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High Field Asymmetric Waveform Ion Mobility Spectrometry in Nontargeted Bottom-up Proteomics of Dried Blood Spots
Author(s) -
Cecilie Rosting,
Jinglei Yu,
Helen J. Cooper
Publication year - 2018
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.7b00746
Subject(s) - ion mobility spectrometry , proteomics , mass spectrometry , waveform , spots , dried blood , materials science , ion , chromatography , field (mathematics) , chemistry , analytical chemistry (journal) , computer science , biochemistry , gene , telecommunications , radar , mathematics , organic chemistry , pure mathematics
Despite the great potential of dried blood spots (DBS) as a source of endogenous proteins for biomarker discovery, the literature relating to nontargeted bottom-up proteomics of DBS is sparse, primarily due to the inherent complexity and very high dynamic range associated with these samples. Here, we present proof-of-concept results in which we have coupled high field asymmetric waveform ion mobility spectrometry (FAIMS) with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for nontargeted bottom-up proteomics of DBS with the aim of addressing these challenges. We, and others, have previously demonstrated the benefits of FAIMS more generally in proteomics including improved signal-to-noise and extended proteome coverage, and the aim of the current work was to extend those benefits specifically to DBS. The DBS samples were either extracted by the more traditional manual "punch and elute" approach or by an automated liquid surface extraction (LESA) approach prior to trypsin digestion. The resulting samples were analyzed by LC-MS/MS and LC-FAIMS-MS/MS analysis. The results show that the total number of proteins identified increased by ∼50% for the punch and elute samples and ∼45% for the LESA samples in the LC-FAIMS-MS/MS analysis. For both the punch and elute samples and the LESA samples, ∼30% of the total proteins identified were observed in both the LC-MS/MS and the LC-FAIMS-MS/MS data sets, illustrating the complementarity of the approaches. Overall, this work demonstrates the benefits of inclusion of FAIMS for nontargeted proteomics of DBS.

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