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

Abstract

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.

Keywords: Helicobacter pylori; Antibiotic resistance; High-throughput sequencing; Pangenome-wide association study.

Fig. 1

The maximum likelihood phylogenetic tree based on whole-genome sequences, resistance patterns, and their corresponding genetic determinants for each antibiotic in the 123 H. pylori genomes sequenced in this study. The antibiotic sensitivity and resistance patterns are represented by dark blue and red rectangles, respectively. The presence and absence of mutations are indicated by green and pink rectangles, respectively

Fig. 2

A Distribution of clarithromycin minimum inhibitory concentrations (MICs) and corresponding mutations for all observed combinations of relevant antibiotic resistance determinants. B Distribution of levofloxacin MICs for all observed combinations of relevant antibiotic resistance determinants. Dotted horizontal lines mark clinical breakpoints. *** indicates p < 0.001 compared with isolates without mutations, ** indicates p < 0.01, * indicates p < 0.05

Fig. 3

A Distribution of amoxicillin minimum inhibitory concentrations (MICs) and corresponding mutations. B Distribution of metronidazole MICs for all observed combinations of relevant antibiotic resistance determinants. Dotted horizontal lines mark clinical breakpoints. *** indicates p < 0.001 compared with groups without mutations, ** indicates p < 0.01, * indicates p < 0.05

Fig. 4

Q‒Q plot constructed to assess the genome-wide association study results. Each dot in (A), (B), (C), and (D) indicates a unitig. Y-axis: observed − log10(P) of each unitig, where P is its P value. X-axis: expected − log10(P) under the null hypothesis of no association