Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

Sci Rep. 2016 Dec 22:6:39223. doi: 10.1038/srep39223.


Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, impacting measurement robustness, quantification and throughput. Here, we coupled LCM with a proteomics workflow that provides fully automated analysis of proteomes from microdissected tissues. Benchmarking against the current state-of-the-art in ultrasensitive global proteomics (FASP workflow), our approach demonstrated significant improvements in quantification (~2-fold lower variance) and throughput (>5 times faster). Using our approach we for the first time characterized, to a depth of >3,400 proteins, the ontogeny of protein changes during normal lung development in microdissected alveolar tissue containing only 4,000 cells. Our analysis revealed seven defined modules of coordinated transcription factor-signaling molecule expression patterns, suggesting a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Animals
  • Animals, Newborn
  • Automation
  • Chromatography, High Pressure Liquid
  • Laser Capture Microdissection
  • Lung / metabolism*
  • Mice
  • Mice, Inbred C57BL
  • Proteome / analysis*
  • Proteomics*
  • Tandem Mass Spectrometry


  • Proteome