Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks

Rescuing error control in crosslinking mass spectrometry

Crosslinking mass spectrometry is a powerful tool to study protein-protein interactions under native or near-native conditions in complex mixtures. Through novel search controls, we show how biassing results towards likely correct proteins can subtly undermine error estimation of crosslinks, with significant consequences. Without adjustments to address this issue, we have misidentified an average of 260 interspecies protein-protein interactions across 16 analyses in which we synthetically mixed data of different species, misleadingly suggesting profound biological connections that do not exist. We also demonstrate how data analysis procedures can be tested and refined to restore the integrity of the decoy-false positive relationship, a crucial element for reliably identifying protein-protein interactions.

Intra-organ cell specific mitochondrial quantitative interactomics

Almost every organ consists of many cell types, each with its unique functions. Proteomes of these cell types are thus unique too. But it is reasonable to assume that interactome (inter and intra molecular interactions of proteins) are also distinct since protein interactions are what ultimately carry out the function. Podocytes and tubules are two cell types within kidney with vastly different functions: podocytes envelop the blood vessels in the glomerulus and act as filters while tubules are located downstream of the glomerulus and are responsible for reabsorption of important nutrients. It has been long known that for tubules mitochondria plays an important role as they require a lot of energy to carry out their functions. In podocytes, however, it has been assumed that mitochondria might not matter as much in both normal physiology and pathology1. Here we have applied quantitative cross-linking mass spectrometry to compare mitochondrial interactomes of tubules and podocytes using a transgenic mitochondrial tagging strategy to immunoprecipitate cell-specific mitochondria directly from whole kidney. We have uncovered that mitochondrial proteomes of these cell types are quite similar, although still showing unique features that correspond to known functions, such as high energy production through TCA cycle in tubules and requirements for detoxification in podocytes which are on the frontline of filtration where they encounter toxic compounds and therefore, as a non-renewing cell type they must have ways to protect themselves from cellular toxicity. But we gained much deeper insight with the interactomics data. We were able to find pathways differentially regulated in podocytes and tubules based on changing cross-link levels and not just protein levels. Among these pathways are betaine metabolism, lysine degradation, and many others. We have also demonstrated how quantitative interactomics could be used to detect different activity levels of an enzyme even when protein abundances of it are the same between cell types. We have validated this finding with an orthogonal activity assay. Overall, this work presents a new view of mitochondrial biology for two important, but functionally distinct, cell types within the mouse kidney showing both similarities and unique features. This data can continue to be explored to find new aspects of mitochondrial biology, especially in podocytes, where mitochondria has been understudied. In the future this methodology can also be applied to other organs to uncover differences in the function of cell types.

Interactome dynamics during heat stress signal transmission and reception

Among evolved molecular mechanisms, cellular stress response to altered environmental conditions to promote survival is among the most fundamental. The presence of stress-induced unfolded or misfolded proteins and molecular registration of these events constitute early steps in cellular stress response. However, what stress-induced changes in protein conformations and protein-protein interactions within cells initiate stress response and how these features are recognized by cellular systems are questions that have remained difficult to answer, requiring new approaches. Quantitative in vivo chemical cross-linking coupled with mass spectrometry (qXL-MS) is an emerging technology that provides new insight on protein conformations, protein-protein interactions and how the interactome changes during perturbation within cells, organelles, and even tissues. In this work, qXL-MS and quantitative proteome analyses were applied to identify significant time-dependent interactome changes that occur prior to large-scale proteome abundance remodeling within cells subjected to heat stress. Interactome changes were identified within minutes of applied heat stress, including stress-induced changes in chaperone systems as expected due to altered functional demand. However, global analysis of all interactome changes revealed the largest significant enrichment in the gene ontology molecular function term of RNA binding. This group included more than 100 proteins among multiple components of protein synthesis machinery, including mRNA binding, spliceosomes, and ribosomes. These interactome data provide new conformational insight on the complex relationship that exists between transcription, translation and cellular stress response mechanisms. Moreover, stress-dependent interactome changes suggest that in addition to conformational stabilization of RNA-binding proteins, adaptation of RNA as interacting ligands offers an additional fitness benefit resultant from generally lower RNA thermal stability. As such, RNA ligands also serve as fundamental temperature sensors that signal stress through decreased conformational regulation of their protein partners as was observed in these interactome dynamics.

Studying Protein-Ligand Interactions by Protein Denaturation and Quantitative Cross-Linking Mass Spectrometry

Recently, several mass spectrometry methods have utilized protein structural stability for the quantitative study of protein-ligand engagement. These protein-denaturation approaches, which include thermal proteome profiling (TPP) and stability of proteins from rates of oxidation (SPROX), evaluate ligand-induced denaturation susceptibility changes with a MS-based readout. The different techniques of bottom-up protein-denaturation methods each have their own advantages and challenges. Here, we report the combination of protein-denaturation principles with quantitative cross-linking mass spectrometry using isobaric quantitative protein interaction reporter technologies. This method enables the evaluation of ligand-induced protein engagement through analysis of cross-link relative ratios across chemical denaturation. As a proof of concept, we found ligand-stabilized cross-linked lysine pairs in well-studied bovine serum albumin and ligand bilirubin. These links map to the known binding sites Sudlow Site I and subdomain IB. We propose that protein denaturation and qXL-MS can be combined with similar peptide-level quantification approaches, like SPROX, to increase the coverage information profiled for facilitating protein-ligand engagement efforts.

Skeletal muscle mitochondrial interactome remodeling is linked to functional decline in aged female mice

Genomic, transcriptomic and proteomic approaches have been used to gain insight into molecular underpinnings of aging in laboratory animals and in humans. However, protein function in biological systems is under complex regulation and includes factors besides abundance levels, such as modifications, localization, conformation and protein-protein interactions. By making use of quantitative chemical cross-linking technologies, we show that changes in the muscle mitochondrial interactome contribute to mitochondrial functional decline in aging in female mice. Specifically, we identify age-related changes in protein cross-links relating to assembly of electron transport system complexes I and IV, activity of glutamate dehydrogenase, and coenzyme-A binding in fatty acid β-oxidation and tricarboxylic acid cycle enzymes. These changes show a remarkable correlation with complex I respiration differences within the same young-old animal pairs. Each observed cross-link can serve as a protein conformational or protein-protein interaction probe in future studies, which will provide further molecular insights into commonly observed age-related phenotypic differences. Therefore, this data set could become a valuable resource for additional in-depth molecular studies that are needed to better understand complex age-related molecular changes.

Mitochondrial interactome quantitation reveals structural changes in metabolic machinery in the failing murine heart

Advancements in cross-linking mass spectrometry (XL-MS) bridge the gap between purified systems and native tissue environments, allowing the detection of protein structural interactions in their native state. Here we use isobaric quantitative protein interaction reporter technology (iqPIR) to compare the mitochondria protein interactomes in healthy and hypertrophic murine hearts, 4 weeks post-transaortic constriction. The failing heart interactome includes 588 statistically significant cross-linked peptide pairs altered in the disease condition. We observed an increase in the assembly of ketone oxidation oligomers corresponding to an increase in ketone metabolic utilization; remodeling of NDUA4 interaction in Complex IV, likely contributing to impaired mitochondria respiration; and conformational enrichment of ADP/ATP carrier ADT1, which is non-functional for ADP/ATP translocation but likely possesses non-selective conductivity. Our application of quantitative cross-linking technology in cardiac tissue provides molecular-level insights into the complex mitochondria remodeling in heart failure while bringing forth new hypotheses for pathological mechanisms.

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine-lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein-protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.

Improved Interpretation of Protein Conformational Differences and Ligand Occupancy in Large-Scale Cross-Link Data

Chemical cross-linking of proteins in complex samples, cells, or even tissues is emerging to provide unique structural information on proteins and complexes that exist within native or nativelike environments. The public database XLinkDB automatically maps cross-links to available structures based on sequence homology. Structures most likely to reflect protein conformations in the cross-linked sample are routinely identified by having cross-linked residues separated by Euclidean distances within the maximum span of the applied cross-linker. Solvent accessible surface distance (SASD), which considers the accessibility of the cross-linked residues and the path connecting them, is a better predictor of consistency than the Euclidean distance. However, SASDs of structures are not publicly available, and their calculation is computationally intensive. Here, we describe in XLinkDB version 4.0 the automatic calculation of SASDs using Jwalk for all cross-links mapped to structures, both with and without regard to ligands, and derive empirical maximum SASD spans for BDP-NHP and DSSO cross-linkers of 51 and 43 Å, respectively. We document ligands proximal to cross-links in structures and demonstrate how SASDs can be used to help infer sample protein conformations and ligand occupancy, highlighting cross-links sensitive to ADP binding in mitochondria isolated from HEK293 cells.

Upregulation of mitochondrial ATPase inhibitory factor 1 (ATPIF1) mediates increased glycolysis in mouse hearts

In hypertrophied and failing hearts, fuel metabolism is reprogrammed to increase glucose metabolism, especially glycolysis. This metabolic shift favors biosynthetic function at the expense of ATP production. Mechanisms responsible for the switch are poorly understood. We found that inhibitory factor 1 of the mitochondrial FoF1-ATP synthase (ATPIF1), a protein known to inhibit ATP hydrolysis by the reverse function of ATP synthase during ischemia, was significantly upregulated in pathological cardiac hypertrophy induced by pressure overload, myocardial infarction, or α-adrenergic stimulation. Chemical cross-linking mass spectrometry analysis of hearts hypertrophied by pressure overload suggested that increased expression of ATPIF1 promoted the formation of FoF1-ATP synthase nonproductive tetramer. Using ATPIF1 gain- and loss-of-function cell models, we demonstrated that stalled electron flow due to impaired ATP synthase activity triggered mitochondrial ROS generation, which stabilized HIF1α, leading to transcriptional activation of glycolysis. Cardiac-specific deletion of ATPIF1 in mice prevented the metabolic switch and protected against the pathological remodeling during chronic stress. These results uncover a function of ATPIF1 in nonischemic hearts, which gives FoF1-ATP synthase a critical role in metabolic rewiring during the pathological remodeling of the heart.

Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx

Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to noncleavable and MS-cleavable cross-linkers. For both, we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For noncleavable peptides, we implemented a novel dipeptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the dipeptide individually. A posterior error probability (PEP) based on total and partial scores is used to control false discovery rates (FDRs). For MS-cleavable cross-linkers, a score of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace the manual filtering of identifications, which is often necessary when using other pipelines. On benchmark data sets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross-linkers and on a proteome-wide data set of cross-linked Drosophila melanogaster cell lysate. The workflow also supports ion mobility-enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra, and is freely available at https://www.maxquant.org/.

Progress in methodologies and quality-control strategies in protein cross-linking mass spectrometry

Deciphering the interaction networks and structural dynamics of proteins is pivotal to better understanding their biological functions. Cross-linking mass spectrometry (XL-MS) is a powerful and increasingly popular technology that provides information about protein-protein interactions and their structural constraints for individual proteins and multiprotein complexes on a proteome-scale. In this review, we first assess the coverage and depth of the XL-MS technique by utilizing publicly available datasets. We then delve into the progress in XL-MS experimental and computational methodologies and examine different quality-control strategies reported in the literature. Finally, we discuss the progress in XL-MS applications along with the scope for future improvements.

Accurate Retention Time Prediction Based on Monolinked Peptide Information to Confidently Identify Cross-Linked Peptides

Cross-linking mass spectrometry methods have not been successfully applied to protein-protein interaction discovery at a proteome-wide level mainly due to the computation complexity (O (n²)) issue. In a previous report, we proposed a decision tree searching strategy (DTSS), which can reduce complexity by orders of magnitude. In this study, we further found that the monolinked peptides carry out the information on the retention time of the corresponding cross-linked pairs; therefore, the retention time of cross-linked peptide pairs can be predicted accurately. By utilizing the retention time as an extra filter, the false positive rate can be reduced by around 86% with a sensitivity loss of 10%. The method combined with DTSS (T-DTSS) not only benefits improving identification confidence but also leads to lower cutoff scores and facilitates substantially increasing inter-cross-link identification. T-DTSS was successfully applied to the identification of inter-cross-links obtained from Escherichia coli cell lysate cross-linked by a newly synthesized enrichable cross-linker, pDSBE. The approach can be applicable to both cleavable and noncleavable methods.

Deciphering the architecture and interactome of hnRNP proteins and enigmRBPs

RNA-binding proteins (RBPs) have conserved domains and consensus sequences that interact with RNAs and other proteins forming ribonucleoprotein (RNP) complexes. RNPs are involved in the regulation of several cellular processes, including transcription, pre-mRNA splicing, mRNA transport, localization, degradation and storage, and ultimately control of translation. Heterogeneous nuclear ribonucleoproteins (hnRNPs) comprise a family of RBPs that mediate transcription control and nuclear processing of transcripts. Some hnRNPs are part of the spliceosome complex, a dynamic machinery formed by RNPs that regulate alternative splicing of pre-mRNAs. Here, chemical crosslinking of proteins was applied to identify specific interacting regions and protein structural features of hnRNPs: hnRNPA1, hnRNPA2/B1, hnRNPC, and RALY. The results reveal interaction of these proteins within RNA-binding domains and conserved motifs, providing evidence of a coordinated action of known regulatory sequences of RBPs. Moreover, these crosslinking data enable structural model generation for RBPs, illustrating how crosslinking mass spectrometry can complement other structural methods.

In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology

Biological systems have evolved to utilize proteins to accomplish nearly all functional roles needed to sustain life. A majority of biological functions occur within the crowded environment inside cells and subcellular compartments where proteins exist in a densely packed complex network of protein-protein interactions. The structural biology field has experienced a renaissance with recent advances in crystallography, NMR, and CryoEM that now produce stunning models of large and complex structures previously unimaginable. Nevertheless, measurements of such structural detail within cellular environments remain elusive. This review will highlight how advances in mass spectrometry, chemical labeling, and informatics capabilities are merging to provide structural insights on proteins, complexes, and networks that exist inside cells. Because of the molecular detection specificity provided by mass spectrometry and proteomics, these approaches provide systems-level information that not only benefits from conventional structural analysis, but also is highly complementary. Although far from comprehensive in their current form, these approaches are currently providing systems structural biology information that can uniquely reveal how conformations and interactions involving many proteins change inside cells with perturbations such as disease, drug treatment, or phenotypic differences. With continued advancements and more widespread adaptation, systems structural biology based on in-cell labeling and mass spectrometry will provide an even greater wealth of structural knowledge.

Leveraging the Entirety of the Protein Data Bank to Enable Improved Structure Prediction Based on Cross-Link Data

XLinkDB is a fast-expanding public database now storing more than 100 000 distinct identified cross-linked protein residue pairs acquired by chemical cross-linking with mass spectrometry from samples of 12 species (J. Proteome Res. 2019, 18 (2), 753-758). Mapping identified cross-links to protein structures, when available, provides valuable guidance on protein conformations detected in the cross-linked samples. As more and more structures become available in the Protein Data Bank (Nucleic Acids Res. 2000, 28 (1), 235-242), we sought to leverage their utility for cross-link studies by automatically mapping identified cross-links to structures based on sequence homology of the cross-linked proteins with those within structures. This enables use of structures derived from organisms different from those of samples, including large multiprotein complexes and complexes in alternative states. We demonstrate utility of mapping to orthologous structures, highlighting a cross-link between two subunits of mouse mitochondrial Complex I that was mapped to 15 structures derived from five mammals, its distances there of 16.2 ± 0.4 Å indicating strong conservation of the protein interaction. We also show how multimeric structures enable reassessment of cross-links presumed to be intraprotein as potentially homodimeric interprotein in origin.

Isobaric Quantitative Protein Interaction Reporter Technology for Comparative Interactome Studies

Chemical cross-linking with mass spectrometry (XL-MS) has emerged as a useful tool for the large-scale study of protein structures and interactions from complex biological samples including intact cells and tissues. Quantitative XL-MS (qXL-MS) provides unique information on protein conformational and interaction changes resulting from perturbations such as drug treatment and disease state. Previous qXL-MS studies relied on the incorporation of stable isotopes into the cross-linker (primarily deuterium) or metabolic labeling with SILAC. Here, we introduce isobaric quantitative protein interaction reporter (iqPIR) technology which utilizes stable isotopes selectively incorporated into the cross-linker design, allowing for isobaric cross-linked peptide pairs originating from different samples to display distinct quantitative isotope signatures in tandem mass spectra. This enables improved quantitation of cross-linked peptide levels from proteome-wide samples because of the reduced complexity of tandem mass spectra relative to MS¹ spectra. In addition, because of the isotope incorporation in the reporter and the residual components of the cross-linker that remain on released peptides, each fragmentation spectrum can offer multiple independent opportunities and, therefore, improved confidence for quantitative assessment of the cross-linker pair level. Finally, in addition to providing information on solvent accessibility of lysine sites, dead end iqPIR cross-linked products can provide protein abundance and/or lysine site modification level information all from a single in vivo cross-linking experiment.

Cross-linking Mass Spectrometry Analysis of the Yeast Nucleus Reveals Extensive Protein-Protein Interactions Not Detected by Systematic Two-Hybrid or Affinity Purification-Mass Spectrometry

Saccharomyces cerevisiae has the most comprehensively characterized protein-protein interaction network, or interactome, of any eukaryote. This has predominantly been generated through multiple, systematic studies of protein-protein interactions by two-hybrid techniques and of affinity-purified protein complexes. A pressing question is to understand how large-scale cross-linking mass spectrometry (XL-MS) can confirm and extend this interactome. Here, intact yeast nuclei were subject to cross-linking with disuccinimidyl sulfoxide (DSSO) and analyzed using hybrid MS2-MS3 methods. XlinkX identified a total of 2,052 unique residue pair cross-links at 1% FDR. Intraprotein cross-links were found to provide extensive structural constraint data, with almost all intralinks that mapped to known structures and slightly fewer of those mapping to homology models being within 30 Å. Intralinks provided structural information for a further 366 proteins. A method for optimizing interprotein cross-link score cut-offs was developed, through use of extensive known yeast interactions. Its application led to a high confidence, yeast nuclear interactome. Strikingly, almost half of the interactions were not previously detected by two-hybrid or AP-MS techniques. Multiple lines of evidence existed for many such interactions, whether through literature or ortholog interaction data, through multiple unique interlinks between proteins, and/or through replicates. We conclude that XL-MS is a powerful means to measure interactions, that complements two-hybrid and affinity-purification techniques.

Cellular Interactome Dynamics during Paclitaxel Treatment

Cell-cycle inhibitors, including paclitaxel, are among the most widely used and effective cancer therapies. However, several challenges limit the success of paclitaxel, including drug resistance and toxic side effects. Paclitaxel is thought to act primarily by stabilizing microtubules, locking cells in a mitotic state. However, the resulting cytotoxicity and tumor shrinkage rates observed cannot be fully explained by this mechanism alone. Here we apply quantitative chemical cross-linking with mass spectrometry analysis to paclitaxel-treated cells. Our results provide large-scale measurements of relative protein levels and, perhaps more importantly, changes to protein conformations and interactions that occur upon paclitaxel treatment. Drug concentration-dependent changes are revealed in known drug targets including tubulins, as well as many other proteins and protein complexes involved in apoptotic signaling and cellular homeostasis. As such, this study provides insight into systems-level changes to protein structures and interactions that occur with paclitaxel treatment.

Development of R7BP inhibitors through cross-linking coupled mass spectrometry and integrated modeling

Protein-protein interaction (PPI) networks are known to be valuable targets for therapeutic intervention; yet the development of PPI modulators as next-generation drugs to target specific vertices, edges, and hubs has been impeded by the lack of structural information of many of the proteins and complexes involved. Building on recent advancements in cross-linking mass spectrometry (XL-MS), we describe an effective approach to obtain relevant structural data on R7BP, a master regulator of itch sensation, and its interfaces with other proteins in its network. This approach integrates XL-MS with a variety of modeling techniques to successfully develop antibody inhibitors of the R7BP and RGS7/Gβ5 duplex interaction. Binding and inhibitory efficiency are studied by surface plasmon resonance spectroscopy and through an R7BP-derived dominant negative construct. This approach may have broader applications as a tool to facilitate the development of PPI modulators in the absence of crystal structures or when structural information is limited.

Prediction of an Upper Limit for the Fraction of Interprotein Cross-Links in Large-Scale In Vivo Cross-Linking Studies

Chemical cross-linking and mass spectrometry is of growing use for establishment of distance constraints on protein conformations and interactions. Whereas intraprotein cross-links can arise from proteins in isolation, interprotein cross-links reflect proximity of two interacting proteins in the sample. Prediction of expected ratios of the number of interprotein to intraprotein cross-links is hindered by lacking comprehensive knowledge on the interactome network and global occupancy levels for all interacting complex subunits. Here we determine the theoretical number of possible inter- and intraprotein cross-links in available PDB structures of proteins bound in complexes to predict a maximum expected fraction of interprotein cross-links in large scale in vivo cross-linking studies. We show how the maximum fraction can guide interpretation of reported interprotein fractions with respect to the extent of sample protein binding, comparing whole cell and lysate cross-linked samples as an example. We also demonstrate how an observation of interprotein cross-link fractions greater than the maximum value can result from the presence of false positive cross-links which are predominantly interprotein, their number estimable from the observed surplus fraction of interprotein cross-links.

Systems structural biology measurements by in vivo cross-linking with mass spectrometry

This protocol describes a workflow for utilizing large-scale cross-linking with mass spectrometry (XL-MS) to make systems-level structural biology measurements in complex biological samples, including cells, isolated organelles, and tissue samples. XL-MS is a structural biology technique that provides information on the molecular structure of proteins and protein complexes using chemical probes that report the proximity of probe-reactive amino acids within proteins, typically lysine residues. Information gained through XL-MS studies is often complementary to more traditional methods, such as X-ray crystallography, nuclear magnetic resonance, and cryo-electron microscopy. The use of MS-cleavable cross-linkers, including protein interaction reporter (PIR) technologies, enables XL-MS studies on protein structures and interactions in extremely complex biological samples, including intact living cells. PIR cross-linkers are designed to contain chemical bonds at specific locations within the cross-linker molecule that can be selectively cleaved by collision-induced dissociation or UV light. When broken, these bonds release the intact peptides that were cross-linked, as well as a reporter ion. Conservation of mass dictates that the sum of the two released peptide masses and the reporter mass equals the measured precursor mass. This relationship is used to identify cross-linked peptide pairs. Release of the individual peptides permits accurate measurement of their masses and independent amino acid sequence determination by tandem MS, allowing the use of standard proteomics search engines such as Comet for peptide sequence assignment, greatly simplifying data analysis of cross-linked peptide pairs. Search results are processed with XLinkProphet for validation and can be uploaded into XlinkDB for interaction network and structural analysis.

Tools for 3D Interactome Visualization

In cells, intra- and intermolecular interactions of proteins confer function, and the dynamic modulation of this interactome is critical to meet the changing needs required to support life. Cross-linking and mass spectrometry (XL-MS) enable the detection of both intra- and intermolecular protein interactions in organelles, cells, tissues, and organs. Quantitative XL-MS enables the detection of interactome changes in cells due to environmental, phenotypic, pharmacological, or genetic perturbations. We have developed new informatics capabilities, the first to enable 3D visualization of multiple quantitative interactome data sets, acquired over time or with varied perturbation levels, to reveal relevant dynamic interactome changes. These new tools are integrated within release 3.0 of our online cross-linked peptide database and analysis tool suite XLinkDB. With the recent rapid expansion in XL-MS for protein structural studies and the extension to quantitative XL-MS measurements, 3D interactome visualization tools are of critical need.