Single-cell RNA sequencing in cardiovascular development, disease and medicine

scRCA: A Siamese network-based pipeline for annotating cell types using noisy single-cell RNA-seq reference data

Accurate cell type annotation is fundamentally critical for single-cell sequencing (scRNA-seq) data analysis to provide insightful knowledge of tissue-specific cell heterogeneity and cell state transition tracking. Cell type annotation is usually conducted by comparative analysis with known data (i.e., reference) - which contains a presumably accurate representation of cell types. However, this assumption is often problematic, as factors such as human errors in wet-lab experiments and methodological limitations can introduce annotation errors in the reference dataset. As current pipelines for single-cell transcriptomic analysis do not adequately consider this challenge, there is a major demand for constructing a computational pipeline that achieves high-quality cell type annotation using reference datasets containing inherent errors (referred to as "noise" in this study). Here, we built a Siamese network-based pipeline, termed scRCA, to accurately annotate cell types based on noisy reference data. To help users evaluate the reliability of scRCA annotations, an interpreter was also developed to explore the factors underlying the model's predictions. Our experiments demonstrate that, across 14 datasets, scRCA outperformed other widely adopted reference-based methods for cell type annotation. Using an independent dataset of four multiple myeloma patients, we further illustrated that scRCA can distinguish cancerous cells based on gene expression levels and identify genes closely associated with multiple myeloma through scRCA's interpretable module, providing significant information for subsequent clinical treatments. With these advancements, we anticipate that scRCA will serve as a practical reference-based approach for accurate annotating cell type annotation.

KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics

KanCell is a deep learning model based on Kolmogorov-Arnold networks (KAN) designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics (ST) data. ST technologies provide insights into gene expression within tissue context, revealing cellular interactions and microenvironments. To fully leverage this potential, effective computational models are crucial. We evaluate KanCell on both simulated and real datasets from technologies such as STARmap, Slide-seq, Visium, and Spatial Transcriptomics. Our results demonstrate that KanCell outperforms existing methods across metrics like PCC, SSIM, COSSIM, RMSE, JSD, ARS, and ROC, with robust performance under varying cell numbers and background noise. Real-world applications on human lymph nodes, hearts, melanoma, breast cancer, dorsolateral prefrontal cortex, and mouse embryo brains confirmed its reliability. Compared with traditional approaches, KanCell effectively captures non-linear relationships and optimizes computational efficiency through KAN, providing an accurate and efficient tool for ST. By improving data accuracy and resolving cell type composition, KanCell reveals cellular heterogeneity, clarifies disease microenvironments, and identifies therapeutic targets, addressing complex biological challenges.

Exploring Origin-Dependent Susceptibility of Smooth Muscle Cells to Aortic Diseases Through Intersectional Genetics

BACKGROUND

The developmental diversity among smooth muscle cells (SMCs) plays a crucial role in segment-specific aortic diseases. However, traditional genetic approaches are inadequate for enabling in vivo analysis of disease susceptibility associated with cellular origin. There is an urgent need to build genetic technologies that target different developmental origins to investigate the mechanisms of aortopathies, thereby facilitating the development of effective therapeutics.

METHODS

To address this challenge, we developed an advanced dual recombinase-mediated intersectional genetic system, specifically designed to precisely target SMCs from various developmental origins in mice. Specifically, we used Isl1-Dre, Wnt1-Dre, Meox1-DreER, and Upk3b-Dre to target SMC progenitors from the second heart field, cardiac neural crest, somites, and mesothelium, respectively. This system was combined with single-cell RNA sequencing to investigate the impact of TGF-β (transforming growth factor-β) signaling in different segments of the aorta by selectively knocking out Tgfbr2 in the ascending aorta and Smad4 in the aortic arch, respectively.

RESULTS

Through intersectional genetic approaches, we use the Myh11-Cre(ER) driver along with origin-specific Dre drivers to trace cells of diverse developmental origins within the SMC population. We found that a deficiency of Tgfbr2 in SMCs of the ascending aorta leads to aneurysm formation in this specific region. We also demonstrate the critical role of Smad4 in preserving aortic wall integrity and homeostasis in SMCs of the aortic arch.

CONCLUSIONS

Our approach to genetically targeting SMC subtypes provides a novel platform for exploring origin-dependent or location-specific aortic vascular diseases. This genetic system enables comprehensive analysis of contributions from different cell lineages to SMC behavior and pathology, thereby paving the way for targeted research and therapeutic interventions in the future.

Deciphering immune cell heterogeneity in vascular diseases: Insights from single-cell sequencing

The complexity and diversity of vascular diseases highlight the urgent need to study their pathogenesis, particularly the key role of immune cell-mediated inflammatory responses in their development. While previous reviews have outlined the involvement of immune cells in vascular pathology, a comprehensive understanding of their dynamic changes, functional states, and intercellular interactions remains incomplete. Recent advances in single-cell sequencing (SCS) have provided unprecedented insights into immune cell heterogeneity, enabling the identification of novel subpopulations and their roles in disease progression.This review extends prior work by systematically summarizing the latest applications of SCS in vascular diseases, highlighting newly discovered immune cell subsets, their interactions, and their impact on vascular pathology. By addressing current gaps in the literature-such as the functional plasticity of immune cells and their temporal dynamics-this review offers new perspectives on immune-mediated mechanisms in vascular diseases and proposes novel therapeutic strategies for their prevention and treatment.

Construction of a deep learning model and identification of the pivotal characteristics of FGF7- and MGST1- positive fibroblasts in heart failure post-myocardial infarction

Dysregulation of fibroblast function is closely associated with the occurrence of heart failure after myocardial infarction (post-MI HF). Myocardial fibrosis is a detrimental consequence of aberrant fibroblast activation and extracellular matrix deposition following myocardial infarction (MI). However, the heterogeneity of fibroblasts in normal cardiac tissue and heart failure tissue remains to be further investigated. We discovered that the abundance of FGF7+MGST1+ fibroblasts were down-regulated in post-MI HF according to scRNA-seq analysis. Key gene characteristics of FGF7+MGST1+ fibroblasts were uncovered through both differential expression analysis and hdWGCNA pipeline. Pseudotime analysis revealed that FGF7+MGST1+ fibroblasts were gradually decreased with the occurrence of heart failure. Cell-cell communication analysis indicated an enhanced secretory ability in FGF7+MGST1+ fibroblasts compared to other fibroblasts. Utilizing machine learning algorithms, we identified 17 feature genes of this cell population. A deep learning model capable of predicting heart failure was successfully built based on these feature genes and immune infiltration levels of post-MI HF. FGF7 was highly related to cardioprotective pathway terms, including "PI3K/AKT pathway" and "protein secretion". Parallelly, mendelian randomization analysis was adopted to better understand the causal relationships between feature genes and post-MI HF. Results indicated that MGST1 was causally associated with heart failure, consistent with single cell data. And the post-MI HF mouse model was constructed and qRT-PCR assays supported that both FGF7 and MGST1 were largely down-regulated in myocardial infarction area than other cardiac tissues. These findings provide new insights into the roles of FGF7+MGST1+ fibroblasts in post MI HF.

Novel insights into kidney disease: the scRNA-seq and spatial transcriptomics approaches: a literature review

Over the past decade, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have revolutionized biomedical research, particularly in understanding cellular heterogeneity in kidney diseases. This review summarizes the application and development of scRNA-seq combined with ST in the context of kidney disease. By dissecting cellular heterogeneity at an unprecedented resolution, these advanced techniques have identified novel cell subpopulations and their dynamic interactions within the renal microenvironment. The integration of scRNA-seq with ST has been instrumental in elucidating the cellular and molecular mechanisms underlying kidney development, homeostasis, and disease progression. This approach has not only identified key cellular players in renal pathophysiology but also revealed the spatial organization of cells within the kidney, which is crucial for understanding their functional specialization. This paper highlights the transformative impact of these techniques on renal research that have paved the way for targeted therapeutic interventions and personalized medicine in the management of kidney disease.

The future of cardiology: Integrating single-cell transcriptomics with multi-omics for enhanced cardiac disease insights

Recent advancements in single-cell transcriptome sequencing (scRNA-seq) have revolutionized our understanding of cellular heterogeneity in cardiovascular diseases, enabling the identification of novel therapeutic targets. This technology allows for high-resolution analysis of gene expression at the single-cell level, revealing the complex dynamics of human heart cell development and the diverse roles of cardiac cell types in health and disease. Despite its transformative potential, current applications of scRNA-seq face limitations, including challenges in data integration and the need for comprehensive multi-omic approaches to fully elucidate the mechanisms underlying cardiovascular pathologies. This review highlights the significant insights gained from scRNA-seq studies in the mammalian heart, emphasizing the importance of integrating spatial transcriptomics and other omics technologies to enhance our understanding of cardiac biology. Furthermore, it addresses the critical research gaps in the field, particularly in the context of personalized medicine and the need for improved methodologies to analyze rare cell populations. By exploring these challenges and opportunities, this review aims to pave the way for innovative diagnostic and therapeutic strategies that can ultimately improve outcomes for patients with cardiovascular diseases.

A systematic review of single-cell RNA sequencing applications and innovations

Bulk RNA sequencing is one type of RNA sequencing technique, as well as targeted RNA sequencing and whole transcriptome sequencing. It provides valuable insights into gene expression in specific cell populations or regions. However, these methods often miss the diversity of cells within complex tissues. This restriction is overcome by single-cell RNA sequencing, which records gene expression at the single-cell level. It offers a detailed picture of the diversity of cells. It is essential to study glucose homeostasis. It offers thorough explanations of cellular variation. Networks and Governance Dynamics The use of scRNA-seq in islet cells is reviewed in this study, along with sample preparation, sequencing, and computational analysis. It highlights advances in understanding cell types. Gene activity and cell interactions. Along with the challenges and limitations of scRNA-seq, this review highlights the importance of scRNA-seq in understanding complex biological processes and diseases. It is an essential resource for future research and method development in this field, which will help to build personalized treatment.

Integration of bulk and single-cell RNA sequencing reveals dynamic changes in epidermal cells

The epidermis and its appendages serve as key systems in stem cell biology. However, despite extensive research, the dynamic changes in these structures and the regulatory mechanisms governing cell behavior during the hair follicle cycle remain incompletely understood. In this study, we employed bulk and single-cell RNA sequencing to investigate the molecular regulation of yak epidermal cell populations across the anagen, catagen, and telogen phases. Through bulk transcriptomics screening, the hub genes potentially involved in the hair follicle cycle of yaks were identified. Single-cell RNA sequencing further revealed the temporal and spatial dynamics of 14 different cell populations in the hair follicle cycle, and reconstructed the trajectory of epidermal cell differentiation. We also found a large overlap of gene modules in the hair follicle microenvironment. Differential gene enrichment analysis of different branches further revealed that the function of hair follicle stem cells is closely related to their spatial location in tissues and their ability to adhere to the basement membrane. Our study not only provides valuable resources for understanding the molecular pathways of the time axis and spatial axis of the hair follicle cycle but is also highly important for future yak breeding.

Integrated single-cell transcriptome and comparative genome analysis reveals the origin of intermuscular bones in zebrafish

The evolutionary process of intermuscular bones (IBs) is complex, the molecular regulatory mechanisms of their development are not clear, and even the genes involved in the evolution and development of IBs are poorly understood. In this study, comparative genomic analysis of four fish species with IBs and eleven fish species without IBs identified 106 genes that are more conservatively evolved in fish species with IBs, but highly variable in fish species without IBs. These genes are mainly involved in swimming behavior and BMP signaling pathways. We performed single-cell transcriptome sequencing of IBs origin tissues in zebrafish before and after IBs formation and found that osteoblasts and mesenchymal stem cells (MSCs) increased significantly after IBs formation. RNA velocity analysis showed that osteoblasts in IBs differentiate from MSCs, and the differentiation trajectory of MSCs into osteoblasts was successfully constructed by pseudo-time analysis. Combined with the results of multi-omics analysis, seven candidate genes associated with IBs development were screened and knocked out in zebrafish. It was found that foxn3 mutation resulted in a delay in IB development, whereas bmp6 mutation resulted in a total loss of IB. By comparing the transcriptome of IBs tissues between bmp6+/+ zebrafish and bmp6-/- zebrafish, we found that bmp6 deletion may inhibit the differentiation of MSCs into osteoblasts while promoting the formation of osteoclasts and ultimately inhibiting the formation of IBs. This study provides new insights into the molecular regulatory mechanisms and evolutionary processes of IB development.

Protocol for the preparation of zebrafish whole heart cell suspension for single-cell analyses

Obtaining viable cell suspension that accurately represents the diversity of complex tissues is challenging due to the distinct characteristics of each cell type. Here, we present a protocol for preparing a single-cell suspension of the zebrafish embryonic whole heart, detailing steps for heart extraction, cell dissociation, quantification, and quality assessment. This suspension is compatible with downstream analysis on various single-cell platforms. For details on the use and execution of this protocol, please refer to Abu Nahia et al.1.

High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.

Applications of Single-Cell Omics Technologies for Induced Pluripotent Stem Cell-Based Cardiovascular Research

Single-cell omics technologies have transformed our investigation of genomic, transcriptomic, and proteomic landscapes at the individual cell level. In particular, the application of single-cell RNA sequencing has unveiled the complex transcriptional variations inherent in cardiac cells, offering valuable perspectives into their dynamics. This review focuses on the integration of single-cell omics with induced pluripotent stem cells (iPSCs) in the context of cardiovascular research, offering a unique avenue to deepen our understanding of cardiac biology. By synthesizing insights from various single-cell technologies, we aim to elucidate the molecular intricacies of heart health and diseases. Beyond current methodologies, we explore the potential of emerging paradigms such as single-cell/spatial omics, delving into their capacity to reveal the spatial organization of cellular components within cardiac tissues. Furthermore, we anticipate their transformative role in shaping the future of cardiovascular research. This review aims to contribute to the advancement of knowledge in the field, offering a comprehensive perspective on the synergistic potential of transcriptomic analyses, iPSC applications, and the evolving frontier of spatial omics.

Atlas of expression of acyl CoA binding protein/diazepam binding inhibitor (ACBP/DBI) in human and mouse

Acyl CoA binding protein encoded by diazepam binding inhibitor (ACBP/DBI) is a tissue hormone that stimulates lipo-anabolic responses and inhibits autophagy, thus contributing to aging and age-related diseases. Protein expression profiling of ACBP/DBI was performed on mouse tissues to identify organs in which this major tissue hormone is expressed. Transcriptomic and proteomic data bases corroborated a high level of human-mouse interspecies conservation of ACBP/DBI expression in different organs. Single-cell RNA-seq data confirmed that ACBP/DBI was strongly expressed by parenchymatous cells from specific human and mouse organs (e.g., kidney, large intestine, liver, lung) as well as by myeloid or glial cells from other organs (e.g., adipose tissue, brain, eye) following a pattern that was conserved among the two species. We identified a panel of 44 mRNAs that are strongly co-expressed with ACBP/DBI mRNA in normal and malignant human and normal mouse tissues. Of note, 22 (50%) of these co-expressed mRNAs encode proteins localized at mitochondria, and mRNAs with metabolism-related functions are strongly overrepresented (66%). Systematic data mining was performed to identify transcription factors that regulate ACBP/DBI expression in human and mouse. Several transcription factors, including growth response 1 (EGR1), E2F Transcription Factor 1 (E2F1, which interacts with retinoblastoma, RB) and transformation-related protein 53 (TRP53, best known as p53), which are endowed with oncosuppressive effects, consistently repress ACBP/DBI expression as well as its co-expressed mRNAs across multiple datasets, suggesting a mechanistic basis for a coregulation network. Furthermore, we identified multiple transcription factors that transactivate ACBP/DBI gene expression together with its coregulation network. Altogether, this study indicates the existence of conserved mechanisms determining the expression of ACBP/DBI in specific cell types of the mammalian organism.

Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research

In recent years, significant advancements in biochemistry, materials science, engineering, and computer-aided testing have driven the development of high-throughput tools for profiling genetic information. Single-cell RNA sequencing (scRNA-seq) technologies have established themselves as key tools for dissecting genetic sequences at the level of single cells. These technologies reveal cellular diversity and allow for the exploration of cell states and transformations with exceptional resolution. Unlike bulk sequencing, which provides population-averaged data, scRNA-seq can detect cell subtypes or gene expression variations that would otherwise be overlooked. However, a key limitation of scRNA-seq is its inability to preserve spatial information about the RNA transcriptome, as the process requires tissue dissociation and cell isolation. Spatial transcriptomics is a pivotal advancement in medical biotechnology, facilitating the identification of molecules such as RNA in their original spatial context within tissue sections at the single-cell level. This capability offers a substantial advantage over traditional single-cell sequencing techniques. Spatial transcriptomics offers valuable insights into a wide range of biomedical fields, including neurology, embryology, cancer research, immunology, and histology. This review highlights single-cell sequencing approaches, recent technological developments, associated challenges, various techniques for expression data analysis, and their applications in disciplines such as cancer research, microbiology, neuroscience, reproductive biology, and immunology. It highlights the critical role of single-cell sequencing tools in characterizing the dynamic nature of individual cells.

Single-cell transcriptomic profiling of heart reveals ANGPTL4 linking fibroblasts and angiogenesis in heart failure with preserved ejection fraction

INTRODUCTION

Despite the high morbidity and mortality, the effective therapies for heart failure with preserved fraction (HFpEF) are limited as the poor understand of its pathophysiological basis.

OBJECTIVE

This study was aimed to characterize the cellular heterogeneity and potential mechanisms of HFpEF at single-cell resolution.

METHODS

An HFpEF mouse model was induced by a high-fat diet with N-nitro-L-arginine methyl ester. Cells from the hearts were subjected to single-cell sequencing. The key protein expression was measured with Immunohistochemistry and immunofluorescence staining.

RESULTS

In HFpEF hearts, myocardial fibroblasts exhibited higher levels of fibrosis. Furthermore, an increased number of fibroblasts differentiated into high-metabolism and high-fibrosis phenotypes. The expression levels of genes encoding certain pro-angiogenic secreted proteins were decreased in the HFpEF group, as confirmed by bulk RNA sequencing. Additionally, the proportion of the endothelial cell (EC) lineages in the HFpEF group was significantly downregulated, with low angiogenesis and high apoptosis phenotypes observed in these EC lineages. Interestingly, the fibroblasts in the HFpEF heart might cross-link with the EC lineages via over-secretion of ANGPTL4, thus displaying an anti-angiogenic function. Immunohistochemistry and immunofluorescence staining then revealed the downregulation of vascular density and upregulation of ANGPTL4 expression in HFpEF hearts. Finally, we predicted ANGPTL4as a potential druggable target using DrugnomeAI.

CONCLUSION

In conclusion, this study comprehensively characterized the angiogenesis impairment in HFpEF hearts at single-cell resolution and proposed that ANGPTL4 secretion by fibroblasts may be a potential mechanism underlying this angiogenic abnormality.

A genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice

BACKGROUND

Despite the use of Next-Generation Sequencing (NGS) as the gold standard for the diagnosis of rare diseases, its clinical implementation has been challenging, limiting the cost-effectiveness of NGS and the understanding, control and safety essential for decision-making in clinical applications. Here, we describe a personalized NGS-based strategy integrating precision medicine into a public healthcare system and its implementation in the routine diagnosis process during a five-year pilot program.

METHODS

Our approach involved customized probe designs, the generation of virtual panels and the development of a personalized medicine module (PMM) for variant prioritization. This strategy was applied to 6500 individuals including 6267 index patients and 233 NGS-based carrier screenings.

RESULTS

Causative variants were identified in 2061 index patients (average 32.9%, ranging from 12 to 62% by condition). Also, 131 autosomal-recessive cases could be partially genetically diagnosed. These results led to over 5000 additional studies including carrier, prenatal and preimplantational tests or pharmacological and gene therapy treatments.

CONCLUSION

This strategy has shown promising improvements in the diagnostic rate, facilitating timely diagnosis and gradually expanding our services portfolio for rare diseases. The steps taken towards the integration of clinical and genomic data are opening new possibilities for conducting both retrospective and prospective healthcare studies. Overall, this study represents a major milestone in the ongoing efforts to improve our understanding and clinical management of rare diseases, a crucial area of medical research and care.

Elucidating cardiomyocyte heterogeneity and maturation dynamics through integrated single-cell and spatial transcriptomics

The intricate development and functionality of the mammalian heart are influenced by the heterogeneous nature of cardiomyocytes (CMs). In this study, single-cell and spatial transcriptomics were utilized to analyze cells from neonatal mouse hearts, resulting in a comprehensive atlas delineating the transcriptional profiles of distinct CM subsets. A continuum of maturation states was elucidated, emphasizing a progressive developmental trajectory rather than discrete stages. This approach enabled the mapping of these states across various cardiac regions, illuminating the spatial organization of CM development and the influence of the cellular microenvironment. Notably, a subset of transitional CMs was identified, characterized by a transcriptional signature marking a pivotal maturation phase, presenting a promising target for therapeutic strategies aimed at enhancing cardiac regeneration. This atlas not only elucidates fundamental aspects of cardiac development but also serves as a valuable resource for advancing research into cardiac physiology and pathology, with significant implications for regenerative medicine.

ScRNA-Seq Analysis of Tongue Tissues in Chronic Hyperplastic Candidiasis

Chronic hyperplastic candidiasis (CHC) is a rare but severe subtype of oral candidiasis distinguished by its potential malignant transformation and suboptimal response to antifungal therapies. However, the cells and mechanisms that play key roles in this process remain unclear. Therefore, we performed the first single-cell RNA sequencing (scRNA-seq) analysis of CHC-affected tongue tissues to reveal the microenvironmental changes and immunological etiology of CHC. First, the features of CHC lesions manifesting as thickening and hardening nodular lesions, including their pathological and microbiological characteristics, were elucidated. Then, a comprehensive cellular atlas and distinct immune landscape in CHC compared with healthy tissues were characterized using scRNA-seq, highlighting significant modifications in the cell number and functionality of fibroblasts and T/NK cells. Importantly, the central role of fibroblasts in cell-cell interactions in CHC was hinted, and possible ligand-receptor pairs mainly associated with inflammation and carcinogenesis were identified. Moreover, it was revealed that significant functional activation of fibroblasts, related to the activation of the epithelial-mesenchymal transition pathways and increased expression of collagen I, matrix metalloproteinase 1 (MMP1), and MMP2, could be a hallmark of CHC, correlating with CHC's clinical characteristics of tongue hardening and intense inflammation. Notably, there is sequencing evidence of the recruitment of CD8+Tex cells and activation of PD-1 and TIGIT immune checkpoint pathways. Moreover, cDC_LAMP3 cells exhibited high CD274 expression, suggesting immune exhaustion and an increased susceptibility to carcinogenesis. This pioneering study provides valuable insights into CHC pathogenesis and immune responses, enhancing our understanding of potential therapeutic strategies.

Multi-omics in exploring the pathophysiology of diabetic retinopathy

Diabetic retinopathy (DR) is a leading global cause of vision impairment, with its prevalence increasing alongside the rising rates of diabetes mellitus (DM). Despite the retina's complex structure, the underlying pathology of DR remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) and recent advancements in multi-omics analyses have revolutionized molecular profiling, enabling high-throughput analysis and comprehensive characterization of complex biological systems. This review highlights the significant contributions of scRNA-seq, in conjunction with other multi-omics technologies, to DR research. Integrated scRNA-seq and transcriptomic analyses have revealed novel insights into DR pathogenesis, including alternative transcription start site events, fluctuations in cell populations, altered gene expression profiles, and critical signaling pathways within retinal cells. Furthermore, by integrating scRNA-seq with genetic association studies and multi-omics analyses, researchers have identified novel biomarkers, susceptibility genes, and potential therapeutic targets for DR, emphasizing the importance of specific retinal cell types in disease progression. The integration of scRNA-seq with metabolomics has also been instrumental in identifying specific metabolites and dysregulated pathways associated with DR. It is highly conceivable that the continued synergy between scRNA-seq and other multi-omics approaches will accelerate the discovery of underlying mechanisms and the development of novel therapeutic interventions for DR.

Research trends and hotspots of the applications of single-cell RNA sequencing in cardiovascular diseases: a bibliometric and visualized study

Background

Cardiovascular diseases (CVDs) are the leading causes of death globally. The use of single-cell RNA sequencing (scRNA-seq) in CVDs has gained significant attention in recent years, and there is a growing body of literature on the subject. However, a thorough and impartial analysis of the existing state and trends of scRNA-seq in CVDs is lacking. This study aims to examine the development of scRNA-seq in CVDs using bibliometric and visualized analysis.

Methods

Global publications on scRNA-seq and CVDs from 2009 to 2023 were extracted from the Web of Science Core Collection (WoSCC) database. The R package "Bibliometrix", VOSviewer, and CiteSpace were employed to perform a bibliometric study.

Results

After applying the screening criteria and omitting documents that met exclusive criteria, this bibliometric study included 1170 papers. These were authored by 8595 scholars from 1565 organizations in 57 countries or regions and were published in 369 journals, with 51 073 co-cited references included. Publication volume, citations, and relative research interest index focusing on this field have dramatically increased since 2019. The cooperation network showed that the USA, the Chinese Academy of Medical Sciences, and Qingbo Xu were the most active countries, institutes, and authors in this field, respectively. Circulation Research was the journal with the most publications, which was confirmed to be the top core source by Bradford's law. The hotspots and emerging direction in the field manifest in (1) three CVDs (atherosclerosis, myocardial infarction, and heart failure) and (2) three cell types (macrophage, fibroblast, and smooth muscle cell).

Conclusions

Our study provides a systematic visualization of the research literature on scRNA-seq in CVDs and provides guidance and reference for understanding the current research status and discovering new research directions.

CardioAtlas: deciphering the single-cell transcriptome landscape in cardiovascular tissues and diseases

Increasing scRNA-seq data in cardiovascular research have substantially improved our knowledge on the development of the cardiovascular system and the mechanisms underlying cardiovascular diseases. However, the single-cell transcriptome datasets were dispersed in literature and no resource for cardiovascular systems and diseases. Here, we constructed an organized resource CardioAtlas, which provides comprehensive analysis results for > 1,929,000 cells in 27 human data sets and > 1,088,000 cells in 39 mouse data sets. Through large-scale literature retrieval and manual annotation, we constructed 12 and 15 scRNA-seq reference atlas for common human and mouse cardiovascular systems and diseases, covering 43 and 39 cell types. In particular, CardioAtlas provides five analytic modules, including cell-type prediction, identification of marker genes, functional enrichment analysis, identification of cell-type-specific transcription regulons, and cell-cell communication analysis. In addition, users can upload scRNA-seq data for personalized analysis. CardioAtlas is available at http://bio-bigdata.hrbmu.edu.cn/CardioAtlas . CardioAtlas provides the first comprehensive and well-crafted reference atlas of cardiovascular systems and diseases and describes in detail previously unrecognized cell populations across a large number of humans and mice.

Time-resolved single-cell transcriptomic sequencing

Cells experience continuous transformation under both physiological and pathological circumstances. Single-cell RNA sequencing (scRNA-seq) is competent in disclosing the disparities of cells; nevertheless, it poses challenges in linking the individual cell state at distinct time points. Although computational approaches based on scRNA-seq data have been put forward for trajectory analysis, the result is based on assumptions and fails to reflect the actual states. Consequently, it is necessary to incorporate a "time anchor" into the scRNA-seq library for the temporal documentation of the dynamic expression pattern. This review comprehensively overviews the time-resolved single-cell transcriptomic sequencing methodologies and applications. As scRNA-seq functions as the basis for profiling single-cell expression patterns, the review initially introduces various scRNA-seq approaches. Subsequently, the review focuses on the different experimental strategies for introducing a "time anchor" to scRNA-seq, highlighting their principles, strengths, weaknesses, and comparing their adaptation in various scenarios. Next, it provides a brief summary of applications in immunity response, cancer progression, and embryo development. Finally, the review concludes with a forward-looking perspective on future advancements in time-resolved single-cell transcriptomic sequencing.

Single-cell RNA-seq in diabetic foot ulcer wound healing

Diabetic foot ulcer (DFU) is a chronic and serious complication of diabetes mellitus. It is mainly caused by hyperglycaemia, diabetic peripheral vasculopathy and diabetic peripheral neuropathy. These conditions result in ulceration of foot tissues and chronic wounds. If left untreated, DFU can lead to amputation or even endanger the patient's life. Single-cell RNA sequencing (scRNA-seq) is a technique used to identify and characterise transcriptional subpopulations at the single-cell level. It provides insight into cellular function and the molecular drivers of disease. The objective of this paper is to examine the subpopulations, genes and molecules of cells associated with chronic wounds of diabetic foot by using scRNA-seq. The paper aims to explore the wound-healing mechanism of DFU from three aspects: inflammation, angiogenesis and extracellular matrix remodelling. The goal is to gain a better understanding of the mechanism of DFU wound healing and identify possible DFU therapeutic targets, providing new insights for the application of DFU personalised therapy.

The multifaceted role of mitochondria in cardiac function: insights and approaches

Cardiovascular disease (CVD) remains a global economic burden even in the 21st century with 85% of deaths resulting from heart attacks. Despite efforts in reducing the risk factors, and enhancing pharmacotherapeutic strategies, challenges persist in early identification of disease progression and functional recovery of damaged hearts. Targeting mitochondrial dysfunction, a key player in the pathogenesis of CVD has been less successful due to its role in other coexisting diseases. Additionally, it is the only organelle with an agathokakological function that is a remedy and a poison for the cell. In this review, we describe the origins of cardiac mitochondria and the role of heteroplasmy and mitochondrial subpopulations namely the interfibrillar, subsarcolemmal, perinuclear, and intranuclear mitochondria in maintaining cardiac function and in disease-associated remodeling. The cumulative evidence of mitochondrial retrograde communication with the nucleus is addressed, highlighting the need to study the genotype-phenotype relationships of specific organelle functions with CVD by using approaches like genome-wide association study (GWAS). Finally, we discuss the practicality of computational methods combined with single-cell sequencing technologies to address the challenges of genetic screening in the identification of heteroplasmy and contributory genes towards CVD.

Clinical trials in-a-dish for cardiovascular medicine

Cardiovascular diseases persist as a global health challenge that requires methodological innovation for effective drug development. Conventional pipelines relying on animal models suffer from high failure rates due to significant interspecies variation between humans and animal models. In response, the recently enacted Food and Drug Administration Modernization Act 2.0 encourages alternative approaches including induced pluripotent stem cells (iPSCs). Human iPSCs provide a patient-specific, precise, and screenable platform for drug testing, paving the way for cardiovascular precision medicine. This review discusses milestones in iPSC differentiation and their applications from disease modelling to drug discovery in cardiovascular medicine. It then explores challenges and emerging opportunities for the implementation of 'clinical trials in-a-dish'. Concluding, this review proposes a framework for future clinical trial design with strategic incorporations of iPSC technology, microphysiological systems, clinical pan-omics, and artificial intelligence to improve success rates and advance cardiovascular healthcare.

Single-Cell RNA Sequencing and Combinatorial Approaches for Understanding Heart Biology and Disease

By directly measuring multiple molecular features in hundreds to millions of single cells, single-cell techniques allow for comprehensive characterization of the diversity of cells in the heart. These single-cell transcriptome and multi-omic studies are transforming our understanding of heart development and disease. Compared with single-dimensional inspections, the combination of transcriptomes with spatial dimensions and other omics can provide a comprehensive understanding of single-cell functions, microenvironment, dynamic processes, and their interrelationships. In this review, we will introduce the latest advances in cardiac health and disease at single-cell resolution; single-cell detection methods that can be used for transcriptome, genome, epigenome, and proteome analysis; single-cell multi-omics; as well as their future application prospects.

New insights gained from cellular landscape changes in myocarditis and inflammatory cardiomyopathy

Advances in the etiological classification of myocarditis and inflammatory cardiomyopathy (ICM) have reached a consensus. However, the mechanism of myocarditis/ICM remains unclear, which affects the development of treatment and the improvement of outcome. Cellular transcription and metabolic reprogramming, and the interactions between cardiomyocytes and non-cardiomyocytes, such as the immune cells, contribute to the process of myocarditis/ICM. Recent efforts have been made by multi-omics techniques, particularly in single-cell RNA sequencing, to gain a better understanding of the cellular landscape alteration occurring in disease during the progression. This article aims to provide a comprehensive overview of the latest studies in myocarditis/ICM, particularly as revealed by single-cell sequencing.

Complement Factor C1q Mediates Vascular Endothelial Dysfunction in STZ-Induced Diabetic Mice

Diabetes is a significant global public health issue with implications for vascular endothelial cells (ECs) dysfunction and the subsequent development and advancement of diabetes complications. This study aims to compare the cellular and molecular properties of the aorta in normal and streptozotocin (STZ)-induced diabetic mice, with a focus on elucidating potential mechanism underlying EC dysfunction. Here, we performed a single-cell RNA sequencing survey of 32,573 cells from the aorta of normal and STZ-induced diabetic mice. We found a compendium of 10 distinct cell types, mainly ECs, smooth muscle cells, fibroblast, pericyte, immune cells, and stromal cells. As the diabetes condition progressed, we observed a subpopulation of aortic ECs that exhibited significantly elevated expression of complement (C) molecule C1qa compared with their healthy counterparts. This increased expression of C1qa was found to induce reactive oxygen species (ROS) production, facilitate EC migration and increased permeability, and impair the vasodilation within the aortic segment of mice. Furthermore, AAV-Tie2-shRNA-C1qa was administered into diabetic mice by tail vein injection, showing that inhibition of C1qa in the endothelium led to a reduction in ROS production, decreased vascular permeability, and improved vasodilation. Collectively, these findings highlight the crucial involvement of C1qa in endothelial dysfunction associated with diabetes.

ARTICLE HIGHLIGHTS

Delving deeper into the mechanisms fundamental to HIV-associated immunopathology using single-cell sequencing techniques: A scoping review of current literature

Human immunodeficiency virus (HIV) infection has evolved into an established global pandemic over the past four decades; however, despite massive research investment globally, the precise underlying mechanisms which are fundamental to HIV-related pathogenesis remain unclear. Single cell ribonucleic acid (RNA) sequencing methods are increasingly being used for the identification of specific cell-type transcriptional changes in HIV infection. In this scoping review, we have considered information extracted from fourteen published HIV-associated single-cell RNA sequencing-related studies, hoping to throw light on the underlying mechanisms of HIV infection and pathogenesis, and to explore potential candidate biomarkers for HIV disease progression and antiviral treatment. Generally, HIV positive individuals tend to manifest disturbances of frequency of multiple cellular types, and specifically exhibit diminished levels of CD4+ T-cells and enriched numbers of CD8+ T-cells. Cell-specific transcriptional changes tend to be linked to cell permissiveness, hyperacute or acute HIV infection, viremia, and cell productivity. The transcriptomes of CD4+ T-cell and CD8+ T-cell subpopulations are also observed to change in HIV-positive diabetic individuals, spontaneous HIV controllers, individuals with high levels of HIV viremia, and those in an acute phase of HIV infection. The transcriptional changes seen in B cells, natural killer (NK) cells, and myeloid dendritic cells (mDCs) of HIV-infected individuals demonstrate that the humoral immune response, antiviral response, and immune response regulation, respectively, are all altered following HIV infection. Antiretroviral therapy (ART) plays a crucial role in achieving immune reconstitution, in improving immunological disruption, and in mitigating immune system imbalances in HIV-infected individuals, while not fully restoring inherent cellular transcription to levels seen in HIV-negative individuals. The preceding observations not only illustrate compelling advances in the understanding of HIV-associated immunopathogenesis, but also identify specific cell-type transcriptional changes that may serve as potential biomarkers for HIV disease monitoring and therapeutic targeting.

Glucagon Receptor Antagonist for Heart Failure With Preserved Ejection Fraction

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is an emerging major unmet need and one of the most significant clinic challenges in cardiology. The pathogenesis of HFpEF is associated with multiple risk factors. Hypertension and metabolic disorders associated with obesity are the 2 most prominent comorbidities observed in patients with HFpEF. Although hypertension-induced mechanical overload has long been recognized as a potent contributor to heart failure with reduced ejection fraction, the synergistic interaction between mechanical overload and metabolic disorders in the pathogenesis of HFpEF remains poorly characterized.

METHOD

We investigated the functional outcome and the underlying mechanisms from concurrent mechanic and metabolic stresses in the heart by applying transverse aortic constriction in lean C57Bl/6J or obese/diabetic B6.Cg-Lepob/J (ob/ob) mice, followed by single-nuclei RNA-seq and targeted manipulation of a top-ranked signaling pathway differentially affected in the 2 experimental cohorts.

RESULTS

In contrast to the post-transverse aortic constriction C57Bl/6J lean mice, which developed pathological features of heart failure with reduced ejection fraction over time, the post-transverse aortic constriction ob/ob mice showed no significant changes in ejection fraction but developed characteristic pathological features of HFpEF, including diastolic dysfunction, worsened cardiac hypertrophy, and pathological remodeling, along with further deterioration of exercise intolerance. Single-nuclei RNA-seq analysis revealed significant transcriptome reprogramming in the cardiomyocytes stressed by both pressure overload and obesity/diabetes, markedly distinct from the cardiomyocytes singularly stressed by pressure overload or obesity/diabetes. Furthermore, glucagon signaling was identified as the top-ranked signaling pathway affected in the cardiomyocytes associated with HFpEF. Treatment with a glucagon receptor antagonist significantly ameliorated the progression of HFpEF-related pathological features in 2 independent preclinical models. Importantly, cardiomyocyte-specific genetic deletion of the glucagon receptor also significantly improved cardiac function in response to pressure overload and metabolic stress.

CONCLUSIONS

These findings identify glucagon receptor signaling in cardiomyocytes as a critical determinant of HFpEF progression and provide proof-of-concept support for glucagon receptor antagonism as a potential therapy for the disease.

DMF-DM-seq: Digital-Microfluidics Enabled Dual-Modality Sequencing of Single-Cell mRNA and microRNA with High Integration, Sensitivity, and Automation

Multimodal measurement of single cells provides deep insights into the intricate relationships between individual molecular layers and the regulatory mechanisms underlying intercellular variations. Here, we reported DMF-DM-seq, a highly integrated, sensitive, and automated platform for single-cell mRNA and microRNA (miRNA) co-sequencing based on digital microfluidics. This platform first integrates the processes of single-cell isolation, lysis, component separation, and simultaneous sequencing library preparation of mRNA and miRNA within a single DMF device. Compared with the current half-cell measuring strategy, DMF-DM-seq enables complete separation of single-cell mRNA and miRNA via a magnetic field application, resulting in a higher miRNA detection ability. DMF-DM-seq revealed differential expression patterns of single cells of noncancerous breast cells and noninvasive and aggressive breast cancer cells at both mRNA and miRNA levels. The results demonstrated the anticorrelated relationship between miRNA and their mRNA targets. Further, we unravel the tumor growth and metastasis-associated biological processes enriched by miRNA-targeted genes, along with important miRNA-interaction networks involved in significant signaling pathways. We also deconstruct the miRNA regulatory mechanisms underlying different signaling pathways across different breast cell types. In summary, DMF-DM-seq offers a powerful tool for a comprehensive study of the expression heterogeneity of single-cell mRNA and miRNA, which will be widely applied in basic and clinical research.

Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data

Annotating cell types of single-cell RNA sequencing (scRNA-seq) data is crucial for studying cellular heterogeneity in the tumor microenvironment. Recently, large-scale pre-trained language models (PLMs) have achieved significant progress in cell-type annotation of scRNA-seq data. This approach effectively addresses previous methods' shortcomings in performance and generalization. However, fine-tuning PLMs for different downstream tasks demands considerable computational resources, rendering it impractical. Hence, a new research branch introduces parameter-efficient fine-tuning (PEFT). This involves optimizing a few parameters while leaving the majority unchanged, leading to substantial reductions in computational expenses. Here, we utilize scBERT, a large-scale pre-trained model, to explore the capabilities of three PEFT methods in scRNA-seq cell type annotation. Extensive benchmark studies across several datasets demonstrate the superior applicability of PEFT methods. Furthermore, downstream analysis using models obtained through PEFT showcases their utility in novel cell type discovery and model interpretability for potential marker genes. Our findings underscore the considerable potential of PEFT in PLM-based cell type annotation, presenting novel perspectives for the analysis of scRNA-seq data.

Endothelial cell diversity: the many facets of the crystal

Endothelial cells (ECs) form the inner lining of blood vessels and play crucial roles in angiogenesis. While it has been known for a long time that there are considerable differences among ECs from lymphatic and blood vessels, as well as among arteries, veins and capillaries, the full repertoire of endothelial diversity is only beginning to be elucidated. It has become apparent that the role of ECs is not just limited to their exchange functions. Indeed, a multitude of organ-specific functions, including release of growth factors, regulation of immune functions, have been linked to ECs. Recent years have seen a surge into the identification of spatiotemporal molecular and functional heterogeneity of ECs, supported by technologies such as single-cell RNA sequencing (scRNA-seq), lineage tracing and intersectional genetics. Together, these techniques have spurred the generation of epigenomic, transcriptomic and proteomic signatures of ECs. It is now clear that ECs across organs and in different vascular beds, but even within the same vessel, have unique molecular identities and employ specialized molecular mechanisms to fulfil highly specialized needs. Here, we focus on the molecular heterogeneity of the endothelium in different organs and pathological conditions.

Single-cell landscape reveals the immune heterogeneity of bone marrow involvement in peripheral T-cell lymphoma

The prognosis of patients with peripheral T-cell lymphoma (PTCL) depends on bone marrow involvement (BMI). The bone marrow (BM) tumor microenvironment in PTCL remains unclear. We performed single-cell RNA sequencing (scRNA-seq) on 11 fresh BM samples from patients with BMI to reveal the associations of immune landscape and genetic variations with the prognosis of PTCL patients. Compared with PTCL not otherwise specified (NOS), angioimmunoblastic T-cell lymphoma (AITL) had a higher number of T cells, lower number of lymphocytes, and greater inflammation. Immune heterogeneity in AITL is associated with prognosis. In particular, specific T-cell receptor (TCR) T cells are enriched in patients with good response to anti-CD30 therapy. We observed RhoA mutation-associated neoantigens. Chidamide-treated patients had a higher number of CD4+ regulatory cells and a better treatment response compared with other patients. In the nonresponder group, T-cell enrichment progressed to secondary B-cell enrichment and subsequently diffuse large B-cell lymphoma. Moreover, AITL patients with lymphoma-associated hemophagocytic syndrome had more T follicular helper (Tfh) cells with copy number variations in CHR5. To our knowledge, this study is the first to reveal the single-cell landscape of BM microenvironment heterogeneity in PTCL patients with BMI. scRNA-seq can be used to investigate the immune heterogeneity and genetic variations in AITL associated with prognosis.

Integrating single-nucleus RNA sequencing and spatial transcriptomics to elucidate a specialized subpopulation of astrocytes, microglia and vascular cells in brains of mouse model of lipopolysaccharide-induced sepsis-associated encephalopathy

BACKGROUND

Understanding the mechanism behind sepsis-associated encephalopathy (SAE) remains a formidable task. This study endeavors to shed light on the complex cellular and molecular alterations that occur in the brains of a mouse model with SAE, ultimately unraveling the underlying mechanisms of this condition.

METHODS

We established a murine model using intraperitoneal injection of lipopolysaccharide (LPS) in wild type and Anxa1-/- mice and collected brain tissues for analysis at 0-hour, 12-hour, 24-hour, and 72-hour post-injection. Utilizing advanced techniques such as single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq, we conducted a comprehensive characterization of the cellular responses and molecular patterns within the brain.

RESULTS

Our study uncovered notable temporal differences in the response to LPS challenge between Anxa1-/- (annexin A1 knockout) and wild type mice, specifically at the 12-hour and 24-hour time points following injection. We observed a significant increase in the proportion of Astro-2 and Micro-2 cells in these mice. These cells exhibited a colocalization pattern with the vascular subtype Vas-1, forming a distinct region known as V1A2M2, where Astro-2 and Micro-2 cells surrounded Vas-1. Moreover, through further analysis, we discovered significant upregulation of ligands and receptors such as Timp1-Cd63, Timp1-Itgb1, Timp1-Lrp1, as well as Ccl2-Ackr1 and Cxcl2-Ackr1 within this region. In addition, we observed a notable increase in the expression of Cd14-Itgb1, Cd14-Tlr2, and Cd14-C3ar1 in regions enriched with Micro-2 cells. Additionally, Cxcl10-Sdc4 showed broad upregulation in brain regions containing both Micro-2 and Astro-2 cells. Notably, upon LPS challenge, there was an observed increase in Anxa1 expression in the mouse brain. Furthermore, our study revealed a noteworthy increase in mortality rates following Anxa1 knockdown. However, we did not observe substantial differences in the types, numbers, or distribution of other brain cells between Anxa1-/- and wildtype mice over time. Nevertheless, when comparing the 24-hour post LPS injection time point, we observed a significant decrease in the proportion and distribution of Micro-2 and Astro-2 cells in the vicinity of blood vessels in Anxa1-/- mice. Additionally, we noted reduced expression levels of several ligand-receptor pairs including Cd14-Tlr2, Cd14-C3ar1, Cd14-Itgb1, Cxcl10-Sdc4, Ccl2-Ackr1, and Cxcl2-Ackr1.

CONCLUSIONS

By combining snRNA-seq and Stereo-seq techniques, our study successfully identified a distinctive cellular colocalization, referred to as a special pathological niche, comprising Astro-2, Micro-2, and Vas-1 cells. Furthermore, we observed an upregulation of ligand-receptor pairs within this niche. These findings suggest a potential association between this cellular arrangement and the underlying mechanisms contributing to SAE or the increased mortality observed in Anxa1 knockdown mice.

scRNA-seq reveals the diversity of the developing cardiac cell lineage and molecular players in heart rhythm regulation

We utilized scRNA-seq to delineate the diversity of cell types in the zebrafish heart. Transcriptome profiling of over 50,000 cells at 48 and 72 hpf defined at least 18 discrete cell lineages of the developing heart. Utilizing well-established gene signatures, we identified a population of cells likely to be the primary pacemaker and characterized the transcriptome profile defining this critical cell type. Two previously uncharacterized genes, atp1b3b and colec10, were found to be enriched in the sinoatrial cardiomyocytes. CRISPR/Cas9-mediated knockout of these two genes significantly reduced heart rate, implicating their role in cardiac development and conduction. Additionally, we describe other cardiac cell lineages, including the endothelial and neural cells, providing their expression profiles as a resource. Our results established a detailed atlas of the developing heart, providing valuable insights into cellular and molecular mechanisms, and pinpointed potential new players in heart rhythm regulation.

Revisiting Cardiac Biology in the Era of Single Cell and Spatial Omics

Throughout our lifetime, each beat of the heart requires the coordinated action of multiple cardiac cell types. Understanding cardiac cell biology, its intricate microenvironments, and the mechanisms that govern their function in health and disease are crucial to designing novel therapeutical and behavioral interventions. Recent advances in single-cell and spatial omics technologies have significantly propelled this understanding, offering novel insights into the cellular diversity and function and the complex interactions of cardiac tissue. This review provides a comprehensive overview of the cellular landscape of the heart, bridging the gap between suspension-based and emerging in situ approaches, focusing on the experimental and computational challenges, comparative analyses of mouse and human cardiac systems, and the rising contextualization of cardiac cells within their niches. As we explore the heart at this unprecedented resolution, integrating insights from both mouse and human studies will pave the way for novel diagnostic tools and therapeutic interventions, ultimately improving outcomes for patients with cardiovascular diseases.

Single-Cell and Spatial Transcriptome Analysis of Dermal Fibroblast Development in Perinatal Mouse Skin: Dynamic Lineage Differentiation and Key Driver Genes

Several single-cell RNA studies of developing mouse skin have elucidated the molecular and cellular processes involved in skin development. However, they have primarily focused on either the fetal or early postnatal period, leaving a gap in our understanding of skin development. In this study, we conducted a comprehensive time-series analysis by combining single-cell RNA-sequencing datasets collected at different stages of development (embryonic days 13.5, 14.5, and 16.5 and postnatal days 0, 2, and 4) and validated our findings through multipanel in situ spatial transcriptomics. Our analysis indicated that embryonic fibroblasts exhibit heterogeneity from a very early stage and that the rapid determination of each lineage occurs within days after birth. The expression of putative key driver genes, including Hey1, Ebf1, Runx3, and Sox11 for the dermal papilla trajectory; Lrrc15 for the dermal sheath trajectory; Zfp536 and Nrn1 for the papillary fibroblast trajectory; and Lrrn4cl and Mfap5 for the fascia fibroblast trajectory, was detected in the corresponding, spatially identified cell types. Finally, cell-to-cell interaction analysis indicated that the dermal papilla lineage is the primary source of the noncanonical Wnt pathway during skin development. Together, our study provides a transcriptomic reference for future research in the field of skin development and regeneration.

Advancing skeletal health and disease research with single-cell RNA sequencing

Orthopedic conditions have emerged as global health concerns, impacting approximately 1.7 billion individuals worldwide. However, the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders. The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity. Nevertheless, investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges. In this comprehensive review, we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines. By utilizing these methodologies, crucial insights into the developmental dynamics, maintenance of homeostasis, and pathological processes involved in spine, joint, bone, muscle, and tendon disorders have been uncovered. Specifically focusing on the joint diseases of degenerative disc disease, osteoarthritis, and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension. These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

The cGAS-STING pathway in cardiovascular diseases: from basic research to clinical perspectives

The cyclic guanosine monophosphate (GMP)-adenosine monophosphate (AMP) synthase-stimulator of interferon genes (cGAS-STING) signaling pathway, an important component of the innate immune system, is involved in the development of several diseases. Ectopic DNA-induced inflammatory responses are involved in several pathological processes. Repeated damage to tissues and metabolic organelles releases a large number of damage-associated molecular patterns (mitochondrial DNA, nuclear DNA, and exogenous DNA). The DNA fragments released into the cytoplasm are sensed by the sensor cGAS to initiate immune responses through the bridging protein STING. Many recent studies have revealed a regulatory role of the cGAS-STING signaling pathway in cardiovascular diseases (CVDs) such as myocardial infarction, heart failure, atherosclerosis, and aortic dissection/aneurysm. Furthermore, increasing evidence suggests that inhibiting the cGAS-STING signaling pathway can significantly inhibit myocardial hypertrophy and inflammatory cell infiltration. Therefore, this review is intended to identify risk factors for activating the cGAS-STING pathway to reduce risks and to simultaneously further elucidate the biological function of this pathway in the cardiovascular field, as well as its potential as a therapeutic target.

A review of single-cell transcriptomics and epigenomics studies in maternal and child health

Single-cell sequencing technologies enhance our understanding of cellular dynamics throughout pregnancy. We outlined the workflow of single-cell sequencing techniques and reviewed single-cell studies in maternal and child health. We conducted a literature review of single cell studies on maternal and child health using PubMed. We summarized the findings from 16 single-cell atlases of the human and mammalian placenta across gestational stages and 31 single-cell studies on maternal exposures and complications including infection, obesity, diet, gestational diabetes, pre-eclampsia, environmental exposure and preterm birth. Single-cell studies provides insights on novel cell types in placenta and cell type-specific marks associated with maternal exposures and complications.

GLP-1 receptor agonists and myocardial metabolism in atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Many medical conditions, including hypertension, diabetes, obesity, sleep apnea, and heart failure (HF), increase the risk for AF. Cardiomyocytes have unique metabolic characteristics to maintain adenosine triphosphate production. Significant changes occur in myocardial metabolism in AF. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been used to control blood glucose fluctuations and weight in the treatment of type 2 diabetes mellitus (T2DM) and obesity. GLP-1RAs have also been shown to reduce oxidative stress, inflammation, autonomic nervous system modulation, and mitochondrial function. This article reviews the changes in metabolic characteristics in cardiomyocytes in AF. Although the clinical trial outcomes are unsatisfactory, the findings demonstrate that GLP-1 RAs can improve myocardial metabolism in the presence of various risk factors, lowering the incidence of AF.

Systematic mapping of TF-mediated cell fate changes by a pooled induction coupled with scRNA-seq and multi-omics approaches

Transcriptional regulation controls cellular functions through interactions between transcription factors (TFs) and their chromosomal targets. However, understanding the fate conversion potential of multiple TFs in an inducible manner remains limited. Here, we introduce iTF-seq as a method for identifying individual TFs that can alter cell fate toward specific lineages at a single-cell level. iTF-seq enables time course monitoring of transcriptome changes, and with biotinylated individual TFs, it provides a multi-omics approach to understanding the mechanisms behind TF-mediated cell fate changes. Our iTF-seq study in mouse embryonic stem cells identified multiple TFs that trigger rapid transcriptome changes indicative of differentiation within a day of induction. Moreover, cells expressing these potent TFs often show a slower cell cycle and increased cell death. Further analysis using bioChIP-seq revealed that GCM1 and OTX2 act as pioneer factors and activators by increasing gene accessibility and activating the expression of lineage specification genes during cell fate conversion. iTF-seq has utility in both mapping cell fate conversion and understanding cell fate conversion mechanisms.

RNA-sequencing expression profile and functional analysis of retinal pigment epithelium in atrophic age-related macular degeneration

The retinal pigment epithelium (RPE) is fundamental to sustaining retinal homeostasis. RPE abnormality leads to visual defects and blindness, including age-related macular degeneration (AMD). Although breakthroughs have been made in the treatment of neovascular AMD, effective intervention for atrophic AMD is largely absent. The inadequate knowledge of RPE pathology is hindered by a lack of patient RPE datasets, especially at the single-cell resolution. In this study, we delved into a large-scale single-cell resource of AMD donors in which RPE cells were occupied in a substantial proportion. Bulk RNA-seq datasets of atrophic AMD were integrated to extract molecular characteristics of RPE in the pathogenesis of atrophic AMD. Both in vivo and in vitro models revealed that carboxypeptidase X, M14 family member 2 (CPXM2) was specifically expressed in the RPE cells of atrophic AMD, which might be induced by oxidative stress and involved in the epithelial-mesenchymal transition of RPE cells. Additionally, silencing of CPXM2 inhibited the mesenchymal phenotype of RPE cells in an oxidative stress cell model. Thus, our results demonstrate that CPXM2 plays a crucial role in regulating atrophic AMD and may serve as a potential therapeutic target for atrophic AMD.

Neutrophil extracellular traps promoting fibroblast activation and aggravating limb ischemia through Wnt5a pathway

Although the formation of NETs contributes to cancer cell invasion and distant metastasis, its role in the pathological progression of limb ischemia remains unknown. This study investigated the functional significance of NETs in cell-cell crosstalk during limb ischemia. The changes of cell subsets in lower limb ischemia samples were detected by single-cell RNA sequencing. The expression of neutrophil extracellular traps (NETs) related markers in lower limb ischemia samples was detected by immunohistochemistry and Western blotting. The signaling pathway of NETs activation in fibroblasts was verified by immunofluorescence, PCR and Western blotting. Through single-cell RNA sequencing (scRNA-seq), we identified 9 distinct cell clusters, with significantly upregulated activation levels in fibroblasts and neutrophils and phenotypic transformation of smooth muscle cells (SMCs) into a proliferative state in ischemic tissue. At the same time, the interaction between fibroblasts and smooth muscle cells was significantly enhanced in ischemic tissue. NETs levels rise and fibroblast activation is induced in ischemic conditions. Mechanistically, activated fibroblasts promote smooth muscle cell proliferation through the Wnt5a pathway. In ischemic mice, inhibition of Wnt5a mitigated vascular remodeling and subsequent ischemia. These findings highlighting the role of cell-cell crosstalk in ischemia and vascular remodeling. We found that the NETs-initiated fibroblast-SMC interaction is a critical regulator of limb ischemia via Wnt5a pathway, a potential therapeutic target for the treatment.

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

Intestinal cell diversity and treatment responses in a parasitic nematode at single cell resolution

BACKGROUND

Parasitic nematodes, significant pathogens for humans, animals, and plants, depend on diverse organ systems for intra-host survival. Understanding the cellular diversity and molecular variations underlying these functions holds promise for developing novel therapeutics, with specific emphasis on the neuromuscular system's functional diversity. The nematode intestine, crucial for anthelmintic therapies, exhibits diverse cellular phenotypes, and unraveling this diversity at the single-cell level is essential for advancing knowledge in anthelmintic research across various organ systems.

RESULTS

Here, using novel single-cell transcriptomics datasets, we delineate cellular diversity within the intestine of adult female Ascaris suum, a parasitic nematode species that infects animals and people. Gene transcripts expressed in individual nuclei of untreated intestinal cells resolved three phenotypic clusters, while lower stringency resolved additional subclusters and more potential diversity. Clusters 1 and 3 phenotypes displayed variable congruence with scRNA phenotypes of C. elegans intestinal cells, whereas the A. suum cluster 2 phenotype was markedly unique. Distinct functional pathway enrichment characterized each A. suum intestinal cell cluster. Cluster 2 was distinctly enriched for Clade III-associated genes, suggesting it evolved within clade III nematodes. Clusters also demonstrated differential transcriptional responsiveness to nematode intestinal toxic treatments, with Cluster 2 displaying the least responses to short-term intra-pseudocoelomic nematode intestinal toxin treatments.

CONCLUSIONS

This investigation presents advances in knowledge related to biological differences among major cell populations of adult A. suum intestinal cells. For the first time, diverse nematode intestinal cell populations were characterized, and associated biological markers of these cells were identified to support tracking of constituent cells under experimental conditions. These advances will promote better understanding of this and other parasitic nematodes of global importance, and will help to guide future anthelmintic treatments.

A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration

Ischaemic heart disease is a global healthcare challenge with high morbidity and mortality. Early revascularisation in acute myocardial infarction has improved survival; however, limited regenerative capacity and microvascular dysfunction often lead to impaired function and the development of heart failure. New mechanistic insights are required to identify robust targets for the development of novel strategies to promote regeneration. Single-cell RNA sequencing (scRNA-seq) has enabled profiling and analysis of the transcriptomes of individual cells at high resolution. Applications of scRNA-seq have generated single-cell atlases for multiple species, revealed distinct cellular compositions for different regions of the heart, and defined multiple mechanisms involved in myocardial injury-induced regeneration. In this review, we summarise findings from studies of healthy and injured hearts in multiple species and spanning different developmental stages. Based on this transformative technology, we propose a multi-species, multi-omics, meta-analysis framework to drive the discovery of new targets to promote cardiovascular regeneration.