Quantifying Missing (Phospho)Proteome Regions with the Broad-Specificity Protease Subtilisin

Accelerating Proteomics Using Broad Specificity Proteases

Trypsin is the gold-standard protease in bottom-up proteomics, but many sequence stretches of the proteome are inaccessible to trypsin and standard LC-MS approaches. Thus, multienzyme strategies are used to maximize sequence coverage in post-translational modification profiling. We present fast and robust SP3- and STRAP-based protocols for the broad-specificity proteases subtilisin, proteinase K, and thermolysin. All three enzymes are remarkably fast, producing near-complete digests in 1-5 min, and cost 200-1000× less than proteomics-grade trypsin. Using FragPipe resolved a major challenge by drastically reducing the duration of the required "unspecific" searches. In-depth analyses of proteinase K, subtilisin, and thermolysin Jurkat digests identified 7374, 8178, and 8753 unique proteins with average sequence coverages of 21, 29, and 37%, including 10,000s of amino acids not reported in PeptideAtlas' >2400 experiments. While we could not identify distinct cleavage patterns, machine learning could distinguish true protease products from random cleavages, potentially enabling the prediction of cleavage products. Finally, proteinase K, subtilisin, and thermolysin enabled label-free quantitation of 3111, 3659, and 4196 unique Jurkat proteins, which in our hands is comparable to trypsin. Our data demonstrate that broad-specificity proteases enable quantitative proteomics of uncharted areas of the proteome. Their fast kinetics may allow "on-the-fly" digestion of samples in the future.

Mapping Peptide-Protein Interactions by Amine-Reactive Cleavable Photoaffinity Reagents

Photoaffinity labeling followed by tandem mass spectrometry is an often used strategy to identify protein targets of small-molecule drugs or drug candidates, which, under ideal conditions, enables the identification of the actual drug binding site. In the case of bioactive peptides, however, identifying the distinct binding site is hampered because of complex fragmentation patterns during tandem mass spectrometry. We here report the development and use of small cleavable photoaffinity reagents that allow functionalization of bioactive peptides for light-induced covalent binding to their protein targets. Upon cleavage of the covalently linked peptide drug, a chemical remnant of a defined mass remains on the bound amino acid, which is then used to unambiguously identify the drug binding site. Applying our approach to known peptide-drug/protein pairs with reported crystal structures, such as the calmodulin-melittin interaction, we were able to validate the identified binding sites based on structural models. Overall, our cleavable photoaffinity labeling strategy represents a powerful tool to enable the identification of protein targets and specific binding sites of a wide variety of bioactive peptides in the future.

Improved Coverage of the N-Terminome by Combining ChaFRADIC with Alternative Proteases

Many proteolytic cleavage events cannot be covered with conventional trypsin-based N-terminomics workflows. These typically involve the derivatization of protein N-termini and Lys residues as an initial step, such that trypsin will cleave C-terminal of arginine but not lysine residues (ArgC-like cleavage). From 20,422 reviewed human protein sequences in Uniprot, 3597 have known N-terminal signal peptides. An in silico ArgC-like digestion of the corresponding 3597 mature protein sequences reveals that-even for these well-known and well-studied proteolytic events-trypsin-based N-terminomics workflows may miss up to 50% of signaling cleavage events as the corresponding neo-N-terminal peptides will have an unfavorable length of <7 (875 peptides) or >30 (911 peptides) amino acids. In this chapter, we provide a protocol that can be applied to all kinds of samples to improve access to this "inaccessible" N-terminome, by making use of the alternative, broad-specificity protease subtilisin for fast and reproducible digestion of proteins.

A Practical Guide to Small Protein Discovery and Characterization Using Mass Spectrometry

Small proteins of up to ∼50 amino acids are an abundant class of biomolecules across all domains of life. Yet due to the challenges inherent in their size, they are often missed in genome annotations, and are difficult to identify and characterize using standard experimental approaches. Consequently, we still know few small proteins even in well-studied prokaryotic model organisms. Mass spectrometry (MS) has great potential for the discovery, validation, and functional characterization of small proteins. However, standard MS approaches are poorly suited to the identification of both known and novel small proteins due to limitations at each step of a typical proteomics workflow, i.e., sample preparation, protease digestion, liquid chromatography, MS data acquisition, and data analysis. Here, we outline the major MS-based workflows and bioinformatic pipelines used for small protein discovery and validation. Special emphasis is placed on highlighting the adjustments required to improve detection and data quality for small proteins. We discuss both the unbiased detection of small proteins and the targeted analysis of small proteins of interest. Finally, we provide guidelines to prioritize novel small proteins, and an outlook on methods with particular potential to further improve comprehensive discovery and characterization of small proteins.

WIDENING THE BOTTLENECK OF PHOSPHOPROTEOMICS: EVOLVING STRATEGIES FOR PHOSPHOPEPTIDE ENRICHMENT

Phosphorylation is a form of protein posttranslational modification (PTM) that regulates many biological processes. Whereas phosphoproteomics is a scientific discipline that identifies and quantifies the phosphorylated proteome using mass spectrometry (MS). This task is extremely challenging as ~30% of the human proteome is phosphorylated; and each phosphoprotein may exist as multiple phospho-isoforms that are present in low abundance and stoichiometry. Hence, phosphopeptide enrichment techniques are indispensable to (phospho)proteomics laboratories. These enrichment methods encompass widely-adopted techniques such as (i) affinity-based chromatography; (ii) ion exchange and mixed-mode chromatography (iii) enrichment with phospho-specific antibodies and protein domains, and (iv) functionalized polymers and other less common but emerging technologies such as hydroxyapatite chromatography and precipitation with inorganic ions. Here, we review these techniques, their history, continuous development and evaluation. Besides, we outline associating challenges of phosphoproteomics that are linked to experimental design, sample preparation, and proteolytic digestion. In addition, we also discuss about the future outlooks in phosphoproteomics, focusing on elucidating the noncanonical phosphoproteome and deciphering the "dark phosphoproteome". © 2020 John Wiley & Sons Ltd.

Label-Free Quantitative Phosphoproteomics of the Fission Yeast Schizosaccharomyces pombe Using Strong Anion Exchange- and Porous Graphitic Carbon-Based Fractionation Strategies

The phosphorylation of proteins modulates various functions of proteins and plays an important role in the regulation of cell signaling. In recent years, label-free quantitative (LFQ) phosphoproteomics has become a powerful tool to analyze the phosphorylation of proteins within complex samples. Despite the great progress, the studies of protein phosphorylation are still limited in throughput, robustness, and reproducibility, hampering analyses that involve multiple perturbations, such as those needed to follow the dynamics of phosphoproteomes. To address these challenges, we introduce here the LFQ phosphoproteomics workflow that is based on Fe-IMAC phosphopeptide enrichment followed by strong anion exchange (SAX) and porous graphitic carbon (PGC) fractionation strategies. We applied this workflow to analyze the whole-cell phosphoproteome of the fission yeast Schizosaccharomyces pombe. Using this strategy, we identified 8353 phosphosites from which 1274 were newly identified. This provides a significant addition to the S. pombe phosphoproteome. The results of our study highlight that combining of PGC and SAX fractionation strategies substantially increases the robustness and specificity of LFQ phosphoproteomics. Overall, the presented LFQ phosphoproteomics workflow opens the door for studies that would get better insight into the complexity of the protein kinase functions of the fission yeast S. pombe.

ExteNDing Proteome Coverage with Legumain as a Highly Specific Digestion Protease

Bottom-up mass spectrometry-based proteomics utilizes proteolytic enzymes with well characterized specificities to generate peptides amenable for identification by high-throughput tandem mass spectrometry. Trypsin, which cuts specifically after the basic residues lysine and arginine, is the predominant enzyme used for proteome digestion, although proteases with alternative specificities are required to detect sequences that are not accessible after tryptic digest. Here, we show that the human cysteine protease legumain exhibits a strict substrate specificity for cleavage after asparagine and aspartic acid residues during in-solution digestions of proteomes extracted from Escherichia coli, mouse embryonic fibroblast cell cultures, and Arabidopsis thaliana leaves. Generating peptides highly complementary in sequence, yet similar in their biophysical properties, legumain (as compared to trypsin or GluC) enabled complementary proteome and protein sequence coverage. Importantly, legumain further enabled the identification and enrichment of protein N-termini not accessible in GluC- or trypsin-digested samples. Legumain cannot cleave after glycosylated Asn residues, which enabled the robust identification and orthogonal validation of N-glycosylation sites based on alternating sequential sample treatments with legumain and PNGaseF and vice versa. Taken together, we demonstrate that legumain is a practical, efficient protease for extending the proteome and sequence coverage achieved with trypsin, with unique possibilities for the characterization of post-translational modification sites.

Proteogenomics of Colorectal Cancer Liver Metastases: Complementing Precision Oncology with Phenotypic Data

Hotspot testing for activating KRAS mutations is used in precision oncology to select colorectal cancer (CRC) patients who are eligible for anti-EGFR treatment. However, even for KRAS^wildtype tumors anti-EGFR response rates are <30%, while mutated-KRAS does not entirely rule out response, indicating the need for improved patient stratification. We performed proteogenomic phenotyping of KRAS^wildtype and KRAS^G12V CRC liver metastases (mCRC). Among >9000 proteins we detected considerable expression changes including numerous proteins involved in progression and resistance in CRC. We identified peptides representing a number of predicted somatic mutations, including KRAS^G12V. For eight of these, we developed a multiplexed parallel reaction monitoring (PRM) mass spectrometry assay to precisely quantify the mutated and canonical protein variants. This allowed phenotyping of eight mCRC tumors and six paired healthy tissues, by determining mutation rates on the protein level. Total KRAS expression varied between tumors (0.47–1.01 fmol/µg total protein) and healthy tissues (0.13–0.64 fmol/µg). In KRAS^G12V-mCRC, G12V-mutation levels were 42–100%, while one patient had only 10% KRAS^G12V but 90% KRAS^wildtype. This might represent a missed therapeutic opportunity: based on hotspot sequencing, the patient was excluded from anti-EGFR treatment and instead received chemotherapy, while PRM-based tumor-phenotyping indicates the patient might have benefitted from anti-EGFR therapy.

Effective Assignment of α2,3/α2,6-Sialic Acid Isomers by LC-MS/MS-Based Glycoproteomics

Distinct structural changes of the α2,3/α2,6-sialic acid glycosidic linkages on glycoproteins are of importance in cancer biology, inflammatory diseases, and virus tropism. Current glycoproteomic methodologies are, however, not amenable toward high-throughput characterization of sialic acid isomers. To enable such assignments, a mass spectrometry method utilizing synthetic model glycopeptides for the analysis of oxonium ion intensity ratios was developed. This method was successfully applied in large-scale glycoproteomics, thus allowing the site-specific structural characterization of sialic acid isomers.