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Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen Presentation

机译:质谱技术的人类白细胞抗原I类肽揭示了蛋白质丰度和营业额对抗原呈递的强烈影响。

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HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins - those with at least fivefold higher density score than expected for their abundance - we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use.
机译:HLA I类分子通过展示内源性衍生肽的种类,将细胞的健康状态反映为细胞毒性T细胞。但是,蛋白质组对肽组的形成程度仍是未知之数。在这里,我们提出了一种基于质谱的高通量工作流程,该流程允许严格,准确地鉴定数千种此类肽,并直接确定结合基序。将工作流程应用于七个癌细胞系和原代细胞,可产生跨越不同等位基因结合特异性的22,000多种独特HLA肽。通过计算代表HLA-1采样密度的分数,我们显示了蛋白质丰度与HLA表示之间的紧密联系(p <0.0001)。在分析过量表达的蛋白质时-那些密度得分至少比其预期丰度高出五倍的蛋白质-我们注意到它们的降解速度比相似但不存在的蛋白质快了将近3小时(丰度等级最高的20%;半衰期中位数为20.8h和23.6h ,p <0.0001)。这证实了蛋白质降解是HLA呈递的重要因素。核糖体,线粒体呼吸链和核小体蛋白表现得特别好。以一组与癌症相关的蛋白质为基础,我们在数据集中将先前验证的T细胞表位与这些蛋白质的其他肽的预测免疫原性进行了比较。经验证的表位确实往往比其他检测到的HLA肽具有更高的免疫原性评分。值得注意的是,我们从人结肠癌细胞系中鉴定出5种突变的肽,最近已预测它们是HLA-1结合物。总而言之,我们证明了将MS分析与免疫原性预测结合起来用于识别,分级和选择用于治疗的肽的有用性。

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