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Record W3021110573 · doi:10.1136/sextrans-2019-sti.712

P644 Analyzing the genomes of<i>neisseria gonorrhoeae</i>isolates using a novel integrated bioinformatic pipeline: Gen2Epi

2019· article· en· W3021110573 on OpenAlexaffabout
Nidhi Parmar, Reema Singh, Irene Martin, Sumudu R Perera, Walter Demczuk, Anthony Kusalik, Jessica Minion, Jo‐Anne R. Dillon

Bibliographic record

VenuePoster presentations · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsSaskatchewan Health AuthorityRegina Qu'Appelle Health RegionUniversity of Saskatchewan
Fundersnot available
KeywordsNeisseria gonorrhoeaeMultilocus sequence typingBiologyCefiximeTetracyclineNeisseriaMicrobiologyGenomeLincosamidesGeneticsAntibiotic resistanceCephalosporinGeneGenotypeAntibioticsBacteria

Abstract

fetched live from OpenAlex

Background Whole genome sequencing (WGS) is a high-resolution approach for tracking the transmission and antimicrobial susceptibility (AMS) of Neisseria gonorrhoeae (Ng). Multiple bioinformatics tools currently used for the analysis of WGS data for Ng complicate their application in clinical settings. We determined the genomic epidemiology and AMS of Ng from Saskatchewan (SK) using our integrated pipeline, Gen2Epi, previously validated on 1484 publicly available Ng genome datasets. Methods WGS was performed on 99 Ng isolates (2017–2018) from SK submitted to the Roy Romanow Provincial Laboratory. Genomic DNA was isolated using the DNAeasy mini kit (QIAGEN) and sequenced using MiSeq (Illumina). MICs were determined by agar dilution. Gen2Epi includes read assembly, scaffolding, strain typing (ST) by MLST and NG-MAST, plasmid identification, and, identification of mutations in antibiotic resistance genes by NG-STAR. Results Nine MLST/NG-MAST/NG-STAR (M/M/S) STs comprised 75.6% (75/99) of the isolates; other M/M/S STs (24.3%, 24/99) comprised single isolates. M/M/S ST 1901/10451/90 predominated (21.3%, 21/99), carrying mosaic penA type 34.001 and mutations in mtrR/porB/ponA/gyrA/parC. These isolates were chromosomally resistant to penicillin (38%, 8/21), tetracycline (95.2%, 20/21), and ciprofloxacin (90%, 19/21); they were susceptible to ceftriaxone and 38% (8/21) had cefixime MICs of 0.125 mg/L. The second-most prevalent ST was 1584/7638/160 (18/99); most of these isolates (16/18) were susceptible to all antibiotics. Overall, 57.6% (57/99) of the isolates were tetracycline resistant; 29.8% (17/57) of these were from Regina and carried a tetM gene (M/M/S ST 12462/5985/42). One sporadic isolate was azithromycin resistant (23S rRNA-A2059G), carried tetM and was M/M/S ST 7822/304/515. Conclusion Gen2Epi is a one-stop pipeline that both assembles and annotates raw reads and simplifies the analysis of transmission markers and AMS in Ng. We showed the emergence of M/M/S ST 1901/10451/90 as the predominant ST in SK. NG-MAST ST 10451 is similar (≤2bp) to ST 1407 which is implicated in reduced susceptibility to cefixime. Disclosure No significant relationships.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.309
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes2
Has abstractyes

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