Single-cell RNA Sequencing Datasets Research Articles

Disease-specific transcriptional programs govern airway goblet cell metaplasia

Hypersecretion of airway mucus caused by goblet cell metaplasia is a characteristic of chronic pulmonary inflammatory diseases including asthma, cystic fibrosis (CF), and chronic obstructive pulmonary disease (COPD). Goblet cells mainly originate from airway progenitor club cells. However, the molecular mechanisms and features of goblet cell metaplasia in lung disease are poorly understood. Herein, public single-cell RNA sequencing datasets of human lungs were reanalyzed to explore the transitional phase as club cells differentiate into goblet cells in asthma, CF, and COPD. We found that changes in club and goblet cells during pathogenesis and cellular transition were associated with signalling pathways related to immune response, oxidative stress, and apoptosis. Moreover, other key drivers of goblet cell specification appeared to be pathologically specific, with interleukin (IL)-13 and hypoxia inducible factor 1 (HIF-1)-induced genetic changes in asthma, cystic fibrosis transmembrane conductance regulator (CFTR) mutation being present in CF, and interactions with CD8+ T cells, mitophagy, and mitochondria-induced apoptosis in COPD. In conclusion, this study revealed the similarities and differences in goblet cell metaplasia in asthma, CF, and COPD at the transcriptome level, thereby providing insights into possible novel therapeutic approaches for these diseases.

T-distributed Stochastic Neighbor Network for unsupervised representation learning

Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution kernel) for exploring meaningful structural information from generic data including vector, image and tabular data. In this paper, we propose a simple end-to-end T-distributed Stochastic Neighbor Network (TsNet) for URL with clustering downstream task. Concretely, our TsNet model has three major components: (1) an adaptive connectivity distribution learning module is presented to construct a pairwise graph for preserving the local structure of generic data; (2) a T-distributed stochastic neighbor embedding based loss function is designed to learn a transformation between embeddings and original data, which improves the discrimination of representations; (3) a nonlinear parametric mapping is learned via our TsNet on an unsupervised generalized manner, which can address the “out-of-sample” issue. By combining these components, our method is able to considerably outperform previous related unsupervised learning approaches on visualization and clustering of generic data. A simple deep neural network equipped on our model respectively achieves 74.90%, 76.56% ACC and NMI, which is 8% relative improvement over previous state-of-the-art on real single-cell RNA-sequencing (scRNA-seq) datasets clustering.

Single-Cell Analysis Identifies Distinct Populations of Cytotoxic CD4+ T Cells Linked to the Therapeutic Efficacy of Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma.

The involvement of cytotoxic CD4+ T cells (CD4+ CTLs) and their potential role in dictating the response to immune checkpoint inhibitors (ICIs) in patients with metastatic renal cell carcinoma (mRCC) remains an unexplored area of research. Utilizing single-cell RNA sequencing, we analyzed the immunophenotype and expression patterns of CD4+ T lymphocyte subtypes in mRCC patients, followed by preliminary validation via multi-immunofluorescent staining. In addition, we obtained a comprehensive immunotherapy dataset encompassing single-cell RNA sequencing datasets and bulk RNA-seq cohorts from the European Genome-Phenome Archive and ArrayExpress database. Utilizing the CIBERSORTx deconvolution algorithms, we derived a signature score for CD4+ CTLs from the bulk-RNA-seq datasets of the CheckMate 009/025 clinical trials. Single-cell analysis of CD4+ T lymphocytes in mRCC reveals several cancer-specific states, including diverse phenotypes of regulatory T cells. Remarkably, we observe that CD4+ CTLs cells constitute a substantial proportion of all CD4+ T lymphocyte sub-clusters in mRCC patients, highlighting their potential significance in the disease. Furthermore, within mRCC patients, we identify two distinct cytotoxic states of CD4+ T cells: CD4+GZMK+ T cells, which exhibit a weaker cytotoxic potential, and CD4+GZMB+ T cells, which demonstrate robust cytotoxic activity. Both regulatory T cells and CD4+ CTLs originate from proliferating CD4+ T cells within mRCC tissues. Intriguingly, our trajectory analysis indicates that the weakly cytotoxic CD4+GZMK+ T cells differentiate from their more cytotoxic CD4+GZMB+ counterparts. In comparing patients with lower CD4+ CTLs levels to those with higher CD4+ CTLs abundance in the CheckMate 009 and 25 immunotherapy cohorts, the latter group exhibited significantly improved OS and PFS probability. Our study underscores the pivotal role that intratumoral CD4+ CTLs may play in bolstering anti-tumor immunity, suggesting their potential as a promising biomarker for predicting response to ICIs in patients with mRCC.

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma.

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response. RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types. Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8. TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.

Synthetic DNA barcodes identify singlets in scRNA-seq datasets and evaluate doublet algorithms

Single-cell RNA sequencing (scRNA-seq) datasets contain true single cells, or singlets, in addition to cells that coalesce during the protocol, or doublets. Identifying singlets with high fidelity in scRNA-seq is necessary to avoid false negative and false positive discoveries. Although several methodologies have been proposed, they are typically tested on highly heterogeneous datasets and lack a priori knowledge of true singlets. Here, we leveraged datasets with synthetically introduced DNA barcodes for a hitherto unexplored application: to extract ground-truth singlets. We demonstrated the feasibility of our framework, "singletCode," to evaluate existing doublet detection methods across a range of contexts. We also leveraged our ground-truth singlets to train a proof-of-concept machine learning classifier, which outperformed other doublet detection algorithms. Our integrative framework can identify ground-truth singlets and enable robust doublet detection in non-barcoded datasets.

Cell type-specific expression of angiotensin receptors in the human lung with implications for health, aging, and chronic disease.

The renin-angiotensin system is a highly characterized integrative pathway in mammalian homeostasis whose clinical spectrum has been expanded to lung disorders such as chronic obstructive pulmonary disease (COPD)-emphysema, idiopathic pulmonary fibrosis (IPF), and COVID pathogenesis. Despite this widespread interest, specific localization of this receptor family in the mammalian lung is limited, partially due to the imprecision of available antibody reagents. In this study, we establish the expression pattern of the two predominant angiotensin receptors in the human lung, AGTR1 and AGTR2, using complementary and comprehensive bulk and single-cell RNA-sequence datasets that are publicly available. We show these two receptors have distinct localization patterns and developmental trajectories in the human lung, pericytes for AGTR1 and a subtype of alveolar epithelial type 2 cells for AGTR2. In the context of disease, we further pinpoint AGTR2 localization to the COPD-associated subpopulation of alveolar epithelial type 2 (AT2B) and AGTR1 localization to fibroblasts, where their expression is upregulated in individuals with COPD, but not in individuals with IPF. Finally, we examine the genetic variation of the angiotensin receptors, finding AGTR2 associated with lung phenotype (i.e., cystic fibrosis) via rs1403543. Together, our findings provide a critical foundation for delineating this pathway's role in lung homeostasis and constructing rational approaches for targeting specific lung disorders.

Recessive variants in MYO1C as a potential novel cause of proteinuric kidney disease.

Steroid-resistant nephrotic syndrome is the second leading cause of chronic kidney disease among patients < 25years of age. Through exome sequencing, identification of > 65 monogenic causes has revealed insights into disease mechanisms of nephrotic syndrome (NS). To elucidate novel monogenic causes of NS, we combined homozygosity mapping with exome sequencing in a worldwide cohort of 1649 pediatric patients with NS. We identified homozygous missense variants in MYO1C in two unrelated children with NS (c.292C > T, p.R98W; c.2273 A > T, p.K758M). We evaluated publicly available kidney single-cell RNA sequencing datasets and found MYO1C to be predominantly expressed in podocytes. We then performed structural modeling for the identified variants in PyMol using aligned shared regions from two available partial structures of MYO1C (4byf and 4r8g). In both structures, calmodulin, a common regulator of myosin activity, is shown to bind to the IQ motif. At both residue sites (K758; R98), there are ion-ion interactions stabilizing intradomain and ligand interactions: R98 binds to nearby D220 within the myosin motor domain and K758 binds to E14 on a calmodulin molecule. Variants of these charged residues to non-charged amino acids could ablate these ionic interactions, weakening protein structure and function establishing the impact of these variants. We here identified recessive variants in MYO1C as a potential novel cause of NS in children.

The transcriptomic and spatial organization of telencephalic GABAergic neuronal types.

The telencephalon of the mammalian brain comprises multiple regions and circuit pathways that play adaptive and integrative roles in a variety of brain functions. There is a wide array of GABAergic neurons in the telencephalon; they play a multitude of circuit functions, and dysfunction of these neurons has been implicated in diverse brain disorders. In this study, we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished by utilizing 611,423 single-cell transcriptomes from the comprehensive and high-resolution transcriptomic and spatial cell type atlas for the adult whole mouse brain we have generated, supplemented with an additional single-cell RNA-sequencing dataset containing 99,438 high-quality single-cell transcriptomes collected from the pre- and postnatal developing mouse brain. We present a hierarchically organized adult telencephalic GABAergic neuronal cell type taxonomy of 7 classes, 52 subclasses, 284 supertypes, and 1,051 clusters, as well as a corresponding developmental taxonomy of 450 clusters across different ages. Detailed charting efforts reveal extraordinary complexity where relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types can often be found in distant and diverse brain regions indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Additionally, we find various spatial dimensions of both discrete and continuous variations among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal and most pallidal GABAergic neuronal types emerge simultaneously during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell type taxonomy can serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

Disease activity drives divergent epigenetic and transcriptomic reprogramming of monocyte subpopulations in systemic lupus erythematosus

ObjectivesSystemic lupus erythematosus (SLE) is characterised by systemic inflammation involving various immune cell types. Monocytes, pivotal in promoting and regulating inflammation in SLE, differentiate from classic monocytes into intermediate and...

Integrated spatial and multimodal single-cell transcriptomics reveal patient-dependent cell heterogeneity in splenic marginal zone lymphoma.

Biological hallmarks of splenic marginal zone lymphoma (SMZL) remain poorly described. Herein, we performed in-depth SMZL characterization through multimodal single-cell analyses of paired blood/spleen samples. The 3'-single-cell RNA-sequencing, Cellular Indexing of Transcriptomes and Epitopes by sequencing, and 5'-V(D)J single-cell RNA-sequencing datasets were integrated to characterize SMZL transcriptome profiles, including B-cell receptor and T-cell receptor repertoires. Hyperexpanded B-cell clones in the spleen were at a memory-like stage, whereas recirculating tumor B-cells in blood encompassed multiple differentiation stages, indicating an unexpected desynchronization of the B-cell maturation program in SMZL cells. Spatial transcriptomics showed the enrichment of T-effector and T-follicular helper (TFH) signatures in the nodular subtype of SMZL. This latter also exhibited gene-based cell-cell interactions suggestive of dynamic crosstalk between TFH and cancer cells in transcriptomics, further substantiated by using imaging mass cytometry. Our findings provide a comprehensive high-resolution description of SMZL biological hallmarks and characterize, for the first time in situ, inter- and intra-patient heterogeneity at both transcriptomic and protein levels. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Single-cell transcriptome analysis reveals the regulatory functions of islet exocrine cells after short-time obesogenic diet.

This study aims to investigate the functions of exocrine islet cell subtypes in the early stage of obesity induced by high-fat diet (HFD), which is accompanied with deterioration of the systemic insulin response and islet subpopulation abnormalities. In this study, we analyzed published islet single-cell RNA sequencing (scRNA-seq) datasets from the early stage induced by HFD feeding. Bioinformatics tools such as findMarkers, Cellchat, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and Gene Ontology (GO) terms were applied to identify the different functions of exocrine cell clusters. A total of 26 cell clusters were obtained were identified from this dietary intervention model. Most proportions of cell subtypes were consistent between high-fat diet (HFD) and low-fat diet (LFD) groups, except for partial endocrine islet clusters and exocrine clusters. Most differentiated expression of genes in the HFD group was found in exocrine cluster. And we also found that the cell-cell interactions between ductal and endothelial cells were reduced in the HFD group, with the significant alteration in C17 (ductal) cluster. By further analyzing the co-expression regulatory network of transcription in the C17 cluster, we speculate that differentially expressed transcription factors affected the function of duct cells by affecting the expression of related genes in intercellular interaction networks, thereby promoting insulin resistance (IR) development. Our results provide a reference for the function and regulatory mechanisms of exocrine cells in the obesity induced by HFD and probably influence the process of following insulin resistance.

Non-canonical Wnt pathway expression in the developing mouse and human retina

The non-canonical Wnt pathway is an evolutionarily conserved pathway essential for tissue patterning and development across species and tissues. In mammals, this pathway plays a role in neuronal migration, dendritogenesis, axon growth, and synapse formation. However, its role in development and synaptogenesis of the human retina remains less established. In order to address this knowledge gap, we analyzed publicly available single-cell RNA sequencing (scRNAseq) datasets for mouse retina, human retina, and human retinal organoids over multiple developmental time points during outer retinal maturation. We identified ligands, receptors, and mediator genes with a putative role in retinal development, including those with novel or species-specific expression, and validated this expression using fluorescence in situ hybridization (FISH). By quantifying outer nuclear layer (ONL) versus inner nuclear layer (INL) expression, we provide evidence for the differential expression of certain non-canonical Wnt signaling components in the developing mouse and human retina during outer plexiform layer (OPL) development. Importantly, we identified distinct expression patterns of mouse and human FZD3 and WNT10A, as well as previously undescribed expression, such as for mouse Wnt2b in Chat+ starburst amacrine cells. Human retinal organoids largely recapitulated the human non-canonical Wnt pathway expression. Together, this work provides the basis for further study of non-canonical Wnt signaling in mouse and human retinal development and synaptogenesis.

Identification of a Macrophage marker gene signature to evaluate immune infiltration and therapeutic response in hepatocellular carcinoma

BackgroundOnly a minority of hepatocellular carcinoma (HCC) patients can benefit from systemic regimens. Macrophages, which abundantly infiltrate in HCC, could mediate tumour microenvironment remodelling and immune escape, proving to be powerful weapons in combating HCC. Thus, a deeper understanding of macrophages is necessary for improving existing antitumour treatments. MethodsWith a series of bioinformatic approaches, we comprehensively explored the role of macrophage-related genes in human HCCs from multiple single-cell and bulk RNA sequencing datasets. Unsupervised clustering was performed to cluster the macrophage marker genes (MMGs). GSVA and functional enrichment analysis were used to elucidate the functional differences among the MMG-associated clusters. Subsequently, a component analysis algorithm was used to construct a Macrosig score, and the prognosis, biological characteristics, mutation profile, TME cell infiltration status and drug response of patients with different Macrosig scores were further analysed. ResultsWe identified 13 MMGs in 574 HCC samples, based on which three MMG-associated clusters were defined. Overall survival time, clinicopathological features and immune infiltration scores differed among the different clusters. On this basis, 12 hub genes were identified among these clusters; subsequently, a scoring system was constructed to determine the Macrosig score. Importantly, patients with low-Macrosig scores, characterized by increased immune infiltration, increased mutation frequency and increased immune checkpoint expression, including CTLA-4, LAG3, PDCD1 and TIGIT, exhibited enhanced efficacy of immunotherapy when validated in an external database. Moreover, a low-Macrosig score indicates increased sensitivity to AZD.2281, A.443654, ABT.263, ABT.888, AG.014699 and ATRA, while a high Macrosig score indicates increased sensitivity to AZD6482, AKT inhibitor VIII, AS601245, AZ628, AZD.0530 and AZD6244. ConclusionsA novel scoring system was constructed to guide more effective prognostic evaluation and tailoring therapeutic regimens for HCC patients.

A multi-platform analysis of human gingival crevicular fluid reveals ferroptosis as a relevant regulated cell death mechanism during the clinical progression of periodontitis.

Ferroptosis is implicated in the pathogenesis of numerous chronic-inflammatory diseases, yet its association with progressive periodontitis remains unexplored. To investigate the involvement and significance of ferroptosis in periodontitis progression, we assessed sixteen periodontitis-diagnosed patients. Disease progression was clinically monitored over twelve weeks via weekly clinical evaluations and gingival crevicular fluid (GCF) collection was performed for further analyses. Clinical metrics, proteomic data, in silico methods, and bioinformatics tools were combined to identify protein profiles linked to periodontitis progression and to explore their potential connection with ferroptosis. Subsequent western blot analyses validated key findings. Finally, a single-cell RNA sequencing (scRNA-seq) dataset (GSE164241) for gingival tissues was analyzed to elucidate cellular dynamics during periodontitis progression. Periodontitis progression was identified as occurring at a faster rate than traditionally thought. GCF samples from progressing and non-progressing periodontal sites showed quantitative and qualitatively distinct proteomic profiles. In addition, specific biological processes and molecular functions during progressive periodontitis were revealed and a set of hub proteins, including SNCA, CA1, HBB, SLC4A1, and ANK1 was strongly associated with the clinical progression status of periodontitis. Moreover, we found specific proteins - drivers or suppressors - associated with ferroptosis (SNCA, FTH1, HSPB1, CD44, and GCLC), revealing the co-occurrence of this specific type of regulated cell death during the clinical progression of periodontitis. Additionally, the integration of quantitative proteomic data with scRNA-seq analysis suggested the susceptibility of fibroblasts to ferroptosis. Our analyses reveal proteins and processes linked to ferroptosis for the first time in periodontal patients, which offer new insights into the molecular mechanisms of progressive periodontal disease. These findings may lead to novel diagnostic and therapeutic strategies.

SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.

SuperFeat: Quantitative Features Learning from Single-cell RNAseq Data Facilitates Drug Repurposing

Abstract In this study, we have devised a computational framework called Supervised Feature Learning and Scoring (SuperFeat) that allows for the training of a machine learning model and evaluates the canonical cellular status/features in pathological tissues that underlie the progression of disease. This framework also enables the identification of potential drugs that target the presumed detrimental cellular features. This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes. The training data comprised single-cell RNA sequencing datasets that encompassed the specific cell lineage during the developmental progression of cell features. A few models of the canonical cancer-involved cellular status/features were tested by such framework. Finally, we have illustrated the drug repurposing pipeline, utilizing the training parameters derived from the adverse cellular status/features, which has yielded successful validation results both in vitro and in vivo. SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

P39 Using single-cell transcriptomics to investigate the potential role of the human hair follicle dermal papilla in controlling hair fibre pigmentation

Abstract Introduction and aims The human dermal papilla (DP) is a population of cells located at the base of the hair follicle, which signals to surrounding matrix cells facilitating their incorporation into the layers of the hair fibre and the hair follicle. The DP controls the process of hair follicle induction, reflecting its critical role in orchestrating processes integral in hair growth. We hypothesize that distinct functional subgroups exist within the structure, which would mean that there are different types of DP cells within each follicle. Methods To begin testing this, we reanalysed the single-cell RNA sequencing (RNA-Seq) dataset of the human anagen hair follicle used in the 2022 study by Shim et al. To expand on this, we are now generating single-cell RNA-Seq datasets of patient-matched pigmented and nonpigmented hair follicles (n = 4 patients). These datasets will be used to explore heterogeneity in the human DP, and to investigate which subpopulations are potentially changed in the case of pigmentation loss. This will allow us to explore a potentially undiscovered role of the DP in controlling hair fibre pigmentation. Results We found four distinct subpopulations in the DP with statistically significant marker genes in the Shim dataset. This confirms transcriptional heterogeneity in the human DP, hinting at clusters of DP cells with specialized functions within each hair follicle. One subcluster, which expressed S100B, endothelin-3 and bone morphogenetic protein (BMP)4, was of particular interest and gene ontology analysis of the genes in this cluster revealed terms associated with skeletal development and BMP signalling. We hypothesize that this DP cluster regulates melanin transfer from bulbar melanocytes to neighbouring keratinocytes, owing to the known involvement of the mentioned genes in both melanogenesis and melanin transfer. Conclusions The human DP is a heterogeneic structure, with a potentially unexplored role in controlling hair fibre pigmentation.

P14 Characterizing the hair follicle–nervous system connection

Abstract Introduction and aims The human hair follicle (HF) is a miniorgan in the skin that possesses a rich microenvironment composed of a complex assembly of sensory nerves that surround it. Recent studies have explored the effects of this perineural niche on the HF, but the influence of HF on the nervous system from a folliculocentric and skin-centric perspective remains underexplored. To explore the potential bidirectionality of the HF–nervous system connection in the context of nerve development, we asked whether the HF influences the differentiation and maturation of sensory neuron subtypes around it through the release of distinct neurotransmitters and neurotrophic factors. Methods To first identify which cell types might be involved in directing sensory neuron development, we reanalysed available skin and HF single-cell RNA sequencing (scRNA-Seq) datasets. Next, to evaluate neurotransmitter release from these cell types, we used fast-scan cyclic voltammetry (FSCV). Lastly, to interrogate the role of the HF on directing neuronal development in vitro, we used induced pluripotent stem cell-derived sensory neurons as a model for developing nerves. Results We found that a higher percentage of KRT14- (epithelial) and PDGFRA-expressing (mesenchymal) cells in the HF coexpressed genes encoding specific neurotrophic factors and enzymatic machinery for neurotransmitter production compared with equivalent cells in the skin, suggesting that the HF possesses a greater capacity to signal to the nervous system compared with interfollicular skin. Using FSCV, we then found that follicular outer root sheath and directionally selective cells are capable of releasing neurotransmitters such as serotonin and histamine. Conclusions We postulate that HF-derived neurotransmitters are important for aspects of sensory neuron development such as axonal growth, as serotonin has previously been shown to be an attractive guidance cue for neuronal growth cones. Overall, our work sheds light on the HF–nervous system connection and how the HF may regulate its microenvironment in the skin.

Comprehensive analysis of gene signatures associated with aging in human aortic dissection

BackgroundAortic dissection (AD) is a lethal aortic disease with limited effective therapeutic strategies. Aging increases the risk of AD, yet the underlying mechanisms remain unclear. This study aims to analyze the association of aging-related genes (Args) and AD using bioinformatic analysis. This helps provide novel insights into AD pathogenesis and contributes to developing novel therapeutic strategies. MethodsmRNA (GSE52093, GSE153434), miRNA (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded from GEO database. Args were downloaded from Aging Atlas database. Differentially-expressed Args were determined by intersecting Args and differentially-expressed mRNAs of two mRNA datasets. Cytoscape was used to identify hub genes and construct hub gene regulatory networks related to miRNAs. Seurat and clusterProfiler R package were used for investigating expression patterns of hub genes at single-cell level, and functional analysis, respectively. To validate the cellular expression pattern of hub genes, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determined using the DGIdb database. ResultsHGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD. miR-221-3p was predicted to interact with ESR1. A decreased ESR1 expression in smooth muscle cell subpopulation 4 (SMC4) was observed in AD versus normal aortic tissues, which was validated by sequencing 197,605 aortic cells from 13 AD patients. Additionally, upregulated genes of SMC4 in AD tissues were enriched in the “cellular senescence” pathway. These data indicated that decreased ESR1 might promote SMC4 aging during AD formation. Eleven existing drugs targeting hub genes were identified, including ruxolitinib and filgrastim, which are associated with AD. ConclusionsBy sequencing transcriptomic data, this study revealed aging-related hub genes and regulatory network involved in AD formation. Additionally, this study proposed a noteworthy hypothesis that downregulated ESR1 may exacerbate AD by promoting SMC aging, which requires further investigation.

Type 17 immune response promotes oral epithelial cell proliferation in periodontitis

ObjectivesThis study aims to investigate the effects of type 17 immune response on the proliferation of oral epithelial cells in periodontitis. DesignA time-dependent ligature induced periodontitis mouse model was utilized to explore gingival hyperplasia and the infiltration of interleukin 17A (IL-17A) positive cells. Immunohistochemistry and flow cytometry were employed to determine the localization and expression of IL-17A in the ligature induced periodontitis model. A pre-existing single-cell RNA sequencing dataset, comparing individuals affected by periodontitis with healthy counterparts, was reanalyzed to evaluate IL-17A expression levels. We examined proliferation markers, including proliferating cell nuclear antigen (PCNA), signal transducer and activator of transcription (STAT3), Yes-associated protein (YAP), and c-JUN, in the gingival and tongue epithelium of the periodontitis model. An anti-IL-17A agent was administered daily to observe proliferative changes in the oral mucosa within the periodontitis model. Cell number quantification, immunofluorescence, and western blot analyses were performed to assess the proliferative responses of human normal oral keratinocytes to IL-17A treatment in vitro. ResultsThe ligature induced periodontitis model exhibited a marked infiltration of IL-17A-positive cells, alongside significant increase in thickness of the gingival and tongue epithelium. IL-17A triggers the proliferation of human normal oral keratinocytes, accompanied by upregulation of PCNA, STAT3, YAP, and c-JUN. The administration of an anti-IL-17A agent attenuated the proliferation in oral mucosa. ConclusionsThese findings indicate that type 17 immune response, in response to periodontitis, facilitates the proliferation of oral epithelial cells, thus highlighting its crucial role in maintaining the oral epithelial barrier.