Genomic Analysis of Antimicrobial Resistance Genotype-to-Phenotype Agreement in Helicobacter pylori
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Updated: Nov 23, 2025

Gastric Mucosa Quantitative Polymerase Chain Reaction Analysis for Detecting Helicobacter pylori and Antibiotic Resistance
Published on: March 7, 2025
Tal Domanovich-Asor1, Yair Motro1, Boris Khalfin1
1MAGICAL Group, Department of Health Systems Management, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
Abstract:
Antimicrobial resistance (AMR) in Helicobacter pylori is increasing and can result in treatment failure and inappropriate antibiotic usage. This study used whole genome sequencing (WGS) to comprehensively analyze the H. pylori resistome and phylogeny in order to characterize Israeli H. pylori. Israeli H. pylori isolates (n = 48) underwent antimicrobial susceptibility testing (AST) against five antimicrobials and WGS analysis. Literature review identified 111 mutations reported to correlate with phenotypic resistance to these antimicrobials. Analysis was conducted via our in-house bioinformatics pipeline targeting point mutations in the relevant genes (pbp1A, 23S rRNA, gyrA, rdxA, frxA, and rpoB) in order to assess genotype-to-phenotype correlation. Resistance rates of study isolates were as follows: clarithromycin 54%, metronidazole 31%, amoxicillin 10%, rifampicin 4%, and levofloxacin 2%. Genotype-to-phenotype correlation was inconsistent; for every analyzed gene at least one phenotypically susceptible isolate was found to have a mutation previously associated with resistance. This was also observed regarding mutations commonly used in commercial kits to diagnose AMR in H. pylori cases. Furthermore, 11 novel point mutations associated with a resistant phenotype were detected. Analysis of a unique set of H. pylori isolates demonstrates that inferring resistance phenotypes from WGS in H. pylori remains challenging and should be optimized further.
Insights
Antimicrobial resistance in Helicobacter pylori is a growing problem. Whole genome sequencing shows that predicting resistance from bacterial genes is challenging and requires further optimization.
Area of Science:
- Microbiology
- Genomics
- Infectious Diseases
Background:
- Increasing antimicrobial resistance (AMR) in Helicobacter pylori leads to treatment failures.
- Accurate prediction of AMR is crucial for effective H. pylori eradication therapy.
Purpose of the Study:
- To characterize the H. pylori resistome and phylogeny in Israeli isolates using whole genome sequencing (WGS).
- To assess the correlation between genotypic mutations and phenotypic antimicrobial resistance.
- To identify novel mutations associated with H. pylori antimicrobial resistance.
Main Methods:
- Antimicrobial susceptibility testing (AST) was performed on 48 H. pylori isolates.
- Whole genome sequencing (WGS) was used to analyze bacterial DNA.
- An in-house bioinformatics pipeline identified point mutations in resistance-associated genes (pbp1A, 23S rRNA, gyrA, rdxA, frxA, rpoB).
Main Results:
- High resistance rates were observed: clarithromycin (54%), metronidazole (31%), amoxicillin (10%), rifampicin (4%), and levofloxacin (2%).
- Genotype-to-phenotype correlation was inconsistent, with susceptible isolates showing resistance-associated mutations.
- Eleven novel point mutations linked to a resistant phenotype were discovered.
Conclusions:
- Inferring H. pylori resistance phenotypes from WGS data is challenging.
- Current methods for diagnosing AMR in H. pylori require further optimization.
- WGS analysis revealed complexities in H. pylori antimicrobial resistance mechanisms.
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