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Record W4409996787 · doi:10.1186/s12866-025-03990-w

Identification of genetic determinants of antibiotic resistance in Helicobacter pylori isolates in Vietnam by high-throughput sequencing

2025· article· en· W4409996787 on OpenAlexfundno aff
Trang Ngoc Cao, Thanh Tran, Takashi Matsumoto, Junko Akada, Yoshio Yamaoka

Bibliographic record

VenueBMC Microbiology · 2025
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsnot available
FundersScience and Technology Research Partnership for Sustainable DevelopmentInstitute of GeneticsMinistry of Education, Culture, Sports, Science and TechnologyJapan Society for the Promotion of ScienceNational Institute of Diabetes and Digestive and Kidney DiseasesJapan International Cooperation AgencyNational Institutes of HealthJapan Agency for Medical Research and Development
KeywordsBiologyHelicobacter pyloriAntibiotic resistanceIdentification (biology)ParasitologyDNA sequencingAntibioticsMicrobiologyGeneticsComputational biologyGeneZoology

Abstract

fetched live from OpenAlex

The aim of this study was to identify genetic factors responsible for antibiotic resistance in Helicobacter pylori, a bacterium that can cause long-term gastroduodenal disease. The primary resistance of H. pylori to commonly used antibiotics was studied, and high-throughput next-generation sequencing (NGS) was employed to discover genetic determinants of resistance using a reference-based approach. A total of 123 H. pylori strains were cultured and tested for antibiotic susceptibility using an E test. Genotypic analysis was performed using NGS data with ARIBA v2.14.7 and PlasmidSeeker v1.3 for plasmid detection. Statistical correlations between resistant genotypes and phenotypes were evaluated. In addition, a genome-wide association study (GWAS) and linear mixed model were used to identify genetic variants associated with antimicrobial resistance phenotypes while adjusting for covariates such as population structure. Our results showed that 78.2% of the strains were resistant to metronidazole (MTZ), 22.5% to levofloxacin (LVX), 43.5% to clarithromycin (CLR) and 13.7% to amoxicillin (AMX). Resistance to tetracycline was not detected. Multi-drug resistance was detected in 48.8% of the strains. While plasmids were not detected, chromosomal genetic determinants of resistance to CLR, LVX, and AMX were identified, including mutations in 23S rRNA (A2142G and A2143G), gyrA (N87K/Y and D91Y/N/G), and pbp1 A (F366L, S414R, F473V, G595_V596insE, as well as the mutations T558S and T593A/G/P/S). Additionally, missense, frameshift, and nonsense mutations in rdxA were identified as genetic determinants of resistance to MTZ. No genetic determinants associated with tetracycline resistance were detected. A strong correlation was observed between resistance genotypes and phenotypes for CLR, LVX, AMX, and MTZ. In addition, we found that missense, frameshift and nonsense mutations in rdxA were genetic determinants of resistance to MTZ. We did not detect any genetic determinants associated with tetracycline resistance. There was a strong correlation between resistance genotypes and phenotypes for CLR, LVX, AMX, and MTZ. Furthermore, unitig-based GWAS revealed that AMX, LVX, and CLR resistance in H. pylori was mainly caused by chromosomal mutations that affected the targets of these antibiotics (pbp1 A, gyrA, and 23S rRNA, respectively). Our results highlight the need for regular evaluation and alternative therapies in Vietnam, given the high rates of H. pylori resistance to CLR, MTZ, and LVX. Our study also demonstrated the high capacity of NGS to detect genetic resistance determinants and its potential for implementation in local treatment policies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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