Inflammatory bowel disease (IBD) is a chronic and debilitating disorder that has few treatment options due to a lack of comprehensive understanding of its molecular pathogenesis. We used multiplexed mass spectrometry to collect high-content information on protein phosphorylation in two different mouse models of IBD. Because the biological function of the vast majority of phosphorylation sites remains unknown, we developed Substrate-based Kinase Activity Inference (SKAI), a methodology to infer kinase activity from phosphoproteomic data. This approach draws upon prior knowledge of kinase-substrate interactions to construct custom lists of kinases and their respective substrate sites, termed kinase-substrate sets that employ prior knowledge across organisms. This expansion as much as triples the amount of prior knowledge available. We then used these sets within the Gene Set Enrichment Analysis framework to infer kinase activity based on increased or decreased phosphorylation of its substrates in a dataset. When applied to the phosphoproteomic datasets from the two mouse models, SKAI predicted largely non-overlapping kinase activation profiles. These results suggest that chronic inflammation may arise through activation of largely divergent signaling networks. However, the one kinase inferred to be activated in both mouse models was mitogen-activated protein kinase-activated protein kinase 2 (MAPKAPK2 or MK2), a serine/threonine kinase that functions downstream of p38 stress-activated mitogen-activated protein kinase. Treatment of mice with active colitis with ATI450, an orally bioavailable small molecule inhibitor of the MK2 pathway, reduced inflammatory signaling in the colon and alleviated the clinical and histological features of inflammation. These studies establish MK2 as a therapeutic target in IBD and identify ATI450 as a potential therapy for the disease.

中文翻译：

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基于底物的激酶活性推断可将MK2识别为结肠炎的驱动因素。

炎症性肠病（IBD）是一种慢性衰弱性疾病，由于对其分子发病机理缺乏全面的了解，因此几乎没有治疗选择。我们使用多重质谱技术收集了两种不同的IBD小鼠模型中有关蛋白质磷酸化的高含量信息。因为绝大多数磷酸化位点的生物学功能仍是未知的，所以我们开发了基于底物的激酶活性推断（SKAI），一种从磷酸化蛋白质组学数据推断激酶活性的方法。该方法利用了激酶与底物相互作用的先验知识来构建激酶及其各自底物位点的自定义列表，称为激酶-底物集，它利用了跨生物体的先验知识。这种扩展使现有知识的数量增加了三倍。然后，我们在“基因集富集分析”框架内使用了这些集合，以根据数据集中底物的磷酸化程度的升高或降低来推断激酶活性。当应用于来自两个小鼠模型的磷酸化蛋白质组学数据集时，SKAI预测了很大程度上不重叠的激酶激活谱。这些结果表明，慢性炎症可能是由于激活大量不同的信号网络而引起的。但是，在两种小鼠模型中均被认为是激活的一种激酶是促分裂原激活的蛋白激酶激活的蛋白激酶2（MAPKAPK2或MK2），一种丝氨酸/苏氨酸激酶，在p38应激激活的促分裂原激活的蛋白激酶的下游起作用。用ATI450（一种可口服生物利用的MK2途径的小分子抑制剂）治疗活动性结肠炎小鼠，减少了结肠中的炎症信号，并减轻了炎症的临床和组织学特征。这些研究将MK2确定为IBD的治疗靶标，并将ATI450鉴定为该疾病的潜在治疗方法。