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SJTRC Study Team,

Publications and source records attributed to SJTRC Study Team,.

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TIRTL-seq: Deep, quantitative, and affordable paired TCR repertoire sequencing

[a]/{beta} 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) [a] and {beta} 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 (Throughput-Intensive Rapid TCR Library sequencing), 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 [a]{beta}TCR 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 5RACE 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 [a] and {beta} 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.

immunology↗

Establishing thresholds for cytokine storm and defining their relationship to disease severity in respiratory viral infections

Previous studies have identified cytokines associated with respiratory virus infection illness outcome. However, few studies have included comprehensive cytokine panels, longitudinal analyses, and/or simultaneous assessment across the severity spectrum. This, coupled with subjective definitions of cytokine storm syndrome (CSS), have contributed to inconsistent findings of cytokine signatures, particularly with COVID severity. Here, we measured 38 plasma cytokines and compared profiles in healthy, SARS-CoV-2 infected, and multisystem inflammatory syndrome in children (MIS-C) patients (n = 169). Infected patients spanned the severity spectrum and were classified as Asymptomatic, Mild, Moderate or Severe. Our results showed acute cytokine profiles and longitudinal dynamics of IL1Ra, IL10, MIP1b, and IP10 can differentiate COVID severity groups. Only 4% of acutely infected patients exhibited hypercytokinemia. Of these subjects, 3 were Mild, 3 Moderate, and 1 Severe, highlighting the lack of association between CSS and COVID severity. Additionally, we identified IL1Ra and TNFa as potential biomarkers for patients at high risk for long COVID. Lastly, we compare hypercytokinemia profiles across COVID and influenza patients and show distinct elevated cytokine signatures, wherein influenza induces the most elevated cytokine profile. Together, these results identify key analytes that, if obtained at early time points, can predict COVID illness outcome and/or risk of complications, and provide novel insight for improving the conceptual framework of hypercytokinemia, wherein CSS is a subgroup that requires concomitant severe clinical manifestations, and including a list of cytokines that can distinguish between subtypes of hypercytokinemia.

immunology↗