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. 2023 Oct 23;14:6725. doi: 10.1038/s41467-023-42430-z

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© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 5 — a Summary of LLL tetramer⁺ CD8⁺ T cells isolated from uninfected, COVID-19 convalescent donors, and in vitro expanded donors by cell sorting and scTCR-seq. b Top ten most used V genes of LLL⁺ CD8⁺ T cells. Histogram depicting the top ten most used V-genes (Vα and Vβ) in all LLL⁺ CD8⁺ T cells. c Validation of LLL-HLA-A2 binding and signaling of cloned selected LLL⁺TCRs. Tetramer binding percentage and LLL-HLA-A2 stimulation induced signaling presented by the ratio of GFP% induced by LLL-HLA-A2 over anti-CD3/CD28 stimulation post 4 h. d Classification of LLL-TCRs using TRAV12-2 by TCRDist. Dendrogram of clusters of LLL-TCR (TRAV-12-2) (N = 575 with percentage of each cluster) defined by TCRDist. Cluster 1,2,4 and 5 containing confirmed LLL-TCRs (N = 524) while cluster 3 did not (N = 51). e CDR3α and CDR3β motifs and their pairings of cluster 2. Motifs of each CDR3 length were generated by MEME Suite 5.5. The percentages of each combination between a CDR3α and a CDR3β motif in total number of LLL-TCRs (TRAV12-2) are presented. f Machine learning (ML) algorithm for predicting LLL-HLA-A2 binding TCRs. ROC of the predictive ability on unexposed testing TCRs of the ML algorithm for LLL-HLA-A2 TCR binding is 92.2%. g Proportion of ML predicted LLL-HLA-A2 binding TCRs in unique LLL⁺ TCRs (TRAV12-2) and total LLL⁺ (TRAV12-2) CD8⁺ T cells. The percentages of ML predicted LLL⁺ TCRs with scores greater than 0.8 are shown in unique LLL⁺ TCRs (TRAV12-2) and in total LLL⁺ (TRAV12-2) CD8⁺ T cells.