Knowledge Based Gene Set analysis (KB-GSA): A novel method for gene expression analysis

Abstract Microarray technology allows measurement of the expression levels o

Artificial Intelligence Supports Automated Characterization of Differentiated Human Pluripotent Stem Cells

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, that is, 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 toward 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

Human Embryonic Stem Cell Derived Hepatocyte-Like Cells as a Tool for In Vitro Hazard Assessment of Chemical Carcinogenicity

Hepatocyte-like cells derived from the differentiation of human embryonic stem cells (hES-Hep) have potential to provide a human relevant in vitro test system in which to evaluate the carcinogenic hazard of chemicals. In this study, we have investigated this potential using a panel of 15 chemicals classified as noncarcinogens, genotoxic carcinogens, and nongenotoxic carcinogens and measured whole-genome transcriptome responses with gene expression microarrays. We applied an ANOVA model that identified 592 genes highly discriminative for the panel of chemicals. Supervised classification with these genes achieved a cross-validation accuracy of > 95%. Moreover, the expression of the response genes in hES-Hep was strongly correlated with that in human primary hepatocytes cultured in vitro. In order to infer mechanistic information on the consequences of chemical exposure in hES-Hep, we developed a computational method that measures the responses of biochemical pathways to the panel of treatments and showed that these responses were discriminative for the three toxicity classes and linked to carcinogenesis through p53, mitogen-activated protein kinases, and apoptosis pathway modules. It could further be shown that the discrimination of toxicity classes was improved when analyzing the microarray data at the pathway level. In summary, our results demonstrate, for the first time, the potential of human embryonic stem cell--derived hepatic cells as an in vitro model for hazard assessment of chemical carcinogenesis, although it should be noted that more compounds are needed to test the robustness of the assay

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

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

Transcriptional profiling of human embryonic stem cells and their functional derivatives

Human embryonic stem cells (hESCs) represent populations of pluripotent, undifferentiated cells with unlimited replication capacity, and with the ability to differentiate into any functional cell type in the human body. Based on these properties, hESCs and their derivatives provide unique model systems for basic research on embryonic development. Also, industrial in vitro applications of hESCs are now beginning to find their way into the fields of drug discovery and toxicology. Moreover, hESC-derivatives are anticipated to be promising resources for future cell replacement therapies. However, in order to fully utilize the potential of hESCs it is necessary to increase our knowledge about the processes that govern the differentiation of these cells. At present, some of the major challenges in stem cell research are heterogeneous cell populations, insufficient yield of the differentiated cell types and immature derivatives with limited functionality. To address these problems, a better understanding of the regulatory mechanisms that control the lineage commitment is needed. The aim of this thesis has been to increase the knowledge of the global transcriptional programs which are activated when cells differentiate along specific pathways, and to identify key genes that show differential expression at specific stages of differentiation. The results indicate that hESCs express a unique set of housekeeping genes that are stably expressed in this specific cell type and in their derivatives, which highlights the importance of proper validation of reference genes for usage in hESCs. Furthermore, an extensive characterization of hESCs and differentiated progenies of the cardiac and hepatic lineages has been conducted, and sets of differentially expressed genes were identified. Two different protocols, which mediate definitive and primitive endoderm respectively, were studied, and important discrepancies between these two cell types were identified. Moreover, the global expression profile of hESC-derived cardiomyocyte clusters were thoroughly investigated and compared to that of foetal and adult heart. To further study regulatory mechanisms of importance during stem cell differentiation, the global expression of microRNAs (miRNAs) was also investigated. Putative target genes of differentially expressed miRNAs were identified using computational predictions, and their mRNA expression was analysed. Notably, an interesting correlation between the miRNA and mRNA expression was observed, which supports the general notion that miRNAs bind to and degrade their target mRNAs, and thus act as fine-tuning regulators of gene expression. Taken together, the results described in this thesis provide important information for further studies on regulatory mechanisms that control the differentiation of hESCs into functional cell types such as cardiomyocytes and hepatocytes

Understanding the differentiation of human embryonic stem cells

The proposed research project will apply an information fusion approach to various types of experimental data in order to increase our understanding of the differentiation of human embryonic stem (hES) cells into various specialized cell types. Gene expression profiles from hES cells in different stages of differentiation will be analysed to identify significantly over- and underexpressed genes. The purpose of the analysis is to find genes that might be important in the differentiation process and that are crucial for directing stem cells into specialized cell types. The project will focus on the endoderm development and one issue will be to increase our knowledge about two different types of endoderm development occurring in humans; primitive and definitive endoderm and their derivates. Another issue will be to compare gene expression profiles from cells that lack chromosome 13 with a sub-clone with normal karyotype (Heins et al., 2004). A comparison of gene expression profiles from in vitro derived specialized cells with gene expression profiles from adult cells from the same tissue type will also be conducted. The project will start, however, with an investigation and validation of “housekeeping genes”, which will be used for normalization and calibration of the gene expression levels in the subsequent analyses. The novelty of the project arises from the fact that most previous research in understanding the differentiation of ES cells has been done on animals (Yamada et al., 2002; Stainier, 2002; Asahina et al., 2004), while very little has been done on human ES cells. Since substantial differences both in morphology and in the gene expression pattern are well known between ES cells from these two organisms, it is important to characterize the genetic regulation of the processes responsible for these differences. This project will work with hES cells supplied by Cellartis, a company specialized in hES cell technologies