Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates.

Background/Objectives: Microbiomes surrounding mining sites have been found to harbor both antibiotic resistance genes and metal resistance genes. Within the "One Health" framework, which spans human, veterinary and environmental health, it is crucial to determine whether bacterial metal resistance (MR) genes can independently trigger antimicrobial resistance (AMR) or if they are linked to AMR genes and co-transferred horizontally. Methods and Results: Bacteria were isolated from an active and an inactive mining site in the alpine region of Austria. Most of the isolated bacteria harbored antimicrobial and metal resistance genes (88%). MALDI-TOF and whole genome sequencing (WGS) revealed that species from the Pseudomonadaceae family were the most identified, accounting for 32.5%. All Pseudomonas spp. carried AMR genes from the mex family, which encode multidrug efflux pumps. β-lactamase production encoded by bla genes were detected as the second most common (26%). The same AMR genes have often been detected within a particular bacterial genus. No tetracycline resistance gene has been identified. Among metal resistance genes, rufB (tellurium resistance) was the most prevalent (33%), followed by recGM (selenium resistance, 30%), copA (copper resistance, 26%), and mgtA (magnesium and cobalt resistance, 26%). Notably, the mer gene family (mercury resistance) was found exclusively in isolates from the inactive mining site (n = 6). In addition, genes associated with both antimicrobial and metal resistance, including arsBM, acrD, and the mer operon, were identified in 19 out of the 43 isolates. Conclusions: Bacteria isolated from mine water harbored both MR and AMR genes. Given the exceptional diversity of bacterial species in these settings, 16S rRNA gene sequence analysis is the recommended method for accurate species identification. Moreover, the presence of multi-drug transporters and transferable resistance genes against critically important antimicrobials such as fluoroquinolones and colistin identified in these environmental bacteria emphasizes the importance of retrieving environmental data within the "One Health" framework.

The main work of this study is to analyze antimicrobial resistant E. coli based on whole genome sequencing data. Three stages were included for isolates from different sources (ready-to-eat food, retail raw meats and human patients). 
\nAt the first stage, a retrospective study for antimicrobial resistant E. coli in ready-to-eat (RTE) food sold in retail food premises in Singapore was performed in collaboration with Environmental Health Institute under NEA. A total of 99 E. coli isolates from poultry-based dishes (n=77) and fish-based dishes (n=22) were obtained between 2009 and 2014 during the surveillance project. All the isolates were included for disk diffusion testing for antimicrobial susceptibility testing. Of the 99 isolates, 24 (24.2%) were resistant to at least one antimicrobial agent. These isolates were then subjected to broth microdilution testing against 33 antimicrobial agents, including β-lactams, aminoglycosides, tetracycline, fluoroquinolones and polymyxin E (colistin), to determine the minimum inhibitory concentration (MIC) of isolates. Whole genome sequence (WGS) was carried out on the strains in order to correlate resistant phenotypes to putative antimicrobial resistance-related genes. Of the 24 isolates, 15 (62.5%) were found to be resistant to three or more classes of antimicrobials and thus were defined as multi-drug resistant strains. Two isolates (8.3%) were confirmed as Extended-Spectrum β-lactamase (ESBL)- producing E. coli by double disk synergy test. Based on WGS data, online analysis tool ResFinder detected 7 classes of antimicrobial resistance genes and resistance-related chromosomal point mutations in 19 of the 24 E. coli isolates. By analyzing the WGS contigs using BLASTn and KmerFinder, ESBL genes and transferable colistin resistance gene mcr-1 (2/24) and mcr-5 (1/24) were determined to be located on plasmids, which could pose a greater risk of AMR transfer among bacteria. Mutations were detected in four isolates within genes previously shown to confer resistance to quinolones (gyrA and parE) and tetracycline (rrsB). Prediction of AMR using WGS data was evaluated for six antimicrobials including ampicillin, chloramphenicol, colistin, fluoroquinolones, tetracycline and trimethoprim. The evaluation indicates WGS–based genotype and phenotype showed high consistency, however, for some antimicrobial resistance whose mechanism is not totally clear yet (such as colistin), there is challenge for resistance gene detection.
\nTo have a better understanding of genetic environment and mobility of colistin resistance gene mcr-5.1, the isolates carrying mcr-5.1 were sequenced using long-read sequencing technology. The plasmid sequences were assembled into a closed circle using both long-read sequencing data and short-read sequencing data. The blasting result showed the closest plasmid sequence to pSGMCR103 in NCBI is plasmid pYD786-3 (accession number KU254580.1) with 77% query coverage and 99% identity, which was carried by one E. coli isolate from human urine in USA. They share antimicrobial resistance gene aph(3’)-la, aadA1 (aminoglycoside resistance), blaTEM-176 (beta-lactam resistance) and sul3 (sulphonamide resistance). Gene mcr-5.1 was harbored on a Tn3 transposon-like element, which is similar with pSE13-SA01718 (accession number KY807921.1) carried by a Salmonella isolate reported before. Also, other insertion elements such as IS5, IS6, IS91, IS256 family were found on the plasmid, which may indicate the recombination activity of the plasmid. Moreover, the mobility of this plasmid was confirmed by the conjugation experiment. The frequency of conjugation after 24 hours is 10-6.
\nAfter knowing the AMR profile in ready-to-eat food in Singapore, at the second stage, an important resistance type was studied: Extended-Spectrum Beta-Lactamase (ESBL)-caused resistance to most of beta-lactams. We collected 634 meat samples including chicken, pork and beef from 97 supermarkets and 65 wet markets in Singapore during June 2017-October 2018. The samples were enriched before bacteria isolation. Presumptive ESBLs were screened by Brilliance TM ESBL Agar and confirmed by Double Disk Synergy Test (DDST). E. coli isolates were identified by EMB agar and indole test. The genomic DNA of ESBL-producing E. coli were extracted and sent for WGS. Besides the analysis for AMR genes, MLST, annotation and genetic environment, these sequence collection was also compared with sequence data of ESBL E. coli isolated from community in Singapore for phylogenetic study based on SNPs. A total of 225 ESBL-producing E. coli were isolated from 184 samples. The prevalence of ESBL in chicken, pork and beef was 51.2% (109/213), 26.9% (58/216), 7.3% (15/205), respectively. The most common AMR genes in all 225 ESBL isolates were beta-lactam-resistance genes (100%), aminoglycoside resistance gens (92.4%), sulphonamide resistance genes (86.2%). In terms of beta-lactam resistance genes, 172 of isolates (76.4%) carry blaCTX-M genes, 102 (45.3%) of isolates carry blaTEM genes and 52 of isolates (23.1%) carry blaSHV genes. Besides these most common three beta-lactamase genes, blaCMY-2, blaOXA and blaDHA were also found. Gene blaCTX-M-55 (57/225, 25.3%) and blaCTX-M-65 (40/225, 17.8%) were the most frequent ESBL genes. Among all these classes of antimicrobials, beta-lactam-resistance genes and aminoglycoside resistance genes exhibit great variety. The last-resort antimicrobial colistin resistance mcr genes exist in 15.6% of all isolates (33 isolates carry mcr-1, one carries mcr-3.1 and one carries mcr-5). Phylogeny tree based on SNPs of our isolates and previous ESBL isolates from human community in Singapore shows obvious separate human clusters and food clusters, however, two E. coli isolates from human fell into food clusters and showed high similarity with our isolates from meats, which indicates the possible transmission of resistant E. coli from meats to human may exist. Occurrence of AMR genes especially for last resort drug resistance genes was observed, raising concerns on food safety and public health.
\nAt the last stage, we applied WGS to the analysis of clinical isolates. We collaborated with the university in Thailand to get 28 ESBL-producing E. coli isolated from diarrhea patients hospitalized at the Phayao Ram Hospital in Thailand. Result shows all E. coli carried CTX-Ms beta-lactamase (including CTX-M-14, CTX-M-15, CTX-M-27, CTX-M-55), and half of these isolates (14/28) belong to the important pathogenic cluster ST131. CTX-M-55s were detected only in non-ST131s. Two serotypes O16:H5 (6/14) and O25:H4 (8/14) were observed in ST131 isolates. Generally, ST131 isolates showed different virulence factor patterns with non-ST131 isolates. BLAST results indicate that for half of ST131 isolates, blaCTX-M genes are located on chromosome adjacent to insert sequences (IS). For the other half ST131s, blaCTX-M genes are located on plasmids. Besides CTX-Ms, other beta-lactamases such as TEM-1B, OXA-1 and CMY-2 were also observed in our study. Phylogenetic analysis for a global collection and our clinical isolates in Thailand based on SNPs showed the closest isolates with our isolates are from Thailand, Singapore, Australia, Laos and New Zealand. A special strain cluster O16:H5-ST131 was found from 2015-2017 as well as other previous Thailand studies. These isolates showed high similarity in term of serotype, MLST, virulence factor / AMR patterns, and phylogeny, which indicates the persistence and spread of this cluster. This study provides an insight on characteristics of clinical ESBL-producing E. coli with special focus on ST131 in Thailand.
\nIt is noteworthy that four isolates in our study showed same serotype, ST (O16:H5-ST131), same virulence factor pattern (cnf1, iha, sat, senB) and even resistance gene pattern. In terms of SNP analysis, these isolates were located the same cluster 3 and the SNP difference range 17-20, which indicate the high similarity of these strains. But actually they are isolated in different years from 2015-2017, respectively. In cluster 3, other four isolates from Thailand (ERR1218557, ERR1218609, ERR1218624, ERR1218628) in a previous study also showed less than 30 SNPs difference with our four isolates. This also strengthens the hypothesis that these isolates diverged from one ancestor and this cluster of isolates are persistent in Thailand in recent years. This strain should raise our attention of further spread. The phylogenetic study indicates that the closest isolates with Thailand ST131 isolates are from Oceania and Southeast Asia. Our data based on whole genome add more evidence on ubiquity of ESBL-ST131 E. coli in Thailand. The co-existence of multi-resistance and multi-virulence factors adds challenges to clinical treatment. Although resistances to carbapenem and/or colistin are rare in this study, more epidemiology studies are needed to verify their actual prevalence. 
\nOverall speaking, WGS is a useful tool for prevalence and epidemiological analysis and source tracking. With the development of sequencing technology and the decrease of cost, whole-genome-based analysis is becoming more and more necessary for AMR study.

Aeromonas species are Gram-negative bacteria that infect various living organisms and are ubiquitously found in different aquatic environments. In this study, we used whole genome sequencing (WGS) to identify and compare the antimicrobial resistance (AMR) genes, integrons, transposases and plasmids found in Aeromonas hydrophila, Aeromonas caviae and Aeromonas veronii isolated from Indian major carp (Catla catla), Indian carp (Labeo rohita), catfish (Clarias batrachus) and Nile tilapia (Oreochromis niloticus) sampled in India. To gain a wider comparison, we included 11 whole genome sequences of Aeromonas spp. from different host species in India deposited in the National Center for Biotechnology Information (NCBI). Our findings show that all 15 Aeromonas sequences examined had multiple AMR genes of which the Ambler classes B, C and D β-lactamase genes were the most dominant. The high similarity of AMR genes in the Aeromonas sequences obtained from different host species point to interspecies transmission of AMR genes. Our findings also show that all Aeromonas sequences examined encoded several multidrug efflux-pump proteins. As for genes linked to mobile genetic elements (MBE), only the class I integrase was detected from two fish isolates, while all transposases detected belonged to the insertion sequence (IS) family. Only seven of the 15 Aeromonas sequences examined had plasmids and none of the plasmids encoded AMR genes. In summary, our findings show that Aeromonas spp. isolated from different host species in India carry multiple AMR genes. Thus, we advocate that the control of AMR caused by Aeromonas spp. in India should be based on a One Health approach.

Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance and SRST2, run with the ResFinder database) and their outputs compared. For simulation tests where 3079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3076 (99.9 %) simulations, ABRicate for 3054 (99.2 %), ARIBA for 2783 (90.4 %) and SRST2 for 2108 (68.5 %). For simulation tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance identified the correct alleles in 35 338/46 318 (76.3 %) simulations, ABRicate identified them in 11 842/46 318 (25.6 %) simulations, ARIBA identified them in 1679/46 318 (3.6 %) simulations and SRST2 identified them in 2000/46 318 (4.3 %) simulations. In real data, across all methods, 1392/1818 (76 %) isolates had discrepant allele calls for at least 1 gene. In addition to highlighting areas for improvement in challenging scenarios, (e.g. identification of AMR genes at <10× coverage, identifying multiple closely related AMR genes present in the same sample), our evaluations identified some more systematic errors that could be readily soluble, such as repeated misclassification (i.e. naming) of genes as shorter variants of the same gene present within the reference resistance gene database. Such naming errors accounted for at least 2530/4321 (59 %) of the discrepancies seen in real data. Moreover, many of the remaining discrepancies were likely ‘artefactual’, with reporting of cut-off differences accounting for at least 1430/4321 (33 %) discrepants. Whilst we found that comparing outputs generated by running multiple algorithms on the same dataset could identify and resolve these algorithmic artefacts, the results of our evaluations emphasize the need for developing new and more robust genotyping algorithms to further improve accuracy and performance.

ABSTRACTProphages 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.

Identification of antimicrobial resistance genes and drug resistance analysis of Escherichia coli in the animal farm environment

ABSTRACTContamination of food animal products by Escherichia coli is a leading cause of foodborne disease outbreaks, hospitalizations, and deaths in humans. Chicken is the most consumed meat both in the United States and across the globe according to the U.S. Department of Agriculture. Although E. coli is a ubiquitous commensal bacterium of the guts of humans and animals, its ability to acquire antimicrobial resistance (AMR) genes and virulence factors (VFs) can lead to the emergence of pathogenic strains that are resistant to critically important antibiotics. Thus, it is important to identify the genetic factors that contribute to the virulence and AMR of E. coli. In this study, we performed in-depth genomic evaluation of AMR genes and VFs of E. coli genomes available through the National Antimicrobial Resistance Monitoring System GenomeTrackr database. Our objective was to determine the genetic relatedness of chicken production isolates and human clinical isolates. To achieve this aim, we first developed a massively parallel analytical pipeline (Reads2Resistome) to accurately characterize the resistome of each E. coli genome, including the AMR genes and VFs harbored. We used random forests and hierarchical clustering to show that AMR genes and VFs are sufficient to classify isolates into different pathogenic phylogroups and host origin. We found that the presence of key type III secretion system and AMR genes differentiated human clinical isolates from chicken production isolates. These results further improve our understanding of the interconnected role AMR genes and VFs play in shaping the evolution of pathogenic E. coli strains.IMPORTANCE Pathogenic Escherichia coli causes disease in both humans and food-producing animals. E. coli pathogenesis is dependent on a repertoire of virulence factors and antimicrobial resistance genes. Food-borne outbreaks are highly associated with the consumption of undercooked and contaminated food products. This association highlights the need to understand the genetic factors that make E. coli virulent and pathogenic in humans and poultry. This research shows that E. coli isolates originating from human clinical settings and chicken production harbor different antimicrobial resistance genes and virulence factors that can be used to classify them into phylogroups and host origins. In addition, to aid in the repeatability and reproducibility of the results presented in this study, we have made a public repository of the Reads2Resistome pipeline and have provided the accession numbers associated with the E. coli genomes analyzed.

Background Antimicrobial resistance (AMR) is a growing global public health threat. In 2019, resistant bacterial infections and respiratory tract infections were a leading cause of death in children worldwide. While the gut is a known reservoir of AMR genes, there is little data on the AMR burden in the respiratory tract. We used metagenomic RNA next-generation sequencing (mNGS) to describe bacterial AMR genes detected in the upper respiratory tract of children and compare with adults. Methods We leveraged two established cohort studies of children and adults diagnosed with acute respiratory illnesses in the inpatient and outpatient setting in California and Colorado. Nasopharyngeal (NP) swabs were collected between March to September 2020. Specimens underwent RNA extraction and paired-end Illumina sequencing. AMR genes were detected using the ARG-ANNOT database and the CZID pipeline. Children ≤18 years of age and adults≥ 40 years of age were eligible for inclusion in the analysis. We described and compared AMR genes and AMR gene classes detected in children and adults. P-values were calculated using the Wilcoxon rank-sum test. A multiple logistic regression model was fitted to evaluate the association of age cohort (children vs adults) with presence of AMR genes, while accounting for possible confounding from sex and encounter setting. 95% confidence intervals (CI) were calculated using the Wald CI. Results NP swab mNGS data from 236 patients (82 children, 154 adults) were analyzed. Children were a median age of 4 years (range: 0-17 years), and adults were a median age of 62 years (range: 40-89 years). Both cohorts were 50% male. AMR genes were detected in 44 (54%) children and 109 (71%) adults. Genes conferring resistance to beta-lactams (n=112, 47%), macrolides (n=89, 38%), and tetracyclines (n=72, 31%) were the most frequently detected. Among children, children ages 0 to 2 years had a higher number of AMR genes than children of other age groups, particularly when compared with children ages 3 to 10 years (p-value: 0.031) (Figure 1A). When comparing children with adults, children had fewer AMR genes (p-value: 0.014) as well as fewer AMR gene classes (p-value: 0.031) (Figure 1B). In the multiple logistic regression model, children still had lower odds of any AMR genes detected compared with adults (odds ratio: 0.39, 95% CI: 0.21-0.71). Figure 1. Box plots of (A) the number of antimicrobial resistance (AMR) genes detected in children stratified by age, and (B) the number of AMR genes and AMR gene classes detected in children (n=82) and adults (n=154). The size of the individual data points within the box plots correlates with the number of patients at each data point. Conclusion Children had fewer AMR genes and gene classes than adults in their upper respiratory tract microbiome. Despite this, over half of the children had detectable resistance genes, and children 2 years and younger had more AMR genes than other children. Almost half of the children had resistance genes to beta-lactams, the most frequently prescribed antibiotics to children. These findings suggest that presence of AMR organisms in the airway is common even in children, and that continued efforts to reduce AMR burden in this population are essential.

Background The global rise in antimicrobial resistance (AMR) poses a major threat to public health, requiring robust bioinformatic tools essential for extracting and tracking resistance genes from databases to understand AMR gene transmission and spread. Hence, this study benchmarked AMR gene extraction methods from databases such as Comprehensive Antibiotic Resistance Database (CARD) and AMRFinderPlus.Table 1:Comparison of operating systems seamlessly supported by RGI and AMRFinderPlusFigure 1:Workflow for AMR Gene Extraction from Bacterial Genomes Methods Genomic sequences of Klebsiella pneumoniae (KP) and Acinetobacter baumannii (AB) were first downloaded using Python codes. To find and categorize the AMR genes we first used Resistance Gene Identifier (RGI), the recommended tool by CARD. We also evaluated KP and AB genome characterization using the AMRFinderPlus, a tool supported by the National Center for Biotechnology Information. We compared the ease of AMR genome characterization across Windows, macOS, and Linux systems. A custom Python pipeline was developed to automate extraction and characterization of AMR gene sequences from genome FASTA files. The workflow was designed to be capable of handling strand orientation, contig structure, and formatting differences across genomes (Figure 1).Figure 2:A detailed breakdown of gene coordinates, contig IDs, and gene annotations is included for representative samples Results Resistance Gene Identifier had installation issues on macOS and windows due to strict Python version dependencies. However, it worked reliably on Windows when containerized using Docker. Also, RGI resulted in incomplete annotations, coordinate discrepancies, and file access errors. In contrast, AMRFinderPlus exhibited structured output and consistent performance across Windows, macOS, and Linux systems (Table 1). The final workflow enabled accurate extraction of resistance genes from 1123 AB isolates (10,651 Contig IDs) and 3286 KP isolates (31,406 Contig IDs). Sequences were stratified by gene name, resistance class, contig ID, start-stop location and compiled into structured datasets by Python coding. Representative annotations are shown in Figure 2. Conclusion These findings suggest that AMRFinderPlus is a reliable solution for resistance gene characterization which could support broader applications in genomic surveillance and comparative analysis. Disclosures All Authors: No reported disclosures

Simple SummaryWorldwide, antimicrobial resistance (AMR) is of major concern for human and animal health since infections with multidrug-resistant bacteria are often more challenging and costly. In the family Staphyloccocaceae, the species Staphylococcusaureus in particular was reported to cause severe infections. Although most of the other Staphylococcaceae members were not shown to cause severe illnesses, the transmission of AMR genes to harmful species might take place. Therefore, the monitoring of AMR potential in different environments is of high relevance. Mammaliicocci on dairy farms might represent such an AMR gene reservoir. Thus, in this study, the AMR potential of mammaliicocci isolates from German dairy farms was investigated. Whole-genome sequencing (WGS) of the isolates was conducted to evaluate the phylogenetic relationship of the isolates and analyze AMR genes. In addition, antimicrobial susceptibility testing was performed to compare the AMR genotype with the phenotype. It turned out that mammaliicocci may harbor large numbers of different AMR genes and exhibit phenotypic resistance to various antibiotics. Since some AMR genes are likely located on mobile genetic elements, such as plasmids, AMR gene transmission between members of the Staphylococcaceae family might occur.Mammaliicocci might play a major role in antimicrobial resistance (AMR) gene transmission between organisms of the family Staphylococcaceae, such as the potentially pathogenic species Staphylococcus aureus. The interest of this study was to analyze AMR profiles of mammaliicocci from German dairy farms to evaluate the AMR transmission potential. In total, 65 mammaliicocci isolates from 17 dairy farms with a history of MRSA detection were analyzed for AMR genotypes and phenotypes using whole genome sequencing and antimicrobial susceptibility testing against 19 antibiotics. The various genotypic and phenotypic AMR profiles of mammaliicocci from German dairy farms indicated the simultaneous occurrence of several different strains on the farms. The isolates exhibited a non-wildtype phenotype to penicillin (58/64), cefoxitin (25/64), chloramphenicol (26/64), ciprofloxacin (25/64), clindamycin (49/64), erythromycin (17/64), fusidic acid (61/64), gentamicin (8/64), kanamycin (9/64), linezolid (1/64), mupirocin (4/64), rifampicin (1/64), sulfamethoxazol (1/64), streptomycin (20/64), quinupristin/dalfopristin (26/64), tetracycline (37/64), tiamulin (59/64), and trimethoprim (30/64). Corresponding AMR genes against several antimicrobial classes were detected. Linezolid resistance was associated with the cfr gene in the respective isolate. However, discrepancies between genotypic prediction and phenotypic resistance profiles, such as for fusidic acid and tiamulin, were also observed. In conclusion, mammaliicocci from dairy farms may carry a broad variety of antimicrobial resistance genes and exhibit non-wildtype phenotypes to several antimicrobial classes; therefore, they may represent an important source for horizontal gene transfer of AMR genes to pathogenic Staphylococcaceae.

Interpreting the phenotypes of bla SHV alleles in Klebsiella pneumoniae genomes is complex. Whilst all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal bla SHV alleles or additional plasmid-borne bla SHV alleles that have extended-spectrum β-lactamase (ESBL) activity and/or β-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/a changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases [e.g. the National Center for Biotechnology Information (NCBI) Reference Gene Catalog and the β-lactamase database (BLDB)] over the specific functionality of individual sulfhydryl variable (SHV) protein variants. Therefore, the identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific aa substitutions. We then systematically assigned SHV alleles to functional classes (WT, ESBL and BLI resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with the current assignments in the NCBI's Reference Gene Catalog and/or BLDB (21 to WT, 12 to ESBL and 4 to BLI resistant). Phylogenetic and comparative genomic analyses support that (i) SHV-1 (encoded by bla SHV-1) is the ancestral chromosomal variant, (ii) ESBL- and BLI-resistant variants have evolved multiple times through parallel substitution mutations, (iii) ESBL variants are mostly mobilized to plasmids and (iv) BLI-resistant variants mostly result from mutations in chromosomal bla SHV. We used matched genome-phenotype data from the KlebNET-GSP AMR Genotype-Phenotype Group to identify 3999 K. pneumoniae isolates carrying one or more bla SHV alleles but no other acquired β-lactamases to assess genotype-phenotype relationships for bla SHV. This collection includes human, animal and environmental isolates collected between 2001 and 2021 from 24 countries. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, whilst most omega-loop substitutions do not. Our data also provide support for the WT assignment of 67 protein variants, including 8 that were noted in public databases as ESBL. These eight variants were reclassified as WT because they lack ESBL-associated mutations, and our phenotype data support susceptibility to third-generation cephalosporins (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164 and SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae), whereby known and novel bla SHV alleles are classified based on causative mutations. Kleborate v2.4.1 was updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve the understanding of resistance mechanisms.

<h3>Abstract</h3> Increased colonisation by antimicrobial resistant organisms is closely associated with international travel. This study investigated the diversity of mobile genetic elements involved with antimicrobial resistance (AMR) gene carriage in extended-spectrum beta-lactamase (ESBL) -producing <i>Escherichia coli</i> that colonised travellers to Laos. Long-read sequencing was used to reconstruct complete plasmid sequences from 49 isolates obtained from the daily stool samples of 23 travellers over a three-week period. This method revealed a collection of 105 distinct plasmids, 38.1% of which carried AMR genes. The plasmids in this population were diverse, mostly unreported and included 38 replicon types, with F-type plasmids (n=22) the most prevalent amongst those carrying AMR genes. Fine-scale analysis of all plasmids identified numerous AMR gene contexts and emphasised the importance of IS elements, specifically members of the IS<i>6</i>/IS<i>26</i> family, in the creation of complex multi-drug resistance regions. We found a concerning convergence of ESBL and colistin resistance determinants, with three plasmids from two different F-type lineages carrying <i>bla</i>_CTX-M and <i>mcr</i> genes. The extensive diversity seen here highlights the worrying probability that stable new vehicles for AMR will evolve in <i>E. coli</i> populations that can disseminate internationally through travel networks. <h3>Impact Statement</h3> The global spread of AMR is closely associated with international travel. AMR is a severe global concern and has compromised treatment options for many bacterial pathogens, among them pathogens carrying ESBL and colistin resistance genes. Colonising MDR organisms have the potential to cause serious consequences. Infections caused by MDR bacteria are associated with longer hospitalisation, poorer patient outcomes, greater mortality, and higher costs compared to infections with susceptible bacteria. This study elucidates the numerous different types of plasmids carrying AMR genes in colonising ESBL-producing <i>E. coli</i> isolates found in faecal samples from in travellers to Vientiane, Laos. Here we add to known databases of AMR plasmids by adding these MDR plasmids found in Southeast Asia, an area of high AMR prevalence. We characterised novel AMR plasmids including complex ESBL (<i>bla</i>_CTX-M) and colistin (<i>mcr</i>) resistance co-carriage plasmids, emphasising the potential exposure of travellers to Laos to a wide variety of mobile genetic elements that may facilitate global AMR spread. This in-depth study has revealed further detail of the numerous factors that may influence AMR transfer, therefore potential routes of AMR spread internationally, and is a step towards finding methods to combat AMR spread. <h3>Data Summary</h3> Long-read sequencing data is available through National Center for Biotechnology Information under the BioProject PRJNA853172. Complete plasmid sequences have been uploaded to GenBank with accession numbers in supplementary S1. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

Detection of plasmids in Salmonella from poultry and investigating the potential horizontal transfer of antimicrobial resistance and virulence genes: PLASMID TRANSFER OF RESISTANCE AND VIRULENCE.

Co-occurrence of antimicrobial and metal resistance genes in pig feces and agricultural fields fertilized with slurry

BackgroundThe Joint Programming Initiative on Antimicrobial Resistance (JPIAMR) networks ‘Seq4AMR’ and ‘B2B2B AMR Dx’ were established to promote collaboration between microbial whole genome sequencing (WGS) and antimicrobial resistance (AMR) stakeholders. A key topic discussed was the frequent variability in results obtained between different microbial WGS-related AMR gene prediction workflows. Further, comparative benchmarking studies are difficult to perform due to differences in AMR gene prediction accuracy and a lack of agreement in the naming of AMR genes (semantic conformity) for the results obtained. To illustrate this problem, and as a capacity-building exercise to encourage stakeholder involvement, a comparative Galaxy-based BenchAMRking platform was developed and validated using datasets from bacterial species with PCR-verified AMR gene presence or absence information from abritAMR.ResultsThe Galaxy-based BenchAMRking platform (https://erasmusmc-bioinformatics.github.io/benchAMRking/) specifically focusses on the steps involved in identifying AMR genes from raw reads and sequence assemblies. The platform currently comprises four well-characterised and published workflows that have previously been used to identify AMR genes using WGS data from several different bacterial species. These four workflows, which include the ISO certified abritAMR workflow, make use of different computational tools (or tool versions), and interrogate different AMR gene sequence databases. By utilising their own data, users can investigate potential AMR gene-calling problems associated with their own in silico workflows/protocols, with a potential use case outlined in this publication.ConclusionsBenchAMRking is a Galaxy-based comparison platform where users can access, visualise, and explore some of the major discrepancies associated with AMR gene prediction from microbial WGS data.