Dataset Information

Age-Specific Regulation of Drug-Processing Genes in Mouse Liver by Ligands of Xenobiotic-Sensing Transcription Factors.

ABSTRACT: The xenobiotic-sensing transcription factors (xeno-sensors) AhR, CAR, and PXR upregulate the expression of many drug-processing genes (DPGs) in liver. Previous studies have unveiled profound changes in the basal expression of DPGs during development; however, knowledge on the ontogeny of the inducibility of DPGs in response to pharmacological activation of xeno-sensors is still limited. The goal of this study was to investigate the age-specific regulation of DPGs by prototypical xeno-sensor ligands: 2,3,7,8-tetrachlorodibenzodioxin (TCDD) for AhR; 1,4-bis [2-(3,5-dichloropyridyloxy)] benzene (TCPOBOP) for CAR; and pregnane-16?-carbonitrile (PCN) for PXR during mouse liver development. The basal mRNAs of most DPGs were low during neonatal age, but gradually increased to adult levels, whereas some DPGs (Cyp1a2, Cyp2b10, Cyp3a11, Gstm2, Gstm3, Papss2, and Oatp1a4) exhibited an adolescent-predominant expression pattern. The inducibility of DPGs was age-specific: 1) during neonatal age, the highest fold increase in the mRNA expression was observed for Cyp1a2, Sult5a1, and Ugt1a9 by TCDD; Cyp3a11 and Mrp2 by TCPOBOP; as well as Gstm2 and Gstm3 by PCN; 2) during adolescent age, the highest fold increase in the mRNA expression was observed for Ugt1a6 and Mrp4 by TCDD, Cyp2b10, Ugt2b34, and Ugt2b35 by TCPOBOP, as well as Gsta1, Gsta4, Sult1e1, Ugt1a1, Mrp3, and Mrp4 by PCN; 3) in adults, the highest fold increase in the mRNA expression was observed for Aldh1a1, Aldh1a7, and Ugt2b36 by TCPOBOP, as well as Papss2 and Oatp1a4 by PCN. In conclusion, the inducibility of hepatic DPGs following the pharmacological activation of xeno-sensors is age specific.

SUBMITTER: Li CY

PROVIDER: S-EPMC4931882 | biostudies-other | 2016 Jul

REPOSITORIES: biostudies-other

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Age-Specific Regulation of Drug-Processing Genes in Mouse Liver by Ligands of Xenobiotic-Sensing Transcription Factors.

Li Cindy Yanfei CY Renaud Helen J HJ Klaassen Curtis D CD Cui Julia Yue JY

Drug metabolism and disposition: the biological fate of chemicals 20151117 7

The xenobiotic-sensing transcription factors (xeno-sensors) AhR, CAR, and PXR upregulate the expression of many drug-processing genes (DPGs) in liver. Previous studies have unveiled profound changes in the basal expression of DPGs during development; however, knowledge on the ontogeny of the inducibility of DPGs in response to pharmacological activation of xeno-sensors is still limited. The goal of this study was to investigate the age-specific regulation of DPGs by prototypical xeno-sensor liga ...[more]

PMID: 26577535

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Project description:Purpose: Next-generation sequencing (NGS) has been utilized for systems-based analysis of all liver samples. The goals of this study are to use NGS-derived mouse CAR and human CAR initiated transcriptome profiling (RNA-seq) and find out similarity and difference drug processing gene (DPG) pattern after CAR activation in different genotype include WT (C57BL/6 and human CAR transgenic mice with C57BL/6 background) Methods: Liver mRNA profiles of wild-type (WT) and human CAR knockin (hCAR-TG) mice at the age of day 5 and day 60 treated with mouse CAR activator (TCPOBOP) and human CAR activator (CITCO) respectively were generated by deep sequencing, in triplicate, using HiSeq 2000 sequencer. The sequence reads that passed quality filters were analyzed at the transcript level with followed method: HISAT followed by Cufflinks. Results: Using an optimized data analysis workflow,RNA-Seq generated approximately 47 to 68 million reads per sample, among which approximately 40 to 60 million reads were uniquely mapped to the mouse reference genome (NCBI GRCm/38/mm10). And we identified 393 drug processing genes in the livers of WT and hCAR-TG with with HISAT workflow. RNA-seq data confirmed that among all the 393 DPGs with known important functions in xenobiotic biotransformation, 90 DPGs were not expressed in livers of any groups (threshold: average FPKM < 1 in all treatment groups); whereas a total of 303 genes were expressed in livers of at least one groups, among which 258 DPGs were differentially regulated by mCAR or hCAR activation in either Day 5 or Day 60 (FDR-BH<0.05), and 45 genes were stably expressed among all treatment groups. Conclusions: Our study represents the first detailed analysis of drug processing genes, with 3 biologic replicates, generated by RNA-seq technology. The optimized data analysis reported here should provide a framework for comparative investigations of expression profiles by mouse CAR activation and human CAR activation. Our results show that NGS offers a comprehensive and accurate quantitative and qualitative evaluation of mRNA content within tissues.

Project description:The regulatory mechanisms by which hydrogen peroxide (H2O2) modulates the activity of transcription factors in bacteria (OxyR and PerR), lower eukaryotes (Yap1, Maf1, Hsf1 and Msn2/4) and mammalian cells (AP-1, NRF2, CREB, HSF1, HIF-1, TP53, NF-κB, NOTCH, SP1 and SCREB-1) are reviewed. The complexity of regulatory networks increases throughout the phylogenetic tree, reaching a high level of complexity in mammalians. Multiple H2O2 sensors and pathways are triggered converging in the regulation of transcription factors at several levels: (1) synthesis of the transcription factor by upregulating transcription or increasing both mRNA stability and translation; (ii) stability of the transcription factor by decreasing its association with the ubiquitin E3 ligase complex or by inhibiting this complex; (iii) cytoplasm-nuclear traffic by exposing/masking nuclear localization signals, or by releasing the transcription factor from partners or from membrane anchors; and (iv) DNA binding and nuclear transactivation by modulating transcription factor affinity towards DNA, co-activators or repressors, and by targeting specific regions of chromatin to activate individual genes. We also discuss how H2O2 biological specificity results from diverse thiol protein sensors, with different reactivity of their sulfhydryl groups towards H2O2, being activated by different concentrations and times of exposure to H2O2. The specific regulation of local H2O2 concentrations is also crucial and results from H2O2 localized production and removal controlled by signals. Finally, we formulate equations to extract from typical experiments quantitative data concerning H2O2 reactivity with sensor molecules. Rate constants of 140 M(-1) s(-1) and ≥1.3 × 10(3) M(-1) s(-1) were estimated, respectively, for the reaction of H2O2 with KEAP1 and with an unknown target that mediates NRF2 protein synthesis. In conclusion, the multitude of H2O2 targets and mechanisms provides an opportunity for highly specific effects on gene regulation that depend on the cell type and on signals received from the cellular microenvironment.

Dataset Information

Age-Specific Regulation of Drug-Processing Genes in Mouse Liver by Ligands of Xenobiotic-Sensing Transcription Factors.

Publications

Age-Specific Regulation of Drug-Processing Genes in Mouse Liver by Ligands of Xenobiotic-Sensing Transcription Factors.

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