Digital Microfluidics for Microproteomic Analysis of Minute Mammalian Tissue Samples Enabled by a Photocleavable Surfactant

Proteome profiles of precious tissue samples have great clinical potential for accelerating disease biomarker discovery and promoting novel strategies for early diagnosis and treatment. However, tiny clinical tissue samples are often difficult to handle and analyze with conventional proteomic methods. Automated digital microfluidic (DMF) workflows facilitate the manipulation of size-limited tissue samples. Here, we report the assessment of a DMF microproteomics workflow enabled by a photocleavable surfactant for proteomic analysis of minute tissue samples. The surfactant 4-hexylphenylazosulfonate (Azo) was found to facilitate fast droplet movement on DMF and enhance the proteomics analysis. Comparisons of Azo and n-Dodecyl beta-D-maltoside (DDM) using small samples of HeLa digest standards and MCF-7 cell digests revealed distinct differences at the peptide level despite similar results at the protein level. The DMF microproteomics workflow was applied for the sample preparation of similar to 3 mu g biopsies from murine brain tissue. A total of 1969 proteins were identified in three samples, including established neural biomarkers and proteins related to synaptic signaling. Going forward, we propose that the Azo-enabled DMF workflow has the potential to advance the practical clinical application of DMF for the analysis of size-limited tissue samples.

Automated summary

The proteome profiles of small tissue samples have great clinical potential, but conventional proteomic methods are not suitable for analyzing these samples. Researchers have developed an automated digital microfluidic workflow using a photocleavable surfactant, which enables the efficient analysis of small tissue samples and identifies a large number of proteins.