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Updated: Jan 13, 2026

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor
Published on: April 6, 2016
Rapid and efficient in situ digestion of proteins by SoniCoat for MALDI mass spectrometry imaging
Yixin Pan1,2, Ke Jia3, Yijiao Qu1,2
1Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China.
Abstract:
Visualizing the spatial distribution of proteins in biological tissue sections is fundamental to proteomic analysis, as they provide intuitive and comprehensive information for understanding their function. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a powerful tool for characterizing the spatial distribution of biomolecules. Due to the low sensitivity and insufficient mass resolution of time-of-flight (TOF) mass spectrometers in the high mass range, conventional proteomics strategies typically employ tryptic digestion to cleave proteins into peptides (500-3500 Da) prior to detection. However, existing in situ digestion methods often require long digestion times (> 2h) and are prone to molecule diffusion, leading to the loss of intrinsic spatial information. The present study presented a rapid in situ tryptic digestion method using our self-developed automatic ultrasonic matrix sprayer, SoniCoat. Following digestion with trypsin sprayed with SoniCoat, the tissue was directly coated with α-cyano-4-hydroxycinnamic acid (CHCA) without incubation. Results demonstrated that this method yielded more peptide signals compared with conventional incubation-based approaches and commercial devices. In addition, high-quality images were obtained without molecule diffusion. The established protocol was subsequently applied to a mouse model of liver cancer, revealing spatial distribution differences of proteins between diseased and healthy regions. Our protocol holds promise for supporting the discovery of protein biomarkers for cancer diagnosis.
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