A New in Vivo Cross-linking Mass Spectrometry Platform to Define Protein–Protein Interactions in Living Cells

Protein–protein interactions (PPIs) are fundamental to the structure and function of protein complexes. Resolving the physical contacts between proteins as they occur in cells is critical to uncovering the molecular details underlying various cellular activities. To advance the study of PPIs in living cells, we have developed a new in vivo cross-linking mass spectrometry platform that couples a novel membrane-permeable, enrichable, and MS-cleavable cross-linker with multistage tandem mass spectrometry. This strategy permits the effective capture, enrichment, and identification of in vivo cross-linked products from mammalian cells and thus enables the determination of protein interaction interfaces. The utility of the developed method has been demonstrated by profiling PPIs in mammalian cells at the proteome scale and the targeted protein complex level. Our work represents a general approach for studying in vivo PPIs and provides a solid foundation for future studies toward the complete mapping of PPI networks in living systems.Protein–protein interactions (PPIs)¹ play a key role in defining protein functions in biological systems. Aberrant PPIs can have drastic effects on biochemical activities essential to cell homeostasis, growth, and proliferation, and thereby lead to various human diseases (1). Consequently, PPI interfaces have been recognized as a new paradigm for drug development. Therefore, mapping PPIs and their interaction interfaces in living cells is critical not only for a comprehensive understanding of protein function and regulation, but also for describing the molecular mechanisms underlying human pathologies and identifying potential targets for better therapeutics.Several strategies exist for identifying and mapping PPIs, including yeast two-hybrid, protein microarray, and affinity purification mass spectrometry (AP-MS) (2–5). Thanks to new developments in sample preparation strategies, mass spectrometry technologies, and bioinformatics tools, AP-MS has become a powerful and preferred method for studying PPIs at the systems level (6–9). Unlike other approaches, AP-MS experiments allow the capture of protein interactions directly from their natural cellular environment, thus better retaining native protein structures and biologically relevant interactions. In addition, a broader scope of PPI networks can be obtained with greater sensitivity, accuracy, versatility, and speed. Despite the success of this very promising technique, AP-MS experiments can lead to the loss of weak/transient interactions and/or the reorganization of protein interactions during biochemical manipulation under native purification conditions. To circumvent these problems, in vivo chemical cross-linking has been successfully employed to stabilize protein interactions in native cells or tissues prior to cell lysis (10–16). The resulting covalent bonds formed between interacting partners allow affinity purification under stringent and fully denaturing conditions, consequently reducing nonspecific background while preserving stable and weak/transient interactions (12–16). Subsequent mass spectrometric analysis can reveal not only the identities of interacting proteins, but also cross-linked amino acid residues. The latter provides direct molecular evidence describing the physical contacts between and within proteins (17). This information can be used for computational modeling to establish structural topologies of proteins and protein complexes (17–22), as well as for generating experimentally derived protein interaction network topology maps (23, 24). Thus, cross-linking mass spectrometry (XL-MS) strategies represent a powerful and emergent technology that possesses unparalleled capabilities for studying PPIs.Despite their great potential, current XL-MS studies that have aimed to identify cross-linked peptides have been mostly limited to in vitro cross-linking experiments, with few successfully identifying protein interaction interfaces in living cells (24, 25). This is largely because XL-MS studies remain challenging due to the inherent difficulty in the effective MS detection and accurate identification of cross-linked peptides, as well as in unambiguous assignment of cross-linked residues. In general, cross-linked products are heterogeneous and low in abundance relative to non-cross-linked products. In addition, their MS fragmentation is too complex to be interpreted using conventional database searching tools (17, 26). It is noted that almost all of the current in vivo PPI studies utilize formaldehyde cross-linking because of its membrane permeability and fast kinetics (10–16). However, in comparison to the most commonly used amine reactive NHS ester cross-linkers, identification of formaldehyde cross-linked peptides is even more challenging because of its promiscuous nonspecific reactivity and extremely short spacer length (27). Therefore, further developments in reagents and methods are urgently needed to enable simple MS detection and effective identification of in vivo cross-linked products, and thus allow the mapping of authentic protein contact sites as established in cells, especially for protein complexes.Various efforts have been made to address the limitations of XL-MS studies, resulting in new developments in bioinformatics tools for improved data interpretation (28–32) and new designs of cross-linking reagents for enhanced MS analysis of cross-linked peptides (24, 33–39). Among these approaches, the development of new cross-linking reagents holds great promise for mapping PPIs on the systems level. One class of cross-linking reagents containing an enrichment handle have been shown to allow selective isolation of cross-linked products from complex mixtures, boosting their detectability by MS (33–35, 40–42). A second class of cross-linkers containing MS-cleavable bonds have proven to be effective in facilitating the unambiguous identification of cross-linked peptides (36–39, 43, 44), as the resulting cross-linked products can be identified based on their characteristic and simplified fragmentation behavior during MS analysis. Therefore, an ideal cross-linking reagent would possess the combined features of both classes of cross-linkers. To advance the study of in vivo PPIs, we have developed a new XL-MS platform based on a novel membrane-permeable, enrichable, and MS-cleavable cross-linker, Azide-A-DSBSO (azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide), and multistage tandem mass spectrometry (MSⁿ). This new XL-MS strategy has been successfully employed to map in vivo PPIs from mammalian cells at both the proteome scale and the targeted protein complex level.     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Sip1, a Novel RS Domain-Containing Protein Essential for Pre-mRNA Splicing

Previous studies have shown that protein-protein interactions among splicing factors may play an important role in pre-mRNA splicing. We report here identification and functional characterization of a new splicing factor, Sip1 (SC35-interacting protein 1). Sip1 was initially identified by virtue of its interaction with SC35, a splicing factor of the SR family. Sip1 interacts with not only several SR proteins but also with U1-70K and U2AF65, proteins associated with 5′ and 3′ splice sites, respectively. The predicted Sip1 sequence contains an arginine-serine-rich (RS) domain but does not have any known RNA-binding motifs, indicating that it is not a member of the SR family. Sip1 also contains a region with weak sequence similarity to the Drosophila splicing regulator suppressor of white apricot (SWAP). An essential role for Sip1 in pre-mRNA splicing was suggested by the observation that anti-Sip1 antibodies depleted splicing activity from HeLa nuclear extract. Purified recombinant Sip1 protein, but not other RS domain-containing proteins such as SC35, ASF/SF2, and U2AF65, restored the splicing activity of the Sip1-immunodepleted extract. Addition of U2AF65 protein further enhanced the splicing reconstitution by the Sip1 protein. Deficiency in the formation of both A and B splicing complexes in the Sip1-depleted nuclear extract indicates an important role of Sip1 in spliceosome assembly. Together, these results demonstrate that Sip1 is a novel RS domain-containing protein required for pre-mRNA splicing and that the functional role of Sip1 in splicing is distinct from those of known RS domain-containing splicing factors.Pre-mRNA splicing takes place in spliceosomes, the large RNA-protein complexes containing pre-mRNA, U1, U2, U4/6, and U5 small nuclear ribonucleoprotein particles (snRNPs), and a large number of accessory protein factors (for reviews, see references 21, 22, 37, 44, and 48). It is increasingly clear that the protein factors are important for pre-mRNA splicing and that studies of these factors are essential for further understanding of molecular mechanisms of pre-mRNA splicing.Most mammalian splicing factors have been identified by biochemical fractionation and purification (3, 15, 19, 31–36, 45, 69–71, 73), by using antibodies recognizing splicing factors (8, 9, 16, 17, 61, 66, 67, 74), and by sequence homology (25, 52, 74).Splicing factors containing arginine-serine-rich (RS) domains have emerged as important players in pre-mRNA splicing. These include members of the SR family, both subunits of U2 auxiliary factor (U2AF), and the U1 snRNP protein U1-70K (for reviews, see references 18, 41, and 59). Drosophila alternative splicing regulators transformer (Tra), transformer 2 (Tra2), and suppressor of white apricot (SWAP) also contain RS domains (20, 40, 42). RS domains in these proteins play important roles in pre-mRNA splicing (7, 71, 75), in nuclear localization of these splicing proteins (23, 40), and in protein-RNA interactions (56, 60, 64). Previous studies by us and others have demonstrated that one mechanism whereby SR proteins function in splicing is to mediate specific protein-protein interactions among spliceosomal components and between general splicing factors and alternative splicing regulators (1, 1a, 6, 10, 27, 63, 74, 77). Such protein-protein interactions may play critical roles in splice site recognition and association (for reviews, see references 4, 18, 37, 41, 47 and 59). Specific interactions among the splicing factors also suggest that it is possible to identify new splicing factors by their interactions with known splicing factors.Here we report identification of a new splicing factor, Sip1, by its interaction with the essential splicing factor SC35. The predicted Sip1 protein sequence contains an RS domain and a region with sequence similarity to the Drosophila splicing regulator, SWAP. We have expressed and purified recombinant Sip1 protein and raised polyclonal antibodies against the recombinant Sip1 protein. The anti-Sip1 antibodies specifically recognize a protein migrating at a molecular mass of approximately 210 kDa in HeLa nuclear extract. The anti-Sip1 antibodies sufficiently deplete Sip1 protein from the nuclear extract, and the Sip1-depleted extract is inactive in pre-mRNA splicing. Addition of recombinant Sip1 protein can partially restore splicing activity to the Sip1-depleted nuclear extract, indicating an essential role of Sip1 in pre-mRNA splicing. Other RS domain-containing proteins, including SC35, ASF/SF2, and U2AF65, cannot substitute for Sip1 in reconstituting splicing activity of the Sip1-depleted nuclear extract. However, addition of U2AF65 further increases splicing activity of Sip1-reconstituted nuclear extract, suggesting that there may be a functional interaction between Sip1 and U2AF65 in nuclear extract.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Combinatorial Approach for Large-scale Identification of Linked Peptides from Tandem Mass Spectrometry Spectra

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein–protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides.The study of protein–protein interactions is crucial to understanding how cellular systems function because proteins act in concert through a highly organized set of interactions. Most cellular processes are carried out by large macromolecular assemblies and regulated through complex cascades of transient protein–protein interactions (1). In the past several years numerous high-throughput studies have pioneered the systematic characterization of protein–protein interactions in model organisms (2–4). Such studies mainly utilize two techniques: the yeast two-hybrid system, which aims at identifying binary interactions (5), and affinity purification combined with tandem mass spectrometry analysis for the identification of multi-protein assemblies (6–8). Together these led to a rapid expansion of known protein–protein interactions in human and other model organisms. Patche and Aloy recently estimated that there are more than one million interactions catalogued to date (9).But despite rapid progress, most current techniques allow one to determine only whether proteins interact, which is only the first step toward understanding how proteins interact. A more complete picture comes from characterizing the three-dimensional structures of protein complexes, which provide mechanistic insights that govern how interactions occur and the high specificity observed inside the cell. Traditionally the gold-standard methods used to solve protein structures are x-ray crystallography and NMR, and there have been several efforts similar to structural genomics (10) aiming to comprehensively solve the structures of protein complexes (11, 12). Although there has been accelerated growth of structures for protein monomers in the Protein Data Bank in recent years (11), the growth of structures for protein complexes has remained relatively small (9). Many factors, including their large size, transient nature, and dynamics of interactions, have prevented many complexes from being solved via traditional approaches in structural biology. Thus, the development of complementary analytical techniques with which to probe the structure of large protein complexes continues to evolve (13–18).Recent developments have advanced the analysis of protein structures and interaction by combining cross-linking and tandem mass spectrometry (17, 19–24). The basic idea behind this technique is to capture and identify pairs of amino acid residues that are spatially close to each other. When these linked pairs of residues are from the same protein (intraprotein cross-links), they provide distance constraints that help one infer the possible conformations of protein structures. Conversely, when pairs of residues come from different proteins (interprotein cross-links), they provide information about how proteins interact with one another. Although cross-linking strategies date back almost a decade (25, 26), difficulty in analyzing the complex MS/MS spectrum generated from linked peptides made this approach challenging, and therefore it was not widely used. With recent advances in mass spectrometry instrumentation, there has been renewed interest in employing this strategy to determine protein structures and identify protein–protein interactions. However, most studies thus far have been focused on purified protein complexes. With today''s mass spectrometers being capable of analyzing tens of thousands of spectra in a single experiment, it is now potentially feasible to extend this approach to the analysis of complex biological samples. Researchers have tried to realize this goal using both experimental and computational approaches. Indeed, a plethora of chemical cross-linking reagents are now available for stabilizing these complexes, and some are designed to allow for easier peptide identification when employed in concert with MS analysis (20, 27, 28). There have also been several recent efforts to develop computational methods for the automatic identification of linked peptides from MS/MS spectra (29–36). However, because of the lack of large annotated training data, most approaches to date either borrow fragmentation models learned from unlinked, linear peptides or learn the fragmentation statistics from training data of limited size (30, 37), which might not generalize well across different samples. In some cases it is possible to generate relatively large training data, but it is often very labor intensive and involves hundreds of separate LC-MS/MS runs (36). Here, employing disulfide-bridged peptides as an example, we propose a novel method that uses a combinatorial peptide library to (a) efficiently generate a large mass spectral reference dataset for linked peptides and (b) use these data to automatically train our new algorithm, MXDB, which can efficiently and accurately identify linked peptides from MS/MS spectra.     

Identification of Tumor-associated Autoantigens for the Diagnosis of Colorectal Cancer in Serum Using High Density Protein Microarrays

There is a mounting evidence of the existence of autoantibodies associated to cancer progression. Antibodies are the target of choice for serum screening because of their stability and suitability for sensitive immunoassays. By using commercial protein microarrays containing 8000 human proteins, we examined 20 sera from colorectal cancer (CRC) patients and healthy subjects to identify autoantibody patterns and associated antigens. Forty-three proteins were differentially recognized by tumoral and reference sera (p value <0.04) in the protein microarrays. Five immunoreactive antigens, PIM1, MAPKAPK3, STK4, SRC, and FGFR4, showed the highest prevalence in cancer samples, whereas ACVR2B was more abundant in normal sera. Three of them, PIM1, MAPKAPK3, and ACVR2B, were used for further validation. A significant increase in the expression level of these antigens on CRC cell lines and colonic mucosa was confirmed by immunoblotting and immunohistochemistry on tissue microarrays. A diagnostic ELISA based on the combination of MAPKAPK3 and ACVR2B proteins yielded specificity and sensitivity values of 73.9 and 83.3% (area under the curve, 0.85), respectively, for CRC discrimination after using an independent sample set containing 94 sera representative of different stages of progression and control subjects. In summary, these studies confirmed the presence of specific autoantibodies for CRC and revealed new individual markers of disease (PIM1, MAPKAPK3, and ACVR2B) with the potential to diagnose CRC with higher specificity and sensitivity than previously reported serum biomarkers.Colorectal cancer (CRC)¹ is the second most prevalent cancer in the western world. The development of this disease takes decades and involves multiple genetic events. CRC remains a major cause of mortality in developed countries because most of the patients are diagnosed at advanced stages because of the reluctance to use highly invasive diagnostic tools like colonoscopy. Actually only a few proteins have been described as biomarkers in CRC (carcinoembryonic antigen (CEA), CA19.9, and CA125 (1–3)), although none of them is recommended for clinical screening (4). Proteomics analysis is actively used for the identification of new biomarkers. In previous studies, the use of two-dimensional DIGE and antibody microarrays allowed the identification of differentially expressed proteins in CRC tissue, including isoforms and post-translational modifications responsible for modifications in signaling pathways (5–8). Both approaches resulted in the identification of a collection of potential tumoral tissue biomarkers that is currently being investigated.However, the implementation of simpler, non-invasive methods for the early detection of CRC should be based on the identification of proteins or antibodies in serum or plasma (9–13). There is ample evidence of the existence of an immune response to cancer in humans as demonstrated by the presence of autoantibodies in cancer sera. Self-proteins (autoantigens) altered before or during tumor formation can elicit an immune response (13–19). These tumor-specific autoantibodies can be detected at early cancer stages and prior to cancer diagnosis revealing a great potential as biomarkers (14, 15, 20). Tumor proteins can be affected by specific point mutations, misfolding, overexpression, aberrant glycosylation, truncation, or aberrant degradation (e.g. p53, HER2, NY-ESO1, or MUC1 (16, 21–25)). In fact, a number of tumor-associated autoantigens (TAAs) were identified previously in different studies involving autoantibody screening in CRC (26–28).Several approaches have been used to identify TAAs in cancer, including natural protein arrays prepared with fractions obtained from two-dimensional LC separations of tumoral samples (29, 30) or protein extracts from cancer cells or tissue (9, 31) probed by Western blot with patient sera, cancer tissue peptide libraries expressed as cDNA expression libraries for serological screening (serological analysis of recombinant cDNA expression libraries (SEREX)) (22, 32), or peptides expressed on the surface of phages in combination with microarrays (17, 18, 33, 34). However, these approaches suffer from several drawbacks. In some cases TAAs have to be isolated and identified from the reactive protein lysate by LC-MS techniques, or in the phage display approach, the reactive TAA could be a mimotope without a corresponding linear amino acid sequence. Moreover, cDNA libraries might not be representative of the protein expression levels in tumors as there is a poor correspondence between mRNA and protein levels.Protein arrays provide a novel platform for the identification of both autoantibodies and their respective TAAs for diagnostic purposes in cancer serum patients. They present some advantages. Proteins printed on the microarray are known “a priori,” avoiding the need for later identifications and the discovery of mimotopes. There is no bias in protein selection as the proteins are printed at a similar concentration. This should result in a higher sensitivity for biomarker identification (13, 35, 36).In this study, we used commercially available high density protein microarrays for the identification of autoantibody signatures and tumor-associated antigens in colorectal cancer. We screened 20 CRC patient and control sera with protein microarrays containing 8000 human proteins to identify the CRC-associated autoantibody repertoire and the corresponding TAAs. Autoantibody profiles that discriminated the different types of CRC metastasis were identified. Moreover a set of TAAs showing increased or decreased expression in cancer cell lines and paired tumoral tissues was found. Finally an ELISA was set up to test the ability of the most immunoreactive proteins to detect colorectal adenocarcinoma. On the basis of the antibody response, combinations of three antigens, PIM1, MAPKAPK3, and ACVR2B, showed a great potential for diagnosis.     

Heparan Sulfate Proteoglycans Are Receptors for the Cell-surface Trafficking and Biological Activity of Transglutaminase-2

Transglutaminase type 2 (TG2) is both a protein cross-linking enzyme and a cell adhesion molecule with an elusive unconventional secretion pathway. In normal conditions, TG2-mediated modification of the extracellular matrix modulates cell motility, proliferation and tissue repair, but under continuous cell insult, higher expression and elevated extracellular trafficking of TG2 contribute to the pathogenesis of tissue scarring. In search of TG2 ligands that could contribute to its regulation, we characterized the affinity of TG2 for heparan sulfate (HS) and heparin, an analogue of the chains of HS proteoglycans (HSPGs). By using heparin/HS solid-binding assays and surface plasmon resonance we showed that purified TG2 has high affinity for heparin/HS, comparable to that for fibronectin, and that cell-surface TG2 interacts with heparin/HS. We demonstrated that cell-surface TG2 directly associates with the HS chains of syndecan-4 without the mediation of fibronectin, which has affinity for both syndecan-4 and TG2. Functional inhibition of the cell-surface HS chains of wild-type and syndecan-4-null fibroblasts revealed that the extracellular cross-linking activity of TG2 depends on the HS of HSPG and that syndecan-4 plays a major but not exclusive role. We found that heparin binding did not alter TG2 activity per se. Conversely, fibroblasts deprived of syndecan-4 were unable to effectively externalize TG2, resulting in its cytosolic accumulation. We propose that the membrane trafficking of TG2, and hence its extracellular activity, is linked to TG2 binding to cell-surface HSPG.Transglutaminase type 2 (TG2,² EC 2.3.2.13) is the most widespread member of a large family of enzymes that catalyze the Ca²⁺-dependent post-translational modification of proteins leading to intra- or intermolecular Nϵ(γ-glutamyl)lysine bonds (1, 2). Unlike other family members, TG2 is uniquely exported through a yet to be elucidated non-conventional pathway. Once secreted, TG2 finds in the extracellular compartment the ideal conditions of high Ca²⁺ and low GTP concentration for the activation of its intrinsic transamidation activity (cross-linking) (2, 3). Intracellularly, GTP binding suppresses the Ca²⁺-dependent cross-linking activity and determines the additional GTPase activity of TG2 (4, 5), which is responsible for signal transduction (6). Once externalized, TG2 remains tightly bound to the cell surface and to the extracellular matrix (ECM) (7, 8), and it is rarely found free in the conditioned medium, unless overexpressed by cell transfection (9).Extracellular TG2 activity is involved in the cross-linking of the ECM, conferring resistance to matrix metalloproteinase and promoting cell-matrix interactions via cross-linking of fibronectin (FN) and collagen (1, 7, 11, 12). TG2 has an additional non-enzymatic role in the matrix as an integrin-β₁ co-receptor (8) by supporting RGD-independent cell adhesion to FN (8, 13, 14).Extracellular cross-linking and TG2-mediated adhesion facilitate the repair process in many tissue compartments (1, 2, 15, 16). On the other hand, uncontrolled cross-linking as a consequence of chronic cell insult and secretion of TG2 has been implicated in a number of pathological conditions, including kidney, liver, and pulmonary fibrosis (17–20).Understanding how TG2 is exported and targeted to the cell surface is critical for limiting its cellular secretion and extracellular action. Although a key trigger for TG2 export is cell stress (2, 21, 22), TG2 is not unspecifically released, because extracellular trafficking occurs in the absence of leakage of intracellular components and cells remain viable (23). We know that TG2 requires the tertiary structure of its active site region to be secreted (9); moreover, TG2 is acetylated on the N terminus (24), a process reported to affect membrane targeting of non-conventional secreted proteins (25). Two main binding partners for TG2, FN and integrin-β1, have both been attributed a possible role in the transport of TG2 to the cell surface (8, 26). FN was shown to co-localize with TG2 once released (26), and integrin-β1 to co-associate with TG2 in cells induced to differentiate (8).TG2 has also long been known to have some affinity for heparin (27, 28), a highly sulfated analogue of heparan sulfate (HS) glycosaminoglycan chains, which are abundant constituents of the cell surface/ECM. HS chains are linear polysaccharides consisting of alternating N-acetylated or N-sulfated glucosamine units (GlcNAc or GlcNS), and uronic acids (glucuronic acid GlcA or iduronic acid IdoA residues) (29), which only exist covalently bound to the core protein of cell-surface proteoglycans (syndecans and glypicans) and secreted proteoglycans (29). Heparin binding is a property common to many ECM proteins (29), but the level of affinity has never been established for TG2, which makes it difficult to estimate the real biological significance of this interaction. Heparan sulfate proteoglycans (HSPG) bind ECM ligands through the HS chains, influencing their biological activity, trafficking, and secretion. Among the HSPG subfamilies, the syndecans act as co-receptors for both ECM components and soluble ligands (30), and syndecan-4 has overlapping roles with extracellular TG2 in wound healing and fibrosis (31, 32). In this study, we show that TG2 has a surprisingly high affinity for heparin and HS, raising the hypothesis that HSPG are involved in its biological activity. We demonstrate that HSPGs are essential for the transamidating activity of TG2 at the cell surface and that syndecan-4 acts as a receptor for TG2, which is involved in the trafficking and cell-surface localization, and thus activity of TG2.     

Development of a Novel Cross-linking Strategy for Fast and Accurate Identification of Cross-linked Peptides of Protein Complexes

Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS³ analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS³) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes.Proteins form stable and dynamic multisubunit complexes under different physiological conditions to maintain cell viability and normal cell homeostasis. Detailed knowledge of protein interactions and protein complex structures is fundamental to understanding how individual proteins function within a complex and how the complex functions as a whole. However, structural elucidation of large multisubunit protein complexes has been difficult because of a lack of technologies that can effectively handle their dynamic and heterogeneous nature. Traditional methods such as nuclear magnetic resonance (NMR) analysis and x-ray crystallography can yield detailed information on protein structures; however, NMR spectroscopy requires large quantities of pure protein in a specific solvent, whereas x-ray crystallography is often limited by the crystallization process.In recent years, chemical cross-linking coupled with mass spectrometry (MS) has become a powerful method for studying protein interactions (1–3). Chemical cross-linking stabilizes protein interactions through the formation of covalent bonds and allows the detection of stable, weak, and/or transient protein-protein interactions in native cells or tissues (4–9). In addition to capturing protein interacting partners, many studies have shown that chemical cross-linking can yield low resolution structural information about the constraints within a molecule (2, 3, 10) or protein complex (11–13). The application of chemical cross-linking, enzymatic digestion, and subsequent mass spectrometric and computational analyses for the elucidation of three-dimensional protein structures offers distinct advantages over traditional methods because of its speed, sensitivity, and versatility. Identification of cross-linked peptides provides distance constraints that aid in constructing the structural topology of proteins and/or protein complexes. Although this approach has been successful, effective detection and accurate identification of cross-linked peptides as well as unambiguous assignment of cross-linked sites remain extremely challenging due to their low abundance and complicated fragmentation behavior in MS analysis (2, 3, 10, 14). Therefore, new reagents and methods are urgently needed to allow unambiguous identification of cross-linked products and to improve the speed and accuracy of data analysis to facilitate its application in structural elucidation of large protein complexes.A number of approaches have been developed to facilitate MS detection of low abundance cross-linked peptides from complex mixtures. These include selective enrichment using affinity purification with biotinylated cross-linkers (15–17) and click chemistry with alkyne-tagged (18) or azide-tagged (19, 20) cross-linkers. In addition, Staudinger ligation has recently been shown to be effective for selective enrichment of azide-tagged cross-linked peptides (21). Apart from enrichment, detection of cross-linked peptides can be achieved by isotope-labeled (22–24), fluorescently labeled (25), and mass tag-labeled cross-linking reagents (16, 26). These methods can identify cross-linked peptides with MS analysis, but interpretation of the data generated from interlinked peptides (two peptides connected with the cross-link) by automated database searching remains difficult. Several bioinformatics tools have thus been developed to interpret MS/MS data and determine interlinked peptide sequences from complex mixtures (12, 14, 27–32). Although promising, further developments are still needed to make such data analyses as robust and reliable as analyzing MS/MS data of single peptide sequences using existing database searching tools (e.g. Protein Prospector, Mascot, or SEQUEST).Various types of cleavable cross-linkers with distinct chemical properties have been developed to facilitate MS identification and characterization of cross-linked peptides. These include UV photocleavable (33), chemical cleavable (19), isotopically coded cleavable (24), and MS-cleavable reagents (16, 26, 34–38). MS-cleavable cross-linkers have received considerable attention because the resulting cross-linked products can be identified based on their characteristic fragmentation behavior observed during MS analysis. Gas-phase cleavage sites result in the detection of a “reporter” ion (26), single peptide chain fragment ions (35–38), or both reporter and fragment ions (16, 34). In each case, further structural characterization of the peptide product ions generated during the cleavage reaction can be accomplished by subsequent MSⁿ1 analysis. Among these linkers, the “fixed charge” sulfonium ion-containing cross-linker developed by Lu et al. (37) appears to be the most attractive as it allows specific and selective fragmentation of cross-linked peptides regardless of their charge and amino acid composition based on their studies with model peptides.Despite the availability of multiple types of cleavable cross-linkers, most of the applications have been limited to the study of model peptides and single proteins. Additionally, complicated synthesis and fragmentation patterns have impeded most of the known MS-cleavable cross-linkers from wide adaptation by the community. Here we describe the design and characterization of a novel and simple MS-cleavable cross-linker, DSSO, and its application to model peptides and proteins and the yeast 20 S proteasome complex. In combination with new software developed for data integration, we were able to identify DSSO-cross-linked peptides from complex peptide mixtures with speed and accuracy. Given its effectiveness and simplicity, we anticipate a broader application of this MS-cleavable cross-linker in the study of structural topology of other protein complexes using cross-linking and mass spectrometry.     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Dithiothreitol (DTT) Acts as a Specific,UV-inducible Cross-linker in Elucidation of Protein–RNA Interactions*

Protein–RNA cross-linking by UV irradiation at 254 nm wavelength has been established as an unbiased method to identify proteins in direct contact with RNA, and has been successfully applied to investigate the spatial arrangement of protein and RNA in large macromolecular assemblies, e.g. ribonucleoprotein-complex particles (RNPs). The mass spectrometric analysis of such peptide-RNA cross-links provides high resolution structural data to the point of mapping protein–RNA interactions to specific peptides or even amino acids. However, the approach suffers from the low yield of cross-linking products, which can be addressed by improving enrichment and analysis methods. In the present article, we introduce dithiothreitol (DTT) as a potent protein–RNA cross-linker. In order to evaluate the efficiency and specificity of DTT, we used two systems, a small synthetic peptide from smB protein incubated with U1 snRNA oligonucleotide and native ribonucleoprotein complexes from S. cerevisiae. Our results unambiguously show that DTT covalently participates in cysteine-uracil crosslinks, which is observable as a mass increment of 151.9966 Da (C₄H₈S₂O₂) upon mass spectrometric analysis. DTT presents advantages for cross-linking of cysteine containing regions of proteins. This is evidenced by comparison to experiments where (tris(2-carboxyethyl)phosphine) is used as reducing agent, and significantly less cross-links encompassing cysteine residues are found. We further propose insertion of DTT between the cysteine and uracil reactive sites as the most probable structure of the cross-linking products.Cross-linking of biomolecules combined with mass spectrometry (MS) has emerged as a powerful tool to characterize not only the tertiary and quaternary arrangements of individual biomolecules, but especially their interaction sites in biologically active complexes. By MS-based identification of the cross-linked parts or even the exact cross-linking sites of the respective biomolecules, proximity information can be derived. This has proven highly useful for computational approaches to problems such as docking or the arrangement of subunits (1–3).In principle, cross-linking can be achieved in two ways: (1) By using a chemical cross-linker that connects reactive groups of the respective biomolecules within a certain distance range, the range depending on the reagent used. (2) By generating a so-called zero-length cross-link that connects reactive groups of biomolecules that are already directly adjacent to one another. The latter is usually achieved by (UV) light-induced cross-linking, with or without the addition of compounds that induce the generation of radicals on reactive groups of the cross-linkable components or in close vicinity to them.Cross-linking in combination with MS analysis is nowadays frequently used in protein-protein interaction studies (4–7) but can also be applied to protein-nucleic acid complexes. Indeed much attention is currently paid to their MS-based analysis owing to the crucial cellular function of many such complexes. A large variety of studies over decades have examined chemical cross-linking between proteins and DNA, using reagents such as the genotoxic diepoxybutane, endogenous aldehydes, transition metals, nitrogen mustard, and platinum compounds, alkynitrosoureas, and formaldehyde (8). In addition, UV irradiation has been used to establish cross-links between proteins and protein-bound single-stranded DNA (ssDNA), which can then be identified by mass spectrometry (9, 10). UV cross-linking makes use of the natural sensitivity of nucleobases to UV light (11, 12). The site of cross-linking can then be determined by mass spectrometric analysis (including gas phase fragmentation of the corresponding peptide-nucleic acid conjugates) and database searching. To enhance the low yield of protein-DNA cross-linking, derivatives with higher UV reactivity, such as halonucleotides, can be employed (13–15).UV-induced cross-linking is more frequently used to monitor protein–RNA interactions. RNA is mainly present in its single-stranded form, and adopts a variety of tertiary structures in which the bases of the nucleotides are in close contact with amino acid residues of the proteins that are bound to the RNA. Several studies have used this technique to identify globally the proteins that directly interact with e.g. poly(A) mRNA in yeast and human systems, and have yielded insight into the large variety of RNA-binding proteins that exist within the cell (16–21). More detailed approaches apply UV-induced protein–RNA cross-linking in a similar manner, but extend the MS analysis toward the identification of the cross-linked amino acids together with the corresponding nucleotide moieties, allowing exact definition of the RNA-binding regions in the cross-linked proteins (22–24). To improve the yield of cross-linking, more reactive nucleoside derivatives (4-thiouridine and 6-thioguanosine) have been incorporated into RNA in growing cells. The cross-linking reaction of these derivatives with amino acids is not entirely additive, however, but is accompanied by the loss of H₂S ((22), U.Z. and H.U, unpublished results). Other cross-linking reactions between proteins and RNA have made use of nucleotide derivatives that contain a cross-linkable function at the 2′ hydroxyl group or the phosphate moiety (25–27), but have not been characterized by MS yet.Additional cross-linking agents for the analysis of protein–RNA interactions have been exploited, but have not yet found their way into modern MS-based proteome analyses. For instance, methylene blue has been described as a light-inducible cross-linker, in particular for mapping interactions of proteins with dsRNA (28). Similarly, protein–RNA interaction studies in ribosomal subunits have made use of diepoxybutane, or nitrogen mustard (29–31). The same holds true for the use of 2-iminothiolane (“Traut''s reagent”), which is a protein–RNA cross-linking reagent that combines chemical and UV-inducible features and has been extensively applied to the analysis of protein–RNA contacts in ribosomal subunits (33, 32). Here, we introduce dithiothreitol (DTT)¹ as a potent UV-inducible cross-linking reagent for the analysis of protein–RNA linkages following UV irradiation. By exhaustive mass-spectrometric analyses we found that upon UV light exposure DTT forms a covalent linkage between cysteine residues within proteins and uracil bases of RNA in close proximity. We applied this to protein–RNA complexes isolated from yeast cells and compared the protein–RNA cross-linking patterns that were obtained in the presence and absence of DTT. We found that the cross-linking reaction is surprisingly efficient and specific.     

In Vivo Identification of Nuclear Factors Interacting with the Conserved Elements of Box C/D Small Nucleolar RNAs

The U16 small nucleolar RNA (snoRNA) is encoded by the third intron of the L1 (L4, according to the novel nomenclature) ribosomal protein gene of Xenopus laevis and originates from processing of the pre-mRNA in which it resides. The U16 snoRNA belongs to the box C/D snoRNA family, whose members are known to assemble in ribonucleoprotein particles (snoRNPs) containing the protein fibrillarin. We have utilized U16 snoRNA in order to characterize the factors that interact with the conserved elements common to the other members of the box C/D class. In this study, we have analyzed the in vivo assembly of U16 snoRNP particles in X. laevis oocytes and identified the proteins which interact with the RNA by label transfer after UV cross-linking. This analysis revealed two proteins, of 40- and 68-kDa apparent molecular size, which require intact boxes C and D together with the conserved 5′,3′-terminal stem for binding. Immunoprecipitation experiments showed that the p40 protein corresponds to fibrillarin, indicating that this protein is intimately associated with the RNA. We propose that fibrillarin and p68 represent the RNA-binding factors common to box C/D snoRNPs and that both proteins are essential for the assembly of snoRNP particles and the stabilization of the snoRNA.One of the most interesting recent findings related to ribosome biogenesis has been the identification of a large number of small RNAs localized in the nucleolus (snoRNAs). So far, more than 60 snoRNAs have been identified in vertebrates (17), and more than 30 have been identified in yeast (2). The total number of snoRNAs is not known, but it is likely to be close to 200 (33, 38). These snoRNAs, with the exception of the mitochondrial RNA processing (MRP) species (38), can be grouped into two major families on the basis of conserved structural and sequence elements. The first group includes molecules referred to as box C/D snoRNAs, whereas the second one comprises the species belonging to the box H/ACA family (2, 15).The two families differ in many aspects. The box C/D snoRNAs are functionally heterogeneous. Most of them function as antisense RNAs in site-specific ribose methylation of the pre-rRNA (1, 10, 17, 26); a minority have been shown to play a direct role in pre-rRNA processing in both yeast and metazoan cells (11, 21). The box C/D snoRNAs play their role by means of unusually long (up to 21 contiguous nucleotides) regions of complementarity to highly conserved sequences of 28S and 18S rRNAs (1). In contrast, several members of the H/ACA RNA family have been shown to direct site-specific isomerization of uridines into pseudouridines and to display shorter regions of complementarity to rRNA (14, 24). Mutational analysis suggests that H/ACA snoRNAs can also play a role as antisense RNAs by base pairing with complementary regions on rRNA (15, 24).Another difference between the two families can be seen by comparison of secondary structures. A Y-shaped motif, where a 5′,3′-terminal stem adjoins the C and D conserved elements, has been proposed for many box C/D snoRNAs (16, 26, 40, 42), whereas box H/ACA snoRNAs have been proposed to fold into two conserved hairpin structures connected by a single-stranded hinge region, followed by a short 3′ tail (15).Despite these differences, analogies have been found in the roles played by the conserved box elements. Mutational analysis and competition experiments indicated that C/D and H/ACA boxes are required both for processing and stable accumulation of the mature snoRNA, suggesting that they represent binding sites for specific trans-acting factors (2, 3, 8, 15, 16, 28, 36, 41).All snoRNAs are associated with proteins to form specific ribonucleoparticles (snoRNPs). The study of these particles began only recently, and so far, very few aspects of their structure and biosynthesis have been clarified. The only detailed analysis performed was on the mammalian U3 (19) and the yeast snR30 (20) snoRNPs. Of the identified components, a few appear to be more general factors: fibrillarin, which was shown to be associated with C/D snoRNPs (3, 4, 8, 13, 28, 31, 39), and the nucleolar protein GAR1, which was found associated with H/ACA snoRNAs in yeast (20). Just as the study of small nuclear RNP (snRNP) particles was crucial to the understanding of the splicing process, a detailed structural and functional analysis of snoRNP particles will be essential to elucidate the complex process of ribosome biosynthesis.In this study, we have analyzed the snoRNP assembly of wild-type and mutant U16 snoRNAs by following the kinetics of complex formation in the in vivo system of the Xenopus laevis oocyte. By a UV cross-linking technique, we have identified two proteins, of 40- and 68-kDa apparent molecular mass, which require intact boxes C and D together with the terminal stem for their binding. The 40-kDa species is specifically recognized by fibrillarin antibodies, indicating that this protein is intimately associated with the RNA.     

Structural Characterization by Cross-linking Reveals the Detailed Architecture of a Coatomer-related Heptameric Module from the Nuclear Pore Complex

Most cellular processes are orchestrated by macromolecular complexes. However, structural elucidation of these endogenous complexes can be challenging because they frequently contain large numbers of proteins, are compositionally and morphologically heterogeneous, can be dynamic, and are often of low abundance in the cell. Here, we present a strategy for the structural characterization of such complexes that has at its center chemical cross-linking with mass spectrometric readout. In this strategy, we isolate the endogenous complexes using a highly optimized sample preparation protocol and generate a comprehensive, high-quality cross-linking dataset using two complementary cross-linking reagents. We then determine the structure of the complex using a refined integrative method that combines the cross-linking data with information generated from other sources, including electron microscopy, X-ray crystallography, and comparative protein structure modeling. We applied this integrative strategy to determine the structure of the native Nup84 complex, a stable hetero-heptameric assembly (∼600 kDa), 16 copies of which form the outer rings of the 50-MDa nuclear pore complex (NPC) in budding yeast. The unprecedented detail of the Nup84 complex structure reveals previously unseen features in its pentameric structural hub and provides information on the conformational flexibility of the assembly. These additional details further support and augment the protocoatomer hypothesis, which proposes an evolutionary relationship between vesicle coating complexes and the NPC, and indicates a conserved mechanism by which the NPC is anchored in the nuclear envelope.Macromolecular complexes are the building blocks that drive virtually all cellular and biological processes. In each eukaryotic cell, there exist many hundreds of these protein complexes (1–3), the majority of which are still poorly understood in terms of their structures, dynamics, and functions. The classical structure determination approaches of nuclear magnetic resonance, X-ray crystallography, and electron microscopy (EM)¹ remain challenged in attempts to determine the high-resolution structures of large, dynamic, and flexible complexes in a living cell (4). Thus, additional robust and rapid methods are needed, ideally working in concert with these classical approaches, to allow the greatest structural and functional detail in characterizations of macromolecular assemblies.Integrative modeling approaches help address this need, providing powerful tools for determining the structures of endogenous protein complexes (5, 6) by relying on the collection of an extensive experimental dataset, preferably coming from diverse sources (both classical and new) and different levels of resolution. These data are translated into spatial restraints that are used to calculate an ensemble of structures by satisfying the restraints, which in turn can be analyzed and assessed to determine precision and estimate accuracy (5, 7). A major advantage of this approach is that it readily integrates structural data from different methods and a wide range of resolutions, spanning from a few angstroms to dozens of nanometers. This strategy has been successfully applied to a number of protein complexes (8–16). However, it has proven difficult and time-consuming to generate a sufficient number of accurate spatial restraints to enable high-resolution structural characterization; thus, the determination of spatial restraints currently presents a major bottleneck for widespread application of this integrative approach. An important step forward is therefore the development of technologies for collecting high-resolution and information-rich spatial restraints in a rapid and efficient manner, ideally from endogenous complexes isolated directly from living cells.Chemical cross-linking with mass spectrometric readout (CX-MS) (17, 18) has recently emerged as an enabling approach for obtaining residue-specific restraints on the structures of proteins and protein complexes (19–25). In a CX-MS experiment, the purified protein complex is chemically conjugated by a functional group-specific cross-linker, and this is followed by proteolytic digestion and analysis of the resulting peptide mixture by mass spectrometry (MS). However, because of the complexity of the peptide mixtures and low abundance of most of the informative cross-linked species, comprehensive detection of these cross-linked peptides has proven challenging. This challenge increases substantially in studies of endogenous complexes of modest to low abundance, which encompass the great majority of assemblies in any cell (26, 27). In addition, because most cross-linkers used for CX-MS target primary amines, comprehensive detection of cross-links is further limited by the occurrence of lysine, which constitutes only ∼6% of protein sequences, although these lysine residues are generally present on protein surfaces. The use of cross-linkers with different chemistries and reactive groups, especially toward abundant residues, would increase the cross-linking coverage and could be of great help for downstream structural analysis (28).The nuclear pore complex (NPC) is one of the largest protein assemblies in the cell and is the sole mediator of macromolecular transport between the nucleus and the cytoplasm. The NPC is formed by multiple copies of ∼30 different proteins termed nucleoporins (Nups) that are assembled into discrete subcomplexes (8, 29). These building blocks are arranged into eight symmetrical units called spokes that are radially connected to form several concentric rings. The outer rings of the NPC are mainly formed by the Nup84 complex (a conserved complex, termed the Nup107–Nup160 complex in vertebrates). In budding yeast, the Nup84 complex is an essential, Y-shaped assembly of ∼600 kDa that is formed by seven nucleoporins (Nup133, Nup120, Nup145c, Nup85, Nup84, Seh1, and Sec13 in Saccharomyces cerevisiae) (30). The Nup84 complex has been shown to have a common evolutionary origin with vesicle coating complexes (VCCs), such as COPII, COPI, and clathrin (31, 32), but the evolutionary relationships between these VCCs have not been fully delineated. The Nup84 complex has been extensively characterized; several of its components have been analyzed via X-ray crystallography (33, 34), its overall shape has been defined by means of negative-stain electron microscopy (14, 30, 35, 36), and recently efforts were made to define the protein contacts in the Nup84 complex via CX-MS in humans (35) and a thermophilic fungus (37). Finally, we recently used an integrative modeling approach combining domain mapping, negative-stain electron microscopy (38), and publicly available crystal structures to generate a medium-resolution map of the native Nup84 complex (14). However, despite all these efforts, the fine features of the complex, and in particular the intricate domain orientations and contacts within the complex''s hub, remain poorly described.To address these issues, we present here an optimized CX-MS strategy for robust and in-depth structural characterization of endogenous protein complexes. To test the strategy, we generated a comprehensive high-quality CX-MS dataset on the endogenous Nup84 complex using two complementary cross-linkers, disuccinimidyl suberate (DSS) and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC). Using the resulting cross-linking restraints together with other sources of information (including electron microscopy, X-ray crystallography, and comparative modeling), we computed a detailed structure of the endogenous Nup84 complex. In addition to providing the overall architecture of the yeast Nup84 complex, the resulting structure reveals the previously unknown architecture of its pentameric structural hub. Our results demonstrate that the present approach provides a robust framework for the standardized generation and use of CX-MS spatial restraints toward the structural characterization of endogenous protein complexes.