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Interactions between gastric microbiota and metabolites in gastric cancer
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 performanc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613192/ https://www.ncbi.nlm.nih.gov/pubmed/34819503 http://dx.doi.org/10.1038/s41419-021-04396-y |
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author | Dai, Daofeng Yang, Yan Yu, Jieqing Dang, Tianfeng Qin, Wenjing Teng, Lisong Ye, Jing Jiang, Hongqun |
author_facet | Dai, Daofeng Yang, Yan Yu, Jieqing Dang, Tianfeng Qin, Wenjing Teng, Lisong Ye, Jing Jiang, Hongqun |
author_sort | Dai, Daofeng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8613192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86131922021-12-01 Interactions between gastric microbiota and metabolites in gastric cancer Dai, Daofeng Yang, Yan Yu, Jieqing Dang, Tianfeng Qin, Wenjing Teng, Lisong Ye, Jing Jiang, Hongqun Cell Death Dis Article 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. Nature Publishing Group UK 2021-11-24 /pmc/articles/PMC8613192/ /pubmed/34819503 http://dx.doi.org/10.1038/s41419-021-04396-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dai, Daofeng Yang, Yan Yu, Jieqing Dang, Tianfeng Qin, Wenjing Teng, Lisong Ye, Jing Jiang, Hongqun Interactions between gastric microbiota and metabolites in gastric cancer |
title | Interactions between gastric microbiota and metabolites in gastric cancer |
title_full | Interactions between gastric microbiota and metabolites in gastric cancer |
title_fullStr | Interactions between gastric microbiota and metabolites in gastric cancer |
title_full_unstemmed | Interactions between gastric microbiota and metabolites in gastric cancer |
title_short | Interactions between gastric microbiota and metabolites in gastric cancer |
title_sort | interactions between gastric microbiota and metabolites in gastric cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613192/ https://www.ncbi.nlm.nih.gov/pubmed/34819503 http://dx.doi.org/10.1038/s41419-021-04396-y |
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