Predictable Phenotypes of Antibiotic Resistance Mutations

Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition

Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured if the direct effect of ARGs on host fitness is fixed or if it depends on the host strain, perhaps marking some ARG-host combinations as selective refuges that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse Escherichia spp. strains. Three ARGs (blaTEM-116, cat and dfrA5, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost, but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions can cause the success of ARGs to depend on available host strains, and, to a lesser extent, can cause host strain success to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects across different host strains, and especially the potential of refuge strains to allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.

Assessing Antibiotic-Resistant Genes in University Dormitory Washing Machines

University dormitories represent densely populated environments, and washing machines are potential sites for the spread of bacteria and microbes. However, the extent of antibiotic resistance gene (ARG) variation in washing machines within university dormitories and their potential health risks are largely unknown. To disclose the occurrence of ARGs and antibiotic-resistant bacteria from university dormitories, we collected samples from washing machines in 10 dormitories and used metagenomic sequencing technology to determine microbial and ARG abundance. Our results showed abundant microbial diversity, with Proteobacteria being the dominant microorganism that harbors many ARGs. The majority of the existing ARGs were associated with antibiotic target alteration and efflux, conferring multidrug resistance. We identified tnpA and IS91 as the most abundant mobile genetic elements (MGEs) in washing machines and found that Micavibrio aeruginosavorus, Aquincola tertiaricarbonis, and Mycolicibacterium iranicum had high levels of ARGs. Our study highlights the potential transmission of pathogens from washing machines to humans and the surrounding environment. Pollution in washing machines poses a severe threat to public health and demands attention. Therefore, it is crucial to explore effective methods for reducing the reproduction of multidrug resistance.

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.

High prevalence of heteroresistance in Staphylococcus aureus is caused by a multitude of mutations in core genes

Heteroresistance (HR) is an enigmatic phenotype where, in a main population of susceptible cells, small subpopulations of resistant cells exist. This is a cause for concern, as this small subpopulation is difficult to detect by standard antibiotic susceptibility tests, and upon antibiotic exposure the resistant subpopulation may increase in frequency and potentially lead to treatment complications or failure. Here, we determined the prevalence and mechanisms of HR for 40 clinical Staphylococcus aureus isolates, against 6 clinically important antibiotics: daptomycin, gentamicin, linezolid, oxacillin, teicoplanin, and vancomycin. High frequencies of HR were observed for gentamicin (69.2%), oxacillin (27%), daptomycin (25.6%), and teicoplanin (15.4%) while none of the isolates showed HR toward linezolid or vancomycin. Point mutations in various chromosomal core genes, including those involved in membrane and peptidoglycan/teichoic acid biosynthesis and transport, tRNA charging, menaquinone and chorismite biosynthesis and cyclic-di-AMP biosynthesis, were the mechanisms responsible for generating the resistant subpopulations. This finding is in contrast to gram-negative bacteria, where increased copy number of bona fide resistance genes via tandem gene amplification is the most prevalent mechanism. This difference can be explained by the observation that S. aureus has a low content of resistance genes and absence of the repeat sequences that allow tandem gene amplification of these genes as compared to gram-negative species.

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.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

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.

Identification of combinatorial mutations associated with colistin resistance in Shewanella algae

Colistin is a last-resort antibiotic used to treat infections caused by drug-resistant gram-negative bacteria. However, the genetic mechanisms underlying colistin resistance in Shewanella algae are not well understood. In this study, we sequenced and compared the genomes of 23 mcr-negative colistin-resistant and sensitive S. algae samples from various sources. We applied a computational approach to identify combinatorial mutations associated with colistin resistance. Our analysis revealed a combination of three mutations (PmrB 451, PmrE168, PmrH292) that were strongly associated with colistin resistance in S. algae. This study provides insights into the genetic mechanisms of colistin resistance in S. algae and demonstrates the utility of a computational approach for identifying epistatic interactions among mutations. Identifying the genetic mutations responsible for colistin resistance in S. algae can inform the development of new treatments or strategies to combat infections caused by this emerging pathogen.

Epistasis decreases with increasing antibiotic pressure but not temperature

Predicting mutational effects is essential for the control of antibiotic resistance (ABR). Predictions are difficult when there are strong genotype-by-environment (G × E), gene-by-gene (G × G or epistatic) or gene-by-gene-by-environment (G × G × E) interactions. We quantified G × G × E effects in Escherichia coli across environmental gradients. We created intergenic fitness landscapes using gene knock-outs and single-nucleotide ABR mutations previously identified to vary in the extent of G × E effects in our environments of interest. Then, we measured competitive fitness across a complete combinatorial set of temperature and antibiotic dosage gradients. In this way, we assessed the predictability of 15 fitness landscapes across 12 different but related environments. We found G × G interactions and rugged fitness landscapes in the absence of antibiotic, but as antibiotic concentration increased, the fitness effects of ABR genotypes quickly overshadowed those of gene knock-outs, and the landscapes became smoother. Our work reiterates that some single mutants, like those conferring resistance or susceptibility to antibiotics, have consistent effects across genetic backgrounds in stressful environments. Thus, although epistasis may reduce the predictability of evolution in benign environments, evolution may be more predictable in adverse environments. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Tackling antibiotic resistance by inducing transient and robust collateral sensitivity

Collateral sensitivity (CS) is an evolutionary trade-off traditionally linked to the mutational acquisition of antibiotic resistance (AR). However, AR can be temporally induced, and the possibility that this causes transient, non-inherited CS, has not been addressed. Mutational acquisition of ciprofloxacin resistance leads to robust CS to tobramycin in pre-existing antibiotic-resistant mutants of Pseudomonas aeruginosa. Further, the strength of this phenotype is higher when nfxB mutants, over-producing the efflux pump MexCD-OprJ, are selected. Here, we induce transient nfxB-mediated ciprofloxacin resistance by using the antiseptic dequalinium chloride. Notably, non-inherited induction of AR renders transient tobramycin CS in the analyzed antibiotic-resistant mutants and clinical isolates, including tobramycin-resistant isolates. Further, by combining tobramycin with dequalinium chloride we drive these strains to extinction. Our results support that transient CS could allow the design of new evolutionary strategies to tackle antibiotic-resistant infections, avoiding the acquisition of AR mutations on which inherited CS depends.

Rapid Phenotypic Convergence towards Collateral Sensitivity in Clinical Isolates of Pseudomonas aeruginosa Presenting Different Genomic Backgrounds

Collateral sensitivity (CS) is an evolutionary trade-off by which acquisition of resistance to an antibiotic leads to increased susceptibility to another. This Achilles' heel of antibiotic resistance could be exploited to design evolution-based strategies for treating bacterial infections. To date, most studies in the field have focused on the identification of CS patterns in model strains. However, one of the main requirements for the clinical application of this trade-off is that it must be robust and has to emerge in different genomic backgrounds, including preexisting drug-resistant isolates, since infections are frequently caused by pathogens already resistant to antibiotics. Here, we report the first analysis of CS robustness in clinical strains of Pseudomonas aeruginosa presenting different ab initio mutational resistomes. We identified a robust CS pattern associated with short-term evolution in the presence of ciprofloxacin of clinical P. aeruginosa isolates, including representatives of high-risk epidemic clones belonging to sequence type (ST) 111, ST175, and ST244. We observed the acquisition of different ciprofloxacin resistance mutations in strains presenting varied STs and different preexisting mutational resistomes. Importantly, despite these genetic differences, the use of ciprofloxacin led to a robust CS to aztreonam and tobramycin. In addition, we describe the possible application of this evolutionary trade-off to drive P. aeruginosa infections to extinction by using the combination of ciprofloxacin-tobramycin or ciprofloxacin-aztreonam. Our results support the notion that the identification of robust patterns of CS may establish the basis for developing evolution-informed treatment strategies to tackle bacterial infections, including those due to antibiotic-resistant pathogens. IMPORTANCE Collateral sensitivity (CS) is a trade-off of antibiotic resistance evolution that could be exploited to design strategies for treating bacterial infections. Clinical application of CS requires it to robustly emerge in different genomic backgrounds. In this study, we performed an analysis to identify robust patterns of CS associated with the use of ciprofloxacin in clinical isolates of P. aeruginosa presenting different mutational resistomes and including high-risk epidemic clones (ST111, ST175, and ST244). We demonstrate the robustness of CS to tobramycin and aztreonam and the potential application of this evolutionary observation to drive P. aeruginosa infections to extinction. Our results support the notion that the identification of robust CS patterns may establish the basis for developing evolutionary strategies to tackle bacterial infections, including those due to antibiotic-resistant pathogens.

Review of hospital effluents: special emphasis on characterization, impact, and treatment of pollutants and antibiotic resistance

Health care institutions generate large volumes of liquid effluents from specific activities related to healthcare, analysis, and research. Their direct discharge into the environment has various negative effects on aquatic environments and human health, due to their high organic matter charges and the presence of various emerging contaminants such as disinfectants, drugs, bacteria, viruses, and parasites. Moreover, hospital effluents, by carrying antibiotics, contribute to the development of antibiotic-resistant microorganisms in the environment. This resistance has become a global issue that manifests itself variously in different countries, causing the transmission of different infections. In this respect, an effort is provided to protect water resources by current treatment methods that imply physical-chemical processes such as adsorption and advanced oxidation processes, biological processes such as activated sludge and membrane bioreactors and other hybrid techniques. The purpose of this review is to improve the knowledge on the composition and impact of hospital wastewater on man and the environment, highlighting the different treatment techniques appropriate to this type of disposal before discharge into the environment.

Analysis of Whole-Genome Sequences of Pathogenic Gram-Positive and Gram-Negative Isolates from the Same Hospital Environment to Investigate Common Evolutionary Trends Associated with Horizontal Gene Exchange, Mutations and DNA Methylation Patterning

Hospital-acquired infections are a generally recognized problem for healthcare professionals. Clinical variants of Gram-negative and Gram-positive pathogens are characterized with enhanced antibiotic resistance and virulence due to mutations and the horizontal acquisition of respective genetic determinants. In this study, two Escherichia coli, two Klebsiella pneumoniae, three Pseudomonas aeruginosa, two Staphylococcus aureus, one Staphylococcus epidermidis and one Streptococcus pneumoniae showing broad spectra of antibiotic resistance were isolated from patients suffering from nosocomial infections in a local hospital in Almaty, Kazakhstan. The aim of the study was to compare general and species-specific pathways of the development of virulence and antibiotic resistance through opportunistic pathogens causing hospital-acquired infections. The whole-genome PacBio sequencing of the isolates allowed for the genotyping and identification of antibiotic resistance and virulence genetic determinants located in the chromosomes, plasmids and genomic islands. It was concluded that long-read sequencing is a useful tool for monitoring the epidemiological situation in hospitals. Marker antibiotic resistance mutations common for different microorganisms were identified, which were acquired due to antibiotic-selective pressure in the same clinical environment. The genotyping and identification of strain-specific DNA methylation motifs were found to be promising in estimating the risks associated with hospital infection outbreaks and monitoring the distribution and evolution of nosocomial pathogens.

Antibiotic Cycling Affects Resistance Evolution Independently of Collateral Sensitivity

Antibiotic cycling has been proposed as a promising approach to slow down resistance evolution against currently employed antibiotics. It remains unclear, however, to which extent the decreased resistance evolution is the result of collateral sensitivity, an evolutionary trade-off where resistance to one antibiotic enhances the sensitivity to the second, or due to additional effects of the evolved genetic background, in which mutations accumulated during treatment with a first antibiotic alter the emergence and spread of resistance against a second antibiotic via other mechanisms. Also, the influence of antibiotic exposure patterns on the outcome of drug cycling is unknown. Here, we systematically assessed the effects of the evolved genetic background by focusing on the first switch between two antibiotics against Salmonella Typhimurium, with cefotaxime fixed as the first and a broad variety of other drugs as the second antibiotic. By normalizing the antibiotic concentrations to eliminate the effects of collateral sensitivity, we demonstrated a clear contribution of the evolved genetic background beyond collateral sensitivity, which either enhanced or reduced the adaptive potential depending on the specific drug combination. We further demonstrated that the gradient strength with which cefotaxime was applied affected both cefotaxime resistance evolution and adaptation to second antibiotics, an effect that was associated with higher levels of clonal interference and reduced cost of resistance in populations evolved under weaker cefotaxime gradients. Overall, our work highlights that drug cycling can affect resistance evolution independently of collateral sensitivity, in a manner that is contingent on the antibiotic exposure pattern.

Modeling Polygenic Antibiotic Resistance Evolution in Biofilms

The recalcitrance of biofilms to antimicrobials is a multi-factorial phenomenon, including genetic, physical, and physiological changes. Individually, they often cannot account for biofilm recalcitrance. However, their combination can increase the minimal inhibitory concentration of antibiotics needed to kill bacterial cells by three orders of magnitude, explaining bacterial survival under otherwise lethal drug treatment. The relative contributions of these factors depend on the specific antibiotics, bacterial strain, as well as environmental and growth conditions. An emerging population genetic property—increased biofilm genetic diversity—further enhances biofilm recalcitrance. Here, we develop a polygenic model of biofilm recalcitrance accounting for multiple phenotypic mechanisms proposed to explain biofilm recalcitrance. The model can be used to generate predictions about the emergence of resistance—its timing and population genetic consequences. We use the model to simulate various treatments and experimental setups. Our simulations predict that the evolution of resistance is impaired in biofilms at low antimicrobial concentrations while it is facilitated at higher concentrations. In scenarios that allow bacteria exchange between planktonic and biofilm compartments, the evolution of resistance is further facilitated compared to scenarios without exchange. We compare these predictions to published experimental observations.

Mutational background influences P. aeruginosa ciprofloxacin resistance evolution but preserves collateral sensitivity robustness

Bacterial adaptation to the presence of an antibiotic often involves evolutionary trade-offs, such as increased susceptibility to other drugs (collateral sensitivity). Its exploitation to design improved therapeutic strategies is only feasible if collateral sensitivity is robust, reproducible, and emerges in resistant mutants; these issues are rarely addressed in available publications. We describe a robust collateral sensitivity phenotype that emerges in different antibiotic-resistance mutational backgrounds, due to different genetic events, and propose therapeutic strategies effective for treating infections caused by Pseudomonas aeruginosa antibiotic-resistant mutants. Since conserved collateral sensitivity phenotypes do not confer adaptation to the presence of antibiotics, our results are also relevant for understanding convergent evolution processes in which the force selecting the emerging phenotype remains unclear.

Collateral sensitivity is an evolutionary trade-off whereby acquisition of the adaptive phenotype of resistance to an antibiotic leads to the nonadaptive increased susceptibility to another. The feasibility of harnessing such a trade-off to design evolutionary-based approaches for treating bacterial infections has been studied using model strains. However, clinical application of collateral sensitivity requires its conservation among strains presenting different mutational backgrounds. Particularly relevant is studying collateral sensitivity robustness of already-antibiotic-resistant mutants when challenged with a new antimicrobial, a common situation in clinics that has hardly been addressed. We submitted a set of diverse Pseudomonas aeruginosa antibiotic-resistant mutants to short-term evolution in the presence of different antimicrobials. Ciprofloxacin selects different clinically relevant resistance mutations in the preexisting resistant mutants, which gave rise to the same, robust, collateral sensitivity to aztreonam and tobramycin. We then experimentally determined that alternation of ciprofloxacin with aztreonam is more efficient than ciprofloxacin–tobramycin alternation in driving the extinction of the analyzed antibiotic-resistant mutants. Also, we show that the combinations ciprofloxacin–aztreonam or ciprofloxacin–tobramycin are the most effective strategies for eliminating the tested P. aeruginosa antibiotic-resistant mutants. These findings support that the identification of conserved collateral sensitivity patterns may guide the design of evolution-based strategies to treat bacterial infections, including those due to antibiotic-resistant mutants. Besides, this is an example of phenotypic convergence in the absence of parallel evolution that, beyond the antibiotic-resistance field, could facilitate the understanding of evolution processes, where the selective forces giving rise to new, not clearly adaptive phenotypes remain unclear.

Population genetics, biofilm recalcitrance, and antibiotic resistance evolution

Biofilms are communities of bacteria forming high-density sessile colonies. Such a lifestyle comes associated with costs and benefits: while the growth rate of biofilms is often lower than that of their free-living counterparts, this cost is readily repaid once the colony is subjected to antibiotics. Biofilms can grow in antibiotic concentrations a thousand times higher than planktonic bacteria. While numerous mechanisms have been proposed to explain biofilm recalcitrance towards antibiotics, little is yet known about their effect on the evolution of resistance. We synthesize the current understanding of biofilm recalcitrance from a pharmacodynamic and a population genetics perspective. Using the pharmacodynamic framework, we discuss the effects of various mechanisms and show that biofilms can either promote or impede resistance evolution.

Rapid decline of ceftazidime resistance in antibiotic-free and sub-lethal environments is contingent on genetic background

Trade-offs of antibiotic resistance evolution, such as fitness cost and collateral sensitivity (CS), could be exploited to drive evolution toward antibiotic susceptibility. Decline of resistance may occur when resistance to other drug leads to CS to the first one and when compensatory mutations, or genetic reversion of the original ones, reduce fitness cost. Here we describe the impact of antibiotic-free and sublethal environments on declining ceftazidime resistance in different Pseudomonas aeruginosa resistant mutants. We determined that decline of ceftazidime resistance occurs within 450 generations, which is caused by newly acquired mutations and not by reversion of the original ones, and that the original CS of these mutants is preserved. In addition, we observed that the frequency and degree of this decline is contingent on genetic background. Our results are relevant to implement evolution-based therapeutic approaches, as well as to redefine global policies of antibiotic use, such as drug cycling.

Idiosyncratic Fitness Costs of Ampicillin-Resistant Mutants Derived from a Long-Term Experiment with Escherichia coli

Antibiotic resistance is a growing concern that has prompted a renewed focus on drug discovery, stewardship, and evolutionary studies of the patterns and processes that underlie this phenomenon. A resistant strain’s competitive fitness relative to its sensitive counterparts in the absence of drug can impact its spread and persistence in both clinical and community settings. In a prior study, we examined the fitness of tetracycline-resistant clones that evolved from five different Escherichia coli genotypes, which had diverged during a long-term evolution experiment. In this study, we build on that work to examine whether ampicillin-resistant mutants are also less fit in the absence of the drug than their sensitive parents, and whether the cost of resistance is constant or variable among independently derived lines. Like the tetracycline-resistant lines, the ampicillin-resistant mutants were often less fit than their sensitive parents, with significant variation in the fitness costs among the mutants. This variation was not associated with the level of resistance conferred by the mutations, nor did it vary across the different parental backgrounds. In our earlier study, some of the variation in fitness costs associated with tetracycline resistance was explained by the effects of different mutations affecting the same cellular pathway and even the same gene. In contrast, the variance among the ampicillin-resistant mutants was associated with different sets of target genes. About half of the resistant clones suffered large fitness deficits, and their mutations impacted major outer-membrane proteins or subunits of RNA polymerases. The other mutants experienced little or no fitness costs and with, one exception, they had mutations affecting other genes and functions. Our findings underscore the importance of comparative studies on the evolution of antibiotic resistance, and they highlight the nuanced processes that shape these phenotypes.

The Neglected Contribution of Streptomycin to the Tuberculosis Drug Resistance Problem

The airborne pathogen Mycobacterium tuberculosis is responsible for a present major public health problem worsened by the emergence of drug resistance. M. tuberculosis has acquired and developed streptomycin (STR) resistance mechanisms that have been maintained and transmitted in the population over the last decades. Indeed, STR resistant mutations are frequently identified across the main M. tuberculosis lineages that cause tuberculosis outbreaks worldwide. The spread of STR resistance is likely related to the low impact of the most frequent underlying mutations on the fitness of the bacteria. The withdrawal of STR from the first-line treatment of tuberculosis potentially lowered the importance of studying STR resistance. However, the prevalence of STR resistance remains very high, could be underestimated by current genotypic methods, and was found in outbreaks of multi-drug (MDR) and extensively drug (XDR) strains in different geographic regions. Therefore, the contribution of STR resistance to the problem of tuberculosis drug resistance should not be neglected. Here, we review the impact of STR resistance and detail well-known and novel candidate STR resistance mechanisms, genes, and mutations. In addition, we aim to provide insights into the possible role of STR resistance in the development of multi-drug resistant tuberculosis.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Hidden role of mutations in the evolutionary process

Mutations not only alter allele frequencies in a genetic pool but may also determine the fate of an evolutionary process. Here we study which allele fixes in a one-step, one-way model including the wild type and two adaptive mutations. We study the effect of the four basic evolutionary mechanisms-genetic drift, natural selection, mutation, and gene flow-on mutant fixation and its kinetics. Determining which allele is more likely to fix is not simply a question of comparing fitnesses and mutation rates. For instance, if the allele of interest is less fit than the other, then not only must it have a greater mutation rate, but also its mutation rate must exceed a specific threshold for it to prevail. We find exact expressions for such conditions. Our conclusions are based on the mathematical description of two extreme but important regimes, as well as on simulations.

Allogenous Selection of Mutational Collateral Resistance: Old Drugs Select for New Resistance Within Antibiotic Families

Allogeneous selection occurs when an antibiotic selects for resistance to more advanced members of the same family. The mechanisms of allogenous selection are (a) collateral expansion, when the antibiotic expands the gene and gene-containing bacterial populations favoring the emergence of other mutations, inactivating the more advanced antibiotics; (b) collateral selection, when the old antibiotic selects its own resistance but also resistance to more modern drugs; (c) collateral hyper-resistance, when resistance to the old antibiotic selects in higher degree for populations resistant to other antibiotics of the family than to itself; and (d) collateral evolution, when the simultaneous or sequential use of antibiotics of the same family selects for new mutational combinations with novel phenotypes in this family, generally with higher activity (higher inactivation of the antibiotic substrates) or broader spectrum (more antibiotics of the family are inactivated). Note that in some cases, collateral selection derives from collateral evolution. In this article, examples of allogenous selection are provided for the major families of antibiotics. Improvements in minimal inhibitory concentrations with the newest drugs do not necessarily exclude “old” antibiotics of the same family of retaining some selective power for resistance to the newest agents. If this were true, the use of older members of the same drug family would facilitate the emergence of mutational resistance to the younger drugs of the family, which is frequently based on previously established resistance traits. The extensive use of old drugs (particularly in low-income countries and in farming) might be significant for the emergence and selection of resistance to the novel members of the family, becoming a growing source of variation and selection of resistance to the whole family. In terms of future research, it could be advisable to focus antimicrobial drug discovery more on the identification of new targets and new (unique) classes of antimicrobial agents, than on the perpetual chemical exploitation of classic existing ones.

Multiple sequence types, virulence determinants and antimicrobial resistance genes in multidrug- and colistin-resistant Escherichia coli from agricultural and non-agricultural soils

In soils, the presence of clinically relevant bacteria carrying ARGs, including extended-spectrum β-lactamase- and plasmid-mediated AmpC β-lactamase-encoding genes, is an underestimated public health problem that requires more attention. For this investigation, 300 samples from agricultural and non-agricultural soils were used to obtain 41 MDR E. coli isolates, standing out the resistance to β-lactams, fluoroquinolones and colistin. Virulence genes related to diarrheagenic E. coli and extraintestinal pathogenic E. coli were detected. Several ARGs were found, highlighting the presence of at least one β-lactamase-encoding gene (bla_TEM, bla_CMY, bla_SHV, bla_OXA-1-like, bla_CTX-M-2, and/or bla_CTX-M-15) in each isolate. Among the fluoroquinolone-resistant E. coli isolates, the plasmid-mediated quinolone resistance genes (qnrB and oqxA) and substitutions in the quinolone resistance-determining regions were detected. Some isolates were resistant to colistin (MICs of 4-8 mg/L) and, although no mcr-like gene was detected, substitutions in the two-component systems involving PhoP/PhoQ and PmrA/PmrB were found. Furthermore, the E. coli isolates presented plasmids and class 1 integrons, the last one detected in all isolates. The ARGs bla_TEM, aadA and dfrA and the lpfA virulence-associated gene presented statistically significant differences (P < 0.05) in agricultural soils, while the bla_OXA-1-like gene presented a statistically significant difference in non-agricultural soils. Thirty-eight sequence types (STs) were identified among the isolates, spotlighting the 20 different STs that carried bla_CMY and bla_CTX-M-type genes and those commonly reported in infections worldwide. The occurrence of virulent, multidrug- and colistin-resistant E. coli isolates in soils could lead to contamination of surrounding environments and food, increasing the risk of human and animal exposure. Therefore, this study contributes to a better understanding of E. coli in soils and reinforces the importance of the One Health approach to antimicrobial resistance surveillance.

Metagenomic profiles and health risks of pathogens and antibiotic resistance genes in various industrial wastewaters and the associated receiving surface water

The aquatic environment may represent an essential route for transmission of antibiotic resistance to opportunistic human pathogens. Since industrial wastewater is discharged into the river after treatment, understanding the distribution of antibiotic resistance genes (ARGs) in river systems and the possibility of pathogens acquiring antibiotic resistance are challenges with far-reaching significance. This work mainly studied distribution profiles of pathogens and ARGs, and compared their health risk in various industrial wastewater with that of river water. Results showed that 166 pathogens were concurrently shared by the six water samples, with Salmonella enterica and Pseudomonas aeruginosa being the most abundant, followed by Fusarium graminearum and Magnaporthe oryzae. The similar composition of the pathogens suggests that pathogens in river water may mainly come from sewage discharge of slaughterhouses and that changes in water quality contribute significantly to the prevalence of these pathogens. Of the 57 ARG types detected, bacitracin was the most abundant, followed by sulfonamide, chloramphenicol, tetracycline, and aminoglycoside. Strikingly, the wastewater from a pharmaceutical factory producing Chinese medicine was also rich in bacA, sul1, mexW, mexB, mexF and oprn. It can be seen from the co-occurrence patterns that pathogens and the main ARGs have strong co-occurrence. Higher abundance of offensive virulence factors in industrial wastewater and their strong correlation with pathogens containing ARGs suggest higher microbiological risk. These findings highlight the need to assess ARG acquisition by pathogens in the surface water of human-impacted environments where pathogens and ARGs may co-thrive.

Fast Antibiotic Susceptibility Testing via Raman Microspectrometry on Single Bacteria: An MRSA Case Study

Despite recent advances in molecular diagnostics, ultrafast determination of the antibiotic susceptibility phenotype of pathogenic microorganisms is still a major challenge of in vitro diagnostics (IVD) of infectious diseases. Raman microspectroscopy has been proposed as a means to achieve this goal. Previous studies have shown that susceptibility phenotyping could be done through Raman analysis of microbial cells, either in large clusters or down to the single-cell level in the case of Gram-negative rods. Gram-positive cocci such as Staphylococcus aureus pose several challenges due to their size and their different metabolic and chemical characteristics. Using a tailored automated single-cell Raman spectrometer and a previously proposed sample preparation protocol, we acquired and analyzed 9429 S. aureus single cells belonging to three cefoxitin-resistant strains and two susceptible strains during their incubation in the presence of various concentrations of cefoxitin. We observed an effect on S. aureus spectra that is weaker than what was detected on previous bacteria/drug combinations, with a higher cell-to-cell response variability and an important impact of incubation conditions on the phenotypic resistance of a given strain. Overall, the proposed protocol was able to correlate strains' phenotype with a specific modification of the spectra using majority votes. We, hence, confirm that our previous results on single-cell Raman antibiotic susceptibility testing can be extended to the S. aureus case and further clarify potential limitations and development requirements of this approach in the move toward industrial applications.

Recovery of human gut microbiota genomes with third-generation sequencing

Human gut microbiota modulates normal physiological functions, such as maintenance of barrier homeostasis and modulation of metabolism, as well as various chronic diseases including type 2 diabetes and gastrointestinal cancer. Despite decades of research, the composition of the gut microbiota remains poorly understood. Here, we established an effective extraction method to obtain high quality gut microbiota genomes, and analyzed them with third-generation sequencing technology. We acquired a large quantity of data from each sample and assembled large numbers of reliable contigs. With this approach, we constructed tens of completed bacterial genomes in which there were several new bacteria species. We also identified a new conditional pathogen, Enterococcus tongjius, which is a member of Enterococci. This work provided a novel and reliable approach to recover gut microbiota genomes, facilitating the discovery of new bacteria species and furthering our understanding of the microbiome that underlies human health and diseases.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Idiosyncratic variation in the fitness costs of tetracycline-resistance mutations in Escherichia coli

A bacterium's fitness relative to its competitors, both in the presence and absence of antibiotics, plays a key role in its ecological success and clinical impact. In this study, we examine whether tetracycline-resistant mutants are less fit in the absence of the drug than their sensitive parents, and whether the fitness cost of resistance is constant or variable across independently derived lines. Tetracycline-resistant lines suffered, on average, a reduction in fitness of almost 8%. There was substantial among-line variation in the fitness cost. This variation was not associated with the level of resistance conferred by the mutations, nor did it vary significantly across several genetic backgrounds. The two resistant lines with the most extreme fitness costs involved functionally unrelated mutations on different genetic backgrounds. However, there was also significant variation in the fitness costs for mutations affecting the same pathway and even different alleles of the same gene. Our findings demonstrate that the fitness costs of antibiotic resistance do not always correlate with the phenotypic level of resistance or the underlying genetic changes. Instead, these costs reflect the idiosyncratic effects of particular resistance mutations and the genetic backgrounds in which they occur.

Inhibition of Mitochondrial ATP Synthesis and Regulation of Oxidative Stress Based on {SbW8 O30 } Determined by Single-Cell Proteomics Analysis

The 10-nuclear heteroatom cluster modified {SbW₈ O₃₀ } was successfully synthesized and exhibited inhibitory activity (IC₅₀ =0.29 μM). Based on proteomics analysis, Na₄ Ni₂ Sb₂ W₂ -SbW₈ inhibited ATP production by affecting the expression of 16 related proteins, hindering metabolic functions in vivo and cell proliferation due to reactive oxygen species (ROS) stress. In particular, the low expression of FAD/FMN-binding redox enzymes (relative expression ratio of the experimental group to the control=0.43843) could be attributed to the redox mechanism of Na₄ Ni₂ Sb₂ W₂ -SbW₈ , which was consistent with the effect of polyoxometalates (POMs) and FMN-binding proteins on ATP formation. An electrochemical study showed that Na₄ Ni₂ Sb₂ W₂ -SbW₈ combined with FMN to form Na₄ Ni₂ Sb₂ W₂ -SbW₈ -2FMN complex through a one-electron process of the W atoms. Na₄ Ni₂ Sb₂ W₂ -SbW₈ acted as catalase and glutathione peroxidase to protect the cell from ROS stress, and the inhibition rates were 63.3 % at 1.77 μM of NADPH and 86.06 % at 10.62 μM of 2-hydroxyterephthalic acid. Overall, our results showed that POMs can be specific oxidative/antioxidant regulatory agents.

Antivirulence DsbA inhibitors attenuate Salmonella enterica serovar Typhimurium fitness without detectable resistance

Inhibition of the DiSulfide Bond (DSB) oxidative protein folding machinery, a major facilitator of virulence in Gram‐negative bacteria, represents a promising antivirulence strategy. We previously developed small molecule inhibitors of DsbA from Escherichia coli K‐12 (EcDsbA) and showed that they attenuate virulence of Gram‐negative pathogens by directly inhibiting multiple diverse DsbA homologues. Here we tested the evolutionary robustness of DsbA inhibitors as antivirulence antimicrobials against Salmonella enterica serovar Typhimurium under pathophysiological conditions in vitro. We show that phenylthiophene DsbA inhibitors slow S. Typhimurium growth in minimal media, phenocopying S. Typhimurium isogenic dsbA null mutants. Through passaging experiments, we found that DsbA inhibitor resistance was not induced under conditions that rapidly induced resistance to ciprofloxacin, an antibiotic commonly used to treat Salmonella infections. Furthermore, no mutations were identified in the dsbA gene of inhibitor‐treated S. Typhimurium, and S. Typhimurium virulence remained susceptible to DsbA inhibitors. Our work demonstrates that under in vitro pathophysiological conditions, DsbA inhibitors can have both antivirulence and antibiotic action. Importantly, our finding that DsbA inhibitors appear to be evolutionarily robust offers promise for their further development as next‐generation antimicrobials against Gram‐negative pathogens.

Fitness Cost of Antibiotic Resistance in Staphylococcus aureus: A Systematic Review

Background: Recent reports have shown the potential of Staphylococcus aureus for acquiring resistance to last-resort antibiotics. However, most antibiotic resistance mechanisms were associated with a fitness cost that was typically observed as a reduced bacterial growth rate. This systematic review aimed to address the fitness cost of antibiotic resistance in S. aureus that emerged by mutations. Methods: A systematic review was conducted after searching in two databases (PubMed and Scopus) using specific keywords. We included peer-reviewed articles published only in English. All studies describing the fitness cost associated with antibiotic resistance in S. aureus were selected. For each article, the results of fitness testing, minimum inhibition concentrations of mutants, the position of mutation, and the appearance of compensatory mutations were recorded. Results: At all, 35 articles were recorded in the final analysis examining the fitness cost associated with antibiotic resistance in S. aureus that conferred by mutations. Analysis of the data showed that 26 studies reported that the emergence of antibiotic resistance was frequently associated with a fitness cost. Conclusion: This review summarized that the antibiotic resistance selection caused in the majority of cases a substantial fitness cost. Further in vivo experiments revealed that these mutations affected bacterial virulence and the ability to establish a successful infection.

A novel type of colistin resistance genes selected from random sequence space

Antibiotic resistance is a rapidly increasing medical problem that severely limits the success of antibiotic treatments, and the identification of resistance determinants is key for surveillance and control of resistance dissemination. Horizontal transfer is the dominant mechanism for spread of resistance genes between bacteria but little is known about the original emergence of resistance genes. Here, we examined experimentally if random sequences can generate novel antibiotic resistance determinants de novo. By utilizing highly diverse expression libraries encoding random sequences to select for open reading frames that confer resistance to the last-resort antibiotic colistin in Escherichia coli, six de novocolistin resistance conferring peptides (Dcr) were identified. The peptides act via direct interactions with the sensor kinase PmrB (also termed BasS in E. coli), causing an activation of the PmrAB two-component system (TCS), modification of the lipid A domain of lipopolysaccharide and subsequent colistin resistance. This kinase-activation was extended to other TCS by generation of chimeric sensor kinases. Our results demonstrate that peptides with novel activities mediated via specific peptide-protein interactions in the transmembrane domain of a sensory transducer can be selected de novo, suggesting that the origination of such peptides from non-coding regions is conceivable. In addition, we identified a novel class of resistance determinants for a key antibiotic that is used as a last resort treatment for several significant pathogens. The high-level resistance provided at low expression levels, absence of significant growth defects and the functionality of Dcr peptides across different genera suggest that this class of peptides could potentially evolve as bona fide resistance determinants in natura.

We expressed over 100 million randomly generated DNA sequences in Escherichia coli and selected 6 variants that encode peptides that provide resistance to the last-resort antibiotic colistin. We show that the selected peptides are auxiliary activators of the two-component system PmrAB, and that resistance is mediated via modifications of the cell envelope causing decreased antibiotic uptake. This is the first example where random expression libraries have been employed to select for peptides that perform an activating function by direct peptide-protein interactions in vivo, adding support to the idea that non-coding DNA can serve as a substrate for de novo gene evolution. Additionally, the described peptides expand the narrow list of colistin resistance genes and further analyses of clinical isolates will be necessary to determine if similar resistance determinants have evolved in natura.

Antibiotic resistance: turning evolutionary principles into clinical reality

Antibiotic resistance is one of the major challenges facing modern medicine worldwide. The past few decades have witnessed rapid progress in our understanding of the multiple factors that affect the emergence and spread of antibiotic resistance at the population level and the level of the individual patient. However, the process of translating this progress into health policy and clinical practice has been slow. Here, we attempt to consolidate current knowledge about the evolution and ecology of antibiotic resistance into a roadmap for future research as well as clinical and environmental control of antibiotic resistance. At the population level, we examine emergence, transmission and dissemination of antibiotic resistance, and at the patient level, we examine adaptation involving bacterial physiology and host resilience. Finally, we describe new approaches and technologies for improving diagnosis and treatment and minimizing the spread of resistance.

Exploiting Homoplasy in Genome-Wide Association Studies to Enhance Identification of Antibiotic-Resistance Mutations in Bacterial Genomes

Many antibacterial drugs have multiple mechanisms of resistance, which are often represented simultaneously by a mixture of resistance mutations (some more frequent than others) in a clinical population. This presents a challenge for Genome-Wide Association Studies (GWAS) methods, making it difficult to detect less prevalent resistance mechanisms purely through (weak) statistical associations. Homoplasy, or the occurrence of multiple independent mutations at the same site, is often observed with drug resistance mutations and can be a strong indicator of positive selection. However, traditional GWAS methods, such as those based on allele counting or linear regression, are not designed to take homoplasy into account. In this article, we present a new method, called ECAT (for Evolutionary Cluster-based Association Test), that extends traditional regression-based GWAS methods with the ability to take advantage of homoplasy. This is achieved through a preprocessing step which identifies hypervariable regions in the genome exhibiting statistically significant clusters of distinct evolutionary changes, to which association testing by a linear mixed model (LMM) is applied using GEMMA (a well-established LMM-based GWAS tool). Thus, the approach can be viewed as extending GEMMA from the usual site- or gene-level analysis to focusing on clustered regions of mutations. This approach was evaluated on a large collection of more than 600 clinical isolates of multidrug-resistant (MDR) Mycobacterium tuberculosis from Lima, Peru. We show that ECAT does a better job of detecting known resistance mutations for several antitubercular drugs (including less prevalent mutations with weaker associations), compared with (site- or gene-based) GEMMA, as representative of existing GWAS methods. The power of the multiphase approach in ECAT comes from focusing association testing on the hypervariable regions of the genome, which reduces complexity in the model and increases statistical power.

Rapid and robust evolution of collateral sensitivity in Pseudomonas aeruginosa antibiotic-resistant mutants

The analysis of trade-offs, as collateral sensitivity, associated with the acquisition of antibiotic resistance, is mainly based on the use of model strains. However, the possibility of exploiting these trade-offs for fighting already resistant isolates has not been addressed in depth, despite the fact that bacterial pathogens are frequently antibiotic-resistant, forming either homogeneous or heterogeneous populations. Using a set of Pseudomonas aeruginosa-resistant mutants, we found that ceftazidime selects pyomelanogenic tobramycin-hypersusceptible mutants presenting chromosomal deletions in the analyzed genetic backgrounds. Since pyomelanogenic resistant mutants frequently coexist with other morphotypes in patients with cystic fibrosis, we analyzed the exploitation of this trade-off to drive extinction of heterogeneous resistant populations by using tobramycin/ceftazidime alternation. Our work shows that this approach is feasible because phenotypic trade-offs associated with the use of ceftazidime are robust. The identification of conserved collateral sensitivity networks may guide the rational design of evolution-based antibiotic therapies in P. aeruginosa infections.

Genome editing of Francisella tularensis using (CRISPR-Cas9)

The clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) system is a powerful tool for gene editing in eukaryotic genomes but is still being developed for editing bacterial genomes. Here we describe the construction of an all-in-one vector for generating potentially scarless deletion mutants in Francisella tularensis LVS using a CRISPR-Cas9-based system.

Dysbiosis individualizes the fitness effect of antibiotic resistance in the mammalian gut

In the absence of antibiotics, it is essential that antibiotic resistance has a fitness cost for microorganisms if suspending antibiotics treatment is to be a useful strategy for reducing antibiotic resistance. However, the cost of antibiotic resistance within the complex ecosystem of the mammalian gut is not well understood. Here, using mice, we show that the same antibiotic resistance mutation can reduce fitness in one host, while being neutral or even increasing fitness in other hosts. Such antagonistic pleiotropy is shaped by the microbiota because resistance in germ-free mice is consistently costly across all hosts, and the host-specific effect on antibiotic resistance is reduced in hosts with similar microbiotas. Using an eco-evolutionary model of competition for resources, we identify a general mechanism that underlies between-host variation and predicts that the dynamics of compensatory evolution of resistant bacteria should be host specific, a prediction that was supported by experimental evolution in vivo. The microbiome of each human is close to unique, and our results suggest that the short-term cost of resistances and their long-term within-host evolution are also highly personalized, a finding that may contribute to the observed variable outcome of withdrawing antibiotics to reduce resistance levels.

Ce and Er Co-doped TiO2 for rapid bacteria- killing using visible light

Bacterial infection and related diseases are threatening the health of human beings. Photocatalytic disinfection as a simple and low-cost disinfection strategy is attracting more and more attention. In this work, TiO2 nanoparticles (NPs) were modified by co-doping of Ce and Er using the sol-gel method, which endowed TiO2 NPs with enhanced visible light photocatalytic performance but not pure ultraviolet photocatalytic properties compared the untreated TiO2. Our results disclosed that as the doping content of Er increased, the photocatalytic activity of modified TiO2 NPs initially increased and subsequently decreased. The same trend occurred for Ce doping. When the doping dose of Er and Ce is 0.5 mol% and 0.2 mol%, the 0.5Ce0.2Ti-O calcined at 800 °C presented the best antibacterial properties, with the antibacterial efficiency of 91.23% and 92.8% for Staphylococcus aureus and Escherichia coli, respectively. The existence of Er ions is thought to successfully turn the near-infrared radiation into visible region, which is easier to be absorbed by TiO2 NPs. Meanwhile, the addition of Ce ions can effectively extend spectral response range and inhibit the recombination of electrons and holes, enhancing the photocatalytic disinfection activity of co-doped TiO2.

Parallel Evolution of Tobramycin Resistance across Species and Environments

The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.

Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms’ genetic backgrounds and environments.

Predictable properties of fitness landscapes induced by adaptational tradeoffs

Fitness effects of mutations depend on environmental parameters. For example, mutations that increase fitness of bacteria at high antibiotic concentration often decrease fitness in the absence of antibiotic, exemplifying a tradeoff between adaptation to environmental extremes. We develop a mathematical model for fitness landscapes generated by such tradeoffs, based on experiments that determine the antibiotic dose-response curves of Escherichia coli strains, and previous observations on antibiotic resistance mutations. Our model generates a succession of landscapes with predictable properties as antibiotic concentration is varied. The landscape is nearly smooth at low and high concentrations, but the tradeoff induces a high ruggedness at intermediate antibiotic concentrations. Despite this high ruggedness, however, all the fitness maxima in the landscapes are evolutionarily accessible from the wild type. This implies that selection for antibiotic resistance in multiple mutational steps is relatively facile despite the complexity of the underlying landscape.

Resident microbial communities inhibit growth and antibiotic-resistance evolution of Escherichia coli in human gut microbiome samples

Countering the rise of antibiotic-resistant pathogens requires improved understanding of how resistance emerges and spreads in individual species, which are often embedded in complex microbial communities such as the human gut microbiome. Interactions with other microorganisms in such communities might suppress growth and resistance evolution of individual species (e.g., via resource competition) but could also potentially accelerate resistance evolution via horizontal transfer of resistance genes. It remains unclear how these different effects balance out, partly because it is difficult to observe them directly. Here, we used a gut microcosm approach to quantify the effect of three human gut microbiome communities on growth and resistance evolution of a focal strain of Escherichia coli. We found the resident microbial communities not only suppressed growth and colonisation by focal E. coli but also prevented it from evolving antibiotic resistance upon exposure to a beta-lactam antibiotic. With samples from all three human donors, our focal E. coli strain only evolved antibiotic resistance in the absence of the resident microbial community, even though we found resistance genes, including a highly effective resistance plasmid, in resident microbial communities. We identified physical constraints on plasmid transfer that can explain why our focal strain failed to acquire some of these beneficial resistance genes, and we found some chromosomal resistance mutations were only beneficial in the absence of the resident microbiota. This suggests, depending on in situ gene transfer dynamics, interactions with resident microbiota can inhibit antibiotic-resistance evolution of individual species.

Selenite Cystine Agar for Enumeration of Inoculated Salmonella Serovars Recovered from Stressful Conditions During Antimicrobial Validation Studies

Process validation studies often require the inoculation of select foodborne pathogens into targeted foods to determine the lethality of the process or antimicrobial ingredients, and quantitative recovery of surviving inoculum bacteria helps to make those assessments. Such processes introduce various stressors on the inoculated challenge microorganisms whereby traditional selective media are too harsh to enumerate the remaining viable and injured population quantitatively. Innate antibiotic resistance of challenge organisms has often been used to establish simple selective media (i.e., Tryptic Soy Agar/TSA + antibiotics) for recovering inoculated strains, but sometimes antibiotic resistant background microorganisms are higher than desired. Salmonella Thompson 120, Salmonella Heidelberg F5038BG1, Salmonella Hadar MF60404, Salmonella Enteritidis H3527, and Salmonella Typhimurium H3380 were characterized for antibiotic resistance and acid adaptation in Tryptic Soy Broth containing 0%, 0.25%, or 1.0% glucose. Sodium pyruvate was evaluated for recovery after stress but no enhancing effect was observed, possibly because the strains were acid-adapted. Selenite Cystine Broth, traditionally used as a selective enrichment broth, was used as the basis for Selenite Cystine Agar (SCA) in combination with three antibiotics to which our Salmonella are resistant. Serovars of Salmonella, both individually and in mixtures, were enumerated on TSA, SCA, Xylose Lysine Desoxycholate (XLD), and Hektoen Enteric (HE) selective agars (all containing the same antibiotics) after conditions of nutrient starvation, desiccation, acid stress, and thermal stress. The data show that quantitative enumeration of our Salmonella serovars on SCA was not significantly different (p > 0.05) than those achieved on TSA for all tested stress categories. Levels of Salmonella enumerated on XLD and/or HE were significantly different (p < 0.05) than on TSA and SCA and often more than 1-2-log lower, consistent with the inhibition of injured cells. These data confirm that SCA (+ antibiotics) is a suitable selective medium for enumeration of these acid-adapted Salmonella serovars as challenge organisms recovered from various conditions of stress.

VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning

Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches, and there remains incomplete understanding of AMR mechanisms for many pathogen-antimicrobial combinations. Given the rapid, ongoing increase in availability of high-density genomic data for a diverse array of bacteria, development of algorithms that could utilize genomic information to predict phenotype could both be useful clinically and assist with discovery of heretofore unrecognized AMR pathways. To facilitate understanding of the connections between DNA variation and phenotypic AMR, we developed a new bioinformatics tool, variant mapping and prediction of antibiotic resistance (VAMPr), to (1) derive gene ortholog-based sequence features for protein variants; (2) interrogate these explainable gene-level variants for their known or novel associations with AMR; and (3) build accurate models to predict AMR based on whole genome sequencing data. We curated the publicly available sequencing data for 3,393 bacterial isolates from 9 species that contained AMR phenotypes for 29 antibiotics. We detected 14,615 variant genotypes and built 93 association and prediction models. The association models confirmed known genetic antibiotic resistance mechanisms, such as blaKPC and carbapenem resistance consistent with the accurate nature of our approach. The prediction models achieved high accuracies (mean accuracy of 91.1% for all antibiotic-pathogen combinations) internally through nested cross validation and were also validated using external clinical datasets. The VAMPr variant detection method, association and prediction models will be valuable tools for AMR research for basic scientists with potential for clinical applicability.

Antimicrobial resistance (AMR) is a global health threat. The current method to determine AMR is inefficient and complete understanding of the mechanisms of AMR is lacking. With the increased feasibility of sequencing bacterial genomes, it is now easier, faster and cheaper to have genomic insights into AMR. In this manuscript, we propose a novel bioinformatic tool for variant mapping and prediction of antibiotic resistance (VAMPr). We curated 3,393 bacterial genomes from 9 bacterial species that contained AMR phenotypes for 29 antibiotics. We used protein orthology and detected 14,615 variants. Combined with AMR phenotypes, we built 93 association and prediction models. The association model confirms known genetic AMR mechanisms, and the prediction models achieved high accuracies. Together, our work will be valuable for AMR research for basic scientists with the potential for clinical applicability.

Antibiotic Resistance Evolution Is Contingent on the Quorum-Sensing Response in Pseudomonas aeruginosa

Different works have explored independently the evolution toward antibiotic resistance and the role of eco-adaptive mutations in the adaptation to a new habitat (as the infected host) of bacterial pathogens. However, knowledge about the connection between both processes is still limited. We address this issue by comparing the evolutionary trajectories toward antibiotic resistance of a Pseudomonas aeruginosa lasR defective mutant and its parental wild-type strain, when growing in presence of two ribosome-targeting antibiotics. Quorum-sensing lasR defective mutants are selected in P. aeruginosa populations causing chronic infections. Further, we observed they are also selected in vitro as a first adaptation for growing in culture medium. By using experimental evolution and whole-genome sequencing, we found that the evolutionary trajectories of P. aeruginosa in presence of these antibiotics are different in lasR defective and in wild-type backgrounds, both at the phenotypic and the genotypic levels. Recreation of a set of mutants in both genomic backgrounds (either wild type or lasR defective) allowed us to determine the existence of negative epistatic interactions between lasR and antibiotic resistance determinants. These epistatic interactions could lead to mutual contingency in the evolution of antibiotic resistance when P. aeruginosa colonizes a new habitat in presence of antibiotics. If lasR mutants are selected first, this would constraint antibiotic resistance evolution. Conversely, when resistance mutations (at least those studied in the present work) are selected, lasR mutants may not be selected in presence of antibiotics. These results underlie the importance of contingency and epistatic interactions in modulating antibiotic resistance evolution.

Soil biota, antimicrobial resistance and planetary health

The concept of planetary health acknowledges the links between ecosystems, biodiversity and human health and well-being. Soil, the critical component of the interconnected ecosystem, is the most biodiverse habitat on Earth, and soil microbiomes play a major role in human health and well-being through ecosystem services such as nutrient cycling, pollutant remediation and synthesis of bioactive compounds such as antimicrobials. Soil is also a natural source of antimicrobial resistance, which is often termed intrinsic resistance. However, increasing use and misuse of antimicrobials in humans and animals in recent decades has increased both the diversity and prevalence of antimicrobial resistance in soils, particularly in areas affected by human and animal wastes, such as organic manures and reclaimed wastewater, and also by air transmission. Antimicrobials and antimicrobial resistance are two sides of the sword, while antimicrobials are essential in health care; globally, antimicrobial resistance is jeopardizing the effectiveness of antimicrobial drugs, thus threatening human health. Soil is a crucial pathway through which humans are exposed to antimicrobial resistance determinants, including those harbored by human pathogens. In this review, we use the nexus of antimicrobials and antimicrobial resistance as a focus to discuss the role of soil in planetary health and illustrate the impacts of soil microbiomes on human health and well-being. This review examines the sources and dynamics of antimicrobial resistance in soils and uses the perspective of planetary health to track the movement of antimicrobial-resistance genes between environmental compartments, including soil, water, food and air.

Phenotypic Resistance in Photodynamic Inactivation Unravelled at the Single Bacterium Level

Herein we report a simple fluorescence microscopy methodology that, jointly with four photosensitizers (PSs) and a cell viability marker, allows monitoring of phenotypic bacterial resistance to photodynamic inactivation (PDI) treatments. The PSs, composed of BODIPY dyes, were selected according to their ability to interact with the cell wall and the photoinactivating mechanism involved (type I or type II). In a first approach, the phenotypic heterogeneity allowing bacteria to persist during PDI treatment was evaluated in methicillin-resistant Staphylococcus aureus (MRSA) and Escherichia coli as Gram-positive and Gram-negative models, respectively. By means of propidium iodide (PI), we monitored with spatiotemporal resolution cell viability at the single bacterium level. All the PSs were effective at inactivating pathogens; however, the cationic nonhalogenated PS (compound 1) surpassed the others and was capable of photoinactivating E. coli even under optimal growth conditions. Compound 1 was further tested on two other Gram-negative strains, Pseudomonas aeruginosa and Klebsiella pneumoniae, with outstanding results. All bacterial strains used here are well-known ESKAPE pathogens, which are the leading cause of nosocomial infections worldwide. Thorough data analysis of individual cell survival times revealed clear phenotypic variation expressed in the cell wall that affected PI permeation and thus its intercalation with DNA. For the same bacterial sample, death times may vary from seconds to hours. In addition, the PI incorporation time is also a parameter governed by the phenotypic characteristics of the microbes. Finally, we demonstrate that the results gathered for the bacteria provide direct and unique experimental evidence that supports the time-kill curve profiles.

Limited Evolutionary Conservation of the Phenotypic Effects of Antibiotic Resistance Mutations

Multidrug-resistant clinical isolates are common in certain pathogens, but rare in others. This pattern may be due to the fact that mutations shaping resistance have species-specific effects. To investigate this issue, we transferred a range of resistance-conferring mutations and a full resistance gene into Escherichia coli and closely related bacteria. We found that resistance mutations in one bacterial species frequently provide no resistance, in fact even yielding drug hypersensitivity in close relatives. In depth analysis of a key gene involved in aminoglycoside resistance (trkH) indicated that preexisting mutations in other genes-intergenic epistasis-underlie such extreme differences in mutational effects between species. Finally, reconstruction of adaptive landscapes under multiple antibiotic stresses revealed that mutations frequently provide multidrug resistance or elevated drug susceptibility (i.e., collateral sensitivity) only with certain combinations of other resistance mutations. We conclude that resistance and collateral sensitivity are contingent upon the genetic makeup of the bacterial population, and such contingency could shape the long-term fate of resistant bacteria. These results underlie the importance of species-specific treatment strategies.