Multi-Omics Characterization of a Human Stem Cell-Based Model of Cardiac Hypertrophy.

Cardiac hypertrophy is an important and independent risk factor for the development of cardiac myopathy that may lead to heart failure. The mechanisms underlying the development of cardiac hypertrophy are yet not well understood. To increase the knowledge about mechanisms and regulatory pathways involved in the progression of cardiac hypertrophy, we have developed a human induced pluripotent stem cell (hiPSC)-based in vitro model of cardiac hypertrophy and performed extensive characterization using a multi-omics approach. In a series of experiments, hiPSC-derived cardiomyocytes were stimulated with Endothelin-1 for 8, 24, 48, and 72 h, and their transcriptome and secreted proteome were analyzed. The transcriptomic data show many enriched canonical pathways related to cardiac hypertrophy already at the earliest time point, e.g., cardiac hypertrophy signaling. An integrated transcriptome-secretome analysis enabled the identification of multimodal biomarkers that may prove highly relevant for monitoring early cardiac hypertrophy progression. Taken together, the results from this study demonstrate that our in vitro model displays a hypertrophic response on both transcriptomic- and secreted-proteomic levels. The results also shed novel insights into the underlying mechanisms of cardiac hypertrophy, and novel putative early cardiac hypertrophy biomarkers have been identified that warrant further investigation to assess their potential clinical relevance.

Multi-assignment clustering: Machine learning from a biological perspective.

A common approach for analyzing large-scale molecular data is to cluster objects sharing similar characteristics. This assumes that genes with highly similar expression profiles are likely participating in a common molecular process. Biological systems are extremely complex and challenging to understand, with proteins having multiple functions that sometimes need to be activated or expressed in a time-dependent manner. Thus, the strategies applied for clustering of these molecules into groups are of key importance for translation of data to biologically interpretable findings. Here we implemented a multi-assignment clustering (MAsC) approach that allows molecules to be assigned to multiple clusters, rather than single ones as in commonly used clustering techniques. When applied to high-throughput transcriptomics data, MAsC increased power of the downstream pathway analysis and allowed identification of pathways with high biological relevance to the experimental setting and the biological systems studied. Multi-assignment clustering also reduced noise in the clustering partition by excluding genes with a low correlation to all of the resulting clusters. Together, these findings suggest that our methodology facilitates translation of large-scale molecular data into biological knowledge. The method is made available as an R package on GitLab (https://gitlab.com/wolftower/masc).

Cardiac hypertrophy in a dish: a human stem cell based model.

Cardiac hypertrophy is an important and independent risk factor for the development of heart failure. To better understand the mechanisms and regulatory pathways involved in cardiac hypertrophy, there is a need for improved in vitro models. In this study, we investigated how hypertrophic stimulation affected human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CMs). The cells were stimulated with endothelin-1 (ET-1) for 8, 24, 48, 72, or 96 h. Parameters including cell size, ANP-, proBNP-, and lactate concentration were analyzed. Moreover, transcriptional profiling using RNA-sequencing was performed to identify differentially expressed genes following ET-1 stimulation. The results show that the CMs increase in size by approximately 13% when exposed to ET-1 in parallel to increases in ANP and proBNP protein and mRNA levels. Furthermore, the lactate concentration in the media was increased indicating that the CMs consume more glucose, a hallmark of cardiac hypertrophy. Using RNA-seq, a hypertrophic gene expression pattern was also observed in the stimulated CMs. Taken together, these results show that hiPSC-derived CMs stimulated with ET-1 display a hypertrophic response. The results from this study also provide new molecular insights about the underlying mechanisms of cardiac hypertrophy and may help accelerate the development of new drugs against this condition.

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

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.

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

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.

Expression Profiling of Human Pluripotent Stem Cell-Derived Cardiomyocytes Exposed to Doxorubicin-Integration and Visualization of Multi-Omics Data.

Anthracyclines, such as doxorubicin, are highly efficient chemotherapeutic agents against a variety of cancers. However, anthracyclines are also among the most cardiotoxic therapeutic drugs presently on the market. Chemotherapeutic-induced cardiomyopathy is one of the leading causes of disease and mortality in cancer survivors. The exact mechanisms responsible for doxorubicin-induced cardiomyopathy are not completely known, but the fact that the cardiotoxicity is dose-dependent and that there is a variation in time-to-onset of toxicity, and gender- and age differences suggests that several mechanisms may be involved. In this study, we investigated doxorubicin-induced cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes using proteomics. In addition, different sources of omics data (protein, mRNA, and microRNA) from the same experimental setup were further combined and analyzed using newly developed methods to identify differential expression in data of various origin and types. Subsequently, the results were integrated in order to generate a combined visualization of the findings. In our experimental model system, we exposed cardiomyocytes derived from human pluripotent stem cells to doxorubicin for up to 2 days, followed by a wash-out period of additionally 12 days. Besides an effect on the cell morphology and cardiomyocyte functionality, the data show a strong effect of doxorubicin on all molecular levels investigated. Differential expression patterns that show a linkage between the proteome, transcriptome, and the regulatory microRNA network, were identified. These findings help to increase the understanding of the mechanisms behind anthracycline-induced cardiotoxicity and suggest putative biomarkers for this condition.

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

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.

A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells.

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic- and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

MicroRNAs as potential biomarkers for doxorubicin-induced cardiotoxicity.

Anthracyclines, such as doxorubicin, are well-established, highly efficient anti-neoplastic drugs used for treatment of a variety of cancers, including solid tumors, leukemia, lymphomas, and breast cancer. The successful use of doxorubicin has, however, been hampered by severe cardiotoxic side-effects. In order to prevent or reverse negative side-effects of doxorubicin, it is important to find early biomarkers of heart injury and drug-induced cardiotoxicity. The high stability under extreme conditions, presence in various body fluids, and tissue-specificity, makes microRNAs very suitable as clinical biomarkers. The present study aimed towards evaluating the early and late effects of doxorubicin on the microRNA expression in cardiomyocytes derived from human pluripotent stem cells. We report on several microRNAs, including miR-34a, miR-34b, miR-187, miR-199a, miR-199b, miR-146a, miR-15b, miR-130a, miR-214, and miR-424, that are differentially expressed upon, and after, treatment with doxorubicin. Investigation of the biological relevance of the identified microRNAs revealed connections to cardiomyocyte function and cardiotoxicity, thus supporting the findings of these microRNAs as potential biomarkers for drug-induced cardiotoxicity.

Anti-inflammatory effect of insulin in the human hepatoma cell line HepG2 involves decreased transcription of IL-6 target genes and nuclear exclusion of FOXO1.

The liver is an important target for interleukin-6 (IL-6) action leading to an increased inflammatory response with impaired insulin signaling and action. The aims of this study are to address if insulin is anti-inflammatory and attenuates IL-6-induced inflammation in the human hepatoma cell line HepG2 and if this involves signal transducer and activator of transcription 3 (STAT3) signal transduction. It was found that insulin significantly reduced IL-6-induced gene transcription of serum amyloid 1 (SAA1), serum amyloid 2 (SAA2), haptoglobin, orosomucoid, and plasmin activator inhibitor-1 (PAI-1). However, the authors did not find any evidence that insulin inhibited IL-6 signal transduction, i.e., no effect of insulin was detected on STAT3 phosphorylation or its translocation to cell nucleus. The potential role of PKCδ was also analyzed but no evidence of its involvement was found. Taken together, these results suggest that the anti-inflammatory effect of insulin on IL-6 action is exerted at the level of the transcriptional activation of the genes. Further analysis revealed that insulin regulates nuclear localization of FOXO1, which is an important co-activator for STAT3 mediated transcription. Insulin induced nuclear exit and Thr24 phosphorylation of FOXO1, thus, inhibiting STAT3-mediated transcription.

Inflamed adipose tissue, insulin resistance and vascular injury.

Type 2 diabetes is the most common metabolic disorder today and has reached epidemic proportions in many countries. Insulin resistance and inflammation play a central role in the pathogenesis of type 2 diabetes and are present long before the onset of the disease. During this time, many of the complications associated with type 2 diabetes are initiated. Of major concern is the two- to fourfold increase in cardiovascular morbidity and mortality in this group compared to a nondiabetic population. Obesity, characterized by enlarged fat cells, and insulin resistance are, like type 2 diabetes, associated with impaired adipogenesis and a low-grade chronic inflammation that to a large extent emanates from the adipose tissue. Both these processes contribute to unfavourable alterations of the circulating levels of several bioactive molecules (adipokines) that are secreted from the adipose tissue, many of which have documented inhibitory effects on insulin sensitivity in the liver and peripheral tissues and, in addition, have negative effects on the cardiovascular system.Here we review current knowledge of the adipose tissue as an endocrine organ, the local and systemic effects of a chronic state of low-grade inflammation residing in the adipose tissue, and, in particular, the effects of inflammation and circulating adipokines on the vascular wall.

Inflamed adipose tissue: a culprit underlying the metabolic syndrome and atherosclerosis.

The metabolic syndrome is associated with a dysregulated adipose tissue; in part a consequence of adipose cell enlargement and the associated infiltration of macrophages. Adipose cell enlargement leads to a proinflammatory state in the cells with reduced secretion of adiponectin and with increased secretion of several cytokines and chemokines including interleukin (IL)-6, IL-8, and MCP-1. MCP-1 has been shown to play an important role for the associated recruitment of macrophages into the adipose tissue. The increased release of cytokines leads to an impaired differentiation of the preadipocytes with reduced lipid accumulation and induction of adiponectin, thus promoting ectopic lipid storage. In particular tumor necrosis factor (TNF) alpha, but also IL-6, has been shown to induce these effects in preadipocytes and this is associated with an increased Wnt signaling maintaining the cells in an undifferentiated and proinflammatory state. The proinflammatory state in the adipose tissue also leads to a local insulin resistance including an impaired inhibitory effect of insulin on FFA release. The insulin resistance further supports the proinflammatory state because insulin, by itself, is both antilipolytic and antiinflammatory by antagonizing cytokine-induced activation of STAT signaling.

Insulin antagonizes interleukin-6 signaling and is anti-inflammatory in 3T3-L1 adipocytes.

Adipose tissue secretes different adipokines, including interleukin-6 (IL-6), that have been implicated in the insulin resistance and inflammatory state characterizing obesity. We examined the putative cross-talk between insulin and IL-6 in adipose cells and found that insulin exerts an inhibitory effect on the IL-6 signaling pathway by altering the post-translational modifications of the signal transducer and activator of transcription 3 (STAT3). Insulin reduces the tyrosine phosphorylation and increases the serine phosphorylation of STAT3, thereby reducing its nuclear localization and transcriptional activity. Signaling through the MEK/MAPK pathway plays an important role as treatment with the MEK inhibitor PD98059 reduces the effects of insulin on IL-6 signaling. We also show that the protein tyrosine phosphatase SHP2 is activated upon insulin signaling and is required for the dephosphorylation of STAT3 and that insulin exerts a synergistic effect with IL-6 on suppressor of cytokine signaling 3 expression. As a consequence, the IL-6-induced expression of the inflammatory markers serum amyloid A 3 and haptoglobin are significantly decreased in cells incubated with both IL-6 and insulin. Thus, insulin exerts an important anti-inflammatory effect in adipose cells by impairing the IL-6 signal at several levels.

Shedding and gamma-secretase-mediated intramembrane proteolysis of the mucin-type molecule CD43.

CD43 is a transmembrane molecule that contains a 123-aminoacids-long cytoplasmic tail and a highly O-glycosylated extracellular domain of mucin type. Endogenous CD43 expressed in COLO 205, K562 and Jurkat cells revealed a membrane-associated, 20 kDa CD43-specific cytoplasmic tail fragment (CD43-CTF) upon inhibition of gamma-secretase. This fragment was formed by an extracellular cleavage, as it was not accumulated after treating cells with 1,10-phenanthroline, a metalloprotease inhibitor. When CD43 was transfected into HEK-293 cells expressing dominant-negative PS1 (presenilin-1), the CD43-CTF was accumulated, but not in cells with wild-type PS1. Owing to its accumulation in the presence of a non-functional PS variant, it may thus be a novel gamma-secretase substrate. This CTF is formed by an extracellular cleavage close to the membrane, is a fragment that can be concluded to be a substrate for gamma-secretase. However, the intracellular gamma-secretase product has not been possible to detect, suggesting a quick processing of this product. During normal growth the CTF was not found without gamma-secretase inhibition, but when the cells (COLO 205) were very confluent the fragment could be detected. The intracellular domain of CD43 has previously been shown to contain a functional nuclear localization signal, and has been suggested to be involved in gene activation. From this and the present results, a novel way to explain how mucin-type molecules may transduce intracellular signals can be proposed.

Bcr (breakpoint cluster region) protein binds to PDZ-domains of scaffold protein PDZK1 and vesicle coat protein Mint3.

The breakpoint cluster region protein (Bcr) is a large soluble oligomeric multidomain protein best known because of its involvement in chronic myelogenous leukemia (CML). A chromosomal translocation between its gene and that of the c-abl kinase ('Philadelphia chromosome') plays a major causative role in that malignancy. Thus most attention has been paid to the role of the protein in hemopoietic cells. However, Bcr is also expressed in other cell types including epithelia. Bcr is generally considered to be a cytoplasmic protein but in addition to its kinase and GTPase exchange and activating domains it contains potentially membrane-interacting pleckstrin homology and C2 domains as well as a PDZ-binding C terminus mediating an interaction with a PDZ-domain protein at intercellular junctions of epithelial cells. We have examined the ability of Bcr to interact with other epithelial PDZ proteins and found specific binding to both the apical PDZK1 protein and the Golgi-localized Mint3. The former is important in the organization of several apical functions and the latter in vesicular trafficking in the secretory pathway. Hence these findings extend the interactions and likely signaling impact of Bcr in epithelia from the cytosol to at least these two membrane compartments.

CD43 has a functional NLS, interacts with beta-catenin, and affects gene expression.

CD43 is a transmembrane molecule with a highly O-glycosylated extracellular domain of mucin type. It is a normal constituent of leukocytes and found in colon adenoma, but not in normal colon epithelia. Here it is shown that the cytoplasmic tail of CD43 contains a functional bipartite nuclear localization signal directing it to the nucleus. The intracellular domain of CD43 interacts with beta-catenin and causes an upregulation of the beta-catenin target genes c-MYC and CyclinD1. The present results suggest that CD43 can be involved in nuclear signaling and via beta-catenin interaction be involved in cell proliferation.