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Updated: Oct 12, 2025

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota
Published on: July 31, 2019
Interactions between gastric microbiota and metabolites in gastric cancer
Daofeng Dai1, Yan Yang2, Jieqing Yu3
1Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China. ddf2010@alumni.sjtu.edu.cn.
Abstract:
The development and progression of gastric cancer (GC) is greatly influenced by gastric microbiota and their metabolites. Here, we characterized the gastric microbiome and metabolome profiles of 37 GC tumor tissues and matched non-tumor tissues using 16s rRNA gene sequencing and ultrahigh performance liquid chromatography tandem mass spectrometry, respectively. Microbial diversity and richness were higher in GC tumor tissues than in non-tumor tissues. The abundance of Helicobacter was increased in non-tumor tissues, while the abundance of Lactobacillus, Streptococcus, Bacteroides, Prevotella, and 6 additional genera was increased in the tumor tissues. The untargeted metabolome analysis revealed 150 discriminative metabolites, among which the relative abundance of the amino acids, carbohydrates and carbohydrate conjugates, glycerophospholipids, and nucleosides was higher in tumor tissues compared to non-tumor tissues. The targeted metabolome analysis further demonstrated that the combination of 1-methylnicotinamide and N-acetyl-D-glucosamine-6-phosphate could serve as a robust biomarker for distinction between GC tumors and non-tumor tissues. Correlation analysis revealed that Helicobacter and Lactobacillus were negatively and positively correlated with the majority of differential metabolites in the classes of amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids, respectively, suggesting that Helicobacter and Lactobacillus might play a role in degradation and synthesis of the majority of differential metabolites in these classes, respectively. Acinetobacter, Comamonas, Faecalibacterium, Sphingomonas, and Streptococcus were also significantly correlated with many differential amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids. In conclusion, the differences in metabolome profiles between GC tumor and matched non-tumor tissues may be partly due to the collective activities of Helicobacter, Lactobacillus, and other bacteria, which eventually affects GC carcinogenesis and progression.
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