Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States.
Program in Chemical & Physical Biology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States.
J Proteome Res. 2023 May 5;22(5):1394-1405. doi: 10.1021/acs.jproteome.2c00206. Epub 2022 Jul 18.
Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from -infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, -means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.
空间靶向蛋白质组学分析特定细胞类型和组织内功能区域的蛋白质组。虽然空间背景对于理解生物过程通常是必不可少的，但由于数据的高维性质，解释亚区域特异性蛋白质谱可能具有挑战性。在这里，我们开发了一种用于快速探索从不同组织区域获得的差异蛋白质谱的多变量方法，并将其应用于分析从感染的鼠肾中收集的已发表的空间靶向蛋白质组学数据集，感染后 4 天和 10 天。数据分析过程快速过滤高维蛋白质组学数据，以揭示数百到数千个测量分子中相关的差异物种。我们采用主成分分析（PCA）对通过微液相提取表面分析质谱测量的蛋白质谱进行降维。随后，-均值聚类对 PCA 处理后的数据组按化学相似性对样本进行分组。聚类中心解释揭示了在两个时间点区分感染空间区域的蛋白质子集。这些蛋白质似乎参与三羧酸代谢组学途径、钙依赖性过程和细胞骨架组织。GO 分析进一步揭示了与组织损伤/修复和钙相关防御机制的关系。在传染病中的应用强调了随时间在脓肿区域的差异蛋白质组学变化，反映了宿主-病原体相互作用的动态性质。
