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Updated: Jan 1, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
Automated Spatially Targeted Optical Microproteomics (autoSTOMP) to Determine Protein Complexity of Subcellular
Bocheng Yin1, Roberto Mendez2, Xiao-Yu Zhao1
1Department of Microbiology, Immunology and Cancer Biology and the Carter Immunology Center , University of Virginia School of Medicine , Charlottesville , Virginia 22908-0395 , United States.
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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