Quantitative interactome analysis reveals a chemoresistant edgotype

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.

Mucin 1 promotes salivary gland cancer cell proliferation and metastasis by regulating the epidermal growth factor receptor signaling pathway

Background/purpose

Salivary gland cancer (SGC) is the common malignant tumor of the head and neck region with poor prognosis. Mucin 1 (MUC1) has been reported to be associated with the development of cancer. However, whether MUC1 contributed to the progression of SGC remains to be explored.

Materials and methods

Immunohistochemical analysis was used to explore the expression levels of MUC1 in SGC tissues. Cell proliferation, colony formation, wound healing, transwell, and xenograft assays were performed to examine the effects of MUC1 on SGC in vitro and in vivo.

Results

We found that the expression level of MUC1 was significantly upregulated in SGC tissues, and the expression level of MUC1 was significantly correlated with lymph node metastasis and TNM stage of SGC. Further exploration demonstrated that MUC1 knockdown drastically inhibited, while its overexpression promoted, cell growth, colony formation, migration, and invasion abilities of SGC cells in vitro. MUC1 knockdown significantly inhibited tumor growth in vivo, and vice versa. More importantly, we found that MUC1 promotes malignant phenotypes of SGC cells by regulating the epidermal growth factor receptor (EGFR) signaling pathway.

Conclusion

Our results revealed that MUC1 promotes the development of SGC by mediating the EGFR signaling pathway, which highlights the potential therapeutic target of MUC1/ EGFR in SGC.

Integrated Analysis of Cross-Links and Dead-End Peptides for Enhanced Interpretation of Quantitative XL-MS

Chemical cross-linking with mass spectrometry provides low-resolution structural information on proteins in cells and tissues. Combined with quantitation, it can identify changes in the interactome between samples, for example, control and drug-treated cells or young and old mice. A difference can originate from protein conformational changes that alter the solvent-accessible distance separating the cross-linked residues. Alternatively, a difference can result from conformational changes localized to the cross-linked residues, for example, altering the solvent exposure or reactivity of those residues or post-translational modifications of the cross-linked peptides. In this manner, cross-linking is sensitive to a variety of protein conformational features. Dead-end peptides are cross-links attached only at one end to a protein with the other terminus being hydrolyzed. As a result, changes in their abundance reflect only conformational changes localized to the attached residue. For this reason, analyzing both quantified cross-links and their corresponding dead-end peptides can help elucidate the likely conformational changes giving rise to observed differences in cross-link abundance. We describe analysis of dead-end peptides in the XLinkDB public cross-link database and, with quantified mitochondrial data isolated from failing heart versus healthy mice, show how a comparison of abundance ratios between cross-links and their corresponding dead-end peptides can be leveraged to reveal possible conformational explanations.

Integrated Analysis of Cross-Links and Dead-End Peptides for Enhanced Interpretation of Quantitative XL-MS

XL-MS provides low-resolution structural information of proteins in cells and tissues. Combined with quantitation, it can identify changes in the interactome between samples, for example, control and drug-treated cells, or young and old mice. A difference can originate from protein conformational changes altering the solvent-accessible distance separating the cross-linked residues. Alternatively, a difference can result from conformational changes localized to the cross-linked residues, for example, altering the solvent exposure or reactivity of those residues or post-translational modifications on the cross-linked peptides. In this manner, cross-linking is sensitive to a variety of protein conformational features. Dead-end peptides are cross-links attached only at one end to a protein, the other terminus being hydrolyzed. As a result, changes in their abundance reflect only conformational changes localized to the attached residue. For this reason, analyzing both quantified cross-links and their corresponding dead-end peptides can help elucidate the likely conformational changes giving rise to observed differences of cross-link abundance. We describe analysis of dead-end peptides in the XLinkDB public cross-link database and, with quantified mitochondrial data isolated from failing heart versus healthy mice, show how a comparison of abundance ratios between cross-links and their corresponding dead-end peptides can be leveraged to reveal possible conformational explanations.

Cross-linking mass spectrometry for mapping protein complex topologies in situ

Cross-linking mass spectrometry has become an established technology to provide structural information on the topology and dynamics of protein complexes. Readily accessible workflows can provide detailed data on simplified systems, such as purified complexes. However, using this technology to study the structure of protein complexes in situ, such as in organelles, cells, and even tissues, is still a technological frontier. The complexity of these systems remains a considerable challenge, but there have been dramatic improvements in sample handling, data acquisition, and data processing. Here, we summarise these developments and describe the paths towards comprehensive and comparative structural interactomes by cross-linking mass spectrometry.

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.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

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.

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.

Multiplexed Isobaric Quantitative Cross-Linking Reveals Drug-Induced Interactome Changes in Breast Cancer Cells

The study of protein structures and interactions is critical to understand their function. Chemical cross-linking of proteins with mass spectrometry (XL-MS) is a rapidly developing structural biology technique able to provide valuable insight into protein conformations and interactions, even as they exist within their native cellular environment. Quantitative analysis of cross-links can reveal protein conformational and interaction changes that occur as a result of altered biological states, environmental conditions, or pharmacological perturbations. Our laboratory recently developed an isobaric quantitative protein interaction reporter (iqPIR) cross-linking strategy for comparative interactome studies. This strategy relies on isotope encoded chemical cross-linkers that have the same molecular mass yet produce unique and specific isotope signatures upon fragmentation in the mass spectrometer which can be used for quantitative analysis of cross-linked peptides. The initial set of iqPIR molecules allowed for binary comparisons. Here, we describe the in vivo application of an extended set of six iqPIR reagents (6-plex iqPIR), allowing multiplexed quantitative interactome analysis of up to six biological samples in a single LC-MS acquisition. Multiplexed iqPIR is demonstrated on MCF-7 breast cancer cells treated with five different Hsp90 inhibitors revealing large scale protein conformational and interaction changes specific to the molecular class of the inhibitors.

Mapping oncogenic protein interactions for precision medicine

Normal protein‐protein interactions (normPPIs) occur with high fidelity to regulate almost every physiological process. In cancer, this highly organised and precisely regulated network is disrupted, hijacked or reprogrammed resulting in oncogenic protein‐protein interactions (oncoPPIs). OncoPPIs, which can result from genomic alterations, are a hallmark of many types of cancers. Recent technological advances in the field of mass spectrometry (MS)‐based interactomics, structural biology and drug discovery have prompted scientists to identify and characterise oncoPPIs. Disruption of oncoPPI interfaces has become a major focus of drug discovery programs and has resulted in the use of PPI‐specific drugs clinically. However, due to several technical hurdles, studies to build a reference oncoPPI map for various cancer types have not been undertaken. Therefore, there is an urgent need for experimental workflows to overcome the existing challenges in studying oncoPPIs in various cancers and to build comprehensive reference maps. Here, we discuss the important hurdles for characterising oncoPPIs and propose a three‐phase multidisciplinary workflow to identify and characterise oncoPPIs. Systematic identification of cancer‐type‐specific oncogenic interactions will spur new opportunities for PPI‐focused drug discovery projects and precision medicine.

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.

Multiplexed Cross-Linking with Isobaric Quantitative Protein Interaction Reporter Technology

Chemical cross-linking with mass spectrometry (XL-MS) has emerged as a useful technique for interrogating protein structures and interactions. When combined with quantitative proteomics strategies, protein conformational and interaction dynamics can be probed. Quantitative XL-MS has been demonstrated with the use of stable isotopes incorporated metabolically or into the cross-linker molecules. Isotope-labeled cross-linkers have primarily utilized deuterium and rely on MS1-based quantitation of precursor ion extracted ion chromatograms. Recently the development and application of isobaric quantitative protein interaction reporter (iqPIR) cross-linkers were reported, which utilize ¹³C and ¹⁵N isotope labels. Quantitation is accomplished using relative fragment ion isotope abundances in tandem mass spectra. Here we describe the synthesis and initial evaluation of a multiplexed set of iqPIR molecules, allowing for up to six cross-linked samples to be quantified simultaneously. To analyze data for such cross-linkers, the two-channel mode of iqPIR quantitative analysis was adapted to accommodate any number of channels with defined ion isotope peak mass offsets. The summed ion peak intensities in the overlapping channel isotope envelopes are apportioned among the channels to minimize the difference with respect to the predicted ion isotope envelopes. The result is accurate and reproducible relative quantitation enabling direct comparison among six differentially labeled cross-linked samples. The approach described here is generally extensible for the iqPIR strategy, accommodating future iqPIR reagent design, and enables large-scale in vivo quantitative XL-MS investigation of the interactome.

Grouped-seq for integrated phenotypic and transcriptomic screening of patient-derived tumor organoids

Patient-derived tumor organoids (PDOs) have emerged as a reliable in vitro model for drug discovery. However, RNA sequencing-based analysis of PDOs treated with drugs has not been realized in a high-throughput format due to the limited quantity of organoids. Here, we translated a newly developed pooled RNA-seq methodology onto a superhydrophobic microwell array chip to realize an assay of genome-wide RNA output unified with phenotypic data (Grouped-seq). Over 10-fold reduction of sample and reagent consumption together with a new ligation-based barcode synthesis method lowers the cost to ∼$2 per RNA-seq sample. Patient-derived colorectal cancer (CRC) organoids with a number of 10 organoids per microwell were treated with four anti-CRC drugs across eight doses and analyzed by the Grouped-seq. Using a phenotype-assisted pathway enrichment analysis (PAPEA) method, the mechanism of actions of the drugs were correctly derived, illustrating the great potential of Grouped-seq for pharmacological screening with tumor organoids.

Leveraging crosslinking mass spectrometry in structural and cell biology

Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.

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.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

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.

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.

Quantitative Cross-Linking of Proteins and Protein Complexes

Cross-linking, in general, involves the covalent linkage of two amino acid residues of proteins or protein complexes in close proximity. Mass spectrometry and computational analysis are then applied to identify the formed linkage and deduce structural information such as distance restraints. Quantitative cross-linking coupled with mass spectrometry is well suited to study protein dynamics and conformations of protein complexes. The quantitative cross-linking workflow described here is based on the application of isotope labelled cross-linkers. Proteins or protein complexes present in different structural states are differentially cross-linked using a "light" and a "heavy" cross-linker. The intensity ratios of cross-links (i.e., light/heavy or heavy/light) indicate structural changes or interactions that are maintained in the different states. These structural insights lead to a better understanding of the function of the proteins or protein complexes investigated. The described workflow is applicable to a wide range of research questions including, for instance, protein dynamics or structural changes upon ligand binding.

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.

Composition of hemidesmosomes in basal keratinocytes of normal buccal mucosa and oral lichen planus

Oral lichen planus (OLP) is a chronic inflammatory disease displaying ultrastructural disturbances in epithelial hemidesmosomes. The expression of several key hemidesmosomal components in OLP as well as in normal buccal mucosa is, however, unknown. The aim of the study was therefore to examine intracellular and extracellular components involved in hemidesmosomal attachment, in OLP (n = 20) and in normal buccal mucosa (n = 10), by immunofluorescence. In normal buccal mucosa, laminin-α3γ2, integrin-α6β4, CD151, collagen α-1(XVII) chain, and dystonin showed linear expression along the basal membrane, indicating the presence of type I hemidesmosomes. Plectin stained most epithelial cell membranes and remained unphosphorylated at S4642. In OLP, most hemidesmosomal molecules examined showed disturbed expression consisting of discontinuous increases, apicolateral location, and/or intracellular accumulation. Plectin showed S4642-phosphorylation at the basement membrane, and deposits of laminin-α3 and laminin-γ2 were found within the connective tissue. The disturbed expression of hemidesmosomal proteins in OLP indicates deficient attachment of the basal cell layer, which can contribute to detachment and cell death of basal keratinocytes seen in the disease.

A Cross-linking Mass Spectrometry Approach Defines Protein Interactions in Yeast Mitochondria

Protein cross-linking and the analysis of cross-linked peptides by mass spectrometry is currently receiving much attention. Not only is this approach applied to isolated complexes to provide information about spatial arrangements of proteins, but it is also increasingly applied to entire cells and their organelles. As in quantitative proteomics, the application of isotopic labeling further makes it possible to monitor quantitative changes in the protein-protein interactions between different states of a system. Here, we cross-linked mitochondria from Saccharomyces cerevisiae grown on either glycerol- or glucose-containing medium to monitor protein-protein interactions under non-fermentative and fermentative conditions. We investigated qualitatively the protein-protein interactions of the 400 most abundant proteins applying stringent data-filtering criteria, i.e. a minimum of two cross-linked peptide spectrum matches and a cut-off in the spectrum scoring of the used search engine. The cross-linker BS3 proved to be equally suited for connecting proteins in all compartments of mitochondria when compared with its water-insoluble but membrane-permeable derivative DSS. We also applied quantitative cross-linking to mitochondria of both the growth conditions using stable-isotope labeled BS3. Significant differences of cross-linked proteins under glycerol and glucose conditions were detected, however, mainly because of the different copy numbers of these proteins in mitochondria under both the conditions. Results obtained from the glycerol condition indicate that the internal NADH:ubiquinone oxidoreductase Ndi1 is part of an electron transport chain supercomplex. We have also detected several hitherto uncharacterized proteins and identified their interaction partners. Among those, Min8 was found to be associated with cytochrome c oxidase. BN-PAGE analyses of min8Δ mitochondria suggest that Min8 promotes the incorporation of Cox12 into cytochrome c oxidase.

MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a "MS2-centric" approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics ["fraction of mis-identifications" (FMI) and "fraction of interprotein cross-links from known interactions" (FKI)]. We then address this problem, by designing a novel "MS3-centric" approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

A protocol for studying structural dynamics of proteins by quantitative crosslinking mass spectrometry and data-independent acquisition

Quantitative crosslinking mass spectrometry (QCLMS) reveals structural details of protein conformations in solution. QCLMS can benefit from data-independent acquisition (DIA), which maximises accuracy, reproducibility and throughput of the approach. This DIA-QCLMS protocol comprises of three main sections: sample preparation, spectral library generation and quantitation. The DIA-QCLMS workflow supports isotope-labelling as well as label-free quantitation strategies, uses xiSEARCH for crosslink identification, and xiDIA-Library to create a spectral library for a peptide-centric quantitative approach. We integrated Spectronaut, a leading quantitation software, to analyse DIA data. Spectronaut supports DIA-QCLMS data to quantify crosslinks. It can be used to reveal the structural dynamics of proteins and protein complexes, even against a complex background. In combination with photoactivatable crosslinkers (photo-DIA-QCLMS), the workflow can increase data density and better capture protein dynamics due to short reaction times. Additionally, this can reveal conformational changes caused by environmental influences that would otherwise affect crosslinking itself, such as changing pH conditions. SIGNIFICANCE: This protocol is an detailed step-by-step description on how to implement our previously published DIA-QCLMS workflow (Müller et al. Mol Cell Proteomics. 2019 Apr;18(4):786-795). It includes sample preparation for QCLMS, Optimization of DIA strategies, implementation of the Spectronaut software and required python scripts and guideline on how to analyse quantitative crosslinking data. The DIA-QCLMS workflow widen the scope for a range of new crosslinking applications and this step-by-step protocol enhances the accessibility to a broad scientific user base.

In Vivo Cross-Linking MS Reveals Conservation in OmpA Linkage to Different Classes of β-Lactamase Enzymes

Molecular interactions between two different classes of β-lactamase enzymes and outer membrane protein A (OmpA) were studied by in vivo chemical cross-linking of a multi-drug-resistant strain of Acinetobacter baumannii AB5075. Class A β-lactamase blaGES-11 and Class D β-lactamase Oxa23, responsible for hydrolysis of different types of β-lactam antibiotics, were found to be cross-linked to similar lysine sites of the periplasmic domain of outer membrane protein OmpA, despite low sequence homology between the two enzymes. The findings from in vivo XL-MS suggest that the interacting surfaces between both β-lactamase enzymes and OmpA are conserved during molecular evolution, and the OmpA C-terminus domain serves an important function of anchoring different types of β-lactamase enzymes in the periplasmic space.

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.

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.

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.

Quantitative cross-linking/mass spectrometry to elucidate structural changes in proteins and their complexes

Quantitative cross-linking/mass spectrometry (QCLMS/QXL-MS) probes structural changes of proteins in solution. This method has revealed induced conformational changes, composition shifts in conformational ensembles and changes in protein interactions. It illuminates different structural states of proteins or protein complexes by comparing which residue pairs can be cross-linked in these states. Cross-links provide information about structural changes that may be inaccessible by alternative technologies. Small local conformational changes affect relative abundances of nearby cross-links, whereas larger conformational changes cause new cross-links to be formed. Distinguishing between minor and major changes requires a robust analysis based on carefully selected replicates and, when using isotope-labeled cross-linkers, replicated analysis with a permutated isotope-labeling scheme. A label-free workflow allows for application of a wide range of cross-linking chemistries and enables parallel comparison of multiple conformations. In this protocol, we demonstrate both label-free and isotope-labeled cross-linker-based workflows using the cross-linker bis(sulfosuccinimidyl)suberate (BS3). The software XiSearch, developed by our group, is used to identify cross-linked residue pairs, although the workflow is not limited to this search software. The open-access software Skyline is used for automated quantitation. Note that additional manual correction greatly enhances quantitation accuracy. The protocol has been applied to purified multi-protein complexes but is not necessarily limited to that level of sample complexity. Optimizing the cross-linker/protein ratio and fractionating peptides increase the data density of quantified cross-links, and thus the resolution of QCLMS. The entire procedure takes ~1-3 weeks.

Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry

Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS3) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS.

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.

Cross-linking mass spectrometry: methods and applications in structural, molecular and systems biology

Over the past decade, cross-linking mass spectrometry (CLMS) has developed into a robust and flexible tool that provides medium-resolution structural information. CLMS data provide a measure of the proximity of amino acid residues and thus offer information on the folds of proteins and the topology of their complexes. Here, we highlight notable successes of this technique as well as common pipelines. Novel CLMS applications, such as in-cell cross-linking, probing conformational changes and tertiary-structure determination, are now beginning to make contributions to molecular biology and the emerging fields of structural systems biology and interactomics.

Identification of Integrin β1 as a Novel PAG1-Interacting Protein Involved in the Inherent Radioresistance of Human Laryngeal Carcinoma

Inherent radioresistance plays a crucial role in the failure of radiotherapy. Using the inherent radioresistant (Hep-2max) and radiosensitive (Hep-2min) cell lines established from the parental cell line Hep-2, we previously reported that phosphoprotein associated with glycosphingolipid-enriched microdomains 1(PAG1) overexpression in laryngeal carcinoma cells was correlated with inherent radioresistant phenotypes. However, the underlying mechanisms of this effect remain unknown. In the present study, we performed a proteomic screen to investigate the interactome of PAG1 in Hep-2max cells resulting in the identification of several interaction partners. Bioinformatic analysis and immunofluorescence experiments indicated the integrin β1 to be a crucial interaction partner of PAG1. PAG1 was also highly expressed in laryngeal carcinoma radioresistant tissues and showed co-localization with integrin β1. In addition, we demonstrated that integrin β1's binding to PAG1 could be interrupted by MβCD, an inhibitor of lipid rafts formation. Moreover, knockdown of integrin β1 by RNA interference sensitized radioresistant cells to irradiation. Importantly, we identified 2 potential interaction sites (Pro²¹⁶-Arg²³² and Asn³⁵⁶-Gly³⁷⁷) in the cytoplasmic domain of PAG1 using high throughput peptide arrays. Taken together, these results suggest that the binding of PAG1 to integrin β1 in lipid rafts is essential for inherent radioresistance of human laryngeal carcinoma.

Protein Dynamics in Solution by Quantitative Crosslinking/Mass Spectrometry

The dynamics of protein structures and their interactions are responsible for many cellular processes. The rearrangements and interactions of proteins, which are often transient, occur in solution and may require a biological environment that is difficult to maintain in traditional structural biological approaches. Quantitative crosslinking/mass spectrometry (QCLMS) has emerged as an excellent method to fill this gap. Numerous recent applications of the technique have demonstrated that protein dynamics can now be studied in solution at sufficient resolution to gain valuable biological insights, suggesting that extending these investigations to native environments is possible. These breakthroughs have been based on the maturation of CLMS at large, and its recent fusion with quantitative proteomics. We provide here an overview of the current state of the technique, the available workflows and their applications, and remaining challenges.

In-solution dynamics of protein structures and their interactions can be studied by QCLMS.

Successful applications of QCLMS provide insights into multiple different biological processes.

Recent advances in QCLMS allow analyses in the context of native cellular environments, including living cells.

Alternative workflows allow researchers to tailor the analysis to their biological question.

Progress in data processing now offers this technique to researchers with limited initial expertise in crosslinking and quantitative proteomics.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

Chemical cross-linking with mass spectrometry: a tool for systems structural biology

Biological processes supporting life are orchestrated by a highly dynamic array of protein structures and interactions comprising the interactome. Defining the interactome, visualizing how structures and interactions change and function to support life is essential to improved understanding of fundamental molecular processes, but represents a challenge unmet by any single analytical technique. Chemical cross-linking with mass spectrometry provides identification of proximal amino acid residues within proteins and protein complexes, yielding low resolution structural information. This approach has predominantly been employed to provide structural insight on isolated protein complexes, and has been particularly useful for molecules that are recalcitrant to conventional structural biology studies. Here we discuss recent developments in cross-linking and mass spectrometry technologies that are providing large-scale or systems-level interactome data with successful applications to isolated organelles, cell lysates, virus particles, intact bacterial and mammalian cultured cells and tissue samples.

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

Chemical cross-linking combined with mass spectrometry provides a method to study protein structures and interactions. The introduction of cleavable bonds in a cross-linker provides an avenue to decouple released peptide masses from their precursor species, greatly simplifying the downstream search, allowing for whole proteome investigations to be performed. Typically, these experiments have been challenging to carry out, often utilizing nonstandard methods to fully identify cross-linked peptides. Mango is an open source software tool that extracts precursor masses from chimeric spectra generated using cleavable cross-linkers, greatly simplifying the downstream search. As it is designed to work with chimeric spectra, Mango can be used on traditional high-resolution tandem mass spectrometry (MS/MS) capable mass spectrometers without the need for additional modifications. When paired with a traditional proteomics search engine, Mango can be used to identify several thousand cross-linked peptide pairs searching against the entire Escherichia coli proteome. Mango provides an avenue to perform whole proteome cross-linking experiments without specialized instrumentation or access to nonstandard methods.

XPlex: An Effective, Multiplex Cross-Linking Chemistry for Acidic Residues

Cross-linking/Mass spectrometry (XLMS) is a consolidated technique for structural characterization of proteins and protein complexes. Despite its success, the cross-linking chemistry currently used is mostly based on N-hydroxysuccinimide (NHS) esters, which react primarily with lysine residues. One way to expand the current applicability of XLMS into several new areas is to increase the number of cross-links obtainable for a target protein. We introduce a multiplex chemistry (denoted XPlex) that targets Asp, Glu, Lys, and Ser residues. XPlex can generate significantly more cross-links with reactions occurring at lower temperatures and enables targeting proteins that are not possible with NHS ester-based cross-linkers. We demonstrate the effectiveness of our approach in model proteins as well as a target Lys-poor protein, SalBIII. Identification of XPlex spectra requires a search engine capable of simultaneously considering multiple cross-linkers on the same run; to achieve this, we updated the SIM-XL search algorithm with a search mode tailored toward XPlex. In summary, we present a complete chemistry/computational solution for significantly increasing the number of possible distance constraints by mass spectrometry experiments, and thus, we are convinced that XPlex poses as a real complementary approach for structural proteomics studies.

Integrating Cross-Linking Experiments with Ab Initio Protein-Protein Docking

Ab initio protein-protein docking algorithms often rely on experimental data to identify the most likely complex structure. We integrated protein-protein docking with the experimental data of chemical cross-linking followed by mass spectrometry. We tested our approach using 19 cases that resulted from an exhaustive search of the Protein Data Bank for protein complexes with cross-links identified in our experiments. We implemented cross-links as constraints based on Euclidean distance or void-volume distance. For most test cases, the rank of the top-scoring near-native prediction was improved by at least twofold compared with docking without the cross-link information, and the success rate for the top 5 predictions nearly tripled. Our results demonstrate the delicate balance between retaining correct predictions and eliminating false positives. Several test cases had multiple components with distinct interfaces, and we present an approach for assigning cross-links to the interfaces. Employing the symmetry information for these cases further improved the performance of complex structure prediction.

Chemical Crosslinking Mass Spectrometry Analysis of Protein Conformations and Supercomplexes in Heart Tissue

While modern structural biology technologies have greatly expanded the size and type of protein complexes that can now be studied, the ability to derive large-scale structural information on proteins and complexes as they exist within tissues is practically nonexistent. Here, we demonstrate the application of crosslinking mass spectrometry to identify protein structural features and interactions in tissue samples, providing systems structural biology insight into protein complexes as they exist in the mouse heart. This includes insights into multiple conformational states of sarcomere proteins, as well as interactions among OXPHOS complexes indicative of supercomplex assembly. The extension of crosslinking mass spectrometry analysis into the realm of tissues opens the door to increasing our understanding of protein structures and interactions within the context of the greater biological system.