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Gastric juice microbiota in pediatric chronic gastritis that clinically tested positive and negative for Helicobacter pylori

PURPOSE: Helicobacter pylori (HP) infection is an identified risk factor for pediatric chronic gastritis (PCG), but its impact on gastric juice microbiota (GJM) remains to be further elucidated in PCG. This study aimed to analyze and compare the microbial communities and microbial interactive networ...

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Detalles Bibliográficos
Autores principales: Chen, Ying, Xia, Shou-Yue, Ru, Fu-Xia, Feng, Jun-Jie, Tao, Ji, Wei, Zhi-Yuan, Li, Xiu, Qian, Chengjia, Lin, Qiong, Chen, Jian-Huan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168005/
https://www.ncbi.nlm.nih.gov/pubmed/37180270
http://dx.doi.org/10.3389/fmicb.2023.1112709
Descripción
Sumario:PURPOSE: Helicobacter pylori (HP) infection is an identified risk factor for pediatric chronic gastritis (PCG), but its impact on gastric juice microbiota (GJM) remains to be further elucidated in PCG. This study aimed to analyze and compare the microbial communities and microbial interactive networks of GJM in PCG that clinically tested positive and negative for HP (HP+ and HP−, respectively). METHODS: A total of 45 PCG patients aged from 6 to 16 years were recruited, including 20 HP+ and 25 HP− patients tested by culture and rapid urease test. Gastric juice samples were collected from these PCG patients and subjected to high-throughput amplicon sequencing and subsequent analysis of 16S rRNA genes. RESULTS: While no significant change in alpha diversity, significant differences in beta diversity were observed between HP+ and HP− PCG. At the genus level, Streptococcus, Helicobacter, and Granulicatella were significantly enriched in HP+ PCG, whereas Campylobacter and Absconditabacteriales (SR1) were significantly enriched in HP− PCG. Network analysis showed that Streptococcus was the only genus positively correlated with Helicobacter (r = 0.497) in the GJM network of overall PCG. Moreover, compared to HP− PCG, HP+ PCG showed a reduction in microbial network connectivity in GJM. Netshift analysis identified driver microbes including Streptococcus and other four genera, which substantially contributed to the GJM network transition from HP− PCG to HP+ PCG. Furthermore, Predicted GJM function analysis indicated up-regulated pathways related to the metabolism of nucleotides, carbohydrates, and L-Lysine, the urea cycle, as well as endotoxin peptidoglycan biosynthesis and maturation in HP+ PCG. CONCLUSION: GJM in HP+ PCG exhibited dramatically altered beta diversity, taxonomic structure, and function, with reduced microbial network connectivity, which could be involved in the disease etiology.