Nanopore-based metagenomics analysis reveals prevalence of mobile antibiotic and heavy metal resistome in wastewater

Ultra pure high molecular weight DNA from soil for Nanopore shotgun metagenomics and metabarcoding sequencing

Soil microbes are among the most abundant and diverse organisms on Earth but remain poorly characterized. New technologies have made possible to sequence the DNA of uncultivated microorganisms in soil and other complex ecosystems. Genome assembly is crucial for understanding their functional potential. Nanopore sequencing technologies allow to sequence long DNA fragments, optimizing production of metagenome-assembled genomes compared to short-read technology. Extracting DNA with a very high purity and high molecular weight is key to get the most out of this long read technologies. Here we present two extraction protocols to get DNA with high purity. First protocol is optimized to reach DNA quality suiting Nanopore shotgun metagenomics. It uses a non-toxic centrifugation gradient to separate bacterial cells from soil to extract DNA directly on cells. The median length of the acquired DNA sequences (N50) was 3 to 7 times greater than previously published in the literature, achieving an N50 of ∼14 kb. The other, a modification of a commercially available MP Biomedical DNA extraction kit, yielded high-purity DNA for full-length 16S Oxford Nanopore metabarcoding, with an N50 of ∼8 kb. The MP-based protocol achieves higher yields of ultra-pure DNA compared to the Nycodenz protocol, at the expense of shorter fragment lengths.

Accelerating enrichment of ARGs and MGEs with increasing ammonium removal during partial nitrification treating high-strength ammonia wastewater

Free ammonia (FA) and free nitrous acid (FNA) are critical operational parameters to maintain partial nitrification (PN) in treating high-strength ammonia wastewater. However, whether FA and FNA, as non-antibiotic antimicrobial chemicals, could directly enhance antibiotic resistance genes (ARGs) enrichment during PN is still unclear. This study deciphered the prevalence of ARGs, potential mobility, and hosts under different ammonium removal efficiencies (ARE) (different FA and FNA) during stable PN. The results showed that when ARE increased from 52.2 ± 6.2 % to 91.8 ± 3.3 %, total abundances of ARGs and mobile gene elements (MGEs) were stepwise increased. In particular, four types of ARGs (aminoglycoside, bacitracin, peptide, and sulfonamide) and six subtypes of ARGs (bacA, ugd, sul2, baeR, aph(3")-I and aph(6)-I) increased with the increasing ARE. Under selection pressures of FA and FNA, plasmids tended to encode aminoglycoside and MLS, while chromosomes had a tendency to carry multidrug, bacitracin, peptide, and fosmidomycin. Furthermore, FA and FNA enhanced the spread of ARGs mediated by the dominated transposase and recombinase. Nitrosomonas dominated the host of ARGs co-occurring with MGEs during the operation of PN. This study highlights the effect of FA and FNA on ARGs and provides theoretical support for the control of ARGs in biological nitrogen removal processes via nitrite pathway.

Proximity-Ligation Metagenomic Sequence Analysis Reveals That the Antibiotic Resistome Makes Significant Transitions During Municipal Wastewater Treatment

Shotgun and proximity-ligation metagenomic sequencing were used to generate thousands of metagenome assembled genomes (MAGs) from the untreated wastewater, activated sludge bioreactors, and anaerobic digesters from two full-scale municipal wastewater treatment facilities. Analysis of the antibiotic resistance genes (ARGs) in the pool of contigs from the shotgun metagenomic sequences revealed significantly different relative abundances and types of ARGs in the untreated wastewaster compared to the activated sludge bioreactors or the anaerobic digesters (p < 0.05). In contrast, these results were statistically similar when comparing the ARGs in the pool of MAGs, suggesting that proximity-ligation metagenomic sequencing is particularly useful for pairing ARGs with their hosts but less adept at discerning quantitative differences in ARG types and relative abundances. For example, numerous MAGs of the genera Acinetobacter, Enterococcus, Klebsiella and Pseudomonas were identified in the untreated wastewater, many of which harboured plasmid-borne and/or chromosomal-borne ARGs; none of these MAGs, however, were detected in the activated sludge bioreactors or anaerobic digesters. In conclusion, this research demonstrates that the antibiotic resistome undergoes significant transitions in both the relative abundance and the host organisms during the municipal wastewater treatment process.

Comparative genomic analysis of ESBL-selected and non-selected Escherichia coli in Australian wastewater: Elucidating differences in diversity, antimicrobial resistance, and virulence profiles

Extended-spectrum β-lactamases (ESBLs)-producing E. coli have been proposed as an indicator bacterium for antimicrobial resistance (AMR) surveillance within a OneHealth framework. However, it is important to understand the effects and potential biases ESBL-selection has on E. coli populations. Utilising whole genome sequencing, this study compared 80 ESBL-selected E. coli isolates with 201 non-selected isolates from Australian wastewater. The findings revealed significant variations between these cohorts in genetic diversity, AMR profiles, and carriage of virulence-associated genes (VAGs), plasmids, and the transmissible Locus of Stress Tolerance (tLST), a genomic island that imparts resistance to extreme heat and chlorination. The study highlights the predominance of certain sequence types (STs), particularly ST131 (75 % clade A), in ESBL-selected isolates (40 % vs 2 %) and overall the ESBL-selected isolates were largely multidrug-resistant (MDR), predominantly carrying genes for resistance to aminoglycosides, extended-spectrum β-lactams, fluoroquinolone, macrolides, sulphonamides/trimethoprim, and tetracyclines. The ESBLs identified were almost exclusively blaCTX-M genes, most commonly blaCTX-M-15 > blaCTX-M-27 > blaCTX-M-14. These were predominately carried on IncF plasmids or chromosomally (always ISEcp1 associated), in equal numbers. In contrast, 80 % of non-selected isolates carried no acquired ARGs, and none carried blaCTX-M genes. In both cohorts, extraintestinal pathogenic E. coli (ExPEC) was the dominate pathotype (35 % total) with few (4 % total) intestinal pathogenic E. coli pathotypes identified (aEPEC > ETEC > EAEC). Nevertheless, some clinically important genes were only identified in the non-selected group, namely tigecycline-resistance gene tet(X4) and AmpC ESBL blaCMY-2. Additionally, the presence of tLST, associated with higher metal resistance gene carriage (Ag, As, Cu, Hg, Ni), in a substantial portion of non-selected isolates (20 % vs 0 %), underscores environmental pressures shaping bacterial populations in wastewater ecosystems. These insights are important for developing comprehensive, less biased genomic surveillance strategies to understand and manage public health threats posed by pathogenic E. coli and AMR.

Comparative assessment of microbiome and resistome of influent and effluent of sewage treatment plant and common effluent treatment plant located in Delhi, India using shotgun approach

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%-16%), aminoglycosides (7%-9%), multi-drug (5%-9%), and rifampin (3%-9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance.

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances.

IMPORTANCE

Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities

Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.

Sequence-based Functional Metagenomics Reveals Novel Natural Diversity of Functional CopA in Environmental Microbiomes

Exploring the natural diversity of functional genes/proteins from environmental DNA in high throughput remains challenging. In this study, we developed a sequence-based functional metagenomics procedure for mining the diversity of copper (Cu) resistance gene copA in global microbiomes, by combining the metagenomic assembly technology, local BLAST, evolutionary trace analysis (ETA), chemical synthesis, and conventional functional genomics. In total, 87 metagenomes were collected from a public database and subjected to copA detection, resulting in 93,899 hits. Manual curation of 1214 hits of high confidence led to the retrieval of 517 unique CopA candidates, which were further subjected to ETA. Eventually, 175 novel copA sequences of high quality were discovered. Phylogenetic analysis showed that almost all these putative CopA proteins were distantly related to known CopA proteins, with 55 sequences from totally unknown species. Ten novel and three known copA genes were chemically synthesized for further functional genomic tests using the Cu-sensitive Escherichia coli (ΔcopA). The growth test and Cu uptake determination showed that five novel clones had positive effects on host Cu resistance and uptake. One recombinant harboring copA-like 15 (copAL15) successfully restored Cu resistance of the host with a substantially enhanced Cu uptake. Two novel copA genes were fused with the gfp gene and expressed in E. coli for microscopic observation. Imaging results showed that they were successfully expressed and their proteins were localized to the membrane. The results here greatly expand the diversity of known CopA proteins, and the sequence-based procedure developed overcomes biases in length, screening methods, and abundance of conventional functional metagenomics.

A Comprehensive Review for the Surveillance of Human Pathogenic Microorganisms in Shellfish

Bivalve molluscan shellfish have been consumed for centuries. Being filter feeders, they may bioaccumulate some microorganisms present in coastal water, either naturally or through the discharge of human or animal sewage. Despite regulations set up to avoid microbiological contamination in shellfish, human outbreaks still occur. After providing an overview showing their implication in disease, this review aims to highlight the diversity of the bacteria or enteric viruses detected in shellfish species, including emerging pathogens. After a critical discussion of the available methods and their limitations, we address the interest of technological developments using genomics to anticipate the emergence of pathogens. In the coming years, further research needs to be performed and methods need to be developed in order to design the future of surveillance and to help risk assessment studies, with the ultimate objective of protecting consumers and enhancing the microbial safety of bivalve molluscan shellfish as a healthy food.

Globally distributed mining-impacted environments are underexplored hotspots of multidrug resistance genes

Mining is among the human activities with widest environmental impacts, and mining-impacted environments are characterized by high levels of metals that can co-select for antibiotic resistance genes (ARGs) in microorganisms. However, ARGs in mining-impacted environments are still poorly understood. Here, we conducted a comprehensive study of ARGs in such environments worldwide, taking advantage of 272 metagenomes generated from a global-scale data collection and two national sampling efforts in China. The average total abundance of the ARGs in globally distributed studied mine sites was 1572 times per gigabase, being rivaling that of urban sewage but much higher than that of freshwater sediments. Multidrug resistance genes accounted for 40% of the total ARG abundance, tended to co-occur with multimetal resistance genes, and were highly mobile (e.g. on average 16% occurring on plasmids). Among the 1848 high-quality metagenome-assembled genomes (MAGs), 85% carried at least one multidrug resistance gene plus one multimetal resistance gene. These high-quality ARG-carrying MAGs considerably expanded the phylogenetic diversity of ARG hosts, providing the first representatives of ARG-carrying MAGs for the Archaea domain and three bacterial phyla. Moreover, 54 high-quality ARG-carrying MAGs were identified as potential pathogens. Our findings suggest that mining-impacted environments worldwide are underexplored hotspots of multidrug resistance genes.

Metagenomic Analysis of Urban Wastewater Treatment Plant Effluents in Tokyo

Purpose

Urban wastewater treatment plant (WWTP) effluents, even with proper treatment, may cause antimicrobial resistance (AMR) burden, with a high frequency of acquired antimicrobial resistance genes (ARGs). The dissemination of ARGs into the environment increases the risk of infectious diseases; however, there is little direct evidence regarding their epidemiological effects. This study aimed to assess effluents from urban WWTPs around the Tama River and Tokyo Bay using metagenomic analysis of (AMR) genes (ARGs) and heavy-metal resistance genes.

Methods

Metagenomic DNA-seq analysis of water samples and resistome analysis were performed.

Results

The most prevalent ARG was the sulfonamide resistance gene, sul1, followed by the quaternary ammonium compound resistance gene, qacE, suggesting that basic gene sets (sul1 and ∆qacE) in the class 1 integrons are the predominant ARGs. The aminoglycoside resistance genes, aadA and aph, and macrolide resistance genes, msr(E) and mph(E), were the predominant ARGs against each antimicrobial. bla _OXA and bla _GES were frequently detected, whereas the bla _CTX-M cluster was faintly detected. Non-metric multidimensional scaling plot analysis and canonical correspondence analysis results suggested that marked differences in ARGs could be involved in the seasonal differences; qnrS2, aac(6')-Ib, and mef(C) increased markedly in summer, whereas msr(E) was more frequently detected in winter. Heavy-metal (Hg and Cu) resistance genes (HMRGs) were significantly detected in effluents from all WWTPs.

Conclusion

We characterized a baseline level of the environmental ARG/HMRG profile in the overall community, suggesting that environmental AMR surveillance, particularly in urban WWTPs, is a valuable first step in monitoring the AMR dissemination of bacteria from predominantly healthy individuals carrying notable ARG/Bs.

Occurrence of antibiotic resistance genes and multidrug-resistant bacteria during wastewater treatment processes

Wastewater treatment plants (WWTPs) constantly receive a wide variety of contaminants, including pharmaceuticals, and are potential reservoirs of antibiotic resistance genes (ARGs). This favors the development of multidrug-resistant bacteria (MRB) through horizontal gene transfer. Samples from five different WWTP processes were collected in September 2020 and January 2021 to monitor ARG resistomes and culturable MRB in the presence of eight different antibiotics. Nanopore-based ARG abundance and bacterial community analyses suggested that ARG accumulation favors the generation of MRB. Activated and mixed sludges tended to have lower bacterial diversity and ARG abundance because of selective forces that favored the growth of specific microorganisms during aeration processes. Escherichia strains enriched in WWTPs (up to 71%) were dominant in all the samples, whereas Cloacamonas species were highly abundant only in anaerobically digested sludge samples (60%-79%). Two ARG types [sulfonamide resistance genes (sul1) and aminoglycoside resistance genes (aadA1, aadA13, and aadA2)] were prevalent in all the processes. The total counts of culturable MRB, such as Niabella, Enterococcus, Bacillus, and Chryseobacterium species, gradually increased during aerobic WWTP processes. Genomic analyses of all MRB isolated from the samples revealed that the resistome of Enterococcus species harbored the highest number of ARGs (7-18 ARGs), commonly encoding ant(6)-la, lnu(B), erm(B), and tet(S/M). On the other hand, Niablella strains possibly had intrinsic resistant phenotypes without ARGs. All MRB possessed ARGs originating from the same mobile genetic elements, suggesting that WWTPs are hotspots for the migration of ARGs and emergence of MRB.

Occurrence and removal of antibiotics, antibiotic resistance genes, and bacterial communities in hospital wastewater

Hospital wastewater contains a variety of human antibiotics and pathogens, which makes the treatment of hospital wastewater essential. However, there is a lack of research on these pollutants at hospital wastewater treatment plants. In this study, the characteristics and removal of antibiotics and antibiotic resistance genes (ARGs) in the independent treatment processes of hospitals of different scales (primary hospital, H1; secondary hospital, H2; and tertiary hospital, H3) were investigated. The occurrence of antibiotics and ARGs in wastewater from three hospitals varied greatly. The first-generation cephalosporin cefradine was detected at a concentration of 2.38 μg/L in untreated wastewater from H1, while the fourth-generation cephalosporin cefepime had the highest concentration, 540.39 μg/L, at H3. Ofloxacin was detected at a frequency of 100% and had removal efficiencies of 44.2%, 51.5%, and 81.6% at H1, H2, and H3, respectively. The highest relative abundances of the β-lactam resistance gene bla_GES-1 (1.77×10^-3 copies/16S rRNA), the quinolone resistance gene qnrA (8.81×10^-6 copies/16S rRNA), and the integron intI1 (1.86×10^-4 copies/16S rRNA) were detected in the treated wastewater. The concentrations of several ARGs were increased in the treated wastewater (e.g. bla_OXA-1, bla_OXA-10, and bla_TEM-1). Several pathogenic or opportunistic bacteria (e.g. Acinetobacter, Klebsiella, Aeromonas, and Pseudomonas) were observed at high relative abundances in the treated wastewater. These results suggested the co-occurrence of antibiotics, ARGs, and antibiotic-resistant pathogens in hospital wastewater, and these factors may spread into the receiving aquatic environment.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.