To improve proteome coverage and protein C-terminal identification, we characterized the Methanosarcina acetivorans thermophilic proteinase LysargiNase, which cleaves before lysine and arginine up to 55 °C. Unlike trypsin, LysargiNase-generated peptides had N-terminal lysine or arginine residues and fragmented with b ion-dominated spectra. This improved protein C terminal-peptide identification and several arginine-rich phosphosite assignments. Notably, cleavage also occurred at methylated or dimethylated lysine and arginine, facilitating detection of these epigenetic modifications.

A combined glycomics and glycoproteomics strategy was developed for the site-specific analysis of N-linked glycosylation heterogeneity from a complex mammalian protein mixture. Initially, global characterization of the N-glycome was performed using porous graphitized carbon liquid chromatography-tandem mass spectrometry (PGC-LC-MS/MS) and the data used to create an N-glycan modification database. In the next step, tryptic glycopeptides were enriched using zwitterionic hydrophilic interaction liquid chromatography (Zic-HILIC) and fractionated by reversed-phase liquid chromatography (RPLC; pH 7.9). The resulting fractions were each separated into two equal aliquots. The first set of aliquots were treated with peptide-N-glycosidase F (PNGase F) to remove N-glycans and the former N-glycopeptides analyzed by nano-RPLC-MS/MS (pH 2.7) and identified by Mascot database search. This enabled the creation of a glycopeptide-centric concatenated database for each fraction. The second set of aliquots was analyzed directly by nanoRPLC-MS/MS (pH 2.7), employing fragmentation by CID and HCD. The assignment of glycan compositions to peptide sequences was achieved by searching the N-glycopeptide HCD MS/MS spectra against the glycopeptide-centric concatenated databases employing the N-glycan modification database. CID spectra were used to assign glycan structures identified in the glycomic analysis to peptide sequences. This multidimensional approach allowed confident identification of 863 unique intact N-linked glycopeptides from 161 rat brain glycoproteins.

The main viral protease (3CL pro ) is indispensable for SARS-CoV-2 replication. We delineate the human protein substrate landscape of 3CL pro by TAILS substrate-targeted N-terminomics. We identify >100 substrates in human lung and kidney cells supported by analyses of SARS-CoV-2-infected cells. Enzyme kinetics and molecular docking simulations of 3CL pro engaging substrates reveal how noncanonical cleavage sites, which diverge from SARS-CoV, guide substrate specificity. Cleaving the interactors of essential effector proteins, effectively stranding them from their binding partners, amplifies the consequences of proteolysis. We show that 3CL pro targets the Hippo pathway, including inactivation of MAP4K5, and key effectors of transcription, mRNA processing, and translation. We demonstrate that Spike glycoprotein directly binds galectin-8, with galectin-8 cleavage disengaging CALCOCO2/NDP52 to decouple antiviral-autophagy. Indeed, in post-mortem COVID-19 lung samples, NDP52 rarely colocalizes with galectin-8, unlike healthy lung cells. The 3CL pro substrate degradome establishes a foundational substrate atlas to accelerate exploration of SARS-CoV-2 pathology and drug design.

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The spatiotemporal proteome of the intervertebral disc (IVD) underpins its integrity and function. We present DIPPER, a deep and comprehensive IVD proteomic resource comprising 94 genome-wide profiles from 17 individuals. To begin with, protein modules defining key directional trends spanning the lateral and anteroposterior axes were derived from high-resolution spatial proteomes of intact young cadaveric lumbar IVDs. They revealed novel region-specific profiles of regulatory activities and displayed potential paths of deconstruction in the level- and location-matched aged cadaveric discs. Machine learning methods predicted a ‘hydration matrisome’ that connects extracellular matrix with MRI intensity. Importantly, the static proteome used as point-references can be integrated with dynamic proteome (SILAC/degradome) and transcriptome data from multiple clinical samples, enhancing robustness and clinical relevance. The data, findings, and methodology, available on a web interface (http://www.sbms.hku.hk/dclab/DIPPER/), will be valuable references in the field of IVD biology and proteomic analytics.