Assessing phenotypic and genotypic antibiotic resistance in bacillus-related bacteria isolated from biogas digestates. - Related Documents




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322401.0000Assessing phenotypic and genotypic antibiotic resistance in bacillus-related bacteria isolated from biogas digestates. Antibiotic resistance poses a significant public health challenge, with biogas digestate, a byproduct of anaerobic digestion (AD), presenting potential risks when applied as a biofertilizer. Understanding the actual resistance levels in digestate is crucial for its safe application. While many studies have investigated antibiotic resistance in AD processes using culture-independent molecular methods, these approaches are limited by their reliance on reference databases and inability to account for gene expression, leading to potential inaccuracies in resistance assessment. This study addresses these limitations by combining culture-independent whole-genome sequencing (WGS) with culture-dependent phenotypic testing to provide a more accurate understanding of antibiotic resistance in digestate. We investigated the phenotypic and genotypic resistance profiles of 18 antibiotic-resistant bacteria (ARB) isolated from digestates produced from food waste and animal manure. Resistance was assessed using WGS and Estrip testing across 12 antibiotics from multiple classes. This is the first study to directly compare phenotypic and genotypic resistance in bacteria isolated from digestate, revealing significant discrepancies between the two methods. Approximately 30 % of resistance levels were misinterpreted when relying solely on culture-independent methods, with both over- and underestimation observed. These findings highlight the necessity of integrating both methods for reliable resistance assessments. Additionally, our WGS analysis indicated low potential for transferability of detected ARGs among the isolated ARB, suggesting a limited risk of environmental dissemination. This study provides new insights into antibiotic resistance in digestate and underscores the importance of integrating methodological approaches to achieve accurate evaluations of resistance risks.202539947064
659510.9998Methodological aspects of investigating the resistome in pig farm environments. A typical One Health issue, antimicrobial resistance (AMR) development and its spread among people, animals, and the environment attracts significant research attention. The animal sector is one of the major contributors to the development and dissemination of AMR and accounts for more than 50 % of global antibiotics usage. The use of antibiotics exerts a selective pressure for resistant bacteria in the exposed microbiome, but many questions about the epidemiology of AMR in farm environments remain unanswered. This is connected to several methodological challenges and limitations, such as inconsistent sampling methods, complexity of farm environment samples and the lack of standardized protocols for sample collection, processing and bioinformatical analysis. In this project, we combined metagenomics and bioinformatics to optimise the methodology for reproducible research on the resistome in complex samples from the indoor farm environment. The work included optimizing sample collection, transportation, and storage, as well as DNA extraction, sequencing, and bioinformatic analysis, such as metagenome assembly and antibiotic resistance gene (ARG) detection. Our studies suggest that the current most optimal and cost-effective pipeline for ARG search should be based on Illumina sequencing of sock sample material at high depth (at least 25 M 250 bp PE for AMR gene families and 43 M for gene variants). We present a computational analysis utilizing MEGAHIT assembly to balance the identification of bacteria carrying ARGs with the potential loss of diversity and abundance of resistance genes. Our findings indicate that searching against multiple ARG databases is essential for detecting the highest diversity of ARGs.202539954816
325420.9998Temporal trends of antibiotic resistance in culturable bacteria reveal the role of potential pathogens as pioneering carriers and resistance accumulators. Understanding the occurrence and temporal trends of antibiotic resistance genes (ARGs) within bacteria is crucial for controlling and predicting the proliferation of antibiotic-resistant bacteria. However, gaps remain in understanding the long-term trends across different bacterial species and in assessing related health risks. We collected 22,360 bacterial complete genome sequences with collection time and compiled a temporal dataset of ARGs in culturable bacteria. Our results revealed the widespread presence of ARGs among culturable bacterial species, with potential pathogens carrying significantly more ARGs than non-pathogenic species. Temporal trend analysis revealed that only 11.0 % of bacterial species experienced an increase of more than one unit in ARG quantity and diversity over one century, with 83.3 % of them being potential pathogenic species. The temporal accumulation of ARGs in many potential pathogenic species is influenced by the abundance of mobile genetic elements, with several species also exhibiting temporal accumulation of plasmid-borne ARGs. Notably, Shigella flexneri and Klebsiella pneumoniae exhibited an accumulation of high-risk ARGs associated with at least five antibiotic types over at least 40 years. Furthermore, the distribution of ARG-carrying strains before the use of antibiotics revealed a wide range of bacterial species and antibiotic types for intrinsic resistance, including some synthetic antibiotics. This work reveals the significant role of potential pathogens in the expansion of antibiotic resistance and highlights the importance of strengthening vigilance against the emergence of novel multidrug-resistant pathogens.202540712179
656630.9998Antimicrobial resistance bacteria and genes detected in hospital sewage provide valuable information in predicting clinical antimicrobial resistance. Extensive use of antibiotics is significantly associated with development of antibiotic-resistant (AR) bacteria. However, their causal relationships have not been adequately investigated, especially in human population and hospitals. Our aims were to understand clinical AR through revealing co-occurrence patterns between antibiotic-resistant bacteria and genes (ARB and ARGs), and their association with antibiotic use, and to consider impact of ARB and ARGs on environmental and human health. Antibiotic usage was calculated based on the actual consumption in our target hospital. ARB was identified by culture. In isolates collected from hospital sewage, bacterial-specific DNA sequences and ARGs were determined using metagenomics. Our data revealed that the use of culture-based single-indicator-strain approaches only captured ARB in 16.17% of the infectious samples. On the other hand, 1573 bacterial species and 885 types of ARGs were detected in the sewage. Furthermore, hospital use of antibiotics influenced the resistance profiles, but the strength varied among bacteria. From our metagenomics analyses, ARGs for aminoglycosides were the most common, followed by sulfonamide, tetracycline, phenicol, macrolides, and quinolones, comprising 82.6% of all ARGs. Association analyses indicated that 519 pairs of ARGs were significantly correlated with ARB species (r > 0.8). The co-occurrence patterns of bacteria-ARGs mirrored the AR in the clinic. In conclusion, our systematic investigation further emphasized that antibiotic usage in hospital significantly influenced the abundance and types of ARB and ARGs in dose- and time-dependent manners which, in turn, mirrored clinical AR. In addition, our data provide novel information on development of certain ARB with multiple antibiotic resistance. These ARB and ARGs from sewage can also be disseminated into the environment and communities to create health problems. Therefore, it would be helpful to use such data to develop improved predictive risk model of AR, to enhance effective use of antibiotics, and to reduce environmental pollution.202134247085
345840.9998MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage. Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them.201729163399
732350.9998Identification and quantification of bacterial genomes carrying antibiotic resistance genes and virulence factor genes for aquatic microbiological risk assessment. Aquatic ecosystems have been increasingly threatened by anthropogenic activities, e.g., wastewater discharge and farm operation. Several methods are adopted to evaluate the effects of anthropogenic activities on biological risk in the environment, such as qPCR and amplicon next-generation sequencing. However, these methods fall short of providing genomic information of target species, which is vital for risk assessment from genomic aspect. Here, we developed a novel approach integrating metagenomic analysis and flow cytometry to identify and quantify potential pathogenic antibiotic resistant bacteria (PARB; carrying both antibiotic resistance genes (ARGs) and virulence factor genes (VFGs)) in the environment, which are of particular concern due to their infection ability and antibiotic resistance. Based on the abundance/density of PARB, we evaluated microbiological risk in a river impacted by both municipal drainage and agriculture runoff. We collected samples upstream (mountainous area) as the control. Results showed that 81.8% of dominant PARB (33) recovered using our approach were related to known pathogenic taxa. In addition, intragenomic ARGs-VFGs coexistence patterns in the dominant Pseudomonas genomes (20 out of 71 PARB) showed high similarity with the most closely related Pseudomonas genomes from the NCBI RefSeq database. These results reflect acceptable reliability of the approach for (potential) pathogen identification in environmental samples. According to the PARB density, microbiological risk in samples from the agricultural area was significantly higher than in samples from the urban area. We speculated that this was due to the higher antibiotic usage in agriculture as well as intragenomic ARGs-VFGs co-evolution under antibiotic selective pressure. This study provides an alternative approach for the identification and quantification of PARB in aquatic environments, which can be applied for microbiological risk assessment.202031614233
659660.9998Shotgun metagenomic sequencing of bulk tank milk filters reveals the role of Moraxellaceae and Enterobacteriaceae as carriers of antimicrobial resistance genes. In the present context of growing antimicrobial resistance (AMR) concern, understanding the distribution of AMR determinants in food matrices such as milk is crucial to protect consumers and maintain high food safety standards. Herein, the resistome of different dairy farms was investigated through a shotgun metagenomic sequencing approach, taking advantage of in-line milk filters as promising tools. The application of both the reads-based and the assembly-based approaches has allowed the identification of numerous AMR determinants, enabling a comprehensive resolution of the resistome. Notably most of the species harboring AMR genes were predicted to be Gram-negative genera, namely Enterobacter, Acinetobacter, Escherichia, and Pseudomonas, pointing out the role of these bacteria as reservoirs of AMR determinants. In this context, the use of de novo assembly has allowed a more holistic AMR detection strategy, while the reads-based approach has enabled the detection of AMR genes from low abundance bacteria, usually undetectable by assembly-based methods. The application of both reads-based and assembly-based approaches, despite being computationally demanding, has facilitated the comprehensive characterization of a food chain resistome, while also allowing the construction of complete metagenome assembled genomes and the investigation of mobile genetic elements. Our findings suggest that milk filters can successfully be used to investigate the resistome of bulk tank milk through the application of the shotgun metagenomic sequencing. In accordance with our results, raw milk can be considered a source of AMR bacteria and genes; this points out the importance of properly informing food business operators about the risk associated with poor hygiene practices in the dairy production environment and consumers of the potential microbial food safety risks derived from raw milk products consumption. Translating these findings as risk assessment outputs heralds the next generation of food safety controls.202235840264
345970.9998Diversity of antibiotic resistance gene variants at subsequent stages of the wastewater treatment process revealed by a metagenomic analysis of PCR amplicons. Wastewater treatment plants have been recognised as point sources of various antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARG) which are considered recently emerging biological contaminants. So far, culture-based and molecular-based methods have been successfully applied to monitor antimicrobial resistance (AMR) in WWTPs. However, the methods applied do not permit the comprehensive identification of the true diversity of ARGs. In this study we applied next-generation sequencing for a metagenomic analysis of PCR amplicons of ARGs from the subsequent stages of the analysed WWTP. The presence of 14 genes conferring resistance to different antibiotic families was screened by PCR. In the next step, three genes were selected for detailed analysis of changes of the profile of ARG variants along the process. A relative abundance of 79 variants was analysed. The highest diversity was revealed in the ermF gene, with 52 variants. The relative abundance of some variants changed along the purification process, and some ARG variants might be present in novel hosts for which they were currently unassigned. Additionally, we identified a pool of novel ARG variants present in the studied WWTP. Overall, the results obtained indicated that the applied method is sufficient for analysing ARG variant diversity.202338274111
711080.9998The "best practices for farming" successfully contributed to decrease the antibiotic resistance gene abundances within dairy farms. INTRODUCTION: Farms are significant hotspots for the dissemination of antibiotic-resistant bacteria and genes (ARGs) into the environment and directly to humans. The prevalence of ARGs on farms underscores the need for effective strategies to reduce their spread. This study aimed to evaluate the impact of a guideline on "best practices for farming" aimed at reducing the dissemination of antibiotic resistance. METHODS: A guideline focused on prudent antibiotic use, selective therapy, and hygienic and immune-prophylactic practices was developed and provided to the owners of 10 selected dairy farms and their veterinarians. Fecal samples were collected from lactating cows, dry cows, and calves both before and after the implementation of the guideline. ARGs (bla (TEM), ermB, sul2, and tetA) were initially screened by end-point PCR, followed by quantification using digital droplet PCR. ARG abundance was expressed in relative terms by dividing the copy number of ARGs by the copy number of the 16S rRNA gene. RESULTS: The ARG abundances were higher in lactating cows compared to other categories. Despite similar levels of antibiotic administration (based on veterinary prescription data from the sampled farms) in both sampling campaigns, the total abundance of selected ARGs, particularly bla (TEM) and tetA, significantly decreased after the adoption of the farming guidelines. DISCUSSION: This study highlights the positive impact of prudent antibiotic use and the implementation of farming best practices in reducing the abundance of ARGs. The lactating cow category emerged as a crucial point of intervention for reducing the spread of antibiotic resistance. These findings contribute to ongoing efforts to address antibiotic resistance in farm environments and strengthen the evidence supporting the adoption of good farming practices.202439840338
659490.9998An omics-based framework for assessing the health risk of antimicrobial resistance genes. Antibiotic resistance genes (ARGs) are widespread among bacteria. However, not all ARGs pose serious threats to public health, highlighting the importance of identifying those that are high-risk. Here, we developed an 'omics-based' framework to evaluate ARG risk considering human-associated-enrichment, gene mobility, and host pathogenicity. Our framework classifies human-associated, mobile ARGs (3.6% of all ARGs) as the highest risk, which we further differentiate as 'current threats' (Rank I; 3%) - already present among pathogens - and 'future threats' (Rank II; 0.6%) - novel resistance emerging from non-pathogens. Our framework identified 73 'current threat' ARG families. Of these, 35 were among the 37 high-risk ARGs proposed by the World Health Organization and other literature; the remaining 38 were significantly enriched in hospital plasmids. By evaluating all pathogen genomes released since framework construction, we confirmed that ARGs that recently transferred into pathogens were significantly enriched in Rank II ('future threats'). Lastly, we applied the framework to gut microbiome genomes from fecal microbiota transplantation donors. We found that although ARGs were widespread (73% of genomes), only 8.9% of genomes contained high-risk ARGs. Our framework provides an easy-to-implement approach to identify current and future antimicrobial resistance threats, with potential clinical applications including reducing risk of microbiome-based interventions.202134362925
7384100.9998Uncovering antimicrobial resistance in three agricultural biogas plants using plant-based substrates. Antimicrobial resistance (AMR) is becoming an increasing global concern and the anaerobic digestion (AD) process represents a potential transmission route when digestates are used as fertilizing agents. AMR contaminants, e.g. antibiotic-resistant bacteria (ARB) and plasmid-mediated antibiotic resistance genes (ARGs) have been found in different substrates and AD systems, but not yet been investigated in plant-based substrates. AMR transfer from soils to vegetable microbiomes has been observed, and thus crop material potentially represents a so far neglected AMR load in agricultural AD processes, contributing to AMR spread. In order to test this hypothesis, this study examined the AMR situation throughout the process of three biogas plants using plant-based substrates only, or a mixture of plant-based and manure substrates. The evaluation included a combination of culture-independent and -dependent methods, i.e., identification of ARGs, plasmids, and pathogenic bacteria by DNA arrays, and phylogenetic classification of bacterial isolates and their phenotypic resistance pattern. To our knowledge, this is the first study on AMR in plant-based substrates and the corresponding biogas plant. The results showed that the bacterial community isolated from the investigated substrates and the AD processing facilities were mainly Gram-positive Bacillus spp. Apart from Pantoea agglomerans, no other Gram-negative species were found, either by bacteria culturing or by DNA typing array. In contrast, the presence of ARGs and plasmids clearly indicated the existence of Gram-negative pathogenic bacteria, in both substrate and AD process. Compared with substrates, digestates had lower levels of ARGs, plasmids, and culturable ARB. Thus, digestate could pose a lower risk of spreading AMR than substrates per se. In conclusion, plant-based substrates are associated with AMR, including culturable Gram-positive ARB and Gram-negative pathogenic bacteria-associated ARGs and plasmids. Thus, the AMR load from plant-based substrates should be taken into consideration in agricultural biogas processing.202235306061
3462110.9998Environmental health of water bodies from a Brazilian Amazon Metropolis based on a conventional and metagenomic approach. AIMS: The present study aimed to use a conventional and metagenomic approach to investigate the microbiological diversity of water bodies in a network of drainage channels and rivers located in the central area of the city of Belém, northern Brazil, which is considered one of the largest cities in the Brazilian Amazon. METHODS AND RESULTS: In eight of the analyzed points, both bacterial and viral microbiological indicators of environmental contamination-physical-chemical and metals-were assessed. The bacterial resistance genes, drug resistance mechanisms, and viral viability in the environment were also assessed. A total of 473 families of bacteria and 83 families of viruses were identified. Based on the analysis of metals, the levels of three metals (Cd, Fe, and Mn) were found to be above the recommended acceptable level by local legislation. The levels of the following three physicochemical parameters were also higher than recommended: biochemical oxygen demand, dissolved oxygen, and turbidity. Sixty-three bacterial resistance genes that conferred resistance to 13 different classes of antimicrobials were identified. Further, five mechanisms of antimicrobial resistance were identified and viral viability in the environment was confirmed. CONCLUSIONS: Intense human actions combined with a lack of public policies and poor environmental education of the population cause environmental degradation, especially in water bodies. Thus, urgent interventions are warranted to restore the quality of this precious and scarce asset worldwide.202438627246
4980120.9998Co-selection of antibiotic and disinfectant resistance in environmental bacteria: Health implications and mitigation strategies. BACKGROUND: The rapid emergence of co-selection between antimicrobials, including antibiotics and disinfectants, presents a significant challenge to healthcare systems. This phenomenon exacerbates contamination risks and limits the effectiveness of strategies to combat antibiotic resistance in clinical settings. This study aimed to investigate the prevalence and characteristics of bacteria in hospital environments that exhibit co-selection mechanisms and their potential implications for patient health, framed within the One Health perspective. METHODS: Air and surface samples were collected from seven large hospitals and analyzed to detect antibiotic-resistant bacteria (ARB). The resistance profiles of isolated ARB to various disinfectants were determined. Bacterial species were identified using 16S rRNA gene sequencing, and the presence of antibiotic resistance genes (ARGs) and class 1 integrons (intI1) was investigated. RESULTS: A high percentage (85%) of samples contained ARB, with β-lactam resistance being the most frequently observed. Alarmingly, 94% of isolated ARB exhibited resistance to at least one disinfectant, and 91% demonstrated resistance to three or more disinfectants. Staphylococcus and Bacillus emerged as the dominant genera displaying co-selection. The presence of ARGs, including mecA (associated with methicillin resistance) and qacB (associated with disinfectant resistance), along with intI1, provided further evidence supporting co-selection mechanisms. CONCLUSION: These findings underscore the critical need for robust antimicrobial resistance surveillance and the prudent use of disinfectants in healthcare settings. Further research into co-selection mechanisms is essential to inform the development of effective infection control strategies and minimize the spread of resistant bacteria.202539732420
4653130.9998Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints. Current surveillance of antimicrobial resistance (AMR) is mostly based on testing indicator bacteria using minimum inhibitory concentration (MIC) panels. Metagenomics has the potential to identify all known antimicrobial resistant genes (ARGs) in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and the subsequent spread to the entire population. To make the simulation realistic, the total cost of the surveillance was constrained, and the sampling schedule was set at one pool per month with 5, 20, 50, or 100 samples. Our simulations demonstrate that a pool of 20-50 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time delay to detection of change of [Formula: see text]15 months in all scenarios. Compared with culture-based surveillance, our simulation indicates that there are neither significant reductions nor increases in time to detect a change using metagenomics. The benefit of metagenomics is that it is possible to monitor all known resistance in one sampling and laboratory procedure in contrast to the current monitoring that is based on the phenotypic characterisation of selected indicator bacterial species. Therefore, overall changes in AMR in a population will be detected earlier using metagenomics due to the fact that the resistance gene does not have to be transferred to and expressed by an indicator bacteria before it is possible to detect.202337990114
3238140.9998Extensive metagenomic analysis of the porcine gut resistome to identify indicators reflecting antimicrobial resistance. BACKGROUND: Antimicrobial resistance (AMR) has been regarded as a major threat to global health. Pigs are considered an important source of antimicrobial resistance genes (ARGs). However, there is still a lack of large-scale quantitative data on the distribution of ARGs in the pig production industry. The bacterial species integrated ARGs in the gut microbiome have not been clarified. RESULTS: In the present study, we used deep metagenomic sequencing data of 451 samples from 425 pigs including wild boars, Tibetan pigs, and commercial or cross-bred experimental pigs under different rearing modes, to comprehensively survey the diversity and distribution of ARGs and detect the bacteria integrated in these ARGs. We identified a total of 1295 open reading frames (ORFs) recognized as antimicrobial resistance protein-coding genes. The ORFs were clustered into 349 unique types of ARGs, and these could be further classified into 69 drug resistance classes. Tetracycline resistance was most enriched in pig feces. Pigs raised on commercial farms had a significantly higher AMR level than pigs under semi-free ranging conditions or wild boars. We tracked the changes in the composition of ARGs at different growth stages and gut locations. There were 30 drug resistance classes showing significantly different abundances in pigs between 25 and 240 days of age. The richness of ARGs and 41 drug resistance classes were significantly different between cecum lumen and feces in pigs from commercial farms, but not in wild boars. We identified 24 bacterial species that existed in almost all tested samples (core bacteria) and were integrated 128 ARGs in their genomes. However, only nine ARGs of these 128 ARGs were core ARGs, suggesting that most of the ARGs in these bacterial species might be acquired rather than constitutive. We selected three subsets of ARGs as indicators for evaluating the pollution level of ARGs in samples with high accuracy (r = 0.73~0.89). CONCLUSIONS: This study provides a primary overview of ARG profiles in various farms under different rearing modes, and the data serve as a reference for optimizing the use of antimicrobials and evaluating the risk of pollution by ARGs in pig farms. Video abstract.202235246246
3460150.9997Bioprospecting for β-lactam resistance genes using a metagenomics-guided strategy. Emergence of new antibiotic resistance bacteria poses a serious threat to human health, which is largely attributed to the evolution and spread of antibiotic resistance genes (ARGs). In this work, a metagenomics-guided strategy consisting of metagenomic analysis and function validation was proposed for rapidly identifying novel ARGs from hot spots of ARG dissemination, such as wastewater treatment plants (WWTPs) and animal feces. We used an antibiotic resistance gene database to annotate 76 putative β-lactam resistance genes from the metagenomes of sludge and chicken feces. Among these 76 candidate genes, 25 target genes that shared 40~70% amino acid identity to known β-lactamases were cloned by PCR from the metagenomes. Their resistances to four β-lactam antibiotics were further demonstrated. Furthermore, the validated ARGs were used as the reference sequences to identify novel ARGs in eight environmental samples, suggesting the necessity of re-examining the profiles of ARGs in environmental samples using the validated novel ARG sequences. This metagenomics-guided pipeline does not rely on the activity of ARGs during the initial screening process and may specifically select novel ARG sequences for function validation, which make it suitable for the high-throughput screening of novel ARGs from environmental metagenomes.201728584911
6569160.9997Unveiling Rare Pathogens and Antibiotic Resistance in Tanzanian Cholera Outbreak Waters. The emergence of antibiotic resistance is a global health concern. Therefore, understanding the mechanisms of its spread is crucial for implementing evidence-based strategies to tackle resistance in the context of the One Health approach. In developing countries where sanitation systems and access to clean and safe water are still major challenges, contamination may introduce bacteria and bacteriophages harboring antibiotic resistance genes (ARGs) into the environment. This contamination can increase the risk of exposure and community transmission of ARGs and infectious pathogens. However, there is a paucity of information on the mechanisms of bacteriophage-mediated spread of ARGs and patterns through the environment. Here, we deploy Droplet Digital PCR (ddPCR) and metagenomics approaches to analyze the abundance of ARGs and bacterial pathogens disseminated through clean and wastewater systems. We detected a relatively less-studied and rare human zoonotic pathogen, Vibrio metschnikovii, known to spread through fecal--oral contamination, similarly to V. cholerae. Several antibiotic resistance genes were identified in both bacterial and bacteriophage fractions from water sources. Using metagenomics, we detected several resistance genes related to tetracyclines and beta-lactams in all the samples. Environmental samples from outlet wastewater had a high diversity of ARGs and contained high levels of blaOXA-48. Other identified resistance profiles included tetA, tetM, and blaCTX-M9. Specifically, we demonstrated that blaCTX-M1 is enriched in the bacteriophage fraction from wastewater. In general, however, the bacterial community has a significantly higher abundance of resistance genes compared to the bacteriophage population. In conclusion, the study highlights the need to implement environmental monitoring of clean and wastewater to inform the risk of infectious disease outbreaks and the spread of antibiotic resistance in the context of One Health.202337894148
6570170.9997Impact of point sources on antibiotic resistance genes in the natural environment: a systematic review of the evidence. There is a growing concern about the role of the environment in the dissemination of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG). In this systematic review, we summarize evidence for increases of ARG in the natural environment associated with potential sources of ARB and ARG such as agricultural facilities and wastewater treatment plants. A total of 5247 citations were identified, including studies that ascertained both ARG and ARB outcomes. All studies were screened for relevance to the question and methodology. This paper summarizes the evidence only for those studies with ARG outcomes (n = 24). Sixteen studies were at high (n = 3) or at unclear (n = 13) risk of bias in the estimation of source effects due to lack of information or failure to control for confounders. Statistical methods were used in nine studies; three studies assessed the effect of multiple sources using modeling approaches, and none reported effect measures. Most studies reported higher ARG concentration downstream/near the source, but heterogeneous findings hindered making any sound conclusions. To quantify increases of ARG in the environment due to specific point sources, there is a need for studies that emphasize analytic or design control of confounding, and that provide effect measure estimates.201729231804
6597180.9997Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods. BACKGROUND: With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT: A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS: For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.202336991496
7108190.9997Characterization of the resistome in manure, soil and wastewater from dairy and beef production systems. It has been proposed that livestock production effluents such as wastewater, airborne dust and manure increase the density of antimicrobial resistant bacteria and genes in the environment. The public health risk posed by this proposed outcome has been difficult to quantify using traditional microbiological approaches. We utilized shotgun metagenomics to provide a first description of the resistome of North American dairy and beef production effluents, and identify factors that significantly impact this resistome. We identified 34 mechanisms of antimicrobial drug resistance within 34 soil, manure and wastewater samples from feedlot, ranch and dairy operations. The majority of resistance-associated sequences found in all samples belonged to tetracycline resistance mechanisms. We found that the ranch samples contained significantly fewer resistance mechanisms than dairy and feedlot samples, and that the resistome of dairy operations differed significantly from that of feedlots. The resistome in soil, manure and wastewater differed, suggesting that management of these effluents should be tailored appropriately. By providing a baseline of the cattle production waste resistome, this study represents a solid foundation for future efforts to characterize and quantify the public health risk posed by livestock effluents.201627095377