Bentzen Amalie K, Such Lina, Jensen Kamilla K, Marquard Andrea M, Jessen Leon E, Miller Natalie J, Church Candice D, Lyngaa Rikke, Koelle David M, Becker Jürgen C, Linnemann Carsten, Schumacher Ton N M, Marcatili Paolo, Nghiem Paul, Nielsen Morten, Hadrup Sine R
Department of Micro and Nanotechnology, Technical University of Denmark, Lyngby, Denmark.
Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.
Nat Biotechnol. 2018 Nov 19. doi: 10.1038/nbt.4303.
The promiscuous nature of T-cell receptors (TCRs) allows T cells to recognize a large variety of pathogens, but makes it challenging to understand and control T-cell recognition. Existing technologies provide limited information about the key requirements for T-cell recognition and the ability of TCRs to cross-recognize structurally related elements. Here we present a 'one-pot' strategy for determining the interactions that govern TCR recognition of peptide-major histocompatibility complex (pMHC). We measured the relative affinities of TCRs to libraries of barcoded peptide-MHC variants and applied this knowledge to understand the recognition motif, here termed the TCR fingerprint. The TCR fingerprints of 16 different TCRs were identified and used to predict and validate cross-recognized peptides from the human proteome. The identified fingerprints differed among TCRs recognizing the same epitope, demonstrating the value of this strategy for understanding T-cell interactions and assessing potential cross-recognition before selection of TCRs for clinical development.
T细胞受体(TCR)杂乱的特性使T细胞能够识别多种病原体,但这也给理解和控制T细胞识别带来了挑战。现有技术提供的关于T细胞识别关键要求以及TCR交叉识别结构相关元件能力的信息有限。在此,我们提出一种“一锅法”策略,用于确定支配TCR对肽 - 主要组织相容性复合体(pMHC)识别的相互作用。我们测量了TCR对条形码化肽 - MHC变体文库的相对亲和力,并运用这些知识来理解识别基序,在此称为TCR指纹。鉴定出了16种不同TCR的TCR指纹,并用于预测和验证来自人类蛋白质组的交叉识别肽。识别出的指纹在识别相同表位的TCR之间存在差异,这证明了该策略对于理解T细胞相互作用以及在选择用于临床开发的TCR之前评估潜在交叉识别的价值。