A single cell transcriptional roadmap for human pacemaker cell differentiation

Each heartbeat is triggered by the sinoatrial node, the natural pacemaker of the heart. Animal models have revealed that pacemaker cells share a common progenitor with the (pro)epicardium, and that the pacemaker cardiomyocytes further diversify into "transitional", "tail" and "head" subtypes. However, the underlying molecular mechanisms are poorly understood. Here, we studied the differentiation of human induced pluripotent stem cells into pacemaker cardiomyocytes. Single cell RNA sequencing identified the presence of myocardial populations resembling subtypes present in the formed sinoatrial node, and in addition revealed a side population of (pro)epicardial cells. Time-course trajectory analysis uncovered a role for WNT signaling in determining myocardial versus proepicardial cell fate. We experimentally demonstrate that presence of WNT signaling prior to the branching point of a common progenitor enhances proepicardial cell differentiation at the expense of myocardial pacemaker cells. Furthermore, we uncover a role for TGF? and WNT signaling in differentiation towards transitional and head pacemaker subtypes, respectively. Our findings provide new biological insights into human pacemaker differentiation, open avenues for complex disease modeling and inform regenerative approaches.

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Generative modeling of single-cell population time series for inferring cell differentiation landscapes

10.1101/2020.08.26.269332 ◽

2020 ◽

Author(s):

Grace H.T. Yeo ◽

Sachit D. Saksena ◽

David K. Gifford

Keyword(s):

Gene Expression ◽

Time Series ◽

Cell Differentiation ◽

Single Cell ◽

Cell Fate ◽

Lineage Tracing ◽

Model Framework ◽

Modeling Framework ◽

Generative Modeling ◽

Model Complex

SummaryExisting computational methods that use single-cell RNA-sequencing for cell fate prediction either summarize observations of cell states and their couplings without modeling the underlying differentiation process, or are limited in their capacity to model complex differentiation landscapes. Thus, contemporary methods cannot predict how cells evolve stochastically and in physical time from an arbitrary starting expression state, nor can they model the cell fate consequences of gene expression perturbations. We introduce PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative modeling framework that learns an underlying differentiation landscape from single-cell time-series gene expression data. Our generative model framework provides insight into the process of differentiation and can simulate differentiation trajectories for arbitrary gene expression progenitor states. We validate our method on a recently published experimental lineage tracing dataset that provides observed trajectories. We show that this model is able to predict the fate biases of progenitor cells in neutrophil/macrophage lineages when accounting for cell proliferation, improving upon the best-performing existing method. We also show how a model can predict trajectories for cells not found in the model’s training set, including cells in which genes or sets of genes have been perturbed. PRESCIENT is able to accommodate complex perturbations of multiple genes, at different time points and from different starting cell populations. PRESCIENT models are able to recover the expected effects of known modulators of cell fate in hematopoiesis and pancreatic β cell differentiation.

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Abstract 16005: Highly Efficient Derivation of Human Pacemaker Cells From Pluripotent Stem Cells in Chemically Defined Conditions

Circulation ◽

10.1161/circ.132.suppl_3.16005 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Zaniar Ghazizadeh ◽

Seyedeh Faranak Fattahi ◽

Mehdi Sharifi-tabar ◽

Shahab Mirshahvaladi ◽

Parisa Shabani ◽

...

Keyword(s):

Stem Cells ◽

Signaling Pathways ◽

Pluripotent Stem Cells ◽

Molecular Mechanisms ◽

Disease Modeling ◽

Conduction System ◽

Cardiac Conduction ◽

Substantial Contribution ◽

Cardiac Conduction System ◽

Pacemaker Cells

The cardiac conduction system is a complex network of cells that together orchestrate the rhythmic and coordinated depolarization of the heart. Dysfunction of the cardiac conduction system plays a central role in the pathogenesis of arrhythmia. While much progress has been made understanding cardiomyocyte differentiation, the molecular mechanisms regulating the specification and patterning of cells that form this conductive network is largely unknown. The LIM-homeodomain transcription factor ISL1 is highly expressed in the secondary heart field (SHF) progenitor population that makes a substantial contribution to the developing heart, comprising most cells in the right ventricle, both atria and pacemaker cells. Pacemaker cells comprise the most proximal component of the cardiac conduction system, which have been proposed as the source of most arrhythmogenic events. Their dominance on other spontaneous beating cell types makes them a suitable target for pharmacologic compounds, making access to this cell lineage necessary for the study of new therapeutic agents. To identify the signaling pathways that control the differentiation of human embryonic stem cell (hESC)-derived SHF cells into pacemaker cells, we performed RNA sequencing to compare the hESC-derived ISL1 + population, non-enriched population and undifferentiated hESCs. Furthermore, using a small molecule screen we identified compounds that can improve differentiation of hESCs toward pacemaker cells. Pathway analysis identified the Wnt pathway as the most significant regulator of SHF specification. Further differentiation of human pluripotent stem cells by stage-specific activation of BMP and WNT signaling pathways resulted in phenotypic pacemaker cells, which display morphological characteristics. More than 80% of these cells stained positively for HCN4, Contactin2(CNTN2) and GATA6, key markers of pacemaker cells. The differentiated cells express pacemaker markers, including CNTN2, TBX2, TBX3, HCN4, TBX18, GATA6 indicated by qRT-PCR. They show inward potassium currents through HCN channels in patch clamp experiments. Our data provides a new strategy to obtain human cardiac conduction cells in large scale for disease modeling, drug screening and cell therapy.

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Regulatory Potential of bHLH-Type Transcription Factors on the Road to Rubber Biosynthesis in Hevea brasiliensis

Plants ◽

10.3390/plants9060674 ◽

2020 ◽

Vol 9 (6) ◽

pp. 674

Author(s):

Tomoko Yamaguchi ◽

Yukio Kurihara ◽

Yuko Makita ◽

Emiko Okubo-Kurihara ◽

Ami Kageyama ◽

...

Keyword(s):

Cell Differentiation ◽

Natural Rubber ◽

Hevea Brasiliensis ◽

Time Course ◽

Molecular Mechanisms ◽

Cultured Cells ◽

Early Stage ◽

Rubber Biosynthesis ◽

On The Road

Natural rubber is the main component of latex obtained from laticifer cells of Hevea brasiliensis. For improving rubber yield, it is essential to understand the genetic molecular mechanisms responsible for laticifer differentiation and rubber biosynthesis. Jasmonate enhances both secondary laticifer differentiation and rubber biosynthesis. Here, we carried out time-course RNA-seq analysis in suspension-cultured cells treated with methyljasmonic acid (MeJA) to characterize the gene expression profile. Gene Ontology (GO) analysis showed that the term “cell differentiation” was enriched in upregulated genes at 24 h after treatment, but inversely, the term was enriched in downregulated genes at 5 days, indicating that MeJA could induce cell differentiation at an early stage of the response. Jasmonate signaling is activated by MYC2, a basic helix–loop–helix (bHLH)-type transcription factor (TF). The aim of this work was to find any links between transcriptomic changes after MeJA application and regulation by TFs. Using an in vitro binding assay, we traced candidate genes throughout the whole genome that were targeted by four bHLH TFs: Hb_MYC2-1, Hb_MYC2-2, Hb_bHLH1, and Hb_bHLH2. The latter two are highly expressed in laticifer cells. Their physical binding sites were found in the promoter regions of a variety of other TF genes, which are differentially expressed upon MeJA exposure, and rubber biogenesis-related genes including SRPP1 and REF3. These studies suggest the possibilities that Hb_MYC2-1 and Hb_MYC2-2 regulate cell differentiation and that Hb_bHLH1 and Hb_bHLH2 promote rubber biosynthesis. We expect that our findings will help to increase natural rubber yield through genetic control in the future.

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Generation, transcriptome profiling, and functional validation of cone-rich human retinal organoids

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1901572116 ◽

2019 ◽

Vol 116 (22) ◽

pp. 10824-10833 ◽

Cited By ~ 32

Author(s):

Sangbae Kim ◽

Albert Lowe ◽

Rachayata Dharmat ◽

Seunghoon Lee ◽

Leah A. Owen ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Cell Fate ◽

Time Course ◽

Transcriptome Profiling ◽

Retinal Cell ◽

Peripheral Retina ◽

Functional Validation ◽

Retinal Progenitor ◽

Retinal Differentiation

Rod and cone photoreceptors are light-sensing cells in the human retina. Rods are dominant in the peripheral retina, whereas cones are enriched in the macula, which is responsible for central vision and visual acuity. Macular degenerations affect vision the most and are currently incurable. Here we report the generation, transcriptome profiling, and functional validation of cone-rich human retinal organoids differentiated from hESCs using an improved retinal differentiation system. Induced by extracellular matrix, aggregates of hESCs formed single-lumen cysts composed of epithelial cells with anterior neuroectodermal/ectodermal fates, including retinal cell fate. Then, the cysts were en bloc-passaged, attached to culture surface, and grew, forming colonies in which retinal progenitor cell patches were found. Following gentle cell detachment, retinal progenitor cells self-assembled into retinal epithelium—retinal organoid—that differentiated into stratified cone-rich retinal tissue in agitated cultures. Electron microscopy revealed differentiating outer segments of photoreceptor cells. Bulk RNA-sequencing profiling of time-course retinal organoids demonstrated that retinal differentiation in vitro recapitulated in vivo retinogenesis in temporal expression of cell differentiation markers and retinal disease genes, as well as in mRNA alternative splicing. Single-cell RNA-sequencing profiling of 8-mo retinal organoids identified cone and rod cell clusters and confirmed the cone enrichment initially revealed by quantitative microscopy. Notably, cones from retinal organoids and human macula had similar single-cell transcriptomes, and so did rods. Cones in retinal organoids exhibited electrophysiological functions. Collectively, we have established cone-rich retinal organoids and a reference of transcriptomes that are valuable resources for retinal studies.

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Single-Cell Genomics: Catalyst for Cell Fate Engineering

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2021.748942 ◽

2021 ◽

Vol 9 ◽

Author(s):

Boxun Li ◽

Gary C. Hon

Keyword(s):

Single Cell ◽

Cell Fate ◽

Molecular Mechanisms ◽

Cell Types ◽

Cellular Heterogeneity ◽

State Transitions ◽

Small Scale ◽

Specific Cell ◽

Direct Reprogramming ◽

Cell State

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.

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Androgen action in cell fate and communication during prostate development at single-cell resolution

Development ◽

10.1242/dev.196048 ◽

2020 ◽

pp. dev.196048

Author(s):

Dong-Hoon Lee ◽

Adam W. Olson ◽

Jinhui Wang ◽

Won Kyung Kim ◽

Jiaqi Mi ◽

...

Keyword(s):

Single Cell ◽

Signaling Pathways ◽

Cell Fate ◽

Molecular Mechanisms ◽

Bud Formation ◽

Master Regulators ◽

Prostate Development ◽

Dynamic Cell ◽

Cell Signaling Networks

Androgens/androgen receptor (AR) mediated signaling pathways are essential for prostate development, morphogenesis, and regeneration. Specifically, stromal AR-signaling has been shown to be essential for prostatic initiation. However, the molecular mechanisms underlying AR-initiated mesenchymal-epithelial interactions in prostate development remain unclear. Here, using a newly generated mouse model, we directly addressed the fate and role of genetically marked AR-expressing cells during embryonic prostate development. Androgen signaling-initiated signaling pathways were identified in mesenchymal niche populations at single cell transcriptomic resolution. The dynamic cell-signaling networks regulated by stromal AR were characterized in regulating prostatic epithelial bud formation. Pseudotime analyses further revealed the differentiation trajectory and fate of AR-expressing cells in both prostatic mesenchymal and epithelial cell populations. Specifically, the cellular properties of Zeb1-expressing progenitors were assessed. Selective deletion of AR signaling in a subpopulation mesenchymal rather than epithelial cells dysregulates the expression of the master regulators and significantly impairs prostatic bud formation. These data provide novel, high-resolution evidence demonstrating the important role of mesenchymal androgen signaling as cellular niches controlling prostate early development by initiating dynamic mesenchyme-epithelia cell interactions.

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β-catenin Signaling Regulates Cell Fate Decisions at the Transition Zone of the Chondro-Osseous Junction During Fracture Healing

10.1101/2020.03.11.986141 ◽

2020 ◽

Author(s):

Sarah Anne Wong ◽

Diane Hu ◽

Tiffany Shao ◽

Erene Niemi ◽

Emilie Barruet ◽

...

Keyword(s):

Wnt Signaling ◽

Fracture Healing ◽

Cell Fate ◽

Molecular Mechanisms ◽

Lineage Tracing ◽

Fracture Callus ◽

Knock Out ◽

Marrow Cavity ◽

Cell Fate Decisions ◽

Wnt Ligands

AbstractChondrocytes within the fracture callus transform into osteoblasts during bone regeneration, but the molecular mechanisms regulating this process are unknown. Wnt ligands are expressed within the fracture callus, and hypertrophic chondrocytes undergoing transformation to osteoblasts exhibit nuclear localization of β-catenin, indicating active Wnt signaling in these cells. Here, we show that conditional knock out (cKO) of β-catenin in chondrocytes inhibits the transformation of chondrocytes to osteoblasts, while stabilization of β-catenin in chondrocytes accelerates this process. After cKO, chondrocyte-derived cells were located in the bone marrow cavity and upon re-fracture formed cartilage. Lineage tracing in wild type mice revealed that in addition to osteoblasts, chondrocytes give rise to stem cells that contribute to repair of subsequent fractures. These data indicate that Wnt signaling directs cell fate choices of chondrocytes during fracture healing by stimulating transformation of chondrocytes to osteoblasts, and provide a framework for developing Wnt-therapies to stimulate repair.

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Targeting Wnt Signaling through Small molecules in Governing Stem Cell Fate and Diseases

Endocrine Metabolic & Immune Disorders - Drug Targets ◽

10.2174/1871530319666190118103907 ◽

2019 ◽

Vol 19 (3) ◽

pp. 233-246 ◽

Cited By ~ 1

Author(s):

Antara Banerjee ◽

Ganesan Jothimani ◽

Suhanya Veronica Prasad ◽

Francesco Marotta ◽

Surajit Pathak

Keyword(s):

Stem Cells ◽

Stem Cell ◽

Wnt Signaling ◽

Small Molecules ◽

Signaling Pathway ◽

Cell Fate ◽

Wnt Pathway ◽

Molecular Mechanisms ◽

Wnt Signaling Pathway ◽

Stem Cell Fate

Background:The conserved Wnt/β-catenin signaling pathway is responsible for multiple functions including regulation of stem cell pluripotency, cell migration, self-renewability and cell fate determination. This signaling pathway is of utmost importance, owing to its ability to fuel tissue repair and regeneration of stem cell activity in diverse organs. The human adult stem cells including hematopoietic cells, intestinal cells, mammary and mesenchymal cells rely on the manifold effects of Wnt pathway. The consequences of any dysfunction or manipulation in the Wnt genes or Wnt pathway components result in specific developmental defects and may even lead to cancer, as it is often implicated in stem cell control. It is absolutely essential to possess a comprehensive understanding of the inhibition and/ or stimulation of the Wnt signaling pathway which in turn is implicated in determining the fate of the stem cells.Results:In recent years, there has been considerable interest in the studies associated with the implementation of small molecule compounds in key areas of stem cell biology including regeneration differentiation, proliferation. In support of this statement, small molecules have unfolded as imperative tools to selectively activate and inhibit specific developmental signaling pathways involving the less complex mechanism of action. These compounds have been reported to modulate the core molecular mechanisms by which the stem cells regenerate and differentiate.Conclusion:This review aims to provide an overview of the prevalent trends in the small molecules based regulation of stem cell fate via targeting the Wnt signaling pathway.

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ON SIMULATING THE GENERATION OF MOSAICISM DURING MAMMALIAN CEREBRAL CORTICAL DEVELOPMENT

Journal of Biological System ◽

10.1142/s0218339009002740 ◽

2009 ◽

Vol 17 (01) ◽

pp. 27-62 ◽

Cited By ~ 1

Author(s):

MICHAEL A. CASE ◽

HUGH R. MACMILLAN

Keyword(s):

Decision Making ◽

Single Cell ◽

Cell Fate ◽

Cell Population ◽

Cellular Response ◽

Molecular Mechanisms ◽

Cortical Development ◽

Coarse Grained ◽

Biological Organization ◽

Cellular Processes

Renewed calls for a systems biology reflect the hope hat enduring biological questions at single-cell and cell-population scales will be resolved as modern molecular biology, with its reductionist program, approaches a nearly-complete characterization of the molecular mechanisms of specific cellular processes. Due to the confounding complexity of biological organization across these scales, computational science is sought to complement the intuition of experimentalists. However, with respect to the molecular basis of cellular processes during development and disease, a gulf between feasible simulations and realistic biology persists. Formidable are the mathematical and computational challenges to conducting and validating cell population-scale simulations, drawn from single-cell level and molecular level details. Nonetheless, in some biological contexts, a focus on core processes crafted by evolution can yield coarse-grained mathematical models that retain explanatory potential despite drastic simplification of known biochemical kinetics. In this article, we bring this modeling philosophy to bear on the nature of neural progenitor cell decision making during mammalian cerebral cortical development. Specifically, we present the computational component to a research program addressing developmental links between (i) the cellular response to endogenous DNA damage, (ii) primary mechanisms of neuronal genetic heterogeneity, or mosaicism, and (iii) the cell fate decision making that defines the population kinetics of neurogenesis.

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SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions

10.1101/046110 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ning Leng ◽

Li-Fang Chu ◽

Jeea Choi ◽

Christina Kendziorski ◽

James A. Thomson ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Empirical Bayes ◽

Time Course ◽

Expression Patterns ◽

R Package ◽

Embryonic Cell ◽

Rna Seq ◽

Cell Fate Decisions ◽

Probability Estimates

AbstractMotivationWith the development of single cell RNA-seq (scRNA-seq) technology, scRNA-seq experiments with ordered conditions (e.g. time-course) are becoming common. Methods developed for analyzing ordered bulk RNA-seq experiments are not applicable to scRNA-seq, since their distributional assumptions are often violated by additional heterogeneities prevalent in scRNA-seq. Here we present SC-Pattern - an empirical Bayes model to characterize genes with expression changes in ordered scRNA-seq experiments. SCPattern utilizes the non-parametrical Kolmogorov-Smirnov statistic, thus it has the flexibility to identify genes with a wide variety of types of changes. Additionally, the Bayes framework allows SCPattern to classify genes into expression patterns with probability estimates.ResultsSimulation results show that SCPattern is well powered for identifying genes with expression changes while the false discovery rate is well controlled. SCPattern is also able to accurately classify these dynamic genes into directional expression patterns. Applied to a scRNA-seq time course dataset studying human embryonic cell differentiation, SCPattern detected a group of important genes that are involved in mesendoderm and definitive endoderm cell fate decisions, positional patterning, and cell cycle.Availability and ImplementationThe SCPattern is implemented as an R package along with a user-friendly graphical interface, which are available at:https://github.com/lengning/SCPatternContact:[email protected]

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