Lipoprotein profile and lipid metabolism of PXB-cells®, human primary hepatocytes from liver-humanized mice: proposal of novel in vitro system for screening anti-lipidemic drugs

The hypolipidemic effect of MI-883, the combined CAR agonist/ PXR antagonist, in diet-induced hypercholesterolemia model

Constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are closely related nuclear receptors with overlapping regulatory functions in xenobiotic clearance but distinct roles in endobiotic metabolism. Car activation has been demonstrated to ameliorate hypercholesterolemia by regulating cholesterol metabolism and bile acid elimination, whereas PXR activation is associated with hypercholesterolemia and liver steatosis. Here we show a human CAR agonist/PXR antagonist, MI-883, which effectively regulates genes related to xenobiotic metabolism and cholesterol/bile acid homeostasis by leveraging CAR and PXR interactions in gene regulation. Through comprehensive analyses utilizing lipidomics, bile acid metabolomics, and transcriptomics in humanized PXR-CAR-CYP3A4/3A7 mice fed high-fat and high-cholesterol diets, we demonstrate that MI-883 significantly reduces plasma cholesterol levels and enhances fecal bile acid excretion. This work paves the way for the development of ligands targeting multiple xenobiotic nuclear receptors. Such ligands hold the potential for precise modulation of liver metabolism, offering new therapeutic strategies for metabolic disorders.

Liver-humanized mice: A translational strategy to study metabolic disorders

The liver is the metabolic core of the whole body. Tools commonly used to study the human liver metabolism include hepatocyte cell lines, primary human hepatocytes, and pluripotent stem cells-derived hepatocytes in vitro, and liver genetically humanized mouse model in vivo. However, none of these systems can mimic the human liver in physiological and pathological states satisfactorily. Liver-humanized mice, which are established by reconstituting mouse liver with human hepatocytes, have emerged as an attractive animal model to study drug metabolism and evaluate the therapeutic effect in "human liver" in vivo because the humanized livers greatly replicate enzymatic features of human hepatocytes. The application of liver-humanized mice in studying metabolic disorders is relatively less common due to the largely uncertain replication of metabolic profiles compared to humans. Here, we summarize the metabolic characteristics and current application of liver-humanized mouse models in metabolic disorders that have been reported in the literature, trying to evaluate the pros and cons of using liver-humanized mice as novel mouse models to study metabolic disorders.

Transcriptome-Wide Off-Target Effects of Steric-Blocking Oligonucleotides

Steric-blocking oligonucleotides (SBOs) are short, single-stranded nucleic acids designed to modulate gene expression by binding to RNA transcripts and blocking access from cellular machinery such as splicing factors. SBOs have the potential to bind to near-complementary sites in the transcriptome, causing off-target effects. In this study, we used RNA-seq to evaluate the off-target differential splicing events of 81 SBOs and differential expression events of 46 SBOs. Our results suggest that differential splicing events are predominantly hybridization driven, whereas differential expression events are more common and driven by other mechanisms (including spurious experimental variation). We further evaluated the performance of in silico screens for off-target splicing events, and found an edit distance cutoff of three to result in a sensitivity of 14% and false discovery rate (FDR) of 99%. A machine learning model incorporating splicing predictions substantially improved the ability to prioritize low edit distance hits, increasing sensitivity from 4% to 26% at a fixed FDR of 90%. Despite these large improvements in performance, this approach does not detect the majority of events at an FDR <99%. Our results suggest that in silico methods are currently of limited use for predicting the off-target effects of SBOs, and experimental screening by RNA-seq should be the preferred approach.