Lack of significant differences between gastrointestinal tract microbial population structure of Helicobacter pylori‐infected subjects before and 2 years after a single eradication event. Issue 5 (9th August 2020)

• Record Type: Journal Article
• Authors: Gudra, Dita; Pupola, Darta; Skenders, Girts; Leja, Marcis; Radovica‐Spalvina, Ilze; Gorskis, Henrihs; Vangravs, Reinis; Fridmanis, Davids
• Is Part Of: Helicobacter. Volume 25:Issue 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-09
• Subjects: 16S sequencing -- Helicobacter pylori -- microbiome -- OC‐Sensor; Helicobacter -- Periodicals; Helicobacter infections -- Periodicals; Stomach -- Diseases -- Periodicals; 616.3301405
• DOI: 10.1111/hel.12748
• Languages: English
• ISSNs: 1083-4389

Abstract

Abstract: Background: According to recent estimates 80% of Latvian population is infected with Helicobacter pylori thus their susceptibility to numerous gastric tract diseases is increased. The 1 st line H. pylori eradication therapy includes treatment with clarithromycin in combination with amoxicillin or metronidazole and a proton pump inhibitor. However, potential adverse events caused by such therapies to microbiome are insufficiently studied. Objective: This study aimed to evaluate the long‐term effect of H. pylori eradication on human gastrointestinal tract (GIT) microbiome. Methods: The assessment of H pylori eradication impact on GIT microbiome was done by analyzing 120 samples acquired from 60 subjects. Each individual was prescribed the following 10‐day eradication regimen: Esomeprazolum 40 mg, Clarithromycinum 500 mg, and Amoxicillinum 1000 mg, BID. Samples from each individual were collected before starting H pylori eradication therapy, and 2 years after the completion of the therapy in OC‐Sensor (Eiken Chemical Co.) sample collection containers and stored at −86°C. Prior to DNA extraction, the samples were lyophilized, and total DNA was extracted using FastDNA Spin Kit for Soil. 16S V3 rRNA gene sequencing was done employing Ion Torrent PGM, and the obtained raw sequences were analyzed using vsearch and R (phyloseq, cluster packages). Results: Alpha diversity measurements—observed OTUs, Chao1 and Shannon index did not differ significantly between the pre‐ and post‐eradication states (two‐tailed paired t test: P = .95; P = .71, P = .24, respectively). Unweighted and weighted UniFrac distances of beta diversity analysis indicated a non‐specific pattern of sample clustering. Enterotype shift was observed for the majority of individuals comparing pre‐ and post‐eradication study groups. Association analysis revealed that certain bacterial genera significantly correlated with age (eg, Dialister, Paraprevotella, Bifidobacterium ), individual (eg, Thermotunica, Streptomyces, Faecalibacterium ), and history of respiratory and/or allergic diseases (eg, Colinsella, Faecalibacterium ). Redundancy analysis confirmed that the individual was a significant determinant of the subject's microbial community composition (ANOVA, 999 perm., P = .001) with the further lower impact of subject‐specific medical history (eg, medication used as prescribed: P = .005, history of cardiovascular diseases: P = .005, history of respiratory, and/or allergic diseases: P = .015) and physiological (eg, age: P = .005, gender: P = .02) parameters. In the post‐eradication study group, number of influential genera (n = 260) was increased compared to the pre‐eradication study group (n = 209). Conclusion: Modest global differences at the community level exist between individuals before and after the eradication therapy; however, the microbiome structure is more related to the subject‐specific parameters rather than by the eradication therapy itself.