Balasubramaniam Meenakshisundaram, Ayyadevara Srinivas, Ganne Akshatha, Kakraba Samuel, Penthala Narsimha Reddy, Du Xiuxia, Crooks Peter A, Griffin Sue T, Shmookler Reis Robert J
McClellan Veterans Medical Ctr., Central Arkansas Veterans Healthcare Service, Little Rock, AR 72205, USA; Department of Geriatrics, Reynolds Institute on Aging, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Bioinformatics Program, University of Arkansas for Medical Sciences, University of Arkansas at Little Rock, Little Rock, AR 72205, USA.
iScience. 2019 Oct 25;20:248-264. doi: 10.1016/j.isci.2019.09.026. Epub 2019 Sep 21.
Diagnosis of neurodegenerative diseases hinges on "seed" proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APP-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the "aggregate contactome." Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases.
神经退行性疾病的诊断取决于在疾病特异性聚集体中检测到的“种子”蛋白。这些内含物包含多种成分，通过异常相互作用结合在一起，我们之前的数据表明这些相互作用是非随机的。为了确定介导聚集体聚结的优先蛋白质-蛋白质接触，我们创建了点击化学试剂，该试剂可交联人源APP驱动的神经母细胞瘤细胞聚集体中的相邻蛋白质。这些试剂含有一个生物素基团，以有效地回收连接的胰蛋白酶肽对。对质谱输出结果进行筛选，以找出聚集体蛋白质组中所有可能的肽对。这些按丰度排序的经验性连接涉及一个称为“聚集体接触组”的蛋白质粘附网络。通过RNAi介导的衰老线虫趋化性拯救来评估关键枢纽和枢纽-枢纽相互作用，并通过多元回归和神经网络方法推断聚集驱动特性。阿司匹林在破坏聚集的同时，极大地简化了聚集体接触组。这种方法及其所暗示的聚集体积累动态模型，揭示了不溶性聚集体网络的结构，并可能揭示易受干预以改善蛋白质聚集疾病的靶点。
