Single-cell transcriptomics to explore the immune system in health and disease

High-throughput microfluidic droplets in biomolecular analytical system: A review

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

Transcriptomic analysis of B cells suggests that CD70 and LY9 may be novel features in patients with systemic lupus erythematosus

Dysfunction of B-cell subsets is critical in the development of systemic lupus erythematosus (SLE). There is a great diversity of B-lineage cells, and their features and functions in SLE need to be clarified. In this study, we analyzed single-cell RNA sequencing (scRNA-seq) data from peripheral blood mononuclear cells (PBMCs) and bulk transcriptomic data of isolated B-cell subsets from patients with SLE and healthy controls (HCs). We preformed scRNA-seq analysis focused on the diversity of B-cell subsets and identified a subset of antigen-presenting B cells in SLE patients that highly expressed ITGAX. A list of marker genes of each B-cell subset in patients with SLE was also identified. Comparison of bulk transcriptomic data of isolated B-cell subpopulations between SLE patients and HCs revealed the upregulated differentially expressed genes (DEGs) for each B-cell subpopulation in SLE. Common genes identified using these two methods were considered to be upregulated marker genes of B cells in SLE. The scRNA-seq data of SLE patients and HCs revealed that CD70 and LY9 were overexpressed in B cells vs. other cell types from SLE patients, and this pattern was validated by RT‒qPCR. Because CD70 is the cellular ligand of CD27, previous studies on CD70 have focused mainly on T cells from SLE patients. LY9 appears to have different functions in mice and humans: its expression is decreased in lupus-prone mice but is increased in T cells and some B-cell subpopulations in SLE patients. Here, we describe the overexpression of two costimulatory molecules, CD70 and LY9, which may be a novel feature of B cells in SLE patients.

The heterogeneous cellular landscape of atherosclerosis: Implications for future research and therapies. A collaborative review from the EAS young fellows

Single cell technologies, lineage tracing mouse models and advanced imaging techniques unequivocally improved the resolution of the cellular landscape of atherosclerosis. Although the discovery of the heterogeneous nature of the cellular plaque architecture has undoubtedly improved our understanding of the specific cellular states in atherosclerosis progression, it also adds more complexity to current and future research and will change how we approach future drug development. In this review, we will discuss how the revolution of new single cell technologies allowed us to map the cellular networks in the plaque, but we will also address current (technological) limitations that confine us to identify the cellular drivers of the disease and to pinpoint a specific cell state, cell subset or cell surface antigen as new candidate drug target for atherosclerosis.

Genomic Analysis of Foxp3 Function in Regulatory T Cells

Regulatory T (Treg) cells are critical for tolerance to self-antigens and for preventing autoimmunity. Foxp3 has been identified as a Treg cell lineage-defining transcription factor controlling Treg cell differentiation and function. In this article, we review the current mechanistic and systemic understanding of Foxp3 function enabled by experimental and computational advances in high-throughput genomics.

CD4+ T cells produce GM-CSF and drive immune-mediated glomerular disease by licensing monocyte-derived cells to produce MMP12

GM-CSF in glomerulonephritisDespite glomerulonephritis being an immune-mediated disease, the contributions of individual immune cell types are not clear. To address this gap in knowledge, Paust et al. characterized pathological immune cells in samples from patients with glomerulonephritis and in samples from mice with the disease. The authors found that CD4+ T cells producing granulocyte-macrophage colony-stimulating factor (GM-CSF) licensed monocytes to promote disease by producing matrix metalloproteinase 12 and disrupting the glomerular basement membrane. Targeting GM-CSF to inhibit this axis reduced disease severity in mice, implicating this cytokine as a potential therapeutic target for patients with glomerulonephritis. -CM.

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.

BLTSA: pseudotime prediction for single cells by branched local tangent space alignment

MOTIVATION

The development of single-cell RNA sequencing (scRNA-seq) technology makes it possible to study the cellular dynamic processes such as cell cycle and cell differentiation. Due to the difficulties in generating genuine time-series scRNA-seq data, it is of great importance to computationally infer the pseudotime of the cells along differentiation trajectory based on their gene expression patterns. The existing pseudotime prediction methods often suffer from the high level noise of single-cell data, thus it is still necessary to study the single-cell trajectory inference methods.

RESULTS

In this study, we propose a branched local tangent space alignment (BLTSA) method to infer single-cell pseudotime for multi-furcation trajectories. By assuming that single cells are sampled from a low-dimensional self-intersecting manifold, BLTSA first identifies the tip and branching cells in the trajectory based on cells' local Euclidean neighborhoods. Local coordinates within the tangent spaces are then determined by each cell's local neighborhood after clustering all the cells to different branches iteratively. The global coordinates for all the single cells are finally obtained by aligning the local coordinates based on the tangent spaces. We evaluate the performance of BLTSA on four simulation datasets and five real datasets. The experimental results show that BLTSA has obvious advantages over other comparison methods.

AVAILABILITY AND IMPLEMENTATION

R codes are available at https://github.com/LiminLi-xjtu/BLTSA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data

The progress of single-cell RNA sequencing (scRNA-seq) has led to a large number of scRNA-seq data, which are widely used in biomedical research. The noise in the raw data and tens of thousands of genes pose a challenge to capture the real structure and effective information of scRNA-seq data. Most of the existing single-cell analysis methods assume that the low-dimensional embedding of the raw data belongs to a Gaussian distribution or a low-dimensional nonlinear space without any prior information, which limits the flexibility and controllability of the model to a great extent. In addition, many existing methods need high computational cost, which makes them difficult to be used to deal with large-scale datasets. Here, we design and develop a depth generation model named Gaussian mixture adversarial autoencoders (scGMAAE), assuming that the low-dimensional embedding of different types of cells follows different Gaussian distributions, integrating Bayesian variational inference and adversarial training, as to give the interpretable latent representation of complex data and discover the statistical distribution of different types of cells. The scGMAAE is provided with good controllability, interpretability and scalability. Therefore, it can process large-scale datasets in a short time and give competitive results. scGMAAE outperforms existing methods in several ways, including dimensionality reduction visualization, cell clustering, differential expression analysis and batch effect removal. Importantly, compared with most deep learning methods, scGMAAE requires less iterations to generate the best results.

Single-cell transcriptomics of peripheral blood in the aging mouse

Compositional and transcriptional changes in the hematopoietic system have been used as biomarkers of immunosenescence and aging. Here, we use single-cell RNA-sequencing to study the aging peripheral blood in mice and characterize the changes in cell-type composition and transcriptional profiles associated with age. We identified 17 clusters from a total of 14,588 single cells. We detected a general upregulation of antigen processing and presentation and chemokine signaling pathways and a downregulation of genes involved in ribosome pathways with age. In old peripheral blood, we also observed an increased percentage of cells expressing senescence markers (Cdkn1a, and Cdkn2a). In addition, we detected a cluster of activated T cells exclusively found in old blood, with lower expression of Cd28 and higher expression of Bcl2 and Cdkn2a, suggesting that the cells are senescent and resistant to apoptosis.

HUSCH: an integrated single-cell transcriptome atlas for human tissue gene expression visualization and analyses

Understanding gene expression patterns across different human cell types is crucial for investigating mechanisms of cell type differentiation, disease occurrence and progression. The recent development of single-cell RNA-seq (scRNA-seq) technologies significantly boosted the characterization of cell type heterogeneities in different human tissues. However, the huge number of datasets in the public domain also posed challenges in data integration and reuse. We present Human Universal Single Cell Hub (HUSCH, http://husch.comp-genomics.org), an atlas-scale curated database that integrates single-cell transcriptomic profiles of nearly 3 million cells from 185 high-quality human scRNA-seq datasets from 45 different tissues. All the data in HUSCH were uniformly processed and annotated with a standard workflow. In the single dataset module, HUSCH provides interactive gene expression visualization, differentially expressed genes, functional analyses, transcription regulators and cell-cell interaction analyses for each cell type cluster. Besides, HUSCH integrated different datasets in the single tissue module and performs data integration, batch correction, and cell type harmonization. This allows a comprehensive visualization and analysis of gene expression within each tissue based on single-cell datasets from multiple sources and platforms. HUSCH is a flexible and comprehensive data portal that enables searching, visualizing, analyzing, and downloading single-cell gene expression for the human tissue atlas.

Single-cell profiling identifies ACE+ granuloma macrophages as a nonpermissive niche for intracellular bacteria during persistent Salmonella infection

Macrophages mediate key antimicrobial responses against intracellular bacterial pathogens, such as Salmonella enterica. Yet, they can also act as a permissive niche for these pathogens to persist in infected tissues within granulomas, which are immunological structures composed of macrophages and other immune cells. We apply single-cell transcriptomics to investigate macrophage functional diversity during persistent S. enterica serovar Typhimurium (STm) infection in mice. We identify determinants of macrophage heterogeneity in infected spleens and describe populations of distinct phenotypes, functional programming, and spatial localization. Using an STm mutant with impaired ability to polarize macrophage phenotypes, we find that angiotensin-converting enzyme (ACE) defines a granuloma macrophage population that is nonpermissive for intracellular bacteria, and their abundance anticorrelates with tissue bacterial burden. Disruption of pathogen control by neutralizing TNF is linked to preferential depletion of ACE+ macrophages in infected tissues. Thus, ACE+ macrophages have limited capacity to serve as cellular niche for intracellular bacteria to establish persistent infection.

Tumor infiltrating lymphocytes as an endpoint in cancer vaccine trials

Checkpoint inhibitors have invigorated cancer immunotherapy research, including cancer vaccination. Classic early phase trial design and endpoints used in developing chemotherapy are not suited for evaluating all forms of cancer treatment. Peripheral T cell response dynamics have demonstrated inconsistency in assessing the efficacy of cancer vaccination. Tumor infiltrating lymphocytes (TILs), reflect the local tumor microenvironment and may prove a superior endpoint in cancer vaccination trials. Cancer vaccines may also promote success in combination immunotherapy treatment of weakly immunogenic tumors. This review explores the impact of TILs as an endpoint for cancer vaccination in multiple malignancies, summarizes the current literature regarding TILs analysis, and discusses the challenges of providing validity and a standardized implementation of this approach.

The evolutionary and functional significance of germline immunoglobulin gene variation

The recombination between immunoglobulin (IG) gene segments determines an individual's naïve antibody repertoire and, consequently, (auto)antigen recognition. Emerging evidence suggests that mammalian IG germline variation impacts humoral immune responses associated with vaccination, infection, and autoimmunity - from the molecular level of epitope specificity, up to profound changes in the architecture of antibody repertoires. These links between IG germline variants and immunophenotype raise the question on the evolutionary causes and consequences of diversity within IG loci. We discuss why the extreme diversity in IG loci remains a mystery, why resolving this is important for the design of more effective vaccines and therapeutics, and how recent evidence from multiple lines of inquiry may help us do so.

Canine peripheral blood TCRαβ T cell atlas: Identification of diverse subsets including CD8A+ MAIT-like cells by combined single-cell transcriptome and V(D)J repertoire analysis

The dog is valued as a companion animal and increasingly recognized as a model for human disorders. Given the importance of T cells in health and disease, comprehensive knowledge of canine T cells can contribute to our understanding of pathogenesis mechanisms and inform the development of new treatment strategies. However, the diversity of canine T cells is still poorly understood mainly due to the lack of species-reactive antibodies for use in flow cytometry. The aim of this study was to generate a detailed atlas of peripheral blood TCRαβ⁺ T cells of healthy dogs using single-cell RNA-sequencing (scRNAseq) combined with immune repertoire sequencing. A total of 22 TCRαβ⁺ T cell clusters were identified, which were classified into three major groups: CD4-dominant (11 clusters), CD8A-dominant (8 clusters), and CD4/CD8A-mixed (3 clusters). Based on differential gene expression, distinct differentiation states (naïve, effector, memory, exhausted) and lineages (e.g. CD4 T helper and regulatory T cells) could be distinguished. Importantly, several T cell populations were identified, which have not been described in dogs before. Of particular note, our data provide first evidence for the existence of canine mucosa-associated invariant T cell (MAIT)-like cells, representing one of three newly identified FCER1G⁺ innate-like CD8A⁺ T cell populations in the peripheral blood of healthy dogs. In conclusion, using scRNAseq combined with immune repertoire sequencing we were able to resolve canine TCRαβ⁺ T cell populations at unprecedented resolution. The peripheral blood TCRαβ⁺ T cell atlas of healthy dogs generated here represents an important reference data set for future studies and is of relevance for identifying new targets for T cell-specific therapies.

Innate Immune Memory in Macrophages

Macrophages have been recognized as the primary mediators of innate immunity starting from embryonic/fetal development. Macrophage-mediated defenses may not be as antigen-specific as adaptive immunity, but increasing information suggests that these responses do strengthen with repeated immunological triggers. The concept of innate memory in macrophages has been described as "trained immunity" or "innate immune memory (IIM)." As currently understood, this cellular memory is rooted in epigenetic and metabolic reprogramming. The recognition of IIM may be particularly important in the fetus and the young neonate who are yet to develop protective levels of adaptive immunity, and could even be of preventive/therapeutic importance in many disorders. There may also be a possibility of therapeutic enhancement with targeted vaccination. This article presents a review of the properties, mechanisms, and possible clinical significance of macrophage-mediated IIM.

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.

From immune equilibrium to immunodynamics

Objective

The immunology field has long been short of a universally applicable theoretical model that can quantitatively describe the immune response, and the theory of immune equilibrium (balance) is usually limited to the interpretation of the philosophical significance of immune phenomena. Therefore, it is necessary to establish a new immunological theory, namely, immunodynamic theory, to reanalyze the immune response.

Methods

By quantifying the immune dynamic equilibrium as the ratio of positive and negative immune power, the immune dynamic equilibrium equation was established. Then, the area under the curve of the positive and negative immune power was assumed to be equal in the whole process of immune response (regardless of correct or not), and through thought experiments based on this key hypothesis, a series of new concepts and expressions were derived, to establish a series of immunodynamic equations.

Results

New concepts of immune force and immune braking force and their expression equations, namely, the theoretical equations of immunodynamics, were derived through thought experiments, and the theoretical curves of immunodynamics were obtained according to these equations. Via the equivalent transformation of the theoretical equations and practical calculation of functional data, and by the methods of curve comparison and fitting, some practical equations of immunodynamics were established, and these practical equations were used to solve theoretical and practical problems that are related to the immunotherapy of infectious diseases and cancers.

Conclusion

The traditional theory of immune equilibrium has been mathematized and transformed from a philosophical category into a new concrete scientific theory, namely the theory of immunodynamics, which solves the dilemma that the traditional theory cannot guide individualized medical practice for a long time. This new theory may develop into one of the core theories of immunology in the future.

Single-Cell Sequencing Reveals the Regulatory Role of Maresin1 on Neutrophils during Septic Lung Injury

Acute lung injury (ALI) is the most common type of organ injury in sepsis, with high morbidity and mortality. Sepsis is characterized by an inappropriate inflammatory response while neutrophils exert an important role in the excessive inflammatory response. The discovery of specialized pro-resolving mediators (SPMs) provides a new direction for the treatment of a series of inflammatory-related diseases including sepsis. Among them, the regulation of Maresin1 on immune cells was widely demonstrated. However, current research on the regulatory effects of Maresin1 on immune cells has remained at the level of certain cell types. Under inflammatory conditions, the immune environment is complex and immune cells exhibit obvious heterogeneity. Neutrophils play a key role in the occurrence and development of septic lung injury. Whether there is a subpopulation bias in the regulation of neutrophils by Maresin1 has not been elucidated. Therefore, with the well-established cecal ligation and puncture (CLP) model and single-cell sequencing technology, our study reveals for the first time the regulatory mechanism of Maresin1 on neutrophils at the single-cell level. Our study suggested that Maresin1 can significantly reduce neutrophil infiltration in septic lung injury and that this regulatory effect is more concentrated in the Neutrophil-Cxcl3 subpopulation. Maresin1 can significantly reduce the infiltration of the Neutrophil-Cxcl3 subpopulation and inhibit the expression of related inflammatory genes and key transcription factors in the Neutrophil-Cxcl3 subpopulation. Our study provided new possibilities for specific modulation of neutrophil function in septic lung injury.

CD8+ T cell metabolic rewiring defined by scRNA-seq identifies a critical role of ASNS expression dynamics in T cell differentiation

T cells dynamically rewire their metabolism during an immune response. We applied single-cell RNA sequencing to CD8⁺ T cells activated and differentiated in vitro in physiological medium to resolve these metabolic dynamics. We identify a differential time-dependent reliance of activating T cells on the synthesis versus uptake of various non-essential amino acids, which we corroborate with functional assays. We also identify metabolic genes that potentially dictate the outcome of T cell differentiation, by ranking them based on their expression dynamics. Among them, we find asparagine synthetase (Asns), whose expression peaks for effector T cells and decays toward memory formation. Disrupting these expression dynamics by ASNS overexpression promotes an effector phenotype, enhancing the anti-tumor response of adoptively transferred CD8⁺ T cells in a mouse melanoma model. We thus provide a resource of dynamic expression changes during CD8⁺ T cell activation and differentiation, and identify ASNS expression dynamics as a modulator of CD8⁺ T cell differentiation.

Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material

Background

Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.

Results

We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.

Conclusion

We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.

Integrating bulk and single-cell sequencing reveals the phenotype-associated cell subpopulations in sepsis-induced acute lung injury

The dysfunctional immune response and multiple organ injury in sepsis is a recurrent theme impacting prognosis and mortality, while the lung is the first organ invaded by sepsis. To systematically elucidate the transcriptomic changes in the main constituent cells of sepsis-injured lung tissue, we applied single-cell RNA sequencing to the lung tissue samples from septic and control mice and created a comprehensive cellular landscape with 25044 cells, including 11317 immune and 13727 non-immune cells. Sepsis alters the composition of all cellular compartments, particularly neutrophils, monocytes, T cells, endothelial, and fibroblasts populations. Our study firstly provides a single-cell view of cellular changes in septic lung injury. Furthermore, by integrating bulk sequencing data and single-cell data with the Scissors-method, we identified the cell subpopulations that are most associated with septic lung injury phenotype. The phenotypic-related cell subpopulations identified by Scissors-method were consistent with the cell subpopulations with significant composition changes. The function analysis of the differentially expressed genes (DEGs) and the cell-cell interaction analysis further reveal the important role of these phenotype-related subpopulations in septic lung injury. Our research provides a rich resource for understanding cellular changes and provides insights into the contributions of specific cell types to the biological processes that take place during sepsis-induced lung injury.

T cell Repertoire Profiling and the Mechanism by which HLA-B27 Causes Ankylosing Spondylitis

Purpose of Review

Ankylosing spondylitis (AS) is strongly associated with the HLA-B27 gene. The canonical function of HLA-B27 is to present antigenic peptides to CD8 lymphocytes, leading to adaptive immune responses. The ‘arthritogenic peptide’ theory as to the mechanism by which HLA-B27 induces ankylosing spondylitis proposes that HLA-B27 presents peptides derived from exogenous sources such as bacteria to CD8 lymphocytes, which subsequently cross-react with antigens at the site of inflammation of the disease, causing inflammation. This review describes findings of studies in AS involving profiling of T cell expansions and discusses future research opportunities based on these findings.

Recent Findings

Consistent with this theory, there is an expanding body of data showing that expansion of a restricted pool of CD8 lymphocytes is found in most AS patients yet only in a small proportion of healthy HLA-B27 carriers.

Summary

These exciting findings strongly support the theory that AS is driven by presentation of antigenic peptides to the adaptive immune system by HLA-B27. They point to new potential approaches to identify the exogenous and endogenous antigens involved and to potential therapies for the disease.

Long-range phasing of dynamic, tissue-specific and allele-specific regulatory elements

Epigenomic maps identify gene regulatory elements by their chromatin state. However, prevailing short-read sequencing methods cannot effectively distinguish alleles, evaluate the interdependence of elements in a locus or capture single-molecule dynamics. Here, we apply targeted nanopore sequencing to profile chromatin accessibility and DNA methylation on contiguous ~100-kb DNA molecules that span loci relevant to development, immunity and imprinting. We detect promoters, enhancers, insulators and transcription factor footprints on single molecules based on exogenous GpC methylation. We infer relationships among dynamic elements within immune loci, and order successive remodeling events during T cell stimulation. Finally, we phase primary sequence and regulatory elements across the H19/IGF2 locus, uncovering primate-specific features. These include a segmental duplication that stabilizes the imprinting control region and a noncanonical enhancer that drives biallelic IGF2 expression in specific contexts. Our study advances emerging strategies for phasing gene regulatory landscapes and reveals a mechanism that overrides IGF2 imprinting in human cells.

cGAS/STING and innate brain inflammation following acute high-fat feeding

Obesity, prediabetes, and diabetes are growing in prevalence worldwide. These metabolic disorders are associated with neurodegenerative diseases, particularly Alzheimer's disease and Alzheimer's disease related dementias. Innate inflammatory signaling plays a critical role in this association, potentially via the early activation of the cGAS/STING pathway. To determine acute systemic metabolic and inflammatory responses and corresponding changes in the brain, we used a high fat diet fed obese mouse model of prediabetes and cognitive impairment. We observed acute systemic changes in metabolic and inflammatory responses, with impaired glucose tolerance, insulin resistance, and alterations in peripheral immune cell populations. Central inflammatory changes included microglial activation in a pro-inflammatory environment with cGAS/STING activation. Blocking gap junctions in neuron-microglial co-cultures significantly decreased cGAS/STING activation. Collectively these studies suggest a role for early activation of the innate immune system both peripherally and centrally with potential inflammatory crosstalk between neurons and glia.

Understanding Mammalian Hair Follicle Ecosystems by Single-Cell RNA Sequencing

Simple Summary

Single-cell sequencing technology can reflect cell population heterogeneity at the single-cell level, leading to a better understanding of the role of individual cells in the microenvironment. Over the past few years, single-cell sequencing technology has not only made more new discoveries in the study of cellular heterogeneity of other rare cells such as stem cells, but has also become the most powerful research method for embryonic development, organ differentiation, cancer occurrence, and cell mapping. In this review, we outline the use of scRNA-seq in hair follicles. In particular, by focusing on landmark studies and the recent discovery of novel subpopulations of hair follicles, we summarize the phenotypic diversity of hair follicle cells and their links to hair follicle morphogenesis. Enhancing our understanding of the progress of hair follicle research will help to elucidate the regulatory mechanisms that determine the fate of different types of cells in the hair follicle, thereby guiding hair loss treatment and hair-producing economic animal breeding research.

Abstract

Single-cell sequencing technology can fully reflect the heterogeneity of cell populations at the single cell level, making it possible for us to re-recognize various tissues and organs. At present, the sequencing study of hair follicles is transiting from the traditional ordinary transcriptome level to the single cell level, which will provide diverse insights into the function of hair follicle cells. This review focuses on research advances in the hair follicle microenvironment obtained from scRNA-seq studies of major cell types in hair follicle development, with a special emphasis on the discovery of new subpopulations of hair follicles by single-cell techniques. We also discuss the problems and current solutions in scRNA-seq observation and look forward to its prospects.

Single cell RNA sequencing reveals hemocyte heterogeneity in Biomphalaria glabrata: Plasticity over diversity

The freshwater snail Biomphalaria glabrata is an intermediate host of Schistosoma mansoni, the agent of human intestinal schistosomiasis. However, much is to be discovered about its innate immune system that appears as a complex black box, in which the immune cells (called hemocytes) play a major role in both cellular and humoral response towards pathogens. Until now, hemocyte classification has been based exclusively on cell morphology and ultrastructural description and depending on the authors considered from 2 to 5 hemocyte populations have been described. In this study, we proposed to evaluate the hemocyte heterogeneity at the transcriptomic level. To accomplish this objective, we used single cell RNA sequencing (scRNAseq) technology coupled to a droplet-based system to separate hemocytes and analyze their transcriptome at a unique cell level in naive Biomphalaria glabrata snails. We were able to demonstrate the presence of 7 hemocyte transcriptomic populations defined by the expression of specific marker genes. As a result, scRNAseq approach showed a high heterogeneity within hemocytes, but provides a detailed description of the different hemocyte transcriptomic populations in B. glabrata supported by distinct cellular functions and lineage trajectory. As a main result, scRNAseq revealed the 3 main population as a super-group of hemocyte diversity but, on the contrary, a great hemocytes plasticity with a probable capacity of hemocytes to engage to different activation pathways. This work opens a new field of research to understand the role of hemocytes particularly in response to pathogens, and towards S. mansoni parasites.

Identification of differently expressed mRNAs by peripheral blood mononuclear cells in Vogt-Koyanagi-Harada disease

Vogt-Koyanagi-Harada disease (VKH) is a rare autoimmune disease characterized by diffuse and bilateral uveitis, alopecia, tinnitus, hearing loss, vitiligo and headache. The transcriptional expression pattern of peripheral blood mononuclear cells (PBMC) in VKH remains largely unknown. In this study, mRNA sequencing was conducted in PBMC from VKH patients with active uveitis before treatment (n = 7), the same patients after prednisone combined with cyclosporine treatment (n = 7) and healthy control subjects strictly matched with gender and age (n = 7). We found 118 differentially expressed genes (DEGs) between VKH patients and healthy control subjects, and 21 DEGs between VKH patients before and after treatment. TRIB1 was selected as a potential biomarker to monitor the development of VKH according to the mRNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to predict the possible biological functions and signaling pathways of DEGs. Neutrophil degranulation, peptidase regulator activity, secretory granule membrane, cellular response to peptide, growth factor binding and cell projection membrane were enriched as GO annotations of DEGs. Arachidonic acid metabolism and mitogen-activated protein kinase (MAPK) signaling pathway were potential signaling pathways involved in pathogenesis and drug response of VKH. A protein–protein interaction (PPI) network was constructed by STRING, and colony stimulating factor 1 receptor (CSF1R) was identified as the hubgene of all DEGs by Cytoscape. The cell type presumed to contribute to the aberrant expression of DEGs was analyzed with the use of publicly available single-cell sequencing data of PBMC from a healthy donor and single-cell sequencing dataset of monocytes from VKH patients. Our findings may help to decipher the underlying cellular and molecular pathogenesis of VKH and may lead novel therapeutic applications.

High-throughput imaging of mRNA at the single-cell level in human primary immune cells

Measurement of gene expression at the single-cell level has advanced the study of transcriptional regulation programs in healthy and disease states. In particular, single-cell approaches have shed light on the high level of transcriptional heterogeneity of individual cells, both at baseline and in response to experimental or environmental perturbations. We have developed a method for high-content imaging (HCI)-based quantification of relative changes in transcript abundance at the single-cell level in human primary immune cells and have validated its performance under multiple experimental conditions to demonstrate its general applicability. This method, named hcHCR, combines the sensitivity of the hybridization chain reaction (HCR) for the visualization of RNA in single cells, with the speed, scalability, and reproducibility of HCI. We first tested eight cell attachment substrates for short-term culture of primary human B cells, T cells, monocytes, or neutrophils. We then miniaturized HCR in 384-well format and documented the ability of the method to detect changes in transcript abundance at the single-cell level in thousands of cells for each experimental condition by HCI. Furthermore, we demonstrated the feasibility of multiplexing gene expression measurements by simultaneously assaying the abundance of three transcripts per cell at baseline and in response to an experimental stimulus. Finally, we tested the robustness of the assay to technical and biological variation. We anticipate that hcHCR will be suitable for low- to medium-throughput chemical or functional genomics screens in primary human cells, with the possibility of performing screens on cells obtained from patients with a specific disease.

Distinctive populations of CD4+T cells associated with vaccine efficacy

Memory T cells underpin vaccine-induced immunity but are not yet fully understood. To distinguish features of memory cells that confer protective immunity, we used single cell transcriptome analysis to compare antigen-specific CD4⁺T cells recalled to lungs of mice that received a protective or nonprotective subunit vaccine followed by challenge with a fungal pathogen. We unexpectedly found populations specific to protection that expressed a strong type I interferon response signature, whose distinctive transcriptional signature appeared unconventionally dependent on IFN-γ receptor. We also detected a unique population enriched in protection that highly expressed the gene for the natural killer cell marker NKG7. Lastly, we detected differences in TCR gene use and in Th1- and Th17-skewed responses after protective and nonprotective vaccine, respectively, reflecting heterogeneous Ifng- and Il17a-expressing populations. Our findings highlight key features of transcriptionally diverse and distinctive antigen-specific T cells associated with protective vaccine-induced immunity.

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Protective and nonprotective vaccines generate distinct T cells in fungal infection

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A strong type I interferon signal is seen among CD4 T cells in protective immunity

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Th1 bias is seen with protective immunity; Th17 bias with nonprotective immunity

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Nkg7-expressing CD4 T cells are enriched in protective immunity

Impact of single-cell RNA sequencing on understanding immune regulation

Single‐cell RNA sequencing (scRNA‐seq), one of the most powerful technologies, can describe the transcriptomic heterogeneity of single cells and reveal previously unreported cell types or states in complex tissues. With the rapid development of scRNA‐seq, it has renewed our view of cellular heterogeneity and its significance for deeply understanding cell development and function. There are a large number of studies applying scRNA‐seq to investigate the heterogeneity of immune cells and disease pathogenesis, focusing on differences among every individual cell, which have provided novel inspiration for disease therapy and biological processes. In this review, we describe the development of scRNA‐seq and its application in immune‐related physiological states, regulatory mechanisms and diseases. In addition, we further discuss the opportunities and challenges of scRNA‐seq in immune regulation.

New Insights into Cerebral Vessel Disease Landscapes at Single-Cell Resolution: Pathogenetic and Therapeutic Perspectives

Cerebrovascular diseases are a leading cause of death and disability globally. The development of new therapeutic targets for cerebrovascular diseases (e.g., ischemic, and hemorrhagic stroke, vascular dementia) is limited by a lack of knowledge of the cellular and molecular biology of health and disease conditions and the factors that cause injury to cerebrovascular structures. Here, we describe the role of advances in omics technology, particularly RNA sequencing, in studying high-dimensional, multifaceted profiles of thousands of individual blood and vessel cells at single-cell resolution. This analysis enables the dissection of the heterogeneity of diseased cerebral vessels and their atherosclerotic plaques, including the microenvironment, cell evolutionary trajectory, and immune response pathway. In animal models, RNA sequencing permits the tracking of individual cells (including immunological, endothelial, and vascular smooth muscle cells) that compose atherosclerotic plaques and their alteration under experimental settings such as phenotypic transition. We describe how single-cell RNA transcriptomics in humans allows mapping to the molecular and cellular levels of atherosclerotic plaques in cerebral arteries, tracking individual lymphocytes and macrophages, and how these data can aid in identifying novel immune mechanisms that could be exploited as therapeutic targets for cerebrovascular diseases. Single-cell multi-omics approaches will likely provide the unprecedented resolution and depth of data needed to generate clinically relevant cellular and molecular signatures for the precise treatment of cerebrovascular diseases.

Benchmarking computational methods for B-cell receptor reconstruction from single-cell RNA-seq data

Multiple methods have recently been developed to reconstruct full-length B-cell receptors (BCRs) from single-cell RNA sequencing (scRNA-seq) data. This need emerged from the expansion of scRNA-seq techniques, the increasing interest in antibody-based drug development and the importance of BCR repertoire changes in cancer and autoimmune disease progression. However, a comprehensive assessment of performance-influencing factors such as the sequencing depth, read length or number of somatic hypermutations (SHMs) as well as guidance regarding the choice of methodology is still lacking. In this work, we evaluated the ability of six available methods to reconstruct full-length BCRs using one simulated and three experimental SMART-seq datasets. In addition, we validated that the BCRs assembled in silico recognize their intended targets when expressed as monoclonal antibodies. We observed that methods such as BALDR, BASIC and BRACER showed the best overall performance across the tested datasets and conditions, whereas only BASIC demonstrated acceptable results on very short read libraries. Furthermore, the de novo assembly-based methods BRACER and BALDR were the most accurate in reconstructing BCRs harboring different degrees of SHMs in the variable domain, while TRUST4, MiXCR and BASIC were the fastest. Finally, we propose guidelines to select the best method based on the given data characteristics.

Single-Cell RNA Sequencing for Analyzing the Intestinal Tract in Healthy and Diseased Individuals

The intestinal tract is composed of different cell lineages with distinct functions and gene expression profiles, providing uptake of nutrients and protection against insults to the gut lumen. Changes in or damage to the cellulosity or local environment of the intestinal tract can cause various diseases. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for profiling and analyzing individual cell data, making it possible to resolve rare and intermediate cell states that are hardly observed at the bulk level. In this review, we discuss the application of intestinal tract scRNA-seq in identifying novel cell subtypes and states, targets, and explaining the molecular mechanisms involved in intestinal diseases. Finally, we provide future perspectives on using single-cell techniques to discover molecular and cellular targets and biomarkers as a new approach for developing novel therapeutics for intestinal diseases.

Exploring mechanisms of Chaihu-Shugan-San against liver fibrosis by integrated multi-omics and network pharmacology approach

Chaihu-Shugan-San (CHSGS), a noted traditional Chinese medicine formula, has been used as a complementary and alternative therapy for liver fibrosis. However, the antifibrotic mechanisms of CHSGS still remain unclear. Thus, we used network pharmacology approach in combination with single cell and bulk transcriptomics to elucidate the antifibrotic mechanisms of CHSGS. We first screened out 134 bioactive ingredients of CHSGS through the defined criteria. Then, 1,150 genes were predicted to be targets for CHSGS, while 625 liver fibrosis-associated genes were identified by single cell transcriptomics analysis. Next, 71 intersecting genes of CHSGS and liver fibrosis were defined as the therapeutic targets in CHSGS against liver fibrosis. Further, 21 core targets and 12 core ingredients of CHSGS against liver fibrosis were also identified. Meanwhile, enrichment analyses of core targets highlighted that the key mechanisms of CHSGS against liver fibrosis include modulation of inflammation responses, inhibition of angiogenesis, and regulation of ECM remodeling, of which the most important mechanism was the regulation of ECM remodeling. The molecular docking simulation validated strong binding affinity between the core targets and core ingredients. Furthermore, 62-gene signature may be used for determining the prognosis in cirrhotic patients based on the results of ssGSEA-Cox analysis. In conclusion, this study revealed the multiple pharmacological targets and therapeutic mechanisms of CHSGS against liver fibrosis, which may thus serve as an effective antifibrotic therapy. Meanwhile, CHSGS may improve survival of patients with liver cirrhosis by the interaction of 62-gene signature.

Multi-tissue scRNA-seq reveals immune cell landscape of turbot (Scophthalmus maximus)

In vertebrates, bony fishes possess not only innate immune cells but also T and B cells that are equivalent to those in mammals. However, the precise sub-cluster of immune cells in teleost fish remains largely unknown. Herein, we developed a dynamic bacterial infection model in turbot (Scophthalmus maximus) and created a fish immune cell landscape (FICL) for a primary lymphoid organ (head kidney), a secondary lymphoid organ (spleen), and barrier tissues (gills and posterior intestine). Moreover, through comprehensive characterization of the expression profiles of 16 clusters, including dendritic cells-like (DCs-like), macrophages (MΦs), neutrophils, NK cells, as well as 12 sub-clusters of T and B cells, we found that CD8+ CTLs, CD4-CD8- T, Th17 and ILC3-2 like cells possess a bifunctional role associated with cytotoxicity and immunoregulation during bacterial infection. To our knowledge, these results could provide a useful resource for a better understanding of immune cells in teleost fish and could act as a comprehensive knowledge base for assessing the evolutionary mechanism of adaptive immunity in vertebrates.

Frontiers in single cell analysis: multimodal technologies and their clinical perspectives

Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.

Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons

Despite the fact that proteins carry out nearly all cellular functions and mark the differences of cells, the existing single-cell tools can only analyze dozens of proteins, a scale far from full characterization of cells and tissue yet. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology that affords the comprehensive functional proteome profiling of single cells. We demonstrate the technology by detecting 182 proteins that include surface markers, neuron function proteins, neurodegeneration markers, signaling pathway proteins, and transcription factors. Further studies on cells derived from the 5XFAD mice, an Alzheimer's Disease (AD) model, validate the utility of our technology and reveal the deep heterogeneity of brain cells. Through comparison with control mouse cells, we have identified differentially expressed proteins in AD pathology. Our technology could offer new insights into cell machinery and thus may advance many fields including drug discovery, molecular diagnostics, and clinical studies.

Spatial transcriptomics identifies enriched gene expression and cell types in human liver fibrosis

Liver fibrosis and cirrhosis have limited therapeutic options and represent a serious unmet patient need. Recent use of single‐cell RNA sequencing (scRNAseq) has identified enriched cell types infiltrating cirrhotic livers but without defining the microanatomical location of these lineages thoroughly. To assess whether fibrotic liver regions specifically harbor enriched cell types, we explored whether whole‐tissue spatial transcriptomics combined with scRNAseq and gene deconvolution analysis could be used to localize cell types in cirrhotic explants of patients with end‐stage liver disease (total n = 8; primary sclerosing cholangitis, n = 4; primary biliary cholangitis, n = 2, alcohol‐related liver disease, n = 2). Spatial transcriptomics clearly identified tissue areas of distinct gene expression that strongly correlated with the total area (Spearman r = 0.97, p = 0.0004) and precise location (parenchyma, 87.9% mean congruency; range, 73.1%–97.1%; fibrosis, 68.5% mean congruency; range, 41.0%–91.7%) of liver regions classified as parenchymal or fibrotic by conventional histology. Deconvolution and enumeration of parenchymal and fibrotic gene content as measured by spatial transcriptomics into distinct cell states revealed significantly higher frequencies of ACTA2+ FABP4+ and COL3A1+ mesenchymal cells, IL17RA+ S100A8+ and FCER1G+ tissue monocytes, VCAM1+ SDC3+ Kupffer cells, CCL4+ CCL5+ KLRB1+ and GZMA+ IL17RA+ T cells and HLA‐DR+, CD37+ CXCR4+ and IGHM+ IGHG+ B cells in fibrotic liver regions compared with parenchymal areas of cirrhotic explants. Conclusion: Our findings indicate that spatial transcriptomes of parenchymal and fibrotic liver regions express unique gene content within cirrhotic liver and demonstrate proof of concept that spatial transcriptomes combined with additional RNA sequencing methodologies can refine the localization of gene content and cell lineages in the search for antifibrotic targets.

IgE-Mediated food allergy: Current diagnostic modalities and novel biomarkers with robust potential

Food allergy (FA) is a serious public health issue afflicting millions of people globally, with an estimated prevalence ranging from 1-10%. Management of FA is challenging due to overly restrictive diets and the lack of diagnostic approaches with high accuracy and prediction. Although measurement of serum-specific antibodies combined with patient medical history and skin prick test is a useful diagnostic tool, it is still an imprecise predictor of clinical reactivity with a high false-positive rate. The double-blind placebo-controlled food challenge represents the gold standard for FA diagnosis; however, it requires large healthcare and involves the risk of acute onset of allergic reactions. Improvement in our understanding of the molecular mechanism underlying allergic disease pathology, development of omics-based methods, and advances in bioinformatics have boosted the generation of a number of robust diagnostic biomarkers of FA. In this review, we discuss how traditional diagnostic modalities guide appropriate diagnosis and management of FA in clinical practice, as well as uncover the potential of the latest biomarkers for the diagnosis, monitoring, and prediction of FA. We also raise perspectives for precise and targeted medical intervention to fill the gap in the diagnosis of FA.

Intensive single-cell analysis reveals immune-cell diversity among healthy individuals

Immune responses are different between individuals and personal health histories and unique environmental conditions should collectively determine the present state of immune cells. However, the molecular systems underlying such heterogeneity remain elusive. Here, we conducted a systematic time-lapse single-cell analysis, using 171 single-cell libraries and 30 mass cytometry datasets intensively for seven healthy individuals. We found substantial diversity in immune-cell profiles between different individuals. These patterns showed daily fluctuations even within the same individual. Similar diversities were also observed for the T-cell and B-cell receptor repertoires. Detailed immune-cell profiles at healthy statuses should give essential background information to understand their immune responses, when the individual is exposed to various environmental conditions. To demonstrate this idea, we conducted the similar analysis for the same individuals on the vaccination of influenza and SARS-CoV-2. In fact, we detected distinct responses to vaccines between individuals, although key responses are common. Single-cell immune-cell profile data should make fundamental data resource to understand variable immune responses, which are unique to each individual.

A universal deep neural network for in-depth cleaning of single-cell RNA-Seq data

Single cell RNA sequencing (scRNA-Seq) is being widely used in biomedical research and generated enormous volume and diversity of data. The raw data contain multiple types of noise and technical artifacts, which need thorough cleaning. Existing denoising and imputation methods largely focus on a single type of noise (i.e., dropouts) and have strong distribution assumptions which greatly limit their performance and application. Here we design and develop the AutoClass model, integrating two deep neural network components, an autoencoder, and a classifier, as to maximize both noise removal and signal retention. AutoClass is distribution agnostic as it makes no assumption on specific data distributions, hence can effectively clean a wide range of noise and artifacts. AutoClass outperforms the state-of-art methods in multiple types of scRNA-Seq data analyses, including data recovery, differential expression analysis, clustering analysis, and batch effect removal. Importantly, AutoClass is robust on key hyperparameter settings including bottleneck layer size, pre-clustering number and classifier weight. We have made AutoClass open source at: https://github.com/datapplab/AutoClass .

Evaluation of Immune Infiltration Based on Image Plus Helps Predict the Prognosis of Stage III Gastric Cancer Patients with Significantly Different Outcomes in Northeastern China

Gastric cancer (GC) might have significantly different outcomes within the same AJCC/UICC-TNM stage. The purpose of this study is to help predict the different prognosis through the pattern of immune cell infiltration. We retrospectively analyzed 2605 patients who underwent radical gastrectomy in the Harbin Medical University Cancer Hospital between 2002 and 2013. For stage III with significantly different survival probability, we analyzed the relationship between immune cell surface antigen and survival in TCGA dataset. Furthermore, 200 cases in stage III GC with different survival outcomes were randomly selected for immunohistochemical verification. Image Plus software was used to evaluate the area of immune cell infiltration. We found that patients in stage III had significantly different outcomes. Bioinformatics analysis showed that there was a significant negative correlation between the expression of immune cell surface antigen and prognosis. In order to investigate whether immune infiltration can distinguish GC patients in stage III with differences in prognosis, we verified by immunohistochemistry that CD4+ T cells, CD20+ B cells, and CD177+ neutrophils infiltrated more in group B with better prognosis; CD8+ T cells, CD68+ macrophages, and CD117+ mast cells infiltrated more in group A with poor prognosis. CD117+ mast cells have the same trend of predicting significance for prognosis in the RNA and protein levels. In conclusion, patients with GC in northeastern China have significant prognostic differences only in stage III. CD117+ mast cells may be important evaluation factors in further studies of Immunoscore.

Single-cell transcriptomics reveals distinct effector profiles of infiltrating T cells in lupus skin and kidney

Cutaneous lupus is commonly present in patients with systemic lupus erythematosus (SLE). T cells have been strongly suspected to contribute to the pathology of cutaneous lupus, yet our understanding of the relevant T cell phenotypes and functions remains incomplete. Here, we present a detailed single-cell RNA sequencing profile of T and NK cell populations present within lesional and non-lesional skin biopsies of patients with cutaneous lupus. T cells across clusters from lesional and non-lesional skin biopsies expressed elevated levels of interferon-simulated genes (ISGs); however, compared to T cells from control skin, T cells from cutaneous lupus lesions did not show elevated expression profiles of activation, cytotoxicity, or exhaustion. Integrated analyses indicated that skin lymphocytes appeared less activated and lacked the expanded cytotoxic populations prominent in lupus nephritis kidney T/NK cells. Comparison of skin T cells from lupus and systemic sclerosis skin biopsies further revealed an elevated ISG signature specific to cells from lupus biopsies. Overall, these data represent the first detailed transcriptomic analysis of the T and NK cells in cutaneous lupus at the single cell level and have enabled a cross-tissue comparison that highlights stark differences in composition and activation of T/NK cells in distinct tissues in lupus.

Single-cell immunology: Past, present, and future

The immune system is a complex, dynamic, and plastic ecosystem composed of multiple cell types that constantly sense and interact with their local microenvironment to protect from infection and maintain homeostasis. For over a century, great efforts and ingenuity have been applied to the characterization of immune cells and their microenvironments, but traditional marker-based and bulk technologies left key questions unanswered. In the past decade, the advent of single-cell genomic approaches has revolutionized our knowledge of the cellular and molecular makeup of the immune system. In this perspective, we outline the past, present, and future applications of single-cell genomics in immunology and discuss how the integration of multiomics at the single-cell level will pave the way for future advances in immunology research and clinical translation.

How Single-Cell Technologies Have Provided New Insights Into Atherosclerosis

The development of innovative single-cell technologies has allowed the high-dimensional transcriptomic and proteomic profiling of individual blood and tissue cells. Recent single-cell studies revealed a new cellular heterogeneity of atherosclerotic plaque tissue and allowed a better understanding of distinct immune functional states in the context of atherosclerosis. In this brief review, we describe how single-cell technologies have shed a new light on the cellular composition of atherosclerotic plaques, and their response to diet perturbations or genetic manipulation in mouse models of atherosclerosis. We discuss how single-cell RNA sequencing, cellular indexing of transcriptomes and epitopes by sequencing, transposase-accessible chromatin with high-throughput sequencing, and cytometry by time-of-flight platforms have empowered the identification of discrete immune, endothelial, and smooth muscle cell alterations in atherosclerosis progression and regression. Finally, we review how single-cell approaches have allowed mapping the cellular and molecular composition of human atherosclerotic plaques and the discovery of new immune alterations in plaques from patients with stroke.

Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain

A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues into single-cell suspensions. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression. Here, we demonstrate that use of enzymatic dissociation on brain tissue induces an aberrant ex vivo gene expression signature, most prominently in microglia, which is prevalent in published literature and can substantially confound downstream analyses. To address this issue, we present a rigorously validated protocol that preserves both in vivo transcriptional profiles and cell-type diversity and yield across tissue types and species. We also identify a similar signature in postmortem human brain single-nucleus RNA-sequencing datasets, and show that this signature is induced in freshly isolated human tissue by exposure to elevated temperatures ex vivo. Together, our results provide a methodological solution for preventing artifactual gene expression changes during fresh tissue digestion and a reference for future deeper analysis of the potential confounding states present in postmortem human samples.