Comparative analysis of small molecule and growth factor-derived human induced pluripotent stem cell-derived hepatocyte-like cells

Abstract

The growth factor and small molecule protocol are the two primary approaches for generating human induced pluripotent stem cell-derived hepatocyte-like cells (iPSC-HLCs). We compared the efficacy of the growth factor and small molecule protocols across fifteen different human iPSC lines. Morphological assessment, relative quantification of gene expression, protein expression and proteomic studies were carried out. HLCs derived from the growth factor protocol displayed mature hepatocyte morphological features including a raised, polygonal shape with well-defined refractile borders, granular cytoplasm with lipid droplets and/or vacuoles with multiple spherical nuclei or a large centrally located nucleus; significantly elevated hepatocyte gene and protein expression including AFP, HNF4A, ALBUMIN, and proteomic and metabolic features that are more aligned with a mature phenotype. HLCs derived from the small molecule protocol showed a dedifferentiated, proliferative phenotype that is more akin to liver tumor-derived cell lines. These experimental results suggest that HLCs derived from growth factors are better suited for studies of metabolism, biotransformation, and viral infection.

Keywords: growth factors; hepatocyte-like cells; hepatocytes; induced pluripotent stem cells; small molecules.

FIGURE 1

Characterization of human iPSCs. Phase Contrast Micrograph of one representative human iPSC line (20 ×). Images shown are for iPSC1 (A). qRT-PCR analysis for relative expression of OCT-4, SOX-2, NANOG, cMYC, KLF4, and REX-4 (B). Columns show the combined mean ΔΔC_t values for each marker. Data represent relative expression of transcripts normalized relative to GAPDH and expressed at the Mean ± SEM. Representative data from three independent experiments are shown. Immunostaining of human iPSC clones for pluripotency markers SOX2, OCT4, NANOG, SSEA-4, Tra-1–80 and Tra-1–60. Nuclei were stained with DAPI (C). All 15 iPSC lines were stained and imaged.

FIGURE 2

Characterization of Hepatocyte-like cell differentiation. Phase Contrast Micrographs of one representative differentiated iPSC cell line (iPSC1) (20 ×). Images shown are for GFHLC1 (A), SMHLC1 (B) and PHH for comparison (C) (20 ×). qRT-PCR analysis for relative expression of hepatic genes in GFHLCs and SMHLCs (D–G). Columns show the combined mean ΔΔC_t values for each marker. Data represents relative expression of transcripts normalized relative to GAPDH and undifferentiated controls. Data are represented as Mean ± SEM for three biologically independent experiments (n = 3). Immunostaining of hepatic protein expression in GFHLC1 (H) and SMHLC1 (I). Representative data from three independent experiments are shown.

FIGURE 3

Proteomic analysis of iPSCs, GF HLCs, and SM HLCs compared to Controls (CTR). Diagrammatic presentation of the mass spectrometry workflow used in this study (A). Principal component analysis (PCA) showing the various cell types: CTR, iPSc, GFHLCs, SMHLCs as different shapes. The CTR is represented in red, iPSC in green, GFHLCs in light blue, and SMHLCs in dark blue (B). The PCA plot was generated using peptide abundance data of all peptides analysed per cell type with 10 replicates. A bar graph showing the number of significantly upregulated (red) and downregulated (blue) proteins in each cell type compared to the CTR (C). A Venn diagram illustrating the unique differently expressed proteins in each condition was generated (D). Comparative heatmap of all the replicates per cell type (iPSC, CTR, GFHLC and SMHLC) and the identified protein groups (E). Proteomic pathways analysis of significantly differentially expressed proteins. Volcano plots of the differentially expressed proteins from the different cell types: iPSC, GFHLCs, SMHLCs (F–H). The negative x-axis represents downregulation (blue) in cell type and the positive axis represents upregulated (red) proteins in the different cell types (F–H). Dot plots were generated using the uniquely differentially expressed proteins in ShinyGO analysis, with KEGG pathway enrichment and fold enrichment based on the number of genes present in each pathway (I–K). The FDR cut-off was set at 0.05, and the number of pathways was set to 20.

FIGURE 4

Proteomic analysis of GF hepatocytes compared to SM hepatocytes. A Venn diagram illustrating the total number of proteins in GFHLCs versus SMHLCs (A). Volcano plots of the differentially expressed proteins in GFHLCs and SMHLCs (B). The negative x-axis represents downregulation (blue) in GFHLCs compared to SMHLCs, and the positive axis represents upregulated (red) proteins in the different GFHLCs compared to SMHLCs. Dot plot generated using the differentially expressed proteins in ShinyGO analysis, with KEGG pathway enrichment and fold enrichment based on the number of genes present in each pathway (C). The FDR cut-off was set at 0.05, and the number of pathways was set to 20. String analysis Network analysis of the differentially expressed proteins corresponding to the different pathways using STRING network (Fold cut-off set to 0.7) (D).

FIGURE 5

Affected TCA cycle proteins in GF HLCs compared to SM HLCs. Graphical representation of the differentially expressed proteins in the central carbon metabolism pathway. Upregulated proteins are represented in red and downregulated proteins are represented in blue.