Detection Of Antimicrobial Resistance Genes Research Articles

Overcoming Microbial Inhibition of S. Sonnei Through the Exploitation of Genomically Predicted Antibiotic Resistance Profiles for the Development of Food Enrichment Media

Linking outbreaks of Shigella spp. to specific foods is challenging due to poor selectivity of current enrichment media. We have previously shown that enrichment media, tailored to the genomically-predicted antimicrobial resistance (AMR) of Shiga toxigenic E. coli strains, enhances their isolation from foods. This study investigates the application of this approach for Shigella isolation. The AMR gene profiles of 21,908 published S. sonnei genomes indicated a high prevalence of genes conferring resistance to streptomycin (aadA, aph(3″)-Ib, aph(6)-Id, 92.8%), sulfonamides (sul1, sul2, 74.8%), and/or trimethoprim (dfrA, 96.2%). Genomic analysis and antibiotic susceptibility testing conducted with a panel of 17 outbreak-associated S. sonnei strains confirmed the correlation of AMR gene detection with resistance phenotypes. Supplementation of Shigella Broth (SB) with up to 400 µg/mL of trimethoprim or sulfadiazine did not suppress the growth of sensitive strains, whereas 100 µg/mL of streptomycin increased the selectivity of this broth. All three antibiotics increased the selectivity of modified Tryptone Soya Broth (mTSB). Based on these results, supplemented media formulations were developed and assessed by measuring the relative growth of S. sonnei in cultures coinoculated with a strain of bacteriocin-producing E. coli that is inhibitory to Shigella growth. S. sonnei was not recovered from cocultures grown in SB or mTSB without antibiotics. In contrast, media supplemented with streptomycin at 50 and 100 µg/mL, trimethoprim at 25 and 50 µg/mL, and sulfadiazine at 100 µg/mL increased the relative proportion of S. sonnei in postenrichment cultures. The enhanced recovery of resistant S. sonnei strains achieved in this study indicates that, in cases where genomic data are available for clinical S. sonnei isolates, customization of selective enrichment media based on AMR gene detection could be a valuable tool for supporting the investigation of foodborne shigellosis outbreaks.

Bacterial enrichment prior to third-generation metagenomic sequencing improves detection of BRD pathogens and genetic determinants of antimicrobial resistance in feedlot cattle.

Bovine respiratory disease (BRD) is one of the most important animal health problems in the beef industry. While bacterial culture and antimicrobial susceptibility testing have been used for diagnostic testing, the common practice of examining one isolate per species does not fully reflect the bacterial population in the sample. In contrast, a recent study with metagenomic sequencing of nasal swabs from feedlot cattle is promising in terms of bacterial pathogen identification and detection of antimicrobial resistance genes (ARGs). However, the sensitivity of metagenomic sequencing was impeded by the high proportion of host biomass in the nasal swab samples. This pilot study employed a non-selective bacterial enrichment step before nucleic acid extraction to increase the relative proportion of bacterial DNA for sequencing. Non-selective bacterial enrichment increased the proportion of bacteria relative to host sequence data, allowing increased detection of BRD pathogens compared with unenriched samples. This process also allowed for enhanced detection of ARGs with species-level resolution, including detection of ARGs for bacterial species of interest that were not targeted for culture and susceptibility testing. The long-read sequencing approach enabled ARG detection on individual bacterial reads without the need for assembly. Metagenomics following non-selective bacterial enrichment resulted in substantial agreement for four of six comparisons with culture for respiratory bacteria and substantial or better correlation with qPCR. Comparison between isolate susceptibility results and detection of ARGs was best for macrolide ARGs in Mannheimia haemolytica reads but was also substantial for sulfonamide ARGs within M. haemolytica and Pasteurella multocida reads and tetracycline ARGs in Histophilus somni reads. By increasing the proportion of bacterial DNA relative to host DNA through non-selective enrichment, we demonstrated a corresponding increase in the proportion of sequencing data identifying BRD-associated pathogens and ARGs in deep nasopharyngeal swabs from feedlot cattle using long-read metagenomic sequencing. This method shows promise as a detection strategy for BRD pathogens and ARGs and strikes a balance between processing time, input costs, and generation of on-target data. This approach could serve as a valuable tool to inform antimicrobial management for BRD and support antimicrobial stewardship.

Dental plaque microbiota sequence counts for microbial profiling and resistance genes detection

Shotgun metagenomics sequencing experiments are finding a wide range of applications. Nonetheless, there are still limited guidelines regarding the number of sequences needed to acquire meaningful information for taxonomic profiling and antimicrobial resistance gene (ARG) identification. In this study, we explored this issue in the context of oral microbiota by sequencing with a very high number of sequences (~ 100 million), four human plaque samples, and one microbial community standard and by evaluating the performance of microbial identification and ARGs detection through a downsampling procedure. When investigating the impact of a decreasing number of sequences on quantitative taxonomic profiling in the microbial community standard datasets, we found some discrepancies in the identified microbial species and their abundances when compared to the expected ones. Such differences were consistent throughout downsampling, suggesting their link to taxonomic profiling methods limitations. Overall, results showed that the number of sequences has a great impact on metagenomic samples at the qualitative (i.e., presence/absence) level in terms of loss of information, especially in experiments having less than 40 million reads, whereas abundance estimation was minimally affected, with only slight variations observed in low-abundance species. The presence of ARGs was also assessed: a total of 133 ARGs were identified. Notably, 23% of them inconsistently resulted as present or absent across downsampling datasets of the same sample. Moreover, over half of ARGs were lost in datasets having less than 20 million reads. This study highlights the importance of carefully considering sequencing aspects and suggests some guidelines for designing shotgun metagenomics experiments with the final goal of maximizing oral microbiome analyses. Our findings suggest varying optimized sequence numbers according to different study aims: 40 million for microbiota profiling, 50 million for low-abundance species detection, and 20 million for ARG identification.Key points• Forty million sequences are a cost-efficient solution for microbiota profiling• Fifty million sequences allow low-abundance species detection• Twenty million sequences are recommended for ARG identificationGraphical

Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes.

Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.

Molecular detection of antimicrobial resistance genes in multidrug-resistant Gram-negative bacteria isolated from clinical samples in two hospitals in Niger

Background: According to the World Health Organization (WHO), bacterial resistance to antibiotics is a global public health challenge, which is also developing in Niger. The aim of this study was to determine the prevalence of antibiotic resistance genes in Gram-negative bacilli isolated from clinical samples in the biological laboratories of two selected health facilities in Niger.
 Methodology: Clinical bacterial isolates were randomly collected from two biological laboratories of Zinder National Hospital and Niamey General Reference Hospital. These were multi-resistant Gram-negative bacteria that have been routinely isolated from pathological samples of patients. Molecular detection of resistance genes was carried out by polymerase chain reaction (PCR) amplification using specific primers. These include plasmid-mediated AmpC beta lactamase genes (blaCITM, blaDHAM, blaFOXM), ‘Cefotaxime-Munich’ type beta lactamase genes (blaCTX-M-1, blaCTX-M-2, blaCTX-M-9), KPC-type beta lactamase gene (blaKPC), Oxa-type beta lactamase gene (blaOXA-48), SHV-type beta lactamase gene (blaSHV), TEM-type beta lactamase gene (blaTEM), quinolone resistance genes (qnrA, qnrB, qnrS), and sulfonamide resistance genes (sul1, sul2, sul3).
 Results: A total of 24 strains of multidrug-resistant Gram-negative bacteria isolated from different clinical samples were analysed. The distribution of the resistance genes detected is as follows; AmpC blaCITM (n=6; 25.0%), AmpC blaDHAM (n=4; 17.0%), AmpC blaFOXM (n=0), blaCTX-M-1 (n=11; 46.0%), blaCTX-M-2 (n=0), blaCTX-M-9 (n=0), blaKPC (n=0), blaOXA-48 (n=2; 8..0%), blaSHV (n=5; 21.0%), blaTEM (n=0), qnrA (n=0), qnrB (n=5; 21.0%), qnrS (n=17; 71.0%), sul1 (n=22; 92.0%), sul2 (n=12; 50.0%), and sul3 (n=0). All isolates tested had at least two resistance genes.
 Conclusion: The results of this study provide a better understanding of the resistance situation of clinical isolates in Niger. Therefore, it is more than necessary to intensify the detection on a larger number of samples and on a national scale. This will make it possible to assess the true extent of the phenomenon and consequently guide control strategies through a national multisectoral plan.
 Contexte: Selon l'Organisation Mondiale de la Santé (OMS), la résistance bactérienne aux antibiotiques constitue un défi mondial de santé publique, qui se développe également au Niger. Le but de cette étude était de déterminer la prévalence des gènes de résistance aux antibiotiques chez les bacilles Gram négatif isolés à partir d'échantillons cliniques dans les laboratoires de biologie de deux formations sanitaires sélectionnées au Niger.
 Méthodologie: Des isolats bactériens cliniques ont été collectés de manière aléatoire dans deux laboratoires de biologie de l'Hôpital National de Zinder et de l'Hôpital Général de Référence de Niamey. Il s’agissait de bactéries Gram-négatives multirésistantes qui ont été systématiquement isolées à partir d’échantillons pathologiques de patients. La détection moléculaire des gènes de résistance a été réalisée par amplification par réaction en chaîne par polymérase (PCR) à l'aide d'amorces spécifiques. Il s'agit notamment des gènes de bêta-lactamase AmpC à médiation plasmidique (blaCITM, blaDHAM, blaFOXM), des gènes de bêta-lactamase de type «Céfotaxime-Munich» (blaCTX-M-1, blaCTX-M-2, blaCTX-M-9), du gène de bêta-lactamase de type KPC (blaKPC), du gène de bêta-lactamase de type Oxa (blaOXA-48), le gène bêta-lactamase de type SHV (blaSHV), le gène bêta-lactamase de type TEM (blaTEM), les gènes de résistance aux quinolones (qnrA, qnrB, qnrS) et les gènes de résistance aux sulfamides (sul1, sul2, sul3).
 Résultats: Au total, 24 souches de bactéries Gram-négatives multirésistantes isolées de différents échantillons cliniques ont été analysées. La répartition des gènes de résistance détectés est la suivante; AmpC blaCITM (n=6; 25,0%), AmpC blaDHAM (n=4; 17,0%), AmpC blaFOXM (n=0), blaCTX-M-1 (n=11; 46,0%), blaCTX-M-2 (n=0), blaCTX-M-9 (n=0), blaKPC (n=0), blaOXA-48 (n=2; 8,0%), blaSHV (n=5; 21,0%), blaTEM (n=0), qnrA (n=0), qnrB (n=5; 21,0%), qnrS (n=17; 71,0%), sul1 (n=22; 92,0%), sul2 (n=12; 50,0%) et sul3 (n=0). Tous les isolats testés possédaient au moins deux gènes de résistance.
 Conclusion: Les résultats de cette étude permettent de mieux comprendre la situation de résistance des isolats cliniques au Niger. Il est donc plus que nécessaire d’intensifier la détection sur un plus grand nombre d’échantillons et à l’échelle nationale. Cela permettra d'évaluer l'ampleur réelle du phénomène et par conséquent d'orienter les stratégies de lutte à travers un plan national multisectoriel.

Antimicrobial resistance in wildlife: detection of antimicrobial resistance genes in Apennine wolves (Canis lupus italicus Altobello, 1921) from Central Italy.

The aim of this study was to molecularly investigate the presence of antimicrobial resistance genes (ARGs) in organ samples from 11 Apennine wolves (Canis lupus italicus) collected in Central Italy. Samples from lung, liver, spleen, kidney, tongue and intestine were investigated by PCRs targeting the following genes: tet(A), tet(B), tet(C), tet(D), tet(E), tet(G), tet(K), tet(L), tet(M), tet(O), tetA(P), tet(Q), tet(S), tet(X), sul1, sul2, sul3, blaCTX-M, blaSHV, blaTEM and mcr-1. A PCR positivity was highlighted for 13 out of the 21 tested genes; no positive results were obtained for tet(C), tet(D), tet(E), tet(G), sul3, blaCTX, blaSHV and mcr-1 genes. All 11 animals sampled showed positivity for one or more resistance genes. The results confirm the potential role of the wolf as an indicator and/or vector of antimicrobial-resistant bacteria or ARGs.

Laboratory tools for the direct detection of bacterial respiratory infections and antimicrobial resistance: a scoping review.

Rapid laboratory tests are urgently required to inform antimicrobial use in food animals. Our objective was to synthesize knowledge on the direct application of long-read metagenomic sequencing to respiratory samples to detect bacterial pathogens and antimicrobial resistance genes (ARGs) compared to PCR, loop-mediated isothermal amplification, and recombinase polymerase amplification. Our scoping review protocol followed the Joanna Briggs Institute and PRISMA Scoping Review reporting guidelines. Included studies reported on the direct application of these methods to respiratory samples from animals or humans to detect bacterial pathogens ±ARGs and included turnaround time (TAT) and analytical sensitivity. We excluded studies not reporting these or that were focused exclusively on bioinformatics. We identified 5,636 unique articles from 5 databases. Two-reviewer screening excluded 3,964, 788, and 784 articles at 3 levels, leaving 100 articles (19 animal and 81 human), of which only 7 studied long-read sequencing (only 1 in animals). Thirty-two studies investigated ARGs (only one in animals). Reported TATs ranged from minutes to 2 d; steps did not always include sample collection to results, and analytical sensitivity varied by study. Our review reveals a knowledge gap in research for the direct detection of bacterial respiratory pathogens and ARGs in animals using long-read metagenomic sequencing. There is an opportunity to harness the rapid development in this space to detect multiple pathogens and ARGs on a single sequencing run. Long-read metagenomic sequencing tools show potential to address the urgent need for research into rapid tests to support antimicrobial stewardship in food animal production.

Development and validation of multiplex real-time PCR for simultaneous detection of six bacterial pathogens causing lower respiratory tract infections and antimicrobial resistance genes

BackgroundKlebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Escherichia coli, Streptococcus pneumoniae and Staphylococcus aureus are major bacterial causes of lower respiratory tract infections (LRTIs) globally, leading to substantial morbidity and mortality. The rapid increase of antimicrobial resistance (AMR) in these pathogens poses significant challenges for their effective antibiotic therapy. In low-resourced settings, patients with LRTIs are prescribed antibiotics empirically while awaiting several days for culture results. Rapid pathogen and AMR gene detection could prompt optimal antibiotic use and improve outcomes.MethodsHere, we developed multiplex quantitative real-time PCR using EvaGreen dye and melting curve analysis to rapidly identify six major pathogens and fourteen AMR genes directly from respiratory samples. The reproducibility, linearity, limit of detection (LOD) of real-time PCR assays for pathogen detection were evaluated using DNA control mixes and spiked tracheal aspirate. The performance of RT-PCR assays was subsequently compared with the gold standard, conventional culture on 50 tracheal aspirate and sputum specimens of ICU patients.ResultsThe sensitivity of RT-PCR assays was 100% for K. pneumoniae, A. baumannii, P. aeruginosa, E. coli and 63.6% for S. aureus and the specificity ranged from 87.5% to 97.6%. The kappa correlation values of all pathogens between the two methods varied from 0.63 to 0.95. The limit of detection of target bacteria was 1600 CFU/ml. The quantitative results from the PCR assays demonstrated 100% concordance with quantitative culture of tracheal aspirates. Compared to culture, PCR assays exhibited higher sensitivity in detecting mixed infections and S. pneumoniae. There was a high level of concordance between the detection of AMR gene and AMR phenotype in single infections.ConclusionsOur multiplex quantitative RT-PCR assays are fast and simple, but sensitive and specific in detecting six bacterial pathogens of LRTIs and their antimicrobial resistance genes and should be further evaluated for clinical utility.

An integrated method for targeted Oxford Nanopore sequencing and automated bioinformatics for the simultaneous detection of bacteria, fungi, and ARG.

The use of metagenomics for pathogen identification in clinical practice has been limited. Here we describe a workflow to encourage the clinical utility and potential of NGS for the screening of bacteria, fungi, and antimicrobial resistance genes (ARGs). The method includes target enrichment, long-read sequencing, and automated bioinformatics. Evaluation of several tools and databases was undertaken across standard organisms (n=12), clinical isolates (n=114), and blood samples from patients with suspected bloodstream infections (n=33). The strategy used could offset the presence of host background DNA, error rates of long-read sequencing, and provide accurate and reproducible detection of pathogens. Eleven targets could be successfully tested in a single assay. Organisms could be confidently identified considering≥60% of best hits of a BLAST-based threshold of e-value 0.001 and a percent identity of>80%. For ARGs, reads with percent identity of>90% and>60% overlap of the complete gene could be confidently annotated. A kappa of 0.83 was observed compared to standard diagnostic methods. Thus, a workflow for the direct-from-sample, on-site sequencing combined with automated genomics was demonstrated to be reproducible. NGS-based technologies overcome several limitations of current day diagnostics. Highly sensitive and comprehensive methods of pathogen screening are the need of the hour. We developed a framework for reliable, on-site, screening of pathogens.

Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools

BackgroundAlthough the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches.ResultsWe simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome.ConclusionsThis study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.

Rapid Detection of Antimicrobial Resistance Genes in Critically Ill Children Using a Custom TaqMan Array Card.

Bacteria are identified in only 22% of critically ill children with respiratory infections treated with antimicrobial therapy. Once an organism is isolated, antimicrobial susceptibility results (phenotypic testing) can take another day. A rapid diagnostic test identifying antimicrobial resistance (AMR) genes could help clinicians make earlier, informed antimicrobial decisions. Here we aimed to validate a custom AMR gene TaqMan Array Card (AMR-TAC) for the first time and assess its feasibility as a screening tool in critically ill children. An AMR-TAC was developed using a combination of commercial and bespoke targets capable of detecting 23 AMR genes. This was validated using isolates with known phenotypic resistance. The card was then tested on lower respiratory tract and faecal samples obtained from mechanically ventilated children in a single-centre observational study of respiratory infection. There were 82 children with samples available, with a median age of 1.2 years. Major comorbidity was present in 29 (35%) children. A bacterial respiratory pathogen was identified in 13/82 (16%) of children, of which 4/13 (31%) had phenotypic AMR. One AMR gene was detected in 49/82 (60%), and multiple AMR genes were detected in 14/82 (17%) children. Most AMR gene detections were not associated with the identification of phenotypic AMR. AMR genes are commonly detected in samples collected from mechanically ventilated children with suspected respiratory infections. AMR-TAC may have a role as an adjunct test in selected children in whom there is a high suspicion of antimicrobial treatment failure.

2454. Deep detection of antimicrobial resistance genes in hospital wastewater using the multiplex hybrid capture method

Abstract Background Wastewater can be useful in monitoring the spread of antimicrobial resistance (AMR) within a hospital. The abundance of antibiotic resistance genes (ARGs) in hospital effluent was assessed using metagenomic sequencing (mDNA-seq) and hybrid capture (xHYB). Methods mDNA-seq analysis and subsequent xHYB targeted enrichment were conducted on two effluent samples per month from November 2018 to May 2021 from a sewer pipe connected to inpatient buildings at a university hospital with 1,200 beds and approximately 1,000 new admissions per month. Reads per kilobase per million (RPKM) values were calculated for all 1,272 ARGs in the constructed database. The monthly numbers of patients with presumed ESBL-producing and metallo-β-lactamase (MBL)-producing bacteria, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE) were compared with the monthly RPKM values of blaCTX-M, blaIMP, mecA, vanA, and vanB by xHYB. Results The AMROTU hit count ratios for xHYB and mDNA-seq were well correlated (R2 = 0.99). The average RPKM value for all ARGs detected by xHYB was significantly higher than that of mDNA-seq (665,225 and 328, respectively, p &amp;lt; 0.05, Figure 1). The average RPKM values for blaCTX-M, blaTEM, blaIMP, blaVIM, mcr, qnrS, aac(6’)-Ib, aph, ermB, ermF, tetM, sul1 and sul2, mecA, and vanB by xHYB were significantly higher than that of mDNA-seq (1,330, 9,120, 6,173, 224, 777, 1,272, 69,921, 61,927, 18,854, 1,885, 51,788, 6, and 125 vs. 1, 1, 4, 0, 0, 1, 30, 20, 16, 1, 22, 0, and 0, respectively, p &amp;lt; 0.05; Figure 1). The average number of patients with ESBL producers and RPKM values of blaCTX-M-1 genes for xHYB in 2020 were significantly higher than that in 2019 (17 vs. 13 patients per month and 921 vs. 232 per month, respectively, both p &amp;lt; 0.05, Figure 2). The average numbers of patients with MBL-producers, MRSA, and VRE were 1, 28, and 0 per month, respectively, while the average RPKM values of blaIMP, mecA, vanA, and vanB were 6,163, 6, 0, and 126 per month, respectively (Figure 2).Figure 1.Comparison of reads per kilobase of gene per million (RPKM) value for each antimicrobial resistance gene (ARG) between metagenomic sequencing (mDNA-seq) and hybrid capture (xHYB). In each box and whisker plot, the box marks the interquartile range; the horizontal line across the box shows the median. The white box indicates RPKM values of mDNA-seq and the gray box indicates that of xHYB.Figure 2.The monthly average number of patients with extended-spectrum β-lactamase (ESBL)-producing and metallo-β-lactamase (MBL)-producing bacteria, and MRSA, and the monthly Reads per kilobase of gene per million (RPKM) values of blaCTX-M-1, blaCTX-M-2, blaIMP-1 and mec A. The left axis showed the number of patients, and the right showed the RPKM value, Log10(n+1). The blue, red, and green bars indicate the number of patients with ESBL and MBL-producers, and MRSA respectively. Purple and blue circle, red square, and the green triangle indicates RPKM values of blaCTX-M-1, blaCTX-M-2, blaIMP-1, and mecA, respectively. Conclusion Monitoring ARGs in hospital effluent using xHYB was found to be more useful than conventional mDNA-seq in detecting ARGs including blaCTX-M, blaIMP, and vanB, which are important for infection control. Disclosures Hiroaki Baba, MD, PhD, Amano Co., Ltd.: Grant/Research Support Hajime Kanamori, MD, PhD, MPH, Amano Co., Ltd.: Grant/Research Support

Performance of targeted next-generation sequencing in the detection of respiratory pathogens and antimicrobial resistance genes for children.

Introduction. Respiratory tract infection, which is associated with high morbidity and mortality, occurs frequently in children. At present, the main diagnostic method is culture. However, the low pathogen detection rate of the culture approach prevents timely and accurate diagnosis. Fortunately, next-generation sequencing (NGS) can compensate for the deficiency of culture, and its application in clinical diagnostics has become increasingly available.Gap Statement. Targeted NGS (tNGS) is a platform that can select and enrich specific regions before data enter the NGS pipeline. However, the performance of tNGS in the detection of respiratory pathogens and antimicrobial resistance genes (ARGs) in infections in children is unclear.Aim and methodology. In this study, we estimated the performance of tNGS in the detection of respiratory pathogens and ARGs in 47 bronchoalveolar lavage fluid (BALF) specimens from children using conventional culture and antimicrobial susceptibility testing (AST) as the gold standard.Results. RPIP (Respiratory Pathogen ID/AMR enrichment) sequencing generated almost 500 000 reads for each specimen. In the detection of pathogens, RPIP sequencing showed targeted superiority in detecting difficult-to-culture bacteria, including Mycoplasma pneumoniae. Compared with the results of culture, the sensitivity and specificity of RPIP were 84.4 % (confidence interval 70.5-93.5 %) and 97.7 % (95.9 -98.8%), respectively. Moreover, RPIP results showed that a single infection was detected in 10 of the 47 BALF specimens, and multiple infections were detected in 34, with the largest number of bacterial/viral coinfections. Nevertheless, there were also three specimens where no pathogen was detected. Furthermore, we analysed the drug resistance genes of specimens containing Streptococcus pneumoniae, which was detected in 25 out of 47 specimens in the study. A total of 58 ARGs associated with tetracycline, macrolide-lincosamide-streptogramin, beta-lactams, sulfonamide and aminoglycosides were identified by RPIP in 19 of 25 patients. Using the results of AST as a standard, the coincidence rates of erythromycin, tetracycline, penicillin and sulfonamides were 89.5, 79.0, 36.8 and 42.1 %, respectively.Conclusion. These results demonstrated the superiority of RPIP in pathogen detection, particularly for multiple and difficult-to-culture pathogens, as well as in predicting resistance to erythromycin and tetracycline, which has significance for the accurate diagnosis of pathogenic infection and in the guidance of clinical treatment.

A Whole-Genome Sequencing-Based Approach for the Characterization of Klebsiella pneumoniae Co-Producing KPC and OXA-48-like Carbapenemases Circulating in Sardinia, Italy.

Whole-genome sequencing (WGS) provides important information for the characterization, surveillance, and monitoring of antimicrobial resistance (AMR) determinants, particularly in cases of multi- and extensively drug-resistant microorganisms. We reported the results of a WGS analysis carried out on carbapenemases-producing Klebsiella pneumoniae, which causes hospital-acquired infections (HAIs) and is characterized by a marked resistance profile. Clinical, phenotypic, and genotypic data were collected for the AMR surveillance screening program of the University Hospital of Sassari (Italy) during 2020-2021. Genomic DNA was sequenced using the Illumina Nova Seq 6000 platform. Final assemblies were manually curated and carefully verified for the detection of antimicrobial resistance genes, porin mutations, and virulence factors. A phylogenetic analysis was performed using the maximum likelihood method. All 17 strains analyzed belonged to ST512, and most of them carried the blaKPC-31 variant blaOXA-48-like, an OmpK35 truncation, and an OmpK36 mutation. Phenotypic analysis showed a marked resistance profile to all antibiotic classes, including β-lactams, carbapenems, aminoglycosides, fluoroquinolone, sulphonamides, and novel β-lactam/β-lactamase inhibitors (BL/BLI). WGS characterization revealed the presence of several antibiotic resistance determinants and porin mutations in highly resistant K. pneumoniae strains responsible for HAIs. The detection of blaKPC-31 in our hospital wards highlights the importance of genomic surveillance in hospital settings to monitor the emergence of new clones and the need to improve control and preventive strategies to efficiently contrast AMR.

Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements

Antimicrobial resistance genes (ARGs) can be transferred between members of a bacterial population by mobile genetic elements (MGE). Understanding the risk of these transfer events is important in monitoring and predicting antimicrobial resistance (AMR), especially in the context of a One Health Continuum. However, there is no universally accepted method for detection of ARGs and MGEs, and especially for determining their linkages. This study used publicly available shotgun metagenomic DNA short-read (Illumina, 100 bp paired-end) sequence data from samples across the One Health Continuum (including beef cattle composite feces from feedlots, catch basin water at feedlots, agricultural soil from feedlot manured surrounding fields, and urban/municipal sewage influent from two municipal wastewater treatment plants) to develop a workflow to identify and associate ARGs and MGEs. ARG- and MGE-based targeted-assemblies with available short-read data were unable to meet this analysis goal. In contrast, de novo assembly of contigs provided enough sequence context to associate ARGs and MGEs, without compromising discovery rate. However, to estimate the relative abundance of these elements, unassembled sequence data must still be used.

Comparing antimicrobial resistant genes and phenotypes across multiple sequencing platforms and assays for Enterobacterales clinical isolates

IntroductionWhole genome sequencing (WGS) of bacterial isolates can be used to identify antimicrobial resistance (AMR) genes. Previous studies have shown that genotype-based AMR has variable accuracy for predicting carbapenem resistance in carbapenem-resistant Enterobacterales (CRE); however, the majority of these studies used short-read platforms (e.g. Illumina) to generate sequence data. In this study, our objective was to determine whether Oxford Nanopore Technologies (ONT) long-read WGS would improve detection of carbapenem AMR genes with respect to short-read only WGS for nine clinical CRE samples. We measured the minimum inhibitory breakpoint (MIC) using two phenotype assays (MicroScan and ETEST) for six antibiotics, including two carbapenems (meropenem and ertapenem) and four non-carbapenems (gentamicin, ciprofloxacin, cefepime, and trimethoprim/sulfamethoxazole). We generated short-read data using the Illumina NextSeq and long-read data using the ONT MinION. Four assembly methods were compared: ONT-only assembly; ONT-only assembly plus short-read polish; ONT + short-read hybrid assembly plus short-read polish; short-read only assembly.ResultsConsistent with previous studies, our results suggest that the hybrid assembly produced the highest quality results as measured by gene completeness and contig circularization. However, ONT-only methods had minimal impact on the detection of AMR genes and plasmids compared to short-read methods, although, notably, differences in gene copy number differed between methods. All four assembly methods showed identical presence/absence of the blaKPC-2 carbapenemase gene for all samples. The two phenotype assays showed 100% concordant results for the non-carbapenems, but only 65% concordance for the two carbapenems. The presence/absence of AMR genes was 100% concordant with AMR phenotypes for all four non-carbapenem drugs, although only 22%—50% sensitivity for the carbapenems.ConclusionsOverall, these findings suggest that the lack of complete correspondence between CRE AMR genotype and phenotype for carbapenems, while concerning, is independent of sequencing platform/assembly method.

Multiplex Hybrid Capture Improves the Deep Detection of Antimicrobial Resistance Genes from Wastewater Treatment Plant Effluents to Assess Environmental Issues.

Metagenomic sequencing (mDNA-seq) is one of the best approaches to address antimicrobial resistance (AMR) issues and characterize AMR genes (ARGs) and their host bacteria (ARB); however, the sensitivity provided is insufficient for the overall detection in wastewater treatment plant (WWTP) effluents because the effluent is well treated. This study investigated the multiplex hybrid capture (xHYB) method (QIAseq × HYB AMR Panel) and its potential to increase AMR assessment sensitivity. The mDNA-Seq analysis suggested that the WWTP effluents had an average of 104 reads per kilobase of gene per million (RPKM) for the detection of all targeted ARGs, whereas xHYB significantly improved detection at 601,576 RPKM, indicating an average 5,805-fold increase in sensitivity. For instance, sul1 was detected at 15 and 114,229 RPKM using mDNA-seq and xHYB, respectively. The blaCTX-M, blaKPC, and mcr gene variants were not detected by mDNA-Seq but were detected by xHYB at 67, 20, and 1,010 RPKM, respectively. This study demonstrates that the multiplex xHYB method could be a suitable evaluation standard with high sensitivity and specificity for deep-dive detection, highlighting a broader illustration of ongoing dissemination in the entire community.

Genomic Insights into Virulence Factors and Multi-Drug Resistance in Clostridium perfringens IRMC2505A.

Clostridium perfringens is a spore-forming, Gram-positive anaerobic pathogen that causes several disorders in humans and animals. A multidrug-resistant Clostridium strain was isolated from the fecal sample of a patient who was clinically suspected of gastrointestinal infection and had a recent history of antibiotic exposure and diarrhea. The strain was identified by 16s rRNA sequencing as Clostridium perfringens. The strain's pathogenesis was analyzed through its complete genome, specifically antimicrobial resistance-related genes. The Clostridium perfringens IRMC2505A genome contains 19 (Alr, Ddl, dxr, EF-G, EF-Tu, folA, Dfr, folP, gyrA, gyrB, Iso-tRNA, kasA, MurA, rho, rpoB, rpoC, S10p, and S12p) antibiotic-susceptible genetic species according to the k-mer-based detection of antimicrobial resistance genes. Genome mapping using CARD and VFDB databases revealed significant (p-value = 1 × 10-26) genes with aligned reads against antibiotic-resistant genes or virulence factors, including phospholipase C, perfringolysin O, collagenase, hyaluronidase, alpha-clostripain, exo-alpha-sialidase, and sialidase activity. In conclusion, this is the first report on C. perfringens from Saudi Arabia that conducted whole genome sequencing of IRMC2505A and confirmed the strain as an MDR bacterium with several virulence factors. Developing control strategies requires a detailed understanding of the epidemiology of C. perfringens, its virulence factors, and regional antimicrobial resistance patterns.

Highly sensitive detection of antimicrobial resistance genes in hospital wastewater using the multiplex hybrid capture target enrichment.

Wastewater can be useful in monitoring the spread of antimicrobial resistance (AMR) within a hospital. The abundance of antibiotic resistance genes (ARGs) in hospital effluent was assessed using metagenomic sequencing (mDNA-seq) and hybrid capture (xHYB). mDNA-seq analysis and subsequent xHYB targeted enrichment were conducted on two effluent samples per month from November 2018 to May 2021. Reads per kilobase per million (RPKM) values were calculated for all 1,272 ARGs in the constructed database. The monthly numbers of patients with presumed extended-spectrum β-lactamase (ESBL)-producing and metallo-β-lactamase (MBL)-producing bacteria, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE) were compared with the monthly RPKM values of blaCTX-M, blaIMP, mecA, vanA, and vanB by xHYB. The average RPKM value for all ARGs detected by xHYB was significantly higher than that of mDNA-seq (665, 225, and 328, respectively, and P < 0.05). The average number of patients with ESBL producers and RPKM values of blaCTX-M-1 genes in 2020 were significantly higher than that in 2019 (17 and 13 patients per month and 921 vs 232 per month, respectively, both P < 0.05). The average numbers of patients with MBL-producers, MRSA, and VRE were 1, 28, and 0 per month, respectively, while the average RPKM values of blaIMP, mecA, vanA, and vanB were 6,163, 6, 0, and 126 per month, respectively. Monitoring ARGs in hospital effluent using xHYB was found to be more useful than conventional mDNA-seq in detecting ARGs including blaCTX-M, blaIMP, and vanB, which are important for infection control.IMPORTANCEEnvironmental ARGs play a crucial role in the emergence and spread of AMR that constitutes a significant global health threat. One major source of ARGs is effluent from healthcare facilities, where patients are frequently administered antimicrobials. Culture-independent methods, including metagenomics, can detect environmental ARGs carried by non-culturable bacteria and extracellular ARGs. mDNA-seq is one of the most comprehensive methods for environmental ARG surveillance; however, its sensitivity is insufficient for wastewater surveillance. This study demonstrates that xHYB appropriately monitors ARGs in hospital effluent for sensitive identification of nosocomial AMR dissemination. Correlations were observed between the numbers of inpatients with antibiotic-resistant bacteria and the ARG RPKM values in hospital effluent over time. ARG surveillance in hospital effluent using the highly sensitive and specific xHYB method could improve our understanding of the emergence and spread of AMR within a hospital.

Detection of Antimicrobial Resistance Genes from Shiga Toxin Producing Escherichia coli by Multiplex PCR

Background: Shiga toxin-producing Escherichia coli (STEC) strains are considered to be most common food-borne enteric zoonotic pathogen, causing various disease conditions in both animals and humans and are highly pathogenic to human in low infectious doses. Resistance against antibiotics by STEC is also a big concern now a days. Hence in view of the public health significance of STEC, present work was planned to know the combination of phenotypic and genotypic resistance patterns against certain most commonly used antibiotics by using disk diffusion method and multiplex PCR respectively. Methods: A total of 426 PCR confirmed STEC isolates isolated from pooled samples (animal faecal(179), farm water(122) and human faecal samples (125) of different livestock farms in and around Proddatur andhra Pradesh, were subjected to antibiotic sensitivity test by using disc diffusion method. The isolates that showed resistance for tetracycline, streptomycin, sulphonamides and ampicillin were selected and subjected to multiplex PCR for the detection of resistance genes. Result: Disk diffusion assay revealed highest phenotypic resistance for STEC isolates against Cepahlothin (100%), followed by Ampicillin (99.06%), Tetracycline (97.2%), Streptomycin (94.3%), Sulphonamides (90.8%) and Trimethoprim (84.5%). Pooled samples also revealed the presence of antimicrobial resistance genes like tetA(59.2%), tetB(43.5%), tetC (9.2%), strA (39.3%), strB(54.1%), sul1 (40.8%), sul2 (58.7%), sul3 (3.8%) and blaTEM(83.4%). These findings indicate the highest prevalence of antimicrobial resistance among the STEC isolates, which alarms indiscriminate use of antibiotics both for therapeutic purpose and as growth promoters. Strict hygienic, sanitation and HACCP programmes should be applied to counter STEC prevalence.