Date of Award

1-1-2017

Language

English

Document Type

Master's Thesis

Degree Name

Master of Science (MS)

College/School/Department

Department of Environmental Health Sciences

Content Description

1 online resource (ii, v, 29 pages) : illustrations (some color)

Dissertation/Thesis Chair

Qing-Yu Zhang

Committee Members

Xinxin Ding, David C Spink

Keywords

Ampicillin, Antibiotic, Cytochrome P450, Intestine, Microbiota, Microflora, Cytochrome P-450, Antibiotics, Gallbladder, Bile acids

Subject Categories

Molecular Biology | Pharmacology | Toxicology

Abstract

Expression of metabolic enzymes Cytochrome P450 (CYP) is highly affected by drugs, diseases, age and gender. The Intestinal microflora has been suggested to play a role in regulating CYP expression and antibiotic treatments would lead to changes in level and composition of microbiota in mouse gut. This study aims to analyze CYP expression changes in the liver and small intestine resulted from the reduction of intestinal microflora by antibiotics. Impacts on bile acid signaling were also analyzed for a better comprehension of the mechanisms involved in this modulation. Female C57BL/6J mice (9- to 13-week old) were treated with ampicillin (AMP) or vehicle for 3 or 7 days. Analysis of mRNA expression level indicated decreased expression of CYP2B10 in liver and intestine of mice treated for 3 days. In 7 days of AMP treatment, CYP3A11 mRNA levels were decreased in liver and increased in the intestine of mice. The AMP treatment reduced the population of lithocholic acid-producing bacterial strains and led to decreased expression of fibroblast growth factor 15 (FGF15) and increased expression of apical sodium-dependent bile acid transporter (ASBT). Enlarged gallbladders and the increased levels of CYP7A1 mRNA suggested an increase of bile acid synthesis and bile secretion. This study indicates that changes in the microflora can modulate CYP expression in mouse liver and intestine. A full understanding of the role of gut microflora in xenobiotic metabolism is desirable in order to predict drug-drug interactions, drug-diet interactions, and individual pharmacokinetic differences.

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