Effects of sample preservation and DNA extraction on enumeration of antibiotic resistance genes in wastewater

Assessment of nucleic acid extraction protocols for antibiotic resistance genes (ARGs) quantification in aircraft wastewater

This study evaluated ten nucleic acid extraction protocols (EP1 to EP10) for measuring five endogenous antibiotic resistance genes (ARGs) in four aircraft wastewater samples (AWW1 to AWW4). The targeted ARGs, including blaCTX-M, blaNDM-1, ermB, qnrS, and tetA, encompassed highly and minimally abundant ARGs. TetA and ermB were consistently detected across four aircraft wastewater samples using the DNeasy Blood and Tissue Kit and the AllPrep PowerViral DNA/RNA kit. QnrS displayed high detection rates with specific extraction protocols and aliquot volumes. Concentrations of ARGs varied across aircraft wastewater samples, with differing extraction protocols influencing quantitative results. The concentrations of tetA, ermB, and qnrS in AWW1 were distinct, while AWW2 to AWW4 exhibited a broader range for tetA, ermB, qnrS, blaCTX-M, and blaNDM-1. EP1 consistently produced the highest concentrations for several ARGs. Collective data analysis revealed varying ARG concentrations across the ten extraction protocols, suggesting the importance of careful extraction protocol selection in ARG monitoring in aircraft wastewater samples. Based on the results, we suggest that a small sample volume (as low as 0.2 mL) may be sufficient for ARG characterization in aircraft wastewater samples. The findings also emphasize the need for considering toilet paper removal without compromising nucleic acid extraction efficiency. The study highlights promising prospects for aircraft wastewater monitoring of ARGs, calling for further investigation into the import and spread of unique ARGs through transport hubs.

Improving the efficiency of DNA extraction from iron incrustations and oilfield-produced water

The quantity and quality of DNA isolated from environmental samples are crucial for getting robust high-throughput sequencing data commonly used for microbial community analysis. The differences in the nature and physicochemical properties of environmental samples impact DNA yields, and therefore, an optimisation of the protocols is always recommended. For instance, samples collected from corroded areas contain high concentrations of metals, salts, and hydrocarbons that can interfere with several steps of the DNA extraction protocols, thereby reducing yield and quality. In this study, we compared the efficiency of commercially available DNA extraction kits and laboratory-adopted methods for microbial community analysis of iron incrustations and oilfield-produced water samples. Modifications to the kits manufacturers' protocols were included to maximise the yield and quality. For iron incrustations, the modified protocol for FastDNA Spin Kit for Soil yielded higher DNA and resulted in higher diversity, including the recovery of low-abundant and rare taxa in the samples, compared to DNeasy PowerSoil Pro Kit. The DNA extracted with modified phenol-chloroform methods yielded higher DNA but failed to pass quality control PCR for 16S sequencing with and without purification. The protocols mentioned here can be used to maximise DNA recovery from iron incrustations and oilfield-produced water samples.

Comparison of concentration and extraction workflows for qPCR quantification of intI1 and vanA in untreated wastewater

Quantitative polymerase chain reaction (qPCR) measurement of antibiotic resistance genes (ARGs) in untreated municipal wastewater may prove useful in combating the antimicrobial resistance crisis. However, harmonizing and optimizing qPCR-based workflows is essential to facilitate comparisons across studies, and includes achieving highly-effective ARG capture through efficient concentration and extraction procedures. In the current study, combinations of sample volume, membrane types and DNA extraction kits within filtration and centrifugation-based workflows were used to quantify 16S ribosomal RNA (16S rRNA), class 1 integron-integrase gene (intI1) and an ARG encoding resistance to vancomycin (vanA) in untreated wastewater sampled from three wastewater treatment plants (WWTPs). Highly abundant 16S rRNA and intI1 were detected in 100 % of samples from all three WWTPs using both 2 and 20 mL sample volumes, while lower prevalence vanA was only detected when using the 20 mL volume. When filtering 2 mL of wastewater, workflows with 0.20-/0.40-μm polycarbonate (PC) membranes generally yielded greater concentrations of the three targets than workflows with 0.22-/0.45-μm mixed cellulose ester (MCE) membranes. The improved performance was diminished when the sample volume was increased to 20 mL. Consistently greater concentrations of 16S rRNA, intI1 and vanA were yielded by filtration-based workflows using PC membranes combined with a DNeasy PowerWater (DPW) Kit, regardless of the sample volume used, and centrifugation-based workflows with DNeasy Blood & Tissue Kit for 2-mL wastewater extractions. Within the filtration-based workflows, the DPW kit yielded more detection and quantifiable results for less abundant vanA than the DNeasy PowerSoil Pro Kit and FastDNA™ SPIN Kit for Soil. These findings indicate that the performance of qPCR-based workflows for surveillance of ARGs in wastewater varies across targets, sample volumes, concentration methods and extraction kits. Workflows must be carefully considered and validated considering the target ARGs to be monitored.

Establishing reference material for the quest towards standardization in environmental microbial metagenomic studies

Breakthroughs in DNA-based technologies, especially in metagenomic sequencing, have drastically enhanced researchers' ability to explore environmental microbiome and the associated interplays within. However, as new methodologies are being actively developed for improvements in different aspects, metagenomic workflows become diversified and heterogeneous. Through a single-variable control approach, we quantified the microbial profiling variations arising from 6 common technical variables associated with metagenomic workflows for both simple and complex samples. The incurred variations were constantly the lowest in replicates of DNA isolation and DNA sequencing library construction. Different DNA extraction kits often caused the highest variation among all the tested variables. Additionally, sequencing run batch was an important source of variability for targeted platforms. As such, the development of an environmental reference material for complex environmental samples could be beneficial in benchmarking accrued non-biological variability within and between protocols and insuring reliable and reproducible sequencing outputs immediately upstream of bioinformatic analysis. To develop an environment reference material, sequencing of a well-homogenized environmental sample composed of activated sludge was performed using different pre-analytical assays in replications. In parallel, a certified mock community was processed and sequenced. Assays were ranked based on the reconstruction of the theoretical mock community profile. The reproducibility of the best-performing assay and the microbial profile of the reference material were further ascertained. We propose the adoption of our complex environmental reference material, which could reflect the degree of diversity in environmental microbiome studies, to facilitate accurate, reproducible, and comparable environmental metagenomics-based studies.

Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Awareness of the need for surveillance of antimicrobial resistance (AMR) in water environments is growing, but there is uncertainty regarding appropriate monitoring targets. Adapting culture-based fecal indicator monitoring to include antibiotics in the media provides a potentially low-tech and accessible option, while quantitative polymerase chain reaction (qPCR) targeting key genes of interest provides a broad, quantitative measure across the microbial community. The purpose of this study was to compare findings obtained from the culture of cefotaxime-resistant (cefR) Escherichia coli with two qPCR methods for quantification of antibiotic resistance genes across wastewater, recycled water, and surface waters. The culture method was a modification of US EPA Method 1603 for E. coli, in which cefotaxime is included in the medium to capture cefR strains, while qPCR methods quantified sul1 and intI1. A common standard operating procedure for each target was applied to samples collected by six water utilities across the United States and processed by two laboratories. The methods performed consistently, and all three measures reflected the same overarching trends across water types. The qPCR detection of sul1 yielded the widest dynamic range of measurement as an AMR indicator (7-log versus 3.5-log for cefR E. coli), while intI1 was the most frequently detected target (99% versus 96.5% and 50.8% for sul1 and cefR E. coli, respectively). All methods produced comparable measurements between labs (p < 0.05, Kruskal-Wallis). Further study is needed to consider how relevant each measure is to capturing hot spots for the evolution and dissemination of AMR in the environment and as indicators of AMR-associated human health risk.

The Phenomenon of Antibiotic Resistance in the Polar Regions: An Overview of the Global Problem

The increasing prevalence of antibiotic resistance is a global problem in human and animal health. This leads to a reduction in the therapeutic effectiveness of the measures used so far and to the limitation of treatment options, which may pose a threat to human health and life. The problem of phenomenon of antibiotic resistance affects more and more the polar regions. This is due to the increase in tourist traffic and the number of people staying at research stations, unmodernised sewage systems in inhabited areas, as well as the migration of animals or the movement of microplastics, which may contain resistant bacteria. Research shows that the presence of antibiotic resistance genes is more dominant in zones of human and wildlife influence than in remote areas. In a polluted environment, there is evidence of a direct correlation between human activity and the spread and survival of antibiotic-resistant bacteria. Attention should be paid to the presence of resistance to synthetic and semi-synthetic antibiotics in the polar regions, which is likely to be correlated with human presence and activity, and possible steps to be taken. We need to understand many more aspects of this, such as bacterial epigenetics and environmental stress, in order to develop effective strategies for minimizing the spread of antibiotic resistance genes. Studying the diversity and abundance of antibiotic resistance genes in regions with less anthropogenic activity could provide insight into the diversity of primary genes and explain the historical evolution of antibiotic resistance.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

Antimicrobial Resistance Monitoring of Water Environments: A Framework for Standardized Methods and Quality Control

Antimicrobial resistance (AMR) is a grand societal challenge with important dimensions in the water environment that contribute to its evolution and spread. Environmental monitoring could provide vital information for mitigating the spread of AMR; this includes assessing antibiotic resistance genes (ARGs) circulating among human populations, identifying key hotspots for evolution and dissemination of resistance, informing epidemiological and human health risk assessment models, and quantifying removal efficiencies by domestic wastewater infrastructure. However, standardized methods for monitoring AMR in the water environment will be vital to producing the comparable data sets needed to address such questions. Here we sought to establish scientific consensus on a framework for such standardization, evaluating the state of the science and practice of AMR monitoring of wastewater, recycled water, and surface water, through a literature review, survey, and workshop leveraging the expertise of academic, governmental, consulting, and water utility professionals.

Metagenomic analysis reveals microbiome and resistome in the seawater and sediments of Kongsfjorden (Svalbard, High Arctic)

Kongsfjorden in the high Arctic, a typical Arctic fjord, experienced long-time input of nutrients and pollutants from the remote and local resources, providing a platform for characterizing the diversity and distribution of antibiotic resistance genes (ARGs). However, the microbiome and antibiotic resistome in this pristine marine system have not been well documented. The present study aimed to characterize the diversity and distribution of bacterial communities and associated ARGs in seawater (12 samples) and sediments (13 samples) of Kongsfjorden via metagenomic analysis. In terms of both bacterial community compositions and ARG profiles, the seawater was significantly distinct from sediment. Only 29 ARG subtypes were detected in the Arctic seawater and sediments. Furthermore, three geochemical factors (i.e., longitude, depth, and PO₄^3-) greatly influenced the bacterial communities in sediment samples, while longitude, depth, and latitude were crucial geochemical factors influencing the ARG profiles in sediment samples. Procrustes analysis revealed a significant correlation between bacterial community compositions and ARG profiles in seawater and sediment samples. Further analysis revealed the metagenome-assembled genomes (MAGs) with ARG subtypes. Overall, our study provides insights into the microbiome and resistome in a pristine Arctic fjord, thereby providing vital information for environmental management.

Comparative Metagenomics of Anaerobic Digester Communities Reveals Sulfidogenic and Methanogenic Microbial Subgroups in Conventional and Plug Flow Residential Septic Tank Systems

On-site wastewater treatment systems (OWTS) are primarily monitored using physiochemical factors, including chemical oxygen demand (COD) and residual total suspended solids (TSS), which are indirect measures of the microbial action during the anaerobic digestion process. Changes in anaerobic digester microbial communities can alter the digester performance, but this information cannot be directly obtained from traditional physicochemical indicators. The potential of metagenomic DNA sequencing as a tool for taxonomic and functional profiling of microbial communities was examined in both common conventional and plug flow-type anaerobic digesters (single-pass and recirculating). Compared to conventional digesters, plug flow-type digesters had higher relative levels of sulfate-reducing bacteria (Desulfovibrio spp.) and hydrogenotrophic methanogens (Methanospirillum spp.). In contrast, recirculating anaerobic digesters were enriched with denitrifier bacteria and hydrogenotrophic methanogens, and both were significantly correlated with physicochemical factors such as COD and TSS. Stratification of microbial communities was observed along the digester treatment process according to hydrolytic, acidogenic, acetogenic, and methanogenic subgroups. These results indicate that the high-throughput DNA sequencing may be useful as a monitoring tool to characterize the changes in bacterial communities and the functional profile due to differences in digester design in on-site systems.

Monitoring antibiotic resistance genes in wastewater environments: The challenges of filling a gap in the One-Health cycle

Antibiotic resistance (AR) is a global problem requiring international cooperation and coordinated action. Global monitoring must rely on methods available and comparable across nations to quantify AR occurrence and identify sources and reservoirs, as well as paths of AR dissemination. Numerous analytical tools that are gaining relevance in microbiology, have the potential to be applied to AR research. This review summarizes the state of the art of AR monitoring methods, considering distinct needs, objectives and available resources. Based on the overview of distinct approaches that are used or can be adapted to monitor AR, it is discussed the potential to establish reliable and useful monitoring schemes that can be implemented in distinct contexts. This discussion places the environmental monitoring within the One-Health approach, where two types of risk, dissemination across distinct environmental compartments, and transmission to humans, must be considered. The plethora of methodological approaches to monitor AR and the variable features of the monitored sites challenge the capacity of the scientific community and policy makers to reach a common understanding. However, the dialogue between different methods and the production of action-oriented data is a priority. The review aims to warm up this discussion.

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.

Changes in Vaginal Microbiome Diversity in Women With Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that affects women. It can be accompanied by many clinical manifestations that can vary between individuals. Previous studies have found that there are specific changes in the intestinal flora of PCOS patients, and interventions to modify the intestinal flora can significantly improve the symptoms of PCOS. Women with PCOS have a higher incidence of vaginitis compared to healthy women. Few studies to-date have focused on investigating vaginal flora. Here, we aimed to explore distribution changes of the vaginal microbiome in PCOS patients. We recruited 42 PCOS patients (T-PCOS) and 24 healthy controls (T-control). 16s rRNA gene sequencing was used to sequence their vaginal microbiome. Normally, Lactobacillus was dominated in vaginal. Lactobacillus-dominated-type vaginal microbiome in T-PCOS and T-control (L-PCOS and L-control) and non-Lactobacillus-dominated-type vaginal microbiome in T-PCOS and T-control (N-PCOS and N-control) were analyzed separately. A total of 655 operational taxonomic units were detected in this sequencing, including 306 unique to T-PCOS, 202 unique to T-control, and 147 common between the two groups. At the genus level, Lactobacillus accounted for more than 70% of the total microbiome. Observed species (P = 0.021), Chao1 index (P = 0.020), and ACE index (P = 0.023) decreased significantly in L-PCOS. Principal component analysis showed no statistically significant differences among the subgroups. There were significant statistical differences in principal coordinate analysis in the Jaccard distance between the T-PCOS and T-control groups and between the L-PCOS and L-control groups. Linear discriminant analysis effect size found that Enterococcus and Actinomycetes were significantly different in the T-PCOS group. Atopobium and Actinomyces were statistically significantly different in patients with L-PCOS and N-PCOS group, respectively. Environmental factor analysis found that Ezakiella was significantly negatively correlated with age, while Streptococcus was significantly negatively correlated with follicle stimulating hormone. There were statistically significant differences between PCOS patients and healthy women in the vaginal microbiome, regardless of the abundance of Lactobacillus. Alpha diversity of vaginal microbiome decreased markedly in PCOS patients when it was dominated by Lactobacillus spp. Actinomyces could be a potential biomarker to identify PCOS. Streptococcus may have an impact on the pathological changes in PCOS by affecting the female reproductive endocrine environment.

Optimization of Fenton process on removing antibiotic resistance genes from excess sludge by single-factor experiment and response surface methodology

Excess sludge contains large amounts of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs), posing a risk for human health. However, most current studies usually ignored their abundance and removal in excess sludge. Therefore, this study aimed to reduce ARGs/MGEs in sludge by Fenton process, and applied single-factor experiment (SFE) and response surface methodology (RSM) to optimize the Fenton reaction condition for higher removal rates of ARGs/MGEs. The results demonstrated that the removal rates of target genes by SFE optimized condition ranged from 10.91% to 66.86%, while the removal rates caused by RSM optimized condition were 48.02% - 76.36%, indicating RSM was a useful tool to improve the removal rates of ARGs in excess sludge. Additionally, the scanning electron microscope and cell apoptosis results suggested that the Fenton treatment altered the structure of sludge and reduced the numbers of normal cells, thus causing the reductions of target genes.

Monitoring Microbial Populations and Antibiotic Resistance Gene Enrichment Associated with Arctic Waste Stabilization Ponds

Given that the microbial communities of Arctic waste stabilization ponds (WSPs) are poorly studied to date, our characterization of multiple WSP systems and time points provides important baseline data that will assist with ongoing monitoring of effluent impacts on downstream aquatic ecosystems in the Arctic. This research also identifies indicator amplicon sequence variants (ASVs) of WSPs that will be helpful for future monitoring for WSP effluent attenuation and demonstrates that WSP microbial communities are enriched in antibiotic resistance genes.

Wastewater management in the Canadian Arctic is challenging due to climate extremes, small population sizes, and lack of conventional infrastructure for wastewater treatment. Although many northern communities use waste stabilization ponds (WSPs) as their primary form of wastewater treatment, few studies have explored WSP microbial communities and assessed effluent impacts on receiving waters from a microbiological perspective. Here, we used 16S rRNA gene and metagenome sequencing to characterize WSP and receiving water microbial communities for two time points bracketing the spring WSP thaw in Baker Lake (Nunavut) and compared these results to other Nunavut WSPs in Cambridge Bay and Kugluktuk. Most amplicon sequence variants (ASVs) recovered from these WSP samples belonged to the phylum Proteobacteria, with considerable variation between the three locations and only six ASVs shared among the WSPs at >0.2% relative abundance. Wastewater indicator ASVs for the Baker Lake WSP were identified, and few indicator ASVs were detected in samples originating from other upstream or downstream sites. The metagenomic data revealed a strong enrichment of antibiotic resistance genes for WSP samples relative to downstream and reference samples, especially for genes associated with macrolide resistance. Together, our results provide a baseline characterization for WSP microbial communities, demonstrate how indicator ASVs can be used to monitor attenuation and dilution of effluent microorganisms, and reveal that WSPs can serve as hot spots for antibiotic resistance genes.

IMPORTANCE Given that the microbial communities of Arctic waste stabilization ponds (WSPs) are poorly studied to date, our characterization of multiple WSP systems and time points provides important baseline data that will assist with ongoing monitoring of effluent impacts on downstream aquatic ecosystems in the Arctic. This research also identifies indicator amplicon sequence variants (ASVs) of WSPs that will be helpful for future monitoring for WSP effluent attenuation and demonstrates that WSP microbial communities are enriched in antibiotic resistance genes. Given operational and infrastructure changes anticipated for wastewater treatment systems in the Arctic, baseline data such as these are essential for further development of safe and effective wastewater treatment systems.

Critical evaluation of short, long, and hybrid assembly for contextual analysis of antibiotic resistance genes in complex environmental metagenomes

In the fight to limit the global spread of antibiotic resistance, the assembly of environmental metagenomes has the potential to provide rich contextual information (e.g., taxonomic hosts, carriage on mobile genetic elements) about antibiotic resistance genes (ARG) in the environment. However, computational challenges associated with assembly can impact the accuracy of downstream analyses. This work critically evaluates the impact of assembly leveraging short reads, nanopore MinION long-reads, and a combination of the two (hybrid) on ARG contextualization for ten environmental metagenomes using seven prominent assemblers (IDBA-UD, MEGAHIT, Canu, Flye, Opera-MS, metaSpades and HybridSpades). While short-read and hybrid assemblies produced similar patterns of ARG contextualization, raw or assembled long nanopore reads produced distinct patterns. Based on an in-silico spike-in experiment using real and simulated reads, we show that low to intermediate coverage species are more likely to be incorporated into chimeric contigs across all assemblers and sequencing technologies, while more abundant species produce assemblies with a greater frequency of inversions and insertion/deletions (indels). In sum, our analyses support hybrid assembly as a valuable technique for boosting the reliability and accuracy of assembly-based analyses of ARGs and neighboring genes at environmentally-relevant coverages, provided that sufficient short-read sequencing depth is achieved.

Sulfidated nanoscale zero-valent iron is an efficient material for the removal and regrowth inhibition of antibiotic resistance genes

Antibiotic resistance genes (ARGs) and mobile gene elements (MGEs), the emerging genetic contaminants, are regarded as severe risks to public health for impairing the inactivation efficacy of antibiotics. Secondary effluents from wastewater treatment plants are the hotspots for spreading these menaces. Herein, sulfidated nanoscale zero-valent iron (S-nZVI) was occupied to remove ARGs and MGEs in secondary effluents and weaken the regrowth capacity of their bacterial carriers. The effects of S/Fe molar ratios (S/Fe), initial pH and dosages on 16S rRNA and ARGs removal were also investigated. Characterization, mass balance and scavenging experiments were conducted to explore the mechanisms of the gene removal. Quantitative PCR (qPCR) and high throughput fluorescence qPCR showed more than 3 log unit of 16S rRNA and seven out of 10 ARGs existed in secondary effluent could be removed after S-nZVI treatment. The mechanisms might be that DNA accepted the electron provided by the Fe⁰ core of S-nZVI after being adsorbed onto S-nZVI surface, causing the decrease of 16S rRNA, ARGs and lost their regrowth capacity, especially for typical MGE (intI1) and further inhibiting the vertical gene transfer (VGT) and intI1-induced horizontal gene transfer (HGT). Fe⁰ core was oxidized to iron oxides and hydroxides at the same time. High throughput sequencing, network analysis and variation partitioning analysis revealed the complex correlations between bacteria and ARGs in secondary effluent, S/Fe could directly influence ARGs variations, and bacterial genera made the greatest contribution to ARGs variations, followed by MGEs and operational parameters. As a result, S-nZVI could be an available reductive approach to deal with bacteria and ARGs.

Quantitative Microbial Risk Assessment and Molecular Biology: Paths to Integration

Quantitative microbial risk assessment (QMRA) has now been in use for over 35 years and has formed the basis for developing criteria for ensuring public health related to water, food, and remediation, to name a few areas. The initial data for QMRA (both in exposure assessment and in dose response assessment) came from measurements using assays for viability, such as plate counts, plaque assays, or animal infectivity. With the increasing use of molecular methods for the measurement of microorganisms in the environment, it has become important to assess how to use such data to estimate infectious disease risks. The limitations to the use of such data and needs to resolve the limitations will be addressed.

Prevalence and seasonal dynamics of blaCTX-M antibiotic resistance genes and fecal indicator organisms in the lower Lahn River, Germany

Antibiotic-resistant bacteria represent an emerging global health problem and are frequently detected in riverine environments. Analyzing the occurrence of corresponding antibiotic-resistant genes in rivers is of public interest as it contributes towards understanding the origin and dissemination of these emerging microbial contaminants via surface water. This is critical for devising strategies to mitigate the spread of resistances in the environment. Concentrations of bla_CTX-M antibiotic resistance genes were quantified weekly over a 12-month period in Lahn River surface water at two sampling sites using quantitative real-time PCR. Gene abundances were statistically assessed with regard to previously determined concentrations of fecal indicator organisms Escherichia coli, intestinal enterococci and somatic coliphages, as well as influential environmental factors. Similar seasonal patterns and strong positive correlations between fecal indicators and bla_CTX-M genes indicated identical sources. Accordingly, linear regression analyses showed that bla_CTX-M concentrations could largely be explained by fecal pollution. E. coli provided the best estimates (75% explained variance) at the upstream site, where proportions of bla_CTX-M genes in relation to fecal indicator organisms were highest. At this site, rainfall proved to be more influential, hinting at surface runoff as an emission source. The level of agricultural impact increased from downstream to upstream, linking increasing bla_CTX-M concentrations after rainfall events to the degree of agricultural land use. Exposure assessment revealed that even participants in non-swimming recreational activities were at risk of incidentally ingesting bla_CTX-M genes and thus potentially antibiotic resistant bacteria. Considering that bla_CTX-M genes are ubiquitous in Lahn River and participants in bathing and non-bathing water sports are at risk of exposure, results highlight the importance of microbial water quality monitoring with an emphasis on antibiotic resistance not only in designated bathing waters. Moreover, E. coli might serve as a suitable estimate for the presence of respective antibiotic resistant strains.

Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms

This Opinion considers the application of whole genome sequencing (WGS) and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne pathogens. WGS offers the highest level of bacterial strain discrimination for food‐borne outbreak investigation and source‐attribution as well as potential for more precise hazard identification, thereby facilitating more targeted risk assessment and risk management. WGS improves linking of sporadic cases associated with different food products and geographical regions to a point source outbreak and can facilitate epidemiological investigations, allowing also the use of previously sequenced genomes. Source attribution may be favoured by improved identification of transmission pathways, through the integration of spatial‐temporal factors and the detection of multidirectional transmission and pathogen–host interactions. Metagenomics has potential, especially in relation to the detection and characterisation of non‐culturable, difficult‐to‐culture or slow‐growing microorganisms, for tracking of hazard‐related genetic determinants and the dynamic evaluation of the composition and functionality of complex microbial communities. A SWOT analysis is provided on the use of WGS and metagenomics for Salmonella and Shigatoxin‐producing Escherichia coli (STEC) serotyping and the identification of antimicrobial resistance determinants in bacteria. Close agreement between phenotypic and WGS‐based genotyping data has been observed. WGS provides additional information on the nature and localisation of antimicrobial resistance determinants and on their dissemination potential by horizontal gene transfer, as well as on genes relating to virulence and biological fitness. Interoperable data will play a major role in the future use of WGS and metagenomic data. Capacity building based on harmonised, quality controlled operational systems within European laboratories and worldwide is essential for the investigation of cross‐border outbreaks and for the development of international standardised risk assessments of food‐borne microorganisms.

Identification of discriminatory antibiotic resistance genes among environmental resistomes using extremely randomized tree algorithm

BACKGROUND

The interconnectivities of built and natural environments can serve as conduits for the proliferation and dissemination of antibiotic resistance genes (ARGs). Several studies have compared the broad spectrum of ARGs (i.e., "resistomes") in various environmental compartments, but there is a need to identify unique ARG occurrence patterns (i.e., "discriminatory ARGs"), characteristic of each environment. Such an approach will help to identify factors influencing ARG proliferation, facilitate development of relative comparisons of the ARGs distinguishing various environments, and help pave the way towards ranking environments based on their likelihood of contributing to the spread of clinically relevant antibiotic resistance. Here we formulate and demonstrate an approach using an extremely randomized tree (ERT) algorithm combined with a Bayesian optimization technique to capture ARG variability in environmental samples and identify the discriminatory ARGs. The potential of ERT for identifying discriminatory ARGs was first evaluated using in silico metagenomic datasets (simulated metagenomic Illumina sequencing data) with known variability. The application of ERT was then demonstrated through analyses using publicly available and in-house metagenomic datasets associated with (1) different aquatic habitats (e.g., river, wastewater influent, hospital effluent, and dairy farm effluent) to compare resistomes between distinct environments and (2) different river samples (i.e., Amazon, Kalamas, and Cam Rivers) to compare resistome characteristics of similar environments.

RESULTS

The approach was found to readily identify discriminatory ARGs in the in silico datasets. Also, it was not found to be biased towards ARGs with high relative abundance, which is a common limitation of feature projection methods, and instead only captured those ARGs that elicited significant profiles. Analyses of publicly available metagenomic datasets further demonstrated that the ERT approach can effectively differentiate real-world environmental samples and identify discriminatory ARGs based on pre-defined categorizing schemes.

CONCLUSIONS

Here a new methodology was formulated to characterize and compare variances in ARG profiles between metagenomic data sets derived from similar/dissimilar environments. Specifically, identification of discriminatory ARGs among samples representing various environments can be identified based on factors of interest. The methodology could prove to be a particularly useful tool for ARG surveillance and the assessment of the effectiveness of strategies for mitigating the spread of antibiotic resistance. The python package is hosted in the Git repository: https://github.com/gaarangoa/ExtrARG.

Potential use of high-throughput sequencing of bacterial communities for postmortem submersion interval estimation

Microorganisms play vital roles in the natural decomposition of carcasses in aquatic systems. Using high-throughput sequencing techniques, we evaluated the composition and succession of microbial communities throughout the decomposition of rat carcasses in freshwater. A total of 4,428,781 high-quality 16S rRNA gene sequences and 2144 operational taxonomic units were obtained. Further analysis revealed that the microbial composition differed significantly between the epinecrotic (rat skins) and the epilithic (rocks) samples. During the carcass decomposition process, Proteobacteria became the dominant phylum in the epinecrotic, epilithic, and environmental (water) samples, followed by Firmicutes in the epinecrotic samples and Bacteroidetes in the epilithic and water samples. Microbial communities were influenced by numerous environmental factors, such as dissolved oxygen content and conductivity. Our study provides new insight about postmortem submersion interval (PMSI) estimation in aquatic environments.

Antibiotic resistance in wastewater treatment plants: Tackling the black box

Wastewater is among the most important reservoirs of antibiotic resistance in urban environments. The abundance of carbon sources and other nutrients, a variety of possible electron acceptors such as oxygen or nitrate, the presence of particles onto which bacteria can adsorb, or a fairly stable pH and temperature are examples of conditions favouring the remarkable diversity of microorganisms in this peculiar habitat. The wastewater microbiome brings together bacteria of environmental, human and animal origins, many harbouring antibiotic resistance genes (ARGs). Although numerous factors contribute, mostly in a complex interplay, for shaping this microbiome, the effect of specific potential selective pressures such as antimicrobial residues or metals, is supposedly determinant to dictate the fate of antibiotic resistant bacteria (ARB) and ARGs during wastewater treatment. This paper aims to enrich the discussion on the ecology of ARB&ARGs in urban wastewater treatment plants (UWTPs), intending to serve as a guide for wastewater engineers or other professionals, who may be interested in studying or optimizing the wastewater treatment for the removal of ARB&ARGs. Fitting this aim, the paper overviews and discusses: i) aspects of the complexity of the wastewater system and/or treatment that may affect the fate of ARB&ARGs; ii) methods that can be used to explore the resistome, meaning the whole ARB&ARGs, in wastewater habitats; and iii) some frequently asked questions for which are proposed addressing modes. The paper aims at contributing to explore how ARB&ARGs behave in UWTPs having in mind that each plant is a unique system that will probably need a specific procedure to maximize ARB&ARGs removal.

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.