Emerging enterococcus pore-forming toxins with MHC/HLA-I as receptors.

Enterococci are a part of human microbiota and a leading cause of multidrug resistant infections. Here, we identify a family of Enterococcus pore-forming toxins (Epxs) in E. faecalis, E. faecium, and E. hirae strains isolated across the globe. Structural studies reveal that Epxs form a branch of ß-barrel pore-forming toxins with a ß-barrel protrusion (designated the top domain) sitting atop the cap domain. Through a genome-wide CRISPR-Cas9 screen, we identify human leukocyte antigen class I (HLA-I) complex as a receptor for two members (Epx2 and Epx3), which preferentially recognize human HLA-I and homologous MHC-I of equine, bovine, and porcine, but not murine, origin. Interferon exposure, which stimulates MHC-I expression, sensitizes human cells and intestinal organoids to Epx2 and Epx3 toxicity. Co-culture with Epx2-harboring E. faecium damages human peripheral blood mononuclear cells and intestinal organoids, and this toxicity is neutralized by an Epx2 antibody, demonstrating the toxin-mediated virulence of Epx-carrying Enterococcus.

Tracing the Enterococci from Paleozoic Origins to the Hospital.

We examined the evolutionary history of leading multidrug resistant hospital pathogens, the enterococci, to their origin hundreds of millions of years ago. Our goal was to understand why, among the vast diversity of gut flora, enterococci are so well adapted to the modern hospital environment. Molecular clock estimation, together with analysis of their environmental distribution, phenotypic diversity, and concordance with host fossil records, place the origins of the enterococci around the time of animal terrestrialization, 425-500 mya. Speciation appears to parallel the diversification of hosts, including the rapid emergence of new enterococcal species following the End Permian Extinction. Major drivers of speciation include changing carbohydrate availability in the host gut. Life on land would have selected for the precise traits that now allow pathogenic enterococci to survive desiccation, starvation, and disinfection in the modern hospital, foreordaining their emergence as leading hospital pathogens.

Discovery of a structural class of antibiotics with explainable deep learning.

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1-9. Deep learning approaches have aided in exploring chemical spaces1,10-15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies.

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

Global diversity of enterococci and description of 18 previously unknown species.

Enterococci are gut microbes of most land animals. Likely appearing first in the guts of arthropods as they moved onto land, they diversified over hundreds of millions of years adapting to evolving hosts and host diets. Over 60 enterococcal species are now known. Two species, Enterococcus faecalis and Enterococcus faecium, are common constituents of the human microbiome. They are also now leading causes of multidrug-resistant hospital-associated infection. The basis for host association of enterococcal species is unknown. To begin identifying traits that drive host association, we collected 886 enterococcal strains from widely diverse hosts, ecologies, and geographies. This identified 18 previously undescribed species expanding genus diversity by >25%. These species harbor diverse genes including toxins and systems for detoxification and resource acquisition. Enterococcus faecalis and E. faecium were isolated from diverse hosts highlighting their generalist properties. Most other species showed a more restricted distribution indicative of specialized host association. The expanded species diversity permitted the Enterococcus genus phylogeny to be viewed with unprecedented resolution, allowing features to be identified that distinguish its four deeply rooted clades, and the entry of genes associated with range expansion such as B-vitamin biosynthesis and flagellar motility to be mapped to the phylogeny. This work provides an unprecedentedly broad and deep view of the genus Enterococcus, including insights into its evolution, potential new threats to human health, and where substantial additional enterococcal diversity is likely to be found.

Comparison of long- and short-read metagenomic assembly for low-abundance species and resistance genes.

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

SAFPred: synteny-aware gene function prediction for bacteria using protein embeddings.

MOTIVATION: Today, we know the function of only a small fraction of the protein sequences predicted from genomic data. This problem is even more salient for bacteria, which represent some of the most phylogenetically and metabolically diverse taxa on Earth. This low rate of bacterial gene annotation is compounded by the fact that most function prediction algorithms have focused on eukaryotes, and conventional annotation approaches rely on the presence of similar sequences in existing databases. However, often there are no such sequences for novel bacterial proteins. Thus, we need improved gene function prediction methods tailored for bacteria. Recently, transformer-based language models-adopted from the natural language processing field-have been used to obtain new representations of proteins, to replace amino acid sequences. These representations, referred to as protein embeddings, have shown promise for improving annotation of eukaryotes, but there have been only limited applications on bacterial genomes. RESULTS: To predict gene functions in bacteria, we developed SAFPred, a novel synteny-aware gene function prediction tool based on protein embeddings from state-of-the-art protein language models. SAFpred also leverages the unique operon structure of bacteria through conserved synteny. SAFPred outperformed both conventional sequence-based annotation methods and state-of-the-art methods on multiple bacterial species, including for distant homolog detection, where the sequence similarity to the proteins in the training set was as low as 40%. Using SAFPred to identify gene functions across diverse enterococci, of which some species are major clinical threats, we identified 11 previously unrecognized putative novel toxins, with potential significance to human and animal health. AVAILABILITY AND IMPLEMENTATION: https://github.com/AbeelLab/safpred.

Clinical and Genomic Characterization of a Cohort of Patients With Klebsiella pneumoniae Bloodstream Infection.

BACKGROUND: The clinical and microbial factors associated with Klebsiella pneumoniae bloodstream infections (BSIs) are not well characterized. Prior studies have focused on highly resistant or hypervirulent isolates, limiting our understanding of K. pneumoniae strains that commonly cause BSI. We performed a record review and whole-genome sequencing to investigate the clinical characteristics, bacterial diversity, determinants of antimicrobial resistance, and risk factors for in-hospital death in a cohort of patients with K. pneumoniae BSI. METHODS: We identified 562 patients at Massachusetts General Hospital with K. pneumoniae BSIs between 2016 and 2022. We collected data on comorbid conditions, infection source, clinical outcomes, and antibiotic resistance and performed whole-genome sequencing on 108 sequential BSI isolates from 2021 to 2022. RESULTS: Intra-abdominal infection was the most common source of infection accounting for 34% of all BSIs. A respiratory tract source accounted for 6% of BSIs but was associated with a higher in-hospital mortality rate (adjusted odds ratio, 5.4 [95% confidence interval, 2.2-12.8]; P < .001 for comparison with other sources). Resistance to the first antibiotic prescribed was also associated with a higher risk of death (adjusted odds ratio, 5.2 [95% confidence interval, 2.2-12.4]; P < .001). BSI isolates were genetically diverse, and no clusters of epidemiologically and genetically linked cases were observed. Virulence factors associated with invasiveness were observed at a low prevalence, although an unexpected association between O-antigen type and the source of infection was found. CONCLUSIONS: These observations demonstrate the versatility of K. pneumoniae as an opportunistic pathogen and highlight the need for new approaches for surveillance and the rapid identification of patients with invasive antimicrobial-resistant K. pneumoniae infection.

Utility of Mycobacterium tuberculosis genome sequencing snapshots to assess transmission dynamics over time.

We explored the utility of brief Mycobacterium tuberculosis whole-genome sequencing (WGS) "snapshots" at a sentinel site within Lima, Peru for evaluating local transmission dynamics over time. Within a 17 km2 area, 15/70 (21%) isolates with WGS collected during 2011-2012 and 22/81 (27%) collected during 2020-2021 were clustered (p = 0.414), and additional isolates clustered with those from outside the area. Isolates from the later period were disproportionately related to large historic clusters in Lima from the earlier period. WGS snapshots at a sentinel site may not be useful for monitoring transmission, but monitoring the persistence of large transmission clusters might be.

Intrinsic Resistance to Colistin in the Genus Hafnia.

A bacterial species is considered to be intrinsically resistant to an antimicrobial when nearly all of the wild-type isolates (i.e., those without acquired resistance) exhibit minimum inhibitory concentration (MIC) values that are sufficiently high such that susceptibility testing is unnecessary, and that the antimicrobial should not be considered for therapy. Accordingly, knowledge of intrinsic resistance influences both the selection of treatment regimens and the approach to susceptibility testing in the clinical laboratory, where unexpected results also facilitate the recognition of microbial identification or susceptibility testing errors. Previously, limited data have suggested that Hafnia spp. may be intrinsically resistant to colistin. We evaluated the in vitro activity of colistin against 119 Hafniaceae that were isolated from human samples: 75 (63%) from routine clinical cultures and 44 (37%) from stool samples of travelers undergoing screening for antimicrobial resistant organisms. Broth microdilution colistin MICs were ≥4 µg/mL for 117 of 119 (98%) isolates. Whole-genome sequencing of 96 of the isolates demonstrated that the colistin-resistant phenotype was not lineage-specific. 2 of the 96 (2%) isolates harbored mobile colistin resistance genes. Compared to whole-genome sequencing, VITEK MS matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and VITEK 2 GN ID failed to consistently distinguish between Hafnia alvei, Hafnia paralvei, and Obesumbacterium proteus. In conclusion, using a reference antimicrobial susceptibility testing method and a genetically diverse collection of isolates, we found Hafnia spp. to be intrinsically resistant to colistin. The recognition of this phenotype will help inform rational approaches by which to perform antimicrobial susceptibility testing and therapy for patients with infections that are caused by Hafnia spp.

Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery.

Efficient identification of drug mechanisms of action remains a challenge. Computational docking approaches have been widely used to predict drug binding targets; yet, such approaches depend on existing protein structures, and accurate structural predictions have only recently become available from AlphaFold2. Here, we combine AlphaFold2 with molecular docking simulations to predict protein-ligand interactions between 296 proteins spanning Escherichia coli's essential proteome, and 218 active antibacterial compounds and 100 inactive compounds, respectively, pointing to widespread compound and protein promiscuity. We benchmark model performance by measuring enzymatic activity for 12 essential proteins treated with each antibacterial compound. We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance. We demonstrate that rescoring of docking poses using machine learning-based approaches improves model performance, resulting in average auROCs as large as 0.63, and that ensembles of rescoring functions improve prediction accuracy and the ratio of true-positive rate to false-positive rate. This work indicates that advances in modeling protein-ligand interactions, particularly using machine learning-based approaches, are needed to better harness AlphaFold2 for drug discovery.

Transcriptomics Reveals How Minocycline-Colistin Synergy Overcomes Antibiotic Resistance in Multidrug-Resistant Klebsiella pneumoniae.

Multidrug-resistant Gram-negative bacteria are a rapidly growing public health threat, and the development of novel antimicrobials has failed to keep pace with their emergence. Synergistic combinations of individually ineffective drugs present a potential solution, yet little is understood about the mechanisms of most such combinations. Here, we show that the combination of colistin (polymyxin E) and minocycline has a high rate of synergy against colistin-resistant and minocycline-intermediate or -resistant strains of Klebsiella pneumoniae. Furthermore, using transcriptome sequencing (RNA-Seq), we characterized the transcriptional profiles of these strains when treated with the drugs individually and in combination. We found a striking similarity between the transcriptional profiles of bacteria treated with the combination of colistin and minocycline at individually subinhibitory concentrations and those of the same isolates treated with minocycline alone. We observed a similar pattern with the combination of polymyxin B nonapeptide (a polymyxin B analogue that lacks intrinsic antimicrobial activity) and minocycline. We also found that genes involved in polymyxin resistance and peptidoglycan biosynthesis showed significant differential gene expression in the different treatment conditions, suggesting possible mechanisms for the antibacterial activity observed in the combination. These findings suggest that the synergistic activity of this combination against bacteria resistant to each drug alone involves sublethal outer membrane disruption by colistin, which permits increased intracellular accumulation of minocycline.

Limited effects of long-term daily cranberry consumption on the gut microbiome in a placebo-controlled study of women with recurrent urinary tract infections.

BACKGROUND: Urinary tract infections (UTIs) affect 15 million women each year in the United States, with > 20% experiencing frequent recurrent UTIs. A recent placebo-controlled clinical trial found a 39% reduction in UTI symptoms among recurrent UTI sufferers who consumed a daily cranberry beverage for 24 weeks. Using metagenomic sequencing of stool from a subset of these trial participants, we assessed the impact of cranberry consumption on the gut microbiota, a reservoir for UTI-causing pathogens such as Escherichia coli, which causes > 80% of UTIs. RESULTS: The overall taxonomic composition, community diversity, carriage of functional pathways and gene families, and relative abundances of the vast majority of observed bacterial taxa, including E. coli, were not changed significantly by cranberry consumption. However, one unnamed Flavonifractor species (OTU41), which represented ≤1% of the overall metagenome, was significantly less abundant in cranberry consumers compared to placebo at trial completion. Given Flavonifractor's association with negative human health effects, we sought to determine OTU41 characteristic genes that may explain its differential abundance and/or relationship to key host functions. Using comparative genomic and metagenomic techniques, we identified genes in OTU41 related to transport and metabolism of various compounds, including tryptophan and cobalamin, which have been shown to play roles in host-microbe interactions. CONCLUSION: While our results indicated that cranberry juice consumption had little impact on global measures of the microbiome, we found one unnamed Flavonifractor species differed significantly between study arms. This suggests further studies are needed to assess the role of cranberry consumption and Flavonifractor in health and wellbeing in the context of recurrent UTI. TRIAL REGISTRATION: Clinical trial registration number: ClinicalTrials.gov NCT01776021 .

QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data.

BACKGROUND: Mixed infections of Mycobacterium tuberculosis and antibiotic heteroresistance continue to complicate tuberculosis (TB) diagnosis and treatment. Detection of mixed infections has been limited to molecular genotyping techniques, which lack the sensitivity and resolution to accurately estimate the multiplicity of TB infections. In contrast, whole genome sequencing offers sensitive views of the genetic differences between strains of M. tuberculosis within a sample. Although metagenomic tools exist to classify strains in a metagenomic sample, most tools have been developed for more divergent species, and therefore cannot provide the sensitivity required to disentangle strains within closely related bacterial species such as M. tuberculosis. Here we present QuantTB, a method to identify and quantify individual M. tuberculosis strains in whole genome sequencing data. QuantTB uses SNP markers to determine the combination of strains that best explain the allelic variation observed in a sample. QuantTB outputs a list of identified strains, their corresponding relative abundances, and a list of drugs for which resistance-conferring mutations (or heteroresistance) have been predicted within the sample. RESULTS: We show that QuantTB has a high degree of resolution and is capable of differentiating communities differing by less than 25 SNPs and identifying strains down to 1× coverage. Using simulated data, we found QuantTB outperformed other metagenomic strain identification tools at detecting strains and quantifying strain multiplicity. In a real-world scenario, using a dataset of 50 paired clinical isolates from a study of patients with either reinfections or relapses, we found that QuantTB could detect mixed infections and reinfections at rates concordant with a manually curated approach. CONCLUSION: QuantTB can determine infection multiplicity, identify hetero-resistance patterns, enable differentiation between relapse and re-infection, and clarify transmission events across seemingly unrelated patients - even in low-coverage (1×) samples. QuantTB outperforms existing tools and promises to serve as a valuable resource for both clinicians and researchers working with clinical TB samples.

Evidence for Expanding the Role of Streptomycin in the Management of Drug-Resistant Mycobacterium tuberculosis.

In 2019, the WHO tuberculosis (TB) treatment guidelines were updated to recommend only limited use of streptomycin, in favor of newer agents or amikacin as the preferred aminoglycoside for drug-resistant Mycobacterium tuberculosis However, the emergence of resistance to newer drugs, such as bedaquiline, has prompted a reanalysis of antitubercular drugs in search of untapped potential. Using 211 clinical isolates of M. tuberculosis from South Africa, we performed phenotypic drug susceptibility testing (DST) to aminoglycosides by both critical concentration and MIC determination in parallel with whole-genome sequencing to identify known genotypic resistance elements. Isolates with low-level streptomycin resistance mediated by gidB were frequently misclassified with respect to streptomycin resistance when using the WHO-recommended critical concentration of 2 µg/ml. We identified 29 M. tuberculosis isolates from South Africa with low-level streptomycin resistance concomitant with high-level amikacin resistance, conferred by gidB and rrs 1400, respectively. Using a large global data set of M. tuberculosis genomes, we observed 95 examples of this corresponding resistance genotype (gidB-rrs 1400), including identification in 81/257 (31.5%) of extensively drug resistant (XDR) isolates. In a phylogenetic analysis, we observed repeated evolution of low-level streptomycin and high-level amikacin resistance in multiple countries. Our findings suggest that current critical concentration methods and the design of molecular diagnostics need to be revisited to provide more accurate assessments of streptomycin resistance for gidB-containing isolates. For patients harboring isolates of M. tuberculosis with high-level amikacin resistance conferred by rrs 1400, and for whom newer agents are not available, treatment with streptomycin may still prove useful, even in the face of low-level resistance conferred by gidB.

Multi-institute analysis of carbapenem resistance reveals remarkable diversity, unexplained mechanisms, and limited clonal outbreaks.

Carbapenem-resistant Enterobacteriaceae (CRE) are among the most severe threats to the antibiotic era. Multiple different species can exhibit resistance due to many different mechanisms, and many different mobile elements are capable of transferring resistance between lineages. We prospectively sampled CRE from hospitalized patients from three Boston-area hospitals, together with a collection of CRE from a single California hospital, to define the frequency and characteristics of outbreaks and determine whether there is evidence for transfer of strains within and between hospitals and the frequency with which resistance is transferred between lineages or species. We found eight species exhibiting resistance, with the majority of our sample being the sequence type 258 (ST258) lineage of Klebsiella pneumoniae There was very little evidence of extensive hospital outbreaks, but a great deal of variation in resistance mechanisms and the genomic backgrounds carrying these mechanisms. Local transmission was evident in clear phylogeographic structure between the samples from the two coasts. The most common resistance mechanisms were KPC (K. pneumoniae carbapenemases) beta-lactamases encoded by blaKPC2, blaKPC3, and blaKPC4, which were transferred between strains and species by seven distinct subgroups of the Tn4401 element. We also found evidence for previously unrecognized resistance mechanisms that produced resistance when transformed into a susceptible genomic background. The extensive variation, together with evidence of transmission beyond limited clonal outbreaks, points to multiple unsampled transmission chains throughout the continuum of care, including asymptomatic carriage and transmission of CRE. This finding suggests that to control this threat, we need an aggressive approach to surveillance and isolation.

Extensive global movement of multidrug-resistantM. tuberculosis strains revealed by whole-genome analysis.

BACKGROUND: While the international spread of multidrug-resistant (MDR) Mycobacterium tuberculosis strains is an acknowledged public health threat, a broad and more comprehensive examination of the global spread of MDR-tuberculosis (TB) using whole-genome sequencing has not yet been performed. METHODS: In a global dataset of 5310 M. tuberculosis whole-genome sequences isolated from five continents, we performed a phylogenetic analysis to identify and characterise clades of MDR-TB with respect to geographic dispersion. RESULTS: Extensive international dissemination of MDR-TB was observed, with identification of 32 migrant MDR-TB clades with descendants isolated in 17 unique countries. Relatively recent movement of strains from both Beijing and non-Beijing lineages indicated successful global spread of varied genetic backgrounds. Migrant MDR-TB clade members shared relatively recent common ancestry, with a median estimate of divergence of 13-27 years. Migrant extensively drug-resistant (XDR)-TB clades were not observed, although development of XDR-TB within migratory MDR-TB clades was common. CONCLUSIONS: Application of genomic techniques to investigate global MDR migration patterns revealed extensive global spread of MDR clades between countries of varying TB burden. Further expansion of genomic studies to incorporate isolates from diverse global settings into a single analysis, as well as data sharing platforms that facilitate genomic data sharing across country lines, may allow for future epidemiological analyses to monitor for international transmission of MDR-TB. In addition, efforts to perform routine whole-genome sequencing on all newly identified M. tuberculosis, like in England, will serve to better our understanding of the transmission dynamics of MDR-TB globally.

Chicken Meat-Associated Enterococci: Influence of Agricultural Antibiotic Use and Connection to the Clinic.

Industrial farms are unique, human-created ecosystems that provide the perfect setting for the development and dissemination of antibiotic resistance. Agricultural antibiotic use amplifies naturally occurring resistance mechanisms from soil ecologies, promoting their spread and sharing with other bacteria, including those poised to become endemic within hospital environments. To better understand the role of enterococci in the movement of antibiotic resistance from farm to table to clinic, we characterized over 300 isolates of Enterococcus cultured from raw chicken meat purchased at U.S. supermarkets by the Consumers Union in 2013. Enterococcus faecalis and Enterococcus faecium were the predominant species found, and antimicrobial susceptibility testing uncovered striking levels of resistance to medically important antibiotic classes, particularly from classes approved by the FDA for use in animal production. While nearly all isolates were resistant to at least one drug, bacteria from meat labeled as raised without antibiotics had fewer resistances, particularly for E. faecium Whole-genome sequencing of 92 isolates revealed that both commensal- and clinical-isolate-like enterococcal strains were associated with chicken meat, including isolates bearing important resistance-conferring elements and virulence factors. The ability of enterococci to persist in the food system positions them as vehicles to move resistance genes from the industrial farm ecosystem into more human-proximal ecologies.IMPORTANCE Bacteria that contaminate food can serve as a conduit for moving drug resistance genes from farm to table to clinic. Our results show that chicken meat-associated isolates of Enterococcus are often multidrug resistant, closely related to pathogenic lineages, and harbor worrisome virulence factors. These drug-resistant agricultural isolates could thus represent important stepping stones in the evolution of enterococci into drug-resistant human pathogens. Although significant efforts have been made over the past few years to reduce the agricultural use of antibiotics, continued assessment of agricultural practices, including the roles of processing plants, shared breeding flocks, and probiotics as sources for resistance spread, is needed in order to slow the evolution of antibiotic resistance. Because antibiotic resistance is a global problem, global policies are needed to address this threat. Additional measures must be taken to mitigate the development and spread of antibiotic resistance elements from farms to clinics throughout the world.

Transferable vancomycin resistance in clade B commensal-type Enterococcus faecium.

Objectives: Vancomycin-resistant Enterococcus faecium is a leading cause of MDR hospital infection. Two genetically definable populations of E. faecium have been identified: hospital-adapted MDR isolates (clade A) and vancomycin-susceptible commensal strains (clade B). VanN-type vancomycin resistance was identified in two isolates of E. faecium recovered from blood and faeces of an immunocompromised patient. To understand the genomic context in which VanN occurred in the hospitalized patient, the risk it posed for transmission in the hospital and its origins, it was of interest to determine where these strains placed within the E. faecium population structure. Methods: We obtained the genome sequence of the VanN isolates and performed comparative and functional genomics of the chromosome and plasmid content. Results: We show that, in these strains, VanN occurs in a genetic background that clusters with clade B E. faecium, which is highly unusual. We characterized the chromosome and the conjugative plasmid that carries VanN resistance in these strains, pUV24. This plasmid exhibits signatures of in-host selection on the vanN operon regulatory system, which are associated with a constitutive expression of vancomycin resistance. VanN resistance in clade B strains may go undetected by current methods. Conclusions: We report a case of vancomycin resistance in a commensal lineage of E. faecium responsible for an atypical bacteraemia in an immunocompromised patient. A reservoir of transferable glycopeptide resistance in the community could pose a concern for public health.