Mikhail V. Pogorelyy

Proteome diversity is generated through alternative mRNA splicing ¹ . In tumours, mis-spliced transcripts that contain intronic sequences, skipped exons or noncanonical donor/acceptor splice junctions resulting in frameshifts are often translated into neoantigens that drive anti-tumour immunity ^2,3 . Here we report that neutrophils from patients with systemic lupus erythematosus (SLE), unlike neutrophils from healthy donors or patients with rheumatoid arthritis, contain many aberrantly spliced gene transcripts, the translation of which was predicted to result in novel amino acid sequences that are absent in normal splice variants or any other proteins. Twenty-one peptides derived from these novel amino acid sequences were detected by mass spectrometry on class I major histocompatibility complex molecules in patient samples. Co-culture of T cells from patients with overlapping sets of 15-mer peptides from the novel sequences resulted in the expansion of CD4 ⁺ and CD8 ⁺ T cells that were rapidly reactivated to secrete interferon-γ. T cell antigen receptor sequencing and re-expression transferred neoantigen reactivity to a reporter T cell. Serum from patients with SLE also contained IgG autoantibodies that recognized epitopes within the novel amino acid sequences. Our findings demonstrate that dysregulated mRNA splicing in SLE neutrophils generates neoantigens that have caused T and B cell activation, clonal expansion, IgG class-switch and autoimmunity.

Combinatorial pairing of independently recombined T cell receptor (TCR) α- and β-chains is central to diversifying the TCR repertoire. Although sequence motifs in one chain correlate with epitope recognition, the extent to which a single chain dictates specificity remains unclear. Here, we systematically tested TCR chain coupling constraints by enforcing the pairing of individual chains with hundreds of thousands of partners. Although most chains paired stably, the preservation of epitope specificity was rare and highly variable, with the frequency of compatible partners ranging from ~10 to 70,000 epitope-specific TCRs across 10 epitopes. Our work illuminates the distinct contributions of TCR chains, highlights the limitations of single-chain data, and provides an experimental and analytical framework for refining TCR-peptide-major histocompatibility complex specificity inference.

The specificity of T cells is determined by T cell receptor (TCR) α and β chain sequences. While bulk TCR sequencing enables cost-effective repertoire profiling without chain pairing information, single-cell approaches provide paired data but are costly and limited in throughput. Here we present throughput-intensive rapid TCR library sequencing (TIRTL-seq), an experimental and computational methodology for paired TCR repertoire sequencing (TCR-seq). TIRTL-seq is based on the parallel generation of hundreds of TCR libraries in 384-well plates at less than US$200 per plate, allowing cohort-scale paired TCR-seq studies. We benchmarked TIRTL-seq against state-of-the-art bulk TCR-seq and 10x Genomics Chromium technologies on longitudinal samples and identified severe acute respiratory syndrome coronavirus 2- and Epstein–Barr virus-specific clonal expansions after infection with distinct dynamics. TIRTL-seq offers a universal protocol scalable from a single cell to millions of T cells per sample, simultaneously delivering both precise clonal frequency estimation and accurate TCR chain pairing, combining the strengths of bulk and single-cell TCR-seq.

T cell receptors (TCRs) recognize peptides presented by polymorphic human leukocyte antigen (HLA) molecules, but HLA genotype data are often missing from TCR repertoire sequencing studies. To address this, we developed TCR2HLA, an open-source tool that infers HLA genotypes from TCRβ repertoires. Expanding on work linking public TRBV-CDR3 sequences to HLA genotypes, we incorporated “quasi-public” metaclonotypes – composed of rarer TCRβ sequences with shared amino acid features – enriched by HLA genotypes. Using four TCRβseq datasets from 3,150 individuals, we applied TRBV gene partitioning and locality-sensitive hashing to identify ∼96,000 TCRβ features strongly associated with specific HLA alleles from 71M input TCRs. Binary HLA classifiers built with these features achieved high balanced accuracy (>0.9) across common HLA-A (9/12), B (9/12), C (6/13), DRB1 (11/11) alleles and prevalent DPA1/DPB1 (6/10), DQA1/DQB1 (8/17) heterodimers. We also introduced a high-sensitivity calibration to support predictions in samples with as few as 5,000 unique clonotypes. Calibrated predictions with confidence filtering improved reliability. Beyond genotype imputation, TCR2HLA enables the discovery of novel HLA- and exposure-associated TCRs, as shown by the identification of SARS-CoV-2 related TCRs in a large COVID-19 dataset lacking HLA data. TCR2HLA provides a scalable framework for bridging the gap between TCRseq data and HLA genotype for biomarker discovery.

ɑ/β T cells are key players in adaptive immunity. The specificity of T cells is determined by the sequences of the hypervariable T cell receptor (TCR) ɑ and β chains. Although bulk TCR sequencing offers a cost-effective approach for in-depth TCR repertoire profiling, it does not provide chain pairings, which are essential for determining T cell specificity. In contrast, single-cell TCR sequencing technologies produce paired chain data, but are limited in throughput to thousands of cells and are cost-prohibitive for cohort-scale studies. Here, we present TIRTL-seq (T hroughput- I ntensive R apid T CR L ibrary seq uencing ) , a novel approach that generates ready-to-sequence TCR libraries from live cells in less than 7 hours. The protocol is optimized for use with non-contact liquid handlers in an automation-friendly 384-well plate format. Reaction volume miniaturization reduces library preparation costs to <$0.50 per well. The core principle of TIRTL-seq is the parallel generation of hundreds of libraries providing multiple biological replicates from a single sample that allows precise inference of both frequencies of individual clones and TCR chain pairings from well-occurrence patterns. We demonstrate scalability of our approach up to 1 million unique paired ɑβTCR clonotypes corresponding to over 30 million T cells per sample at a cost of less than $2000. For a sample of 10 million cells the cost is ∼$200. We benchmarked TIRTL-seq against state-of-the-art 5’RACE bulk TCR-seq and 10x Genomics Chromium technologies on longitudinal samples. We show that TIRTL-seq is able to quantitatively identify expanding and contracting clonotypes between timepoints while providing accurate TCR chain pairings, including distinct temporal dynamics of SARS-CoV-2-specific and EBV-specific CD8+ T cell responses after infection. While clonal expansion was followed by sharp contraction for SARS-CoV-2 specific TCRs, EBV-specific TCRs remained stable once established. The sequences of both ɑ and β TCR chains are essential for determining T cell specificity. As the field moves towards greater applications in diagnostics and immunotherapy that rely on TCR specificity, we anticipate that our scalable paired TCR sequencing methodology will be instrumental for collecting large paired-chain datasets and ultimately extracting therapeutically relevant information from the TCR repertoire.

T cell receptor (TCR) repertoire diversity enables the antigen-specific immune responses against the vast space of possible pathogens. Identifying TCR-antigen binding pairs from the large TCR repertoire and antigen space is crucial for biomedical research. Here, we introduce copepodTCR , an open-access tool to design and interpret high-throughput experimental TCR specificity assays. copepodTCR implements a combinatorial peptide pooling scheme for efficient experimental testing of T cell responses against large overlapping peptide libraries, that can be used to identify the specificity of (or “deorphanize”) TCRs. The scheme detects experimental errors and, coupled with a hierarchical Bayesian model for unbiased interpretation, identifies the response-eliciting peptide sequence for a TCR of interest out of hundreds of peptides tested using a simple experimental set-up. Using in silico simulations, we demonstrate the varied experimental settings in which copepodTCR yields efficient and interpretable TCR specificity results. We validated our approach on a library of 253 overlapping peptides covering the SARS-CoV-2 spike protein, split across 12 pools. A single stimulation with combinatorial pools identified the correct epitope of two TCRs with known specificity and then deorphanized two SARS-CoV-2 associated TCRs shared among a large cohort of COVID-19 patients. We provide experimental guides to efficiently design larger screens covering thousands of peptides which will be crucial to identify antigen-specific T cells and their targets from limited clinical material.

Current chimeric antigen receptor-modified (CAR) T-cell products are evaluated in bulk, without assessing functional heterogeneity. We therefore generated a comprehensive single-cell gene expression and T-cell receptor (TCR) sequencing data set using pre- and postinfusion CD19-CAR T cells from blood and bone marrow samples of pediatric patients with B-cell acute lymphoblastic leukemia. We identified cytotoxic postinfusion cells with identical TCRs to a subset of preinfusion CAR T cells. These effector precursor cells exhibited a unique transcriptional profile compared with other preinfusion cells, corresponding to an unexpected surface phenotype (TIGIT+, CD62Llo, CD27−). Upon stimulation, these cells showed functional superiority and decreased expression of the exhaustion-associated transcription factor TOX. Collectively, these results demonstrate diverse effector potentials within preinfusion CAR T-cell products, which can be exploited for therapeutic applications. Furthermore, we provide an integrative experimental and analytic framework for elucidating the mechanisms underlying effector development in CAR T-cell products.Significance:Utilizing clonal trajectories to define transcriptional potential, we find a unique signature of CAR T-cell effector precursors present in preinfusion cell products. Functional assessment of cells with this signature indicated early effector potential and resistance to exhaustion, consistent with postinfusion cellular patterns observed in patients.This article is highlighted in the In This Issue feature, p. 2007

Supplementary Data from Common Trajectories of Highly Effective CD19-Specific CAR T Cells Identified by Endogenous T-cell Receptor Lineages

Supplementary Figure from Common Trajectories of Highly Effective CD19-Specific CAR T Cells Identified by Endogenous T-cell Receptor Lineages

Supplementary Data from Common Trajectories of Highly Effective CD19-Specific CAR T Cells Identified by Endogenous T-cell Receptor Lineages