Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic Nanopore sequencing.

ABSTRACT: The rise of antimicrobial-resistant Neisseria gonorrhoeae is a significant public health concern. Against this background, rapid culture-independent diagnostics may allow targeted treatment and prevent onward transmission. We have previously shown metagenomic sequencing of urine samples from men with urethral gonorrhea can recover near-complete N. gonorrhoeae genomes. However, disentangling the N. gonorrhoeae genome from metagenomic samples and robustly identifying antimicrobial resistance determinants from error-prone Nanopore sequencing is a substantial bioinformatics challenge. Here, we show an N. gonorrhoeae diagnostic workflow for analysis of metagenomic sequencing data obtained from clinical samples using R9.4.1 Nanopore sequencing. We compared results from simulated and clinical infections with data from known reference strains and Illumina sequencing of isolates cultured from the same patients. We evaluated three Nanopore variant callers and developed a random forest classifier to filter called SNPs. Clair was the most suitable variant caller after SNP filtering. A minimum depth of 20× reads was required to confidently identify resistant determinants over the entire genome. Our findings show that metagenomic Nanopore sequencing can provide reliable diagnostic information in N. gonorrhoeae infection.

SUBMITTER: Sanderson ND

PROVIDER: S-EPMC7545138 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford Nanopore MinION sequencer.

Project description:Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is common, compromising gonorrhoea treatment internationally. Rapid characterisation of AMR strains could ensure appropriate and personalised treatment, and support identification and investigation of gonorrhoea outbreaks in nearly real-time. Whole-genome sequencing is ideal for investigation of emergence and dissemination of AMR determinants, predicting AMR, in the gonococcal population and spread of AMR strains in the human population. The novel, rapid and revolutionary long-read sequencer MinION is a small hand-held device that generates bacterial genomes within one day. However, accuracy of MinION reads has been suboptimal for many objectives and the MinION has not been evaluated for gonococci. In this first MinION study for gonococci, we show that MinION-derived sequences analysed with existing open-access, web-based sequence analysis tools are not sufficiently accurate to identify key gonococcal AMR determinants. Nevertheless, using an in house-developed CLC Genomics Workbench including de novo assembly and optimised BLAST algorithms, we show that 2D ONT-derived sequences can be used for accurate prediction of decreased susceptibility or resistance to recommended antimicrobials in gonococcal isolates. We also show that the 2D ONT-derived sequences are useful for rapid phylogenomic-based molecular epidemiological investigations, and, in hybrid assemblies with Illumina sequences, for producing contiguous assemblies and finished reference genomes.

| S-EPMC6279828 | biostudies-literature

Target enrichment improves culture-independent detection of <i>Neisseria gonorrhoeae</i> and antimicrobial resistance determinants direct from clinical samples with Nanopore sequencing.

Project description:Multi-drug-resistant Neisseria gonorrhoeae infection is a significant public health risk. Rapidly detecting N. gonorrhoeae and antimicrobial-resistant (AMR) determinants by metagenomic sequencing of urine is possible, although high levels of host DNA and overgrowth of contaminating species hamper sequencing and limit N. gonorrhoeae genome coverage. We performed Nanopore sequencing of nucleic acid amplification test-positive urine samples and culture-positive urethral swabs with and without probe-based target enrichment, using a custom SureSelect panel, to investigate whether selective enrichment of N. gonorrhoeae DNA improves detection of both species and AMR determinants. Probes were designed to cover the entire N. gonorrhoeae genome, with tenfold enrichment of probes covering selected AMR determinants. Multiplexing was tested in a subset of samples. The proportion of sequence bases classified as N. gonorrhoeae increased in all samples after enrichment, from a median (IQR) of 0.05 % (0.01-0.1 %) to 76 % (42-82 %), giving a corresponding median improvement in fold genome coverage of 365 times (112-720). Over 20-fold coverage, required for robust AMR determinant detection, was achieved in 13/15(87 %) samples, compared to 2/15(13 %) without enrichment. The four samples multiplexed together also achieved >20-fold genome coverage. Coverage of AMR determinants was sufficient to predict resistance conferred by changes in chromosomal genes, where present, and genome coverage also enabled phylogenetic relationships to be reconstructed. Probe-based target enrichment can improve N. gonorrhoeae genome coverage when sequencing DNA extracts directly from urine or urethral swabs, allowing for detection of AMR determinants. Additionally, multiplexing prior to enrichment provided enough genome coverage for AMR detection and reduces the costs associated with this method.

| S-EPMC10995632 | biostudies-literature

Evaluation of Germline Structural Variant Calling Methods for Nanopore Sequencing Data.

Project description:Structural variants (SVs) are genomic rearrangements that involve at least 50 nucleotides and are known to have a serious impact on human health. While prior short-read sequencing technologies have often proved inadequate for a comprehensive assessment of structural variation, more recent long reads from Oxford Nanopore Technologies have already been proven invaluable for the discovery of large SVs and hold the potential to facilitate the resolution of the full SV spectrum. With many long-read sequencing studies to follow, it is crucial to assess factors affecting current SV calling pipelines for nanopore sequencing data. In this brief research report, we evaluate and compare the performances of five long-read SV callers across four long-read aligners using both real and synthetic nanopore datasets. In particular, we focus on the effects of read alignment, sequencing coverage, and variant allele depth on the detection and genotyping of SVs of different types and size ranges and provide insights into precision and recall of SV callsets generated by integrating the various long-read aligners and SV callers. The computational pipeline we propose is publicly available at https://github.com/davidebolo1993/EViNCe and can be adjusted to further evaluate future nanopore sequencing datasets.

| S-EPMC8637281 | biostudies-literature

Molecular Antimicrobial Resistance Surveillance for Neisseria gonorrhoeae, Northern Territory, Australia.

Project description:Neisseria gonorrhoeae antimicrobial resistance (AMR) is a globally recognized health threat; new strategies are needed to enhance AMR surveillance. The Northern Territory of Australia is unique in that 2 different first-line therapies, based primarily on geographic location, are used for gonorrhea treatment. We tested 1,629 N. gonorrhoeae nucleic acid amplification test-positive clinical samples, collected from regions where ceftriaxone plus azithromycin or amoxicillin plus azithromycin are recommended first-line treatments, by using 8 N. gonorrhoeae AMR PCR assays. We compared results with those from routine culture-based surveillance data. PCR data confirmed an absence of ceftriaxone resistance and a low level of azithromycin resistance (0.2%), and that penicillin resistance was <5% in amoxicillin plus azithromycin regions. Rates of ciprofloxacin resistance and penicillinase-producing N. gonorrhoeae were lower when molecular methods were used. Molecular methods to detect N. gonorrhoeae AMR can increase the evidence base for treatment guidelines, particularly in settings where culture-based surveillance is limited.

| S-EPMC5572890 | biostudies-literature

Whole-Genome Sequencing to Predict Antimicrobial Susceptibility Profiles in Neisseria gonorrhoeae.

Project description:BackgroundNeisseria gonorrhoeae is a major public health problem due to increasing incidence and antimicrobial resistance. Genetic markers of reduced susceptibility have been identified; the extent to which those are representative of global antimicrobial resistance is unknown. We evaluated the performance of whole-genome sequencing (WGS) used to predict susceptibility to ciprofloxacin and other antimicrobials using a global collection of N. gonorrhoeae isolates.MethodsSusceptibility testing of common antimicrobials and the recently developed zolifodacin was performed using agar dilution to determine minimum inhibitory concentrations (MICs). We identified resistance alleles at loci known to contribute to antimicrobial resistance in N. gonorrhoeae from WGS data. We tested the ability of each locus to predict antimicrobial susceptibility.ResultsA total of 481 N. gonorrhoeae isolates, collected between 2004 and 2019 and making up 457 unique genomes, were sourced from 5 countries. All isolates with demonstrated susceptibility to ciprofloxacin (MIC ≤0.06 μg/mL) had a wild-type gyrA codon 91. Multilocus approaches were needed to predict susceptibility to other antimicrobials. All isolates were susceptible to zoliflodacin, defined by an MIC ≤0.25 μg/mL.ConclusionsSingle marker prediction can be used to inform ciprofloxacin treatment of N. gonorrhoeae infection. A combination of molecular markers may be needed to determine susceptibility for other antimicrobials.

| S-EPMC10319951 | biostudies-literature

Equations To Predict Antimicrobial MICs in Neisseria gonorrhoeae Using Molecular Antimicrobial Resistance Determinants.

Project description:The emergence of Neisseria gonorrhoeae strains that are resistant to azithromycin and extended-spectrum cephalosporins represents a public health threat, that of untreatable gonorrhea infections. Multivariate regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to the overall antimicrobial MICs for ceftriaxone, cefixime, azithromycin, tetracycline, ciprofloxacin, and penicillin. A training data set consisting of 1,280 N. gonorrhoeae strains was used to generate regression equations which were then applied to validation data sets of Canadian (n = 1,095) and international (n = 431) strains. The predicted MICs for extended-spectrum cephalosporins (ceftriaxone and cefixime) were fully explained by 5 amino acid substitutions in PenA, A311V, A501P/T/V, N513Y, A517G, and G543S; the presence of a disrupted mtrR promoter; and the PorB G120 and PonA L421P mutations. The correlation of predicted MICs within one doubling dilution to phenotypically determined MICs of the Canadian validation data set was 95.0% for ceftriaxone, 95.6% for cefixime, 91.4% for azithromycin, 98.2% for tetracycline, 90.4% for ciprofloxacin, and 92.3% for penicillin, with an overall sensitivity of 99.9% and specificity of 97.1%. The correlations of predicted MIC values to the phenotypically determined MICs were similar to those from phenotype MIC-only comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular data will facilitate the transition to whole-genome sequencing analysis from phenotypic testing and can fill the surveillance gap in an era of increased reliance on nucleic acid assay testing (NAAT) diagnostics to better monitor the dynamics of N. gonorrhoeae.

| S-EPMC7038236 | biostudies-literature

Optimizing DNA Extraction Methods for Nanopore Sequencing of Neisseria gonorrhoeae Directly from Urine Samples.

Project description:Empirical gonorrhea treatment at initial diagnosis reduces onward transmission. However, increasing resistance to multiple antibiotics may necessitate waiting for culture-based diagnostics to select an effective treatment. There is a need for same-day culture-free diagnostics that identify infection and detect antimicrobial resistance. We investigated if Nanopore sequencing can detect sufficient Neisseria gonorrhoeae DNA to reconstruct whole genomes directly from urine samples. We used N. gonorrhoeae-spiked urine samples and samples from gonorrhea infections to determine optimal DNA extraction methods that maximize the amount of N. gonorrhoeae DNA sequenced while minimizing contaminating host DNA. In simulated infections, the Qiagen UCP pathogen mini kit provided the highest ratio of N. gonorrhoeae to human DNA and the most consistent results. Depletion of human DNA with saponin increased N. gonorrhoeae yields in simulated infections but decreased yields in clinical samples. In 10 urine samples from men with symptomatic urethral gonorrhea, ≥92.8% coverage of an N. gonorrhoeae reference genome was achieved in all samples, with ≥93.8% coverage breath at ≥10-fold depth in 7 (70%) samples. In simulated infections, if ≥104 CFU/ml of N. gonorrhoeae was present, sequencing of the large majority of the genome was frequently achieved. N. gonorrhoeae could also be detected from urine in cobas PCR medium tubes and from urethral swabs and in the presence of simulated Chlamydia coinfection. Using Nanopore sequencing of urine samples from men with urethral gonorrhea, sufficient data can be obtained to reconstruct whole genomes in the majority of samples without the need for culture.

| S-EPMC7041563 | biostudies-literature

Whole-Genome Sequencing of Neisseria gonorrhoeae Isolates with Antimicrobial Resistance Plasmids from a Homeless Community in Colombia.

Project description:Neisseria gonorrhoeae is a pathogenic bacterium causing sexually transmitted infections, and it is associated with high antibiotic resistance rates. Here, we describe the genome sequences of four isolates from a homeless community in Colombia.

| S-EPMC9670893 | biostudies-literature

Genomic epidemiology and antimicrobial resistance of Neisseria gonorrhoeae in New Zealand.

Project description:Background:Antimicrobial-resistant Neisseria gonorrhoeae is a major threat to public health. No studies to date have examined the genomic epidemiology of gonorrhoea in the Western Pacific Region, where the incidence of gonorrhoea is particularly high. Methods:A population-level study of N. gonorrhoeae in New Zealand (October 2014 to May 2015). Comprehensive susceptibility testing and WGS data were obtained for 398 isolates. Relatedness was inferred using phylogenetic trees, and pairwise core SNPs. Mutations and genes known to be associated with resistance were identified, and correlated with phenotype. Results:Eleven clusters were identified. In six of these clusters, >25% of isolates were from females, while in eight of them, >15% of isolates were from females. Drug resistance was common; 98%, 32% and 68% of isolates were non-susceptible to penicillin, ciprofloxacin and tetracycline, respectively. Elevated MICs to extended-spectrum cephalosporins (ESCs) were observed in 3.5% of isolates (cefixime MICs ≥ 0.12 mg/L, ceftriaxone MICs ≥ 0.06 mg/L). Only nine isolates had penA XXXIV genotypes, three of which had decreased susceptibility to ESCs (MIC = 0.12 mg/L). Azithromycin non-susceptibility was identified in 43 isolates (10.8%); two of these isolates had 23S mutations (C2611T, 4/4 alleles), while all had mutations in mtrR or its promoter. Conclusions:The high proportion of females in clusters suggests transmission is not exclusively among MSM in New Zealand; re-assessment of risk factors for transmission may be warranted in this context. As elevated MICs of ESCs and/or azithromycin were found in closely related strains, targeted public health interventions to halt transmission are urgently needed.

| S-EPMC5890773 | biostudies-literature

Neisseria gonorrhoeae Sequence Typing for Antimicrobial Resistance, a Novel Antimicrobial Resistance Multilocus Typing Scheme for Tracking Global Dissemination of N. gonorrhoeae Strains.

Project description:A curated Web-based user-friendly sequence typing tool based on antimicrobial resistance determinants in Neisseria gonorrhoeae was developed and is publicly accessible (https://ngstar.canada.ca). The N. gonorrhoeae Sequence Typing for Antimicrobial Resistance (NG-STAR) molecular typing scheme uses the DNA sequences of 7 genes (penA, mtrR, porB, ponA, gyrA, parC, and 23S rRNA) associated with resistance to β-lactam antimicrobials, macrolides, or fluoroquinolones. NG-STAR uses the entire penA sequence, combining the historical nomenclature for penA types I to XXXVIII with novel nucleotide sequence designations; the full mtrR sequence and a portion of its promoter region; portions of ponA, porB, gyrA, and parC; and 23S rRNA sequences. NG-STAR grouped 768 isolates into 139 sequence types (STs) (n = 660) consisting of 29 clonal complexes (CCs) having a maximum of a single-locus variation, and 76 NG-STAR STs (n = 109) were identified as unrelated singletons. NG-STAR had a high Simpson's diversity index value of 96.5% (95% confidence interval [CI] = 0.959 to 0.969). The most common STs were NG-STAR ST-90 (n = 100; 13.0%), ST-42 and ST-91 (n = 45; 5.9%), ST-64 (n = 44; 5.72%), and ST-139 (n = 42; 5.5%). Decreased susceptibility to azithromycin was associated with NG-STAR ST-58, ST-61, ST-64, ST-79, ST-91, and ST-139 (n = 156; 92.3%); decreased susceptibility to cephalosporins was associated with NG-STAR ST-90, ST-91, and ST-97 (n = 162; 94.2%); and ciprofloxacin resistance was associated with NG-STAR ST-26, ST-90, ST-91, ST-97, ST-150, and ST-158 (n = 196; 98.0%). All isolates of NG-STAR ST-42, ST-43, ST-63, ST-81, and ST-160 (n = 106) were susceptible to all four antimicrobials. The standardization of nomenclature associated with antimicrobial resistance determinants through an internationally available database will facilitate the monitoring of the global dissemination of antimicrobial-resistant N. gonorrhoeae strains.

| S-EPMC5405263 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data