antipsychotic aripiprazole alters the outcome of disseminated Candida albicans infections

Invasive fungal infections (IFIs) impose an enormous clinical, social, and economic burden on humankind. For many IFIs, ≥ 30% of patients fail therapy with existing antifungal drugs, including the widely used azole class. We previously identified a collection of 13 approved medications that antagonize azole activity. While gain-of-function mutants resulting in antifungal resistance are often associated with reduced fitness and virulence, it is currently unknown how exposure to azole antagonistic drugs impact C. albicans physiology, fitness, or virulence. In this study, we examined how exposure to azole antagonists affected C. albicans phenotype and capacity to cause disease. We discovered that most of the azole antagonists had little impact on fungal growth, morphology, stress tolerance, or gene transcription. However, aripiprazole had a modest impact on C. albicans hyphal growth and increased cell wall chitin content. It also worsened the outcome of disseminated infections in mice at human equivalent concentrations. This effect was abrogated in immunosuppressed mice, indicating an additional impact of aripiprazole on host immunity. Collectively, these data provide proof-of-principle that unanticipated drug-fungus interactions have the potential to influence the incidence and outcomes of invasive fungal disease.

Sub-inhibitory antibiotic treatment selects for enhanced metabolic efficiency

Bacterial growth and metabolic rates are often closely related. However, under antibiotic selection, a paradox in this relationship arises: antibiotic efficacy decreases when bacteria are metabolically dormant, yet antibiotics select for resistant cells that grow fastest during treatment. That is, antibiotic selection counterintuitively favors bacteria with fast growth but slow metabolism. Despite this apparent contradiction, antibiotic resistant cells have historically been characterized primarily in the context of growth, whereas the extent of analogous changes in metabolism is comparatively unknown. Here, we observed that previously evolved antibiotic-resistant strains exhibited a unique relationship between growth and metabolism whereby nutrient utilization became more efficient, regardless of the growth rate. To better understand this unexpected phenomenon, we used a simplified model to simulate bacterial populations adapting to sub-inhibitory antibiotic selection through successive bottlenecking events. Simulations predicted that sub-inhibitory bactericidal antibiotic concentrations could select for enhanced metabolic efficiency, defined based on nutrient utilization: drug-adapted cells are able to achieve the same biomass while utilizing less substrate, even in the absence of treatment. Moreover, simulations predicted that restoring metabolic efficiency would re-sensitize resistant bacteria exhibiting metabolic-dependent resistance; we confirmed this result using adaptive laboratory evolutions of Escherichia coli under carbenicillin treatment. Overall, these results indicate that metabolic efficiency is under direct selective pressure during antibiotic treatment and that differences in evolutionary context may determine both the efficacy of different antibiotics and corresponding re-sensitization approaches.IMPORTANCEThe sustained emergence of antibiotic-resistant pathogens combined with the stalled drug discovery pipelines highlights the critical need to better understand the underlying evolution mechanisms of antibiotic resistance. To this end, bacterial growth and metabolic rates are often closely related, and resistant cells have historically been characterized exclusively in the context of growth. However, under antibiotic selection, antibiotics counterintuitively favor cells with fast growth, and slow metabolism. Through an integrated approach of mathematical modeling and experiments, this study thereby addresses the significant knowledge gap of whether antibiotic selection drives changes in metabolism that complement, and/or act independently, of antibiotic resistance phenotypes.

Horizontal gene transfer facilitates the molecular reverse-evolution of antibiotic sensitivity in experimental populations of H. pylori

Reversing the evolution of traits harmful to humans, such as antimicrobial resistance, is a key ambition of applied evolutionary biology. A major impediment to reverse evolution is the relatively low spontaneous mutation rates that revert evolved genotypes back to their ancestral state. However, the repeated re-introduction of ancestral alleles by horizontal gene transfer (HGT) could make reverse evolution likely. Here we evolve populations of an antibiotic-resistant strain of Helicobacter pylori in growth conditions without antibiotics while introducing an ancestral antibiotic-sensitive allele by HGT. We evaluate reverse evolution using DNA sequencing and find that HGT facilitates the molecular reverse evolution of the antibiotic resistance allele, and that selection for high rates of HGT drives the evolution of increased HGT rates in low-HGT treatment populations. Finally, we use a theoretical model and carry out simulations to infer how the fitness costs of antibiotic resistance, rates of HGT and effects of genetic drift interact to determine the probability and predictability of reverse evolution.

Discovery of an adjuvant that resensitizes polymyxin B-resistant bacteria

Infections caused by antibiotic-resistant bacteria are a major threat to health, increasing mortality rates and straining health systems worldwide. Adjuvants targeted to beta-lactamase function are able to resensitize bacteria to beta-lactam antibiotics, but there is comparatively little research into the use of adjuvants against other resistance phenotypes. In this study, we performed a high-throughput screen of 74 natural products to identify adjuvants that synergized with antibiotics to eradicate resistant Gram-negative bacteria. From this, we identified six adjuvant hits which restored growth inhibition when combined with the relevant antibiotic, and pursued a lead candidate, perforone, which possessed selective adjuvant activity in combination with polymyxin B against polymyxin-resistant Escherichia coli cells. These results suggest that pairing adjuvants with antibiotics could be a useful general intervention against resistant bacteria, helping to mitigate the effects of antimicrobial resistance.

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterised using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.

Trade-offs constrain adaptive pathways to the type VI secretion system survival

The Type VI Secretion System (T6SS) is a nano-harpoon used by many bacteria to inject toxins into neighboring cells. While much is understood about mechanisms of T6SS-mediated toxicity, less is known about the ways that competitors can defend themselves against this attack, especially in the absence of their own T6SS. Here we subjected eight replicate populations of Escherichia coli to T6SS attack by Vibrio cholerae. Over ∼500 generations of competition, isolates of the E. coli populations evolved to survive T6SS attack an average of 27-fold better, through two convergently evolved pathways: apaH was mutated in six of the eight replicate populations, while the other two populations each had mutations in both yejM and yjeP. However, the mutations we identified are pleiotropic, reducing cellular growth rates, and increasing susceptibility to antibiotics and elevated pH. These trade-offs help us understand how the T6SS shapes the evolution of bacterial interactions.

Long-term exposure to food-grade disinfectants causes cross-resistance to antibiotics in Salmonella enterica serovar Typhimurium strains with different antibiograms and sequence types

BACKGROUND

Disinfectants are important in the food industry to prevent the transmission of pathogens. Excessive use of disinfectants may increase the probability of bacteria experiencing long-term exposure and consequently resistance and cross-resistance to antibiotics. This study aims to investigate the cross-resistance of multidrug-resistant, drug-resistant, and drug-susceptible isolates of Salmonella enterica serovar Typhimurium (S. Typhimurium) with different sequence types (STs) to a group of antibiotics after exposure to different food-grade disinfectants.

METHODS

A panel of 27 S. Typhimurium strains with different antibiograms and STs were exposed to increasing concentrations of five food-grade disinfectants, including hydrogen peroxide (H2O2), benzalkonium chloride (BAC), chlorine dioxide (ClO2), sodium hypochlorite (NaClO), and ethanol. Recovered evolved strains were analyzed using genomic tools and phenotypic tests. Genetic mutations were screened using breseq pipeline and changes in resistance to antibiotics and to the same disinfectant were determined. The relative fitness of evolved strains was also determined.

RESULTS

Following exposure to disinfectants, 22 out of 135 evolved strains increased their resistance to antibiotics from a group of 14 clinically important antibiotics. The results also showed that 9 out of 135 evolved strains had decreased resistance to some antibiotics. Genetic mutations were found in evolved strains. A total of 77.78% of ST34, 58.33% of ST19, and 66.67% of the other STs strains exhibited changes in antibiotic resistance. BAC was the disinfectant that induced the highest number of strains to cross-resistance to antibiotics. Besides, H2O2 induced the highest number of strains with decreased resistance to antibiotics.

CONCLUSIONS

These findings provide a basis for understanding the effect of disinfectants on the antibiotic resistance of S. Typhimurium. This work highlights the link between long-term exposure to disinfectants and the evolution of resistance to antibiotics and provides evidence to promote the regulated use of disinfectants.

Heterogeneous Phenotypic Responses of Antibiotic-Resistant Salmonella Typhimurium to Food Preservative-Related Stresses

This study was designed to evaluate the response of antibiotic-resistant Salmonella Typhimurium to food preservative-related stresses, such as lactic acid and sodium chloride (NaCl). S. Typhimurium cells were exposed to 1 µg/mL of ciprofloxacin (CIP), 0.2% lactic acid (LA), 6% NaCl, CIP followed by LA (CIP-LA), and CIP followed by NaCl (CIP-NaCl). The untreated S. Typhimurium cells were the control (CON). All treatments were as follows: CON, CIP, LA, NaCl, CIP-LA, and CIP-NaCl. The phenotypic heterogeneity was evaluated by measuring the antimicrobial susceptibility, bacterial fluctuation, cell injury, persistence, and cross-resistance. The CIP, CIP-LA, and CIP-NaCl groups were highly resistant to ciprofloxacin, showing MIC values of 0.70, 0.59, and 0.54 µg/mL, respectively, compared to the CON group (0.014 µg/mL). The susceptibility to lactic acid was not changed after exposure to NaCl, while that to NaCl was decreased after exposure to NaCl. The Eagle phenomenon was observed in the CIP, CIP-LA, and CIP-NaCl groups, showing Eagle effect concentrations (EECs) of more than 8 µg/mL. No changes in the MBCs of lactic acid and NaCl were observed in the CIP, LA, and CIP-LA groups, and the EECs of lactic acid and NaCl were not detected in all treatments. The bacterial fluctuation rates of the CIP-LA and CIP-NaCl groups were considerably increased to 33% and 41%, respectively, corresponding to the injured cell proportions of 82% and 89%. CIP-NaCl induced persister cells as high as 2 log cfu/mL. The LA and NaCl treatments decreased the fitness cost. The CIP-NaCl treatment showed positive cross-resistance to erythromycin (ERY) and tetracycline (TET), while the LA and NaCl treatments were collaterally susceptible to chloramphenicol (CHL), ciprofloxacin (CIP), piperacillin (PIP), and TET. The results provide new insight into the fate of antibiotic-resistant S. Typhimurium during food processing and preservation.

Modelling the effects of antibiotic usage in livestock on human salmonellosis

Antibiotic usage in livestock has been suggested as a driver of antimicrobial resistance in human and livestock populations. This has contributed to the implementation of stewardship programs to curtail usage of antibiotics in livestock. However, the consequences of antibiotic curtailment in livestock on human health are poorly understood. There is the potential for increases in the carriage of pathogens such as Salmonella spp. in livestock, and subsequent increases in human foodborne disease. We use a mathematical model fitted to four case studies, ampicillin and tetracycline usage in fattening pig and broiler poultry populations, to explore the impact of curtailing antibiotic usage in livestock on salmonellosis in humans. Increases in the daily incidence of salmonellosis and a decrease in the proportion of resistant salmonellosis were identified following curtailment of antibiotic usage in livestock. The extent of these increases in human foodborne disease ranged from negligible, to controllable through interventions to target the farm-to-fork pathway. This study provides a motivating example of one plausible scenario following curtailment of antibiotic usage in livestock and suggests that a focus on ensuring good farm-to-fork hygiene and livestock biosecurity is sufficient to mitigate the negative human health consequences of antibiotic stewardship in livestock populations.

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.

On the De Novo Emergence of Ecological Interactions during Evolutionary Diversification: A Conceptual Framework and Experimental Test

AbstractEcological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities.

Deriving Novel Quaternary Ammonium Compound Disinfectant Scaffolds from a Natural Product: Mechanistic Insights of the Quaternization of Ianthelliformisamine C

In the search for novel quaternary ammonium compound (QAC) disinfectants that can evade bacterial resistance, we turned to natural products as a source of inspiration. Herein we used natural product ianthelliformisamine C as a scaffold to design a small library of QACs. We first synthesized ianthelliformisamine C via an amide coupling that allowed for facile purification without the need for protecting groups. We then alkylated and quaternized the internal amines to yield four novel QACs, but all but one demonstrated no antibacterial activity against the tested strains. Using a combination of membrane depolarization and permeabilization assays, we were able to demonstrate that ianthelliformisamine C and the active QAC analog enact cell death via membrane permeabilization, contrary to prior reports on ianthelliformisamine C's mechanism of action.

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.

Nothing makes sense in drug resistance except in the light of evolution

Our ability to fight infectious diseases is being increasingly compromised due to the emergence and spread of pathogens that become resistant to one or several drugs. This phenomenon is ubiquitous among pathogens and has parallels in cancer treatment. Given the urgency of the problem, there is a need for a paradigm shift in drug therapy toward one in which the objective to prevent the evolution of drug resistance is considered alongside the main objective of eliminating the infection or tumor. Here, I stress the importance of considering an evolutionary perspective to achieve this goal, and review recent advances in this direction, including therapies that exploit the fitness trade-offs of resistance.

The balance between antibiotic resistance and fitness/virulence in Pseudomonas aeruginosa: an update on basic knowledge and fundamental research

The interplay between antibiotic resistance and bacterial fitness/virulence has attracted the interest of researchers for decades because of its therapeutic implications, since it is classically assumed that resistance usually entails certain biological costs. Reviews on this topic revise the published data from a general point of view, including studies based on clinical strains or in vitro-evolved mutants in which the resistance phenotype is seen as a final outcome, i.e., a combination of mechanisms. However, a review analyzing the resistance/fitness balance from the basic research perspective, compiling studies in which the different resistance pathways and respective biological costs are individually approached, was missing. Here we cover this gap, specifically focusing on Pseudomonas aeruginosa, a pathogen that stands out because of its extraordinary capacity for resistance development and for which a considerable number of recent and particular data on the interplay with fitness/virulence have been released. The revised information, split into horizontally-acquired vs. mutation-driven resistance, suggests a great complexity and even controversy in the resistance-fitness/virulence balance in the acute infection context, with results ranging from high costs linked to certain pathways to others that are seemingly cost-free or even cases of resistance mechanisms contributing to increased pathogenic capacities. The elusive mechanistic basis for some enigmatic data, knowledge gaps, and possibilities for therapeutic exploitation are discussed. The information gathered suggests that resistance-fitness/virulence interplay may be a source of potential antipseudomonal targets and thus, this review poses the elementary first step for the future development of these strategies harnessing certain resistance-associated biological burdens.

Fully accessible fitness landscape of oncogene-negative lung adenocarcinoma

Cancer genomes are almost invariably complex with genomic alterations cooperating during each step of carcinogenesis. In cancers that lack a single dominant oncogene mutation, cooperation between the inactivation of multiple tumor suppressor genes can drive tumor initiation and growth. Here, we shed light on how the sequential acquisition of genomic alterations generates oncogene-negative lung tumors. We couple tumor barcoding with combinatorial and multiplexed somatic genome editing to characterize the fitness landscapes of three tumor suppressor genes NF1, RASA1, and PTEN, the inactivation of which jointly drives oncogene-negative lung adenocarcinoma initiation and growth. The fitness landscape was surprisingly accessible, with each additional mutation leading to growth advantage. Furthermore, the fitness landscapes remained fully accessible across backgrounds with the inactivation of additional tumor suppressor genes. These results suggest that while predicting cancer evolution will be challenging, acquiring the multiple alterations that drive the growth of oncogene-negative tumors can be facilitated by the lack of constraints on mutational order.

Assessing the additional health burden of antibiotic resistant Enterobacteriaceae in surface waters through an integrated QMRA and DALY approach

Antibiotic resistant Enterobacteriaceae pose a significant threat to public health. However, limited studies have evaluated the health risks associated with exposure to antibiotic-resistant bacteria (ARB), especially in natural environments. While quantitative microbial risk assessment (QMRA) assesses microbial risks in terms of the probability of infection, it does not account for the severity of health outcomes. In this study, a QMRA-DALY model was developed to integrate QMRA with health burden (disability-adjusted life years (DALY)) from infections caused by ARB. The model considers uncertainties in probability of infection and health burden assessment using Monte Carlo simulations. The study collected antimicrobial resistance (AMR) surveillance data from surface waters with different land uses. Results revealed water bodies with agricultural land use to be the main AMR hotspots, with the highest additional health burden observed in infections caused by meropenem-resistant E. coli (∆DALY = 0.0105 DALY/event) compared to antibiotic-susceptible E. coli. The estimated ∆DALY for antibiotic-resistant K. pneumoniae was lower than for antibiotic-resistant E. coli (highest ∆DALY = 0.00048 DALY/event). The study highlights the need for better evaluation of AMR associated health burden, and effective measures to mitigate the risks associated with antibiotic-resistant bacteria in natural environments.

Phytochemical Cue for the Fitness Costs of Herbicide-Resistant Weeds

Despite increasing knowledge of the fitness costs of viability and fecundity involved in the herbicide-resistant weeds, relatively little is known about the linkage between herbicide resistance costs and phytochemical cues in weed species and biotypes. This study demonstrated relative fitness and phytochemical responses in six herbicide-resistant weeds and their susceptible counterparts. There were significant differences in the parameters of viability (growth and photosynthesis), fecundity fitness (flowering and seed biomass) and a ubiquitous phytochemical (-)-loliolide levels between herbicide-resistant weeds and their susceptible counterparts. Fitness costs occurred in herbicide-resistant Digitaria sanguinalis and Leptochloa chinensis but they were not observed in herbicide-resistant Alopecurus japonicas, Eleusine indica, Ammannia arenaria, and Echinochloa crus-galli. Correlation analysis indicated that the morphological characteristics of resistant and susceptible weeds were negatively correlated with (-)-loliolide concentration, but positively correlated with lipid peroxidation malondialdehyde and total phenol contents. Principal component analysis showed that the lower the (-)-loliolide concentration, the stronger the adaptability in E. crus-galli and E. indica. Therefore, not all herbicide-resistant weeds have fitness costs, but the findings showed several examples of resistance leading to improved fitness even in the absence of herbicides. In particular, (-)-loliolide may act as a phytochemical cue to explain the fitness cost of herbicide-resistant weeds by regulating vitality and fecundity.

Development of an antibody fused with an antimicrobial peptide targeting Pseudomonas aeruginosa: A new approach to prevent and treat bacterial infections

The increase in emerging drug resistant Gram-negative bacterial infections is a global concern. In addition, there is growing recognition that compromising the microbiota through the use of broad-spectrum antibiotics can impact long term patient outcomes. Therefore, there is the need to develop new bactericidal strategies to combat Gram-negative infections that would address these specific issues. In this study, we report and characterize one such approach, an antibody-drug conjugate (ADC) that combines (i) targeting the surface of a specific pathogenic organism through a monoclonal antibody with (ii) the high killing activity of an antimicrobial peptide. We focused on a major pathogenic Gram-negative bacterium associated with antibacterial resistance: Pseudomonas aeruginosa. To target this organism, we designed an ADC by fusing an antimicrobial peptide to the C-terminal end of the VH and/or VL-chain of a monoclonal antibody, VSX, that targets the core of P. aeruginosa lipopolysaccharide. This ADC demonstrates appropriately minimal levels of toxicity against mammalian cells, rapidly kills P. aeruginosa strains, and protects mice from P. aeruginosa lung infection when administered therapeutically. Furthermore, we found that the ADC was synergistic with several classes of antibiotics. This approach described in this study might result in a broadly useful strategy for targeting specific pathogenic microorganisms without further augmenting antibiotic resistance.