4.7 Article

Automated Spatially Targeted Optical Microproteomics Investigates Inflammatory Lesions In Situ

期刊

JOURNAL OF PROTEOME RESEARCH
卷 20, 期 9, 页码 4543-4552

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.1c00505

关键词

AutoSTOMP; discovery proteomics; inflammation; proximity biotinylation

资金

  1. NIH [R21AI156153, R35GM138381]
  2. AHA/Allen Institute [31315]
  3. University of Virginia SOM
  4. Emily Couric Cancer Center

向作者/读者索取更多资源

The study developed a new method (AutoSTOMP) to investigate protein expression in tissues, by UV-biotinylating proteins in specific regions, using liquid chromatography-mass spectrometry and label-free quantification to measure protein abundance in cell types or structures. This method has been successfully applied in studies of rat cardiac infarcts and human esophageal tissues.
Tissue microenvironment properties like blood flow, extracellular matrix, or proximity to immune-infiltrate are important regulators of cell biology. However, methods to study regional protein expression in the native tissue environment are limited. To address this need, we developed a novel approach to visualize, purify, and measure proteins in situ using automated spatially targeted optical microproteomics (AutoSTOMP). Here, we report custom codes to specify regions of heterogeneity in a tissue section and UV-biotinylate proteins within those regions. We have developed liquid chromatography-mass spectrometry (LC-MS)/MS-compatible biochemistry to purify those proteins and label-free quantification methodology to determine protein enrichment in target cell types or structures relative to nontarget regions in the same sample. These tools were applied to (a) identify inflammatory proteins expressed by CD68(+) macrophages in rat cardiac infarcts and (b) characterize inflammatory proteins enriched in IgG4(+) lesions in human esophageal tissues. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools and sample availability are limited.

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