Spatial top-down proteomics for the functional characterization of human kidney.
Spatial top-down proteomics for the functional characterization of human kidney.
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用于人类肾脏功能表征的空间自上而下蛋白质组学。
DOI：
10.1101/2024.02.13.580062
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Paša-Tolić,Ljiljana
中科院分区：
文献类型：
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作者：
Zemaitis,KevinJ;Fulcher,JamesM;Kumar,Rashmi;Degnan,DavidJ;Lewis,LoganA;Liao,Yen-Chen;Veličković,Marija;Williams,SarahM;Moore,RonaldJ;Bramer,LisaM;Veličković,Dušan;Zhu,Ying;Zhou,Mowei;Paša-Tolić,Ljiljana
人类蛋白质组计划已经可靠地检测到人类基因组预测的大约20,000种蛋白质中的近93%。然而，蛋白质组是一个谜，其中多态性和选择性剪接引起的氨基酸序列改变，翻译错误和翻译后修饰导致蛋白质组深度估计为数百万种独特的蛋白质形式。最近，质谱法已经在几项具有里程碑意义的工作中得到了证明，这些工作绘制了大量分析中的人类变形形态景观。在此，我们开发了一个集成的工作流程，通过耦合激光捕获显微解剖，纳米级样品制备和质谱成像，以空间分辨的方式表征来自人体组织的蛋白质形态。结果以健康人体肾脏切片为例，重点分析了肾小球、小管和髓质射线等主要功能组织单位。在激光捕获显微解剖后，这些分离的功能组织单元用微罐处理（微量样品在一个锅中微滴处理）进行敏感的自上而下的蛋白质组学测量。这提供了一个616种蛋白质形态的定量数据库，进一步利用它作为整个剖面的质谱成像库，具有近细胞的空间分辨率。值得注意的是，在肾小球和曲小管之间发现了几种线粒体蛋白形式的差异丰度，质谱成像进一步提供了空间背景，证实了micropot鉴定的独特差异，并进一步扩大了独特分布的视野，如皮质区域内泛素截断形式（1-74）的丰度增强。结论建立了一套完整的工作流程，可以直接识别蛋白质形态并揭示其空间分布。在微罐鉴定的区分小管和肾小球的20种差异丰富的蛋白形态中，绝大多数小管蛋白形态是线粒体起源的（10个中的8个），而肾小球中的区分蛋白形态主要是血红蛋白亚基（10个中的9个）。这些趋势也在离子图像中被识别出来，展示了蛋白质形态的空间分辨特征，这有可能重塑基于发现的蛋白质组学，因为蛋白质形态是细胞功能的最终效应器。该技术的应用有可能揭示疾病状态的病因学和病理生理学，揭示生物活性蛋白质形态，从而重塑慢性和急性疾病的蛋白质组学格局。
BackgroundThe Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging.ResultsUsing healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1–74) of ubiquitin within cortical regions.ConclusionsWe developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) while discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.