Three Distinct Annotation Platforms Differ in Detection of Antimicrobial Resistance Genes in Long-Read, Short-Read, and Hybrid Sequences Derived from Total Genomic DNA or from Purified Plasmid DNA. - Related Documents




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493501.0000Three Distinct Annotation Platforms Differ in Detection of Antimicrobial Resistance Genes in Long-Read, Short-Read, and Hybrid Sequences Derived from Total Genomic DNA or from Purified Plasmid DNA. Recent advances and lower costs in rapid high-throughput sequencing have engendered hope that whole genome sequencing (WGS) might afford complete resistome characterization in bacterial isolates. WGS is particularly useful for the clinical characterization of fastidious and slow-growing bacteria. Despite its potential, several challenges should be addressed before adopting WGS to detect antimicrobial resistance (AMR) genes in the clinical laboratory. Here, with three distinct ESKAPE bacteria (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.), different approaches were compared to identify best practices for detecting AMR genes, including: total genomic DNA and plasmid DNA extractions, the solo assembly of Illumina short-reads and of Oxford Nanopore Technologies (ONT) long-reads, two hybrid assembly pipelines, and three in silico AMR databases. We also determined the susceptibility of each strain to 21 antimicrobials. We found that all AMR genes detected in pure plasmid DNA were also detectable in total genomic DNA, indicating that, at least in these three enterobacterial genera, the purification of plasmid DNA was not necessary to detect plasmid-borne AMR genes. Illumina short-reads used with ONT long-reads in either hybrid or polished assemblies of total genomic DNA enhanced the sensitivity and accuracy of AMR gene detection. Phenotypic susceptibility closely corresponded with genotypes identified by sequencing; however, the three AMR databases differed significantly in distinguishing mobile dedicated AMR genes from non-mobile chromosomal housekeeping genes in which rare spontaneous resistance mutations might occur. This study indicates that each method employed in a WGS workflow has an impact on the detection of AMR genes. A combination of short- and long-reads, followed by at least three different AMR databases, should be used for the consistent detection of such genes. Further, an additional step for plasmid DNA purification and sequencing may not be necessary. This study reveals the need for standardized biochemical and informatic procedures and database resources for consistent, reliable AMR genotyping to take full advantage of WGS in order to expedite patient treatment and track AMR genes within the hospital and community.202236290058
493610.9999A New Tool for Analyses of Whole Genome Sequences Reveals Dissemination of Specific Strains of Vancomycin-Resistant Enterococcus faecium in a Hospital. A new easy-to-use online bioinformatic tool analyzing whole genome sequences of healthcare associated bacteria was used by a local infection control unit to retrospectively map genetic relationship of isolates of E. faecium carrying resistance genes to vancomycin in a hospital. Three clusters of isolates were detected over a period of 5 years, suggesting transmission between patients. Individual relatedness between isolates within each cluster was established by SNP analyses provided by the system. Genetic antimicrobial resistance mechanisms to antibiotics other than vancomycin were identified. The results suggest that the system is suited for hospital surveillance of E. faecium carrying resistance genes to vancomycin in settings with access to next Generation Sequencing without bioinformatic expertise for interpretation of the genome sequences.202134778297
500220.9998Genomic Diversity of Hospital-Acquired Infections Revealed through Prospective Whole-Genome Sequencing-Based Surveillance. Healthcare-associated infections (HAIs) cause mortality, morbidity, and waste of health care resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAIs using prospective whole-genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here, we describe the diversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of bacterial isolate genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 groups of related species. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal-component analysis of accessory genes (PCA-A). Core genome genetic distances and rates of evolution varied among species, which has practical implications for defining shared ancestry during outbreaks and for our broader understanding of the origins of bacterial strains and species. Finally, antimicrobial resistance genes and putative mobile genetic elements were frequently observed, and our systematic analysis revealed patterns of occurrence across the different species sampled from our hospital. Overall, this study shows how understanding the population structure of diverse pathogens circulating in a single health care setting can improve the discriminatory power of genomic epidemiology studies and can help define the processes leading to strain and species differentiation. IMPORTANCE Hospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 clinical bacterial isolates collected from hospitalized patients at a large medical center over a 2-year period. We identified nearly 100 different bacterial species, which we divided into 14 different groups of related species. When we examined how genetic relatedness differed between species, we found that different species were likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cutoffs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant and were shared among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolutionary processes of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts.202235695507
494330.9998Targeted sequencing of Enterobacterales bacteria using CRISPR-Cas9 enrichment and Oxford Nanopore Technologies. Sequencing DNA directly from patient samples enables faster pathogen characterization compared to traditional culture-based approaches, but often yields insufficient sequence data for effective downstream analysis. CRISPR-Cas9 enrichment is designed to improve the yield of low abundance sequences but has not been thoroughly explored with Oxford Nanopore Technologies (ONT) for use in clinical bacterial epidemiology. We designed CRISPR-Cas9 guide RNAs to enrich the human pathogen Klebsiella pneumoniae, by targeting multi-locus sequence type (MLST) and transfer RNA (tRNA) genes, as well as common antimicrobial resistance (AMR) genes and the resistance-associated integron gene intI1. We validated enrichment performance in 20 K. pneumoniae isolates, finding that guides generated successful enrichment across all conserved sites except for one AMR gene in two isolates. Enrichment of MLST genes led to a correct allele call in all seven loci for 8 out of 10 isolates that had depth of 30× or more in these regions. We then compared enriched and unenriched sequencing of three human fecal samples spiked with K. pneumoniae at varying abundance. Enriched sequencing generated 56× and 11.3× the number of AMR and MLST reads, respectively, compared to unenriched sequencing, and required approximately one-third of the computational storage space. Targeting the intI1 gene often led to detection of 10-20 proximal resistance genes due to the long reads produced by ONT sequencing. We demonstrated that CRISPR-Cas9 enrichment combined with ONT sequencing enabled improved genomic characterization outcomes over unenriched sequencing of patient samples. This method could be used to inform infection control strategies by identifying patients colonized with high-risk strains. IMPORTANCE: Understanding bacteria in complex samples can be challenging due to their low abundance, which often results in insufficient data for analysis. To improve the detection of harmful bacteria, we implemented a technique aimed at increasing the amount of data from target pathogens when combined with modern DNA sequencing technologies. Our technique uses CRISPR-Cas9 to target specific gene sequences in the bacterial pathogen Klebsiella pneumoniae and improve recovery from human stool samples. We found our enrichment method to significantly outperform traditional methods, generating far more data originating from our target genes. Additionally, we developed new computational techniques to further enhance the analysis, providing a thorough method for characterizing pathogens from complex biological samples.202539772804
497540.9998Comprehensive genomic and plasmid characterization of multidrug-resistant bacterial strains by R10.4.1 nanopore sequencing. The escalating prevalence of multidrug-resistant (MDR) bacteria pose a significant public health threat. Understanding the genomic features and deciphering the antibiotic resistance profiles of these pathogens is crucial for development of effective surveillance and treatment strategies. In this study, we employed the R10.4.1 nanopore sequencing technology, specifically through the use of the MinION platform, to analyze eight MDR bacterial strains originating from clinical, ecological and food sources. A single 72-hour sequencing run could yield approximately 12 million reads which covered a total of 34 gigabases (Gbp). The nanopore R10.4.1 data was processed using the Flye assembler, successfully assembling the genomes of eight bacterial strains and their 18 plasmids. Notably, the assemblies generated solely from R10.4.1 nanopore data closely matched those from next-generation sequencing data. Diverse antibiotic resistance patterns and specific resistance genes in the test strains were identified. Hospital strains that exhibited multidrug resistance were found to harbor various resistance genes that encode efflux pumps and extended-spectrum β-lactamases. Environmental and food sources were found to display resistance profiles in a species-specific manner. The composition of structurally complex plasmids in the test strains could also be revealed by analysis of nanopore long reads, which also suggested evidence of horizontal transfer of plasmids between different bacterial species. These findings provide valuable insights into the genetic characteristics of MDR bacteria and demonstrating the practicality of nanopore sequencing technology for detecting of resistance elements in bacterial pathogens.202438460283
512450.9998Oxford nanopore long-read sequencing enables the generation of complete bacterial and plasmid genomes without short-read sequencing. INTRODUCTION: Genome-based analysis is crucial in monitoring antibiotic-resistant bacteria (ARB)and antibiotic-resistance genes (ARGs). Short-read sequencing is typically used to obtain incomplete draft genomes, while long-read sequencing can obtain genomes of multidrug resistance (MDR) plasmids and track the transmission of plasmid-borne antimicrobial resistance genes in bacteria. However, long-read sequencing suffers from low-accuracy base calling, and short-read sequencing is often required to improve genome accuracy. This increases costs and turnaround time. METHODS: In this study, a novel ONT sequencing method is described, which uses the latest ONT chemistry with improved accuracy to assemble genomes of MDR strains and plasmids from long-read sequencing data only. Three strains of Salmonella carrying MDR plasmids were sequenced using the ONT SQK-LSK114 kit with flow cell R10.4.1, and de novo genome assembly was performed with average read accuracy (Q > 10) of 98.9%. RESULTS AND DISCUSSION: For a 5-Mb-long bacterial genome, finished genome sequences with accuracy of >99.99% could be obtained at 75× sequencing coverage depth using Flye and Medaka software. Thus, this new ONT method greatly improves base-calling accuracy, allowing for the de novo assembly of high-quality finished bacterial or plasmid genomes without the need for short-read sequencing. This saves both money and time and supports the application of ONT data in critical genome-based epidemiological analyses. The novel ONT approach described in this study can take the place of traditional combination genome assembly based on short- and long-read sequencing, enabling pangenomic analyses based on high-quality complete bacterial and plasmid genomes to monitor the spread of antibiotic-resistant bacteria and antibiotic resistance genes.202337256057
497760.9998In silico analyses of diversity and dissemination of antimicrobial resistance genes and mobile genetics elements, for plasmids of enteric pathogens. INTRODUCTION: The antimicrobial resistance (AMR) mobilome plays a key role in the dissemination of resistance genes encoded by mobile genetics elements (MGEs) including plasmids, transposons (Tns), and insertion sequences (ISs). These MGEs contribute to the dissemination of multidrug resistance (MDR) in enteric bacterial pathogens which have been considered as a global public health risk. METHODS: To further understand the diversity and distribution of AMR genes and MGEs across different plasmid types, we utilized multiple sequence-based computational approaches to evaluate AMR-associated plasmid genetics. A collection of 1,309 complete plasmid sequences from Gammaproteobacterial species, including 100 plasmids from each of the following 14 incompatibility (Inc) types: A/C, BO, FIA, FIB, FIC, FIIA, HI1, HI2, I1, K, M, N, P except W, where only 9 sequences were available, was extracted from the National Center for Biotechnology Information (NCBI) GenBank database using BLAST tools. The extracted FASTA files were analyzed using the AMRFinderPlus web-based tools to detect antimicrobial, disinfectant, biocide, and heavy metal resistance genes and ISFinder to identify IS/Tn MGEs within the plasmid sequences. RESULTS AND DISCUSSION: In silico prediction based on plasmid replicon types showed that the resistance genes were diverse among plasmids, yet multiple genes were widely distributed across the plasmids from enteric bacterial species. These findings provide insights into the diversity of resistance genes and that MGEs mediate potential transmission of these genes across multiple plasmid replicon types. This notion was supported by the observation that many IS/Tn MGEs and resistance genes known to be associated with them were common across multiple different plasmid types. Our results provide critical insights about how the diverse population of resistance genes that are carried by the different plasmid types can allow for the dissemination of AMR across enteric bacteria. The results also highlight the value of computational-based approaches and in silico analyses for the assessment of AMR and MGEs, which are important elements of molecular epidemiology and public health outcomes.202236777021
493970.9998Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. OBJECTIVES: The introduction of metagenomic sequencing to diagnostic microbiology has been hampered by slowness, cost and complexity. We explored whether MinION nanopore sequencing could accelerate diagnosis and resistance profiling, using complicated urinary tract infections as an exemplar. METHODS: Bacterial DNA was enriched from clinical urines (n = 10) and from healthy urines 'spiked' with multiresistant Escherichia coli (n = 5), then sequenced by MinION. Sequences were analysed using external databases and bioinformatic pipelines or, ultimately, using integrated real-time analysis applications. Results were compared with Illumina data and resistance phenotypes. RESULTS: MinION correctly identified pathogens without culture and, among 55 acquired resistance genes detected in the cultivated bacteria by Illumina sequencing, 51 were found by MinION sequencing directly from the urines; with three of the four failures in an early run with low genome coverage. Resistance-conferring mutations and allelic variants were not reliably identified. CONCLUSIONS: MinION sequencing comprehensively identified pathogens and acquired resistance genes from urine in a timeframe similar to PCR (4 h from sample to result). Bioinformatic pipeline optimization is needed to better detect resistances conferred by point mutations. Metagenomic-sequencing-based diagnosis will enable clinicians to adjust antimicrobial therapy before the second dose of a typical (i.e. every 8 h) antibiotic.201727667325
497680.9998Trans-Regional and Cross-Host Spread of mcr-Carrying Plasmids Revealed by Complete Plasmid Sequences - 44 Countries, 1998-2020. BACKGROUND: The surveillance of antimicrobial resistance genes (ARGs) and bacteria is one critical approach to prevent and control antimicrobial resistance (AMR). Next-generation sequencing (NGS) is a powerful tool in monitoring the emergence and spread of ARGs and resistant bacteria. The horizontal transfer of ARGs across host bacteria mediated by plasmids is a challenge in NGS surveillance for resistance because short-read sequencing can hardly generate the complete plasmid genome sequence, and the correlation between ARGs and plasmids are difficult to determine. METHODS: The complete genome sequences of 455 mcr-carrying plasmids (pMCRs), and the data of their host bacteria and isolation regions were collected from the NCBI database. Genes of Inc types and ARGs were searched for each plasmid. The genome similarity of these plasmids was analyzed by pangenome clustering and genome alignment. RESULTS: A total of 52 Inc types, including a variety of fusion plasmids containing 2 or more Inc types were identified in these pMCRs and carried by complex host bacteria. The cooccurrence of ARGs in pMCRs was generally observed, with an average of 3.9 ARGs per plasmid. Twenty-two clusters with consistent or highly similar sequences and gene compositions were identified by the pangenome clustering, which were characterized with distributions in different countries/regions, years or host bacteria in each cluster. DISCUSSION: Based on the complete plasmid sequences, distribution of mcr genes in different Inc type plasmids, their co-existence with other AMRs, and transmission of one pMCR across regions and host bacteria can be revealed definitively. Complete plasmid genomes and comparisons in the laboratory network are necessary for spread tracing of ARG-carrying plasmids and risk assessment in AMR surveillance.202235433080
493490.9998Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates. Emerging antibiotic resistance is a major global health threat. The analysis of nucleic acid sequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistance determinants to inform molecular diagnostics and drug development. We collected genetic data (11,087 newly-sequenced whole genomes) and culture-based resistance profiles (10,991 out of the 11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including 18 main species spanning a time period of 30 years. Species and drug specific resistance patterns were observed including increased resistance rates for Acinetobacter baumannii to carbapenems and for Escherichia coli to fluoroquinolones. Species-level pan-genomes were constructed to reflect the genetic repertoire of the respective species, including conserved essential genes and known resistance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed to infer gene-drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into GEAR-base, a resource available for academic research use free of charge at https://gear-base.com.201931100356
4924100.9998PlaScope: a targeted approach to assess the plasmidome from genome assemblies at the species level. Plasmid prediction may be of great interest when studying bacteria of medical importance such as Enterobacteriaceae as well as Staphylococcus aureus or Enterococcus. Indeed, many resistance and virulence genes are located on such replicons with major impact in terms of pathogenicity and spreading capacities. Beyond strain outbreak, plasmid outbreaks have been reported in particular for some extended-spectrum beta-lactamase- or carbapenemase-producing Enterobacteriaceae. Several tools are now available to explore the 'plasmidome' from whole-genome sequences with various approaches, but none of them are able to combine high sensitivity and specificity. With this in mind, we developed PlaScope, a targeted approach to recover plasmidic sequences in genome assemblies at the species or genus level. Based on Centrifuge, a metagenomic classifier, and a custom database containing complete sequences of chromosomes and plasmids from various curated databases, PlaScope classifies contigs from an assembly according to their predicted location. Compared to other plasmid classifiers, PlasFlow and cBar, it achieves better recall (0.87), specificity (0.99), precision (0.96) and accuracy (0.98) on a dataset of 70 genomes of Escherichia coli containing plasmids. In a second part, we identified 20 of the 21 chromosomal integrations of the extended-spectrum beta-lactamase coding gene in a clinical dataset of E. coli strains. In addition, we predicted virulence gene and operon locations in agreement with the literature. We also built a database for Klebsiella and correctly assigned the location for the majority of resistance genes from a collection of 12 Klebsiella pneumoniae strains. Similar approaches could also be developed for other well-characterized bacteria.201830265232
4964110.9998Distribution of Antimicrobial Resistance and Virulence Genes within the Prophage-Associated Regions in Nosocomial Pathogens. Prophages are often involved in host survival strategies and contribute toward increasing the genetic diversity of the host genome. Prophages also drive horizontal propagation of various genes as vehicles. However, there are few retrospective studies contributing to the propagation of antimicrobial resistance (AMR) and virulence factor (VF) genes by prophage. We extracted the complete genome sequences of seven pathogens, including ESKAPE bacteria and Escherichia coli from a public database, and examined the distribution of both the AMR and VF genes in prophage-like regions. We found that the ratios of AMR and VF genes greatly varied among the seven species. More than 70% of Enterobacter cloacae strains had VF genes, but only 1.2% of Klebsiella pneumoniae strains had VF genes from prophages. AMR and VF genes are unlikely to exist together in the same prophage region except in E. coli and Staphylococcus aureus, and the distribution patterns of prophage types containing AMR genes are distinct from those of VF gene-carrying prophage types. AMR genes in the prophage were located near transposase and/or integrase. The prophage containing class 1 integrase possessed a significantly greater number of AMR genes than did prophages with no class 1 integrase. The results of this study present a comprehensive picture of AMR and VF genes present within, or close to, prophage-like elements and different prophage patterns between AMR- or VF-encoding prophage-like elements. IMPORTANCE Although we believe phages play an important role in horizontal gene transfer in exchanging genetic material, we do not know the distribution of the antimicrobial resistance (AMR) and/or virulence factor (VF) genes in prophages. We collected different prophage elements from the complete genome sequences of seven species-Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter cloacae, and Escherichia coli-and characterized the distribution of antimicrobial resistance and virulence genes located in the prophage region. While virulence genes in prophage were species specific, antimicrobial resistance genes in prophages were highly conserved in various species. An integron structure was detected within specific prophage regions such as P1-like prophage element. Maximum of 10 antimicrobial resistance genes were found in a single prophage region, suggesting that prophages act as a reservoir for antimicrobial resistance genes. The results of this study show the different characteristic structures between AMR- or VF-encoding prophages.202134232073
5111120.9998Antimicrobial Resistance Prediction for Gram-Negative Bacteria via Game Theory-Based Feature Evaluation. The increasing prevalence of antimicrobial-resistant bacteria drives the need for advanced methods to identify antimicrobial-resistance (AMR) genes in bacterial pathogens. With the availability of whole genome sequences, best-hit methods can be used to identify AMR genes by differentiating unknown sequences with known AMR sequences in existing online repositories. Nevertheless, these methods may not perform well when identifying resistance genes with sequences having low sequence identity with known sequences. We present a machine learning approach that uses protein sequences, with sequence identity ranging between 10% and 90%, as an alternative to conventional DNA sequence alignment-based approaches to identify putative AMR genes in Gram-negative bacteria. By using game theory to choose which protein characteristics to use in our machine learning model, we can predict AMR protein sequences for Gram-negative bacteria with an accuracy ranging from 93% to 99%. In order to obtain similar classification results, identity thresholds as low as 53% were required when using BLASTp.201931597945
5715130.9998Genomic Characterization of Mobile Genetic Elements Associated with Multidrug-Resistant Acinetobacter Non-baumannii Species from Southern Thailand. This study investigated the genetic diversity, antimicrobial resistance profiles, and virulence characteristics of Acinetobacter non-baumannii isolates obtained from four hospitals in southern Thailand. Clinical data, genome information, and average nucleotide identity (ANI) were analyzed for eight isolates, revealing diverse genetic profiles and novel sequence types (STs). Minimum spanning tree analysis indicated potential clonal spread of certain STs across different geographic regions. Antimicrobial resistance genes (ARGs) were detected in all isolates, with a high prevalence of genes conferring resistance to carbapenems, highlighting the challenge of antimicrobial resistance in Acinetobacter spp. infections. Mobile genetic elements (MGEs) carrying ARGs were also identified, emphasizing the role of horizontal gene transfer in spreading resistance. Evaluation of virulence-associated genes revealed a diverse range of virulence factors, including those related to biofilm formation and antibiotic resistance. However, no direct correlation was found between virulence-associated genes in Acinetobacter spp. and specific clinical outcomes, such as infection severity or patient mortality. This complexity suggests that factors beyond gene presence may influence disease progression and outcomes. This study emphasizes the importance of continued surveillance and molecular epidemiological studies to combat the spread of multidrug-resistant (MDR) Acinetobacter non-baumannii strains. The findings provide valuable insights into the epidemiology and genetic characteristics of this bacteria in southern Thailand, with implications for infection control and antimicrobial management efforts.202438391535
4942140.9998Nanopore-based enrichment of antimicrobial resistance genes - a case-based study. Rapid screening of hospital admissions to detect asymptomatic carriers of resistant bacteria can prevent pathogen outbreaks. However, the resulting isolates rarely have their genome sequenced due to cost constraints and long turn-around times to get and process the data, limiting their usefulness to the practitioner. Here we used real-time, on-device target enrichment ("adaptive") sequencing as a highly multiplexed assay covering 1,147 antimicrobial resistance genes. We compared its utility against standard and metagenomic sequencing, focusing on an isolate of Raoultella ornithinolytica harbouring three carbapenemases (NDM, KPC, VIM). Based on this experimental data, we then modelled the influence of several variables on the enrichment results and predicted the large effect of nucleotide identity (higher is better) and read length (shorter is better). Lastly, we showed how all relevant resistance genes are detected using adaptive sequencing on a miniature ("Flongle") flow cell, motivating its use in a clinical setting to monitor similar cases and their surroundings.202336949817
4558150.9997Connectiveness of Antimicrobial Resistance Genotype-Genotype and Genotype-Phenotype in the "Intersection" of Skin and Gut Microbes. The perianal skin is a unique "skin-gut" boundary that serves as a critical hotspot for the exchange and evolution of antibiotic resistance genes (ARGs). However, its role in the dissemination of antimicrobial resistance (AMR) has often been underestimated. To characterize the resistance patterns in the perianal skin environment of patients with perianal diseases and to investigate the drivers of AMR in this niche, a total of 51 bacterial isolates were selected from a historical strain bank containing isolates originally collected from patients with perianal diseases. All the isolates originated from the skin site and were subjected to antimicrobial susceptibility testing, whole-genome sequencing, and co-occurrence network analysis. The analysis revealed a highly structured resistance pattern, dominated by two distinct modules: one representing a classic Staphylococcal resistance platform centered around mecA and the bla operon, and a broad-spectrum multidrug resistance module in Gram-negative bacteria centered around tet(A) and predominantly carried by IncFIB and other IncF family plasmids. Further analysis pinpointed IncFIB-type plasmids as potent vehicles driving the efficient dissemination of the latter resistance module. Moreover, numerous unexplained resistance phenotypes were observed in a subset of isolates, indicating the potential presence of emerging and uncharacterized AMR threats. These findings establish the perianal skin as a complex reservoir of multidrug resistance genes and a hub for mobile genetic element exchange, highlighting the necessity of enhanced surveillance and targeted interventions in this clinically important ecological niche.202540906148
5106160.9997Metagenomic diagnostics for the simultaneous detection of multiple pathogens in human stool specimens from Côte d'Ivoire: a proof-of-concept study. BACKGROUND: The intestinal microbiome is a complex community and its role in influencing human health is poorly understood. While conventional microbiology commonly attributes digestive disorders to a single microorganism, a metagenomic approach can detect multiple pathogens simultaneously and might elucidate the role of microbial communities in the pathogenesis of intestinal diseases. We present a proof-of-concept that a shotgun metagenomic approach provides useful information on the diverse composition of intestinal pathogens and antimicrobial resistance profiles in human stool samples. METHODS: In October 2012, we obtained stool specimens from patients with persistent diarrhea in south Côte d'Ivoire. Four stool samples were purposefully selected and subjected to microscopy, multiplex polymerase chain reaction (PCR), and a metagenomic approach. For the latter, we employed the National Center for Biotechnology Information nucleotide database and screened for 36 pathogenic organisms (bacteria, helminths, intestinal protozoa, and viruses) that may cause digestive disorders. We further characterized the bacterial population and the prevailing resistance patterns by comparing our metagenomic datasets with a genome-specific marker database and with a comprehensive antibiotic resistance database. RESULTS: In the four patients, the metagenomic approach identified between eight and 11 pathogen classes that potentially cause digestive disorders. For bacterial pathogens, the diagnostic agreement between multiplex PCR and metagenomics was high; yet, metagenomics diagnosed several bacteria not detected by multiplex PCR. In contrast, some of the helminth and intestinal protozoa infections detected by microscopy were missed by metagenomics. The antimicrobial resistance analysis revealed the presence of genes conferring resistance to several commonly used antibiotics. CONCLUSIONS: A metagenomic approach provides detailed information on the presence and diversity of pathogenic organisms in human stool samples. Metagenomic studies allow for in-depth molecular characterization such as the antimicrobial resistance status, which may be useful to develop setting-specific treatment algorithms. While metagenomic approaches remain challenging, the benefits of gaining new insights into intestinal microbial communities call for a broader application in epidemiologic studies. TRIAL REGISTRATION: ISRCTN86951400.201626391184
5001170.9997Intensive care unit sinks are persistently colonized with multidrug resistant bacteria and mobilizable, resistance-conferring plasmids. Contamination of hospital sinks with microbial pathogens presents a serious potential threat to patients, but our understanding of sink colonization dynamics is largely based on infection outbreaks. Here, we investigate the colonization patterns of multidrug-resistant organisms (MDROs) in intensive care unit sinks and water from two hospitals in the USA and Pakistan collected over 27 months of prospective sampling. Using culture-based methods, we recovered 822 bacterial isolates representing 104 unique species and genomospecies. Genomic analyses revealed long-term colonization by Pseudomonas spp. and Serratia marcescens strains across multiple rooms. Nanopore sequencing uncovered examples of long-term persistence of resistance-conferring plasmids in unrelated hosts. These data indicate that antibiotic resistance (AR) in Pseudomonas spp. is maintained both by strain colonization and horizontal gene transfer (HGT), while HGT maintains AR within Acinetobacter spp. and Enterobacterales, independent of colonization. These results emphasize the importance of proactive, genomic-focused surveillance of built environments to mitigate MDRO spread. IMPORTANCE Hospital sinks are frequently linked to outbreaks of antibiotic-resistant bacteria. Here, we used whole-genome sequencing to track the long-term colonization patterns in intensive care unit (ICU) sinks and water from two hospitals in the USA and Pakistan collected over 27 months of prospective sampling. We analyzed 822 bacterial genomes, representing over 100 different species. We identified long-term contamination by opportunistic pathogens, as well as transient appearance of other common pathogens. We found that bacteria recovered from the ICU had more antibiotic resistance genes (ARGs) in their genomes compared to matched community spaces. We also found that many of these ARGs are harbored on mobilizable plasmids, which were found shared in the genomes of unrelated bacteria. Overall, this study provides an in-depth view of contamination patterns for common nosocomial pathogens and identifies specific targets for surveillance.202337439570
4930180.9997Whole-genome sequencing based characterization of antimicrobial resistance in Enterococcus. Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, yielding new insights into the genetics underlying resistance. To date, most studies using WGS to study antimicrobial resistance have focused on gram-negative bacteria in the family Enterobacteriaceae, such as Salmonella spp. and Escherichia coli, which have well-defined resistance mechanisms. In contrast, relatively few studies have been performed on gram-positive organisms. We sequenced 197 strains of Enterococcus from various animal and food sources, including 100 Enterococcus faecium and 97 E. faecalis. From analyzing acquired resistance genes and known resistance-associated mutations, we found that resistance genotypes correlated with resistance phenotypes in 96.5% of cases for the 11 drugs investigated. Some resistances, such as those to tigecycline and daptomycin, could not be investigated due to a lack of knowledge of mechanisms underlying these phenotypes. This study showed the utility of WGS for predicting antimicrobial resistance based on genotype alone.201829617860
4938190.9997Optical maps of plasmids as a proxy for clonal spread of MDR bacteria: a case study of an outbreak in a rural Ethiopian hospital. OBJECTIVES: MDR bacteria have become a prevailing health threat worldwide. We here aimed to use optical DNA mapping (ODM) as a rapid method to trace nosocomial spread of bacterial clones and gene elements. We believe that this method has the potential to be a tool of pivotal importance for MDR control. METHODS: Twenty-four Escherichia coli samples of ST410 from three different wards were collected at an Ethiopian hospital and their plasmids were analysed by ODM. Plasmids were specifically digested with Cas9 targeting the antibiotic resistance genes, stained by competitive binding and confined in nanochannels for imaging. The resulting intensity profiles (barcodes) for each plasmid were compared to identify potential clonal spread of resistant bacteria. RESULTS: ODM demonstrated that a large fraction of the patients carried bacteria with a plasmid of the same origin, carrying the ESBL gene blaCTX-M-15, suggesting clonal spread. The results correlate perfectly with core genome (cg)MLST data, where bacteria with the same plasmid also had very similar cgMLST profiles. CONCLUSIONS: ODM is a rapid discriminatory method for identifying plasmids and antibiotic resistance genes. Long-range deletions/insertions, which are challenging for short-read next-generation sequencing, can be easily identified and used to trace bacterial clonal spread. We propose that plasmid typing can be a useful tool to identify clonal spread of MDR bacteria. Furthermore, the simplicity of the method enables possible future application in low- and middle-income countries.202032653928