Cross-linking Mass Spectrometry Analysis of the Yeast Nucleus Reveals Extensive Protein-Protein Interactions Not Detected by Systematic Two-Hybrid or Affinity Purification-Mass Spectrometry

Integrating cellular electron microscopy with multimodal data to explore biology across space and time

Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.

Capturing the hierarchically assorted modules of protein-protein interactions in the organized nucleome

Nuclear proteins are major constituents and key regulators of nucleome topological organization and manipulators of nuclear events. To decipher the global connectivity of nuclear proteins and the hierarchically organized modules of their interactions, we conducted two rounds of cross-linking mass spectrometry (XL-MS) analysis, one of which followed a quantitative double chemical cross-linking mass spectrometry (in vivoqXL-MS) workflow, and identified 24,140 unique crosslinks in total from the nuclei of soybean seedlings. This in vivo quantitative interactomics enabled the identification of 5340 crosslinks that can be converted into 1297 nuclear protein-protein interactions (PPIs), 1220 (94%) of which were non-confirmative (or novel) nuclear PPIs compared with those in repositories. There were 250 and 26 novel interactors of histones and the nucleolar box C/D small nucleolar ribonucleoprotein complex, respectively. Modulomic analysis of orthologous Arabidopsis PPIs produced 27 and 24 master nuclear PPI modules (NPIMs) that contain the condensate-forming protein(s) and the intrinsically disordered region-containing proteins, respectively. These NPIMs successfully captured previously reported nuclear protein complexes and nuclear bodies in the nucleus. Surprisingly, these NPIMs were hierarchically assorted into four higher-order communities in a nucleomic graph, including genome and nucleolus communities. This combinatorial pipeline of 4C quantitative interactomics and PPI network modularization revealed 17 ethylene-specific module variants that participate in a broad range of nuclear events. The pipeline was able to capture both nuclear protein complexes and nuclear bodies, construct the topological architectures of PPI modules and module variants in the nucleome, and probably map the protein compositions of biomolecular condensates.

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein-protein interactions in the human cell

Significant recent advances in structural biology, particularly in the field of cryoelectron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability, or-in the case of complexes-simply not having yet been analyzed. Here, we demonstrate the power of using cross-linking mass spectrometry (XL-MS) for the high-throughput experimental assessment of the structures of proteins and protein complexes. This included those produced by high-resolution but in vitro experimental data, as well as in silico predictions based on amino acid sequence alone. We present the largest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein-protein interactions. We show that models of proteins and their complexes predicted by AlphaFold2, and inspired and corroborated by the XL-MS data, offer opportunities to deeply mine the structural proteome and interactome and reveal mechanisms underlying protein structure and function.

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

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

Identifying and characterising Thrap3, Bclaf1 and Erh interactions using cross-linking mass spectrometry

Background: Cross-linking mass spectrometry (XL-MS) is a powerful technology capable of yielding structural insights across the complex cellular protein interaction network. However, up to date most of the studies utilising XL-MS to characterise individual protein complexes' topology have been carried out on over-expressed or recombinant proteins, which might not accurately represent native cellular conditions. Methods: We performed XL-MS using MS-cleavable crosslinker disuccinimidyl sulfoxide (DSSO) after immunoprecipitation of endogenous BRG/Brahma-associated factors (BAF) complex and co-purifying proteins. Data are available via ProteomeXchange with identifier PXD027611. Results: Although we did not detect the expected enrichment of crosslinks within the BAF complex, we identified numerous crosslinks between three co-purifying proteins, namely Thrap3, Bclaf1 and Erh. Thrap3 and Bclaf1 are mostly disordered proteins for which no 3D structure is available. The XL data allowed us to map interaction surfaces on these proteins, which overlap with the non-disordered portions of both proteins. The identified XLs are in agreement with homology-modelled structures suggesting that the interaction surfaces are globular. Conclusions: Our data shows that MS-cleavable crosslinker DSSO can be used to characterise in detail the topology and interaction surfaces of endogenous protein complexes without the need for overexpression. We demonstrate that Bclaf1, Erh and Thrap3 interact closely with each other, suggesting they might form a novel complex, hereby referred to as BET complex. This data can be exploited for modelling protein-protein docking to characterise the three-dimensional structure of the complex. Endogenous XL-MS might be challenging due to crosslinker accessibility, protein complex abundance or isolation efficiency, and require further optimisation for some complexes like the BAF complex to detect a substantial number of crosslinks.

Identifying and characterising Thrap3, Bclaf1 and Erh interactions using cross-linking mass spectrometry

Background: Cross-linking mass spectrometry (XL-MS) is a powerful technology capable of yielding structural insights across the complex cellular protein interaction network. However, up to date most of the studies utilising XL-MS to characterise individual protein complexes' topology have been carried out on over-expressed or recombinant proteins, which might not accurately represent native cellular conditions. Methods: We performed XL-MS using MS-cleavable crosslinker disuccinimidyl sulfoxide (DSSO) after immunoprecipitation of endogenous BRG/Brahma-associated factors (BAF) complex and co-purifying proteins. Data are available via ProteomeXchange with identifier PXD027611. Results: Although we did not detect the expected enrichment of crosslinks within the BAF complex, we identified numerous crosslinks between three co-purifying proteins, namely Thrap3, Bclaf1 and Erh. Thrap3 and Bclaf1 are mostly disordered proteins for which no 3D structure is available. The XL data allowed us to map interaction surfaces on these proteins, which overlap with the non-disordered portions of both proteins. The identified XLs are in agreement with homology-modelled structures suggesting that the interaction surfaces are globular. Conclusions: Our data shows that MS-cleavable crosslinker DSSO can be used to characterise in detail the topology and interaction surfaces of endogenous protein complexes without the need for overexpression. We demonstrate that Bclaf1, Erh and Thrap3 interact closely with each other, suggesting they might form a novel complex, hereby referred to as TEB complex. This data can be exploited for modelling protein-protein docking to characterise the three-dimensional structure of the complex. Endogenous XL-MS might be challenging due to crosslinker accessibility, protein complex abundance or isolation efficiency, and require further optimisation for some complexes like the BAF complex to detect a substantial number of crosslinks.

Progress in methodologies and quality-control strategies in protein cross-linking mass spectrometry

Deciphering the interaction networks and structural dynamics of proteins is pivotal to better understanding their biological functions. Cross-linking mass spectrometry (XL-MS) is a powerful and increasingly popular technology that provides information about protein-protein interactions and their structural constraints for individual proteins and multiprotein complexes on a proteome-scale. In this review, we first assess the coverage and depth of the XL-MS technique by utilizing publicly available datasets. We then delve into the progress in XL-MS experimental and computational methodologies and examine different quality-control strategies reported in the literature. Finally, we discuss the progress in XL-MS applications along with the scope for future improvements.

Crosslinking mass spectrometry unveils novel interactions and structural distinctions in the model green alga Chlamydomonas reinhardtii

Interactomics is an emerging field that seeks to identify both transient and complex-bound protein interactions that are essential for metabolic functions. Crosslinking mass spectrometry (XL-MS) has enabled untargeted global analysis of these protein networks, permitting largescale simultaneous analysis of protein structure and interactions. Increased commercial availability of highly specific, cell permeable crosslinkers has propelled the study of these critical interactions forward, with the development of MS-cleavable crosslinkers further increasing confidence in identifications. Herein, the global interactome of the unicellular alga Chlamydomonas reinhardtii was analyzed via XL-MS by implementing the MS-cleavable disuccinimidyl sulfoxide (DSSO) crosslinker and enriching for crosslinks using strong cation exchange chromatography. Gentle lysis via repeated freeze-thaw cycles facilitated in vitro analysis of 157 protein-protein crosslinks (interlinks) and 612 peptides linked to peptides of the same protein (intralinks) at 1% FDR throughout the C. reinhardtii proteome. The interlinks confirmed known protein relationships across the cytosol and chloroplast, including coverage on 42% and 38% of the small and large ribosomal subunits, respectively. Of the 157 identified interlinks, 92% represent the first empirical evidence of interaction observed in C. reinhardtii. Several of these crosslinks point to novel associations between proteins, including the identification of a previously uncharacterized Mg-chelatase associated protein (Cre11.g477733.t1.2) bound to seven distinct lysines on Mg-chelatase (Cre06.g306300.t1.2). Additionally, the observed intralinks facilitated characterization of novel protein structures across the C. reinhardtii proteome. Together, these data establish a framework of protein-protein interactions that can be further explored to facilitate understanding of the dynamic protein landscape in C. reinhardtii.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

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.

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Cleavable Cross-Linkers and Mass Spectrometry for the Ultimate Task of Profiling Protein-Protein Interaction Networks in Vivo

Cross-linking mass spectrometry (XL-MS) has matured into a potent tool to identify protein-protein interactions or to uncover protein structures in living cells, tissues, or organelles. The unique ability to investigate the interplay of proteins within their native environment delivers valuable complementary information to other advanced structural biology techniques. This Review gives a comprehensive overview of the current possible applications as well as the remaining limitations of the technique, focusing on cross-linking in highly complex biological systems like cells, organelles, or tissues. Thanks to the commercial availability of most reagents and advances in user-friendly data analysis, validation, and visualization tools, studies using XL-MS can, in theory, now also be utilized by nonexpert laboratories.

Accelerating the Field of Epigenetic Histone Modification Through Mass Spectrometry-Based Approaches

Histone post-translational modifications (PTMs) are one of the main mechanisms of epigenetic regulation. Dysregulation of histone PTMs leads to many human diseases, such as cancer. Because of its high throughput, accuracy, and flexibility, mass spectrometry (MS) has emerged as a powerful tool in the epigenetic histone modification field, allowing the comprehensive and unbiased analysis of histone PTMs and chromatin-associated factors. Coupled with various techniques from molecular biology, biochemistry, chemical biology, and biophysics, MS has been used to characterize distinct aspects of histone PTMs in the epigenetic regulation of chromatin functions. In this review, we will describe advancements in the field of MS that have facilitated the analysis of histone PTMs and chromatin biology.

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Middle–down is the most suitable to study histone combinatorial post-translational modifications.

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Crosslinking MS has a variety of potential applications in exploring histone post-translational modifications.

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Hydrogen–deuterium exchange MS holds great promise to study the compaction of nucleosome.

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Multi-omics approaches are useful to study complex regulatory networks.

Leveraging the Entirety of the Protein Data Bank to Enable Improved Structure Prediction Based on Cross-Link Data

XLinkDB is a fast-expanding public database now storing more than 100 000 distinct identified cross-linked protein residue pairs acquired by chemical cross-linking with mass spectrometry from samples of 12 species (J. Proteome Res. 2019, 18 (2), 753-758). Mapping identified cross-links to protein structures, when available, provides valuable guidance on protein conformations detected in the cross-linked samples. As more and more structures become available in the Protein Data Bank (Nucleic Acids Res. 2000, 28 (1), 235-242), we sought to leverage their utility for cross-link studies by automatically mapping identified cross-links to structures based on sequence homology of the cross-linked proteins with those within structures. This enables use of structures derived from organisms different from those of samples, including large multiprotein complexes and complexes in alternative states. We demonstrate utility of mapping to orthologous structures, highlighting a cross-link between two subunits of mouse mitochondrial Complex I that was mapped to 15 structures derived from five mammals, its distances there of 16.2 ± 0.4 Å indicating strong conservation of the protein interaction. We also show how multimeric structures enable reassessment of cross-links presumed to be intraprotein as potentially homodimeric interprotein in origin.

Structure-based validation can drastically underestimate error rate in proteome-wide cross-linking mass spectrometry studies

Thorough quality assessment of novel interactions identified by proteome-wide cross-linking mass spectrometry (XL-MS) studies is critical. Almost all current XL-MS studies have validated cross-links against known 3D structures of representative protein complexes. Here we provide theoretical and experimental evidence demonstrating this approach can drastically underestimate error rates for proteome-wide XL-MS datasets, and propose a comprehensive set of four data-quality metrics to address this issue.

The current standard approach for estimating error in proteome-scale crosslinking-mass spectrometry datasets has severe limitations. A proposed set of data-quality metrics provides a more accurate assessment of error rate.