The effect of environmental heterogeneity on the fitness of antibiotic resistance mutations in Escherichia coli

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.

Plasmids, a molecular cornerstone of antimicrobial resistance in the One Health era

Antimicrobial resistance (AMR) poses a substantial threat to human health. The widespread prevalence of AMR is, in part, due to the horizontal transfer of antibiotic resistance genes (ARGs), typically mediated by plasmids. Many of the plasmid-mediated resistance genes in pathogens originate from environmental, animal or human habitats. Despite evidence that plasmids mobilize ARGs between these habitats, we have a limited understanding of the ecological and evolutionary trajectories that facilitate the emergence of multidrug resistance (MDR) plasmids in clinical pathogens. One Health, a holistic framework, enables exploration of these knowledge gaps. In this Review, we provide an overview of how plasmids drive local and global AMR spread and link different habitats. We explore some of the emerging studies integrating an eco-evolutionary perspective, opening up a discussion about the factors that affect the ecology and evolution of plasmids in complex microbial communities. Specifically, we discuss how the emergence and persistence of MDR plasmids can be affected by varying selective conditions, spatial structure, environmental heterogeneity, temporal variation and coexistence with other members of the microbiome. These factors, along with others yet to be investigated, collectively determine the emergence and transfer of plasmid-mediated AMR within and between habitats at the local and global scale.

Pervasive genotype-by-environment interactions shape the fitness effects of antibiotic resistance mutations

The fitness effects of antibiotic resistance mutations are a major driver of resistance evolution. While the nutrient environment affects bacterial fitness, experimental studies of resistance typically measure fitness of mutants in a single environment only. We explored how the nutrient environment affected the fitness effects of rifampicin-resistant rpoB mutations in Escherichia coli under several conditions critical for the emergence and spread of resistance-the presence of primary or secondary antibiotic, or the absence of any antibiotic. Pervasive genotype-by-environment (GxE) interactions determined fitness in all experimental conditions, with rank order of fitness in the presence and absence of antibiotics being strongly dependent on the nutrient environment. GxE interactions also affected the magnitude and direction of collateral effects of secondary antibiotics, in some cases so drastically that a mutant that was highly sensitive in one nutrient environment exhibited cross-resistance to the same antibiotic in another. It is likely that the mutant-specific impact of rpoB mutations on the global transcriptome underpins the observed GxE interactions. The pervasive, mutant-specific GxE interactions highlight the importance of doing what is rarely done when studying the evolution and spread of resistance in experimental and clinical work: assessing fitness of antibiotic-resistant mutants across a range of relevant environments.

Monitoring the Microevolution of Salmonella enterica in Healthy Dairy Cattle Populations at the Individual Farm Level Using Whole-Genome Sequencing

Livestock represent a possible reservoir for facilitating the transmission of the zoonotic foodborne pathogen Salmonella enterica to humans; there is also concern that strains can acquire resistance to antimicrobials in the farm environment. Here, whole-genome sequencing (WGS) was used to characterize Salmonella strains (n = 128) isolated from healthy dairy cattle and their associated environments on 13 New York State farms to assess the diversity and microevolution of this important pathogen at the level of the individual herd. Additionally, the accuracy and concordance of multiple in silico tools are assessed, including: (i) two in silico serotyping tools, (ii) combinations of five antimicrobial resistance (AMR) determinant detection tools and one to five AMR determinant databases, and (iii) one antimicrobial minimum inhibitory concentration (MIC) prediction tool. For the isolates sequenced here, in silico serotyping methods outperformed traditional serotyping and resolved all un-typable and/or ambiguous serotype assignments. Serotypes assigned in silico showed greater congruency with the Salmonella whole-genome phylogeny than traditional serotype assignments, and in silico methods showed high concordance (99% agreement). In silico AMR determinant detection methods additionally showed a high degree of concordance, regardless of the pipeline or database used (≥98% agreement among susceptible/resistant assignments for all pipeline/database combinations). For AMR detection methods that relied exclusively on nucleotide BLAST, accuracy could be maximized by using a range of minimum nucleotide identity and coverage thresholds, with thresholds of 75% nucleotide identity and 50-60% coverage adequate for most pipeline/database combinations. In silico characterization of the microevolution and AMR dynamics of each of six serotype groups (S. Anatum, Cerro, Kentucky, Meleagridis, Newport, Typhimurium/Typhimurium variant Copenhagen) revealed that some lineages were strongly associated with individual farms, while others were distributed across multiple farms. Numerous AMR determinant acquisition and loss events were identified, including the recent acquisition of cephalosporin resistance-conferring bla CMY- and bla CTX-M-type beta-lactamases. The results presented here provide high-resolution insight into the temporal dynamics of AMR Salmonella at the scale of the individual farm and highlight both the strengths and limitations of WGS in tracking zoonotic pathogens and their associated AMR determinants at the livestock-human interface.

Antibiotic-Resistant Genes and Bacteria as Evolving Contaminants of Emerging Concerns (e-CEC): Is It Time to Include Evolution in Risk Assessment?

The pressing issue of the abundance of antibiotic resistance genes and resistant bacteria in the environment (ARGs and ARB, respectively) requires procedures for assessing the risk to health. The chemo-centric environmental risk assessment models identify hazard(s) in a dose–response manner, obtaining exposure, toxicity, risk, impact and policy. However, this risk assessment approach based on ARGs/ARB evaluation from a quantitative viewpoint shows high unpredictability because ARGs/ARB cannot be considered as standard hazardous molecules: ARB duplicate and ARGs evolve within a biological host. ARGs/ARB are currently listed as Contaminants of Emerging Concern (CEC). In light of such characteristics, we propose to define ARGs/ARB within a new category of evolving CEC (or e-CEC). ARGs/ARB, like any other evolving determinants (e.g., viruses, bacteria, genes), escape environmental controls. When they do so, just one molecule left remaining at a control point can form the origin of a new dangerous and selection-responsive population. As a consequence, perhaps it is time to acknowledge this trait and to include evolutionary concepts within modern risk assessment of e-CEC. In this perspective we analyze the evolutionary responses most likely to influence risk assessment, and we speculate on the means by which current methods could measure evolution. Further work is required to implement and exploit such experimental procedures in future risk assessment protocols.

Differential Survival of Non-O157 Shiga Toxigenic Escherichia coli in Simulated Cattle Feedlot Runoff

Environmental survival time is important when evaluating adverse health outcomes from foodborne pathogens. Although outbreaks associated with manure-impacted irrigation or runoff water are relatively infrequent, their broad scope, regulatory importance, and severe health outcomes highlight the need to better understand the environmental survival of manure-borne pathogens. Shiga toxigenic Escherichia coli (STEC) are excreted in feces and persist in the environment until they die or recolonize a new host. Surface waters contaminated with manure-borne STEC can infect humans through drinking and recreational water use or irrigated crops that are minimally cooked. In this study, manure-impacted water microcosms mimicking beef cattle feedlot runoff were used to assess survival of STEC strains representing seven STEC serotypes (O26, O45, O103, O111, O121, O145, and O157) and persistence of target O antigen genes. Microcosms were sampled over the course of 1 year, and the entire experiment was repeated in a second year. Culture and polymerase chain reaction (PCR)-based techniques were used for detection and enumeration. Serotype-specific survival results were observed. Both STEC O26 and O45 declined slowly and remained culturable at 24 months. In contrast, STEC O121 and O145 decreased rapidly (-0.84 and -1.99 log10 abundance per month, respectively) and were unculturable by months 4 and 5, but detectable by PCR for a mean of 4.5 and 8.3 months, respectively. STEC O103, O111, and O157 remained culturable for a mean of 11.6, 5.5, and 15 months and detectable by PCR for a mean of 12, 13.8, and 18.6 months after inoculation, respectively. Results document that some STEC serotypes have the biological potential to survive in manure-impacted waters for extended periods of time when competing microflora are eliminated. Serotype-specific differences in survival of target bacteria and persistence of target genes were observed in this sample set, with STEC O26 and O45 strains appearing the most robust in these microcosm studies.

Role played by the environment in the emergence and spread of antimicrobial resistance (AMR) through the food chain

The role of food-producing environments in the emergence and spread of antimicrobial resistance (AMR) in EU plant-based food production, terrestrial animals (poultry, cattle and pigs) and aquaculture was assessed. Among the various sources and transmission routes identified, fertilisers of faecal origin, irrigation and surface water for plant-based food and water for aquaculture were considered of major importance. For terrestrial animal production, potential sources consist of feed, humans, water, air/dust, soil, wildlife, rodents, arthropods and equipment. Among those, evidence was found for introduction with feed and humans, for the other sources, the importance could not be assessed. Several ARB of highest priority for public health, such as carbapenem or extended-spectrum cephalosporin and/or fluoroquinolone-resistant Enterobacterales (including Salmonella enterica), fluoroquinolone-resistant Campylobacter spp., methicillin-resistant Staphylococcus aureus and glycopeptide-resistant Enterococcus faecium and E. faecalis were identified. Among highest priority ARGs bla CTX -M, bla VIM, bla NDM, bla OXA -48-like, bla OXA -23, mcr, armA, vanA, cfr and optrA were reported. These highest priority bacteria and genes were identified in different sources, at primary and post-harvest level, particularly faeces/manure, soil and water. For all sectors, reducing the occurrence of faecal microbial contamination of fertilisers, water, feed and the production environment and minimising persistence/recycling of ARB within animal production facilities is a priority. Proper implementation of good hygiene practices, biosecurity and food safety management systems is very important. Potential AMR-specific interventions are in the early stages of development. Many data gaps relating to sources and relevance of transmission routes, diversity of ARB and ARGs, effectiveness of mitigation measures were identified. Representative epidemiological and attribution studies on AMR and its effective control in food production environments at EU level, linked to One Health and environmental initiatives, are urgently required.

Extreme Antagonism Arising from Gene-Environment Interactions

Antagonistic interactions in biological systems, which occur when one perturbation blunts the effect of another, are typically interpreted as evidence that the two perturbations impact the same cellular pathway or function. Yet, this interpretation ignores extreme antagonistic interactions wherein an otherwise deleterious perturbation compensates for the function lost because of a prior perturbation. Here, we report on gene-environment interactions involving genetic mutations that are deleterious in a permissive environment but beneficial in a specific environment that restricts growth. These extreme antagonistic interactions constitute gene-environment analogs of synthetic rescues previously observed for gene-gene interactions. Our approach uses two independent adaptive evolution steps to address the lack of experimental methods to systematically identify such extreme interactions. We apply the approach to Escherichia coli by successively adapting it to defined glucose media without and with the antibiotic rifampicin. The approach identified multiple mutations that are beneficial in the presence of rifampicin and deleterious in its absence. The analysis of transcription shows that the antagonistic adaptive mutations repress a stringent response-like transcriptional program, whereas nonantagonistic mutations have an opposite transcriptional profile. Our approach represents a step toward the systematic characterization of extreme antagonistic gene-drug interactions, which can be used to identify targets to select against antibiotic resistance.

Tackling Antibiotic Resistance with Compounds of Natural Origin: A Comprehensive Review

Drug-resistant bacteria pose a serious threat to human health worldwide. Current antibiotics are losing efficacy and new antimicrobial agents are urgently needed. Living organisms are an invaluable source of antimicrobial compounds. The antimicrobial activity of the most representative natural products of animal, bacterial, fungal and plant origin are reviewed in this paper. Their activity against drug-resistant bacteria, their mechanisms of action, the possible development of resistance against them, their role in current medicine and their future perspectives are discussed. Electronic databases such as PubMed, Scopus and ScienceDirect were used to search scientific contributions until September 2020, using relevant keywords. Natural compounds of heterogeneous origins have been shown to possess antimicrobial capabilities, including against antibiotic-resistant bacteria. The most commonly found mechanisms of antimicrobial action are related to protein biosynthesis and alteration of cell walls and membranes. Various natural compounds, especially phytochemicals, have shown synergistic capacity with antibiotics. There is little literature on the development of specific resistance mechanisms against natural antimicrobial compounds. New technologies such as -omics, network pharmacology and informatics have the potential to identify and characterize new natural antimicrobial compounds in the future. This knowledge may be useful for the development of future therapeutic strategies.