Department of Animal Science, North Carolina State University, Raleigh, NC 27695-7621, USA.
Department of Population Health and Pathobiology, Center for Chemical Toxicology and Research Pharmacokinetics, North Carolina State University, College of Veterinary Medicine, 4700 Hillsborough Road, Raleigh, North Carolina, 27606, USA.
Sci Rep. 2017 May 2;7(1):1357. doi: 10.1038/s41598-017-01526-5.
Identifying 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.
确定药物代谢途径中的个体遗传变异不仅在畜牧业中很重要,而且在人类中也很重要,目的是为了实现“在适当的时间给予适当剂量的适当药物”这一终极目标。本研究的目的是鉴定参与猪肝脏中芬苯达唑(FBZ)和氟尼辛葡甲胺(FLU)代谢的个体基因和基因网络。该群体由母猪所生的雌性和去势公猪组成,公猪来自 4 个品种。后代随机分为 3 组:不给予药物(UNT)、给予 FLU 或 FBZ。从 60 只具有极端(即药物代谢快速或缓慢)药代动力学(PK)特征的动物的肝脏转录组图谱中,通过 RNA 测序生成了 60 只动物的转录组图谱。与 UNT 相比,多个细胞色素 P450(CYP1A1、CYP2A19 和 CYP2C36)基因在处理组和 UNT 组之间显示出不同的转录水平。加权基因共表达网络分析鉴定出与 PK 参数相关的 5 个和 3 个基因模块,其中一部分与 FBZ 和 FLU 的药物代谢相关的生物学过程富集。与 UNT 相比,处理组中鉴定模块内的基因具有更高的转录水平关系(即连通性)。对鉴定出的基因进行研究将有助于深入了解 FBZ 和 FLU 的代谢。