Research Techniques Made Simple: Single-Cell RNA Sequencing and its Applications in Dermatology

A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Furthermore, we propose that bridging the gap between computational and wet lab scientists through user-friendly web-based platforms is needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

CHAI: Consensus Clustering Through Similarity Matrix Integration for Cell-Type Identification

Several methods have been developed to computationally predict cell-types for single cell RNA sequencing (scRNAseq) data. As methods are developed, a common problem for investigators has been identifying the best method they should apply to their specific use-case. To address this challenge, we present CHAI (consensus Clustering tHrough similArIty matrix integratIon for single cell type identification), a wisdom of crowds approach for scRNAseq clustering. CHAI presents two competing methods which aggregate the clustering results from seven state of the art clustering methods: CHAI-AvgSim and CHAI-SNF. Both methods demonstrate improved performance on a diverse selection of benchmarking datasets, besides also outperforming a previous consensus clustering method. We demonstrate CHAI's practical use case by identifying a leader tumor cell cluster enriched with CDH3. CHAI provides a platform for multiomic integration, and we demonstrate CHAI-SNF to have improved performance when including spatial transcriptomics data. CHAI is intuitive and easily customizable; it provides a way for users to add their own clustering methods to the pipeline, or down-select just the ones they want to use for the clustering aggregation. CHAI is available as an open source R package on GitHub: https://github.com/lodimk2/chai.

A guide to single-cell RNA sequencing analysis using web-based tools for non-bioinformatician

Single-cell RNA sequencing (scRNA-seq) is a technique that has proven to be a powerful tool for a wide range of fields and research studies. However, scRNA-seq data analysis has been dominated by scientists highly trained in bioinformatics or those with extensive computational experience and understanding. Recently, this trend has begun to shift as more user-friendly web-based scRNA-seq analysis tools have been developed that require little computational experience to use. However, barriers persist for nonbioinformaticians in using this technique. Complex, unfamiliar language and scarce comprehensive literature guidance to provide a framework for understanding scRNA-seq analysis outputs are among the obstacles. This work introduces many popular web-based tools for scRNA-seq and provides a general overview of their user interfaces and features. Then, a comprehensive start-to-finish introductory scRNA-seq analysis pipeline is described in detail, which aims to enable researchers to carry out scRNA-seq analysis, regardless of computational experience. Companion video tutorials can be found at "EasyScRNAseqTutorials" on YouTube (https://www.youtube.com/@scrnaseqtutorials). However, as scRNA-seq continues to penetrate new fields and expand in importance, there remains a need for more literature to help overcome barriers to its use by explaining further the highly complex and advanced analyses that are introduced within this paper.

Current annotation strategies for T cell phenotyping of single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) has become a popular technique for interrogating the diversity and dynamic nature of cellular gene expression and has numerous advantages in immunology. For example, scRNA-seq, in contrast to bulk RNA sequencing, can discern cellular subtypes within a population, which is important for heterogenous populations such as T cells. Moreover, recent advancements in the technology allow the parallel capturing of the highly diverse T-cell receptor (TCR) sequence with the gene expression. However, the field of single-cell RNA sequencing data analysis is still hampered by a lack of gold-standard cell phenotype annotation. This problem is particularly evident in the case of T cells due to the heterogeneity in both their gene expression and their TCR. While current cell phenotype annotation tools can differentiate major cell populations from each other, labelling T-cell subtypes remains problematic. In this review, we identify the common automated strategy for annotating T cells and their subpopulations, and also describe what crucial information is still missing from these tools.

How to explore what is hidden? A review of techniques for vascular tissue expression profile analysis

The evolution of plants to efficiently transport water and assimilates over long distances is a major evolutionary success that facilitated their growth and colonization of land. Vascular tissues, namely xylem and phloem, are characterized by high specialization, cell heterogeneity, and diverse cell components. During differentiation and maturation, these tissues undergo an irreversible sequence of events, leading to complete protoplast degradation in xylem or partial degradation in phloem, enabling their undisturbed conductive function. Due to the unique nature of vascular tissue, and the poorly understood processes involved in xylem and phloem development, studying the molecular basis of tissue differentiation is challenging. In this review, we focus on methods crucial for gene expression research in conductive tissues, emphasizing the importance of initial anatomical analysis and appropriate material selection. We trace the expansion of molecular techniques in vascular gene expression studies and discuss the application of single-cell RNA sequencing, a high-throughput technique that has revolutionized transcriptomic analysis. We explore how single-cell RNA sequencing will enhance our knowledge of gene expression in conductive tissues.

Human dermal fibroblast subpopulations and epithelial mesenchymal transition signals in hidradenitis suppurativa tunnels are normalized by spleen tyrosine kinase antagonism in vivo

Hidradenitis Suppurativa is a chronic inflammatory disease of which the pathogenesis is incompletely understood. Dermal fibroblasts have been previously identified as a major source of inflammatory cytokines, however information pertaining to the characteristics of subpopulations of fibroblasts in HS remains unexplored. Using in silico-deconvolution of whole-tissue RNAseq, Nanostring gene expression panels and confirmatory immunohistochemistry we identified fibroblast subpopulations in HS tissue and their relationship to disease severity and lesion morphology. Gene signatures of SFRP2+ fibroblast subsets were increased in lesional tissue, with gene signatures of SFRP1+ fibroblast subsets decreased. SFRP2+ and CXCL12+ fibroblast numbers, measured by IHC, were increased in HS tissue, with greater numbers associated with epithelialized tunnels and Hurley Stage 3 disease. Pro-inflammatory CXCL12+ fibroblasts were also increased, with reductions in SFRP1+ fibroblasts compared to healthy controls. Evidence of Epithelial Mesenchymal Transition was seen via altered gene expression of SNAI2 and altered protein expression of ZEB1, TWIST1, Snail/Slug, E-Cadherin and N-Cadherin in HS lesional tissue. The greatest dysregulation of EMT associated proteins was seen in biopsies containing epithelialized tunnels. The use of the oral Spleen tyrosine Kinase inhibitor Fostamatinib significantly reduced expression of genes associated with chronic inflammation, fibroblast proliferation and migration suggesting a potential role for targeting fibroblast activity in HS.

Applications of Human Pluripotent Stem Cell-Derived Skin Organoids in Dermatology

Pluripotent stem cells have the potential to become any cell type, and recently, they have been used to create organoids that can recapitulate several pertinent features of human organs. Skin organoids have been developed that possess many of the crucial accessory organs, including hair follicles, sebaceous glands, nerves, fat, and melanocytes. These skin organoids present the opportunity to study skin development and disease as well as perform screens to identify new drug candidates. In the future, skin organoids might augment clinical practice by serving as source material for transplantation to treat wounds or other conditions. Nevertheless, several limitations, such as the lengthy differentiation protocol, which can result in heterogeneous products, must first be addressed before the full potential of skin organoids can be realized. The purpose of this article is to provide a broad overview of skin organoids so that a broader audience can become familiar with this technology, which has important implications for dermatologic research and medicine.

Updated skin transcriptomic atlas depicted by reciprocal contribution of single-nucleus RNA sequencing and single-cell RNA sequencing

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of skin biology, but its utility is restricted by the requirement of fresh samples, inadequate dissociation-induced cell loss or death, and activation during tissue digestion. Single-nucleus RNA sequencing (snRNA-seq) can use frozen, hard-to-dissociate materials, which might be a promising method to circumvent the limitations of scRNA-seq for the skin tissue.

OBJECTIVE

To profile skin cells using snRNA-seq in parallel with scRNA-seq.

METHODS

We performed snRNA-seq in parallel with scRNA-seq for the bisected skin sample of one person and integrated previously published scRNA-seq data for analysis. We comparatively analyzed the differences in cell proportions and gene expression between the two methods. The differentiation trajectories of keratinocytes and fibroblasts were analyzed by Slingshot analysis.

RESULTS

snRNA-seq was less susceptible to contamination from mitochondrial and ribosomal RNA, and exhibited a greater capacity to detect transcription factors. snRNA-seq identified more spatially and functionally relevant keratinocyte clusters that constitute cell trajectories with expected differentiation dynamics. Novel markers, e.g., LYPD3, EMP2, and CSTB, were revealed for different differentiation stages of keratinocytes, and NFIB and GRHL1 were identified as transcription factors involving in the proliferation and functional differentiation of keratinocytes. Fibroblasts were found in a state of activation in scRNA-seq. And scRNA-seq detected a greater number of immune cells.

CONCLUSIONS

We generated an updated atlas of the skin transcriptome based on the reciprocal contribution of scRNA-seq and snRNA-seq.

The Use of Single-Cell RNA-Sequencing and Spatial Transcriptomics in Understanding the Pathogenesis and Treatment of Skin Diseases

The development of multiomic profiling tools has rapidly expanded in recent years, along with their use in profiling skin tissues in various contexts, including dermatologic diseases. Among these tools, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST) have emerged as widely adopted and powerful assays for elucidating key cellular components and their spatial arrangement within skin disease. In this paper, we review the recent biological insights gained from the use of scRNA-seq and ST and the advantages of combining both for profiling skin diseases, including aberrant wound healing, inflammatory skin diseases, and cancer. We discuss the role of scRNA-seq and ST in improving skin disease treatments and moving toward the goal of achieving precision medicine in dermatology, whereby patients can be optimally matched to treatments that maximize therapeutic response.

What has single-cell transcriptomics taught us about long non-coding RNAs in the ventricular-subventricular zone?

Long non-coding RNA (lncRNA) function is mediated by the process of transcription or through transcript-dependent associations with proteins or nucleic acids to control gene regulatory networks. Many lncRNAs are transcribed in the ventricular-subventricular zone (V-SVZ), a postnatal neural stem cell niche. lncRNAs in the V-SVZ are implicated in neurodevelopmental disorders, cancer, and brain disease, but their functions are poorly understood. V-SVZ neurogenesis capacity declines with age due to stem cell depletion and resistance to neural stem cell activation. Here we analyzed V-SVZ transcriptomics by pooling current single-cell RNA-seq data. They showed consistent lncRNA expression during stem cell activation, lineage progression, and aging. In conjunction with epigenetic and genetic data, we predicted V-SVZ lncRNAs that regulate stem cell activation and differentiation. Some of the lncRNAs validate known epigenetic mechanisms, but most remain uninvestigated. Our analysis points to several lncRNAs that likely participate in key aspects of V-SVZ stem cell activation and neurogenesis in health and disease.

Single-cell transcriptome profile of mouse skin undergoing antigen-driven allergic inflammation recapitulates findings in atopic dermatitis skin lesions

BACKGROUND

Allergic skin inflammation elicited in mice by epicutaneous (EC) sensitization with antigen shares characteristics with human atopic dermatitis (AD).

OBJECTIVE

We characterized gene expression by single cells in mouse skin undergoing antigen-driven allergic inflammation and compared the results with findings in AD skin lesions.

METHODS

Mice were EC sensitized by application of ovalbumin (OVA) or saline to tape-stripped skin. Single-cell RNA sequencing was performed on skin cells 12 days later. Flow cytometry analysis was performed to validate results.

RESULTS

Sequencing identified 7 nonhematopoietic and 6 hematopoietic cell subsets in EC-sensitized mouse skin. OVA sensitization resulted in the expansion in the skin of T cells, dendritic cells, macrophages, mast cells/basophils, fibroblasts, and myocytes cell clusters, and in upregulation of T_H2 cytokine gene expression in CD4⁺ T cells and mast cells/basophils. Genes differentially expressed in OVA-sensitized skin included genes important for inflammation in dendritic cells and macrophages, collagen deposition, and leukocyte migration in fibroblasts, chemotaxis in endothelial cells and skin barrier integrity, and differentiation in KCs-findings that recapitulate those in AD skin lesions. Unexpectedly, mast cells/basophils, rather than T cells, were the major source of Il4 and ll13 in OVA-sensitized mouse skin. In addition, our results suggest novel pathways in fibroblast and endothelial cells that may contribute to allergic skin inflammation.

CONCLUSION

The gene expression profile of single cells in mouse skin undergoing antigen-driven shares many features with that in AD skin lesions and unveils novel pathways that may be involved in allergic skin inflammation.

Single‐cell RNA sequencing in oral science: Current awareness and perspectives

The emergence of single‐cell RNA sequencing enables simultaneous sequencing of thousands of cells, making the analysis of cell population heterogeneity more efficient. In recent years, single‐cell RNA sequencing has been used in the investigation of heterogeneous cell populations, cellular developmental trajectories, stochastic gene transcriptional kinetics, and gene regulatory networks, providing strong support in life science research. However, the application of single‐cell RNA sequencing in the field of oral science has not been reviewed comprehensively yet. Therefore, this paper reviews the development and application of single‐cell RNA sequencing in oral science, including fields of tissue development, teeth and jaws diseases, maxillofacial tumors, infections, etc., providing reference and prospects for using single‐cell RNA sequencing in studying the oral diseases, tissue development, and regeneration.

Research Techniques Made Simple: Spatial Transcriptomics

Transcriptome profiling of tissues and single cells facilitates interrogation of gene expression changes within diverse biological contexts. However, spatial information is often lost during tissue homogenization or dissociation. Recent advances in transcriptome profiling preserve the in situ spatial contexts of RNA molecules and together comprise a group of techniques known as spatial transcriptomics (ST), enabling localization of cell types and their associated gene expression within intact tissues. In this paper, we review ST methods; summarize data analysis approaches, including integration with single-cell transcriptomics data; and discuss their applications in dermatologic research. These tools offer a promising avenue toward improving our understanding of niche patterning and cell‒cell interactions within heterogeneous tissues that encompass skin homeostasis and disease.

Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis-and what ceases to work in diverse dermatological diseases-have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-the-art of skin biology using single-cell technologies, with a special focus on skin pathologies and the translation of mechanistic findings to the clinic. The main implications of this review are to summarize the benefits and limitations of single-cell analysis and thus help translate the emerging insights from these novel techniques to the bedside.

Advances in single-cell sequencing and its application to musculoskeletal system research

In recent years, single-cell sequencing (SCS) technologies have continued to advance with improved operating procedures and reduced cost, leading to increasing practical adoption among researchers. These emerging technologies have superior abilities to analyse cell heterogeneity at a single-cell level, which have elevated multi-omics research to a higher level. In some fields of research, application of SCS has enabled many valuable discoveries, and musculoskeletal system offers typical examples. This article reviews some major scientific issues and recent advances in musculoskeletal system. In addition, combined with SCS technologies, the research of cell or tissue heterogeneity in limb development and various musculoskeletal system clinical diseases also provides new possibilities for treatment strategies. Finally, this article discusses the challenges and future development potential of SCS and recommends the direction of future applications of SCS to musculoskeletal medicine.

Single-cell RNA sequencing and bioinformatics as tools to decipher cancer heterogenicity and mechanisms of drug resistance

It is well known that cancer is an aggressive disease, often associated with relapse, in many cases due to drug resistance. Cancer stem cell and clonal evolution are frequently causes of innate or acquired drug resistance. Current RNA sequencing technologies do not distinguish gene expression of different cell lineages because they are based on bulk cell studies. Single-cell RNA sequencing technologies and related bioinformatics clustering and differential expression analysis represent a turning point in cancer research. They are emerging as essential tools for dissecting tumors at single-cell resolution and represent novel tools to understand carcinogenesis and drug response. In this review, we will outline the role of these new technologies in addressing cancer heterogeneity and cell lineage-dependent drug resistance.

An easy-to-operate method for single-cell isolation and retrieval using a microfluidic static droplet array

In-depth study of cellular heterogeneity of rare cells (e.g. circulating tumour cells (CTCs) and circulating foetal cells (CFCs)) is greatly needed in disease management but has never been completely explored due to the current technological limitations. We have developed a retrieval method for single-cell detection using a static droplet array (SDA) device through liquid segmentation with almost no sample loss. We explored the potential of using SDA for low sample input and retrieving the cells of interest using everyday laboratory equipment for downstream molecular analysis. This single-cell isolation and retrieval method is low-cost, rapid and provides a solution to the remaining challenge for single rare cell detection. The entire process takes less than 15 min, is easy to fabricate and allows for on-chip analysis of cells in nanolitre droplets and retrieval of desired droplets. To validate the applicability of our device and method, we mimicked detection of single CTCs by isolating and retrieving single cells and perform real-time PCR on their mRNA contents.

Translational Research in Vitiligo

Vitiligo is a disease of the skin characterized by the appearance of white spots. Significant progress has been made in understanding vitiligo pathogenesis over the past 30 years, but only through perseverance, collaboration, and open-minded discussion. Early hypotheses considered roles for innervation, microvascular anomalies, oxidative stress, defects in melanocyte adhesion, autoimmunity, somatic mosaicism, and genetics. Because theories about pathogenesis drive experimental design, focus, and even therapeutic approach, it is important to consider their impact on our current understanding about vitiligo. Animal models allow researchers to perform mechanistic studies, and the development of improved patient sample collection methods provides a platform for translational studies in vitiligo that can also be applied to understand other autoimmune diseases that are more difficult to study in human samples. Here we discuss the history of vitiligo translational research, recent advances, and their implications for new treatment approaches.

Advances in resolving the heterogeneity and dynamics of keratinocyte differentiation

The mammalian skin is equipped with a highly dynamic stratified epithelium. The maintenance and regeneration of this epithelium is supported by basally located keratinocytes, which display stem cell properties, including lifelong proliferative potential and the ability to undergo diverse differentiation trajectories. Keratinocytes support not just the surface of the skin, called the epidermis, but also a range of ectodermal structures including hair follicles, sebaceous glands, and sweat glands. Recent studies have shed light on the hitherto underappreciated heterogeneity of keratinocytes by employing state-of-the-art imaging technologies and single-cell genomic approaches. In this mini review, we highlight major recent discoveries that illuminate the dynamics and cellular mechanisms that govern keratinocyte differentiation in the live mammalian skin and discuss the broader implications of these findings for our understanding of epithelial and stem cell biology in general.

Single-cell transcriptomics in dermatology

The skin is an ecosystem composed of specialized cell types that work together to serve as a physical protective barrier. Single-cell resolution is therefore essential to deconvolve skin's heterogeneity by identifying novel, distinct cell subsets in health and disease. Single-cell RNA sequencing is a highly meticulous methodology used to study the distinct transcriptional profiles of each cell within large tissue libraries at uniquely high resolution. The investigative capabilities achieved by this methodology allow previously unattainable analyses, including identification of rare cell populations, evaluation of cell-to-cell variation, and the ability to track trajectories of distinct cell lineages through development. In the past decade, application of transcriptomic analysis to skin biology and dermatology has greatly advanced understanding of homeostatic physiology in the skin, as well as a multitude of dermatologic diseases. Single-cell RNA sequencing offers tremendous promise for identification of novel therapeutic targets in dermatologic diseases, with broad implications of improving therapeutic interventions.

Application of single-cell RNA sequencing in embryonic development

Embryonic development is a complex process that is regulated by a series of precise cellular behaviours. The limited number of cells in the early stages of embryonic development represents a challenge for studying early gene regulation and maintaining cell sternness. Single-cell sequencing is a new technology for high-throughput sequencing analysis at the single-cell level that not only reflects the heterogeneity between cells but also reveals gene expression characteristics in different cells from limited samples. Currently, the widespread application of single-cell RNA sequencing technology is gradually changing our understanding of disease pathogenesis. This article reviews the application of single-cell RNA sequencing in embryonic development in recent years and provides innovative ideas for research on embryonic development and the treatment of diseases related to embryonic development.

Histone deacetylase 3 controls lung alveolar macrophage development and homeostasis

Alveolar macrophages (AMs) derived from embryonic precursors seed the lung before birth and self-maintain locally throughout adulthood, but are regenerated by bone marrow (BM) under stress conditions. However, the regulation of AM development and maintenance remains poorly understood. Here, we show that histone deacetylase 3 (HDAC3) is a key epigenetic factor required for AM embryonic development, postnatal homeostasis, maturation, and regeneration from BM. Loss of HDAC3 in early embryonic development affects AM development starting at E14.5, while loss of HDAC3 after birth affects AM homeostasis and maturation. Single-cell RNA sequencing analyses reveal four distinct AM sub-clusters and a dysregulated cluster-specific pathway in the HDAC3-deficient AMs. Moreover, HDAC3-deficient AMs exhibit severe mitochondrial oxidative dysfunction and deteriorative cell death. Mechanistically, HDAC3 directly binds to Pparg enhancers, and HDAC3 deficiency impairs Pparg expression and its signaling pathway. Our findings identify HDAC3 as a key epigenetic regulator of lung AM development and homeostasis.

Alveolar macrophages are known to derive from embryonic precursors although the regulation of this process is poorly understood. Here the authors propose a key role for histone deacetylase 3 as an epigenetic regulator of lung alveolar macrophage development.

Defining the Skin Cellular Community Using Single-Cell Genomics to Advance Precision Medicine

Single-cell genomics has revolutionized biological science, enabling high-resolution analysis of human tissues. The ability to demonstrate the role and function of distinct cell types comprising human tissues paves the way for a new understanding of cellular pathways, interactions, and future research directions. The skin, easily accessible and possessing a diverse and complex role in defending us both physically and immunologically from the outside world, lends itself ideally to single-cell genomics analysis. Here, we outline the benefits of single-cell RNA sequencing while also highlighting the challenges in achieving a meaningful result from its use. Key milestones relating to the study of skin in this way are introduced, covering both healthy and diseased states, and we discuss the potential promise of single-cell RNA sequencing to result in tangible medical advances, with a particular focus on precision medicine.

Corneal epithelial biology: Lessons stemming from old to new

The anterior surface of the eye functions as a barrier to the external environment and protects the delicate underlying tissues from injury. Central to this protection are the corneal, limbal and conjunctival epithelia. The corneal epithelium is a self-renewing stratified squamous epithelium that protects the underlying delicate structures of the eye, supports a tear film and maintains transparency so that light can be transmitted to the interior of the eye (Basu et al., 2014; Cotsarelis et al., 1989; Funderburgh et al., 2016; Lehrer et al., 1998; Pajoohesh-Ganji and Stepp, 2005; Parfitt et al., 2015; Peng et al., 2012b; Stepp and Zieske, 2005). In this review, dedicated to James Funderburgh and his contributions to visual science, in particular the limbal niche, corneal stroma and corneal stromal stem cells, we will focus on recent data on the identification of novel regulators in corneal epithelial cell biology, their roles in stem cell homeostasis, wound healing, limbal/corneal boundary maintenance and the utility of single cell RNA sequencing (scRNA-seq) in vision biology studies.

An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components

This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components. The information technology is presented as a structural block-chart, which contains all stages of the studied data processing. The hybrid model of objective clustering based on the SOTA algorithm and the technology of gene regulatory networks reconstruction have been investigated to evaluate the stability to the level of the noise components. The results of the simulation have shown that the hybrid model of the objective clustering has high level of stability to noise components and vice versa, the technology of gene regulatory networks reconstruction is rather sensitive to the level of noise component. The obtained results indicate the importance of gene expression profiles preprocessing at the early stage of the gene regulatory network reconstruction in order to remove background noise and non-informative genes in terms of the used criteria.