2017 journal article

Gene co-expression network analysis identifies porcine genes associated with variation in metabolizing fenbendazole and flunixin meglumine in the liver

SCIENTIFIC REPORTS, 7.

By: J. Howard n, M. Ashwell  n, R. Baynes n , J. Brooks n, J. Yeatts n & C. Maltecca n 

MeSH headings : Animals; Antinematodal Agents / pharmacokinetics; Clonixin / analogs & derivatives; Clonixin / pharmacokinetics; Female; Fenbendazole / pharmacokinetics; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Liver / drug effects; Liver / metabolism; Male; Sus scrofa / genetics; Transcriptome
TL;DR: The objective was to identify individual genes and gene networks involved in metabolizing fenbendazole (FBZ) and flunixin meglumine (FLU) in swine liver to allow for greater insight into FBZ and FLU metabolism. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

AbstractIdentifying individual genetic variation in drug metabolism pathways is of importance not only in livestock, but also in humans in order to provide the ultimate goal of giving the right drug at the right dose at the right time. Our objective was to identify individual genes and gene networks involved in metabolizing fenbendazole (FBZ) and flunixin meglumine (FLU) in swine liver. The population consisted of female and castrated male pigs that were sired by boars represented by 4 breeds. Progeny were randomly placed into groups: no drug (UNT), FLU or FBZ administered. Liver transcriptome profiles from 60 animals with extreme (i.e. fast or slow drug metabolism) pharmacokinetic (PK) profiles were generated from RNA sequencing. Multiple cytochrome P450 (CYP1A1, CYP2A19 and CYP2C36) genes displayed different transcript levels across treated versus UNT. Weighted gene co-expression network analysis identified 5 and 3 modules of genes correlated with PK parameters and a portion of these were enriched for biological processes relevant to drug metabolism for FBZ and FLU, respectively. Genes within identified modules were shown to have a higher transcript level relationship (i.e. connectivity) in treated versus UNT animals. Investigation into the identified genes would allow for greater insight into FBZ and FLU metabolism.