Deciphering complex antibiotic resistance patterns in Helicobacter pylori through whole genome sequencing and machine learning.

ABSTRACT:

Introduction

Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp using next-generation sequencing could enhance our understanding of this resistance.

Methods

In this study, we analyzed 52 Hp strains collected from various hospitals. The susceptibility of these strains to five antibiotics was assessed using the agar dilution assay. Whole-genome sequencing was then performed to screen the antimicrobial resistance (AMR) genotypes of these Hp strains. To model the relationship between drug resistance and genotype, we employed univariate statistical tests, unsupervised machine learning, and supervised

SUBMITTER: Yu J 

PROVIDER: S-EPMC10878306 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature