Department II of Internal Medicine, University of Cologne, 50931 Cologne, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, 50931 Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD), University of Cologne, 50931 Cologne, Germany; Systems Biology of Ageing Cologne (Sybacol), University of Cologne, 50931 Cologne, Germany.
III. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany; Department of Medicine IV, Medical Center and Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany.
Cell Rep. 2018 May 22;23(8):2495-2508. doi: 10.1016/j.celrep.2018.04.059.
Damage to and loss of glomerular podocytes has been identified as the culprit lesion in progressive kidney diseases. Here, we combine mass spectrometry-based proteomics with mRNA sequencing, bioinformatics, and hypothesis-driven studies to provide a comprehensive and quantitative map of mammalian podocytes that identifies unanticipated signaling pathways. Comparison of the in vivo datasets with proteomics data from podocyte cell cultures showed a limited value of available cell culture models. Moreover, in vivo stable isotope labeling by amino acids uncovered surprisingly rapid synthesis of mitochondrial proteins under steady-state conditions that was perturbed under autophagy-deficient, disease-susceptible conditions. Integration of acquired omics dimensions suggested FARP1 as a candidate essential for podocyte function, which could be substantiated by genetic analysis in humans and knockdown experiments in zebrafish. This work exemplifies how the integration of multi-omics datasets can identify a framework of cell-type-specific features relevant for organ health and disease.
肾小球足细胞的损伤和丢失已被确定为进行性肾脏疾病的罪魁祸首病变。在这里,我们结合基于质谱的蛋白质组学与 mRNA 测序、生物信息学和假设驱动的研究,提供了哺乳动物足细胞的全面和定量图谱,确定了意想不到的信号通路。将体内数据集与足细胞细胞培养的蛋白质组学数据进行比较表明,现有的细胞培养模型的价值有限。此外,在稳定状态条件下,通过氨基酸进行体内稳定同位素标记出人意料地揭示了线粒体蛋白的快速合成,而在自噬缺陷、易患病的条件下,这种合成会受到干扰。获得的组学维度的整合表明 FARP1 是足细胞功能所必需的候选物,这可以通过人类的遗传分析和斑马鱼的敲低实验得到证实。这项工作例证了如何整合多组学数据集可以确定与器官健康和疾病相关的细胞类型特异性特征的框架。