Single-Cell Landscape and a Macrophage Subset Enhancing Brown Adipocyte Function in Diabetes.

Background: Metabolic dysregulation is a hallmark of type 2 diabetes mellitus (T2DM), in which the abnormalities in brown adipose tissue (BAT) play important roles. However, the cellular composition and function of BAT as well as its pathological significance in diabetes remain incompletely understood. Our objective is to delineate the single-cell landscape of BAT-derived stromal vascular fraction (SVF) and their characteristic alterations in T2DM rats. Methods: T2DM was induced in rats by intraperitoneal injection of low-dose streptozotocin and high-fat diet feeding. Single-cell mRNA sequencing was then performed on BAT samples and compared to normal rats to characterize changes in T2DM rats. Subsequently, the importance of key cell subsets in T2DM was elucidated using various functional studies. Results: Almost all cell types in the BAT-derived SVF of T2DM rats exhibited enhanced inflammatory responses, increased angiogenesis, and disordered glucose and lipid metabolism. The multidirectional differentiation potential of adipose tissue-derived stem cells was also reduced. Moreover, macrophages played a pivotal role in intercellular crosstalk of BAT-derived SVF. A novel Rarres2+macrophage subset promoted the differentiation and metabolic function of brown adipocytes via adipose-immune crosstalk. Conclusion: BAT SVF exhibited strong heterogeneity in cellular composition and function and contributed to T2DM as a significant inflammation source, in which a novel macrophage subset was identified that can promote brown adipocyte function.

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn's Disease.

BACKGROUND: The lack of reliable biomarkers in response to anti-TNFα biologicals hinders personalized therapy for Crohn's disease (CD) patients. The motivation behind our study is to shift the paradigm of anti-TNFα biomarker discovery toward specific immune cell sub-populations using single-cell RNA sequencing and an innovative approach designed to uncover PBMCs gene expression signals, which may be masked due to the treatment or ongoing inflammation; Methods: The single-cell RNA sequencing was performed on PBMC samples from CD patients either naïve to biological therapy, in remission while on adalimumab, or while on ustekinumab but previously non-responsive to adalimumab. Sieves for stringent downstream gene selection consisted of gene ontology and independent cohort genomic profiling. Replication and meta-analyses were performed using publicly available raw RNA sequencing files of sorted immune cells and an association analysis summary. Machine learning, Mendelian randomization, and oligogenic risk score methods were deployed to validate DEGs highly relevant to anti-TNFα therapy response; Results: This study found PLCB1 in CD4+ T cells and CRTAM in double-negative T cells, which met the stringent statistical thresholds throughout the analyses. An additional assessment proved causal inference of both genes in response to anti-TNFα therapy; Conclusions: This study, jointly with an innovative design, uncovered novel candidate genes in the anti-TNFα response landscape of CD, potentially obscured by therapy or inflammation.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

BACKGROUND: The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. METHODS: For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). RESULTS: Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. CONCLUSIONS: Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Super-enhancer interactomes from single cells link clustering and transcription.

Regulation of gene expression hinges on the interplay between enhancers and promoters, traditionally explored through pairwise analyses. Recent advancements in mapping genome folding, like GAM, SPRITE, and multi-contact Hi-C, have uncovered multi-way interactions among super-enhancers (SEs), spanning megabases, yet have not measured their frequency in single cells or the relationship between clustering and transcription. To close this gap, here we used multiplexed imaging to map the 3D positions of 376 SEs across thousands of mammalian nuclei. Notably, our single-cell images reveal that while SE-SE contacts are rare, SEs often form looser associations we termed "communities". These communities, averaging 4-5 SEs, assemble cooperatively under the combined effects of genomic tethers, Pol2 clustering, and nuclear compartmentalization. Larger communities are associated with more frequent and larger transcriptional bursts. Our work provides insights about the SE interactome in single cells that challenge existing hypotheses on SE clustering in the context of transcriptional regulation.

Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans.

BACKGROUND: In recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals. On the other hand, the influence of cell type heterogeneity should also be considered during clustering, aiming to obtain more biologically significant clustering results. RESULTS: A biclustering model is proposed for tree-shaped single-cell gene expression data of Caenorhabditis elegans. Detailedly, a tree-shaped piecewise polynomial function is first employed to fit non-pairwise gene expression time series data. Then, four factors are considered in the objective function, including Pearson correlation coefficients capturing gene correlations, p-values from the Kolmogorov-Smirnov test measuring the similarity between cells, as well as gene expression size and bicluster overlapping size. After that, Genetic Algorithm is utilized to optimize the function. CONCLUSION: The results on the small-scale dataset analysis validate the feasibility and effectiveness of our model and are superior to existing classical biclustering models. Besides, gene enrichment analysis is employed to assess the results on the complete real dataset analysis, confirming that the discovered biclustering results hold significant biological relevance.

DPSCs regulate epithelial-T cell interactions in oral submucous fibrosis.

BACKGROUND: Oral submucous fibrosis (OSF) is a precancerous lesion characterized by fibrous tissue deposition, the incidence of which correlates positively with the frequency of betel nut chewing. Prolonged betel nut chewing can damage the integrity of the oral mucosal epithelium, leading to chronic inflammation and local immunological derangement. However, currently, the underlying cellular events driving fibrogenesis and dysfunction are incompletely understood, such that OSF has few treatment options with limited therapeutic effectiveness. Dental pulp stem cells (DPSCs) have been recognized for their anti-inflammatory and anti-fibrosis capabilities, making them promising candidates to treat a range of immune, inflammatory, and fibrotic diseases. However, the application of DPSCs in OSF is inconclusive. Therefore, this study aimed to explore the pathogenic mechanism of OSF and, based on this, to explore new treatment options. METHODS: A human cell atlas of oral mucosal tissues was compiled using single-cell RNA sequencing to delve into the underlying mechanisms. Epithelial cells were reclustered to observe the heterogeneity of OSF epithelial cells and their communication with immune cells. The results were validated in vitro, in clinicopathological sections, and in animal models. In vivo, the therapeutic effect and mechanism of DPSCs were characterized by histological staining, immunohistochemical staining, scanning electron microscopy, and atomic force microscopy. RESULTS: A unique epithelial cell population, Epi1.2, with proinflammatory and profibrotic functions, was predominantly found in OSF. Epi1.2 cells also induced the fibrotic process in fibroblasts by interacting with T cells through receptor-ligand crosstalk between macrophage migration inhibitory factor (MIF)-CD74 and C-X-C motif chemokine receptor 4 (CXCR4). Furthermore, we developed OSF animal models and simulated the clinical local injection process in the rat buccal mucosa using DPSCs to assess their therapeutic impact and mechanism. In the OSF rat model, DPSCs demonstrated superior therapeutic effects compared with the positive control (glucocorticoids), including reducing collagen deposition and promoting blood vessel regeneration. DPSCs mediated immune homeostasis primarily by regulating the numbers of KRT19 + MIF + epithelial cells and via epithelial-stromal crosstalk. CONCLUSIONS: Given the current ambiguity surrounding the cause of OSF and the limited treatment options available, our study reveals that epithelial cells and their crosstalk with T cells play an important role in the mechanism of OSF and suggests the therapeutic promise of DPSCs.

A Roadmap for Selecting and Utilizing Optimal Features in scRNA Sequencing Data Analysis for Stem Cell Research: A Comprehensive Review.

Stem cells and the cells they produce are unique because they vary from one cell to another. Traditional methods of studying cells often overlook these differences. However, the development of new technologies for studying individual cells has greatly changed biological research in recent years. Among these innovations, single-cell RNA sequencing (scRNA-seq) stands out. This technique allows scientists to examine the activity of genes in each cell, across thousands or even millions of cells. This makes it possible to understand the diversity of cells, identify new types of cells, and see how cells differ across different tissues, individuals, species, times, and conditions. This paper discusses the importance of scRNA-seq and the computational tools and software that are essential for analyzing the vast amounts of data generated by scRNA-seq studies. Our goal is to provide practical advice for bioinformaticians and biologists who are using scRNA-seq to study stem cells. We offer an overview of the scRNA-seq field, including the tools available, how they can be used, and how to present the results of these studies effectively. Our findings include a detailed overview and classification of tools used in scRNA-seq analysis, based on a review of 2,733 scientific publications. This review is complemented by information from the scRNA-tools database, which lists over 1,400 tools for analyzing scRNA-seq data. This database is an invaluable resource for researchers, offering a wide range of options for analyzing their scRNA-seq data.

Comprehensive molecular and cellular characterization of endoplasmic reticulum stress-related key genes in renal ischemia/reperfusion injury.

Background: Renal ischemia-reperfusion injury (RIRI) is an inevitable complication in the process of kidney transplantation and lacks specific therapy. The study aims to determine the underlying mechanisms of RIRI to uncover a promising target for efficient renoprotection. Method: Four bulk RNA-seq datasets including 495 renal samples of pre- and post-reperfusion were collected from the GEO database. The machine learning algorithms were utilized to ascertain pivotal endoplasmic reticulum stress genes. Then, we incorporated correlation analysis and determined the interaction pathways of these key genes. Considering the heterogeneous nature of bulk-RNA analysis, the single-cell RNA-seq analysis was performed to investigate the mechanisms of key genes at the single-cell level. Besides, 4-PBA was applied to inhibit endoplasmic reticulum stress and hence validate the pathological role of these key genes in RIRI. Finally, three clinical datasets with transcriptomic profiles were used to assess the prognostic role of these key genes in renal allograft outcomes after RIRI. Results: In the bulk-RNA analysis, endoplasmic reticulum stress was identified as the top enriched pathway and three endoplasmic reticulum stress-related genes (PPP1R15A, JUN, and ATF3) were ranked as top performers in both LASSO and Boruta analyses. The three genes were found to significantly interact with kidney injury-related pathways, including apoptosis, inflammatory response, oxidative stress, and pyroptosis. For oxidative stress, these genes were more strongly related to oxidative markers compared with antioxidant markers. In single-cell transcriptome, the three genes were primarily upregulated in endothelium, distal convoluted tubule cells, and collecting duct principal cells among 12 cell types of renal tissues in RIRI. Furthermore, distal convoluted tubule cells and collecting duct principal cells exhibited pro-inflammatory status and the highest pyroptosis levels, suggesting their potential as main effectors of three key genes for mediating RIRI-associated injuries. Importantly, inhibition of these key genes using 4-phenyl butyric acid alleviated functional and histological damage in a mouse RIRI model. Finally, the three genes demonstrated highly prognostic value in predicting graft survival outcomes. Conclusion: The study identified three key endoplasmic reticulum stress-related genes and demonstrated their prognostic value for graft survival, providing references for individualized clinical prevention and treatment of postoperative complications after renal transplantation.

Directed Differentiation of Human Induced Pluripotent Stem Cells to Heart Valve Cells.

BACKGROUND: A main obstacle in current valvular heart disease research is the lack of high-quality homogeneous functional heart valve cells. Human induced pluripotent stem cells (hiPSCs)-derived heart valve cells may help with this dilemma. However, there are no well-established protocols to induce hiPSCs to differentiate into functional heart valve cells, and the networks that mediate the differentiation have not been fully elucidated. METHODS: To generate heart valve cells from hiPSCs, we sequentially activated the Wnt, BMP4, VEGF (vascular endothelial growth factor), and NFATc1 signaling pathways using CHIR-99021, BMP4, VEGF-165, and forskolin, respectively. The transcriptional and functional similarity of hiPSC-derived heart valve cells compared with primary heart valve cells were characterized. Longitudinal single-cell RNA sequencing was used to uncover the trajectory, switch genes, pathways, and transcription factors of the differentiation. RESULTS: An efficient protocol was developed to induce hiPSCs to differentiate into functional hiPSC-derived valve endothelial-like cells and hiPSC-derived valve interstitial-like cells. After 6-day differentiation and CD144 magnetic bead sorting, ≈70% CD144+ cells and 30% CD144- cells were obtained. On the basis of single-cell RNA sequencing data, the CD144+ cells and CD144- cells were found to be highly similar to primary heart valve endothelial cells and primary heart valve interstitial cells in gene expression profile. Furthermore, CD144+ cells had the typical function of primary heart valve endothelial cells, including tube formation, uptake of low-density lipoprotein, generation of endothelial nitric oxide synthase, and response to shear stress. Meanwhile, CD144- cells could secret collagen and matrix metalloproteinases, and differentiate into osteogenic or adipogenic lineages like primary heart valve interstitial cells. Therefore, we identified CD144+ cells and CD144- cells as hiPSC-derived valve endothelial-like cells and hiPSC-derived valve interstitial-like cells, respectively. Using single-cell RNA sequencing analysis, we demonstrated that the trajectory of heart valve cell differentiation was consistent with embryonic valve development. We identified the main switch genes (NOTCH1, HEY1, and MEF2C), signaling pathways (TGF-ß, Wnt, and NOTCH), and transcription factors (MSX1, SP5, and MECOM) that mediated the differentiation. Finally, we found that hiPSC-derived valve interstitial-like cells might derive from hiPSC-derived valve endothelial-like cells undergoing endocardial-mesenchymal transition. CONCLUSIONS: In summary, this is the first study to report an efficient strategy to generate functional hiPSC-derived valve endothelial-like cells and hiPSC-derived valve interstitial-like cells from hiPSCs, as well as to elucidate the differentiation trajectory and transcriptional dynamics of hiPSCs differentiated into heart valve cells.

Single-Cell Transcriptome Reveals Potential Mechanisms for Coronary Artery Lesions in Kawasaki Disease.

BACKGROUND: Coronary artery lesions (CALs) are the most common and major complication of Kawasaki disease (KD) in developed countries. However, the underlying immunologic mechanisms of CAL development in KD remain unclear. METHODS: Here, we conducted single-cell transcriptome analyses of 212 210 peripheral blood mononuclear cells collected from a cross-sectional cohort of 16 children, including 4 patients with KD with CALs, 5 patients with KD without CALs, 4 healthy controls, and 3 febrile controls. RESULTS: KD altered the proportion of peripheral blood mononuclear cells, including an increasing trend in inflammatory cells (megakaryocytes and monocytes) and a decreasing trend in lymphocytes (eg, CD4+ T, CD8+ T, mucosal-associated invariant T, natural killer, and γδ T cells), highlighting the potential presence of lymphopenia phenomenon in KD. Our data indicated the presence of inflammatory cytokine storm in patients with KD with CALs, caused by systemic upregulation of TNFSF13B (tumor necrosis factor superfamily member 13b), CXCL16 (C-X-C motif chemokine ligand 16), TNFSF10 (tumor necrosis factor superfamily member 10), and IL1RN (interleukin 1 receptor antagonist), mainly produced by monocytes (especially for the Mono_CD14-CD16 cluster) and megakaryocytes. We also found that myeloid cells of patients with KD, particularly in those with CALs, might play a role in vascular injury (eg, increased MMP [matrix metalloproteinase] 9, MMP17, and MMP25) and immune cell recruitment. The immune landscape of patients with KD with CALs was featured by lower exhaustion levels in natural killer cells, a high cytotoxic state in the CD8_Pro cluster, and activation of the complement system in monocytes. Additionally, the activation of B cells was more pronounced in the early stage of KD. CONCLUSIONS: Collectively, this study provides a comprehensive understanding of the roles of various immune cells and inflammatory cytokine storms in the development of CALs in KD and offers a valuable resource for identifying novel therapeutic targets for patients with KD with CALs.

Molecular and Spatial Signatures of Mouse Embryonic Endothelial Cells at Single-Cell Resolution.

BACKGROUND: Mature endothelial cells (ECs) are heterogeneous, with subtypes defined by tissue origin and position within the vascular bed (ie, artery, capillary, vein, and lymphatic). How this heterogeneity is established during the development of the vascular system, especially arteriovenous specification of ECs, remains incompletely characterized. METHODS: We used droplet-based single-cell RNA sequencing and multiplexed error-robust fluorescence in situ hybridization to define EC and EC progenitor subtypes from E9.5, E12.5, and E15.5 mouse embryos. We used trajectory inference to analyze the specification of arterial ECs (aECs) and venous ECs (vECs) from EC progenitors. Network analysis identified candidate transcriptional regulators of arteriovenous differentiation, which we tested by CRISPR (clustered regularly interspaced short palindromic repeats) loss of function in human-induced pluripotent stem cells undergoing directed differentiation to aECs or vECs (human-induced pluripotent stem cell-aECs or human-induced pluripotent stem cell-vECs). RESULTS: From the single-cell transcriptomes of 7682 E9.5 to E15.5 ECs, we identified 19 EC subtypes, including Etv2+Bnip3+ EC progenitors. Spatial transcriptomic analysis of 15 448 ECs provided orthogonal validation of these EC subtypes and established their spatial distribution. Most embryonic ECs were grouped by their vascular-bed types, while ECs from the brain, heart, liver, and lung were grouped by their tissue origins. Arterial (Eln, Dkk2, Vegfc, and Egfl8), venous (Fam174b and Clec14a), and capillary (Kcne3) marker genes were identified. Compared with aECs, embryonic vECs and capillary ECs shared fewer markers than their adult counterparts. Early capillary ECs with venous characteristics functioned as a branch point for differentiation of aEC and vEC lineages. CONCLUSIONS: Our results provide a spatiotemporal map of embryonic EC heterogeneity at single-cell resolution and demonstrate that the diversity of ECs in the embryo arises from both tissue origin and vascular-bed position. Developing aECs and vECs share common venous-featured capillary precursors and are regulated by distinct transcriptional regulatory networks.

The CD4 Versus CD8 T Cell Fate Decision: A Multiomics-Informed Perspective.

The choice of developing thymocytes to become CD8+ cytotoxic or CD4+ helper T cells has been intensely studied, but many of the underlying mechanisms remain to be elucidated. Recent multiomics approaches have provided much higher resolution analysis of gene expression in developing thymocytes than was previously achievable, thereby offering a fresh perspective on this question. Focusing on our recent studies using CITE-seq (cellular indexing of transcriptomes and epitopes) analyses of mouse thymocytes, we present a detailed timeline of RNA and protein expression changes during CD8 versus CD4 T cell differentiation. We also revisit our current understanding of the links between T cell receptor signaling and expression of the lineage-defining transcription factors ThPOK and RUNX3. Finally, we propose a sequential selection model to explain the tight linkage between MHC-I versus MHC-II recognition and T cell lineage choice. This model incorporates key aspects of previously proposed kinetic signaling, instructive, and stochastic/selection models.

Sputum Transcriptomics Reveals FCN1+ Macrophage Activation in Mild Eosinophilic Asthma Compared to Non-Asthmatic Eosinophilic Bronchitis.

PURPOSE: Eosinophilic asthma (EA) and non-asthmatic eosinophilic bronchitis (EB) share similar eosinophilic airway inflammation. Unlike EA, EB did not present airway hyperresponsiveness or airflow obstruction. We aimed to compare the mechanism underlying the different manifestations between EA and EB via sputum transcriptomics analysis. METHODS: Induced-sputum cells from newly physician-diagnosed EA, EB patients, and healthy controls (HCs) were collected for RNA sequencing. RESULTS: Bulk RNA sequencing was performed using sputum cells from patients with EA (n = 18), EB (n = 15) and HCs (n = 28). Principal component analysis revealed similar gene expression patterns in EA and EB. The most differentially expressed genes in EB compared with HC were also shared by EA, including IL4, IL5 IL13, CLC, CPA3, and DNASE1L3. However, gene set enrichment analysis showed that the signatures regulating macrophage activation were enriched in EA compared to EB. Sputum cells were profiled using single-cell RNA sequencing. FABP4+ macrophages, SPP1+ macrophages, FCN1+ macrophages, dendritic cells, T cells, B cells, mast cells, and epithelial cells were identified based on gene expression profiling. Analysis of cell-cell communication revealed that interactions between FCN1+ macrophages and other cells were higher in EA than in EB. A wealth of transforming growth factor beta (TGF-ß) and vascular endothelial growth factor (VEGF) interactions between FCN1+ macrophages and other cells have been shown in EA. The gene expression levels of EREG, TGFBI, and VEGFA in FCN1+ macrophages of EA were significantly higher than those of EB. Furthermore, signatures associated with the response to TGF-ß, cellular response to VEGF stimulus and developmental cell growth were enriched in FCN1+ macrophages of EA compared to those of EB. CONCLUSIONS: FCN1+ macrophage activation associated with airway remodeling processes was upregulated in EA compared to that in EB, which may contribute to airway hyperresponsiveness and airflow obstruction.

Division-Independent Differentiation of Muscle Stem Cells During a Growth Stimulus.

Adult muscle stem cells (MuSCs) are known to replicate upon activation before differentiating and fusing to regenerate myofibers. It is unclear whether MuSC differentiation is intrinsically linked to cell division, which has implications for stem cell population maintenance. We use single-cell RNA-sequencing to identify transcriptionally diverse subpopulations of MuSCs after 5 days of a growth stimulus in adult muscle. Trajectory inference in combination with a novel mouse model for tracking MuSC-derived myonuclei and in vivo labeling of DNA replication revealed an MuSC population that exhibited division-independent differentiation and fusion. These findings demonstrate that in response to a growth stimulus in the presence of intact myofibers, MuSC division is not obligatory.

Single-Molecule Spatial Transcriptomics of Human Thoracic Aortic Aneurysms Uncovers Calcification-Related CARTPT-Expressing Smooth Muscle Cells.

BACKGROUND: Although single-cell RNA-sequencing is commonly applied to dissect the heterogeneity in human tissues, it involves the preparation of single-cell suspensions via cell dissociation, causing loss of spatial information. In this study, we employed high-resolution single-cell transcriptome imaging to reveal rare smooth muscle cell (SMC) types in human thoracic aortic aneurysm (TAA) tissue samples. METHODS: Single-molecule spatial distribution of transcripts from 140 genes was analyzed in fresh-frozen human TAA samples with region and sex-matched controls. In vitro studies and tissue staining were performed to examine human CART prepropeptide (CARTPT) regulation and function. RESULTS: We captured thousands of cells per sample including a spatially distinct CARTPT-expressing SMC subtype enriched in male TAA samples. Immunoassays confirmed human CART (cocaine- and amphetamine-regulated transcript) protein enrichment in male TAA tissue and truncated CARTPT secretion into cell culture medium. Oxidized low-density lipoprotein, a cardiovascular risk factor, induced CARTPT expression, whereas CARTPT overexpression in human aortic SMCs increased the expression of key osteochondrogenic transcription factors and reduced contractile gene expression. Recombinant human CART treatment of human SMCs further confirmed this phenotype. Alizarin red staining revealed calcium deposition in male TAA samples showing similar localization with human CART staining. CONCLUSIONS: Here, we demonstrate the feasibility of single-molecule imaging in uncovering rare SMC subtypes in the diseased human aorta, a difficult tissue to dissociate. We identified a spatially distinct CARTPT-expressing SMC subtype enriched in male human TAA samples. Our functional studies suggest that human CART promotes osteochondrogenic switch of aortic SMCs, potentially leading to medial calcification of the thoracic aorta.

Identification of Clinically Relevant Brain Endothelial Cell Biomarkers in Plasma.

BACKGROUND: Proteins expressed by brain endothelial cells (BECs), the primary cell type of the blood-brain barrier, may serve as sensitive plasma biomarkers for neurological and neurovascular conditions, including cerebral small vessel disease. METHODS: Using data from the BLSA (Baltimore Longitudinal Study of Aging; n=886; 2009-2020), BEC-enriched proteins were identified among 7268 plasma proteins (measured with SomaScanv4.1) using an automated annotation algorithm that filtered endothelial cell transcripts followed by cross-referencing with BEC-specific transcripts reported in single-cell RNA-sequencing studies. To identify BEC-enriched proteins in plasma most relevant to the maintenance of neurological and neurovascular health, we selected proteins significantly associated with 3T magnetic resonance imaging-defined white matter lesion volumes. We then examined how these candidate BEC biomarkers related to white matter lesion volumes, cerebral microhemorrhages, and lacunar infarcts in the ARIC study (Atherosclerosis Risk in Communities; US multisite; 1990-2017). Finally, we determined whether these candidate BEC biomarkers, when measured during midlife, were related to dementia risk over a 25-year follow-up period. RESULTS: Of the 28 proteins identified as BEC-enriched, 4 were significantly associated with white matter lesion volumes (CDH5 [cadherin 5], CD93 [cluster of differentiation 93], ICAM2 [intracellular adhesion molecule 2], GP1BB [glycoprotein 1b platelet subunit beta]), while another approached significance (RSPO3 [R-Spondin 3]). A composite score based on 3 of these BEC proteins accounted for 11% of variation in white matter lesion volumes in BLSA participants. We replicated the associations between the BEC composite score, CDH5, and RSPO3 with white matter lesion volumes in ARIC, and further demonstrated that the BEC composite score and RSPO3 were associated with the presence of ≥1 cerebral microhemorrhages. We also showed that the BEC composite score, CDH5, and RSPO3 were associated with 25-year dementia risk. CONCLUSIONS: In addition to identifying BEC proteins in plasma that relate to cerebral small vessel disease and dementia risk, we developed a composite score of plasma BEC proteins that may be used to estimate blood-brain barrier integrity and risk for adverse neurovascular outcomes.

Identifying genes associated with resistance to KRAS G12C inhibitors via machine learning methods.

BACKGROUND: Targeted therapy has revolutionized cancer treatment, greatly improving patient outcomes and quality of life. Lung cancer, specifically non-small cell lung cancer, is frequently driven by the G12C mutation at the KRAS locus. The development of KRAS inhibitors has been a breakthrough in the field of cancer research, given the crucial role of KRAS mutations in driving tumor growth and progression. However, over half of patients with cancer bypass inhibition show limited response to treatment. The mechanisms underlying tumor cell resistance to this treatment remain poorly understood. METHODS: To address above gap in knowledge, we conducted a study aimed to elucidate the differences between tumor cells that respond positively to KRAS (G12C) inhibitor therapy and those that do not. Specifically, we analyzed single-cell gene expression profiles from KRAS G12C-mutant tumor cell models (H358, H2122, and SW1573) treated with KRAS G12C (ARS-1620) inhibitor, which contained 4297 cells that continued to proliferate under treatment and 3315 cells that became quiescent. Each cell was represented by the expression levels on 8687 genes. We then designed an innovative machine learning based framework, incorporating seven feature ranking algorithms and four classification algorithms to identify essential genes and establish quantitative rules. RESULTS: Our analysis identified some top-ranked genes, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5, that are known to be associated with the progression of multiple cancers. CONCLUSION: Above genes were relevant to tumor cell resistance to targeted therapy. This study provides important insights into the molecular mechanisms underlying tumor cell resistance to KRAS inhibitor treatment.

Single-Cell RNA Sequencing of Coronary Perivascular Adipose Tissue From End-Stage Heart Failure Patients Identifies SPP1+ Macrophage Subpopulation as a Target for Alleviating Fibrosis.

BACKGROUND: Perivascular adipose tissue (PVAT) is vital for vascular homeostasis, and PVAT dysfunction is associated with increased atherosclerotic plaque burden. But the mechanisms underlining coronary PVAT dysfunction in coronary atherosclerosis remain elusive. METHODS: We performed single-cell RNA sequencing of the stromal vascular fraction of coronary PVAT from 3 groups of heart transplant recipients with end-stage heart failure, including 3 patients with nonobstructive coronary atherosclerosis, 3 patients with obstructive coronary artery atherosclerosis, and 4 nonatherosclerosis control subjects. Bioinformatics was used to annotate the cellular populations, depict the cellular developmental trajectories and interactions, and explore the differences among 3 groups of coronary PVAT at the cellular and molecular levels. Pathological staining, quantitative real-time polymerase chain reaction, and in vitro studies were performed to validate the key findings. RESULTS: Ten cell types were identified among 67 936 cells from human coronary PVAT. Several cellular subpopulations, including SPP1+ (secreted phosphoprotein 1) macrophages and profibrotic fibroadipogenic progenitor cells, were accumulated in PVAT surrounding atherosclerotic coronary arteries compared with nonatherosclerosis coronary arteries. The fibrosis percentage was increased in PVAT surrounding atherosclerotic coronary arteries, and it was positively associated with the grade of coronary artery stenosis. Cellular interaction analysis suggested OPN (osteopontin) secreted by SPP1+ macrophages interacted with CD44 (cluster of differentiation 44)/integrin on fibroadipogenic progenitor cells. Strikingly, correlation analyses uncovered that higher level of SPP1 in PVAT correlates with a more severe fibrosis degree and a higher coronary stenosis grade. In vitro studies showed that conditioned medium from atherosclerotic coronary PVAT promoted the migration and proliferation of fibroadipogenic progenitor cells, while such effect was prevented by blocking CD44 or integrin. CONCLUSIONS: SPP1+ macrophages accumulated in the PVAT surrounding atherosclerotic coronary arteries, and they promoted the migration and proliferation of fibroadipogenic progenitor cells via OPN-CD44/integrin interaction and thus aggravated the fibrosis of coronary PVAT, which was positively correlated to the coronary stenosis burden. Therefore, SPP1+ macrophages in coronary PVAT may participate in the progression of coronary atherosclerosis.

A single-cell level comparison of human inner ear organoids with the human cochlea and vestibular organs.

Inner ear disorders are among the most common congenital abnormalities; however, current tissue culture models lack the cell type diversity to study these disorders and normal otic development. Here, we demonstrate the robustness of human pluripotent stem cell-derived inner ear organoids (IEOs) and evaluate cell type heterogeneity by single-cell transcriptomics. To validate our findings, we construct a single-cell atlas of human fetal and adult inner ear tissue. Our study identifies various cell types in the IEOs including periotic mesenchyme, type I and type II vestibular hair cells, and developing vestibular and cochlear epithelium. Many genes linked to congenital inner ear dysfunction are confirmed to be expressed in these cell types. Additional cell-cell communication analysis within IEOs and fetal tissue highlights the role of endothelial cells on the developing sensory epithelium. These findings provide insights into this organoid model and its potential applications in studying inner ear development and disorders.