Metabolomics

Dataset Information

0

Gut Microbiome and Metabolome Alterations in Mice with Arsenic Exposure and Antibiotic Treatment: Potential Role of Arsenic Biotransformation Genes


ABSTRACT:

Arsenic is the most prevalent toxic metalloid in environment. Evidence of mouse models (germ-free or antibiotic treatment) indicates the gut microbiota’s involvement in the metabolism of ingested arsenic. Linking genes to gut microbial arsenic metabolism with altered toxicity and lifetime in the human body remains challenging. To investigate the role of arsenic biotransformation genes (ABGs) in gut microbial arsenic metabolism, conventional and antibiotic-treated mice (gut microbiota depletion by cefoperazone) were exposed to arsenic via drinking water for 2 weeks. A total of 17 ABGs were detected in the mouse gut, and their abundances (e.g., arsC, arsH and arsB genes) were markedly reduced in antibiotic-treated mice exposed to arsenic in comparison with conventional mice. Arsenic accumulation in liver, spleen and ileum were decreased as well. Consistently, both antibiotic treatment and arsenic exposure significantly induced gut microbiome perturbations including Erysipelotrichaceae and Bacteroidaceae, and metabolic alterations with up-regulated metabolites classified as flavonoids and amino acids. The ABGs were remarkably correlated with specific gut bacteria and metabolic profiles, exemplified by Prevotellaceae carrying arsC gene involved in amino acid metabolism, and Erysipelotrichaceae as aoxA gene carrier alleviating histamine accumulation. These findings provide a strong basis for studying arsenic induced toxicity and disease risk.

INSTRUMENT(S): Liquid Chromatography MS - positive - hilic, Liquid Chromatography MS - negative - hilic

PROVIDER: MTBLS11508 | MetaboLights | 2025-05-12

REPOSITORIES: MetaboLights

Dataset's files

Source:
Action DRS
F1.mzXML Mzxml
F10.mzXML Mzxml
F11.mzXML Mzxml
F12.mzXML Mzxml
F13.mzXML Mzxml
Items per page:
1 - 5 of 96

Similar Datasets

2023-01-25 | GSE144266 | GEO
2013-12-28 | E-GEOD-34630 | biostudies-arrayexpress
2017-03-16 | GSE81318 | GEO
2012-06-30 | E-GEOD-38880 | biostudies-arrayexpress
2020-08-26 | GSE156837 | GEO
| EGAS00001000729 | EGA
2018-11-01 | GSE104871 | GEO
| PRJNA997120 | ENA
2024-08-28 | E-MTAB-14264 | biostudies-arrayexpress
2024-08-28 | E-MTAB-14261 | biostudies-arrayexpress