Circulating Tumor Reactive KIR+CD8+ T cells Suppress Anti-Tumor Immunity in Patients with Melanoma

Effective anti-tumor immunity is largely driven by cytotoxic CD8+ T cells that can specifically recognize tumor antigens. However, the factors which ultimately dictate successful tumor rejection remain poorly understood. Here we identify a subpopulation of CD8+ T cells which are tumor antigen-specific in patients with melanoma but resemble KIR+CD8+ T cells with a regulatory function (Tregs). These tumor antigen-specific KIR+CD8+ T cells are detectable in both the tumor and the blood, and higher levels of this population are associated with worse overall survival. Our findings therefore suggest that KIR+CD8+ Tregs are tumor antigen-specific but uniquely suppress anti-tumor immunity in patients with melanoma.

High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq

In this study, we extended co-indexing of transcriptomes and epitopes (CITE) to the spatial dimension and demonstrated high-plex protein and whole transcriptome co-mapping. We profiled 189 proteins and whole transcriptome in multiple mouse tissue types with spatial CITE sequencing and then further applied the method to measure 273 proteins and transcriptome in human tissues, revealing spatially distinct germinal center reactions in tonsil and early immune activation in skin at the Coronavirus Disease 2019 mRNA vaccine injection site.

Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mapping

We present spatial-CITE-seq for high-plex protein and whole transcriptome co-mapping, which was firstly demonstrated for profiling 198 proteins and transcriptome in multiple mouse tissue types. It was then applied to human tissues to measure 283 proteins and transcriptome that revealed spatially distinct germinal center reaction in tonsil and early immune activation in skin at the COVID-19 mRNA vaccine injection site. Spatial-CITE-seq may find a range of applications in biomedical research.

Type I Interferon Transcriptional Network Regulates Expression of Coinhibitory Receptors in Human T cells

While inhibition of T cell co-inhibitory receptors has revolutionized cancer therapy, the mechanisms governing their expression on human T cells have not been elucidated. Type 1 interferon (IFN-I) modulates T cell immunity in viral infection, autoimmunity, and cancer, and may facilitate induction of T cell exhaustion in chronic viral infection. Here we show that IFN-I regulates co-inhibitory receptor expression on human T cells, inducing PD-1/TIM-3/LAG-3 while surprisingly inhibiting TIGIT expression. High-temporal-resolution mRNA profiling of IFN-I responses enabled the construction of dynamic transcriptional regulatory networks uncovering three temporal transcriptional waves. Perturbation of key transcription factors on human primary T cells revealed unique regulators that control expression of co-inhibitory receptors. We found that the dynamic IFN-I response in vitro closely mirrored T cell features with IFN-I linked acute SARS-CoV-2 infection in human, with high LAG3 and decreased TIGIT expression. Finally, our gene regulatory network identified SP140 as a key regulator for differential LAG3 and TIGIT expression, which were validated at the level of protein expression. The construction of IFN-I regulatory networks with identification of unique transcription factors controlling co-inhibitory receptor expression may provide targets for enhancement of immunotherapy in cancer, infectious diseases, and autoimmunity.

Correction: Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting

Correction for 'Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting' by Coleman Murray et al., Lab Chip, 2018, 18, 2396-2409.

Regulatory T Cells: From Discovery to Autoimmunity

Multiple sclerosis (MS) is a genetically mediated autoimmune disease of the central nervous system. Allelic variants lead to lower thresholds of T-cell activation resulting in activation of autoreactive T cells. Environmental factors, including, among others, diet, vitamin D, and smoking, in combination with genetic predispositions, play a substantial role in disease development and activation of autoreactive T cells. FoxP3⁺ regulatory T cells (Tregs) have emerged as central in the control of autoreactive T cells. A consistent finding in patients with MS is defects in Treg cell function with reduced suppression of effector T cells and production of proinflammatory cytokines. Emerging data suggests that functional Tregs become effector-like T cells with loss of function associated with T-bet expression and interferon γ (IFN-γ) secretion.

Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting

Immunotherapies (IT) require induction, expansion, and maintenance of specific changes to a patient's immune cell repertoire which yield a therapeutic benefit. Recently, mechanistic understanding of these changes at the cellular level has revealed that IT results in complex phenotypic transitions in target cells, and that therapeutic effectiveness may be predicted by monitoring these transitions during therapy. However, monitoring will require unique tools that enable capture, manipulation, and profiling of rare immune cell populations. In this study, we introduce a method of automated and unsupervised separation and processing of rare immune cells, using high-force and multidimensional magnetic ratcheting (MR). We demonstrate capture of target immune cells using samples with up to 1 : 10 000 target cell to background cell ratios from input volumes as small as 25 microliters (i.e. a low volume and low cell frequency sample sparing assay interface). Cell capture is shown to achieve up to 90% capture efficiency and purity, and captured cell analysis is shown using both on-chip culture/activity assays and off-chip ejection and nucleic acid analysis. These results demonstrate that multi-directional magnetic ratcheting offers a unique separation system for dealing with blood cell samples that contain either rare cells or significantly small volumes, and the "sample sparing" capability leads to an expanded spectrum of parameters that can be measured. These tools will be paramount to advancing techniques for immune monitoring under conditions in which both the sample volume and number of antigen-specific target cells are often exceedingly small, including during IT and treatment of allergy, asthma, autoimmunity, immunodeficiency, cell based therapy, transplantation, and infection.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.

Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls

Multiple sclerosis (MS) is an inflammatory CNS disease with a substantial genetic component, originally mapped to only the human leukocyte antigen (HLA) region. In the last 5 years, a total of seven genome-wide association studies and one meta-analysis successfully identified 57 non-HLA susceptibility loci. Here, we merged nominal statistical evidence of association and physical evidence of interaction to conduct a protein-interaction-network-based pathway analysis (PINBPA) on two large genetic MS studies comprising a total of 15,317 cases and 29,529 controls. The distribution of nominally significant loci at the gene level matched the patterns of extended linkage disequilibrium in regions of interest. We found that products of genome-wide significantly associated genes are more likely to interact physically and belong to the same or related pathways. We next searched for subnetworks (modules) of genes (and their encoded proteins) enriched with nominally associated loci within each study and identified those modules in common between the two studies. We demonstrate that these modules are more likely to contain genes with bona fide susceptibility variants and, in addition, identify several high-confidence candidates (including BCL10, CD48, REL, TRAF3, and TEC). PINBPA is a powerful approach to gaining further insights into the biology of associated genes and to prioritizing candidates for subsequent genetic studies of complex traits.

FlowCAP: comparison of automated and manual gating of standardized lyoplate flow cytometry data (P3374)

Standardization of immunological assays, including flow cytometry, in terms of reagents, sample handling, instrument setup, and data analysis, is essential for successful cross-study and cross-center analysis in order to mitigate the effects of technical variability in assay results. The Human Immunology Project and the Federation of Clinical Immunology Societies (FOCIS) have partnered to develop five standardized, lyophilized, eight-color staining reagent panels (termed lyoplates) for this purpose. In collaboration with the FlowCAP consortium, standardized samples (Cytotrol control cells) were distributed to nine participating centers and analyzed by flow cytometry using the lyoplate reagents and SOP's to minimize experimental variability. Data from two of these panels (T-cell and B-cell) were entered into the FlowCAP-III challenge, where participants analyzed the data using automated gating methods for comparison against cell population statistics for major T and B-cell subsets as defined by a consensus manual gating scheme. This evaluation showed that several automated gating algorithms could successfully recapitulate centralized manual gating statistics for T-cell and B-cell subsets with little statistical bias, and with within-center and between-center variability as low or lower than centralized manual gating. These results demonstrate that automated gating algorithms are ready for use in performing reproducible analyses and comparisons of immunological data.

Prostaglandin E2 affects T cell responses through modulation of CD46 expression. (178.8)

The complement regulator CD46 controls T cell activation and differentiation. CD46-mediated differentiation pathway is defective in several chronic inflammatory diseases, underlying the importance of CD46 in controlling T cell function and the need to understand its regulatory mechanisms. Using an RNAi-based screening approach in primary T cells, we have identified that two members of the G-protein coupled receptor (GPCR) kinase family were involved in regulating CD46 expression at the T cell surface. We have investigated the role of prostaglandin E2 (PGE2), which binds to GPCRs, in the regulation of CD46 expression and function. Conflicting roles of PGE2 in T cell functions have been reported, and the reasons for these apparent discrepancies are not well understood. We show that: i) addition of PGE2 strongly downregulates CD46 expression in activated T cells, ii) PGE2 differentially affects T cell activation, cytokine production and phenotype depending on the activation signals received by the T cells, iii) this was correlated with a distinct pattern of the EP2-EP4 PGE2 receptors induced, with EP4 being preferentially expressed upon CD46, and iv) addition of an EP4 antagonist could reverse the effects observed on cytokine production upon CD46 costimulation. These data demonstrate a novel role of the PGE2-EP4-GRK axis in CD46 functions, which might partly explain the diverse roles of PGE2 in T cell functions.

High salt induces pathogenic Th17 cells and exacerbates autoimmune diseases (60.13)

Interleukin (IL)-17 producing CD4+ helper T cells (Th17 cells) play a pivotal role in autoimmune diseases. Apart from their importance for the control of certain pathogens, IL-23 dependent Th17 cells have been shown to be critical for the development of experimental autoimmune encephalomyelitis (EAE). Moreover, genetic risk factors associated with multiple sclerosis (MS) are linked to the IL23/Th17 pathway. Besides genetic factors, the increased incidence of autoimmune diseases like MS in developed countries is also believed to be related to environmental risk factors. However, how environmental risk factors such as changes in diet, sun exposure or medications could directly influence the development of pathogenic Th17 cells is not well established. Here we show that increased salt (sodium chloride; NaCl) concentrations dramatically boost the induction of murine and human Th17 cells in vitro. Moreover, mice fed with a high salt diet develop a very severe form of EAE, dependent on the induction of highly pathogenic Th17 cells. The generation of Th17 cells under high salt conditions is well regulated on the molecular level and seems to be dependent on specific pathways. Thus, increased salt intake, which may represents one of the biggest contributors to changes in diet during the last half century and accounts for cardiovascular disease, might also represent an environmental risk factor for autoimmune diseases through the exacerbated induction of pathogenic Th17 cells.

Unraveling the autoimmune translational research process layer by layer

Autoimmune diseases have a complex etiology and despite great progress having been made in our comprehension of these disorders, there has been limited success in the development of approved medications based on these insights. Development of drugs and strategies for application in translational research and medicine are hampered by an inadequate molecular definition of the human autoimmune phenotype and the organizational models that are necessary to clarify this definition.

A model for harmonizing flow cytometry in clinical trials

Complexities in sample handling, instrument setup and data analysis are barriers to the effective use of flow cytometry to monitor immunological parameters in clinical trials. The novel use of a central laboratory may help mitigate these issues.

Functionally defective germline variants of sialic acid acetylesterase in autoimmunity

Sialic acid acetylesterase (SIAE) is an enzyme that negatively regulates B lymphocyte antigen receptor signaling and is required for the maintenance of immunological tolerance in mice1, 2. Heterozygous loss-of-function germline rare variants and a homozygous defective polymorphic variant of SIAE were identified in 24/923 Caucasian subjects with relatively common autoimmune disorders and in 2/648 Caucasian controls. All heterozygous loss-of-function SIAE mutations tested were capable of functioning in a dominant negative manner. A homozygous secretion-defective polymorphic variant of SIAE was catalytically active, lacked the ability to function in a dominant negative manner, and was seen in 8 autoimmune subjects but in no control subjects. The Odds Ratio for inheriting defective SIAE alleles was 8.6 in all autoimmune subjects, 8.3 in subjects with rheumatoid arthritis, and 7.9 in subjects with type I diabetes. Functionally defective SIAE rare and polymorphic variants represent a strong genetic link to susceptibility in relatively common human autoimmune disorders.

IL-12 induces human CD4+CD45RA-CD25hiCD127low/neg regulatory T cells to secrete IFNγ and IL-10 and acquire a non-regulatory effector phenotype (138.9)

Regulatory T cells (Treg) play a pivotal role in maintaining a balance between the immune response and peripheral tolerance. Recent evidence indicates that regulatory T cells are more functionally plastic than originally thought. Not only does the cytokine milieu modulate their capacity to suppress, but it can also induce Tregs to secrete cytokines (IL-17). The IL-12 family of cytokines (IL-12, IL-23, IL-27, IL-35) are key players in the regulation of T cell responses. We have studied the distinct effects that these cytokines (IL-12, IL-23 and IL-27) exert on human Treg function and phenotype. RESULTS: Surprisingly, we have found that IL-12 induces memory CD127lo Tregs to express T-bet and produce IFN-gamma and IL-10. Furthermore, in this state, these Tregs not only exhibit a non-regulatory effector phenotype, but they are also markedly less able to suppress the activation of co-cultured CD4 T cells. Importantly, although these IL-12-treated Tregs are less suppressive, their Foxp3 expression is not significantly altered. Additional data indicates that this is a transient state of reduced Treg suppression.. Thus this represents a way for the immune system to inactivate Treg function to allow an immune response to proceed.

Infection-triggered familial or recurrent cases of acute necrotizing encephalopathy caused by mutations in a component of the nuclear pore, RANBP2

Acute necrotizing encephalopathy (ANE) is a rapidly progressive encephalopathy that can occur in otherwise healthy children after common viral infections such as influenza and parainfluenza. Most ANE is sporadic and nonrecurrent (isolated ANE). However, we identified a 7 Mb interval containing a susceptibility locus (ANE1) in a family segregating recurrent ANE as an incompletely penetrant, autosomal-dominant trait. We now report that all affected individuals and obligate carriers in this family are heterozygous for a missense mutation (c.1880C-->T, p.Thr585Met) in the gene encoding the nuclear pore protein Ran Binding Protein 2 (RANBP2). To determine whether this mutation is the susceptibility allele, we screened controls and other patients with ANE who are unrelated to the index family. Patients from 9 of 15 additional kindreds with familial or recurrent ANE had the identical mutation. It arose de novo in two families and independently in several other families. Two other patients with familial ANE had different RANBP2 missense mutations that altered conserved residues. None of the three RANBP2 missense mutations were found in 19 patients with isolated ANE or in unaffected controls. We conclude that missense mutations in RANBP2 are susceptibility alleles for familial and recurrent cases of ANE.

Genetic analysis of human traits in vitro: drug response and gene expression in lymphoblastoid cell lines

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype–phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance—i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.

The use of lymphoblastoid cell lines (LCLs) has evolved from a renewable source of DNA to an in vitro model system to study the genetics of gene expression, drug response, and other traits in a controlled laboratory setting. While convincing relationships between SNPs and mRNA levels (eQTLs) have been described, the degree to which non-genetic variables also influence phenotypes in LCLs is less well characterized. In the course of attempting to map genes for drug responses in vitro, we evaluated the reproducibility of in vitro traits across replicates, the impact of the EBV virus used to transform B cells into cell lines, and the effect of in vitro culture conditions. We found that responses to at least some drugs and levels of many mRNAs can be technically well measured, but vary both across experiments and with non-genetic confounders such as growth rates, EBV levels, and ATP levels. The influence of such non-genetic factors can both decrease power to detect true relationships between DNA variation and traits and create the potential for non-genetic confounding and spurious associations between DNA variants and traits.

Polyspecificity of T cell and B cell receptor recognition

A recent workshop discussed the recognition of multiple distinct ligands by individual T cell and B cell receptors and the implications of this discovery for lymphocyte biology. The workshop recommends general use of the term polyspecificity because it emphasizes two fundamental aspects, the inherent specificity of receptor recognition and the ability to recognize multiple ligands. Many different examples of polyspecificity and the structural mechanisms were discussed, and the group concluded that polyspecificity is a general, inherent feature of TCR and antibody recognition. This review summarizes the relevance of polyspecificity for lymphocyte development, activation and disease processes.