MS Annika: A New Cross-Linking Search Engine

Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex

The field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce an algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. We compare our algorithm to other state-of-the-art crosslinking search engines commonly used in the field and conclude that MS Annika unifies high sensitivity, accurate FDR estimation and computational performance, outperforming competing tools. Application of this algorithm enabled us to employ a proteome-wide search of C. elegans nuclei samples, where we were able to uncover previously unknown protein interactions and conclude a comprehensive structural analysis that provides a detailed view of the Box C/D complex. Moreover, our algorithm will enable researchers to conduct similar studies that were previously unfeasible.

Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics

Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results.

Mass Spectrometry Structural Proteomics Enabled by Limited Proteolysis and Cross-Linking

The exploration of protein structure and function stands at the forefront of life science and represents an ever-expanding focus in the development of proteomics. As mass spectrometry (MS) offers readout of protein conformational changes at both the protein and peptide levels, MS-based structural proteomics is making significant strides in the realms of structural and molecular biology, complementing traditional structural biology techniques. This review focuses on two powerful MS-based techniques for peptide-level readout, namely limited proteolysis-mass spectrometry (LiP-MS) and cross-linking mass spectrometry (XL-MS). First, we discuss the principles, features, and different workflows of these two methods. Subsequently, we delve into the bioinformatics strategies and software tools used for interpreting data associated with these protein conformation readouts and how the data can be integrated with other computational tools. Furthermore, we provide a comprehensive summary of the noteworthy applications of LiP-MS and XL-MS in diverse areas including neurodegenerative diseases, interactome studies, membrane proteins, and artificial intelligence-based structural analysis. Finally, we discuss the factors that modulate protein conformational changes. We also highlight the remaining challenges in understanding the intricacies of protein conformational changes by LiP-MS and XL-MS technologies.

xiVIEW: Visualisation of Crosslinking Mass Spectrometry Data

Crosslinking mass spectrometry (MS) has emerged as an important technique for elucidating the in-solution structures of protein complexes and the topology of protein-protein interaction networks. However, the expanding user community lacked an integrated visualisation tool that helped them make use of the crosslinking data for investigating biological mechanisms. We addressed this need by developing xiVIEW, a web-based application designed to streamline crosslinking MS data analysis, which we present here. xiVIEW provides a user-friendly interface for accessing coordinated views of mass spectrometric data, network visualisation, annotations extracted from trusted repositories like UniProtKB, and available 3D structures. In accordance with recent recommendations from the crosslinking MS community, xiVIEW (i) provides a standards compliant parser to improve data integration and (ii) offers accessible visualisation tools. By promoting the adoption of standard file formats and providing a comprehensive visualisation platform, xiVIEW empowers both experimentalists and modellers alike to pursue their respective research interests. We anticipate that xiVIEW will advance crosslinking MS-inspired research, and facilitate broader and more effective investigations into complex biological systems.

Structural proteomics of a bacterial mega membrane protein complex: FtsH-HflK-HflC

Recent advances in mass spectrometry (MS) yielding sensitive and accurate measurements along with developments in software tools have enabled the characterization of complex systems routinely. Thus, structural proteomics and cross-linking mass spectrometry (XL-MS) have become a useful method for structural modeling of protein complexes. Here, we utilized commonly used XL-MS software tools to elucidate the protein interactions within a membrane protein complex containing FtsH, HflK, and HflC, over-expressed in E. coli. The MS data were processed using MaxLynx, MeroX, MS Annika, xiSEARCH, and XlinkX software tools. The number of identified inter- and intra-protein cross-links varied among software. Each interaction was manually checked using the raw MS and MS/MS data and distance restraints to verify inter- and intra-protein cross-links. A total of 37 inter-protein and 148 intra-protein cross-links were determined in the FtsH-HflK-HflC complex. The 59 of them were new interactions on the lacking region of recently published structures. These newly identified interactions, when combined with molecular docking and structural modeling, present opportunities for further investigation. The results provide valuable information regarding the complex structure and function to decipher the intricate molecular mechanisms underlying the FtsH-HflK-HflC complex.

New advances in cross-linking mass spectrometry toward structural systems biology

Elucidating protein-protein interaction (PPI) networks and their structural features within cells is central to understanding fundamental biology and associations of cell phenotypes with human pathologies. Owing to technological advancements during the last decade, cross-linking mass spectrometry (XL-MS) has become an enabling technology for delineating interaction landscapes of proteomes as they exist in living systems. XL-MS is unique due to its capability to simultaneously capture PPIs from native environments and uncover interaction contacts though identification of cross-linked peptides, thereby permitting the determination of both identity and connectivity of PPIs in cells. In combination with high resolution structural tools such as cryo-electron microscopy and AI-assisted prediction, XL-MS has contributed significantly to elucidating architectures of large protein assemblies. This review highlights the latest developments in XL-MS technologies and their applications in proteome-wide analysis to advance structural systems biology.

Innovation in Cross-Linking Mass Spectrometry Workflows: Toward a Comprehensive, Flexible, and Customizable Data Analysis Platform

Cross-linking mass spectrometry (XL-MS) is widely used in the analysis of protein structure and protein-protein interactions (PPIs). Throughout the entire workflow, the utilization of cross-linkers and the interpretation of cross-linking data are the core steps. In recent years, the development of cross-linkers and analytical software mostly follow up on the classical models of non-cleavable cross-linkers such as BS3/DSS and MS-cleavable cross-linkers such as DSSO. Although such a paradigm promotes the maturity and robustness of the XL-MS field, it confines the innovation and flexibility of new cross-linkers and analytical software. This critical insight will discuss the classification, advantages, and disadvantages of existing data analysis search engines. Take the new platinum-based metal cross-linker as an example, potential pitfalls in characterization of cross-linked peptides using existing software are discussed. Finally, ideas on developing more flexible, comprehensive, and user-friendly cross-linkers and software tools are proposed.

MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity

Cross-linking mass spectrometry has become a powerful tool for the identification of protein-protein interactions and for gaining insight into the structures of proteins. We previously published MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable cross-linkers. In this publication, we present MS Annika 2.0, an updated version implementing a new search algorithm that, in addition to MS2 level, only supports the processing of data from MS2-MS3-based approaches for the identification of peptides from MS3 spectra, and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. All mass spectrometry proteomics data along with result files have been deposited to the ProteomeXchange consortium via the PRIDE partner repository with the dataset identifier PXD041955.

Comparative Analysis of Chemical Cross-Linking Mass Spectrometry Data Indicates That Protein STY Residues Rarely React with N-Hydroxysuccinimide Ester Cross-Linkers

When it comes to mass spectrometry data analysis for identification of peptide pairs linked by N-hydroxysuccinimide (NHS) ester cross-linkers, search engines bifurcate in their setting of cross-linkable sites. Some restrict NHS ester cross-linkable sites to lysine (K) and protein N-terminus, referred to as K only for short, whereas others additionally include serine (S), threonine (T), and tyrosine (Y) by default. Here, by setting amino acids with chemically inert side chains such as glycine (G), valine (V), and leucine (L) as cross-linkable sites, which serves as a negative control, we show that software-identified STY-cross-links are only as reliable as GVL-cross-links. This is true across different NHS ester cross-linkers including DSS, DSSO, and DSBU, and across different search engines including MeroX, xiSearch, and pLink. Using a published data set originated from synthetic peptides, we demonstrate that STY-cross-links indeed have a high false discovery rate. Further analysis revealed that depending on the data and the search engine used to analyze the data, up to 65% of the STY-cross-links identified are actually K-K cross-links of the same peptide pairs, up to 61% are actually K-mono-links, and the rest tend to contain short peptides at high risk of false identification.

Real-Time Library Search Increases Cross-Link Identification Depth across All Levels of Sample Complexity

Cross-linking mass spectrometry (XL-MS) is a universal tool for probing structural dynamics and protein-protein interactions in vitro and in vivo. Although cross-linked peptides are naturally less abundant than their unlinked counterparts, recent experimental advances improved cross-link identification by enriching the cross-linker-modified peptides chemically with the use of enrichable cross-linkers. However, mono-links (i.e., peptides modified with a hydrolyzed cross-linker) still hinder efficient cross-link identification since a large proportion of measurement time is spent on their MS2 acquisition. Currently, cross-links and mono-links cannot be separated by sample preparation techniques or chromatography because they are chemically almost identical. Here, we found that based on the intensity ratios of four diagnostic peaks when using PhoX/tBu-PhoX cross-linkers, cross-links and mono-links can be partially distinguished. Harnessing their characteristic intensity ratios for real-time library search (RTLS)-based triggering of high-resolution MS2 scans increased the number of cross-link identifications from both single protein samples and intact E. coli cells. Specifically, RTLS improves cross-link identification from unenriched samples and short gradients, emphasizing its advantages in high-throughput approaches and when instrument time or sample amount is limited.

The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data

The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.

Exhaustive Cross-Linking Search with Protein Feedback

Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

Unraveling Structural Information of Multi-Domain Nonribosomal Peptide Synthetases by Using Photo-Cross-Linking Analysis with Genetic Code Expansion

Nonribosomal peptide synthetases (NRPSs) are large, multifunctional enzymes that facilitate the stepwise synthesis of modified peptides, many of which serve as important pharmaceutical products. Typically, NRPSs contain one module for the incorporation of one amino acid into the growing peptide chain. A module consists of the domains required for activation, covalent binding, condensation, termination, and optionally modification of the aminoacyl or peptidyl moiety. We here describe a protocol using genetically encoded photo-cross-linking amino acids to probe the 3D architecture of NRPSs by determining spatial proximity constraints. p-benzoyl-L-phenylalanine (BpF) is incorporated at positions of presumed contact interfaces between domains. The covalent cross-link products are visualized by SDS-PAGE-based methods and precisely mapped by tandem mass spectrometry. Originally intended to study the communication (COM) domains, a special pair of docking domains of unknown structure between two interacting subunits of one NRPS system, this cross-linking approach was also found to be useful to interrogate the spatial proximity of domains that are not connected on the level of the primary structure. The presented photo-cross-linking technique thus provides structural insights complementary to those obtained by protein crystallography and reports on the protein in solution.

A molecular network of conserved factors keeps ribosomes dormant in the egg

Ribosomes are produced in large quantities during oogenesis and are stored in the egg. However, the egg and early embryo are translationally repressed1-4. Here, using mass spectrometry and cryo-electron microscopy analyses of ribosomes isolated from zebrafish (Danio rerio) and Xenopus laevis eggs and embryos, we provide molecular evidence that ribosomes transition from a dormant state to an active state during the first hours of embryogenesis. Dormant ribosomes are associated with four conserved factors that form two modules, consisting of Habp4-eEF2 and death associated protein 1b (Dap1b) or Dap in complex with eIF5a. Both modules occupy functionally important sites and act together to stabilize ribosomes and repress translation. Dap1b (also known as Dapl1 in mammals) is a newly discovered translational inhibitor that stably inserts into the polypeptide exit tunnel. Addition of recombinant zebrafish Dap1b protein is sufficient to block translation and reconstitute the dormant egg ribosome state in a mammalian translation extract in vitro. Thus, a developmentally programmed, conserved ribosome state has a key role in ribosome storage and translational repression in the egg.

Deep Proteome Profiling with Reduced Carryover Using Superficially Porous Microfabricated nanoLC Columns

In the field of liquid chromatography-mass spectrometry (LC-MS)-based proteomics, increases in the sampling depth and proteome coverage have mainly been accomplished by rapid advances in mass spectrometer technology. The comprehensiveness and quality of the data that can be generated do, however, also depend on the performance provided by nano-liquid chromatography (nanoLC) separations. Proper selection of reversed-phase separation columns can be important to provide the MS instrument with peptides at the highest possible concentration and separated at the highest possible resolution. In the current contribution, we evaluate the use of the prototype generation 2 μPAC nanoLC columns, which use C18-functionalized superficially porous micropillars as a stationary phase. When compared to traditionally used fully porous silica stationary phases, more precursors could be characterized when performing single shot data-dependent LC-MS/MS analyses of a human cell line tryptic digest. Up to 30% more protein groups and 60% more unique peptides were identified for short gradients (10 min) and limited sample amounts (10-100 ng of cell lysate digest). With LC-MS gradient times of 10, 60, 120, and 180 min, respectively, we identified 2252, 6513, 7382, and 8174 protein groups with 25, 500, 1000, and 2000 ng of the sample loaded on the column. Reduction of sample carryover to the next run (up to 2 to 3%) and decreased levels of methionine oxidation (up to 3-fold) were identified as additional figures of merit. When analyzing a disuccinimidyl dibutyric urea-crosslinked synthetic library, 29 to 59 more unique crosslinked peptides could be identified at an experimentally validated false discovery rate of 1-2%.

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows

Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.

Optimized TMT-Based Quantitative Cross-Linking Mass Spectrometry Strategy for Large-Scale Interactomic Studies

Cross-linking mass spectrometry (XL-MS) is a powerful method for the investigation of protein-protein interactions (PPI) from highly complex samples. XL-MS combined with tandem mass tag (TMT) labeling holds the promise of large-scale PPI quantification. However, a robust and efficient TMT-based XL-MS quantification method has not yet been established due to the lack of a benchmarking dataset and thorough evaluation of various MS parameters. To tackle these limitations, we generate a two-interactome dataset by spiking in TMT-labeled cross-linked Escherichia coli lysate into TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Using this benchmarking dataset, we assess the efficacy of cross-link identification and accuracy of cross-link quantification using different MS acquisition strategies. For identification, we compare various MS2- and MS3-based XL-MS methods, and optimize stepped higher energy collisional dissociation (HCD) energies for TMT-labeled cross-links. We observed a need for notably higher fragmentation energies compared to unlabeled cross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3-, and synchronous precursor selection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vast number of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexed quantitative PPI characterization from complex biological systems.

Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons

Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.

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

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