Analysis of differentially expressed genes among human hair follicle–derived iPSCs, induced hepatocyte-like cells, and primary hepatocytes

Abstract

BackgroundDifferentiation of human induced pluripotent stem cells (hiPSCs) into hepatocytes has important clinical significance in providing a new stem cell source for cell therapy of terminal liver disease. The differential gene expression analysis of hiPSCs, induced hepatocyte-like cells (HLCs), and primary human hepatocytes (PHHs) provides valuable information for optimization of an induction scheme and exploration of differentiation mechanisms.MethodsHuman hair follicle-derived iPSCs (hHF-iPSCs) were induced in vitro by mimicking the environment of a developing liver for 19 days. Expression of specific proteins was determined by immunofluorescence staining; the function of HLCs in storage and metabolism was identified by detecting periodic acid–Schiff, indocyanine green, and low-density lipoprotein. Based on the transcriptomics data, the differential gene expression profiles of hHF-iPSCs, HLCs, and PHHs were analyzed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, FunRich, and network analysis methods.ResultsHLCs were able to express albumin (ALB), alpha-fetoprotein, CYP3A4, and CYP7A1, and exhibited matured liver cell functions such as glycogen synthesis and storage. Complement and coagulation cascades and metabolic pathways ranked top in the downregulated list of HLCs/PHHs, while the cell cycle ranked top in the upregulated list of HLCs/PHHs. In the protein–protein interaction network, according to the degree rankings, TOP2A, CDK1, etc. were the important upregulated differentially expressed genes (DEGs), while ALB, ACACB, etc. were the major downregulated DEGs in HLCs/PHHs; the module analysis indicated that CDCA8, AURKB, and AURKA were the top upregulated DEGs in HLCs/PHHs.ConclusionsWe presented the differences in gene expression among hHF-iPSCs, HLCs, and PHHs through transcriptome array data and provided new ideas for the optimization of induction.Electronic supplementary materialThe online version of this article (10.1186/s13287-018-0940-z) contains supplementary material, which is available to authorized users.

Genomic Regions Associated with the Position and Number of Hair Whorls in Horses

“…The number of hair whorls on the neck has not yet been associated with behavioral traits, but there is evidence of neurological action of some of the cited genes: NCSTN [36], PBX1 [37,38], and VANGL2 [39]. A series of genes expressed in the hair follicle were also found in the second window, located on ECA11: TP53 [40], AURKB [41], PER1 [42], ALOXE3 and ALOX12B [43] and DVL2 [44]. Some of these genes are associated with hair loss: ALOX15B [45], SHBG [46], and ALOX15 [47].…”

Determine transposable genes when the orders of genes are different

“…After the knockdown of transcription factor ZNF143, AURKB, MCM2, MCM4, MCM5 are down-regulated [14]. In hepatocyte-like cells and primary human hepatocytes, AURKB and MCM4 are both up-regulated [64]. AURKB and MCM2 are both positively correlated with TK1 [63].…”

Induction and Maturation of Hepatocyte-Like Cells In Vitro: Focus on Technological Advances and Challenges

“…The classic reprogramming technique involves introducing Oct4/Sox2/KLF4/c-MYC genes into candidate cells to reverse cells from a differentiated state to the ground state with the ability to re-differentiate (Takahashi and Yamanaka, 2006). However, the reprogramming efficiency is affected by the expression level of the four transcription factors, and the method poses a potential risk of insertion mutation; furthermore, the continuous expression of c-MYC may pose a risk of tumorigenesis in vivo (Xu et al, 2018;Haridhasapavalan et al, 2020). Based on efficiency and safety considerations, reprogramming methods have been explored and optimized, such as reducing or replacing the application of c-MYC (Huang et al, 2018;Nakagawa et al, 2008), shifting from genetic integration to integration-free methods, or using smallmolecule cocktails for direct reprogramming (Fusaki et al, 2009;Okita et al, 2011;Ma et al, 2017).…”

“…Disease modeling from HLCs is not limited by the ethical issues of cell origin, because the current reprogramming technology of iPSCs can be applied to most adult cells in the human body, including the easily available urine epithelial cells and hair follicle epithelial cells (Zhou et al, 2011;Xu et al, 2018). In addition, HLCs can be used to establish disease models based on genetic backgrounds (e.g., autosomal recessive hypercholesterolemia) or specific disease models, such as in vitro HBV, HCV infection, and CYP2C19deficient metabolism models (Schwartz et al, 2012;Sakurai et al, 2017;Deguchi et al, 2019;Nikasa et al, 2021).…”

“…Nevertheless, even with this immature state, HLCs show an ideal effect in treating animal models of liver diseases and, are used for generating in vitro organoid models for predicting the hepatotoxicity of new drug (Corbett and Duncan, 2019). Unfortunately, immature phenotypes and the inconsistent differentiation of HLCs in the same batch, especially those derived from stem cells, pose a risk of tumorigenesis after transplantation into humans (Xu et al, 2018). All of these obstacles block the transformation of HLCs as an alternative to HHs in clinical applications, and greatly discount the authenticity of drug prediction results in some basic experiments, because HLCs cannot fully express the function of mature hepatocytes.…”