Exploring the mobilome and resistome of Enterococcus faecium in a One Health context across two continents

Plaseval: a framework for comparing and evaluating plasmid detection tools

BACKGROUND

Plasmids play a major role in the transfer of antimicrobial resistance (AMR) genes among bacteria via horizontal gene transfer. The identification of plasmids in short-read assemblies is a challenging problem and a very active research area. Plasmid binning aims at detecting, in a draft genome assembly, groups (bins) of contigs likely to originate from the same plasmid. Several methods for plasmid binning have been developed recently, such as PlasBin-flow, HyAsP, gplas, MOB-suite, and plasmidSPAdes. This motivates the problem of evaluating the performances of plasmid binning methods, either against a given ground truth or between them.

RESULTS

We describe PlasEval, a novel method aimed at comparing the results of plasmid binning tools. PlasEval computes a dissimilarity measure between two sets of plasmid bins, that can originate either from two plasmid binning tools, or from a plasmid binning tool and a ground truth set of plasmid bins. The PlasEval dissimilarity accounts for the contig content of plasmid bins, the length of contigs and is repeat-aware. Moreover, the dissimilarity score computed by PlasEval is broken down into several parts, that allows to understand qualitative differences between the compared sets of plasmid bins. We illustrate the use of PlasEval by benchmarking four recently developed plasmid binning tools-PlasBin-flow, HyAsP, gplas, and MOB-recon-on a data set of 53 E. coli bacterial genomes.

CONCLUSION

Analysis of the results of plasmid binning methods using PlasEval shows that their behaviour varies significantly. PlasEval can be used to decide which specific plasmid binning method should be used for a specific dataset. The disagreement between different methods also suggests that the problem of plasmid binning on short-read contigs requires further research. We believe that PlasEval can prove to be an effective tool in this regard. PlasEval is publicly available at https://github.com/acme92/PlasEval.

Bacteriophage Therapy as a Promising Alternative for Antibiotic-Resistant Enterococcus faecium: Advances and Challenges

Enterococcus faecium is a Gram-positive bacterium increasingly identified as a critical nosocomial pathogen that poses significant treatment challenges due to its resistance to multiple antibiotics, particularly vancomycin-resistant E. faecium (VRE) strains. The urgent need for alternative therapeutic strategies has renewed interest in bacteriophage (phage) therapy, given phages specificity and bactericidal potential. This review explores the advancements in phage therapy against antibiotic-resistant E. faecium, including phage morphological diversity, genomic characteristics, and infection mechanisms. The efficacy of phage therapy in in vitro, ex vivo, and in vivo models and the compassionate use in clinical settings are evaluated, highlighting the promising outcomes of phage-antibiotic synergies and biofilm disruption. Key challenges and future research directions are discussed, with a focus on improving therapeutic efficacy and overcoming bacterial resistance. This review emphasizes the potential of phage therapy as a viable solution for managing multidrug-resistant E. faecium infections and underscores the importance of future investigations to enhance clinical applications.

Enterococcus faecium: evolution, adaptation, pathogenesis and emerging therapeutics

The opportunistic pathogen Enterococcus faecium colonizes humans and a wide range of animals, endures numerous stresses, resists antibiotic treatment and stubbornly persists in clinical environments. The widespread application of antibiotics in hospitals and agriculture has contributed to the emergence of vancomycin-resistant E. faecium, which causes many hospital-acquired infections. In this Review, we explore recent discoveries about the evolutionary history, the environmental adaptation and the colonization and dissemination mechanisms of E. faecium and vancomycin-resistant E. faecium. These studies provide critical insights necessary for developing novel preventive and therapeutic approaches against vancomycin-resistant E. faecium and also reveal the intricate interrelationships between the environment, the microorganism and the host, providing knowledge that is broadly relevant to how antibiotic-resistant pathogens emerge and endure.

Identification of key drivers of antimicrobial resistance in Enterococcus using machine learning

With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML) models show promise for AMR prediction in diagnostics but require a deep understanding of internal processes to use effectively. Our study utilised AMR gene, pangenomic, and predicted plasmid features from 647 Enterococcus faecium and Enterococcus faecalis genomes across the One Health continuum, along with corresponding resistance phenotypes, to develop interpretive ML classifiers. Vancomycin resistance could be predicted with 99% accuracy with AMR gene features, 98% with pangenome features, and 96% with plasmid clusters. Top pangenome features overlapped with the resistance genes of the vanA operon, which are often laterally transmitted via plasmids. Doxycycline resistance prediction achieved approximately 92% accuracy with pangenome features, with the top feature being elements of Tn916 conjugative transposon, a tet(M) carrier. Erythromycin resistance prediction models achieved about 90% accuracy, but top features were negatively correlated with resistance due to the confounding effect of population structure. This work demonstrates the importance of reviewing ML models' features to discern biological relevance even when achieving high-performance metrics. Our workflow offers the potential to propose hypotheses for experimental testing, enhancing the understanding of AMR mechanisms, which are crucial for combating the AMR crisis.

Methods for Genomic Epidemiology of Bacterial Pathogens: Example Salmonella

Genomics has revolutionized how we characterize and monitor infectious diseases for public health. The surveillance and characterization of Salmonella has improved drastically within the past decade. In this chapter, we discuss the prerequisites for good bacterial genomics studies and make note of advantages and disadvantages of this research approach. We discuss methods for outbreak detection and the evolutionary and epidemiological characterization of Salmonella spp. We provide an outline for determining the sequence type and serotype of isolates, building a core genome phylogenetic tree, and detecting antimicrobial resistance genes, virulence factors, and mobile genetic elements. These methods can be used to study other pathogenic bacterial species.

A standardized nomenclature for resistance-modifying agents in the Comprehensive Antibiotic Resistance Database

IMPORTANCE

While increasing rates of antimicrobial resistance undermine our current arsenal of antibiotics, resistance-modifying agents (RMAs) hold promise to extend the lifetime of these important molecules. We here provide a standardized nomenclature for RMAs within the Comprehensive Antibiotic Resistance Database in aid of RMA discovery, data curation, and genome mining.

Comparative genomic analysis of clinical Enterococcus faecalis distinguishes strains isolated from the bladder

BACKGROUND

Enterococcus faecalis is the most commonly isolated enterococcal species in clinical infection. This bacterium is notorious for its ability to share genetic content within and outside of its species. With this increased proficiency for horizontal gene transfer, tremendous genomic diversity within this species has been identified. Many researchers have hypothesized E. faecalis exhibits niche adaptation to establish infections or colonize various parts of the human body. Here, we hypothesize that E. faecalis strains isolated from the human bladder will carry unique genomic content compared to clinical strains isolated from other sources.

RESULTS

This analysis includes comparison of 111 E. faecalis genomes isolated from bladder, urogenital, blood, and fecal samples. Phylogenomic comparison shows no association between isolation source and lineage; however, accessory genome comparison differentiates blood and bladder genomes. Further gene enrichment analysis identifies gene functions, virulence factors, antibiotic resistance genes, and plasmid-associated genes that are enriched or rare in bladder genomes compared to urogenital, blood, and fecal genomes. Using these findings as training data and 682 publicly available genomes as test data, machine learning classifiers successfully distinguished between bladder and non-bladder strains with high accuracy. Genes identified as important for this differentiation were often related to transposable elements and phage, including 3 prophage species found almost exclusively in bladder and urogenital genomes.

CONCLUSIONS

E. faecalis strains isolated from the bladder contain unique genomic content when compared to strains isolated from other body sites. This genomic diversity is most likely due to horizontal gene transfer, as evidenced by lack of phylogenomic clustering and enrichment of transposable elements and prophages. Investigation into how these enriched genes influence host-microbe interactions may elucidate gene functions required for successful bladder colonization and disease establishment.

Identification of plasmids in avian-associated Escherichia coli using nanopore and illumina sequencing

BACKGROUND

Avian pathogenic Escherichia coli (APEC) are the causative agents of colibacillosis in chickens, a disease which has significant economic impact on the poultry industry. Large plasmids detected in APEC are known to contribute to strain diversity for pathogenicity and antimicrobial resistance, but there could be other plasmids that are missed in standard analysis. In this study, we determined the impact of sequencing and assembly factors for the detection of plasmids in an E. coli whole genome sequencing project.

RESULTS

Hybrid assembly (Illumina and Nanopore) combined with plasmid DNA extractions allowed for detection of the greatest number of plasmids in E. coli, as detected by MOB-suite software. In total, 79 plasmids were identified in 19 E. coli isolates. Hybrid assemblies were robust and consistent in quality regardless of sequencing kit used or if long reads were filtered or not. In contrast, long read only assemblies were more variable and influenced by sequencing and assembly parameters. Plasmid DNA extractions allowed for the detection of physically smaller plasmids, but when averaged over 19 isolates did not significantly change the overall number of plasmids detected.

CONCLUSIONS

Hybrid assembly can be reliably used to detect plasmids in E. coli, especially if researchers are focused on large plasmids containing antimicrobial resistance genes and virulence factors. If the goal is comprehensive detection of all plasmids, particularly if smaller sized vectors are desired for biotechnology applications, the addition of plasmid DNA extractions to hybrid assemblies is prudent. Long read sequencing is sufficient to detect many plasmids in E. coli, however, it is more prone to errors when expanded to analyze a large number of isolates.