Synergistic Arg-C Ultra and Lys-C Digestion for Quantitative Proteomics

Abstract

Shotgun proteomics hinges on complete enzymatic digestion of proteins into peptides. Incomplete digestion narrows proteome coverage and inflates variability in quantitative workflows, whether label-free DIA or multiplexing with isobaric tags. Sequential Lys-C/Trypsin digestions mitigate missed cleavages at lysine residues, but arginine sites remain a persistent challenge. Arg-C Ultra, a recently released cysteine protease, efficiently targets arginine residues but requires reducing conditions that inactivate Lys-C activity and compromise NHS- ester labeling in multiplexed workflows. Here, we systematically characterized Arg-C Ultra and Lys-C with chromogenic substrates that mimic arginine- and lysine-containing peptides, as well as shotgun proteomics. Arg-C Ultra operates optimally at room temperature, pH 7.5-8.5, under reducing conditions, whereas Lys-C is most active at 37 {degrees}C, pH 7.5-8.5, yet rapidly loses activity when exposed to common reductants. Among tested reducing agents, 1 mM TCEP uniquely preserved TMTpro integrity while sustaining Arg-C Ultra activity. Guided by these insights, we established a sequential digestion workflow that is fully compatible with both label- free DIA and TMTpro multiplexing. Proteins are first digested overnight with Lys-C at 37 {degrees}C (pH 8.5), then treated with 1 mM TCEP and Arg-C Ultra at room temperature (pH 8.5). The resulting peptides can be analyzed directly by label-free DIA or subjected to TMTpro labeling for multiplexed quantification. Applied to HeLa cell lysates, this protocol achieved >99% arginine and 95% lysine cleavage efficiencies, boosting the number of quantified proteins by 6% in label- free DIA and 11% in TMTproC experiments. Replicate measurements displayed reproducibility that approached the limits set by ion statistics. Thus, the introduced synergistic Lys-C/Arg-C Ultra digestion strategy enhances proteome coverage with excellent quantitative reproducibility across both label-free and multiplexed platforms.