Resistome Profiles Research Articles

Agricultural land-use change and rotation system exert considerable influences on the soil antibiotic resistome in Lake Tai Basin

In this study, we use high-throughput quantitative polymerase chain reaction approaches to comprehensively assess the effects of agricultural land-use change on the antibiotic resistome of agricultural runoffs after rainfalls in Lake Tai Basin. For the first time in this region, our findings show that orchard runoffs harbored more diverse and abundant antibiotic resistance genes (ARGs) than traditional cropland runoffs. Network analysis demonstrated that orchard runoffs possessed a strong ability for ARG dissemination via horizontal gene transfer. These results suggest that residents might be exposed to a higher public health threat than before. Moreover, the present study confirmed that the rice–wheat rotation system plays a key role in regulating the soil antibiotic resistome profile. Using 16S rRNA high-throughput sequencing technology, this study clarified the relationships between the antibiotic resistome and soil microbiome composition. Finally, we discuss the key environmental factors driving changes in the soil antibiotic resistome. In summary, this study gives insight into the dissemination of environmental ARGs to the people living in the Lake Tai Basin.

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.

High prevalence of blaCTX-M-15 and nosocomial transmission of hypervirulent epidemic clones of Klebsiella pneumoniae at a tertiary hospital in Ethiopia

BackgroundGenomic epidemiology of antibiotic resistance is not sufficiently studied in low-income countries.ObjectivesTo determine prevalence of ESBL production, and resistome and virulome profiles, of Klebsiella pneumoniae isolated at Jimma Medical Center, Ethiopia.MethodsStrains isolated from patients with suspected infections between June and November 2016 were characterized by MALDI-TOF for species identification and disc diffusion for antimicrobial susceptibility testing. All K. pneumoniae isolates were characterized by double disc diffusion for ESBL production and all ESBL-producing strains (ESBL-KP) were subjected to WGS on the Illumina (HiSeq 2500) platform. DNA was extracted by automated systems (MagNA Pure 96). Genome assembly was performed using SPAdes (v. 3.9) and draft genomes were used for analysing molecular features of the strains. Maximum likelihood trees were generated using FastTree/2.1.8 based on SNPs in shared genomic regions to identify transmission clusters.ResultsOf the 146 K. pneumoniae strains isolated, 76% were ESBL-KP; 93% of the ESBL-KP strains showed resistance to multiple antimicrobial classes. blaCTX-M-15 (84.4%) was the most prevalent ESBL gene. Resistance genes for aminoglycosides and/or fluoroquinolones [aac(6′)-Ib-cr (65.1%)], phenicols [catB3 (28.4%)], sulphonamides [sul1 (61.2%) and sul2 (60.5%)], trimethoprim [dfrA27 (32.1%)], macrolides [mph(A) (12.8%)] and rifampicin [arr2/arr3 (39.4%)] were prevalent. Plasmids of the IncF and IncR families were prevalent among ST218, ST147, ST15 and ST39. KL64 and KL57 capsular types and O1 and O2 LPSs were prevalent. A high-risk clone, ST218-KL57 encoding rmpA1/rmpA2 and iutA, was detected. Phylogenetic analysis showed a cluster of clonally related strains from different units of the hospital.ConclusionsPrevalence of ESBL-KP was high and blaCTX-M-15 was the predominant ESBL gene. ESBL genes had spread through both clonal and polyclonal expansion of high-risk and hypervirulent clones. Nosocomial transmission of MDR strains between different units of the hospital was observed.

ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data.

The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.

Resistome and microbial profiling of pediatric patient’s gut infected with multidrug-resistant diarrhoeagenic Enterobacteriaceae using next-generation sequencing; the first study from Pakistan

ABSTRACT A high prevalence of multidrug-resistant (MDR) pathogens has been reported in adult and pediatric populations of Pakistan. However, data describing the effect of MDR microbes on the gut microbiota is scarce. We designed a cross-sectional pediatric study to investigate the effect of MDR microbes’ infection on the gut microbiome and its resistome of children using high-throughput next-generation sequencing (NGS). A cross-sectional study was conducted at a tertiary health care hospital in Peshawar Pakistan, between 5 September 2019 to 15 February 2020. Pediatric patients with acute gastroenteritis (n = 200) were enrolled. All the enrolled pediatric patients underwent initial antimicrobial resistance (AMR) screening using the disk diffusion method. Children with MDR infections were identified and selected for gut microbiome and its resistome profiling using NGS. Out of 200 enrolled pediatric patients, 80 (40%) were found infected with MDR diarrheagenic Enterobacteriaceae consisting of 50 (62.5%) infections caused by extended-spectrum beta-lactamase (ESBL) producing E. coli while 30 (37.5%) by MDR Enterobacter specie. A total of 63 and 17 antibiotic-resistant genes (ARGs) conferring resistance to 7 and 5 classes of antibiotics were identified in the resistomes of MDR diarrheagenic Enterobacteriaceae infected and healthy children, respectively. NGS-based gut microbial profiling of MDR Enterobacter spp., ESBL producing E. coli infected pediatric patients and healthy controls revealed the predominance of Proteobacteria and Actinobacteria, respectively. An increased abundance of several pathogenic gram-negative bacteria namely E. coli, Enterobacter cloacae, and Salmonella enterica was observed in the gut microbiota of children infected with MDR bacterial infections than that of the healthy controls. This work indicates that children with MDR infections have reduced microbial diversity and enriched ARGs than healthy controls. The emergence of MDR bacterial strains and their association with gut dysbiosis needs immediate attention to regulate antibiotics usage in Pakistani children.

1078. Renal Transplant Recipient Resistomes Reveal Expansive Sub-Clinical Burden of Resistance After Treatment for ESBL-Producing Bacterial Infections

BackgroundRenal transplant recipients have frequent infection and colonization with antibiotic resistant (AR) bacteria. However, little is known about the burden of AR following targeted antibiotic treatment.MethodsThis was a prospective study conducted as part of a single center clinical trial at Emory University. Demographic and clinical data regarding transplant and AR bacterial infection were abstracted. Stool samples were collected from renal transplant recipients treated with antibiotics for ESBL-producing gram negative infections. Bacterial cultures with AR-selective media and Illumina short-read sequencing were performed on stool samples. Confirmatory phenotypic isolate AR testing was performed with the Vitek2 platform. Resistome profiles were produced by assembling short reads into scaffolds using MetaSPAdes, predicting protein coding sequences using Prodigal and classifying proteins as antimicrobial resistance determinants using AMRFinderPlus. AMRFinderPlus results for patients were then compared to fecal metagenomes from 3 healthy Human Microbiome Project controls. Differences in AR genes in renal transplant patients vs controls were compared.ResultsMetagenome sequencing was performed for 6 (5 female) patient stool samples. Stools were collected a median of 30 days after infection. The median number of AR genes per patient metagenome was 48.5 (range 23 to 87 genes). The median number of AR genes per control metagenome was 24 (range 16 to 25 genes). We detected 97 unique AR genes across all samples, 63 of which (65%) were detected in patient samples but not controls. All AR genes found in control metagenomes were present in at least one patient metagenome. No AR genes detected in patients were common to all patients. Subsets of clinically relevant genes corresponded with patient stool AR bacteria culture results.Antimicrobial resistance gene detection heatmap for renal transplant recipient stool samples after antibiotic treatment for ESBL infection. ConclusionViable AR bacteria and diverse AR gene profiles were frequently detected from renal transplant recipient stool samples after antibiotic treatment for infection. These data suggest that AR bacterial colonization and AR gene profiles may require distinct treatments other than systemic antibiotics for eradication.Disclosures All Authors: No reported disclosures

Prevalence of antibiotic resistance genes and bacterial pathogens along the soil–mangrove root continuum

Plants roots are colonised by soil bacteria that are known to be the reservoir of antibiotic resistance genes (ARGs). ARGs can transfer between these microorganisms and pathogens, but to what extent these ARGs and pathogens disseminate from soil into plant is poorly understood. Here, we examined a high-resolution resistome profile along the soil–root continuum of mangrove saplings using amplicon and metagenomic sequencing. Data revealed that 91.4% of total ARGs were shared across four root–associated compartments (endosphere, episphere, rhizosphere and unplanted soil). Rather than compartment-selective dynamics of microbiota, the resistome was disseminated in a continuous fashion along the soil–root continuum. Such dissemination was independent of underlying root–associated bacterial and fungal microbiota, but might be facilitated by a multiplicity of mobile genetic elements. As the multiple-drug resistant pathogens, Vibrio vulnificus, pathogenic Escherichia coli and Klebsiella pneumoniae consistently predominated across four compartments, indicating the potential dissemination of antibiotic pathogens along the soil–root continuum. Through deciphering the profile and dynamics of the root–associated resistome and pathogens, our study identified the soil–root continuum as an interconnected sink through which certain ARGs and pathogens can flow from soil into the plant.

Cross-comparison of methods for quantifying antibiotic resistance in agricultural soils amended with dairy manure and compost

Agricultural soils are often amended with livestock manure, making them a key reservoir of antibiotic resistance genes (ARGs). Given that soils are among the most microbially-diverse environments on the planet; effective characterization and quantification of the effects of manure-derived amendments on soil resistomes is a major challenge. This study examined the effects of dairy manure-derived amendments on agricultural soils via two strategies: quantification of anthropogenic ARG markers via qPCR and shotgun metagenomic resistome profiling; and these strategies were compared to a previously published antibiotic resistant fecal coliform dataset. Soil samples were collected throughout a 120 day complete block field experiment to compare the effects of amendment type on antibiotic resistance. Results of all three measurements were consistent with the hypothesis that the application of composted manure reduced antibiotic resistance in soil relative to the application of raw manure, although some differences were noted in comparing the patterns of the three measurements with time. Raw dairy manure-amended soils yielded high sul1 and tet(W) relative abundances on Day 0 (following amendment application), but significantly decreased to background levels by Day 67 (harvest) and Day 120 (study completion). Shotgun metagenomics similarly detected a decrease in the relative abundances of sulfonamide and tetracycline-associated ARGs over time in the raw manure- and compost-amended soils; however, these levels were significantly lower than those estimated by qPCR. Interestingly, although patterns of sulfonamide and tetracycline resistance among culturable fecal coliforms echoed those observed via qPCR and metagenomics; erythromycin resistant coliforms were directly recovered by culture in amended soils, but corresponding ARGs were not detected by qPCR or metagenomics. This study supports both composting and time restrictions as means of reducing the potential for antibiotic resistance in manure to spread via soil application. Results suggest some differences in finer conclusions drawn depending on which antibiotic resistance monitoring target is selected.

UCARE Chem Suite and uCAREChemSuiteCLI: An online tool and a standalone R package for the prediction of drug resistome

Background: In the era of antibiotic resistance, the prediction of bacterial resistome profiles, likely to cause resistance against novel drugs is of utmost importance. Despite this, to the best of our knowledge, no tool exists for the same. Therefore, with the rationale that drugs with similar structures have similar resistome profiles, two algorithms were developed viz., the deterministic model and the stochastic model to predict bacterial resistome for uncharacterized, but potential chemical structures. Methods and materials: Two separate databases were developed for Escherichia coli and Pseudomonas aeruginosa through exhaustive manual curation of published literature. Prediction of drug classes and bacterial resistome was carried out by the rules-based algorithm in the deterministic model, whereas the nearest neighbor algorithm was utilized in the stochastic model. Results: The models have been implemented in both standalone R package and an online server i.e., uCAREChemSuiteCLI and uCARE Chem Suite. In addition to resistome prediction, the online version of the suite enables the user to visualize the chemical structure, classify compound in predefined 19 drug classes, perform pairwise alignment and cluster with database compounds using graphical user interface. uCARE Chem Suite can be browsed from http://ucare.chem.e-bioinformatics.net, whereas uCAREChemSuiteCLI can be installed from CRAN (https://cran.r-project.org/package=uCAREChemSuiteCLI) and GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI). Conclusion: We envisage that the said tool will enable the acceleration of the traditional drug discovery pipeline.

The distribution of microbiomes and resistomes across farm environments in conventional and organic dairy herds in Pennsylvania

BackgroundAntimicrobial resistance is a serious concern. Although the widespread use of antimicrobials in livestock has exacerbated the emergence and dissemination of antimicrobial resistance genes (ARG) in farm environments, little is known about whether antimicrobial use affects distribution of ARG in livestock systems. This study compared the distribution of microbiomes and resistomes (collections of ARG) across different farm sectors in dairy herds that differed in their use of antimicrobials. Feces from heifers, non-lactating, and lactating cows, manure storage, and soil from three conventional (antimicrobials used to treat cows) and three organic (no antimicrobials used for at least four years) farms in Pennsylvania were sampled. Samples were extracted for genomic DNA, processed, sequenced on the Illumina NextSeq platform, and analyzed for microbial community and resistome profiles using established procedures.ResultsMicrobial communities and resistome profiles clustered by sample type across all farms. Overall, abundance and diversity of ARG in feces was significantly higher in conventional herds compared to organic herds. The ARG conferring resistance to betalactams, macrolide-lincosamide-streptogramin (MLS), and tetracyclines were significantly higher in fecal samples of dairy cows from conventional herds compared to organic herds. Regardless of farm type, all manure storage samples had greater diversity (albeit low abundance) of ARG conferring resistance to aminoglycosides, tetracyclines, MLS, multidrug resistance, and phenicol. All soil samples had lower abundance of ARG compared to feces, manure, and lagoon samples and were comprised of ARG conferring resistance to aminoglycosides, glycopeptides, and multi-drug resistance. The distribution of ARG is likely driven by the composition of microbiota in the respective sample types.ConclusionsAntimicrobial use on farms significantly influenced specific groups of ARG in feces but not in manure storage or soil samples.

Plant resistome profiling in evolutionary old bog vegetation provides new clues to understand emergence of multi-resistance

The expanding antibiotic resistance crisis calls for a more in depth understanding of the importance of antimicrobial resistance genes (ARGs) in pristine environments. We, therefore, studied the microbiome associated with Sphagnum moss forming the main vegetation in undomesticated, evolutionary old bog ecosystems. In our complementary analysis of culture collections, metagenomic data and a fosmid library from different geographic sites in Europe, we identified a low abundant but highly diverse pool of resistance determinants, which targets an unexpectedly broad range of 29 antibiotics including natural and synthetic compounds. This derives both, from the extraordinarily high abundance of efflux pumps (up to 96%), and the unexpectedly versatile set of ARGs underlying all major resistance mechanisms. Multi-resistance was frequently observed among bacterial isolates, e.g. in Serratia, Rouxiella, Pandoraea, Paraburkholderia and Pseudomonas. In a search for novel ARGs, we identified the new class A β-lactamase Mm3. The native Sphagnum resistome comprising a highly diversified and partially novel set of ARGs contributes to the bog ecosystem´s plasticity. Our results reinforce the ecological link between natural and clinically relevant resistomes and thereby shed light onto this link from the aspect of pristine plants. Moreover, they underline that diverse resistomes are an intrinsic characteristic of plant-associated microbial communities, they naturally harbour many resistances including genes with potential clinical relevance.

Study of indiscriminate distribution of restrained antimicrobial resistome of different environmental niches.

Prophylactic usage and high persistent nature of several antibiotics have put selective pressure on the native microbial population that led to the emergence, propagation, and persistence of antibiotic resistance in nature. The surveillance of antibiotic resistome pattern and identification of points of intervention throughout the different environmental habitats will help to break the flow of antibiotic resistance from environmental bacteria to human pathogens. The present study compares the occurrence, diversity, and abundance of ARGs in industrial sludge, wetland sludge, and sediment sample contaminated with pharmaceutical discharge. Metagenomes were mined for the presence of ARGs against the ResFinder 3.2 database using BLASTn program. Pharmaceutical sample (2.52%) showed high degree of ARG abundance and richness as compared with ETP sludge (2.28%) and wetland sludge samples (1.29%). The modern resistome pattern represented by critically important resistance genes against tetracycline (tetA, tetC, tetW, tetT, and tetS/M) and quinolone (qnrS, qnrVC, and qnrD) was identified in pharmaceutical sediment sample. However, effluent treatment plant (ETP) sludge sample showed abundance of multidrug efflux pumps indicating the presence of primitive resistome profile. In conclusion, the indiscriminate distribution pattern of antibiotic resistance genes in three selected environmental sites suggests enrichment and distribution of environmental niche-driven resistance. The study also suggests effluent discharge site from pharmaceutical industries and ETPs as pivotal points of intervention for the mitigation of antibiotic resistance.

Metagenomic insights into differences in environmental resistome profiles between integrated and monoculture aquaculture farms in China

Cumulative research on resistomes and microbiomes from aquatic environments has revealed that both integrated freshwater and monoculture freshwater aquaculture systems can cause the development and dissemination of antibiotic resistance genes (ARGs) and associated mobile genetic elements (MGEs). However, few studies have examined differences in resistomes between the different aquaculture modes, and those that do have focused on antibiotic residues or individual resistance genes. In the current study, we collected 44 environmental samples from two monoculture freshwater aquaculture farms and four integrated farms (two duck and fish farms, two laying duck and fish farms) in Guangdong, China, in 2018. After measuring the concentrations of antibiotic residues in the samples, we characterized MGEs and ARGs and examined their association with potential bacterial hosts in the microbial communities using high-throughput sequencing-based metagenomic and network analyses. We then compared the resistome profiles of the different aquaculture models. We found that the number and total relative abundance of ARG and MGE subtypes in the integrated (fish and duck/laying duck) farm samples were significantly higher than those in samples from monoculture freshwater aquaculture farms. Specifically, both the mobile colistin resistance genes mcr variants and tigecycline resistance gene tet(X) variants in integrated farms exhibited higher total relative abundance than that in monoculture farms. Moreover, the interrelationships among ARGs and microbial taxa, ARGs and MGEs, and MGEs and microbial taxa in the integrated farm samples were also more complex than those observed in monoculture freshwater aquaculture farm samples. Meanwhile, the species of Acinetobacter and Escherichia were identified to be the possible host of tet(X) and ESBL gene blaCTX-M in aquaculture, respectively. To the best of our knowledge, this is the first metagenomic study to analyze differences in resistome profiles between integrated and monoculture ponds. Overall, integrated aquaculture systems exhibited a higher prevalence of resistance genes compared with monoculture freshwater aquaculture farms. Therefore, additional antimicrobial resistance surveillance should be focused on this type of freshwater aquaculture system.

Effect of mesophilic anaerobic digestion on the resistome profile of dairy manure

The effect of mesophilic anaerobic digestion (AD) on the resistome profile of manures from two different dairy farms was evaluated using a metagenomic approach. A total of 187 unique Antibiotic resistance genes (ARGs) for 17 different classes of antibiotics were detected in raw (undigested) manures. The results indicate that regardless of the origin of the dairy manure, mesophilic AD was capable of reducing or enriching the relative abundance of some ARGs. The main driver of these changes was strongly correlated with the evolution of the microbial community during the AD process. Putative ARG hosts were suggested by analyses of the co-occurrence of microbial groups and ARGs. Finally, network analyses revealed that mesophilic AD could also reduce the co-occurrence of different groups of ARGs potentially located in the same genetic elements. Our results provide valuable insights into the microbial mechanisms driving the diversity and abundance of ARGs during mesophilic AD.

UCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction

In the era of antibiotic resistance, in silico prediction of bacterial resistome profiles, likely to be associated with inactivation of new potential antibiotics is of utmost importance. Despite this, to the best of our knowledge, no tool exists for such prediction. Therefore, under the rationale that drugs with similar structures have similar resistome profiles, we developed two models, a deterministic model and a stochastic model, to predict the bacterial resistome likely to neutralize uncharacterized but potential chemical structures. The current version of the tool involves the prediction of a resistome for Escherichia coli and Pseudomonas aeruginosa. The deterministic model on omitting two diverse but relatively less characterized drug classes, polyketides and polypeptides showed an accuracy of 87%, a sensitivity of 85%, and a precision of 89%, whereas the stochastic model predicted antibiotic classes of the test set compounds with an accuracy of 72%, a sensitivity of 75%, and a precision of 83%. The models have been implemented in both a standalone package and an online server, uCAREChemSuiteCLI and uCARE Chem Suite, respectively. In addition to resistome prediction, the online version of the suite enables the user to visualize the chemical structure, classify compounds in 19 predefined drug classes, perform pairwise alignment, and cluster with database compounds using a graphical user interface. AvailabilityuCARE Chem Suite can be browsed at: https://sauravsaha.shinyapps.io/ucarechemsuite2/, and uCAREChemSuiteCLI can be installed from:1. CRAN (https://cran.r-project.org/package=uCAREChemSuiteCLI) and2. GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI).

Microbiome and antibiotic resistome in household dust from Beijing, China

We spend ever-increasing time indoors along with urbanization; however, the geographical distribution patterns of microbiome and antibiotic resistome, and their driving forces in household environment remains poorly characterized. Here, we surveyed the bacterial and fungal communities, and the resistome in settled dust gathered from 82 homes located across Beijing, China, employing Illumina sequencing and high-throughput quantitative PCR techniques. There was no clear geographical distribution pattern in dust-related bacterial communities although a slight but significant (P < 0.05) distance-decay relationship occurred in its community similarity; by contrast, a relatively distinct geographical clustering and a stronger distance-decay relationship were observed in fungal communities at the local scale. The cross-domain (bacteria versus fungi) relationships in the microbiome of the dust samples were mostly observed as robust co-occurrence correlations. The bacterial communities were dominated by Proteobacteria and Actinobacteria phyla, with human skin, soil and plants being potential major sources. The fungal communities largely comprised potential allergens (a median 61% of the fungal sequences), with Alternaria genus within Ascomycota phylum being the most predominant taxa. The profile of dust-related bacterial communities was mainly affected by housing factors related to occupants and houseplants, while that of fungal communities was determined by georeferenced environmental factors, particularly vascular plant diversity. Additionally, a great diversity (1.96 on average for Shannon index) and normalized abundance (2.22 copies per bacterial cell on average) of antibiotic resistance genes were detected across the dust samples, with the dominance of genes resistant to vancomycin and Macrolide-Lincosamide-Streptogramin B. The resistome profile exhibited no distinct geographical pattern, and was primarily driven by certain bacterial phyla and occupancy-related factors. Overall, we underline the significance of anthropogenic impacts and house location in structuring bacterial and fungal communities inside homes, respectively, and suggest that household dust is an overlooked reservoir for antibiotic resistance.

Residential urban stormwater runoff: A comprehensive profile of microbiome and antibiotic resistance

Non-point stormwater runoff is a major contamination source of receiving waterbodies. Heightened incidence of waterborne disease outbreaks related to recreational use and source water contamination is associated with extreme rainfall events. Such extreme events are predicted to increase in some regions due to climate change. Consequently, municipal separate storm sewer systems (MS4s) conveying pathogens to receiving waters are a growing public health concern. In addition, the spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria in various environmental matrices, including urban runoff, is an emerging threat. The resistome and microbiota profile of MS4 discharges has yet to be fully characterized. To address this knowledge gap, we first analyzed the relationship between rainfall depth and intensity and E. coli densities (fecal indicator) in stormwater from four MS4 outflows in Columbus, Ohio, USA during the spring and summer of 2017. Microbial source tracking (MST) was conducted to examine major fecal contamination sources in the study sewersheds. A subset of samples was analyzed for microbial and resistome profiles using a metagenomic approach. The results showed a significant positive relationship between outflow E. coli density and rainfall intensity. MST results indicate prevalent fecal contamination from ruminant populations in the study sites (91% positive among the samples tested). Protobacteria and Actinobacteria were two dominant bacteria at a phylum level. A diverse array of ARGs and potentially pathogenic bacteria (e.g. Salmonella enterica Typhimurium), fungi (e.g. Scedosporium apiospermum), and protists (e.g. Acanthamoeba palestinensis) were found in urban stormwater outflows that discharge into adjacent streams. The most prevalent ARGs among samples were β-lactam resistance genes and the most predominant virulence genes within bacterial community were related with Staphylococcus aureus. A comprehensive contamination profile indicates a need for sustainable strategies to manage urban stormwater runoff amid increasingly intense rainfall events to protect public and environmental health.

SraX: A Novel Comprehensive Resistome Analysis Tool.

The accurate identification of the assortment of antibiotic resistance genes within a collection of genomes enables the discernment of intricate antimicrobial resistance (AMR) patterns while depicting the diversity of resistome profiles of the analyzed samples. The availability of large amount of sequence data, owing to the advancement of novel sequencing technologies, have conceded exciting possibilities for developing suitable AMR exploration tools. However, the level of complexity of bioinformatic analyses has raised as well, since the achievement of desired results involves executing several challenging steps. Here, sraX is proposed as a fully automated analytical pipeline for performing a precise resistome analysis. Our nominated tool is capable of scrutinizing hundreds of bacterial genomes in-parallel for detecting and annotating putative resistant determinants. Particularly, sraX presents unique features: genomic context analysis, validation of known mutations conferring resistance, illustration of drug classes and type of mutated loci proportions and integration of results into a single hyperlinked navigable HTML-formatted file. Furthermore, sraX also exhibits relevant operational features since the complete analysis is accomplished by executing a single-command step. The capacity and efficacy of sraX was demonstrated by re-analyzing 197 strains belonging to Enterococcus spp., from which we confirmed 99.15% of all detection events that were reported in the original study. sraX can be downloaded from https://github.com/lgpdevtools/srax.

Abundance and diversity of resistomes differ between healthy human oral cavities and gut

The global threat of antimicrobial resistance has driven the use of high-throughput sequencing techniques to monitor the profile of resistance genes, known as the resistome, in microbial populations. The human oral cavity contains a poorly explored reservoir of these genes. Here we analyse and compare the resistome profiles of 788 oral cavities worldwide with paired stool metagenomes. We find country and body site-specific differences in the prevalence of antimicrobial resistance genes, classes and mechanisms in oral and stool samples. Within individuals, the highest abundances of antimicrobial resistance genes are found in the oral cavity, but the oral cavity contains a lower diversity of resistance genes compared to the gut. Additionally, co-occurrence analysis shows contrasting ARG-species associations between saliva and stool samples. Maintenance and persistence of antimicrobial resistance is likely to vary across different body sites. Thus, we highlight the importance of characterising the resistome across body sites to uncover the antimicrobial resistance potential in the human body.

Drinking water treatment residuals from cyanobacteria bloom-affected areas: Investigation of potential impact on agricultural land application

In cyanobacteria bloom-affected areas, drinking water treatment processes are optimized to ensure the absence of cyanotoxins in their finished water. A concern about the sludge generated from water treatment has emerged because the removed cyanotoxins and cyanobacteria can get concentrated in the sludge, called water treatment residuals (WTR), and these WTR are often applied on land for beneficial purposes. However, the impact of WTR from bloom-affected areas on the agricultural application and public health is hardly reported. The objective of this study was to characterize bloom-affected WTR by focusing on cyanotoxins, toxin-producing cyanobacteria, microbiomes, and resistome profiles. In addition, the fate of WTR-originated microcystin in crops and soil was examined.WTR samples were obtained from a bloom-affected area in Ohio, USA in November 2017. Cyanotoxins and toxin-producing cyanobacteria were quantified with the enzyme-linked immunosorbent assay and droplet digital PCR, respectively. Microbiome and resistome were determined with Nanopore sequencing. Cyanotoxin concentrations were measured: microcystin (259 μg/kg), saxitoxin (0.16 μg/kg), anatoxin-a (not detected), and β-Methylamino-L-alanine (BMAA) (575 μg/kg). MC-producing cyanobacteria concentrations were determined: Planktothrix (5.3 × 107 gene copies/g) and Microcystis (3.3 × 103 gene copies/g). Proteobacteria was the most predominant and Planktothrix phage was a remarkably dominant virus in the WTR microbiome. Aminoglycoside resistance was the most abundant class, and antibiotic resistance was found in multiple pathogens (e.g. Mycobacterium).WTR land application was simulated by growing carrots with a mixture of WTR and soil in a greenhouse. At harvest, ~80% of WTR-originated microcystin was found in the soil (83–96 μg/kg) and 5% accumulated in carrots (19–28 μg/kg). This study provides the first insight into the cyanotoxin, microbiome, and resistome profile of bloom-affected WTR. Our finding suggests that careful WTR management is needed for the beneficial use of WTR for protecting agricultural environments, especially soil and groundwater, and food safety.