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. 2021 Apr 20;93(15):6278-6286.
doi: 10.1021/acs.analchem.1c01205. Epub 2021 Apr 6.

Isobaric Peptide Labeling on Digital Microfluidics for Quantitative Low Cell Number Proteomics

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Isobaric Peptide Labeling on Digital Microfluidics for Quantitative Low Cell Number Proteomics

Jan Leipert et al. Anal Chem. .

Abstract

Digital microfluidics (DMF) is a technology suitable for bioanalytical applications requiring miniaturized, automated, and multiplexed liquid handling. Its use in LC-MS-based proteomics, however, has so far been limited to qualitative proteome analyses. This is mainly due to the need for detergents that enable facile, reproducible droplet movement, which are compatible with organic solvents commonly used in targeted chemical modifications of peptides. Aiming to implement isobaric peptide labeling, a widely applied technique allowing multiplexed quantitative proteome studies, on DMF devices, we tested different commercially available detergents. We identified the maltoside-based detergent 3-dodecyloxypropyl-1-β-d-maltopyranoside (DDOPM) to enable facile droplet movement and show micelle formation even in the presence of organic solvent, which is necessary for isobaric tandem mass tag (TMT) labeling. The detergent is fully compatible with reversed phase LC-MS, not interfering with peptide identification. Tryptic digestion in the presence of DDOPM was more efficient than without detergent, resulting in more protein identifications. Using this detergent, we report the first on-DMF chip isobaric labeling strategy, with TMT-labeling efficiency comparable to conventional protocols. The newly developed labeling protocol was evaluated in the multiplexed analyses of a protein standard digest spiked into 25 cells. Finally, using only 75 cells per biological replicate, we were able to identify 39 proteins being differentially abundant after treatment of Jurkat T cells with the anticancer drug doxorubicin. In summary, we demonstrate an important step toward multiplexed quantitative proteomics on DMF, which, in combination with larger chip arrays and optimized hardware, could enable high throughput low cell number proteomics.

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