Single-cell reconstruction of differentiation trajectory reveals a critical role of ETS1 in human cardiac lineage commitment

LMNA -Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-derived iPSC Differentiation Support Cell type and Lineage-specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency

LMNA -Related Dilated Cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C ( LMNA ) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. Molecular mechanisms of disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA -Related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (4 Patient and 8 Control) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for Cardiac Progenitors to Cardiomyocytes (CM) and Epicardium-Derived Cells (EPDC). Data integration and comparative analyses of Patient and Control cells found cell type and lineage differentially expressed genes (DEG) with enrichment to support pathway dysregulation. Top DEG and enriched pathways included: 10 ZNF genes and RNA polymerase II transcription in Pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CM; LMNA and epigenetic regulation and DDIT4 and mTORC1 signaling in EPDC. Top DEG also included: XIST and other X-linked genes, six imprinted genes: SNRPN , PWAR6 , NDN , PEG10 , MEG3 , MEG8 , and enriched gene sets in metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.

Unsupervised analysis of whole transcriptome data from human pluripotent stem cells cardiac differentiation

The main objective of the present work was to highlight differences and similarities in gene expression patterns between different pluripotent stem cell cardiac differentiation protocols, using a workflow based on unsupervised machine learning algorithms to analyse the transcriptome of cells cultured as a 2D monolayer or as 3D aggregates. This unsupervised approach effectively allowed to portray the transcriptomic changes that occurred throughout the differentiation processes, with a visual representation of the entire transcriptome. The results allowed to corroborate previously reported data and also to unveil new gene expression patterns. In particular, it was possible to identify a correlation between low cardiomyocyte differentiation efficiencies and the early expression of a set of non-mesodermal genes, which can be further explored as predictive markers of differentiation efficiency. The workflow here developed can also be applied to analyse other stem cell differentiation transcriptomic datasets, envisaging future clinical implementation of cellular therapies.

Pressure overload-induced systolic heart failure is associated with characteristic myocardial microRNA expression signature and post-transcriptional gene regulation in male rats

Although systolic function characteristically shows gradual impairment in pressure overload (PO)-evoked left ventricular (LV) hypertrophy (LVH), rapid progression to congestive heart failure (HF) occurs in distinct cases. The molecular mechanisms for the differences in maladaptation are unknown. Here, we examined microRNA (miRNA) expression and miRNA-driven posttranscriptional gene regulation in the two forms of PO-induced LVH (with/without systolic HF). PO was induced by aortic banding (AB) in male Sprague-Dawley rats. Sham-operated animals were controls. The majority of AB animals demonstrated concentric LVH and slightly decreased systolic function (termed as ABLVH). In contrast, in some AB rats severely reduced ejection fraction, LV dilatation and increased lung weight-to-tibial length ratio was noted (referred to as ABHF). Global LV miRNA sequencing revealed fifty differentially regulated miRNAs in ABHF compared to ABLVH. Network theoretical miRNA-target analysis predicted more than three thousand genes with miRNA-driven dysregulation between the two groups. Seventeen genes with high node strength value were selected for target validation, of which five (Fmr1, Zfpm2, Wasl, Ets1, Atg16l1) showed decreased mRNA expression in ABHF by PCR. PO-evoked systolic HF is associated with unique miRNA alterations, which negatively regulate the mRNA expression of Fmr1, Zfmp2, Wasl, Ets1 and Atg16l1.

Single-cell transcriptomics for the assessment of cardiac disease

Cardiovascular disease is the leading cause of death globally. An advanced understanding of cardiovascular disease mechanisms is required to improve therapeutic strategies and patient risk stratification. State-of-the-art, large-scale, single-cell and single-nucleus transcriptomics facilitate the exploration of the cardiac cellular landscape at an unprecedented level, beyond its descriptive features, and can further our understanding of the mechanisms of disease and guide functional studies. In this Review, we provide an overview of the technical challenges in the experimental design of single-cell and single-nucleus transcriptomics studies, as well as a discussion of the type of inferences that can be made from the data derived from these studies. Furthermore, we describe novel findings derived from transcriptomics studies for each major cardiac cell type in both health and disease, and from development to adulthood. This Review also provides a guide to interpreting the exhaustive list of newly identified cardiac cell types and states, and highlights the consensus and discordances in annotation, indicating an urgent need for standardization. We describe advanced applications such as integration of single-cell data with spatial transcriptomics to map genes and cells on tissue and define cellular microenvironments that regulate homeostasis and disease progression. Finally, we discuss current and future translational and clinical implications of novel transcriptomics approaches, and provide an outlook of how these technologies will change the way we diagnose and treat heart disease.

Multimodal charting of molecular and functional cell states via in situ electro-sequencing

Paired mapping of single-cell gene expression and electrophysiology is essential to understand gene-to-function relationships in electrogenic tissues. Here, we developed in situ electro-sequencing (electro-seq) that combines flexible bioelectronics with in situ RNA sequencing to stably map millisecond-timescale electrical activity and profile single-cell gene expression from the same cells across intact biological networks, including cardiac and neural patches. When applied to human-induced pluripotent stem-cell-derived cardiomyocyte patches, in situ electro-seq enabled multimodal in situ analysis of cardiomyocyte electrophysiology and gene expression at the cellular level, jointly defining cell states and developmental trajectories. Using machine-learning-based cross-modal analysis, in situ electro-seq identified gene-to-electrophysiology relationships throughout cardiomyocyte development and accurately reconstructed the evolution of gene expression profiles based on long-term stable electrical measurements. In situ electro-seq could be applicable to create spatiotemporal multimodal maps in electrogenic tissues, potentiating the discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

Trajectory reconstruction identifies dysregulation of perinatal maturation programs in pluripotent stem cell-derived cardiomyocytes

A limitation in the application of pluripotent stem cell-derived cardiomyocytes (PSC-CMs) is the failure of these cells to achieve full functional maturity. The mechanisms by which directed differentiation differs from endogenous development, leading to consequent PSC-CM maturation arrest, remain unclear. Here, we generate a single-cell RNA sequencing (scRNA-seq) reference of mouse in vivo CM maturation with extensive sampling of previously difficult-to-isolate perinatal time periods. We subsequently generate isogenic embryonic stem cells to create an in vitro scRNA-seq reference of PSC-CM-directed differentiation. Through trajectory reconstruction, we identify an endogenous perinatal maturation program that is poorly recapitulated in vitro. By comparison with published human datasets, we identify a network of nine transcription factors (TFs) whose targets are consistently dysregulated in PSC-CMs across species. Notably, these TFs are only partially activated in common ex vivo approaches to engineer PSC-CM maturation. Our study can be leveraged toward improving the clinical viability of PSC-CMs.

Single-cell RNA sequencing reveals maturation trajectory in human pluripotent stem cell-derived cardiomyocytes in engineered tissues

Cardiac in vitro models have become increasingly obtainable and affordable with the optimization of human pluripotent stem cell-derived cardiomyocyte (hPSC-CM) differentiation. However, these CMs are immature compared to their in vivo counterparts. Here we study the cellular phenotype of hPSC-CMs by comparing their single-cell gene expression and functional profiles in three engineered cardiac tissue configurations: human ventricular (hv) cardiac anisotropic sheet, cardiac tissue strip, and cardiac organoid chamber (hvCOC), with spontaneously aggregated 3D cardiac spheroids (CS) as control. The CM maturity was found to increase with increasing levels of complexity of the engineered tissues from CS to hvCOC. The contractile components are the first function to mature, followed by electrophysiology and oxidative metabolism. Notably, the 2D tissue constructs show a higher cellular organization whereas metabolic maturity preferentially increases in the 3D constructs. We conclude that the tissue engineering models resembling configurations of native tissues may be reliable for drug screening or disease modeling.

Single-cell transcriptomes in the heart: when every epigenome counts

The response of an organ to stimuli emerges from the actions of individual cells. Recent cardiac single-cell RNA-sequencing studies of development, injury, and reprogramming have uncovered heterogeneous populations even among previously well-defined cell types, raising questions about what level of experimental resolution corresponds to disease-relevant, tissue-level phenotypes. In this review, we explore the biological meaning behind this cellular heterogeneity by undertaking an exhaustive analysis of single-cell transcriptomics in the heart (including a comprehensive, annotated compendium of studies published to date) and evaluating new models for the cardiac function that have emerged from these studies (including discussion and schematics that depict new hypotheses in the field). We evaluate the evidence to support the biological actions of newly identified cell populations and debate questions related to the role of cell-to-cell variability in development and disease. Finally, we present emerging epigenomic approaches that, when combined with single-cell RNA-sequencing, can resolve basic mechanisms of gene regulation and variability in cell phenotype.

Models of Congenital Adrenal Hyperplasia for Gene Therapies Testing

The adrenal glands are important endocrine organs that play a major role in the stress response. Some adrenal glands abnormalities are treated with hormone replacement therapy, which does not address physiological requirements. Modern technologies make it possible to develop gene therapy drugs that can completely cure diseases caused by mutations in specific genes. Congenital adrenal hyperplasia (CAH) is an example of such a potentially treatable monogenic disease. CAH is an autosomal recessive inherited disease with an overall incidence of 1:9500–1:20,000 newborns. To date, there are several promising drugs for CAH gene therapy. At the same time, it remains unclear how new approaches can be tested, as there are no models for this disease. The present review focuses on modern models for inherited adrenal gland insufficiency and their detailed characterization. In addition, the advantages and disadvantages of various pathological models are discussed, and ways of further development are suggested.

Copy-number variation in congenital heart disease

Genomic copy-number variants (CNVs) contribute to as many congenital heart disease (CHD) cases (10-15%) as chromosomal aberrations or single-gene mutations and influence clinical outcomes. CNVs in a few genomic hotspots (1q21.1, 2q13, 8p23.1, 11q24, 15q11.2, 16p11.2, and 22q11.2) are recurrently enriched in CHD cohorts and affect dosage-sensitive transcriptional regulators that are required for cardiac development. Reduced penetrance and pleiotropic effects on brain and heart development are common features of these CNVs. Therefore, additional genetic 'hits,' such as a second CNV or gene mutation, are probably required to cause CHD in most cases. Integrative analysis of CNVs, genome sequence, epigenetic alterations, and gene function will be required to delineate the complete genetic landscape of CHD.

Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis

Objective: Sepsis is a common disease in internal medicine, with a high incidence and dangerous condition. Due to the limited understanding of its pathogenesis, the prognosis is poor. The goal of this project is to screen potential biomarkers for the diagnosis of sepsis and to identify competitive endogenous RNA (ceRNA) networks associated with sepsis.

Methods: The expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) were derived from the Gene Expression Omnibus (GEO) dataset. The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were screened by bioinformatics analysis. DEmRNAs were analyzed by protein-protein interaction (PPI) network analysis, transcription factor enrichment analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Set Enrichment Analysis (GSEA). After the prediction of the relevant database, the competitive ceRNA network is built in Cytoscape. The gene-drug interaction was predicted by DGIgb. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm five lncRNAs from the ceRNA network.

Results: Through Venn diagram analysis, we found that 57 DElncRNAs, 6 DEmiRNAs and 317 DEmRNAs expressed abnormally in patients with sepsis. GO analysis and KEGG pathway analysis showed that 789 GO terms and 36 KEGG pathways were enriched. Through intersection analysis and data mining, 5 key KEGG pathways and related core genes were revealed by GSEA. The PPI network consists of 247 nodes and 1,163 edges, and 50 hub genes are screened by the MCODE plug-in. In addition, there are 5 DElncRNAs, 6 DEmiRNAs and 28 DEmRNAs in the ceRNA network. Drug action analysis showed that 7 genes were predicted to be molecular targets of drugs. Five lncRNAs in ceRNA network are verified by qRT-PCR, and the results showed that the relative expression of five lncRNAs was significantly different between sepsis patients and healthy control subjects.

Conclusion: A sepsis-specific ceRNA network has been effectively created, which is helpful to understand the interaction between lncRNAs, miRNAs and mRNAs. We discovered prospective sepsis peripheral blood indicators and proposed potential treatment medicines, providing new insights into the progression and development of sepsis.

Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research

With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.

CFIm25 regulates human stem cell function independently of its role in mRNA alternative polyadenylation

It has recently been shown that CFIm25, a canonical mRNA 3’ processing factor, could play a variety of physiological roles through its molecular function in the regulation of mRNA alternative polyadenylation (APA). Here, we used CRISPR/Cas9-mediated gene editing approach in human embryonic stem cells (hESCs) for CFIm25, and obtained three gene knockdown/mutant cell lines. CFIm25 gene editing resulted in higher proliferation rate and impaired differentiation potential for hESCs, with these effects likely to be directly regulated by the target genes, including the pluripotency factor rex1. Mechanistically, we unexpected found that perturbation in CFIm25 gene expression did not significantly affect cellular mRNA 3’ processing efficiency and APA profile. Rather, we provided evidences that CFIm25 may impact RNA polymerase II (RNAPII) occupancy at the body of transcribed genes, and promote the expression level of a group of transcripts associated with cellular proliferation and/or differentiation. Taken together, these results reveal novel mechanisms underlying CFIm25ʹs modulation in determination of cell fate, and provide evidence that the process of mammalian gene transcription may be regulated by an mRNA 3’ processing factor.

Deciphering Cardiac Biology and Disease by Single-Cell Transcriptomic Profiling

By detecting minute molecular changes in hundreds to millions of single cells, single-cell RNA sequencing allows for the comprehensive characterization of the diversity and dynamics of cells in the heart. Our understanding of the heart has been transformed through the recognition of cellular heterogeneity, the construction of regulatory networks, the building of lineage trajectories, and the mapping of intercellular crosstalk. In this review, we introduce cardiac progenitors and their transcriptional regulation during embryonic development, highlight cellular heterogeneity and cell subtype functions in cardiac health and disease, and discuss insights gained from the study of pluripotent stem-cell-derived cardiomyocytes.

CpG site hypomethylation at ETS1‑binding region regulates DLK1 expression in Chinese patients with Tetralogy of Fallot

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart malformation accounting for ~10% of cases. Although the pathogenesis of TOF is complex and largely unknown, epigenetics plays a huge role, specifically DNA methylation. The protein δ like non-canonical Notch ligand 1 (DLK1) gene encodes a non-canonical ligand of the Notch signaling pathway, which is involved in heart development. However, the epigenetic mechanism of DLK1 in the pathogenesis of TOF is yet to be elucidated. Therefore, the present study aimed to clarify its specific mechanism. In this study, immunohistochemistry was used to detect the protein expression of DLK1 and the methylation status of the DLK1 promoter was measured via bisulfite sequencing PCR. Dual-luciferase reporter assays were performed to examine the influence of transcription factor ETS proto-oncogene 1 (ETS1) on DLK1 gene expression. The electrophoretic mobility shift assay and chromatin immunoprecipitation assay, both in vivo and in vitro, were used to verify the binding of the ETS1 transcription factor to the DLK1 promoter as well as the influence of methylation status of DLK1 promoter on this binding affinity. The expression of DLK1 in the right ventricular outflow tract was significantly lower in patients with Tetralogy of Fallot (TOF) than that in controls (P<0.001). Moreover, the methylation level of CpG site 10 and CpG site 11 in the DLK1_R region was significantly decreased in TOF cases compared with controls (P<0.01). The integral methylation levels of DLK1_R and the methylation status of the CpG site 11 were both positively associated with DLK1 protein expression in TOF cases. ETS1 was found to inhibit DLK1 transcriptional activity by binding to the CpG site 11 and this affinity could be influenced by the methylation level of the DLK1 promoter. These findings demonstrated that the hypomethylation of the DLK1 promoter could increase the binding affinity of ETS1 transcription factor, which in turn inhibited DLK1 gene transcriptional activity and contributed to the development of TOF.

Single-Cell RNA Sequencing (scRNA-seq) in Cardiac Tissue: Applications and Limitations

Cardiovascular diseases (CVDs) are a group of disorders of the blood vessels and heart, which are considered as the leading causes of death worldwide. The pathology of CVDs could be related to the functional abnormalities of multiple cell types in the heart. Single-cell RNA sequencing (scRNA-seq) technology is a powerful method for characterizing individual cells and elucidating the molecular mechanisms by providing a high resolution of transcriptomic changes at the single-cell level. Specifically, scRNA-seq has provided novel insights into CVDs by identifying rare cardiac cell types, inferring the trajectory tree, estimating RNA velocity, elucidating the cell-cell communication, and comparing healthy and pathological heart samples. In this review, we summarize the different scRNA-seq platforms and published single-cell datasets in the cardiovascular field, and describe the utilities and limitations of this technology. Lastly, we discuss the future perspective of the application of scRNA-seq technology into cardiovascular research.

Single-cell analysis at the protein level delineates intracellular signaling dynamic during hematopoiesis

BACKGROUND

Hematopoietic stem and progenitor cell (HSPC) subsets in mice have previously been studied using cell surface markers, and more recently single-cell technologies. The recent revolution of single-cell analysis is substantially transforming our understanding of hematopoiesis, confirming the substantial heterogeneity of cells composing the hematopoietic system. While dynamic molecular changes at the DNA/RNA level underlying hematopoiesis have been extensively explored, a broad understanding of single-cell heterogeneity in hematopoietic signaling programs and landscapes, studied at protein level and reflecting post-transcriptional processing, is still lacking. Here, we accurately quantified the intracellular levels of 9 phosphorylated and 2 functional proteins at the single-cell level to systemically capture the activation dynamics of 8 signaling pathways, including EGFR, Jak/Stat, NF-κB, MAPK/ERK1/2, MAPK/p38, PI3K/Akt, Wnt, and mTOR pathways, during mouse hematopoiesis using mass cytometry.

RESULTS

With fine-grained analyses of 3.2 million of single hematopoietic stem and progenitor cells (HSPCs), and lineage cells in conjunction with multiparameter cellular phenotyping, we mapped trajectories of signaling programs during HSC differentiation and identified specific signaling biosignatures of cycling HSPC and multiple differentiation routes from stem cells to progenitor and lineage cells. We also investigated the recovery pattern of hematopoietic cell populations, as well as signaling regulation in these populations, during hematopoietic reconstruction. Overall, we found substantial heterogeneity of pathway activation within HSPC subsets, characterized by diverse patterns of signaling.

CONCLUSIONS

These comprehensive single-cell data provide a powerful insight into the intracellular signaling-regulated hematopoiesis and lay a solid foundation to dissect the nature of HSC fate decision. Future integration of transcriptomics and proteomics data, as well as functional validation, will be required to verify the heterogeneity in HSPC subsets during HSC differentiation and to identify robust markers to phenotype those HSPC subsets.

Multiomic Approaches to Uncover the Complexities of Dystrophin-Associated Cardiomyopathy

Despite major progress in treating skeletal muscle disease associated with dystrophinopathies, cardiomyopathy is emerging as a major cause of death in people carrying dystrophin gene mutations that remain without a targeted cure even with new treatment directions and advances in modelling abilities. The reasons for the stunted progress in ameliorating dystrophin-associated cardiomyopathy (DAC) can be explained by the difficulties in detecting pathophysiological mechanisms which can also be efficiently targeted within the heart in the widest patient population. New perspectives are clearly required to effectively address the unanswered questions concerning the identification of authentic and effectual readouts of DAC occurrence and severity. A potential way forward to achieve further therapy breakthroughs lies in combining multiomic analysis with advanced preclinical precision models. This review presents the fundamental discoveries made using relevant models of DAC and how omics approaches have been incorporated to date.

A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes

We performed a comprehensive analysis of the transcriptional changes occurring during human induced pluripotent stem cell (hiPSC) differentiation to cardiomyocytes. Using single cell RNA-seq, we sequenced > 20,000 single cells from 55 independent samples representing two differentiation protocols and multiple hiPSC lines. Samples included experimental replicates ranging from undifferentiated hiPSCs to mixed populations of cells at D90 post-differentiation. Differentiated cell populations clustered by time point, with differential expression analysis revealing markers of cardiomyocyte differentiation and maturation changing from D12 to D90. We next performed a complementary cluster-independent sparse regression analysis to identify and rank genes that best assigned cells to differentiation time points. The two highest ranked genes between D12 and D24 (MYH7 and MYH6) resulted in an accuracy of 0.84, and the three highest ranked genes between D24 and D90 (A2M, H19, IGF2) resulted in an accuracy of 0.94, revealing that low dimensional gene features can identify differentiation or maturation stages in differentiating cardiomyocytes. Expression levels of select genes were validated using RNA FISH. Finally, we interrogated differences in cardiac gene expression resulting from two differentiation protocols, experimental replicates, and three hiPSC lines in the WTC-11 background to identify sources of variation across these experimental variables.

Myosin light chain 2 marks differentiating ventricular cardiomyocytes derived from human embryonic stem cells

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have great value for studies of human cardiac development, drug discovery, disease modeling, and cell therapy. However, the mixed cardiomyocyte subtypes (ventricular-, atrial-, and nodal-like myocytes) and the maturation heterogeneity of hPSC-CMs restrain their application in vitro and in vivo. Myosin light chain 2 (MYL2, encoding the ventricular/cardiac muscle isoform MLC2v protein) is regarded as a ventricular-specific marker of cardiac myocardium; however, its restricted localization to ventricles during human heart development has been questioned. Consequently, it is currently unclear whether MYL2 definitively marks ventricular hESC-CMs. Here, by using a MYL2-Venus hESC reporter line, we characterized a time-dependent increase of the MYL2-Venus positive (MLC2v-Venus⁺) hESC-CMs during differentiation. We also compared the molecular, cellular, and functional properties between the MLC2v-Venus⁺ and MYL2-Venus negative (MLC2v-Venus^-) hESC-CMs. At early differentiation stages of hESC-CMs, we reported that both MLC2v-Venus^- and MLC2v-Venus⁺ CMs displayed ventricular-like traits but the ventricular-like cells from MLC2v-Venus⁺ hESC-CMs displayed more developed action potential (AP) properties than that from MLC2v-Venus^- hESC-CMs. Meanwhile, about a half MLC2v-Venus^- hESC-CM population displayed atrial-like AP properties, and a half showed ventricular-like AP properties, whereas only ~ 20% of the MLC2v-Venus^- hESC-CMs expressed the atrial marker nuclear receptor subfamily 2 group F member 2 (NR2F2, also named as COUPTFII). At late time points, almost all MLC2v-Venus⁺ hESC-CMs exhibited ventricular-like AP properties. Further analysis demonstrates that the MLC2v-Venus⁺ hESC-CMs had enhanced Ca²⁺ transients upon increase of the MLC2v level during cultivation. Concomitantly, the MLC2v-Venus⁺ hESC-CMs showed more defined sarcomeric structures and better mitochondrial function than those in the MLC2v-Venus^- hESC-CMs. Moreover, the MLC2v-Venus⁺ hESC-CMs were more sensitive to hypoxic stimulus than the MLC2v-Venus^- hESC-CMs. These results provide new insights into the development of human ventricular myocytes and reveal a direct correlation between the expression profile of MLC2v and ventricular hESC-CM development. Our findings that MLC2v is predominantly a ventricular marker in developmentally immature hESC-CMs have implications for human development, drug screening, and disease modeling, and this marker should prove useful in overcoming issues associated with hESC-CM heterogeneity.

Ex uno, plures-From One Tissue to Many Cells: A Review of Single-Cell Transcriptomics in Cardiovascular Biology

Recent technological advances have revolutionized the study of tissue biology and garnered a greater appreciation for tissue complexity. In order to understand cardiac development, heart tissue homeostasis, and the effects of stress and injury on the cardiovascular system, it is essential to characterize the heart at high cellular resolution. Single-cell profiling provides a more precise definition of tissue composition, cell differentiation trajectories, and intercellular communication, compared to classical bulk approaches. Here, we aim to review how recent single-cell multi-omic studies have changed our understanding of cell dynamics during cardiac development, and in the healthy and diseased adult myocardium.

Reading the heart at single-cell resolution

The burgeoning field of single-cell transcriptomics augments our ability to scrutinize organ systems at unprecedented resolutions. Single-cell RNA sequencing (scRNA-seq) and analytical techniques have shed light on the cellular heterogeneity, developmental trajectories, intercellular communications of the cardiac system, and thus contributed much to the understanding of cardiac development, homeostasis and disorders. Although generalized protocols are well established for scRNA-seq pipelines, customized sample preparation, quality control, and data interpretation are still needed in cardiac research. In this article, we highlight major steps that impact data quality in scRNA-seq experiments, with particular focus on sample and data processing of cardiomyocytes. We also summarize popular applications of scRNA-seq, outlining general tools, caveats and examples in cardiac research.

The Importance of Computational Modeling in Stem Cell Research

The generation of large amounts of omics data is increasingly enabling not only the processing and analysis of large data sets but also the development of computational models in the field of stem cell research. Although computational models have been proposed in recent decades, we believe that the stem cell community is not fully aware of the potentiality of computational modeling in guiding their experimental research. In this regard, we discuss how single-cell technologies provide the right framework for computational modeling at different scales of biological organization in order to address challenges in the stem cell field and to guide experimentalists in the design of new strategies for stem cell therapies and treatment of congenital disorders.

Transcriptional Profiling of Single Cardiomyocytes in Health and Disease

PURPOSE OF REVIEW

Cardiomyocytes are the chief cell type in the heart, and are central to the pathogenesis of many cardiac diseases. Increasing recognition of its cellular, molecular, and functional heterogeneity prompted us to review the latest advancements in cardiac health and disease at single-cell resolution.

RECENT FINDINGS

Single-cell RNA profiling of cardiac lineage commitment events uncovered immense heterogeneity amongst ostensibly homogeneous cell populations. Classic cardiac transcription factors and new regulatory genes exhibit cell subtype-specific and temporally controlled expression patterns that serve the phenotypic changes in development, disease progression, and regeneration. Dissection of dynamically changing cell-cell communications and cardiac cell plasticity offers new opportunities in disease intervention and cardiac repair. Finally, updates in research models, platforms, and pipelines are continuously increasing the efficiency and reliability in data generation and interpretation. Transcriptional profiling of cardiac lineage cells, especially cardiomyocytes, has tremendously enriched our knowledge of the cellular milieu and the transcriptional network in the heart. Implementing technical standards and interrogating underexplored research areas will further our understanding of this organ and increase the likelihood of finding tractable therapeutic targets.

Trajectory mapping of human embryonic stem cell cardiogenesis reveals lineage branch points and an ISL1 progenitor-derived cardiac fibroblast lineage

A family of multipotent heart progenitors plays a central role in the generation of diverse myogenic and nonmyogenic lineages in the heart. Cardiac progenitors in particular play a significant role in lineages involved in disease, and have also emerged to be a strong therapeutic candidate. Based on this premise, we aimed to deeply characterize the progenitor stage of cardiac differentiation at a single-cell resolution. Integrated comparison with an embryonic 5-week human heart transcriptomic dataset validated lineage identities with their late stage in vitro counterparts, highlighting the relevance of an in vitro differentiation for progenitors that are developmentally too early to be accessed in vivo. We utilized trajectory mapping to elucidate progenitor lineage branching points, which are supported by RNA velocity. Nonmyogenic populations, including cardiac fibroblast-like cells and endoderm, were found, and we identified TGFBI as a candidate marker for human cardiac fibroblasts in vivo and in vitro. Both myogenic and nonmyogenic populations express ISL1, and its loss redirected myogenic progenitors into a neural-like fate. Our study provides important insights into processes during early heart development.

Single-cell analysis of murine fibroblasts identifies neonatal to adult switching that regulates cardiomyocyte maturation

Cardiac maturation lays the foundation for postnatal heart development and disease, yet little is known about the contributions of the microenvironment to cardiomyocyte maturation. By integrating single-cell RNA-sequencing data of mouse hearts at multiple postnatal stages, we construct cellular interactomes and regulatory signaling networks. Here we report switching of fibroblast subtypes from a neonatal to adult state and this drives cardiomyocyte maturation. Molecular and functional maturation of neonatal mouse cardiomyocytes and human embryonic stem cell-derived cardiomyocytes are considerably enhanced upon co-culture with corresponding adult cardiac fibroblasts. Further, single-cell analysis of in vivo and in vitro cardiomyocyte maturation trajectories identify highly conserved signaling pathways, pharmacological targeting of which substantially delays cardiomyocyte maturation in postnatal hearts, and markedly enhances cardiomyocyte proliferation and improves cardiac function in infarcted hearts. Together, we identify cardiac fibroblasts as a key constituent in the microenvironment promoting cardiomyocyte maturation, providing insights into how the manipulation of cardiomyocyte maturity may impact on disease development and regeneration.

Novel insights into cardiac regeneration based on differential fetal and adult ovine heart transcriptomic analysis

The adult mammalian cardiomyocyte has a very limited capacity to reenter the cell cycle and advance into mitosis. Therefore, diseases characterized by lost contractile tissue usually evolve into myocardial remodeling and heart failure. Analyzing the cardiac transcriptome at different developmental stages in a large mammal closer to the human than laboratory rodents may serve to disclose positive and negative cardiomyocyte cell cycle regulators potentially targetable to induce cardiac regeneration in the clinical setting. Thus we aimed at characterizing the transcriptomic profiles of the early fetal, late fetal, and adult sheep heart by employing RNA-seq technique and bioinformatic analysis to detect protein-encoding genes that in some of the stages were turned off, turned on, or differentially expressed. Genes earlier proposed as positive cell cycle regulators such as cyclin A, cdk2, meis2, meis3, and PCNA showed higher expression in fetal hearts and lower in AH, as expected. In contrast, genes previously proposed as cell cycle inhibitors, such as meis1, p16, and sav1, tended to be higher in fetal than in adult hearts, suggesting that these genes are involved in cell processes other than cell cycle regulation. Additionally, we described Gene Ontology (GO) enrichment of different sets of genes. GO analysis revealed that differentially expressed gene sets were mainly associated with metabolic and cellular processes. The cell cycle-related genes fam64a, cdc20, and cdk1, and the metabolism-related genes pitx and adipoq showed strong differential expression between fetal and adult hearts, thus being potent candidates to be targeted in human cardiac regeneration strategies.NEW & NOTEWORTHY We characterized the transcriptomic profiles of the fetal and adult sheep hearts employing RNAseq technique and bioinformatic analyses to provide sets of transcripts whose variation in expression level may link them to a specific role in cell cycle regulation. It is important to remark that this study was performed in a large mammal closer to humans than laboratory rodents. In consequence, the results can be used for further translational studies in cardiac regeneration.

Single-Cell Reconstruction of Progression Trajectory Reveals Intervention Principles in Pathological Cardiac Hypertrophy

BACKGROUND

Pressure overload-induced pathological cardiac hypertrophy is a common predecessor of heart failure, the latter of which remains a major cardiovascular disease with increasing incidence and mortality worldwide. Current therapeutics typically involve partially relieving the heart's workload after the onset of heart failure. Thus, more pathogenesis-, stage-, and cell type-specific treatment strategies require refined dissection of the entire progression at the cellular and molecular levels.

METHODS

By analyzing the transcriptomes of 11,492 single cells and identifying major cell types, including both cardiomyocytes and noncardiomyocytes, on the basis of their molecular signatures, at different stages during the progression of pressure overload-induced cardiac hypertrophy in a mouse model, we characterized the spatiotemporal interplay among cell types, and tested potential pharmacological treatment strategies to retard its progression in vivo.

RESULTS

We illustrated the dynamics of all major cardiac cell types, including cardiomyocytes, endothelial cells, fibroblasts, and macrophages, as well as those of their respective subtypes, during the progression of disease. Cellular crosstalk analysis revealed stagewise utilization of specific noncardiomyocytes during the deterioration of heart function. Specifically, macrophage activation and subtype switching, a key event at middle-stage of cardiac hypertrophy, was successfully targeted by Dapagliflozin, a sodium glucose cotransporter 2 inhibitor, in clinical trials for patients with heart failure, as well as TD139 and Arglabin, two anti-inflammatory agents new to cardiac diseases, to preserve cardiac function and attenuate fibrosis. Similar molecular patterns of hypertrophy were also observed in human patient samples of hypertrophic cardiomyopathy and heart failure.

CONCLUSIONS

Together, our study not only illustrated dynamically changing cell type crosstalk during pathological cardiac hypertrophy but also shed light on strategies for cell type- and stage-specific intervention in cardiac diseases.