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Smutny T, Hyrsova L, Braeuning A, Ingelman-Sundberg M, Pavek P. Transcriptional and post-transcriptional regulation of the pregnane X receptor: a rationale for interindividual variability in drug metabolism. Arch Toxicol 2020; 95:11-25. [PMID: 33164107 DOI: 10.1007/s00204-020-02916-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 09/17/2020] [Indexed: 12/15/2022]
Abstract
The pregnane X receptor (PXR, encoded by the NR1I2 gene) is a ligand-regulated transcription factor originally described as a master regulator of xenobiotic detoxification. Later, however, PXR was also shown to interact with endogenous metabolism and to be further associated with various pathological states. This review focuses predominantly on such aspects, currently less covered in literature, as the control of PXR expression per se in the context of inter-individual differences in drug metabolism. There is growing evidence that non-coding RNAs post-transcriptionally regulate PXR. Effects on PXR have especially been reported for microRNAs (miRNAs), which include miR-148a, miR-18a-5p, miR-140-3p, miR-30c-1-3p and miR-877-5p. Likewise, miRNAs control the expression of both transcription factors involved in PXR expression and regulators of PXR function. The impact of NR1I2 genetic polymorphisms on miRNA-mediated PXR regulation is also discussed. As revealed recently, long non-coding RNAs (lncRNAs) appear to interfere with PXR expression. Reciprocally, PXR activation regulates non-coding RNA expression, thus comprising another level of PXR action in addition to the direct transactivation of protein-coding genes. PXR expression is further controlled by several transcription factors (cross-regulation) giving rise to different PXR transcript variants. Controversies remain regarding the suggested role of feedback regulation (auto-regulation) of PXR expression. In this review, we comprehensively summarize the miRNA-mediated, lncRNA-mediated and transcriptional regulation of PXR expression, and we propose that deciphering the precise mechanisms of PXR expression may bridge our knowledge gap in inter-individual differences in drug metabolism and toxicity.
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Affiliation(s)
- Tomas Smutny
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, 500 05, Hradec Kralove, Czech Republic.
| | - Lucie Hyrsova
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, 500 05, Hradec Kralove, Czech Republic
| | - Albert Braeuning
- Department Food Safety, German Federal Institute for Risk Assessment, Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, Solna vägen 9, 17165, Stockholm, Sweden
| | - Petr Pavek
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, 500 05, Hradec Kralove, Czech Republic
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Randhawa V, Pathania S. Advancing from protein interactomes and gene co-expression networks towards multi-omics-based composite networks: approaches for predicting and extracting biological knowledge. Brief Funct Genomics 2020; 19:364-376. [PMID: 32678894 DOI: 10.1093/bfgp/elaa015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/31/2020] [Accepted: 06/15/2020] [Indexed: 01/17/2023] Open
Abstract
Prediction of biological interaction networks from single-omics data has been extensively implemented to understand various aspects of biological systems. However, more recently, there is a growing interest in integrating multi-omics datasets for the prediction of interactomes that provide a global view of biological systems with higher descriptive capability, as compared to single omics. In this review, we have discussed various computational approaches implemented to infer and analyze two of the most important and well studied interactomes: protein-protein interaction networks and gene co-expression networks. We have explicitly focused on recent methods and pipelines implemented to infer and extract biologically important information from these interactomes, starting from utilizing single-omics data and then progressing towards multi-omics data. Accordingly, recent examples and case studies are also briefly discussed. Overall, this review will provide a proper understanding of the latest developments in protein and gene network modelling and will also help in extracting practical knowledge from them.
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Affiliation(s)
- Vinay Randhawa
- Department of Biochemistry, Panjab University, Chandigarh, 160014, India
| | - Shivalika Pathania
- Department of Biotechnology, Panjab University, Chandigarh, 160014, India
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Swart M, Dandara C. MicroRNA Mediated Changes in Drug Metabolism and Target Gene Expression by Efavirenz and Rifampicin In Vitro: Clinical Implications. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 23:496-507. [PMID: 31526233 PMCID: PMC6806364 DOI: 10.1089/omi.2019.0122] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Efavirenz (EFV) and rifampicin (RMP) are widely prescribed in Africa for treatment of HIV/AIDS and tuberculosis epidemics. Exposure to medicines can alter drug metabolism, for example, through changes in expression of microRNAs. We report, in this study, novel observations on the ways in which EFV and RMP change microRNA expression signatures in vitro in HepaRG cells. Additionally, we discuss the clinical implications of changes in expression of drug-metabolizing enzyme genes, such as CYP3A4, CYP3A5, UGT1A1, CYP2B6, and NR1I3. Differentiated HepaRG cells were treated with EFV (6.4 μM) or RMP (24.4 μM) for 24 h. Treatment of HepaRG cells with EFV resulted in a significant increase in messenger RNA (mRNA) expression for CYP3A4 (12.51-fold, p = 0.002), CYP3A5 (2.10-fold, p = 0.019), and UGT1A1 (2.52-fold, p = 0.005), whereas NR1I3 expression decreased (0.41-fold, p = 0.02). On the other hand, treatment of HepaRG cells with RMP resulted in a significant increase in mRNA expression for CYP2B6 (6.68-fold, p = 0.007) and CYP3A4 (111.96-fold, p = 0.001), whereas NR1I3 expression decreased (0.46-fold, p = 0.033). These data point to several important clinical implications through changes in drug/drug interaction risks and achieving optimal therapeutics. All in all, this study shows that differential expression of microRNAs after treatment with EFV and RMP adds another layer of complexity that should be incorporated in pharmacogenomic algorithms to render drug response more predictable.
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Affiliation(s)
- Marelize Swart
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa.,Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Collet Dandara
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa.,Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
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Ghanem CI, Manautou JE. Modulation of Hepatic MRP3/ABCC3 by Xenobiotics and Pathophysiological Conditions: Role in Drug Pharmacokinetics. Curr Med Chem 2019; 26:1185-1223. [PMID: 29473496 DOI: 10.2174/0929867325666180221142315] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Revised: 01/17/2018] [Accepted: 02/05/2018] [Indexed: 12/13/2022]
Abstract
Liver transporters play an important role in the pharmacokinetics and disposition of pharmaceuticals, environmental contaminants, and endogenous compounds. Among them, the family of ATP-Binding Cassette (ABC) transporters is the most important due to its role in the transport of endo- and xenobiotics. The ABCC sub-family is the largest one, consisting of 13 members that include the cystic fibrosis conductance regulator (CFTR/ABCC7); the sulfonylurea receptors (SUR1/ABCC8 and SUR2/ABCC9) and the multidrug resistanceassociated proteins (MRPs). The MRP-related proteins can collectively confer resistance to natural, synthetic drugs and their conjugated metabolites, including platinum-containing compounds, folate anti-metabolites, nucleoside and nucleotide analogs, among others. MRPs can be also catalogued into "long" (MRP1/ABCC1, -2/C2, -3/C3, -6/C6, and -7/C10) and "short" (MRP4/C4, -5/C5, -8/C11, -9/C12, and -10/C13) categories. While MRP2/ABCC2 is expressed in the canalicular pole of hepatocytes, all others are located in the basolateral membrane. In this review, we summarize information from studies examining the changes in expression and regulation of the basolateral hepatic transporter MPR3/ABCC3 by xenobiotics and during various pathophysiological conditions. We also focus, primarily, on the consequences of such changes in the pharmacokinetic, pharmacodynamic and/or toxicity of different drugs of clinical use transported by MRP3.
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Affiliation(s)
- Carolina I Ghanem
- Instituto de Investigaciones Farmacologicas (ININFA), Facultad de Farmacia y Bioquimica. CONICET. Universidad de Buenos Aires, Buenos Aires, Argentina.,Catedra de Fisiopatologia. Facultad de Farmacia y Bioquimica. Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Jose E Manautou
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT, United States
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Huang K, Liu Y, Huang Y, Li L, Cooper L, Ruan J, Zhao Z. Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science. BMC Genomics 2016; 17 Suppl 7:524. [PMID: 27556295 PMCID: PMC5001210 DOI: 10.1186/s12864-016-2893-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
We summarize the 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) and the editorial report of the supplement to BMC Genomics. The supplement includes 20 research articles selected from the manuscripts submitted to ICIBM 2015. The conference was held on November 13-15, 2015 at Indianapolis, Indiana, USA. It included eight scientific sessions, three tutorials, four keynote presentations, three highlight talks, and a poster session that covered current research in bioinformatics, systems biology, computational biology, biotechnologies, and computational medicine.
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Affiliation(s)
- Kun Huang
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210 USA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Yufei Huang
- Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78249 USA
| | - Lang Li
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Lee Cooper
- Department of Biomedical Informatics, Emory University, Atlanta, GA 30322 USA
- Department of Biomedical Engineering, Emory University / Georgia Institute of Technology, Atlanta, GA 30322 USA
| | - Jianhua Ruan
- Department of Computer Science, The University of Texas at San Antonio, San Antonio, TX 78249 USA
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA
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