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Botticelli L, Bakhtina AA, Kaiser NK, Keller A, McNutt S, Bruce JE, Chu F. Chemical cross-linking and mass spectrometry enabled systems-level structural biology. Curr Opin Struct Biol 2024; 87:102872. [PMID: 38936319 PMCID: PMC11283951 DOI: 10.1016/j.sbi.2024.102872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 05/22/2024] [Accepted: 06/04/2024] [Indexed: 06/29/2024]
Abstract
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.
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Affiliation(s)
- Luke Botticelli
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH, USA
| | - Anna A Bakhtina
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Nathan K Kaiser
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Andrew Keller
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Seth McNutt
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH, USA
| | - James E Bruce
- Department of Genome Sciences, University of Washington, Seattle WA, USA.
| | - Feixia Chu
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH, USA.
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2
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Bakhtina AA, Wippel HH, Chavez JD, Bruce JE. Combining quantitative proteomics and interactomics for a deeper insight into molecular differences between human cell lines. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.12.598691. [PMID: 38915502 PMCID: PMC11195184 DOI: 10.1101/2024.06.12.598691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Cellular functional pathways have evolved through selection based on fitness benefits conferred through protein intra- and inter-molecular interactions that comprise all protein conformational features and protein-protein interactions, collectively referred to as the interactome. While the interactome is regulated by proteome levels, it is also regulated independently by, post translational modification, co-factor, and ligand levels, as well as local protein environmental factors, such as osmolyte concentration, pH, ionic strength, temperature and others. In modern biomedical research, cultivatable cell lines have become an indispensable tool, with selection of optimal cell lines that exhibit specific functional profiles being critical for success in many cases. While it is clear that cell lines derived from different cell types have differential proteome levels, increased understanding of large-scale functional differences requires additional information beyond abundance level measurements, including how protein conformations and interactions are altered in certain cell types to shape functional landscapes. Here, we employed quantitative in vivo protein cross-linking coupled to mass spectrometry to probe large-scale protein conformational and interaction changes among three commonly employed human cell lines, HEK293, MCF-7, and HeLa cells. Isobaric quantitative Protein Interaction Reporter (iqPIR) technologies were used to obtain quantitative values of cross-linked peptides across three cell lines. These data illustrated highly reproducible (R2 values larger than 0.8 for all biological replicates) quantitative interactome levels across multiple biological replicates. We also measured protein abundance levels in these cells using data independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteomics information allowed visualization of cell type-specific interactome changes mediated by proteome level adaptations as well as independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the biggest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study systems-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight on cellular functional landscapes.
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Affiliation(s)
- Anna A. Bakhtina
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Helisa H. Wippel
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Juan D. Chavez
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - James E. Bruce
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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3
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Park SG, Keller A, Kaiser NK, Bruce JE. Interactome dynamics during heat stress signal transmission and reception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591712. [PMID: 38746244 PMCID: PMC11092488 DOI: 10.1101/2024.04.29.591712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Among evolved molecular mechanisms, cellular stress response to altered environmental conditions to promote survival is among the most fundamental. The presence of stress-induced unfolded or misfolded proteins and molecular registration of these events constitute early steps in cellular stress response. However, what stress-induced changes in protein conformations and protein-protein interactions within cells initiate stress response and how these features are recognized by cellular systems are questions that have remained difficult to answer, requiring new approaches. Quantitative in vivo chemical cross-linking coupled with mass spectrometry (qXL-MS) is an emerging technology that provides new insight on protein conformations, protein-protein interactions and how the interactome changes during perturbation within cells, organelles, and even tissues. In this work, qXL-MS and quantitative proteome analyses were applied to identify significant time-dependent interactome changes that occur prior to large-scale proteome abundance remodeling within cells subjected to heat stress. Interactome changes were identified within minutes of applied heat stress, including stress-induced changes in chaperone systems as expected due to altered functional demand. However, global analysis of all interactome changes revealed the largest significant enrichment in the gene ontology molecular function term of RNA binding. This group included more than 100 proteins among multiple components of protein synthesis machinery, including mRNA binding, spliceosomes, and ribosomes. These interactome data provide new conformational insight on the complex relationship that exists between transcription, translation and cellular stress response mechanisms. Moreover, stress-dependent interactome changes suggest that in addition to conformational stabilization of RNA-binding proteins, adaptation of RNA as interacting ligands offers an additional fitness benefit resultant from generally lower RNA thermal stability. As such, RNA ligands also serve as fundamental temperature sensors that signal stress through decreased conformational regulation of their protein partners as was observed in these interactome dynamics.
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4
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Zhang Z, Zhao Q, Gong Z, Du R, Liu M, Zhang Y, Zhang L, Li C. Progress, Challenges and Opportunities of NMR and XL-MS for Cellular Structural Biology. JACS AU 2024; 4:369-383. [PMID: 38425916 PMCID: PMC10900494 DOI: 10.1021/jacsau.3c00712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/05/2024] [Accepted: 01/16/2024] [Indexed: 03/02/2024]
Abstract
The validity of protein structures and interactions, whether determined under ideal laboratory conditions or predicted by AI tools such as Alphafold2, to precisely reflect those found in living cells remains to be examined. Moreover, understanding the changes in protein structures and interactions in response to stimuli within living cells, under both normal and disease conditions, is key to grasping proteins' functionality and cellular processes. Nevertheless, achieving high-resolution identification of these protein structures and interactions within living cells presents a technical challenge. In this Perspective, we summarize the recent advancements in in-cell nuclear magnetic resonance (NMR) and in vivo cross-linking mass spectrometry (XL-MS) for studying protein structures and interactions within a cellular context. Additionally, we discuss the challenges, opportunities, and potential benefits of integrating in-cell NMR and in vivo XL-MS in future research to offer an exhaustive approach to studying proteins in their natural habitat.
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Affiliation(s)
- Zeting Zhang
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Qun Zhao
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Zhou Gong
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Ruichen Du
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
- University
of Chinese Academy of Sciences, Beijing 10049, China
| | - Maili Liu
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Yukui Zhang
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Lihua Zhang
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Conggang Li
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
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5
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Ruwolt M, Piazza I, Liu F. The potential of cross-linking mass spectrometry in the development of protein-protein interaction modulators. Curr Opin Struct Biol 2023; 82:102648. [PMID: 37423038 DOI: 10.1016/j.sbi.2023.102648] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/03/2023] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Cross-linking mass spectrometry (XL-MS) can provide a wealth of information on endogenous protein-protein interaction (PPI) networks and protein binding interfaces. These features make XL-MS an attractive tool to support the development of PPI-targeting drugs. Though not yet widely used, applications of XL-MS to drug characterization are beginning to emerge. Here, we compare XL-MS to established structural proteomics methods in drug research, discuss the current state and remaining challenges of XL-MS technology, and provide a perspective on the future role XL-MS can play in drug development, with a particular emphasis on PPI modulators.
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Affiliation(s)
- Max Ruwolt
- Department of Structural Biology, Leibniz, Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany. https://twitter.com/@MRuwolt
| | - Ilaria Piazza
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC Berlin), Berlin, Germany.
| | - Fan Liu
- Department of Structural Biology, Leibniz, Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany; Charité - Universitätsmedizin Berlin, Charitépl. 1, 10117 Berlin, Germany.
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6
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Yu C, Huang L. New advances in cross-linking mass spectrometry toward structural systems biology. Curr Opin Chem Biol 2023; 76:102357. [PMID: 37406423 PMCID: PMC11091472 DOI: 10.1016/j.cbpa.2023.102357] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/02/2023] [Accepted: 06/04/2023] [Indexed: 07/07/2023]
Abstract
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.
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Affiliation(s)
- Clinton Yu
- Department of Physiology & Biophysics, University of California, Irvine, Irvine, CA 92697, USA
| | - Lan Huang
- Department of Physiology & Biophysics, University of California, Irvine, Irvine, CA 92697, USA.
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7
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Keller A, Tang X, Bruce JE. Integrated Analysis of Cross-Links and Dead-End Peptides for Enhanced Interpretation of Quantitative XL-MS. J Proteome Res 2023; 22:2900-2908. [PMID: 37552582 PMCID: PMC10866149 DOI: 10.1021/acs.jproteome.3c00191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2023]
Abstract
Chemical cross-linking with mass spectrometry provides low-resolution structural information on proteins in cells and tissues. Combined with quantitation, it can identify changes in the interactome between samples, for example, control and drug-treated cells or young and old mice. A difference can originate from protein conformational changes that alter the solvent-accessible distance separating the cross-linked residues. Alternatively, a difference can result from conformational changes localized to the cross-linked residues, for example, altering the solvent exposure or reactivity of those residues or post-translational modifications of the cross-linked peptides. In this manner, cross-linking is sensitive to a variety of protein conformational features. Dead-end peptides are cross-links attached only at one end to a protein with the other terminus being hydrolyzed. As a result, changes in their abundance reflect only conformational changes localized to the attached residue. For this reason, analyzing both quantified cross-links and their corresponding dead-end peptides can help elucidate the likely conformational changes giving rise to observed differences in cross-link abundance. We describe analysis of dead-end peptides in the XLinkDB public cross-link database and, with quantified mitochondrial data isolated from failing heart versus healthy mice, show how a comparison of abundance ratios between cross-links and their corresponding dead-end peptides can be leveraged to reveal possible conformational explanations.
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Affiliation(s)
- Andrew Keller
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105 ,United States
| | - Xiaoting Tang
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105 ,United States
| | - James E Bruce
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105 ,United States
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8
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Mathay M, Keller A, Bruce JE. Studying Protein-Ligand Interactions by Protein Denaturation and Quantitative Cross-Linking Mass Spectrometry. Anal Chem 2023; 95:9432-9436. [PMID: 37307416 PMCID: PMC10848897 DOI: 10.1021/acs.analchem.2c04501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Recently, several mass spectrometry methods have utilized protein structural stability for the quantitative study of protein-ligand engagement. These protein-denaturation approaches, which include thermal proteome profiling (TPP) and stability of proteins from rates of oxidation (SPROX), evaluate ligand-induced denaturation susceptibility changes with a MS-based readout. The different techniques of bottom-up protein-denaturation methods each have their own advantages and challenges. Here, we report the combination of protein-denaturation principles with quantitative cross-linking mass spectrometry using isobaric quantitative protein interaction reporter technologies. This method enables the evaluation of ligand-induced protein engagement through analysis of cross-link relative ratios across chemical denaturation. As a proof of concept, we found ligand-stabilized cross-linked lysine pairs in well-studied bovine serum albumin and ligand bilirubin. These links map to the known binding sites Sudlow Site I and subdomain IB. We propose that protein denaturation and qXL-MS can be combined with similar peptide-level quantification approaches, like SPROX, to increase the coverage information profiled for facilitating protein-ligand engagement efforts.
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Affiliation(s)
- Martin Mathay
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - Andrew Keller
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - James E Bruce
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
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9
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Keller A, Tang X, Bruce JE. Integrated Analysis of Cross-Links and Dead-End Peptides for Enhanced Interpretation of Quantitative XL-MS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.26.542474. [PMID: 37398466 PMCID: PMC10312474 DOI: 10.1101/2023.05.26.542474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
XL-MS provides low-resolution structural information of proteins in cells and tissues. Combined with quantitation, it can identify changes in the interactome between samples, for example, control and drug-treated cells, or young and old mice. A difference can originate from protein conformational changes altering the solvent-accessible distance separating the cross-linked residues. Alternatively, a difference can result from conformational changes localized to the cross-linked residues, for example, altering the solvent exposure or reactivity of those residues or post-translational modifications on the cross-linked peptides. In this manner, cross-linking is sensitive to a variety of protein conformational features. Dead-end peptides are cross-links attached only at one end to a protein, the other terminus being hydrolyzed. As a result, changes in their abundance reflect only conformational changes localized to the attached residue. For this reason, analyzing both quantified cross-links and their corresponding dead-end peptides can help elucidate the likely conformational changes giving rise to observed differences of cross-link abundance. We describe analysis of dead-end peptides in the XLinkDB public cross-link database and, with quantified mitochondrial data isolated from failing heart versus healthy mice, show how a comparison of abundance ratios between cross-links and their corresponding dead-end peptides can be leveraged to reveal possible conformational explanations.
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10
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Chen ZA, Rappsilber J. Protein structure dynamics by crosslinking mass spectrometry. Curr Opin Struct Biol 2023; 80:102599. [PMID: 37104977 DOI: 10.1016/j.sbi.2023.102599] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/29/2023]
Abstract
Crosslinking mass spectrometry captures protein structures in solution. The crosslinks reveal spatial proximities as distance restraints, but do not easily reveal which of these restraints derive from the same protein conformation. This superposition can be reduced by photo-crosslinking, and adding information from protein structure models, or quantitative crosslinking reveals conformation-specific crosslinks. As a consequence, crosslinking MS has proven useful already in the context of multiple dynamic protein systems. We foresee a breakthrough in the resolution and scale of studying protein dynamics when crosslinks are used to guide deep-learning-based protein modelling. Advances in crosslinking MS, such as photoactivatable crosslinking and in-situ crosslinking, will then reveal protein conformation dynamics in the cellular context, at a pseudo-atomic resolution, and plausibly in a time-resolved manner.
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Affiliation(s)
- Zhuo Angel Chen
- Technische Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
| | - Juri Rappsilber
- Technische Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany; Si-M/"Der Simulierte Mensch", a Science Framework of Technische Universität Berlin and Charité - Universitätsmedizin Berlin, 10623 Berlin, Germany; Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK.
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11
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Cross-linking mass spectrometry for mapping protein complex topologies in situ. Essays Biochem 2023; 67:215-228. [PMID: 36734207 PMCID: PMC10070479 DOI: 10.1042/ebc20220168] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 02/04/2023]
Abstract
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.
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12
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Ruwolt M, Schnirch L, Borges Lima D, Nadler-Holly M, Viner R, Liu F. Optimized TMT-Based Quantitative Cross-Linking Mass Spectrometry Strategy for Large-Scale Interactomic Studies. Anal Chem 2022; 94:5265-5272. [PMID: 35290030 DOI: 10.1021/acs.analchem.1c04812] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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.
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Affiliation(s)
- Max Ruwolt
- Department of Structural Biology, Leibniz - ForschungsinstitutfürMolekularePharmakologie (FMP), Robert-Roessle-Str. 10, Berlin13125, Germany
| | - Lennart Schnirch
- Department of Structural Biology, Leibniz - ForschungsinstitutfürMolekularePharmakologie (FMP), Robert-Roessle-Str. 10, Berlin13125, Germany
| | - Diogo Borges Lima
- Department of Structural Biology, Leibniz - ForschungsinstitutfürMolekularePharmakologie (FMP), Robert-Roessle-Str. 10, Berlin13125, Germany
| | - Michal Nadler-Holly
- Department of Structural Biology, Leibniz - ForschungsinstitutfürMolekularePharmakologie (FMP), Robert-Roessle-Str. 10, Berlin13125, Germany
| | - Rosa Viner
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California95134, United States
| | - Fan Liu
- Department of Structural Biology, Leibniz - ForschungsinstitutfürMolekularePharmakologie (FMP), Robert-Roessle-Str. 10, Berlin13125, Germany
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