Development of Large-scale Cross-linking Mass Spectrometry

Characterize direct protein interactions with enrichable, cleavable and latent bioreactive unnatural amino acids

Latent bioreactive unnatural amino acids (Uaas) have been widely used in the development of covalent drugs and identification of protein interactors, such as proteins, DNA, RNA and carbohydrates. However, it is challenging to perform high-throughput identification of Uaa cross-linking products due to the complexities of protein samples and the data analysis processes. Enrichable Uaas can effectively reduce the complexities of protein samples and simplify data analysis, but few cross-linked peptides were identified from mammalian cell samples with these Uaas. Here we develop an enrichable and multiple amino acids reactive Uaa, eFSY, and demonstrate that eFSY is MS cleavable when eFSY-Lys and eFSY-His are the cross-linking products. An identification software, AixUaa is developed to decipher eFSY mass cleavable data. We systematically identify direct interactomes of Thioredoxin 1 (Trx1) and Selenoprotein M (SELM) with eFSY and AixUaa.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

Cross-linking of the endolysosomal system reveals potential flotillin structures and cargo

Lysosomes are well-established as the main cellular organelles for the degradation of macromolecules and emerging as regulatory centers of metabolism. They are of crucial importance for cellular homeostasis, which is exemplified by a plethora of disorders related to alterations in lysosomal function. In this context, protein complexes play a decisive role, regulating not only metabolic lysosomal processes but also lysosome biogenesis, transport, and interaction with other organelles. Using cross-linking mass spectrometry, we analyze lysosomes and early endosomes. Based on the identification of 5376 cross-links, we investigate protein-protein interactions and structures of lysosome- and endosome-related proteins. In particular, we present evidence for a tetrameric assembly of the lysosomal hydrolase PPT1 and a heterodimeric structure of FLOT1/FLOT2 at lysosomes and early endosomes. For FLOT1-/FLOT2-positive early endosomes, we identify >300 putative cargo proteins and confirm eleven substrates for flotillin-dependent endocytosis, including the latrophilin family of adhesion G protein-coupled receptors.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons

Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.

Mass Spectrometric Identification of a Novel Factor XIIIa Cross-Linking Site in Fibrinogen

Transglutaminases are a class of enzymes that catalyze the formation of a protein:protein cross-link between a lysine and a glutamine residue. These cross-links play important roles in diverse biological processes. Analysis of cross-linking sites in target proteins is required to elucidate their molecular action on target protein function and the molecular specificity of different transglutaminase isozymes. Mass-spectrometry using settings designed for linear peptide analysis and software designed for the analysis of disulfide bridges and chemical cross-links have previously been employed to identify transglutaminase cross-linking sites in proteins. As no control peptide with which to assess and improve the mass spectrometric analysis of TG cross-linked proteins was available, we developed a method for the enzymatic synthesis of a well-defined transglutaminase cross-linked peptide pair that mimics a predicted tryptic digestion product of collagen I. We then used this model peptide to determine optimal score thresholds for correct peptide identification from y- and b-ion series of fragments produced by collision-induced dissociation. We employed these settings in an analysis of fibrinogen cross-linked by the transglutaminase Factor XIIIa. This approach resulted in identification of a novel cross-linked peptide in the gamma subunit. We discuss the difference in behavior of ions derived from different cross-linked peptide sequences and the consequent demand for a more tailored mass spectrometry approach for cross-linked peptide identification compared to that routinely used for linear peptide analysis.

Basic pH reversed-phase liquid chromatography (bRPLC) in combination with tip-based strong cation exchange (SCX-Tip), ReST, an efficient approach for large-scale cross-linked peptide analysis

Chemical cross-linking in combination with mass spectrometry (XL-MS) has emerged as a useful method for structural elucidation of proteins and protein complexes. Due to the low stoichiometry of cross-linked peptides, a specific enrichment method is always necessary prior to LC-MS/MS analysis, especially for complex samples. Currently, strong cation exchange chromatography (SCX), size exclusion chromatography (SEC), and affinity tag-based enrichment are among the widely used enrichment strategies. Herein, we present a two-dimensional strategy combining basic pH reversed-phase liquid chromatography (bRPLC) fractionation and tip-based SCX (SCX-Tip) enrichment, termed ReST, for the characterization of cross-linked peptides. We revealed the unbiased separation effects of the bRPLC in the cross-linked peptide fractionation. We optimized the enrichment conditions of SCX-Tip using well-designed cross-linked peptides. Taking advantage of the high resolution of bRPLC separation and the high enrichment efficiency of SCX-Tip, we were able to identify 43.6% more cross-linked peptides than the conventional SCX approach. The presented ReST is a simple and efficient approach for proteome-scale protein-protein interaction studies.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

New insights into the mechanisms of age-related protein-protein crosslinking in the human lens

Although protein crosslinking is often linked with aging as well as some age-related diseases, very few molecular details are available on the nature of the amino acids involved, or mechanisms that are responsible for crosslinking. Recent research has shown that several amino acids are able to generate reactive intermediates that ultimately lead to covalent crosslinking through multiple non-enzymatic mechanisms. This information has been derived from proteomic investigations on aged human lenses and the mechanisms of crosslinking, in each case, have been elucidated using model peptides. Residues involved in spontaneous protein-protein crosslinking include aspartic acid, asparagine, cysteine, lysine, phosphoserine, phosphothreonine, glutamic acid and glutamine. It has become clear, therefore, that several amino acids can act as potential sites for crosslinking in the long-lived proteins that are present in aged individuals. Moreover, the lens has been an invaluable model tissue and source of crosslinked proteins from which to determine crosslinking mechanisms that may lead to crosslinking in other human tissues.

Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry

Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits the numbers of protein-protein interactions that can be confidently identified. Here, we leverage chromatographic retention time information to aid the identification of crosslinked peptides from mass spectra. Our Siamese machine learning model xiRT achieves highly accurate retention time predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. Importantly, supplementing the search engine score with retention time features leads to a substantial increase in protein-protein interactions without affecting confidence. This approach is not limited to cell lysates and multi-dimensional separation but also improves considerably the analysis of crosslinked multiprotein complexes with a single chromatographic dimension. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of crosslinking mass spectrometry analyses.

TGFβ-1 Induced Cross-Linking of the Extracellular Matrix of Primary Human Dermal Fibroblasts

Excessive cross-linking is a major factor in the resistance to the remodelling of the extracellular matrix (ECM) during fibrotic progression. The role of TGFβ signalling in impairing ECM remodelling has been demonstrated in various fibrotic models. We hypothesised that increased ECM cross-linking by TGFβ contributes to skin fibrosis in Systemic Sclerosis (SSc). Proteomics was used to identify cross-linking enzymes in the ECM of primary human dermal fibroblasts, and to compare their levels following treatment with TGFβ-1. A significant upregulation and enrichment of lysyl-oxidase-like 1, 2 and 4 and transglutaminase 2 were found. Western blotting confirmed the upregulation of lysyl hydroxylase 2 in the ECM. Increased transglutaminase activity in TGFβ-1 treated ECM was revealed from a cell-based assay. We employed a mass spectrometry-based method to identify alterations in the ECM cross-linking pattern caused by TGFβ-1. Cross-linking sites were identified in collagens I and V, fibrinogen and fibronectin. One cross-linking site in fibrinogen alpha was found only in TGFβ-treated samples. In conclusion, we have mapped novel cross-links between ECM proteins and demonstrated that activation of TGFβ signalling in cultured dermal fibroblasts upregulates multiple cross-linking enzymes in the ECM.

High Confidence Identification of Cross-Linked Peptides by an Enrichment-Based Dual Cleavable Cross-Linking Technology and Data Analysis tool Cleave-XL

Cleavable cross-linking technology requires further MS/MS of the cleavable fragments for unambiguous identification of cross-linked peptides. These spectra are sometimes very ambiguous due to the sensitivity and complex fragmentation pattern of the peptides with the cross-linked residues. We recently reported a dual cleavable cross-linking technology (DUCCT), which can enhance the confidence in the identification of cross-linked peptides. The heart of this strategy is a novel dual mass spectrometry cleavable cross linker that can be cleaved preferentially by two differential tandem mass spectrometry methods, collision induced dissociation and electron transfer dissociation (CID and ETD). Different signature ions from two different mass spectra for the same cross-linked peptide helped identify the cross-linked peptides with high confidence. In this study, we developed an enrichment-based photocleavable DUCCT (PC-DUCCT-biotin), where cross-linked products were enriched from biological samples using affinity purification, and subsequently, two sequential tandem (CID and ETD) mass spectrometry processes were utilized. Furthermore, we developed a prototype software called Cleave-XL to analyze cross-linked products generated by DUCCT. Photocleavable DUCCT was demonstrated in standard peptides and proteins. Efficiency of the software tools to search and compare CID and ETD data of photocleavable DUCCT biotin in standard peptides and proteins as well as regular DUCCT in protein complexes from immune cells were tested. The software is efficient in pinpointing cross-linked sites using CID and ETD cross-linking data. We believe this new DUCCT and associated software tool Cleave-XL will advance high confidence identification of protein cross-linking sites and automated identification of low-resolution protein structures.

Identification of Sulfenylated Cysteines in Arabidopsis thaliana Proteins Using a Disulfide-Linked Peptide Reporter

In proteins, hydrogen peroxide (H₂O₂) reacts with redox-sensitive cysteines to form cysteine sulfenic acid, also known as S-sulfenylation. These cysteine oxidation events can steer diverse cellular processes by altering protein interactions, trafficking, conformation, and function. Previously, we had identified S-sulfenylated proteins by using a tagged proteinaceous probe based on the yeast AP-1-like (Yap1) transcription factor that specifically reacts with sulfenic acids and traps them through a mixed disulfide bond. However, the identity of the S-sulfenylated amino acid residues within a protein remained enigmatic. By using the same transgenic YAP1C probe, we present here a technological advancement to identify in situ sulfenylated cysteine sites in Arabidopsis thaliana cells under control condition and oxidative stress. Briefly, the total extract of transgenic YAP1C A. thaliana cells was initially purified on IgG-Sepharose beads, followed by a tryptic digest. Then, the mixed disulfide-linked peptides were further enriched at the peptide level on an anti-YAP1C-derived peptide (C₅₉₈SEIWDR) antibody. Subsequent mass spectrometry analysis with pLink 2 identified 1,745 YAP1C cross-linked peptides, indicating sulfenylated cysteines in over 1,000 proteins. Approximately 55% of these YAP1C-linked cysteines had previously been reported as redox-sensitive cysteines (S-sulfenylation, S-nitrosylation, and reversibly oxidized cysteines). The presented methodology provides a noninvasive approach to identify sulfenylated cysteines in any species that can be genetically modified.

Next Generation Techniques for Determination of Protein-Protein Interactions: Beyond the Crystal Structure

PURPOSE OF REVIEW

We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development.

RECENT FINDINGS

Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates.

SUMMARY

Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.

Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review

Studying protein-protein interaction networks provide key evidence for the underlying molecular mechanisms. Mass spectrometry-based proteomic approaches have been playing a pivotal role in deciphering these interaction networks, along with precise quantification for individual interactions. In this mini-review we discuss the available techniques and methods for qualitative and quantitative elucidation of protein-protein interaction networks. We then summarize the down-stream computational strategies for identification and quantification of interactions from those techniques. Finally, we highlight the challenges and limitations of current computational pipelines in eliminating false positive interactors, followed by a summary of the innovative algorithms to address these issues, along with the scope for future improvements.

Optimized Cross-Linking Mass Spectrometry for in Situ Interaction Proteomics

Recent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the coverage of protein-protein interaction maps is significantly improved through the use of multiple proteases. In addition, the use of focused sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

Systems vaccinology and big data in the vaccine development chain

Systems vaccinology has proven a fascinating development in the last decade. Where traditionally vaccine development has been dominated by trial and error, systems vaccinology is a tool that provides novel and comprehensive understanding if properly used. Data sets retrieved from systems‐based studies endorse rational design and effective development of safe and efficacious vaccines. In this review we first describe different omics‐techniques that form the pillars of systems vaccinology. In the second part, the application of systems vaccinology in the different stages of vaccine development is described. Overall, this review shows that systems vaccinology has become an important tool anywhere in the vaccine development chain.

Chromatographic separation strategies for precision mass spectrometry to study protein-protein interactions and protein phosphorylation

Investigating protein-protein interactions and protein phosphorylation can be of great significance when studying biological processes and human diseases at the molecular level. However, sample complexity, presence of low abundance proteins, and dynamic nature of the proteins often impede in achieving sufficient analytical depth in proteomics research. In this regard, chromatographic separation methodologies have played a vital role in the identification and quantification of proteins in complex sample mixtures. The combination of peptide and protein fractionation techniques with advanced high-performance mass spectrometry has allowed the researchers to successfully study the protein-protein interactions and protein phosphorylation. Several new fractionation strategies for large scale analysis of proteins and peptides have been developed to study protein-protein interactions and protein phosphorylation. These emerging chromatography methodologies have enabled the identification of several hundred protein complexes and even thousands of phosphorylation sites in a single study. In this review, we focus on current workflow strategies and chromatographic tools, highlighting their advantages and disadvantages, and examining their associated challenges and future potential.

eXL-MS: An Enhanced Cross-Linking Mass Spectrometry Workflow To Study Protein Complexes

The analysis of proteins and protein complexes by cross-linking mass spectrometry (XL-MS) has expanded in the past decade. However, mostly used approaches suffer important limitations in term of efficiency and sensitivity. We describe here a new workflow based on the advanced use of the trifunctional cross-linker NNP9. NNP9 carries an azido group allowing the quantitative and selective introduction of a biotin molecule into cross-linked proteins. The incorporation is performed by click-chemistry using an adapted version of the enhanced filter-aided sample preparation (eFASP) protocol. This protocol, based on the use of a molecular filter, allows a very high recovery of peptides after enzymatic digestion and complete removal of contaminants. This in turn offers the possibility for one to analyze very large membrane proteins solubilized in detergent. After trypsin digestion, biotinylated peptides can be easily enriched on monoavidin beads and analyzed by LC-MS/MS. The whole workflow was developed on creatine kinase in the presence of detergent. It led to a drastic improvement in the number of identified cross-linked peptides (407 vs 81), compared to the conventional approach using a gel-based separation. One great advantage of our enhanced cross-linking mass spectrometry (eXL-MS) workflow is its high efficiency, allowing the analysis of a very low amount of material (15 μg). We also demonstrate that higher-energy collision dissociation (HCD) outperforms electron-transfer/higher-energy collision dissociation (EThcD) in terms of number of cross-linked peptides identified, but EThcD leads to better sequence coverage than HCD and thus easier localization of cross-linking sites.

Identification of MS-Cleavable and Noncleavable Chemically Cross-Linked Peptides with MetaMorpheus

Protein chemical cross-linking combined with mass spectrometry has become an important technique for the analysis of protein structure and protein-protein interactions. A variety of cross-linkers are well developed, but reliable, rapid, and user-friendly tools for large-scale analysis of cross-linked proteins are still in need. Here we report MetaMorpheusXL, a new search module within the MetaMorpheus software suite that identifies both MS-cleavable and noncleavable cross-linked peptides in MS data. MetaMorpheusXL identifies MS-cleavable cross-linked peptides with an ion-indexing algorithm, which enables an efficient large database search. The identification does not require the presence of signature fragment ions, an advantage compared with similar programs such as XlinkX. One complication associated with the need for signature ions from cleavable cross-linkers such as DSSO (disuccinimidyl sulfoxide) is the requirement for multiple fragmentation types and energy combinations, which is not necessary for MetaMorpheusXL. The ability to perform proteome-wide analysis is another advantage of MetaMorpheusXL compared with programs such as MeroX and DXMSMS. MetaMorpheusXL is also faster than other currently available MS-cleavable cross-link search software programs. It is imbedded in MetaMorpheus, an open-source and freely available software suite that provides a reliable, fast, user-friendly graphical user interface that is readily accessible to researchers.

CLMSVault: A Software Suite for Protein Cross-Linking Mass-Spectrometry Data Analysis and Visualization

Protein cross-linking mass spectrometry (CL-MS) enables the sensitive detection of protein interactions and the inference of protein complex topology. The detection of chemical cross-links between protein residues can identify intra- and interprotein contact sites or provide physical constraints for molecular modeling of protein structure. Recent innovations in cross-linker design, sample preparation, mass spectrometry, and software tools have significantly improved CL-MS approaches. Although a number of algorithms now exist for the identification of cross-linked peptides from mass spectral data, a dearth of user-friendly analysis tools represent a practical bottleneck to the broad adoption of the approach. To facilitate the analysis of CL-MS data, we developed CLMSVault, a software suite designed to leverage existing CL-MS algorithms and provide intuitive and flexible tools for cross-platform data interpretation. CLMSVault stores and combines complementary information obtained from different cross-linkers and search algorithms. CLMSVault provides filtering, comparison, and visualization tools to support CL-MS analyses and includes a workflow for label-free quantification of cross-linked peptides. An embedded 3D viewer enables the visualization of quantitative data and the mapping of cross-linked sites onto PDB structural models. We demonstrate the application of CLMSVault for the analysis of a noncovalent Cdc34-ubiquitin protein complex cross-linked under different conditions. CLMSVault is open-source software (available at https://gitlab.com/courcelm/clmsvault.git ), and a live demo is available at http://democlmsvault.tyerslab.com/ .