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

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
approach that combines three proteolytic digests (Trypsin, AspN, and
GluC) into a single sample. We first optimize data acquisition conditions
for each protease individually with both the canonical DIA fragmentation
mode (beam type CID), as well as resonance excitation CID, to determine
optimal consensus conditions across proteases. Next, we demonstrate
that application of these conditions to a protease-multiplexed sample
of human peptides results in similar protein identifications and quantitative
performance as compared to trypsin alone, but enables up to a 63%
increase in peptide detections, and a 45% increase in nonredundant
amino acid detections. Nontryptic peptides enabled noncanonical protein
isoform determination and resulted in 100% sequence coverage for numerous
proteins, suggesting the utility of this approach in applications
where sequence coverage is critical, such as protein isoform analysis.