Detection Of Antibiotic Resistance Genes Research Articles

The drainome: longitudinal metagenomic characterisation of wastewater from hospital ward sinks to characterize the microbiome and resistome and assess the effects of decontamination interventions

BackgroundHospital drains and water interfaces are implicated in nosocomial transmission of pathogens. Metagenomics can assess the microbial composition and presence of antimicrobial resistance genes in drains (‘the drainome’) but studies applying these methods longitudinally and to assess infection control interventions are lacking. AimApply long-read metagenomics coupled with microbiological measurements to investigate the drainome and assess the effects of a peracetic acid-containing decontamination product. Methods12-week study in three phases: a baseline phase, an intervention phase of enhanced decontamination with peracetic acid, and a post-intervention phase. Five hospital sink drains on an intensive care unit were sampled twice weekly. Each sample had 1) measurement of total viable count (TVC), 2) metagenomic analyses including i) taxonomic classification of bacteria and fungi ii) antibiotic resistance gene detection iii) plasmid identification, and 3) immunochromatographic detection of antimicrobial residues. FindingsOverall TVCs remain unchanged in the intervention phase (+386 CFU/mL, SE 705, p=0.59). There was a small but significant increase in the microbial diversity in the intervention phase (-0.07 in Simpson’s index, SE 0.03, p=0.007), which was not sustained post-intervention (-0.05, SE 0.03, p=0.08). The intervention was associated with increased relative abundance of the Pseudomonas genus (18.3% to 40.5% [+22.2%], SE 5.7%, p<0.001). Extended spectrum beta-lactamases were found in all samples, with NDM-carbapenemase found in 3 drains in 6 samples. Antimicrobial residues were detected in a large proportion of samples (31/115, 27%), suggesting use of sinks for non-handwashing activities. ConclusionsMetagenomics and other measurements can measure the composition of the drainome and assess the effectiveness of decontamination interventions.

Molecular detection of Antibiotic resistance genes (TEM, GES and OXA) in Uropathogens

Molecular detection of Antibiotic resistance genes (TEM, GES and OXA) in Uropathogens

Optimized Antibiotic Resistance Genes Monitoring Scenarios Promote Sustainability of Urban Water Cycle.

Dissemination of antibiotic resistance genes (ARGs) in urban water bodies has become a significant environmental and health concern. Many approaches based on real-time quantitative PCR (qPCR) have been developed to offer rapid and highly specific detection of ARGs in water environments, but the complicated and time-consuming procedures have hindered their widespread use. Herein, we developed a facile one-step approach for rapid detection of ARGs by leveraging the trans-cleavage activity of Cas12a and recombinase polymerase amplification (RPA). This efficient method matches the sensitivity and specificity of qPCR and requires no complex equipment. The results show a strong correlation between the prevalence of four ARG markers (ARGs: sul1, qnrA-1, mcr-1, and class 1 integrons: intl1) in tap water, human urine, farm wastewater, hospital wastewater, municipal wastewater treatment plants (WWTPs), and proximate natural aquatic ecosystems, indicating the circulation of ARGs within the urban water cycle. Through monitoring the ARG markers in 18 WWTPs in 9 cities across China during both peak and declining stages of the COVID epidemic, we found an increased detection frequency of mcr-1 and qnrA-1 in wastewater during peak periods. The ARG detection method developed in this work may offer a useful tool for promoting a sustainable urban water cycle.

High-throughput microfluidic quantitative PCR system for the simultaneous detection of antibiotic resistance genes and bacterial and viral pathogens in wastewater

Comprehensive data on bacterial and viral pathogens of diarrhea and studies applying culture-independent methods for examining antibiotic resistance in wastewater are lacking. This study aimed to simultaneously quantify antibiotic resistance genes (ARGs), class 1 integron-integrase (int1), bacterial and viral pathogens of diarrhea, 16S rRNA, and other indicators using a high-throughput quantitative PCR (HT-qPCR) system. Thirty-six grab wastewater samples from a wastewater treatment plant in Japan, collected three times a month between August 2022 and July 2023, were centrifuged, followed by nucleic acid extraction, reverse transcription, and HT-qPCR. Fourteen targets were included, and HT-qPCR was performed on the Biomark X9™ System (Standard BioTools). For all qPCR assays, R2 was ≥0.978 and the efficiencies ranged from 90.5% to 117.7%, exhibiting high performance. Of the 36 samples, 20 (56%) were positive for Norovirus genogroup II (NoV-GII), whereas Salmonella spp. and Campylobacter jejuni were detected in 24 (67%) and Campylobacter coli in 13 (36%) samples, with mean concentrations ranging from 3.2 ± 0.8 to 4.7 ± 0.3 log10 copies/L. NoV-GII detection ratios and concentrations were higher in winter and spring. None of the pathogens of diarrhea correlated with acute gastroenteritis cases, except for NoV-GII, suggesting the need for data on specific bacterial infections to validate bacterial wastewater-based epidemiology (WBE). All samples tested positive for sul1, int1, and blaCTX-M, irrespective of season. The less explored blaNDM-1 showed a wide prevalence (>83%) and consistent abundance ranging from 4.3 ± 1.0 to 4.9 ± 0.2 log10 copies/L in all seasons. sul1 was the predominant ARG, whereas absolute abundances of 16S rRNA, int1, and blaCTX-M varied seasonally. int1 was significantly correlated with blaCTX-M in autumn and spring, whereas it showed no correlation with blaNDM-1, questioning the applicability of int1 as a sole indicator of overall resistance determinants. This study exhibited that the HT-qPCR system is pivotal for WBE.

Whole genome sequencing analysis on antibiotic-resistant Escherichia coli isolated from pig farms in Banten Province, Indonesia.

The emergence and rapid increase in the incidence of multidrug-resistant (MDR) bacteria in pig farms has become a serious concern and reduced the choice of effective antibiotics. This study analyzed the phylogenetics and diversity of antibiotic resistance genes (ARGs) and molecularly identified the source of ARGs in antibiotic-resistant Escherichia coli isolated from pig farms in Banten Province, Indonesia. Forty-four antibiotic-resistant E. coli isolates from fecal samples from 44 pig farms in Banten Province, Indonesia, were used as samples. The samples were categorized into 14 clusters. Sequencing was performed using the Oxford Nanopore Technologies MinION platform, with barcoding before sequencing with Nanopore Rapid sequencing gDNA-barcoding (SQK-RBK110.96) according to manufacturing procedures. ARG detection was conducted using ResFinder, and the plasmid replicon was determined using PlasmidFinder. Three phylogenetic leaves of E. coli were identified in the pig farming cluster in Banten Province. The E. coli isolates exhibited potential resistance to nine classes of antibiotics. Fifty-one ARGs were identified across all isolates, with each cluster carrying a minimum of 10 ARGs. The ant(3'')-Ia and qnrS1 genes were present in all isolates. ARGs in the E. coli pig farming cluster originated mainly from plasmids, accounting for an average of 89.4%. The elevated potential for MDR events, coupled with the dominance of ARGs originating from plasmids, increases the risk of ARG spread among bacterial populations in animals, humans, and the environment.

Spread of antibiotic resistance genes in drinking water reservoirs: Insights from a deep metagenomic study using a curated database

The exploration of antibiotic resistance genes (ARGs) in drinking water reservoirs is an emerging field. Using a curated database, we enhanced the ARG detection and conducted a comprehensive analysis using 2.2 Tb of deep metagenomic sequencing data to determine the distribution of ARGs across 16 drinking water reservoirs and associated environments. Our findings reveal a greater diversity of ARGs in sediments than in water, underscoring the importance of extensive background surveys. Crucial ARG carriers—specifically Acinetobacter, Pseudomonas, and Mycobacterium were identified in drinking water reservoirs. Extensive analysis of the data uncovered a considerable concern for drinking water safety, particularly in regions reliant on river sources. Mobile genetic elements have been found to contribute markedly to the propagation of ARGs. The results of this research suggest that the establishment of drinking water reservoirs for supplying raw water may be an effective strategy for alleviating the spread of water-mediated ARGs.

City-scale monitoring of antibiotic resistance genes by digital PCR and metagenomics

BackgroundAnthropogenic activities significantly contribute to the dissemination of antibiotic resistance genes (ARGs), posing a substantial threat to humankind. The development of methods that allow robust ARG surveillance is a long-standing challenge. Here, we use city-scale monitoring of ARGs by using two of the most promising cutting-edge technologies, digital PCR (dPCR) and metagenomics.MethodsARG hot-spots were sampled from the urban water and wastewater distribution systems. Metagenomics was used to provide a broad view of ARG relative abundance and richness in the prokaryotic and viral fractions. From the city-core ARGs in all samples, the worldwide dispersed sul2 and tetW conferring resistance to sulfonamide and tetracycline, respectively, were monitored by dPCR and metagenomics.ResultsThe largest relative overall ARG abundance and richness were detected in the hospital wastewater and the WWTP inlet (up to ≈6,000 ARGs/Gb metagenome) with a large fraction of unclassified resistant bacteria. The abundance of ARGs in DNA and RNA contigs classified as viruses was notably lower, demonstrating a reduction of up to three orders of magnitude compared to contigs associated to prokaryotes. By metagenomics and dPCR, a similar abundance tendency of sul2 and tetW was obtained, with higher abundances in hospital wastewater and WWTP input (≈125–225 ARGs/Gb metagenome). dPCR absolute abundances were between 6,000 and 18,600 copies per ng of sewage DNA (≈105–7 copies/mL) and 6.8 copies/mL in seawater near the WWTP discharging point.ConclusionsdPCR was more sensitive and accurate, while metagenomics provided broader coverage of ARG detection. While desirable, a reliable correlation of dPCR absolute abundance units into metagenomic relative abundance units was not obtained here (r2 < 0.4) suggesting methodological factors that introduce variability. Evolutionary pressure does not significantly select the targeted ARGs in natural aquatic environments.

Sensitivity and consistency of long- and short-read metagenomics and epicPCR for the detection of antibiotic resistance genes and their bacterial hosts in wastewater

Wastewater surveillance is a powerful tool to assess the risks associated with antibiotic resistance in communities. One challenge is selecting which analytical tool to deploy to measure risk indicators, such as antibiotic resistance genes (ARGs) and their respective bacterial hosts. Although metagenomics is frequently used for analyzing ARGs, few studies have compared the performance of long-read and short-read metagenomics in identifying which bacteria harbor ARGs in wastewater. Furthermore, for ARG host detection, untargeted metagenomics has not been compared to targeted methods such as epicPCR. Here, we 1) evaluated long-read and short-read metagenomics as well as epicPCR for detecting ARG hosts in wastewater, and 2) investigated the host range of ARGs across the wastewater treatment plant (WWTP) to evaluate host proliferation. Results highlighted long-read revealed a wider range of ARG hosts compared to short-read metagenomics. Nonetheless, the ARG host range detected by long-read metagenomics only represented a subset of the hosts detected by epicPCR. The ARG-host linkages across the influent and effluent of the WWTP were characterized. Results showed the ARG-host phylum linkages were relatively consistent across the WWTP, whereas new ARG-host species linkages appeared in the WWTP effluent. The ARG-host linkages of several clinically relevant species found in the effluent were identified.

AiGeneR 1.0: An Artificial Intelligence Technique for the Revelation of Informative and Antibiotic Resistant Genes in Escherichia coli.

There are several antibiotic resistance genes (ARG) for the Escherichia coli (E. coli) bacteria that cause urinary tract infections (UTI), and it is therefore important to identify these ARG. Artificial Intelligence (AI) has been used previously in the field of gene expression data, but never adopted for the detection and classification of bacterial ARG. We hypothesize, if the data is correctly conferred, right features are selected, and Deep Learning (DL) classification models are optimized, then (i) non-linear DL models would perform better than Machine Learning (ML) models, (ii) leads to higher accuracy, (iii) can identify the hub genes, and, (iv) can identify gene pathways accurately. We have therefore designed aiGeneR, the first of its kind system that uses DL-based models to identify ARG in E. coli in gene expression data. The aiGeneR consists of a tandem connection of quality control embedded with feature extraction and AI-based classification of ARG. We adopted a cross-validation approach to evaluate the performance of aiGeneR using accuracy, precision, recall, and F1-score. Further, we analyzed the effect of sample size ensuring generalization of models and compare against the power analysis. The aiGeneR was validated scientifically and biologically for hub genes and pathways. We benchmarked aiGeneR against two linear and two other non-linear AI models. The aiGeneR identifies tetM (an ARG) and showed an accuracy of 93% with area under the curve (AUC) of 0.99 (p < 0.05). The mean accuracy of non-linear models was 22% higher compared to linear models. We scientifically and biologically validated the aiGeneR. aiGeneR successfully detected the E. coli genes validating our four hypotheses.

Distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity

Purpose This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease. Design/methodology/approach In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing. Findings The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health. Originality/value The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

Ultrasensitive Dual-Mode Visual/Photoelectrochemical Bioassay for Antibiotic Resistance Genes through Incorporating Rolling Circle Amplicons into a Tailored Nanoassembly.

As emerging contaminants in the environment, antibiotic resistance genes (ARGs) have aroused a global health crisis and posed a serious threat to ecological safety and human health. Thus, efficient and accurate onsite detection of ARGs is crucial for environmental surveillance. Here, we presented a colorimetric-photoelectrochemical (PEC) dual-mode bioassay for simultaneous detection of multiple ARGs by smartly incorporating rolling circle amplification (RCA) into a stimuli-responsive DNA nanoassembly, using the tetracycline resistance genes tetA and tetC as models. The tailored DNA nanoassembly containing RCA amplicons hybridized with specific signal probes: CuO nanoflowers-anchored signal DNA1 and HgO nanoparticles-anchored signal DNA2, respectively. Upon exposure to an acidic stimulus, numerous Cu2+ and Hg2+ were released, serving as the reporting agent of colorimetric/PEC dual-mode assay. The released Cu2+ and Hg2+ induced localized surface plasmon resonance shifts in Au nanorods and triangular Ag nanoplates through an etching process, respectively, enabling visual analysis of ARGs with distinguishing color changes. Meanwhile, numerous Cu2+ and Hg2+ triggered the amplified PEC variations via reacting with the photoactive layers of CuS/CdS and ZnS, respectively. Thus, a rapid and ultrasensitive colorimetric/PEC dual-mode detection of multiple ARGs was achieved with the detection limit down to 17.2 aM. Furthermore, such dual-mode bioassay could discriminate single-base mismatch and successfully determine ARGs in E. coli plasmids and sludge samples, holding great promise for point-of-care genetic diagnostics.

Antimicrobial Resistance Profiles of Multidrug-Resistant Enterobacteria Isolated from Feces of Weaned Piglets.

Nosocomial infections caused by multidrug-resistant enterobacteria have become a major challenge in global public health. Previous studies have indicated that use of antibiotics in livestock production chains is linked to the rising threat of antibiotic resistance in humans. In this study, we aimed to evaluate the distribution of genes encoding resistance to tetracycline, β-lactams, and colistin in multidrug-resistant enterobacteria isolated from feces of weaned pigs. Ninety-four enterobacteria isolates were submitted to antibiotic susceptibility test by minimum inhibitory concentration (MIC). In addition, we performed conjugation experiments to verify if plasmid-bearing isolates containing the mcr-1 gene could transfer their resistance determinant to a colistin-sensitive recipient strain. Our results demonstrated a positive association between the detection of antibiotic resistance genes in enterobacteria and the phenotypic resistance profiles of the bacterial isolates. At least one of the extended-spectrum β-lactamases (ESBL) genes (blaCTX-M, blaTEM, or bla SHV) and tetA was found among most bacterial genera analyzed. In addition, results revealed that the mcr-1 gene can be transferred from E. coli UFV-627 isolate to an F- recipient (Escherichia coli K12) by conjugation. Our findings support the hypothesis that swine represents an important reservoir of antibiotic resistance genes and suggest that horizontal transfer mechanisms (e.g., conjugation) may mediate the spread of these genes in the swine gastrointestinal tract.

Antibiotic resistance gene-free probiont administration to tilapia for growth performance and Streptococcus agalactiae resistance.

The rapid development of aquaculture as a major food sector is accompanied by challenges, including diseases that affect tilapia farming worldwide. One such infectious disease caused by Streptococcus agalactiae poses a serious threat to tilapia populations. Probiotics have emerged as a potentially safe preventive measure against S. agalactiae infection. However, antimicrobial resistance from antibiotic-resistant bacteria remains a concern because it can lead to the spread of resistant bacteria and serve as a reservoir of antibiotic-resistant genes in fishes and the surrounding environment. This study aimed to identify candidate probiotic bacteria capable of promoting tilapia growth, providing resistance to S. agalactiae infection, devoid of potential pathogenicity, and free from antibiotic resistance genes. Subsequently, the performance of these probiotic candidates in tilapia was evaluated. Lactococcus garvieae, Priestia megaterium, Bacterium spp., Bacillus megaterium, Bacillus subtilis, and Bacillus pumilus were examined to assess their antibacterial properties, hemolytic patterns, and antibiotic resistance genes. We used the specific primers tetA, tetB, tetD, tetE, tetO, tetQ, ermB, and qnrS that were used for antibiotic resistance gene detection. In vivo probiotic efficacy was evaluated by administering probiotic candidates in tilapia feed at a concentration of 1 × 106 colonies/mL/50 g of feed over a 60-day maintenance period. Resistance to S. agalactiae infection was observed for 14 days after the challenge test. Lactococcus garvieae, P. megaterium, and Bacterium spp. were identified as promising probiotic candidates among the bacterial isolates. On the other hand, B. megaterium, B. subtilis, and B. pumilus carried resistance genes and exhibited a β hemolytic pattern, rendering them unsuitable as probiotic candidates. The selected probiotic candidates (L. garvieae, P. megaterium, and Bacterium spp.) demonstrated the potential to enhance tilapia growth, exhibited no pathogenic tendencies, and were free from antibiotic resistance genes. Supplementation with L. garvieae and Bacterium spp. enhanced tilapia resistance to S. agalactiae infection, whereas P. megaterium supplementation showed an insignificant survival rate compared with controls after the challenge test period. Probiotics, particularly L. garvieae, P. megaterium, and Bacterium spp., enhance growth and resistance against S. agalactiae infection, without harboring antibiotic resistance genes. Selecting probiotic candidates based on antibiotic resistance genes is essential to ensure the safety of fish, the environment, and human health.

Assessing the nonlinear association of environmental factors with antibiotic resistance genes (ARGs) in the Yangtze River Mouth, China

The emergence of antibacterial resistance (ABR) is an urgent and complex public health challenge worldwide. Antibiotic resistant genes (ARGs) are considered as a new pollutant by the WHO because of their wide distribution and emerging prevalence. The role of environmental factors in developing ARGs in bacterial populations is still poorly understood. Therefore, the relationship between environmental factors and bacteria should be explored to combat ABR and propose more tailored solutions in a specific region. Here, we collected and analyzed surface water samples from Yangtze Delta, China during 2021, and assessed the nonlinear association of environmental factors with ARGs through a sigmoid model. A high abundance of ARGs was detected. Amoxicillin, phosphorus (P), chromium (Cr), manganese (Mn), calcium (Ca), and strontium (Sr) were found to be strongly associated with ARGs and identified as potential key contributors to ARG detection. Our findings suggest that the suppression of ARGs may be achieved by decreasing the concentration of phosphorus in surface water. Additionally, Group 2A light metals (e.g., magnesium and calcium) may be candidates for the development of eco-friendly reagents for controlling antibiotic resistance in the future.

Portable biosensor combining CRISPR/Cas12a and loop-mediated isothermal amplification for antibiotic resistance gene ermB in wastewater

Wastewater is among the main sources of antibiotic resistance genes (ARGs) in the environment, but effective methods to quickly assess ARGs on-site in wastewater are lacking. Here, using the typical ARG ermB as the target, we report a portable biosensor combining CRISPR/Cas12a and loop-mediated isothermal amplification (LAMP) for the detection of ARGs. Six primers of LAMP and the crRNA of CRISPR/Cas12a were first designed to be preamplification with LAMP and lead Cas12a to recognize the ermB via base pairing. Due to the trans-cleavage activity of CRISPR/Cas12a after amplicon recognition, ssDNA probes modified with reporter molecules were used to implement a visual assay with lateral flow test strips and fluorescence. After a simple nucleic acid extraction with magnetic beads, the constructed biosensor possesses excellent sensitivity and selectivity as low as 2.75 × 103 copies/μL using fluorescence and later flow strips in wastewater. We further evaluated the community-wide prevalence of ermB in wastewater influent and found high mass loads of ermB during different months. This user-friendly and low-cost biosensor is applicable for rapid on-site ARG detection, providing a potential point-of-use method for rapid assessments of ARG abundance in wastewater from large city areas with many wastewater treatment plants and in resource-limited rural areas.

Prevalence of antibiotic resistance genes in resistome of adult residents of Arkhangelsk with regard to the severity of COVID-19

Objective: to estimate the prevalence of antibiotic resistance genes in the resistome of adult residents of Arkhangelsk with regard to the severity of the novel coronavirus infection (COVID-19).Materials and methods. A cross-sectional study was conducted between October and November 2022 (2.5 years after the start of the COVID-19 pandemic) on a random sample (N=455) of Arkhangelsk population aged 42-76 years. The data collection involved a questionnaire survey, assessment of immunoglobulins G to S-, S2, N-proteins of SARS-CoV-2 and detection of antibiotic resistance genes in fecal samples by polymerase chain reaction.Results. Almost all participants (98.5%) had at least one antibiotic resistance gene, the resistance determinants to three classes of antibiotics simultaneously were detected in 5.6%. The prevalence of resistance genes to macrolides was 98.5%, to beta-lactams – 29.0%, and to glycopeptides – 16.0%. Antibiotic resistance genes to beta-lactams were more prevalent among participants who had previously been hospitalized for COVID-19 (44.8%) and among those having had frequent acute respiratory infections (50.0%). Individuals vaccinated against SARS-CoV-2 (26.6%) and participants with cardiovascular diseases (17.0%) were less likely to have beta-lactam resistance genes.Conclusion. The high prevalence of antibiotic resistance genes has been revealed in the resistome of adult residents of Arkhangelsk. We determined the association between resistance to beta-lactams and COVID-19 severity. The study results could be used to improve the protocols of antibiotic therapy and to guide a decision-making related to the antibiotic prescription in adults.

MGS2AMR: a gene-centric mining of metagenomic sequencing data for pathogens and their antimicrobial resistance profile

BackgroundIdentification of pathogenic bacteria from clinical specimens and evaluating their antimicrobial resistance (AMR) are laborious tasks that involve in vitro cultivation, isolation, and susceptibility testing. Recently, a number of methods have been developed that use machine learning algorithms applied to the whole-genome sequencing data of isolates to approach this problem. However, making AMR assessments from more easily available metagenomic sequencing data remains a big challenge.ResultsWe present the Metagenomic Sequencing to Antimicrobial Resistance (MGS2AMR) pipeline, which detects antibiotic resistance genes (ARG) and their possible organism of origin within a sequenced metagenomics sample. This in silico method allows for the evaluation of bacterial AMR directly from clinical specimens, such as stool samples. We have developed two new algorithms to optimize and annotate the genomic assembly paths within the raw Graphical Fragment Assembly (GFA): the GFA Linear Optimal Path through seed segments (GLOPS) algorithm and the Adapted Dijkstra Algorithm for GFA (ADAG). These novel algorithms improve the sensitivity of ARG detection and aid in species annotation. Tests based on 1200 microbiome samples show a high ARG recall rate and correct assignment of the ARG origin. The MGS2AMR output can further be used in many downstream applications, such as evaluating AMR to specific antibiotics in samples from emerging intestinal infections. We demonstrate that the MGS2AMR-derived data is as informative for the entailing prediction models as the whole-genome sequencing (WGS) data. The performance of these models is on par with our previously published method (WGS2AMR), which is based on the sequencing data of bacterial isolates.ConclusionsMGS2AMR can provide researchers with valuable insights into the AMR content of microbiome environments and may potentially improve patient care by providing faster quantification of resistance against specific antibiotics, thereby reducing the use of broad-spectrum antibiotics. The presented pipeline also has potential applications in other metagenome analyses focused on the defined sets of genes.6MP9Kjm5NAthB1ioNbPxBHVideo

Molecular characterization of tetracycline and vancomycin-resistant Enterococcus faecium isolates from healthy dogs in Egypt: a public health threat

BackgroundVancomycin-resistant enterococci (VRE) are among the most common causative pathogens for nosocomial infections worldwide. Moreover, strains of VRE have been isolated from several domestic livestock in Egypt.MethodsThis study examined if healthy dogs are a potential source of VRE infection by isolating and characterizing Enterococcus faecium strains from stool samples on a morphological basis and biochemical activities. Subsequently, it was confirmed by genotypic characterization using polymerase chain reaction (PCR), followed by the detection of antibiotic resistance genes, virulence determinants, and genes contributing to enterocin production by PCR. Furthermore, the phylogenetic relationships among vanB and tetL genes were analyzed.ResultsAll ten fecal samples were identified as E. faecium and confirmed by PCR. In addition, 90% of the isolates tested were positive for the virulence genes gelE and esp, and all the isolates tested were positive for the antibiotic resistance genes tetL and vanB. Only three of the five enterocin genes examined were detected. Ent As-48, bacteriocin 31, and Ent L50 were identified in 100%, 80%, and 60% of the samples, respectively.ConclusionDogs should be regarded as a reservoir of E. faecium that carries vancomycin resistance and virulence determinants that may affect public health in Egypt, considering a "One Health" task force approach to restrict their spread.

A-272 Challenges in Designing an Antibiotic Gene Resistance Panel for Clinical Use

Abstract Background We faced 3 major challenges in our journey of designing a custom panel for antibiotic resistance genes (ABR). Challenge 1# Fast, robust, and affordable antimicrobial resistance testing (ABR) In general, qPCR-based methods are efficient, reliable, and fast with high specificity and sensitivity, and with the test results available within 2–3 h. We offer urinary tract infection identification by qPCR and wanted to supplement this test with detection of antibiotic resistance genes. we narrowed our choice of method to be qPCR based, Applied Biosystems™ OpenArray™ technology on the Applied Biosystems™ QuantStudio™ 12K Flex Real-Time PCR System. Challenge2# Genes to be tested. Antibiotic resistance occurs via various mechanism. Based on the literature review, we included the following gene in our custom panel 1. Aminoglycosides: aac(6′)-Ib-cr6, aac(6′)-Ib-cr, aac(6′)-Ib-cr4 2. Tetracycline: tet(M), tet(B) 3. Sulfonamides: sul1, sul2 4. Macrolide-lincosamide-streptogramin B-ketolides-oxazolidinones: erm C, erm A, erm B 5. Quinolone/(fluoroquinolones): qnrS , qnrA, aac(6′)-Ib-cr6, aac(6′)-Ib-cr, aac(6′)-Ib-cr4 6. Glycopeptides: VanA, VanB 7. Beta-lactam Class A: SHV, KPC, CTX-M 8. Beta-lactam Class B: NDM, VIM, IMP 9. Beta-lactam Class C: CMY, DHA, FOX, KPC 10. Beta-lactam Class D: OXA1, OXA-23, OXA- 48, 11. Methicillin resistance: mecA. Results Validation of the ABR panel Accuracy: 50 isolates were ordered from CDC AR isolate bank and were used to test the accuracy. The accuracy was detected to be 98% concordant. Sensitivity: The assay was sensitive to detect all urinary pathogens upto 10^3 CFU/mL. Precision: the inter and intra reproducibility was shown to be 99% concordant Specific: when tested against the CDC controls, the assays were 100% specific Challenge 3# Genotype—Phenotype correlation and prevalence of antibiotic resistance genes in USA. We compared 100 consecutive clinical specimens (urine) for genotype -phenotype co-relation. Data from the current qPCR panel and Microscan instrument was compared. It was observed for the pathogens that were phenotypically resistant to certain antibiotics, the corresponding gene association was not found in (2–50%) of antibiotic groups. This can be explained due to the limited number of genes in each drug class. Resistance to some antibiotics such as nitrofurantoin drug (100% missed) and sulphonamide drug resistance (50% missed) is induced by point mutations, which are not captured in open array genotyping qPCR assay. To overcome this gap between genotype and phenotype correlation and to understand the prevalence of antibiotic resistance genes in USA, we initiated a new project. We aim to test for 300–400 clinical samples which known resistance phenotypes and check for antibiotic resistance gene in a new expanded panel. We were successful in designing the new panel to include 88 genes (vs 30 genes in the old panel). Conclusion The current assay was approved by the CLIA authorities for clinical testing. In general, qPCR-based methods are efficient, reliable, and fast with high specificity and sensitivity, and with the test results available within 2–3 h.

An experimental comparison between primer and nucleotide labelling to produce RPA-amplicons used for multiplex detection of antibiotic resistance genes

Direct labelling of amplification products using isothermal amplification is currently done most frequently by incorporating previously labelled primer. Although this method is well proven and widely used, it is not a universal solution due to some weaknesses. Alternatively, labelled nucleotides could be used, whose application and functionality have been already partially demonstrated. It remains to be determined how this method performs in comparison to traditional labelling, in particular combined with isothermal amplification methods. In this work, we show a detailed analysis of the labelling efficiency under different conditions and compare the results with the traditional primer-labelling method in the context of RPA amplification. Impressively, our results showed that using Cy5-labelled dUTPs can achieve much more efficient labelling for fragments above 200 bp, while using them for smaller fragments does not bring any relevant disadvantages, but also no major benefit. Furthermore, this work successfully demonstrate for the first time a quadruplex microarray for the detection of resistance genes using RPA and direct labelling with Cy5-dUTP as a potential application scenario. The sensitivities achieved here extend to SNP discovery for the detection of the proper blaKPC variant.