The Enzyme Effect: Broadening the Horizon of MS Optimization to Nontryptic Digestion in Proteomics

In
recent years, alternative enzymes with varied specificities
have gained importance in MS-based bottom-up proteomics, offering
orthogonal information about biological samples and advantages in
certain applications. However, most mass spectrometric workflows are
optimized for tryptic digests. This raises the questions of whether
enzyme specificity impacts mass spectrometry and if current methods
for nontryptic digests are suboptimal. The success of peptide and
protein identifications relies on the information content of MS/MS
spectra, influenced by collision energy in collision-induced dissociation.
We investigated this by conducting LC-MS/MS measurements with different
enzymes, including trypsin, Arg-C, Glu-C, Asp-N, and chymotrypsin,
at varying collision energies. We analyzed peptide scores for thousands
of peptides and determined optimal collision energy (CE) values. Our
results showed a linear m/z dependence
for all enzymes, with Glu-C, Asp-N, and chymotrypsin requiring significantly
lower energies than trypsin and Arg-C. We proposed a tailored CE selection
method for these alternative enzymes, applying ca. 20% lower energy
compared to tryptic peptides. This would result in a 10–15
eV decrease on a Bruker QTof instrument and a 5–6 NCE% (normalized
collision energy) difference on an Orbitrap. The optimized method
improved bottom-up proteomics performance by 8–32%, as measured
by peptide identification and sequence coverage. The different trends
in fragmentation behavior were linked to the effects of C-terminal
basic amino acids for Arg-C and trypsin, stabilizing y fragment ions.
This optimized method boosts the performance and provides insight
into the impact of enzyme specificity. Data sets are available in
the MassIVE repository (MSV000095066).