Confronting false discoveries in single-cell differential expression

Novel Cell-to-Cell Communications Between Macrophages and Fibroblasts Regulate Obesity-Induced Adipose Tissue Fibrosis

Recent evidence has shown that adipose tissue eventually develops fibrosis through complex cellular cross talk. Although advances in single-cell transcriptomics have provided new insights into cell diversity during this process, little is known about the interactions among the distinct cell types. In this study, we used single-cell analytical approaches to investigate cell-to-cell communications between macrophages and fibroblasts in the adipose tissue of diet-induced obese mice. Spatial transcriptomics was used to understand local cellular interaction within crown-like structures (CLS), a characteristic histological feature of adipose tissue in obesity driving inflammation and fibrosis. Macrophages and fibroblasts were divided into several subclusters that appeared to interact more intensely and complexly with the degree of obesity. Besides previously reported lipid-associated macrophages (LAMs), we found a small subcluster expressing macrophage-inducible C-type lectin (Mincle), specifically localizing to CLS. Mincle signaling increased the expression of oncostatin M (Osm), suppressing collagen gene expression in adipose tissue fibroblasts. Consistent with these findings, Osm deficiency in immune cells enhanced obesity-induced adipose tissue fibrosis in vivo. Moreover, OSM expression was positively correlated with MINCLE expression in human adipose tissue during obesity. Our results suggest that Osm secreted by Mincle-expressing macrophages is involved in dynamic adipose tissue remodeling in the proximity of CLS.

ARTICLE HIGHLIGHTS

Adipose tissue fibrosis is a complex and dynamic process that involves many cell types, such as macrophages and fibroblasts. Crown-like structures, which drive inflammation and fibrosis in obesity, are excellent targets for single-cell and spatial transcriptomics. We found novel cell-to-cell communications between macrophages and fibroblasts in adipose tissue from diet-induced obese mice, particularly during the fibrotic phase. We elucidated the role of the macrophage-inducible C-type lectin-oncostatin M axis in obesity-induced adipose tissue fibrosis.

Whole genome sequencing and single-cell transcriptomics identify KMT2D inactivation as a potential new driver for pituitary tumors: a case report

The pituitary gland is a main component of the endocrine system and a master controller of hormone production and secretion. Unlike neoplastic formation in other organs, Pituitary Neuroendocrine Tumors (PitNETs) are frequent in the population (16%) and, for unknown reasons, almost never metastatic. So far, few genes have been identified as drivers for PitNETs, such as GNAS in somatotroph tumors and USP8 in corticotroph tumors. Using whole genome sequencing, we uncover a potential novel driver, the histone methyltransferase KMT2D, in a patient in his 50s suffering from a mixed somato-lactotroph tumor. Coverage ratio between germline and tumor revealed extensive chromosomal alterations. Single-cell RNA sequencing of the tumor shows up-regulation of known tumorigenic pathways compared to a healthy reference, as well as a different immune infiltration profile compared to other PitNETs, more closely resembling the profile of carcinomas than adenomas. Genome-wide DNA methylation analysis identified 796 differentially methylated regions, including notable hypomethylation in the promoter of SPON2, an immune-related gene. Our results show that tumors considered quiet and non-aggressive can share drivers, features, and epigenetic alterations with metastatic forms of cancer, raising questions about the biological mechanisms controlling their homeostasis.

scMetaIntegrator: a meta-analysis approach to paired single-cell differential expression analysis

Traditional differential gene expression methods are limited for analysis of single cell RNA-sequencing (scRNA-seq) studies that use paired repeated measures and matched cohort designs. Many existing approaches consider cells as independent samples, leading to high false positive rates while ignoring inherent sampling structures. Although pseudobulk methods address this, they ignore intra-sample expression variability and have higher false negatives rates. We propose a novel meta-analysis approach that accounts for biological replicates and cell variability in paired scRNA-seq data. Using both real and synthetic datasets, we show that our method, single-cell MetaIntegrator (https://github.com/Khatri-Lab/scMetaIntegrator), provides robust effect size estimates and reproducible p-values.

Transcription factors SP5 and SP8 drive primary cilia formation

While specific transcription factors are known to regulate cell fate decisions, the degree to which they can stimulate formation of specific cell organelles is less clear. We used a multi-omics comparison of the transcriptomes of ciliated and non-ciliated embryonic cells to identify transcription factors upregulated in ciliated cells, and conditional genetics in mouse embryos and stem cells to demonstrate that SP5/8 regulate cilia formation and gene expression. In Sp5/8 mutant embryos primary and motile cilia are shorter than normal and reduced in number across cell types, contributing to situs inversus and hydrocephalus. Moreover, expression of SP8 is sufficient to induce primary cilia in unciliated cells. This work opens new avenues for studying cilia assembly using stem cell models and offers new insights into human ciliopathies.

Single-cell transcriptomics reveal how root tissues adapt to soil stress

Land plants thrive in soils showing vastly different properties and environmental stresses1. Root systems can adapt to contrasting soil conditions and stresses, yet how their responses are programmed at the individual cell scale remains unclear. Using single-cell RNA sequencing and spatial transcriptomic approaches, we showed major expression changes in outer root cell types when comparing the single-cell transcriptomes of rice roots grown in gel versus soil conditions. These tissue-specific transcriptional responses are related to nutrient homeostasis, cell wall integrity and defence in response to heterogeneous soil versus homogeneous gel growth conditions. We also demonstrate how the model soil stress, termed compaction, triggers expression changes in cell wall remodelling and barrier formation in outer and inner root tissues, regulated by abscisic acid released from phloem cells. Our study reveals how root tissues communicate and adapt to contrasting soil conditions at single-cell resolution.

Glioma-neuronal circuit remodeling induces regional immunosuppression

Neuronal activity-driven mechanisms influence glioblastoma cell proliferation and invasion, while glioblastoma remodels neuronal circuits. Although a subpopulation of malignant cells enhances neuronal connectivity, their impact on the immune system remains unclear. Here, we show that glioblastoma regions with enhanced neuronal connectivity exhibit regional immunosuppression, characterized by distinct immune cell compositions and the enrichment of anti-inflammatory tumor-associated macrophages (TAMs). In preclinical models, knockout of Thrombospondin-1 (TSP1/Thbs1) in glioblastoma cells suppresses synaptogenesis and glutamatergic neuronal hyperexcitability. Furthermore, TSP1 knockout restores antigen presentation-related genes, promotes the infiltration of pro-inflammatory TAMs and CD8 + T-cells in the tumor, and alleviates TAM-mediated T-cell suppression. Pharmacological inhibition of glutamatergic signaling also shifts TAMs toward a less immunosuppressive state, prolongs survival in mice, and shows the potential to enhance the efficacy of immune cell-based therapy. These findings confirm that glioma-neuronal circuit remodeling is strongly linked with regional immunosuppression and suggest that targeting glioma-neuron-immune crosstalk could provide avenues for immunotherapy.

Growth of the maternal intestine during reproduction

The organs of many female animals are remodeled by reproduction. Using the mouse intestine, a striking and tractable model of organ resizing, we find that reproductive remodeling is anticipatory and distinct from diet- or microbiota-induced resizing. Reproductive remodeling involves partially irreversible elongation of the small intestine and fully reversible growth of its epithelial villi, associated with an expansion of isthmus progenitors and accelerated enterocyte migration. We identify induction of the SGLT3a transporter in a subset of enterocytes as an early reproductive hallmark. Electrophysiological and genetic interrogations indicate that SGLT3a does not sustain digestive functions or enterocyte health; rather, it detects protons and sodium to extrinsically support the expansion of adjacent Fgfbp1-positive isthmus progenitors, promoting villus growth. Our findings reveal unanticipated specificity to physiological organ remodeling. We suggest that organ- and state-specific growth programs could be leveraged to improve pregnancy outcomes or prevent maladaptive consequences of such growth.

Allometry of cell types in planarians by single-cell transcriptomics

Allometry explores the relationship between an organism's body size and its various components, offering insights into ecology, physiology, metabolism, and disease. The cell is the basic unit of biological systems, and yet the study of cell-type allometry remains relatively unexplored. Single-cell RNA sequencing (scRNA-seq) provides a promising tool for investigating cell-type allometry. Planarians, capable of growing and degrowing following allometric scaling rules, serve as an excellent model for these studies. We used scRNA-seq to examine cell-type allometry in asexual planarians of different sizes, revealing that they consist of the same basic cell types but in varying proportions. Notably, the gut basal cells are the most responsive to changes in size, suggesting a role in energy storage. We capture the regulated gene modules of distinct cell types in response to body size. This research sheds light on the molecular and cellular aspects of cell-type allometry in planarians and underscores the utility of scRNA-seq in these investigations.

Spatial and multiomics analysis of human and mouse lung adenocarcinoma precursors reveals TIM-3 as a putative target for precancer interception

How tumor microenvironment shapes lung adenocarcinoma (LUAD) precancer evolution remains poorly understood. Spatial immune profiling of 114 human LUAD and LUAD precursors reveals a progressive increase of adaptive response and a relative decrease of innate immune response as LUAD precursors progress. The immune evasion features align the immune response patterns at various stages. TIM-3-high features are enriched in LUAD precancers, which decrease in later stages. Furthermore, single-cell RNA sequencing (scRNA-seq) and spatial immune and transcriptomics profiling of LUAD and LUAD precursor specimens from 5 mouse models validate high TIM-3 features in LUAD precancers. In vivo TIM-3 blockade at precancer stage, but not at advanced cancer stage, decreases tumor burden. Anti-TIM-3 treatment is associated with enhanced antigen presentation, T cell activation, and increased M1/M2 macrophage ratio. These results highlight the coordination of innate and adaptive immune response/evasion during LUAD precancer evolution and suggest TIM-3 as a potential target for LUAD precancer interception.

Two-stage CD8+ CAR T-cell differentiation in patients with large B-cell lymphoma

Advancements in chimeric antigen receptor (CAR) T-cell therapy for treating diffuse large B-cell lymphoma (DLBCL) have been limited by an incomplete understanding of CAR T-cell differentiation in patients. Here, we show via single-cell, multi-modal, and longitudinal analyses, that CD8+ CAR T cells from DLBCL patients successfully treated with axicabtagene ciloleucel undergo two distinct waves of clonal expansion in vivo. The first wave is dominated by an exhausted-like effector memory phenotype during peak expansion (day 8-14). The second wave is dominated by a terminal effector phenotype during the post-peak persistence period (day 21-28). Importantly, the two waves have distinct ontogeny from the infusion product and are biologically uncoupled. Precursors of the first wave exhibit more effector-like signatures, whereas precursors of the second wave exhibit more stem-like signatures. We demonstrate that CAR T-cell expansion and persistence are mediated by clonally, phenotypically, and ontogenically distinct CAR T-cell populations that serve complementary clinical purposes.

CD55 upregulation in T cells of COVID-19 patients suppresses type-I interferon responses

Complement overactivation, has been verified in COVID-19 patients. Complement regulatory proteins, including CD55, control complement overactivation thus eliminating complement deposition and cell lysis. We investigated complement regulatory protein expression in COVID-19 for potential deregulated expression patterns driving disease pathogenesis. Single-cell RNA-seq revealed increased PBMCs CD55 expression in severely and critically ill patients. This increase was also detected upon integrated subclustering analysis of monocyte, T cell and B cell populations. FACS analysis confirmed the significant upregulation of CD55 expression in CD4+ and CD8+ T cells and monocyte populations of severely and critically ill COVID-19 patients. This upregulation was associated with decreased expression of type-I IFN-stimulated genes (ISGs) in patients with severe and critical COVID-19, indicating a suppressor effect of CD55. Silencing of CD55 in T cells from COVID-19 severely ill patients in vitro and sensitization with SARS-CoV-2 peptides resulted in significantly augmented expression of ISGs and a reversal of their expression to levels similar to control or higher. The present study uncovers, to the best of our knowledge, a novel regulatory effect of CD55 on type-I IFN responses of severely ill COVID-19 patients, thus indicating its contribution to COVID-19 pathogenesis, and identifies a novel mechanistic pathway in the COVID-19 immune response.

Mechanism and Efficacy of Etanercept in Treating Autoimmune-like Manifestations of Coronavirus Disease 2019 in elderly individuals

During the COVID-19 pandemic, extensive research focused on universal treatments, but few studies addressed treatment regimens for elderly patients. This study aimed to evaluate the effects of etanercept, a TNF inhibitor, in elderly individuals with COVID-19 through observational analysis of compassionate use cases. The results showed that after one month of etanercept treatment, clinical indicators such as C-reactive protein, D-dimer, and fibrinogen normalised, whereas the control group receiving conventional treatment did not fully recover. Single-cell sequencing was performed on seven patients treated with etanercept and two uninfected individuals. Based on our data and in conjunction with external data, a comprehensive characterization map involving 400,000 cells was created. Transcriptomic analysis revealed autoimmune-like manifestations in elderly patients, highlighting the importance of immunotherapy. Plasma cells, platelets, and B cells were the most treatment-sensitive cells. Analysis of five drug types, including antiviral, etanercept, glucocorticoids, tocilizumab, and others, showed that tocilizumab was associated with an increased thrombosis risk in elderly patients. Meanwhile, etanercept alleviated autoimmune-like manifestations by inhibiting platelet factor 4 and suppressing TNF-α. Molecular docking showed etanercept's strong affinity (-15.0 kcal/mol) for the spike protein of the SARS-CoV-2 Omicron variant, suggesting it may protect immune-compromised patients. Our findings support etanercept as a potential treatment for elderly COVID-19 patients with autoimmune-like manifestations.

Towards a consensus atlas of human and mouse adipose tissue at single-cell resolution

Adipose tissue (AT) is a complex connective tissue with a high relative proportion of adipocytes, which are specialized cells with the ability to store lipids in large droplets. AT is found in multiple discrete depots throughout the body, where it serves as the primary repository for excess calories. In addition, AT has an important role in functions as diverse as insulation, immunity and regulation of metabolic homeostasis. The Human Cell Atlas Adipose Bionetwork was established to support the generation of single-cell atlases of human AT as well as the development of unified approaches and consensus for cell annotation. Here, we provide a first roadmap from this bionetwork, including our suggested cell annotations for humans and mice, with the aim of describing the state of the field and providing guidelines for the production, analysis, interpretation and presentation of AT single-cell data.

Semaglutide and bariatric surgery induce distinct changes in the composition of mouse white adipose tissue

Adipose tissue is a central player in energy balance and glucose homeostasis, expanding in the face of caloric overload in order to store energy safely. If caloric overload continues unabated, however, adipose tissue becomes dysfunctional, leading to systemic metabolic compromise in the form of insulin resistance and type 2 diabetes. Changes in adipose tissue during the development of metabolic disease are varied and complex, made all the more so by the heterogeneity of cell types within the tissue. Here we present detailed comparisons of atlases of murine WAT in the setting of diet-induced obesity, as well as after weight loss induced by either vertical sleeve gastrectomy (VSG) or treatment with the GLP-1 receptor agonist semaglutide. We focus on identifying populations of cells that return to a lean-like phenotype versus those that persist from the obese state, and examine pathways regulated in these cell types across conditions. These data provide a resource for the study of the cell type changes in WAT during weight loss, and paint a clearer picture of the differences between adipose tissue from lean animals that have never been obese, versus those that have.

Single cell analysis reveals that SPP1+ macrophages enhance tumor progression by triggering fibroblast extracellular vesicles

Patients with liver metastatic colorectal cancer (mCRC) have a poor prognosis and are the leading cause of death in colorectal cancer (CRC) patients, but the mechanisms associated with CRC metastasis have not been fully elucidated. In this study, we obtained data from the Gene Expression Omnibus database and characterized the single-cell profiles of CRC, mCRC and healthy samples at single-cell resolution, and explored the cells that influence CRC metastasis. We find that AQP1+ CRC identified as highly malignant tumor cells exhibited proliferative and metastatic characteristics. Immunosuppressive properties are present in the tumor microenvironment (TME), while NOTCH3+ Fib is identified to play a facilitating role in the metastatic colonization of CRC. Importantly, we reveal that tumor-associated macrophages (TAM) characterized by SPP1-specific high expression may be involved in TME remodeling through intercellular communication. Specifically, SPP1+ TAM mediates the generation of Fib-derived extracellular vesicle through the APOE-LRP1 axis, which in turn delivers tumor growth-promoting factors in the TME. This study deepens the understanding of the mechanism of TME in mCRC and lays the scientific foundation for the development of therapeutic regimens for mCRC patients.

CHOIR improves significance-based detection of cell types and states from single-cell data

Clustering is a critical step in the analysis of single-cell data, enabling the discovery and characterization of cell types and states. However, most popular clustering tools do not subject results to statistical inference testing, leading to risks of overclustering or underclustering data and often resulting in ineffective identification of cell types with widely differing prevalence. To address these challenges, we present CHOIR (cluster hierarchy optimization by iterative random forests), which applies a framework of random forest classifiers and permutation tests across a hierarchical clustering tree to statistically determine clusters representing distinct populations. We demonstrate the performance of CHOIR through extensive benchmarking against 15 existing clustering methods across 230 simulated and five real single-cell RNA sequencing, assay for transposase-accessible chromatin sequencing, spatial transcriptomic and multi-omic datasets. CHOIR can be applied to any single-cell data type and provides a flexible, scalable and robust solution to the challenge of identifying biologically relevant cell groupings within heterogeneous single-cell data.

ARID5A orchestrates cardiac aging and inflammation through MAVS mRNA stabilization

Elucidating the regulatory mechanisms of human cardiac aging remains a great challenge. Here, using human heart tissues from 74 individuals ranging from young (≤35 years) to old (≥65 years), we provide an overview of the histological, cellular and molecular alterations underpinning the aging of human hearts. We decoded aging-related gene expression changes at single-cell resolution and identified increased inflammation as the key event, driven by upregulation of ARID5A, an RNA-binding protein. ARID5A epi-transcriptionally regulated Mitochondrial Antiviral Signaling Protein (MAVS) mRNA stability, leading to NF-κB and TBK1 activation, amplifying aging and inflammation phenotypes. The application of gene therapy using lentiviral vectors encoding shRNA targeting ARID5A into the myocardium not only mitigated the inflammatory and aging phenotypes but also bolstered cardiac function in aged mice. Altogether, our study provides a valuable resource and advances our understanding of cardiac aging mechanisms by deciphering the ARID5A-MAVS axis in post-transcriptional regulation.

Replicability of bulk RNA-Seq differential expression and enrichment analysis results for small cohort sizes

The high-dimensional and heterogeneous nature of transcriptomics data from RNA sequencing (RNA-Seq) experiments poses a challenge to routine downstream analysis steps, such as differential expression analysis and enrichment analysis. Additionally, due to practical and financial constraints, RNA-Seq experiments are often limited to a small number of biological replicates. In light of recent studies on the low replicability of preclinical cancer research, it is essential to understand how the combination of population heterogeneity and underpowered cohort sizes affects the replicability of RNA-Seq research. Using 18'000 subsampled RNA-Seq experiments based on real gene expression data from 18 different data sets, we find that differential expression and enrichment analysis results from underpowered experiments are unlikely to replicate well. However, low replicability does not necessarily imply low precision of results, as data sets exhibit a wide range of possible outcomes. In fact, 10 out of 18 data sets achieve high median precision despite low recall and replicability for cohorts with more than five replicates. To assist researchers constrained by small cohort sizes in estimating the expected performance regime of their data sets, we provide a simple bootstrapping procedure that correlates strongly with the observed replicability and precision metrics. We conclude with practical recommendations to alleviate problems with underpowered RNA-Seq studies.

Transcriptome-wide analysis of differential expression in perturbation atlases

Single-cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are noisy, and many effects may go undetected. Here we introduce transcriptome-wide analysis of differential expression (TRADE)-a statistical model for the distribution of true differential expression effects that accounts for estimation error appropriately. TRADE estimates the 'transcriptome-wide impact', which quantifies the total effect of a perturbation across the transcriptome. Analyzing several large Perturb-seq datasets, we show that many transcriptional effects remain undetected in standard analyses but emerge in aggregate using TRADE. A typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene affects over 500. We find moderate consistency of perturbation effects across cell types, identify perturbations where transcriptional responses vary qualitatively across dosage levels and clarify the relationship between genetic and transcriptomic correlations across neuropsychiatric disorders.

Ucenprubart is an agonistic antibody to CD200R with the potential to treat inflammatory skin disease: preclinical development and a phase 1 clinical study

CD200R is a checkpoint inhibitory receptor central to the pathogenesis of inflammatory skin disease. Here we describe the development and phase 1 clinical study (NCT03750643) of ucenprubart, a CD200R agonist antibody to downregulate immune system inflammation. Preclinical studies find ucenprubart inhibiting Fcγ receptor-induced cytokine secretion from myeloid cells in vitro and demonstrating efficacy in a mouse contact hypersensitivity model. The randomized, placebo-controlled, NCT03750643 trial assesses safety and pharmacokinetics in healthy subjects, and efficacy in atopic dermatitis patients. The primary efficacy outcome is the proportion of patients achieving Validated Investigator's Global Assessment for Atopic Dermatitis (vIGA-AD) 0 or 1 with ≥2-point improvement from baseline at week 12. Secondary outcomes are proportions of patients achieving the primary outcome and mean changes in Eczema Area and Severity Index (EASI) and SCORing Atopic Dermatitis (SCORAD) across weeks 1 through 12, and cutoffs at week 12. Sixty-two healthy participants and 40 patients are enrolled. No serious adverse events or discontinuations due to adverse events is seen with ucenprubart. The primary endpoint is not met; however, overall improvements are observed in EASI-75 and SCORAD through 12 weeks. CD200R may be a promising therapeutic target for treating autoimmune disease, including inflammatory skin diseases.

Single-cell multi-omics profiling uncovers the immune heterogeneity in HIV-infected immunological non-responders

BACKGROUND

Immunological non-responders (INRs) are people living with HIV-1 who fail to achieve full immune reconstitution despite long-term effective antiretroviral therapy (ART). This incomplete recovery of CD4+ T cells increase the risk of opportunistic infections and non-AIDS-related morbidity and mortality. Understanding the mechanisms driving this immune dysfunction is critical for developing targeted therapies.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) and single-cell VDJ sequencing (scVDJ-seq) on peripheral blood mononuclear cells (PBMCs) from INRs, immune responders (IRs), and healthy controls (HCs). We developed scGeneANOVA, a novel mixed model differential gene analysis tool, to detect differentially expressed genes and pathways. In addition, we developed the Viral Identification and Load Detection Analysis (VILDA) tool to quantify HIV-1 transcripts and investigate their relationship with interferon (IFN) pathway activation.

FINDINGS

Our analysis revealed that INRs exhibit a dysregulated IFN response, closely associated with CD4+ T cell exhaustion and immune recovery failure. The scGeneANOVA tool identified critical genes and pathways that were missed by traditional analysis methods, while VILDA showed higher levels of HIV-1 transcripts in INRs, which may drive the heightened IFN response. These findings support a potential contribution of IFN signalling in INR-related immune dysfunction.

INTERPRETATION

Our study provides new insights into the pathogenic mechanisms behind immune recovery failure in INRs, suggesting that IFN signalling might be involved in the development of CD4+ T cell exhaustion. The identification of key genes and pathways offers potential biomarkers and therapeutic targets for improving immune recovery in this vulnerable population.

FUNDING

This study was supported by the grants from Special Research Fund for the Central High-level Hospitals of Peking Union Medical College Hospital (Grant No. 2022-PUMCH-D-008), Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (Grant No. 2021-I2M-1-037), National Key Technologies R&D Program for the 13th Five-year Plan (Grant No. 2017ZX10202101-001). The funders played no role in the design, experiment conduction, data analysis and preparation of the manuscript of this work.

scMultiMap: Cell-type-specific mapping of enhancers and target genes from single-cell multimodal data

Mapping enhancers and target genes in disease-related cell types provides critical insights into the functional mechanisms of genome-wide association studies (GWAS) variants. Single-cell multimodal data, which measure gene expression and chromatin accessibility in the same cells, enable the cell-type-specific inference of enhancer-gene pairs. However, this task is challenged by high data sparsity, sequencing depth variation, and the computational burden of analyzing a large number of pairs. We introduce scMultiMap, a statistical method that infers enhancer-gene association from sparse multimodal counts using a joint latent-variable model. It adjusts for technical confounding, permits fast moment-based estimation and provides analytically derived p-values. In blood and brain data, scMultiMap shows appropriate type I error control, high statistical power, and computational efficiency (1% of existing methods). When applied to Alzheimer's disease (AD) data, scMultiMap gives the highest heritability enrichment in microglia and reveals insights into the regulatory mechanisms of AD GWAS variants.

Testosterone affects female CD4+ T cells in healthy individuals and autoimmune liver diseases

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases with strong female predominance. They are caused by T cell-mediated injury of hepatic parenchymal cells, but the mechanisms underlying this sex bias are unknown. Here, we investigated whether testosterone contributes to T cell activation in women with PBC. Compared with sex- and age-matched healthy controls (n = 23), cisgender (cis) women with PBC (n = 24) demonstrated decreased testosterone serum levels and proinflammatory CD4+ T cell profile in peripheral blood. Testosterone suppressed the expression of TNF and IFN-γ by human CD4+ T cells in vitro. In trans men receiving gender-affirming hormone therapy (GAHT) (n = 25), testosterone affected CD4+ T cell function by inhibiting Th1 and Th17 differentiation and by supporting the differentiation into regulatory Treg. Mechanistically, we provide evidence for a direct effect of testosterone on T cells using mice with T cell-specific deletion of the cytosolic androgen receptor. Supporting a role for testosterone in autoimmune liver disease, we observed an improved disease course and profound changes in T cell states in a trans man with AIH/primary sclerosing cholangitis (PSC) variant syndrome receiving GAHT. We here report a direct effect of testosterone on CD4+ T cells that may contribute to future personalized treatment strategies.

Asian diversity in human immune cells

The relationships of human diversity with biomedical phenotypes are pervasive yet remain understudied, particularly in a single-cell genomics context. Here, we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 donors, spanning 7 population groups across 5 Asian countries, and 6 controls. Though population groups are frequently compared at the continental level, we found that sub-continental diversity, age, and sex pervasively impacted cellular and molecular properties of immune cells. These included differential abundance of cell neighborhoods as well as cell populations and genes relevant to disease risk, pathogenesis, and diagnostics. We discovered functional genetic variants influencing cell-type-specific gene expression, which were under-represented in non-Asian populations, and helped contextualize disease-associated variants. AIDA enables analyses of multi-ancestry disease datasets and facilitates the development of precision medicine efforts in Asia and beyond.

A spatially resolved transcriptome landscape during thyroid cancer progression

Tumor microenvironment (TME) remodeling plays a pivotal role in thyroid cancer progression, yet its spatial dynamics remain unclear. In this study, we integrate spatial transcriptomics and single-cell RNA sequencing to map the TME architecture across para-tumor thyroid (PT) tissue, papillary thyroid cancer (PTC), locally advanced PTC (LPTC), and anaplastic thyroid carcinoma (ATC). Our integrative analysis reveals extensive molecular and cellular heterogeneity during thyroid cancer progression, enabling the identification of three distinct thyrocyte meta-clusters, including TG+IYG+ subpopulation in PT, HLA-DRB1+HLA-DRA+ subpopulation in early cancerous stages, and APOE+APOC1+ subpopulation in late-stage progression. We reveal stage-specific tumor leading edge remodeling and establish high-confidence cell-cell interactions, such as COL8A1-ITHB1 in PTC, LAMB2-ITGB4 in LPTC, and SERPINE1-PLAUR in ATC. Notably, both SERPINE1 expression level and SERPINE1+ fibroblast abundance correlate with malignant progression and prognosis. These findings provide a spatially resolved framework of TME remodeling, offering insights for thyroid cancer diagnosis and treatment.

Sphingolipid metabolism orchestrates establishment of the hair follicle stem cell compartment

Sphingolipids serve as building blocks of membranes to ensure subcellular compartmentalization and facilitate intercellular communication. How cell type-specific lipid compositions are achieved and what is their functional significance in tissue morphogenesis and maintenance has remained unclear. Here, we identify a stem cell-specific role for ceramide synthase 4 (CerS4) in orchestrating fate decisions in skin epidermis. Deletion of CerS4 prevents the proper development of the adult hair follicle bulge stem cell (HFSC) compartment due to altered differentiation trajectories. Mechanistically, HFSC differentiation defects arise from an imbalance of key ceramides and their derivate sphingolipids, resulting in hyperactivation of noncanonical Wnt signaling. This impaired HFSC compartment establishment leads to disruption of hair follicle architecture and skin barrier function, ultimately triggering a T helper cell 2-dominated immune infiltration resembling human atopic dermatitis. This work uncovers a fundamental role for a cell state-specific sphingolipid profile in stem cell homeostasis and in maintaining an intact skin barrier.

Functional maturation of preterm intestinal epithelium through CFTR activation

Preterm birth disrupts intestinal epithelial maturation, impairing digestive and absorptive functions. This study integrates analysis of single-cell RNA sequencing datasets, spanning fetal to adult stages, with human preterm intestinal models derived from the ileal tissue of preterm infants. We investigate the potential of extracellular vesicles (EVs) derived from human Wharton's jelly mesenchymal stem cells to promote intestinal maturation. Distinct enterocyte differentiation trajectories are identified during the transition from immature to mature stages of human intestinal development. EV treatment, particularly with the EV39 line, significantly upregulates maturation-specific gene expression related to enterocyte function. Gene set enrichment analysis reveals an enrichment of TGFβ1 signaling pathways, and proteomic analysis identifies TGFβ1 and FGF2 as key mediators of EV39's effects. These treatments enhance cell proliferation, epithelial barrier integrity, and fatty acid uptake, primarily through CFTR-dependent mechanisms-unique to human preterm models, not observed in mouse intestinal organoids. This highlights the translational potential of EV39 and CFTR activation in promoting the functional maturation of the premature human intestine.

CD45+/ Col I+ Fibrocytes: Major source of collagen in the fibrotic lung, but not in passaged fibroblast cultures

The role of cells of the hematopoietic lineage in fibrosis is controversial. Here we evaluate the contribution of Col I+/CD45+ cells (fibrocytes) to lung fibrosis. Systemic bleomycin treatment was used to induce fibrosis in a bone marrow transplant and two transgenic mouse models. Lung cells from these mice were analyzed by flow cytometry, both immediately upon release from the tissue or following growth on tissue-culture plastic. Fibrotic and control human lung tissue were also used. Fibroblasts and fibrocytes derived from a transgenic mouse model were compared in terms of their morphology, growth, and adhesion to fibronectin. Single cell RNAseq was performed with the analysis focusing on CD45-/Col I+ "fibroblasts" and CD45+/Col I+ "fibrocytes" in control and fibrotic mouse lung tissue. Finally, we inhibited fibrosis in mice using a novel, water-soluble version of caveolin scaffolding domain (CSD) called WCSD. In both mouse and human lung tissue, we observed by flow cytometry a large increase in fibrocyte number and Col I expression associated with fibrosis. In contrast, fibroblast number was not significantly increased. A large increase (>50-fold) in fibrocyte number associated with fibrosis was also observed by single cell RNAseq. In this case, fibroblasts increased 5-fold. Single cell RNAseq also revealed that myofibroblast markers in fibrotic tissue are associated with a cluster containing a similar number of fibrocytes and fibroblasts, not with a resident fibroblast cluster. Some investigators claim that fibrocytes are not present among primary fibroblasts. However, we found that fibrocytes were the predominant cell type present in these cultures prior to passage. Fewer fibrocytes were present after one passage, and almost none after two passages. Our experiments suggest that fibrocytes are crowded out of cultures during passage because fibroblasts have a larger footprint than fibrocytes, even though fibrocytes bind more efficiently to fibronectin. Finally, we observed by flow cytometry that in mice treated with bleomycin and WCSD compared to bleomycin alone, there was a large decrease in the number of fibrocytes present but not in the number of fibroblasts. In summary, fibrocytes are a major collagen-producing cell type that is increased in number in association with fibrosis as well as a major source of myofibroblasts. The common observation that collagen-producing spindle-shaped cells associated with fibrosis are CD45- may be an artifact of passage in cell culture.

Therapeutic strategies to reverse cigarette smoke-induced ion channel and mucociliary dysfunction in COPD airway epithelial cells

Cigarette smoke (CS) is a leading cause of chronic obstructive pulmonary disease (COPD). Here, we investigated whether the ion channel amplifier nesolicaftor rescues CS-induced mucociliary and ion channel dysfunction. As CS increases the expression of transforming growth factor-beta1 (TGF-β1), human bronchial epithelial cells (HBECs) from healthy donors were used for TGF-β1 and COPD donors (COPD-HBEC) for CS exposure experiments. CS and TGF-β1 induce mucociliary dysfunction by increasing MUC5AC and decreasing ion channel conductance important for mucus hydration. These include cystic fibrosis transmembrane conductance regulator (CFTR) and apical large-conductance, Ca2+-activated K+ (BK) channels. Nesolicaftor rescued CFTR and BK channel dysfunction, restored ciliary beat frequency (CBF), and decreased mucus viscosity and MUC5AC expression in CS-exposed COPD-HBEC. Nesolicaftor further reversed reductions in airway surface liquid (ASL) volumes, CBF, and CFTR and BK conductance, and blocked the increase in extracellular signal-regulated kinase (ERK) signaling in TGF-β1-exposed normal HBECs. Mechanistically, nesolicaftor increased, as expected, not only binding of PCBP1 to CFTR mRNA but also surprisingly to LRRC26 mRNA, which encodes the gamma subunit required for BK function. Similar to nesolicaftor, the angiotensin receptor blocker (ARB) losartan rescued TGF-β1-mediated decreases in PCBP1 binding to LRRC26 mRNA. In addition, the ARB telmisartan restored PCBP1 binding to CFTR and LRRC26 mRNAs to rescue CFTR and BK function in CS-exposed COPD-HBEC. Thus, nesolicaftor and ARBs act on the same target and were therefore neither additive nor synergistic in their actions. These data demonstrate that nesolicaftor and ARBs may provide benefits in COPD by improving ion channel function important for mucus hydration.NEW & NOTEWORTHY Cigarette smoke (CS) increases transforming growth factor-beta1 (TGF-β1) expression that causes mucociliary dysfunction by decreasing ion channel function. In our study, a CFTR amplifier (nesolicaftor) and angiotensin II receptor blockers (losartan and telmisartan) improve CS-induced ion channel dysfunction, by increasing binding of PCBP1 to CFTR and LRRC26 mRNAs. Therefore, nesolicaftor and ARBs, acting on the same target, may provide therapeutic benefits for treating smoking-related diseases.

Human Neonatal MR1T Cells Have Diverse TCR Usage, are Less Cytotoxic and are Unable to Respond to Many Common Childhood Pathogens

Neonatal sepsis is a leading cause of childhood mortality. Understanding immune cell development can inform strategies to combat this. MR1-restricted T (MR1T) cells can be defined by their recognition of small molecules derived from microbes, self, and drug and drug-like molecules, presented by the MHC class 1-related molecule (MR1). In healthy adults, the majority of MR1T cells express an invariant α-chain; TRAV1-2/TRAJ33/12/20 and are referred to as mucosal-associated invariant T (MAIT) cells. Neonatal MR1T cells isolated from cord blood (CB) demonstrate more diversity in MR1T TCR usage, with the majority of MR1-5-OP-RU-tetramer(+) cells being TRAV1-2(-). To better understand this diversity, we performed single-cell-RNA-seq/TCR-seq (scRNA-seq/scTCR-seq) on MR1-5-OP-RU-tetramer(+) cells from CB (n=5) and adult participants (n=5). CB-derived MR1T cells demonstrate a less cytotoxic/pro-inflammatory phenotype, and a more diverse TCR repertoire. A panel of CB and adult MAIT and TRAV1-2(-) MR1T cell clones were generated, and CB-derived clones were unable to recognize several common riboflavin-producing childhood pathogens (S. aureus, S. pneumoniae, M. tuberculosis). Biochemical and structural investigation of one CB MAIT TCR (CB964 A2; TRAV1-2/TRBV6-2) showed a reduction in binding affinity toward the canonical MR1-antigen, 5-OP-RU, compared to adult MAIT TCRs that correlated with differences in β-chain contribution in the TCR-MR1 interface. Overall, this data shows that CB MAIT and TRAV1-2(-) MR1T cells, express a diverse TCR repertoire, a more restricted childhood pathogen recognition profile and diminished cytotoxic and pro-inflammatory capacity. Understanding this diversity, along with the functional ability of TRAV1-2(-) MR1T cells, could provide insight into increased neonatal susceptibility to infections.

The single-cell immune landscape of HIV-associated aggressive B-cell lymphoma

Background

Human immunodeficiency virus (HIV)-associated lymphomas (HAL), mainly aggressive B-cell lymphomas, pose a significant challenge in cancer research due to their multifaceted pathogenesis and aggressive clinical course. Despite the clinical importance, the genomic and immune characteristics of these lymphomas remain poorly elucidated.

Methods

We employed single-cell RNA sequencing (scRNA-seq) on lymph node samples from aggressive B-cell lymphomas, mainly including 6 cases of diffuse large B-cell lymphoma (DLBCL) and 5 cases of Burkitt lymphoma (BL) from people living with HIV (PLWH), along with 3 DLBCL cases from individuals without HIV for comparison.

Results

Malignant B cells in HAL consistently exhibited high proliferative and oxidative phosphorylation (OXPHOS)-type metabolic signatures. Moreover, these cells demonstrated loss expression of major histocompatibility complex class I (MHC-I), strategically reducing tumor immunogenicity. HAL harbors special populations of naive and atypical memory B cells that exhibited high metabolic and immune-activated transcriptional profiles. Additionally, HAL exhibited senescence-like dysfunction in T cells, characterized by the reductions in regulatory activity of Treg and cytotoxic activity of CD8+ T cells, as well as decreases expression of IL7R genes and increases expression of FOS and FOSB genes. Our immunofluorescence results showed that the cytotoxic CD8+ T cells in HAL may have a dysfunction of lytic granule polarization. Furthermore, macrophages from HAL exhibited stronger immunosuppressive transcriptional characteristics, and a robust immunosuppressive SPP1-CD44 interaction was predicted between C1QA+ macrophages and T cells.

Conclusions

Our findings clearly indicate that HAL differs significantly from non-HAL, ranging from malignant B cells to the immune microenvironment. This study provides a comprehensive single-cell atlas of HIV-associated aggressive B-cell lymphomas, offering new insights into aggressiveness and immune evasion observed in HAL.

Cellular deconstruction of the human skeletal muscle microenvironment identifies an exercise-induced histaminergic crosstalk

Plasticity of skeletal muscle is induced by transcriptional and translational events in response to exercise, leading to multiple health and performance benefits. The skeletal muscle microenvironment harbors myofibers and mononuclear cells, but the rich cell diversity has been largely ignored in relation to exercise adaptations. Using our workflow of transcriptome profiling of individual myofibers, we observed that their exercise-induced transcriptional response was surprisingly modest compared with the bulk muscle tissue response. Through the integration of single-cell data, we identified a small mast cell population likely responsible for histamine secretion during exercise and for targeting myeloid and vascular cells rather than myofibers. We demonstrated through histamine H1 or H2 receptor blockade in humans that this paracrine histamine signaling cascade drives muscle glycogen resynthesis and coordinates the transcriptional exercise response. Altogether, our cellular deconstruction of the human skeletal muscle microenvironment uncovers a histamine-driven intercellular communication network steering muscle recovery and adaptation to exercise.

Single-cell sequencing uncovers a high ESM1-expression endothelial cell subpopulation associated with bladder cancer progression and the immunosuppressive microenvironment

Despite remarkable advancements in therapeutic strategies, a considerable proportion of patients with bladder cancer (BC) still experience disease progression and unfavorable prognosis. The heterogeneity and biological functions of tumor endothelial cells (ECs) during BC progression remain poorly understood. We collected scRNA-seq data from BC samples and identified two EC subpopulations through hierarchical clustering analysis. The activity of signaling pathways in distinct EC subpopulations was assessed utilizing AUCell analysis. Gene regulatory networks (GRN) were constructed and analyzed for different EC subpopulations using the pySCENIC algorithm. Additionally, we investigated the association between the abundance of EC subpopulations and both clinical prognosis and immune cell infiltration. The biological effects of ESM1 protein on BC cells were further validated through EdU and Transwell assays. We analyzed 7,519 CD45-negative single cells from BC tissues and discerned two distinct EC subpopulations. The two subpopulations were characterized by high expression of ESM1 (S1 ECs) and CXCL2 (S2 ECs), respectively. In S1 ECs, we observed significant activation of signaling pathways involved in tumor promotion, including angiogenesis and cell proliferation. Additionally, our GRN analysis uncovered notable differences in transcription factor activity between S1 and S2 ECs. Moreover, ESM1 protein promoted proliferation and migration of BC cells. Patients with higher abundance of the S1 EC subpopulation exhibited more unfavorable clinical outcomes and increased infiltration of inhibitory immune cells. Our findings elucidate the transcriptional profiles and biological roles of the high ESM1-expression endothelial cell subpopulation in BC. This subpopulation is associated with poor prognosis and immunosuppressive tumor microenvironment. Accordingly, targeting endothelial cells with high ESM1 expression may offer a novel therapeutic strategy for patients with BC.

Reelin marks cocaine-activated striatal neurons, promotes neuronal excitability, and regulates cocaine reward

Drugs of abuse activate defined neuronal populations in reward structures such as the nucleus accumbens (NAc), which promote the enduring synaptic, circuit, and behavioral consequences of drug exposure. While the molecular and cellular effects arising from experience with drugs like cocaine are increasingly well understood, mechanisms that dictate NAc neuronal recruitment remain unknown. Here, we leveraged unbiased single-nucleus transcriptional profiling and targeted in situ detection to identify Reln (encoding the secreted glycoprotein, Reelin) as a marker of cocaine-activated neuronal populations within the rat NAc. A CRISPR interference approach enabling selective Reln knockdown in the adult NAc altered expression of calcium signaling genes, promoted a transcriptional trajectory consistent with loss of cocaine sensitivity, and decreased MSN excitability. Behaviorally, Reln knockdown prevented cocaine locomotor sensitization, abolished cocaine place preference memory, and decreased cocaine self-administration behavior. These results identify Reelin as a critical mechanistic link between neuronal activation and cocaine-induced behavioral adaptations.

An aging bone marrow exacerbates lung fibrosis by fueling profibrotic macrophage persistence

Pulmonary fibrosis is an incurable disease that manifests with advanced age. Yet, how hematopoietic aging influences immune responses and fibrosis progression remains unclear. Using heterochronic bone marrow transplant mouse models, we found that an aged bone marrow exacerbates lung fibrosis irrespective of lung tissue age. Upon lung injury, there was an increased accumulation of monocyte-derived alveolar macrophages (Mo-AMs) driven by cell-intrinsic hematopoietic aging. These Mo-AMs exhibited an enhanced profibrotic profile and stalled maturation into a homeostatic, tissue-resident phenotype. This delay was shaped by cell-extrinsic environmental signals such as reduced pulmonary interleukin-10 (IL-10), perpetuating a profibrotic macrophage state. We identified regulatory T cells (Tregs) as critical providers of IL-10 upon lung injury that promote Mo-AM maturation and attenuate fibrosis progression. Our study highlights the impact of an aging bone marrow on lung immune regulation and identifies Treg-mediated IL-10 signaling as a promising target to mitigate fibrosis and promote tissue repair.

Leveraging miRNA-mediated expression profiles to predict prognosis and identify distinct molecular subtypes in ovarian cancer: a multi-cohort study

Ovarian cancer (OV) remains the deadliest gynecological malignancy, with non-coding RNA-mediated transcriptomic deregulation significantly influencing its prognosis and heterogeneous progression. In this study, we prioritized miRNA-mediated gene expression profiles by identifying key negative correlations between miRNA-mRNA pairs. We developed a machine learning-based non-coding index (NCI), incorporating a four-gene signature (GAS1, GFPT2, ZFHX4, and KCNA1) to predict patient prognosis and therapeutic response. Validation across multiple datasets revealed that OV patients with higher NCI scores had significantly poorer survival outcomes and resistance to immunotherapy. Additionally, we established a four-class subtyping taxonomy through unsupervised clustering, validated in four independent datasets. The S1 and S3 subtypes were characterized by high NCI scores, abundant stromal and immune infiltration, with the S3 subtype exhibiting the worst survival. Conversely, the S2 subtype showed downregulation of immune response genes, while the S4 subtype displayed epithelial differentiation and favourable prognosis. Integrative analyses of bulk and single-cell transcriptomic data revealed that the S3 subtype had a significantly higher fibroblast proportion compared to other subtypes, whereas the S1 subtype was marked by high T cell content. Through ridge regression-based drug sensitivity analyses, we prioritized candidate therapeutics for each subtype. Notably, the S3 subtype demonstrated sensitivity to dasatinib but resistance to methotrexate. Finally, we developed a user-friendly Shiny-based website to facilitate the application of our prognostic and subtype classification models (https://jli-bioinfo.shinyapps.io/NCI_online/). This study establishes a critical prognostic marker and proposes a novel molecular classification framework grounded in miRNA-regulated gene expression profiles, advancing our understanding of the non-coding mechanisms driving OV heterogeneity.

Decoding the ontogeny of myeloid lineage diversity by cross-species and developmental analyses of hematopoietic progenitor atlases

Myeloid cells play vital roles in homeostasis and immune responses in vertebrates, but the developmental pathway underlying their lineage diversity remains elusive. Here, we construct a single-cell transcriptional map of myeloid progenitors from mouse bone marrow and conduct cross-species and developmental analyses across human, monkey, mouse, and zebrafish. We uncover a conserved specification program separating the eosinophil-basophil-mast cell (EBM) lineage and neutrophil-monocyte (NM) lineage, reclassifying myeloid cells beyond the conventional granulocytic and monocytic framework. By generating Ikzf2-EGFP reporter mice, we identify IKZF2 as a priming marker for EBM lineage specification. Ikzf2-EGFP+ and Ikzf2-EGFP- granulocyte-monocyte progenitors (GMPs) exhibit distinct potential to generate EBM and NM lineages, and Ikzf2-EGFP expression robustly distinguishes their progenies. Additionally, we demonstrate that lineage specification emerges early during myelopoiesis. These findings provide a redefined perspective on myeloid lineage ontogeny, highlighting the conservation of lineage specification and offering insights into the understanding and therapeutic development of myelopoiesis.

Protocol for interpretable and context-specific single-cell-informed deconvolution of bulk RNA-seq data

Single-cell sequencing provides rich information; however, its clinical use is limited due to high costs and complex data output. Here, we present a protocol for extracting single-cell-related information from bulk RNA-sequencing (RNA-seq) data using the pathway-level information extractor (PLIER) algorithm. We describe the steps for extracting single-cell signatures from literature, training a PLIER model based on single-cell signatures (named CLIER), and applying it to a new dataset. This produces latent variables that are interpretable in the context of specific single-cell biology. For complete details on the use and execution of this protocol, please refer to Legouis et al.,1 where this approach is used within the renal context.

Exploring cell-to-cell variability and functional insights through differentially variable gene analysis

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular variability by capturing gene expression profiles of individual cells. The importance of cell-to-cell variability in determining and shaping cell function has been widely appreciated. Nevertheless, differential expression (DE) analysis remains a cornerstone method in analytical practice. Current computational analyses overlook the rich information encoded by variability within the single-cell gene expression data by focusing exclusively on mean expression. To offer a deeper understanding of cellular systems, there is a need for approaches to assess data variability rather than just the mean. Here we present spline-DV, a statistical framework for differential variability (DV) analysis using scRNA-seq data. The spline-DV method identifies genes exhibiting significantly increased or decreased expression variability among cells derived from two experimental conditions. Case studies show that DV genes identified using spline-DV are representative and functionally relevant to tested cellular conditions, including obesity, fibrosis, and cancer.

Distinct mismatch-repair complex genes set neuronal CAG-repeat expansion rate to drive selective pathogenesis in HD mice

Huntington's disease (HD) modifiers include mismatch-repair (MMR) genes, but their connections to neuronal pathogenesis remain unclear. Here, we genetically tested 9 HD genome-wide association study (GWAS)/MMR genes in mutant Huntingtin (mHtt) mice with 140 inherited CAG repeats (Q140). Knockout (KO) of genes encoding a distinct MMR complex either strongly (Msh3 and Pms1) or moderately (Msh2 and Mlh1) rescues phenotypes with early onset in striatal medium-spiny neurons (MSNs) and late onset in the cortical neurons: somatic CAG-repeat expansion, transcriptionopathy, and mHtt aggregation. Msh3 deficiency ameliorates open-chromatin dysregulation in Q140 neurons. Mechanistically, the fast linear rate of mHtt modal-CAG-repeat expansion in MSNs (8.8 repeats/month) is drastically reduced or stopped by MMR mutants. Msh3 or Pms1 deficiency prevents mHtt aggregation by keeping somatic MSN CAG length below 150. Importantly, Msh3 deficiency corrects synaptic, astrocytic, and locomotor defects in HD mice. Thus, Msh3 and Pms1 drive fast somatic mHtt CAG-expansion rates in HD-vulnerable neurons to elicit repeat-length/threshold-dependent, selective, and progressive pathogenesis in vivo.

Spatial genomics reveals cholesterol metabolism as a key factor in colorectal cancer immunotherapy resistance

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape across multiple cancer types achieving durable responses for a significant number of patients. Despite their success, many patients still fail to respond to ICIs or develop resistance soon after treatment. We sought to identify early treatment features associated with ICI outcome. We leveraged the MC38 syngeneic tumor model because it has variable response to ICI therapy driven by tumor intrinsic heterogeneity. ICI response was assessed based on the level of immune cell infiltration into the tumor - a well-established clinical hallmark of ICI response. We generated a spatial atlas of 48,636 transcriptome-wide spots across 16 tumors using spatial transcriptomics; given the tumors were difficult to profile, we developed an enhanced transcriptome capture protocol yielding high quality spatial data. In total, we identified 8 tumor cell subsets (e.g., proliferative, inflamed, and vascularized) and 4 stroma subsets (e.g., immune and fibroblast). Each tumor had orthogonal histology and bulk-RNA sequencing data, which served to validate and benchmark observations from the spatial data. Our spatial atlas revealed that increased tumor cell cholesterol regulation, synthesis, and transport were associated with a lack of ICI response. Conversely, inflammation and T cell infiltration were associated with response. We further leveraged spatially aware gene expression analysis, to demonstrate that high cholesterol synthesis by tumor cells was associated with cytotoxic CD8 T cell exclusion. Finally, we demonstrate that bulk RNA-sequencing was able to detect immune correlates of response but lacked the sensitivity to detect cholesterol synthesis as a feature of resistance.

Human Neonatal MR1T Cells Have Diverse TCR Usage, are Less Cytotoxic and are Unable to Respond to Many Common Childhood Pathogens

Neonatal sepsis is a leading cause of childhood mortality. Understanding immune cell development can inform strategies to combat this. MR1-restricted T (MR1T) cells can be defined by their recognition of small molecules derived from microbes, self, and drug and drug-like molecules, presented by the MHC class 1-related molecule (MR1). In healthy adults, the majority of MR1T cells express an invariant α-chain; TRAV1-2/TRAJ33/12/20 and are referred to as mucosal-associated invariant T (MAIT) cells. Neonatal MR1T cells isolated from cord blood (CB) demonstrate more diversity in MR1T TCR usage, with the majority of MR1-5-OP-RU-tetramer(+) cells being TRAV1-2(-). To better understand this diversity, we performed single-cell-RNA-seq/TCR-seq (scRNA-seq/scTCR-seq) on MR1-5-OP-RU-tetramer(+) cells from CB (n=5) and adult participants (n=5). CB-derived MR1T cells demonstrate a less cytotoxic/pro-inflammatory phenotype, and a more diverse TCR repertoire. A panel of CB and adult MAIT and TRAV1-2(-) MR1T cell clones were generated, and CB-derived clones were unable to recognize several common riboflavin-producing childhood pathogens (S. aureus, S. pneumoniae, M. tuberculosis). Biochemical and structural investigation of one CB MAIT TCR (CB964 A2; TRAV1-2/TRBV6-2) showed a reduction in binding affinity toward the canonical MR1-antigen, 5-OP-RU, compared to adult MAIT TCRs that correlated with differences in β-chain contribution in the TCR-MR1 interface. Overall, this data shows that CB MAIT and TRAV1-2(-) MR1T cells, express a diverse TCR repertoire, a more restricted childhood pathogen recognition profile and diminished cytotoxic and pro-inflammatory capacity. Understanding this diversity, along with the functional ability of TRAV1-2(-) MR1T cells, could provide insight into increased neonatal susceptibility to infections.

Exploring and mitigating shortcomings in single-cell differential expression analysis with a new statistical paradigm

BACKGROUND

Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type-specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell-specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell differential expression analysis: excessive zeros, normalization, donor effects, and cumulative biases. These "curses" underscore the limitations and conceptual pitfalls in existing workflows.

RESULTS

To address the limitations of current single-cell differential expression analysis methods, we propose GLIMES, a statistical framework that leverages UMI counts and zero proportions within a generalized Poisson/Binomial mixed-effects model to account for batch effects and within-sample variation. We rigorously benchmarked GLIMES against six existing differential expression methods using three case studies and simulations across different experimental scenarios, including comparisons across cell types, tissue regions, and cell states. Our results demonstrate that GLIMES is more adaptable to diverse experimental designs in single-cell studies and effectively mitigates key shortcomings of current approaches, particularly those related to normalization procedures. By preserving biologically meaningful signals, GLIMES offers improved performance in detecting differentially expressed genes.

CONCLUSIONS

By using absolute RNA expression rather than relative abundance, GLIMES improves sensitivity, reduces false discoveries, and enhances biological interpretability. This paradigm shift challenges existing workflows and highlights the need for careful consideration of normalization strategies, ultimately paving the way for more accurate and robust single-cell transcriptomic analyses.

Two-Stage CD8+ CAR T-Cell Differentiation in Patients with Large B-Cell Lymphoma

Chimeric antigen receptor (CAR) T-cell therapy has expanded therapeutic options for patients with diffuse large B-cell lymphoma (DLBCL). However, progress in improving clinical outcomes has been limited by an incomplete understanding of CAR T-cell differentiation in patients. To comprehensively investigate CAR T-cell differentiation in vivo, we performed single-cell, multimodal, and longitudinal analyses of CD28-costimulated CAR T cells from infusion product and peripheral blood (day 8-28) of patients with DLBCL who were successfully treated with axicabtagene ciloleucel. Here, we show that CD8+ CAR T cells undergo two distinct waves of clonal expansion. The first wave is dominated by CAR T cells with an exhausted-like effector memory phenotype during the peak expansion period (day 8-14). The second wave is dominated by CAR T cells with a terminal effector phenotype during the post-peak persistence period (day 21-28). Importantly, the two waves have distinct ontogeny and are biologically uncoupled. Furthermore, lineage tracing analysis via each CAR T cell's endogenous TCR clonotype demonstrates that the two waves originate from different effector precursors in the infusion product. Precursors of the first wave exhibit more effector-like signatures, whereas precursors of the second wave exhibit more stem-like signatures. These findings suggest that pre-infusion heterogeneity mediates the two waves of in vivo clonal expansion. Our findings provide evidence against the intuitive idea that the post-peak contraction in CAR abundance is solely apoptosis or extravasation of short-lived CAR T cells from peak expansion. Rather, our findings demonstrate that CAR T-cell expansion and persistence are mediated by clonally, phenotypically, and ontogenically distinct CAR T-cell populations that serve complementary clinical purposes.

Longitudinal single cell profiling of epitope specific memory CD4+ T cell responses to recombinant zoster vaccine

Vaccination leads to rapid expansion of antigen-specific T cells within in the first few days. However, understanding of transcriptomic changes and fates of antigen-specific T cells upon vaccination remains limited. Here, we investigate the fate of memory CD4+ T cells upon reactivation to recombinant zoster vaccine for shingles at cellular and transcriptional levels. We show that glycoprotein E-specific memory CD4+ T cells respond strongly, their frequencies remain high, and they retain markers of cell activation one year following vaccination. Memory T cells with the most dominant TCR clonotype pre-vaccination remain prevalent at year one post-vaccination. These data implicate a major role for pre-existing memory T cells in perpetuating immune repertoires upon re-encountering cognate antigens. Differential gene expression indicates that cells post-vaccination are distinct from cells at baseline, suggesting committed memory T cells display transcriptional changes upon vaccination that could alter their responses against cognate immunogens.

FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis

Single-cell multi-omics technologies have revolutionized the study of cell states and functions by simultaneously profiling multiple molecular layers within individual cells. However, existing methods for integrating these data struggle to preserve critical feature information and fail to exploit known regulatory knowledge, which is essential for understanding cell functions. This limitation hinders their ability to provide comprehensive and accurate insights into cells. Here, we propose FactVAE, an innovative factorized variational autoencoder designed for the robust and accurate understanding of single-cell multi-omics data. FactVAE integrates the factorization principle into the variational autoencoder framework, ensuring the preservation of feature information while leveraging the non-linear capture of sample information by neural networks. Additionally, known regulatory knowledge is incorporated during model training, and a knowledge transfer strategy is employed for cell embedding optimization and data augmentation. Comparative analyses of single-cell multi-omics datasets from different protocols and the spatial multi-omics dataset demonstrate that FactVAE not only outperforms benchmark methods in clustering performance but also generates augmented data that reveals the clearest cell-type-specific motif expression. Moreover, the feature embeddings captured by FactVAE enable the inference of potential and reliable gene regulatory relationships. Overall, FactVAE's superior performance and strong scalability make it a promising new solution for single-cell multi-omics data analysis.

mastR: an R package for automated identification of tissue-specific gene signatures in multi-group differential expression analysis

MOTIVATION

Biomarker discovery is important and offers insight into potential underlying mechanisms of disease. While existing biomarker identification methods primarily focus on single cell RNA sequencing (scRNA-seq) data, there remains a need for automated methods designed for labeled bulk RNA-seq data from sorted cell populations or experiments. Current methods require curation of results or statistical thresholds and may not account for tissue background expression. Here we bridge these limitations with an automated marker identification method for labeled bulk RNA-seq data that explicitly considers background expressions.

RESULTS

We developed mastR, a novel tool for accurate marker identification using transcriptomic data. It leverages robust statistical pipelines like edgeR and limma to perform pairwise comparisons between groups, and aggregates results using rank-product-based permutation test. A signal-to-noise ratio approach is implemented to minimize background signals. We assessed the performance of mastR-derived NK cell signatures against published curated signatures and found that the mastR-derived signature performs as well, if not better than the published signatures. We further demonstrated the utility of mastR on simulated scRNA-seq data and in comparison with Seurat in terms of marker selection performance.

AVAILABILITY AND IMPLEMENTATION

mastR is freely available from https://bioconductor.org/packages/release/bioc/html/mastR.html. A vignette and guide are available at https://davislaboratory.github.io/mastR. All statistical analyses were carried out using R (version ≥4.3.0) and Bioconductor (version ≥3.17).

Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms

A central challenge in developing personalized cancer cell immunotherapy is the identification of tumor-reactive T cell receptors (TCRs). By exploiting the distinct transcriptomic profile of tumor-reactive T cells relative to bystander cells, we build and benchmark TRTpred, an antigen-agnostic in silico predictor of tumor-reactive TCRs. We integrate TRTpred with an avidity predictor to derive a combinatorial algorithm of clinically relevant TCRs for personalized T cell therapy and benchmark it in patient-derived xenografts.

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but predicting causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single-cell sequencing (Perturb-seq) to systematically identify the targets of signalling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signalling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signalling pathway activation for in vivo and in situ samples. Our work enhances our understanding of signalling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.