Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx

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.

PLK1-mediated phosphorylation cascade activates Mis18 complex to ensure centromere inheritance

Accurate chromosome segregation requires the attachment of microtubules to centromeres, epigenetically defined by the enrichment of CENP-A nucleosomes. During DNA replication, CENP-A nucleosomes undergo dilution. To preserve centromere identity, correct amounts of CENP-A must be restored in a cell cycle-controlled manner orchestrated by the Mis18 complex (Mis18α-Mis18β-Mis18BP1). We demonstrate here that PLK1 interacts with the Mis18 complex by recognizing self-primed phosphorylations of Mis18α (Ser54) and Mis18BP1 (Thr78 and Ser93) through its Polo-box domain. Disrupting these phosphorylations perturbed both centromere recruitment of the CENP-A chaperone HJURP and new CENP-A loading. Biochemical and functional analyses showed that phosphorylation of Mis18α and PLK1 binding were required to activate Mis18α-Mis18β and promote Mis18 complex-HJURP interaction. Thus, our study reveals key molecular events underpinning the licensing role of PLK1 in ensuring accurate centromere inheritance.

Protein assemblies in the Arabidopsis thaliana chloroplast compartment

Introduction

Equipped with a photosynthetic apparatus that uses the energy of solar radiation to fuel biosynthesis of organic compounds, chloroplasts are the metabolic factories of mature leaf cells. The first steps of energy conversion are catalyzed by a collection of protein complexes, which can dynamically interact with each other for optimizing metabolic efficiency under changing environmental conditions.

Materials and methods

For a deeper insight into the organization of protein assemblies and their roles in chloroplast adaption to changing environmental conditions, an improved complexome profiling protocol employing a MS-cleavable cross-linker is used to stabilize labile protein assemblies during the organelle isolation procedure.

Results and discussion

Changes in protein:protein interaction patterns of chloroplast proteins in response to four different light intensities are reported. High molecular mass assemblies of central chloroplast electron transfer chain components as well as the PSII repair machinery react to different light intensities. In addition, the chloroplast encoded RNA-polymerase complex was found to migrate at a molecular mass of ~8 MDa, well above its previously reported molecular mass. Complexome profiling data produced during the course of this study can be interrogated by interested readers via a web-based online resource (https://complexomemap.de/projectsinteraction-chloroplasts).

Chemical cross-linking and mass spectrometry enabled systems-level structural biology

Structural information on protein-protein interactions (PPIs) is essential for improved understanding of regulatory interactome networks that confer various physiological and pathological responses. Additionally, maladaptive PPIs constitute desirable therapeutic targets due to inherently high disease state specificity. Recent advances in chemical cross-linking strategies coupled with mass spectrometry (XL-MS) have positioned XL-MS as a promising technology to not only elucidate the molecular architecture of individual protein assemblies, but also to characterize proteome-wide PPI networks. Moreover, quantitative in vivo XL-MS provides a new capability for the visualization of cellular interactome dynamics elicited by drug treatments, disease states, or aging effects. The emerging field of XL-MS based complexomics enables unique insights on protein moonlighting and protein complex remodeling. These techniques provide complimentary information necessary for in-depth structural interactome studies to better comprehend how PPIs mediate function in living systems.

The small CRL4CSA ubiquitin ligase component DDA1 regulates transcription-coupled repair dynamics

Transcription-blocking DNA lesions are specifically targeted by transcription-coupled nucleotide excision repair (TC-NER), which removes a broad spectrum of DNA lesions to preserve transcriptional output and thereby cellular homeostasis to counteract aging. TC-NER is initiated by the stalling of RNA polymerase II at DNA lesions, which triggers the assembly of the TC-NER-specific proteins CSA, CSB and UVSSA. CSA, a WD40-repeat containing protein, is the substrate receptor subunit of a cullin-RING ubiquitin ligase complex composed of DDB1, CUL4A/B and RBX1 (CRL4CSA). Although ubiquitination of several TC-NER proteins by CRL4CSA has been reported, it is still unknown how this complex is regulated. To unravel the dynamic molecular interactions and the regulation of this complex, we apply a single-step protein-complex isolation coupled to mass spectrometry analysis and identified DDA1 as a CSA interacting protein. Cryo-EM analysis shows that DDA1 is an integral component of the CRL4CSA complex. Functional analysis reveals that DDA1 coordinates ubiquitination dynamics during TC-NER and is required for efficient turnover and progression of this process.

Sequestosome-1 (SQSTM1/p62) as a target in dopamine catabolite-mediated cellular dyshomeostasis

Alterations in the dopamine catabolic pathway are known to contribute to the degeneration of nigrostriatal neurons in Parkinson's disease (PD). The progressive cellular buildup of the highly reactive intermediate 3,4-dihydroxyphenylacetaldehye (DOPAL) generates protein cross-linking, oligomerization of the PD-linked αSynuclein (αSyn) and imbalance in protein quality control. In this scenario, the autophagic cargo sequestome-1 (SQSTM1/p62) emerges as a target of DOPAL-dependent oligomerization and accumulation in cytosolic clusters. Although DOPAL-induced oxidative stress and activation of the Nrf2 pathway promote p62 expression, p62 oligomerization rather seems to be a consequence of direct DOPAL modification. DOPAL-induced p62 clusters are positive for ubiquitin and accumulate within lysosomal-related structures, likely affecting the autophagy-lysosomal functionality. Finally, p62 oligomerization and clustering is synergistically augmented by DOPAL-induced αSyn buildup. Hence, the substantial impact on p62 proteostasis caused by DOPAL appears of relevance for dopaminergic neurodegeneration, in which the progressive failure of degradative pathways and the deposition of proteins like αSyn, ubiquitin and p62 in inclusion bodies represent a major trait of PD pathology.

Chemical Protein Crosslinking-Coupled Mass Spectrometry Reveals Interaction of LHCI with LHCII and LHCSR3 in Chlamydomonas reinhardtii

The photosystem I (PSI) of the green alga Chlamydomonas reinhardtii associates with 10 light-harvesting proteins (LHCIs) to form the PSI-LHCI complex. In the context of state transitions, two LHCII trimers bind to the PSAL, PSAH and PSAO side of PSI to produce the PSI-LHCI-LHCII complex. In this work, we took advantage of chemical crosslinking of proteins in conjunction with mass spectrometry to identify protein-protein interactions between the light-harvesting proteins of PSI and PSII. We detected crosslinks suggesting the binding of LHCBM proteins to the LHCA1-PSAG side of PSI as well as protein-protein interactions of LHCSR3 with LHCA5 and LHCA3. Our data indicate that the binding of LHCII to PSI is more versatile than anticipated and imply that LHCSR3 might be involved in the regulation of excitation energy transfer to the PSI core via LHCA5/LHCA3.

CHCHD4 binding affects the active site of apoptosis inducing factor (AIF): Structural determinants for allosteric regulation

Apoptosis-inducing factor (AIF), which is confined to mitochondria of normal healthy cells, is the first identified caspase-independent cell death effector. Moreover, AIF is required for the optimal functioning of the respiratory chain machinery. Recent findings have revealed that AIF fulfills its pro-survival function by interacting with CHCHD4, a soluble mitochondrial protein which promotes the entrance and the oxidative folding of different proteins in the inner membrane space. Here, we report the crystal structure of the ternary complex involving the N-terminal 27-mer peptide of CHCHD4, NAD+, and AIF harboring its FAD (flavin adenine dinucleotide) prosthetic group in oxidized form. Combining this information with biophysical and biochemical data on the CHCHD4/AIF complex, we provide a detailed structural description of the interaction between the two proteins, validated by both chemical cross-linking mass spectrometry analysis and site-directed mutagenesis.

Methylation of elongation factor 1A by yeast Efm4 or human eEF1A-KMT2 involves a beta-hairpin recognition motif and crosstalks with phosphorylation

Translation elongation factor 1A (eEF1A) is an essential and highly conserved protein required for protein synthesis in eukaryotes. In both Saccharomyces cerevisiae and human, five different methyltransferases methylate specific residues on eEF1A, making eEF1A the eukaryotic protein targeted by the highest number of dedicated methyltransferases after histone H3. eEF1A methyltransferases are highly selective enzymes, only targeting eEF1A and each targeting just one or two specific residues in eEF1A. However, the mechanism of this selectivity remains poorly understood. To reveal how S. cerevisiae elongation factor methyltransferase 4 (Efm4) specifically methylates eEF1A at K316, we have used AlphaFold-Multimer modeling in combination with crosslinking mass spectrometry (XL-MS) and enzyme mutagenesis. We find that a unique beta-hairpin motif, which extends out from the core methyltransferase fold, is important for the methylation of eEF1A K316 in vitro. An alanine mutation of a single residue on this beta-hairpin, F212, significantly reduces Efm4 activity in vitro and in yeast cells. We show that the equivalent residue in human eEF1A-KMT2 (METTL10), F220, is also important for its activity towards eEF1A in vitro. We further show that the eEF1A guanine nucleotide exchange factor, eEF1Bα, inhibits Efm4 methylation of eEF1A in vitro, likely due to competitive binding. Lastly, we find that phosphorylation of eEF1A at S314 negatively crosstalks with Efm4-mediated methylation of K316. Our findings demonstrate how protein methyltransferases can be highly selective towards a single residue on a single protein in the cell.

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.

ECL 3.0: a sensitive peptide identification tool for cross-linking mass spectrometry data analysis

BACKGROUND

Cross-linking mass spectrometry (XL-MS) is a powerful technique for detecting protein-protein interactions (PPIs) and modeling protein structures in a high-throughput manner. In XL-MS experiments, proteins are cross-linked by a chemical reagent (namely cross-linker), fragmented, and then fed into a tandem mass spectrum (MS/MS). Cross-linkers are either cleavable or non-cleavable, and each type requires distinct data analysis tools. However, both types of cross-linkers suffer from imbalanced fragmentation efficiency, resulting in a large number of unidentifiable spectra that hinder the discovery of PPIs and protein conformations. To address this challenge, researchers have sought to improve the sensitivity of XL-MS through invention of novel cross-linking reagents, optimization of sample preparation protocols, and development of data analysis algorithms. One promising approach to developing new data analysis methods is to apply a protein feedback mechanism in the analysis. It has significantly improved the sensitivity of analysis methods in the cleavable cross-linking data. The application of the protein feedback mechanism to the analysis of non-cleavable cross-linking data is expected to have an even greater impact because the majority of XL-MS experiments currently employs non-cleavable cross-linkers.

RESULTS

In this study, we applied the protein feedback mechanism to the analysis of both non-cleavable and cleavable cross-linking data and observed a substantial improvement in cross-link spectrum matches (CSMs) compared to conventional methods. Furthermore, we developed a new software program, ECL 3.0, that integrates two algorithms and includes a user-friendly graphical interface to facilitate wider applications of this new program.

CONCLUSIONS

ECL 3.0 source code is available at https://github.com/yuweichuan/ECL-PF.git . A quick tutorial is available at https://youtu.be/PpZgbi8V2xI .

4D-diaXLMS: Proteome-wide Four-Dimensional Data-Independent Acquisition Workflow for Cross-Linking Mass Spectrometry

Cross-linking mass spectrometry (XL-MS) is a powerful tool for examining protein structures and interactions. Nevertheless, analysis of low-abundance cross-linked peptides is often limited in the data-dependent acquisition (DDA) mode due to its semistochastic nature. To address this issue, we introduced a workflow called 4D-diaXLMS, representing the first-ever application of four-dimensional data-independent acquisition for proteome-wide cross-linking analysis. Cross-linking studies of the HeLa cell proteome were evaluated using the classical cross-linker disuccinimidyl suberate as an example. Compared with the DDA analysis, 4D-diaXLMS exhibited marked improvement in the identification coverage of cross-linked peptides, with a total increase of 36% in single-shot analysis across all 16 SCX fractions. This advantage was further amplified when reducing the fraction number to 8 and 4, resulting in 125 and 149% improvements, respectively. Using 4D-diaXLMS, up to 83% of the cross-linked peptides were repeatedly identified in three replicates, more than twice the 38% in the DDA mode. Furthermore, 4D-diaXLMS showed good performance in the quantitative analysis of yeast cross-linked peptides even in a 15-fold excess amount of HeLa cell matrix, with a low coefficient of variation and high quantitative accuracies in all concentrations. Overall, 4D-diaXLMS was proven to have high coverage, good reproducibility, and accurate quantification for in-depth XL-MS analysis in complex samples, demonstrating its immense potential for advances in the field.

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.

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.

Prediction of peptide mass spectral libraries with machine learning

The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods for peptide identification, such as search engines and experimental spectral libraries, are being superseded by deep learning models that allow the fragmentation spectra of peptides to be predicted from their amino acid sequence. These new approaches, including recurrent neural networks and convolutional neural networks, use predicted in silico spectral libraries rather than experimental libraries to achieve higher sensitivity and/or specificity in the analysis of proteomics data. Machine learning is galvanizing applications that involve large search spaces, such as immunopeptidomics and proteogenomics. Current challenges in the field include the prediction of spectra for peptides with post-translational modifications and for cross-linked pairs of peptides. Permeation of machine-learning-based spectral prediction into search engines and spectrum-centric data-independent acquisition workflows for diverse peptide classes and measurement conditions will continue to push sensitivity and dynamic range in proteomics applications in the coming years.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.