Automated Spatially Targeted Optical Microproteomics (autoSTOMP) to Determine Protein Complexity of Subcellular Structures

自动化空间靶向光学微蛋白质组学 (autoSTOMP) 确定亚细胞结构的蛋白质复杂性

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作者:Bocheng Yin, Roberto Mendez, Xiao-Yu Zhao, Rishi Rakhit, Ku-Lung Hsu, Sarah E Ewald

Abstract

Spatially targeted optical microproteomics (STOMP) is a method to study region-specific protein complexity in primary cells and tissue samples. STOMP uses a confocal microscope to visualize structures of interest and to tag the proteins within those structures by a photodriven cross-linking reaction so that they can be affinity purified and identified by mass spectrometry (eLife 2015, 4, e09579). However, the use of a custom photo-cross-linker and the requirement for extensive user intervention during sample tagging have posed barriers to the utilization of STOMP. To address these limitations, we built automated STOMP (autoSTOMP) which uses a customizable code in SikuliX to coordinate image capture and cross-linking functions in Zeiss Zen Black with image processing in FIJI. To increase protocol accessibility, we implemented a commercially available biotin-benzophenone photo-cross-linking and purification protocol. Here we demonstrate that autoSTOMP can efficiently label, purify, and identify proteins belonging to 1-2 μm structures in primary human foreskin fibroblasts or mouse bone marrow-derived dendritic cells infected with the protozoan parasite Toxoplasma gondii (Tg). AutoSTOMP can easily be adapted to address a range of research questions using Zeiss Zen Black microscopy systems and LC-MS protocols that are standard in many research cores.

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