4.7 Article

Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets

期刊

MOLECULAR & CELLULAR PROTEOMICS
卷 17, 期 9, 页码 1864-1874

出版社

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/mcp.TIR118.000686

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资金

  1. NCI NIH HHS [R33 CA225248] Funding Source: Medline
  2. NIBIB NIH HHS [R21 EB020976] Funding Source: Medline
  3. NIDDK NIH HHS [DP3 DK110844, UC4 DK104167] Funding Source: Medline
  4. NIGMS NIH HHS [P41 GM103493] Funding Source: Medline
  5. NATIONAL CANCER INSTITUTE [R33CA225248] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [R21EB020976] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [DP3DK110844, UC4DK104167] Funding Source: NIH RePORTER
  8. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P41GM103493] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution because of the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 mu m in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-mu m-thick rat brain cortex tissue sections having diameters of 50, 100, and 200 m, respectively. We also analyzed 100-mu m-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified similar to 1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues.

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