Single-cell RNA Sequencing in Immunology

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Single-Cell Sequencing Combined with Transcriptome Sequencing Constructs a Predictive Model of Key Genes in Multiple Sclerosis and Explores Molecular Mechanisms Related to Cellular Communication

Background

Multiple sclerosis (MS) causes chronic inflammation and demyelination of the central nervous system and comprises a class of neurodegenerative diseases in which interactions between multiple immune cell types mediate the involvement of MS development. However, the early diagnosis and treatment of MS remain challenging.

Methods

Gene expression profiles of MS patients were obtained from the Gene Expression Omnibus (GEO) database. Single-cell and intercellular communication analyses were performed to identify candidate gene sets. Predictive models were constructed using LASSO regression. Relationships between genes and immune cells were analyzed by single sample gene set enrichment analysis (ssGSEA). The molecular mechanisms of key genes were explored using gene enrichment analysis. An miRNA network was constructed to search for target miRNAs related to key genes, and related transcription factors were searched by transcriptional regulation analysis. We utilized the GeneCard database to detect the correlations between disease-regulated genes and key genes. We verified the mRNA expression of 4 key genes by reverse transcription-quantitative PCR (RT‒qPCR).

Results

Monocyte marker genes were selected as candidate gene sets. CD3D, IL2RG, MS4A6A, and NCF2 were found to be the key genes by LASSO regression. We constructed a prediction model with AUC values of 0.7569 and 0.719. The key genes were closely related to immune factors and immune cells. We explored the signaling pathways and molecular mechanisms involving the key genes by gene enrichment analysis. We obtained and visualized the miRNAs associated with the key genes using the miRcode database. We also predicted the transcription factors involved. We used validated key genes in MS patients, several of which were confirmed by RT‒qPCR.

Conclusion

The prediction model constructed with the CD3D, IL2RG, MS4A6A, and NCF2 genes has good diagnostic efficacy and provides new ideas for the diagnosis and treatment of MS.

Single-Cell RNA Sequencing Reveals Alterations in Patient Immune Cells with Pulmonary Long COVID-19 Complications

Since the emergence of the COVID-19 pandemic, the effects of SARS-CoV-2 have been extensively researched. While much is already known about the acute phase of the infection, increasing attention has turned to the prolonged symptoms experienced by a subset of individuals, commonly referred to as long COVID-19 patients. This study aims to delve deeper into the immune landscape of patients with prolonged symptoms by implementing single-cell mRNA analysis. A 71-year-old COVID-19 patient presenting with persistent viral pneumonia was recruited, and peripheral blood samples were taken at 3 and 2 years post-acute infection onset. Patients and control peripheral blood mononuclear cells (PBMCs) were isolated and single-cell sequenced. Immune cell population identification was carried out using the ScType script. Three months post-COVID-19 patients' PBMCs contained a significantly larger immature neutrophil population compared to 2-year and control samples. However, the neutrophil balance shifted towards a more mature profile after 18 months. In addition, a notable increase in the CD8+ NKT-like cells could be observed in the 3-month patient sample as compared to the later one and control. The subsequent change in these cell populations over time may be an indicator of an ongoing failure to clear the SARS-CoV-2 infection and, thus, lead to chronic COVID-19 complications.

Therapeutic Potential of Stem Cells in Natural Killer-Like B Cell-Associated Diseases

Stem cells are undifferentiated cells possessing a remarkable capacity to develop into multiple cell types. NKB cells, referred to "natural killer-like B cells," are recently identified subtype of B lymphocytes possessing characteristics that are similar to both natural killer (NK) cells and regular B lymphocytes. NK cells are lymphocyte-like in structure and cytotoxic in nature participating in the immediate immune response to the infected or malignant cells, whereas B lymphocytes produce antibodies and participate in adaptive immune response by binding to the specific antigen. The identification of NKB cells brings up new possibilities for studying and perhaps modulating immune responses in a variety of diseases, particularly those associated with microbial infections or inflammatory responses. Further, correlation of NKB cells with interleukins allows us to understand the molecular mechanism of diseases. Stem cell research offers a better understanding of NKB cell participation and provides new insights for novel treatment methods wherein mesenchymal stem cells (MSCs) have found to be the most promising stem cell showing positive outcomes in NKB cell-associated inflammatory diseases. Additionally, the perceptions acquired from researching NKB cells in diverse diseases leads to innovative treatment options, improving our capacity to control and cure immunological dysregulation-related ailments.

Single cell RNA sequencing – a valuable tool for cancer immunotherapy: a mini review

Single-cell RNA sequencing (scRNA-seq) technology has made great strides in research over the last decade. Data analysis has been aided by developments in bioinformatics tools and artificial intelligence, allowing biological and clinical researchers to get a deeper understanding of the different cell clusters and their dynamics within tumours. Combining conventional treatment modalities like chemotherapy and radiation with immunotherapy is a growing trend in cancer treatment. Hence, knowledge of the tumour microenvironment and the effect of each treatment modality on the TME, at a single cell level can provide treating clinicians with better clues for patient stratification and prognostication. With this knowledge, immunotherapy could become successful in treating a wide range of cancers, opening the path for the creation of even more effective treatment strategies. Despite the widespread availability of scRNA-seq technology, computational analysis and data interpretation are still challenges. Worldwide, such challenges are being addressed by various researchers, strengthening the contribution of this technology towards cancer elimination. In this mini-review, we primarily focus on the technique, its workflow, and the computational aspects of scRNA technology, along with an overview of the current challenges in the analysis and interpretation of the data generated.

Impact of delayed PBMC processing on functional and genomic assays

Peripheral blood mononuclear cells (PBMCs) are commonly isolated from whole blood samples in clinical trials. Isolated PBMCs can be cryopreserved for use in downstream assays such as flow cytometry, single-cell RNA sequencing (scRNA-seq) and enzyme-linked immunosorbent spot (ELISpot) assays to aid understanding of disease biology and treatment effects, and biomarker identification. However, due to logistical practicalities, delays from blood collection to PBMC processing may exceed 24 h, which can potentially affect PBMC function and, ultimately, downstream assay results. Whole blood samples from 20 healthy adults were collected and incubated at 20-25 °C for 2-48 h before PBMC processing. PBMC viability was measured, and flow cytometry immunophenotyping, scRNA-seq and ELISpot were performed following increasing PBMC processing delays. The RosetteSep™ granulocyte depletion kit was used to evaluate the impact of granulocyte contamination following processing delay. Processed scRNA-seq reads were used to identify cell clusters based on marker genes. scRNA-seq data was further used to determine gene expression correlation and pathway activity score in major PBMC cell types (T cells, B cells, natural killer cells, monocytes and dendritic cells) between PBMC preparations subjected to shorter (2-4 h) and longer (8-48 h) processing delays. ELISpot assays evaluated the impact of processing delays on the number of interferon-γ (IFN-γ) secreting cells from ex vivo stimulated PBMCs. PBMC viability was reduced after a 48-h processing delay. Flow cytometry showed that granulocyte contamination of PBMCs increased after 24 h. Cluster analysis of scRNA-seq data identified 23 immune cell type gene expression clusters that were not significantly changed upon granulocyte depletion. Gene expression correlations across the major PBMC cell types were < 0.8 after 24 h of delay compared with 2 or 4 h of delay. Inflammatory, proliferation and signaling pathway activities increased, whereas IFN-γ and metabolic pathway activities decreased with increasing PBMC processing delays. The number of IFN-γ secreting cells trended towards a reduction as PBMC processing delays increased. PBMC processing delays should be minimised when designing clinical trials to reduce outcome variability in downstream assays. Ideally clinical trial sites should have on-site PBMC processing capabilities or be located close to such facilities.

Single-Cell B-Cell Sequencing to Generate Natively Paired scFab Yeast Surface Display Libraries

The immune cell profiling capabilities of single-cell RNA sequencing (scRNA-seq) are powerful tools that can be applied to the design of theranostic monoclonal antibodies (mAbs). Using scRNA-seq to determine natively paired B-cell receptor (BCR) sequences of immunized mice as a starting point for design, this method outlines a simplified workflow to express single-chain antibody fragments (scFabs) on the surface of yeast for high-throughput characterization and further refinement with directed evolution experiments. While not extensively detailed in this chapter, this method easily accommodates the implementation of a growing body of in silico tools that improve affinity and stability among a range of other developability criteria (e.g., solubility and immunogenicity).

Polygenic autoimmune disease risk alleles impacting B cell tolerance act in concert across shared molecular networks in mouse and in humans

Most B cells produced in the bone marrow have some level of autoreactivity. Despite efforts of central tolerance to eliminate these cells, many escape to periphery, where in healthy individuals, they are rendered functionally non-responsive to restimulation through their antigen receptor via a process termed anergy. Broad repertoire autoreactivity may reflect the chances of generating autoreactivity by stochastic use of germline immunoglobulin gene segments or active mechanisms may select autoreactive cells during egress to the naïve peripheral B cell pool. Likewise, it is unclear why in some individuals autoreactive B cell clones become activated and drive pathophysiologic changes in autoimmune diseases. Both of these remain central questions in the study of the immune system(s). In most individuals, autoimmune diseases arise from complex interplay of genetic risk factors and environmental influences. Advances in genome sequencing and increased statistical power from large autoimmune disease cohorts has led to identification of more than 200 autoimmune disease risk loci. It has been observed that autoantibodies are detectable in the serum years to decades prior to the diagnosis of autoimmune disease. Thus, current models hold that genetic defects in the pathways that control autoreactive B cell tolerance set genetic liability thresholds across multiple autoimmune diseases. Despite the fact these seminal concepts were developed in animal (especially murine) models of autoimmune disease, some perceive a disconnect between human risk alleles and those identified in murine models of autoimmune disease. Here, we synthesize the current state of the art in our understanding of human risk alleles in two prototypical autoimmune diseases - systemic lupus erythematosus (SLE) and type 1 diabetes (T1D) along with spontaneous murine disease models. We compare these risk networks to those reported in murine models of these diseases, focusing on pathways relevant to anergy and central tolerance. We highlight some differences between murine and human environmental and genetic factors that may impact autoimmune disease development and expression and may, in turn, explain some of this discrepancy. Finally, we show that there is substantial overlap between the molecular networks that define these disease states across species. Our synthesis and analysis of the current state of the field are consistent with the idea that the same molecular networks are perturbed in murine and human autoimmune disease. Based on these analyses, we anticipate that murine autoimmune disease models will continue to yield novel insights into how best to diagnose, prognose, prevent and treat human autoimmune diseases.

Single Cell RNA Sequencing in Autoimmune Inflammatory Rheumatic Diseases: Current Applications, Challenges and a Step Toward Precision Medicine

Single cell RNA sequencing (scRNA-seq) represents a new large scale and high throughput technique allowing analysis of the whole transcriptome at the resolution of an individual cell. It has emerged as an imperative method in life science research, uncovering complex cellular networks and providing indices that will eventually lead to the development of more targeted and personalized therapies. The importance of scRNA-seq has been particularly highlighted through the analysis of complex biological systems, in which cellular heterogeneity is a key aspect, such as the immune system. Autoimmune inflammatory rheumatic diseases represent a group of disorders, associated with a dysregulated immune system and high patient heterogeneity in both pathophysiological and clinical aspects. This complicates the complete understanding of underlying pathological mechanisms, associated with limited therapeutic options available and their long-term inefficiency and even toxicity. There is an unmet need to investigate, in depth, the cellular and molecular mechanisms driving the pathogenesis of rheumatic diseases and drug resistance, identify novel therapeutic targets, as well as make a step forward in using stratified and informed therapeutic decisions, which could now be achieved with the use of single cell approaches. This review summarizes the current use of scRNA-seq in studying different rheumatic diseases, based on recent findings from published in vitro, in vivo, and clinical studies, as well as discusses the potential implementation of scRNA-seq in the development of precision medicine in rheumatology.

Single-Cell Transcriptome Profiling Unravels Distinct Peripheral Blood Immune Cell Signatures of RRMS and MOG Antibody-Associated Disease

Relapsing-remitting multiple sclerosis (RRMS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) are inflammatory demyelinating diseases of the central nervous system (CNS). Due to the shared clinical manifestations, detection of disease-specific serum antibody of the two diseases is currently considered as the gold standard for the diagnosis; however, the serum antibody levels are unpredictable during different stages of the two diseases. Herein, peripheral blood single-cell transcriptome was used to unveil distinct immune cell signatures of the two diseases, with the aim to provide predictive discrimination. Single-cell RNA sequencing (scRNA-seq) was conducted on the peripheral blood from three subjects, i.e., one patient with RRMS, one patient with MOGAD, and one patient with healthy control. The results showed that the CD19+ CXCR4+ naive B cell subsets were significantly expanded in both RRMS and MOGAD, which was verified by flow cytometry. More importantly, RRMS single-cell transcriptomic was characterized by increased naive CD8+ T cells and cytotoxic memory-like Natural Killer (NK) cells, together with decreased inflammatory monocytes, whereas MOGAD exhibited increased inflammatory monocytes and cytotoxic CD8 effector T cells, coupled with decreased plasma cells and memory B cells. Collectively, our findings indicate that the two diseases exhibit distinct immune cell signatures, which allows for highly predictive discrimination of the two diseases and paves a novel avenue for diagnosis and therapy of neuroinflammatory diseases.

CTN 328: immunogenicity outcomes in people living with HIV in Canada following vaccination for COVID-19 (HIV-COV): protocol for an observational cohort study

INTRODUCTION

Most existing vaccines require higher or additional doses or adjuvants to provide similar protection for people living with HIV (PLWH) compared with HIV-uninfected individuals. Additional research is necessary to inform COVID-19 vaccine use in PLWH.

METHODS AND ANALYSIS

This multicentred observational Canadian cohort study will enrol 400 PLWH aged >16 years from Montreal, Ottawa, Toronto and Vancouver. Subpopulations of PLWH of interest will include individuals: (1) >55 years of age; (2) with CD4 counts <350 cells/mm3; (3) with multimorbidity (>2 comorbidities) and (4) 'stable' or 'reference' PLWH (CD4 T cells >350 cells/mm3, suppressed viral load for >6 months and <1 comorbidity). Data for 1000 HIV-negative controls will be obtained via a parallel cohort study (Stop the Spread Ottawa), using similar time points and methods. Participants receiving >1 COVID-19 vaccine will attend five visits: prevaccination; 1 month following the first vaccine dose; and at 3, 6 and 12 months following the second vaccine dose. The primary end point will be the percentage of PLWH with COVID-19-specific antibodies at 6 months following the second vaccine dose. Humoral and cell-mediated immune responses, and the interplay between T cell phenotypes and inflammatory markers, will be described. Regression techniques will be used to compare COVID-19-specific immune responses to determine whether there are differences between the 'unstable' PLWH group (CD4 <350 cells/mm3), the stable PLWH cohort and the HIV-negative controls, adjusting for factors believed to be associated with immune response. Unadjusted analyses will reveal whether there are differences in driving factors associated with group membership.

ETHICS AND DISSEMINATION

Research ethics boards at all participating institutions have granted ethics approval for this study. Written informed consent will be obtained from all study participants prior to enrolment. The findings will inform the design of future COVID-19 clinical trials, dosing strategies aimed to improve immune responses and guideline development for PLWH.

TRIAL REGISTRATION NUMBER

NCT04894448.

Baby's skin bacteria: first impressions are long-lasting

Early life is a dynamic period for skin microbial colonization and immune development. We postulate that microbial exposures in this period durably alter the skin immune trajectory and later disease susceptibility. Bacteria contribute to infant skin immune imprinting via interactions with microbes as well as with cutaneous epithelial and immune cells. Excellent research is underway at the skin microbiome-immune interface, both in deciphering basic mechanisms and implementing their therapeutic applications. As emphasized herein, focusing on the unique opportunities and challenges presented by microbial immune modulation in early life will be important. In our view, only through dedicated study of skin-microbe crosstalk in this developmental window can we elucidate the molecular underpinnings of pivotal events that contribute to sustained host-microbe symbiosis.

Microenvironmental regulation of tumour immunity and response to immunotherapy

The confluence of immunology and oncology has led to a lot of uncertainty and questions about relevant biomarkers. Despite the complexity of the tumour microenvironment, most clinical studies have relied on a single‐parameter immunohistochemical assay to prospectively select patients for checkpoint inhibitor therapy; the results of this strategy have been highly variable and often less than optimal. While great efforts have been made to identify additional or alternative biomarkers, pathologists, drug developers, and clinicians alike have faced technical, logistical, and regulatory challenges on how to implement them successfully. In this review, we will discuss these challenges; we will also highlight recent advances in dissecting the functional diversity of immune cell populations within the tumour microenvironment and their potential for improved, biomarker‐driven therapeutic strategies. The dynamic nature and cellular diversity of the tumour microenvironment may challenge past models of a single biomarker predicting patient response and clinical outcome. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

DNA Methylation in LIME1 and SPTBN2 Genes Is Associated with Attention Deficit in Children

DNA methylation levels are associated with neurodevelopment. Attention-deficit/hyperactivity disorder (ADHD), characterized by attention deficits, is a common neurodevelopmental disorder. We used methylation microarray and pyrosequencing to detect peripheral blood DNA methylation markers of ADHD. DNA methylation profiling data from the microarray assays identified potential differentially methylated CpG sites between 12 ADHD patients and 9 controls. Five candidate CpG sites (cg00446123, cg20513976, cg07922513, cg17096979, and cg02506324) in four genes (LIME1, KCNAB2, CAPN9, and SPTBN2) were further examined with pyrosequencing. The attention of patients were tested using the Conners’ Continuous Performance Test (CPT). In total, 126 ADHD patients with a mean age of 9.2 years (78.6% males) and 72 healthy control subjects with a mean age of 9.3 years (62.5% males) were recruited. When all participants were categorized by their CPT performance, the DNA methylation levels in LIME1 (cg00446123 and cg20513976) were found to be significantly higher and those in SPTBN2 (cg02506324) were significantly lower in children with worse CPT performance. Therefore, DNA methylation of two CpG sites in LIME1 and one CpG site in SPTBN2 is associated with attention deficits in children. DNA methylation biomarkers may assist in identifying attention deficits of children in clinical settings.