MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage

Application of high-throughput sequencing technologies and analytical tools for pathogen detection in urban water systems: Progress and future perspectives

The ubiquitous presence of pathogenic microorganisms, such as viruses, bacteria, fungi, and protozoa, in urban water systems poses a significant risk to public health. The emergence of infectious waterborne diseases mediated by urban water systems has become one of the leading global causes of mortality. However, the detection and monitoring of these pathogenic microorganisms have been limited by the complexity and diversity in the environmental samples. Conventional methods were restricted by long assay time, high benchmarks of identification, and narrow application sceneries. Novel technologies, such as high-throughput sequencing technologies, enable potentially full-spectrum detection of trace pathogenic microorganisms in complex environmental matrices. This review discusses the current state of high-throughput sequencing technologies for identifying pathogenic microorganisms in urban water systems with a concise summary. Furthermore, future perspectives in pathogen research emphasize the need for detection methods with high accuracy and sensitivity, the establishment of precise detection standards and procedures, and the significance of bioinformatics software and platforms. We have compiled a list of pathogens analysis software/platforms/databases that boast robust engines and high accuracy for preference. We highlight the significance of analyses by combining targeted and non-targeted sequencing technologies, short and long reads technologies, sequencing technologies, and bioinformatic tools in pursuing upgraded biosafety in urban water systems.

Detection of Biological Molecules Using Nanopore Sensing Techniques

Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.

Microbial Water Quality Assessment of Private Wells Using 16S rRNA Gene Amplicon Sequencing with a Nanopore Sequencer

Private wells are used daily worldwide as convenient household water sources. In Japan, where water supply coverage is high, well water is occasionally used for non-potable purposes, such as irrigation and watering. Currently, the main microbiological test of well water is designed to detect Escherichia coli, which is an indicator of fecal contamination, using culture methods. Water use such as watering generates bioaerosols, which may cause airborne infection. However, many causative bacteria of aerosol-derived infections, such as Legionella spp., are difficult to detect using culture methods. Thus, more comprehensive modern assessment is desirable for securing the microbiological quality of well water. Here, the bacterial community structure of five private wells located in different environments was examined using the rapid and portable MinION sequencer, which enabled us to identify bacteria to the species level based on full-length 16S ribosomal RNA (rRNA) gene sequences. The results revealed the differences in the bacterial community structures of water samples from the five wells and detected Legionella pneumophila and Aeromonas hydrophila as new candidate microbial indicators. The comprehensive analysis method used in this study successfully detected bacteria causing opportunistic infections, which are difficult to detect by conventional methods. This approach is expected to be routinely applied in the future as a highly accurate method for assessing the microbiological quality of private well water.

Strategies and tools in illumina and nanopore-integrated metagenomic analysis of microbiome data

Metagenomic strategy serves as the foundation for the ecological exploration of novel bioresources (e.g., industrial enzymes and bioactive molecules) and biohazards (e.g., pathogens and antibiotic resistance genes) in natural and engineered microbial systems across multiple disciplines. Recent advancements in sequencing technology have fostered rapid development in the field of microbiome research where an increasing number of studies have applied both illumina short reads (SRs) and nanopore long reads (LRs) sequencing in their metagenomic workflow. However, given the high complexity of an environmental microbiome data set and the bioinformatic challenges caused by the unique features of these sequencing technologies, integrating SRs and LRs is not as straightforward as one might assume. The fast renewal of existing tools and growing diversity of new algorithms make access to this field even more difficult. Therefore, here we systematically summarized the complete workflow from DNA extraction to data processing strategies for applying illumina and nanopore-integrated metagenomics in the investigation in environmental microbiomes. Overall, this review aims to provide a timely knowledge framework for researchers that are interested in or are struggling with the SRs and LRs integration in their metagenomic analysis. The discussions presented will facilitate improved ecological understanding of community functionalities and assembly of natural, engineered, and human microbiomes, benefiting researchers from multiple disciplines.

Antibiotic and metal resistance of Stenotrophomonas maltophilia isolates from Eboling permafrost of the Tibetan Plateau

Whole-genome sequencing of pathogenic bacteria Stenotrophomonas maltophilia from a less polluted environment of permafrost can help understand the intrinsic resistome of both antibiotics and metals. This study aimed to examine the maximum minimum inhibitory concentration (MIC) of both antibiotics and metals, as well as antibiotic resistance genes and metal resistance genes annotated from whole-genome sequences. The permafrost S. maltophilia was sensitive to ciprofloxacin, tetracycline, streptomycin, and bacitracin, and resistant to chloramphenicol, trimethoprim-sulfamethoxazole, erythromycin, Zn²⁺, Ni²⁺, Cu²⁺, and Cr⁶⁺, with a lower maximum MIC, compared with clinical S. maltophilia. The former strain belonged to the lower antibiotic resistance gene (ARG) and metal resistance gene (MRG) clusters compared with the latter ones. The permafrost strain contained no or only one kind of ARG or MRG on a single genomic island, which explained the aforementioned lower maximum MIC and less diversity of ARGs or MRGs. The result indicated that the co-occurrence of antibiotic and metal resistance was due to a certain innate ability of S. maltophilia. The continuous human use of antibiotics or metals induced selective pressure, resulting in higher MIC and more diverse ARGs and MRGs in human-impacted environments.

Florfenicol and oxazolidone resistance status in livestock farms revealed by short- and long-read metagenomic sequencing

Antibiotic resistance genes (ARGs) as a novel type of environmental pollutant pose a health risk to humans. Oxazolidinones are one of the most important antibiotics for the treatment of Gram-positive bacterial infections in humans. Although oxazolidinones are not utilized in the livestock industry, florfenicol is commonly used on farms to treat bacterial infections, which may contribute to the spread of the cfr, optrA, and poxtA genes on farms. Using metagenomics sequencing, we looked into the antibiotic resistome context of florfenicol and oxazolidinone in 10 large-scale commercial farms in China. We identified 490 different resistance genes and 1,515 bacterial genera in the fecal samples obtained from 10 farms. Florfenicol-resistant Kurthia, Escherichia, and Proteus were widely present in these samples. The situation of florfenicol and oxazolidone resistance in pig farms is even more severe. The total number of genes and the abundance of drug resistance genes were higher in pigs than in chickens, including optrA and poxtA. All the samples we collected had a high abundance of fexA and floR. Through nanopore metagenomic analysis of the genetic environment, we found that plasmids, integrative and conjugative element (ICE), and transposons (Tn7-like and Tn558) may play an important role in the spread of floR, cfr, and optrA. Our findings suggest that florfenicol and oxazolidinone resistance genes have diverse genetic environments and are at risk of co-transmission with, for example, tetracycline and aminoglycoside resistance genes. The spread of florfenicol- and oxazolidinone-resistant bacteria on animal farms should be continuously monitored.

Metagenomic Analysis Reveals Changes in Bacterial Communities and Antibiotic Resistance Genes in an Eye Specialty Hospital and a General Hospital Before and After Wastewater Treatment

The spread of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in hospital wastewater poses a great threat to public health, and wastewater treatment plants (WWTPs) play an important role in reducing the levels of ARB and ARGs. In this study, high-throughput metagenomic sequencing was used to analyze the bacterial community composition and ARGs in two hospitals exposed to different antibiotic use conditions (an eye specialty hospital and a general hospital) before and after wastewater treatment. The results showed that there were various potential pathogenic bacteria in the hospital wastewater, and the abundance and diversity of the influent ARGs in the general hospital were higher than those in the eye hospital. The influent of the eye hospital was mainly composed of Thauera and Pseudomonas, and sul1 (sulfonamide) was the most abundant ARG. The influent of the general hospital contained mainly Aeromonas and Acinetobacter, and tet39 (tetracycline) was the most abundant ARG. Furthermore, co-occurrence network analysis showed that the main bacteria carrying ARGs in hospital wastewater varied with hospital type; the same bacteria in wastewater from different hospitals could carry different ARGs, and the same ARG could also be carried by different bacteria. The changes in the bacterial community and ARG abundance in the effluent from the two hospitals showed that the activated sludge treatment and the direct chlorination disinfection can effectively remove some bacteria and ARGs in wastewater but have limitations. The species diversity increased significantly after the activated sludge treatment, while the direct chlorination disinfection did not increase the diversity. The activated sludge treatment has a better effect on the elimination of ARGs than the direct chlorination disinfection. In summary, we investigated the differences in bacterial communities and ARGs in wastewater from two hospitals exposed to different antibiotic usage conditions, evaluated the effects of different wastewater treatment methods on the bacterial communities and ARGs in hospital wastewater, and recommended appropriate methods for certain clinical environments.

Application of MinION Amplicon Sequencing to Buccal Swab Samples for Improving Resolution and Throughput of Rumen Microbiota Analysis

The Illumina MiSeq platform has been widely used as a standard method for studying the rumen microbiota. However, the low resolution of taxonomic identification is the only disadvantage of MiSeq amplicon sequencing, as it targets a part of the 16S rRNA gene. In the present study, we performed three experiments to establish a high-resolution and high-throughput rumen microbial profiling approach using a combination of MinION platform and buccal swab sample, which is a proxy for rumen contents. In experiment 1, rumen contents and buccal swab samples were collected simultaneously from cannulated cattle (n = 6) and used for microbiota analysis using three different analytical workflows: amplicon sequencing of the V3–V4 region of the 16S rRNA gene using MiSeq and amplicon sequencing of near full-length 16S rRNA gene using MinION or PacBio Sequel II. All reads derived from the MinION and PacBio platforms were classified at the species-level. In experiment 2, rumen fluid samples were collected from beef cattle (n = 28) and used for 16S rRNA gene amplicon sequencing using the MinION platform to evaluate this sequencing platform for rumen microbiota analysis. We confirmed that the MinION platform allowed species-level taxa assignment for the predominant bacterial groups, which were previously identified at the family- and genus-level using the MiSeq platform. In experiment 3, buccal swab samples were collected from beef cattle (n = 30) and used for 16S rRNA gene amplicon sequencing using the MinION platform to validate the applicability of a combination of the MinION platform and buccal swab samples for rumen microbiota analysis. The distribution of predominant bacterial taxa in the buccal swab samples was similar to that in the rumen samples observed in experiment 2. Based on these results, we concluded that the combination of the MinION platform and buccal swab samples may be potentially applied for rumen microbial analysis in large-scale studies.

Long-read metagenomic sequencing reveals shifts in associations of antibiotic resistance genes with mobile genetic elements from sewage to activated sludge

BACKGROUND

There is concern that the microbially rich activated sludge environment of wastewater treatment plants (WWTPs) may contribute to the dissemination of antibiotic resistance genes (ARGs). We applied long-read (nanopore) sequencing to profile ARGs and their neighboring genes to illuminate their fate in the activated sludge treatment by comparing their abundance, genetic locations, mobility potential, and bacterial hosts within activated sludge relative to those in influent sewage across five WWTPs from three continents.

RESULTS

The abundances (gene copies per Gb of reads, aka gc/Gb) of all ARGs and those carried by putative pathogens decreased 75-90% from influent sewage (192-605 gc/Gb) to activated sludge (31-62 gc/Gb) at all five WWTPs. Long reads enabled quantification of the percent abundance of ARGs with mobility potential (i.e., located on plasmids or co-located with other mobile genetic elements (MGEs)). The abundance of plasmid-associated ARGs decreased at four of five WWTPs (from 40-73 to 31-68%), and ARGs co-located with transposable, integrative, and conjugative element hallmark genes showed similar trends. Most ARG-associated elements decreased 0.35-13.52% while integrative and transposable elements displayed slight increases at two WWTPs (1.4-2.4%). While resistome and taxonomic compositions both shifted significantly, host phyla for chromosomal ARG classes remained relatively consistent, indicating vertical gene transfer via active biomass growth in activated sludge as the key pathway of chromosomal ARG dissemination.

CONCLUSIONS

Overall, our results suggest that the activated sludge process acted as a barrier against the proliferation of most ARGs, while those that persisted or increased warrant further attention. Video abstract.

Molecular Methods for Pathogenic Bacteria Detection and Recent Advances in Wastewater Analysis

With increasing concerns about public health and the development of molecular techniques, new detection tools and the combination of existing approaches have increased the abilities of pathogenic bacteria monitoring by exploring new biomarkers, increasing the sensitivity and accuracy of detection, quantification, and analyzing various genes such as functional genes and antimicrobial resistance genes (ARG). Molecular methods are gradually emerging as the most popular detection approach for pathogens, in addition to the conventional culture-based plate enumeration methods. The analysis of pathogens in wastewater and the back-estimation of infections in the community, also known as wastewater-based epidemiology (WBE), is an emerging methodology and has a great potential to supplement current surveillance systems for the monitoring of infectious diseases and the early warning of outbreaks. However, as a complex matrix, wastewater largely challenges the analytical performance of molecular methods. This review synthesized the literature of typical pathogenic bacteria in wastewater, types of biomarkers, molecular methods for bacterial analysis, and their recent advances in wastewater analysis. The advantages and limitation of these molecular methods were evaluated, and their prospects in WBE were discussed to provide insight for future development.

Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review

Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. This review summarizes available biological fecal indicators focusing on host specificity, degree of association with fecal pollution, environmental persistence, and quantification methods in fecal pollution assessment. The development of practical tools is a crucial requirement for the implementation of mitigation strategies that may help confine the types of host-specific pathogens and determine the source control point, such as sourcing fecal wastes from point sources and nonpoint sources. Emerging multidisciplinary bacterial enumeration platforms are also discussed, including individual working mechanisms, applications, advantages, and limitations.

A review of the resistome within the digestive tract of livestock

Antimicrobials have been widely used to prevent and treat infectious diseases and promote growth in food-production animals. However, the occurrence of antimicrobial resistance poses a huge threat to public and animal health, especially in less developed countries where food-producing animals often intermingle with humans. To limit the spread of antimicrobial resistance from food-production animals to humans and the environment, it is essential to have a comprehensive knowledge of the role of the resistome in antimicrobial resistance (AMR), The resistome refers to the collection of all antimicrobial resistance genes associated with microbiota in a given environment. The dense microbiota in the digestive tract is known to harbour one of the most diverse resistomes in nature. Studies of the resistome in the digestive tract of humans and animals are increasing exponentially as a result of advancements in next-generation sequencing and the expansion of bioinformatic resources/tools to identify and describe the resistome. In this review, we outline the various tools/bioinformatic pipelines currently available to characterize and understand the nature of the intestinal resistome of swine, poultry, and ruminants. We then propose future research directions including analysis of resistome using long-read sequencing, investigation in the role of mobile genetic elements in the expression, function and transmission of AMR. This review outlines the current knowledge and approaches to studying the resistome in food-producing animals and sheds light on future strategies to reduce antimicrobial usage and control the spread of AMR both within and from livestock production systems.

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

In-depth studies of the microbiome and mobile resistome profile of different environments is central to understanding the role of the environment in antimicrobial resistance (AMR), which is one of the urgent threats to global public health. In this study, we demonstrated the use of a rapid (and easily portable) sequencing approach coupled with user-friendly bioinformatics tools, the MinION (Oxford Nanopore Technologies), on the evaluation of the microbial as well as mobile metal and antibiotic resistome profile of semi-rural wastewater. A total of 20 unique phyla, 43 classes, 227 genera, and 469 species were identified in samples collected from the Amherst Wastewater Treatment Plant, both from primary and secondary treated wastewater. Alpha diversity indices indicated that primary samples were significantly richer and more microbially diverse than secondary samples. A total of 1041 ARGs, 68 MRGs, and 17 MGEs were detected in this study. There were more classes of AMR genes in primary than secondary wastewater, but in both cases multidrug, beta-lactam and peptide AMR predominated. Of note, OXA β-lactamases, some of which are also carbapenemases, were enriched in secondary samples. Metal resistance genes against arsenic, copper, zinc and molybdenum were the dominant MRGs in the majority of the samples. A larger proportion of resistome genes were located in chromosome-derived sequences except for mobilome genes, which were predominantly located in plasmid-derived sequences. Genetic elements related to transposase were the most common MGEs in all samples. Mobile or MGE/plasmid-associated resistome genes that confer resistance to last resort antimicrobials such as carbapenems and colistin were detected in most samples. Worryingly, several of these potentially transferable genes were found to be carried by clinically-relevant hosts including pathogenic bacterial species in the orders Aeromonadales, Clostridiales, Enterobacterales and Pseudomonadales. This study demonstrated that the MinION can be used as a metagenomics approach to evaluate the microbiome, resistome, and mobilome profile of primary and secondary wastewater.

Revealing antimicrobial resistance in stormwater with MinION

Discharge of urban stormwater containing organic matter, heavy metals and sometime human feces, to the natural aquatic reservoirs without any treatment is not only an environmental problem. It can lead to prevalence of antibiotic resistant bacteria in stormwater systems and transmission of antibiotic resistance genes to the environment. We performed antibiotic resistome identification and virus detection in stormwater samples from Stockholm, using publicly available metagenomic sequencing MinION data. A MinION platform offers low-cost, precise environmental metagenomics analysis. 37 groups of antibiotic resistant bacteria (ARB), 11 resistance types with 26 resistance mechanisms - antibiotic resistance genes (ARGs) giving tolerance to the aminoglycoside, beta-lactams, fosmidomycin, MLS, multidrug and vancomycin were identified using ARGpore pipeline. The majority of the identified bacteria species were related to the natural environment such as soil and were not dangerous to human. Alarmingly, human pathogenic bacteria carrying resistance to antibiotics currently used against them (Bordetella resistant to macrolides and multidrug resistant Propionibacterium avidum) were also found in the samples. Most abundant viruses identified belonged to Caudovirales and Herpesvirales and they were not carrying ARGs. Unlike the virome, resistome and ARB were not unique for stormwater sampling points. This results underline the need for extensive monitoring of the microbial community structure in the urban stormwater systems to assess antimicrobial resistance spread.

Experimental approaches to tracking mobile genetic elements in microbial communities

Horizontal gene transfer is an important mechanism of microbial evolution and is often driven by the movement of mobile genetic elements between cells. Due to the fact that microbes live within communities, various mechanisms of horizontal gene transfer and types of mobile elements can co-occur. However, the ways in which horizontal gene transfer impacts and is impacted by communities containing diverse mobile elements has been challenging to address. Thus, the field would benefit from incorporating community-level information and novel approaches alongside existing methods. Emerging technologies for tracking mobile elements and assigning them to host organisms provide promise for understanding the web of potential DNA transfers in diverse microbial communities more comprehensively. Compared to existing experimental approaches, chromosome conformation capture and methylome analyses have the potential to simultaneously study various types of mobile elements and their associated hosts. We also briefly discuss how fermented food microbiomes, given their experimental tractability and moderate species complexity, make ideal models to which to apply the techniques discussed herein and how they can be used to address outstanding questions in the field of horizontal gene transfer in microbial communities.

Characteristics of the antibiotic resistance genes in the soil of medical waste disposal sites

The inappropriate disposal of medical waste allows bacteria to acquire antibiotic resistance, which results in a threat to public health. Antibiotic resistance gene (ARG) profiles were determined for 45 different soil samples containing medical waste and 15 nearby soil samples as controls. Besides physical and chemical analyses (i.e., dry matter content, pH value, and metal content), the genomes of microorganisms from the soil samples were extracted for high-throughput sequencing. ARG abundances of these samples were obtained by searching the metagenomic sequences against the antibiotic resistance gene database and the copies of ARGs per copy of the 16S rRNA gene at different levels were assessed. The results showed medical waste accumulation significantly enriched the contents of Cu, Cr, Pb, and As in the tested soil samples. Compared to the controls, the samples collected from areas containing medical waste were significantly enriched (p < 0.05, t-test) with ARGs annotated as sulfonamide and multidrug resistance genes, and in particular, the subtypes sul1 and sul2 (sulfonamide resistance genes), and multidrug_transporter (multidrug resistance gene). Moreover, the ARGs of the samples from the polluted areas were more diverse than those of the control samples (p < 0.05, t-test). The comparatively higher abundance and diversity of ARGs in contaminated soil pose a potential risk to human health.

Two Cases of Vancomycin-Resistant Enterococcus faecium Bacteremia With Development of Daptomycin-Resistant Phenotype and its Detection Using Oxford Nanopore Sequencing

In this work, we report 2 cases of vancomycin-resistant Enterococcus faecium bacteremia with development of daptomycin resistance in 2 patients with acute myeloid leukemia and myelodysplastic syndrome. Mutations related to daptomycin-nonsusceptible phenotype in liaSR genes were found in all strains of the study, including those with a minimum inhibitory concentration <1 µg/mL collected before daptomycin therapy. Epidemiological investigation using core genome single nucleotide polymorphism and core genome multilocus sequence typing revealed clonality of all the isolates. In this study, we conclude that real-time genome sequencing of clinical isolates can provide rapid access to timely information on daptomycin-resistant genotypes that would help clinicians speed up and optimize the selection of the antibiotic for treatment.

Rapid MinION profiling of preterm microbiota and antimicrobial-resistant pathogens

The MinION sequencing platform offers near real-time analysis of DNA sequence; this makes the tool attractive for deployment in fieldwork or clinical settings. We used the MinION platform coupled to the NanoOK RT software package to perform shotgun metagenomic sequencing and profile mock communities and faecal samples from healthy and ill preterm infants. Using Nanopore data, we reliably classified a 20-species mock community and captured the diversity of the immature gut microbiota over time and in response to interventions such as probiotic supplementation, antibiotic treatment or episodes of suspected sepsis. We also performed rapid real-time runs to assess gut-associated microbial communities in critically ill and healthy infants, facilitated by NanoOK RT software package, which analysed sequences as they were generated. Our pipeline reliably identified pathogenic bacteria (that is, Klebsiella pneumoniae and Enterobacter cloacae) and their corresponding antimicrobial resistance gene profiles within as little as 1 h of sequencing. Results were confirmed using pathogen isolation, whole-genome sequencing and antibiotic susceptibility testing, as well as mock communities and clinical samples with known antimicrobial resistance genes. Our results demonstrate that MinION (including cost-effective Flongle flow cells) with NanoOK RT can process metagenomic samples to a rich dataset in < 5 h, which creates a platform for future studies aimed at developing these tools and approaches in clinical settings with a focus on providing tailored patient antimicrobial treatment options.

Diverse Fluoroquinolone Resistance Plasmids From Retail Meat E. coli in the United States

Fluoroquinolones are used to treat serious bacterial infections, including those caused by Escherichia coli and Salmonella enterica. The emergence of plasmid-mediated quinolone resistance (PMQR) represent a new challenge to the successful treatment of Gram-negative infections. As part of a long-term strategy to generate a reference database of closed plasmids from antimicrobial resistant foodborne bacteria, we performed long-read sequencing of 11 E. coli isolates from retail meats that were non-susceptible to ciprofloxacin. Each of the isolates had PMQR genes, including qnrA1, qnrS1, and qnrB19. The four qnrB19 genes were carried on two distinct ColE-type plasmids among isolates from pork chop and ground turkey and were identical to plasmids previously identified in Salmonella. Seven other plasmids differed from any other sequences in GenBank and comprised IncF and IncR plasmids that ranged in size from 48 to 180 kb. These plasmids also contained different combinations of resistance genes, including those conferring resistance to beta-lactams, macrolides, sulfonamides, tetracycline, and heavy metals. Although relatively few isolates have PMQR genes, the identification of diverse plasmids in multiple retail meat sources suggests the potential for further spread of fluoroquinolone resistance, including through co-selection. These results highlight the value of long-read sequencing in characterizing antimicrobial resistance genes of public health concern.

Shotgun metagenome data of a defined mock community using Oxford Nanopore, PacBio and Illumina technologies

Metagenomic sequence data from defined mock communities is crucial for the assessment of sequencing platform performance and downstream analyses, including assembly, binning and taxonomic assignment. We report a comparison of shotgun metagenome sequencing and assembly metrics of a defined microbial mock community using the Oxford Nanopore Technologies (ONT) MinION, PacBio and Illumina sequencing platforms. Our synthetic microbial community BMock12 consists of 12 bacterial strains with genome sizes spanning 3.2–7.2 Mbp, 40–73% GC content, and 1.5–7.3% repeats. Size selection of both PacBio and ONT sequencing libraries prior to sequencing was essential to yield comparable relative abundances of organisms among all sequencing technologies. While the Illumina-based metagenome assembly yielded good coverage with few misassemblies, contiguity was greatly improved by both, Illumina + ONT and Illumina + PacBio hybrid assemblies but increased misassemblies, most notably in genomes with high sequence similarity to each other. Our resulting datasets allow evaluation and benchmarking of bioinformatics software on Illumina, PacBio and ONT platforms in parallel.

Measurement(s)	metagenomic data • sequence_assembly
Technology Type(s)	ONT MinION • Illumina sequencing • PacBio RS II
Factor Type(s)	sequencing platform
Sample Characteristic - Organism	Bacteria
Sample Characteristic - Environment	mock community

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.10260740

Metagenomic approaches: effective tools for monitoring the structure and functionality of microbiomes in anaerobic digestion systems

Microbial metagenome analysis has proven its usefulness to investigate the microbiomes present in technical engineered ecosystems such as anaerobic digestion systems. The analysis of the total microbial genomic DNA allows the detailed determination of both the microbial community structure and its functionality. In addition, it enables to study the response of the microbiome to alterations in technical process parameters. Strategies of functional microbial networks to face abiotic stressors, e.g., resistance, resilience, and reorganization, can be evaluated with respect to overall process optimization. The objective of this paper is to review the main metagenomic tools used for effective studies on anaerobic digestion systems in monitoring the dynamic of the microbiomes, as well as the factors that have been identified so far as limiting the metagenomic studies in this ecosystems.

Antibiotic resistance and class 1 integron gene dynamics along effluent, reclaimed wastewater irrigated soil, crop continua: elucidating potential risks and ecological constraints

Reuse of municipal wastewater is a growing global trend, but currently there is lack of consensus regarding the potential dissemination of antibiotic resistance elements by treated wastewater irrigation. We tracked intI1, a proxy for anthropogenic pollution, and an assemblage of antibiotic resistance genes associated with mobile elements and/or wastewater (bla_GES, bla_OXA2, bla_OXA10, bla_TEM, bla_CTX-M-32 and qnrS) in treated wastewater effluents, effluent stabilization reservoirs, and along irrigation water-soil-crop continua in experimental lysimeters and large-scale commercial fields. While several of the targeted antibiotic resistance genes were profuse in effluents, there was almost no correlation between gene abundance in irrigation water and those detected in soil, and no evidence of systematic gene transfer to irrigated soil or crops. In contrast, soil intI1 abundance correlated strongly to irrigation water levels in lysimeters and sandy field soils, but this was not the case for clay-rich soils or for most of the analyzed crops, suggesting that intI1 may not always be a reliable marker for tracking the impact of treated wastewater irrigation. We hypothesize that "ecological boundaries" expedited by biotic and abiotic factors constrain dissemination of antibiotic resistance elements, and assert that a more holistic perception of these factors is crucial for understanding and managing antibiotic resistance dissemination.

Nanopore metagenomics enables rapid clinical diagnosis of bacterial lower respiratory infection

The gold standard for clinical diagnosis of bacterial lower respiratory infections (LRIs) is culture, which has poor sensitivity and is too slow to guide early, targeted antimicrobial therapy. Metagenomic sequencing could identify LRI pathogens much faster than culture, but methods are needed to remove the large amount of human DNA present in these samples for this approach to be feasible. We developed a metagenomics method for bacterial LRI diagnosis that features efficient saponin-based host DNA depletion and nanopore sequencing. Our pilot method was tested on 40 samples, then optimized and tested on a further 41 samples. Our optimized method (6 h from sample to result) was 96.6% sensitive and 41.7% specific for pathogen detection compared with culture and we could accurately detect antibiotic resistance genes. After confirmatory quantitative PCR and pathobiont-specific gene analyses, specificity and sensitivity increased to 100%. Nanopore metagenomics can rapidly and accurately characterize bacterial LRIs and might contribute to a reduction in broad-spectrum antibiotic use.

Mobile antibiotic resistome in wastewater treatment plants revealed by Nanopore metagenomic sequencing

BACKGROUND

Wastewater treatment plants (WWTPs) are recognized as hotspots for horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). Despite our understanding of the composition and distribution of ARGs in WWTPs, the genetic location, host, and fate of ARGs remain largely unknown.

RESULTS

In this study, we combined Oxford Nanopore and Illumina metagenomics sequencing to comprehensively uncover the resistome context of influent, activated sludge, and effluent of three WWTPs and simultaneously track the hosts of the ARGs. The results showed that most of the ARGs detected in all compartments of the WWTPs were carried by plasmids. Transposons and integrons also showed higher prevalence on plasmids than on the ARG-carrying chromosome. Notably, integrative and conjugative elements (ICEs) carrying five types of ARGs were detected, and they may play an important role in facilitating the transfer of ARGs, particularly for tetracycline and macrolide-lincosamide-streptogramin (MLS). A broad spectrum of ARGs carried by plasmids (29 subtypes) and ICEs (4 subtypes) was persistent across the WWTPs. Host tracking showed a variety of antibiotic-resistant bacteria in the effluent, suggesting the high potential for their dissemination into receiving environments. Importantly, phenotype-genotype analysis confirmed the significant role of conjugative plasmids in facilitating the survival and persistence of multidrug-resistant bacteria in the WWTPs. At last, the consistency in the quantitative results for major ARGs types revealed by Nanopore and Illumina sequencing platforms demonstrated the feasibility of Nanopore sequencing for resistome quantification.

CONCLUSION

Overall, these findings substantially expand our current knowledge of resistome in WWTPs, and help establish a baseline analysis framework to study ARGs in the environment.

Applying Rapid Whole-Genome Sequencing To Predict Phenotypic Antimicrobial Susceptibility Testing Results among Carbapenem-Resistant Klebsiella pneumoniae Clinical Isolates

Standard antimicrobial susceptibility testing (AST) approaches lead to delays in the selection of optimal antimicrobial therapy. Here, we sought to determine the accuracy of antimicrobial resistance (AMR) determinants identified by Nanopore whole-genome sequencing in predicting AST results. Using a cohort of 40 clinical isolates (21 carbapenemase-producing carbapenem-resistant Klebsiella pneumoniae, 10 non-carbapenemase-producing carbapenem-resistant K. pneumoniae, and 9 carbapenem-susceptible K. pneumoniae isolates), three separate sequencing and analysis pipelines were performed, as follows: (i) a real-time Nanopore analysis approach identifying acquired AMR genes, (ii) an assembly-based Nanopore approach identifying acquired AMR genes and chromosomal mutations, and (iii) an approach using short-read correction of Nanopore assemblies. The short-read correction of Nanopore assemblies served as the reference standard to determine the accuracy of Nanopore sequencing results. With the real-time analysis approach, full annotation of acquired AMR genes occurred within 8 h from subcultured isolates. Assemblies sufficient for full resistance gene and single-nucleotide polymorphism annotation were available within 14 h from subcultured isolates. The overall agreement of genotypic results and anticipated AST results for the 40 K. pneumoniae isolates was 77% (range, 30% to 100%) and 92% (range, 80% to 100%) for the real-time approach and the assembly approach, respectively. Evaluating the patients contributing the 40 isolates, the real-time approach and assembly approach could shorten the median time to effective antibiotic therapy by 20 h and 26 h, respectively, compared to standard AST. Nanopore sequencing offers a rapid approach to both accurately identify resistance mechanisms and to predict AST results for K. pneumoniae isolates. Bioinformatics improvements enabling real-time alignment, coupled with rapid extraction and library preparation, will further enhance the accuracy and workflow of the Nanopore real-time approach.