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

Howard, Jeremy; Ashwell, M.S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

doi:10.1038/s41598-017-01526-5

Cited by 9 publications

(13 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Module GS (MS) was the mean value of GS of the module genes. According to the selection criteria for critical modules reported in previous studies, modules with MTRs > 0.30 and MS > 0.25 were considered as candidate modules for the following functional enrichment analysis (Howard et al, 2017;Yang et al, 2018).…”

Section: Weighted Gene Coexpression Network Analysismentioning

confidence: 99%

Muscle Transcriptome Analysis Reveals Potential Candidate Genes and Pathways Affecting Intramuscular Fat Content in Pigs

Zhao

Lin

et al. 2020

Front. Genet.

View full text Add to dashboard Cite

Intramuscular fat (IMF) content plays an essential role in meat quality. For identifying potential candidate genes and pathways regulating IMF content, the IMF content and the longissimus dorsi transcriptomes of 28 purebred Duroc pigs were measured. As a result, the transcriptome analysis of four high-and four low-IMF individuals revealed a total of 309 differentially expressed genes (DEGs) using edgeR and DESeq2 (p < 0.05, |log 2 (fold change)| ≥ 1). Functional enrichment analysis of the DEGs revealed 19 hub genes significantly enriched in the Gene Ontology (GO) terms and pathways (q < 0.05) related to lipid metabolism and fat cell differentiation. The weighted gene coexpression network analysis (WGCNA) of the 28 pigs identified the most relevant module with 43 hub genes. The combined results of DEGs, WGCNA, and proteinprotein interactions revealed ADIPOQ, PPARG, LIPE, CIDEC, PLIN1, CIDEA, and FABP4 to be potential candidate genes affecting IMF. Furthermore, the regulation of lipolysis in adipocytes and the peroxisome proliferator-activated receptor (PPAR) signaling pathway were significantly enriched for both the DEGs and genes in the most relevant module. Some DEGs and pathways detected in our study play essential roles and are potential candidate genes and pathways that affect IMF content in pigs. This study provides crucial information for understanding the molecular mechanism of IMF content and would be helpful in improving pork quality.

show abstract

Section: Weighted Gene Coexpression Network Analysismentioning

confidence: 99%

Muscle Transcriptome Analysis Reveals Potential Candidate Genes and Pathways Affecting Intramuscular Fat Content in Pigs

Zhao

Lin

et al. 2020

Front. Genet.

View full text Add to dashboard Cite

show abstract

“…CYP1A1 is known to be responsible for the metabolism of pro-carcinogens such as polycyclic aromatic hydrocarbons (Moorthy et al 2015; Shimada 2006). The toxicological and clinical importance of CYP1A1 in drug metabolism warrants further investigation (Howard et al 2017; Lin et al 2017; Ma and Lu 2007) and our results suggest that precaution should be taken in patients with elevated CYP1A1 activity.…”

Section: Discussionmentioning

confidence: 80%

The role of hepatic cytochrome P450s in the cytotoxicity of dronedarone

Chen

Bryant

et al. 2018

Arch Toxicol

View full text Add to dashboard Cite

Dronedarone is used to treat patients with cardiac arrhythmias and has been reported to be associated with liver injury. Our previous mechanistic work demonstrated that DNA damage-induced apoptosis contributes to the cytotoxicity of dronedarone. In this study, we examined further the underlying mechanisms and found that after a 24-h treatment of HepG2 cells, dronedarone caused cytotoxicity, G1-phase cell cycle arrest, suppression of topoisomerase II, and DNA damage in a concentration-dependent manner. We also investigated the role of cytochrome P450s (CYPs)-mediated metabolism in the dronedarone-induced toxicity using our previously established HepG2 cell lines expressing individually 14 human CYPs (1A1, 1A2, 1B1, 2A6, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 3A4, 3A5, and 3A7). We demonstrated that CYP3A4, 3A5, and 2D6 were the major enzymes that metabolize dronedarone, and that CYP3A7, 2E1, 2C19, 2C18, 1A1, and 2B6 also metabolize dronedarone, but to a lesser extent. Our data showed that the cytotoxicity of dronedarone was decreased in CYP3A4-, 3A5-, or 2D6-overexpressing cells compared to the control HepG2 cells, indicating that the parent dronedarone has higher potency than the metabolites to induce cytotoxicity in these cells. In contrast, cytotoxicity was increased in CYP1A1-overexpressing cells, demonstrating that CYP1A1 exerts an opposite effect in dronedarone's toxicity, comparing to CYP3A4, 3A5, or 2D6. We also studied the involvement of topoisomerase II in dronedarone-induced toxicity, and demonstrated that the overexpression of topoisomerase II caused an increase in cell viability and a decrease in γ-H2A.X induction, suggesting that suppression of topoisomerase II may be one of the mechanisms involved in dronedarone-induced liver toxicity.

show abstract

“…The resource population that was utilized to estimate genetic parameters was developed to investigate the phenotypic and genetic variability related to drug metabolism in swine (Howard et al, 2014 , 2015 , 2017 ). The animals consisted of crossbred female and castrated male nursery pigs ( n = 198) housed in individual pens (0.9 × 1.8 m) at a room temperature of 17–24°C.…”

Section: Methodsmentioning

confidence: 99%

“…For both drugs, our recent work suggest that CYP1A1 and CYP2E1 are primarily involved in phase one metabolism and phase two often involves sulfate ( SULT1A1 ) and possibly glucuronide conjugation. (Howard et al, 2015 , 2017 ). The objective of the current study is to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics.…”

Section: Introductionmentioning

confidence: 99%

“…This was further verified at the genomic level based on gene expression differences for genes previously shown to play a role in drug metabolism, which include SULT1A1 and CYP2E1 for flunixin meglumine and SULT1A1 for fenbendazole (Howard et al, 2015 ). Furthermore, across the liver transcriptome, multiple cytochrome P450 (CYP1A1, CYP2A19, and CYP2C36) genes displayed different transcript levels across animals administered a drug vs. untreated animals (Howard et al, 2017 ). Gene expression differences highlighted that genetic variation exists in how pigs metabolize drugs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

et al. 2018

Self Cite

View full text Add to dashboard Cite

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study.

show abstract

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

Cited by 9 publications

References 47 publications

Muscle Transcriptome Analysis Reveals Potential Candidate Genes and Pathways Affecting Intramuscular Fat Content in Pigs

Muscle Transcriptome Analysis Reveals Potential Candidate Genes and Pathways Affecting Intramuscular Fat Content in Pigs

The role of hepatic cytochrome P450s in the cytotoxicity of dronedarone

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

Contact Info

Product

Resources

About