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

Abstract

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).