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Uncovering the Peptide-Binding Specificities of HLA-C: A General Strategy To Determine the Specificity of Any MHC Class I Molecule

机译:揭示HLa-C的肽结合特异性:确定任何mHC I类分子特异性的一般策略

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摘要

MHC class I molecules (HLA-I in humans) present peptides derived from endogenous proteins to CTLs. Whereas the peptide-binding specificities of HLA-A and -B molecules have been studied extensively, little is known about HLA-C specificities. Combining a positional scanning combinatorial peptide library approach with a peptide-HLA-I dissociation assay, in this study we present a general strategy to determine the peptide-binding specificity of any MHC class I molecule. We applied this novel strategy to 17 of the most common HLA-C molecules, and for 16 of these we successfully generated matrices representing their peptide-binding motifs. The motifs prominently shared a conserved C-terminal primary anchor with hydrophobic amino acid residues, as well as one or more diverse primary and auxiliary anchors at P1, P2, P3, and/or P7. Matrices were used to generate a large panel of HLA-C-specific peptide-binding data and update our pan-specific NetMHCpan predictor, whose predictive performance was considerably improved with respect to peptide binding to HLA-C. The updated predictor was used to assess the specificities of HLA-C molecules, which were found to cover a more limited sequence space than HLA-A and -B molecules. Assessing the functional significance of these new tools, HLA-C*07:01 transgenic mice were immunized with stable HLA-C*07:01 binders; six of six tested stable peptide binders were immunogenic. Finally, we generated HLA-C tetramers and labeled human CD8(+) T cells and NK cells. These new resources should support future research on the biology of HLA-C molecules. The data are deposited at the Immune Epitope Database, and the updated NetMHCpan predictor is available at the Center for Biological Sequence Analysis and the Immune Epitope Database.
机译:MHC I类分子(人类中的HLA-1)将源自内源性蛋白质的肽呈递给CTL。尽管已经广泛研究了HLA-A和-B分子的肽结合特异性,但对HLA-C特异性知之甚少。将位置扫描组合肽库方法与肽-HLA-I解离分析相结合,在这项研究中,我们提出了确定任何I类MHC分子的肽结合特异性的一般策略。我们将这种新颖的策略应用于17种最常见的HLA-C分子,对于其中的16种,我们成功生成了代表其肽结合基序的基质。这些基序突出地共有一个保守的C端主要锚,带有疏水氨基酸残基,以及一个或多个在P1,P2,P3和/或P7处的主要和辅助锚。矩阵用于生成大量HLA-C特异性肽结合数据,并更新了我们的泛特异性NetMHCpan预测因子,其预测性能相对于与HLA-C的肽结合显着提高。使用更新的预测因子评估HLA-C分子的特异性,发现该分子比HLA-A和-B分子具有更有限的序列空间。评估这些新工具的功能意义后,用稳定的HLA-C * 07:01结合剂免疫HLA-C * 07:01转基因小鼠。六个测试的稳定肽结合物中的六个具有免疫原性。最后,我们生成了HLA-C四聚体并标记了人类CD8(+)T细胞和NK细胞。这些新资源应支持HLA-C分子生物学的未来研究。数据存放在免疫表位数据库中,更新的NetMHCpan预测因子可在生物序列分析中心和免疫表位数据库中获得。

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