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dittoSeq: Universal User-Friendly Single-Cell and Bulk RNA Sequencing Visualization Toolkit
Abstract
A visualization suite for major forms of bulk and single-cell RNAseq data in R. dittoSeq is color blindness-friendly by default, robustly documented to power ease-of-use, and allows highly customizable generation of both daily-use and publication-quality figures.
Availability and implementation:
dittoSeq is an R package available through Bioconductor via an open source MIT license.
Supplementary information:
Supplementary Code and figures are available at Bioinformatics online. Full vignettes are available through Bioconductor, https://bioconductor.org/packages/dittoSeq/, and github, github.com/dtm2451/dittoSeq/.
... Tools that integrate with existing R packages provide user-friendly interfaces for scRNA-seq data visualization. Bunis et al. [30] developed an R-based toolkit, dittoSeq, which integrates with popular analysis structures like Seurat. In the same vein, scViewer, introduced by Patil et al. [36] utilizes Seurat for data analysis and provides functionalities such as cell-type-specific gene expression visualization, co-expression analysis, and differential expression analysis across various biological conditions. ...
... Users can customize and export visualizations in various formats, making the tool accessible even for non-experts. Bunis et al. [30] presented dittoSeq , a universal, user-friendly toolkit for visualizing both single-cell and bulk RNA sequencing data. dittoSeq integrates with popular analysis structures like Seurat and supports various data formats. ...
... Moreover, the increasing number of visualization tools indicates a recognition of the importance of making complex RNA-seq data accessible to a broader range of users, including clinicians who may not have extensive computational expertise. Tools with user-friendly interfaces, such as dittoSeq [30] and scViewer [36], lower the barriers to entry, allowing more researchers to leverage RNA-seq data in clinical studies. Although both dittoSeq and scViewer have been widely utilized in research settings for analyzing and visualizing RNA-seq data, specific examples of their adoption in clinical laboratories remain sparse. ...
RNA sequencing (RNA-seq) has emerged as a prominent resource for transcriptomic analysis due to its ability to measure gene expression in a highly sensitive and accurate manner. With the increasing availability of RNA-seq data analysis from clinical studies and patient samples, the development of effective visualization tools for RNA-seq analysis has become increasingly important to help clinicians and biomedical researchers better understand the complex patterns of gene expression associated with health and disease. This review aims to outline the current state-of-the-art data visualization techniques and tools commonly used to frame clinical inferences from RNA-seq data and point out their benefits, applications, and limitations. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included “RNA-seq”, “visualization”, “plots”, and “clinical”. Only full-text studies reported between 2017 and 2024 were included for analysis. Following PRISMA guidelines, a total of 126 studies were identified, of which 33 studies met the inclusion criteria. We found that 18% of studies have visualization techniques and tools for circular RNA-seq data, 56% for single-cell RNA-seq data, 23% for bulk RNA-seq data, and 3% for long non-coding RNA-seq data. Overall, this review provides a comprehensive overview of the common visualization tools and their potential applications, which is a useful resource for researchers and clinicians interested in using RNA-seq data for various clinical purposes (e.g., diagnosis or prognosis).
... Expression plots, as well as boxplots and stacked bar plots of cell proportions, were generated using the R package dittoSeq [122]. Seurat, ggplot2 (v3.4.4), and our interactive ShinyApp (https:// eengelbrecht.shinyapps.io/ILD_NSCLC_ECs/). ...
Lung vasculature arises from both pulmonary and systemic (bronchial) circulations. Remodeling and structural changes in lung vasculature have been recognized in end‐stage fibrotic lung diseases such as idiopathic pulmonary fibrosis (IPF) but have not been well characterized. The vasculature that expands and supplies lung cancers is better described, with the recent recognition that systemic bronchial circulation expands to be the main blood supply to primary lung tumors. Here, we use publicly available single‐cell RNA‐sequencing (scRNA‐seq) data to compare vascular endothelial cell (EC) populations in multiple progressive interstitial lung diseases (ILD) and non‐small cell lung cancer (NSCLC) to identify common and distinct features. Lung tissue specimens were collected from healthy lung tissue (n = 59), ILD (n = 97), chronic obstructive pulmonary disease (n = 22), and NSCLC (n = 8). We identify two subtypes of expanded EC populations in both ILD and NSCLC, “Bronch‐1” and “Bronch‐2”, expressing transcripts associated with venules and angiogenic tip/stalk cells, respectively. Relative to pulmonary capillary and arterial ECs, bronchial ECs show low expression of transcripts associated with vascular barrier integrity. The pan‐bronchial EC marker COL15A1 showed positive staining in lung parenchyma from patients with IPF, SSc‐ILD, and NSCLC, whereas positive staining was limited to subpleural and peri‐bronchial regions in non‐fibrotic controls. In conclusion, expansion of a subset of ECs expressing markers of the bronchial circulation is one of the most pronounced changes in vascular cell composition across multiple ILDs and NSCLC. These data support additional studies to determine the role of the bronchial vasculature in ILD progression.
... Data were visualized with ggplot2 43 and dittoSeq. 44 The raw scRNAseq data of healthy human neutrophils 17 were downloaded from ArrayExpress (accession no. E-MTAB-11188) and processed with the same version of Cell Ranger with the same parameters used to process all other samples. ...
... ggpubr v.0.6.0. [22][23][24][25][26] Other R packages were employed as described in the relevant methods section. ...
Parkinson’s disease is most recognized for its impact on the CNS. However, recent breakthroughs underscore the crucial role of interactions between central and peripheral systems in Parkinson’s disease pathogenesis. The spotlight is now shifting as we explore beyond the CNS, discovering that peripheral changes such as inflammatory dysfunctions may predict the rate of disease progression and severity. Despite more than 200 years of research on Parkinson’s disease, reliable diagnostic or progression biomarkers and effective disease-modifying treatments are still lacking. Additionally, the cellular mechanisms that drive changes in immunity are largely unknown. Thus, understanding peripheral immune signatures could lead to earlier diagnosis and more effective treatments for Parkinson’s disease. Here, we sought to define the transcriptomic alterations of the complete peripheral immune cell compartment by single-cell RNA and T-cell-receptor sequencing with hopes of uncovering Parkinson’s disease signatures and potential peripheral blood biomarkers.
Following transcriptional profiling of 78 876 cells from 10 healthy controls and 14 Parkinson’s disease donors, we observed all expected major classes of immune cells; the myeloid (monocytes, dendritic cells) and lymphoid (T lymphocytes, B lymphocytes, natural killer) compartments were further analysed through bioinformatics re-clustering to obtain the final 38 cellular subtypes. Comparing immune cell subtypes and phenotypes between patients with Parkinson’s disease and healthy control subjects revealed notable features of Parkinson’s disease: (i) a significant shift of classical CD14+ monocytes towards an activated CD14+/CD83+ state; (ii) changes in lymphocyte subtype abundance, including a significant decrease in CD4+ naive and mucosal-associated invariant T-cell subtypes, along with an increase in CD56+ natural killer cells; (iii) the identification of several specific T-cell clones shared between multiple patients, suggesting the implication of common epitopes in Parkinson’s disease pathogenesis; and (iv) a notable increase in the expression of activation signature genes, including the AP-1 stress-response transcription factor complex, across all Parkinson’s disease cell types. This signal was not present in atypical parkinsonism patients with multiple system atrophy or progressive supranuclear palsy.
Overall, we present a comprehensive atlas of peripheral blood mononuclear cells from healthy and Parkinson’s disease donors which should serve as a tool to improve our understanding of the role the immune cell landscape plays in Parkinson’s disease pathogenesis.
... We used the colour-deficiency-friendly code from dit-toSeq [44]. For visualisation, we used mainly ggplot2 [45]. ...
Background
Circulating immune cells play a crucial role in the anti-tumour immune response, yet the systemic immune system in metastatic breast cancers is not fully characterised. Investigating the cellular and molecular changes in peripheral blood mononuclear cells (PBMCs) from breast cancer patients could elucidate the role of circulating immune cells in metastasis and aid in identifying biomarkers for disease burden and progression.
Methods
In this study, we characterised the systemic immune landscape associated with varying levels of metastatic burden by analysing the single-cell transcriptomes of PBMCs from breast cancer patients and healthy controls. Our research focused on identifying changes in immune cell composition, transcriptional programs, and immune-cell communication networks linked to metastatic burden. Additionally, we compared these PBMC features onto a single-cell atlas of primary breast tumours to study corresponding traits in tumour-infiltrating immune cells.
Results
In metastatic breast cancer, PBMCs exhibit a significant downregulation of the adaptive immune system and a decreased number and activity of unconventional T cells, such as γδ T cells. Additionally, metastatic burden is associated with impaired cell communication pathways involved in immunomodulatory functions. We also identified a gene signature derived from myeloid cells shared between tumour immune infiltrates and circulating immune cells in breast cancer patients.
Conclusions
Our study provides a comprehensive single-cell molecular profile of the peripheral immune system in breast cancer, offering a valuable resource for understanding metastatic disease in terms of tumour burden. By identifying immune traits linked to metastasis, we have unveiled potential new biomarkers of metastatic disease.
... available at (https://cran.r-project.org/web/ packages/pheatmap), and the dittoSeq R package (version 1.2.4) 83 . During the visualisation process, data was automatically scaled using the default parameters provided by these packages. ...
Breast cancer, particularly triple-negative breast cancer (TNBC), evades the body’s immune defences, in part by cultivating an immunosuppressive tumour microenvironment. Here, we show that suppressing local steroidogenesis can augment anti-tumour immunity against TNBC. Through targeted metabolomics of steroids coupled with immunohistochemistry, we profiled the existence of immunosuppressive steroids in TNBC patient tumours and discerned the steroidogenic activity in immune-infiltrating regions. In mouse, genetic inhibition of immune cell steroidogenesis restricted TNBC tumour progression with a significant reduction in immunosuppressive components such as tumour associated macrophages. Steroidogenesis inhibition appears to bolster anti-tumour immune responses in dendritic and T cells by impeding glucocorticoid signalling. Undertaking metabolic modelling of the single-cell transcriptomics and targeted tumour-steroidomics, we pinpointed the predominant steroidogenic cells. Inhibiting steroidogenesis pharmacologically using a identified drug, posaconazole, curtailed tumour expansion in a humanised TNBC mouse model. This investigation paves the way for targeting steroidogenesis and its signalling pathways in breast cancer affected by immune-steroid maladaptation.
... package 77 . The cell type distribution plots across different treatments utilized the dittoBarPlot function from the dittoSeq v1.13.1 package 78 . The FindMarkers function in the Seurat package was employed for differential expression analysis between two treatments, considering genes with |avg_log2FC| > 0.25 and adjusted p-value (p_val_adj) < 0.1 as significantly DEGs. ...
Coral reef ecosystems face escalating threats from anthropogenic global climate challenges, leading to frequent bleaching events. A key issue in coral transplantation is the inability of fragments to rapidly grow to sizes that can resist environmental pressures. The observation of accelerated growth during the early stages of coral regeneration provides new insights for addressing this challenge. To investigate the underlying molecular mechanisms, we study the fast-growing stony coral Acropora muricata. Using single-cell RNA sequencing, bulk RNA sequencing, and high-resolution micro-computed tomography, we identify a critical regeneration phase around 2–4 weeks post-injury. Single-cell transcriptome analysis reveals 11 function-specific cell clusters. Pseudotime analysis indicates epidermal cell differentiation into calicoblasts. Bulk RNA-seq results highlight a temporal limitation in coral’s rapid regeneration. Through integrated multi-omics analysis, this study emphasizes the importance of a comprehensive understanding of coral regeneration, providing insights beyond fundamental knowledge and offering potential protective strategies to promote coral growth.
... The 'DittoSeq' package was used to compute and visualise cell type proportions per sample, across treatment cycles and across response groups. 80 DESeq2 was used to perform a pseudobulk differential expression analysis between 'pre', 'mid' and 'post' samples. 81 Differentially expressed genes were identified using |LogFold change| >1.5 and an adjusted p value of <0.05. ...
We present the clinical results of a phase 2 trial combining neoadjuvant docetaxel, cisplatin, 5 Flourouracil, and the PD-L1 inhibitor avelumab in locally advanced gastro-esophageal adenocarcinoma (GEA). Fifty-one patients receive neoadjuvant therapy with 50 proceeding to surgery. Grade 3–4 adverse events occur in 40%; complete/major pathological response is found in 7/50 (14%) and 9/50 (18%), with 2-year disease-free survival of 67.5%. There is no correlation between tumor regression and PD-L1 or mismatch repair (MMR) status. Multiplex immunohistochemistry and longitudinal single-cell transcriptomic profiling reveal alterations in certain innate immune cell populations, particularly noting an M2-tumor-associated macrophage (M2-TAM) proliferation in non-responding tumors. These findings describe the effective nature of this treatment regimen for GEA and reveal associated features of the inflammatory milieux associated with response to chemo-immunotherapy. The specific character of the inflammatory environment in non-responders may, in the future, help personalize treatment. This study was registered at ClinicalTrials.gov (NCT03288350).
... RNA-seq data analysis typically involves several key steps [10]. Popular steps are: I) Trimming: Removal of low-quality bases and sequencing adapters from reads; II) Filtering: Exclusion of reads with low quality or insufficient length; III) Alignment: Mapping of RNA-seq reads to a reference genome or transcriptome [20,31,36]; IV) Count: Quantification of gene expression by counting reads mapped to each gene or region of interest [1, 23]; VI) Normalization: Adjustment of count data to correct for technical factors and ensure comparability between different samples, standard normalization methods include FPKM, TPM, RPKM, and others; VI) Differential expression analysis: Identification of genes with a significantly different expression between different conditions or groups of samples [24,34]; VII)Visualization: Presentation of results in graphical and tabular formats to facilitate comprehension [5,18,27]. ...
Motivation: Bulk RNA-Seq is a widely used method for studying gene expression across a variety of contexts. The significance of RNA-Seq studies has grown with the advent of high-throughput sequencing technologies. Computational methods have been developed for each stage of the identification of differentially expressed genes. Nevertheless, there are few studies exploring the association between different types of methods. In this study, we evaluated the impact of the association of methodologies in the results of differential expression analysis. By adopting two data sets with qPCR data (to gold-standard reference), seven methods were implemented and assessed in R packages (EBSeq, edgeR, DESeq2, limma, SAMseq, NOISeq, and Knowseq), which was performed and assessed separately and in association. The results were evaluated considering the adopted qPCR data. Results: Here, we introduce consexpressionR, an R package that automates differential expression analysis using consensus of at least seven methodologies, producing more assertive results with a significant reduction in false positives. Availability: consexpressionR is an R package available via source code and support are available at GitHub (https://github.com/costasilvati/consexpressionR).
... The first 50 PCs were then used to perform Mutual nearest neighbors (MNNs) sample/batch correction and integration using the batchelor [52] package. For gene expression visualization, the cell UMAP plots and heatmap plots were generated using dittoSeq [53] package. The gene expression kernel density plots were generated using Nebulosa [54] package. ...
Background
Low back pain impacts over 600 million people worldwide, predominantly due to intervertebral disc degeneration. This study focuses on the role of Piezo1, a crucial mechanosensitive ion channel protein, in the pathology and potential treatment of disc degeneration.
Materials and methods
To investigate the effects of disc-specific Piezo1 deletion, we generated AggrecanCreERT2; Piezo1fl/fl mice and examined both lumbar spine instability (LSI)- and aging-induced disc degeneration. Additionally, the effect of pharmacological inhibition of Piezo1 was evaluated using GsMTx4, a potent Piezo1 antagonist, in an ex vivo model stimulated with IL-1β to induce disc degeneration. Assessments included histological examinations, immunofluorescence, and western blot analyses to thoroughly characterize the alterations in the intervertebral discs.
Results
Elevated expression of Piezo1 was detected in the nucleus pulposus (NP) of intervertebral discs with advanced disc degeneration in both aged mice and human patients. Inducible deletion of Piezo1 expression in aggrecan-expressing disc cells significantly reduced lumbar disc degeneration, decreased extracellular matrix (ECM) degradation, and lowered apoptosis in NP cells, observed in both aged mice and those undergoing LSI surgery. Excessive compression loading (CL) upregulated Piezo1 expression, induced ECM disruption, and increased apoptosis in NP cells, whereas inhibition of Piezo1 with GsMTx4 effectively mitigated these pathological changes. Furthermore, in ex vivo cultured mouse discs, GsMTx4 treatment significantly alleviated IL-1β-induced degenerative damages, restored ECM anabolism, and reduced apoptosis.
Conclusions
The findings suggest that Piezo1 plays a critical role in the development of disc degeneration and highlight its potential as a therapeutic target. Inhibiting Piezo1 could offer a novel strategy for treating or preventing this critical disease.
Translational potential of this article
This research highlights the involvement of Piezo1 in the development of intervertebral disc degeneration and emphasizes the potential for targeting Piezo1 as a therapeutic strategy to delay or reverse this condition.
... For visualization of cluster numbers distribution barplots downstream analysis we used the dittoseq package (v.1.10.0). 66 Myeloid cell sub-clustering For myeloid cell specific clustering, we isolated myeloid cell cluster from the general object (of Figures 1 and 2), containing all the broad clusters. To correct batch effects between samples, we used the harmony 69 integration method applied on the RNA assay of the selected samples. ...
Chemotherapy combined with immune checkpoint blockade has shown clinical activity in breast cancer. Response, however, occurs in only a low proportion of patients. How the immune landscape of the tumor determines the immune and clinical responses to chemoimmunotherapy is not well understood. Here, using a combination of single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq), we profile 40 biopsies from 27 patients with metastatic triple-negative breast cancer (TNBC), receiving chemotherapy and anti-PD-L1 alone or in combination with anti-CD73, in a phase 2 randomized clinical trial. Our results show an enrichment of late-dysfunctional, clonally expanded CD8⁺ T cells in responder (R) patients. On treatment, R display an influx of newly emerging clonotypes, as well as expansion of the CD8⁺ precursors. Collectively, our data suggest that baseline clonal expansion could be a potential predictor of response and that both clonal reinvigoration of pre-existing tumor-reactive T cells and clonal replacement on-treatment are important for a protective response to chemoimmunotherapy.
... Clusters were re-annotated using known cell type marker genes and cell types were assigned to each cluster using scanpy 31 with specific markers from previous publications 15, 16 . The detailed markers for each cell type are listed in Table 4. Cell proportion plots were generated using dittoseq 35 . www.nature.com/scientificdata ...
The trabecular meshwork within the outflow apparatus is critical in maintaining intraocular pressure homeostasis. In vitro studies employing primary cell cultures of the human trabecular meshwork (hTM) have conventionally served as surrogates for investigating the pathobiology of TM dysfunction. Despite its abundant use, translation of outcomes from in vitro studies to ex vivo and/or in vivo studies remains a challenge. Given the cell heterogeneity, performing single-cell RNA sequencing comparing primary hTM cell cultures to hTM tissue may provide important insights on cellular identity and translatability, as such an approach has not been reported before. In this study, we assembled a total of 14 primary hTM in vitro samples across passages 1–4, including 4 samples from individuals diagnosed with glaucoma. This dataset offers a comprehensive transcriptomic resource of primary hTM in vitro scRNA-seq data to study global changes in gene expression in comparison to cells in tissue in situ. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource.
... All other FMRP-target genes expressed across both ythdf2 knockdown and YTHDF2 mRNA conditions in at least 0.01% of cells were selected for subsequent analysis (n = 675). scCustomize (Marsh n.d.) and dittoSeq (Bunis et al. 2021) were used for figure creation. Nebulosa (Alquicira-Hernandez and Powell 2021) was used to visualize individual and joint expression from multiple FMRP-DEGs using a kernel gene-weighted density estimation. ...
Among autistic individuals, a subphenotype of disproportionate megalencephaly (ASD‐DM) seen at three years of age is associated with co‐occurring intellectual disability and poorer prognoses later in life. However, many of the genes contributing to ASD‐DM have yet to be delineated. In this study, we identified additional ASD‐DM candidate genes with the aim to better define the genetic etiology of this subphenotype of autism. We expanded the previously studied sample size of ASD‐DM individuals ten fold by including probands from the Autism Phenome Project and Simons Simplex Collection, totaling 766 autistic individuals meeting the criteria for megalencephaly or macrocephaly and revealing 154 candidate ASD‐DM genes harboring de novo protein‐impacting variants. Our findings include 14 high confidence autism genes and seven genes previously associated with DM. Five impacted genes have previously been associated with both autism and DM, including CHD8 and PTEN. By performing functional network analysis, we expanded to additional candidate genes, including one previously implicated in ASD‐DM (PIK3CA) as well as 184 additional genes connected with ASD or DM alone. Using zebrafish, we modeled a de novo tandem duplication impacting YTHDF2, encoding an N6‐methyladenosine (m⁶A)‐mRNA reader, in an ASD‐DM proband. Testing zebrafish CRISPR knockdown led to reduced head/brain size, while overexpressing YTHDF2 resulted in increased head/brain size matching that of the proband. Single‐cell transcriptomes of YTHDF2 gain‐of‐function larvae point to reduced expression of Fragile‐X‐syndrome‐associated FMRP‐target genes globally and in the developing brain, providing insight into the mechanism underlying autistic phenotypes. We additionally discovered a variant impacting a different gene encoding an m⁶A reader, YTHDC1, in our ASD‐DM cohort. Though we highlight only two cases to date, our study provides support for the m⁶A‐RNA modification pathway as potentially contributing to this severe form of autism.
... Cell-cell communication analysis was performed using CellChat (66). Data were visualized using Seurat, dittoSeq, and ShinyCell R packages (see S. Methods 1 for additional information about the quality control and analytical approaches used to evaluate the scRNA-Seq data) (76). S. Figure 6 LTL/Biotin AQP2 V-ATPase Overlay S. Figure 6. ...
Urinary obstruction causes injury to the renal medulla, impairing the ability to concentrate urine and increasing the risk of progressive kidney disease. However, the regenerative capacity of the renal medulla after reversal of obstruction is poorly understood. To investigate this, we developed a mouse model of reversible urinary obstruction. Despite robust regeneration and complete histological recovery of the renal medulla, these mice exhibited a permanent defect in urinary concentrating capacity. However, there were lasting changes in the composition, organization, and transcriptional profiles of epithelial, endothelial, and interstitial cells. Persistent inflammatory responses were also seen in patients with renal stone disease, but there were also adaptive responses to the increasingly hypoxic environment of the renal medulla that occurred only after reversal of obstruction. These findings indicate that while partial repair occurs after reversal of urinary obstruction, there are lasting structural and functional changes across all major cellular compartments of the renal medulla. These changes reflect shared and distinct responses to different renal medullary injuries in humans and mice.
... These cells were renormalized and rescaled, followed by dimensionality reduction, SNN graph generation and clustered as above. UMAP visualization was performed using dittoSeq2 (v.1.14.3), followed by differential expression analysis (non-treated control versus day 4 and non-treated control versus day 7) using FindMarkers() to identity DEGs (adjusted P < 0.05) in response to β-glucan stimulation 78 . ...
Disease tolerance is an evolutionarily conserved host defense strategy that preserves tissue integrity and physiology without affecting pathogen load. Unlike host resistance, the mechanisms underlying disease tolerance remain poorly understood. In the present study, we investigated whether an adjuvant (β-glucan) can reprogram innate immunity to provide protection against influenza A virus (IAV) infection. β-Glucan treatment reduces the morbidity and mortality against IAV infection, independent of host resistance. The enhanced survival is the result of increased recruitment of neutrophils via RoRγt⁺ T cells in the lung tissue. β-Glucan treatment promotes granulopoiesis in a type 1 interferon-dependent manner that leads to the generation of a unique subset of immature neutrophils utilizing a mitochondrial oxidative metabolism and producing interleukin-10. Collectively, our data indicate that β-glucan reprograms hematopoietic stem cells to generate neutrophils with a new ‘regulatory’ function, which is required for promoting disease tolerance and maintaining lung tissue integrity against viral infection.
... Journal of Translational Medicine (2025) 23:19 suitable cell clusterings for subsequent cell type identification. The R dittoSeq [11] package is used to visualize the proportion of cell composition in each sample. ...
Small cell neuroendocrine cervical carcinoma is a highly aggressive tumor characterized by early metastasis, a high recurrence rate, and poor prognosis. This study represents the first instance of single-cell sequencing conducted on small cell neuroendocrine carcinoma of the cervix worldwide. Analysis of gene expression regulatory networks revealed that the transcription factor TFF3 drived up-regulation of ELF3. Furthermore, our findings indicated that the neuroendocrine marker genes and gene regulatory networks associated with small cell neuroendocrine cervical carcinoma differed from those observed in lung, small intestine, and liver neuroendocrine carcinoma within the GEO database, suggesting tissue-specific origins for these malignancies. Overall, this study addresses a significant research in understanding small cell neuroendocrine cervical carcinoma in vivo and provides valuable insights for guiding radiotherapy, chemotherapy, and targeted therapy.
Graphical abstract
... [46]), scRepertoire [47], Biostrings [48], DittoSeq (version 1.12.2; [49]) and EnhancedVolcano (version 1.18.0; [50]). ...
Aims/hypothesis
Immunotherapeutics targeting T cells are crucial for inhibiting autoimmune disease progression proximal to disease onset in type 1 diabetes. There is an outstanding need to augment the durability and effectiveness of T cell targeting therapies by directly restraining proinflammatory T cell subsets, while simultaneously augmenting regulatory T cell (Treg) activity. Here, we present a novel strategy for preventing diabetes incidence in the NOD mouse model using a blocking monoclonal antibody targeting the type 1 diabetes risk-associated T cell co-stimulatory receptor, CD226.
Methods
Female NOD mice were treated with anti-CD226 at 7–8 weeks of age and then monitored for diabetes incidence and therapeutic mechanism of action.
Results
Compared with isotype-treated controls, anti-CD226-treated NOD mice showed reduced insulitis severity (0.84-fold, p=0.0002) at 12 weeks and decreased disease incidence (HR 0.41, p=0.015) at 30 weeks. Flow cytometric analysis performed 5 weeks post treatment demonstrated reduced proliferation of conventional CD4⁺ T cells (0.87-fold, p=0.030) and CD8⁺ (0.78-fold, p=0.0018) effector memory T cells in spleens of anti-CD226-treated mice. Phenotyping of pancreatic Tregs revealed increased CD25 expression (2.05-fold, p=0.0073) and signal transducer and activator of transcription 5 (STAT5) phosphorylation (1.39-fold, p=0.0007) following anti-CD226, with splenic Tregs displaying augmented suppression of CD4⁺ responder T cells (Tresps) (1.49-fold, p=0.0008, 1:2 Treg:Tresp) in vitro. Anti-CD226-treated mice exhibited reduced frequencies of islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP)-reactive CD8⁺ T cells in the pancreas, using both ex vivo tetramer staining (0.50-fold, p=0.0317) and single-cell T cell receptor sequencing (0.61-fold, p=0.022) approaches. ⁵¹Cr-release assays demonstrated reduced cell-mediated lysis of beta cells (0.61-fold, p<0.0001, 1:1 effector:target) by anti-CD226-treated autoreactive cytotoxic T lymphocytes.
Conclusions/interpretation
CD226 blockade reduces T cell cytotoxicity and improves Treg function, representing a targeted and rational approach for restoring immune regulation in type 1 diabetes.
Graphical Abstract
... The PDF file includes: Methods Figs. S1 to S12 Tables S1 and S2 references (78)(79)(80)(81)(82)(83)(84)(85)(86)(87) Other Supplementary Material for this manuscript includes the following: Data file S1 MDar reproducibility checklist ...
Age-related thymic involution, leading to reduced T cell production, is one of the major causes of immunosenescence. This results in an increased susceptibility to cancers, infections, and autoimmunity and in reduced vaccine efficacy. Here, we identified that the receptor activator of nuclear factor κB (RANK)–RANK ligand (RANKL) axis in the thymus is altered during aging. Using a conditional transgenic mouse model, we demonstrated that endothelial cells depend on RANK signaling for their cellularity and functional maturation. Decreased RANKL availability during aging resulted in a decline in cellularity and function of both endothelial cells and thymic epithelial cells, contributing to thymic involution. We then found that, whereas RANKL neutralization in young mice mimicked thymic involution, exogenous RANKL treatment in aged mice restored thymic architecture as well as endothelial cell and epithelial cell abundance and functional properties. Consequently, RANKL improved T cell progenitor homing to the thymus and boosted T cell production. This cascade of events resulted in peripheral T cell renewal and effective antitumor and vaccine responses in aged mice. Furthermore, we conducted a proof-of-concept study that showed that RANKL stimulates endothelial cells and epithelial cells in human thymic organocultures. Overall, our findings suggest that targeting the RANK-RANKL axis through exogenous RANKL administration could represent a therapeutic strategy to rejuvenate thymic function and improve T cell immunity during aging.
... Cell-cluster/type compositions are plotted using the dittoBar-Plot() function from the dittoSeq package (106). The annotation of M1 and M2 macrophages is based on the Tumor Immune Single-cell Hub (59) annotation for the BRCA_GSE114727_inDrop dataset published by Azizi and colleagues (107). ...
Low intratumor heterogeneity correlates with increased patient survival and immunotherapy response. However, even highly homogeneous tumors are variably aggressive, and the immunologic factors impacting aggressiveness remain understudied. In this study, we analyzed the mechanisms underlying immune escape in murine tumors with low intratumor heterogeneity. We used immunophenotyping and single-cell RNA sequencing to compare the temporal growth of in vivo transplanted, genetically similar, rejected and nonrejected single-cell clones. Nonrejected clones showed high infiltration of tumor-associated macrophages, lower T cell infiltration, and increased T cell exhaustion when compared with rejected clones. Comparative analysis of rejection-associated gene expression programs, combined with in vivo CRISPR knockout screens of candidate regulators, identified macrophage migration inhibitory factor (Mif) as a major contributor to preventing immune rejection. Mif knockout resulted in smaller tumors and reduced tumor-associated macrophage infiltration. These results were validated in patients with melanoma. Overall, our homogeneous tumor system can uncover factors regulating growth variability and identifies Mif as critical in aggressive melanoma.
Significance
In this study, we find that Mif expression is associated with tumor growth and aggressiveness, specifically in tumors with low heterogeneity. These findings could facilitate the development of new strategies to treat patients with homogeneous, high MIF–expressing tumors that are unresponsive to immune checkpoint therapy.
... 1.0.12) R packages were used to visualize gene sets that characterize specific molecular and biological pathways (54). ...
Introduction
Single-cell RNA sequencing (scRNA-seq) has become an essential tool for uncovering the complexities of various physiological and immunopathological conditions in veterinary medicine. However, there is currently limited information on immune-suppressive cancer subsets in canine breast cancers. In this study, we aimed to identify and characterize immune-suppressive subsets of triple-negative canine breast cancer (TNBC) by utilizing integrated scRNA-seq data from published datasets.
Methods
Published scRNA-seq datasets, including data from six groups of 30 dogs, were subjected to integrated bioinformatic analysis.
Results
Immune modulatory TNBC subsets were identified through functional enrichment analysis using immune-suppressive gene sets, including those associated with anti-inflammatory and M2-like macrophages. Key immune-suppressive signaling, such as viral infection, angiogenesis, and leukocyte chemotaxis, was found to play a role in enabling TNBC to evade immune surveillance. In addition, interactome analysis revealed significant interactions between distinct subsets of cancer cells and effector T cells, suggesting potential T-cell suppression.
Discussion
The present study demonstrates a versatile and scalable approach to integrating and analyzing scRNA-seq data, which successfully identified immune-modulatory subsets of canine TNBC. It also revealed potential mechanisms through which TNBC promotes immune evasion in dogs. These findings are crucial for advancing the understanding of the immune pathogenesis of canine TNBC and may aid in the development of new immune-based therapeutic strategies.
... Heatmaps, volcano plots, violin plots, and GO analyses were generated using the clusterProfiler R package and OriginLab 2024. Violin plots were created using the dittoSeq (1.8.1) package in R (4.2.1) 139 . ...
2-Arachidonoylglycerol (2-AG) is the most prevalent endocannabinoid involved in maintaining brain homeostasis. Previous studies have demonstrated that inactivating monoacylglycerol lipase (MAGL), the primary enzyme responsible for degrading 2-AG in the brain, alleviates neuropathology and prevents synaptic and cognitive decline in animal models of neurodegenerative diseases. However, we show that selectively inhibiting 2-AG metabolism in neurons impairs cognitive function in mice. This cognitive impairment appears to result from decreased expression of synaptic proteins and synapse numbers, impaired long-term synaptic plasticity and cortical circuit functional connectivity, and diminished neurogenesis. Interestingly, the synaptic and cognitive deficits induced by neuronal MAGL inactivation can be counterbalanced by inhibiting astrocytic 2-AG metabolism. Transcriptomic analyses reveal that inhibiting neuronal 2-AG degradation leads to widespread changes in expression of genes associated with synaptic function. These findings suggest that crosstalk in 2-AG signaling between astrocytes and neurons is crucial for maintaining synaptic and cognitive functions and that excessive 2-AG in neurons alone is detrimental to cognitive function.
... The Monocle 3 software tool was employed to mimic the developmental trajectory of SSCs [38], and the genes differentially expressed at different stages were analyzed. The plot1cell [39] and dittoseq R packages [40] were used to optimize the images, and the flowcharts were created using the plotting tools from home for researcher. ...
Background
Spermatogonial stem cells (SSCs) are essential for male fertility, maintaining sperm production throughout life. While mouse SSCs have been studied extensively, the mechanisms regulating human SSCs are less understood.
Objectives
To investigate the role of EEF1B2 in regulating human SSC proliferation and apoptosis.
Material and methods
Single cell RNA sequencing (scRNA-seq) analysis was utilized to investigate the differentially expressed genes of SSC. The distribution of EEF1B2 in the human testis was examined using immunofluorescence and immunohistochemistry techniques. Cell proliferation, DNA replication, and self-renewal were analyzed using CCK8, EdU, Western blot, and flow cytometry. RNA sequencing was employed to analyze the downstream target molecules and signaling pathways of EEF1B2.
Results
In this study, we analyzed single-cell sequencing data from human testicular samples and identified EEF1B2 as a protein highly expressed in SSCs, with expression decreasing during development. Immunohistochemistry and immunofluorescence confirmed this pattern and showed co-localization with the proliferation marker KI67. Knockdown of EEF1B2 in human SSC lines impaired proliferation and viability, reducing self-renewal proteins like PLZF and CCNE1. RNA sequencing revealed decreased TAF4B following EEF1B2 knockdown, which could be rescued by replenishing TAF4B. Testicular SSCs from non-obstructive azoospermia (NOA) patients also showed reduced EEF1B2.
Discussion and conclusion
Our findings reveal a novel regulatory mechanism involving EEF1B2 and TAF4B in human SSCs, suggesting EEF1B2 deficiency may contribute to male infertility.
... Enrichment of Reactome IFN signaling pathway was found using UCell (v 3.15) [41]. To determine the cell type proportions by sample, we used dittoBarPlot() from DittoSeq [68]. The dataset was then subset to only include samples previously identified as T cells [34]. ...
Adenosine to inosine (A-to-I) RNA editing by ADAR1 has been implicated in maintaining self-tolerance, preventing autoimmunity, and mediating antiviral immunity. Foreign viral double-stranded RNA triggers rapid interferon response and activates ADAR1 in the host immune system. Emerging data points to a role of ADAR1 A-to-I editing in the inflammatory response associated with severe COVID-19 disease. We identify A-to-I editing events within human whole transcriptome data from SARS-CoV-2 infected individuals, non-infected individuals, and individuals with other viral illnesses from nasopharyngeal swabs. High levels of RNA editing in host cells are associated with low SARS-CoV-2 viral load (p = 9.27 E-06), suggesting an inhibitory effect of ADAR1 on viral infection. Additionally, we find differentially expressed genes associated with RNA-modifications and interferon response. Single cell RNA-sequencing analysis of SARS-CoV-2 infected nasopharyngeal swabs reveals that cytotoxic CD8 T cells upregulate ADAR1 in COVID-19 positive samples (p = 0.0269). We further reveal ADAR1 expression increases with CD4 and CD8 T cell activation, and knockdown of ADAR1 leads to apoptosis and aberrant IL-2 secretion. Together, our data suggests A-to-I RNA editing is required to maintain healthy homeostasis of activated T cells to combat SARS-CoV-2 infection.
Teplizumab is approved for delaying the diagnosis of type 1 diabetes by modulating progression of disease. Compared to EBV-seronegative patients, those who are EBV-seropositive prior to treatment have a more robust response to teplizumab in two clinical trials. Here we compare the phenotypes, transcriptomes and development of peripheral blood cells before and after teplizumab treatment in participants. Higher number of regulatory T cells and partially exhausted CD8+ T cells are found in EBV-seropositive individuals than in EBV-seronegative controls at the baseline in the TN10 and AbATE trials. Mechanistically, single cell transcriptomics and functional assays identify the downregulation of NFκB and T cell activation pathways after treatment in EBV-seropositive patients; among diabetes antigen-specific CD8+ T cells, T cell receptor and mTOR signaling are also reduced. In parallel, signaling impairment is greater in adaptive than innate immune cells following teplizumab treatment in EBV-seropositive individuals. Our data thus indicate that EBV can impair signaling pathways in immune cells to modulate their responses in the context of type 1 diabetes.
Macrophages are key regulators of adipose tissue plasticity. Obesity impairs brown adipose tissue (BAT) function in humans, yet macrophage-mediated mechanisms remain elusive. Here, we introduce MACanalyzeR, a single-cell RNA sequencing (scRNAseq) tool designed for comprehensive monocyte/macrophage metabolic profiling. Applying MACanalyzeR to BAT from obese male murine models (db/db and HFD-fed mice), we identify lipid-associated macrophages (LAMs) with foamy characteristics. Unlike db/db BAT LAMs, those in HFD BAT correlate with thermogenic gene expression and PPAR signaling activation. A distinct PpargHIGH LAM subcluster progressively accumulates in thermogenically active BAT. Macrophage-specific Pparg depletion disrupts BAT thermogenesis, inducing a white-like phenotype and metabolic dysfunctions. Mechanistically, PpargHIGH LAMs secrete GDF15, a key regulator of BAT identity and lipid metabolism under high-energy demand. Our study establishes MACanalyzeR as a powerful tool for immunometabolic interrogation and identifies PpargHIGH LAMs as critical mediators of BAT homeostasis.
Teplizumab is approved for delaying the diagnosis of type 1 diabetes by modulating progression of disease. Compared to EBV-seronegative patients, those who are EBV-seropositive prior to treatment have a more robust response to teplizumab in two clinical trials. Here we compare the phenotypes, transcriptomes and development of peripheral blood cells before and after teplizumab treatment in participants. Higher number of regulatory T cells and partially exhausted CD8⁺ T cells are found in EBV-seropositive individuals than in EBV-seronegative controls at the baseline in the TN10 and AbATE trials. Mechanistically, single cell transcriptomics and functional assays identify the downregulation of NFκB and T cell activation pathways after treatment in EBV-seropositive patients; among diabetes antigen-specific CD8⁺ T cells, T cell receptor and mTOR signaling are also reduced. In parallel, signaling impairment is greater in adaptive than innate immune cells following teplizumab treatment in EBV-seropositive individuals. Our data thus indicate that EBV can impair signaling pathways in immune cells to modulate their responses in the context of type 1 diabetes.
Acute myeloid leukemia (AML) resides in an immune-rich microenvironment, yet, immune-based therapies have faltered in eliciting durable responses. Bridging this paradox requires a comprehensive understanding of leukemic interactions within the bone marrow microenvironment. We optimized a high-throughput tissue-microarray-based pipeline for high-plex spatial immunofluorescence and mass cytometry imaging on a single slide, capturing immune, tumor, and structural components. Using unbiased clustering on the spatial K function, we unveiled the presence of tertiary lymphoid-like aggregates in bone marrow, which we validated using spatial transcriptomics and an independent proteomics approach. We then found validated TLS signatures predictive of outcomes in AML using an integrated public 480-patient transcriptomic dataset. By harnessing high-plex spatial proteomics, we open the possibility of discovering novel structures and interactions that underpin leukemic immune response. Further, our study's methodologies and resources can be adapted for other bone marrow diseases where decalcification and autofluorescence present challenges.
Human skin is not a uniform organ but a mosaic of anatomically distinct niches, with each site finely tuned to unique environmental demands and immune pressures. Yet, the molecular determinants that define these regional identities and their relationship to site-specific vulnerability to inflammatory disease remain poorly understood. Here, we generate a high-resolution single-cell atlas of human skin, profiling 274,834 cells from 96 healthy samples across 7 anatomically distinct sites (acral, arm, axilla, back, face, leg and scalp). Our analysis reveals striking region-specific transcriptional and cellular networks, uncovering how local immune-stromal crosstalk governs tissue homeostasis and underpins anatomical susceptibility to distinct inflammatory diseases such as such as systemic lupus erythematosus (SLE), atopic dermatitis (AD), and psoriasis. These findings illuminate the tissue-intrinsic foundations of regional immune identity and provide a blueprint/resource for the development of precision therapies tailored to the distinct immunological microenvironments of specific anatomical skin sites.
Clonal fitness and plasticity drive cancer heterogeneity. We used expressed lentiviral-based cellular barcodes combined with single-cell RNA sequencing to associate single-cell profiles with in vivo clonal growth. This generated a significant resource of growth measurements from over 20,000 single-cell-derived clones in 110 xenografts from 26 patient-derived breast cancer xenograft models. 167,375 single-cell RNA profiles were obtained from 5 models and revealed that rare propagating clones display a highly conserved model-specific differentiation program with reproducible regeneration of the entire transcriptomic landscape of the original xenograft. In 2 models of basal breast cancer, propagating clones demonstrated remarkable transcriptional plasticity at single-cell resolution. Dichotomous cell populations with different clonal growth properties, signaling pathways, and metabolic programs were characterized. By directly linking clonal growth with single-cell transcriptomes, these findings provide a profound understanding of clonal fitness and plasticity with implications for cancer biology and therapy.
Crohn’s disease (CD) is a persistent inflammatory disorder primarily affecting the terminal ileum. The TnfΔΑRE mice, which spontaneously develop CD-like ileitis due to TNF overexpression, represent a faithful model of the human disease. Here, via single-cell RNA sequencing in TnfΔΑRE mice, we show that murine TNF-dependent ileitis is characterized by cell expansion in tertiary lymphoid organs (TLO), T cell effector reprogramming, and accumulation of activated macrophages in the submucosal granulomas. Within the stromal cell compartment, fibroblast subsets (telocytes, trophocytes, PdgfraloCd81⁻ cells) are less abundant while lymphatic endothelial cells (LEC) and fibroblastic reticular cells (FRC) show relative expansion compared to the wild type. All three fibroblast subsets show strong pro-inflammatory signature. TNFR1 loss or gain of function experiments in specific fibroblast subsets suggest that the TnfΔΑRE-induced ileitis is initiated in the lamina propria via TNF pathway activation in villus-associated fibroblasts (telocytes and PdgfraloCd81⁻ cells), which are responsible for the organization of TLOs. Trophocytes drive disease progression in the submucosal layer, accompanied by the excessive formation of granulomas. These findings provide evidence for spatial regulation of inflammation by fibroblast subsets and underscore the pivotal role of fibroblasts in the inception and advancement of ileitis.
Recurrent gain-of-function mutations in the histone reader protein ENL have been identified in Wilms tumor, the most prevalent pediatric kidney cancer. However, their pathological significance in kidney development and tumorigenesis in vivo remains elusive. Here, we generate mouse models mimicking ENL tumor (ENLT) mutations and show that heterozygous mutant expression in Six2⁺ nephrogenic or Foxd1⁺ stromal lineages leads to severe, lineage-specific kidney defects, both resulting in neonatal lethality. Six2-ENLT mutant kidneys display compromised cap mesenchyme, scant nephron tubules, and cystic glomeruli, indicative of premature progenitor commitment and blocked differentiation. Bulk and spatial transcriptomic analyses reveal aberrant activation of Hox and Wnt signaling genes in mutant nephrogenic cells. In contrast, Foxd1-ENLT mutant kidneys exhibit expansion in renal capsule and cap mesenchyme, with dysregulated stromal gene expression affecting stroma-epithelium crosstalk. Our findings uncover distinct pathways through which ENL mutations disrupt nephrogenesis, providing a foundation for further investigations into their role in tumorigenesis.
The sentinel lymph node (SLN) is the first lymph node encountered by a metastatic cancer cell and serves as a predictor of poor prognosis, as patients with clinically occult SLN metastases are classified as stage III with elevated rates of recurrence and diminished overall survival. However, the dynamics of immune infiltrates in SLNs remain poorly characterized. Here, using an unbiased Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) technique, we profiled 97,777 cells from SLN tissues obtained from patients with stages I/II and III cutaneous melanoma. We describe the transcriptional programs of a multitude of T, B, and myeloid cell subtypes in SLNs. Based on the proportions of cell types, we determined that SLN subtypes are stratified along a naive → activated axis; patients with a 'high activated' signature score appear to be undergoing a robust melanoma antigen-driven adaptive immune response and thus, could be responsive to immunotherapy. Additionally, we identified transcriptomic signatures of SLN-infiltrating dendritic cell subsets that compromise anti-tumor immune responses. Our analyses provide valuable insights into tumor-driven immune changes in the SLN tissue, offering a powerful tool for the informed design of immune therapies for high-risk melanoma patients.
Tuberous Sclerosis Complex (TSC) is a genetic neurodevelopmental disorder associated with early onset epilepsy, intellectual disability and neuropsychiatric disorders. A hallmark of the disorder is cortical tubers, which are focal malformations of brain development that contain dysplastic cells with hyperactive mTORC1 signaling. One barrier to developing therapeutic approaches and understanding the origins of tuber cells is the lack of a model system that recapitulates this pathology. To address this, we established a genetically mosaic cortical organoid system that models a somatic second-hit mutation, which is thought to drive the formation of tubers in TSC. With this model, we find that loss of TSC2 cell-autonomously promotes the differentiation of astrocytes, which exhibit features of a disease-associated reactive state. TSC-/- astrocytes have pronounced changes in morphology and upregulation of proteins that are risk factors for neurodegenerative diseases, such as clusterin and APOE. Using multiplexed immunofluorescence in primary tubers from TSC patients, we show that tuber cells with hyperactive mTORC1 activity also express reactive astrocyte proteins, and we identify a unique population of cells with expression profiles that match the those observed in organoids. Together, this work reveals that reactive astrogliosis is a primary feature of TSC that arises early in cortical development. Dysfunctional glia are therefore poised to be drivers of pathophysiology, nominating a potential therapeutic target for treating TSC and related mTORopathies.
Recognition of macrophages infected with Mycobacterium tuberculosis (Mtb) is essential for CD4+ T cells to prevent tuberculosis (TB). Yet not all antigen-specific T cells recognize infected macrophages in human and murine models. Using monocyte-derived macrophages (MDMs) and autologous memory CD4+ T cells from individuals with latent Mtb infection (LTBI), we quantify T cell activation in response to infected macrophages. T cell antigen receptor (TCR) sequencing revealed >70% of unique and >90% of total Mtb-specific TCR clonotypes in stable LTBI are linked to recognition of infected macrophages, while a subset required exogenous antigen exposure, suggesting incomplete recognition. Clonotypes specific for multiple Mtb antigens and other pathogens were identified, indicating Mtb-specific and non-specific activation. Single-cell transcriptomics demonstrates Mtb-specific T cells express signature effector functions dominated by IFNg, TNF, IL-2, and GM-CSF or chemokine production and signaling. We propose TB vaccines that elicit T cells capable of recognizing infected macrophages and expressing these canonical effector functions will offer protection against TB.
Single-cell (sc) RNA, ATAC, and Multiome sequencing became powerful tools for uncovering biological and disease mechanisms. Unfortunately, manual analysis of sc data presents multiple challenges due to large data volumes and complexity of configuration parameters. This complexity, as well as not being able to reproduce a computational environment, affects the reproducibility of analysis results. The Scientific Data Analysis Platform (https://SciDAP.com) allows biologists without computational expertise to analyze sequencing-based data using portable and reproducible pipelines written in Common Workflow Language (CWL). Our suite of computational pipelines addresses the most common needs in scRNA-Seq, scATAC-Seq and scMultiome data analysis. When executed on SciDAP, it offers a user-friendly alternative to manual data processing, eliminating the need for coding expertise. In this protocol, we describe the use of SciDAP to analyze scMultiome data. Similar approaches can be used for analysis of scRNA-Seq, scATAC-Seq and scVDJ-Seq datasets.
Oncolytic viruses (OVs) emerge as a promising cancer immunotherapy. However, the temporal impact on tumor cells and the tumor microenvironment, and the nature of anti-tumor immunity post-therapy remain largely unclear. Here we report that CD4⁺ T cells are required for durable tumor control in syngeneic murine models of glioblastoma multiforme after treatment with an oncolytic herpes simplex virus (oHSV) engineered to express IL-12. The upregulated MHCII on residual tumor cells facilitates programmed polyfunctional CD4⁺ T cells for tumor control and for recall responses. Mechanistically, the proper ratio of Bcl-6 to T-bet in CD4⁺ T cells navigates their enhanced anti-tumor capacity, and a reciprocal IL6ra-Bcl-6 regulatory axis in a memory CD4⁺ T-cell subset, which requires MHCII signals from reprogrammed tumor cells, tumor-infiltrating and resident myeloid cells, is necessary for the prolonged response. These findings uncover an OV-induced tumor/myeloid-CD4⁺ T-cell partnership, leading to long-term anti-tumor immune memory, and improved OV therapeutic efficacy.
The spatial organization of cells within a tissue is dictated throughout dynamic developmental processes. We sought to understand whether cells geometrically coordinate with one another throughout development to achieve their organization. The pancreas is a complex cellular organ with a particular spatial organization. Signals from the mesenchyme, neurons, and endothelial cells instruct epithelial cell differentiation during pancreatic development. To understand the cellular diversity and spatial organization of the developing pancreatic niche, we mapped the spatial relationships between single cells over time. We found that four transcriptionally unique subtypes of mesenchyme in the developing pancreas spatially coordinate throughout development, with each subtype at fixed locations in space and time in relation to other cells, including beta cells, vasculature, and epithelial cells. Our work provides insight into the mechanisms of pancreatic development by showing that cells are organized in a space and time manner.
This study integrated and analyzed human single-cell RNA sequencing data from four publicly available datasets to enhance cellular resolution, unveiling a complex landscape of tuft cell heterogeneity within the human colon. Four tuft subtypes (TC1-TC4) emerged as defined by unique gene expression profiles, indicating potentially novel biological function. Tuft cell 1 (TC1) was characterized by an antimicrobial peptide signature; TC2 had an increased transcription machinery gene expression profile consistent with a progenitor-like cell; TC3 expressed genes related to ganglion (neuronal) development; and TC4 expressed genes related to tight junctions. Our analysis of subtype-specific gene expression and pathway enrichment showed variances in tuft cell subtypes between healthy individuals and those with inflammatory bowel disease (IBD). The frequency of TC1 and TC2 differed between healthy controls and IBD. Relative to healthy controls, TC1 and TC2 in IBD-tissue showed an upregulation of gene expression, favouring increased metabolism and immune function. These findings provide foundational knowledge about the complexity of the human colon tuft cell population and hint at their potential contributions to gut health. They provide a basis for future studies to explore the specific roles these cells may play in gut function during homeostasis and disease. We demonstrate the value of in silico approaches for hypothesis generation in relation to the putative functions of low-frequency gut cells for subsequent physiological analyses.
Purpose
Preclinical data motivate clinical evaluation of inhibitors of MAPK-interacting kinases 1 and 2 (MNK1/2). We conducted a phase 1b clinical trial to study target engagement and safety of tomivosertib, a MNK1/2 inhibitor, alone and in combination with paclitaxel.
Patients and Methods
Eligible patients had metastatic breast cancer resistant to standard-of-care treatments. Biopsies were obtained at baseline and during treatment with tomivosertib, and then tomivosertib was continued with the addition of paclitaxel until disease progression or toxicity. Serum drug levels were measured, and pharmacodynamic endpoints included IHC, proteomics, translatomics, and imaging mass cytometry.
Results
Tomivosertib alone and in combination with paclitaxel was well tolerated. There was no pharmacokinetic interaction between the drugs. We observed a clear reduction in phosphorylation of eIF4E at S209, a major substrate of MNK1/2, and identified tomivosertib-induced perturbations in the proteome, translatome, and cellular populations of biopsied metastatic breast cancer tissue.
Conclusions
We conclude that tomivosertib effectively inhibits MNK1/2 activity in metastatic breast cancer tissue and that it can safely be combined with paclitaxel in future phase II studies. We demonstrate feasibility of using proteomic profiles, translatomic profiles, and spatial distribution of immune cell infiltrates for clinical pharmacodynamic studies.
The human brain undergoes protracted postnatal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell-type-specific gene expression dynamics. Here, using single-nucleus RNA sequencing on temporal lobe tissue, including samples of African ancestry, we build a joint pediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between pediatric and adult cell subtypes, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in pediatric tissue. The resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.
Autophagy-lysosomal degradation is a conserved homeostatic process considered to be crucial for cardiac morphogenesis. However, both its cell specificity and functional role during heart development remain unclear. Here, we introduced zebrafish models to visualize autophagic vesicles in vivo and track their temporal and cellular localization in the larval heart. We observed a significant accumulation of autolysosomal and lysosomal vesicles in the atrioventricular and bulboventricular regions and their respective valves. We addressed the role of lysosomal degradation based on the Spinster homolog 1 (spns1) mutant (not really started, nrs). nrs larvae displayed morphological and functional cardiac defects, including abnormal endocardial organization, impaired valve formation and retrograde blood flow. Single-nuclear transcriptome analyses revealed endocardial-specific differences in lysosome-related genes and alterations of notch1-signalling. Endocardial-specific overexpression of spns1 and notch1 rescued features of valve formation and function. Altogether, our results reveal a cell-autonomous role of lysosomal processing during cardiac valve formation affecting notch1-signalling.
Breast cancer is the most commonly diagnosed cancer in women, with distant metastasis being the main cause of breast cancer–related deaths. Elucidating the changes in the tumor and immune ecosystems that are associated with metastatic disease is essential to improve understanding and ultimately treatment of metastasis. Here, we developed an in-depth, spatially resolved single-cell atlas of the phenotypic diversity of tumor and immune cells in primary human breast tumors and matched distant metastases, using imaging mass cytometry to analyze a total of 75 unique antibody targets. Although the same tumor cell phenotypes were typically present in primary tumors and metastatic sites, suggesting a strong founder effect of the primary tumor, their proportions varied between matched samples. Notably, the metastatic site did not influence tumor phenotype composition, except for the brain. Metastatic sites exhibited a lower number of immune cells overall but had a higher proportion of myeloid cells as well as exhausted and cytotoxic T cells. Myeloid cells showed distinct tissue-specific compositional signatures and increased presence of potentially matrix remodeling phenotypes in metastatic sites. This analysis of tumor and immune cell phenotypic composition of metastatic breast cancer highlights the heterogeneity of the disease within patients and across distant metastatic sites, indicating myeloid cells as the predominant immune modulators that could potentially be targeted at these sites.
Significance: Multiplex imaging analysis of matched primary and metastatic breast tumors provides a phenotypic and spatial map of tumor microenvironments, revealing similar compositions of cancer cells and divergent immunologic features between matched samples.
The unfolded protein response maintains endoplasmic reticulum homeostasis by sensing protein-folding stress and orchestrating cellular adaptation via the endoplasmic reticulum transmembrane proteins IRE1, PERK, and ATF6. Malignant cells can co-opt IRE1 and PERK to sustain growth; however, the importance of ATF6 in cancer remains poorly deciphered. We observed elevated ATF6 transcriptional activity in several cancers, including colorectal carcinoma. Genetic silencing or small-molecule inhibition of ATF6 blocked cell-cycle progression and reduced viability of several human colorectal cancer cell lines in vitro, and disrupted tumor progression in vivo. Unexpectedly, ATF6 interference disabled Wnt and Myc signaling and reduced stemness. ATF6 inhibition attenuated growth of organoids derived from malignant but not normal human intestinal tissue, decreasing Wnt pathway activity and driving cellular differentiation. Wnt-surrogate agonism in a Wnt ligand-dependent colorectal cancer organoid restored pathway activity and rescued growth under ATF6 blockade. Our findings uncover ATF6 as an unexpected facilitator of oncogenic Wnt signaling in colorectal cancer.
Significance
ATF6 intervention reduces colorectal cancer cell and organoid viability by interrupting dysregulated Wnt signaling, identifying a novel facilitator and potential therapeutic target in colorectal cancer.
Immune cells in the pancreas are known to participate in organ development. However, the resident pancreatic immune system has yet to be fully defined. Immune cells also play a role in pathology and are implicated in diseases such as diabetes induced by intrauterine growth restriction (IUGR). We hypothesized that the resident immune system is established during neonatal development and disrupted by IUGR. Using single cell RNAseq and flow cytometry we identified many immune cell populations in the near-term fetus (at embryologic day 22) and neonatal (postnatal day 1, 7, &14) islets, non-endocrine pancreas, and the spleen in the rat. Using flow cytometry, we observed the resident immune system is established during neonatal development in the pancreas and spleen. We identified 9 distinct immune populations in the pancreatic islets and 8 distinct immune populations in the spleen by single cell RNAseq. There were no sex-specific differences in the relative proportion of immune cells in the pancreas or spleen. Finally, we tested if IUGR disrupted the neonatal immune system using bilateral uterine artery ligation. We found significant changes to the percentage of CD11B+ HIS48- and CD8+ T cells in the islets and non-endocrine pancreas and in the spleen. IUGR-induced alterations were influenced by the tissue environment and the sex of the offspring. Future research to define the role of these immune cells in pancreatic development may identify disrupted pathways that contribute to the development of diabetes following IUGR.
Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.
It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data.
Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).
Contact: mrobinson@wehi.edu.au
Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.
Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.
Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data.Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).Contact: mrobinson@wehi.edu.au