We present tetramer-associated T-cell receptor sequencing (TetTCR-Seq), a method to link T cell receptor (TCR) sequences to their cognate antigens in single cells at high throughput. Binding is determined using a library of DNA-barcoded antigen tetramers that is rapidly generated by in vitro transcription and translation. We applied TetTCR-Seq to identify patterns in TCR cross-reactivity with cancer neo-antigens and to rapidly isolate neo-antigen-specific TCRs with no cross-reactivity to the wild-type antigen.

T cells recognize and kill a myriad of pathogen-infected or cancer cells using a diverse set of T cell receptors (TCR). The affinity of TCR to cognate antigen is of high interest in adoptive T cell transfer immunotherapy and antigen-specific T cell repertoire immune profiling because it is widely known to correlate with downstream T cell responses. Here, we introduce the in situ TCR affinity and sequence test (iTAST) for simultaneous measurement of TCR affinity and sequence from single primary CD8+ T cells in human blood. We demonstrate that the repertoire of primary antigen-specific T cells from pathogen inexperienced individuals has a surprisingly broad affinity range of 1000-fold composed of diverse TCR sequences. Within this range, samples from older individuals contained a reduced frequency of high affinity T cells compared to young individuals, demonstrating an age-related effect of T cell attrition that could cause holes in the repertoire. iTAST should enable the rapid selection of high affinity TCRs ex vivo for adoptive immunotherapy and measurement of T cell response for immune monitoring applications.

The discovery of naturally occurring T cell receptors (TCRs) that confer specific, high-affinity recognition of pathogen and cancer-associated antigens remains a major goal in cellular immunotherapies. The contribution of the CD8 co-receptor to the interaction between the TCR and peptide-bound major histocompatibility complex (pMHC) has previously been correlated with the activation and responsiveness of CD8+ T cells. However, these studies have been limited to model systems of genetically engineered hybridoma TCRs or transgenic mouse TCRs against either a single epitope or an array of altered peptide ligands. CD8 contribution in a native human antigen-specific T cell response remains elusive. Here, using Hepatitis C Virus-specific precursor CTLs spanning a large range of TCR affinities, we discovered that the functional responsiveness of any given TCR correlated with the contribution of CD8 to TCR/pMHC binding. Furthermore, we found that CD8 contribution to TCR/pMHC binding in the two-dimensional (2D) system was more accurately reflected by normalized synergy (CD8 cooperation normalized by total TCR/pMHC bonds) rather than synergy (total CD8 cooperation) alone. While synergy showed an increasing trend with TCR affinity, normalized synergy was demonstrated to decrease with the increase of TCR affinity. Critically, normalized synergy was shown to correlate with CTL functionality and peptide sensitivity, corroborating three-dimensional (3D) analysis of CD8 contribution with respect to TCR affinity. In addition, we identified TCRs that were independent of CD8 for TCR/pMHC binding. Our results resolve the current discrepancy between 2D and 3D analysis on CD8 contribution to TCR/pMHC binding, and demonstrate that naturally occurring high-affinity TCRs are more capable of CD8-independent interactions that yield greater functional responsiveness even with CD8 blocking. Taken together, our data suggest that addition of the normalized synergy parameter to our previously established TCR discovery platform using 2D TCR affinity and sequence test would allow for selection of TCRs specific to any given antigen with the desirable attributes of high TCR affinity, CD8 co-receptor independence and functional superiority. Utilizing TCRs with less CD8 contribution could be beneficial for adoptive cell transfer immunotherapies using naturally occurring or genetically engineered T cells against viral or cancer-associated antigens.

The complex wavelet transform modulus maximum of the PD signal increases with scale, while the complex wavelet transform modulus maximum of white noise decreases with scale. According to the characteristics, a study on white noise suppression using the effective complex wavelet coefficient (ECWC) threshold method is launched in this paper and a comparison is conducted with the wavelet threshold denoising method of threshold selection of Stein unbiased risk estimate theory and threshold selection of minimax theory. The PD signal denoising results show that ECWC threshold method is more effective and the distortion of the extract PD signal is lower compared with the other method.