Mango: A General Tool for Collision Induced Dissociation-Cleavable Cross-Linked Peptide Identification

Combining quantitative proteomics and interactomics for a deeper insight into molecular differences between human cell lines

Cellular functional pathways have evolved through selection based on fitness benefits conferred through protein intra- and inter-molecular interactions that comprise all protein conformational features and protein-protein interactions, collectively referred to as the interactome. While the interactome is regulated by proteome levels, it is also regulated independently by, post translational modification, co-factor, and ligand levels, as well as local protein environmental factors, such as osmolyte concentration, pH, ionic strength, temperature and others. In modern biomedical research, cultivatable cell lines have become an indispensable tool, with selection of optimal cell lines that exhibit specific functional profiles being critical for success in many cases. While it is clear that cell lines derived from different cell types have differential proteome levels, increased understanding of large-scale functional differences requires additional information beyond abundance level measurements, including how protein conformations and interactions are altered in certain cell types to shape functional landscapes. Here, we employed quantitative in vivo protein cross-linking coupled to mass spectrometry to probe large-scale protein conformational and interaction changes among three commonly employed human cell lines, HEK293, MCF-7, and HeLa cells. Isobaric quantitative Protein Interaction Reporter (iqPIR) technologies were used to obtain quantitative values of cross-linked peptides across three cell lines. These data illustrated highly reproducible (R2 values larger than 0.8 for all biological replicates) quantitative interactome levels across multiple biological replicates. We also measured protein abundance levels in these cells using data independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteomics information allowed visualization of cell type-specific interactome changes mediated by proteome level adaptations as well as independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the biggest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study systems-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight on cellular functional landscapes.

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.

Photoaffinity labeling coupled to MS to identify peptide biological partners: Secondary reactions, for better or for worse?

Affinity photolabeling is a smart method to study noncovalent and transient interactions and provide a submolecular picture of the contacts between interacting partners. In this review, we will focus on the identification of peptide partners using photoaffinity labeling coupled to mass spectrometry in different contexts such as in vitro with a purified potential partner, in model systems such as model membranes, and with live cells using both targeted and nontargeted proteomics studies. Different biological partners will be described, among which glycoconjugates, oligonucleotides, peptides, proteins, and lipids, with the photoreactive label inserted either on the peptide of interest or on the potential partner. Particular attention will be paid to the observation and characterization of specific rearrangements following the photolabeling reaction, which can help characterize photoadducts and provide a better understanding of the interacting systems and environment.

Multidimensional Cross-Linking and Real-Time Informatics for Multiprotein Interaction Studies

Chemical cross-linking combined with mass spectrometry is a technique used to study protein structures and identify protein complexes. Traditionally, chemical cross-linkers contain two reactive groups, allowing them to covalently bond a pair of proximal residues, either within a protein or between two proteins. The output of a cross-linking experiment is a list of interacting site pairs that provide structural constraints for modeling of new structures and complexes. Due to the binary reactive nature of cross-linking reagents, only pairs of interacting sites can be directly observed, and assembly of higher-order structures typically requires prior knowledge of complex composition or iterative docking to produce a putative model. Here, we describe a new tetrameric cross-linker bearing four amine-reactive groups, allowing it to covalently link up to four proteins simultaneously and a real-time instrument method to facilitate the identification of these tetrameric cross-links. We applied this new cross-linker to isolated mitochondria and identified a number of higher-order cross-links in various OXPHOS complexes and ATP synthase, demonstrating its utility in characterizing complex interfaces. We also show that higher-order cross-links can be used to effectively filter models of large protein assemblies generated by using Alphafold. Higher-dimensional cross-linking provides a new avenue for characterizing multiple protein interfaces, even in complex samples such as intact mitochondria.

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.

Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline

Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.

Exhaustive Cross-Linking Search with Protein Feedback

Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

Cross-linking reactions in food proteins and proteomic approaches for their detection

Various protein cross-linking reactions leading to molecular polymerization and covalent aggregates have been described in processed foods. They are an undesired side effect of processes designed to reduce bacterial load, extend shelf life, and modify technological properties, as well as being an expected result of treatments designed to modify raw material texture and function. Although the formation of these products is known to affect the sensory and technological properties of foods, the corresponding cross-linking reactions and resulting protein polymers have not yet undergone detailed molecular characterization. This is essential for describing how their generation can be related to food processing conditions and quality parameters. Due to the complex structure of cross-linked species, bottom-up proteomic procedures developed to characterize various amino acid modifications associated with food processing conditions currently offer a limited molecular description of bridged peptide structures. Recent progress in cross-linking mass spectrometry for the topological characterization of protein complexes has facilitated the development of various proteomic methods and bioinformatic tools for unveiling bridged species, which can now also be used for the detailed molecular characterization of polymeric cross-linked products in processed foods. We here examine their benefits and limitations in terms of evaluating cross-linked food proteins and propose future scenarios for application in foodomics. They offer potential for understanding the protein cross-linking formation mechanisms in processed foods, and how the inherent beneficial properties of treated foodstuffs can be preserved or enhanced.

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.

Applications and advancements of FT-ICR-MS for interactome studies

The set of all intra- and intermolecular interactions, collectively known as the interactome, is currently an unmet challenge for any analytical method, but if measured, could provide unparalleled insight on molecular function in living systems. Developments and applications of chemical cross-linking and high-performance mass spectrometry technologies are beginning to reveal details on how proteins interact in cells and how protein conformations and interactions inside cells change with phenotype or during drug treatment or other perturbations. A major contributor to these advances is Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) technology and its implementation with accurate mass measurements on cross-linked peptide-pair precursor and fragment ions to enable improved identification methods. However, these applications place increased demands on mass spectrometer performance in terms of high-resolution spectral acquisition rates for on-line MSⁿ experiments. Moreover, FT-ICR-MS also offers unique opportunities to develop and implement parallel ICR cells for multiplexed signal acquisition and the potential to greatly advance accurate mass acquisition rates for interactome studies. This review highlights our efforts to exploit accurate mass FT-ICR-MS technologies with chemical cross-linking and developments being pursued to realize parallel MS array capabilities that will further advance visualization of the interactome.

Quantitative interactome analysis with chemical cross-linking and mass spectrometry

Structural plasticity and dynamic protein-protein interactions are critical determinants of protein function within living systems. Quantitative chemical cross-linking with mass spectrometry (qXL-MS) is an emerging technology able to provide information on changes in protein conformations and interactions. Importantly, qXL-MS is applicable to complex biological systems, including living cells and tissues, thereby providing insights into proteins within their native environments. Here, we present an overview of recent technological developments and applications involving qXL-MS, including design and synthesis of isotope-labeled cross-linkers, development of new liquid chromatography-MS methodologies, and computational developments enabling interpretation of the data.

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.

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.

Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics

BACKGROUND

Proteins are highly dynamic and their biological function is controlled by not only temporal abundance changes but also via regulated protein-protein interaction networks, which respond to internal and external perturbations. A wealth of novel analytical reagents and workflows allow studying spatiotemporal protein environments with great granularity while maintaining high throughput and ease of analysis.

AREAS COVERED

We review technology advances for measuring protein-protein proximity interactions with an emphasis on proximity labeling, and briefly summarize other spatiotemporal approaches including protein localization, and their dynamic changes over time, specifically in human cells and mammalian tissues. We focus especially on novel technologies and workflows emerging within the past 5 years. This includes enrichment-based techniques (proximity labeling and crosslinking), separation-based techniques (organelle fractionation and size exclusion chromatography), and finally sorting-based techniques (laser capture microdissection and mass spectrometry imaging).

EXPERT OPINION

Spatiotemporal proteomics is a key step in assessing biological complexity, understanding refined regulatory mechanisms, and forming protein complexes and networks. Studying protein dynamics across space and time holds promise for gaining deep insights into how protein networks may be perturbed during disease and aging processes, and offer potential avenues for therapeutic interventions, drug discovery, and biomarker development.

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.

MS Annika: A New Cross-Linking Search Engine

Cross-linking mass spectrometry (XL-MS) has become a powerful technique that enables insights into protein structures and protein interactions. The development of cleavable cross-linkers has further promoted XL-MS through search space reduction, thereby allowing for proteome-wide studies. These new analysis possibilities foster the development of new cross-linkers, which not every search engine can deal with out of the box. In addition, some search engines for XL-MS data also struggle with the validation of identified cross-linked peptides, that is, false discovery rate (FDR) estimation, as FDR calculation is hampered by the fact that not only one but two peptides in a single spectrum have to be correct. We here present our new search engine, MS Annika, which can identify cross-linked peptides in MS2 spectra from a wide variety of cleavable cross-linkers. We show that MS Annika provides realistic estimates of FDRs without the need of arbitrary score cutoffs, being able to provide on average 44% more identifications at a similar or better true FDR than comparable tools. In addition, MS Annika can be used on proteome-wide studies due to fast, parallelized processing and provides a way to visualize the identified cross-links in protein 3D structures.

Towards low false discovery rate estimation for protein-protein interactions detected by chemical cross-linking

Chemical cross-linking (CX) of proteins in vivo or in cell free extracts followed by mass spectrometric (MS) identification of linked peptide pairs (CXMS) can reveal protein-protein interactions (PPIs) both at a proteome wide scale and the level of cross-linked amino acid residues. However, error estimation at the level of PPI remains challenging in large scale datasets. Here we discuss recent advances in the recognition of spurious inter-protein peptide pairs and in diminishing the FDR for these PPI-signaling cross-links, such as the use of chromatographic retention time prediction, in order to come to a more reliable reporting of PPIs.

LinX: A Software Tool for Uncommon Cross-Linking Chemistry

Chemical cross-linking mass spectrometry has become a popular tool in structural biology. Although several algorithms exist that efficiently analyze data-dependent mass spectrometric data, the algorithm to identify and quantify intermolecular cross-links located at the interaction interface of homodimer molecules was missing. The algorithm in LinX utilizes high mass accuracy for ion identification. In contrast with standard data-dependent analysis, LinX enables the elucidation of cross-linked peptides originating from the interaction interface of homodimers labeled by ¹⁴N/¹⁵N, including their ratio or cross-links from protein-nucleic acid complexes. The software is written in Java language, and its source code and a detailed user's guide are freely available at https://github.com/KukackaZ/LinX or https://ms-utils.org/LinX. Data are accessible via the ProteomeXchange server with the data set identifier PXD023522.

Crosslinking mass spectrometry: A link between structural biology and systems biology

Protein structure underpins functional roles in all biological processes; therefore, improved understanding of protein structures is of fundamental importance in nearly all biological and biomedical research areas. Traditional techniques such as X-ray crystallography and more recently, cryo-EM, can reveal structural features on isolated proteins/protein complexes at atomic resolution level and have become indispensable tools for structural biology. Crosslinking mass spectrometry (XL-MS), on the other hand, is an emerging technique capable of capturing transient and dynamic information on protein interactions and assemblies in their native environment. The combination of XL-MS with traditional techniques holds potential for bridging the gap between structural biology and systems biology approaches. Such a combination will enable visualization of protein structures and interactions within the crowded macromolecular environment in living systems that can dramatically increase understanding of biological functions. In this review, we first discuss general strategies of XL-MS and then survey recent examples to show how qualitative and quantitative XL-MS studies can be integrated with available protein structural data to better understand biological function at systems level.

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.

Mitochondrial protein interaction landscape of SS-31

Mitochondrial dysfunction underlies the etiology of a broad spectrum of diseases including heart disease, cancer, neurodegenerative diseases, and the general aging process. Therapeutics that restore healthy mitochondrial function hold promise for treatment of these conditions. The synthetic tetrapeptide, elamipretide (SS-31), improves mitochondrial function, but mechanistic details of its pharmacological effects are unknown. Reportedly, SS-31 primarily interacts with the phospholipid cardiolipin in the inner mitochondrial membrane. Here we utilize chemical cross-linking with mass spectrometry to identify protein interactors of SS-31 in mitochondria. The SS-31-interacting proteins, all known cardiolipin binders, fall into two groups, those involved in ATP production through the oxidative phosphorylation pathway and those involved in 2-oxoglutarate metabolic processes. Residues cross-linked with SS-31 reveal binding regions that in many cases, are proximal to cardiolipin-protein interacting regions. These results offer a glimpse of the protein interaction landscape of SS-31 and provide mechanistic insight relevant to SS-31 mitochondrial therapy.

Improving Identification of In-organello Protein-Protein Interactions Using an Affinity-enrichable, Isotopically Coded, and Mass Spectrometry-cleavable Chemical Crosslinker

An experimental and computational approach for identification of protein-protein interactions by ex vivo chemical crosslinking and mass spectrometry (CLMS) has been developed that takes advantage of the specific characteristics of cyanurbiotindipropionylsuccinimide (CBDPS), an affinity-tagged isotopically coded mass spectrometry (MS)-cleavable crosslinking reagent. Utilizing this reagent in combination with a crosslinker-specific data-dependent acquisition strategy based on MS2 scans, and a software pipeline designed for integrating crosslinker-specific mass spectral information led to demonstrated improvements in the application of the CLMS technique, in terms of the detection, acquisition, and identification of crosslinker-modified peptides. This approach was evaluated on intact yeast mitochondria, and the results showed that hundreds of unique protein-protein interactions could be identified on an organelle proteome-wide scale. Both known and previously unknown protein-protein interactions were identified. These interactions were assessed based on their known sub-compartmental localizations. Additionally, the identified crosslinking distance constraints are in good agreement with existing structural models of protein complexes involved in the mitochondrial electron transport chain.

An experimentally generated peptide database increases the sensitivity of XL-MS with complex samples

Cross-linking mass spectrometry (XL-MS) is steadily expanding its range of applications from purified protein complexes to more complex samples like organelles and even entire cells. One main challenge using non-cleavable cross-linkers is the so-called n² problem: With linearly increasing database size, the search space for the identification of two covalently linked peptides per spectrum increases quadratically. Here, we report an alternative search strategy that focuses on only those peptides, which were demonstrated to cross-link under the applied experimental conditions. The performance of a parallel XL-MS experiment using a thiol-cleavable cross-linker enabled the identification of peptides that carried a cleaved cross-link moiety after reduction and hence were involved in cross-linking reactions. Based on these identifications, a peptide database was generated and used for the database search of the actual cross-linking experiment with a non-cleavable cross-linker. This peptide-focused approach was tested on protein complexes with a reported structural model and obtained results corresponded well to a conventional database search. An application of the strategy on in vivo cross-linked Bacillus subtilis and Bacillus cereus cells revealed a five- to tenfold reduction in search time and led to significantly more identifications with the latter species than a search against the entire proteome. SIGNIFICANCE: Instead of considering all theoretically cross-linkable peptides in a proteome, identification and pre-filtering for a subset of cross-link peptide candidates allows for a dramatically decreased search space. Hence, there is less potential for the random accumulation of false positives ultimately leading to a higher sensitivity in the XL-MS experiment. Using the peptide-focused approach, a cross-linking database search can be conducted in a fraction of time while yielding a similar or higher number of identifications, thereby enabling the cross-linking analysis of samples of mammalian proteome complexity.

Parallel Detection of Fundamental and Sixth Harmonic Signals Using an ICR Cell with Dipole and Sixth Harmonic Detectors

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful instrument for high-resolution analysis of biomolecules. However, relatively long signal acquisition periods are needed to achieve mass spectra with high resolution. The use of multiple detector electrodes for detection of harmonic frequencies has been introduced as one approach to increase scan rate for a given resolving power or to obtain increased resolving power for a given detection period. The achieved resolving power and scan rate increase linearly with the order of detected harmonic signals. In recent years, ICR cell geometries have been investigated to increase the order of the harmonic frequencies and enhance harmonic signal intensities. In this study, we demonstrated PCB-based ICR cell designs with dipole and sixth harmonic detectors for parallel detection of fundamental and harmonic (6f) signals. The sixth harmonic signals from the sixth harmonic detector showed an expected 6 times higher resolving power with (M + 3H)3+ charge state insulin ions as compared with that from fundamental signals from the dipole detector. Moreover, the insulin isotopic peaks with sixth harmonic frequency signals acquired with the sixth harmonic detector were resolved for a 40 ms data acquisition period but unresolved with the same duration dipole detector signals, corresponding to a 6-fold improvement in achievable spectral acquisition rates for a given resolving power.

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.

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

MOTIVATION

Peptides crosslinked with cleavable chemical crosslinkers are identified with mass spectrometry by independent database search of spectra associated with the two linked peptides. A major challenge is to combine together the evidence of the two peptides into an overall assessment of the two-peptide crosslink.

RESULTS

Here, we describe software that models crosslink specific information to automatically validate XL-MS cleavable peptide crosslinks. Using a dataset of crosslinked protein mixtures, we demonstrate that it computes accurate and highly discriminating probabilities, enabling as many as 75% more identifications than was previously possible using only search scores and a predictable false discovery rate.

AVAILABILITY AND IMPLEMENTATION

XLinkProphet software is freely available on the web at http://brucelab.gs.washington.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

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.