Performance Characteristics of Next-Generation Sequencing for the Detection of Antimicrobial Resistance Determinants in Escherichia coli Genomes and Metagenomes

Rooney, Ashley; Raphenya, Amogelang R.; Melano, Roberto G.; Seah, Christine; Yee, Nathan; MacFadden, Derek R.; McArthur, Andrew G.; Schneeberger, Pierre H. H.; Coburn, Bryan

doi:10.1128/msystems.00022-22

Cited by 13 publications

(10 citation statements)

References 58 publications

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“…These bla CTX-M genes were found in contigs assembled from the metagenome data of the three samples, and the coverage of the three contigs was 777 (top 0.02 % among all contigs for coverage), 19.6 (top 3 %) and 2.0 (top 59 %) (), indicating that antimicrobial genes could be detected in contigs with a coverage of at least 2.0 and within the top 59 %. This result is consistent with that of a previous study [29] that reported median ARG detection rates ranging from approximately 60 to 90 % among E. coli ARGs under conditions of 2× genome coverage. In other words, if coverage is lower than this, such a low-abundance gene may not be detected in the metagenomic data (corresponding to the bottom right in Fig.…”

Section: Resultssupporting

confidence: 93%

Exploring the effects of antimicrobial treatment on the gut and oral microbiomes and resistomes from elderly long-term care facility residents via shotgun DNA sequencing

Kitamura,

Kajihara,

Volpiano

et al. 2024

Microbial Genomics

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Monitoring antibiotic-resistant bacteria (ARB) and understanding the effects of antimicrobial drugs on the human microbiome and resistome are crucial for public health. However, no study has investigated the association between antimicrobial treatment and the microbiome–resistome relationship in long-term care facilities, where residents act as reservoirs of ARB but are not included in the national surveillance for ARB. We conducted shotgun metagenome sequencing of oral and stool samples from long-term care facility residents and explored the effects of antimicrobial treatment on the human microbiome and resistome using two types of comparisons: cross-sectional comparisons based on antimicrobial treatment history in the past 6 months and within-subject comparisons between stool samples before, during and 2–4 weeks after treatment using a single antimicrobial drug. Cross-sectional analysis revealed two characteristics in the group with a history of antimicrobial treatment: the archaeon Methanobrevibacter was the only taxon that significantly increased in abundance, and the total abundance of antimicrobial resistance genes (ARGs) was also significantly higher. Within-subject comparisons showed that taxonomic diversity did not decrease during treatment, suggesting that the effect of the prescription of a single antimicrobial drug in usual clinical treatment on the gut microbiota is likely to be smaller than previously thought, even among very elderly people. Additional analysis of the detection limit of ARGs revealed that they could not be detected when contig coverage was <2.0. This study is the first to report the effects of usual antimicrobial treatments on the microbiome and resistome of long-term care facility residents.

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Section: Resultssupporting

confidence: 93%

Exploring the effects of antimicrobial treatment on the gut and oral microbiomes and resistomes from elderly long-term care facility residents via shotgun DNA sequencing

Kitamura,

Kajihara,

Volpiano

et al. 2024

Microbial Genomics

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“…This suggests that NTS results can also rapidly provide potentially useful evidence in clinical scenarios where culturing and phenotypic resistance information cannot be obtained. However, it's worth noting that, in comparison to pathogen identi cation, the accuracy of high-throughput sequencing techniques in detecting and predicting antibiotic resistance genes is more challenging, involving several ongoing issues: (1) the comprehensiveness, of functional annotations, and the timeliness of updates of antibiotic resistance gene mutations in resistance databases [20]; (2) accurately associating genotypic resistance with phenotypic resistance in multi-microbial samples [33]; (3) establishing standardized bioinformatics analysis pipelines [34]; (4) improving sequencing depth to enhance sensitivity [35]. Currently, clinicians need to consider a patient's prior antibiotic usage history and their response to treatment to determine whether adjusting the treatment plan based on the resistance information provided by NTS tests.…”

Section: Discussionmentioning

confidence: 99%

Molecular Rapid Diagnostic Testing for Bloodstream Infections: Nanopore Targeted Sequencing with Pathogen-Specific Primers

Han,

Yu,

Zhang

et al. 2024

Preprint

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Background Nanopore sequencing, known for real-time analysis, shows promise for rapid clinical infection diagnosis but lacks effective assays for bloodstream infections (BSIs). Methods We prospectively assessed a novel nanopore targeted sequencing (NTS) assay's performance in identifying pathogens and predicting antibiotic resistance in BSIs, analyzing 387 blood samples from December 2021 to April 2023. Results The positivity rate for NTS (69.5%, 269/387) nearly matches that of metagenomic next-generation sequencing (mNGS) (74.7%, 289/387; p = 0.128) and surpasses the positivity rate of conventional blood culture (BC) (33.9%, 131/387; p < 0.01). Frequent pathogens detected by NTS included Klebsiella pneumoniae (n = 54), Pseudomonas aeruginosa (n = 36), Escherichia coli (n = 36), Enterococcus faecium (n = 30), Acinetobacter baumannii(n = 26), Staphylococcus aureus(n = 23), and Human cytomegalovirus (n = 37). Against a composite BSI diagnostic standard, NTS demonstrated a sensitivity and specificity of 84.0% (95% CI 79.5%-87.7%) and 90.1% (95% CI 81.7%-88.5%), respectively. The concordance between NTS and mNGS results (the percentage of total cases where both either detected BSI-related pathogens or were both negative) was 90.2% (359/387), whereas the consistency between NTS and BC was only 60.2% (233/387). In 80.6% (50/62) of the samples with identical pathogens identified by both NTS tests and BCs, the genotypic resistance identified by NTS correlated with culture-confirmed phenotypic resistance. Using NTS, 95% of samples can be tested and analyzed in approximately 7 hours, allowing for early patient diagnosis. Conclusions NTS is rapid, sensitive, and efficient for detecting BSIs and drug-resistant genes, making it a potential preferred diagnostic tool for early infection identification in critically ill patients.

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“…Therefore, filtering out these false positives by enforcing strict settings might also result in loss of sensitivity as some true positives could be discarded ( Sun et al, 2021 ; Portik et al, 2022 ). This was experienced by Rooney et al (2022) who tested different filtering strategies on KMA output data to improve AMR gene detection, resulting in a decrease in false positives, and the detriment of true positives. To avoid this, instead of setting a minimum threshold that will eliminate part of the results, confidence detection levels were elaborated in the present study, allowing an increase in the specificity of KMA without sacrificing its sensitivity.…”

Section: Discussionmentioning

confidence: 99%

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

Gand,

Navickaite,

Bartsch

et al. 2024

Front. Microbiol.

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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.

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Performance Characteristics of Next-Generation Sequencing for the Detection of Antimicrobial Resistance Determinants in Escherichia coli Genomes and Metagenomes

Cited by 13 publications

References 58 publications

Exploring the effects of antimicrobial treatment on the gut and oral microbiomes and resistomes from elderly long-term care facility residents via shotgun DNA sequencing

Exploring the effects of antimicrobial treatment on the gut and oral microbiomes and resistomes from elderly long-term care facility residents via shotgun DNA sequencing

Molecular Rapid Diagnostic Testing for Bloodstream Infections: Nanopore Targeted Sequencing with Pathogen-Specific Primers

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

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