Transcriptomic profiling of induced steatosis in human and mouse precision-cut liver slices.
Eric SimonMaciej MotykaGrietje H PrinsMei LiWerner RustStefan KauschkeCoralie ViolletPeter OlingaAnouk OldenburgerPublished in: Scientific data (2023)
There is a high need for predictive human ex vivo models for non-alcoholic fatty liver disease (NAFLD). About a decade ago, precision-cut liver slices (PCLSs) have been established as an ex vivo assay for humans and other organisms. In the present study, we use transcriptomics by RNASeq to profile a new human and mouse PCLSs based assay for steatosis in NAFLD. Steatosis as quantified by an increase of triglycerides after 48 h in culture, is induced by incremental supplementation of sugars (glucose and fructose), insulin, and fatty acids (palmitate, oleate). We mirrored the experimental design for human vs. mouse liver organ derived PCLSs and profiled each organ at eight different nutrient conditions after 24 h and 48 h time in culture. Thus, the provided data allows a comprehensive analysis of the donor, species, time, and nutrient factor specific regulation of gene expression in steatosis, despite the heterogeneity of the human tissue samples. Exemplified this is demonstrated by ranking homologous gene pairs by convergent or divergent expression pattern across nutrient conditions.
Keyphrases
- endothelial cells
- gene expression
- induced pluripotent stem cells
- insulin resistance
- single cell
- high fat diet
- dna methylation
- high glucose
- type diabetes
- adipose tissue
- blood pressure
- dna damage
- machine learning
- poor prognosis
- transcription factor
- genome wide
- metabolic syndrome
- oxidative stress
- high fat diet induced
- big data
- deep learning
- rna seq
- multidrug resistant
- liver fibrosis