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.

Private information leakage from single-cell count matrices.

The increase in publicly available human single-cell datasets, encompassing millions of cells from many donors, has significantly enhanced our understanding of complex biological processes. However, the accessibility of these datasets raises significant privacy concerns. Due to the inherent noise in single-cell measurements and the scarcity of population-scale single-cell datasets, recent private information quantification studies have focused on bulk gene expression data sharing. To address this gap, we demonstrate that individuals in single-cell gene expression datasets are vulnerable to linking attacks, where attackers can infer their sensitive phenotypic information using publicly available tissue or cell-type-specific expression quantitative trait loci (eQTLs) information. We further develop a method for genotype prediction and genotype-phenotype linking that remains effective without relying on eQTL information. We show that variants from one study can be exploited to uncover private information about individuals in another study.

Loop stacking organizes genome folding from TADs to chromosomes.

Although population-level analyses revealed significant roles for CTCF and cohesin in mammalian genome organization, their contributions at the single-cell level remain incompletely understood. Here, we used a super-resolution microscopy approach to measure the effects of removal of CTCF or cohesin in mouse embryonic stem cells. Single-chromosome traces revealed cohesin-dependent loops, frequently stacked at their loop anchors forming multi-way contacts (hubs), bridging across TAD boundaries. Despite these bridging interactions, chromatin in intervening TADs was not intermixed, remaining separated in distinct loops around the hub. At the multi-TAD scale, steric effects from loop stacking insulated local chromatin from ultra-long range (>4 Mb) contacts. Upon cohesin removal, the chromosomes were more disordered and increased cell-cell variability in gene expression. Our data revise the TAD-centric understanding of CTCF and cohesin and provide a multi-scale, structural picture of how they organize the genome on the single-cell level through distinct contributions to loop stacking.

T Cell Receptor Is Required for Differentiation, but Not Maintenance, of Intestinal CD4+ Intraepithelial Lymphocytes.

The gut epithelium is populated by intraepithelial lymphocytes (IELs), a heterogeneous T cell population with cytotoxic and regulatory properties, which can be acquired at the epithelial layer. However, the role of T cell receptor (TCR) in this process remains unclear. Single-cell transcriptomic analyses revealed distinct clonal expansions between cell states, with CD4+CD8αα+ IELs being one of the least diverse populations. Conditional deletion of TCR on differentiating CD4+ T cells or of major histocompatibility complex (MHC) class II on intestinal epithelial cells prevented CD4+CD8αα+ IEL differentiation. However, TCR ablation on differentiated CD4+CD8αα+ IELs or long-term cognate antigen withdraw did not affect their maintenance. TCR re-engagement of antigen-specific CD4+CD8αα+ IELs by Listeria monocytogenes did not alter their state but correlated with reduced bacterial invasion. Thus, local antigen recognition is an essential signal for differentiation of CD4+ T cells at the epithelium, yet differentiated IELs are able to preserve an effector program in the absence of TCR signaling.

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.

mTORC1 Signaling in Brain Endothelial Progenitors Contributes to CCM Pathogenesis.

BACKGROUND: Cerebral vascular malformations (CCMs) are primarily found within the brain, where they result in increased risk for stroke, seizures, and focal neurological deficits. The unique feature of the brain vasculature is the blood-brain barrier formed by the brain neurovascular unit. Recent studies suggest that loss of CCM genes causes disruptions of blood-brain barrier integrity as the inciting events for CCM development. CCM lesions are proposed to be initially derived from a single clonal expansion of a subset of angiogenic venous capillary endothelial cells (ECs) and respective resident endothelial progenitor cells (EPCs). However, the critical signaling events in the subclass of brain ECs/EPCs for CCM lesion initiation and progression are unclear. METHODS: Brain EC-specific CCM3-deficient (Pdcd10BECKO) mice were generated by crossing Pdcd10fl/fl mice with Mfsd2a-CreERT2 mice. Single-cell RNA-sequencing analyses were performed by the chromium single-cell platform (10× genomics). Cell clusters were annotated into EC subtypes based on visual inspection and GO analyses. Cerebral vessels were visualized by 2-photon in vivo imaging and tissue immunofluorescence analyses. Regulation of mTOR (mechanistic target of rapamycin) signaling by CCM3 and Cav1 (caveolin-1) was performed by cell biology and biochemical approaches. RESULTS: Single-cell RNA-sequencing analyses from P10 Pdcd10BECKO mice harboring visible CCM lesions identified upregulated CCM lesion signature and mitotic EC clusters but decreased blood-brain barrier-associated EC clusters. However, a unique EPC cluster with high expression levels of stem cell markers enriched with mTOR signaling was identified from early stages of the P6 Pdcd10BECKO brain. Indeed, mTOR signaling was upregulated in both mouse and human CCM lesions. Genetic deficiency of Raptor (regulatory-associated protein of mTOR), but not of Rictor (rapamycin-insensitive companion of mTOR), prevented CCM lesion formation in the Pdcd10BECKO model. Importantly, the mTORC1 (mTOR complex 1) pharmacological inhibitor rapamycin suppressed EPC proliferation and ameliorated CCM pathogenesis in Pdcd10BECKO mice. Mechanistic studies suggested that Cav1/caveolae increased in CCM3-depleted EPC-mediated intracellular trafficking and complex formation of the mTORC1 signaling proteins. CONCLUSIONS: CCM3 is critical for maintaining blood-brain barrier integrity and CCM3 loss-induced mTORC1 signaling in brain EPCs initiates and facilitates CCM pathogenesis.

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.

A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection.

Single-cell RNA-seq analysis has become a powerful tool to analyse the transcriptomes of individual cells. In turn, it has fostered the possibility of screening thousands of single cells in parallel. Thus, contrary to the traditional bulk measurements that only paint a macroscopic picture, gene measurements at the cell level aid researchers in studying different tissues and organs at various stages. However, accurate clustering methods for such high-dimensional data remain exiguous and a persistent challenge in this domain. Of late, several methods and techniques have been promulgated to address this issue. In this article, we propose a novel framework for clustering large-scale single-cell data and subsequently identifying the rare-cell sub-populations. To handle such sparse, high-dimensional data, we leverage PaCMAP (Pairwise Controlled Manifold Approximation), a feature extraction algorithm that preserves both the local and the global structures of the data and Gaussian Mixture Model to cluster single-cell data. Subsequently, we exploit Edited Nearest Neighbours sampling and Isolation Forest/One-class Support Vector Machine to identify rare-cell sub-populations. The performance of the proposed method is validated using the publicly available datasets with varying degrees of cell types and rare-cell sub-populations. On several benchmark datasets, the proposed method outperforms the existing state-of-the-art methods. The proposed method successfully identifies cell types that constitute populations ranging from 0.1 to 8% with F1-scores of 0.91 0.09. The source code is available at https://github.com/scrab017/RarPG.

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-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.

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.

Targeting Epsins to Inhibit Fibroblast Growth Factor Signaling While Potentiating Transforming Growth Factor-ß Signaling Constrains Endothelial-to-Mesenchymal Transition in Atherosclerosis.

BACKGROUND: Epsin endocytic adaptor proteins are implicated in the progression of atherosclerosis; however, the underlying molecular mechanisms have not yet been fully defined. In this study, we determined how epsins enhance endothelial-to-mesenchymal transition (EndoMT) in atherosclerosis and assessed the efficacy of a therapeutic peptide in a preclinical model of this disease. METHODS: Using single-cell RNA sequencing combined with molecular, cellular, and biochemical analyses, we investigated the role of epsins in stimulating EndoMT using knockout in Apoe-/- and lineage tracing/proprotein convertase subtilisin/kexin type 9 serine protease mutant viral-induced atherosclerotic mouse models. The therapeutic efficacy of a synthetic peptide targeting atherosclerotic plaques was then assessed in Apoe-/- mice. RESULTS: Single-cell RNA sequencing and lineage tracing revealed that epsins 1 and 2 promote EndoMT and that the loss of endothelial epsins inhibits EndoMT marker expression and transforming growth factor-ß signaling in vitro and in atherosclerotic mice, which is associated with smaller lesions in the Apoe-/- mouse model. Mechanistically, the loss of endothelial cell epsins results in increased fibroblast growth factor receptor-1 expression, which inhibits transforming growth factor-ß signaling and EndoMT. Epsins directly bind ubiquitinated fibroblast growth factor receptor-1 through their ubiquitin-interacting motif, which results in endocytosis and degradation of this receptor complex. Consequently, administration of a synthetic ubiquitin-interacting motif-containing peptide atheroma ubiquitin-interacting motif peptide inhibitor significantly attenuates EndoMT and progression of atherosclerosis. CONCLUSIONS: We conclude that epsins potentiate EndoMT during atherogenesis by increasing transforming growth factor-ß signaling through fibroblast growth factor receptor-1 internalization and degradation. Inhibition of EndoMT by reducing epsin-fibroblast growth factor receptor-1 interaction with a therapeutic peptide may represent a novel treatment strategy for atherosclerosis.

Cellular and molecular landscape of primary dermatofibrosarcoma protuberans: Insights from single-cell RNA sequencing analysis.

Dermatofibrosarcoma protuberans (DFSP) is a rare cutaneous sarcoma characterized by the COL1A1-PDGFB fusion gene. This study utilized single-cell RNA sequencing to dissect the cellular and molecular landscape of primary DFSP. Distinct DFSP cell clusters, exhibiting fibroblast-like traits, revealed variations in pathways associated with proliferation, inflammation and metabolism. Differential gene expression analysis during the differentiation from tumour stem cells to DFSP cells unveiled SMOC2, DCN and TGFBR3 as potential regulators of tumour invasion and immune infiltration through VEGF/TGF-ß signalling modulation. Cellular communication analysis highlighted interactions within DFSP cell clusters and with endothelial cells, implicating molecules such as NAMPT, ANGPT2 and PTN in pathogenesis and treatment resistance. These findings offer insights into DFSP intratumour heterogeneity, elucidate molecular mechanisms underlying tumour behaviour, and suggest potential therapeutic targets.

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.

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.

What Is a Transcriptional Burst?

The idea that gene activity can be discontinuous will not surprise many biologists - many genes are restricted in when and where they can be expressed. Yet during the past 15 years, a collection of observations compiled under the umbrella term 'transcriptional bursting' has received considerable interest. Direct visualization of the dynamics of discontinuous transcription has expanded our understanding of basic transcriptional mechanisms and their regulation and provides a real-time readout of gene activity during the life of a cell. In this review, we try to reconcile the different views of the transcriptional process emerging from studies of bursting, and how this work contextualizes the relative importance of different regulatory inputs to normal dynamic ranges of gene activity.

In vivo and in vitro matured bovine oocytes present a distinct pattern of single-cell gene expression.

Oocyte gene expression is a well controlled event that promotes gamete competence to undergo maturation, fertilization, and to support early embryo development, directly affecting reproductive outcomes. Considering that in vivo controlled ovarian stimulation or in vitro maturation (IVM) for the acquisition of mature oocytes has distinct implications for gene expression, we sought to evaluate the effects of these procedures on the expression of competence-related genes in single-cell oocytes. Healthy Nelore cows of reproductive age were synchronized to harvest in vivo matured oocytes; ovaries from slaughtered animals were used to obtain cumulus-oocyte complexes that were in vitro matured. Single-cell gene expression was performed using TaqMan Low-Density Arrays and 42 genes were evaluated. In silico analysis of protein interactions and Gene Ontology (GO) analysis was performed. Reduced gene expression was observed for 24 targets in IVM oocytes when compared with those of in vivo matured oocytes (P < 0.05). Differences ranged from 1.5-fold to 4.8-fold higher in in vivo oocytes and the BMP15 (5.28), GDF9 (6.23), NOBOX (7.25), HSPA8 (7.85) and MSX1 (11.00) showed the greatest fold increases. The strongest score of functional interactions was observed between the CDC20 and CKS2, with the differentially expressed gene CDC20 being the main marker behind GO enrichment. IVM negatively affected the expression of important genes related to oocyte competency, and showed higher expression levels in in vivo matured oocytes. In vivo controlled ovarian stimulation may be a better strategy to achieve proper oocyte competence and increase the success of assisted reproductive technologies.

SRGS: sparse partial least squares-based recursive gene selection for gene regulatory network inference.

BACKGROUND: The identification of gene regulatory networks (GRNs) facilitates the understanding of the underlying molecular mechanism of various biological processes and complex diseases. With the availability of single-cell RNA sequencing data, it is essential to infer GRNs from single-cell expression. Although some GRN methods originally developed for bulk expression data can be applicable to single-cell data and several single-cell specific GRN algorithms were developed, recent benchmarking studies have emphasized the need of developing more accurate and robust GRN modeling methods that are compatible for single-cell expression data. RESULTS: We present SRGS, SPLS (sparse partial least squares)-based recursive gene selection, to infer GRNs from bulk or single-cell expression data. SRGS recursively selects and scores the genes which may have regulations on the considered target gene based on SPLS. When dealing with gene expression data with dropouts, we randomly scramble samples, set some values in the expression matrix to zeroes, and generate multiple copies of data through multiple iterations to make SRGS more robust. We test SRGS on different kinds of expression data, including simulated bulk data, simulated single-cell data without and with dropouts, and experimental single-cell data, and also compared with the existing GRN methods, including the ones originally developed for bulk data, the ones developed specifically for single-cell data, and even the ones recommended by recent benchmarking studies. CONCLUSIONS: It has been shown that SRGS is competitive with the existing GRN methods and effective in the gene regulatory network inference from bulk or single-cell gene expression data. SRGS is available at: https://github.com/JGuan-lab/SRGS .

CD96 expression determines the inflammatory potential of IL-9-producing Th9 cells.

Recent findings demonstrated proinflammatory functions of interleukin (IL)-9-producing T helper type (Th) 9 cells in the pathogenesis of intestinal bowel diseases (IBDs). However, also antiinflammatory properties have been ascribed to Th9 cells, pointing to a functional heterogeneity. To dissect the specific expression pattern and, especially, diversity of murine antigen-specific Th9 cells, we applied single cell transcription profiling. Th9 cells displayed reduced expression of typical activation markers, such as Cd40 ligand and Cd96, whereas expression of Cd25 and Cd83 was increased compared with other Th subsets. Importantly, we identified two subsets of Th9 cells differing above all in their CD96 expression. The heterogeneous CD96 expression was specific for Th9 cells and not observed for other Th subtypes, such as Th1 cells. Lower CD96 expression was also observed in human IL-9+ compared with IFN-γ+ T cells. Although Il9 was highly transcribed by all Th9 cells, IL-9 mRNA and protein expression was increased in CD96low cells. Transfer of CD96low Th9 cells into recombination activating gene 1-deficient (Rag1-/- ) mice caused severe weight loss, intestinal and colonic inflammation, and destruction of allogeneic skin grafts and thus showed high inflammatory potential. This was associated with their expansion and tissue accumulation. Contrastingly, CD96high Th9 cells did not cause colitis and showed reduced expansion and migratory potential. Blockade of CD96 completely restored the expansion and inflammatory properties of CD96high Th9 cells. Collectively, our data suggest an inhibitory role for the cosignaling receptor CD96 in Th9 cells, raising new opportunities in the treatment of IL-9-associated inflammations such as IBD.