12 research outputs found

    Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells

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    Background & AimsThe differentiation of stem cells to hepatocyte-like cells (HLC) offers the perspective of unlimited supply of human hepatocytes. However, the degree of differentiation of HLC remains controversial. To obtain an unbiased characterization, we performed a transcriptomic study with HLC derived from human embryonic and induced stem cells (ESC, hiPSC) from three different laboratories.MethodsGenome-wide gene expression profiles of ESC and HLC were compared to freshly isolated and up to 14days cultivated primary human hepatocytes. Gene networks representing successful and failed hepatocyte differentiation, and the transcription factors involved in their regulation were identified.ResultsGene regulatory network analysis demonstrated that HLC represent a mixed cell type with features of liver, intestine, fibroblast and stem cells. The “unwanted” intestinal features were associated with KLF5 and CDX2 transcriptional networks. Cluster analysis identified highly correlated groups of genes associated with mature liver functions (n=1057) and downregulated proliferation associated genes (n=1562) that approach levels of primary hepatocytes. However, three further clusters containing 447, 101, and 505 genes failed to reach levels of hepatocytes. Key TF of two of these clusters include SOX11, FOXQ1, and YBX3. The third unsuccessful cluster, controlled by HNF1, CAR, FXR, and PXR, strongly overlaps with genes repressed in cultivated hepatocytes compared to freshly isolated hepatocytes, suggesting that current in vitro conditions lack stimuli required to maintain gene expression in hepatocytes, which consequently also explains a corresponding deficiency of HLC.ConclusionsThe present gene regulatory network approach identifies key transcription factors which require modulation to improve HLC differentiation

    Artificial intelligence supports automated characterization of differentiated human pluripotent stem cells

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    Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy images to e.g., distinguish between pluripotent stem cells and differentiated cell types derived from stem cells. In this work, we investigated the possibility of using a deep learning model to predict the differentiation stage of pluripotent stem cells undergoing differentiation towards hepatocytes, based on morphological features of cell cultures. We were able to achieve close to perfect classification of images from early and late time points during differentiation, and this aligned very well with the experimental validation of cell identity and function. Our results suggest that deep learning models can distinguish between different cell morphologies, and provide alternative means of semi-automated functional characterization of stem cell cultures.CC BY 4.0Corresponding author: Benjamin Ulfenborg, PhD, Department of Biology and Bioinformatics, School of Bioscience, University of Skövde, SE-541 28, Sweden. Email: [email protected] work was supported by the Swedish Knowledge Foundation (grant numbers 20170302 and 20200014), the Systems Biology Research Center, University of Skövde, Sweden and Takara Bio Europe, Gothenburg, Sweden.</p

    Characterization of Human Induced Pluripotent Stem Cell-Derived Hepatocytes with Mature Features and Potential for Modeling Metabolic Diseases

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    There is a strong anticipated future for human induced pluripotent stem cell-derived hepatocytes (hiPS-HEP), but so far, their use has been limited due to insufficient functionality. We investigated the potential of hiPS-HEP as an in vitro model for metabolic diseases by combining transcriptomics with multiple functional assays. The transcriptomics analysis revealed that 86% of the genes were expressed at similar levels in hiPS-HEP as in human primary hepatocytes (hphep). Adult characteristics of the hiPS-HEP were confirmed by the presence of important hepatocyte features, e.g., Albumin secretion and expression of major drug metabolizing genes. Normal energy metabolism is crucial for modeling metabolic diseases, and both transcriptomics data and functional assays showed that hiPS-HEP were similar to hphep regarding uptake of glucose, low-density lipoproteins (LDL), and fatty acids. Importantly, the inflammatory state of the hiPS-HEP was low under standard conditions, but in response to lipid accumulation and ER stress the inflammation marker tumor necrosis factor α (TNFα) was upregulated. Furthermore, hiPS-HEP could be co-cultured with primary hepatic stellate cells both in 2D and in 3D spheroids, paving the way for using these co-cultures for modeling non-alcoholic steatohepatitis (NASH). Taken together, hiPS-HEP have the potential to serve as an in vitro model for metabolic diseases. Furthermore, differently expressed genes identified in this study can serve as targets for future improvements of the hiPS-HEP.CC BY 4.0</p

    Human Pluripotent Stem Cell-Derived Hepatocytes Show Higher Transcriptional Correlation with Adult Liver Tissue than with Fetal Liver Tissue

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    Human pluripotent stem cell-derived hepatocytes (hPSC-HEP) display many properties of mature hepatocytes, including expression of important genes of the drug metabolizing machinery, glycogen storage, and production of multiple serum proteins. To this date, hPSC-HEP do not, however, fully recapitulate the complete functionality of in vivo mature hepatocytes. In this study, we applied versatile bioinformatic algorithms, including functional annotation and pathway enrichment analyses, transcription factor binding-site enrichment, and similarity and correlation analyses, to datasets collected from different stages during hPSC-HEP differentiation and compared these to developmental stages and tissues from fetal and adult human liver. Our results demonstrate a high level of similarity between the in vitro differentiation of hPSC-HEP and in vivo hepatogenesis. Importantly, the transcriptional correlation of hPSC-HEP with adult liver (AL) tissues was higher than with fetal liver (FL) tissues (0.83 and 0.70, respectively). Functional data revealed mature features of hPSC-HEP including cytochrome P450 enzymes activities and albumin secretion. Moreover, hPSC-HEP showed expression of many genes involved in drug absorption, distribution, metabolism, and excretion. Despite the high similarities observed, we identified differences of specific pathways and regulatory players by analyzing the gene expression between hPSC-HEP and AL. These findings will aid future intervention and improvement of in vitro hepatocyte differentiation protocol in order to generate hepatocytes displaying the complete functionality of mature hepatocytes. Finally, on the transcriptional level, our results show stronger correlation and higher similarity of hPSC-HEP to AL than to FL. In addition, potential targets for further functional improvement of hPSC-HEP were also identified.

    Highly Synchronized Expression of Lineage-Specific Genes during In Vitro Hepatic Differentiation of Human Pluripotent Stem Cell Lines

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    Human pluripotent stem cells- (hPSCs-) derived hepatocytes have the potential to replace many hepatic models in drug discovery and provide a cell source for regenerative medicine applications. However, the generation of fully functional hPSC-derived hepatocytes is still a challenge. Towards gaining better understanding of the differentiation and maturation process, we employed a standardized protocol to differentiate six hPSC lines into hepatocytes and investigated the synchronicity of the hPSC lines by applying RT-qPCR to assess the expression of lineage-specific genes (OCT4, NANOG, T, SOX17, CXCR4, CER1, HHEX, TBX3, PROX1, HNF6, AFP, HNF4a, KRT18, ALB, AAT, and CYP3A4) which serve as markers for different stages during liver development. The data was evaluated using correlation and clustering analysis, demonstrating that the expression of these markers is highly synchronized and correlated well across all cell lines. The analysis also revealed a distribution of the markers in groups reflecting the developmental stages of hepatocytes. Functional analysis of the differentiated cells further confirmed their hepatic phenotype. Taken together, these results demonstrate, on the molecular level, the highly synchronized differentiation pattern across multiple hPSC lines. Moreover, this study provides additional understanding for future efforts to improve the functionality of hPSC-derived hepatocytes and thereby increase the value of related models

    Comparative transcriptomics of hepatic differentiation of human pluripotent stem cells and adult human liver tissue

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    Hepatocytes derived from human pluripotent stem cells (hPSC-HEP) have the potential to replace presently used hepatocyte sources applied in liver disease treatment and models of drug discovery and development. Established hepatocyte differentiation protocols are effective and generate hepatocytes, which recapitulate some key features of their in vivo counterparts. However, generating mature hPSC-HEP remains a challenge. In this study, we applied transcriptomics to investigate the progress of in vitro hepatic differentiation of hPSCs at the developmental stages, definitive endoderm, hepatoblasts, early hPSC-HEP, and mature hPSC-HEP, to identify functional targets that enhance efficient hepatocyte differentiation. Using functional annotation, pathway and protein interaction network analyses, we observed the grouping of differentially expressed genes in specific clusters representing typical developmental stages of hepatic differentiation. In addition, we identified hub proteins and modules that were involved in the cell cycle process at early differentiation stages. We also identified hub proteins that differed in expression levels between hPSC-HEP and the liver tissue controls. Moreover, we identified a module of genes that were expressed at higher levels in the liver tissue samples than in the hPSC-HEP. Considering that hub proteins and modules generally are essential and have important roles in the protein-protein interactions, further investigation of these genes and their regulators may contribute to a better understanding of the differentiation process. This may suggest novel target pathways and molecules for improvement of hPSC-HEP functionality, having the potential to finally bring this technology to a wider use

    Identification of an FXR-modulated liver-intestine hybrid state in iPSC-derived hepatocyte-like cells

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    BACKGROUND &amp; AIMS: Pluripotent stem cell (PSC)-derived hepatocyte-like cells (HLC) have enormous potential as a replacement for primary hepatocytes in drug screening, toxicology and cell replacement therapy, but their genome-wide expression patterns differ strongly from primary human hepatocytes (PHH). METHODS: We differentiated human induced pluripotent stem cells (hiPSC) via definitive endoderm to HLC and characterized the cells by single-cell and bulk RNA-seq, with complementary epigenetic analyses. We then compared HLC to PHH and publicly available data on human fetal hepatocytes (FH) ex vivo; we performed bioinformatics-guided interventions to improve HLC differentiation via lentiviral transduction of the nuclear receptor FXR and agonist exposure. RESULTS: Single-cell RNA-seq revealed that transcriptomes of individual HLC display a hybrid state, where hepatocyte-associated genes are expressed in concert with genes that are not expressed in PHH – mostly intestinal genes – within the same cell. Bulk-level overrepresentation analysis, as well as regulon analysis at the single-cell level, identified sets of regulatory factors discriminating HLC, FH, and PHH, hinting at a central role for the nuclear receptor FXR in the functional maturation of HLC. Combined FXR expression plus agonist exposure enhanced the expression of hepatocyte-associated genes and increased the ability of bile canalicular secretion as well as lipid droplet formation, thereby increasing HLCs’ similarity to PHH. The undesired non-liver gene expression was reproducibly decreased, although only by a moderate degree. CONCLUSION: In contrast to physiological hepatocyte precursor cells and mature hepatocytes, HLC co-express liver and hybrid genes in the same cell. Targeted modification of the FXR gene regulatory network improves their differentiation by suppressing intestinal traits whilst inducing hepatocyte features. LAY SUMMARY: Generation of human hepatocytes from stem cells represents an active research field but its success is hampered by the fact that the stem cell-derived ‘hepatocytes’ still show major differences to hepatocytes obtained from a liver. Here, we identified an important reason for the difference, specifically that the stem cell-derived ‘hepatocyte’ represents a hybrid cell with features of hepatocytes and intestinal cells. We show that a specific protein (FXR) suppresses intestinal and induces liver features, thus bringing the stem cell-derived cells closer to hepatocytes derived from human livers
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