Single-cell Transcriptomics Research Articles

Induction of a Müller glial-specific protective pathway safeguards the retina from diabetes induced damage.

Diabetes can lead to cell-type-specific responses in the retina, including vascular lesions, glial dysfunction and neurodegeneration, all of which contribute to retinopathy. However, the molecular mechanisms underlying these cell type-specific responses, and the cell types that are sensitive to diabetes have not been fully elucidated. Employing single cell transcriptomics, we profiled the transcriptional changes induced by diabetes in different retinal cell types in rat models as the disease progressed. Rod photoreceptors, a subtype of amacrine interneurons, and Müller glia exhibited rapid responses to diabetes at the transcript levels. Genes associated with ion regulation were upregulated in all three cell types, suggesting a common response to diabetes. Furthermore, focused studies revealed that while Müller glia initially increased the expression of genes playing protective roles, they cannot sustain this beneficial effect. We explored one of the candidate protective genes, Zinc finger protein 36 homolog (Zfp36), and observed that depleting Zfp36 in rat Müller glial cells in vivo using AAV-based tools exacerbated diabetes-induced phenotypes, including glial reactivation, neurodegeneration, and vascular defects. Over-expression of Zfp36 slowed the development of these phenotypes. This work unveiled retinal cell types that are sensitive to diabetes and demonstrated that Müller glial cells can mount protective responses through Zfp36.

Epstein-Barr virus reactivation induces divergent abortive, reprogrammed, and host shutoff states by lytic progression.

Viral infection leads to heterogeneous cellular outcomes ranging from refractory to abortive and fully productive states. Single cell transcriptomics enables a high resolution view of these distinct post-infection states. Here, we have interrogated the host-pathogen dynamics following reactivation of Epstein-Barr virus (EBV). While benign in most people, EBV is responsible for infectious mononucleosis, up to 2% of human cancers, and is a trigger for the development of multiple sclerosis. Following latency establishment in B cells, EBV reactivates and is shed in saliva to enable infection of new hosts. Beyond its importance for transmission, the lytic cycle is also implicated in EBV-associated oncogenesis. Conversely, induction of lytic reactivation in latent EBV-positive tumors presents a novel therapeutic opportunity. Therefore, defining the dynamics and heterogeneity of EBV lytic reactivation is a high priority to better understand pathogenesis and therapeutic potential. In this study, we applied single-cell techniques to analyze diverse fate trajectories during lytic reactivation in three B cell models. Consistent with prior work, we find that cell cycle and MYC expression correlate with cells refractory to lytic reactivation. We further found that lytic induction yields a continuum from abortive to complete reactivation. Abortive lytic cells upregulate NFκB and IRF3 pathway target genes, while cells that proceed through the full lytic cycle exhibit unexpected expression of genes associated with cellular reprogramming. Distinct subpopulations of lytic cells further displayed variable profiles for transcripts known to escape virus-mediated host shutoff. These data reveal previously unknown and promiscuous outcomes of lytic reactivation with broad implications for viral replication and EBV-associated oncogenesis.

Atp13a5 Marker Reveals Pericyte Specification in the Mouse Central Nervous System.

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also indispensable for the blood-brain barrier (BBB), blood-spinal cord barrier, and blood-retinal barrier and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional specifications of pericytes between CNS and peripheral organs have not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This putative cation-transporting ATPase 13A5 (Atp13a5) marker was identified through single-cell transcriptomics, based on its specificity to brain pericytes. We further generated a knock-in model with both tdTomato reporter and Cre recombinase. Using this model to trace the distribution of Atp13a5-positive pericytes in mice, we found that the tdTomato reporter reliably labels the CNS pericytes, including the ones in spinal cord and retina but not peripheral organs. Interestingly, brain pericytes are likely shaped by the developing neural environment, as Atp13a5-positive pericytes start to appear around murine embryonic day 15 (E15) and expand along the cerebrovasculature. Thus, Atp13a5 is a specific marker of CNS pericyte lineage, and this Atp13a5-based model is a reliable tool to explore the heterogeneity of pericytes and BBB functions in health and diseases.

Identification of HSPG2 as a bladder pro-tumor protein through NID1/AKT signaling

PurposeHeparan sulfate proteoglycans (HSPGs) are complex molecules found on the cell membrane and within the extracellular matrix, increasingly recognized for their role in tumor progression. This study aimed to investigate the involvement of Heparan sulfate proteoglycan 2 (HSPG2) in the progression of bladder cancer.MethodsWe identified HSPG2 as a promoter of bladder tumor progression using single-cell RNA sequencing and transcriptome analysis of sequencing data from seven patient samples obtained from the Gene Expression Omnibus (GEO) database (GSE135337). Transcript profiles of 28 normal tissues and 407 bladder tumor tissues were analyzed for HSPG2 expression and survival outcomes using the Sanger tools and cBioPortal databases. HSPG2-overexpressing T24 and Biu-87 cell lines were generated, and cell proliferation and migration were assessed using CCK-8 and Transwell assays. Western blotting and immunostaining were performed to evaluate the activation of Nidogen-1 (NID1)/protein kinase B (AKT) signaling. Mouse models with patient-derived tumor organoids (HSPG2high and HSPG2low) were established to assess anticancer effects.ResultsOur results demonstrated a marked upregulation of HSPG2 in malignant bladder tumors, which correlated significantly with poor patient prognosis. HSPG2 overexpression consistently enhanced bladder tumor cell proliferation and conferred chemotherapy resistance, as shown in both in vitro and in vivo experiments. Mechanistically, HSPG2 upregulated NID1 expression, leading to the activation of the AKT pro-survival signaling pathway and promoting sustained tumor growth in bladder cancer.ConclusionThis study highlights the critical pro-tumor role of HSPG2/NID1/AKT signaling in bladder cancer and suggests its potential as a therapeutic target in clinical treatment.

Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus

BackgroundOsteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.MethodWe analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.ResultAfter quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.ConclusionThis research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

Bioengineered Extracellular Vesicles Delivering siMDM2 Sensitize Oxaliplatin Therapy Efficacy in Colorectal Cancer.

Oxaliplatin (OXA) is the first-line drug for the treatment of colorectal cancer (CRC), and susceptibility to drug resistance affects patient prognosis. However, the exact underlying mechanisms remain unclear. Platinum-acquired resistance in CRC is a continuous transition process; though, current research has mainly focused on the end state of drug resistance, and the early events of drug resistance have been ignored. In this study, single-cell transcriptome sequencing is combined with a dynamic network biomarker (DNB), and found that the functional inhibition of the mitochondrial electron transport chain complex I occur early in the development of attained resistance to OXA in CRC cells, as evidenced by a decrease in the levels of subunit proteins, primarily NDUFB8. Specifically, the mouse double minute 2 homologue (MDM2) mediates the ubiquitination and degradation of NDUFB8, reducing intracellular reactive oxygen species (ROS) generation under chemotherapeutic stress, consequently contributing to drug resistance. Based on this, the study constructs engineered extracellular vesicles carrying siMDM2 by electroporation and validates the application of EV-siMDM2 to improve the efficacy of OXA-based chemotherapy by inhibiting the MDM2/NDUFB8/ROS signaling axis in patient-derived xenograft (PDX) and hepatic and pulmonary metastasis mouse models, thus providing new ideas and an experimental basis for the platinum-resistant treatment of CRC.

Single-Cell Analysis Reveals the Cellular and Molecular Changes of Liver Injury and Fibrosis in Mice During the Progression of Schistosoma japonicum Infection

Schistosomiasis is a parasitic disease that poses a serious threat to human health. However, the pathogenic mechanism during the progression of Schistosoma japonicum infection remains unclear. In order to elucidate this mechanism, we used single-cell RNA sequencing (scRNA-seq) to investigate the transcriptome characteristics of the cellular (single-cell) landscape in the livers of mice infected with Schistosoma japonicum, which were divided into three groups: uninfected mice (0 week (w)), infected mice at 6 w post-infection (the acute phase), and infected mice at 10 w post-infection (the chronic phase). A total of 31,847 liver cells were included and clustered into 21 groups. The cells and T-cells had high heterogeneity in the liver during the progression of schistosome infection. The number and intensity of the intercellular interactions significantly increased at 6 w after infection but decreased at 10 w. The inflammatory signaling pathways chemoattractant cytokine ligand (CCL)5-chemokine C-C-motif receptor (CCR)5 between macrophages and T-cells were predominant at 6 w post-infection; the CCL6-CCR2 signaling pathway between macrophages was predominant at 10 w. The CD80 signaling pathway related to T-cell activation was increased at 6 w after infection, and increased expression of its receptor CD28 on the surfaces of CD4+ and CD8+ T-cells was confirmed by flow cytometry, suggesting an increase in their activation. In addition, scRNA-seq and quantitative reverse transcription polymerase chain reaction (qRT-PCR) confirmed that the intercellular communication between secretory phosphoprotein 1 (SPP1)-cluster of differentiation (CD44), insulin-like growth factor (IGF)-1-IGF1r and visfatin-insulin receptor (Insr) associated with bone metabolism and insulin metabolism was increased and enhanced in the liver at 6 w post-infection. Overall, we provide the comprehensive single-cell transcriptome landscape of the liver in mice during the progression of schistosome infection and delineate the key cellular and molecular events involved in schistosome infection-induced liver injury and fibrosis. The elevated CCL5-CCR5 and CCL6-CCR2 signaling pathways in the liver may be a drug target for liver injury and fibrosis caused by schistosome infection, respectively.

Single-cell transcriptome analysis identifies a novel tumor-associated macrophage subtype predicting better prognosis in pancreatic ductal adenocarcinoma.

Characterized by an immune-suppressive tumor microenvironment (TME), pancreatic ductal adenocarcinoma (PDAC) is well-known for its poor prognosis. Tumor associated macrophages (TAMs) play a critical role in PDAC TME. An in-depth understanding of TAMs is helpful to develop new strategies for immunotherapy. A large number of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC were collected for systematic bioinformatics analysis. Characterize subtypes of TAMs at single-cell resolution and its effect on prognosis. Differential gene analysis and cell-cell communication were used to describe the effect on prognosis and validated by the TCGA dataset. We used two prognosis-favorable genes, SLC12A5 and ENPP2, to identify a benign M2-like TAMs (bM2-like TAMs), which shared similarities with C1QC + TAMs, CXCL9+ TAMs and CD169+ TAMs, by analyzing scRNA-seq data and bulk RNA data of PDAC. The bM2-like TAMs were revealed to promote T cell activation and proliferation through ALCAM/CD6 interaction. Meanwhile, the bM2-like TAMs were responsible for stroma modeling by altering αSMA+/αSMA-cell ratio. On the contrast, the rest of the M2-like TAMs were defined as malignant M2-like TAMs (mM2-like TAMs), partly overlapping with SPP1+ TAMs. mM2-like TAMs were revealed to promote tumor progression by secretion of MIF and SPP1. Our study used two prognosis-favorable genes to divide M2-like TAMs of PDAC into anti-tumor bM2-like TAMs and pro-tumor mM2-like TAMs. The bM2-like TAMs activate T cells through ALCAM/CD6 and generate prognosis-favorable αSMA+ myofibroblasts through secreting TGFβ, which brings insight into heterogeneity of TAMs, prognosis prediction and immunotherapy of PDAC.

A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease

Precision medicine in immune-mediated inflammatory diseases (IMIDs) requires a cellular understanding of treatment response. We describe a therapeutic atlas for Crohn’s disease (CD) and ulcerative colitis (UC) following adalimumab, an anti-tumour necrosis factor (anti-TNF) treatment. We generated ~1 million single-cell transcriptomes, organised into 109 cell states, from 216 gut biopsies (41 subjects), revealing disease-specific differences. A systems biology-spatial analysis identified granuloma signatures in CD and interferon (IFN)-response signatures localising to T cell aggregates and epithelial damage in CD and UC. Pretreatment differences in epithelial and myeloid compartments were associated with remission outcomes in both diseases. Longitudinal comparisons demonstrated disease progression in nonremission: myeloid and T cell perturbations in CD and increased multi-cellular IFN signalling in UC. IFN signalling was also observed in rheumatoid arthritis (RA) synovium with a lymphoid pathotype. Our therapeutic atlas represents the largest cellular census of perturbation with the most common biologic treatment, anti-TNF, across multiple inflammatory diseases.

Single-Cell Transcriptomics Unveils Skin Cell Specific Antifungal Immune Responses and IL-1Ra- IL-1R Immune Evasion Strategies of Emerging Fungal Pathogen Candida auris.

Candida auris is an emerging multidrug-resistant fungal pathogen that preferentially colonizes and persists in skin tissue, yet the host immune factors that regulate the skin colonization of C. auris in vivo are unknown. In this study, we employed unbiased single-cell transcriptomics of murine skin infected with C. auris to understand the cell type-specific immune response to C. auris. C. auris skin infection results in the accumulation of immune cells such as neutrophils, inflammatory monocytes, macrophages, dendritic cells, T cells, and NK cells at the site of infection. We identified fibroblasts as a major non-immune cell accumulated in the C. auris infected skin tissue. The comprehensive single-cell profiling revealed the transcriptomic signatures in cytokines, chemokines, host receptors (TLRs, C-type lectin receptors, NOD receptors), antimicrobial peptides, and immune signaling pathways in individual immune and non-immune cells during C. auris skin infection. Our analysis revealed that C. auris infection upregulates the expression of the IL-1RN gene (encoding IL-1R antagonist protein) in different cell types. We found IL-1Ra produced by macrophages during C. auris skin infection decreases the killing activity of neutrophils. Furthermore, C. auris uses a unique cell wall mannan outer layer to evade IL-1R-signaling mediated host defense. Collectively, our single-cell RNA seq profiling identified the transcriptomic signatures in immune and non-immune cells during C. auris skin infection. Our results demonstrate the IL-1Ra and IL-1R-mediated immune evasion mechanisms employed by C. auris to persist in the skin. These results enhance our understanding of host defense and immune evasion mechanisms during C. auris skin infection and identify potential targets for novel antifungal therapeutics.

FlyRNAi.org 2025 update-expanded resources for new technologies and species.

The design, analysisand mining of large-scale 'omics studies with the goal of advancing biological and biomedical understanding require use of a range of bioinformatics tools, including approaches tailored to needs specific to a given species and/or technology. The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) Functional Genomics Resources (https://fgr.hms.harvard.edu/tools) supports an increasingly broad group of technologies and species. Recently, for example, we expanded the database to include additional new data-centric resources that facilitate mining and analysis of single-cell transcriptomics. In addition, we have applied our approaches to CRISPR reagent and gene-centric bioinformatics approaches in Drosophila to arthropod vectors of infectious diseases. Building on our previous comprehensive reports on the FlyRNAi database, here we focus on new and updated resources with a primary focus on data-centric tools. Altogether, our suite of online resources supports various stages of functional genomics studies for Drosophila and other arthropods, and facilitate a wide range of reagent design, analysis, data miningand analysis approaches by biologists and biomedical experts studying Drosophila, other common genetic model species, arthropod vectorsand/or human biology.

Single-cell transcriptome analysis reveals atypical monocytes circulating ahead of acute graft-versus-host disease clinical onset.

Acute graft-versus-host disease (aGVHD) represents the rejection of the recipient's skin, gut, and liver tissues of an allogeneic hematopoietic stem cell transplantation (HSCT) by the donor T-cells. The onset of aGVHD is often rapid and its evolution is unpredictable. We undertook the single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) collected before aGVHD clinical onset in three patients and from one patient afterward. We used four HSCT recipients who remained free of aGVHD as controls. This analysis unveiled the presence of particular subpopulations of circulating monocytes and cytotoxic T cells (CTLs) in pre-aGVHD samples up to 18 days before clinical disease. These pre-aGVHD monocytes were characterized by an upregulation of the M2 polarity marker CD163 and the transmembrane protein SIGLEC1/CD169. At the same time, their CTL counterparts stood out for the upregulation of the CXCL10 receptor CXCR3 and the antigenic stimulation marker CD70. The occurrence of CD163/SIGLEC1 co-expressing monocytes upstream of aGVHD onset was validated using transcriptomic data from an independent cohort and by flow cytometry in additional blood samples. These findings point to potential early diagnostic tools and preventive therapeutic strategies for aGVHD.

Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis and machine learning.

Metabolic dysfunction-associated steatohepatitis (MASH) is a highly prevalent liver disease globally, with a significant risk of progressing to cirrhosis and even liver cancer. Efferocytosis, a process implicated in a broad spectrum of chronic inflammatory disorders, has been reported to be associated with the pathogenesis of MASH; however, its precise role remains obscure. Thus, we aimed to identify and validate efferocytosis linked signatures for detection of MASH. We retrieved gene expression patterns of MASH from the GEO database and then focused on assessing the differential expression of efferocytosis-related genes (EFRGs) between MASH and control groups. This analysis was followed by a series of in-depth investigations, including protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis, to uncover the molecular interactions and pathways at play. To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. Additionally, we conducted immune infiltration and single-cell transcriptome analyses in both MASH and control samples, providing insights into the immune cell landscape and cellular heterogeneity in these conditions. This research pinpointed 39 genes exhibiting a robust correlation with efferocytosis in MASH. Among these, five potential diagnostic biomarkers-TREM2, TIMD4, STAB1, C1QC, and DYNLT1-were screened using two distinct machine learning models. Subsequent external validation and animal experimentation validated the upregulation of TREM2 and downregulation of TIMD4 in MASH samples. Notably, both TREM2 and TIMD4 demonstrated area under the curve (AUC) values exceeding 0.9, underscoring their significant potential in facilitating the diagnosis of MASH. Our study comprehensively elucidated the relationship between MASH and efferocytosis, constructing a favorable diagnostic model. Furthermore, we identified potential therapeutic targets for MASH treatment and offered novel insights into unraveling the underlying mechanisms of this disease.

Microglia regulate GABAergic neurogenesis in prenatal human brain through IGF1.

GABAergic neurons are an essential cellular component of neural circuits. Their abundance and diversity have enlarged significantly in the human brain, contributing to the expanded cognitive capacity of humans. However, the developmental mechanism of the extended production of GABAergic neurons in the human brain remains elusive. Here, we use single-cell transcriptomics, bioinformatics, and histological analyses to uncover microglial regulation of the sustained proliferation of GABAergic progenitors and neuroblasts in the human medial ganglionic eminence (hMGE). We show that insulin-like growth factor 1 (IGF1) and its receptor IGR1R as the top ligand-receptor pair underlying microglia-progenitor communication in the prenatal human brain. Using our newly developed neuroimmune hMGE organoids, which mimics hMGE cytoarchitecture and developmental trajectory, we demonstrate that microglia-derived IGF1 promotes progenitor proliferation and the production of GABAergic neurons. Conversely, IGF1-neutralizing antibodies and IGF1 knockout human embryonic stem cells (hESC)-induced microglia (iMG) completely abolished iMG-mediated progenitor proliferation. Together, these findings reveal a previously unappreciated role of microglia-derived IGF1 in promoting proliferation of neural progenitors and the development of GABAergic neurons.

Single-Cell Transcriptomic Analysis of Normal and Malignant B Cells.

In the past decade, single-cell (sc) transcriptomics has overcome the limitations of bulk analysis by measuring gene expression in individual cells, not just a population average. This can identify diverse cell types and states within a sample with high resolution, even without prior purification. Various technologies exist, each with its own capture, barcoding, and library preparation methods. This chapter focuses on the analysis of normal and malignant mature B cells using the 10× Genomics 5' sc-gene expression in parallel with B cell immune repertoire profiling. By integrating the gene expression data from similar cells, the complete transcriptome for each population can be reconstructed, while the identification of the expressed immunoglobulin genes allows investigating clonotype evolution and the detection of tumor clones that share the same clonally rearranged B cell receptor sequence. Researchers are guided through both the experimental protocols and data analysis with a comprehensive, step-by-step walkthrough of how to use some of the more popular single-cell software tools.

Droplet Hi-C enables scalable, single-cell profiling of chromatin architecture in heterogeneous tissues.

Current methods for analyzing chromatin architecture are not readily scalable to heterogeneous tissues. Here we introduce Droplet Hi-C, which uses a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture of the mouse cortex and analyzed gene regulatory programs in major cortical cell types. In addition, we used this technique to detect copy number variations, structural variations and extrachromosomal DNA in human glioblastoma, colorectal and blood cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We refined the technique to allow joint profiling of chromatin architecture and transcriptome in single cells, facilitating exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C both addresses critical gaps in chromatin analysis of heterogeneous tissues and enhances understanding of gene regulation.

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex In Situ Tagging for Single-Cell Proteomic Studies.

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

Astrocytic Ryk signaling coordinates scarring and wound healing after spinal cord injury.

Wound healing after spinal cord injury involves highly coordinated interactions among multiple cell types, which is poorly understood. Astrocytes play a central role in creating a border against the non-neural lesion core. To do so, astrocytes undergo dramatic morphological changes by first thickening the processes and then elongating and overlap them. We show here show that the expression of a cell-surface receptor, Ryk, is induced in astrocytes after injury in both rodent and human spinal cord. Astrocyte-specific knockout of Ryk dramatically elongated the reactive astrocytes and accelerated the formation of the border and reduced the size of the scar. Astrocyte-specific knockout of Ryk also accelerated the injury responses of multiple cell types, including the resolution of neuroinflammation. Single cell transcriptomics analyses revealed a broad range of changes cell signaling among astrocytes, microglia, fibroblasts, endothelial cell, etc, after astrocyte-specific Ryk knockout, suggesting that Ryk not only regulates the injury response of astrocytes but may also regulate signals which coordinate the responses of multiple cell types. The elongation is mediated by NrCAM, a cell adhesion molecule induced by astrocyte-specific conditional knockout of Ryk after spinal cord injury. Our findings suggest a promising therapeutic target to accelerate wound healing and promote neuronal survival and enhance functional recovery.

Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level.

Retrotransposable elements (RTEs) are common mobile genetic elements comprising ∼42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

Scalable identification of lineage-specific gene regulatory networks from metacells with NetID

The identification of gene regulatory networks (GRNs) is crucial for understanding cellular differentiation. Single-cell RNA sequencing data encode gene-level covariations at high resolution, yet data sparsity and high dimensionality hamper accurate and scalable GRN reconstruction. To overcome these challenges, we introduce NetID leveraging homogenous metacells while avoiding spurious gene–gene correlations. Benchmarking demonstrates superior performance of NetID compared to imputation-based methods. By incorporating cell fate probability information, NetID facilitates the prediction of lineage-specific GRNs and recovers known network motifs governing bone marrow hematopoiesis, making it a powerful toolkit for deciphering gene regulatory control of cellular differentiation from large-scale single-cell transcriptome data.