Constitutive androstane receptor 1 is constitutively bound to chromatin and 'primed' for transactivation in hepatocytes

Liver matrin-3 protects mice against hepatic steatosis and stress response via constitutive androstane receptor

OBJECTIVE

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to rise with the increasing obesity epidemic. Rezdiffra as an activator of a thyroid hormone receptor-beta is the only Food and Drug Administration approved therapy. As such, there is a critical need to improve our understanding of gene expression regulation and signaling transduction in MASLD to develop new therapies. Matrin-3 is a DNA- and RNA-binding protein involved in the pathogenesis of human diseases. Here we examined its previously uncharacterized role in limiting hepatic steatosis and stress response via the constitutive androstane receptor (CAR).

METHODS

Matrin-3 floxed and liver-specific knockout mice were fed either a chow diet or 60 kcal% high-fat diet (HFD) for up to 16 weeks. The mice were euthanized for different analysis including liver histology, lipid levels, and gene expression. Bulk RNA-seq, bulk ATAC-seq, and single-nucleus Multiome were used to examine changes of transcriptome and chromatin accessibility in the liver. Integrative bioinformatics analysis of our data and publicly available datasets and different biochemical assays were performed to identify underlying the molecular mechanisms mediating matrin-3's effects. Liver-tropic adeno-associated virus was used to restore the expression of CAR for lipid, acute phase genes, and histological analysis.

RESULTS

Matrin-3 expression is induced in the steatotic livers of mice. Liver-specific matrin-3 deletion exacerbated HFD-induced steatosis, acute phase response, and inflammation in the liver of female mice. The transcriptome and chromatin accessibility were re-programmed in the liver of these mice with signatures indicating that CAR signaling is dysregulated. Mechanistically, matrin-3 interacts with CAR mRNA, and matrin-3 deficiency promotes CAR mRNA degradation. Consequently, matrin-3 deletion impaired CAR signaling by reducing CAR expression. Matrin-3 levels positively correlate with CAR expression in human livers. Ces2a and Il1r1 were identified as new target genes of CAR. Interestingly, we found that CAR discords with the expression of its target genes including Cyp2b10 and Ces2a in response to HFD, indicating CAR signaling is dysregulated by HFD despite increased CAR expression. Dysregulated CAR signaling upon matrin-3 deficiency reduced Ces2a and de-repressed Il1r1 expression. CAR restoration partially abrogated the dysregulated gene expression, exacerbated hepatic steatosis, acute phase response, and inflammation in liver-specific matrin-3 knockout mice fed a HFD.

CONCLUSIONS

Our findings demonstrate that matrin-3 is a key upstream regulator maintaining CAR signaling upon metabolic stress, and the matrin-3-CAR axis limits hepatic steatosis and stress response signaling that may give insights for therapeutic intervention.

Potential of in vivo stress reporter models to reduce animal use and provide mechanistic insights in toxicity studies

Chemical risk assessment ensures protection from the toxic effects of drugs and manmade chemicals. To comply with regulatory guidance, studies in complex organisms are required, as well as mechanistic studies to establish the relevance of any toxicities observed to man. Although in vitro toxicity models are improving, in vivo studies remain central to this process. Such studies are invariably time-consuming and often involve large numbers of animals. New regulatory frameworks recommend the implementation of "smart" in vivo approaches to toxicity testing that can effectively assess safety for humans and comply with societal expectations for reduction in animal use. A major obstacle in reducing the animals required is the time-consuming and complexity of the pathological endpoints used as markers of toxicity. Such endpoints are prone to inter-animal variability, subjectivity and require harmonisation between testing sites. As a consequence, large numbers of animals per experimental group are required. To address this issue, we propose the implementation of sophisticated stress response reporter mice that we have developed. These reporter models provide early biomarkers of toxic potential in a highly reproducible manner at single-cell resolution, which can also be measured non-invasively and have been extensively validated in academic research as early biomarkers of stress responses for a wide range of chemicals at human-relevant exposures. In this report, we describe a new and previously generated models in our lab, provide the methodology required for their use and discuss how they have been used to inform on toxic risk (likelihood of chemical causing an adverse health effect). We propose our in vivo approach is more informative (refinement) and reduces the animal use (reduction) compared to traditional toxicity testing. These models could be incorporated into tiered toxicity testing and used in combination with in vitro assays to generate quantitative adverse outcome pathways and inform on toxic potential.

Potential of in vivo stress reporter models to reduce animal use and provide mechanistic insights in toxicity studies

Chemical risk assessment ensures protection from the toxic effects of drugs and manmade chemicals. To comply with regulatory guidance, studies in complex organisms are required, as well as mechanistic studies to establish the relevance of any toxicities observed to man. Although in vitro toxicity models are improving, in vivo studies remain central to this process. Such studies are invariably time-consuming and often involve large numbers of animals. New regulatory frameworks recommend the implementation of "smart" in vivo approaches to toxicity testing that can effectively assess safety for humans and comply with societal expectations for reduction in animal use. A major obstacle in reducing the animals required is the time-consuming and complexity of the pathological endpoints used as markers of toxicity. Such endpoints are prone to inter-animal variability, subjectivity and require harmonisation between testing sites. As a consequence, large numbers of animals per experimental group are required. To address this issue, we propose the implementation of sophisticated stress response reporter mice that we have developed. These reporter models provide early biomarkers of toxic potential in a highly reproducible manner at single-cell resolution, which can also be measured non-invasively and have been extensively validated in academic research as early biomarkers of stress responses for a wide range of chemicals at human-relevant exposures. In this report, we describe a new and previously generated models in our lab, provide the methodology required for their use and discuss how they have been used to inform on toxic risk (likelihood of chemical causing an adverse health effect). We propose our in vivo approach is more informative (refinement) and reduces the animal use (reduction) compared to traditional toxicity testing. These models could be incorporated into tiered toxicity testing and used in combination with in vitro assays to generate quantitative adverse outcome pathways and inform on toxic potential.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

Through a glass, darkly? HepaRG and HepG2 cells as models of human phase I drug metabolism

The pharmacokinetic and safety assessment of drug candidates is becoming increasingly dependent upon in vitro models of hepatic metabolism and toxicity. Predominant among these is the HepG2 cell line, although HepaRG is becoming increasingly popular because of its perceived closer resemblance to human hepatocytes. We review the functionality of these cell lines in terms of Phase I protein expression, basal cytochrome P450-dependent activity, and utility in P450 induction studies. Our analysis indicates that HepG2 cells are severely compromised: proteomic studies show that they express few key proteins in common with hepatocytes and they lack drug-metabolizing capacity. Differentiated HepaRGs are more hepatocyte-like than HepG2s, but they also have limitations, and it is difficult to assess their utility because of the enormous variability in data reported, possibly arising from the complex differentiation protocols required to obtain hepatocyte-like cells. This is exacerbated by the use of DMSO in the induction protocol, together with proprietary supplements whose composition is a commercial secret. We conclude that, while currently available data on the utility of HepaRG generates a confusing picture, this line does have potential utility in drug metabolism studies. However, to allow studies to be compared directly a standardized, reproducible differentiation protocol is essential and the cell line's functionality in terms of known mechanisms of P450 regulation must be demonstrated. We, therefore, support the development of regulatory guidelines for the use of HepaRGs in induction studies as a first step in generating a database of consistent, reliable data.

Protein conformational switch discerned via network centrality properties

Network analysis has emerged as a powerful tool for examining structural biology systems. The spatial organization of the components of a biomolecular structure has been rendered as a graph representation and analyses have been performed to deduce the biophysical and mechanistic properties of these components. For proteins, the analysis of protein structure networks (PSNs), especially via network centrality measurements and cluster coefficients, has led to identifying amino acid residues that play key functional roles and classifying amino acid residues in general. Whether these network properties examined in various studies are sensitive to subtle (yet biologically significant) conformational changes remained to be addressed. Here, we focused on four types of network centrality properties (betweenness, closeness, degree, and eigenvector centralities) for conformational changes upon ligand binding of a sensor protein (constitutive androstane receptor) and an allosteric enzyme (ribonucleotide reductase). We found that eigenvector centrality is sensitive and can distinguish salient structural features between protein conformational states while other centrality measures, especially closeness centrality, are less sensitive and rather generic with respect to the structural specificity. We also demonstrated that an ensemble-informed, modified PSN with static edges removed (which we term PSN*) has enhanced sensitivity at discerning structural changes.

Splice variants of metabolic nuclear receptors: Relevance for metabolic disease and therapeutic targeting

Metabolic nuclear receptors are ligand-activated transcription factors which control a wide range of metabolic processes and signaling pathways in response to nutrients and xenobiotics. Targeting these NRs is at the forefront of our endeavours to generate novel treatment options for diabetes, metabolic syndrome and fatty liver disease. Numerous splice variants have been described for these metabolic receptors. Structural changes, as a result of alternative splicing, lead to functional differences among NR isoforms, resulting in the regulation of different metabolic pathways by these NR splice variants. In this review, we describe known splice variants of FXR, LXRs, PXR, RXR, LRH-1, CAR and PPARs. We discuss their structure and functions, and elaborate on the regulation of splice variant abundance by nutritional signals. We conclude that NR splice variants pose an intriguing new layer of complexity in metabolic signaling, which needs to be taken into account in the development of treatment strategies for metabolic diseases.

Bile Acids as a New Type of Steroid Hormones Regulating Nonspecific Energy Expenditure of the Body (Review)

The review is devoted to the systematization, classification, and generalization of the results of modern scientific research on the role of bile acids as a new class of steroid hormones. The paper presents the evidence for bile acid participation in the regulation of the body energy metabolism, body weight control, as well as the pathogenesis of obesity, diabetes mellitus, insulin resistance, and cardiovascular diseases. Particular attention is paid to the role of bile acids in the control of nonspecific energy expenditure of the body. The applied aspects of using the novel data about the membrane and intracellular receptors responsible for the development of hormonal regulatory effects of bile acids are analyzed. According to the authors, the modern data on the role of bile acids in the regulation of body functions allow a deeper understanding of the pathogenesis of body weight disorders and associated cardiovascular diseases. The review demonstrates promising directions in the search for specific methods of prevention and correction of these pathological conditions.

Overexpression of the constitutive androstane receptor and shaken 3D-culturing increase biotransformation and oxidative phosphorylation and sensitivity to mitochondrial amiodarone toxicity of HepaRG cells

The liver cell line HepaRG is one of the preferred sources of human hepatocytes for in vitro applications. However, mitochondrial energy metabolism is relatively low, which affects hepatic functionality and sensitivity to hepatotoxins. Culturing in a bioartificial liver (BAL) system with high oxygen, medium perfusion, low substrate stiffness, and 3D conformation increases HepaRG functionality and mitochondrial activity compared to conventional monolayer culturing. In addition, drug metabolism has been improved by overexpression of the constitutive androstane receptor (CAR), a regulator of drug and energy metabolism in the new HepaRG-CAR line. Here, we investigated the effect of BAL culturing on the HepaRG-CAR line by applying a simple and downscaled BAL culture procedure based on shaking 3D cultures, named Bal-in-a-dish (BALIAD). We compared monolayer and BALIAD cultures of HepaRG and HepaRG-CAR cells. CAR overexpression and BALIAD culturing synergistically or additively increased transcript levels of CAR and three of the seven tested CAR target genes in biotransformation. Additionally, Cytochrome P450 3A4 activity was 35-fold increased. The mitochondrial energy metabolism was enhanced; lactate production and glucose consumption switched into lactate elimination and glucose production. BALIAD culturing alone reduced glycogen content and increased oxygen consumption and mitochondrial content. Both CAR overexpression and BALIAD culturing decreased mitochondrial superoxide levels. HepaRG-CAR BALIADs were most sensitive to mitochondrial toxicity induced by the hepatotoxin amiodarone, as indicated by oxygen consumption and mitochondrial superoxide accumulation. These data show that BALIAD culturing of HepaRG-CAR cells induces high mitochondrial energy metabolism and xenobiotic metabolism, increasing its potential for drug toxicity studies.

Optimization of a Deep-Learning Method Based on the Classification of Images Generated by Parameterized Deep Snap a Novel Molecular-Image-Input Technique for Quantitative Structure-Activity Relationship (QSAR) Analysis

Numerous chemical compounds are distributed around the world and may affect the homeostasis of the endocrine system by disrupting the normal functions of hormone receptors. Although the risks associated with these compounds have been evaluated by acute toxicity testing in mammalian models, the chronic toxicity of many chemicals remains due to high cost of the compounds and the testing, etc. However, computational approaches may be promising alternatives and reduce these evaluations. Recently, deep learning (DL) has been shown to be promising prediction models with high accuracy for recognition of images, speech, signals, and videos since it greatly benefits from large datasets. Recently, a novel DL-based technique called DeepSnap was developed to conduct QSAR analysis using three-dimensional images of chemical structures. It can be used to predict the potential toxicity of many different chemicals to various receptors without extraction of descriptors. DeepSnap has been shown to have a very high capacity in tests using Tox21 quantitative qHTP datasets. Numerous parameters must be adjusted to use the DeepSnap method but they have not been optimized. In this study, the effects of these parameters on the performance of the DL prediction model were evaluated in terms of the loss in validation as an indicator for evaluating the performance of the DL using the toxicity information in the Tox21 qHTP database. The relations of the parameters of DeepSnap such as (1) number of molecules per SDF split into (2) zoom factor percentage, (3) atom size for van der waals percentage, (4) bond radius, (5) minimum bond distance, and (6) bond tolerance, with the validation loss following quadratic function curves, which suggests that optimal thresholds exist to attain the best performance with these prediction models. Using the parameter values set with the best performance, the prediction model of chemical compounds for CAR agonist was built using 64 images, at 105° angle, with AUC of 0.791. Thus, based on these parameters, the proposed DeepSnap-DL approach will be highly reliable and beneficial to establish models to assess the risk associated with various chemicals.