A Peek into the Plasmidome of Global Sewage

Deciphering antibiotic resistance genes and plasmids in pathogenic bacteria from 166 hospital effluents in Shanghai, China

Although previous studies using phenotypic or metagenomic approaches have revealed the patterns of antibiotic resistance genes (ARGs) in hospital effluents in local regions, limited information is available regarding the antibiotic resistome and plasmidome in human pathogenic bacteria in hospital effluents of megacity in China. To address this knowledge gap, we analyzed effluent samples from 166 hospitals across 13 geographical districts in Shanghai, China, using both cultivation-based approaches and metagenomics. A total of 357 strains were isolated from these samples, with the predominant species being Escherichia coli (n = 61), Aeromonas hydrophila (n = 57), Klebsiella pneumoniae (n = 48), and Aeromonas caviae (n = 42). Those identified indicator bacteria were classified into biosafety level 1 (BSL-1, 60 %) and BSL-2 (40 %). We identified 1237 ARG subtypes across 22 types, predominantly including beta-lactam, tetracycline, multidrug, polymyxin, and aminoglycoside resistance genes, using culture-enriched phenotypic metagenomics. Mobile genetic elements such as plasmids, transposons (tnpA), integrons (intI1), and insertion sequences (IS91) were abundant. We recovered 135 plasmids classified into mobilizable (n = 94) and non-mobilizable (n = 41) types. Additionally, 80 metagenome-assembled genomes (MAGs) were reconstructed from the hospital effluents for the assessment of ARG transmission risks, including genes for last-line antibiotics such as blaNDM, blaKPC, blaimiH, and mcr. This study is the first to comprehensively characterize and assess the risk of antimicrobial resistance levels and plasmidome in the hospital effluents of China's megacity, providing city-wide surveillance data and evidence to inform public health interventions.

CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range

In recent years, there has been a surge in metagenomic studies focused on identifying plasmids in environmental samples. Although these studies have unearthed numerous novel plasmids, enriching our understanding of their environmental roles, a significant gap remains: the scarcity of information regarding the bacterial hosts of these newly discovered plasmids. Furthermore, even when plasmids are identified within bacterial isolates, the reported host is typically limited to the original isolate, with no insights into alternative hosts or the plasmid's potential host range. Given that plasmids depend on hosts for their existence, investigating plasmids without the knowledge of potential hosts offers only a partial perspective. This study introduces a method for identifying potential hosts and host ranges for plasmids through alignment with CRISPR spacers. To validate the method, we compared the PLSDB plasmids database with the CRISPR spacers database, yielding host predictions for 46% of the plasmids. When compared with reported hosts, our predictions achieved 84% concordance at the family level and 99% concordance at the phylum level. Moreover, the method frequently identified multiple potential hosts for a plasmid, thereby enabling predictions of alternative hosts and the host range. Notably, we found that CRISPR spacers predominantly target plasmid backbone genes while sparing functional genes, such as those linked to antibiotic resistance, aligning with our hypothesis that CRISPR spacers are acquired from plasmid-specific regions rather than insertion elements from diverse sources. Finally, we illustrate the network of connections among different bacterial taxa through plasmids, revealing potential pathways for horizontal gene transfer.IMPORTANCEPlasmids are notorious for their role in distributing antibiotic resistance genes, but they may also carry and distribute other environmentally important genes. Since plasmids are not free-living entities and rely on host bacteria for survival and propagation, predicting their hosts is essential. This study presents a method for predicting potential hosts for plasmids and offers insights into the potential paths for spreading functional genes between different bacteria. Understanding plasmid-host relationships is crucial for comprehending the ecological and clinical impact of plasmids and implications for various biological processes.

Integrative genomics would strengthen AMR understanding through ONE health approach

Emergence of drug-induced antimicrobial resistance (AMR) forms a crippling health and economic crisis worldwide, causing high mortality from otherwise treatable diseases and infections. Next Generation Sequencing (NGS) has significantly augmented detection of culture independent microbes, potential AMR in pathogens and elucidation of mechanisms underlying it. Here, we review recent findings of AMR evolution in pathogens aided by integrated genomic investigation strategies inclusive of bacteria, virus, fungi and AMR alleles. While AMR monitoring is dominated by data from hospital-related infections, we review genomic surveillance of both biotic and abiotic components involved in global AMR emergence and persistence. Identification of pathogen-intrinsic as well as environmental and/or host factors through robust genomics/bioinformatics, along with monitoring of type and frequency of antibiotic usage will greatly facilitate prediction of regional and global patterns of AMR evolution. Genomics-enabled AMR prediction and surveillance will be crucial - in shaping health and economic policies within the One Health framework to combat this global concern.

PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning

Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be difficult to identify plasmid sequences from chromosomal sequences in genomic and metagenomic data. Here, we have developed a new tool called PlasmidHunter, which uses machine learning to predict plasmid sequences based on gene content profile. PlasmidHunter can achieve high accuracies (up to 97.6%) and high speeds in benchmark tests including both simulated contigs and real metagenomic plasmidome data, outperforming other existing tools.

Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes

Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.

Integrating global microbiome data into antibiotic resistance assessment in large rivers

Rivers are important in spreading antimicrobial resistance (AMR). Assessing AMR risk in large rivers is challenged by large spatial scale and numerous contamination sources. Integrating river resistome data into a global framework may help addressing this difficulty. Here, we conducted an omics-based assessment of AMR in a large river (i.e. the Pearl River in China) with global microbiome data. Results showed that antibiotic resistome in river water and sediment was more diversified than that in other rivers, with contamination levels in some river reaches higher than global baselines. Discharge of WWTP effluent and landfill waste drove AMR prevalence in the river, and the resistome level was highly associated with human and animal sources. Detection of 54 risk rank I ARGs and emerging mobilizable mcr and tet(X) highlighted AMR risk in the river reaches with high human population density and livestock pollution. Florfenicol-resistant floR therein deserved priority concerns due to its high detection frequency, dissimilar phylogenetic distance, mobilizable potential, and presence in multiple pathogens. Co-sharing of ARGs across taxonomic ranks implied their transfer potentials in the community. By comparing with global genomic data, we found that Burkholderiaceae, Enterobacteriaceae, Moraxellaceae and Pseudomonadaceae were important potential ARG-carrying bacteria in the river, and WHO priority carbapenem-resistant Enterobacteriaceae, A. baumannii and P. aeruginosa should be included in future surveillance. Collectively, the findings from this study provide an omics-benchmarked assessment strategy for public risk associated with AMR in large rivers.

Mixed waste contamination selects for a mobile genetic element population enriched in multiple heavy metal resistance genes

Mobile genetic elements (MGEs) like plasmids, viruses, and transposable elements can provide fitness benefits to their hosts for survival in the presence of environmental stressors. Heavy metal resistance genes (HMRGs) are frequently observed on MGEs, suggesting that MGEs may be an important driver of adaptive evolution in environments contaminated with heavy metals. Here, we report the meta-mobilome of the heavy metal-contaminated regions of the Oak Ridge Reservation subsurface. This meta-mobilome was compared with one derived from samples collected from unimpacted regions of the Oak Ridge Reservation subsurface. We assembled 1615 unique circularized DNA elements that we propose to be MGEs. The circular elements from the highly contaminated subsurface were enriched in HMRG clusters relative to those from the nearby unimpacted regions. Additionally, we found that these HMRGs were associated with Gamma and Betaproteobacteria hosts in the contaminated subsurface and potentially facilitate the persistence and dominance of these taxa in this region. Finally, the HMRGs were associated with conjugative elements, suggesting their potential for future lateral transfer. We demonstrate how our understanding of MGE ecology, evolution, and function can be enhanced through the genomic context provided by completed MGE assemblies.

Sequencing-based analysis of the microbiomes of Spanish food processing facilities reveals environment-specific variation in the dominant taxa and antibiotic resistance genes

In the last years, advances in high throughput sequencing technologies have opened the possibility to broaden environmental monitoring activities in facilities processing food, offering expanded opportunities for characterizing in an untargeted manner the microbiome and resistome of foods and food processing environments (FPE) with huge potential benefits in food safety management systems. Here the microbiome and resistome of FPE from slaughterhouses (n = 3), dairy (n = 12) and meat (n = 10) processing plants were assessed through whole metagenome sequencing of 2 composite samples for each facility, comprising 10 FPE swabs taken from food contact surfaces and 10 FPE samples from non-food contact surfaces, respectively. FPE from slaughterhouses had more diverse microbiomes and resistomes, while FPE from dairy processing plants showed the highest β-dispersion, consistent with a more heterogeneous microbiome and resistome composition. The predominant bacterial genera depended on the industry type, with Pseudomonas and Psychrobacter being highly dominant in surfaces from slaughterhouses and meat industries, while different lactic acid bacteria predominated in dairy industries. The most abundant antimicrobial resistance genes (ARG) found were associated with resistance to aminoglycosides, tetracyclines and quaternary ammonium compounds (QAC). ARGs relating to resistance to aminoglycosides and tetracyclines were significantly more prevalent in slaughterhouses than in food processing plants, while QAC resistance genes were particularly abundant in some food contact surfaces from dairy and meat processing plants, suggesting that daily sanitation under suboptimal conditions may be selecting for persistent microbiota tolerant to these biocides in some facilities. The taxonomic mapping of ARG pointed to specific bacterial genera, such as Escherichia, Bacillus, or Staphylococcus, as carriers of the most relevant resistance determinants. About 63% of all ARG reads were assigned to contigs classified as plasmid-associated, indicating that the resistome of FPE may be strongly shaped through the spread of mobile genetic elements. Overall, the relevance of FPE as reservoirs of ARG was confirmed and it was demonstrated that next generation sequencing technologies allowing a deep characterisation of sources and routes of spread of microorganisms and antimicrobial resistance determinants in food industry settings hold promise to be integrated in monitoring and food safety management programmes.

Virulence potential of antimicrobial-resistant extraintestinal pathogenic Escherichia coli from retail poultry meat in a Caenorhabditis elegans model

Healthy poultry can be a reservoir for extraintestinal pathogenic Escherichia coli (ExPEC), some of which could be multidrug resistant to antimicrobials. These ExPEC strains could contaminate the environment and/or food chain representing thus, food safety and human health risk. However, few studies have shown the virulence of poultry-source antimicrobial-resistant (AMR) ExPEC in humans. This study characterized AMR ExPEC and investigated the virulence potential of some of their isolates in a Caenorhabditis elegans infection model. A total of 46 E. coli isolates from poultry (chicken, n = 29; turkey, n = 12) retail meats and chicken feces (n = 4), or humans (n = 1) were sequenced and identified as ExPEC. Except eight, all remaining 38 ExPEC isolates were resistant to at least one antibiotic and carried corresponding antimicrobial resistance genes (ARGs). About 27 of the 46 ExPEC isolates were multidrug-resistant (≥3 antibiotic classes). Seven ExPEC isolates from chicken or turkey meats were of serotype O25:H4 and sequence type (ST) 131 which clustered with an isolate from a human urinary tract infection (UTI) case having the same serotype and ST. The C. elegans challenge model using eight of studied ExPEC isolates harboring various ARGs and virulence genes (VGs) showed that regardless of their ARG or VG numbers in tested poultry meat and feces, ExPEC significantly reduced the life span of the nematode (P < 0.05) similarly to a human UTI isolate. This study indicated the pathogenic potential of AMR ExPEC from retail poultry meat or feces, but more studies are warranted to establish their virulence in poultry and human. Furthermore, relationships between specific resistance profiles and/or VGs in these E. coli isolates for their pathogenicity deserve investigations.

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.

Global Distribution and Diversity of Prevalent Sewage Water Plasmidomes

Sewage water from around the world contains an abundance of short plasmids, several of which harbor antimicrobial resistance genes (ARGs). The global dynamics of plasmid-derived antimicrobial resistance and functions are only starting to be unveiled. Here, we utilized a previously created data set of 159,332 assumed small plasmids from 24 different global sewage samples. The detailed phylogeny, as well as the interplay between their protein domains, ARGs, and predicted bacterial host genera, were investigated to understand sewage plasmidome dynamics globally. A total of 58,429 circular elements carried genes encoding plasmid-related features, and MASH distance analyses showed a high degree of diversity. A single (yet diverse) cluster of 520 predicted Acinetobacter plasmids was predominant among the European sewage water. Our results suggested a prevalence of plasmid-backbone gene combinations over others. This could be related to selected bacterial genera that act as bacterial hosts. These combinations also mirrored the geographical locations of the sewage samples. Our functional domain network analysis identified three groups of plasmids. However, these backbone domains were not exclusive to any given group, and Acinetobacter was the dominant host genus among the theta-replicating plasmids, which contained a reservoir of the macrolide resistance gene pair msr(E) and mph(E). Macrolide resistance genes were the most common in the sewage plasmidomes and were found in the largest number of unique plasmids. While msr(E) and mph(E) were limited to Acinetobacter, erm(B) was disseminated among a range of Firmicutes plasmids, including Staphylococcus and Streptococcus, highlighting a potential reservoir of antibiotic resistance for these pathogens from around the globe. IMPORTANCE Antimicrobial resistance is a global threat to human health, as it inhibits our ability to treat infectious diseases. This study utilizes sewage water plasmidomes to identify plasmid-derived features and highlights antimicrobial resistance genes, particularly macrolide resistance genes, as abundant in sewage water plasmidomes in Firmicutes and Acinetobacter hosts. The emergence of macrolide resistance in these bacteria suggests that macrolide selective pressure exists in sewage water and that the resident bacteria can readily acquire macrolide resistance via small plasmids.

Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo

To characterize environmental antimicrobial resistance (AMR) in urban areas, extended-spectrum β-lactamase- (ESBL)/carbapenemase-producing bacteria (EPB/CPB, respectively) from urban wastewater treatment plant effluents in Tokyo were isolated on CHROMagar ESBL plate. Complete genome sequence analysis, including plasmids, indicated that 126 CTX-M-positive isolates (31%) were identified among the 404 obtained isolates. The CTX-M-9 group was predominant (n = 65, 52%), followed by the CTX-M-1 group (n = 44, 35%). Comparative genome analysis revealed that CTX-M-27-positive E. coli O16:H5-ST131-fimH41 exhibited a stable genome structure and clonal-global dissemination. Plasmidome network analysis revealed that 304 complete plasmid sequences among 85 isolates were grouped into 14 incompatibility (Inc) network communities (Co1 to Co14). Co10 consisted of primarily IncFIA/IncFIB plasmids harboring bla_CTX-M in E. coli, whereas Co12 consisted primarily of IncFIA(HI1)/Inc FIB(K) plasmids harboring bla_CTX-M, bla_KPC, and bla_GES in Klebsiella spp. Co11 was markedly located around Co10 and Co12. Co11 exhibited bla_CTX-M, bla_KPC, and bla_NDM, and was mainly detected in E. coli and Klebsiella spp. from human and animal sources, suggesting a mutual role of Co11 in horizontal gene transfer between E. coli and Klebsiella spp. This comprehensive resistome analysis uncovers the mode of relational transfer among bacterial species, highlighting the potential source of AMR burden on public health in urban communities.

Organizing the Global Diversity of Microviruses

Microviruses encompass an astonishing array of small, single-stranded DNA phages that, due to the surge in metagenomic surveys, are now known to be prevalent in most environments. Current taxonomy concedes the considerable diversity within this lineage to a single family (the Microviridae), which has rendered it difficult to adequately and accurately assess the amount of variation that actually exists within this group. We amassed and curated the largest collection of microviral genomes to date and, through a combination of protein-sharing networks and phylogenetic analysis, discovered at least three meaningful taxonomic levels between the current ranks of family and genus. When considering more than 13,000 microviral genomes from recognized lineages and as-yet-unclassified microviruses in metagenomic samples, microviral diversity is better understood by elevating microviruses to the level of an order that consists of three suborders and at least 19 putative families, each with their respective subfamilies. These revisions enable fine-scale assessment of microviral dynamics: for example, in the human gut, there are considerable differences in the abundances of microviral families both between urban and rural populations and in individuals over time. In addition, our analysis of genome contents and gene exchange shows that microviral families carry no recognizable accessory metabolic genes and rarely, if ever, engage in horizontal gene transfer across microviral families or with their bacterial hosts. These insights bring microviral taxonomy in line with current developments in the taxonomy of other phages and increase the understanding of microvirus biology.

Characterization of Carbapenem-Resistant Enterobacteriaceae Cultured From Retail Meat Products, Patients, and Porcine Excrement in China

The emergence and dissemination of carbapenem-resistant Enterobacteriaceae (CRE) is a growing concern to animal and public health. However, little is known about the spread of CRE in food and livestock and its potential transmission to humans. To identify CRE strains from different origins and sources, 53 isolates were cultured from 760 samples including retail meat products, patients, and porcine excrement. Antimicrobial susceptibility testing was carried out, followed by phylogenetic typing, whole-genome sequencing, broth mating assays, and plasmids analyses. Forty-three Escherichia coli, nine Klebsiella pneumoniae, and one Enterobacter cloacae isolates were identified, each exhibiting multidrug-resistant phenotypes. Genetically, the main sequence types (STs) of E. coli were ST156 (n = 7), ST354 (n = 7), and ST48 (n = 7), and the dominant ST of K. pneumoniae is ST11 (n = 5). bla_NDM–5 (n = 40) of E. coli and bla_KPC–2 (n = 5) were the key genes that conferred carbapenem resistance phenotypes in these CRE strains. Additionally, the mcr-1 gene was identified in 17 bla_NDM-producing isolates. The bla_NDM–5 gene from eight strains could be transferred to the recipients via conjugation assays. Two mcr-1 genes in the E. coli isolates could be co-transferred along with the bla_NDM–5 genes. IncF and IncX3 plasmids have been found to be predominantly associated with bla_NDM gene in these strains. Strains isolated in our study from different sources and regions tend to be concordant and overlap. CRE strains from retail meat products are a reservoir for transition of CRE strains between animals and humans. These data also provide evidence of the dissemination of CRE strains and carbapenem-resistant genes between animal and human sources.