Institute for System Analysis and Computer Science "Antonio Ruberti", National Research Council of Italy, Via dei Taurini 19, Rome 00185, Italy.
Institute for System Analysis and Computer Science "Antonio Ruberti", National Research Council of Italy, Via dei Taurini 19, Rome 00185, Italy.
Virus Res. 2022 Aug;317:198814. doi: 10.1016/j.virusres.2022.198814. Epub 2022 May 16.
Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response and, thus, identify potential targets and design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight inter-correlation, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.
适应性免疫反应是在特定的病原体肽（称为表位）被识别为外源性时触发的，根据自我/非我的范例。为了被免疫细胞识别，表位必须暴露（呈递）在细胞表面。预测肽是否暴露对于阐明控制免疫反应的规则很重要，从而识别潜在的靶标并设计疫苗和药物。我们专注于细胞表面暴露的肽，并使其通过 MHC 类 I 复合物可被免疫系统识别。在这之前，必须发生三个连续的选择步骤：a）蛋白酶体切割，b）TAP 转运，和 c）与 MHC 类 I 结合。从一组 211 种宿主人类参考病毒开始，我们计算了对应蛋白质组中出现的独特肽的集合。然后，我们通过已建立的预测软件工具获得与这些肽相关的蛋白酶体切割、TAP 转运和与 MHC 类 I 结合的概率值。通过结合另外两个可能起主要作用的特征来分析这些值：与 nullomers 概念严格相关的自距离，以及测量肽氨基酸组成复杂性的序列熵。该分析在更大、更显著和更一致的数据集上证实和扩展了以前的结果；我们表明，与自我的距离越高，TAP 转运和与 MHC 类 I 结合的得分越高；而与自我的距离与蛋白酶体切割之间没有发现显著的相关性。此外，氨基酸肽组成熵与其他特征显著相关。特别是，较高的熵与蛋白酶体切割、TAP 转运、与 MHC 类 I 结合以及与自我的距离较高的得分相关。三个选择步骤之间的关系提供了紧密的相互关联的证据，清楚地表明这可能是一个共同进化过程的产物。我们认为，这些结果为调节 MHC 类 I 中肽呈递的复杂过程提供了新的见解，并揭示了允许免疫系统区分自我和病毒非自我肽的机制。
