CIPR: a web-based R/shiny app and R package to annotate cell clusters in single cell RNA sequencing experiments

Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data

Annotating cell types of single-cell RNA sequencing (scRNA-seq) data is crucial for studying cellular heterogeneity in the tumor microenvironment. Recently, large-scale pre-trained language models (PLMs) have achieved significant progress in cell-type annotation of scRNA-seq data. This approach effectively addresses previous methods' shortcomings in performance and generalization. However, fine-tuning PLMs for different downstream tasks demands considerable computational resources, rendering it impractical. Hence, a new research branch introduces parameter-efficient fine-tuning (PEFT). This involves optimizing a few parameters while leaving the majority unchanged, leading to substantial reductions in computational expenses. Here, we utilize scBERT, a large-scale pre-trained model, to explore the capabilities of three PEFT methods in scRNA-seq cell type annotation. Extensive benchmark studies across several datasets demonstrate the superior applicability of PEFT methods. Furthermore, downstream analysis using models obtained through PEFT showcases their utility in novel cell type discovery and model interpretability for potential marker genes. Our findings underscore the considerable potential of PEFT in PLM-based cell type annotation, presenting novel perspectives for the analysis of scRNA-seq data.

Single cell RNA sequencing reveals immunomodulatory effects of stem cell factor and granulocyte colony-stimulating factor treatment in the brains of aged APP/PS1 mice

Alzheimers disease leads to progressive neurodegeneration and dementia. Alzheimers disease primarily affects older adults with neuropathological changes including amyloid beta deposition, neuroinflammation, and neurodegeneration. We have previously demonstrated that systemic treatment with combined stem cell factor, SCF, and granulocyte colony stimulating factor, GCSF, reduces amyloid beta load, increases amyloid beta uptake by activated microglia and macrophages, reduces neuroinflammation, and restores dendrites and synapses in the brains of aged APP-PS1 mice. However, the mechanisms underlying SCF-GCSF-enhanced brain repair in aged APP-PS1 mice remain unclear. This study used a transcriptomic approach to identify potential mechanisms by which SCF-GCSF treatment modulates microglia and peripheral myeloid cells to mitigate Alzheimers disease pathology in the aged brain. After injections of SCF-GCSF for 5 consecutive days, single cell RNA sequencing was performed on CD11b positive cells isolated from the brains of 28-month-old APP-PS1 mice. The vast majority of cell clusters aligned with transcriptional profiles of microglia in various activation states. However, SCF-GCSF treatment dramatically increased a cell population showing upregulation of marker genes related to peripheral myeloid cells. Flow cytometry data also revealed an SCF-GCSF-induced increase of cerebral CD45high-CD11b positive active phagocytes. SCF-GCSF treatment robustly increased the transcription of genes implicated in immune cell activation, including gene sets that regulate inflammatory processes and cell migration. Expression of S100a8 and S100a9 were robustly enhanced following SCF-GCSF treatment in all CD11b positive cell clusters. Moreover, the topmost genes differentially expressed with SCF-GCSF treatment were largely upregulated in S100a8-S100a9 positive cells, suggesting a well-conserved transcriptional profile related to SCF-GCSF treatment in resident and peripherally derived CD11b positive immune cells. This S100a8-S100a9-associated transcriptional profile contained notable genes related to proinflammatory and antiinflammatory responses, neuroprotection, and amyloid beta plaque inhibition or clearance. Altogether, this study reveals immunomodulatory effects of SCF-GCSF treatment in the aged brain with Alzheimers disease pathology, which will guide future studies to further uncover the therapeutic mechanisms.

LSD1 drives intestinal epithelial maturation and controls small intestinal immune cell composition independent of microbiota in a murine model

Postnatal development of the gastrointestinal tract involves the establishment of the commensal microbiota, the acquisition of immune tolerance via a balanced immune cell composition, and maturation of the intestinal epithelium. While studies have uncovered an interplay between the first two, less is known about the role of the maturing epithelium. Here we show that intestinal-epithelial intrinsic expression of lysine-specific demethylase 1A (LSD1) is necessary for the postnatal maturation of intestinal epithelium and maintenance of this developed state during adulthood. Using microbiota-depleted mice, we find plasma cells, innate lymphoid cells (ILCs), and a specific myeloid population to depend on LSD1-controlled epithelial maturation. We propose that LSD1 controls the expression of epithelial-derived chemokines, such as Cxcl16, and that this is a mode of action for this epithelial-immune cell interplay in local ILC2s but not ILC3s. Together, our findings suggest that the maturing epithelium plays a dominant role in regulating the local immune cell composition, thereby contributing to gut homeostasis.

Multimodal stimulation screens reveal unique and shared genes limiting T cell fitness

Genes limiting T cell antitumor activity may serve as therapeutic targets. It has not been systematically studied whether there are regulators that uniquely or broadly contribute to T cell fitness. We perform genome-scale CRISPR-Cas9 knockout screens in primary CD8 T cells to uncover genes negatively impacting fitness upon three modes of stimulation: (1) intense, triggering activation-induced cell death (AICD); (2) acute, triggering expansion; (3) chronic, causing dysfunction. Besides established regulators, we uncover genes controlling T cell fitness either specifically or commonly upon differential stimulation. Dap5 ablation, ranking highly in all three screens, increases translation while enhancing tumor killing. Loss of Icam1-mediated homotypic T cell clustering amplifies cell expansion and effector functions after both acute and intense stimulation. Lastly, Ctbp1 inactivation induces functional T cell persistence exclusively upon chronic stimulation. Our results functionally annotate fitness regulators based on their unique or shared contribution to traits limiting T cell antitumor activity.

Single-cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveal heterogeneity of endothelial subtype and response to activating perturbations

Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

Interpreting single-cell messages in normal and aberrant hematopoiesis with the Cell Marker Accordion

Single-cell technologies offer a unique opportunity to explore cellular heterogeneity in hematopoiesis, reveal malignant hematopoietic cells with clinically significant features and measure gene signatures linked to pathological pathways. However, reliable identification of cell types is a crucial bottleneck in single-cell analysis. Available databases contain dissimilar nomenclature and non-concurrent marker sets, leading to inconsistent annotations and poor interpretability. Furthermore, current tools focus mostly on physiological cell types, lacking extensive applicability in disease. We developed the Cell Marker Accordion, a user-friendly platform for the automatic annotation and biological interpretation of single-cell populations based on consistency weighted markers. We validated our approach on peripheral blood and bone marrow single-cell datasets, using surface markers and expert-based annotation as the ground truth. In all cases, we significantly improved the accuracy in identifying cell types with respect to any single source database. Moreover, the Cell Marker Accordion can identify disease-critical cells and pathological processes, extracting potential biomarkers in a wide variety of contexts in human and murine single-cell datasets. It characterizes leukemia stem cell subtypes, including therapy-resistant cells in acute myeloid leukemia patients; it identifies malignant plasma cells in multiple myeloma samples; it dissects cell type alterations in splicing factor-mutant cells from myelodysplastic syndrome patients; it discovers activation of innate immunity pathways in bone marrow from mice treated with METTL3 inhibitors. The breadth of these applications elevates the Cell Marker Accordion as a flexible, faithful and standardized tool to annotate and interpret hematopoietic populations in single-cell datasets focused on the study of hematopoietic development and disease.

Epigenetic signature and key transcriptional regulators of human antigen-specific type 1 regulatory T cells

Human adaptive immunity is orchestrated by effector and regulatory T (Treg) cells. Natural Tregs arise in the thymus where they are shaped to recognize self-antigens, while type 1 Tregs or Tr1 cells are induced from conventional peripheral CD4 + T cells in response to peripheral antigens, such as alloantigens and allergens. Tr1 cells have been developed as a potential therapy for inducing antigen-specific tolerance, because they can be rapidly differentiated in vitro in response to a target antigen. However, the epigenetic landscape and the identity of transcription factors (TFs) that regulate differentiation, phenotype, and functions of human antigen-specific Tr1 cells is largely unknown, hindering Tr1 research and broader clinical development. Here, we reveal the unique epigenetic signature of antigen-specific Tr1 cells, and TFs that regulate their differentiation, phenotype and function. We showed that in vitro induced antigen-specific Tr1 cells are distinct both clonally and transcriptionally from natural Tregs and other conventional CD4 + T cells on a single-cell level. An integrative analysis of Tr1 cell epigenome and transcriptome identified a TF signature unique to antigen-specific Tr1 cells, and predicted that IRF4, BATF, and MAF act as their transcriptional regulators. Using functional genomics, we showed that each of these TFs play a non-redundant role in regulating Tr1 cell differentiation, suppressive function, and expression of co-inhibitory and cytotoxic proteins. By using the Tr1-specific TF signature as a molecular fingerprint, we tracked Tr1 cells in peripheral blood of recipients of allogeneic hematopoietic stem cell transplantation treated with adoptive Tr1 cell therapy. Furthermore, the same signature identified Tr1 cells in resident CD4 + T cells in solid tumors. Altogether, these results reveal the epigenetic signature and the key transcriptional regulators of human Tr1 cells. These data will guide mechanistic studies of human Tr1 cell biology and the development and optimization of adoptive Tr1 cell therapies.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

deltaXpress (ΔXpress): a tool for mapping differentially correlated genes using single-cell qPCR data

BACKGROUND

High-throughput experiments provide deep insight into the molecular biology of different species, but more tools need to be developed to handle this type of data. At the transcriptomics level, quantitative Polymerase Chain Reaction technology (qPCR) can be affordably adapted to produce high-throughput results through a single-cell approach. In addition to comparative expression profiles between groups, single-cell approaches allow us to evaluate and propose new dependency relationships among markers. However, this alternative has not been explored before for large-scale qPCR-based experiments.

RESULTS

Herein, we present deltaXpress (ΔXpress), a web app for analyzing data from single-cell qPCR experiments using a combination of HTML and R programming languages in a friendly environment. This application uses cycle threshold (Ct) values and categorical information for each sample as input, allowing the best pair of housekeeping genes to be chosen to normalize the expression of target genes. ΔXpress emulates a bulk analysis by observing differentially expressed genes, but in addition, it allows the discovery of pairwise genes differentially correlated when comparing two experimental conditions. Researchers can download normalized data or use subsequent modules to map differentially correlated genes, perform conventional comparisons between experimental groups, obtain additional information about their genes (gene glossary), and generate ready-to-publication images (600 dots per inch).

CONCLUSIONS

ΔXpress web app is freely available to non-commercial users at https://alexismurillo.shinyapps.io/dXpress/ and can be used for different experiments in all technologies involving qPCR with at least one housekeeping region.

SCALA: A complete solution for multimodal analysis of single-cell Next Generation Sequencing data

Analysis and interpretation of high-throughput transcriptional and chromatin accessibility data at single-cell (sc) resolution are still open challenges in the biomedical field. The existence of countless bioinformatics tools, for the different analytical steps, increases the complexity of data interpretation and the difficulty to derive biological insights. In this article, we present SCALA, a bioinformatics tool for analysis and visualization of single-cell RNA sequencing (scRNA-seq) and Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) datasets, enabling either independent or integrative analysis of the two modalities. SCALA combines standard types of analysis by integrating multiple software packages varying from quality control to the identification of distinct cell populations and cell states. Additional analysis options enable functional enrichment, cellular trajectory inference, ligand-receptor analysis, and regulatory network reconstruction. SCALA is fully parameterizable, presenting data in tabular format and producing publication-ready visualizations. The different available analysis modules can aid biomedical researchers in exploring, analyzing, and visualizing their data without any prior experience in coding. We demonstrate the functionality of SCALA through two use-cases related to TNF-driven arthritic mice, handling both scRNA-seq and scATAC-seq datasets. SCALA is developed in R, Shiny and JavaScript and is mainly available as a standalone version, while an online service of more limited capacity can be found at http://scala.pavlopouloslab.info or https://scala.fleming.gr.

Synovial macrophage diversity and activation of M-CSF signaling in post-traumatic osteoarthritis

Objective

Synovium is home to immune and stromal cell types that orchestrate inflammation following a joint injury; in particular, macrophages are central protagonists in this process. We sought to define the cellular and temporal dynamics of the synovial immune niche in a mouse model of post-traumatic osteoarthritis (PTOA), and to identify stromal-immune crosstalk mechanisms that coordinate macrophage function and phenotype.

Design

We induced PTOA in mice using a non-invasive tibial compression model of anterior cruciate ligament rupture (ACLR). Single cell RNA-seq and flow cytometry were used to assess immune cell populations in healthy (Sham) and injured (7d and 28d post-ACLR) synovium. Characterization of synovial macrophage polarization states was performed, alongside computational modeling of macrophage differentiation, as well as implicated transcriptional regulators and stromal-immune communication axes.

Results

Immune cell types are broadly represented in healthy synovium, but experience drastic expansion and speciation in PTOA, most notably in the macrophage portion. We identified several polarization states of macrophages in synovium following joint injury, underpinned by distinct transcriptomic signatures, and regulated in part by stromal-derived macrophage colony-stimulating factor signaling. The transcription factors Pu.1, Cebpα, Cebpβ, and Jun were predicted to control differentiation of systemically derived monocytes into pro-inflammatory synovial macrophages.

Conclusions

We defined different synovial macrophage subpopulations present in healthy and injured mouse synovium. Nuanced characterization of the distinct functions, origins, and disease kinetics of macrophage subtypes in PTOA will be critical for targeting these highly versatile cells for therapeutic purposes.

HIF-1 regulates pathogenic cytotoxic T cells in lupus skin disease

Cutaneous lupus erythematosus (CLE) is a disfiguring autoimmune skin disease characterized by an inflammatory infiltrate rich in T cells, which are strongly implicated in tissue damage. How these cells adapt to the skin environment and promote tissue inflammation and damage is not known. In lupus nephritis, we previously identified an inflammatory gene program in kidney-infiltrating T cells that is dependent on HIF-1, a transcription factor critical for the cellular and developmental response to hypoxia as well as inflammation-associated signals. In our present studies using a mouse model of lupus skin disease, we find that skin-infiltrating CD4+ and CD8+ T cells also express high levels of HIF-1. Skin-infiltrating T cells demonstrated a strong cytotoxic signature at the transcript and protein levels, and HIF-1 inhibition abrogated skin and systemic diseases in association with decreased T cell cytotoxic activity. We also demonstrate in human CLE tissue that the T cell-rich inflammatory infiltrate exhibited increased amounts of HIF-1 and a cytotoxic signature. Granzyme B-expressing T cells were concentrated at sites of skin tissue damage in CLE, suggesting relevance of this pathway to human disease.

Senescence-induced immune remodeling facilitates metastatic adrenal cancer in a sex-dimorphic manner

Aging markedly increases cancer risk, yet our mechanistic understanding of how aging influences cancer initiation is limited. Here we demonstrate that the loss of ZNRF3, an inhibitor of Wnt signaling that is frequently mutated in adrenocortical carcinoma, leads to the induction of cellular senescence that remodels the tissue microenvironment and ultimately permits metastatic adrenal cancer in old animals. The effects are sexually dimorphic, with males exhibiting earlier senescence activation and a greater innate immune response, driven in part by androgens, resulting in high myeloid cell accumulation and lower incidence of malignancy. Conversely, females present a dampened immune response and increased susceptibility to metastatic cancer. Senescence-recruited myeloid cells become depleted as tumors progress, which is recapitulated in patients in whom a low myeloid signature is associated with worse outcomes. Our study uncovers a role for myeloid cells in restraining adrenal cancer with substantial prognostic value and provides a model for interrogating pleiotropic effects of cellular senescence in cancer.

scViewer: An Interactive Single-Cell Gene Expression Visualization Tool

Single-cell RNA sequencing (scRNA-seq) is an attractive technology for researchers to gain valuable insights into the cellular processes and cell type diversity present in all tissues. The data generated by the scRNA-seq experiment are high-dimensional and complex in nature. Several tools are now available to analyze the raw scRNA-seq data from public databases; however, simple and easy-to-explore single-cell gene expression visualization tools focusing on differential expression and co-expression are lacking. Here, we present scViewer, an interactive graphical user interface (GUI) R/Shiny application designed to facilitate the visualization of scRNA-seq gene expression data. With the processed Seurat RDS object as input, scViewer utilizes several statistical approaches to provide detailed information on the loaded scRNA-seq experiment and generates publication-ready plots. The major functionalities of scViewer include exploring cell-type-specific gene expression, co-expression analysis of two genes, and differential expression analysis with different biological conditions considering both cell-level and subject-level variations using negative binomial mixed modeling. We utilized a publicly available dataset (brain cells from a study of Alzheimer's disease to demonstrate the utility of our tool. scViewer can be downloaded from GitHub as a Shiny app with local installation. Overall, scViewer is a user-friendly application that will allow researchers to visualize and interpret the scRNA-seq data efficiently for multi-condition comparison by performing gene-level differential expression and co-expression analysis on the fly. Considering the functionalities of this Shiny app, scViewer can be a great resource for collaboration between bioinformaticians and wet lab scientists for faster data visualizations.

MicroRNA-155 Plays Selective Cell-Intrinsic Roles in Brain-Infiltrating Immune Cell Populations during Neuroinflammation

The proinflammatory microRNA-155 (miR-155) is highly expressed in the serum and CNS lesions of patients with multiple sclerosis (MS). Global knockout (KO) of miR-155 in mice confers resistance to a mouse model of MS, experimental autoimmune encephalomyelitis (EAE), by reducing the encephalogenic potential of CNS-infiltrating Th17 T cells. However, cell-intrinsic roles for miR-155 during EAE have not been formally determined. In this study, we use single-cell RNA sequencing and cell-specific conditional miR-155 KOs to determine the importance of miR-155 expression in distinct immune cell populations. Time-course single-cell sequencing revealed reductions in T cells, macrophages, and dendritic cells (DCs) in global miR-155 KO mice compared with wild-type controls at day 21 after EAE induction. Deletion of miR-155 in T cells, driven by CD4 Cre, significantly reduced disease severity similar to global miR-155 KOs. CD11c Cre-mediated deletion of miR-155 in DCs also resulted in a modest yet significant reduction in the development of EAE, with both T cell- and DC-specific KOs showing a reduction in Th17 T cell infiltration into the CNS. Although miR-155 is highly expressed in infiltrating macrophages during EAE, deletion of miR-155 using LysM Cre did not impact disease severity. Taken together, these data show that although miR-155 is highly expressed in most infiltrating immune cells, miR-155 has distinct roles and requirements depending on the cell type, and we have demonstrated this using the gold standard conditional KO approach. This provides insights into which functionally relevant cell types should be targeted by the next generation of miRNA therapeutics.

A pro B cell population forms the apex of the leukemic hierarchy in Hoxa9/Meis1-dependent AML

Relapse is a major challenge to therapeutic success in acute myeloid leukemia (AML) and can be partly associated with heterogeneous leukemic stem cell (LSC) properties. In the murine Hoxa9/Meis1-dependent (H9M) AML model, LSC potential lies in three defined immunophenotypes, including Lin-cKit+ progenitor cells (Lin-), Gr1+CD11b+cKit+ myeloid cells, and lymphoid cells (Lym+). Previous reports demonstrated their interconversion and distinct drug sensitivities. In contrast, we here show that H9M AML is hierarchically organized. We, therefore, tracked the developmental potential of LSC phenotypes. This unexpectedly revealed a substantial fraction of Lin- LSCs that failed to regenerate Lym+ LSCs, and that harbored reduced leukemogenic potential. However, Lin- LSCs capable of producing Lym+ LSCs as well as Lym+ LSCs triggered rapid disease development suggestive of their high relapse-driving potential. Transcriptional analyses revealed that B lymphoid master regulators, including Sox4 and Bach2, correlated with Lym+ LSC development and presumably aggressive disease. Lentiviral overexpression of Sox4 and Bach2 induced dedifferentiation of H9M cells towards a lineage-negative state in vitro as the first step of lineage conversion. This work suggests that the potency to initiate a partial B lymphoid primed transcriptional program as present in infant AML correlates with aggressive disease and governs the H9M LSC hierarchy.

Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases

Neurodegenerative diseases affect millions of people worldwide and there are currently no cures. Two types of common neurodegenerative diseases are Alzheimer's (AD) and Parkinson's disease (PD). Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq) have become powerful tools to elucidate the inherent complexity and dynamics of the central nervous system at cellular resolution. This technology has allowed the identification of cell types and states, providing new insights into cellular susceptibilities and molecular mechanisms underlying neurodegenerative conditions. Exciting research using high throughput scRNA-seq and snRNA-seq technologies to study AD and PD is emerging. Herein we review the recent progress in understanding these neurodegenerative diseases using these state-of-the-art technologies. We discuss the fundamental principles and implications of single-cell sequencing of the human brain. Moreover, we review some examples of the computational and analytical tools required to interpret the extensive amount of data generated from these assays. We conclude by highlighting challenges and limitations in the application of these technologies in the study of AD and PD.

Sustained Infiltration of Neutrophils Into the CNS Results in Increased Demyelination in a Viral-Induced Model of Multiple Sclerosis

Intracranial inoculation of the neuroadapted JHM strain of mouse hepatitis virus (JHMV) into susceptible strains of mice results in acute encephalomyelitis followed by a cimmune-mediated demyelination similar to the human demyelinating disease multiple sclerosis (MS). JHMV infection of transgenic mice in which expression of the neutrophil chemoattractant chemokine CXCL1 is under the control of a tetracycline-inducible promoter active within GFAP-positive cells results in sustained neutrophil infiltration in the central nervous system (CNS) that correlates with an increase in spinal cord demyelination. We used single cell RNA sequencing (scRNAseq) and flow cytometry to characterize molecular and cellular changes within the CNS associated with increased demyelination in transgenic mice compared to control animals. These approaches revealed the presence of activated neutrophils as determined by expression of mRNA transcripts associated with neutrophil effector functions, including CD63, MMP9, S100a8, S100a9, and ASPRV1, as well as altered neutrophil morphology and protein expression. Collectively, these findings reveal insight into changes in the profile of neutrophils associated with increased white matter damage in mice persistently infected with a neurotropic coronavirus.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

PlaqView 2.0: A comprehensive web portal for cardiovascular single-cell genomics

Single-cell RNA-seq (scRNA-seq) is a powerful genomics technology to interrogate the cellular composition and behaviors of complex systems. While the number of scRNA-seq datasets and available computational analysis tools have grown exponentially, there are limited systematic data sharing strategies to allow rapid exploration and re-analysis of single-cell datasets, particularly in the cardiovascular field. We previously introduced PlaqView, an open-source web portal for the exploration and analysis of published atherosclerosis single-cell datasets. Now, we introduce PlaqView 2.0 (www.plaqview.com), which provides expanded features and functionalities as well as additional cardiovascular single-cell datasets. We showcase improved PlaqView functionality, backend data processing, user-interface, and capacity. PlaqView brings new or improved tools to explore scRNA-seq data, including gene query, metadata browser, cell identity prediction, ad hoc RNA-trajectory analysis, and drug-gene interaction prediction. PlaqView serves as one of the largest central repositories for cardiovascular single-cell datasets, which now includes data from human aortic aneurysm, gene-specific mouse knockouts, and healthy references. PlaqView 2.0 brings advanced tools and high-performance computing directly to users without the need for any programming knowledge. Lastly, we outline steps to generalize and repurpose PlaqView's framework for single-cell datasets from other fields.

Snail-regulated exosomal microRNA-21 suppresses NLRP3 inflammasome activity to enhance cisplatin resistance

BACKGROUND

Compared with the precise targeting of drug-resistant mutant cancer cells, strategies for eliminating non-genetic adaptation-mediated resistance are limited. The pros and cons of the existence of inflammasomes in cancer have been reported. Nevertheless, the dynamic response of inflammasomes to therapies should be addressed.

METHODS

Tumor-derived exosomes were purified by differential ultracentrifugation and validated by nanoparticle tracking analysis and transmission electron microscopy. A proximity ligation assay and interleukin-1β (IL-1β) level were used for detecting activation of NLRP3 inflammasomes. RNA sequencing was used to analyze the exosomal RNAs. MIR21 knocked out human monocytic THP cells and mir21 knocked out murine oral cancer MTCQ1 cells were generated for confirming the exosomal delivery of microRNA (miR)-21. Syngeneic murine models for head and neck cancer (C57BLJ/6J), breast cancer (BALB/C) and lung cancer (C57BL/6J) were applied for examining the impact of Snail-miR21 axis on inflammasome activation in vivo. Single-cell RNA sequencing was used for analyzing the tumor-infiltrated immune cells. Head and neck patient samples were used for validating the findings in clinical samples.

RESULTS

We demonstrated that in cancer cells undergoing Snail-induced epithelial-mesenchymal transition (EMT), tumor cells suppress NLRP3 inflammasome activities of tumor-associated macrophages (TAMs) in response to chemotherapy through the delivery of exosomal miR-21. Mechanistically, miR-21 represses PTEN and BRCC3 to facilitate NLRP3 phosphorylation and lysine-63 ubiquitination, inhibiting NLRP3 inflammasome assembly. Furthermore, the Snail-miR-21 axis shapes the post-chemotherapy tumor microenvironment (TME) by repopulating TAMs and by activating CD8⁺ T cells. In patients with head and neck cancer, the Snail-high cases lacked post-chemotherapy IL-1β surge and were correlated with a worse response.

CONCLUSIONS

This finding reveals the mechanism of EMT-mediated resistance beyond cancer stemness through modulation of post-treatment inflammasome activity. It also highlights the dynamic remodeling of the TME throughout metastatic evolution.

scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data

Background

Automatic cell type identification is essential to alleviate a key bottleneck in scRNA-seq data analysis. While most existing classification tools show good sensitivity and specificity, they often fail to adequately not-classify cells that are missing in the used reference. Additionally, many tools do not scale to the continuously increasing size of current scRNA-seq datasets. Therefore, additional tools are needed to solve these challenges.

Results

scAnnotatR is a novel R package that provides a complete framework to classify cells in scRNA-seq datasets using pre-trained classifiers. It supports both Seurat and Bioconductor’s SingleCellExperiment and is thereby compatible with the vast majority of R-based analysis workflows. scAnnotatR uses hierarchically organised SVMs to distinguish a specific cell type versus all others. It shows comparable or even superior accuracy, sensitivity and specificity compared to existing tools while being able to not-classify unknown cell types. Moreover, scAnnotatR is the only of the best performing tools able to process datasets containing more than 600,000 cells.

Conclusions

scAnnotatR is freely available on GitHub (https://github.com/grisslab/scAnnotatR) and through Bioconductor (from version 3.14). It is consistently among the best performing tools in terms of classification accuracy while scaling to the largest datasets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04574-5.

FaDA: A web application for regular laboratory data analyses

Web-based data analysis and visualization tools are mostly designed for specific purposes, such as the analysis of data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, generic tools designed for the analysis of common laboratory data for noncomputational scientists are also needed. The importance of such web-based tools is emphasized by the continuing increases in the sample capacity of conventional laboratory tools such as quantitative PCR, flow cytometry or ELISA instruments. We present a web-based application FaDA, developed with the R Shiny package that provides users with the ability to perform statistical group comparisons, including parametric and nonparametric tests, with multiple testing corrections suitable for most standard wet-laboratory analyses. FaDA provides data visualizations such as heatmaps, principal component analysis (PCA) plots, correlograms and receiver operating curves (ROCs). Calculations are performed through the R language. The FaDA application provides a free and intuitive interface that allows biologists without bioinformatic skill to easily and quickly perform common laboratory data analyses. The application is freely accessible at https://shiny-bird.univ-nantes.fr/app/Fada.

Blocking Short-Form Ron Eliminates Breast Cancer Metastases through Accumulation of Stem-Like CD4+ T Cells That Subvert Immunosuppression

Immunotherapy has potential to prevent and treat metastatic breast cancer, but strategies to enhance immune-mediated killing of metastatic tumors are urgently needed. We report that a ligand-independent isoform of Ron kinase (SF-Ron) is a key target to enhance immune infiltration and eradicate metastatic tumors. Host-specific deletion of SF-Ron caused recruitment of lymphocytes to micrometastases, augmented tumor-specific T-cell responses, and nearly eliminated breast cancer metastasis in mice. Lack of host SF-Ron caused stem-like TCF1+ CD4+ T cells with type I differentiation potential to accumulate in metastases and prevent metastatic outgrowth. There was a corresponding increase in tumor-specific CD8+ T cells, which were also required to eliminate lung metastases. Treatment of mice with a Ron kinase inhibitor increased tumor-specific CD8+ T cells and protected from metastatic outgrowth. These data provide a strong preclinical rationale to pursue small-molecule Ron kinase inhibitors for the prevention and treatment of metastatic breast cancer.

SIGNIFICANCE

The discovery that SF-Ron promotes antitumor immune responses has significant clinical implications. Therapeutic antibodies targeting full-length Ron may not be effective for immunotherapy; poor efficacy of such antibodies in trials may be due to their inability to block SF-Ron. Our data warrant trials with inhibitors targeting SF-Ron in combination with immunotherapy. This article is highlighted in the In This Issue feature, p. 2945.

Epithelial-myeloid exchange of MHC class II constrains immunity and microbiota composition

Intestinal epithelial cells (IECs) have long been understood to express high levels of major histocompatibility complex class II (MHC class II) molecules but are not considered canonical antigen-presenting cells, and the impact of IEC-MHC class II signaling on gut homeostasis remains enigmatic. As IECs serve as the primary barrier between underlying host immune cells, we reasoned that IEC-intrinsic antigen presentation may play a role in responses toward the microbiota. Mice with an IEC-intrinsic deletion of MHC class II (IECΔMHC class II) are healthy but have fewer microbial-bound IgA, regulatory T cells (Tregs), and immune repertoire selection. This was associated with increased interindividual microbiota variation and altered proportions of two taxa in the ileum where MHC class II on IECs is highest. Intestinal mononuclear phagocytes (MNPs) have similar MHC class II transcription but less surface MHC class II and are capable of acquiring MHC class II from IECs. Thus, epithelial-myeloid interactions mediate development of adaptive responses to microbial antigens within the gastrointestinal tract.

Disrupted macrophage metabolic reprogramming in aged soleus muscle during early recovery following disuse atrophy

Aged skeletal muscle is characterized by poor muscle recovery following disuse coinciding with an impaired muscle pro-inflammatory macrophage response. Macrophage inflammatory status is regulated by its metabolic state, but little is understood of macrophage metabolism and its relation to macrophage inflammation in the context of muscle recovery and aging. Therefore, the purpose of this study was to thoroughly characterize macrophage metabolism and inflammation in aged muscle during early recovery following disuse atrophy using single cell transcriptomics and functional assays. Young (4-5 months) and old (20-22 months) male C57BL/6 mice underwent 14 days of hindlimb unloading followed by 4 days of ambulatory recovery. CD45+ cells were isolated from solei muscles and analyzed using 10x Genomics single cell RNA sequencing. We found that aged pro-inflammatory macrophage clusters were characterized with an impaired inflammatory and glycolytic transcriptome, and this dysregulation was accompanied by a suppression of HIF-1α and its immediate downstream target, Glut1. As a follow-up, bone marrow-derived macrophages were isolated from a separate cohort of young and old mice at 4-d recovery and were polarized to a pro-inflammatory phenotype and used for glycolysis stress test, phagocytosis activity assay, and targeted GC-MS metabolomics. Aged bone marrow-derived pro-inflammatory macrophages were characterized with impaired glycolysis and phagocytosis function, decreased succinate and an accumulation of glycolytic metabolic intermediates overall supporting reduced glycolytic flux and macrophage function. Our results indicate that the metabolic reprograming and function of aged skeletal muscle pro-inflammatory macrophages are dysfunctional during early recovery from disuse atrophy possibly attributing to attenuated regrowth.

A Catalogus Immune Muris of the mouse immune responses to diverse pathogens

Immunomodulation strategies are crucial for several biomedical applications. However, the immune system is highly heterogeneous and its functional responses to infections remains elusive. Indeed, the characterization of immune response particularities to different pathogens is needed to identify immunomodulatory candidates. To address this issue, we compiled a comprehensive map of functional immune cell states of mouse in response to 12 pathogens. To create this atlas, we developed a single-cell-based computational method that partitions heterogeneous cell types into functionally distinct states and simultaneously identifies modules of functionally relevant genes characterizing them. We identified 295 functional states using 114 datasets of six immune cell types, creating a Catalogus Immune Muris. As a result, we found common as well as pathogen-specific functional states and experimentally characterized the function of an unknown macrophage cell state that modulates the response to Salmonella Typhimurium infection. Thus, we expect our Catalogus Immune Muris to be an important resource for studies aiming at discovering new immunomodulatory candidates.

Meta-Analysis of Smooth Muscle Lineage Transcriptomes in Atherosclerosis and Their Relationships to In Vitro Models

BACKGROUND

Vascular smooth muscle cells (VSMC) exhibit phenotypic plasticity in atherosclerotic plaques, and among other approaches, has been modeled in vitro by cholesterol loading.

METHODS

Meta-analysis of scRNA-seq data from VSMC lineage traced cells across five experiments of murine atherosclerosis was performed. In vivo expression profiles were compared to three in vitro datasets of VSMCs loaded with cholesterol and three datasets of polarized macrophages.

RESULTS

We identified 24 cell clusters in the meta-analysis of single cells from mouse atherosclerotic lesions with notable heterogeneity across studies, especially for macrophage populations. Trajectory analysis of VSMC lineage positive cells revealed several possible paths of state transitions with one traversing from contractile VSMC to macrophages by way of a proliferative cell cluster. Transcriptome comparisons between in vivo and in vitro states underscored that data from three in vitro cholesterol-treated VSMC experiments did not mirror cell state transitions observed in vivo. However, all in vitro macrophage profiles analyzed (M1, M2, and oxLDL) were more similar to in vivo profiles of macrophages than in vitro VSMCs were to in vivo profiles of VSMCs. oxLDL loaded macrophages showed the most similarity to in vivo states. In contrast to the in vitro data, comparison between mouse and human in vivo data showed many similarities.

CONCLUSIONS

Identification of the sources of variation across single cell datasets in atherosclerosis will be an important step towards understanding VSMC fate transitions in vivo. Also, we conclude that cholesterol-loading in vitro is insufficient to model the VSMC cell state transitions observed in vivo, which underscores the need to develop better cell models. Mouse models, however, appear to reproduce a number of the features of VSMCs in human plaques.

A Stat1 bound enhancer promotes Nampt expression and function within tumor associated macrophages

Tumor associated macrophage responses are regulated by distinct metabolic states that affect their function. However, the ability of specific signals in the local tumor microenvironment to program macrophage metabolism remains under investigation. Here, we identify NAMPT, the rate limiting enzyme in NAD salvage synthesis, as a target of STAT1 during cellular activation by interferon gamma, an important driver of macrophage polarization and antitumor responses. We demonstrate that STAT1 occupies a conserved element within the first intron of Nampt, termed Nampt-Regulatory Element-1 (NRE1). Through disruption of NRE1 or pharmacological inhibition, a subset of M1 genes is sensitive to NAMPT activity through its impact on glycolytic processes. scRNAseq is used to profile in vivo responses by NRE1-deficient, tumor-associated leukocytes in melanoma tumors through the creation of a unique mouse strain. Reduced Nampt and inflammatory gene expression are present in specific myeloid and APC populations; moreover, targeted ablation of NRE1 in macrophage lineages results in greater tumor burden. Finally, elevated NAMPT expression correlates with IFNγ responses and melanoma patient survival. This study identifies IFN and STAT1-inducible Nampt as an important factor that shapes the metabolic program and function of tumor associated macrophages.

How well do brain organoids capture your brain?

Brain organoids closely recapitulate many features and characteristics of in vivo brain tissue. This technology in turn allows unprecedented possibilities to investigate brain development and function in the dish. Several brain organoid protocols have been established, and the studies have focused on validating the architecture, cellular composition, and function of the organoids. In future, the improved and advanced organoid models will enable us to understand cellular and molecular features of the developing brain. However, several obstacles, such as the quality of the organoids, 3D structural analysis, and measurement of the neural connectivity need to be improved. In this perspective, we will provide an overview of the current state of the art of the brain organoid field, with a focus on protocols and organoid characterization. Additionally, we will address the current limitations of this evolving field and provide an understanding of the current brain organoid landscape and insight toward the next steps.

Maternal schistosomiasis impairs offspring Interleukin-4 production and B cell expansion

Epidemiological studies have identified a correlation between maternal helminth infections and reduced immunity to some early childhood vaccinations, but the cellular basis for this is poorly understood. Here, we investigated the effects of maternal Schistosoma mansoni infection on steady-state offspring immunity, as well as immunity induced by a commercial tetanus/diphtheria vaccine using a dual IL-4 reporter mouse model of maternal schistosomiasis. We demonstrate that offspring born to S. mansoni infected mothers have reduced circulating plasma cells and peripheral lymph node follicular dendritic cells at steady state. These reductions correlate with reduced production of IL-4 by iNKT cells, the cellular source of IL-4 in the peripheral lymph node during early life. These defects in follicular dendritic cells and IL-4 production were maintained long-term with reduced secretion of IL-4 in the germinal center and reduced generation of TFH, memory B, and memory T cells in response to immunization with tetanus/diphtheria. Using single-cell RNASeq following tetanus/diphtheria immunization of offspring, we identified a defect in cell-cycle and cell-proliferation pathways in addition to a reduction in Ebf-1, a key B-cell transcription factor, in the majority of follicular B cells. These reductions are dependent on the presence of egg antigens in the mother, as offspring born to single-sex infected mothers do not have these transcriptional defects. These data indicate that maternal schistosomiasis leads to long-term defects in antigen-induced cellular immunity, and for the first time provide key mechanistic insight into the factors regulating reduced immunity in offspring born to S. mansoni infected mothers.

Maternal helminth infections are a global public health concern and correlate with altered infant immune responses to some childhood immunizations, but a mechanistic understanding of how maternal helminth infection alters the cellular immune responses of offspring is lacking. Here we establish a model of maternal Schistosoma mansoni infection in dual IL-4 reporter mice. We find that offspring born to mothers infected with S. mansoni have impaired production of IL-4 during homeostasis, and following immunization with a Tetanus-Diphtheria vaccine. We identified that iNKT cells are the dominant source of IL-4 during early life homeostasis, and that diminished IL-4 production was associated with both reduced B cell and follicular dendritic cell responses. These defects were maintained long-term, affecting memory B and T cell responses. Single-cell RNASeq analysis of immunized offspring identified egg antigen-dependent reductions in B-cell cell cycle and proliferation-related genes. These data reveal that maternal infection leads to long-lasting defects in the cellular responses to heterologous antigens and provide vital insight into the influence of maternal infection on offspring immunity.

Automated methods for cell type annotation on scRNA-seq data

The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell RNA sequencing data, yet manual annotation is time-consuming and partially subjective. As an alternative, tools have been developed for automatic cell type identification. Different strategies have emerged to ultimately associate gene expression profiles of single cells with a cell type either by using curated marker gene databases, correlating reference expression data, or transferring labels by supervised classification. In this review, we present an overview of the available tools and the underlying approaches to perform automated cell type annotations on scRNA-seq data.

Single-Cell RNA Sequencing Reveals the Diversity of the Immunological Landscape following Central Nervous System Infection by a Murine Coronavirus

Intracranial (i.c.) infection of susceptible C57BL/6 mice with the neurotropic JHM strain of mouse hepatitis virus (JHMV) (a member of the Coronaviridae family) results in acute encephalomyelitis and viral persistence associated with an immune-mediated demyelinating disease. The present study was undertaken to better understand the molecular pathways evoked during innate and adaptive immune responses as well as the chronic demyelinating stage of disease in response to JHMV infection of the central nervous system (CNS). Using single-cell RNA sequencing analysis (scRNAseq) on flow-sorted CD45-positive (CD45+) cells enriched from brains and spinal cords of experimental mice, we demonstrate the heterogeneity of the immune response as determined by the presence of unique molecular signatures and pathways involved in effective antiviral host defense. Furthermore, we identify potential genes involved in contributing to demyelination as well as remyelination being expressed by both microglia and macrophages. Collectively, these findings emphasize the diversity of the immune responses and molecular networks at defined stages following viral infection of the CNS.IMPORTANCE Understanding the immunological mechanisms contributing to both host defense and disease following viral infection of the CNS is of critical importance given the increasing number of viruses that are capable of infecting and replicating within the nervous system. With this in mind, the present study was undertaken to evaluate the molecular signatures of immune cells within the CNS at defined times following infection with a neuroadapted murine coronavirus using scRNAseq. This approach has revealed that the immunological landscape is diverse, with numerous immune cell subsets expressing distinct mRNA expression profiles that are, in part, dictated by the stage of infection. In addition, these findings reveal new insight into cellular pathways contributing to control of viral replication as well as to neurologic disease.

Kidney Single-Cell Atlas Reveals Myeloid Heterogeneity in Progression and Regression of Kidney Disease

BACKGROUND

Little is known about the roles of myeloid cell subsets in kidney injury and in the limited ability of the organ to repair itself. Characterizing these cells based only on surface markers using flow cytometry might not provide a full phenotypic picture. Defining these cells at the single-cell, transcriptomic level could reveal myeloid heterogeneity in the progression and regression of kidney disease.

METHODS

Integrated droplet- and plate-based single-cell RNA sequencing were used in the murine, reversible, unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single-cell level during renal injury and the resolution of fibrosis. Paired blood exchange tracked the fate of monocytes recruited to the injured kidney.

RESULTS

A single-cell atlas of the kidney generated using transcriptomics revealed marked changes in the proportion and gene expression of renal cell types during injury and repair. Conventional flow cytometry markers would not have identified the 12 myeloid cell subsets. Monocytes recruited to the kidney early after injury rapidly adopt a proinflammatory, profibrotic phenotype that expresses Arg1, before transitioning to become Ccr2 ⁺ macrophages that accumulate in late injury. Conversely, a novel Mmp12 ⁺ macrophage subset acts during repair.

CONCLUSIONS

Complementary technologies identified novel myeloid subtypes, based on transcriptomics in single cells, that represent therapeutic targets to inhibit progression or promote regression of kidney disease.