Proteomics

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Data-independent acquisition protease-multiplexing enables increased proteome sequence coverage across multiple fragmentation modes


ABSTRACT: The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments, but due to the additional sample preparation and analysis time required, it has not been widely adapted in routine proteomic workflows. While data-independent acquisition (DIA) has been primarily optimized for fragmenting tryptic peptides with beam type (bt)-CID, it has the potential to analyze multiplexed samples from different protease digests. Here we evaluate a DIA multiplexing method that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize DIA conditions for both resonance excitation (re-CID) and bt-CID to determine the optimal consensus fragmentation conditions for tryptic and non-tryptic peptides, and apply these methods to a human cell line. We demonstrate that using this multiplexed approach results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, resulting in up to a 8% increase in average sequence coverage. Importantly, this resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as proteoform analysis.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Alicia Richards  

LAB HEAD: Danielle L. Swaney

PROVIDER: PXD027242 | Pride | 2022-03-18

REPOSITORIES: Pride

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Publications

Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes.

Richards Alicia L AL   Chen Kuei-Ho KH   Wilburn Damien B DB   Stevenson Erica E   Polacco Benjamin J BJ   Searle Brian C BC   Swaney Danielle L DL  

Journal of proteome research 20220302 4


The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments; however, due to the additional analysis time required, it has not been widely adopted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing appr  ...[more]

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