Sulfoproteomics Workflow with Precursor Ion Accurate Mass Shift Analysis Reveals Novel Tyrosine Sulfoproteins in the Golgi

Tyrosine sulfation in the Golgi of secreted and membrane proteins is an important post-translational modification (PTM). However, its labile nature has limited analysis by mass spectrometry (MS), a major reason why no sulfoproteome studies have been previously reported. Here, we show that a phosphoproteomics experimental workflow, which includes serial enrichment followed by high resolution, high mass accuracy MS, and tandem MS (MS/MS) analysis, enables sulfopeptide coenrichment and identification via accurate precursor ion mass shift open MSFragger database search. This approach, supported by manual validation, allows the confident identification of sulfotyrosine-containing peptides in the presence of high levels of phosphorylated peptides, thus enabling these two sterically and ionically similar isobaric PTMs to be distinguished and annotated in a single proteomic analysis. We applied this approach to isolated interphase and mitotic rat liver Golgi membranes and identified 67 tyrosine sulfopeptides, corresponding to 26 different proteins. This work discovered 23 new sulfoproteins with functions related to, for example, Ca2+-binding, glycan biosynthesis, and exocytosis. In addition, we report the first preliminary evidence for crosstalk between sulfation and phosphorylation in the Golgi, with implications for functional control.

No Substrate Left behind-Mining of Shotgun Proteomics Datasets Rescues Evidence of Proteolysis by SARS-CoV-2 3CLpro Main Protease

Proteolytic processing is the most ubiquitous post-translational modification and regulator of protein function. To identify protease substrates, and hence the function of proteases, terminomics workflows have been developed to enrich and detect proteolytically generated protein termini from mass spectrometry data. The mining of shotgun proteomics datasets for such 'neo'-termini, to increase the understanding of proteolytic processing, is an underutilized opportunity. However, to date, this approach has been hindered by the lack of software with sufficient speed to make searching for the relatively low numbers of protease-generated semi-tryptic peptides present in non-enriched samples viable. We reanalyzed published shotgun proteomics datasets for evidence of proteolytic processing in COVID-19 using the recently upgraded MSFragger/FragPipe software, which searches data with a speed that is an order of magnitude greater than many equivalent tools. The number of protein termini identified was higher than expected and constituted around half the number of termini detected by two different N-terminomics methods. We identified neo-N- and C-termini generated during SARS-CoV-2 infection that were indicative of proteolysis and were mediated by both viral and host proteases-a number of which had been recently validated by in vitro assays. Thus, re-analyzing existing shotgun proteomics data is a valuable adjunct for terminomics research that can be readily tapped (for example, in the next pandemic where data would be scarce) to increase the understanding of protease function and virus-host interactions, or other diverse biological processes.

Identification of Non-Canonical Translation Products in C. elegans Using Tandem Mass Spectrometry

Transcriptome and ribosome sequencing have revealed the existence of many non-canonical transcripts, mainly containing splice variants, ncRNA, sORFs and altORFs. However, identification and characterization of products that may be translated out of these remains a challenge. Addressing this, we here report on 552 non-canonical proteins and splice variants in the model organism C. elegans using tandem mass spectrometry. Aided by sequencing-based prediction, we generated a custom proteome database tailored to search for non-canonical translation products of C. elegans. Using this database, we mined available mass spectrometric resources of C. elegans, from which 51 novel, non-canonical proteins could be identified. Furthermore, we utilized diverse proteomic and peptidomic strategies to detect 40 novel non-canonical proteins in C. elegans by LC-TIMS-MS/MS, of which 6 were common with our meta-analysis of existing resources. Together, this permits us to provide a resource with detailed annotation of 467 splice variants and 85 novel proteins mapped onto UTRs, non-coding regions and alternative open reading frames of the C. elegans genome.

Fast Deisotoping Algorithm and Its Implementation in the MSFragger Search Engine

Deisotoping, or the process of removing peaks in a mass spectrum resulting from the incorporation of naturally occurring heavy isotopes, has long been used to reduce complexity and improve the effectiveness of spectral annotation methods in proteomics. We have previously described MSFragger, an ultrafast search engine for proteomics, that did not utilize deisotoping in processing input spectra. Here, we present a new, high-speed parallelized deisotoping algorithm, based on elements of several existing methods, that we have incorporated into the MSFragger search engine. Applying deisotoping with MSFragger reveals substantial improvements to database search speed and performance, particularly for complex methods like open or nonspecific searches. Finally, we evaluate our deisotoping method on data from several instrument types and vendors, revealing a wide range in performance and offering an updated perspective on deisotoping in the modern proteomics environment.

Profiling modifications for glioblastoma proteome using ultra-tolerant database search: Are the peptide mass shifts biologically relevant or chemically induced?

Peptide mass shifts were profiled using ultra-tolerant database search strategy for shotgun proteomics data sets of human glioblastoma cell lines demonstrating strong response to the type I interferon (IFNα-2b) treatment. The main objective of this profiling was revealing the cell response to IFN treatment at the level of protein modifications. To achieve this objective, statistically significant changes in peptide mass shift profiles between IFN treated and untreated glioblastoma samples were analyzed. Detailed analysis of MS/MS spectra allowed further interpretation of the observed mass shifts and differentiation between post-translational and artifact modifications. SIGNIFICANCE: Malignant cells typically acquire increased sensitivity to viruses due to the deregulated antiviral mechanisms. Therefore, a viral therapy is considered as one of the promising approaches to treat cancer. However, recent studies have demonstrated that malignant cells can preserve intact antiviral mechanisms, e.g. interferon signaling, and develop resistance to virus infection in response to interferon treatment. Post translational modifications, e.g. tyrosine phosphorylation, are the interferon signaling drivers. Thus, comprehensive characterization of modifications is crucially important, yet, most challenging problem in cancer proteomics. Here, we report on the application of the recently introduced ultra-tolerant search strategy for profiling peptide modifications in the human glioblastoma cell lines demonstrating strong response to the type I interferon (IFNα-2b) treatment. The specific aim of the study was identification of statistically significant changes in peptide mass shift profiles between IFN treated and untreated glioblastoma samples, as well as determination of whether these shifts represent the biologically relevant modification.