xTract: software for characterizing conformational changes of protein complexes by quantitative cross-linking mass spectrometry

Dissecting diazirine photo-reaction mechanism for protein residue-specific cross-linking and distance mapping

While photo-cross-linking (PXL) with alkyl diazirines can provide stringent distance restraints and offer insights into protein structures, unambiguous identification of cross-linked residues hinders data interpretation to the same level that has been achieved with chemical cross-linking (CXL). We address this challenge by developing an in-line system with systematic modulation of light intensity and irradiation time, which allows for a quantitative evaluation of diazirine photolysis and photo-reaction mechanism. Our results reveal a two-step pathway with mainly sequential generation of diazo and carbene intermediates. Diazo intermediate preferentially targets buried polar residues, many of which are inaccessible with known CXL probes for their limited reactivity. Moreover, we demonstrate that tuning light intensity and duration enhances selectivity towards polar residues by biasing diazo-mediated cross-linking reactions over carbene ones. This mechanistic dissection unlocks the full potential of PXL, paving the way for accurate distance mapping against protein structures and ultimately, unveiling protein dynamic behaviors.

Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry

We propose a pipeline that combines AlphaFold2 (AF2) and crosslinking mass spectrometry (XL-MS) to model the structure of proteins with multiple conformations. The pipeline consists of two main steps: ensemble generation using AF2 and conformer selection using XL-MS data. For conformer selection, we developed two scores-the monolink probability score (MP) and the crosslink probability score (XLP)-both of which are based on residue depth from the protein surface. We benchmarked MP and XLP on a large dataset of decoy protein structures and showed that our scores outperform previously developed scores. We then tested our methodology on three proteins having an open and closed conformation in the Protein Data Bank: Complement component 3 (C3), luciferase, and glutamine-binding periplasmic protein, first generating ensembles using AF2, which were then screened for the open and closed conformations using experimental XL-MS data. In five out of six cases, the most accurate model within the AF2 ensembles-or a conformation within 1 Å of this model-was identified using crosslinks, as assessed through the XLP score. In the remaining case, only the monolinks (assessed through the MP score) successfully identified the open conformation of glutamine-binding periplasmic protein, and these results were further improved by including the "occupancy" of the monolinks. This serves as a compelling proof-of-concept for the effectiveness of monolinks. In contrast, the AF2 assessment score was only able to identify the most accurate conformation in two out of six cases. Our results highlight the complementarity of AF2 with experimental methods like XL-MS, with the MP and XLP scores providing reliable metrics to assess the quality of the predicted models. The MP and XLP scoring functions mentioned above are available at https://gitlab.com/topf-lab/xlms-tools.

DNAJB8 oligomerization is mediated by an aromatic-rich motif that is dispensable for substrate activity

J-domain protein (JDP) molecular chaperones have emerged as central players that maintain a healthy proteome. The diverse members of the JDP family function as monomers/dimers and a small subset assemble into micron-sized oligomers. The oligomeric JDP members have eluded structural characterization due to their low-complexity, intrinsically disordered middle domains. This in turn, obscures the biological significance of these larger oligomers in protein folding processes. Here, we identified a short, aromatic motif within DNAJB8, that drives self-assembly through pi-pi stacking and determined its X-ray structure. We show that mutations in the motif disrupt DNAJB8 oligomerization in vitro and in cells. DNAJB8 variants that are unable to assemble bind to misfolded tau seeds more specifically and retain capacity to reduce protein aggregation in vitro and in cells. We propose a new model for DNAJB8 function in which the sequences in the low-complexity domains play distinct roles in assembly and substrate activity.

A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data

Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. The integrative structure modeling approach characterizes multi-subunit complexes by computational integration of data from fast and accessible experimental techniques. Crosslinking mass spectrometry is one such technique that provides spatial information about the proximity of crosslinked residues. One of the challenges in interpreting crosslinking datasets is designing a scoring function that, given a structure, can quantify how well it fits the data. Most approaches set an upper bound on the distance between Cα atoms of crosslinked residues and calculate a fraction of satisfied crosslinks. However, the distance spanned by the crosslinker greatly depends on the neighborhood of the crosslinked residues. Here, we design a deep learning model for predicting the optimal distance range for a crosslinked residue pair based on the structures of their neighborhoods. We find that our model can predict the distance range with the area under the receiver-operator curve of 0.86 and 0.7 for intra- and inter-protein crosslinks, respectively. Our deep scoring function can be used in a range of structure modeling applications.

Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers

Chemical cross-linking of proteins coupled with mass spectrometry is widely used in protein structural analysis. In this study we develop a class of non-hydrolyzable amine-selective di-ortho-phthalaldehyde (DOPA) cross-linkers, one of which is called DOPA2. Cross-linking of proteins with DOPA2 is 60-120 times faster than that with the N-hydroxysuccinimide ester cross-linker DSS. Compared with DSS cross-links, DOPA2 cross-links show better agreement with the crystal structures of tested proteins. More importantly, DOPA2 has unique advantages when working at low pH, low temperature, or in the presence of denaturants. Using staphylococcal nuclease, bovine serum albumin, and bovine pancreatic ribonuclease A, we demonstrate that DOPA2 cross-linking provides abundant spatial information about the conformations of progressively denatured forms of these proteins. Furthermore, DOPA2 cross-linking allows time-course analysis of protein conformational changes during denaturant-induced unfolding.

Quantitative interactome analysis with chemical cross-linking and mass spectrometry

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

Leveraging crosslinking mass spectrometry in structural and cell biology

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

A chemical probe based on the PreQ1 metabolite enables transcriptome-wide mapping of binding sites

The role of metabolite-responsive riboswitches in regulating gene expression in bacteria is well known and makes them useful systems for the study of RNA-small molecule interactions. Here, we study the PreQ₁ riboswitch system, assessing sixteen diverse PreQ₁-derived probes for their ability to selectively modify the class-I PreQ₁ riboswitch aptamer covalently. For the most active probe (11), a diazirine-based photocrosslinking analog of PreQ₁, X-ray crystallography and gel-based competition assays demonstrated the mode of binding of the ligand to the aptamer, and functional assays demonstrated that the probe retains activity against the full riboswitch. Transcriptome-wide mapping using Chem-CLIP revealed a highly selective interaction between the bacterial aptamer and the probe. In addition, a small number of RNA targets in endogenous human transcripts were found to bind specifically to 11, providing evidence for candidate PreQ₁ aptamers in human RNA. This work demonstrates a stark influence of linker chemistry and structure on the ability of molecules to crosslink RNA, reveals that the PreQ₁ aptamer/ligand pair are broadly useful for chemical biology applications, and provides insights into how PreQ₁, which is similar in structure to guanine, interacts with human RNAs.

Structural Probing of Hsp26 Activation and Client Binding by Quantitative Cross-Linking Mass Spectrometry

Small heat-shock proteins (sHSPs) are important members of the cellular stress response in all species. Their best-described function is the binding of early unfolding states and the resulting prevention of protein aggregation. Many sHSPs exist as a polydisperse composition of oligomers, which undergoes changes in subunit composition, folding status, and relative distribution upon heat activation. To date, only an incomplete picture of the mechanism of sHSP activation exists; in particular, the molecular basis of how sHSPs bind client proteins and mediate client specificity is not fully understood. In this study, we have applied cross-linking mass spectrometry (XL-MS) to obtain detailed structural information on sHSP activation and client binding for yeast Hsp26. Our cross-linking data reveals the middle domain of Hsp26 as a client-independent interface in multiple Hsp26::client complexes and indicates that client specificity is likely mediated via additional binding sites within its α-crystallin domain and C-terminal extension. Our quantitative XL-MS data underpins the middle domain as the main driver of heat-induced activation and client binding but shows that global rearrangements spanning all domains of Hsp26 take place simultaneously. We also investigated a Hsp26::client complex in the presence of Ssa1 (Hsp70) and Ydj1(Hsp40) at the initial stage of refolding and observe that the interaction between refolding chaperones is altered by the presence of a client protein, pointing to a mechanism where the interaction of Ydj1 with the HSP::client complex initiates the assembly of the active refolding machinery.

HspB8 prevents aberrant phase transitions of FUS by chaperoning its folded RNA-binding domain

Aberrant liquid-to-solid phase transitions of biomolecular condensates have been linked to various neurodegenerative diseases. However, the underlying molecular interactions that drive aging remain enigmatic. Here, we develop quantitative time-resolved crosslinking mass spectrometry to monitor protein interactions and dynamics inside condensates formed by the protein fused in sarcoma (FUS). We identify misfolding of the RNA recognition motif of FUS as a key driver of condensate aging. We demonstrate that the small heat shock protein HspB8 partitions into FUS condensates via its intrinsically disordered domain and prevents condensate hardening via condensate-specific interactions that are mediated by its α-crystallin domain (αCD). These αCD-mediated interactions are altered in a disease-associated mutant of HspB8, which abrogates the ability of HspB8 to prevent condensate hardening. We propose that stabilizing aggregation-prone folded RNA-binding domains inside condensates by molecular chaperones may be a general mechanism to prevent aberrant phase transitions.

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

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

Prediction of Protein Complex Structure Using Surface-Induced Dissociation and Cryo-Electron Microscopy

A variety of techniques involving the use of mass spectrometry (MS) have been developed to obtain structural information on proteins and protein complexes. One example of these techniques, surface-induced dissociation (SID), has been used to study the oligomeric state and connectivity of protein complexes. Recently, we demonstrated that appearance energies (AE) could be extracted from SID experiments and that they correlate with structural features of specific protein-protein interfaces. While SID AE provides some structural information, the AE data alone are not sufficient to determine the structures of the complexes. For this reason, we sought to supplement the data with computational modeling, through protein-protein docking. In a previous study, we demonstrated that the scoring of structures generated from protein-protein docking could be improved with the inclusion of SID data; however, this work relied on knowledge of the correct tertiary structure and only built full complexes for a few cases. Here, we performed docking using input structures that require less prior knowledge, using homology models, unbound crystal structures, and bound+perturbed crystal structures. Using flexible ensemble docking (to build primarily subcomplexes from an ensemble of backbone structures), the RMSD₁₀₀ of all (15/15) predicted structures using the combined Rosetta, cryo-electron microscopy (cryo-EM), and SID score was less than 4 Å, compared to only 7/15 without SID and cryo-EM. Symmetric docking (which used symmetry to build full complexes) resulted in predicted structures with RMSD₁₀₀ less than 4 Å for 14/15 cases with experimental data, compared to only 5/15 without SID and cryo-EM. Finally, we also developed a confidence metric for which all (26/26) proteins flagged as high confidence were accurately predicted.

Parkin is an E3 ligase for the ubiquitin-like modifier FAT10, which inhibits Parkin activation and mitophagy

Parkin is an E3 ubiquitin ligase belonging to the RING-between-RING family. Mutations in the Parkin-encoding gene PARK2 are associated with familial Parkinson's disease. Here, we investigate the interplay between Parkin and the inflammatory cytokine-induced ubiquitin-like modifier FAT10. FAT10 targets hundreds of proteins for degradation by the 26S proteasome. We show that FAT10 gets conjugated to Parkin and mediates its degradation in a proteasome-dependent manner. Parkin binds to the E2 enzyme of FAT10 (USE1), auto-FAT10ylates itself, and facilitates FAT10ylation of the Parkin substrate Mitofusin2 in vitro and in cells, thus identifying Parkin as a FAT10 E3 ligase. On mitochondrial depolarization, FAT10ylation of Parkin inhibits its activation and ubiquitin-ligase activity causing impairment of mitophagy progression and aggravation of rotenone-mediated death of dopaminergic neuronal cells. In conclusion, FAT10ylation inhibits Parkin and mitophagy rendering FAT10 a likely inflammation-induced exacerbating factor and potential drug target for Parkinson's disease.

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

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

Regulatory inter-domain interactions influence Hsp70 recruitment to the DnaJB8 chaperone

The Hsp40/Hsp70 chaperone families combine versatile folding capacity with high substrate specificity, which is mainly facilitated by Hsp40s. The structure and function of many Hsp40s remain poorly understood, particularly oligomeric Hsp40s that suppress protein aggregation. Here, we used a combination of biochemical and structural approaches to shed light on the domain interactions of the Hsp40 DnaJB8, and how they may influence recruitment of partner Hsp70s. We identify an interaction between the J-Domain (JD) and C-terminal domain (CTD) of DnaJB8 that sequesters the JD surface, preventing Hsp70 interaction. We propose a model for DnaJB8-Hsp70 recruitment, whereby the JD-CTD interaction of DnaJB8 acts as a reversible switch that can control the binding of Hsp70. These findings suggest that the evolutionarily conserved CTD of DnaJB8 is a regulatory element of chaperone activity in the proteostasis network.

Protein composition and biochemical characterization of venom from Sonoran Coral Snakes (Micruroides euryxanthus)

The elapid genus, Micruroides, is considered the sister clade of all New World coral snakes (Genus Micrurus), is monotypic, and is represented by Sonoran Coral Snakes, Micruroides euryxanthus. Coral snakes of the genus Micrurus have been reported to have venoms that are predominantly composed of phospholipases A₂ (PLA₂) or three finger toxins (3FTx), but the venoms of the genus Micruroides are almost completely unstudied. Here, we present the first description of the venom of M. euryxanthus including identification of some proteins as well as transcriptomic, and biological activity assays. The most abundant components within M. euryxanthus venom are 3FTxs (62.3%) and there was relatively low proportion of PLA₂s (14.2%). The venom phenotype supports the hypothesis that the common ancestor of Micrurus and Micruroides had a 3FTx-dominated venom. Within the venom, there were two nearly identical α-neurotoxins (α-Ntx), one of which was designated Eurytoxin, that account for approximately 60% of the venom's lethality to mice. Eurytoxin was cloned, expressed in a soluble and active form, and used to produce rabbit hyperimmune serum. This allowed the analysis of its immunochemical properties, showing them to be different from the recombinant αNTx D.H., present in the venoms of some species of Micrurus. Finally, we observed that the commercial antivenom produced in Mexico for coral snake envenomation is unable to neutralize the lethality from M. euryxanthus venom. This work allowed the classification of Micruroides venom into the 3FTx-predominant group and identified the main components responsible for toxicity to mice.

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Quantitative Cross-Linking of Proteins and Protein Complexes

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

Hybrid methods for combined experimental and computational determination of protein structure

Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles

Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper's transparent peer review process is included in the Supplemental Information.

Alternative proteins are functional regulators in cell reprogramming by PKA activation

It has been recently shown that many proteins are lacking from reference databases used in mass spectrometry analysis, due to their translation templated on alternative open reading frames. This questions our current understanding of gene annotation and drastically expands the theoretical proteome complexity. The functions of these alternative proteins (AltProts) still remain largely unknown. We have developed a large-scale and unsupervised approach based on cross-linking mass spectrometry (XL-MS) followed by shotgun proteomics to gather information on the functional role of AltProts by mapping them back into known signalling pathways through the identification of their reference protein (RefProt) interactors. We have identified and profiled AltProts in a cancer cell reprogramming system: NCH82 human glioma cells after 0, 16, 24 and 48 h Forskolin stimulation. Forskolin is a protein kinase A activator inducing cell differentiation and epithelial–mesenchymal transition. Our data show that AltMAP2, AltTRNAU1AP and AltEPHA5 interactions with tropomyosin 4 are downregulated under Forskolin treatment. In a wider perspective, Gene Ontology and pathway enrichment analysis (STRING) revealed that RefProts associated with AltProts are enriched in cellular mobility and transfer RNA regulation. This study strongly suggests novel roles of AltProts in multiple essential cellular functions and supports the importance of considering them in future biological studies.

Identification of Small-Molecule Activators of the Ubiquitin Ligase E6AP/UBE3A and Angelman Syndrome-Derived E6AP/UBE3A Variants

Genetic aberrations of the UBE3A gene encoding the E3 ubiquitin ligase E6AP underlie the development of Angelman syndrome (AS). Approximately 10% of AS individuals harbor UBE3A genes with point mutations, frequently resulting in the expression of full-length E6AP variants with defective E3 activity. Since E6AP exists in two states, an inactive and an active one, we hypothesized that distinct small molecules can stabilize the active state and that such molecules may rescue the E3 activity of AS-derived E6AP variants. Therefore, we established an assay that allows identifying modulators of E6AP in a high-throughput format. We identified several compounds that not only stimulate wild-type E6AP but also rescue the E3 activity of certain E6AP variants. Moreover, by chemical cross-linking coupled to mass spectrometry we provide evidence that the compounds stabilize an active conformation of E6AP. Thus, these compounds represent potential lead structures for the design of drugs for AS treatment.

Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications

Proteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein higher-order structures and dynamics requires integrated approaches, where mass spectrometry (MS) is now positioned to play a key role. One of those approaches is protein footprinting. Although the initial demonstration of footprinting was for the HOS determination of protein/nucleic acid binding, the concept was later adapted to MS-based protein HOS analysis, through which different covalent labeling approaches "mark" the solvent accessible surface area (SASA) of proteins to reflect protein HOS. Hydrogen-deuterium exchange (HDX), where deuterium in D2O replaces hydrogen of the backbone amides, is the most common example of footprinting. Its advantage is that the footprint reflects SASA and hydrogen bonding, whereas one drawback is the labeling is reversible. Another example of footprinting is slow irreversible labeling of functional groups on amino acid side chains by targeted reagents with high specificity, probing structural changes at selected sites. A third footprinting approach is by reactions with fast, irreversible labeling species that are highly reactive and footprint broadly several amino acid residue side chains on the time scale of submilliseconds. All of these covalent labeling approaches combine to constitute a problem-solving toolbox that enables mass spectrometry as a valuable tool for HOS elucidation. As there has been a growing need for MS-based protein footprinting in both academia and industry owing to its high throughput capability, prompt availability, and high spatial resolution, we present a summary of the history, descriptions, principles, mechanisms, and applications of these covalent labeling approaches. Moreover, their applications are highlighted according to the biological questions they can answer. This review is intended as a tutorial for MS-based protein HOS elucidation and as a reference for investigators seeking a MS-based tool to address structural questions in protein science.

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

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

High-density chemical cross-linking for modeling protein interactions

Detailed mechanistic understanding of protein complex function is greatly enhanced by insights from its 3-dimensional structure. Traditional methods of protein structure elucidation remain expensive and labor-intensive and require highly purified starting material. Chemical cross-linking coupled with mass spectrometry offers an alternative that has seen increased use, especially in combination with other experimental approaches like cryo-electron microscopy. Here we report advances in method development, combining several orthogonal cross-linking chemistries as well as improvements in search algorithms, statistical analysis, and computational cost to achieve coverage of 1 unique cross-linked position pair for every 7 amino acids at a 1% false discovery rate. This is accomplished without any peptide-level fractionation or enrichment. We apply our methods to model the complex between a carbonic anhydrase (CA) and its protein inhibitor, showing that the cross-links are self-consistent and define the interaction interface at high resolution. The resulting model suggests a scaffold for development of a class of protein-based inhibitors of the CA family of enzymes. We next cross-link the yeast proteasome, identifying 3,893 unique cross-linked peptides in 3 mass spectrometry runs. The dataset includes 1,704 unique cross-linked position pairs for the proteasome subunits, more than half of them intersubunit. Using multiple recently solved cryo-EM structures, we show that observed cross-links reflect the conformational dynamics and disorder of some proteasome subunits. We further demonstrate that this level of cross-linking density is sufficient to model the architecture of the 19-subunit regulatory particle de novo.

Proper evaluation of chemical cross-linking-based spatial restraints improves the precision of modeling homo-oligomeric protein complexes

Background

The function of oligomeric proteins is inherently linked to their quaternary structure. In the absence of high-resolution data, low-resolution information in the form of spatial restraints can significantly contribute to the precision and accuracy of structural models obtained using computational approaches. To obtain such restraints, chemical cross-linking coupled with mass spectrometry (XL-MS) is commonly used. However, the use of XL-MS in the modeling of protein complexes comprised of identical subunits (homo-oligomers) is often hindered by the inherent ambiguity of intra- and inter-subunit connection assignment.

Results

We present a comprehensive evaluation of (1) different methods for inter-residue distance calculations, and (2) different approaches for the scoring of spatial restraints. Our results show that using Solvent Accessible Surface distances (SASDs) instead of Euclidean distances (EUCs) greatly reduces the assignation ambiguity and delivers better modeling precision. Furthermore, ambiguous connections should be considered as inter-subunit only when the intra-subunit alternative exceeds the distance threshold. Modeling performance can also be improved if symmetry, characteristic for most homo-oligomers, is explicitly defined in the scoring function.

Conclusions

Our findings provide guidelines for proper evaluation of chemical cross-linking-based spatial restraints in modeling homo-oligomeric protein complexes, which could facilitate structural characterization of this important group of proteins.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3032-x) contains supplementary material, which is available to authorized users.

The ubiquitin-like modifier FAT10 interferes with SUMO activation

The covalent attachment of the cytokine-inducible ubiquitin-like modifier HLA-F adjacent transcript 10 (FAT10) to hundreds of substrate proteins leads to their rapid degradation by the 26 S proteasome independently of ubiquitylation. Here, we identify another function of FAT10, showing that it interferes with the activation of SUMO1/2/3 in vitro and down-regulates SUMO conjugation and the SUMO-dependent formation of promyelocytic leukemia protein (PML) bodies in cells. Mechanistically, we show that FAT10 directly binds to and impedes the activity of the heterodimeric SUMO E1 activating enzyme AOS1/UBA2 by competing very efficiently with SUMO for activation and thioester formation. Nevertheless, activation of FAT10 by AOS1/UBA2 does not lead to covalent conjugation of FAT10 with substrate proteins which relies on its cognate E1 enzyme UBA6. Hence, we report that one ubiquitin-like modifier (FAT10) inhibits the conjugation and function of another ubiquitin-like modifier (SUMO) by impairing its activation.

FAT10 is an ubiquitin-like modifier that targets proteins to proteasomal degradation. Here, the authors show that FAT10 also regulates SUMO activation in vitro and in cells, providing evidence for functional crosstalk between two ubiquitin-like modifiers.

Early Scanning of Nascent Polypeptides inside the Ribosomal Tunnel by NAC

Cotranslational processing of newly synthesized proteins is fundamental for correct protein maturation. Protein biogenesis factors are thought to bind nascent polypeptides not before they exit the ribosomal tunnel. Here, we identify a nascent chain recognition mechanism deep inside the ribosomal tunnel by an essential eukaryotic cytosolic chaperone. The nascent polypeptide-associated complex (NAC) inserts the N-terminal tail of its β subunit (N-βNAC) into the ribosomal tunnel to sense substrates directly upon synthesis close to the peptidyl-transferase center. N-βNAC escorts the growing polypeptide to the cytosol and relocates to an alternate binding site on the ribosomal surface. Using C. elegans as an in vivo model, we demonstrate that the tunnel-probing activity of NAC is essential for organismal viability and critical to regulate endoplasmic reticulum (ER) protein transport by controlling ribosome-Sec61 translocon interactions. Thus, eukaryotic protein maturation relies on the early sampling of nascent chains inside the ribosomal tunnel.

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

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

Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry

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

Integrative Structure Modeling: Overview and Assessment

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Probing H2O2-mediated Structural Dynamics of the Human 26S Proteasome Using Quantitative Cross-linking Mass Spectrometry (QXL-MS)

Cytotoxic protein aggregation-induced impairment of cell function and homeostasis are hallmarks of age-related neurodegenerative pathologies. As proteasomal degradation represents the major clearance pathway for oxidatively damaged proteins, a detailed understanding of the molecular events underlying its stress response is critical for developing strategies to maintain cell viability and function. Although the 26S proteasome has been shown to disassemble during oxidative stress, its conformational dynamics remains unclear. To this end, we have developed a new quantitative cross-linking mass spectrometry (QXL-MS) workflow to explore the structural dynamics of proteasome complexes in response to oxidative stress. This strategy comprises SILAC-based metabolic labeling, HB tag-based affinity purification, a 2-step cross-linking reaction consisting of mild in vivo formaldehyde and on-bead DSSO cross-linking, and multi-stage tandem mass spectrometry (MSⁿ) to identify and quantify cross-links. This integrated workflow has been successfully applied to explore the molecular events underlying oxidative stress-dependent proteasomal regulation by comparative analyses of proteasome complex topologies from treated and untreated cells. Our results show that H₂O₂ treatment weakens the 19S-20S interaction within the 26S proteasome, along with reorganizations within the 19S and 20S subcomplexes. Altogether, this work sheds light on the mechanistic response of the 26S to acute oxidative stress, suggesting an intermediate proteasomal state(s) before H₂O₂-mediated dissociation of the 26S. The QXL-MS strategy presented here can be applied to study conformational changes of other protein complexes under different physiological conditions.

A conserved filamentous assembly underlies the structure of the meiotic chromosome axis

The meiotic chromosome axis plays key roles in meiotic chromosome organization and recombination, yet the underlying protein components of this structure are highly diverged. Here, we show that 'axis core proteins' from budding yeast (Red1), mammals (SYCP2/SYCP3), and plants (ASY3/ASY4) are evolutionarily related and play equivalent roles in chromosome axis assembly. We first identify 'closure motifs' in each complex that recruit meiotic HORMADs, the master regulators of meiotic recombination. We next find that axis core proteins form homotetrameric (Red1) or heterotetrameric (SYCP2:SYCP3 and ASY3:ASY4) coiled-coil assemblies that further oligomerize into micron-length filaments. Thus, the meiotic chromosome axis core in fungi, mammals, and plants shares a common molecular architecture, and likely also plays conserved roles in meiotic chromosome axis assembly and recombination control.

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

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

Structural dynamics of the E6AP/UBE3A-E6-p53 enzyme-substrate complex

Deregulation of the ubiquitin ligase E6AP is causally linked to the development of human disease, including cervical cancer. In complex with the E6 oncoprotein of human papillomaviruses, E6AP targets the tumor suppressor p53 for degradation, thereby contributing to carcinogenesis. Moreover, E6 acts as a potent activator of E6AP by a yet unknown mechanism. However, structural information explaining how the E6AP-E6-p53 enzyme-substrate complex is assembled, and how E6 stimulates E6AP, is largely missing. Here, we develop and apply different crosslinking mass spectrometry-based approaches to study the E6AP-E6-p53 interplay. We show that binding of E6 induces conformational rearrangements in E6AP, thereby positioning E6 and p53 in the immediate vicinity of the catalytic center of E6AP. Our data provide structural and functional insights into the dynamics of the full-length E6AP-E6-p53 enzyme-substrate complex, demonstrating how E6 can stimulate the ubiquitin ligase activity of E6AP while facilitating ubiquitin transfer from E6AP onto p53.

Chromatographic separation strategies for precision mass spectrometry to study protein-protein interactions and protein phosphorylation

Investigating protein-protein interactions and protein phosphorylation can be of great significance when studying biological processes and human diseases at the molecular level. However, sample complexity, presence of low abundance proteins, and dynamic nature of the proteins often impede in achieving sufficient analytical depth in proteomics research. In this regard, chromatographic separation methodologies have played a vital role in the identification and quantification of proteins in complex sample mixtures. The combination of peptide and protein fractionation techniques with advanced high-performance mass spectrometry has allowed the researchers to successfully study the protein-protein interactions and protein phosphorylation. Several new fractionation strategies for large scale analysis of proteins and peptides have been developed to study protein-protein interactions and protein phosphorylation. These emerging chromatography methodologies have enabled the identification of several hundred protein complexes and even thousands of phosphorylation sites in a single study. In this review, we focus on current workflow strategies and chromatographic tools, highlighting their advantages and disadvantages, and examining their associated challenges and future potential.

Protein Dynamics in Solution by Quantitative Crosslinking/Mass Spectrometry

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

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

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

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

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

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

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

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

Rosetta Protein Structure Prediction from Hydroxyl Radical Protein Footprinting Mass Spectrometry Data

In recent years mass spectrometry-based covalent labeling techniques such as hydroxyl radical footprinting (HRF) have emerged as valuable structural biology techniques, yielding information on protein tertiary structure. These data, however, are not sufficient to predict protein structure unambiguously, as they provide information only on the relative solvent exposure of certain residues. Despite some recent advances, no software currently exists that can utilize covalent labeling mass spectrometry data to predict protein tertiary structure. We have developed the first such tool, which incorporates mass spectrometry derived protection factors from HRF labeling as a new centroid score term for the Rosetta scoring function to improve the prediction of protein tertiary structures. We tested our method on a set of four soluble benchmark proteins with known crystal structures and either published HRF experimental results or internally acquired data. Using the HRF labeling data, we rescored large decoy sets of structures predicted with Rosetta for each of the four benchmark proteins. As a result, the model quality improved for all benchmark proteins as compared to when scored with Rosetta alone. For two of the four proteins we were even able to identify atomic resolution models with the addition of HRF data.

Chemical cross-linking in the structural analysis of protein assemblies

For decades, chemical cross-linking of proteins has been an established method to study protein interaction partners. The chemical cross-linking approach has recently been revived by mass spectrometric analysis of the cross-linking reaction products. Chemical cross-linking and mass spectrometric analysis (CXMS) enables the identification of residues that are close in three-dimensional (3D) space but not necessarily close in primary sequence. Therefore, this approach provides medium resolution information to guide de novo structure prediction, protein interface mapping and protein complex model building. The robustness and compatibility of the CXMS approach with multiple biochemical methods have made it especially appealing for challenging systems with multiple biochemical compositions and conformation states. This review provides an overview of the CXMS approach, describing general procedures in sample processing, data acquisition and analysis. Selection of proper chemical cross-linking reagents, strategies for cross-linked peptide identification, and successful application of CXMS in structural characterization of proteins and protein complexes are discussed.

On the Reproducibility of Label-Free Quantitative Cross-Linking/Mass Spectrometry

Quantitative cross-linking/mass spectrometry (QCLMS) is an emerging approach to study conformational changes of proteins and multi-subunit complexes. Distinguishing protein conformations requires reproducibly identifying and quantifying cross-linked peptides. Here we analyzed the variation between multiple cross-linking reactions using bis[sulfosuccinimidyl] suberate (BS³)-cross-linked human serum albumin (HSA) and evaluated how reproducible cross-linked peptides can be identified and quantified by LC-MS analysis. To make QCLMS accessible to a broader research community, we developed a workflow that integrates the established software tools MaxQuant for spectra preprocessing, Xi for cross-linked peptide identification, and finally Skyline for quantification (MS1 filtering). Out of the 221 unique residue pairs identified in our sample, 124 were subsequently quantified across 10 analyses with coefficient of variation (CV) values of 14% (injection replica) and 32% (reaction replica). Thus our results demonstrate that the reproducibility of QCLMS is in line with the reproducibility of general quantitative proteomics and we establish a robust workflow for MS1-based quantitation of cross-linked peptides. Graphical Abstract ᅟ.

Structures of human PRC2 with its cofactors AEBP2 and JARID2

Transcriptionally repressive histone H3 lysine 27 methylation by Polycomb repressive complex 2 (PRC2) is essential for cellular differentiation and development. Here we report cryo-electron microscopy structures of human PRC2 in a basal state and two distinct active states while in complex with its cofactors JARID2 and AEBP2. Both cofactors mimic the binding of histone H3 tails. JARID2, methylated by PRC2, mimics a methylated H3 tail to stimulate PRC2 activity, whereas AEBP2 interacts with the RBAP48 subunit, mimicking an unmodified H3 tail. SUZ12 interacts with all other subunits within the assembly and thus contributes to the stability of the complex. Our analysis defines the complete architecture of a functionally relevant PRC2 and provides a structural framework to understand its regulation by cofactors, histone tails, and RNA.

Structural Investigation of Proteins and Protein Complexes by Chemical Cross-Linking/Mass Spectrometry

During the last two decades, cross-linking combined with mass spectrometry (MS) has evolved as a valuable tool to gain structural insights into proteins and protein assemblies. Structural information is obtained by introducing covalent connections between amino acids that are in spatial proximity in proteins and protein complexes. The distance constraints imposed by the cross-linking reagent provide information on the three-dimensional arrangement of the covalently connected amino acid residues and serve as basis for de-novo or homology modeling approaches. As cross-linking/MS allows investigating protein 3D-structures and protein-protein interactions not only in-vitro, but also in-vivo, it is especially appealing for studying protein systems in their native environment. In this chapter, we describe the principles of cross-linking/MS and illustrate its value for investigating protein 3D-structures and for unraveling protein interaction networks.

Spontaneous and specific chemical cross-linking in live cells to capture and identify protein interactions

Covalently locking interacting proteins in situ is an attractive strategy for addressing the challenge of identifying weak and transient protein interactions, yet it is demanding to execute chemical reactions in live systems in a biocompatible, specific, and autonomous manner. Harnessing proximity-enabled reactivity of an unnatural amino acid incorporated in the bait toward a target residue of unknown proteins, here we genetically encode chemical cross-linkers (GECX) to cross-link interacting proteins spontaneously and selectively in live cells. Obviating an external trigger for reactivity and affording residue specificity, GECX enables the capture of low-affinity protein binding (affibody with Z protein), elusive enzyme-substrate interaction (ubiquitin-conjugating enzyme UBE2D3 with substrate PCNA), and endogenous proteins interacting with thioredoxin in E. coli cells, allowing for mass spectrometric identification of interacting proteins and crosslinking sites. This live cell chemistry-based approach should be valuable for investigating currently intangible protein interactions in vivo for better understanding of biology in physiological settings.

Proteins associate via weak and transient interactions that are challenging to identify in vivo. Here, the authors use a genetically encoded chemical cross-linker to covalently lock interacting proteins in live cells, allowing them to identify the captured proteins by mass spectrometry.

In Vivo Conformational Dynamics of Hsp90 and Its Interactors

Hsp90 belongs to a family of some of the most highly expressed heat shock proteins that function as molecular chaperones to protect the proteome not only from the heat shock but also from other misfolding events. As many client proteins of Hsp90 are involved in oncogenesis, this chaperone has been the focus of intense research efforts. Yet, we lack structural information for how Hsp90 interacts with co-chaperones and client proteins. Here, we developed a mass-spectrometry-based approach that allowed quantitative measurements of in vitro and in vivo effects of small-molecule inhibitors on Hsp90 conformation, and interaction with co-chaperones and client proteins. From this analysis, we were able to derive structural models for how Hsp90 engages its interaction partners in vivo, and how different drugs affect these structures. In addition, the methodology described here offers a new approach to probe the effects of virtually any inhibitor treatment on the proteome level.