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A spatial sequencing atlas of age-induced changes in the lung during influenza infection.
Influenza virus infection causes increased morbidity and mortality in the elderly. Aging impairs the immune response to influenza, both intrinsically and because of altered interactions with endothelial and pulmonary epithelial cells. To characterize these changes, we performed single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and bulk RNA sequencing (bulk RNA-seq) on lung tissue from young and aged female mice at days 0, 3, and 9 post-influenza infection. Our analyses identified dozens of key genes differentially expressed in kinetic, age-dependent, and cell type-specific manners. Aged immune cells exhibited altered inflammatory, memory, and chemotactic profiles. Aged endothelial cells demonstrated characteristics of reduced vascular wound healing and a prothrombotic state. Spatial transcriptomics identified novel profibrotic and antifibrotic markers expressed by epithelial and non-epithelial cells, highlighting the complex networks that promote fibrosis in aged lungs. Bulk RNA-seq generated a timeline of global transcriptional activity, showing increased expression of genes involved in inflammation and coagulation in aged lungs. Our work provides an atlas of high-throughput sequencing methodologies that can be used to investigate age-related changes in the response to influenza virus, identify novel cell-cell interactions for further study, and ultimately uncover potential therapeutic targets to improve health outcomes in the elderly following influenza infection.
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Dual Single-Nucleus Gene Expression Atlas of Grapevine and Erysiphe necator During Early Powdery Mildew Infection.
We applied dual-organism single-nucleus transcriptomics to study the interaction between grapevine leaves and Erysiphe necator, the causal agent of powdery mildew, at 1 and 5 days postinfection, including controls and three biological replicates. We generated a grapevine leaf atlas encompassing over 100,000 nuclei and a pathogen atlas of more than 3,000 nuclei. We successfully annotated all major grapevine cell types, including mesophyll, epidermis, phloem and xylem parenchyma, companion cells, and guard cells. We identified key E. necator structures, including appressoria, haustoria, and hyphae and provided a list of novel cell type markers for both species. We reveal structure-specific gene expression programs in E. necator, laying a foundation for future studies of fungal development and virulence mechanisms. In the host, we identified spatially distinct expression patterns of defense-related genes. As the infection progressed, we observed the activation of a coordinated immune response involving multiple cell types, mainly epidermal and mesophyll cells. High-dimensional weighted gene co-expression network analysis identified key hubs and networks associated with cell type-specific signaling and defense response. We describe a spatial separation of pattern- and effector-triggered immunity, supporting a model in which pattern-triggered immunity is activated at the site of pathogen contact and effector-triggered immunity is induced in surrounding tissue. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Receptor-ligand pair typing and prognostic risk model for papillary thyroid carcinoma based on single-cell sequencing.
The papillary thyroid carcinoma (PTC) microenvironment consists of various cancer and surrounding cells, and the communication between them is mainly performed through ligand-receptor (LR) interactions. Single-cell RNA sequencing (scRNA-seq) has been performed to investigate the role of intercellular communication networks in tumor progression. In addition, scRNA-seq can accurately identify the characteristics of immune cell subsets, which is of great significance for predicting the efficacy of immunotherapy. In this study, the cell-cell communication network was analyzed through LR pairs, and a new PTC molecular phenotype was developed based on LR pairs. Furthermore, a risk model was established to predict patient response to PD-1 blockade immunotherapy. The scRNA-seq dataset was obtained from GSE184362, and the bulk tumor RNA-seq dataset was obtained from The Cancer Genome Atlas. CellPhoneDB was used for cellular communication analysis. LR pair correlations were calculated and used to identify molecular subtypes, and the least absolute shrinkage and selection operator (Lasso) Cox regression was used to develop a risk model based on LR pairs. The IMvigor210 and GSE78220 cohorts were used as external validations for the LR.score to predict responses to PD-L1 blockade therapy. A total of 149 LR pairs with significant expression and prognostic correlation were included, and three PTC molecular subtypes were obtained from those with significant prognostic differences. Then, five LR pairs were selected to construct the risk scoring model, a reliable and independent prognostic factor in the training set, test set, and whole dataset. Furthermore, two external validation sets confirmed the predictive efficacy of the LR.score for response to PD-1 blockade therapy.
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Distinct mast cell subpopulations within and around lymphatic vessels regulate lymph flow and progression of inflammatory-erosive arthritis in TNF-transgenic mice.
OBJECTIVE: Inflammatory-erosive arthritis is exacerbated by dysfunction of joint-draining popliteal lymphatic vessels (PLVs). Synovial mast cells are known to be pro-inflammatory in rheumatoid arthritis (RA). In other settings they have anti-inflammatory and tissue reparative effects. Herein, we elucidate the role of mast cells on PLV function and inflammatory-erosive arthritis in tumor necrosis factor transgenic (TNF-tg) mice that exhibit defects in PLVs commensurate with disease progression. METHODS: Whole mount immunofluorescent microscopy, toluidine blue stained histology, scanning electron microscopy, and in silico bioinformatics were performed to phenotype and quantify PLV mast cells. Ankle bone volumes were assessed by μCT, while corresponding histology quantified synovitis and osteoclasts. Near-infrared indocyanine green imaging measured lymphatic clearance as an outcome of PLV draining function. Effects of genetic MC depletion were assessed via comparison of 4.5-month-old WT, TNF-tg, MC deficient KitW-sh/W-sh (cKit-/-), and TNF-tg x cKit-/- mice. Pharmacological inhibition of mast cells was assessed by treating TNF-tg mice with placebo or cromolyn sodium (3.15mg/kg/day) for 3-weeks. RESULTS: PLVs are surrounded by MCT+/MCPT1+/MCPT4+ mast cells whose numbers are increased 2.8-fold in TNF-tg mice. The percentage of peri-vascular degranulating mast cells was inversely correlated with ICG clearance. A population of MCT+/MCPT1-/MCPT4- mast cells were embedded within the PLV structure. In silico single-cell RNA-seq (scRNAseq) analyses identified a population of PLV-associated mast cells (marker genes: Mcpt4, Cma1, Cpa3, Tpsb2, Kit, Fcer1a & Gata2) with enhanced TGFβ-related signaling that are phenotypically distinct from known MC subsets in the Mouse Cell Atlas. cKit-/- mice have greater lymphatic defects than TNF-tg mice with exacerbation of lymphatic dysfunction and inflammatory-erosive arthritis in TNF-tg x cKit-/- vs. TNF-Tg mice. Cromolyn sodium therapy stabilized PLV mast cells, increased TNF-induced bone loss, synovitis, and osteoclasts, and decreased ICG clearance. CONCLUSIONS: Mast cells are required for normal lymphatic function. Genetic ablation and pharmacological inhibition of mast cells exacerbates TNF-induced inflammatory-erosive arthritis with decreased lymphatic clearance. Together, these findings support an inflammatory role of activated/degranulated peri-PLV mast cells during arthritic progression, and a homeostatic role of intra-PLV mast cells, in which loss of the latter dominantly exacerbates arthritis secondary to defects in joint-draining lymphatics, warranting investigation into specific cellular mechanisms.
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Single-Cell RNA Sequencing Reveals Transcriptional Landscape of Neutrophils and Highlights the Role of TREM-1 in EAE.
BACKGROUND AND OBJECTIVES: Neutrophils, underestimated in multiple sclerosis (MS), are gaining increased attention for their significant functions in patients with MS and the experimental autoimmune encephalomyelitis (EAE) animal model. However, the precise role of neutrophils in cervical lymph nodes (CLNs), the primary CNS-draining lymph nodes where the autoimmune response is initiated during the progression of EAE, remains poorly understood. METHODS: Applying single-cell RNA sequencing (scRNA-seq), we constructed a comprehensive immune cell atlas of CLNs during development of EAE. Through this atlas, we concentrated on and uncovered the transcriptional landscape, phenotypic and functional heterogeneity of neutrophils, and their crosstalk with immune cells within CLNs in the neuroinflammatory processes in EAE. RESULTS: Notably, we observed a substantial increase in the neutrophil population in EAE mice, with a particular emphasis on the significant rise within the CLNs. Neutrophils in CLNs were categorized into 3 subtypes, and we explored the specific roles and developmental trajectories of each distinct neutrophil subtype. Neutrophils were found to engage in extensive interactions with other immune cells, playing crucial roles in T-cell activation. Moreover, our findings highlighted the strong migratory ability of neutrophils to CLNs, partly regulated by triggering the receptor expressed on myeloid cells 1 (TREM-1). Inhibiting TREM1 with LR12 prevents neutrophil migration both in vivo and in vitro. In addition, in patients with MS, we confirmed an increase in peripheral neutrophils with an upregulation of TREM-1. DISCUSSION: Our research provides a comprehensive and precise single-cell atlas of CLNs in EAE, highlighting the role of neutrophils in regulating the periphery immune response. In addition, TREM-1 emerged as an essential regulator of neutrophil migration to CLNs, holding promise as a potential therapeutic target in MS.
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Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics.
Optimizing and benchmarking data reduction methods for dynamic or spatial visualization and interpretation (DSVI) face challenges due to many factors, including data complexity, lack of ground truth, time-dependent metrics, dimensionality bias and different visual mappings of the same data. Current studies often focus on independent static visualization or interpretability metrics that require ground truth. To overcome this limitation, we propose the MIBCOVIS framework, a comprehensive and interpretable benchmarking and computational approach. MIBCOVIS enhances the visualization and interpretability of high-dimensional data without relying on ground truth by integrating five robust metrics, including a novel time-ordered Markov-based structural metric, into a semi-supervised hierarchical Bayesian model. The framework assesses method accuracy and considers interaction effects among metric features. We apply MIBCOVIS using linear and nonlinear dimensionality reduction methods to evaluate optimal DSVI for four distinct dynamic and spatial biological processes captured by three single-cell data modalities: CyTOF, scRNA-seq and CODEX. These data vary in complexity based on feature dimensionality, unknown cell types and dynamic or spatial differences. Unlike traditional single-summary score approaches, MIBCOVIS compares accuracy distributions across methods. Our findings underscore the joint evaluation of visualization and interpretability, rather than relying on separate metrics. We reveal that prioritizing average performance can obscure method feature performance. Additionally, we explore the impact of data complexity on visualization and interpretability. Specifically, we provide optimal parameters and features and recommend methods, like the optimized variational contractive autoencoder, for targeted DSVI for various data complexities. MIBCOVIS shows promise for evaluating dynamic single-cell atlases and spatiotemporal data reduction models.
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Single-nucleus RNA sequencing-based construction of a hippocampal neuron atlas in mice with epileptic cognitive impairment.
The hippocampus plays a critical role in learning and memory, and mice with epileptic cognitive impairment exhibit hippocampal atrophy. However, there is still a lack of research on the hippocampal cell atlas related to these disorders. Here, we utilized snRNA-seq to characterize the transcriptomic changes in hippocampal neurons of drug-resistant epilepsy (DRE) cognitive-impaired mice. The intercellular heterogeneity of 20 subpopulations of neurons was analyzed, focusing on aspects such as cell communication, gene expressions, GO and KEGG enrichment analysis, and module gene set analysis. Based on the degree of relevance to synaptic biological functions, the subpopulations associated with cognitive impairment (ExN1, 3, 8 and InN1, 6) were preliminarily identified. We also identified some key biomarkers in DRE cognitive-impaired mice, such as Ptprz1 and Calb1. Finally, we integrate and validate our dataset using identified well-annotated marker genes in the hippocampal region, further supporting the functional annotation of neuronal subpopulations.
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Single-cell RNA sequencing reveals intratumoral heterogeneity and multicellular community in primary hepatocellular carcinoma underlying microvascular invasion.
BACKGROUND: Microvascular invasion (MVI) is associated with an unfavorable prognosis and early recurrence of hepatocellular carcinoma (HCC), which is the crucial pathological hallmark of immunotherapy. While microvascular invasion (MVI) in hepatocellular carcinoma (HCC) currently lacks a detailed single-cell analysis of the tumor microenvironment (TME), it holds significant promise for immunotherapy using immune checkpoint inhibitors (ICI). METHODS: We performed single-cell RNA sequencing (scRNA-seq) on 3 MVI positive (MVIP) and 14 MVI-negative (MVIN) tumor tissues, as well as their paired adjacent non-tumoral tissues. RESULTS: We identified SPP1+ macrophages and CD4+ proliferative T cells as intertumoral populations critical for the formation of cold tumors and immunosuppressive environments in MVI-positive patients and verified their prognostic value in correlation with MVIP HCC patients. Additionally, we identified SPP1+ dominated interactions between SPP1+ macrophages and the immunosuppressive T population as contributors to MVI destruction and tumorigenesis. CONCLUSIONS: We provide a comprehensive single-cell atlas of HCC patients with MVI, shedding light on the immunosuppressive ecosystem and upregulated signaling associated with MVI. These findings demonstrate that intercellular mechanisms drive MVI and provide a potential immunotherapeutic target for HCC patients with HCC and underlying MVI.
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Single-cell atlas of neuroma-induced DRG remodeling reveals intervention-specific glial and immune programs.
Peripheral nerve injury caused by cut, crush, or excessive stretch can lead to disordered regeneration and painful neuroma formation. Regrowing axons may terminate in a swollen, hypersensitive nerve stump, producing pain that can outweigh sensory or motor deficits. Despite the frequency of neuromas, treatment outcomes remain inconsistent, and the mechanisms that initiate and sustain neuroma-associated pain are poorly understood. A proximal nerve crush performed upstream of a neuroma or transection may reshape axonal growth and interrupt retrograde injury signaling, potentially promoting a regenerative, pain-resolving state. However, its long-term effects on dorsal root ganglion (DRG) programs remain unclear. Here, we use single-cell RNA sequencing to build an atlas of DRG remodeling after neuroma-forming injury and compare it with two interventions: proximal nerve crush and nerve resection. By resolving transcriptional responses across sensory neurons, satellite glial cells, Schwann cells, and macrophages, we identify intervention-specific glial, neuronal, and immune programs that distinguish regenerative from persistent injury-associated states and nominate pathways that may guide mechanism-based therapies for painful neuromas.
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Targeting METTL3 as a checkpoint to enhance T cells for tumour immunotherapy.
BACKGROUND: Immunotherapy has emerged as a crucial treatment modality for solid tumours, yet tumours often evade immune surveillance. There is an imperative to uncover novel immune regulators that can boost tumour immunogenicity and increase the efficacy of immune checkpoint blockade (ICB) therapy. Epigenetic regulators play critical roles in tumour microenvironment remodelling, and N6-methyladenosine (m6A) is known to be involved in tumourigenesis. However, the role of m6A in regulating T-cell function and enhancing anti-tumour immunity remains unexplored. METHODS: Several cancer cell lines were treated with STM2457, an enzymatic inhibitor of RNA m6A methyltransferase METTL3, and explored the transcriptome changes with RNA sequencing (RNA-seq). We then utilised mouse melanoma (B16) and mouse colorectal adenocarcinoma (MC38) models to investigate the effects of METTL3 inhibition on immunotherapy, and analysed the dynamics of the tumour microenvironment via single-cell RNA-seq (scRNA-seq). Furthermore, in vitro and in vivo T-cell cytotoxicity killing assay and CRISPR Cas9-mediated m6A reader YTHDF1-3 knockout in B16 were performed to assess the role and the molecular mechanism of RNA m6A in tumour killing. Finally, the efficacy of METTL3 inhibition was also tested on human melanoma model (A375) and human T cells. RESULTS: We demonstrate that inhibiting METTL3 augments tumour immunogenicity and sustains T-cell function, thereby enhancing responsiveness to ICB therapy. Mechanistically, METTL3 inhibition triggers an interferon response within tumour cells, amplifying the anti-tumour immune response, along with deletion of the m6A reader protein YTHDF2 in tumours inhibiting major histocompatibility complex (MHC)-I degradation. Remarkably, these anti-tumour effects are reliant on the immune system. Specifically, METTL3 inhibition enhances interferon-gamma (IFNγ) and granzyme B (GzmB) expression, thereby strengthening T-cell killing ability, and concurrently dampening the expression of exhaustion-related genes. CONCLUSION: Targeting METTL3 enhances anti-tumour immunity by boosting T-cell cytotoxicity and reversing T-cell exhaustion. Our study positions METTL3 as an epigenetic checkpoint, highlighting the potential of targeting METTL3 to invigorate intrinsic anti-tumour defenses and overcome immune resistance. KEY POINTS: Targeting METTL3 augments tumour cell immunogenicity and sustains T-cell function. T cell with METTL3 inhibition can reverse T-cell exhaustion, and promote expression of IFNγ and GzmB, thereby enhancing cytotoxicity in anti-PD-1 therapy. YTHDF2 deletion in tumours prolong the lifespan of MHC-I mRNAs.