1
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Goel RK, Bithi N, Emili A. Trends in co-fractionation mass spectrometry: A new gold-standard in global protein interaction network discovery. Curr Opin Struct Biol 2024; 88:102880. [PMID: 38996623 DOI: 10.1016/j.sbi.2024.102880] [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: 04/13/2024] [Revised: 06/13/2024] [Accepted: 06/19/2024] [Indexed: 07/14/2024]
Abstract
Co-fractionation mass spectrometry (CF-MS) uses biochemical fractionation to isolate and characterize macromolecular complexes from cellular lysates without the need for affinity tagging or capture. In recent years, this has emerged as a powerful technique for elucidating global protein-protein interaction networks in a wide variety of biospecimens. This review highlights the latest advancements in CF-MS experimental workflows including machine learning-guided analyses, for uncovering dynamic and high-resolution protein interaction landscapes with enhanced sensitivity, accuracy and throughput, enabling better biophysical characterization of endogenous protein complexes. By addressing challenges and emergent opportunities in the field, this review underscores the transformative potential of CF-MS in advancing our understanding of functional protein interaction networks in health and disease.
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Affiliation(s)
- Raghuveera Kumar Goel
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA.
| | - Nazmin Bithi
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA
| | - Andrew Emili
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA.
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2
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Lazear MR, Remsberg JR, Jaeger MG, Rothamel K, Her HL, DeMeester KE, Njomen E, Hogg SJ, Rahman J, Whitby LR, Won SJ, Schafroth MA, Ogasawara D, Yokoyama M, Lindsey GL, Li H, Germain J, Barbas S, Vaughan J, Hanigan TW, Vartabedian VF, Reinhardt CJ, Dix MM, Koo SJ, Heo I, Teijaro JR, Simon GM, Ghosh B, Abdel-Wahab O, Ahn K, Saghatelian A, Melillo B, Schreiber SL, Yeo GW, Cravatt BF. Proteomic discovery of chemical probes that perturb protein complexes in human cells. Mol Cell 2023; 83:1725-1742.e12. [PMID: 37084731 PMCID: PMC10198961 DOI: 10.1016/j.molcel.2023.03.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/09/2023] [Accepted: 03/28/2023] [Indexed: 04/23/2023]
Abstract
Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.
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Affiliation(s)
- Michael R Lazear
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | - Martin G Jaeger
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Katherine Rothamel
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hsuan-Lin Her
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | | | - Evert Njomen
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Simon J Hogg
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Jahan Rahman
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Landon R Whitby
- Vividion Therapeutics, 5820 Nancy Ridge Drive, San Diego, CA 92121, USA
| | - Sang Joon Won
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | | | - Minoru Yokoyama
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | - Haoxin Li
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Jason Germain
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Sabrina Barbas
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Joan Vaughan
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Thomas W Hanigan
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Vincent F Vartabedian
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA 92037, USA
| | | | - Melissa M Dix
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Seong Joo Koo
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Inha Heo
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - John R Teijaro
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA 92037, USA
| | - Gabriel M Simon
- Vividion Therapeutics, 5820 Nancy Ridge Drive, San Diego, CA 92121, USA
| | - Brahma Ghosh
- Discovery Chemistry, Janssen Research & Development, Spring House, PA 19477, USA
| | - Omar Abdel-Wahab
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Kay Ahn
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Spring House, PA 19477, USA
| | - Alan Saghatelian
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bruno Melillo
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA; Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02142, USA
| | - Stuart L Schreiber
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
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3
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High-Throughput Proteome Profiling of Plasma and Native Plasma Complexes Using Native Chromatography. Methods Mol Biol 2023; 2628:53-79. [PMID: 36781779 DOI: 10.1007/978-1-0716-2978-9_5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
We describe a high-throughput method for co-fractionation mass spectrometry (CF-MS) profiling for native plasma protein profiling. CF-MS allows the profiling of endogenous protein complexes between samples. Proteins often interact with other proteins and form macromolecular complexes that are different in disease states as well as cell states and cell types. This protocol describes an example for the sample preparation of 954 individual size exclusion chromatography (SEC) fractions, derived from 18 plasma samples that were separated into 53 fractions. Eighteen plasma samples were chosen based on the TMTpro multiplexing, but this methodology can be adapted for fewer or larger numbers of samples as appropriate. Our automated sample preparation method allows for high-throughput native plasma profiling, and we provide detailed methods for both a label-free and an isobaric labeling approach, discuss the merits of each approach, and detail the advantages of combining these strategies for comprehensive native plasma proteome profiling.
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4
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Samant RS, Batista S, Larance M, Ozer B, Milton CI, Bludau I, Wu E, Biggins L, Andrews S, Hervieu A, Johnston HE, Al-Lazikhani B, Lamond AI, Clarke PA, Workman P. Native Size-Exclusion Chromatography-Based Mass Spectrometry Reveals New Components of the Early Heat Shock Protein 90 Inhibition Response Among Limited Global Changes. Mol Cell Proteomics 2023; 22:100485. [PMID: 36549590 PMCID: PMC9898794 DOI: 10.1016/j.mcpro.2022.100485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 11/16/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
The molecular chaperone heat shock protein 90 (HSP90) works in concert with co-chaperones to stabilize its client proteins, which include multiple drivers of oncogenesis and malignant progression. Pharmacologic inhibitors of HSP90 have been observed to exert a wide range of effects on the proteome, including depletion of client proteins, induction of heat shock proteins, dissociation of co-chaperones from HSP90, disruption of client protein signaling networks, and recruitment of the protein ubiquitylation and degradation machinery-suggesting widespread remodeling of cellular protein complexes. However, proteomics studies to date have focused on inhibitor-induced changes in total protein levels, often overlooking protein complex alterations. Here, we use size-exclusion chromatography in combination with mass spectrometry (SEC-MS) to characterize the early changes in native protein complexes following treatment with the HSP90 inhibitor tanespimycin (17-AAG) for 8 h in the HT29 colon adenocarcinoma cell line. After confirming the signature cellular response to HSP90 inhibition (e.g., induction of heat shock proteins, decreased total levels of client proteins), we were surprised to find only modest perturbations to the global distribution of protein elution profiles in inhibitor-treated HT29 cells at this relatively early time-point. Similarly, co-chaperones that co-eluted with HSP90 displayed no clear difference between control and treated conditions. However, two distinct analysis strategies identified multiple inhibitor-induced changes, including known and unknown components of the HSP90-dependent proteome. We validate two of these-the actin-binding protein Anillin and the mitochondrial isocitrate dehydrogenase 3 complex-as novel HSP90 inhibitor-modulated proteins. We present this dataset as a resource for the HSP90, proteostasis, and cancer communities (https://www.bioinformatics.babraham.ac.uk/shiny/HSP90/SEC-MS/), laying the groundwork for future mechanistic and therapeutic studies related to HSP90 pharmacology. Data are available via ProteomeXchange with identifier PXD033459.
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Affiliation(s)
- Rahul S Samant
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom; Signalling Programme, The Babraham Institute, Cambridge, United Kingdom.
| | - Silvia Batista
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Mark Larance
- Centre for Gene Regulation & Expression, University of Dundee, Dundee, United Kingdom
| | - Bugra Ozer
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Christopher I Milton
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Isabell Bludau
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Estelle Wu
- Signalling Programme, The Babraham Institute, Cambridge, United Kingdom
| | - Laura Biggins
- Bioinformatics Group, The Babraham Institute, Cambridge, United Kingdom
| | - Simon Andrews
- Bioinformatics Group, The Babraham Institute, Cambridge, United Kingdom
| | - Alexia Hervieu
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Harvey E Johnston
- Signalling Programme, The Babraham Institute, Cambridge, United Kingdom
| | - Bissan Al-Lazikhani
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Angus I Lamond
- Centre for Gene Regulation & Expression, University of Dundee, Dundee, United Kingdom
| | - Paul A Clarke
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Paul Workman
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom.
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5
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Chihara K, Gerovac M, Hör J, Vogel J. Global profiling of the RNA and protein complexes of Escherichia coli by size exclusion chromatography followed by RNA sequencing and mass spectrometry (SEC-seq). RNA (NEW YORK, N.Y.) 2022; 29:rna.079439.122. [PMID: 36328526 PMCID: PMC9808575 DOI: 10.1261/rna.079439.122] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/27/2022] [Indexed: 06/16/2023]
Abstract
New methods for the global identification of RNA-protein interactions have led to greater recognition of the abundance and importance of RNA-binding proteins (RBPs) in bacteria. Here, we expand this tool kit by developing SEC-seq, a method based on a similar concept as the established Grad-seq approach. In Grad-seq, cellular RNA and protein complexes of a bacterium of interest are separated in a glycerol gradient, followed by high-throughput RNA-sequencing and mass spectrometry analyses of individual gradient fractions. New RNA-protein complexes are predicted based on the similarity of their elution profiles. In SEC-seq, we have replaced the glycerol gradient with separation by size exclusion chromatography, which shortens operation times and offers greater potential for automation. Applying SEC-seq to Escherichia coli, we find that the method provides a higher resolution than Grad-seq in the lower molecular weight range up to ~500 kDa. This is illustrated by the ability of SEC-seq to resolve two distinct, but similarly sized complexes of the global translational repressor CsrA with either of its antagonistic small RNAs, CsrB and CsrC. We also characterized changes in the SEC-seq profiles of the small RNA MicA upon deletion of its RNA chaperones Hfq and ProQ and investigated the redistribution of these two proteins upon RNase treatment. Overall, we demonstrate that SEC-seq is a tractable and reproducible method for the global profiling of bacterial RNA-protein complexes that offers the potential to discover yet-unrecognized associations between bacterial RNAs and proteins.
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Affiliation(s)
- Kotaro Chihara
- Helmholtz Institute for RNA-based Infection Research, Würzburg, Germany
| | | | - Jens Hör
- Weizmann Institute, Rehovot, Israel
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6
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Ershov P, Yablokov E, Mezentsev Y, Ivanov A. Interactomics of CXXC proteins involved in epigenetic regulation of gene expression. BIOMEDITSINSKAYA KHIMIYA 2022; 68:339-351. [DOI: 10.18097/pbmc20226805339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Regulation of gene expression is an extremely complex and multicomponent biological phenomenon. Proteins containing the CXXC-domain “zinc fingers” (CXXC-proteins) are master regulators of expression of many genes and have conserved functions of methylation of DNA bases and histone proteins. CXXC proteins function as a part of multiprotein complexes, which indicates the fundamental importance of studying post-translational regulation through modulation of the protein-protein interaction spectrum (PPI) in both normal and pathological conditions. In this paper we discuss general aspects of the involvement of CXXC proteins and their protein partners in neoplastic processes, both from the literature data and our own studies. Special attention is paid to recent data on the particular interactomics of the CFP1 protein encoded by the CXXC1 gene located on the human chromosome 18. CFP1 is devoid of enzymatic activity and implements epigenetic regulation of expression through binding to chromatin and a certain spectrum of PPIs.
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Affiliation(s)
- P.V. Ershov
- Institute of Biomedical Chemistry, Moscow, Russia
| | | | | | - A.S. Ivanov
- Institute of Biomedical Chemistry, Moscow, Russia
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7
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Dafun AS, Marcoux J. Structural mass spectrometry of membrane proteins. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2022; 1870:140813. [PMID: 35750312 DOI: 10.1016/j.bbapap.2022.140813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/10/2022] [Accepted: 06/17/2022] [Indexed: 06/15/2023]
Abstract
The analysis of proteins and protein complexes by mass spectrometry (MS) has come a long way since the invention of electrospray ionization (ESI) in the mid 80s. Originally used to characterize small soluble polypeptide chains, MS has progressively evolved over the past 3 decades towards the analysis of samples of ever increasing heterogeneity and complexity, while the instruments have become more and more sensitive and resolutive. The proofs of concepts and first examples of most structural MS methods appeared in the early 90s. However, their application to membrane proteins, key targets in the biopharma industry, is more recent. Nowadays, a wealth of information can be gathered from such MS-based methods, on all aspects of membrane protein structure: sequencing (and more precisely proteoform characterization), but also stoichiometry, non-covalent ligand binding (metals, drug, lipids, carbohydrates), conformations, dynamics and distance restraints for modelling. In this review, we present the concept and some historical and more recent applications on membrane proteins, for the major structural MS methods.
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Affiliation(s)
- Angelique Sanchez Dafun
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Julien Marcoux
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France.
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8
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Gao H, Zhao L, Zhong B, Zhang B, Gong Z, Zhao B, Liu Y, Zhao Q, Zhang L, Zhang Y. In-Depth In Vivo Crosslinking in Minutes by a Compact, Membrane-Permeable, and Alkynyl-Enrichable Crosslinker. Anal Chem 2022; 94:7551-7558. [PMID: 35575683 DOI: 10.1021/acs.analchem.2c00335] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Chemical crosslinking coupled with mass spectrometry (CXMS) has emerged as a powerful technique to obtain the dynamic conformations and interaction interfaces of protein complexes. Limited by the poor cell membrane permeability, chemical reactivity, and biocompatibility of crosslinkers, in vivo crosslinking to capture the dynamics of protein complexes with finer temporal resolution and higher coverage is attractive but challenging. In this work, a trifunctional crosslinker bis(succinimidyl) with propargyl tag (BSP), involving compact size, proper amphipathy, and enrichment capacity, was developed to enable better cell membrane permeability and efficient crosslinking in 5 min without obvious cellular interference. Followed by a two-step enrichment method based on click chemistry at the peptide level, 13,098 crosslinked peptides (5068 inter-crosslinked peptides and 8030 intra-crosslinked peptides) were identified under the data threshold of peptide-spectrum matches (PSMs) ≥2 on the basic of the FDR control of 1%, which was the most comprehensive dataset for homo species cells by a non-cleavable crosslinker. Besides, the interactome network comprising 1519 proteins connected by 2913 interaction edges in various intracellular compartments, as well as 80S ribosome structural dynamics, were characterized, showing the great potential of our in vivo crosslinking approach in minutes. All these results demonstrated that our developed BSP could provide a valuable toolkit for the in-depth in vivo analysis of protein-protein interactions (PPIs) and protein architectures with finer temporal resolution.
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Affiliation(s)
- Hang Gao
- 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
| | - 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
| | - Bowen Zhong
- 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
| | - Beirong 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
| | - Zhou Gong
- CAS Innovation Academy for Precision Measurement Science and Technology, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China
| | - Baofeng 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
| | - Yi Liu
- 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
| | - Qun 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
| | - 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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9
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Wang S, Wu R, Lu J, Jiang Y, Huang T, Cai YD. Protein-protein interaction networks as miners of biological discovery. Proteomics 2022; 22:e2100190. [PMID: 35567424 DOI: 10.1002/pmic.202100190] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/28/2022] [Accepted: 04/29/2022] [Indexed: 11/12/2022]
Abstract
Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Steven Wang
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Runxin Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jiaqi Lu
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA
| | - Yijia Jiang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Tao Huang
- Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, China
| | - Yu-Dong Cai
- School of Life Sciences, Shanghai University, Shanghai, China
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10
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Xu C, Wang B, Heng H, Huang J, Wan C. Comparative Network Biology Discovers Protein Complexes That Underline Cellular Differentiation in Anabaena sp. Mol Cell Proteomics 2022; 21:100224. [PMID: 35288331 PMCID: PMC9035410 DOI: 10.1016/j.mcpro.2022.100224] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 02/20/2022] [Accepted: 03/10/2022] [Indexed: 01/11/2023] Open
Abstract
The filamentous cyanobacterium Anabaena sp. PCC 7120 can differentiate into heterocysts to fix atmospheric nitrogen. During cell differentiation, cellular morphology and gene expression undergo a series of significant changes. To uncover the mechanisms responsible for these alterations, we built protein–protein interaction (PPI) networks for these two cell types by cofractionation coupled with mass spectrometry. We predicted 280 and 215 protein complexes, with 6322 and 2791 high-confidence PPIs in vegetative cells and heterocysts, respectively. Most of the proteins in both types of cells presented similar elution profiles, whereas the elution peaks of 438 proteins showed significant changes. We observed that some well-known complexes recruited new members in heterocysts, such as ribosomes, diflavin flavoprotein, and cytochrome c oxidase. Photosynthetic complexes, including photosystem I, photosystem II, and phycobilisome, remained in both vegetative cells and heterocysts for electron transfer and energy generation. Besides that, PPI data also reveal new functions of proteins. For example, the hypothetical protein Alr4359 was found to interact with FraH and Alr4119 in heterocysts and was located on heterocyst poles, thereby influencing the diazotrophic growth of filaments. The overexpression of Alr4359 suspended heterocyst formation and altered the pigment composition and filament length. This work demonstrates the differences in protein assemblies and provides insight into physiological regulation during cell differentiation. PPIs in two types of cells of Anabaena sp. 7120 were systematically identified. 10,302 and 8557 high-confidence PPIs were obtained and over 80% were novel. About 438 proteins showed significant changes in vegetative cells and heterocysts. Protein Alr4359 was found to influence the diazotrophic growth of filaments.
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Affiliation(s)
- Chen Xu
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan, Hubei, China
| | - Bing Wang
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan, Hubei, China
| | - Hailu Heng
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan, Hubei, China
| | - Jiangmei Huang
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan, Hubei, China
| | - Cuihong Wan
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan, Hubei, China.
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11
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Wang Y, Hu Y, Höti N, Huang L, Zhang H. Characterization of In Vivo Protein Complexes via Chemical Cross-Linking and Mass Spectrometry. Anal Chem 2021; 94:1537-1542. [PMID: 34962381 DOI: 10.1021/acs.analchem.1c02410] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cells perform various functions by proteins via protein complexes. Characterization of protein complexes is critical to understanding their biological and clinical significance and has been one of the major efforts of functional proteomics. To date, most protein complexes are characterized by the in vitro system from protein extracts after the cells or tissues are lysed, and it has been challenging to determine which of these protein complexes are formed in intact cells. Herein, we report an approach to preserve protein complexes using in vivo cross-linking, followed by size exclusion chromatography and data-independent acquisition mass spectrometry. This approach enables the characterization of in vivo protein complexes from cells or tissues, which allows the determination of protein complexes in clinical research. More importantly, the described approach can identify protein complexes that are not detected by the in vitro system, which provide unique protein function information.
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Affiliation(s)
- Yuefan Wang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Yingwei Hu
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Naseruddin Höti
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Lan Huang
- Department of Physiology and Biophysics, University of California, Irvine, California 92697, United States
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States
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12
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van Strien J, Haupt A, Schulte U, Braun HP, Cabrera-Orefice A, Choudhary JS, Evers F, Fernandez-Vizarra E, Guerrero-Castillo S, Kooij TWA, Páleníková P, Pardo M, Ugalde C, Wittig I, Wöhlbrand L, Brandt U, Arnold S, Huynen MA. CEDAR, an online resource for the reporting and exploration of complexome profiling data. BIOCHIMICA ET BIOPHYSICA ACTA. BIOENERGETICS 2021; 1862:148411. [PMID: 33722514 DOI: 10.1016/j.bbabio.2021.148411] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/02/2021] [Accepted: 03/08/2021] [Indexed: 02/06/2023]
Abstract
Complexome profiling is an emerging 'omics' approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the "minimum information required for a complexome profiling experiment" (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.
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Affiliation(s)
- Joeri van Strien
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Alexander Haupt
- Institute of Physiology, Faculty of Medicine, University of Freiburg, 79104 Freiburg, Germany
| | - Uwe Schulte
- Institute of Physiology, Faculty of Medicine, University of Freiburg, 79104 Freiburg, Germany; Center for Biological Signalling Studies (BIOSS) and Center for Integrative Signalling Studies (CIBSS), 79104 Freiburg, Germany
| | - Hans-Peter Braun
- Institute of Plant Genetics, Leibniz Universität Hannover, Herrenhäuser Str. 2, 30419 Hannover, Germany
| | - Alfredo Cabrera-Orefice
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jyoti S Choudhary
- Functional Proteomics, The Institute of Cancer Research, London SW7 3RP, UK
| | - Felix Evers
- Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Sergio Guerrero-Castillo
- University Children's Research@Kinder-UKE, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Taco W A Kooij
- Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Mercedes Pardo
- Functional Proteomics, The Institute of Cancer Research, London SW7 3RP, UK
| | - Cristina Ugalde
- Hospital 12 de Octubre Research Institute, Madrid 28041, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), U723, Madrid, Spain
| | - Ilka Wittig
- Functional Proteomics, Medical School, Goethe-University, 60590 Frankfurt am Main, Germany
| | - Lars Wöhlbrand
- General and Molecular Microbiology, Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Ulrich Brandt
- Radboud Center for Mitochondrial Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Susanne Arnold
- Radboud Center for Mitochondrial Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Martijn A Huynen
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands.
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13
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Skinnider MA, Foster LJ. Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments. Nat Methods 2021; 18:806-815. [PMID: 34211188 DOI: 10.1038/s41592-021-01194-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 05/20/2021] [Indexed: 02/06/2023]
Abstract
Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful technique for interactome mapping. However, there is little consensus on optimal strategies for the design of CF-MS experiments or their computational analysis. Here, we reanalyzed a total of 206 CF-MS experiments to generate a uniformly processed resource containing over 11 million measurements of protein abundance. We used this resource to benchmark experimental designs for CF-MS studies and systematically optimize computational approaches to network inference. We then applied this optimized methodology to reconstruct a draft-quality human interactome by CF-MS and predict over 700,000 protein-protein interactions across 27 eukaryotic species or clades. Our work defines new resources to illuminate proteome organization over evolutionary timescales and establishes best practices for the design and analysis of CF-MS studies.
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Affiliation(s)
- Michael A Skinnider
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Leonard J Foster
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada. .,Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada.
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14
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Strategy for high-throughput identification of protein complexes by array-based multi-dimensional liquid chromatography-mass spectrometry. J Chromatogr A 2021; 1652:462351. [PMID: 34174714 DOI: 10.1016/j.chroma.2021.462351] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 05/23/2021] [Accepted: 06/07/2021] [Indexed: 11/22/2022]
Abstract
Comprehensive elucidation of the composition of multiprotein complexes in model organisms is essential to understand conserved biological systems, but large-scale mapping physical association networks is still challenging due to limited throughput of present methods. In this work, a strategy coupling array-based online two-dimensional liquid chromatography (array-based 2D-LC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was demonstrated for high throughput and in-depth identification of protein complexes from cultured human HeLa cell extracts. Mixed-bed ion-exchange column was employed as the first dimensional (1stD) separating mode and an array consisting of eight reversed phase columns was developed as the second dimensional (2ndD) mode. Taking advantage of array parallel strategy, this online system showed an 8-fold increase in throughput. After array-based online 2D-LC separation, altogether 256 × 2ndD fractions were collected for further LC-MS/MS analysis. Public databases of protein-protein interaction (PPI) and co-elution curves identified by LC-MS were applied to reconstruct the protein complexes. A rigorous inspection was operated by cataloging the protein complexes into chromatographic fractions to minimize the number of false positives. As result, a total number of 4,436 proteins were identified and 26,092 elution curves were graphed. A network consisting of 47,745 PPIs was established among 2,201 proteins and presented 1,530 putative protein complexes with high confidence. Most of the identified PPIs were linked to diverse biological processes and may reveal further disease mechanism and therapeutic strategy.
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15
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Christopher JA, Stadler C, Martin CE, Morgenstern M, Pan Y, Betsinger CN, Rattray DG, Mahdessian D, Gingras AC, Warscheid B, Lehtiö J, Cristea IM, Foster LJ, Emili A, Lilley KS. Subcellular proteomics. NATURE REVIEWS. METHODS PRIMERS 2021; 1:32. [PMID: 34549195 PMCID: PMC8451152 DOI: 10.1038/s43586-021-00029-y] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/15/2021] [Indexed: 12/11/2022]
Abstract
The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.
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Affiliation(s)
- Josie A. Christopher
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Charlotte Stadler
- Department of Protein Sciences, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Claire E. Martin
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Marcel Morgenstern
- Institute of Biology II, Biochemistry and Functional Proteomics, Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Yanbo Pan
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Cora N. Betsinger
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - David G. Rattray
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Diana Mahdessian
- Department of Protein Sciences, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Anne-Claude Gingras
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Bettina Warscheid
- Institute of Biology II, Biochemistry and Functional Proteomics, Faculty of Biology, University of Freiburg, Freiburg, Germany
- BIOSS and CIBSS Signaling Research Centers, University of Freiburg, Freiburg, Germany
| | - Janne Lehtiö
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Ileana M. Cristea
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Leonard J. Foster
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrew Emili
- Center for Network Systems Biology, Boston University, Boston, MA, USA
| | - Kathryn S. Lilley
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
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16
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Bludau I. Discovery-Versus Hypothesis-Driven Detection of Protein-Protein Interactions and Complexes. Int J Mol Sci 2021; 22:4450. [PMID: 33923221 PMCID: PMC8123138 DOI: 10.3390/ijms22094450] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/13/2021] [Accepted: 04/21/2021] [Indexed: 12/13/2022] Open
Abstract
Protein complexes are the main functional modules in the cell that coordinate and perform the vast majority of molecular functions. The main approaches to identify and quantify the interactome to date are based on mass spectrometry (MS). Here I summarize the benefits and limitations of different MS-based interactome screens, with a focus on untargeted interactome acquisition, such as co-fractionation MS. Specific emphasis is given to the discussion of discovery- versus hypothesis-driven data analysis concepts and their applicability to large, proteome-wide interactome screens. Hypothesis-driven analysis approaches, i.e., complex- or network-centric, are highlighted as promising strategies for comparative studies. While these approaches require prior information from public databases, also reviewed herein, the available wealth of interactomic data continuously increases, thereby providing more exhaustive information for future studies. Finally, guidance on the selection of interactome acquisition and analysis methods is provided to aid the reader in the design of protein-protein interaction studies.
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Affiliation(s)
- Isabell Bludau
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
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17
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Kyrilis FL, Belapure J, Kastritis PL. Detecting Protein Communities in Native Cell Extracts by Machine Learning: A Structural Biologist's Perspective. Front Mol Biosci 2021; 8:660542. [PMID: 33937337 PMCID: PMC8082361 DOI: 10.3389/fmolb.2021.660542] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 03/18/2021] [Indexed: 11/13/2022] Open
Abstract
Native cell extracts hold great promise for understanding the molecular structure of ordered biological systems at high resolution. This is because higher-order biomolecular interactions, dubbed as protein communities, may be retained in their (near-)native state, in contrast to extensively purifying or artificially overexpressing the proteins of interest. The distinct machine-learning approaches are applied to discover protein-protein interactions within cell extracts, reconstruct dedicated biological networks, and report on protein community members from various organisms. Their validation is also important, e.g., by the cross-linking mass spectrometry or cell biology methods. In addition, the cell extracts are amenable to structural analysis by cryo-electron microscopy (cryo-EM), but due to their inherent complexity, sorting structural signatures of protein communities derived by cryo-EM comprises a formidable task. The application of image-processing workflows inspired by machine-learning techniques would provide improvements in distinguishing structural signatures, correlating proteomic and network data to structural signatures and subsequently reconstructed cryo-EM maps, and, ultimately, characterizing unidentified protein communities at high resolution. In this review article, we summarize recent literature in detecting protein communities from native cell extracts and identify the remaining challenges and opportunities. We argue that the progress in, and the integration of, machine learning, cryo-EM, and complementary structural proteomics approaches would provide the basis for a multi-scale molecular description of protein communities within native cell extracts.
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Affiliation(s)
- Fotis L. Kyrilis
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Jaydeep Belapure
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Panagiotis L. Kastritis
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Biozentrum, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
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18
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Gerovac M, Vogel J, Smirnov A. The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches. Front Mol Biosci 2021; 8:661448. [PMID: 33898526 PMCID: PMC8058203 DOI: 10.3389/fmolb.2021.661448] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 03/04/2021] [Indexed: 12/13/2022] Open
Abstract
Macromolecular complexes of proteins and RNAs are essential building blocks of cells. These stable supramolecular particles can be viewed as minimal biochemical units whose structural organization, i.e., the way the RNA and the protein interact with each other, is directly linked to their biological function. Whether those are dynamic regulatory ribonucleoproteins (RNPs) or integrated molecular machines involved in gene expression, the comprehensive knowledge of these units is critical to our understanding of key molecular mechanisms and cell physiology phenomena. Such is the goal of diverse complexomic approaches and in particular of the recently developed gradient profiling by sequencing (Grad-seq). By separating cellular protein and RNA complexes on a density gradient and quantifying their distributions genome-wide by mass spectrometry and deep sequencing, Grad-seq charts global landscapes of native macromolecular assemblies. In this review, we propose a function-based ontology of stable RNPs and discuss how Grad-seq and related approaches transformed our perspective of bacterial and eukaryotic ribonucleoproteins by guiding the discovery of new RNA-binding proteins and unusual classes of noncoding RNAs. We highlight some methodological aspects and developments that permit to further boost the power of this technique and to look for exciting new biology in understudied and challenging biological models.
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Affiliation(s)
- Milan Gerovac
- Institute of Molecular Infection Biology (IMIB), University of Würzburg, Würzburg, Germany
| | - Jörg Vogel
- Institute of Molecular Infection Biology (IMIB), University of Würzburg, Würzburg, Germany
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), Würzburg, Germany
| | - Alexandre Smirnov
- UMR 7156—Génétique Moléculaire, Génomique, Microbiologie (GMGM), University of Strasbourg, CNRS, Strasbourg, France
- University of Strasbourg Institute for Advanced Study (USIAS), Strasbourg, France
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19
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Cryo-EM structures of engineered active bc 1-cbb 3 type CIII 2CIV super-complexes and electronic communication between the complexes. Nat Commun 2021; 12:929. [PMID: 33568648 PMCID: PMC7876108 DOI: 10.1038/s41467-021-21051-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 01/06/2021] [Indexed: 01/30/2023] Open
Abstract
Respiratory electron transport complexes are organized as individual entities or combined as large supercomplexes (SC). Gram-negative bacteria deploy a mitochondrial-like cytochrome (cyt) bc1 (Complex III, CIII2), and may have specific cbb3-type cyt c oxidases (Complex IV, CIV) instead of the canonical aa3-type CIV. Electron transfer between these complexes is mediated by soluble (c2) and membrane-anchored (cy) cyts. Here, we report the structure of an engineered bc1-cbb3 type SC (CIII2CIV, 5.2 Å resolution) and three conformers of native CIII2 (3.3 Å resolution). The SC is active in vivo and in vitro, contains all catalytic subunits and cofactors, and two extra transmembrane helices attributed to cyt cy and the assembly factor CcoH. The cyt cy is integral to SC, its cyt domain is mobile and it conveys electrons to CIV differently than cyt c2. The successful production of a native-like functional SC and determination of its structure illustrate the characteristics of membrane-confined and membrane-external respiratory electron transport pathways in Gram-negative bacteria.
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20
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Chen Z, Chen J. Mass spectrometry-based protein‒protein interaction techniques and their applications in studies of DNA damage repair. J Zhejiang Univ Sci B 2021; 22:1-20. [PMID: 33448183 PMCID: PMC7818012 DOI: 10.1631/jzus.b2000356] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 09/08/2020] [Indexed: 02/06/2023]
Abstract
Proteins are major functional units that are tightly connected to form complex and dynamic networks. These networks enable cells and organisms to operate properly and respond efficiently to environmental cues. Over the past decades, many biochemical methods have been developed to search for protein-binding partners in order to understand how protein networks are constructed and connected. At the same time, rapid development in proteomics and mass spectrometry (MS) techniques makes it possible to identify interacting proteins and build comprehensive protein‒protein interaction networks. The resulting interactomes and networks have proven informative in the investigation of biological functions, such as in the field of DNA damage repair. In recent years, a number of proteins involved in DNA damage response and DNA repair pathways have been uncovered with MS-based protein‒protein interaction studies. As the technologies for enriching associated proteins and MS become more sophisticated, the studies of protein‒protein interactions are entering a new era. In this review, we summarize the strategies and recent developments for exploring protein‒protein interaction. In addition, we discuss the application of these tools in the investigation of protein‒protein interaction networks involved in DNA damage response and DNA repair.
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Affiliation(s)
- Zhen Chen
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Junjie Chen
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
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21
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Abstract
Enzymes are a class of protein that catalyze a wide range of chemical reactions, including the cleavage of specific peptide bonds. They are expressed in all cell types, play vital roles in tissue development and homeostasis, and in many diseases, such as cancer. Enzymatic activity is tightly controlled through the use of inactive pro-enzymes, endogenous inhibitors and spatial localization. Since the presence of specific enzymes is often correlated with biological processes, and these proteins can directly modify biomolecules, they are an ideal biological input for cell-responsive biomaterials. These materials include both natural and synthetic polymers, cross-linked hydrogels and self-assembled peptide nanostructures. Within these systems enzymatic activity has been used to induce biodegradation, release therapeutic agents and for disease diagnosis. As technological advancements increase our ability to quantify the expression and nanoscale organization of proteins in cells and tissues, as well as the synthesis of increasingly complex and well-defined biomaterials, enzyme-responsive biomaterials are poised to play vital roles in the future of biomedicine.
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Affiliation(s)
- E. Thomas Pashuck
- Department of Bioengineering, P.C. Rossin College of Engineering and Applied Science, Lehigh University Bethlehem Pennsylvania USA
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22
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Zheng J, Chen X, Yang Y, Tan CSH, Tian R. Mass Spectrometry-Based Protein Complex Profiling in Time and Space. Anal Chem 2020; 93:598-619. [DOI: 10.1021/acs.analchem.0c04332] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Jiangnan Zheng
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiong Chen
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yun Yang
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Chris Soon Heng Tan
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
| | - Ruijun Tian
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
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23
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Pang CNI, Ballouz S, Weissberger D, Thibaut LM, Hamey JJ, Gillis J, Wilkins MR, Hart-Smith G. Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes. Mol Cell Proteomics 2020; 19:1876-1895. [PMID: 32817346 PMCID: PMC7664123 DOI: 10.1074/mcp.ra120.002154] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 07/14/2020] [Indexed: 11/06/2022] Open
Abstract
Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.
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Affiliation(s)
- Chi Nam Ignatius Pang
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Sara Ballouz
- Garvan Institute of Medical Research, Darlinghurst, Sydney, New South Wales, Australia
| | - Daniel Weissberger
- School of Chemistry, University of New South Wales, Sydney, New South Wales, Australia
| | - Loïc M Thibaut
- School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia
| | - Joshua J Hamey
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, New York, USA
| | - Marc R Wilkins
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Gene Hart-Smith
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia; Department of Molecular Sciences, Macquarie University, Sydney, New South Wales, Australia.
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24
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Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes. Nat Protoc 2020; 15:2341-2386. [PMID: 32690956 DOI: 10.1038/s41596-020-0332-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 04/17/2020] [Indexed: 01/03/2023]
Abstract
Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging. We have recently extended the targeted proteomics rationale to the level of native protein complex analysis (complex-centric proteome profiling). The complex-centric workflow described herein consists of size exclusion chromatography (SEC) to fractionate native protein complexes, data-independent acquisition mass spectrometry to precisely quantify the proteins in each SEC fraction based on a set of proteotypic peptides and targeted, complex-centric analysis where prior information from generic protein interaction maps is used to detect and quantify protein complexes with high selectivity and statistical error control via the computational framework CCprofiler (https://github.com/CCprofiler/CCprofiler). Complex-centric proteome profiling captures most proteins in complex-assembled state and reveals their organization into hundreds of complexes and complex variants observable in a given cellular state. The protocol is applicable to cultured cells and can potentially also be adapted to primary tissue and does not require any genetic engineering of the respective sample sources. At present, it requires ~8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.
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25
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Synaptamide activates the adhesion GPCR GPR110 (ADGRF1) through GAIN domain binding. Commun Biol 2020; 3:109. [PMID: 32144388 PMCID: PMC7060178 DOI: 10.1038/s42003-020-0831-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 02/07/2020] [Indexed: 02/07/2023] Open
Abstract
Adhesion G protein-coupled receptors (aGPCR) are characterized by a large extracellular region containing a conserved GPCR-autoproteolysis-inducing (GAIN) domain. Despite their relevance to several disease conditions, we do not understand the molecular mechanism by which aGPCRs are physiologically activated. GPR110 (ADGRF1) was recently deorphanized as the functional receptor of N-docosahexaenoylethanolamine (synaptamide), a potent synaptogenic metabolite of docosahexaenoic acid. Thus far, synaptamide is the first and only small-molecule endogenous ligand of an aGPCR. Here, we demonstrate the molecular basis of synaptamide-induced activation of GPR110 in living cells. Using in-cell chemical cross-linking/mass spectrometry, computational modeling and mutagenesis-assisted functional assays, we discover that synaptamide specifically binds to the interface of GPR110 GAIN subdomains through interactions with residues Q511, N512 and Y513, causing an intracellular conformational change near TM6 that triggers downstream signaling. This ligand-induced GAIN-targeted activation mechanism provides a framework for understanding the physiological function of aGPCRs and therapeutic targeting in the GAIN domain. Huang et al clarify the molecular mechanism of activation of adhesion G protein-coupled receptor GPR110 by synaptamide, the only small-molecule endogenous ligand known for this class of GPCR. They find through chemical cross-linking mass spectrometry, modeling and mutagenesis that synaptamide binds to residues in the GAIN domain and induces a conformational change triggering downstream signaling.
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A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Syst 2020; 10:133-155.e6. [PMID: 32027860 PMCID: PMC7042714 DOI: 10.1016/j.cels.2020.01.001] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 11/08/2019] [Accepted: 01/10/2020] [Indexed: 12/19/2022]
Abstract
Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins. In proteomic studies, these have been treated as independent entities, disregarding their higher-level organization into complexes that affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell-state-specific changes in the physical arrangement of protein complexes concurrently for thousands of proteins and hundreds of complexes. Applying this technique to a comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and suggest a model of nuclear pore complex disassembly, which we validate by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc. Global quantification of assembly state changes in the mitotic proteome Improved performance over thermostability measurement of proteome states Discovery of a mitotic disassembly intermediate of the nuclear pore complex Introduction of SECexplorer-cc, a publicly available online platform
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Alexandrova E, Giurato G, Saggese P, Pecoraro G, Lamberti J, Ravo M, Rizzo F, Rocco D, Tarallo R, Nyman TA, Collina F, Cantile M, Di Bonito M, Botti G, Nassa G, Weisz A. Interaction Proteomics Identifies ERbeta Association with Chromatin Repressive Complexes to Inhibit Cholesterol Biosynthesis and Exert An Oncosuppressive Role in Triple-negative Breast Cancer. Mol Cell Proteomics 2020; 19:245-260. [PMID: 31792072 PMCID: PMC7000115 DOI: 10.1074/mcp.ra119.001817] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 11/27/2019] [Indexed: 12/31/2022] Open
Abstract
Triple-negative breast cancer (TNBC) is characterized by poor response to therapy and low overall patient survival. Recently, Estrogen Receptor beta (ERβ) has been found to be expressed in a fraction of TNBCs where, because of its oncosuppressive actions on the genome, it represents a potential therapeutic target, provided a better understanding of its actions in these tumors becomes available. To this end, the cell lines Hs 578T, MDA-MB-468 and HCC1806, representing the claudin-low, basal-like 1 and 2 TNBC molecular subtypes respectively, were engineered to express ERβ under the control of a Tetracycline-inducible promoter and used to investigate the effects of this transcription factor on gene activity. The antiproliferative effects of ERβ in these cells were confirmed by multiple functional approaches, including transcriptome profiling and global mapping of receptor binding sites in the genome, that revealed direct negative regulation by ERβ of genes, encoding for key components of cellular pathways associated to TNBC aggressiveness representing novel therapeutic targets such as angiogenesis, invasion, metastasis and cholesterol biosynthesis. Supporting these results, interaction proteomics by immunoprecipitation coupled to nano LC-MS/MS mass spectrometry revealed ERβ association with several potential nuclear protein partners, including key components of regulatory complexes known to control chromatin remodeling, transcriptional and post-transcriptional gene regulation and RNA splicing. Among these, ERβ association with the Polycomb Repressor Complexes 1 and 2 (PRC1/2), known for their central role in gene regulation in cancer cells, was confirmed in all three TNBC subtypes investigated, suggesting its occurrence independently from the cellular context. These results demonstrate a significant impact of ERβ in TNBC genome activity mediated by its cooperation with regulatory multiprotein chromatin remodeling complexes, providing novel ground to devise new strategies for the treatment of these diseases based on ligands affecting the activity of this nuclear receptor or some of its protein partners.
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Affiliation(s)
- Elena Alexandrova
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy; Genomix4Life Srl, Spin-Off of the Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Giorgio Giurato
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy; Genomix4Life Srl, Spin-Off of the Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Pasquale Saggese
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy; Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, 90095
| | - Giovanni Pecoraro
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Jessica Lamberti
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Maria Ravo
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy; Genomix4Life Srl, Spin-Off of the Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Francesca Rizzo
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Domenico Rocco
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Roberta Tarallo
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy
| | - Tuula A Nyman
- Department of Immunology, Institute of Clinical Medicine, University of Oslo and Rikshospitalet Oslo, 0424 Oslo, Norway
| | - Francesca Collina
- Pathology Unit, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Naples (NA), 80131 Italy
| | - Monica Cantile
- Pathology Unit, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Naples (NA), 80131 Italy
| | - Maurizio Di Bonito
- Pathology Unit, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Naples (NA), 80131 Italy
| | - Gerardo Botti
- Scientific Direction, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Naples (NA), 80131, Italy
| | - Giovanni Nassa
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy.
| | - Alessandro Weisz
- Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi (SA), 84081, Italy.
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Salas D, Stacey RG, Akinlaja M, Foster LJ. Next-generation Interactomics: Considerations for the Use of Co-elution to Measure Protein Interaction Networks. Mol Cell Proteomics 2020; 19:1-10. [PMID: 31792070 PMCID: PMC6944233 DOI: 10.1074/mcp.r119.001803] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/26/2019] [Indexed: 12/26/2022] Open
Abstract
Understanding how proteins interact is crucial to understanding cellular processes. Among the available interactome mapping methods, co-elution stands out as a method that is simultaneous in nature and capable of identifying interactions between all the proteins detected in a sample. The general workflow in co-elution methods involves the mild extraction of protein complexes and their separation into several fractions, across which proteins bound together in the same complex will show similar co-elution profiles when analyzed appropriately. In this review we discuss the different separation, quantification and bioinformatic strategies used in co-elution studies, and the important considerations in designing these studies. The benefits of co-elution versus other methods makes it a valuable starting point when asking questions that involve the perturbation of the interactome.
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Affiliation(s)
- Daniela Salas
- Michael Smith Laboratories and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada; Department of Chemistry, Simon Fraser University, Burnaby, BC, Canada
| | - R Greg Stacey
- Michael Smith Laboratories and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Mopelola Akinlaja
- Michael Smith Laboratories and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Leonard J Foster
- Michael Smith Laboratories and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada.
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Classification of Single Particles from Human Cell Extract Reveals Distinct Structures. Cell Rep 2019; 24:259-268.e3. [PMID: 29972786 PMCID: PMC6109231 DOI: 10.1016/j.celrep.2018.06.022] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 05/09/2018] [Accepted: 06/05/2018] [Indexed: 01/27/2023] Open
Abstract
Multi-protein complexes are necessary for nearly all cellular processes, and understanding their structure is required for elucidating their function. Current high-resolution strategies in structural biology are effective but lag behind other fields (e.g., genomics and proteomics) due to their reliance on purified samples rather than heterogeneous mixtures. Here, we present a method combining single-particle analysis by electron microscopy with protein identification by mass spectrometry to structurally characterize macromolecular complexes from human cell extract. We identify HSP60 through two-dimensional classification and obtain three-dimensional structures of native proteasomes directly from ab initio classification of a heterogeneous mixture of protein complexes. In addition, we reveal an ∼1-MDa-size structure of unknown composition and reference our proteomics data to suggest possible identities. Our study shows the power of using a shotgun approach to electron microscopy (shotgun EM) when coupled with mass spectrometry as a tool to uncover the structures of macromolecular machines.
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30
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Brenes A, Hukelmann J, Bensaddek D, Lamond AI. Multibatch TMT Reveals False Positives, Batch Effects and Missing Values. Mol Cell Proteomics 2019; 18:1967-1980. [PMID: 31332098 PMCID: PMC6773557 DOI: 10.1074/mcp.ra119.001472] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 06/14/2019] [Indexed: 12/31/2022] Open
Abstract
Multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent, tandem mass tags (TMT) in particular. Here we used a large iPSC proteomic experiment with twenty-four 10-plex TMT batches to evaluate the effect of integrating multiple TMT batches within a single analysis. We identified a significant inflation rate of protein missing values as multiple batches are integrated and show that this pattern is aggravated at the peptide level. We also show that without normalization strategies to address the batch effects, the high precision of quantitation within a single multiplexed TMT batch is not reproduced when data from multiple TMT batches are integrated.Further, the incidence of false positives was studied by using Y chromosome peptides as an internal control. The iPSC lines quantified in this data set were derived from both male and female donors, hence the peptides mapped to the Y chromosome should be absent from female lines. Nonetheless, these Y chromosome-specific peptides were consistently detected in the female channels of all TMT batches. We then used the same Y chromosome specific peptides to quantify the level of ion coisolation as well as the effect of primary and secondary reporter ion interference. These results were used to propose solutions to mitigate the limitations of multi-batch TMT analyses. We confirm that including a common reference line in every batch increases precision by facilitating normalization across the batches and we propose experimental designs that minimize the effect of cross population reporter ion interference.
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Affiliation(s)
- Alejandro Brenes
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
| | - Jens Hukelmann
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
| | - Dalila Bensaddek
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
| | - Angus I Lamond
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom.
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31
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Rafiei A, Schriemer DC. A microtubule crosslinking protocol for integrative structural modeling activities. Anal Biochem 2019; 586:113416. [PMID: 31499019 DOI: 10.1016/j.ab.2019.113416] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 08/30/2019] [Accepted: 09/05/2019] [Indexed: 11/15/2022]
Abstract
Microtubules (MTs) are key components in the cytoskeleton of the eukaryotic cell, and play roles in processes such as intracellular transport and cell division. An improved understanding MT regulation requires structural analysis of the extensive interactions between the MT lattice and its regulatory proteins, but MT interactions are challenging for even the most advanced structural methods to characterize. Integrative methods involving crosslinking mass spectrometry (XL-MS) can extend structural analysis to many interaction classes, but the representation of MTs in crosslinking data-sets has been surprisingly low. Here, we explore the basis for the underrepresentation of the MT lattice and present an enhanced method for mapping MT structural features using an optimized set of reagents, together with fluorescence detection to ensure MT structural integrity. Through the application of stringent identification criteria, 91 unique crosslinks were identified, 78 of which were uniquely matched to 7 distinct structural features of the MT lattice. Of note, 4 crosslinks were detected for the lattice-A protofilament organization. The lattice-A structure defines a "seam" or discontinuity in MTs and is an emerging site of interest for MT regulation. Our methodology should be broadly applicable to integrative structural studies involving any MT-protein interaction.
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Affiliation(s)
- Atefeh Rafiei
- Department of Chemistry, University of Calgary, Calgary, Alberta, Canada
| | - David C Schriemer
- Department of Chemistry, University of Calgary, Calgary, Alberta, Canada; Department of Biochemistry and Molecular Biology, University of Calgary, Alberta, Canada.
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32
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Brenes A, Afzal V, Kent R, Lamond AI. The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics. Nucleic Acids Res 2019; 46:D1202-D1209. [PMID: 28981707 PMCID: PMC5753345 DOI: 10.1093/nar/gkx807] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 08/31/2017] [Indexed: 11/15/2022] Open
Abstract
Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein-protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.
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Affiliation(s)
- Alejandro Brenes
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK
| | - Vackar Afzal
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK
| | - Robert Kent
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK
| | - Angus I Lamond
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK
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33
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Carlson ML, Stacey RG, Young JW, Wason IS, Zhao Z, Rattray DG, Scott N, Kerr CH, Babu M, Foster LJ, Duong Van Hoa F. Profiling the Escherichia coli membrane protein interactome captured in Peptidisc libraries. eLife 2019; 8:46615. [PMID: 31364989 PMCID: PMC6697469 DOI: 10.7554/elife.46615] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 07/30/2019] [Indexed: 12/23/2022] Open
Abstract
Protein-correlation-profiling (PCP), in combination with quantitative proteomics, has emerged as a high-throughput method for the rapid identification of dynamic protein complexes in native conditions. While PCP has been successfully applied to soluble proteomes, characterization of the membrane interactome has lagged, partly due to the necessary use of detergents to maintain protein solubility. Here, we apply the peptidisc, a ‘one-size fits all’ membrane mimetic, for the capture of the Escherichia coli cell envelope proteome and its high-resolution fractionation in the absence of detergent. Analysis of the SILAC-labeled peptidisc library via PCP allows generation of over 4900 possible binary interactions out of >700,000 random associations. Using well-characterized membrane protein systems such as the SecY translocon, the Bam complex and the MetNI transporter, we demonstrate that our dataset is a useful resource for identifying transient and surprisingly novel protein interactions. For example, we discover a trans-periplasmic supercomplex comprising subunits of the Bam and Sec machineries, including membrane-bound chaperones YfgM and PpiD. We identify RcsF and OmpA as bone fide interactors of BamA, and we show that MetQ association with the ABC transporter MetNI depends on its N-terminal lipid anchor. We also discover NlpA as a novel interactor of MetNI complex. Most of these interactions are largely undetected by standard detergent-based purification. Together, the peptidisc workflow applied to the proteomic field is emerging as a promising novel approach to characterize membrane protein interactions under native expression conditions and without genetic manipulation.
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Affiliation(s)
- Michael Luke Carlson
- Life Sciences Institute, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - R Greg Stacey
- Michael Smith Laboratory, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - John William Young
- Life Sciences Institute, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Irvinder Singh Wason
- Life Sciences Institute, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Zhiyu Zhao
- Life Sciences Institute, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - David G Rattray
- Michael Smith Laboratory, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Nichollas Scott
- Michael Smith Laboratory, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Craig H Kerr
- Michael Smith Laboratory, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Mohan Babu
- Department of Biochemistry, Faculty of Science, University of Regina, Regina, Canada
| | - Leonard J Foster
- Michael Smith Laboratory, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Franck Duong Van Hoa
- Life Sciences Institute, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
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Abstract
Mass spectrometry is one of the key technologies of proteomics, and over the last decade important technical advances in mass spectrometry have driven an increased capability for proteomic discovery. In addition, new methods to capture important biological information have been developed to take advantage of improving proteomic tools.
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Affiliation(s)
- John R Yates
- Molecular Medicine and Neurobiology, Scripps Research, 0550 North Torrey Pines Road, SR302, La Jolla, CA, 92037, USA
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35
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Heusel M, Bludau I, Rosenberger G, Hafen R, Frank M, Banaei-Esfahani A, van Drogen A, Collins BC, Gstaiger M, Aebersold R. Complex-centric proteome profiling by SEC-SWATH-MS. Mol Syst Biol 2019; 15:e8438. [PMID: 30642884 PMCID: PMC6346213 DOI: 10.15252/msb.20188438] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error‐controlled, complex‐centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub‐complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.
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Affiliation(s)
- Moritz Heusel
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Molecular and Translational Biomedicine of the Competence Center Personalized Medicine UZH/ETH, Zurich, Switzerland
| | - Isabell Bludau
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Systems Biology, Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - George Rosenberger
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Robin Hafen
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,Department of Computer Science, ETH Zurich, Zurich, Switzerland
| | - Max Frank
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Amir Banaei-Esfahani
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Systems Biology, Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Audrey van Drogen
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ben C Collins
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Matthias Gstaiger
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland .,Faculty of Science, University of Zurich, Zurich, Switzerland
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2C-BioID: An Advanced Two Component BioID System for Precision Mapping of Protein Interactomes. iScience 2018; 10:40-52. [PMID: 30500481 PMCID: PMC6263017 DOI: 10.1016/j.isci.2018.11.023] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 09/26/2018] [Accepted: 11/12/2018] [Indexed: 12/31/2022] Open
Abstract
The modulation of protein-protein interactions (PPIs) is an essential regulatory activity defining diverse cell functions in development and disease. BioID is an unbiased proximity-dependent biotinylation method making use of a biotin-protein ligase fused to a protein of interest and has become an important tool for mapping of PPIs within cellular contexts. We devised an advanced method, 2C-BioID, in which the biotin-protein ligase is kept separate from the protein of interest, until the two are induced to associate by the addition of a dimerizing agent. As proof of principle, we compared the interactomes of lamina-associated polypeptide 2β (LAP2β) with those of lamins A and C, using 2C- and conventional BioID. 2C-BioID greatly enhanced data robustness by facilitating the in silico elimination of non-specific interactors as well as overcoming the problems associated with aberrant protein localization. 2C-BioID therefore significantly strengthens the specificity and reliability of BioID-based interactome analysis, by the more stringent exclusion of false-positives and more efficient intracellular targeting.
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37
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Minic Z, Dahms TES, Babu M. Chromatographic separation strategies for precision mass spectrometry to study protein-protein interactions and protein phosphorylation. J Chromatogr B Analyt Technol Biomed Life Sci 2018; 1102-1103:96-108. [PMID: 30380468 DOI: 10.1016/j.jchromb.2018.10.022] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 10/19/2018] [Accepted: 10/22/2018] [Indexed: 11/30/2022]
Abstract
Investigating protein-protein interactions and protein phosphorylation can be of great significance when studying biological processes and human diseases at the molecular level. However, sample complexity, presence of low abundance proteins, and dynamic nature of the proteins often impede in achieving sufficient analytical depth in proteomics research. In this regard, chromatographic separation methodologies have played a vital role in the identification and quantification of proteins in complex sample mixtures. The combination of peptide and protein fractionation techniques with advanced high-performance mass spectrometry has allowed the researchers to successfully study the protein-protein interactions and protein phosphorylation. Several new fractionation strategies for large scale analysis of proteins and peptides have been developed to study protein-protein interactions and protein phosphorylation. These emerging chromatography methodologies have enabled the identification of several hundred protein complexes and even thousands of phosphorylation sites in a single study. In this review, we focus on current workflow strategies and chromatographic tools, highlighting their advantages and disadvantages, and examining their associated challenges and future potential.
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Affiliation(s)
- Zoran Minic
- Department of Chemistry and Biomolecular Science, University of Ottawa, John L. Holmes, Mass Spectrometry Facility, 10 Marie-Curie, Marion Hall, Room 02, Ottawa, ON K1N 1A2, Canada.
| | - Tanya E S Dahms
- Department of Chemistry and Biochemistry, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, Canada
| | - Mohan Babu
- Department of Chemistry and Biochemistry, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, Canada
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38
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Skinnider MA, Stacey RG, Foster LJ. Genomic data integration systematically biases interactome mapping. PLoS Comput Biol 2018; 14:e1006474. [PMID: 30332399 PMCID: PMC6192561 DOI: 10.1371/journal.pcbi.1006474] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 08/30/2018] [Indexed: 12/15/2022] Open
Abstract
Elucidating the complete network of protein-protein interactions, or interactome, is a fundamental goal of the post-genomic era, yet existing interactome maps are far from complete. To increase the throughput and resolution of interactome mapping, methods for protein-protein interaction discovery by co-migration have been introduced. However, accurate identification of interacting protein pairs within the resulting large-scale proteomic datasets is challenging. Consequently, most computational pipelines for co-migration data analysis incorporate external genomic datasets to distinguish interacting from non-interacting protein pairs. The effect of this procedure on interactome mapping is poorly understood. Here, we conduct a rigorous analysis of genomic data integration for interactome recovery across a large number of co-migration datasets, spanning diverse experimental and computational methods. We find that genomic data integration leads to an increase in the functional coherence of the resulting interactome maps, but this comes at the expense of a decrease in power to discover novel interactions. Importantly, putative novel interactions predicted by genomic data integration are no more likely to later be experimentally discovered than those predicted from co-migration data alone. Our results reveal a widespread and unappreciated limitation in a methodology that has been widely used to map the interactome of humans and model organisms.
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Affiliation(s)
| | - R. Greg Stacey
- Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Leonard J. Foster
- Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
- Department of Biochemistry, University of British Columbia, Vancouver, Canada
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39
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Yoshikawa H, Larance M, Harney DJ, Sundaramoorthy R, Ly T, Owen-Hughes T, Lamond AI. Efficient analysis of mammalian polysomes in cells and tissues using Ribo Mega-SEC. eLife 2018; 7:36530. [PMID: 30095066 PMCID: PMC6086667 DOI: 10.7554/elife.36530] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Accepted: 07/28/2018] [Indexed: 12/14/2022] Open
Abstract
We describe Ribo Mega-SEC, a powerful approach for the separation and biochemical analysis of mammalian polysomes and ribosomal subunits using Size Exclusion Chromatography and uHPLC. Using extracts from either cells, or tissues, polysomes can be separated within 15 min from sample injection to fraction collection. Ribo Mega-SEC shows translating ribosomes exist predominantly in polysome complexes in human cell lines and mouse liver tissue. Changes in polysomes are easily quantified between treatments, such as the cellular response to amino acid starvation. Ribo Mega-SEC is shown to provide an efficient, convenient and highly reproducible method for studying functional translation complexes. We show that Ribo Mega-SEC is readily combined with high-throughput MS-based proteomics to characterize proteins associated with polysomes and ribosomal subunits. It also facilitates isolation of complexes for electron microscopy and structural studies.
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Affiliation(s)
- Harunori Yoshikawa
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Mark Larance
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia
| | - Dylan J Harney
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia
| | | | - Tony Ly
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom.,Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Tom Owen-Hughes
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Angus I Lamond
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
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40
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Fasci D, van Ingen H, Scheltema RA, Heck AJR. Histone Interaction Landscapes Visualized by Crosslinking Mass Spectrometry in Intact Cell Nuclei. Mol Cell Proteomics 2018; 17:2018-2033. [PMID: 30021884 DOI: 10.1074/mcp.ra118.000924] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 07/17/2018] [Indexed: 02/03/2023] Open
Abstract
Cells organize their actions partly through tightly controlled protein-protein interactions-collectively termed the interactome. Here we use crosslinking mass spectrometry (XL-MS) to chart the protein-protein interactions in intact human nuclei. Overall, we identified ∼8,700 crosslinks, of which 2/3 represent links connecting distinct proteins. From these data, we gain insights on interactions involving histone proteins. We observed that core histones on the nucleosomes expose well-defined interaction hot spots. For several nucleosome-interacting proteins, such as USF3 and Ran GTPase, the data allowed us to build low-resolution models of their binding mode to the nucleosome. For HMGN2, the data guided the construction of a refined model of the interaction with the nucleosome, based on complementary NMR, XL-MS, and modeling. Excitingly, the analysis of crosslinks carrying posttranslational modifications allowed us to extract how specific modifications influence nucleosome interactions. Overall, our data depository will support future structural and functional analysis of cell nuclei, including the nucleoprotein assemblies they harbor.
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Affiliation(s)
- Domenico Fasci
- From the ‡Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences.,§Netherlands Proteomics Centre, and
| | - Hugo van Ingen
- ¶NMR Spectroscopy Research Group, Bijvoet Center for Biomolecular Research, University of Utrecht, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Richard A Scheltema
- From the ‡Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences; .,§Netherlands Proteomics Centre, and
| | - Albert J R Heck
- From the ‡Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences; .,§Netherlands Proteomics Centre, and
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41
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Zhou M, Tang M, Li S, Peng L, Huang H, Fang Q, Liu Z, Xie P, Li G, Zhou J. Effective lock-in strategy for proteomic analysis of corona complexes bound to amino-free ligands of gold nanoparticles. NANOSCALE 2018; 10:12413-12423. [PMID: 29926046 DOI: 10.1039/c8nr01077c] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
For specific applications, gold nanoparticles (GNPs) are commonly functionalized with various biological ligands, including amino-free ligands such as amino acids, peptides, proteins, and nucleic acids. Upon entering a biological fluid, the protein corona that forms around GNPs can conceal the targeting ligands and sterically hinder the functional properties. The protein corona is routinely prepared by standard centrifugation or sucrose cushion centrifugation. However, such methodologies are not applicable to the exclusive analysis of a ligand-binding protein corona. In this study, we first proposed a lock-in strategy based on a combination of rapid crosslinking and stringent washing. Cysteine was used as a model of amino-free ligands and attached to GNPs. After corona formation in the human plasma, GNP cysteine and corona proteins were quickly fixed by 5 s of crosslinking with 7.5% formaldehyde. After stringent washing using SDS buffer with sonication, the cysteine-bound proteins were effectively separated from unbound proteins. Qualitative and quantitative analyses using a mass spectrometry-based proteomics approach indicated that the protein composition of the cysteine-binding corona from the new method was significantly different from the composition of the whole corona from the two conventional methods. Furthermore, network and formaldehyde-linked site analyses of cysteine-binding proteins provided useful information toward a better knowledge of the behavior of protein-ligand and protein-protein interactions. Collectively, our new strategy has the capability to particularly characterize the protein composition of a cysteine-binding corona. The presented methodology in principal provides a generic way to analyze a nanoparticle corona bound to amino-free ligands and has the potential to decipher corona-masked ligand functions.
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Affiliation(s)
- Mi Zhou
- Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing 400016, China.
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42
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Reading E. Structural Mass Spectrometry of Membrane Proteins within Their Native Lipid Environments. Chemistry 2018; 24:13391-13398. [PMID: 29672954 DOI: 10.1002/chem.201801556] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Indexed: 01/22/2023]
Abstract
Mass spectrometry has emerged as an important structural biology tool for understanding membrane protein structure, function, and dynamics. Generally, structural mass spectrometry of membrane proteins has been performed on purified or reconstituted systems which lack the native lipid membrane and cellular environments. However, there has been progress in the use and adaptations of these methods for probing membrane proteins within increasingly more native contexts. In this Concept article the use and utility of structural mass spectrometry techniques for studying membrane proteins within native environments are highlighted.
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Affiliation(s)
- Eamonn Reading
- Department of Chemistry, King's College London, 7 Trinity Street, SE1 1DB, London, UK
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43
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Discovery of new RNA classes and global RNA-binding proteins. Curr Opin Microbiol 2017; 39:152-160. [PMID: 29179042 DOI: 10.1016/j.mib.2017.11.016] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 11/17/2017] [Indexed: 12/15/2022]
Abstract
The identification of new RNA functions and the functional annotation of transcripts in genomes represent exciting yet challenging endeavours of modern biology. Crucial insights into the biological roles of RNA molecules can be gained from the identification of the proteins with which they form specific complexes. Modern interactome techniques permit to profile RNA-protein interactions in a genome-wide manner and identify new RNA classes associated with globally acting RNA-binding proteins. Applied to a variety of organisms, these methods are already revolutionising our understanding of RNA-mediated biological processes. Here, we focus on one such approach-Gradient sequencing or Grad-seq-which has recently guided the discovery of protein ProQ and its associated small RNAs as a new domain of post-transcriptional control in bacteria.
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44
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Ly T, Whigham A, Clarke R, Brenes-Murillo AJ, Estes B, Madhessian D, Lundberg E, Wadsworth P, Lamond AI. Proteomic analysis of cell cycle progression in asynchronous cultures, including mitotic subphases, using PRIMMUS. eLife 2017; 6:e27574. [PMID: 29052541 PMCID: PMC5650473 DOI: 10.7554/elife.27574] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 10/06/2017] [Indexed: 12/22/2022] Open
Abstract
The temporal regulation of protein abundance and post-translational modifications is a key feature of cell division. Recently, we analysed gene expression and protein abundance changes during interphase under minimally perturbed conditions (Ly et al., 2014, 2015). Here, we show that by using specific intracellular immunolabelling protocols, FACS separation of interphase and mitotic cells, including mitotic subphases, can be combined with proteomic analysis by mass spectrometry. Using this PRIMMUS (PRoteomic analysis of Intracellular iMMUnolabelled cell Subsets) approach, we now compare protein abundance and phosphorylation changes in interphase and mitotic fractions from asynchronously growing human cells. We identify a set of 115 phosphorylation sites increased during G2, termed 'early risers'. This set includes phosphorylation of S738 on TPX2, which we show is important for TPX2 function and mitotic progression. Further, we use PRIMMUS to provide the first a proteome-wide analysis of protein abundance remodeling between prophase, prometaphase and anaphase.
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Affiliation(s)
- Tony Ly
- Centre for Gene Regulation and Expression, School of Life SciencesUniversity of DundeeDundeeUnited Kingdom
- Wellcome Centre for Cell BiologyUniversity of EdinburghEdinburghUnited Kingdom
| | - Arlene Whigham
- CAST Flow Cytometry Facility, School of Life SciencesUniversity of DundeeDundeeUnited Kingdom
| | - Rosemary Clarke
- CAST Flow Cytometry Facility, School of Life SciencesUniversity of DundeeDundeeUnited Kingdom
| | - Alejandro J Brenes-Murillo
- Centre for Gene Regulation and Expression, School of Life SciencesUniversity of DundeeDundeeUnited Kingdom
| | - Brett Estes
- Department of BiologyUniversity of MassachusettsMassachusettsUnited States
- Program in Molecular and Cellular BiologyUniversity of MassachusettsMassachusettsUnited States
| | - Diana Madhessian
- Science for Life LaboratoryRoyal Institute of TechnologyStockholmSweden
| | - Emma Lundberg
- Science for Life LaboratoryRoyal Institute of TechnologyStockholmSweden
| | - Patricia Wadsworth
- Department of BiologyUniversity of MassachusettsMassachusettsUnited States
- Program in Molecular and Cellular BiologyUniversity of MassachusettsMassachusettsUnited States
| | - Angus I Lamond
- Centre for Gene Regulation and Expression, School of Life SciencesUniversity of DundeeDundeeUnited Kingdom
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45
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Crozier TWM, Tinti M, Larance M, Lamond AI, Ferguson MAJ. Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning. Mol Cell Proteomics 2017; 16:2254-2267. [PMID: 29042480 PMCID: PMC5724185 DOI: 10.1074/mcp.o117.068122] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Revised: 08/04/2017] [Indexed: 01/10/2023] Open
Abstract
A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis-generating proteomic data are provided in an open access online data visualization environment (http://134.36.66.166:8083/complex_explorer). The data can be searched conveniently via a user friendly, custom graphical interface. We provide examples of both potential new subunits of known protein complexes and of novel trypanosome complexes of suggested function, contributing to improving the functional annotation of the trypanosome proteome. Data are available via ProteomeXchange with identifier PXD005968.
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Affiliation(s)
- Thomas W M Crozier
- From the ‡Division of Biological Chemistry and Drug Discovery and.,§Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee DD2 1NW, UK
| | - Michele Tinti
- From the ‡Division of Biological Chemistry and Drug Discovery and
| | - Mark Larance
- §Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee DD2 1NW, UK
| | - Angus I Lamond
- §Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee DD2 1NW, UK
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46
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McBride Z, Chen D, Reick C, Xie J, Szymanski DB. Global Analysis of Membrane-associated Protein Oligomerization Using Protein Correlation Profiling. Mol Cell Proteomics 2017; 16:1972-1989. [PMID: 28887381 PMCID: PMC5672003 DOI: 10.1074/mcp.ra117.000276] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Indexed: 11/23/2022] Open
Abstract
Membrane-associated proteins are required for essential processes like transport, organelle biogenesis, and signaling. Many are expected to function as part of an oligomeric protein complex. However, membrane-associated proteins are challenging to work with, and large-scale data sets on the oligomerization state of this important class of proteins is missing. Here we combined cell fractionation of Arabidopsis leaves with nondenaturing detergent solubilization and LC/MS-based profiling of size exclusion chromatography fractions to measure the apparent masses of >1350 membrane-associated proteins. Our method identified proteins from all of the major organelles, with more than 50% of them predicted to be part of a stable complex. The plasma membrane was the most highly enriched in large protein complexes compared with other organelles. Hundreds of novel protein complexes were identified. Over 150 proteins had a complicated localization pattern, and were clearly partitioned between cytosolic and membrane-associated pools. A subset of these dual localized proteins had oligomerization states that differed based on localization. Our data set is an important resource for the community that includes new functionally relevant data for membrane-localized protein complexes that could not be predicted based on sequence alone. Our method enables the analysis of protein complex localization and dynamics, and is a first step in the development of a method in which LC/MS profile data can be used to predict the composition of membrane-associated protein complexes.
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Affiliation(s)
- Zachary McBride
- ‡Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - Donglai Chen
- §Department of Statistics, Purdue University, West Lafayette, Indiana
| | - Christy Reick
- ¶College of Osteopathic Medicine, Marian University, Indianapolis
| | - Jun Xie
- §Department of Statistics, Purdue University, West Lafayette, Indiana
| | - Daniel B Szymanski
- ‡Department of Biological Sciences, Purdue University, West Lafayette, Indiana; .,‖Department of Botany and Plant Pathology, Purdue University, West Lafayette, Indiana
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47
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Tay AP, Pang CNI, Winter DL, Wilkins MR. PTMOracle: A Cytoscape App for Covisualizing and Coanalyzing Post-Translational Modifications in Protein Interaction Networks. J Proteome Res 2017; 16:1988-2003. [PMID: 28349685 DOI: 10.1021/acs.jproteome.6b01052] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Post-translational modifications of proteins (PTMs) act as key regulators of protein activity and of protein-protein interactions (PPIs). To date, it has been difficult to comprehensively explore functional links between PTMs and PPIs. To address this, we developed PTMOracle, a Cytoscape app for coanalyzing PTMs within PPI networks. PTMOracle also allows extensive data to be integrated and coanalyzed with PPI networks, allowing the role of domains, motifs, and disordered regions to be considered. For proteins of interest, or a whole proteome, PTMOracle can generate network visualizations to reveal complex PTM-associated relationships. This is assisted by OraclePainter for coloring proteins by modifications, OracleTools for network analytics, and OracleResults for exploring tabulated findings. To illustrate the use of PTMOracle, we investigate PTM-associated relationships and their role in PPIs in four case studies. In the yeast interactome and its rich set of PTMs, we construct and explore histone-associated and domain-domain interaction networks and show how integrative approaches can predict kinases involved in phosphodegrons. In the human interactome, a phosphotyrosine-associated network is analyzed but highlights the sparse nature of human PPI networks and lack of PTM-associated data. PTMOracle is open source and available at the Cytoscape app store: http://apps.cytoscape.org/apps/ptmoracle .
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Affiliation(s)
- Aidan P Tay
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Chi Nam Ignatius Pang
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Daniel L Winter
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Marc R Wilkins
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
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48
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Jensen SM, Kimani FW, Jewett JC. Light-Activated Triazabutadienes for the Modification of a Viral Surface. Chembiochem 2016; 17:2216-2219. [PMID: 27647786 PMCID: PMC5170875 DOI: 10.1002/cbic.201600508] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Indexed: 11/10/2022]
Abstract
Chemical crosslinking is a versatile tool for the examination of biochemical interactions, in particular host-pathogen interactions. We report the critical first step toward the goal of probing these interactions by the synthesis and use of a new heterobifunctional crosslinker containing a triazabutadiene scaffold. The triazabutadiene is stable to protein conjugation and liberates a reactive aryl diazonium species upon irradiation with 350 nm light. We highlight the use of this technology by modifying the surface of several proteins, including the dengue virus envelope protein.
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Affiliation(s)
- Stephanie M Jensen
- Department of Chemistry and Biochemistry, University of Arizona, Building 41, Room 104, 1306 E University Boulevard, Tucson, AZ, 85721, USA
| | - Flora W Kimani
- Department of Chemistry and Biochemistry, University of Arizona, Building 41, Room 104, 1306 E University Boulevard, Tucson, AZ, 85721, USA
| | - John C Jewett
- Department of Chemistry and Biochemistry, University of Arizona, Building 41, Room 104, 1306 E University Boulevard, Tucson, AZ, 85721, USA
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49
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Zhang X. Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine. Proteomics 2016; 17. [PMID: 27633951 DOI: 10.1002/pmic.201600209] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 07/31/2016] [Accepted: 09/13/2016] [Indexed: 01/05/2023]
Abstract
Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine.
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Affiliation(s)
- Xi Zhang
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
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50
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Ciuffa R, Caron E, Leitner A, Uliana F, Gstaiger M, Aebersold R. Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF-α Signaling. J Proteome Res 2016; 16:14-33. [PMID: 27762135 DOI: 10.1021/acs.jproteome.6b00728] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
NF-κB is a family of ubiquitous dimeric transcription factors that play a role in a myriad of cellular processes, ranging from differentiation to stress response and immunity. In inflammation, activation of NF-κB is mediated by pro-inflammatory cytokines, in particular the prototypic cytokines IL-1β and TNF-α, which trigger the activation of complex signaling cascades. In spite of decades of research, the system level understanding of TNF-α signaling is still incomplete. This is partially due to the limited knowledge at the proteome level. The objective of this review is to summarize and critically evaluate the current status of the proteomic research on TNF-α signaling. We will discuss the merits and flaws of the existing studies as well as the insights that they have generated into the proteomic landscape and architecture connected to this signaling pathway. Besides delineating past and current trends in TNF-α proteomic research, we will identify research directions and new methodologies that can further contribute to characterize the TNF-α associated proteome in space and time.
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Affiliation(s)
- Rodolfo Ciuffa
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland
| | - Etienne Caron
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland
| | - Alexander Leitner
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland
| | - Federico Uliana
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland
| | - Matthias Gstaiger
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology, ETH Zurich , 8093 Zurich, Switzerland.,Faculty of Science, University of Zurich , 8006 Zurich, Switzerland
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