Human hepatocytes display substantial functional inter-individual variation regarding drug metabolizing functions. In order to investigate if this diversity is mirrored in hepatocytes derived from different human pluripotent stem cell (hPSC) lines, we evaluated 25 hPSC lines originating from 24 different donors for hepatic differentiation and functionality. Homogenous hepatocyte cultures could be derived from all hPSC lines using one standardized differentiation procedure. To the best of our knowledge this is the first report of a standardized hepatic differentiation procedure that is generally applicable across a large panel of hPSC lines without any adaptations to individual lines. Importantly, with regard to functional aspects, such as Cytochrome P450 activities, we observed that hepatocytes derived from different hPSC lines displayed inter-individual variation characteristic for primary hepatocytes obtained from different donors, while these activities were highly reproducible between repeated experiments using the same line. Taken together, these data demonstrate the emerging possibility to compile panels of hPSC-derived hepatocytes of particular phenotypes/genotypes relevant for drug metabolism and toxicity studies. Moreover, these findings are of significance for applications within the regenerative medicine field, since our stringent differentiation procedure allows the derivation of homogenous hepatocyte cultures from multiple donors which is a prerequisite for the realization of future personalized stem cell based therapies.
Human brain tissue models such as cerebral organoids are essential tools for developmental and biomedical research. Current methods to generate cerebral organoids often utilize Matrigel as an external scaffold to provide structure and biologically relevant signals. Matrigel however is a nonspecific hydrogel of mouse tumor origin and does not represent the complexity of the brain protein environment. In this study, we investigated the application of a decellularized adult porcine brain extracellular matrix (B-ECM) which could be processed into a hydrogel (B-ECM hydrogel) to be used as a scaffold for human embryonic stem cell (hESC)-derived brain organoids. We decellularized pig brains with a novel detergent- and enzyme-based method and analyzed the biomaterial properties, including protein composition and content, DNA content, mechanical characteristics, surface structure, and antigen presence. Then, we compared the growth of human brain organoid models with the B-ECM hydrogel or Matrigel controls in vitro. We found that the native brain source material was successfully decellularized with little remaining DNA content, while Mass Spectrometry (MS) showed the loss of several brain-specific proteins, while mainly different collagen types remained in the B-ECM. Rheological results revealed stable hydrogel formation, starting from B-ECM hydrogel concentrations of 5 mg/mL. hESCs cultured in B-ECM hydrogels showed gene expression and differentiation outcomes similar to those grown in Matrigel. These results indicate that B-ECM hydrogels can be used as an alternative scaffold for human cerebral organoid formation, and may be further optimized for improved organoid growth by further improving protein retention other than collagen after decellularization.
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.
Reference genes, often referred to as housekeeping genes (HKGs), are frequently used to normalize gene expression data based on the assumption that they are expressed at a constant level in the cells. However, several studies have shown that there may be a large variability in the gene expression levels of HKGs in various cell types. In a previous study, employing human embryonic stem cells (hESCs) subjected to spontaneous differentiation, we observed that the expression of commonly used HKG varied to a degree that rendered them inappropriate to use as reference genes under those experimental settings. Here we present a substantially extended study of the HKG signature in human pluripotent stem cells (hPSC), including nine global gene expression datasets from both hESC and human induced pluripotent stem cells, obtained during directed differentiation toward endoderm-, mesoderm-, and ectoderm derivatives. Sets of stably expressed genes were compiled, and a handful of genes (e.g., EID2, ZNF324B, CAPN10, and RABEP2) were identified as generally applicable reference genes in hPSCs across all cell lines and experimental conditions. The stability in gene expression profiles was confirmed by reverse transcription quantitative PCR analysis. Taken together, the current results suggest that differentiating hPSCs have a distinct HKG signature, which in some aspects is different from somatic cell types, and underscore the necessity to validate the stability of reference genes under the actual experimental setup used. In addition, the novel putative HKGs identified in this study can preferentially be used for normalization of gene expression data obtained from differentiating hPSCs.
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.
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.
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.
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