Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation.

Non-lymphoid tissues (NLTs) harbor a pool of adaptive immune cells with largely unexplored phenotype and development. We used single-cell RNA-seq to characterize 35,000 CD4+ regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, their respective draining lymph nodes (LNs) and spleen. In these tissues, we identified Treg cell subpopulations with distinct degrees of NLT phenotype. Subpopulation pseudotime ordering and gene kinetics were consistent in recruitment to skin and colon, yet the initial NLT-priming in LNs and the final stages of NLT functional adaptation reflected tissue-specific differences. Predicted kinetics were recapitulated using an in vivo melanoma-induction model, validating key regulators and receptors. Finally, we profiled human blood and NLT Treg and Tmem cells, and identified cross-mammalian conserved tissue signatures. In summary, we describe the relationship between Treg cell heterogeneity and recruitment to NLTs through the combined use of computational prediction and in vivo validation.

Stereotyped B-cell responses are linked to IgG constant region polymorphisms in multiple sclerosis.

Clonally related B cells infiltrate the brain, meninges, and cerebrospinal fluid of MS patients, but the mechanisms driving the B-cell response and shaping the immunoglobulin repertoires remain unclear. Here, we used single-cell full-length RNA-seq and BCR reconstruction to simultaneously assess the phenotypes, isotypes, constant region polymorphisms, and the paired heavy- and light-chain repertoires in intrathecal B cells. We detected extensive clonal connections between the memory B cell and antibody-secreting cell (ASC) compartments and observed clonally related cells of different isotypes including IgM/IgG1, IgG1/IgA1, IgG1/IgG2, and IgM/IgA1. There was a strong dominance of the G1m1 allotype constant region polymorphisms in ASCs, but not in memory B cells. Tightly linked to the G1m1 allotype, we found a preferential pairing of the immunoglobulin heavy-chain variable (IGHV)4 gene family with the κ variable (IGKV)1 gene family. The IGHV4-39 gene was most used and showed the highest frequency of pairing with IGKV1-5 and IGKV1(D)-33. These results link IgG constant region polymorphisms to stereotyped B-cell responses in MS and indicate that the intrathecal B-cell response in these patients could be directed against structurally similar epitopes.

Polymorphisms in human immunoglobulin heavy chain variable genes and their upstream regions.

Germline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 potential novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-REGION in the 5'UTR, L-PART1 and L-PART2 sequences, and found that identical V-REGION alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-REGION but also in the upstream sequences of IGHV genes. Our findings provide a new perspective for annotating immunoglobulin repertoire sequencing data.

Generation of circulating autoreactive pre-plasma cells fueled by naive B cells in celiac disease.

Autoantibodies against the enzyme transglutaminase 2 (TG2) are characteristic of celiac disease (CeD), and TG2-specific immunoglobulin (Ig) A plasma cells are abundant in gut biopsies of patients. Here, we describe the corresponding population of autoreactive B cells in blood. Circulating TG2-specific IgA cells are present in untreated patients on a gluten-containing diet but not in controls. They are clonally related to TG2-specific small intestinal plasma cells, and they express gut-homing molecules, indicating that they are plasma cell precursors. Unlike other IgA-switched cells, the TG2-specific cells are negative for CD27, placing them in the double-negative (IgD-CD27-) category. They have a plasmablast or activated memory B cell phenotype, and they harbor fewer variable region mutations than other IgA cells. Based on their similarity to naive B cells, we propose that autoreactive IgA cells in CeD are generated mainly through chronic recruitment of naive B cells via an extrafollicular response involving gluten-specific CD4+ T cells.

Single-cell transcriptomics combined with proteomics of intrathecal IgG reveal transcriptional heterogeneity of oligoclonal IgG-secreting cells in multiple sclerosis.

The phenotypes of B lineage cells that produce oligoclonal IgG in multiple sclerosis have not been unequivocally determined. Here, we utilized single-cell RNA-seq data of intrathecal B lineage cells in combination with mass spectrometry of intrathecally synthesized IgG to identify its cellular source. We found that the intrathecally produced IgG matched a larger fraction of clonally expanded antibody-secreting cells compared to singletons. The IgG was traced back to two clonally related clusters of antibody-secreting cells, one comprising highly proliferating cells, and the other consisting of more differentiated cells expressing genes associated with immunoglobulin synthesis. These findings suggest some degree of heterogeneity among cells that produce oligoclonal IgG in multiple sclerosis.

Single-cell approaches to dissect adaptive immune responses involved in autoimmunity: the case of celiac disease.

Single-cell analysis is a powerful technology that has found widespread use in recent years. For diseases with involvement of adaptive immunity, single-cell analysis of antigen-specific T cells and B cells is particularly informative. In autoimmune diseases, the adaptive immune system is obviously at play, yet the ability to identify the culprit T and B cells recognizing disease-relevant antigen can be difficult. Celiac disease, a widespread disorder with autoimmune components, is unique in that disease-relevant antigens for both T cells and B cells are well defined. Furthermore, the celiac disease gut lesion is readily accessible allowing for sampling of tissue-resident cells. Thus, disease-relevant T cells and B cells from the gut and blood can be studied at the level of single cells. Here we review single-cell studies providing information on such adaptive immune cells and outline some future perspectives in the area of single-cell analysis in autoimmune diseases.

Single-Cell Analysis and Tracking of Antigen-Specific T Cells: Integrating Paired Chain AIRR-Seq and Transcriptome Sequencing: A Method by the AIRR Community.

Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) offers the possibility to access the nucleotide sequences of paired receptor chains from T-cell receptors (TCR) or B-cell receptors (BCR ). Here we describe two protocols and the downstream bioinformatic approaches that facilitate the integrated analysis of paired T-cell receptor (TR ) alpha/beta (TRA /TRB ) AIRR-seq, RNA sequencing (RNAseq), immunophenotyping, and antigen-binding information. To illustrate the methodologies with a use case, we describe how to identify, characterize, and track SARS-CoV-2-specific T cells over multiple time points following infection with the virus. The first method allows the analysis of pools of memory CD8+ cells, identifying expansions and contractions of clones of interest. The second method allows the study of rare or antigen-specific cells and allows studying their changes over time.

Longevity, clonal relationship, and transcriptional program of celiac disease-specific plasma cells.

Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGPs) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls and performed RNA sequencing with clonal inference and transcriptomic analysis of 3,251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific and non-disease-specific PCs and between short-lived and long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-Seq Data.

In this chapter, we describe TraCeR and BraCeR, our computational tools for reconstruction of paired full-length antigen receptor sequences and clonality inference from single-cell RNA-seq (scRNA-seq) data. In brief, TraCeR reconstructs T-cell receptor (TCR) sequences from scRNA-seq data by extracting sequencing reads derived from TCRs by aligning the reads from each cell against synthetic TCR sequences. TCR-derived reads are then assembled into full-length recombined TCR sequences. BraCeR builds on the TraCeR pipeline and accounts for somatic hypermutations (SHM) and isotype switching. Here we discuss experimental design, use of the tools, and interpretation of the results.

Mosaic deletion patterns of the human antibody heavy chain gene locus shown by Bayesian haplotyping.

Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding immunoglobulin genes is incomplete, resulting in conflicting VDJ gene assignments and biased genotype and haplotype inference. Haplotypes can be inferred using IGHJ6 heterozygosity, observed in one third of the people. Here, we propose a robust novel method for determining VDJ haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, enabling inference of deletions and copy number variations in the entire population. To test this method, we generated a multi-individual data set of naive B-cell repertoires, and found allele usage bias, as well as a mosaic, tiled pattern of deleted IGHD and IGHV genes. The inferred haplotypes may have clinical implications for genetic disease predispositions. Our findings expand the knowledge that can be extracted from antibody repertoire sequencing data.

Exploiting antigen receptor information to quantify index switching in single-cell transcriptome sequencing experiments.

By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms have been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as "index switching", which causes a proportion of the reads to be assigned to an incorrect sample. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-specific expression of antigen receptors on immune cells to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3000 and HiSeq 4000. By utilizing the unique antigen receptor expression, we could quantify the spread-of-signal from many different wells (n = 55 from total of three batches) due to index switching. Based on full-length T cell receptor (TCR) sequences from all samples reconstructed by TraCeR and TCR gene expression quantified by Kallisto, we found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 3.9% (interquartile range (IQR): 1.7%-7.3%). We did not detect any consistent patterns of certain indices to be more prone to switching than others, suggesting that index switching is a stochastic process. Our results confirm that index switching is a problem that affects samples run in multiplexed libraries on Illumina HiSeq 3000 and HiSeq 4000 platforms.

Genetic analysis of Ikaros target genes and tumor suppressor function in BCR-ABL1+ pre-B ALL.

Inactivation of the tumor suppressor gene encoding the transcriptional regulator Ikaros (IKZF1) is a hallmark of BCR-ABL1+ precursor B cell acute lymphoblastic leukemia (pre-B ALL). However, the mechanisms by which Ikaros functions as a tumor suppressor in pre-B ALL remain poorly understood. Here, we analyzed a mouse model of BCR-ABL1+ pre-B ALL together with a new model of inducible expression of wild-type Ikaros in IKZF1 mutant human BCR-ABL1+ pre-B ALL. We performed integrated genome-wide chromatin and expression analyses and identified Ikaros target genes in mouse and human BCR-ABL1+ pre-B ALL, revealing novel conserved gene pathways associated with Ikaros tumor suppressor function. Notably, genetic depletion of different Ikaros targets, including CTNND1 and the early hematopoietic cell surface marker CD34, resulted in reduced leukemic growth. Our results suggest that Ikaros mediates tumor suppressor function by enforcing proper developmental stage-specific expression of multiple genes through chromatin compaction at its target genes.