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Aljedani SS, Aldehaiman A, Sandholu A, Alharbi S, Mak VC, Wu H, Lugari A, Jaremko M, Morelli X, Backer JW, Ladbury JE, Nowakowski M, Cheung LW, Arold ST. Functional selection in SH3-mediated activation of the PI3 kinase. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.30.591319. [PMID: 38746413 PMCID: PMC11092569 DOI: 10.1101/2024.04.30.591319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
The phosphoinositide-3 kinase (PI3K), a heterodimeric enzyme, plays a pivotal role in cellular metabolism and survival. Its deregulation is associated with major human diseases, particularly cancer. The p85 regulatory subunit of PI3K binds to the catalytic p110 subunit via its C-terminal domains, stabilising it in an inhibited state. Certain Src homology 3 (SH3) domains can activate p110 by binding to the proline-rich (PR) 1 motif located at the N-terminus of p85. However, the mechanism by which this N-terminal interaction activates the C-terminally bound p110 remains elusive. Moreover, the intrinsically poor ligand selectivity of SH3 domains raises the question of how they can control PI3K. Combining structural, biophysical, and functional methods, we demonstrate that the answers to both these unknown issues are linked: PI3K-activating SH3 domains engage in additional "tertiary" interactions with the C-terminal domains of p85, thereby relieving their inhibition of p110. SH3 domains lacking these tertiary interactions may still bind to p85 but cannot activate PI3K. Thus, p85 uses a functional selection mechanism that precludes nonspecific activation rather than nonspecific binding. This separation of binding and activation may provide a general mechanism for how biological activities can be controlled by promiscuous protein-protein interaction domains.
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Affiliation(s)
- Safia S. Aljedani
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
| | - Abdullah Aldehaiman
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
| | - Anandsukeerthi Sandholu
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
| | - Siba Alharbi
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
| | - Victor C.Y. Mak
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Haiyan Wu
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Adrien Lugari
- CRCM, CNRS, INSERM, Institut Paoli-Calmettes, Aix-Marseille University, 13009 Marseille, France
| | - Mariusz Jaremko
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
| | - Xavier Morelli
- CRCM, CNRS, INSERM, Institut Paoli-Calmettes, Aix-Marseille University, 13009 Marseille, France
| | - Jonathan W. Backer
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - John E. Ladbury
- School of Molecular and Cellular Biology, and Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, LS2 9JT
| | - Michał Nowakowski
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Żwirki i Wigury 101, 02-089 Warsaw, Poland
| | - Lydia W.T. Cheung
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Stefan T. Arold
- Biological and Environmental Science and Engineering Division, Computational Biology Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 2395-56900, Kingdom of Saudi Arabia
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Darula Z, McCabe MC, Barrett A, Schmitt LR, Maslanka MD, Saviola AJ, Orgel J, Burlingame A, Staab-Weijnitz CA, Stenmark K, Weaver V, Chalkley RJ, Hansen KC. Assessing Heterogeneity in the N-Telopeptides of Type I Collagen by Mass Spectrometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.31.587441. [PMID: 38585857 PMCID: PMC10996605 DOI: 10.1101/2024.03.31.587441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Collagen cross-links created by the lysyl oxidase and lysyl hydroxylase families of enzymes are a significant contributing factor to the biomechanical strength and rigidity of tissues, which in turn influence cell signaling and ultimately cell phenotype. In the clinic, the proteolytically liberated N-terminal cross-linked peptide of collagen I (NTX) is used as a biomarker of bone and connective tissue turnover, which is altered in several disease processes. Despite the clinical utility of these collagen breakdown products, the majority of the cross-linked peptide species have not been identified in proteomic datasets. Here we evaluate several parameters for the preparation and identification of these peptides from the collagen I-rich Achilles tendon. Our refined approach involving chemical digestion for protein solubilization coupled with mass spectrometry allows for the identification of the NTX cross-links in a range of modification states. Based on the specificity of the enzymatic cross-linking reaction we utilized follow-up variable modification searches to facilitate identification with a wider range of analytical workflows. We then applied a spectral library approach to identify differences in collagen cross-links in bovine pulmonary hypertension. The presented method offers unique opportunities to understand extracellular matrix remodeling events in development, aging, wound healing, and fibrotic disease that modulate collagen architecture through lysyl-hydroxylase and lysyl-oxidase enzymes.
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Brodie NI, Sarpe V, Crowder DA, Schriemer D. All-in-One Pseudo-MS 3 Method for the Analysis of Gas-Phase Cleavable Protein Crosslinking Reactions. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2146-2155. [PMID: 37590165 DOI: 10.1021/jasms.3c00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Crosslinking mass spectrometry (XL-MS) supports structure analysis of individual proteins and highly complex whole-cell interactomes. The identification of crosslinked peptides from enzymatic digests remains challenging, especially at the cell level. Empirical methods that use gas-phase cleavable crosslinkers can simplify the identification process by enabling an MS3-based strategy that turns crosslink identification into a simpler problem of detecting two separable peptides. However, the method is limited to select instrument platforms and is challenged by duty cycle constraints. Here, we revisit a pseudo-MS3 concept that incorporates in-source fragmentation, where a fast switch between gentle high-transmission source conditions and harsher in-source fragmentation settings liberates peptides for standard MS2-based peptide identification. We present an all-in-one method where retention time matches between the crosslink precursor and the liberated peptides establish linkage, and MS2 sequencing identifies the source-liberated peptides. We demonstrate that DC4, a very labile cleavable crosslinker, generates high-intensity peptides in-source. Crosslinks can be identified from these liberated peptides, as they are chromatographically well-resolved from monolinks. Using bovine serum albumin (BSA) as a crosslinking test case, we detect 27% more crosslinks with pseudo-MS3 over a best-in-class MS3 method. While performance is slightly lower for whole-cell lysates (generating two-thirds of the identifications of a standard method), we find that 60% of these hits are unique, highlighting the complementarity of the method.
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Affiliation(s)
- Nicholas I Brodie
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - Vladimir Sarpe
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - D Alex Crowder
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - David Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
- Department of Chemistry, University of Calgary, Calgary, Alberta, Canada T2N-4N1
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4
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Zhou C, Dai S, Lai S, Lin Y, Zhang X, Li N, Yu W. ECL 3.0: a sensitive peptide identification tool for cross-linking mass spectrometry data analysis. BMC Bioinformatics 2023; 24:351. [PMID: 37730532 PMCID: PMC10510197 DOI: 10.1186/s12859-023-05473-z] [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: 06/02/2023] [Accepted: 09/11/2023] [Indexed: 09/22/2023] Open
Abstract
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 .
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Affiliation(s)
- Chen Zhou
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Shuaijian Dai
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Shengzhi Lai
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Yuanqiao Lin
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Xuechen Zhang
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Ning Li
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
- HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Shenzhen, China
| | - Weichuan Yu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.
- HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Shenzhen, China.
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5
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Murvai N, Gellen G, Micsonai A, Schlosser G, Kardos J. Cross-Linked α-Synuclein as Inhibitor of Amyloid Formation. Int J Mol Sci 2023; 24:13403. [PMID: 37686208 PMCID: PMC10487470 DOI: 10.3390/ijms241713403] [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: 07/11/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
The aggregation and amyloid formation of α-synuclein is associated with Parkinson's disease and other synucleinopathies. In its native, monomeric form α-synuclein is an intrinsically disordered protein represented by highly dynamic conformational ensembles. Inhibition of α-synuclein aggregation using small molecules, peptides, or proteins has been at the center of interest in recent years. Our aim was to explore the effects of cross-linking on the structure and aggregation/amyloid formation properties of α-synuclein. Comparative analysis of available high-resolution amyloid structures and representative structural models and MD trajectory of monomeric α-synuclein revealed that potential cross-links in the monomeric protein are mostly incompatible with the amyloid forms and thus might inhibit fibrillation. Monomeric α-synuclein has been intramolecularly chemically cross-linked under various conditions using different cross-linkers. We determined the location of cross-links and their frequency using mass spectrometry and found that most of them cannot be realized in the amyloid structures. The inhibitory potential of cross-linked proteins has been experimentally investigated using various methods, including thioflavin-T fluorescence and transmission electron microscopy. We found that conformational constraints applied by cross-linking fully blocked α-synuclein amyloid formation. Moreover, DTSSP-cross-linked molecules exhibited an inhibitory effect on the aggregation of unmodified α-synuclein as well.
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Affiliation(s)
- Nikoletta Murvai
- Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
- ELTE—Functional Nucleic Acid Motifs Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
| | - Gabriella Gellen
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Department of Analytical Chemistry, Institute of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
- Doctoral School of Molecular Cell and Immune Biology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
- Department of Biophysics and Cell Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
| | - András Micsonai
- Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
- ELTE—Functional Nucleic Acid Motifs Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
| | - Gitta Schlosser
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Department of Analytical Chemistry, Institute of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
| | - József Kardos
- Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary
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6
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Cao Y, Liu XT, Mao PZ, Chen ZL, Tarn C, Dong MQ. Comparative Analysis of Chemical Cross-Linking Mass Spectrometry Data Indicates That Protein STY Residues Rarely React with N-Hydroxysuccinimide Ester Cross-Linkers. J Proteome Res 2023; 22:2593-2607. [PMID: 37494005 DOI: 10.1021/acs.jproteome.3c00037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
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.
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Affiliation(s)
- Yong Cao
- National Institute of Biological Sciences, Beijing, Beijing 102206, China
| | - Xin-Tong Liu
- National Institute of Biological Sciences, Beijing, Beijing 102206, China
| | - Peng-Zhi Mao
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen-Lin Chen
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ching Tarn
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meng-Qiu Dong
- National Institute of Biological Sciences, Beijing, Beijing 102206, China
- Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, Beijing 102206, China
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7
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Park E, Rawson S, Schmoker A, Kim BW, Oh S, Song K, Jeon H, Eck MJ. Cryo-EM structure of a RAS/RAF recruitment complex. Nat Commun 2023; 14:4580. [PMID: 37516774 PMCID: PMC10387098 DOI: 10.1038/s41467-023-40299-6] [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: 09/29/2022] [Accepted: 07/19/2023] [Indexed: 07/31/2023] Open
Abstract
RAF-family kinases are activated by recruitment to the plasma membrane by GTP-bound RAS, whereupon they initiate signaling through the MAP kinase cascade. Prior structural studies of KRAS with RAF have focused on the isolated RAS-binding and cysteine-rich domains of RAF (RBD and CRD, respectively), which interact directly with RAS. Here we describe cryo-EM structures of a KRAS bound to intact BRAF in an autoinhibited state with MEK1 and a 14-3-3 dimer. Analysis of this KRAS/BRAF/MEK1/14-3-3 complex reveals KRAS bound to the RAS-binding domain of BRAF, captured in two orientations. Core autoinhibitory interactions in the complex are unperturbed by binding of KRAS and in vitro activation studies confirm that KRAS binding is insufficient to activate BRAF, absent membrane recruitment. These structures illustrate the separability of binding and activation of BRAF by RAS and suggest stabilization of this pre-activation intermediate as an alternative therapeutic strategy to blocking binding of KRAS.
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Affiliation(s)
- Eunyoung Park
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
- Pfizer R&D Center, 3200 Walnut St, Boulder, CO, 80301, USA
| | - Shaun Rawson
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | - Anna Schmoker
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Byeong-Won Kim
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- New Drug Development Center, Osong Medical Innovation Foundation, Cheongju, Chungbuk, 28160, Republic of Korea
| | - Sehee Oh
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Kangkang Song
- Department of Biochemistry & Molecular Biotechnology, University of Massachusetts Chan Medical School, 364 Plantation St, Worcester, MA, 01605, USA
| | - Hyesung Jeon
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA.
| | - Michael J Eck
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA.
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8
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Srivastava D, Yadav RP, Singh S, Boyd K, Artemyev NO. Unique interface and dynamics of the complex of HSP90 with a specialized cochaperone AIPL1. Structure 2023; 31:309-317.e5. [PMID: 36657440 PMCID: PMC9992320 DOI: 10.1016/j.str.2022.12.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/06/2022] [Accepted: 12/23/2022] [Indexed: 01/19/2023]
Abstract
Photoreceptor phosphodiesterase PDE6 is central for visual signal transduction. Maturation of PDE6 depends on a specialized chaperone complex of HSP90 with aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1). Disruption of PDE6 maturation underlies a severe form of retina degeneration. Here, we report a 3.9 Å cryoelectron microscopy (cryo-EM) structure of the complex of HSP90 with AIPL1. This structure reveals a unique interaction of the FK506-binding protein (FKBP)-like domain of AIPL1 with HSP90 at its dimer interface. Unusually, the N terminus AIPL1 inserts into the HSP90 lumen in a manner that was observed previously for HSP90 clients. Deletion of the 7 N-terminal residues of AIPL1 decreased its ability to cochaperone PDE6. Multi-body refinement of the cryo-EM data indicated large swing-like movements of AIPL1-FKBP. Modeling the complex of HSP90 with AIPL1 using crosslinking constraints indicated proximity of the mobile tetratricopeptide repeat (TPR) domain with the C-terminal domain of HSP90. Our study establishes a framework for future structural studies of PDE6 maturation.
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Affiliation(s)
- Dhiraj Srivastava
- Department of Molecular Physiology and Biophysics, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Ravi P Yadav
- Department of Molecular Physiology and Biophysics, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Sneha Singh
- Department of Molecular Physiology and Biophysics, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Kimberly Boyd
- Department of Molecular Physiology and Biophysics, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Nikolai O Artemyev
- Department of Molecular Physiology and Biophysics, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Department of Ophthalmology and Visual Sciences, The University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA.
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9
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Hoopmann MR, Shteynberg DD, Zelter A, Riffle M, Lyon AS, Agard DA, Luan Q, Nolen BJ, MacCoss MJ, Davis TN, Moritz RL. Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline. J Proteome Res 2023; 22:647-655. [PMID: 36629399 PMCID: PMC10234491 DOI: 10.1021/acs.jproteome.2c00670] [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: 01/12/2023]
Abstract
Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.
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Affiliation(s)
| | | | - Alex Zelter
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
| | - Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
| | - Andrew S. Lyon
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA 94143
| | - David A. Agard
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA 94143
| | - Qing Luan
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, OR, USA 97403
| | - Brad J. Nolen
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, OR, USA 97403
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA 98195
| | - Trisha N. Davis
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
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10
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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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11
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Mummadisetti M, Su X, Liu H. An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry. Methods Enzymol 2023; 680:139-162. [PMID: 36710009 DOI: 10.1016/bs.mie.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the "early events" of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.
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Affiliation(s)
| | - Xinyang Su
- Department of Biology, Washington University in St. Louis, St. Louis, MO, United States
| | - Haijun Liu
- Department of Biology, Washington University in St. Louis, St. Louis, MO, United States.
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12
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Zhou C, Dai S, Lin Y, Lian S, Fan X, Li N, Yu W. Exhaustive Cross-Linking Search with Protein Feedback. J Proteome Res 2023; 22:101-113. [PMID: 36480279 DOI: 10.1021/acs.jproteome.2c00500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Chen Zhou
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Shuaijian Dai
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Yuanqiao Lin
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Sheng Lian
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Xiaodan Fan
- Department of Statistics, The Chinese University of Hong Kong, Hong Kong 999077, China
| | - Ning Li
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong 999077, China.,HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, 518000, China
| | - Weichuan Yu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China.,HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, 518000, China
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13
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Zhang W, Gong P, Shan Y, Zhao L, Hu H, Wei Q, Liang Z, Liu C, Zhang L, Zhang Y. SpotLink enables sensitive and precise identification of site nonspecific cross-links at the proteome scale. Brief Bioinform 2022; 23:6652569. [PMID: 36093786 DOI: 10.1093/bib/bbac316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/27/2022] [Accepted: 07/12/2022] [Indexed: 11/14/2022] Open
Abstract
Nonspecific cross-linker can provide distance restraints between surface residues of any type, which could be used to investigate protein structure construction and protein-protein interaction (PPI). However, the vast number of potential combinations of cross-linked residues or sites obtained with such a cross-linker makes the data challenging to analyze, especially for the proteome-wide applications. Here, we developed SpotLink software for identifying site nonspecific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning algorithm and the quality control of cross-linking sites, SpotLink identified > 3000 cross-links from human cell samples within a short period of days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on the datasets of the simulated succinimidyl 4,4'-azipentanoate dataset and the condensin complexes with known structures. In addition, some valuable PPI were discovered in the datasets of the condensin complexes and the HeLa dataset, indicating the unique identification advantages of site nonspecific cross-linking. These findings reinforce the importance of SpotLink as a fundamental characteristic of site nonspecific cross-linking technologies.
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Affiliation(s)
- Weijie Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China.,University of Chinese Academy of Sciences, Beijing 100039, China
| | - Pengyun Gong
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Yichu Shan
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Lili Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China.,University of Chinese Academy of Sciences, Beijing 100039, China
| | - Hongke Hu
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Qiushi Wei
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Zhen Liang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Chao Liu
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Lihua Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Yukui Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
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14
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Jiang Q, Foglizzo M, Morozov YI, Yang X, Datta A, Tian L, Thada V, Li W, Zeqiraj E, Greenberg RA. Autologous K63 deubiquitylation within the BRCA1-A complex licenses DNA damage recognition. J Cell Biol 2022; 221:213388. [PMID: 35938958 PMCID: PMC9386975 DOI: 10.1083/jcb.202111050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 05/15/2022] [Accepted: 07/15/2022] [Indexed: 02/03/2023] Open
Abstract
The BRCA1-A complex contains matching lysine-63 ubiquitin (K63-Ub) binding and deubiquitylating activities. How these functionalities are coordinated to effectively respond to DNA damage remains unknown. We generated Brcc36 deubiquitylating enzyme (DUB) inactive mice to address this gap in knowledge in a physiologic system. DUB inactivation impaired BRCA1-A complex damage localization and repair activities while causing early lethality when combined with Brca2 mutation. Damage response dysfunction in DUB-inactive cells corresponded to increased K63-Ub on RAP80 and BRCC36. Chemical cross-linking coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and cryogenic-electron microscopy (cryo-EM) analyses of isolated BRCA1-A complexes demonstrated the RAP80 ubiquitin interaction motifs are occupied by ubiquitin exclusively in the DUB-inactive complex, linking auto-inhibition by internal K63-Ub chains to loss of damage site ubiquitin recognition. These findings identify RAP80 and BRCC36 as autologous DUB substrates in the BRCA1-A complex, thus explaining the evolution of matching ubiquitin-binding and hydrolysis activities within a single macromolecular assembly.
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Affiliation(s)
- Qinqin Jiang
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Martina Foglizzo
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Yaroslav I Morozov
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Xuejiao Yang
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Arindam Datta
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Lei Tian
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Vaughn Thada
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Weihua Li
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Elton Zeqiraj
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Roger A Greenberg
- Department of Cancer Biology, Penn Center for Genome Integrity, Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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15
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Renzone G, Arena S, Scaloni A. Cross-linking reactions in food proteins and proteomic approaches for their detection. MASS SPECTROMETRY REVIEWS 2022; 41:861-898. [PMID: 34250627 DOI: 10.1002/mas.21717] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/29/2021] [Accepted: 06/29/2021] [Indexed: 06/13/2023]
Abstract
Various protein cross-linking reactions leading to molecular polymerization and covalent aggregates have been described in processed foods. They are an undesired side effect of processes designed to reduce bacterial load, extend shelf life, and modify technological properties, as well as being an expected result of treatments designed to modify raw material texture and function. Although the formation of these products is known to affect the sensory and technological properties of foods, the corresponding cross-linking reactions and resulting protein polymers have not yet undergone detailed molecular characterization. This is essential for describing how their generation can be related to food processing conditions and quality parameters. Due to the complex structure of cross-linked species, bottom-up proteomic procedures developed to characterize various amino acid modifications associated with food processing conditions currently offer a limited molecular description of bridged peptide structures. Recent progress in cross-linking mass spectrometry for the topological characterization of protein complexes has facilitated the development of various proteomic methods and bioinformatic tools for unveiling bridged species, which can now also be used for the detailed molecular characterization of polymeric cross-linked products in processed foods. We here examine their benefits and limitations in terms of evaluating cross-linked food proteins and propose future scenarios for application in foodomics. They offer potential for understanding the protein cross-linking formation mechanisms in processed foods, and how the inherent beneficial properties of treated foodstuffs can be preserved or enhanced.
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Affiliation(s)
- Giovanni Renzone
- Proteomics and Mass Spectrometry Laboratory, ISPAAM, National Research Council, Naples, Italy
| | - Simona Arena
- Proteomics and Mass Spectrometry Laboratory, ISPAAM, National Research Council, Naples, Italy
| | - Andrea Scaloni
- Proteomics and Mass Spectrometry Laboratory, ISPAAM, National Research Council, Naples, Italy
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16
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Bircher JE, Corcoran EE, Lam TT, Trnka MJ, Koleske AJ. Autoinhibition of the GEF activity of cytoskeletal regulatory protein Trio is disrupted in neurodevelopmental disorder-related genetic variants. J Biol Chem 2022; 298:102361. [PMID: 35963430 PMCID: PMC9467883 DOI: 10.1016/j.jbc.2022.102361] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 11/29/2022] Open
Abstract
TRIO encodes a cytoskeletal regulatory protein with three catalytic domains-two guanine exchange factor (GEF) domains, GEF1 and GEF2, and a kinase domain-as well as several accessory domains that have not been extensively studied. Function-damaging variants in the TRIO gene are known to be enriched in individuals with neurodevelopmental disorders (NDDs). Disease variants in the GEF1 domain or the nine adjacent spectrin repeats (SRs) are enriched in NDDs, suggesting that dysregulated GEF1 activity is linked to these disorders. We provide evidence here that the Trio SRs interact intramolecularly with the GEF1 domain to inhibit its enzymatic activity. We demonstrate that SRs 6-9 decrease GEF1 catalytic activity both in vitro and in cells and show that NDD-associated variants in the SR8 and GEF1 domains relieve this autoinhibitory constraint. Our results from chemical cross-linking and bio-layer interferometry indicate that the SRs primarily contact the pleckstrin homology region of the GEF1 domain, reducing GEF1 binding to the small GTPase Rac1. Together, our findings reveal a key regulatory mechanism that is commonly disrupted in multiple NDDs and may offer a new target for therapeutic intervention for TRIO-associated NDDs.
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Affiliation(s)
- Josie E. Bircher
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA
| | - Ellen E. Corcoran
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA
| | - TuKiet T. Lam
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA,Keck MS & Proteomics Resource, Yale University, New Haven, Connecticut, USA
| | - Michael J. Trnka
- Department of Pharmaceutical Chemistry, University of California at San Francisco, San Francisco, California, USA
| | - Anthony J. Koleske
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA,Department of Neuroscience, Yale University, New Haven, Connecticut, USA,For correspondence: Anthony J. Koleske
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17
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Kolbowski L, Lenz S, Fischer L, Sinn LR, O’Reilly FJ, Rappsilber J. Improved Peptide Backbone Fragmentation Is the Primary Advantage of MS-Cleavable Crosslinkers. Anal Chem 2022; 94:7779-7786. [PMID: 35613060 PMCID: PMC9178559 DOI: 10.1021/acs.analchem.1c05266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 04/06/2022] [Indexed: 12/05/2022]
Abstract
Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of mass spectrometry (MS)-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently, such studies have also been published with noncleavable crosslinkers, suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the commonly used MS-cleavable crosslinker, disuccinimidyl sulfoxide (DSSO). Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS cleavability of the crosslinker, but improved peptide backbone fragmentation which reduces the ambiguity of peptide identifications. This also holds true for another commonly used MS-cleavable crosslinker, DSBU. We show furthermore that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped higher-energy collisional dissociation (HCD) method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.
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Affiliation(s)
- Lars Kolbowski
- Technische
Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
| | - Swantje Lenz
- Technische
Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
| | - Lutz Fischer
- Technische
Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
| | - Ludwig R. Sinn
- Technische
Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
| | | | - Juri Rappsilber
- Technische
Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany
- University
of Edinburgh, Wellcome Centre
for Cell Biology, Edinburgh EH9 3BF, U.K.
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18
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Yılmaz Ş, Busch F, Nagaraj N, Cox J. Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx. Anal Chem 2022; 94:1608-1617. [PMID: 35014260 PMCID: PMC8792900 DOI: 10.1021/acs.analchem.1c03688] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to noncleavable and MS-cleavable cross-linkers. For both, we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For noncleavable peptides, we implemented a novel dipeptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the dipeptide individually. A posterior error probability (PEP) based on total and partial scores is used to control false discovery rates (FDRs). For MS-cleavable cross-linkers, a score of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace the manual filtering of identifications, which is often necessary when using other pipelines. On benchmark data sets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross-linkers and on a proteome-wide data set of cross-linked Drosophila melanogaster cell lysate. The workflow also supports ion mobility-enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra, and is freely available at https://www.maxquant.org/.
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Affiliation(s)
- Şule Yılmaz
- Computational Systems Biochemistry Research Group, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Florian Busch
- Bruker Daltonics GmbH & Co. KG, 28359 Bremen, Germany
| | | | - Jürgen Cox
- Computational Systems Biochemistry Research Group, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.,Department of Biological and Medical Psychology, University of Bergen, 5007 Bergen, Norway
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19
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Hipper E, Blech M, Hinderberger D, Garidel P, Kaiser W. Photo-Oxidation of Therapeutic Protein Formulations: From Radical Formation to Analytical Techniques. Pharmaceutics 2021; 14:72. [PMID: 35056968 PMCID: PMC8779573 DOI: 10.3390/pharmaceutics14010072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/09/2021] [Accepted: 12/14/2021] [Indexed: 12/25/2022] Open
Abstract
UV and ambient light-induced modifications and related degradation of therapeutic proteins are observed during manufacturing and storage. Therefore, to ensure product quality, protein formulations need to be analyzed with respect to photo-degradation processes and eventually protected from light exposure. This task usually demands the application and combination of various analytical methods. This review addresses analytical aspects of investigating photo-oxidation products and related mediators such as reactive oxygen species generated via UV and ambient light with well-established and novel techniques.
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Affiliation(s)
- Elena Hipper
- Institute of Chemistry, Martin-Luther-Universität Halle-Wittenberg, von-Danckelmann-Platz 4, 06120 Halle (Saale), Germany; (E.H.); (D.H.)
| | - Michaela Blech
- Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, PDB, Birkendorfer Strasse 65, 88397 Biberach an der Riss, Germany;
| | - Dariush Hinderberger
- Institute of Chemistry, Martin-Luther-Universität Halle-Wittenberg, von-Danckelmann-Platz 4, 06120 Halle (Saale), Germany; (E.H.); (D.H.)
| | - Patrick Garidel
- Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, PDB, Birkendorfer Strasse 65, 88397 Biberach an der Riss, Germany;
| | - Wolfgang Kaiser
- Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, PDB, Birkendorfer Strasse 65, 88397 Biberach an der Riss, Germany;
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20
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Piersimoni L, Kastritis PL, Arlt C, Sinz A. Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons. Chem Rev 2021; 122:7500-7531. [PMID: 34797068 DOI: 10.1021/acs.chemrev.1c00786] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
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.
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Affiliation(s)
- Lolita Piersimoni
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
| | - Panagiotis L Kastritis
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Kurt-Mothes-Strasse 3a, D-06120 Halle (Saale), Germany.,Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Biozentrum, Weinbergweg 22, D-06120 Halle (Saale), Germany
| | - Christian Arlt
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
| | - Andrea Sinz
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
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21
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Semkova ME, Hsuan JJ. Mass Spectrometric Identification of a Novel Factor XIIIa Cross-Linking Site in Fibrinogen. Proteomes 2021; 9:proteomes9040043. [PMID: 34842803 PMCID: PMC8628943 DOI: 10.3390/proteomes9040043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/20/2021] [Accepted: 10/28/2021] [Indexed: 11/17/2022] Open
Abstract
Transglutaminases are a class of enzymes that catalyze the formation of a protein:protein cross-link between a lysine and a glutamine residue. These cross-links play important roles in diverse biological processes. Analysis of cross-linking sites in target proteins is required to elucidate their molecular action on target protein function and the molecular specificity of different transglutaminase isozymes. Mass-spectrometry using settings designed for linear peptide analysis and software designed for the analysis of disulfide bridges and chemical cross-links have previously been employed to identify transglutaminase cross-linking sites in proteins. As no control peptide with which to assess and improve the mass spectrometric analysis of TG cross-linked proteins was available, we developed a method for the enzymatic synthesis of a well-defined transglutaminase cross-linked peptide pair that mimics a predicted tryptic digestion product of collagen I. We then used this model peptide to determine optimal score thresholds for correct peptide identification from y- and b-ion series of fragments produced by collision-induced dissociation. We employed these settings in an analysis of fibrinogen cross-linked by the transglutaminase Factor XIIIa. This approach resulted in identification of a novel cross-linked peptide in the gamma subunit. We discuss the difference in behavior of ions derived from different cross-linked peptide sequences and the consequent demand for a more tailored mass spectrometry approach for cross-linked peptide identification compared to that routinely used for linear peptide analysis.
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22
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Yugandhar K, Zhao Q, Gupta S, Xiong D, Yu H. Progress in methodologies and quality-control strategies in protein cross-linking mass spectrometry. Proteomics 2021; 21:e2100145. [PMID: 34647422 DOI: 10.1002/pmic.202100145] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 10/04/2021] [Indexed: 11/10/2022]
Abstract
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.
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Affiliation(s)
- Kumar Yugandhar
- Department of Computational Biology, Cornell University, New York, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, New York, USA
| | - Qiuye Zhao
- Department of Computational Biology, Cornell University, New York, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, New York, USA
| | - Shobhita Gupta
- Department of Computational Biology, Cornell University, New York, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, New York, USA
| | - Dapeng Xiong
- Department of Computational Biology, Cornell University, New York, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, New York, USA
| | - Haiyuan Yu
- Department of Computational Biology, Cornell University, New York, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, New York, USA
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23
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Jack A, Ferro LS, Trnka MJ, Wehri E, Nadgir A, Nguyenla X, Fox D, Costa K, Stanley S, Schaletzky J, Yildiz A. SARS-CoV-2 nucleocapsid protein forms condensates with viral genomic RNA. PLoS Biol 2021; 19:e3001425. [PMID: 34634033 PMCID: PMC8553124 DOI: 10.1371/journal.pbio.3001425] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 10/28/2021] [Accepted: 09/28/2021] [Indexed: 12/13/2022] Open
Abstract
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection causes Coronavirus Disease 2019 (COVID-19), a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. While the N protein forms spherical assemblies with homopolymeric RNA substrates that do not form base pairing interactions, it forms asymmetric condensates with viral RNA strands. Cross-linking mass spectrometry (CLMS) identified a region that drives interactions between N proteins in condensates, and deletion of this region disrupts phase separation. We also identified small molecules that alter the size and shape of N protein condensates and inhibit the proliferation of SARS-CoV-2 in infected cells. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle.
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Affiliation(s)
- Amanda Jack
- Biophysics Graduate Group, University of California, Berkeley, California, United States of America
| | - Luke S. Ferro
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
| | - Michael J. Trnka
- Department of Pharmaceutical Chemistry, University of California, San Francisco, California, United States of America
| | - Eddie Wehri
- Center for Emerging and Neglected Diseases, University of California, Berkeley, California, United States of America
| | - Amrut Nadgir
- Physics Department, University of California, Berkeley, California, United States of America
| | - Xammy Nguyenla
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, California, United States of America
| | - Douglas Fox
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, California, United States of America
| | - Katelyn Costa
- Press West Illustrations, Boston, Massachusetts, United States of America
| | - Sarah Stanley
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, California, United States of America
| | - Julia Schaletzky
- Center for Emerging and Neglected Diseases, University of California, Berkeley, California, United States of America
| | - Ahmet Yildiz
- Biophysics Graduate Group, University of California, Berkeley, California, United States of America
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Physics Department, University of California, Berkeley, California, United States of America
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24
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Britt HM, Cragnolini T, Thalassinos K. Integration of Mass Spectrometry Data for Structural Biology. Chem Rev 2021; 122:7952-7986. [PMID: 34506113 DOI: 10.1021/acs.chemrev.1c00356] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.
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Affiliation(s)
- Hannah M Britt
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom
| | - Tristan Cragnolini
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom.,Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, United Kingdom
| | - Konstantinos Thalassinos
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom.,Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, United Kingdom
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25
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Synthesis, LC-MS/MS analysis, and biological evaluation of two vaccine candidates against ticks based on the antigenic P0 peptide from R. sanguineus linked to the p64K carrier protein from Neisseria meningitidis. Anal Bioanal Chem 2021; 413:5885-5900. [PMID: 34341841 PMCID: PMC8328535 DOI: 10.1007/s00216-021-03569-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 07/12/2021] [Accepted: 07/20/2021] [Indexed: 11/24/2022]
Abstract
A peptide from the P0 acidic ribosomal protein (pP0) of ticks conjugated to keyhole limpet hemocyanin from Megathura crenulata has shown to be effective against different tick species when used in host vaccination. Turning this peptide into a commercial anti-tick vaccine will depend on finding the appropriate, technically and economically feasible way to present it to the host immune system. Two conjugates (p64K-Cys1pP0 and p64K-βAla1pP0) were synthesized using the p64K carrier protein from Neisseria meningitidis produced in Escherichia coli, the same cross-linking reagent, and two analogues of pP0. The SDS-PAGE analysis of p64K-Cys1pP0 showed a heterogeneous conjugate compared to p64K-βAla1pP0 that was detected as a protein band at 91kDa. The pP0/p64K ratio determined by MALDI-MS for p64K-Cys1pP0 ranged from 1 to 8, being 3-5 the predominant ratio, while in the case of p64K-βAla1pP0 this ratio was 5-7. Cys1pP0 was partially linked to 35 out of 39 Lys residues and the N-terminal end, while βAla1pP0 was mostly linked to the six free cysteine residues, to the N-terminal end, and, in a lesser extent, to Lys residues. The assignment of the conjugation sites and side reactions were based on the identification of type 2 peptides. Rabbit immunizations showed the best anti-pP0 titers and the highest efficacy against Rhipicephalus sanguineus ticks when the p64K-Cys1pP0 was used as vaccine antigen. The presence of high molecular mass aggregates observed in the SDS-PAGE analysis of p64K-Cys1pP0 could be responsible for a better immune response against pP0 and consequently for its better efficacy as an anti-tick vaccine. Graphical abstract ![]()
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26
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Schopfer LM, Onder S, Lockridge O. Evaluation of mass spectrometry MS/MS spectra for the presence of isopeptide crosslinked peptides. PLoS One 2021; 16:e0254450. [PMID: 34242352 PMCID: PMC8270460 DOI: 10.1371/journal.pone.0254450] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 06/25/2021] [Indexed: 12/14/2022] Open
Abstract
Isopeptide crosslinked proteins can be the product of transglutaminase or of exposure to organophosphorus toxicants (OP). Transglutaminase links glutamine to lysine with loss of ammonia. OP toxicants induce a link between glutamic acid and lysine with loss of water. Our goal was to establish criteria to distinguish real from false isopeptide crosslinks reported by software searches of mass spectrometry data. We used fragmentation spectra of tryptic peptides from MAP-rich tubulin Sus scrofa as a test system for detection of naturally-occurring isopeptide crosslinks. Data were analyzed with Protein Prospector. Criteria for the assignments included the presence of at least 1 crosslink specific product ion, fragment ions from both peptides, Protein Prospector scores ≥20, and best fit of the MS/MS data to the crosslinked peptide as opposed to a linear peptide. Out of 301,364 spectra, 15 potential transglutaminase-type crosslinked peptide candidates were identified. Manual evaluation of these MS/MS spectra reduced the number to 1 valid crosslink between Q112 of NFH and K368 of Tau. Immunopurification with anti-isopeptide 81D1C2 confirmed that MAP-rich tubulin contained only one isopeptide. Support for this isopeptide bond was obtained by showing that transglutaminase was capable of incorporating dansyl-aminohexyl -QQIV into K368. A model of the KIETHK-QLEAHNR isopeptide was synthesized with the aid of transglutaminase. MS/MS spectra of the model validated our interpretation of the native isopeptide. An OP-induced isopeptide bond between K163 of tubulin alpha-1A and E158 of tubulin beta-4B was induced by treating MAP-rich tubulin with 100 μM chlorpyrifos oxon. This crosslink was supported by the criteria described above and by the presence of diethoxyphospho-lysine 163 in the tubulin alpha-1A peptide. The information obtained in this work is valuable for future studies that aim to understand why exposure to OP is associated with increased risk of neurodegenerative disease.
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Affiliation(s)
- Lawrence M. Schopfer
- Eppley Institute, University of Nebraska Medical Center, Omaha, NE, United States of America
| | - Seda Onder
- Eppley Institute, University of Nebraska Medical Center, Omaha, NE, United States of America
- Department of Biochemistry, School of Pharmacy, Hacettepe University, Ankara, Turkey
| | - Oksana Lockridge
- Eppley Institute, University of Nebraska Medical Center, Omaha, NE, United States of America
- * E-mail:
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27
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Giese SH, Sinn LR, Wegner F, Rappsilber J. Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry. Nat Commun 2021; 12:3237. [PMID: 34050149 PMCID: PMC8163845 DOI: 10.1038/s41467-021-23441-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 04/26/2021] [Indexed: 12/13/2022] Open
Abstract
Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits the numbers of protein-protein interactions that can be confidently identified. Here, we leverage chromatographic retention time information to aid the identification of crosslinked peptides from mass spectra. Our Siamese machine learning model xiRT achieves highly accurate retention time predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. Importantly, supplementing the search engine score with retention time features leads to a substantial increase in protein-protein interactions without affecting confidence. This approach is not limited to cell lysates and multi-dimensional separation but also improves considerably the analysis of crosslinked multiprotein complexes with a single chromatographic dimension. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of crosslinking mass spectrometry analyses.
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Affiliation(s)
- Sven H Giese
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
- Data Analytics and Computational Statistics, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany
- Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Ludwig R Sinn
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Fritz Wegner
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany.
- Wellcome Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.
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28
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Chen ZL, Mao PZ, Zeng WF, Chi H, He SM. pDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning. J Proteome Res 2021; 20:2570-2582. [PMID: 33821641 DOI: 10.1021/acs.jproteome.0c01004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In cross-linking mass spectrometry, the identification of cross-linked peptide pairs heavily relies on the ability of a database search engine to measure the similarities between experimental and theoretical MS/MS spectra. However, the lack of accurate ion intensities in theoretical spectra impairs the performance of search engines, in particular, on proteome scales. Here we introduce pDeepXL, a deep neural network to predict MS/MS spectra of cross-linked peptide pairs. To train pDeepXL, we used the transfer-learning technique because it facilitated the training with limited benchmark data of cross-linked peptide pairs. Test results on more than ten data sets showed that pDeepXL accurately predicted the spectra of both noncleavable DSS/BS3/Leiker cross-linked peptide pairs (>80% of predicted spectra have Pearson's r values higher than 0.9) and cleavable DSSO/DSBU cross-linked peptide pairs (>75% of predicted spectra have Pearson's r values higher than 0.9). pDeepXL also achieved the accurate prediction on unseen data sets using an online fine-tuning technique. Lastly, integrating pDeepXL into a database search engine increased the number of identified cross-link spectra by 18% on average.
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Affiliation(s)
- Zhen-Lin Chen
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peng-Zhi Mao
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wen-Feng Zeng
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hao Chi
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Si-Min He
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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29
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de Jong L, Roseboom W, Kramer G. Towards low false discovery rate estimation for protein-protein interactions detected by chemical cross-linking. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2021; 1869:140655. [PMID: 33812047 DOI: 10.1016/j.bbapap.2021.140655] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/28/2021] [Accepted: 03/29/2021] [Indexed: 01/16/2023]
Abstract
Chemical cross-linking (CX) of proteins in vivo or in cell free extracts followed by mass spectrometric (MS) identification of linked peptide pairs (CXMS) can reveal protein-protein interactions (PPIs) both at a proteome wide scale and the level of cross-linked amino acid residues. However, error estimation at the level of PPI remains challenging in large scale datasets. Here we discuss recent advances in the recognition of spurious inter-protein peptide pairs and in diminishing the FDR for these PPI-signaling cross-links, such as the use of chromatographic retention time prediction, in order to come to a more reliable reporting of PPIs.
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Affiliation(s)
- Luitzen de Jong
- Swammerdam Institute for Life Sciences, Mass Spectrometry of Biomolecules, University of Amsterdam, Science Park 904, 1098 HX Amsterdam, the Netherlands.
| | - Winfried Roseboom
- Swammerdam Institute for Life Sciences, Mass Spectrometry of Biomolecules, University of Amsterdam, Science Park 904, 1098 HX Amsterdam, the Netherlands
| | - Gertjan Kramer
- Swammerdam Institute for Life Sciences, Mass Spectrometry of Biomolecules, University of Amsterdam, Science Park 904, 1098 HX Amsterdam, the Netherlands
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30
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Jack A, Ferro LS, Trnka MJ, Wehri E, Nadgir A, Nguyenla X, Costa K, Stanley S, Schaletzky J, Yildiz A. SARS-CoV-2 nucleocapsid protein forms condensates with viral genomic RNA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2020.09.14.295824. [PMID: 32995779 PMCID: PMC7523105 DOI: 10.1101/2020.09.14.295824] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes COVID-19, a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. Phase separation is driven, in part, by hydrophobic and electrostatic interactions. While the N protein forms spherical assemblies with unstructured RNA, it forms asymmetric condensates with viral RNA strands that contain secondary structure elements. Cross-linking mass spectrometry identified a region that forms interactions between N proteins in condensates, and truncation of this region disrupts phase separation. We also identified small molecules that alter the formation of N protein condensates. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle.
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Affiliation(s)
- Amanda Jack
- Biophysics Graduate Group, University of California, Berkeley CA
| | - Luke S. Ferro
- Department of Molecular and Cellular Biology, University of California, Berkeley CA
| | - Michael J. Trnka
- Department of Pharmaceutical Chemistry, University of California, San Francisco CA
| | - Eddie Wehri
- Center for Emerging and Neglected Diseases, University of California, Berkeley CA
| | - Amrut Nadgir
- Physics Department, University of California, Berkeley CA
| | - Xammy Nguyenla
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, CA
| | | | - Sarah Stanley
- Department of Molecular and Cellular Biology, University of California, Berkeley CA
- School of Public Health, Division of Infectious Diseases and Vaccinology, University of California, Berkeley, CA
| | - Julia Schaletzky
- Center for Emerging and Neglected Diseases, University of California, Berkeley CA
| | - Ahmet Yildiz
- Biophysics Graduate Group, University of California, Berkeley CA
- Department of Molecular and Cellular Biology, University of California, Berkeley CA
- Physics Department, University of California, Berkeley CA
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31
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Mendes ML, Dittmar G. Analysis of the Dynamic Proteasome Structure by Cross-Linking Mass Spectrometry. Biomolecules 2021; 11:biom11040505. [PMID: 33801594 PMCID: PMC8067131 DOI: 10.3390/biom11040505] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/19/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
The 26S proteasome is a macromolecular complex that degrades proteins maintaining cell homeostasis; thus, determining its structure is a priority to understand its function. Although the 20S proteasome's structure has been known for some years, the highly dynamic nature of the 19S regulatory particle has presented a challenge to structural biologists. Advances in cryo-electron microscopy (cryo-EM) made it possible to determine the structure of the 19S regulatory particle and showed at least seven different conformational states of the proteasome. However, there are still many questions to be answered. Cross-linking mass spectrometry (CLMS) is now routinely used in integrative structural biology studies, and it promises to take integrative structural biology to the next level, answering some of these questions.
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32
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Abstract
Cross-linking, in general, involves the covalent linkage of two amino acid residues of proteins or protein complexes in close proximity. Mass spectrometry and computational analysis are then applied to identify the formed linkage and deduce structural information such as distance restraints. Quantitative cross-linking coupled with mass spectrometry is well suited to study protein dynamics and conformations of protein complexes. The quantitative cross-linking workflow described here is based on the application of isotope labelled cross-linkers. Proteins or protein complexes present in different structural states are differentially cross-linked using a "light" and a "heavy" cross-linker. The intensity ratios of cross-links (i.e., light/heavy or heavy/light) indicate structural changes or interactions that are maintained in the different states. These structural insights lead to a better understanding of the function of the proteins or protein complexes investigated. The described workflow is applicable to a wide range of research questions including, for instance, protein dynamics or structural changes upon ligand binding.
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Affiliation(s)
- Marie Barth
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Institute for Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Carla Schmidt
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Institute for Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle, Germany.
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33
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Saltzberg DJ, Viswanath S, Echeverria I, Chemmama IE, Webb B, Sali A. Using Integrative Modeling Platform to compute, validate, and archive a model of a protein complex structure. Protein Sci 2020; 30:250-261. [PMID: 33166013 DOI: 10.1002/pro.3995] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/06/2020] [Accepted: 11/06/2020] [Indexed: 12/18/2022]
Abstract
Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).
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Affiliation(s)
- Daniel J Saltzberg
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Ignacia Echeverria
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA.,Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
| | - Ilan E Chemmama
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Ben Webb
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
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34
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Netz E, Dijkstra TMH, Sachsenberg T, Zimmermann L, Walzer M, Monecke T, Ficner R, Dybkov O, Urlaub H, Kohlbacher O. OpenPepXL: An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides in XL-MS. Mol Cell Proteomics 2020; 19:2157-2168. [PMID: 33067342 PMCID: PMC7710140 DOI: 10.1074/mcp.tir120.002186] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 09/15/2020] [Indexed: 11/06/2022] Open
Abstract
Cross-linking MS (XL-MS) has been recognized as an effective source of information about protein structures and interactions. In contrast to regular peptide identification, XL-MS has to deal with a quadratic search space, where peptides from every protein could potentially be cross-linked to any other protein. To cope with this search space, most tools apply different heuristics for search space reduction. We introduce a new open-source XL-MS database search algorithm, OpenPepXL, which offers increased sensitivity compared with other tools. OpenPepXL searches the full search space of an XL-MS experiment without using heuristics to reduce it. Because of efficient data structures and built-in parallelization OpenPepXL achieves excellent runtimes and can also be deployed on large compute clusters and cloud services while maintaining a slim memory footprint. We compared OpenPepXL to several other commonly used tools for identification of noncleavable labeled and label-free cross-linkers on a diverse set of XL-MS experiments. In our first comparison, we used a data set from a fraction of a cell lysate with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL finds from 7% to over 50% more unique residue pairs (URPs) than other tools. On data sets with available high-resolution structures for cross-link validation OpenPepXL reports from 7% to over 40% more structurally validated URPs than other tools. Additionally, we used a synthetic peptide data set that allows objective validation of cross-links without relying on structural information and found that OpenPepXL reports at least 12% more validated URPs than other tools. It has been built as part of the OpenMS suite of tools and supports Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML 1.2 format for XL-MS identification results. It is freely available under a three-clause BSD license at https://openms.org/openpepxl.
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Affiliation(s)
- Eugen Netz
- Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany.
| | - Tjeerd M H Dijkstra
- Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany; Center for Women's Health, University Clinic Tübingen, Tübingen, Germany
| | - Timo Sachsenberg
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany
| | - Lukas Zimmermann
- Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany
| | - Mathias Walzer
- Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Thomas Monecke
- X-Ray Crystallography Facility, Institute of Pharmaceutical Biotechnology, University of Ulm, Ulm, Germany; Department of Molecular Structural BiologyInstitute for Microbiology and GeneticsGZMB, Georg-August-University Göttingen, Göttingen, Germany
| | - Ralf Ficner
- Department of Molecular Structural BiologyInstitute for Microbiology and GeneticsGZMB, Georg-August-University Göttingen, Göttingen, Germany
| | - Olexandr Dybkov
- Department for Cellular BiochemistryMax Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Henning Urlaub
- Bioanalytical Mass SpectrometryMax Planck Institute for Biophysical Chemistry, Göttingen, Germany; BioanalyticsInstitute for Clinical Chemistry, University Medical Center, Göttingen, Germany
| | - Oliver Kohlbacher
- Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany; Quantitative Biology Center, University of Tübingen, Tübingen, Germany.
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35
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Toward Increased Reliability, Transparency, and Accessibility in Cross-linking Mass Spectrometry. Structure 2020; 28:1259-1268. [PMID: 33065067 DOI: 10.1016/j.str.2020.09.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 09/02/2020] [Accepted: 09/24/2020] [Indexed: 01/09/2023]
Abstract
Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative.
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36
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Gupta R, Liu Y, Wang H, Nordyke CT, Puterbaugh RZ, Cui W, Varga K, Chu F, Ke H, Vashisth H, Cote RH. Structural Analysis of the Regulatory GAF Domains of cGMP Phosphodiesterase Elucidates the Allosteric Communication Pathway. J Mol Biol 2020; 432:5765-5783. [PMID: 32898583 PMCID: PMC7572642 DOI: 10.1016/j.jmb.2020.08.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/28/2020] [Accepted: 08/31/2020] [Indexed: 12/26/2022]
Abstract
Regulation of photoreceptor phosphodiesterase (PDE6) activity is responsible for the speed, sensitivity, and recovery of the photoresponse during visual signaling in vertebrate photoreceptor cells. It is hypothesized that physiological differences in the light responsiveness of rods and cones may result in part from differences in the structure and regulation of the distinct isoforms of rod and cone PDE6. Although rod and cone PDE6 catalytic subunits share a similar domain organization consisting of tandem GAF domains (GAFa and GAFb) and a catalytic domain, cone PDE6 is a homodimer whereas rod PDE6 consists of two homologous catalytic subunits. Here we provide the x-ray crystal structure of cone GAFab regulatory domain solved at 3.3 Å resolution, in conjunction with chemical cross-linking and mass spectrometric analysis of conformational changes to GAFab induced upon binding of cGMP and the PDE6 inhibitory γ-subunit (Pγ). Ligand-induced changes in cross-linked residues implicate multiple conformational changes in the GAFa and GAFb domains in forming an allosteric communication network. Molecular dynamics simulations of cone GAFab revealed differences in conformational dynamics of the two subunits forming the homodimer and allosteric perturbations on cGMP binding. Cross-linking of Pγ to GAFab in conjunction with solution NMR spectroscopy of isotopically labeled Pγ identified the central polycationic region of Pγ interacting with the GAFb domain. These results provide a mechanistic basis for developing allosteric activators of PDE6 with therapeutic implications for halting the progression of several retinal degenerative diseases.
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Affiliation(s)
- Richa Gupta
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA
| | - Yong Liu
- Department of Chemical Engineering, University of New Hampshire, 33 Academic Way, Durham, NH 03824, USA
| | - Huanchen Wang
- Signal Transduction Laboratory, NIEHS/NIH, 111 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA
| | - Christopher T Nordyke
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA
| | - Ryan Z Puterbaugh
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA
| | - Wenjun Cui
- Department of Biochemistry and Biophysics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Krisztina Varga
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA
| | - Feixia Chu
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA
| | - Hengming Ke
- Department of Biochemistry and Biophysics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, 33 Academic Way, Durham, NH 03824, USA
| | - Rick H Cote
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, 46 College Rd., Durham, NH 03824, USA.
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Huang R, Gao X, Xu Z, Zhu W, Wei D, Jiang B, Chen H, Chen W. Decision Tree Searching Strategy to Boost the Identification of Cross-Linked Peptides. Anal Chem 2020; 92:13702-13710. [DOI: 10.1021/acs.analchem.0c00452] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Rong Huang
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Xiuxia Gao
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Zili Xu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Wei Zhu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Ding Wei
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Biao Jiang
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Hongli Chen
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Wenzhang Chen
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
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McGilvray PT, Anghel SA, Sundaram A, Zhong F, Trnka MJ, Fuller JR, Hu H, Burlingame AL, Keenan RJ. An ER translocon for multi-pass membrane protein biogenesis. eLife 2020; 9:e56889. [PMID: 32820719 PMCID: PMC7505659 DOI: 10.7554/elife.56889] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 08/20/2020] [Indexed: 12/23/2022] Open
Abstract
Membrane proteins with multiple transmembrane domains play critical roles in cell physiology, but little is known about the machinery coordinating their biogenesis at the endoplasmic reticulum. Here we describe a ~ 360 kDa ribosome-associated complex comprising the core Sec61 channel and five accessory factors: TMCO1, CCDC47 and the Nicalin-TMEM147-NOMO complex. Cryo-electron microscopy reveals a large assembly at the ribosome exit tunnel organized around a central membrane cavity. Similar to protein-conducting channels that facilitate movement of transmembrane segments, cytosolic and luminal funnels in TMCO1 and TMEM147, respectively, suggest routes into the central membrane cavity. High-throughput mRNA sequencing shows selective translocon engagement with hundreds of different multi-pass membrane proteins. Consistent with a role in multi-pass membrane protein biogenesis, cells lacking different accessory components show reduced levels of one such client, the glutamate transporter EAAT1. These results identify a new human translocon and provide a molecular framework for understanding its role in multi-pass membrane protein biogenesis.
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Affiliation(s)
- Philip T McGilvray
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
| | - S Andrei Anghel
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
- Department of Molecular Genetics and Cell Biology, The University of ChicagoChicagoUnited States
| | - Arunkumar Sundaram
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
| | - Frank Zhong
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
- Department of Molecular Genetics and Cell Biology, The University of ChicagoChicagoUnited States
| | - Michael J Trnka
- Department of Pharmaceutical Chemistry, University of California, San FranciscoSan FranciscoUnited States
| | - James R Fuller
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
| | - Hong Hu
- Center for Research Informatics, The University of ChicagoChicagoUnited States
| | - Alma L Burlingame
- Department of Pharmaceutical Chemistry, University of California, San FranciscoSan FranciscoUnited States
| | - Robert J Keenan
- Department of Biochemistry and Molecular Biology, The University of ChicagoChicagoUnited States
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Ziemianowicz DS, Sarpe V, Crowder D, Pells TJ, Raval S, Hepburn M, Rafiei A, Schriemer DC. Harmonizing structural mass spectrometry analyses in the mass spec studio. J Proteomics 2020; 225:103844. [DOI: 10.1016/j.jprot.2020.103844] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 05/23/2020] [Accepted: 05/24/2020] [Indexed: 01/06/2023]
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Rodríguez Mallón A, Javier González L, Encinosa Guzmán PE, Bechara GH, Sanches GS, Pousa S, Cabrera G, Cabrales A, Garay H, Mejías R, López Álvarez JR, Bello Soto Y, Almeida F, Guirola O, Rodríguez Fernández R, Fuentes Castillo A, Méndez L, Jiménez S, Licea-Navarro A, Portela M, Durán R, Estrada MP. Functional and Mass Spectrometric Evaluation of an Anti-Tick Antigen Based on the P0 Peptide Conjugated to Bm86 Protein. Pathogens 2020; 9:pathogens9060513. [PMID: 32630414 PMCID: PMC7350365 DOI: 10.3390/pathogens9060513] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 06/20/2020] [Accepted: 06/21/2020] [Indexed: 11/16/2022] Open
Abstract
A synthetic 20 amino acid peptide of the ribosomal protein P0 from ticks, when conjugated to keyhole limpet hemocyanin from Megathura crenulata and used as an immunogen against Rhipicephalus microplus and Rhipicephalus sanguineus s.l. species, has shown efficacies of around 90%. There is also experimental evidence of a high efficacy of this conjugate against Amblyomma mixtum and Ixodes ricinus species, which suggest that this antigen could be a good broad-spectrum anti-tick vaccine candidate. In this study, the P0 peptide (pP0) was chemically conjugated to Bm86 as a carrier protein. SDS-PAGE analysis of this conjugate demonstrated that it is highly heterogeneous in size, carrying from 1 to 18 molecules of pP0 per molecule of Bm86. Forty-nine out of the 54 lysine residues and the N-terminal end of Bm86 were found partially linked to pP0 by using LC-MS/MS analysis and the combination of four different softwares. Several post-translational modifications of Bm86 protein were also identified by mass spectrometry. High immunogenicity and efficacy were achieved when dogs and cattle were vaccinated with the pP0-Bm86 conjugate and challenged with R. sanguineus s.l. and R. microplus, respectively. These results encourage the development of this antigen with promising possibilities as an anti-tick vaccine.
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Affiliation(s)
- Alina Rodríguez Mallón
- Animal Biotechnology Department, Center for Genetic Engineering and Biotechnology (CIGB), Havana 10600, Cuba; (P.E.E.G.); (Y.B.S.); (M.P.E.)
- Correspondence: ; Tel.: +53-72504407
| | - Luis Javier González
- Mass Spectrometry Laboratory and GlycoLab, Department of Proteomics, CIGB, Havana 10600, Cuba; (L.J.G.); (S.P.); (G.C.); (F.A.)
| | - Pedro Enrique Encinosa Guzmán
- Animal Biotechnology Department, Center for Genetic Engineering and Biotechnology (CIGB), Havana 10600, Cuba; (P.E.E.G.); (Y.B.S.); (M.P.E.)
| | - Gervasio Henrique Bechara
- Programa de Pós-graduação em Ciência Animal, Pontifícia Universidade Católica do Paraná (PUCPR), Paraná 80215-901, Brazil; (G.H.B.); (G.S.S.)
- Departamento de Patologia Veterinária, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (FCAV-UNESP), São Paulo 14884-900, Brazil
| | - Gustavo Seron Sanches
- Programa de Pós-graduação em Ciência Animal, Pontifícia Universidade Católica do Paraná (PUCPR), Paraná 80215-901, Brazil; (G.H.B.); (G.S.S.)
- Departamento de Patologia Veterinária, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (FCAV-UNESP), São Paulo 14884-900, Brazil
| | - Satomy Pousa
- Mass Spectrometry Laboratory and GlycoLab, Department of Proteomics, CIGB, Havana 10600, Cuba; (L.J.G.); (S.P.); (G.C.); (F.A.)
| | - Gleysin Cabrera
- Mass Spectrometry Laboratory and GlycoLab, Department of Proteomics, CIGB, Havana 10600, Cuba; (L.J.G.); (S.P.); (G.C.); (F.A.)
| | - Ania Cabrales
- Synthetic Peptides Group, CIGB, Havana 10600, Cuba; (A.C.); (H.G.)
| | - Hilda Garay
- Synthetic Peptides Group, CIGB, Havana 10600, Cuba; (A.C.); (H.G.)
| | - Raúl Mejías
- Instituto de Ciencia Animal (ICA), San José de las Lajas 32700, Cuba; (R.M.); (J.R.L.Á.)
| | | | - Yamil Bello Soto
- Animal Biotechnology Department, Center for Genetic Engineering and Biotechnology (CIGB), Havana 10600, Cuba; (P.E.E.G.); (Y.B.S.); (M.P.E.)
| | - Fabiola Almeida
- Mass Spectrometry Laboratory and GlycoLab, Department of Proteomics, CIGB, Havana 10600, Cuba; (L.J.G.); (S.P.); (G.C.); (F.A.)
| | | | | | - Alier Fuentes Castillo
- National Laboratory for Parasitology, San Antonio de los Banos 32500, Cuba; (R.R.F.); (A.F.C.); (L.M.)
| | - Luis Méndez
- National Laboratory for Parasitology, San Antonio de los Banos 32500, Cuba; (R.R.F.); (A.F.C.); (L.M.)
| | - Samanta Jiménez
- Departamento de Innovación Biomédica, CICESE, Ensenada 22860, Mexico; (S.J.); (A.L.-N.)
| | - Alexei Licea-Navarro
- Departamento de Innovación Biomédica, CICESE, Ensenada 22860, Mexico; (S.J.); (A.L.-N.)
| | - Madelón Portela
- Unidad de Bioquímica y Proteómica Analítica, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay; (M.P.); (R.D.)
- Instituto de Investigaciones Biológicas Clemente Estable (IIBCE), Montevideo 11600, Uruguay
| | - Rosario Durán
- Unidad de Bioquímica y Proteómica Analítica, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay; (M.P.); (R.D.)
- Instituto de Investigaciones Biológicas Clemente Estable (IIBCE), Montevideo 11600, Uruguay
| | - Mario Pablo Estrada
- Animal Biotechnology Department, Center for Genetic Engineering and Biotechnology (CIGB), Havana 10600, Cuba; (P.E.E.G.); (Y.B.S.); (M.P.E.)
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41
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Na S, Paek E. Computational methods in mass spectrometry-based structural proteomics for studying protein structure, dynamics, and interactions. Comput Struct Biotechnol J 2020; 18:1391-1402. [PMID: 32637038 PMCID: PMC7322682 DOI: 10.1016/j.csbj.2020.06.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/01/2020] [Accepted: 06/01/2020] [Indexed: 12/28/2022] Open
Abstract
Mass spectrometry (MS) has made enormous contributions to comprehensive protein identification and quantification in proteomics. MS is also gaining momentum for structural biology in a variety of ways, complementing conventional structural biology techniques. Here, we will review how MS-based techniques, such as hydrogen/deuterium exchange, covalent labeling, and chemical cross-linking, enable the characterization of protein structure, dynamics, and interactions, especially from a perspective of their data analyses. Structural information encoded by chemical probes in intact proteins is decoded by interpreting MS data at a peptide level, i.e., revealing conformational and dynamic changes in local regions of proteins. The structural MS data are not amenable to data analyses in traditional proteomics workflow, requiring dedicated software for each type of data. We first provide basic principles of data interpretation, including isotopic distribution and peptide sequencing. We then focus particularly on computational methods for structural MS data analyses and discuss outstanding challenges in a proteome-wide large scale analysis.
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Affiliation(s)
- Seungjin Na
- Dept. of Computer Science, Hanyang University, Seoul 04763, Republic of Korea
| | - Eunok Paek
- Dept. of Computer Science, Hanyang University, Seoul 04763, Republic of Korea
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42
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Zhao B, Reilly CP, Davis C, Matouschek A, Reilly JP. Use of Multiple Ion Fragmentation Methods to Identify Protein Cross-Links and Facilitate Comparison of Data Interpretation Algorithms. J Proteome Res 2020; 19:2758-2771. [PMID: 32496805 DOI: 10.1021/acs.jproteome.0c00111] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Multiple ion fragmentation methods involving collision-induced dissociation (CID), higher-energy collisional dissociation (HCD) with regular and very high energy settings, and electron-transfer dissociation with supplementary HCD (EThcD) are implemented to improve the confidence of cross-link identifications. Three different S. cerevisiae proteasome samples cross-linked by diethyl suberthioimidate (DEST) or bis(sulfosuccinimidyl)suberate (BS3) are analyzed. Two approaches are introduced to combine interpretations from the above four methods. Working with cleavable cross-linkers such as DEST, the first approach searches for cross-link diagnostic ions and consistency among the best interpretations derived from all four MS2 spectra associated with each precursor ion. Better agreement leads to a more definitive identification. Compatible with both cleavable and noncleavable cross-linkers such as BS3, the second approach multiplies scoring metrics from a number of fragmentation experiments to derive an overall best match. This significantly increases the scoring gap between the target and decoy matches. The validity of cross-links fragmented by HCD alone and identified by Kojak, MeroX, pLink, and Xi was evaluated using multiple fragmentation data. Possible ways to improve the identification credibility are discussed. Data are available via ProteomeXchange with identifier PXD018310.
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Affiliation(s)
- Bingqing Zhao
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Colin P Reilly
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Caroline Davis
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Andreas Matouschek
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, United States
| | - James P Reilly
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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43
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von Appen A, LaJoie D, Johnson IE, Trnka MJ, Pick SM, Burlingame AL, Ullman KS, Frost A. LEM2 phase separation promotes ESCRT-mediated nuclear envelope reformation. Nature 2020; 582:115-118. [PMID: 32494070 PMCID: PMC7321842 DOI: 10.1038/s41586-020-2232-x] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 02/26/2020] [Indexed: 01/01/2023]
Abstract
During cell division, remodelling of the nuclear envelope enables chromosome segregation by the mitotic spindle1. The reformation of sealed nuclei requires ESCRTs (endosomal sorting complexes required for transport) and LEM2, a transmembrane ESCRT adaptor2-4. Here we show how the ability of LEM2 to condense on microtubules governs the activation of ESCRTs and coordinated spindle disassembly. The LEM motif of LEM2 binds BAF, conferring on LEM2 an affinity for chromatin5,6, while an adjacent low-complexity domain (LCD) promotes LEM2 phase separation. A proline-arginine-rich sequence within the LCD binds to microtubules and targets condensation of LEM2 to spindle microtubules that traverse the nascent nuclear envelope. Furthermore, the winged-helix domain of LEM2 activates the ESCRT-II/ESCRT-III hybrid protein CHMP7 to form co-oligomeric rings. Disruption of these events in human cells prevented the recruitment of downstream ESCRTs, compromised spindle disassembly, and led to defects in nuclear integrity and DNA damage. We propose that during nuclear reassembly LEM2 condenses into a liquid-like phase and coassembles with CHMP7 to form a macromolecular O-ring seal at the confluence between membranes, chromatin and the spindle. The properties of LEM2 described here, and the homologous architectures of related inner nuclear membrane proteins7,8, suggest that phase separation may contribute to other critical envelope functions, including interphase repair8-13 and chromatin organization14-17.
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Affiliation(s)
- Alexander von Appen
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
| | - Dollie LaJoie
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Isabel E Johnson
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
| | - Michael J Trnka
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Sarah M Pick
- Faculty of Chemistry and Pharmacy, University of Freiburg, Freiburg, Germany
| | - Alma L Burlingame
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Katharine S Ullman
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
| | - Adam Frost
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA.
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44
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Yu C, Novitsky EJ, Cheng NW, Rychnovsky SD, Huang L. Exploring Spacer Arm Structures for Designs of Asymmetric Sulfoxide-Containing MS-Cleavable Cross-Linkers. Anal Chem 2020; 92:6026-6033. [PMID: 32202417 PMCID: PMC7363200 DOI: 10.1021/acs.analchem.0c00298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cross-linking mass spectrometry (XL-MS) has become a powerful structural tool for defining protein-protein interactions (PPIs) and elucidating architectures of large protein assemblies. To advance XL-MS studies, we have previously developed a series of sulfoxide-containing MS-cleavable cross-linkers to facilitate the detection and identification of cross-linked peptides using multistage mass spectrometry (MSn). While current sulfoxide-based cross-linkers are effective for in vivo and in vitro XL-MS studies at the systems-level, new reagents are still needed to help expand PPI coverage. To this end, we have designed and synthesized six variable-length derivatives of disuccinimidyl sulfoxide (DSSO) to better understand the effects of spacer arm modulation on MS-cleavability, fragmentation characteristics, and MS identification of cross-linked peptides. In addition, the impact on cross-linking reactivity was evaluated. Moreover, alternative MS2-based workflows were explored to determine their feasibility for analyzing new sulfoxide-containing cross-linked products. Based on the results of synthetic peptides and a model protein, we have further demonstrated the robustness and predictability of sulfoxide chemistry in designing MS-cleavable cross-linkers. Importantly, we have identified a unique asymmetric design that exhibits preferential fragmentation of cross-links over peptide backbones, a desired feature for MSn analysis. This work has established a solid foundation for further development of sulfoxide-containing MS-cleavable cross-linkers with new functionalities.
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Affiliation(s)
- Clinton Yu
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
| | - Eric J. Novitsky
- Department of Chemistry, University of California, Irvine, CA 92697
| | - Nicholas W. Cheng
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
| | | | - Lan Huang
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
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45
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Identifying transglutaminase reaction products via mass spectrometry as exemplified by the MUC2 mucin - Pitfalls and traps. Anal Biochem 2020; 597:113668. [PMID: 32222540 PMCID: PMC7184670 DOI: 10.1016/j.ab.2020.113668] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 02/15/2020] [Accepted: 02/27/2020] [Indexed: 12/26/2022]
Abstract
In order to demonstrate transglutaminase activity in biological samples immunological as well as glutamine- and amine-donor based assays are commonly used. However, the identification of the transglutaminase reaction product, i. e. the isopeptide cross-linked peptides/proteins or the deamidated protein/peptide are often neglected. This article describes a workflow for the detection of the products of transglutaminase-catalyzed reactions. In particular, possible pitfalls and traps that can arise during the mass spectrometry-based identification of isopeptide cross-links are addressed and characterised on actual samples.
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46
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Beveridge R, Stadlmann J, Penninger JM, Mechtler K. A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes. Nat Commun 2020; 11:742. [PMID: 32029734 PMCID: PMC7005041 DOI: 10.1038/s41467-020-14608-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 01/21/2020] [Indexed: 01/06/2023] Open
Abstract
Crosslinking-mass spectrometry (XL-MS) serves to identify interaction sites between proteins. Numerous search engines for crosslink identification exist, but lack of ground truth samples containing known crosslinks has precluded their systematic validation. Here we report on XL-MS data arising from measuring synthetic peptide libraries that provide the unique benefit of knowing which identified crosslinks are true and which are false. The data are analysed with the most frequently used search engines and the results filtered to an estimated false discovery rate of 5%. We find that the actual false crosslink identification rates range from 2.4 to 32%, depending on the analysis strategy employed. Furthermore, the use of MS-cleavable crosslinkers does not reduce the false discovery rate compared to non-cleavable crosslinkers. We anticipate that the datasets acquired during this research will further drive optimisation and development of XL-MS search engines, thereby advancing our understanding of vital biological interactions.
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Affiliation(s)
- Rebecca Beveridge
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030, Vienna, Austria
| | - Johannes Stadlmann
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030, Vienna, Austria.
| | - Josef M Penninger
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030, Vienna, Austria
- Department of medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver Campus, 2350 Health Sciences Mall, Vancouver, BCV6T 1Z3, Canada
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030, Vienna, Austria.
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030, Vienna, Austria.
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47
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Bartolec TK, Smith DL, Pang CNI, Xu YD, Hamey JJ, Wilkins MR. 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. Anal Chem 2020; 92:1874-1882. [PMID: 31851481 DOI: 10.1021/acs.analchem.9b03975] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Saccharomyces cerevisiae has the most comprehensively characterized protein-protein interaction network, or interactome, of any eukaryote. This has predominantly been generated through multiple, systematic studies of protein-protein interactions by two-hybrid techniques and of affinity-purified protein complexes. A pressing question is to understand how large-scale cross-linking mass spectrometry (XL-MS) can confirm and extend this interactome. Here, intact yeast nuclei were subject to cross-linking with disuccinimidyl sulfoxide (DSSO) and analyzed using hybrid MS2-MS3 methods. XlinkX identified a total of 2,052 unique residue pair cross-links at 1% FDR. Intraprotein cross-links were found to provide extensive structural constraint data, with almost all intralinks that mapped to known structures and slightly fewer of those mapping to homology models being within 30 Å. Intralinks provided structural information for a further 366 proteins. A method for optimizing interprotein cross-link score cut-offs was developed, through use of extensive known yeast interactions. Its application led to a high confidence, yeast nuclear interactome. Strikingly, almost half of the interactions were not previously detected by two-hybrid or AP-MS techniques. Multiple lines of evidence existed for many such interactions, whether through literature or ortholog interaction data, through multiple unique interlinks between proteins, and/or through replicates. We conclude that XL-MS is a powerful means to measure interactions, that complements two-hybrid and affinity-purification techniques.
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Affiliation(s)
- Tara K Bartolec
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences , University of New South Wales , Sydney , New South Wales 2052 , Australia
| | - Daniela-Lee Smith
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences , University of New South Wales , Sydney , New South Wales 2052 , Australia
| | - Chi Nam Ignatius Pang
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences , University of New South Wales , Sydney , New South Wales 2052 , Australia
| | - You Dan Xu
- Centre for Advanced Macromolecular Design, School of Chemistry , University of New South Wales , Sydney , New South Wales 2052 , Australia
| | - Joshua J Hamey
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences , University of New South Wales , Sydney , New South Wales 2052 , Australia
| | - Marc R Wilkins
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences , University of New South Wales , Sydney , New South Wales 2052 , Australia
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48
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Abstract
Macromolecular complexes play a key role in cellular function. Predicting the structure and dynamics of these complexes is one of the key challenges in structural biology. Docking applications have traditionally been used to predict pairwise interactions between proteins. However, few methods exist for modeling multi-protein assemblies. Here we present two methods, CombDock and DockStar, that can predict multi-protein assemblies starting from subunit structural models. CombDock can assemble subunits without any assumptions about the pairwise interactions between subunits, while DockStar relies on the interaction graph or, alternatively, a homology model or a cryo-electron microscopy (EM) density map of the entire complex. We demonstrate the two methods using RNA polymerase II with 12 subunits and TRiC/CCT chaperonin with 16 subunits.
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Affiliation(s)
- Dina Schneidman-Duhovny
- School of Computer Science and Engineering and the Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Haim J Wolfson
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
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Xiang Y, Shen Z, Shi Y. Chemical Cross-Linking and Mass Spectrometric Analysis of the Endogenous Yeast Exosome Complexes. Methods Mol Biol 2020; 2062:383-400. [PMID: 31768986 DOI: 10.1007/978-1-4939-9822-7_18] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Chemical cross-linking and mass spectrometric readout (CX-MS) has become a useful toolkit for structural analysis of protein complexes. CX-MS enables rapid detection of a larger number of cross-link peptides from the chemically cross-linked protein assembly, providing invaluable cross-link spatial restraints to understand the architecture of the complex. Since CX-MS is complementary with other structural and computational modeling tools, it can be used for integrative structural determination of large native protein assemblies. However, due to technical limitations, current CX-MS applications have still been predominantly confined to complexes reconstituted from recombinant proteins where large amount of purified materials are available. Cross-linking and hybrid structural proteomic analysis of endogenous protein complexes remains a challenge. In this chapter, we present a protocol that efficiently couples affinity capture of endogenous complexes with sensitive CX-MS analysis, with particular application to the yeast RNA processing exosome complexes.
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Affiliation(s)
- Yufei Xiang
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Zhuolun Shen
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- School of Medicine, Tsinghua University, Beijing, China
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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50
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Keller A, Chavez JD, Bruce JE. Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks. Bioinformatics 2019; 35:895-897. [PMID: 30137231 DOI: 10.1093/bioinformatics/bty720] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 06/12/2018] [Accepted: 08/17/2018] [Indexed: 12/21/2022] Open
Abstract
MOTIVATION Peptides crosslinked with cleavable chemical crosslinkers are identified with mass spectrometry by independent database search of spectra associated with the two linked peptides. A major challenge is to combine together the evidence of the two peptides into an overall assessment of the two-peptide crosslink. RESULTS Here, we describe software that models crosslink specific information to automatically validate XL-MS cleavable peptide crosslinks. Using a dataset of crosslinked protein mixtures, we demonstrate that it computes accurate and highly discriminating probabilities, enabling as many as 75% more identifications than was previously possible using only search scores and a predictable false discovery rate. AVAILABILITY AND IMPLEMENTATION XLinkProphet software is freely available on the web at http://brucelab.gs.washington.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Andrew Keller
- 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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