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.     

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.     

A Study into the Collision-induced Dissociation (CID) Behavior of Cross-Linked Peptides

Cross-linking/mass spectrometry resolves protein–protein interactions or protein folds by help of distance constraints. Cross-linkers with specific properties such as isotope-labeled or collision-induced dissociation (CID)-cleavable cross-linkers are in frequent use to simplify the identification of cross-linked peptides. Here, we analyzed the mass spectrometric behavior of 910 unique cross-linked peptides in high-resolution MS1 and MS2 from published data and validate the observation by a ninefold larger set from currently unpublished data to explore if detailed understanding of their fragmentation behavior would allow computational delivery of information that otherwise would be obtained via isotope labels or CID cleavage of cross-linkers. Isotope-labeled cross-linkers reveal cross-linked and linear fragments in fragmentation spectra. We show that fragment mass and charge alone provide this information, alleviating the need for isotope-labeling for this purpose. Isotope-labeled cross-linkers also indicate cross-linker-containing, albeit not specifically cross-linked, peptides in MS1. We observed that acquisition can be guided to better than twofold enrich cross-linked peptides with minimal losses based on peptide mass and charge alone. By help of CID-cleavable cross-linkers, individual spectra with only linear fragments can be recorded for each peptide in a cross-link. We show that cross-linked fragments of ordinary cross-linked peptides can be linearized computationally and that a simplified subspectrum can be extracted that is enriched in information on one of the two linked peptides. This allows identifying candidates for this peptide in a simplified database search as we propose in a search strategy here. We conclude that the specific behavior of cross-linked peptides in mass spectrometers can be exploited to relax the requirements on cross-linkers.Cross-linking/mass spectrometry extends the use of mass-spectrometry-based proteomics from identification (1, 2), quantification (3), and characterization of protein complexes (4) into resolving protein structures and protein–protein interactions (5–8). Chemical reagents (cross-linkers) covalently connect amino acid pairs that are within a cross-linker-specific distance range in the native three-dimensional structure of a protein or protein complex. A cross-linking/mass spectrometry experiment is typically conducted in four steps: (1) cross-linking of the target protein or complex, (2) protein digestion (usually with trypsin), (3) LC-MS analysis, and (4) database search. The digested peptide mixture consists of linear and cross-linked peptides, and the latter can be enriched by strong cation exchange (9) or size exclusion chromatography (10). Cross-linked peptides are of high value as they provide direct information on the structure and interactions of proteins.Cross-linked peptides fragment under collision-induced dissociation (CID) conditions primarily into b- and y-ions, as do their linear counterparts. An important difference regarding database searches between linear and cross-linked peptides stems from not knowing which peptides might be cross-linked. Therefore, one has to consider each single peptide and all pairwise combinations of peptides in the database. Having n peptides leads to (n2 + n)/2 possible pairwise combinations. This leads to two major challenges: With increasing size of the database, search time and the risk of identifying false positives increases. One way of circumventing these problems is to use MS2-cleavable cross-linkers (11, 12), at the cost of limited experimental design and choice of cross-linker.In a first database search approach (13), all pairwise combinations of peptides in a database were considered in a concatenated and linearized form. Thereby, all possible single bond fragments are considered in one of the two database entries per peptide pair, and the cross-link can be identified by a normal protein identification algorithm. Already, the second search approach split the peptides for the purpose of their identification (14). Linear fragments were used to retrieve candidate peptides from the database that are then matched based on the known mass of the cross-linked pair and scored as a pair against the spectrum. Isotope-labeled cross-linkers were used to sort the linear and cross-linked fragments apart. Many other search tools and approaches have been developed since (10, 15–19); see (20) for a more detailed list, at least some of which follow the general idea of an open modification search (21–24).As a general concept for open modification search of cross-linked peptides, cross-linked peptides represent two peptides, each with an unknown modification given by the mass of the other peptide and the cross-linker. One identifies both peptides individually and then matches them based on knowing the mass of cross-linked pair (14, 22, 24). Alternatively, one peptide is identified first and, using that peptide and the cross-linker as a modification mass, the second peptide is identified from the database (21, 23). An important element of the open modification search approach is that it essentially converts the quadratic search space of the cross-linked peptides into a linear search space of modified peptides. Still, many peptides and many modification positions have to be considered, especially when working with large databases or when using highly reactive cross-linkers with limited amino acid selectivity (25).We hypothesize that detailed knowledge of the fragmentation behavior of cross-linked peptides might reveal ways to improve the identification of cross-linked peptides. Detailed analyses of the fragmentation behavior of linear peptides exist (26–28), and the analysis of the fragmentation behavior of cross-linked peptides has guided the design of scores (24, 29). Further, cross-link-specific ions have been observed from higher energy collision dissociation (HCD) data (30). Isotope-labeled cross-linkers are used to distinguish cross-linked from linear fragments, generally in low-resolution MS2 of cross-linked peptides (14).We compared the mass spectrometric behavior of cross-linked peptides to that of linear peptides, using 910 high-resolution fragment spectra matched to unique cross-linked peptides from multiple different public datasets at 5% peptide-spectrum match (PSM)¹ false discovery rate (FDR). In addition, we repeated all experiments with a larger sample set that contains 8,301 spectra—also including data from ongoing studies from our lab (Supplemental material S9-S12). This paper presents the mass spectrometric signature of cross-linked peptides that we identified in our analysis and the resulting heuristics that are incorporated into an integrated strategy for the analysis and identification of cross-linked peptides. We present computational strategies that indicate the possibility of alleviating the need for mass-spectrometrically restricted cross-linker choice.     

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.     

Dynamics of Ribosomal Protein S1 on a Bacterial Ribosome with Cross-Linking and Mass Spectrometry

Ribosomal protein S1 has been shown to be a significant effector of prokaryotic translation. The protein is in fact capable of efficiently initiating translation, regardless of the presence of a Shine-Dalgarno sequence in mRNA. Structural insights into this process have remained elusive, as S1 is recalcitrant to traditional techniques of structural analysis, such as x-ray crystallography. Through the application of protein cross-linking and high resolution mass spectrometry, we have detailed the ribosomal binding site of S1 and have observed evidence of its dynamics. Our results support a previous hypothesis that S1 acts as the mRNA catching arm of the prokaryotic ribosome. We also demonstrate that in solution the major domains of the 30S subunit are remarkably flexible, capable of moving 30–50Å with respect to one another.Initiation of translation is often the rate-limiting step of protein biosynthesis (1). In prokaryotes, this process is widely recognized to be directed by the Shine-Dalgarno (S.D.)¹ sequence of mRNA and its complementation with the 3′ end of 16S rRNA (2). However, binding of the S.D. sequence to the ribosome is not obligatory for initiation. Ribosomal protein S1, widely conserved in prokaryotes, (3) has been shown to efficiently initiate translation, regardless of the presence of an S.D. sequence (4, 5).S1 is a strikingly atyptical ribosomal protein, being both the largest (61 kDa) and the most acidic (pI 4.7) (6). The protein is composed of six homologous repeats each forming beta barrel domains (3) that in solution comprise a highly elongated structure spanning up to ca. 230 Å (7). This length is comparable to the diameter of the ribosome itself. In addition to these anomalous characteristics, S1 is also one of only two ribosomal proteins that has been attributed functional significance (6). Ribosomal protein S1, for instance, has no apparent role in the assembly of the ribosome, (2) yet is critical for translation in E. coli (8, 9). The functional significance of S1 is related to its most pronounced characteristic, the ability to simultaneously bind mRNA and the ribosome. Analysis of fragments produced by limited proteolysis and chemical cleavage of S1 has shown that an N-terminal fragment of S1 (residues 1–193) binds the ribosome (10) but not RNA (11). Likewise, a C-terminal fragment (res 172–557) binds RNA (12, 13) but not the ribosome (6, 10). By nature of this bi-functional structure, S1 enhances the E. coli ribosome''s affinity for RNA ∼5000 fold (14) and can directly mediate initiation of translation by binding the 5′ UTR of mRNA (4, 5). These observations have led to the hypothesis that S1 acts as a catching arm for the prokaryotic ribosome, working to bring mRNA to the proximity of the ribosome and thereby facilitate initiation (6).Unfortunately, structural analyses capturing how S1 is able to function in this manner remain elusive. A high-resolution crystal structure of ribosome bound S1, or even free S1, does not exist, because S1 is recalcitrant to crystallography (6). Preparation of ribosomes for x-ray crystallography actually involves the deliberate removal of ribosomal protein S1 as a means to improve the reproducibility of crystallization and the quality of the ribosome crystals formed (15–17). The structure and interactions of the protein have nevertheless intrigued structural biologists for decades. However, studies completed to date have failed to convincingly demonstrate the interaction between S1 and the rest of the 30S subunit, because they were incapable of localizing the individual S1 domains (16, 18–20).We have studied the binding of S1 to the 30S subunit by combining cross-linking with mass spectrometry. Chemical cross-linking has long been appreciated as a technique to probe protein-protein interactions (21, 22). With the advent of modern mass spectrometers, it can be very effectively employed to confidently identify the exact residues involved in linkages (23–28). In most cross-linking analyses, protein residues are targeted for covalent modification with a molecule that contains two reactive groups separated by a spacer arm of known length. Only protein residues closer than the length of the spacer arm are capable of being linked. Identification of cross-linked residues thereby provides distance constraints for structural modeling. In this work, the novel amidinating protein cross-linker, DEST (diethyl suberthioimidate), was employed (29, 30). This amine reactive reagent, unlike commercially available reagents, preserves the native basicity of the residues it modifies while being effective at physiological pH. Use of the reagent is unlikely to perturb protein structure and the modifications it imparts are compatible with ionization for mass spectrometry. We have additionally shown that the cross-links it forms can be efficiently enriched from other components of proteolytic digests using strong cation exchange (SCX) chromatography, (30) and that DEST cross-linking of ribosomes yields structural information in excellent agreement with x-ray crystallography (29). Although DEST is an 11Å spacer arm cross-linker, it links alpha carbons up to 24Å apart because of the length and flexibility of lysine side chains. Nevertheless, this is sufficient resolution to approximate the binding positions of the 10kDa domains of S1. Furthermore, multiple cross-linking of a single domain significantly enhances the resolution with which it can be localized.Here, through the application of protein cross-linking and high resolution mass spectrometry, we show that S1 binds to the 30S subunit near the anti-S.D. motif of the 16S rRNA, demonstrate that it is highly elongated even when bound to the ribosome, and provide evidence that its C-terminal mRNA binding region is remarkably dynamic. Our results thus indicate S1 is structurally poised, as previously hypothesized, (6) to act as the mRNA catching arm of the prokaryotic ribosome.     

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.     

Mapping the Structural Topology of the Yeast 19S Proteasomal Regulatory Particle Using Chemical Cross-linking and Probabilistic Modeling

Structural characterization of proteasome complexes is an essential step toward understanding the ubiquitin-proteasome system. Currently, high resolution structures are not available for the 26S proteasome holocomplex as well as its subcomplex, the 19S regulatory particle (RP). Here we have employed a novel integrated strategy combining chemical cross-linking with multistage tandem mass spectrometry to define the proximity of subunits within the yeast 19S RP to elucidate its topology. This has resulted in the identification of 174 cross-linked peptides of the yeast 19S RP, representing 43 unique lysine-lysine linkages within 24 nonredundant pair-wise subunit interactions. To map the spatial organization of the 19S RP, we have developed and utilized a rigorous probabilistic framework to derive maximum likelihood (ML) topologies based on cross-linked peptides determined from our analysis. Probabilistic modeling of the yeast 19S AAA-ATPase ring (i.e., Rpt1–6) has produced an ML topology that is in excellent agreement with known topologies of its orthologs. In addition, similar analysis was carried out on the 19S lid subcomplex, whose predicted ML topology corroborates recently reported electron microscopy studies. Together, we have demonstrated the effectiveness and potential of probabilistic modeling for unraveling topologies of protein complexes using cross-linking data. This report describes the first study of the 19S RP topology using a new integrated strategy combining chemical cross-linking, mass spectrometry, and probabilistic modeling. Our results have provided a solid foundation to advance our understanding of the 19S RP architecture at peptide level resolution. Furthermore, our methodology developed here is a valuable proteomic tool that can be generalized for elucidating the structures of protein complexes.Basic cellular homeostasis depends on the regulated protein degradation and turnover by the ubiquitin-proteasome system (1, 2). Central to this pathway is the 26S proteasome complex, which is responsible for ubiquitin/ATP-dependent protein degradation (3–5). The 26S holocomplex is a megadalton-sized protein assembly consisting of the 20S catalytic core particle (CP)¹ and the 19S regulatory particle (RP). The eukaryotic 20S CP is composed of two copies of 14 nonidentical subunits (α_1–7 and β_1–7) arranged into four stacked heptameric rings in an order of α₇β₇β₇α₇. The crystal structure and topology of the highly ordered 20S CP has been resolved and is evolutionarily conserved (6). Although α subunits of the 20S CP are essential for the assembly of the complex and its interactions with the regulatory complex, three catalytic β subunits (β1, β2, and β5) harbor various catalytic activities responsible for regulated proteasomal degradation. The 19S RP is composed of 19 subunits, which forms two subcomplexes, the base consisting of six related AAA-ATPase (Rpt1–6) and four non-ATPase (Rpn1, Rpn2, Rpn10, and Rpn13) subunits and the lid containing nine non-ATPase subunits (Rpn3, Rpn5–9, Rpn11, Rpn12, and Rpn15/Sem1) (7, 8). In comparison with the 20S core, the function and structure of the 19S RP is much less well understood. Nevertheless, it is believed that the 19S RP is involved in multiple functions including recognition of polyubiquitinated substrates (9, 10), cleavage of the polyubiquitin chains to recycle ubiquitin (11), unfolding of substrates, assisting in opening the gate of the 20S chamber, and subsequently translocating the unfolded substrates into the catalytic chamber (4, 12–14). The six AAA-ATPase subunits (Rpt1–6), which directly interact with the 20S α-ring, function as a molecular chaperone responsible for protein unfolding and are involved in substrate translocation and modulating gating of the CP (5, 15). Although detailed functions for most of the 19S non-ATPase subunits remain elusive, Rpn11 is known to carry an Mpr1p and Pad1p N-termini (MPN) domain, which harbors an essential deubiquitination activity responsible for cleaving polyubiquitin chains from proteasomal substrates (11, 16). In addition, two proteasome subunits, Rpn10 and Rpn13, have been identified as ubiquitin receptors, which are important in docking ubiquitinated substrates to the proteasome for degradation (4). Moreover, the two largest proteasome subunits, Rpn1 and Rpn2, interact with a variety of proteins including ubiquitin receptors and deubiquitinases and thus may function as scaffolding proteins to assist proteasomal degradation. Thus far, no atomic resolution structures are available for either the 19S RP or the 26S holocomplex. New insights of the overall topology of the 19S RP will illuminate protein interactions within, thus providing evidence for its otherwise unknown functions.Although many studies have been performed to characterize the 19S structure utilizing various techniques including cryo-EM (17, 18) and native mass spectrometry (19), details on spatial interfaces and subunit interconnectivity of the 19S RP remain to be unraveled. During the course of our study, the rough topology of the 19S RP was determined by cryo-EM alone (20) or coupled with other approaches (21); nevertheless more detailed information at the peptide or atomic level is still required. In addition to technological limitations in current approaches, the highly dynamic and heterogeneous nature of the 19S RP may attribute to the difficulty in obtaining its high resolution structure. In recent years, chemical cross-linking coupled with mass spectrometry (XL-MS) has become an attractive alternative for structure analysis of proteins and protein complexes (22, 23). The ability of XL-MS to identify interaction interfaces between proteins allows us to define low resolution protein topology. In addition to protein interaction networks and the site of protein interactions at binding interfaces, cross-linking analysis can reveal information about the spatial distance between cross-linked amino acids on the surface of folded proteins. Although such knowledge only reveals the maximum distance given by the length of the cross-linker and can be influenced by protein conformational flexibility, it can be used as the distance constraint for molecular modeling of protein folds and complex topologies, i.e., the arrangement of the constituents of a complex in space. A recent study by Chen et al. (24) on yeast RNA polymerase II (RNAPII) complex has exemplified the power of XL-MS in elucidating the architecture of large multisubunit complexes. Although effective, cross-linking studies have been challenging because of the low abundance of cross-linked products and the inherent complexity of sequencing interlinked peptides by MS for unambiguous identification. To facilitate MS detection and identification of cross-linked products, we have recently developed a novel homobifunctional amine reactive, low energy MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO), and successfully applied it to cross-link the yeast 20S proteasome for rapid, accurate, and simplified determination of protein interaction interfaces within the complex (25). The unique functionality of our cross-linking reagent and specialized bioinformatics tools significantly increase our confidence and speed in the identification of cross-linked products when compared with cross-linking studies using traditional noncleavable reagents. Current cross-linking studies have been focused on protein complexes with known crystal structures, but topological structures of protein complexes based primarily on cross-linking data have not yet been reported. This is due to the lack of computational tools that use cross-linking data to deduce the spatial organization of subunits in a given complex. To define the architecture of the yeast 19S RP, we have characterized the proximity and interconnectivity of the subunits by employing our newly developed cross-linking strategy. The resulting cross-linking information serves as a basis for a rigorous probabilistic analysis to obtain the maximum likelihood (ML) topology. This strategy is developed by first analyzing our cross-linking data for the 19S six-member AAA-ATPase base ring, as the topology ordering of yeast orthologs has been recently determined (14, 26–28). The effectiveness of this new probabilistic platform is supported by the agreement between our derived ML topology of the AAA-ATPase base ring and previous reports. When the same probabilistic approach is applied to the 19S lid subcomplex, the resulting topology is also in agreement with recently proposed models (20, 21). This work represents the first application of probabilistic modeling of protein complexes based solely on cross-link data, establishing a new workflow for future structural analysis of large protein complexes using XL-MS.     

Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology

Chemical cross-linking combined with mass spectrometry has proven useful for studying protein-protein interactions and protein structure, however the low density of cross-link data has so far precluded its use in determining structures de novo. Cross-linking density has been typically limited by the chemical selectivity of the standard cross-linking reagents that are commonly used for protein cross-linking. We have implemented the use of a heterobifunctional cross-linking reagent, sulfosuccinimidyl 4,4′-azipentanoate (sulfo-SDA), combining a traditional sulfo-N-hydroxysuccinimide (sulfo-NHS) ester and a UV photoactivatable diazirine group. This diazirine yields a highly reactive and promiscuous carbene species, the net result being a greatly increased number of cross-links compared with homobifunctional, NHS-based cross-linkers. We present a novel methodology that combines the use of this high density photo-cross-linking data with conformational space search to investigate the structure of human serum albumin domains, from purified samples, and in its native environment, human blood serum. Our approach is able to determine human serum albumin domain structures with good accuracy: root-mean-square deviation to crystal structure are 2.8/5.6/2.9 Å (purified samples) and 4.5/5.9/4.8Å (serum samples) for domains A/B/C for the first selected structure; 2.5/4.9/2.9 Å (purified samples) and 3.5/5.2/3.8 Å (serum samples) for the best out of top five selected structures. Our proof-of-concept study on human serum albumin demonstrates initial potential of our approach for determining the structures of more proteins in the complex biological contexts in which they function and which they may require for correct folding. Data are available via ProteomeXchange with identifier PXD001692.High-resolution structures of proteins are essential for understanding cellular processes. Determining protein structures, however, is difficult: protein stability, purity, quantity, and solubility critically affect success. Nuclear magnetic resonance (NMR)¹ spectroscopy can only be applied to proteins of limited size, whereas x-ray crystallography necessitates prior crystallization of the protein. These conditions make structure determination challenging for many proteins of biological relevance. This includes especially proteins that contain intrinsically unstructured or long coiled-coil regions, proteins associated to a membrane (1, 2) or parts of multi-protein complexes (3). New developments to overcome some of these restrictions include x-ray free electron lasers (XFEL) (4), which only require microcrystals, new detectors in cryo-electron microscopy (5) and in-cell NMR (6), which analyzes the structure of small proteins in a cellular context. Further advancements that assist with protein structure determination have included the development of being able to use sparse NMR data, for example using backbone only data (7), and the understanding of evolutionary constraints for predicting protein structure (8).We present a novel approach to obtain structural details of proteins by mass spectrometry. This can be accomplished through cross-linking and mass spectrometry (CLMS) (9–11). Cross-links establish covalent bonds between residue pairs close in space but not necessarily in sequence. This conserves structural information throughout an analysis that follows the standard proteomics workflow. Typically, a bi-functional chemical reagent, the cross-linker, is incubated with a protein of interest. The cross-linker reacts with two residues—often involving the side-chain amine of lysine—that are near each other in the folded protein. A protease such as trypsin is used to degrade the protein. The resulting mix of cross-linked peptides is then analyzed by mass spectrometry and database searching akin to other shotgun proteomics approaches (12). The pairs of cross-linked residues are identified from the mass spectrometric data and provide information on which residues are near each other in the folded protein. This information is represented in the form of distance constraints, deducible from the length of the cross-linking agent.CLMS data has been used to study large multi-protein complexes (13), networks (14) and proteins in whole cells (15). The distance constraints obtained are sparse but complement other structural data in integrated structural biology well (10). Cross-link data allow placing high-resolution structures of individual sub-units in the electron microscopy structure of an assembled multi-protein complex to obtain its quasi-atomic resolution structure, e.g. the proteasome (16). In an alternative approach, genetic site-directed positioning of a photo-reactive group, azide, as part of a phenylalanine analog, was recently used to derive proximity information that allowed modeling of receptor CRF1R bound to its native ligand (17). Young et al. used 15 cross-links to identify the correct fold of bovine basic fibroblast growth factor using threading and homology modeling (18). In a similar study, Singh et al. used eight cross-links to build a monomer homology model of the major capsid protein E of bacteriophage lambda and to derive a pseudoatomic model of the lambda procapsid shell (19). In both of the aforementioned cases, the cross-link information was merely used to verify structural models by threading and homology modeling, and did not significantly impact model building. Prior attempts to leverage cross-linking data in structure determination delivered improvements, however, without leading to high-resolution models (20).Here, we increase the spatial resolution of information obtained through cross-linking by using a highly reactive chemical as a cross-linking agent. This broadens the specificity of cross-linking and thus increases the spatial resolution in conjunction with mass spectrometry. We employ the heterobifunctional chemical cross-linker sulfosuccinimidyl 4,4′-azipentanoate, sulfo-SDA (21), to chemically cross-link a protein, human serum albumin (HSA).We combine the distance constraints provided by cross-linking and mass spectrometry with computational, conformational space search. This approach allows us to generate structural models of HSA domains that correlate highly with the structure of HSA solved by x-ray crystallography. With this method, we show that our pipeline can be used to analyze the structure of HSA domains from HSA not only in it''s purified form, but additionally unpurified and in its native environment, human blood serum.     

Targeting Synaptic Pathology with a Novel Affinity Mass Spectrometry Approach

We report a novel strategy for studying synaptic pathology by concurrently measuring levels of four SNARE complex proteins from individual brain tissue samples. This method combines affinity purification and mass spectrometry and can be applied directly for studies of SNARE complex proteins in multiple species or modified to target other key elements in neuronal function. We use the technique to demonstrate altered levels of presynaptic proteins in Alzheimer disease patients and prion-infected mice.One prominent pathological feature of neuropsychiatric disorders such as Alzheimer disease (AD)¹ is severe synaptic loss (1–3). Previous reports of AD patients have shown that presynaptic dysfunction might occur early in the disease process (1, 4). Cortical synapse pathology has also been shown to correlate to the severity of dementia more closely than other pathological hallmarks of AD such as plaques and neurofibrillary tangles (5, 6). The SNARE proteins are essential components for the regulation of neurotransmitter exocytosis at the presynaptic site (7). Animal models suggest that changed expression or modification of SNARE complex proteins (synaptosomal-associated protein 25 (SNAP-25), syntaxin-1, and vesicle-associated membrane protein (VAMP)) alters synaptic function and is an interesting target for the development of therapeutics for neuropsychiatric illness (8, 9). The constituents of the SNARE complex are either localized in synaptic vesicles (VAMPs) or anchored at the presynaptic plasma membrane (SNAP-25 and syntaxin). The SNARE proteins are tightly assembled, and subsequent neurotransmitter release of the complex is quickly dissociated by N-ethylmaleimide-sensitive factor (7, 10–12). Because they are both strongly associated into complexes and membrane associated, the SNARE proteins are difficult to analyze via mass spectrometry, which is incompatible with most detergents necessary for the solubilization of proteins. Each SNARE complex protein exists in several isoforms that are differently distributed within the central nervous system (13–18). Post-translational modifications and truncated variants of the SNARE proteins make investigation of the protein expression even more complicated.In this study we developed an approach for the characterization and concurrent quantification of SNARE complex proteins that combines affinity purification by immunoprecipitation and mass spectrometry (IP-MS). We used precipitation with monoclonal antibodies against SNAP-25 to target the SNARE complex proteins and nanoflow LC–tandem mass spectrometry (LC-MS/MS) to characterize the co-immunoprecipitated interaction partners. Selected reaction monitoring (SRM) on a triple quadrupole mass spectrometer coupled to a microflow LC system was used for quantification of the SNARE proteins. To demonstrate the usability of the IP-MS method, we performed a comparison of SNARE complex protein levels in brain tissue from AD patients and age-matched controls, as well as a study of SNARE complex protein levels in brain tissue from prion-infected mice.     

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.     

Laserspray Ionization, a New Method for Protein Analysis Directly from Tissue at Atmospheric Pressure with Ultrahigh Mass Resolution and Electron Transfer Dissociation

Laserspray ionization (LSI) mass spectrometry (MS) allows, for the first time, the analysis of proteins directly from tissue using high performance atmospheric pressure ionization mass spectrometers. Several abundant and numerous lower abundant protein ions with molecular masses up to ∼20,000 Da were detected as highly charged ions from delipified mouse brain tissue mounted on a common microscope slide and coated with 2,5-dihydroxyacetophenone as matrix. The ability of LSI to produce multiply charged ions by laser ablation at atmospheric pressure allowed protein analysis at 100,000 mass resolution on an Orbitrap Exactive Fourier transform mass spectrometer. A single acquisition was sufficient to identify the myelin basic protein N-terminal fragment directly from tissue using electron transfer dissociation on a linear trap quadrupole (LTQ) Velos. The high mass resolution and mass accuracy, also obtained with a single acquisition, are useful in determining protein molecular weights and from the electron transfer dissociation data in confirming database-generated sequences. Furthermore, microscopy images of the ablated areas show matrix ablation of ∼15 μm-diameter spots in this study. The results suggest that LSI-MS at atmospheric pressure potentially combines speed of analysis and imaging capability common to matrix-assisted laser desorption/ionization and soft ionization, multiple charging, improved fragmentation, and cross-section analysis common to electrospray ionization.Tissue imaging by mass spectrometry (MS) is proving useful in areas such as detecting tumor margins, determining sites of high drug uptake, and mapping signaling molecules in brain tissue (1–8). Imaging using secondary ion mass spectrometry is well established but is only marginally useful with intact molecular mass measurements from biological tissue (9–11). Matrix-assisted laser desorption/ionization (MALDI)-MS operating under vacuum conditions has been used for tissue imaging with success, especially for abundant components such as membrane lipids, drug metabolites, and proteins (12–14). Spatial resolution of ∼20 μm has been achieved (15), and the MALDI-MS method has been applied in an attempt to shed light on Parkinson disease (16, 17), muscular dystrophy (18), obesity, and cancer (12, 19).Unfortunately, there are disadvantages in using vacuum-based MS for tissue imaging in relation to analysis of unadulterated tissue. Also, the mass spectrometers used in these studies frequently have much lower mass resolution and mass accuracy than are available with atmospheric pressure ionization (API)¹ instruments and are not as widely available. Because the vacuum ionization methods produce singly charged ions, mass-selected fragmentation methods provide only limited information, especially for proteins. In addition, no advanced fragmentation such as electron transfer dissociation (ETD) (20–22) is available for confident protein confirmation or identification. Atmospheric pressure (AP) MALDI can be coupled to high performance mass spectrometers but suffers from sensitivity issues for tissue imaging where high spatial resolution is desired (23). AP MALDI also primarily produces singly charged ions (24, 25). Thus, mass and cross-section analysis of intact proteins has yet to be accomplished using AP MALDI because of intrinsic mass range limitations of API instruments, which frequently have a mass-to-charge (m/z) limit of <4000. Thus, new improved methods of mass-specific tissue imaging, especially at AP, are needed.The potential of laserspray ionization (LSI) (Scheme 1) (26–33) for protein tissue analysis is reported here. LSI has advantages relative to other MS-based methods, including speed of analysis, laser ablation of small volumes, more relevant AP conditions, extended mass range and improved fragmentation through multiple charging, and the ability to obtain cross-section data for proteins on appropriate instrumentation. The applicability of LSI for high mass compounds on high performance API mass spectrometers (Orbitrap Exactive and SYNAPT G2) has been demonstrated producing ESI-like multiply protonated ions (26–28). The first experiments showing sequence analysis by ETD using the LSI method were successfully carried out on a Thermo Fisher Scientific (San Jose, CA) LTQ-ETD mass spectrometer (26). Nearly complete sequence coverage was obtained for ubiquitin, an important regulatory protein. Applying ETD fragmentation to LSI-MS analyses potentially provides a new method for studying biological processes, including the mapping of phosphorylation, glycosylation, and ubiquitination sites from intact proteins and directly from tissue.Open in a separate windowScheme 1.Overview of LSI-MS operated in transmission geometry.Furthermore, unlike ESI and related ESI-based methods such as desorption-ESI (34), the LSI method has been shown to allow analysis of lipids in tissue from ablated areas <80 μm (30). In comparison with literature reports for AP MALDI at the same stage of development (35), LSI is more than an order of magnitude more sensitive and is capable of analyzing proteins on high resolution mass spectrometers as was demonstrated by obtaining full-acquisition mass spectra at 100,000 mass resolution (FWHH, m/z 200) after application of only 20 fmol of bovine pancreas insulin in the matrix 2,5-dihydroxyacetophenone (2,5-DHAP) onto a glass microscope slide (33). The analysis speed of LSI was demonstrated by obtaining mass spectra of five samples in 8 s (32). Here, we show the utility of LSI for intact peptide and protein analyses directly from mouse brain tissue. The ability to obtain a protein mass spectrum directly from mouse brain tissue in a single laser shot at 100,000 mass resolution and with ETD fragmentation is demonstrated.     

Proteomic Analyses Reveal Divergent Ubiquitylation Site Patterns in Murine Tissues

Posttranslational modifications of proteins increase the complexity of the cellular proteome and enable rapid regulation of protein functions in response to environmental changes. Protein ubiquitylation is a central regulatory posttranslational modification that controls numerous biological processes including proteasomal degradation of proteins, DNA damage repair and innate immune responses. Here we combine high-resolution mass spectrometry with single-step immunoenrichment of di-glycine modified peptides for mapping of endogenous putative ubiquitylation sites in murine tissues. We identify more than 20,000 unique ubiquitylation sites on proteins involved in diverse biological processes. Our data reveals that ubiquitylation regulates core signaling pathways common for each of the studied tissues. In addition, we discover that ubiquitylation regulates tissue-specific signaling networks. Many tissue-specific ubiquitylation sites were obtained from brain highlighting the complexity and unique physiology of this organ. We further demonstrate that different di-glycine-lysine-specific monoclonal antibodies exhibit sequence preferences, and that their complementary use increases the depth of ubiquitylation site analysis, thereby providing a more unbiased view of protein ubiquitylation.Ubiquitin is a small 76-amino-acid protein that is conjugated to the ε-amino group of lysines in a highly orchestrated enzymatic cascade involving ubiquitin activating (E1), ubiquitin conjugating (E2), and ubiquitin ligase (E3) enzymes (1). Ubiquitylation is involved in the regulation of diverse cellular processes including protein degradation (2, 3, 4), DNA damage repair (5, 6), DNA replication (7), cell surface receptor endocytosis, and innate immune signaling (8, 9). Deregulation of protein ubiquitylation is implicated in the development of cancer and neurodegenerative diseases (10, 11). Inhibitors targeting the ubiquitin proteasome system are used in the treatment of hematologic malignancies such as multiple myeloma (12, 13).Recent developments in the mass spectrometry (MS)-based proteomics have greatly expedited proteome-wide analysis of posttranslational modifications (PTMs) (14–17). Large-scale mapping of ubiquitylation sites by mass spectrometry is based on the identification of the di-glycine remnant that results from trypsin digestion of ubiquitylated proteins and remains attached to ubiquitylated lysines (18). Recently, two monoclonal antibodies were developed that specifically recognize di-glycine remnant modified peptides enabling their efficient enrichment from complex peptide mixtures (19, 20). These antibodies have been used to identify thousands of endogenous ubiquitylation sites in human cells, and to quantify site-specific changes in ubiquitylation in response to different cellular perturbations (20–22). It should be noted that the di-glycine remnant is not specific for proteins modified by ubiquitin but also proteins modified by NEDD8 or ISG15 generate an identical di-glycine remnant on modified lysines making it impossible to distinguish between these modifications by mass spectrometry. However, expression of NEDD8 in mouse tissues was shown to be developmentally down-regulated (23), and ISG15 expression in bovine tissues is low in the absence of interferon stimulation (24). In cell culture experiments it was shown that a great majority of sites identified using di-glycine-lysine-specific antibodies stems from ubiquitylated peptides (20).The rates of cell proliferation and protein turnover in mammals vary dramatically between different tissues. Immortalized cell lines, often derived from cancer, are selected for high proliferation rates and fail to represent the complex conditions in tissues. Tissue proteomics can help to gain a more comprehensive understanding of physiological processes in multicellular organisms. Analysis of tissue proteome and PTMs can provide important insights into tissue-specific processes and signaling networks that regulate these processes (25–32). In addition, development of mass spectrometric methods for analysis of PTMs in diseased tissues might lead to the identification of biomarkers.In this study, we combined high-resolution mass spectrometry with immunoenrichment of di-glycine modified peptides to investigate endogenous ubiquitylation sites in murine tissues. We identified more than 20,000 ubiquitylation sites from five different murine tissues and report the largest ubiquitylation dataset obtained from mammalian tissues to date. Furthermore, we compared the performance of the two monoclonal di-glycine-lysine-specific antibodies available for enrichment of ubiquitylated peptides, and reveal their relative preferences for different amino acids flanking ubiquitylation sites.     

Defining,Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples.Recent developments in methods and instruments for mass spectrometry enable quantitative proteomics analysis of complex samples with good coverage (1–4). Several techniques for quantification by mass spectrometry exist, both using isotopic labeling and label free methods (5, 6). Quantification by isotopic labeling can be done on precursor ion level or by quantifying isobaric label fragments in fragment spectra. Isotope-coded affinity tag (7), isobaric tags for relative and absolute quantification (iTRAQ)¹ (8), and stable isotope labeling by amino acids in cell culture (SILAC) (9) are among the most commonly used labeling methods based on stable isotopes. iTRAQ allows for simultaneous relative quantification of up to eight samples within a single run. Quantification by mass spectrometry is however a challenge, and several factors contribute to the uncertainty in the quantitative estimate; differences in labeling efficiency, protein digestion, precursor mixing, ion suppression, peak detection, data preprocessing, and data analysis (10). The quality of quantitation methods can be measured in terms of precision and accuracy. Precision is affected by random errors, that is, random fluctuations around the true value (variance). Lack of accuracy is caused by systematic errors, that is, differences between true and observed values (bias).Several studies have shown that iTRAQ labeling is associated with bias; fold changes are compressed toward one (11–14). It has been suggested that this underestimation of fold change is caused by co-eluting peptides with similar m/z values that are isolated together, creating mixed iTRAQ intensities in complex samples (14). Concerning precision, iTRAQ data has been reported to exhibit variance heterogeneity. The coefficient of variance (CV) of the signal depends on the intensity, with larger CV for low intensity peaks (11, 12, 15, 16). Measurements of iTRAQ intensities for quantification are made in the MS/MS spectra of the peptides, and thereafter combined to calculate a summarized relative protein quantity. There are several different approaches for combining the iTRAQ peptide data to compute a reliable protein ratio. Methods to improve the protein quantification by addressing the variance heterogeneity have been based on excluding low intensity peptide data (17, 18), weighting the peptide data according to intensity (18–21) or stabilizing the variance (12).Quantitative studies of complex human samples are subject to even more challenges related to large biological variation, large and unknown complexity of the human proteome and a large concentration range of proteins. This in turn results in many peptides and a large variety of peptides that can cause interference and related problems in the mass spectrometry analysis. In, for example, biomarker discovery research the goal is to measure quantitative changes or differences in protein levels between two or more clinical conditions. It is therefore crucial to achieve as accurate and precise quantitative information from the data as possible as well as to correctly estimate the limitations of the quantification. Setting adequate standards for quantitative proteomics analysis is hence essential for being able to detect relevant changes in protein abundance, select important proteins, and further use those proteins to interpret the biological and clinical meaning (10, 22). Selecting a protein as significant and taking it to further validation in other clinical material using complementary techniques is time consuming and costly (23). For successful use of iTRAQ labeling in biomarker discovery, and to avoid false discoveries, it is hence essential to assess the accuracy and precision of the methodology.A common approach to study variance and bias in mass spectrometry based protein quantification is to spike a set of standard proteins into a sample and then measure the CV and bias of the intensities of those peptides. Spike-in of proteins has the benefit of looking at a small controlled set of peptides and how they behave in the studied system. This strategy has been used in several of the previously mentioned papers that address iTRAQ quantification (11–14). However, the number of data points studied may be unlikely to represent the complexity of a real biological sample, which often contains thousands of proteins (24). In the current study, all peptides detected in a complex human cell line sample (A549) are used to get an estimate of the quantitative accuracy and precision. This experimental setup is hence more similar to a real biomarker discovery study with high complex human proteome samples. The quality of the protein quantifications is compared among several different mass spectrometers in this work; also the influence of different loaded peptide amounts and the use of different methods for sample separation are examined. Factors such as variance and bias of peptide quantification by iTRAQ are systematically evaluated in those high complex samples. Further, methods for improving the protein quantification are investigated; by filtering on the peptide level to remove low quality intensities and by weighting the peptide values to account for the higher risk of errors at low intensities (20).We have described the factors contributing to bias and variance in protein quantification by iTRAQ labeling. This has generated guidelines for how to estimate the accuracy of protein quantities, which will be an essential tool in both biomarker discovery and studies of biological systems. Based on the results, we suggest an experimental design where each labeling set (e.g., iTRAQ) includes duplicate samples, and we describe how these duplicates are used for calculating peptide weights that can be used in addressing the accuracy of protein quantities. This novel approach is shown to improve protein quantification by iTRAQ in six data sets of A431 cell line samples treated with drug and a clinical data set of lung cancer tissue samples.     

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.     

Defining Elastic Fiber Interactions by Molecular Fishing: AN AFFINITY PURIFICATION AND MASS SPECTROMETRY APPROACH*

Deciphering interacting networks of the extracellular matrix is a major challenge. We describe an affinity purification and mass spectrometry strategy that has provided new insights into the molecular interactions of elastic fibers, essential extracellular assemblies that provide elastic recoil in dynamic tissues. Using cell culture models, we defined primary and secondary elastic fiber interaction networks by identifying molecular interactions with the elastic fiber molecules fibrillin-1, MAGP-1, fibulin-5, and lysyl oxidase. The sensitivity and validity of our method was confirmed by identification of known interactions with the bait proteins. Our study revealed novel extracellular protein interactions with elastic fiber molecules and delineated secondary interacting networks with fibronectin and heparan sulfate-associated molecules. This strategy is a novel approach to define the macromolecular interactions that sustain complex extracellular matrix assemblies and to gain insights into how they are integrated into their surrounding matrix.Mass spectrometry is emerging as a powerful approach to identify protein interaction partners in molecular complexes. We have developed an affinity purification and mass spectrometry strategy that is applicable to the analysis of molecular interactions of extracellular matrix complexes. The extracellular matrix provides structural support to tissues and profoundly influences cell survival, proliferation, migration, and phenotypic state. It is a complex multimolecular and three-dimensional milieu that comprises assembled networks of tissue-specific combinations of structural and cell-adhesive glycoproteins, proteoglycans, and cross-linking enzymes. The matrix also sequesters numerous growth factors and cytokines, thereby controlling their bioavailability. Delineating the molecular nature of the fundamental interacting networks within complex extracellular matrices is a challenging task. Here, mass spectrometry has given new insights into elastic fiber interactions.Elastic fibers are essential structural elements of the extracellular matrix of dynamic connective tissues such as blood vessels, lungs, skin, and ligaments, endowing these tissues with elastic recoil (1, 2). Their importance is emphasized by elastic fiber defects that cause severe acquired diseases such as aortic aneurysms and pulmonary emphysema and life-threatening heritable disorders such as Marfan syndrome, supravalvular stenosis, and cutis laxa. These fibers are extensive multimolecular assemblies that adopt intricate tissue-specific architectural arrangements. At the morphological level, the fibers comprise a cross-linked elastin core and an outer mantle of fibrillin microfibrils. It has proved challenging to define the composition of tissue elastic fibers biochemically. Cross-linked elastin is highly insoluble and its isolation from tissues requires extreme conditions of hot alkali, which destroys other proteins (2). The efficient extraction of tissue microfibrils requires collagenase and other proteolytic activities that may destroy associated molecules (3). Despite these difficulties, a number of associated proteins, including MAGP-1,1 βigH3, fibulins, and lysyl oxidases (LOX and LOXL (also known as LOXL1)), as well as latent TGFβ-binding proteins (LTBPs), collagen VIII, and emilin-1 have been identified in biochemical and/or colocalization studies (1).Fibrillins are very large glycoproteins (350 kDa) containing 43 calcium-binding epidermal growth factor-like domains and seven TGFβ-binding protein-like (8-cysteine) domains (4). Fibrillin-1 is the more abundant isoform; fibrillin-2 is mainly expressed during development (5, 6). Tropoelastin, the secreted soluble form of elastin, comprises alternating hydrophobic and lysine-rich cross-linking domains. LOX and LOXL are copper-dependent amine oxidases that cross-link elastin through the oxidative deamination of specific lysines (7–9). Elastin is mainly expressed and deposited early in life and undergoes very little turnover in healthy tissues (2). MAGP-1 is a microfibril-associated glycoprotein that binds fibrillin-1 and elastin (10, 11) but is not essential for elastic fiber formation (12). βigH3 was originally identified as a matrix protein, MP78/70, in tissue extracts that solubilized elastin-associated microfibrils (13, 14). Fibulin-4 and -5 play essential roles in elastic fiber formation (15, 16), most likely by regulating elastin deposition onto microfibrils (17, 18). Fibulin-2 interacts with fibrillin-1 (19) but is not essential for elastic fiber formation (20). Fibulin-1-null mice, among other symptoms, display anomalies of aortic arch arteries and hemorrhagic blood vessels, suggesting some involvement in elastic fiber biology (21). Fibulin-3 (also known as Efemp1)-deficient mice exhibit early aging and herniation associated with reduced elastic fiber integrity (22). Collagen VIII and emilin-1 also colocalize to elastic fibers (23, 24).The assembly of microfibrils and elastic fibers remains incompletely understood. We and others recently showed that assembly of the microfibril component is orchestrated by the cell surface through interactions with fibronectin and integrin receptors (25, 26). Heparan sulfate, an abundant pericellular glycosaminoglycan chain attached to syndecan and glypican proteoglycan receptors, also critically influences microfibril formation (27–29). Elastin deposition and stabilization on microfibrils require fibulins and the cross-linking enzymes LOX and/or LOXL.To obtain new insights into the molecular interactions of elastic fibers and how they are integrated into their surrounding matrix, we conducted a detailed affinity capture LC-MS/MS analysis of molecules that interact in culture specifically with four His₆-tagged recombinant human elastic fiber molecules (fibrillin-1, MAGP-1, fibulin-5, and LOX). Tropoelastin was not used as bait because of its highly adhesive nature. Our protocol proved to be an effective strategy for defining specific interactions of elastic fiber molecules in the extracellular matrix. Efficacy was demonstrated through confirmation of known interactions and validation of novel extracellular matrix protein-protein interactions. This approach further allowed us to predict secondary elastic fiber interactions, giving powerful insights into the molecular networks that sustain elastic fibers within higher order extracellular matrices.