Small ubiquitin-like modifiers (SUMO) and ubiquitin are frequent post-translational modifications of proteins that play pivotal roles in all cellular processes. We previously reported mass spectrometry-based proteomics methods that enable profiling of lysines modified by endogenous SUMO or ubiquitin in an unbiased manner, without the need for genetic engineering. Here we investigated the applicability of precursor mass filtering enabled by MaxQuant.Live to our SUMO and ubiquitin proteomics workflows, which efficiently avoided sequencing of precursors too small to be modified but otherwise indistinguishable by mass-to-charge ratio. Using precursor mass filtering, we achieved a much higher selectivity of modified peptides, ultimately resulting in up to 30% more SUMO and ubiquitin sites identified from replicate samples. Real-time exclusion of unmodified peptides by MQL resulted in 90% SUMO-modified precursor selectivity from a 25% pure sample, demonstrating great applicability for digging deeper into ubiquitin-like modificomes. We adapted the precursor mass filtering strategy to the new Exploris 480 mass spectrometer, achieving comparable gains in SUMO precursor selectivity and identification rates. Collectively, precursor mass filtering via MQL significantly increased identification rates of SUMO- and ubiquitin-modified peptides from the exact same samples, without the requirement for prior knowledge or spectral libraries.
Keywords: MQL; MaxQuant.Live; SUMO; exclusion; precursor mass filtering; targeting; ubiquitin.