Underrepresentation of activating KIR gene expression in single-cell RNA-seq data is due to KIR gene misassignment.

Standard single-cell RNA-sequencing alignment pipelines exhibit a propensity for misassigning killer immunoglobulin-like receptor (KIR) transcripts, thereby giving rise to inaccuracies in quantifying KIR expression. Alves et al. elucidated that these default workflows frequently misclassify activating KIR transcripts as inhibitory KIR expression, resulting in a skewed representation of the KIR repertoire.

Increased H3K27 trimethylation contributes to cone survival in a mouse model of cone dystrophy.

Inherited retinal diseases (IRDs) are a heterogeneous group of blinding disorders, which result in dysfunction or death of the light-sensing cone and rod photoreceptors. Despite individual IRDs (Inherited retinal disease) being rare, collectively, they affect up to 1:2000 people worldwide, causing a significant socioeconomic burden, especially when cone-mediated central vision is affected. This study uses the Pde6ccpfl1 mouse model of achromatopsia, a cone-specific vision loss IRD (Inherited retinal disease), to investigate the potential gene-independent therapeutic benefits of a histone demethylase inhibitor GSK-J4 on cone cell survival. We investigated the effects of GSK-J4 treatment on cone cell survival in vivo and ex vivo and changes in cone-specific gene expression via single-cell RNA sequencing. A single intravitreal GSK-J4 injection led to transcriptional changes in pathways involved in mitochondrial dysfunction, endoplasmic reticulum stress, among other key epigenetic pathways, highlighting the complex interplay between methylation and acetylation in healthy and diseased cones. Furthermore, continuous administration of GSK-J4 in retinal explants increased cone survival. Our results suggest that IRD (Inherited retinal disease)-affected cones respond positively to epigenetic modulation of histones, indicating the potential of this approach in developing a broad class of novel therapies to slow cone degeneration.

Profiling and genetic control of the murine immunoglobulin G glycome.

Immunoglobulin G (IgG) glycosylation is essential for function of the immune system, but the genetic and environmental factors that underlie its inter-individual variability are not well defined. The Collaborative Cross (CC) genetic resource harnesses over 90% of the common genetic variation of the mouse. By analyzing the IgG glycome composition of 95 CC strains, we made several important observations: (i) glycome variation between mouse strains was higher than between individual humans, despite all mice having the same environmental influences; (ii) five genetic loci were found to be associated with murine IgG glycosylation; (iii) variants outside traditional glycosylation site motifs affected glycome variation; (iv) bisecting N-acetylglucosamine (GlcNAc) was produced by several strains although most previous studies have reported the absence of glycans containing the bisecting GlcNAc on murine IgGs; and (v) common laboratory mouse strains are not optimal animal models for studying effects of glycosylation on IgG function.

Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility.

Genome-wide association studies have found >60 loci that confer genetic susceptibility to type 1 diabetes (T1D). Many of these are defined only by anonymous single nucleotide polymorphisms: the underlying causative genes, as well as the molecular bases by which they mediate susceptibility, are not known. Identification of how these variants affect the complex mechanisms contributing to the loss of tolerance is a challenge. In this study, we performed systematic analyses to characterize these variants. First, all known genes in strong linkage disequilibrium (r(2) > 0.8) with the reported single nucleotide polymorphisms for each locus were tested for commonly occurring nonsynonymous variations. We found only a total of 22 candidate genes at 16 T1D loci with common nonsynonymous alleles. Next, we performed functional studies to examine the effect of non-HLA T1D risk alleles on regulating expression levels of genes in four different cell types: EBV-transformed B cell lines (resting and 6 h PMA stimulated) and purified CD4(+) and CD8(+) T cells. We mapped cis-acting expression quantitative trait loci and found 24 non-HLA loci that affected the expression of 31 transcripts significantly in at least one cell type. Additionally, we observed 25 loci that affected 38 transcripts in trans. In summary, our systems genetics analyses defined the effect of T1D risk alleles on levels of gene expression and provide novel insights into the complex genetics of T1D, suggesting that most of the T1D risk alleles mediate their effect by influencing expression of multiple nearby genes.

CTSH regulates ß-cell function and disease progression in newly diagnosed type 1 diabetes patients.

Over 40 susceptibility loci have been identified for type 1 diabetes (T1D). Little is known about how these variants modify disease risk and progression. Here, we combined in vitro and in vivo experiments with clinical studies to determine how genetic variation of the candidate gene cathepsin H (CTSH) affects disease mechanisms and progression in T1D. The T allele of rs3825932 was associated with lower CTSH expression in human lymphoblastoid cell lines and pancreatic tissue. Proinflammatory cytokines decreased the expression of CTSH in human islets and primary rat ß-cells, and overexpression of CTSH protected insulin-secreting cells against cytokine-induced apoptosis. Mechanistic studies indicated that CTSH exerts its antiapoptotic effects through decreased JNK and p38 signaling and reduced expression of the proapoptotic factors Bim, DP5, and c-Myc. CTSH overexpression also up-regulated Ins2 expression and increased insulin secretion. Additionally, islets from Ctsh(-/-) mice contained less insulin than islets from WT mice. Importantly, the TT genotype was associated with higher daily insulin dose and faster disease progression in newly diagnosed T1D patients, indicating agreement between the experimental and clinical data. In line with these observations, healthy human subjects carrying the T allele have lower ß-cell function, which was evaluated by glucose tolerance testing. The data provide strong evidence that CTSH is an important regulator of ß-cell function during progression of T1D and reinforce the concept that candidate genes for T1D may affect disease progression by modulating survival and function of pancreatic ß-cells, the target cells of the autoimmune assault.

Multiomic single-cell sequencing defines tissue-specific responses in Stevens-Johnson Syndrome and Toxic epidermal necrolysis.

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) is a rare but life-threatening cutaneous drug reaction mediated by human leukocyte antigen (HLA) class I-restricted CD8+ T-cells. To obtain an unbiased assessment of SJS/TEN cellular immunopathogenesis, we performed single-cell (sc) transcriptome, surface proteome, and TCR sequencing on unaffected skin, affected skin, and blister fluid from 17 SJS/TEN patients. From 119,784 total cells, we identified 16 scRNA-defined subsets, confirmed by subset-defining surface protein expression. Keratinocytes upregulated HLA and IFN-response genes in the affected skin. Cytotoxic CD8+ T-cell subpopulations of expanded and unexpanded TCRαß clonotypes were shared in affected skin and blister fluid but absent or unexpanded in SJS/TEN unaffected skin. SJS/TEN blister fluid is a rich reservoir of oligoclonal CD8+ T-cells with an effector phenotype driving SJS/TEN pathogenesis. This multiomic database will act as the basis to define antigen-reactivity, HLA restriction, and signatures of drug-antigen-reactive T-cell clonotypes at a tissue level.

Multiomic single-cell sequencing defines tissue-specific responses in Stevens-Johnson syndrome and toxic epidermal necrolysis.

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) is a rare but life-threatening cutaneous drug reaction mediated by human leukocyte antigen (HLA) class I-restricted CD8+ T cells. For unbiased assessment of cellular immunopathogenesis, here we perform single-cell (sc) transcriptome, surface proteome, and T cell receptor (TCR) sequencing on unaffected skin, affected skin, and blister fluid from 15 SJS/TEN patients. From 109,888 cells, we identify 15 scRNA-defined subsets. Keratinocytes express markers indicating HLA class I-restricted antigen presentation and appear to trigger the proliferation of and killing by cytotoxic CD8+ tissue-resident T cells that express granulysin, granzyme B, perforin, LAG3, CD27, and LINC01871, and signal through the PKM, MIF, TGFß, and JAK-STAT pathways. In affected tissue, cytotoxic CD8+ T cells express private expanded and unexpanded TCRαß that are absent or unexpanded in unaffected skin, and mixed populations of macrophages and fibroblasts express pro-inflammatory markers or those favoring repair. This data identifies putative cytotoxic TCRs and therapeutic targets.

Tracking of activated cTfh cells following sequential influenza vaccinations reveals transcriptional profile of clonotypes driving a vaccine-induced immune response.

Introduction: A vaccine against influenza is available seasonally but is not 100% effective. A predictor of successful seroconversion in adults is an increase in activated circulating T follicular helper (cTfh) cells after vaccination. However, the impact of repeated annual vaccinations on long-term protection and seasonal vaccine efficacy remains unclear. Methods: In this study, we examined the T cell receptor (TCR) repertoire and transcriptional profile of vaccine-induced expanded cTfh cells in individuals who received sequential seasonal influenza vaccines. We measured the magnitude of cTfh and plasmablast cell activation from day 0 (d0) to d7 post-vaccination as an indicator of a vaccine response. To assess TCR diversity and T cell expansion we sorted activated and resting cTfh cells at d0 and d7 post-vaccination and performed TCR sequencing. We also single cell sorted activated and resting cTfh cells for TCR analysis and transcriptome sequencing. Results and discussion: The percent of activated cTfh cells significantly increased from d0 to d7 in each of the 2016-17 (p < 0.0001) and 2017-18 (p = 0.015) vaccine seasons with the magnitude of cTfh activation increase positively correlated with the frequency of circulating plasmablast cells in the 2016-17 (p = 0.0001) and 2017-18 (p = 0.003) seasons. At d7 post-vaccination, higher magnitudes of cTfh activation were associated with increased clonality of cTfh TCR repertoire. The TCRs from vaccine-expanded clonotypes were identified and tracked longitudinally with several TCRs found to be present in both years. The transcriptomic profile of these expanded cTfh cells at the single cell level demonstrated overrepresentation of transcripts of genes involved in the type-I interferon pathway, pathways involved in gene expression, and antigen presentation and recognition. These results identify the expansion and transcriptomic profile of vaccine-induced cTfh cells important for B cell help.

Visual Genomics Analysis Studio as a Tool to Analyze Multiomic Data.

Type B adverse drug reactions (ADRs) are iatrogenic immune-mediated syndromes with mechanistic etiologies that remain incompletely understood. Some of the most severe ADRs, including delayed drug hypersensitivity reactions, are T-cell mediated, restricted by specific human leukocyte antigen risk alleles and sometimes by public or oligoclonal T-cell receptors (TCRs), central to the immunopathogenesis of tissue-damaging response. However, the specific cellular signatures of effector, regulatory, and accessory immune populations that mediate disease, define reaction phenotype, and determine severity have not been defined. Recent development of single-cell platforms bringing together advances in genomics and immunology provides the tools to simultaneously examine the full transcriptome, TCRs, and surface protein markers of highly heterogeneous immune cell populations at the site of the pathological response at a single-cell level. However, the requirement for advanced bioinformatics expertise and computational hardware and software has often limited the ability of investigators with the understanding of diseases and biological models to exploit these new approaches. Here we describe the features and use of a state-of-the-art, fully integrated application for analysis and visualization of multiomic single-cell data called Visual Genomics Analysis Studio (VGAS). This unique user-friendly, Windows-based graphical user interface is specifically designed to enable investigators to interrogate their own data. While VGAS also includes tools for sequence alignment and identification of associations with host or organism genetic polymorphisms, in this review we focus on its application for analysis of single-cell TCR-RNA-Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE)-seq, enabling holistic cellular characterization by unbiased transcriptome and select surface proteome. Critically, VGAS does not require user-directed coding or access to high-performance computers, instead incorporating performance-optimized hidden code to provide application-based fast and intuitive tools for data analyses and production of high-resolution publication-ready graphics on standard specification laptops. Specifically, it allows analyses of comprehensive single-cell TCR sequencing (scTCR-seq) data, detailing (i) functional pairings of α-ß heterodimer TCRs, (ii) one-click histograms to display entropy and gene rearrangements, and (iii) Circos and Sankey plots to visualize clonality and dominance. For unbiased single-cell RNA sequencing (scRNA-seq) analyses, users extract cell transcriptome signatures according to global structure via principal component analysis, t-distributed stochastic neighborhood embedding, or uniform manifold approximation and projection plots, with overlay of scTCR-seq enabling identification and selection of the immunodominant TCR-expressing populations. Further integration with similar sequence-based detection of surface protein markers using oligo-labeled antibodies (CITE-seq) provides comparative understanding of surface protein expression, with differential gene or protein analyses visualized using volcano plot or heatmap functions. These data can be compared to reference cell atlases or suitable controls to reveal discrete disease-specific subsets, from epithelial to tissue-resident memory T-cells, and activation status, from senescence through exhaustion, with more finite transcript expression displayed as violin and box plots. Importantly, guided tutorial videos are available, as are regular application updates based on the latest advances in bioinformatics and user feedback.

Cross-Reactivity to Mutated Viral Immune Targets Can Influence CD8+ T Cell Functionality: An Alternative Viral Adaptation Strategy.

Loss of T cell immunogenicity due to mutations in virally encoded epitopes is a well-described adaptation strategy to limit host anti-viral immunity. Another described, but less understood, adaptation strategy involves the selection of mutations within epitopes that retain immune recognition, suggesting a benefit for the virus despite continued immune pressure (termed non-classical adaptation). To understand this adaptation strategy, we utilized a single cell transcriptomic approach to identify features of the HIV-specific CD8+ T cell responses targeting non-adapted (NAE) and adapted (AE) forms of epitopes containing a non-classical adaptation. T cell receptor (TCR) repertoire and transcriptome were obtained from antigen-specific CD8+ T cells of chronic (n=7) and acute (n=4) HIV-infected subjects identified by either HLA class I tetramers or upregulation of activation markers following peptide stimulation. CD8+ T cells were predominantly dual tetramer+, confirming a large proportion of cross-reactive TCR clonotypes capable of recognizing the NAE and AE form. However, single-reactive CD8+ T cells were identified in acute HIV-infected subjects only, providing the potential for the selection of T cell clones over time. The transcriptomic profile of CD8+ T cells was dependent on the autologous virus: subjects whose virus encoded the NAE form of the epitope (and who transitioned to the AE form at a later timepoint) exhibited an 'effective' immune response, as indicated by expression of transcripts associated with polyfunctionality, cytotoxicity and apoptosis (largely driven by the genes GZMB, IFNÉ£, CCL3, CCL4 and CCL5). These data suggest that viral adaptation at a single amino acid residue can provide an alternative strategy for viral survival by modulating the transcriptome of CD8+ T cells and potentially selecting for less effective T cell clones from the acute to chronic phase.

Single-cell analysis shows that adipose tissue of persons with both HIV and diabetes is enriched for clonal, cytotoxic, and CMV-specific CD4+ T cells.

Persons with HIV are at increased risk for diabetes mellitus compared with individuals without HIV. Adipose tissue is an important regulator of glucose and lipid metabolism, and adipose tissue T cells modulate local inflammatory responses and, by extension, adipocyte function. Persons with HIV and diabetes have a high proportion of CX3CR1+ GPR56+ CD57+ (C-G-C+) CD4+ T cells in adipose tissue, a subset of which are cytomegalovirus specific, whereas individuals with diabetes but without HIV have predominantly CD69+ CD4+ T cells. Adipose tissue CD69+ and C-G-C+ CD4+ T cell subsets demonstrate higher receptor clonality compared with the same cells in blood, potentially reflecting antigen-driven expansion, but C-G-C+ CD4+ T cells have a more inflammatory and cytotoxic RNA transcriptome. Future studies will explore whether viral antigens have a role in recruitment and proliferation of pro-inflammatory C-G-C+ CD4+ T cells in adipose tissue of persons with HIV.

Adipose Tissue in Persons With HIV Is Enriched for CD4+ T Effector Memory and T Effector Memory RA+ Cells, Which Show Higher CD69 Expression and CD57, CX3CR1, GPR56 Co-expression With Increasing Glucose Intolerance.

Chronic T cell activation and accelerated immune senescence are hallmarks of HIV infection, which may contribute to the increased risk of cardiometabolic diseases in people living with HIV (PLWH). T lymphocytes play a central role in modulating adipose tissue inflammation and, by extension, adipocyte energy storage and release. Here, we assessed the CD4+ and CD8+ T cell profiles in the subcutaneous adipose tissue (SAT) and blood of non-diabetic (n = 9; fasting blood glucose [FBG] < 100 mg/dL), pre-diabetic (n = 8; FBG = 100-125 mg/dL) and diabetic (n = 9; FBG ≥ 126 mg/dL) PLWH, in addition to non- and pre-diabetic, HIV-negative controls (n = 8). SAT was collected by liposuction and T cells were extracted by collagenase digestion. The proportion of naïve (TNai) CD45RO-CCR7+, effector memory (TEM) CD45RO+CCR7-, central memory (TCM) CD45RO+CCR7+, and effector memory revertant RA+(TEMRA) CD45RO-CCR7- CD4+ and CD8+ T cells were measured by flow cytometry. CD4+ and CD8+ TEM and TEMRA were significantly enriched in SAT of PLWH compared to blood. The proportions of SAT CD4+ and CD8+ memory subsets were similar across metabolic status categories in the PLWH, but CD4+ T cell expression of the CD69 early-activation and tissue residence marker, particularly on TEM cells, increased with progressive glucose intolerance. Use of t-distributed Stochastic Neighbor Embedding (t-SNE) identified a separate group of predominantly CD69lo TEM and TEMRA cells co-expressing CD57, CX3CR1, and GPR56, which were significantly greater in diabetics compared to non-diabetics. Expression of the CX3CR1 and GPR56 markers indicate these TEM and TEMRA cells may have anti-viral specificity. Compared to HIV-negative controls, SAT from PLWH had an increased CD8:CD4 ratio, but the distribution of CD4+ and CD8+ memory subsets was similar irrespective of HIV status. Finally, whole adipose tissue from PLWH had significantly higher expression of TLR2, TLR8, and multiple chemokines potentially relevant to immune cell homing compared to HIV-negative controls with similar glucose tolerance.

RNA-Seq Analysis of Islets to Characterise the Dedifferentiation in Type 2 Diabetes Model Mice db/db.

Type 2 diabetes (T2D) is a global health issue and dedifferentiation plays underlying causes in the pathophysiology of T2D; however, there is a lack of understanding in the mechanism. Dedifferentiation results from the loss of function of pancreatic ß-cells alongside a reduction in essential transcription factors under various physiological stressors. Our study aimed to establish db/db as an animal model for dedifferentiation by using RNA sequencing to compare the gene expression profile in islets isolated from wild-type, db/+ and db/db mice, and qPCR was performed to validate those significant genes. A reduction in both insulin secretion and the expression of Ins1, Ins2, Glut2, Pdx1 and MafA was indicative of dedifferentiation in db/db islets. A comparison of the db/+ and the wild-type islets indicated a reduction in insulin secretion perhaps related to the decreased Mt1. A significant reduction in both Rn45s and Mir6236 was identified in db/+ compared to wild-type islets, which may be indicative of pre-diabetic state. A further significant reduction in RasGRF1, Igf1R and Htt was also identified in dedifferentiated db/db islets. Molecular characterisation of the db/db islets was performed via Ingenuity analysis which identified highly significant genes that may represent new molecular markers of dedifferentiation.

Effects of Type 1 Diabetes Risk Alleles on Immune Cell Gene Expression.

Genetic studies have identified 61 variants associated with the risk of developing Type 1 Diabetes (T1D). The functions of most of the non-HLA (Human Leukocyte Antigen) genetic variants remain unknown. We found that only 16 of these risk variants could potentially be linked to a protein-coding change. Therefore, we investigated whether these variants affected susceptibility by regulating changes in gene expression. To do so, we examined whole transcriptome profiles of 600 samples from the Type 1 Diabetes Genetics Consortium (T1DGC). These comprised four different immune cell types (Epstein-Barr virus (EBV)-transformed B cells, either basal or after stimulation; and cluster of differentiation (CD)4+ and CD8+ T cells). Many of the T1D-associated risk variants regulated expression of either neighboring (cis-) or distant (trans-) genes. In brief, 24 of the non-HLA T1D variants affected the expression of 31 nearby genes (cis) while 25 affected 38 distant genes (trans). The effects were highly significant (False Discovery Rate p < 0.001). In addition, we searched in public databases for expression effects of T1D single nucleotide polymorphisms (SNPs) in other immune cell types such as CD14+ monocytes, lipopolysaccharide (LPS) stimulated monocytes, and CD19+ B cells. In this paper, we review the (expression quantitative trait loci (eQTLs) associated with each of the 60 T1D variants and provide a summary of the genes impacted by T1D risk alleles in various immune cells. We then review the methodological steps involved in analyzing the function of genome wide association studies (GWAS)-identified variants, with emphasis on those affecting gene expression. We also discuss recent advancements in the methodologies and their advantages. We conclude by suggesting future study designs that will aid in the study of T1D risk variants.

Complex Trait Analyses of the Collaborative Cross: Tools and Databases.

The Collaborative cross (CC) is a powerful mouse resource for investigating complex genetic traits. Here we discuss various tools and techniques for gene mapping and identification using the CC. The data analyses procedures are illustrated with examples.

Using Systems Genetics to Understanding the Etiology of Complex Disease.

Here, we discuss Systems Genetics applications for systematic evaluation of candidate causal genes together with follow-up bioinformatics pathway analysis. The aim of this chapter is to illustrate analytic procedures and we provide examples in the context of Type 1 diabetes (T1day), the risk of which is conferred by over 60 loci. We also describe the Type 1 Diabetes Systems Genetics website and provide a guide for its use and application to other diseases.

Analysis of early mesothelial cell responses to Staphylococcus epidermidis isolated from patients with peritoneal dialysis-associated peritonitis.

The major complication of peritoneal dialysis (PD) is the development of peritonitis, an infection within the abdominal cavity, primarily caused by bacteria. PD peritonitis is associated with significant morbidity, mortality and health care costs. Staphylococcus epidermidis is the most frequently isolated cause of PD-associated peritonitis. Mesothelial cells are integral to the host response to peritonitis, and subsequent clinical outcomes, yet the effects of infection on mesothelial cells are not well characterised. We systematically investigated the early mesothelial cell response to clinical and reference isolates of S. epidermidis using primary mesothelial cells and the mesothelial cell line Met-5A. Using an unbiased whole genome microarray, followed by a targeted panel of genes known to be involved in the human antibacterial response, we identified 38 differentially regulated genes (adj. p-value < 0.05) representing 35 canonical pathways after 1 hour exposure to S. epidermidis. The top 3 canonical pathways were TNFR2 signaling, IL-17A signaling, and TNFR1 signaling (adj. p-values of 0.0012, 0.0012 and 0.0019, respectively). Subsequent qPCR validation confirmed significant differences in gene expression in a number of genes not previously described in mesothelial cell responses to infection, with heterogeneity observed between clinical isolates of S. epidermidis, and between Met-5A and primary mesothelial cells. Heterogeneity between different S. epidermidis isolates suggests that specific virulence factors may play critical roles in influencing outcomes from peritonitis. This study provides new insights into early mesothelial cell responses to infection with S. epidermidis, and confirms the importance of validating findings in primary mesothelial cells.

Variable cardiac α-actin (Actc1) expression in early adult skeletal muscle correlates with promoter methylation.

Different genes encode the α-actin isoforms that are predominantly expressed in heart and skeletal muscle. Mutations in the skeletal muscle α-actin gene (ACTA1) cause muscle diseases that are mostly lethal in the early postnatal period. We previously demonstrated that the disease phenotype of ACTA1 mouse models could be rescued by transgenic over-expression of cardiac α-actin (ACTC1). ACTC1 is the predominant striated α-actin isoform in the heart but is also expressed in developing skeletal muscle. To develop a translatable therapy, we investigated the genetic regulation of Actc1 expression. Using strains from The Collaborative Cross (CC) genetic resource, we found that Actc1 varies in expression by up to 24-fold in skeletal muscle. We defined significant expression quantitative trait loci (eQTL) associated with early adult Actc1 expression in soleus and heart. eQTL in both heart and soleus mapped to the Actc1 locus and replicate an eQTL mapped for Actc1 in BXD heart and quadriceps. We built on this previous work by analysing genes within the eQTL peak regions to prioritise likely candidates for modifying Actc1 expression. Additionally we interrogated the CC founder haplotype contributions to enable prioritisation of genetic variants for functional analyses. Methylation around the Actc1 transcriptional start site in early adult skeletal muscle negatively correlated with Actc1 expression in a strain-dependent manner, while other marks of regulatory potential (histone modification and chromatin accessibility) were unaltered. This study provides novel insights into the complex genetic regulation of Actc1 expression in early adult skeletal muscles.