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.

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.

Antimicrobial resistance monitoring in the Danish swine production by phenotypic methods and metagenomics from 1999 to 2018.

BackgroundIn Denmark, antimicrobial resistance (AMR) in pigs has been monitored since 1995 by phenotypic approaches using the same indicator bacteria. Emerging methodologies, such as metagenomics, may allow novel surveillance ways.AimThis study aimed to assess the relevance of indicator bacteria (Escherichia coli and Enterococcus faecalis) for AMR surveillance in pigs, and the utility of metagenomics.MethodsWe collated existing data on AMR and antimicrobial use (AMU) from the Danish surveillance programme and performed metagenomics sequencing on caecal samples that had been collected/stored through the programme during 1999-2004 and 2015-2018. We compared phenotypic and metagenomics results regarding AMR, and the correlation of both with AMU.ResultsVia the relative abundance of AMR genes, metagenomics allowed to rank these genes as well as the AMRs they contributed to, by their level of occurrence. Across the two study periods, resistance to aminoglycosides, macrolides, tetracycline, and beta-lactams appeared prominent, while resistance to fosfomycin and quinolones appeared low. In 2015-2018 sulfonamide resistance shifted from a low occurrence category to an intermediate one. Resistance to glycopeptides consistently decreased during the entire study period. Outcomes of both phenotypic and metagenomics approaches appeared to positively correlate with AMU. Metagenomics further allowed to identify multiple time-lagged correlations between AMU and AMR, the most evident being that increased macrolide use in sow/piglets or fatteners led to increased macrolide resistance with a lag of 3-6 months.ConclusionWe validated the long-term usefulness of indicator bacteria and showed that metagenomics is a promising approach for AMR surveillance.

Genomic analysis of sewage from 101 countries reveals global landscape of antimicrobial resistance.

Antimicrobial resistance (AMR) is a major threat to global health. Understanding the emergence, evolution, and transmission of individual antibiotic resistance genes (ARGs) is essential to develop sustainable strategies combatting this threat. Here, we use metagenomic sequencing to analyse ARGs in 757 sewage samples from 243 cities in 101 countries, collected from 2016 to 2019. We find regional patterns in resistomes, and these differ between subsets corresponding to drug classes and are partly driven by taxonomic variation. The genetic environments of 49 common ARGs are highly diverse, with most common ARGs carried by multiple distinct genomic contexts globally and sometimes on plasmids. Analysis of flanking sequence revealed ARG-specific patterns of dispersal limitation and global transmission. Our data furthermore suggest certain geographies are more prone to transmission events and should receive additional attention.

A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome.

The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have been transmitted around the world. The large pool of sequencing data available in public repositories provides an excellent resource for monitoring the temporal and spatial dissemination of AMR in different ecological settings. However, only a limited number of research groups globally have the computational resources to analyze such data. We retrieved 442 Tbp of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive (ENA) and aligned them using a uniform approach against ARGs and 16S/18S rRNA genes. Here, we present the results of this extensive computational analysis and share the counts of reads aligned. Over 6.76∙108 read fragments were assigned to ARGs and 3.21∙109 to rRNA genes, where we observed distinct differences in both the abundance of ARGs and the link between microbiome and resistome compositions across various sampling types. This collection is another step towards establishing global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.

Detection of mobile genetic elements associated with antibiotic resistance in Salmonella enterica using a newly developed web tool: MobileElementFinder.

OBJECTIVES: Antimicrobial resistance (AMR) in clinically relevant bacteria is a growing threat to public health globally. In these bacteria, antimicrobial resistance genes are often associated with mobile genetic elements (MGEs), which promote their mobility, enabling them to rapidly spread throughout a bacterial community. METHODS: The tool MobileElementFinder was developed to enable rapid detection of MGEs and their genetic context in assembled sequence data. MGEs are detected based on sequence similarity to a database of 4452 known elements augmented with annotation of resistance genes, virulence factors and detection of plasmids. RESULTS: MobileElementFinder was applied to analyse the mobilome of 1725 sequenced Salmonella enterica isolates of animal origin from Denmark, Germany and the USA. We found that the MGEs were seemingly conserved according to multilocus ST and not restricted to either the host or the country of origin. Moreover, we identified putative translocatable units for specific aminoglycoside, sulphonamide and tetracycline genes. Several putative composite transposons were predicted that could mobilize, among others, AMR, metal resistance and phosphodiesterase genes associated with macrophage survivability. This is, to our knowledge, the first time the phosphodiesterase-like pdeL has been found to be potentially mobilized into S. enterica. CONCLUSIONS: MobileElementFinder is a powerful tool to study the epidemiology of MGEs in a large number of genome sequences and to determine the potential for genomic plasticity of bacteria. This web service provides a convenient method of detecting MGEs in assembled sequence data. MobileElementFinder can be accessed at https://cge.cbs.dtu.dk/services/MobileElementFinder/.

Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community.

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

The gut microbiome but not the resistome is associated with urogenital schistosomiasis in preschool-aged children.

Helminth parasites have been shown to have systemic effects in the host. Using shotgun metagenomic sequencing, we characterise the gut microbiome and resistome of 113 Zimbabwean preschool-aged children (1-5 years). We test the hypothesis that infection with the human helminth parasite, Schistosoma haematobium, is associated with changes in gut microbial and antimicrobial resistance gene abundance/diversity. Here, we show that bacteria phyla Bacteroidetes, Firmicutes, Proteobacteria, and fungi phyla Ascomycota, Microsporidia, Zoopagomycota dominate the microbiome. The abundance of Proteobacteria, Ascomycota, and Basidiomycota differ between schistosome-infected versus uninfected children. Specifically, infection is associated with increases in Pseudomonas, Stenotrophomonas, Derxia, Thalassospira, Aspergillus, Tricholoma, and Periglandula, with a decrease in Azospirillum. We find 262 AMR genes, from 12 functional drug classes, but no association with individual-specific data. To our knowledge, we describe a novel metagenomic dataset of Zimbabwean preschool-aged children, indicating an association between urogenital schistosome infection and changes in the gut microbiome.

Midbrain expression of Delta-like 1 homologue is regulated by GDNF and is associated with dopaminergic differentiation.

Affymetrix GeneChip technology and quantitative real-time PCR (Q-PCR) were used to examine changes in gene expression in the adult murine substantia nigra pars compacta (SNc) following lentiviral glial cell line-derived neurotrophic factor (GDNF) delivery in adult striatum. We identified several genes that were upregulated after GDNF treatment. Among these, the gene encoding the transmembrane protein Delta-like 1 homologue (Dlk1) was upregulated with a greater than 4-fold increase in mRNA encoding this protein. Immunohistochemistry with a Dlk1-specific antibody confirmed the observed upregulation with increased positive staining of cell bodies in the SNc and fibers in the striatum. Analysis of the developmental regulation of Dlk1 in the murine ventral midbrain showed that the upregulation of Dlk1 mRNA correlated with the generation of tyrosine hydroxylase (TH)-positive neurons. Furthermore, Dlk1 expression was analyzed in MesC2.10 cells, which are derived from embryonic human mesencephalon and capable of undergoing differentiation into dopaminergic neurons. We detected upregulation of Dlk1 mRNA and protein under conditions where MesC2.10 cells differentiate into a dopaminergic phenotype (41.7+/-7.1% Dlk1+ cells). In contrast, control cultures subjected to default differentiation into non-dopaminergic neurons only expressed very few (3.7+/-1.3%) Dlk1-immunopositive cells. The expression of Dlk1 in MesC2.10 cells was specifically upregulated by the addition of GDNF. Thus, our data suggest that Dlk1 expression precedes the appearance of TH in mesencephalic cells and that levels of Dlk1 are regulated by GDNF.