Genomic analysis of Salmonella isolated from canal water in Bangkok, Thailand.

Antimicrobial resistance (AMR) poses an escalating global public health threat. Canals are essential in Thailand, including the capital city, Bangkok, as agricultural and daily water sources. However, the characteristic and antimicrobial-resistance properties of the bacteria in the urban canals have never been elucidated. This study employed whole genome sequencing to characterize 30 genomes of a causal pathogenic bacteria, Salmonella enterica, isolated from Bangkok canal water between 2016 and 2020. The dominant serotype was Salmonella Agona. In total, 35 AMR genes and 30 chromosomal-mediated gene mutations were identified, in which 21 strains carried both acquired genes and mutations associated with fluoroquinolone resistance. Virulence factors associated with invasion, adhesion, and survival during infection were detected in all study strains. 75.9% of the study stains were multidrug-resistant and all the strains harbored the necessary virulence factors associated with salmonellosis. One strain carried 20 resistance genes, including mcr-3.1, mutations in GyrA, ParC, and ParE, and typhoid toxin-associated genes. Fifteen plasmid replicon types were detected, with Col(pHAD28) being the most common type. Comparative analysis of nine S. Agona from Bangkok and 167 from public databases revealed that specific clonal lineages of S. Agona might have been circulating between canal water and food sources in Thailand and globally. These findings provide insight into potential pathogens in the aquatic ecosystem and support the inclusion of environmental samples into comprehensive AMR surveillance initiatives as part of a One Health approach. This approach aids in comprehending the rise and dissemination of AMR and devising sustainable intervention strategies.IMPORTANCEBangkok is the capital city of Thailand and home to a large canal network that serves the city in various ways. The presence of pathogenic and antimicrobial-resistant Salmonella is alarming and poses a significant public health risk. The present study is the first characterization of the genomic of Salmonella strains from Bangkok canal water. Twenty-two of 29 strains (75.9%) were multidrug-resistant Salmonella and all the strains carried essential virulence factors for pathogenesis. Various plasmid types were identified in these strains, potentially facilitating the horizontal transfer of AMR genes. Additional investigations indicated a potential circulation of S. Agona between canal water and food sources in Thailand. The current study underscores the role of environmental water in an urban city as a reservoir of pathogens and these data obtained can serve as a basis for public health risk assessment and help shape intervention strategies to combat AMR challenges in Thailand.

A novel metagenomic approach uncovers phage genes as markers for increased disinfectant tolerance in mixed Listeria monocytogenes communities.

Listeria monocytogenes is an important human pathogen with a high mortality rate. Consumption of contaminated ready-to-eat food is the main mode of transmission to humans. Disinfectant-tolerant L. monocytogenes have emerged, which are believed to have increased persistence potential. Elucidating the mechanisms of L. monocytogenes disinfectant tolerance has been the focus of previous studies using pure cultures. A limitation of such approach is the difficulty to identify strains with reduced susceptibility due to inter-strain variation and the need to screen large numbers of strains and genes. In this study, we applied a novel metagenomic approach to detect genes associated with disinfectant tolerance in mixed L. monocytogenes planktonic communities. Two communities, consisting of 71 and 80 isolates each, were treated with the food industry disinfectants benzalkonium chloride (BC, 1.75 mg/L) or peracetic acid (PAA, 38 mg/L). The communities were subjected to metagenomic sequencing and differences in individual gene abundances between biocide-free control communities and biocide-treated communities were determined. A significant increase in the abundance of Listeria phage-associated genes was observed in both communities after treatment, suggesting that prophage carriage could lead to an increased disinfectant tolerance in mixed L. monocytogenes planktonic communities. In contrast, a significant decrease in the abundance of a high-copy emrC-harbouring plasmid pLmN12-0935 was observed in both communities after treatment. In PAA-treated community, a putative ABC transporter previously found to be necessary for L. monocytogenes resistance to antimicrobial agents and virulence, was among the genes with the highest weight for differentiating treated from control samples. The undertaken metagenomic approach in this study can be applied to identify genes associated with increased tolerance to other antimicrobials in mixed bacterial communities.

The European livestock resistome.

Metagenomic sequencing has proven to be a powerful tool in the monitoring of antimicrobial resistance (AMR). Here, we provide a comparative analysis of the resistome from pigs, poultry, veal calves, turkey, and rainbow trout, for a total of 538 herds across nine European countries. We calculated the effects of per-farm management practices and antimicrobial usage (AMU) on the resistome in pigs, broilers, and veal calves. We also provide an in-depth study of the associations between bacterial diversity, resistome diversity, and AMR abundances as well as co-occurrence analysis of bacterial taxa and antimicrobial resistance genes (ARGs) and the universality of the latter. The resistomes of veal calves and pigs clustered together, as did those of avian origin, while the rainbow trout resistome was different. Moreover, we identified clear core resistomes for each specific food-producing animal species. We identified positive associations between bacterial alpha diversity and both resistome alpha diversity and abundance. Network analyses revealed very few taxa-ARG associations in pigs but a large number for the avian species. Using updated reference databases and optimized bioinformatics, previously reported significant associations between AMU, biosecurity, and AMR in pig and poultry farms were validated. AMU is an important driver for AMR; however, our integrated analyses suggest that factors contributing to increased bacterial diversity might also be associated with higher AMR load. We also found that dispersal limitations of ARGs are shaping livestock resistomes, and future efforts to fight AMR should continue to emphasize biosecurity measures.IMPORTANCEUnderstanding the occurrence, diversity, and drivers for antimicrobial resistance (AMR) is important to focus future control efforts. So far, almost all attempts to limit AMR in livestock have addressed antimicrobial consumption. We here performed an integrated analysis of the resistomes of five important farmed animal populations across Europe finding that the resistome and AMR levels are also shaped by factors related to bacterial diversity, as well as dispersal limitations. Thus, future studies and interventions aimed at reducing AMR should not only address antimicrobial usage but also consider other epidemiological and ecological factors.

Ongoing mpox outbreak in Kamituga, South Kivu province, associated with monkeypox virus of a novel Clade I sub-lineage, Democratic Republic of the Congo, 2024.

Since the beginning of 2023, the number of people with suspected monkeypox virus (MPXV) infection have sharply increased in the Democratic Republic of the Congo (DRC). We report near-to-complete MPXV genome sequences derived from six cases from the South Kivu province. Phylogenetic analyses reveal that the MPXV affecting the cases belongs to a novel Clade I sub-lineage. The outbreak strain genome lacks the target sequence of the probe and primers of a commonly used Clade I-specific real-time PCR.

ARGprofiler-a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets.

MOTIVATION: Analyzing metagenomic data can be highly valuable for understanding the function and distribution of antimicrobial resistance genes (ARGs). However, there is a need for standardized and reproducible workflows to ensure the comparability of studies, as the current options involve various tools and reference databases, each designed with a specific purpose in mind. RESULTS: In this work, we have created the workflow ARGprofiler to process large amounts of raw sequencing reads for studying the composition, distribution, and function of ARGs. ARGprofiler tackles the challenge of deciding which reference database to use by providing the PanRes database of 14 078 unique ARGs that combines several existing collections into one. Our pipeline is designed to not only produce abundance tables of genes and microbes but also to reconstruct the flanking regions of ARGs with ARGextender. ARGextender is a bioinformatic approach combining KMA and SPAdes to recruit reads for a targeted de novo assembly. While our aim is on ARGs, the pipeline also creates Mash sketches for fast searching and comparisons of sequencing runs. AVAILABILITY AND IMPLEMENTATION: The ARGprofiler pipeline is a Snakemake workflow that supports the reuse of metagenomic sequencing data and is easily installable and maintained at https://github.com/genomicepidemiology/ARGprofiler.

VirulenceFinder for Enterococcus faecium and Enterococcus lactis: an enhanced database for detection of putative virulence markers by using whole-genome sequencing data.

Enterococcus faecium (Efm) is a leading cause of hospital-associated (HA) infections, often enriched in putative virulence markers (PVMs). Recently, the Efm clade B was assigned as Enterococcus lactis (Elts), which usually lack HA-Efm infection markers. Available databases for extracting PVM are incomplete and/or present an intermix of genes from Efm and Enterococcus faecalis, with distinct virulence profiles. In this study, we constructed a new database containing 27 PVMs [acm, scm, sgrA, ecbA, fnm, sagA, hylEfm, ptsD, orf1481, fms15, fms21-fms20 (pili gene cluster 1, PGC-1), fms14-fms17-fms13 (PGC-2), empA-empB-empC (PGC-3), fms11-fms19-fms16 (PGC-4), ccpA, bepA, gls20-glsB1, and gls33-glsB] from nine reference genomes (seven Efm + two Elts). The database was validated against these reference genomes and further evaluated using a collection of well-characterized Efm (n = 43) and Elts (n = 7) control strains, by assessing PVM presence/absence and its variants together with a genomic phylogeny constructed as single-nucleotide polymorphisms. We found a high concordance between the phylogeny and in silico findings of the PVM, with Elts clustering separately and mostly carrying Elts-specific PVM gene variants. Based on our validation results, we recommend using the database with raw reads instead of assemblies to avoid missing gene variants. This newly constructed database of 27 PVMs will enable a more comprehensive characterization of Efm and Elts based on WGS data. The developed database exhibits scalability and boasts a range of applications in public health, including diagnostics, outbreak investigations, and epidemiological studies. It can be further used in risk assessment for distinguishing between safe and unsafe enterococci.IMPORTANCEThe newly constructed database, consisting of 27 putative virulence markers, is highly scalable and serves as a valuable resource for the comprehensive characterization of these closely related species using WGS data. It holds significant potential for various public health applications, including hospital outbreak investigations, surveillance, and risk assessment for probiotics and feed additives.

The first complete genome sequence of Staphylococcus aureus ST5477.

This study presents the first complete genome of Staphylococcus aureus ST5477, one of the most common sequence types (ST) from bovine in eastern Africa. The genome consists of a 2,723,132-bp circular chromosome and a 3,044-bp plasmid. This strain was collected in 2017 from cow milk in Tanzania.

West Nile virus spread in Europe: Phylogeographic pattern analysis and key drivers.

BACKGROUND: West Nile virus (WNV) outbreaks in birds, humans, and livestock have occurred in multiple areas in Europe and have had a significant impact on animal and human health. The patterns of emergence and spread of WNV in Europe are very different from those in the US and understanding these are important for guiding preparedness activities. METHODS: We mapped the evolution and spread history of WNV in Europe by incorporating viral genome sequences and epidemiological data into phylodynamic models. Spatially explicit phylogeographic models were developed to explore the possible contribution of different drivers to viral dispersal direction and velocity. A "skygrid-GLM" approach was used to identify how changes in environments would predict viral genetic diversity variations over time. FINDINGS: Among the six lineages found in Europe, WNV-2a (a sub-lineage of WNV-2) has been predominant (accounting for 73% of all sequences obtained in Europe that have been shared in the public domain) and has spread to at least 14 countries. In the past two decades, WNV-2a has evolved into two major co-circulating clusters, both originating from Central Europe, but with distinct dynamic history and transmission patterns. WNV-2a spreads at a high dispersal velocity (88km/yr-215 km/yr) which is correlated to bird movements. Notably, amongst multiple drivers that could affect the spread of WNV, factors related to land use were found to strongly influence the spread of WNV. Specifically, the intensity of agricultural activities (defined by factors related to crops and livestock production, such as coverage of cropland, pasture, cultivated and managed vegetation, livestock density) were positively associated with both spread direction and velocity. In addition, WNV spread direction was associated with high coverage of wetlands and migratory bird flyways. CONCLUSION: Our results suggest that-in addition to ecological conditions favouring bird- and mosquito- presence-agricultural land use may be a significant driver of WNV emergence and spread. Our study also identified significant gaps in data and the need to strengthen virological surveillance in countries of Central Europe from where WNV outbreaks are likely seeded. Enhanced monitoring for early detection of further dispersal could be targeted to areas with high agricultural activities and habitats of migratory birds.

Predicting Listeria monocytogenes virulence potential using whole genome sequencing and machine learning.

Contamination with food-borne pathogens, such as Listeria monocytogenes, remains a big concern for food safety. Hence, rigorous and continuous microbial surveillance is a standard procedure. At this point, however, the food industry and authorities only focus on detection of Listeria monocytogenes without characterization of individual strains into groups of more or less concern. As whole genome sequencing (WGS) gains increasing interest in the industry, this methodology presents an opportunity to obtain finer resolution of microbial traits such as virulence. Within this study, we therefore aimed to explore the use of WGS in combination with Machine Learning (ML) to predict L. monocytogenes virulence potential on a sub-species level. The WGS datasets used in this study for ML model training consisted of i) national surveillance isolates (n = 169, covering 38 MLST types) and ii) publicly available isolates acquired through the GenomeTrakr network (n = 2880, spanning 80 MLST types). We used the clinical frequency, i.e., ratio of the number of clinical isolates to total amount of isolates, as estimate for virulence potential. The predictive performance of input features from three different genomic levels (i.e., virulence genes, pan-genome genes, and single nucleotide polymorphisms (SNPs)) and six machine learning algorithms (i.e., Support Vector Machine with a linear kernel, Support Vector Machine with a radial kernel, Random Forrest, Neural Networks, LogitBoost, and Majority Voting) were compared. Our machine learning models predicted sub-species virulence potential with nested cross-validation F1-scores up to 0.88 for the majority voting classifier trained on national surveillance data and using pan-genome genes as input features. The validation of the pre-trained ML models based on 101 previously in vivo studied isolates resulted in F1-scores up to 0.76. Furthermore, we found that the more rapid and less computationally intensive raw read alignment yields comparably accurate models as de novo assembly. The results of our study suggest that a majority voting classifier trained on pan-genome genes is the best and most robust choice for the prediction of clinical frequency. Our study contributes to more rapid and precise characterization of L. monocytogenes virulence and its variation on a sub-species level. We further demonstrated a possible application of WGS data in the context of microbial hazard characterization for food safety. In the future, predictive models may assist case-specific microbial risk management in the food industry. The python code, pre-trained models, and prediction pipeline are deposited at (https://github.com/agmei/LmonoVirulenceML).

Transmission of antimicrobial resistance in the gut microbiome of gregarious cockroaches: the importance of interaction between antibiotic exposed and non-exposed populations.

Antimicrobial resistance (AMR) is a major global health concern, further complicated by its spread via the microbiome bacterial members. While mathematical models discuss AMR transmission through the symbiotic microbiome, experimental studies are scarce. Herein, we used a gregarious cockroach, Pycnoscelus surinamensis, as an in vivo animal model for AMR transmission investigations. We explored whether the effect of antimicrobial treatment is detectable with metagenomic sequencing, and whether AMR genes can be spread and established in unchallenged (not treated with antibiotics) individuals following contact with treated donors, and under various frequencies of interaction. Gut and soil substrate microbiomes were investigated by metagenomic sequencing for bacterial community composition and resistome profiling. We found that tetracycline treatment altered the treated gut microbiome by decreasing bacterial diversity and increasing the abundance of tetracycline resistance genes. Untreated cockroaches that interacted with treated donors also had elevated tetracycline resistance. The levels of resistance differed depending on the magnitude and frequency of donor transfer. Additionally, treated donors showed signs of microbiome recovery due to their interaction with the untreated ones. Similar patterns were also recorded in the soil substrate microbiomes. Our results shed light on how interacting microbiomes facilitate AMR gene transmission to previously unchallenged hosts, a dynamic influenced by the interaction frequencies, using an in vivo model to validate theoretical AMR transmission models.IMPORTANCEAntimicrobial resistance is a rising threat to human and animal health. The spread of resistance through the transmission of the symbiotic gut microbiome is of concern and has been explored in theoretical modeling studies. In this study, we employ gregarious insect populations to examine the emergence and transmission of antimicrobial resistance in vivo and validate modeling hypotheses. We find that antimicrobial treatment increases the levels of resistance in treated populations. Most importantly, we show that resistance increased in untreated populations after interacting with the treated ones. The level of resistance transmission was affected by the magnitude and frequency of population mixing. Our results highlight the importance of microbial transmission in the spread of antimicrobial resistance.

Flankophile: a bioinformatic pipeline for prokaryotic genomic synteny analysis.

IMPORTANCE: The Flankophile pipeline enables the analysis and visualization of flanking regions of prokaryotic sequences of interest on large data sets in one step and in a consistent manner. A specific tool for flanking region analysis with automated visualization has not been developed before, and Flankophile will make flanking region analysis easier and accessible to more people. Flankophile will be especially useful in the field of genomic epidemiology of acquired antimicrobial resistance genes. Here, information from flanking region sequences can be instrumental in rejecting or supporting the possibility of a recent common source of the same resistance gene found in different samples.

Association of health, nutrition, and socioeconomic variables with global antimicrobial resistance: a modelling study.

BACKGROUND: Although antimicrobial use is a key selector for antimicrobial resistance, recent studies have suggested that the ecological context in which antimicrobials are used might provide important factors for the prediction of the emergence and spread of antimicrobial resistance. METHODS: We used 1547 variables from the World Bank dataset consisting of socioeconomic, developmental, health, and nutritional indicators; data from a global sewage-based study on antimicrobial resistance (abundance of antimicrobial resistance genes [ARGs]); and data on antimicrobial usage computed from the ECDC database and the IQVIA database. We characterised and built models predicting the global resistome at an antimicrobial class level. We used a generalised linear mixed-effects model to estimate the association between antimicrobial usage and ARG abundance in the sewage samples; a multivariate random forest model to build predictive models for each antimicrobial resistance class and to select the most important variables for ARG abundance; logistic regression models to test the association between the predicted country-level antimicrobial resistance abundance and the country-level proportion of clinical resistant bacterial isolates; finite mixture models to investigate geographical heterogeneities in the abundance of ARGs; and multivariate finite mixture models with covariates to investigate the effect of heterogeneity in the association between the most important variables and the observed ARG abundance across the different country subgroups. We compared our predictions with available clinical phenotypic data from the SENTRY Antimicrobial Surveillance Program from eight antimicrobial classes and 12 genera from 56 countries. FINDINGS: Using antimicrobial use data from between Jan 1, 2016, and Dec 31, 2019, we found that antimicrobial usage was not significantly associated with the global ARG abundance in sewage (p=0·72; incidence rate ratio 1·02 [95% CI 0·92-1·13]), whereas country-specific World Bank's variables explained a large amount of variation. The importance of the World Bank variables differed between antimicrobial classes and countries. Generally, the estimated global ARG abundance was positively associated with the prevalence of clinical phenotypic resistance, with a strong association for bacterial groups in the human gut. The associations between bacterial groups and ARG abundance were positive and significantly different from zero for the aminoglycosides (three of the four of the taxa tested), ß-lactam (all the six microbial groups), fluoroquinolones (seven of nine of the microbial groups), glycopeptide (one microbial group tested), folate pathway antagonists (four of five microbial groups), and tetracycline (two of nine microbial groups). INTERPRETATION: Metagenomic analysis of sewage is a robust approach for the surveillance of antimicrobial resistance in pathogens, especially for bacterial groups associated with the human gut. Additional studies on the associations between important socioeconomic, nutritional, and health factors and antimicrobial resistance should consider the variation in these associations between countries and antimicrobial classes. FUNDING: EU Horizon 2020 and Novo Nordisk Foundation.

Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints.

Current surveillance of antimicrobial resistance (AMR) is mostly based on testing indicator bacteria using minimum inhibitory concentration (MIC) panels. Metagenomics has the potential to identify all known antimicrobial resistant genes (ARGs) in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and the subsequent spread to the entire population. To make the simulation realistic, the total cost of the surveillance was constrained, and the sampling schedule was set at one pool per month with 5, 20, 50, or 100 samples. Our simulations demonstrate that a pool of 20-50 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time delay to detection of change of [Formula: see text]15 months in all scenarios. Compared with culture-based surveillance, our simulation indicates that there are neither significant reductions nor increases in time to detect a change using metagenomics. The benefit of metagenomics is that it is possible to monitor all known resistance in one sampling and laboratory procedure in contrast to the current monitoring that is based on the phenotypic characterisation of selected indicator bacterial species. Therefore, overall changes in AMR in a population will be detected earlier using metagenomics due to the fact that the resistance gene does not have to be transferred to and expressed by an indicator bacteria before it is possible to detect.

Importance of mobile genetic elements for dissemination of antimicrobial resistance in metagenomic sewage samples across the world.

We are facing an ever-growing threat from increasing antimicrobial resistance (AMR) in bacteria. To mitigate this, we need a better understanding of the global spread of antimicrobial resistance genes (ARGs). ARGs are often spread among bacteria by horizontal gene transfer facilitated by mobile genetic elements (MGE). Here we use a dataset consisting of 677 metagenomic sequenced sewage samples from 97 countries or regions to study how MGEs are geographically distributed and how they disseminate ARGs worldwide. The ARGs, MGEs, and bacterial abundance were calculated by reference-based read mapping. We found systematic differences in the abundance of MGEs and ARGs, where some elements were prevalent on all continents while others had higher abundance in separate geographic areas. Different MGEs tended to be localized to temperate or tropical climate zones, while different ARGs tended to separate according to continents. This suggests that the climate is an important factor influencing the local flora of MGEs. MGEs were also found to be more geographically confined than ARGs. We identified several integrated MGEs whose abundance correlated with the abundance of ARGs and bacterial genera, indicating the ability to mobilize and disseminate these genes. Some MGEs seemed to be more able to mobilize ARGs and spread to more bacterial species. The host ranges of MGEs seemed to differ between elements, where most were associated with bacteria of the same family. We believe that our method could be used to investigate the population dynamics of MGEs in complex bacterial populations.

The resistomes of rural and urban pigs and poultry in Ghana.

IMPORTANCE: To the best of our knowledge, this is the first report on the resistomes that are measured using metagenomics in livestock from Sub-Saharan Africa. We find notable differences in the microbiomes between both pigs and poultry, and those also varied markedly compared to similar samples from Europe. However, for both animal species, the same bacterial taxa drove such differences. In pigs and urban free-range poultry, we find a very low abundance of antimicrobial resistance genes (ARGs), whereas rural free-range poultry displayed similarity to the European average, and industrialized poultry exhibited higher levels. These findings show how different African livestock bacterial communities and resistomes are from their European counterparts. They also underscore the importance of continued surveillance and investigation into antimicrobial resistance across diverse ecosystems, contributing significantly to global efforts toward combating the threat of antibiotic resistance.

Nanopore sequencing technology for clinical diagnosis of infectious diseases where laboratory capacity is meager: A case report.

In resource-limited settings, patients are often first presented to clinical settings when seriously ill and access to proper clinical microbial diagnostics is often very limited or non-existing. On February 16th, 2022 we were on a field trip to test a completely field-deployable metagenomics sequencing set-up, that includes DNA purification, sequencing, and bioinformatics analyses using bioinformatics tools installed on a laptop for water samples, just outside Moshi, Tanzania. On our way to the test site, we were contacted by the nearby Machame hospital regarding a child seriously ill with diarrhea and not responding to treatment. Within the same day, we conducted an onsite metagenomics examination of a fecal sample from the child, and Campylobacter jejuni was identified as the causative agent. The treatment was subsequently changed, with almost immediate improvement, and the child was discharged on February 21st.

Various arrangements of mobile genetic elements among CC147 subpopulations of Klebsiella pneumoniae harboring blaNDM-1: a comparative genomic analysis of carbapenem resistant strains.

BACKGROUND: Certain clonal complexes (CCs) of Klebsiella pneumoniae such as CC147 (ST147 and ST392) are major drivers of blaNDM dissemination across the world. ST147 has repeatedly reported from our geographical region, but its population dynamics and evolutionary trajectories need to be further studied. METHODS: Comparative genomic analysis of 51 carbapenem-nonsusceptible strains as well as three hypervirulent K. pneumoniae (hvKp) recovered during 16-months of surveillance was performed using various bioinformatics tools. We investigated the genetic proximity of our ST147 strains with publicly available corresponding genomes deposited globally and from neighbor countries in our geographic region. RESULTS: While IncL/M plasmid harboring blaOXA-48 was distributed among divergent clones, blaNDM-1 was circulated by twenty of the 25 CC147 dominant clone and were mostly recovered from the ICU. The NDM-1 core structure was bracketed by a single isoform of mobile genetic elements (MGEs) [ΔISKpn26-NDM-TnAs3-ΔIS3000-Tn5403] and was located on Col440I plasmid in 68.7% of ST392. However, various arrangements of MGEs including MITESen1/MITESen1 composite transposon or combination of MITESen1/ISSen4/IS903B/IS5/ISEhe3 on IncFIb (pB171) were identified in ST147. It seems that ST392 circulated blaNDM-1 in 2018 before being gradually replaced by ST147 from the middle to the end of sample collection in 2019. ST147 strains possessed the highest number of resistance markers and showed high genetic similarity with four public genomes that harbored blaNDM-1 on the same replicon type. Mainly, there was a convergence between clusters and isolated neighboring countries in the minimum-spanning tree. A conserved arrangement of resistance markers/MGEs was linked to methyltransferase armA which was embedded in class 1 integron in 8 isolates of ST147/ST48 high-risk clones. CONCLUSION: Our findings highlight the dynamic nature of blaNDM-1 transmission among K. pneumoniae in Iran that occurs both clonally and horizontally via various combinations of MGEs. This is the first analysis of Iranian ST147/NDM + clone in the global context.

An Overview of Antimicrobial Resistance Profiles of Publicly Available Salmonella Genomes with Sufficient Quality and Metadata.

Salmonella enterica (S. enterica) is a commensal organism or pathogen causing diseases in animals and humans, as well as widespread in the environment. Antimicrobial resistance (AMR) has increasingly affected both animal and human health and continues to raise public health concerns. A decade ago, it was estimated that the increased use of whole genome sequencing (WGS) combined with sharing of public data would drastically change and improve the surveillance and understanding of Salmonella epidemiology and AMR. This study aimed to evaluate the current usefulness of public WGS data for Salmonella surveillance and to investigate the associations between serovars, antibiotic resistance genes (ARGs), and metadata. Out of 191,306 Salmonella genomes deposited in European Nucleotide Archive and NCBI databases, 47,452 WGS with sufficient minimum metadata (country, year, and source) of S. enterica were retrieved from 116 countries and isolated between 1905 and 2020. For in silico analysis of the WGS data, KmerFinder, SISTR, and ResFinder were used for species, serovars, and AMR identification, respectively. The results showed that the five common isolation sources of S. enterica are human (29.10%), avian (22.50%), environment (11.89%), water (9.33%), and swine (6.62%). The most common ARG profiles for each class of antimicrobials are ß-lactam (blaTEM-1B; 6.78%), fluoroquinolone [(parC[T57S], qnrB19); 0.87%], folate pathway antagonist (sul2; 8.35%), macrolide [mph(A); 0.39%], phenicol (floR; 5.94%), polymyxin B (mcr-1.1; 0.09%), and tetracycline [tet(A); 12.95%]. Our study reports the first overview of ARG profiles in publicly available Salmonella genomes from online databases. All data sets from this study can be searched at Microreact.

Distinctive hospital and community resistomes in Scottish urban wastewater: Metagenomics of a paired wastewater sampling design.

The wastewater microbiome contains a multitude of resistant bacteria of human origin, presenting an opportunity for surveillance of resistance in the general population. However, wastewater microbial communities are also influenced by clinical sources, such as hospitals. Identifying signatures of the community and hospital resistome in wastewater is needed for interpretation and risk analysis. In this study, we compare the resistome and microbiome of hospital, community, and mixed municipal wastewater to investigate how and why the composition of these different sites differ. We conducted shotgun metagenomic analysis on wastewater samples from eight wastewater treatment plants (WWTPs), four hospitals, and four community sites in Scotland, using a paired sampling design. Cluster analysis and source attribution random forest models demonstrated that the hospital resistome was distinct from community and WWTP resistomes. Hospital wastewater had a higher abundance and diversity of resistance genes, in keeping with evidence that hospitals act as a reservoir and enricher of resistance. However, this distinctive 'hospital' signature appeared to be weak in the resistome of downstream WWTPs, likely due to dilution. We conclude that hospital and community wastewater resistomes differ, with the hospital wastewater representing a reservoir of patient- and hospital environment-associated bacteria. However, this 'hospital' signature is transient and does not overwhelm the community signature in the resistome of the downstream WWTP influent.

Trends in Salmonella Dublin over time in Denmark from food and animal related isolates.

Salmonella enterica serovar Dublin is highly adapted to cattle and a relatively rare cause of human infections. In Denmark S. Dublin has been endemic in the cattle population for many years. A national surveillance program in the cattle population was established at herd-level to reduce the occurrence of S. Dublin. In this study, we analyzed 421 S. Dublin genomes from cattle and food in order to determine the trend of S. Dublin's population size over time in Denmark and the impact of intervention in the cattle industry on the bacterial population size. A phylogenetic tree based on SNPs exhibited two major clades and one small cluster. All isolates were ST10. The temporal phylogenetic tree for the S. Dublin isolates showed that the most recent common ancestor was estimated to be in ∼1980 for the two major clades. An effective population size over time based on a Bayesian skyline plot showed that the population size of S. Dublin decreased significantly between 2014 and 2019 in both major clades. This result was concordant with the decrease of infected human cases by S. Dublin in Denmark. The strengthening of a surveillance program in Denmark could be the cause for the reduction of S. Dublin's effective population size. This study showed that whole genome sequencing combined with computer intensive phylogenetic analysis estimating the effective size of the S. Dublin's population over time is a strongly relevant measure with respect to assessing the impact of control measures aiming to reduce the bacterial population in the reservoir and the risk for human infection.