Satoshi Okawa

Transcriptome of human foetal heart compared with cardiomyocytes from pluripotent stem cells

Differentiated derivatives of human pluripotent stem cells (hPSCs) are often considered immature because they resemble foetal cells more than adult, with hPSC-derived cardiomyocytes (hPSC-CMs) being no exception. Many functional features of these cardiomyocytes, such as their cell morphology, electrophysiological characteristics, sarcomere organization and contraction force, are underdeveloped compared with adult cardiomyocytes. However, relatively little is known about how their gene expression profiles compare with the human foetal heart, in part because of the paucity of data on the human foetal heart at different stages of development. Here, we collected samples of matched ventricles and atria from human foetuses during the first and second trimester of development. This presented a rare opportunity to perform gene expression analysis on the individual chambers of the heart at various stages of development, allowing us to identify not only genes involved in the formation of the heart, but also specific genes upregulated in each of the four chambers and at different stages of development. The data showed that hPSC-CMs had a gene expression profile similar to first trimester foetal heart, but after culture in conditions shown previously to induce maturation, they cluster closer to the second trimester foetal heart samples. In summary, we demonstrate how the gene expression profiles of human foetal heart samples can be used for benchmarking hPSC-CMs and also contribute to determining their equivalent stage of development. Summary: The analysis of gene expression in the human foetal heart reveals stage- and chamber-specific genes and provides a dataset that can be used for benchmarking human PSC-derived heart cells.

The RNA helicase DDX6 regulates cell-fate specification in neural stem cells via miRNAs

In neural stem cells (NSCs), the balance between stem cell maintenance and neuronal differentiation depends on cell-fate determinants such as TRIM32. Previously, we have shown that TRIM32 associates with the RNA-induced silencing complex and increases the activity of microRNAs such as Let-7a. However, the exact mechanism of microRNA regulation by TRIM32 during neuronal differentiation has yet to be elucidated. Here, we used a mass spectrometry approach to identify novel protein–protein interaction partners of TRIM32 during neuronal differentiation. We found that TRIM32 associates with proteins involved in neurogenesis and RNA-related processes, such as the RNA helicase DDX6, which has been implicated in microRNA regulation. We demonstrate, that DDX6 colocalizes with TRIM32 in NSCs and neurons and that it increases the activity of Let-7a. Furthermore, we provide evidence that DDX6 is necessary and sufficient for neuronal differentiation and that it functions in cooperation with TRIM32.

Gene regulatory network analysis reveals differences in site-specific cell fate determination in mammalian brain

Neurogenesis—the generation of new neurons—is an ongoing process that persists in the adult mammalian brain of several species, including humans. In this work we analyze two discrete brain regions: the subventricular zone (SVZ) lining the walls of the lateral ventricles; and the subgranular zone (SGZ) of the dentate gyrus (DG) of the hippocampus in mice and shed light on the SVZ and SGZ specific neurogenesis. We propose a computational model that relies on the construction and analysis of region specific gene regulatory networks (GRNs) from the publicly available data on these two regions. Using this model a number of putative factors involved in neuronal stem cell (NSC) identity and maintenance were identified. We also demonstrate potential gender and niche-derived differences based on cell surface and nuclear receptors via Ar, Hif1a, and Nr3c1. We have also conducted cell fate determinant analysis for SVZ NSC populations to Olfactory Bulb interneurons and SGZ NSC populations to the granule cells of the Granular Cell Layer. We report 31 candidate cell fate determinant gene pairs, ready to be validated. We focus on Ar—Pax6 in SVZ and Sox2—Ncor1 in SGZ. Both pairs are expressed and localized in the suggested anatomical structures as shown by in situ hybridization and found to physically interact. Finally, we conclude that there are fundamental differences between SGZ and SVZ neurogenesis. We argue that these regulatory mechanisms are linked to the observed differential neurogenic potential of these regions. The presence of nuclear and cell surface receptors in the region specific regulatory circuits indicate the significance of niche derived extracellular factors, hormones and region specific factors such as the oxygen sensitivity, dictating SGZ and SVZ specific neurogenesis.

A Generalized Gene-Regulatory Network Model of Stem Cell Differentiation for Predicting Lineage Specifiers

Summary Identification of cell-fate determinants for directing stem cell differentiation remains a challenge. Moreover, little is known about how cell-fate determinants are regulated in functionally important subnetworks in large gene-regulatory networks (i.e., GRN motifs). Here we propose a model of stem cell differentiation in which cell-fate determinants work synergistically to determine different cellular identities, and reside in a class of GRN motifs known as feedback loops. Based on this model, we develop a computational method that can systematically predict cell-fate determinants and their GRN motifs. The method was able to recapitulate experimentally validated cell-fate determinants, and validation of two predicted cell-fate determinants confirmed that overexpression of ESR1 and RUNX2 in mouse neural stem cells induces neuronal and astrocyte differentiation, respectively. Thus, the presented GRN-based model of stem cell differentiation and computational method can guide differentiation experiments in stem cell research and regenerative medicine.

A differential network analysis approach for lineage specifier prediction in stem cell subpopulations

Background:Stem cell differentiation is a complex biological process. Cellular heterogeneity, such as the co-existence of different cell subpopulations within a population, partly hampers our understanding of this process. The modern single-cell gene expression technologies, such as single-cell RT-PCR and RNA-seq, have enabled us to elucidate such heterogeneous cell subpopulations. However, the identification of a transcriptional regulatory network (TRN) for each cell subpopulation within a population and genes determining specific cell fates (lineage specifiers) remains a challenge due to the slower development of appropriate computational and experimental workflows. Here, we propose a computational differential network analysis approach for predicting lineage specifiers in binary-fate differentiation events.Methods:The proposed method is based on a model that considers each stem cell subpopulation being in a stable state maintained by its specific TRN stability core, and cell differentiation involves changes in these stability cores between parental and daughter cell subpopulations. The method first reconstructs topologically different cell-subpopulation specific TRNs from single-cell gene expression data, literature knowledge and transcription factor (TF)–DNA binding-site prediction. Then, it systematically predicts lineage specifiers by identifying genes in the TRN stability cores in both parental and daughter cell subpopulations.Results:Application of this method to different stem cell differentiation systems was able to predict known and putative novel lineage specifiers. These examples include the differentiation of inner cell mass into either primitive endoderm or epiblast, different progenitor cells in the hematopoietic system, and the lung alveolar bipotential progenitor into either alveolar type 1 or alveolar type 2.Conclusions:The method is generally applicable to any binary-fate differentiation system, for which single-cell gene expression data are available. Therefore, it should aid in understanding stem cell lineage specification, and in the development of experimental strategies for regenerative medicine.

Regulation of Fn14 Receptor and NF-κB Underlies Inflammation in Meniere’s Disease

Meniere’s disease (MD) is a rare disorder characterized by episodic vertigo, sensorineural hearing loss, tinnitus, and aural fullness. It is associated with a fluid imbalance between the secretion of endolymph in the cochlear duct and its reabsorption into the subarachnoid space, leading to an accumulation of endolymph in the inner ear. Epidemiological evidence, including familial aggregation, indicates a genetic contribution and a consistent association with autoimmune diseases (AD). We conducted a case–control study in two phases using an immune genotyping array in a total of 420 patients with bilateral MD and 1,630 controls. We have identified the first locus, at 6p21.33, suggesting an association with bilateral MD [meta-analysis leading signal rs4947296, OR = 2.089 (1.661–2.627); p = 1.39 × 10−09]. Gene expression profiles of homozygous genotype-selected peripheral blood mononuclear cells (PBMCs) demonstrated that this region is a trans-expression quantitative trait locus (eQTL) in PBMCs. Signaling analysis predicted several tumor necrosis factor-related pathways, the TWEAK/Fn14 pathway being the top candidate (p = 2.42 × 10−11). This pathway is involved in the modulation of inflammation in several human AD, including multiple sclerosis, systemic lupus erythematosus, or rheumatoid arthritis. In vitro studies with genotype-selected lymphoblastoid cells from patients with MD suggest that this trans-eQTL may regulate cellular proliferation in lymphoid cells through the TWEAK/Fn14 pathway by increasing the translation of NF-κB. Taken together; these findings suggest that the carriers of the risk genotype may develop an NF-κB-mediated inflammatory response in MD.

A computational strategy for predicting lineage specifiers in stem cell subpopulations.

Stem cell differentiation is a complex biological event. Our understanding of this process is partly hampered by the co-existence of different cell subpopulations within a given population, which are characterized by different gene expression states driven by different underlying transcriptional regulatory networks (TRNs). Such cellular heterogeneity has been recently explored with the modern single-cell gene expression profiling technologies, such as single-cell RT-PCR and RNA-seq. However, the identification of cell subpopulation-specific TRNs and genes determining specific lineage commitment (i.e., lineage specifiers) remains a challenge due to the slower development of appropriate computational and experimental workflows. Here, we propose a computational method for predicting lineage specifiers for different cell subpopulations in binary-fate differentiation events. Our method first reconstructs subpopulation-specific TRNs, which is more realistic than reconstructing a single TRN representing multiple cell subpopulations. Then, it predicts lineage specifiers based on a model that assumes that each parental stem cell subpopulation is in a stable state maintained by its specific TRN stability core. In addition, this stable state is maintained in the parental cell subpopulation by the balanced gene expression pattern of pairs of opposing lineage specifiers for mutually exclusive different daughter cell subpopulations. To this end, we devised a statistical metric for identifying opposing lineage specifier pairs that show a significant ratio change upon differentiation. Application of this computational method to three different stem cell systems predicted known and putative novel lineage specifiers, which could be experimentally tested. Our method does not require pre-selection of putative candidate genes, and can be applied to any binary-fate differentiation system for which single-cell gene expression data are available. Furthermore, this method is compatible with both single-cell RT-PCR and single-cell RNA-seq data. Given the increasing importance of single-cell gene expression data in stem cell biology and regenerative medicine, approaches like ours would be useful for the identification of lineage specifiers and their associated TRN stability cores.

A systems biology approach to identify niche determinants of cellular phenotypes

Recent reports indicate a dominant role for cellular microenvironment or niche for stably maintaining cellular phenotypic states. Identification of key niche mediated signaling that maintains stem cells in specific phenotypic states remains a challenge, mainly due to the complex and dynamic nature of stem cell-niche interactions. In order to overcome this, we consider that stem cells maintain their phenotypic state by experiencing a constant effect created by the niche by integrating its signals via signaling pathways. Such a constant niche effect should induce sustained activation/inhibition of specific stem cell signaling pathways that controls the gene regulatory program defining the cellular phenotypic state. Based on this view, we propose a computational approach to identify the most likely receptor mediated signaling responsible for transmitting niche signals to the transcriptional regulatory network that maintain cell-specific gene expression patterns, termed as niche determinants. We demonstrate the utility of our method in different stem cell systems by identifying several known and novel niche determinants. Given the key role of niche in several degenerative diseases, identification of niche determinants can aid in developing strategies for potential applications in regenerative medicine.

Single-cell transcriptome analysis during cardiogenesis reveals basis for organ level developmental anomalies

Organogenesis involves integration of myriad cell types with reciprocal interactions, each progressing through successive stages of lineage specification and differentiation. Establishment of unique gene networks within each cell dictates fate determination, and mutations of transcription factors that drive such networks can result in birth defects. Congenital heart defects are the most common malformations and are caused by disruption of discrete subsets of progenitors1–3, however, determining the transcriptional changes in individual cells that lead to organ-level defects in the heart, or other organs, has not been tractable. Here, we employed single-cell RNA sequencing to interrogate early cardiac progenitor cells as they become specified during normal and abnormal cardiogenesis, revealing how dysregulation of specific cellular sub-populations can have catastrophic consequences. A network-based computational method for single-cell RNA-sequencing that predicts lineage specifying transcription factors4,5 identified Hand2 as a specifier of outflow tract cells but not right ventricular cells, despite failure of right ventricular formation in Hand2-null mice6. Temporal single-cell transcriptome analysis of Hand2-null embryos revealed failure of outflow tract myocardium specification, whereas right ventricular myocardium differentiated but failed to migrate into the anterior pole of the developing heart. Dysregulation of retinoic acid signaling, responsible for anterior-posterior patterning7, was associated with posteriorization of anterior cardiac progenitors in Hand2-null mutant hearts and ectopic atrial gene expression in outflow tract and right ventricle precursors. This work reveals transcriptional determinants in individual cells that specify cardiac progenitor cell fate and differentiation and exposes mechanisms of disrupted cardiac development at single-cell resolution, providing a framework to investigate congenital heart defects.

Signaling-Dependent Control of Apical Membrane Size and Self-Renewal in Rosette-Stage Human Neuroepithelial Stem Cells

Summary In the developing nervous system, neural stem cells are polarized and maintain an apical domain facing a central lumen. The presence of apical membrane is thought to have a profound influence on maintaining the stem cell state. With the onset of neurogenesis, cells lose their polarization, and the concomitant loss of the apical domain coincides with a loss of the stem cell identity. Little is known about the molecular signals controlling apical membrane size. Here, we use two neuroepithelial cell systems, one derived from regenerating axolotl spinal cord and the other from human embryonic stem cells, to identify a molecular signaling pathway initiated by lysophosphatidic acid that controls apical membrane size and consequently controls and maintains epithelial organization and lumen size in neuroepithelial rosettes. This apical domain size increase occurs independently of effects on proliferation and involves a serum response factor-dependent transcriptional induction of junctional and apical membrane components.