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Multiplexing in #singlecellproteomics can substantially increase throughput, but requires flexible and easy to implement, scalable and sensitive sample preparation strategies for highest data quality. In collaboration with the Slavov Lab, we demonstrate in this application note, an nPOP workflow that can accommodate different numbers of labels and different reagents simply by programming different configurations of droplets deposited on the surface of glass slides. nPOP with non-isobaric tags, or plexDIA approach, is providing an automated option for scaling up single-cell proteomics for analysis of thousands of single cells with proteome depths comparable to label-free DIA applications. We applied plexDIA in a fully automated 3-label approach on CFPAC-1 pancreatic cancer, WM-989 melanoma, and THP-1 leukemia cell lines (126 single cells in total) using the timsTOF Ultra in dia-PASEF mode. This approach allowed to analyze almost 100 samples per day with a proteome depth of more than 3000 proteins per cell (4500 in total) and quantification of > 80,000 precursors per individual plexDIA run. #TIMS separation aided in complexity reduction by MOMA. Intercalated MS1 scans in the dia-PASEF method increased the average number of data points per peak to 14.6 increasing quantitative accuracy. Read more: https://lnkd.in/euyegGUw #massspectrometry #proteomics #timsTOF

plexDIA for scalable single cell analysis

plexDIA for scalable single cell analysis

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