Abstract
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.
Highlights
Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes
There is considerable interest in proteomic analysis of LCM dissected tissues, as they promise to offer spatially-resolved insights into tissue-specific mechanisms and signaling that are obscured in bulk proteomics[1,11,33]
Current bottom-up proteomics workflows require several manual processing steps to generate peptides for liquid chromatography-mass spectrometry (LC-MS)/MS analysis, incurring significant sample losses and subsequently are not readily amenable to the minute samples generated by LCM
Summary
Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. This ‘proteomic reactor’ strategy has been modified to various supports such as a stop-and-go extraction tip[11], or by using paramagnetic beads to immobilize the sample inside a single test-tube during all the preparation steps[16] These proteomic reactor strategies require several manual steps during sample processing/handling and entail long processing times, challenging throughput, reproducibility and quantification accuracy for ultrasensitive proteomics applications[18,19,20]. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis approaches demonstrated significant improvements in quantification accuracy (approximately 2-fold lower coefficient of variation) and throughput (more than 5 times faster); suggesting that our LCM-proteomics platform provides a powerful approach for enabling spatially-resolved ultrasensitive proteomics analyses in clinical and developmental biology applications where quantification accuracy, sensitivity, and throughput are critical
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