Defining high-resolution T-cell correlates of protection in abortive versus seropositive SARS-CoV-2 infection

我们最近证明，暴露于未检测到感染的SARS-CoV-2（重复PCR-抗体-）会扩大血清阴性卫生保健工作者（HCW）的t细胞反应，这些卫生保健工作者具有与亚临床/流产感染相容的先天特征（Swadling.Nature.2022）。重要的是，我们在这种抵抗显性感染的HCW的独特环境中发现，他们的t细胞优先靶向SARS-CoV-2的非结构区域，特别是复制转录复合体中的必需蛋白（RTC； NSP12聚合酶，NSP7辅助因子，NSP13解旋酶）。相反，t细胞反应在HCW谁有明显的血清阳性感染主要针对病毒的结构区域。最近发现了rtc特异性t细胞的扩增与早期病毒控制之间的关联，我们现在将以更高的分辨率表征这些t细胞，以确定除了特异性之外，是否存在特定的品质，这可以解释它们介导早期病毒控制的能力。我们将研究预先存在的交叉反应性t细胞，招募到免疫反应中，以及在流产感染期间重新产生的t细胞，并将其与显性SARS-CoV-2感染期间的t细胞反应进行比较。第一部分：这将包括通过光谱细胞术对sars - cov -2反应性t细胞的功能评估，该技术允许多参数单细胞分析，最大限度地从罕见样本中获得见解。MHC I/II类多聚体和激活诱导标记测定（AIM）将用于研究t细胞表型，包括：记忆亚群、运输、转录因子谱、共抑制和共刺激受体。高维数据将需要降维和新兴的数据可视化工具，如UMAP/tSNE/SPADE/Flowsom。第二部分：除了全面评估流产感染期间t细胞反应的质量外，我们还将进一步完善与可检测的SARS-COV-2感染保护相关的t细胞的特异性。RTC区域内的表位将使用尖端的机器学习工具进行识别，例如由RBM-MHC的合作者Bravi博士（帝国数学）开发的工具。将对这些表位进行验证，并通过队列筛查（covid - sortium, n=731 ~70例流产感染~140例实验室确诊感染）确定它们与流产感染的关联。第三部分：最后，通过使用RTC肽扩增t细胞并对tcr进行测序，通过创建RTC- t细胞受体文库，利用tcr -库分析鉴定免疫显性表位。重要的是，tcr将根据序列相似性聚集成元克隆型，由Tiffeau-Mayer博士（伦敦大学学院，印度理工学院）的机器学习方法确定，允许针对RTC的tcr进行个体间比较。还将挖掘公开可用的TCR库，以查看哪些rtc特异性TCR在大流行前库中扩增，显示它们与大流行前流行的冠状病毒交叉反应，以及来自支气管肺泡灌洗液样本的库，显示在冠状病毒控制位点富集。这项工作将最终确定特定的TCR序列基序或TCR-表位对是否与可检测的SARS-CoV-2感染的保护相关。总体而言，我们将采取整体方法，检查靶向SARS-CoV-2 RTC的T细胞的精细表位和TCR特异性以及功能和表型特征，以完善这种保护关联，从而更好地了解T细胞在病毒控制中的作用，并告知下一代疫苗应该针对的T细胞免疫类型。

We have recently demonstrated that exposure to SARS-CoV-2 without detectable infection (repeatedly PCR- antibody-) expands T-cell responses in seronegative health care workers (HCW) who have an innate signature compatible with a subclinical/abortive infection (Swadling.Nature.2022). Importantly, we show in this unique setting of HCW who resist overt infection, that their T-cells preferentially target the non-structural regions of SARS-CoV-2, in particular essential proteins within the replication-transcription complex (RTC; NSP12 polymerase, NSP7 cofactor, NSP13 helicase). In contrast, T-cell responses in HCW who have overt seropositive infection predominantly target structural regions of the virus. Having newly identified an association between expansion of RTC-specific T-cells and early viral control, we will now characterise these T-cells at greater resolution to determine if there are specific qualities, other than specificity, which could explain their ability to mediate early viral control. We will investigate both pre-existing cross-reactive T-cells, recruited into the immune response, and T-cells generated de novo during abortive infection, and contrast these with T-cells responses during overt SARS-CoV-2 infection. Part-I: This will include functional assessment of SARS-CoV-2-reactive T-cells via spectral cytometry, which allows multiparameter single cell analysis, maximising insights from rare samples. MHC class I/II multimers and Activation-induced marker assay (AIM) will be used to investigate T-cell phenotypes, including: memory subset, trafficking, transcription factor profile, coinhibitory and costimulatory receptors. High-dimensional data will require dimension reduction and emerging data visualisation tools, such as UMAP/tSNE/SPADE/Flowsom. Part-II: In addition to comprehensive assessment of the quality of the T-cell response during abortive infection, we will further refine the specificity of the T-cells correlating with protection from detectable SARS-COV-2 infection. Epitopes within the RTC region will be identified using cutting-edge machine learning tools, such as those develop by collaborator Dr Bravi (Imperial Mathematics), RBM-MHC. These epitopes will be validated and their association with abortive infection determined through cohort screening (COVIDSortium, n=731 ~70 abortive infections ~140 lab-confirmed infections). Part-III: Finally, immunodominant epitopes will be identified using TCR-repertoire analysis, through the creation of an RTC-T-cell receptor library, generated by expanding T-cells using RTC peptides and sequencing TCRs. Importantly, TCRs will be clustered into metaclonotypes according to sequenced similarity, determined by machine-learning approach with Dr Tiffeau-Mayer (UCL, IIT), allowing inter-individual comparisons of the TCRs targeting the RTC. Publicly available TCR repertoires will also be mined to see if which RTC-specific TCRs are expanded in pre-pandemic repertoires, showing they are cross-reactive with coronaviruses circulating before the pandemic, and repertoires from bronchoalveolar lavage samples, showing enrichment at the site of coronavirus control. This work will ultimately identify if specific TCR sequence motifs or TCR-epitope pairs correlate with protection from detectable SARS-CoV-2 infection. Overall, we will take a holistic approach, examining the fine epitope and TCR specificity and functional and phenotypic characteristics of T-cells targeting the RTC of SARS-CoV-2 to refine this correlate of protection, leading to a greater understanding of the role of T cells in viral control and informing the type of T-cell immunity that should be aimed for with next generation vaccines.