Disrupting Hepatocyte Cyp51 from Cholesterol Synthesis Leads to Progressive Liver Injury in the Developing Mouse and Decreases RORC Signalling

Development of mice with hepatocyte knockout of lanosterol 14α-demethylase (HCyp51−/−) from cholesterol synthesis is characterized by the progressive onset of liver injury with ductular reaction and fibrosis. These changes begin during puberty and are generally more aggravated in the knockout females. However, a subgroup of (pre)pubertal knockout mice (runts) exhibits a pronounced male prevalent liver dysfunction characterized by downregulated amino acid metabolism and elevated Casp12. RORC transcriptional activity is diminished in livers of all runt mice, in correlation with the depletion of potential RORC ligands subsequent to CYP51 disruption. Further evidence for this comes from the global analysis that identified a crucial overlap between hepatic Cyp51−/− and Rorc−/− expression profiles. Additionally, the reduction in RORA and RORC transcriptional activity was greater in adult HCyp51−/− females than males, which correlates well with their downregulated amino and fatty acid metabolism. Overall, we identify a global and sex-dependent transcriptional de-regulation due to the block in cholesterol synthesis during development of the Cyp51 knockout mice and provide in vivo evidence that sterol intermediates downstream of lanosterol may regulate the hepatic RORC activity.


Sample collection
To evaluate the phenotype of the H Cyp51-/-mice, clinical picture was monitored and recorded on a daily basis. Mice were euthanized by cervical dislocation between 7:30 and 13:30 at the specified ages -at birth (day 0), weaning (3 weeks), puberty (6 weeks) and following sexual maturity (9 and 19 weeks), as recommended by the Working document on genetically altered animals. At autopsy blood was taken by a heart puncture and internal organs (liver, kidney, spleen, heart, gonads) were weighed and macroscopically examined. Plasma was collected into heparin coated Vacuette MiniCollect® 1 ml Plasma Tubes (Greiner Bio-one, Frickenhausen, Germany) and organs were snap-frozen in liquid nitrogen. Left lateral liver lobes were fixed in formalin and embedded in paraffin for further histological analyses.
In case of runt-H Cyp51-/-mice, humane end points were set at which they were euthanized and their organs were taken for further analyses, as described above.

Collagenase perfusion
Following anesthetization of mice with isoflurane, an intraperitoneal incision was made to expose the portal vein and vena cava.

Histological analysis
Paraffin embedded liver was sectioned to 5 μm on glass slides and stained with haematoxylin and eosin (HE) for general histological assessment or with Sirius red (SR; 0,1 % direct red 80, 1,2 % picric acid in water) to evaluate the degree of fibrosis.   (Supplementary Table 8). One-way ANOVA was used for analysing data with only one relevant factor. Two-way ANOVA was used to evaluate the effects of multiple factors. Holm-Sidak correction for multiple comparisons was used and a p value threshold of 0.05 was used as a measurement of significance.

Total sterol extraction and GC/MS analysis
Sterols extraction from frozen liver and coupled gas chromatography/mass spectrometry (GC/MS) analysis were conducted as previously described 7,8 . A minimum of 3 samples per group were analysed. Sterol amounts are expressed as ng of compound per mg of wet liver tissue. One-way ANOVA was used to analysing the impact of one factor (e.g. genotype) and two-way ANOVA for multiple factors (e.g. age and genotype). Holm-Sidak correction for multiple comparisons was used and a p-value threshold of 0.05 was used as a measurement of significance. Quality check and gene expression analysis were done using R and Bioconductor packages. Quality control and RMA-based normalization of gene expression data were performed using xps package 9 . Raw (CEL) as well as normalized data were deposited to GEO under accession number GSE78892. Package limma 10 was used to infer differential expression of genes and enrichment of gene sets using three predictor variables (age, sex and genotype) and their interactions (age x genotype, age x sex, sex x genotype). Gene sets were constructed using KEGG pathways 11 and TRANSFAC database 12 . Sets containing over 5 elements were tested for enrichment using the PGSEA package 13 . In the case of transcription factor enrichment, factors were merged based on their ID irrespective of their binding sites.

Microarray-based gene expression profiling
For RORC and RORA, target genes were updated based on the literature 14-16 (RORalpha -original gene set based on TRANSFAC; Rora -updated gene set).
False discovery rate (FDR) was used to account for multiple hypothesis testing.
Significance level α = 0.05 was used to control the rate of Type I error for the differential gene expression as well as for the pathway enrichment. The network diagram ( Supplementary Fig. 3) was created using Cytoscape program 17 and ClueGo plugin 18 . Analysis of KEGG pathways with kappa score set to 0.2. Gene set enrichment on the proposed RORC target genes was conducted using the FIDEA tool 19 . The Interactome tool 20,21 was used on selected up-or downregulated enriched transcription factors to evaluate their interaction and identify central nodes of regulation.

Library construction and sequencing
RNASeq libraries were prepared using the Illumina TruSeq Stranded Total RNA library prep, with Ribozero Gold, starting from 500 ng of total RNA, following the manufacturer's protocol, with the exception that 13 cycles of PCR were performed to amplify the libraries, to keep the duplication rate lower than with the recommended 15 cycles. The amplified libraries were purified using AMPure beads, quantified by Qubit and QPCR, and visualized in an Agilent Bioanalyzer. The libraries were pooled equimolarly, and loaded at 8 pM, on high output HiSeq 2500 flow cells, using v4 reagents, as paired 50 nucleotide reads. Libraries were pooled and distributed uniformly across 3 lanes in order to generate 60-80 million reads per sample.

RNA-Seq Analysis
RNA-seq alignments were performed using STAR (v2.4.2a modified) 22 . Alignments were filtered to remove those having a quality score less than 30; subsequently reads mapping to exons were counted using featureCounts (v1.4.6) 23 and summarized by gene. TDF views (IGV v2.3.32) 24 were generated from the quality filtered alignments. The UCSC genes annotation (May 23, 2014) 25 , and primary assembly (Dec. 2011 GRCm38/mm10) 26 , for mm10 were obtained from iGenomes (https://support.illumina.com/sequencing/sequencing_software/igenome.html), and were used respectively as annotation and reference genome. Where parameters are not explicitly stated below, defaults of the specified software versions were applied. DESeq2 27 for R was used to normalize the counts and infer gene differential expression.   ZT19=night). An empty list signifies that no differentially expressed genes were found for the selected comparison. Table 3 An empty list signifies that no enriched transcription factors were found for the selected comparison.