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Takagi S, Suzuki N, Ishihama Y. Revisiting Protein Reversed-Phase Chromatography for Bottom-Up Proteomics. J Proteome Res 2024; 23:4704-4714. [PMID: 39293027 DOI: 10.1021/acs.jproteome.4c00642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/20/2024]
Abstract
We revisited protein reversed-phase chromatography (RP), using state-of-the-art RP columns developed for biopharmaceuticals, such as monoclonal antibodies, in order to evaluate the suitability of this methodology as a prefractionation step for bottom-up proteomics. The protein RP prefractionation (Prot-RP) method was compared with two other widely used prefractionation methods, SDS-PAGE and high-pH peptide RP (Pept-RP) by using cell lysates as samples. The overlap between fractions of Prot-RP was comparable to that of SDS-PAGE, and the protein recovery was approximately 2-fold higher. On the other hand, the overlap between fractions of Prot-RP was slightly larger than that of Pept-RP, but Prot-RP was able to identify more protein termini and more isoform-specific peptides than Pept-RP. Our results indicate that the combination of highly efficient protein prefractionation with modern mass spectrometers is particularly effective for proteoform profiling from cellular samples.
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Affiliation(s)
- Shunsuke Takagi
- Department of Molecular Systems BioAnalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Analytical and Quality Evaluation Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka, Kanagawa 254-0014, Japan
| | - Nobuyuki Suzuki
- Analytical and Quality Evaluation Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka, Kanagawa 254-0014, Japan
| | - Yasushi Ishihama
- Department of Molecular Systems BioAnalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Laboratory of Clinical and Analytical Chemistry, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka 567-0085, Japan
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2
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Street LA, Rothamel KL, Brannan KW, Jin W, Bokor BJ, Dong K, Rhine K, Madrigal A, Al-Azzam N, Kim JK, Ma Y, Gorhe D, Abdou A, Wolin E, Mizrahi O, Ahdout J, Mujumdar M, Doron-Mandel E, Jovanovic M, Yeo GW. Large-scale map of RNA-binding protein interactomes across the mRNA life cycle. Mol Cell 2024; 84:3790-3809.e8. [PMID: 39303721 DOI: 10.1016/j.molcel.2024.08.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 04/18/2024] [Accepted: 08/26/2024] [Indexed: 09/22/2024]
Abstract
mRNAs interact with RNA-binding proteins (RBPs) throughout their processing and maturation. While efforts have assigned RBPs to RNA substrates, less exploration has leveraged protein-protein interactions (PPIs) to study proteins in mRNA life-cycle stages. We generated an RNA-aware, RBP-centric PPI map across the mRNA life cycle in human cells by immunopurification-mass spectrometry (IP-MS) of ∼100 endogenous RBPs with and without RNase, augmented by size exclusion chromatography-mass spectrometry (SEC-MS). We identify 8,742 known and 20,802 unreported interactions between 1,125 proteins and determine that 73% of the IP-MS-identified interactions are RNA regulated. Our interactome links many proteins, some with unknown functions, to specific mRNA life-cycle stages, with nearly half associated with multiple stages. We demonstrate the value of this resource by characterizing the splicing and export functions of enhancer of rudimentary homolog (ERH), and by showing that small nuclear ribonucleoprotein U5 subunit 200 (SNRNP200) interacts with stress granule proteins and binds cytoplasmic RNA differently during stress.
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Affiliation(s)
- Lena A Street
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Katherine L Rothamel
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Center for RNA Technologies and Therapeutics, University of California, San Diego, La Jolla, CA, USA
| | - Kristopher W Brannan
- Center for RNA Therapeutics, Houston Methodist Research Institute, Houston, TX, USA; Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, USA
| | - Wenhao Jin
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Benjamin J Bokor
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Kevin Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Kevin Rhine
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Assael Madrigal
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Norah Al-Azzam
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jenny Kim Kim
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Yanzhe Ma
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Darvesh Gorhe
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Ahmed Abdou
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Erica Wolin
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Orel Mizrahi
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Joshua Ahdout
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mayuresh Mujumdar
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Ella Doron-Mandel
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Marko Jovanovic
- Department of Biological Sciences, Columbia University, New York, NY, USA.
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Center for RNA Technologies and Therapeutics, University of California, San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA; Sanford Laboratories for Innovative Medicines, San Diego, CA, USA; Sanford Stem Cell Institute, Innovation Center, San Diego, CA, USA.
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3
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Kim D, Nita-Lazar A. Progress in mass spectrometry approaches to profiling protein-protein interactions in the studies of the innate immune system. JOURNAL OF PROTEINS AND PROTEOMICS 2024; 15:545-559. [PMID: 39380887 PMCID: PMC11460538 DOI: 10.1007/s42485-024-00156-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/04/2024] [Accepted: 06/24/2024] [Indexed: 10/10/2024]
Abstract
Understanding protein-protein interactions (PPIs) is pivotal for deciphering the intricacies of biological processes. Dysregulation of PPIs underlies a spectrum of diseases, including cancer, neurodegenerative disorders, and autoimmune conditions, highlighting the imperative of investigating these interactions for therapeutic advancements. This review delves into the realm of mass spectrometry-based techniques for elucidating PPIs and their profound implications in biological research. Mass spectrometry in the PPI research field not only facilitates the evaluation of protein-protein interaction modulators but also discovers unclear molecular mechanisms and sheds light on both on- and off-target effects, thus aiding in drug development. Our discussion navigates through six pivotal techniques: affinity purification mass spectrometry (AP-MS), proximity labeling mass spectrometry (PL-MS), cross-linking mass spectrometry (XL-MS), size exclusion chromatography coupled with mass spectrometry (SEC-MS), limited proteolysis-coupled mass spectrometry (LiP-MS), and thermal proteome profiling (TPP).
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Affiliation(s)
- Doeun Kim
- Functional Cellular Networks Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-1892, USA
| | - Aleksandra Nita-Lazar
- Functional Cellular Networks Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-1892, USA
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Larson J, Tokmina-Lukaszewska M, Payne D, Spietz RL, Fausset H, Alam MG, Brekke BK, Pauley J, Hasenoehrl EJ, Shepard EM, Boyd ES, Bothner B. Impact of mineral and non-mineral sources of iron and sulfur on the metalloproteome of Methanosarcina barkeri. Appl Environ Microbiol 2024; 90:e0051624. [PMID: 39023267 PMCID: PMC11337800 DOI: 10.1128/aem.00516-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 06/27/2024] [Indexed: 07/20/2024] Open
Abstract
Methanogens often inhabit sulfidic environments that favor the precipitation of transition metals such as iron (Fe) as metal sulfides, including mackinawite (FeS) and pyrite (FeS2). These metal sulfides have historically been considered biologically unavailable. Nonetheless, methanogens are commonly cultivated with sulfide (HS-) as a sulfur source, a condition that would be expected to favor metal precipitation and thus limit metal availability. Recent studies have shown that methanogens can access Fe and sulfur (S) from FeS and FeS2 to sustain growth. As such, medium supplied with FeS2 should lead to higher availability of transition metals when compared to medium supplied with HS-. Here, we examined how transition metal availability under sulfidic (i.e., cells provided with HS- as sole S source) versus non-sulfidic (cells provided with FeS2 as sole S source) conditions impact the metalloproteome of Methanosarcina barkeri Fusaro. To achieve this, we employed size exclusion chromatography coupled with inductively coupled plasma mass spectrometry and shotgun proteomics. Significant changes were observed in the composition and abundance of iron, cobalt, nickel, zinc, and molybdenum proteins. Among the differences were alterations in the stoichiometry and abundance of multisubunit protein complexes involved in methanogenesis and electron transport chains. Our data suggest that M. barkeri utilizes the minimal iron-sulfur cluster complex and canonical cysteine biosynthesis proteins when grown on FeS2 but uses the canonical Suf pathway in conjunction with the tRNA-Sep cysteine pathway for iron-sulfur cluster and cysteine biosynthesis under sulfidic growth conditions.IMPORTANCEProteins that catalyze biochemical reactions often require transition metals that can have a high affinity for sulfur, another required element for life. Thus, the availability of metals and sulfur are intertwined and can have large impacts on an organismismal biochemistry. Methanogens often occupy anoxic, sulfide-rich (euxinic) environments that favor the precipitation of transition metals as metal sulfides, thereby creating presumed metal limitation. Recently, several methanogens have been shown to acquire iron and sulfur from pyrite, an abundant iron-sulfide mineral that was traditionally considered to be unavailable to biology. The work presented here provides new insights into the distribution of metalloproteins, and metal uptake of Methanosarcina barkeri Fusaro grown under euxinic or pyritic growth conditions. Thorough characterizations of this methanogen under different metal and sulfur conditions increase our understanding of the influence of metal availability on methanogens, and presumably other anaerobes, that inhabit euxinic environments.
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Affiliation(s)
- James Larson
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | | | - Devon Payne
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
| | - Rachel L. Spietz
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
| | - Hunter Fausset
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | - Md Gahangir Alam
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
| | - Brooklyn K. Brekke
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | - Jordan Pauley
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | - Ethan J. Hasenoehrl
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | - Eric M. Shepard
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
| | - Eric S. Boyd
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
| | - Brian Bothner
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
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Doron-Mandel E, Bokor BJ, Ma Y, Street LA, Tang LC, Abdou AA, Shah NH, Rosenberger G, Jovanovic M. A Multiplexed SEC-MS Approach to Systematically Study the Interplay Between Protein Assembly-States and Phosphorylation Events. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.12.523793. [PMID: 36711903 PMCID: PMC9882152 DOI: 10.1101/2023.01.12.523793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Protein molecular interactions and post-translational modifications (PTMs), such as phosphorylation, can be co-dependent and reciprocally co-regulate each other. Although this interplay is central for many biological processes, a systematic method to simultaneously study assembly-states and PTMs from the same sample is critically missing. Here, we introduce SEC-MX (Size Exclusion Chromatography fractions MultipleXed), a global quantitative method combining Size Exclusion Chromatography and PTM-enrichment for simultaneous characterization of PTMs and assembly-states. SEC-MX enhances throughput, allows phosphopeptide enrichment, and facilitates quantitative differential comparisons between biological conditions. Applying SEC-MX to HEK293 and HCT116 cells, we generated a proof-of-concept dataset mapping thousands of phosphopeptides and their assembly-states. Our analysis revealed intricate relationships between phosphorylation events and assembly-states and generated testable hypotheses for follow-up studies. Overall, we establish SEC-MX as a valuable tool for exploring protein functions and regulation beyond abundance changes.
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LIU W, WENG L, GAO M, ZHANG X. [Applications of high performance liquid chromatography-mass spectrometry in proteomics]. Se Pu 2024; 42:601-612. [PMID: 38966969 PMCID: PMC11224944 DOI: 10.3724/sp.j.1123.2023.11006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Indexed: 07/06/2024] Open
Abstract
Proteomics profiling plays an important role in biomedical studies. Proteomics studies are much more complicated than genome research, mainly because of the complexity and diversity of proteomic samples. High performance liquid chromatography-mass spectrometry (HPLC-MS) is a fundamental tool in proteomics research owing to its high speed, resolution, and sensitivity. Proteomics research targets from the peptides and individual proteins to larger protein complexes, the molecular weight of which gradually increases, leading to sustained increases in structural and compositional complexity and alterations in molecular properties. Therefore, the selection of various separation strategies and stationary-phase parameters is crucial when dealing with the different targets in proteomics research for in-depth proteomics analysis. This article provides an overview of commonly used chromatographic-separation strategies in the laboratory, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic interaction chromatography (HIC), ion-exchange chromatography (IEC), and size-exclusion chromatography (SEC), as well as their applications and selectivity in the context of various biomacromolecules. At present, no single chromatographic or electrophoretic technology features the peak capacity required to resolve such complex mixtures into individual components. Multidimensional liquid chromatography (MDLC), which combines different orthogonal separation modes with MS, plays an important role in proteomics research. In the MDLC strategy, IEC, together with RPLC, remains the most widely used separation mode in proteomics analysis; other chromatographic methods are also frequently used for peptide/protein fractionation. MDLC technologies and their applications in a variety of proteomics analyses have undergone great development. Two strategies in MDLC separation systems are mainly used in proteomics profiling: the "bottom-up" approach and the "top-down" approach. The "shotgun" method is a typical "bottom-up" strategy that is based on the RPLC or MDLC separation of whole-protein-sample digests coupled with MS; it is an excellent technique for identifying a large number of proteins. "Top-down" analysis is based on the separation of intact proteins and provides their detailed molecular information; thus, this technique may be advantageous for analyzing the post-translational modifications (PTMs) of proteins. In this paper, the "bottom-up" "top-down" and protein-protein interaction (PPI) analyses of proteome samples are briefly reviewed. The diverse combinations of different chromatographic modes used to set up MDLC systems are described, and compatibility issues between mobile phases and analytes, between mobile phases and MS, and between mobile phases in different separation modes in multidimensional chromatography are analyzed. Novel developments in MDLC techniques, such as high-abundance protein depletion and chromatography arrays, are further discussed. In this review, the solutions proposed by researchers when encountering compatibility issues are emphasized. Moreover, the applications of HPLC-MS combined with various sample pretreatment methods in the study of exosomal and single-cell proteomics are examined. During exosome isolation, the combined use of ultracentrifugation and SEC can yield exosomes of higher purity. The use of SEC with ultra-large-pore-size packing materials (200 nm) enables the isolation of exosomal subgroups, and proteomics studies have revealed significant differences in protein composition and function between these subgroups. In the field of single-cell proteomics, researchers have addressed challenges related to reducing sample processing volumes, preventing sample loss, and avoiding contamination during sample preparation. Innovative methods and improvements, such as the utilization of capillaries for sample processing and microchips as platforms to minimize the contact area of the droplets, have been proposed. The integration of these techniques with HPLC-MS shows some progress. In summary, this article focuses on the recent advances in HPLC-MS technology for proteomics analysis and provides a comprehensive reference for future research in the field of proteomics.
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Holfeld A, Schuster D, Sesterhenn F, Gillingham AK, Stalder P, Haenseler W, Barrio-Hernandez I, Ghosh D, Vowles J, Cowley SA, Nagel L, Khanppnavar B, Serdiuk T, Beltrao P, Korkhov VM, Munro S, Riek R, de Souza N, Picotti P. Systematic identification of structure-specific protein-protein interactions. Mol Syst Biol 2024; 20:651-675. [PMID: 38702390 PMCID: PMC11148107 DOI: 10.1038/s44320-024-00037-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 05/06/2024] Open
Abstract
The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.
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Affiliation(s)
- Aleš Holfeld
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Dina Schuster
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zurich, Zurich, Switzerland
- Laboratory of Biomolecular Research, Division of Biology and Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Fabian Sesterhenn
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | | | - Patrick Stalder
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Walther Haenseler
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- University Research Priority Program AdaBD (Adaptive Brain Circuits in Development and Learning), University of Zurich, Zurich, Switzerland
| | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Dhiman Ghosh
- Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland
| | - Jane Vowles
- James and Lillian Martin Centre for Stem Cell Research, Sir William Dunn School of Pathology, University of Oxford, Oxford, UK
| | - Sally A Cowley
- James and Lillian Martin Centre for Stem Cell Research, Sir William Dunn School of Pathology, University of Oxford, Oxford, UK
| | - Luise Nagel
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Basavraj Khanppnavar
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zurich, Zurich, Switzerland
- Laboratory of Biomolecular Research, Division of Biology and Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Tetiana Serdiuk
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Pedro Beltrao
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Volodymyr M Korkhov
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zurich, Zurich, Switzerland
- Laboratory of Biomolecular Research, Division of Biology and Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Sean Munro
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Roland Riek
- Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland
| | - Natalie de Souza
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Paola Picotti
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.
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Ng CCA, Zhou Y, Yao ZP. Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review. Anal Chim Acta 2023; 1268:341330. [PMID: 37268337 DOI: 10.1016/j.aca.2023.341330] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 05/04/2023] [Accepted: 05/06/2023] [Indexed: 06/04/2023]
Abstract
Peptide sequencing is of great significance to fundamental and applied research in the fields such as chemical, biological, medicinal and pharmaceutical sciences. With the rapid development of mass spectrometry and sequencing algorithms, de-novo peptide sequencing using tandem mass spectrometry (MS/MS) has become the main method for determining amino acid sequences of novel and unknown peptides. Advanced algorithms allow the amino acid sequence information to be accurately obtained from MS/MS spectra in short time. In this review, algorithms from exhaustive search to the state-of-art machine learning and neural network for high-throughput and automated de-novo sequencing are introduced and compared. Impacts of datasets on algorithm performance are highlighted. The current limitations and promising direction of de-novo peptide sequencing are also discussed in this review.
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Affiliation(s)
- Cheuk Chi A Ng
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Yin Zhou
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Zhong-Ping Yao
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China.
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9
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Palukuri MV, Patil RS, Marcotte EM. Molecular complex detection in protein interaction networks through reinforcement learning. BMC Bioinformatics 2023; 24:306. [PMID: 37532987 PMCID: PMC10394916 DOI: 10.1186/s12859-023-05425-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 07/20/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND Proteins often assemble into higher-order complexes to perform their biological functions. Such protein-protein interactions (PPI) are often experimentally measured for pairs of proteins and summarized in a weighted PPI network, to which community detection algorithms can be applied to define the various higher-order protein complexes. Current methods include unsupervised and supervised approaches, often assuming that protein complexes manifest only as dense subgraphs. Utilizing supervised approaches, the focus is not on how to find them in a network, but only on learning which subgraphs correspond to complexes, currently solved using heuristics. However, learning to walk trajectories on a network to identify protein complexes leads naturally to a reinforcement learning (RL) approach, a strategy not extensively explored for community detection. Here, we develop and evaluate a reinforcement learning pipeline for community detection on weighted protein-protein interaction networks to detect new protein complexes. The algorithm is trained to calculate the value of different subgraphs encountered while walking on the network to reconstruct known complexes. A distributed prediction algorithm then scales the RL pipeline to search for novel protein complexes on large PPI networks. RESULTS The reinforcement learning pipeline is applied to a human PPI network consisting of 8k proteins and 60k PPI, which results in 1,157 protein complexes. The method demonstrated competitive accuracy with improved speed compared to previous algorithms. We highlight protein complexes such as C4orf19, C18orf21, and KIAA1522 which are currently minimally characterized. Additionally, the results suggest TMC04 be a putative additional subunit of the KICSTOR complex and confirm the involvement of C15orf41 in a higher-order complex with HIRA, CDAN1, ASF1A, and by 3D structural modeling. CONCLUSIONS Reinforcement learning offers several distinct advantages for community detection, including scalability and knowledge of the walk trajectories defining those communities. Applied to currently available human protein interaction networks, this method had comparable accuracy with other algorithms and notable savings in computational time, and in turn, led to clear predictions of protein function and interactions for several uncharacterized human proteins.
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Affiliation(s)
- Meghana V Palukuri
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA.
- Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, TX, 78712, USA.
| | - Ridhi S Patil
- Department of Biomedical Engineering, University of Texas, Austin, TX, 78712, USA.
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA.
- Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, TX, 78712, USA.
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10
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Street L, Rothamel K, Brannan K, Jin W, Bokor B, Dong K, Rhine K, Madrigal A, Al-Azzam N, Kim JK, Ma Y, Abdou A, Wolin E, Doron-Mandel E, Ahdout J, Mujumdar M, Jovanovic M, Yeo GW. Large-scale map of RNA binding protein interactomes across the mRNA life-cycle. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.08.544225. [PMID: 37333282 PMCID: PMC10274859 DOI: 10.1101/2023.06.08.544225] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Messenger RNAs (mRNAs) interact with RNA-binding proteins (RBPs) in diverse ribonucleoprotein complexes (RNPs) during distinct life-cycle stages for their processing and maturation. While substantial attention has focused on understanding RNA regulation by assigning proteins, particularly RBPs, to specific RNA substrates, there has been considerably less exploration leveraging protein-protein interaction (PPI) methodologies to identify and study the role of proteins in mRNA life-cycle stages. To address this gap, we generated an RNA-aware RBP-centric PPI map across the mRNA life-cycle by immunopurification (IP-MS) of ~100 endogenous RBPs across the life-cycle in the presence or absence of RNase, augmented by size exclusion chromatography (SEC-MS). Aside from confirming 8,700 known and discovering 20,359 novel interactions between 1125 proteins, we determined that 73% of our IP interactions are regulated by the presence of RNA. Our PPI data enables us to link proteins to life-cycle stage functions, highlighting that nearly half of the proteins participate in at least two distinct stages. We show that one of the most highly interconnected proteins, ERH, engages in multiple RNA processes, including via interactions with nuclear speckles and the mRNA export machinery. We also demonstrate that the spliceosomal protein SNRNP200 participates in distinct stress granule-associated RNPs and occupies different RNA target regions in the cytoplasm during stress. Our comprehensive RBP-focused PPI network is a novel resource for identifying multi-stage RBPs and exploring RBP complexes in RNA maturation.
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Affiliation(s)
- Lena Street
- These authors contributed equally
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Katherine Rothamel
- These authors contributed equally
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kristopher Brannan
- These authors contributed equally
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Center for RNA Therapeutics, Houston Methodist Research Institute, Houston, TX, USA
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, USA
| | - Wenhao Jin
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Benjamin Bokor
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Kevin Dong
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kevin Rhine
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Assael Madrigal
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Norah Al-Azzam
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jenny Kim Kim
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Yanzhe Ma
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Ahmed Abdou
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Erica Wolin
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Ella Doron-Mandel
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Joshua Ahdout
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Mayuresh Mujumdar
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Marko Jovanovic
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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11
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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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12
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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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13
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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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14
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Peter C, Schulz WA, Whongsiri P. Characterization of Native COMPASS Complex in Urothelial Carcinoma Cells by Size Exclusion Chromatography. Methods Mol Biol 2023; 2684:101-109. [PMID: 37410229 DOI: 10.1007/978-1-0716-3291-8_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
The human COMPASS complexes regulate gene expression during development and cell differentiation. Three distinct subunits, KMT2C, KMT2D, and KDM6A (also known as UTX), are frequently mutated in urothelial carcinoma, possibly disrupting the formation of functional COMPASS complexes. Here, we describe methods to evaluate the formation of these large native protein complexes in urothelial carcinoma (UC) cell lines harboring different mutations in KMT2C/D. To this end COMPASS complexes were purified from nuclear extracts by size exclusion chromatography (SEC) using a Sepharose 6 column. SEC fractions were then separated by 3-8% Tris-acetate gradient polyacrylamide gel and the COMPASS complex subunits KMT2C, UTX, WDR5, and RBBP5 were detected by immunoblotting. In this fashion, the formation of a COMPASS complex could be observed in UC cells with wild-type but not in cells with mutant KMT2C and KMTD.
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Affiliation(s)
- Christoph Peter
- Institute of Molecular Medicine I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Wolfgang A Schulz
- Department of Urology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | - Patcharawalai Whongsiri
- Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
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15
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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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16
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Zhang Y, Yang L, Fang K, Li Q, Xu H, Ren Y, Zi J, Chen CD, Liu S. Dynamic Responses of Chromosome-Binding Protein Complexes to Meiotic Prophase I of Mouse Spermatocyte. J Proteome Res 2022; 21:2715-2726. [PMID: 36223561 DOI: 10.1021/acs.jproteome.2c00414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Meiotic prophase I (MPI) is the most important event in mammalian meiosis. The status of the chromosome-binding proteins (CBPs) and the corresponding complexes and their functions in MPI have not yet been well scrutinized. Quantitative proteomics focused on MPI-related CBPs was accomplished, in which mouse primary spermatocytes in four different subphases of MPI were collected, and chromosome-enriched proteins were extracted and quantitatively identified. According to a stringent criterion, 1136 CBPs in the MPI subphases were quantified. Looking at the dynamic patterns of CBP abundance in response to MPI progression, the patterns were broadly divided into two groups: high abundance in leptotene and zygotene or that in pachytene and diplotene. Furthermore, 152 such CBPs were regarded as 26 CBP complexes with strict filtration, in which some of these complexes were perceived to be MPI-dependent for the first time. These complexes basically belonged to four functional categories, while their dynamic abundance changes following MPI appeared; the functions of DNA replication decreased; and transcription and synapsis were activated in zygotene, pachytene, and diplotene; in contrast to the traditional prediction, condensin activity weakened in pachytene and diplotene. Profiling of protein complexes thus offered convincing evidence of the importance of CBP complexes in MPI.
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Affiliation(s)
- Yuxing Zhang
- BGI-Shenzhen, Shenzhen 518083, China.,College of Life Sciences & Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049 China
| | | | - Kailun Fang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031 China
| | - Qidan Li
- BGI-Shenzhen, Shenzhen 518083, China
| | - Hongkai Xu
- BGI-Shenzhen, Shenzhen 518083, China.,College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yan Ren
- BGI-Shenzhen, Shenzhen 518083, China.,Experiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jin Zi
- BGI-Shenzhen, Shenzhen 518083, China
| | - Charlie Degui Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Shanghai 200031, China
| | - Siqi Liu
- BGI-Shenzhen, Shenzhen 518083, China
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17
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Pauwels J, Fijałkowska D, Eyckerman S, Gevaert K. Mass spectrometry and the cellular surfaceome. MASS SPECTROMETRY REVIEWS 2022; 41:804-841. [PMID: 33655572 DOI: 10.1002/mas.21690] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/05/2021] [Accepted: 02/09/2021] [Indexed: 06/12/2023]
Abstract
The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.
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Affiliation(s)
- Jarne Pauwels
- VIB Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | | | - Sven Eyckerman
- VIB Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Kris Gevaert
- VIB Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
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18
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Global landscape of protein complexes in postprandial-state livers from diet-induced obese and lean mice. Biochem Biophys Res Commun 2022; 629:40-46. [DOI: 10.1016/j.bbrc.2022.08.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 08/23/2022] [Indexed: 11/19/2022]
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19
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Xu C, Wang B, Yang L, Zhongming Hu L, Yi L, Wang Y, Chen S, Emili A, Wan C. Global Landscape of Native Protein Complexes in Synechocystis sp. PCC 6803. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022; 20:715-727. [PMID: 33636367 PMCID: PMC9880817 DOI: 10.1016/j.gpb.2020.06.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Revised: 04/04/2020] [Accepted: 06/12/2020] [Indexed: 01/31/2023]
Abstract
Synechocystis sp. PCC 6803 (hereafter: Synechocystis) is a model organism for studying photosynthesis, energy metabolism, and environmental stress. Although known as the first fully sequenced phototrophic organism, Synechocystis still has almost half of its proteome without functional annotations. In this study, by using co-fractionation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS), we define 291 multi-protein complexes, encompassing 24,092 protein-protein interactions (PPIs) among 2062 distinct gene products. This information not only reveals the roles of photosynthesis in metabolism, cell motility, DNA repair, cell division, and other physiological processes, but also shows how protein functions vary from bacteria to higher plants due to changes in interaction partners. It also allows us to uncover the functions of hypothetical proteins, such as Sll0445, Sll0446, and Sll0447 involved in photosynthesis and cell motility, and Sll1334 involved in regulation of fatty acid biogenesis. Here we present the most extensive PPI data for Synechocystis so far, which provide critical insights into fundamental molecular mechanisms in cyanobacteria.
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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 430079, China
| | - Bing Wang
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China
| | - Lin Yang
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China
| | - Lucas Zhongming Hu
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 2E8, Canada
| | - Lanxing Yi
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China
| | - Yaxuan Wang
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China
| | - Shenglan Chen
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China
| | - Andrew Emili
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 2E8, Canada,Departments of Biochemistry and Biology, Boston University, Boston, MA 02215, USA
| | - Cuihong Wan
- School of Life Sciences and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University, Wuhan 430079, China,Corresponding author.
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20
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Rogawski R, Sharon M. Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry. Chem Rev 2022; 122:7386-7414. [PMID: 34406752 PMCID: PMC9052418 DOI: 10.1021/acs.chemrev.1c00217] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Indexed: 01/11/2023]
Abstract
Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.
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Affiliation(s)
- Rivkah Rogawski
- Department of Biomolecular
Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Michal Sharon
- Department of Biomolecular
Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
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21
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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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22
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Schessner JP, Voytik E, Bludau I. A practical guide to interpreting and generating bottom-up proteomics data visualizations. Proteomics 2022; 22:e2100103. [PMID: 35107884 DOI: 10.1002/pmic.202100103] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/22/2021] [Accepted: 01/20/2022] [Indexed: 11/10/2022]
Abstract
Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data Figures in this review on GitHub (https://github.com/MannLabs/ProteomicsVisualization). This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Julia Patricia Schessner
- Max-Planck-Institute of Biochemistry, Department of Proteomics and Signal Transduction, Planegg, Germany
| | - Eugenia Voytik
- Max-Planck-Institute of Biochemistry, Department of Proteomics and Signal Transduction, Planegg, Germany
| | - Isabell Bludau
- Max-Planck-Institute of Biochemistry, Department of Proteomics and Signal Transduction, Planegg, Germany
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23
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Xiong E, Cao D, Qu C, Zhao P, Wu Z, Yin D, Zhao Q, Gong F. Multilocation proteins in organelle communication: Based on protein-protein interactions. PLANT DIRECT 2022; 6:e386. [PMID: 35229068 PMCID: PMC8861329 DOI: 10.1002/pld3.386] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 12/17/2021] [Accepted: 01/18/2022] [Indexed: 05/25/2023]
Abstract
Protein-protein interaction (PPI) plays a crucial role in most biological processes, including signal transduction and cell apoptosis. Importantly, the knowledge of PPIs can be useful for identification of multimeric protein complexes and elucidation of uncharacterized protein functions. Arabidopsis thaliana, the best-characterized dicotyledonous plant, the steadily increasing amount of information on the levels of its proteome and signaling pathways is progressively enabling more researchers to construct models for cellular processes for the plant, which in turn encourages more experimental data to be generated. In this study, we performed an overview analysis of the 10 major organelles and their associated proteins of the dicotyledonous model plant Arabidopsis thaliana via PPI network, and found that PPI may play an important role in organelle communication. Further, multilocation proteins, especially phosphorylation-related multilocation proteins, can function as a "needle and thread" via PPIs and play an important role in organelle communication. Similar results were obtained in a monocotyledonous model crop, rice. Furthermore, we provide a research strategy for multilocation proteins by LOPIT technique, proteomics, and bioinformatics analysis and also describe their potential role in the field of plant science. The results provide a new view that the phosphorylation-related multilocation proteins play an important role in organelle communication and provide new insight into PPIs and novel directions for proteomic research. The research of phosphorylation-related multilocation proteins may promote the development of organelle communication and provide an important theoretical basis for plant responses to external stress.
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Affiliation(s)
- Erhui Xiong
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Di Cao
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Chengxin Qu
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Pengfei Zhao
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Zhaokun Wu
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Dongmei Yin
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Quanzhi Zhao
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Fangping Gong
- College of AgronomyHenan Agricultural UniversityZhengzhouChina
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24
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Laulumaa S, Varjosalo M. Commander Complex-A Multifaceted Operator in Intracellular Signaling and Cargo. Cells 2021; 10:cells10123447. [PMID: 34943955 PMCID: PMC8700231 DOI: 10.3390/cells10123447] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 12/01/2021] [Accepted: 12/03/2021] [Indexed: 12/18/2022] Open
Abstract
Commander complex is a 16-protein complex that plays multiple roles in various intracellular events in endosomal cargo and in the regulation of cell homeostasis, cell cycle and immune response. It consists of COMMD1-10, CCDC22, CCDC93, DENND10, VPS26C, VPS29, and VPS35L. These proteins are expressed ubiquitously in the human body, and they have been linked to diseases including Wilson's disease, atherosclerosis, and several types of cancer. In this review we describe the function of the commander complex in endosomal cargo and summarize the individual known roles of COMMD proteins in cell signaling and cancer. It becomes evident that commander complex might be a much more important player in intracellular regulation than we currently understand, and more systematic research on the role of commander complex is required.
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25
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Landeira-Viñuela A, Díez P, Juanes-Velasco P, Lécrevisse Q, Orfao A, De Las Rivas J, Fuentes M. Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model. Biomolecules 2021; 11:1776. [PMID: 34944421 PMCID: PMC8699084 DOI: 10.3390/biom11121776] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/11/2021] [Accepted: 11/23/2021] [Indexed: 12/12/2022] Open
Abstract
Human Proteome Project (HPP) presents a systematic characterization of the protein landscape under different conditions using several complementary-omic techniques (LC-MS/MS proteomics, affinity proteomics, transcriptomics, etc.). In the present study, using a B-cell lymphoma cell line as a model, comprehensive integration of RNA-Seq transcriptomics, MS/MS, and antibody-based affinity proteomics (combined with size-exclusion chromatography) (SEC-MAP) were performed to uncover correlations that could provide insights into protein dynamics at the intracellular level. Here, 5672 unique proteins were systematically identified by MS/MS analysis and subcellular protein extraction strategies (neXtProt release 2020-21, MS/MS data are available via ProteomeXchange with identifier PXD003939). Moreover, RNA deep sequencing analysis of this lymphoma B-cell line identified 19,518 expressed genes and 5707 protein coding genes (mapped to neXtProt). Among these data sets, 162 relevant proteins (targeted by 206 antibodies) were systematically analyzed by the SEC-MAP approach, providing information about PTMs, isoforms, protein complexes, and subcellular localization. Finally, a bioinformatic pipeline has been designed and developed for orthogonal integration of these high-content proteomics and transcriptomics datasets, which might be useful for comprehensive and global characterization of intracellular protein profiles.
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Affiliation(s)
- Alicia Landeira-Viñuela
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
| | - Paula Díez
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
- Proteomics Unit, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Pablo Juanes-Velasco
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
| | - Quentin Lécrevisse
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
| | - Alberto Orfao
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
| | - Javier De Las Rivas
- Bioinformatics and Functional Genomics, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain;
| | - Manuel Fuentes
- Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, Spain; (A.L.-V.); (P.D.); (P.J.-V.); (Q.L.); (A.O.)
- Proteomics Unit, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
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26
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Chirițoiu GN, Chirițoiu M, Munteanu CV. Dataset of human EDEM2 melanoma cells proteomics, affinity proteomics and deglycoproteomics. Data Brief 2021; 39:107471. [PMID: 34712749 PMCID: PMC8529096 DOI: 10.1016/j.dib.2021.107471] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/02/2021] [Accepted: 10/04/2021] [Indexed: 11/19/2022] Open
Abstract
EDEM2 (Endoplasmic reticulum Degradation-Enhancing alpha-Mannosidase-like protein 2) is one of the key-proteins suggested to be involved in the selection and degradation of misfolded proteins from the endoplasmic reticulum. The datasets discussed in this article are related to experiments covering affinity proteomics, label-free quantitative proteomics, deglycoproteomics and SILAC (Stable Isotope Labeling by Amino Acids in Cell Culture) proteomics data of A375 melanoma cells with modified expression of EDEM2. Our first aim was to affinity-enrich EDEM2 alongside its potential interaction partners and analyse the obtained samples by nanoLC-MS/MS to identify novel EDEM2 associated proteins. The dataset was substantiated by SDF (Sucrose Density Fractionation)-nanoLC-MS/MS experiments, in an integrated workflow to validate EDEM2 identified partners and corroborate these with previous data. Our second aim was to delineate novel EDEM2 substrate candidates using a two-step strategy. The first one refers to the deglycoproteomics dataset, which covers nanoLC-MS/MS analysis of Concanavalin A enriched glycopeptides released by endoglycosidase digestion from A375 melanoma cell lysates. This allowed us to map the fraction of glycoproteins with non-matured N-glycans from A375 melanoma cells and find or validate N-glycosylation sites of proteins from the secretory pathway. The same dataset was also used to define glycoproteins altered by the down-regulation of endogenous EDEM2, which should contain its candidate-substrates. In a second step we delineate the degradation kinetics of some of these proteins using a pulse SILAC strategy (pSILAC) thus complementing our initial findings with a fourth dataset. Beside nanoLC-MS/MS analysis our findings were also validated by various biochemical experiments. All the data described are associated with a research article published in Molecular and Cellular Proteomics [1].
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Affiliation(s)
- Gabriela N. Chirițoiu
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, Bucharest 060031, Romania
| | - Marioara Chirițoiu
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, Bucharest 060031, Romania
| | - Cristian V.A. Munteanu
- Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry, Splaiul Independenței 296, Bucharest 060031, Romania
- Corresponding author. @CristiVMunteanu
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27
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Munson MJ, Mathai BJ, Ng MYW, Trachsel-Moncho L, de la Ballina LR, Schultz SW, Aman Y, Lystad AH, Singh S, Singh S, Wesche J, Fang EF, Simonsen A. GAK and PRKCD are positive regulators of PRKN-independent mitophagy. Nat Commun 2021; 12:6101. [PMID: 34671015 DOI: 10.1101/2020.11.05.369496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 09/29/2021] [Indexed: 05/28/2023] Open
Abstract
The mechanisms involved in programmed or damage-induced removal of mitochondria by mitophagy remains elusive. Here, we have screened for regulators of PRKN-independent mitophagy using an siRNA library targeting 197 proteins containing lipid interacting domains. We identify Cyclin G-associated kinase (GAK) and Protein Kinase C Delta (PRKCD) as regulators of PRKN-independent mitophagy, with both being dispensable for PRKN-dependent mitophagy and starvation-induced autophagy. We demonstrate that the kinase activity of both GAK and PRKCD are required for efficient mitophagy in vitro, that PRKCD is present on mitochondria, and that PRKCD facilitates recruitment of ULK1/ATG13 to early autophagic structures. Importantly, we demonstrate in vivo relevance for both kinases in the regulation of basal mitophagy. Knockdown of GAK homologue (gakh-1) in C. elegans or knockout of PRKCD homologues in zebrafish led to significant inhibition of basal mitophagy, highlighting the evolutionary relevance of these kinases in mitophagy regulation.
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Affiliation(s)
- Michael J Munson
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway.
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway.
- Advanced Drug Delivery, Pharmaceutical Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
| | - Benan J Mathai
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Matthew Yoke Wui Ng
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Laura Trachsel-Moncho
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Laura R de la Ballina
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sebastian W Schultz
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Molecular Cell Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Yahyah Aman
- Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, 1478, Lørenskog, Norway
| | - Alf H Lystad
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sakshi Singh
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sachin Singh
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Tumor Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Jørgen Wesche
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Tumor Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Evandro F Fang
- Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, 1478, Lørenskog, Norway
| | - Anne Simonsen
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway.
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway.
- Department of Molecular Cell Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway.
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28
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Munson MJ, Mathai BJ, Ng MYW, Trachsel-Moncho L, de la Ballina LR, Schultz SW, Aman Y, Lystad AH, Singh S, Singh S, Wesche J, Fang EF, Simonsen A. GAK and PRKCD are positive regulators of PRKN-independent mitophagy. Nat Commun 2021; 12:6101. [PMID: 34671015 PMCID: PMC8528926 DOI: 10.1038/s41467-021-26331-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 09/29/2021] [Indexed: 12/26/2022] Open
Abstract
The mechanisms involved in programmed or damage-induced removal of mitochondria by mitophagy remains elusive. Here, we have screened for regulators of PRKN-independent mitophagy using an siRNA library targeting 197 proteins containing lipid interacting domains. We identify Cyclin G-associated kinase (GAK) and Protein Kinase C Delta (PRKCD) as regulators of PRKN-independent mitophagy, with both being dispensable for PRKN-dependent mitophagy and starvation-induced autophagy. We demonstrate that the kinase activity of both GAK and PRKCD are required for efficient mitophagy in vitro, that PRKCD is present on mitochondria, and that PRKCD facilitates recruitment of ULK1/ATG13 to early autophagic structures. Importantly, we demonstrate in vivo relevance for both kinases in the regulation of basal mitophagy. Knockdown of GAK homologue (gakh-1) in C. elegans or knockout of PRKCD homologues in zebrafish led to significant inhibition of basal mitophagy, highlighting the evolutionary relevance of these kinases in mitophagy regulation.
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Affiliation(s)
- Michael J Munson
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway.
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway.
- Advanced Drug Delivery, Pharmaceutical Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
| | - Benan J Mathai
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Matthew Yoke Wui Ng
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Laura Trachsel-Moncho
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Laura R de la Ballina
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sebastian W Schultz
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Molecular Cell Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Yahyah Aman
- Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, 1478, Lørenskog, Norway
| | - Alf H Lystad
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sakshi Singh
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
| | - Sachin Singh
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Tumor Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Jørgen Wesche
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway
- Department of Tumor Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway
| | - Evandro F Fang
- Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, 1478, Lørenskog, Norway
| | - Anne Simonsen
- Division of Biochemistry, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, N-0372, Oslo, Norway.
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0316, Oslo, Norway.
- Department of Molecular Cell Biology, The Norwegian Radium Hospital Montebello, N-0379, Oslo, Norway.
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29
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Using yeast two-hybrid system and molecular dynamics simulation to detect venom protein-protein interactions. Curr Res Toxicol 2021; 2:93-98. [PMID: 34345854 PMCID: PMC8320608 DOI: 10.1016/j.crtox.2021.02.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/14/2021] [Accepted: 02/19/2021] [Indexed: 12/13/2022] Open
Abstract
The venom protein-protein interactions in snake venom remain largely unknown. Y2H coupled with MD simulations was used to detect venom protein interactions. Venom PLA2s interact with themselves and Lys49 PLA2 interacts with venom CRISP.
Proteins and peptides are major components of snake venom. Venom protein transcriptomes and proteomes of many snake species have been reported; however, snake venom complexity (i.e., the venom protein-protein interactions, PPIs) remains largely unknown. To detect the venom protein interactions, we used the most common snake venom component, phospholipase A2s (PLA2s) as a “bait” to identify the interactions between PLA2s and 14 of the most common proteins in Western diamondback rattlesnake (Crotalus atrox) venom by using yeast two-hybrid (Y2H) analysis, a technique used to detect PPIs. As a result, we identified PLA2s interacting with themselves, and lysing-49 PLA2 (Lys49 PLA2) interacting with venom cysteine-rich secretory protein (CRISP). To reveal the complex structure of Lys49 PLA2-CRISP interaction at the structural level, we first built the three-dimensional (3D) structures of Lys49 PLA2 and CRISP by a widely used computational program-MODELLER. The binding modes of Lys49 PLA2-CRISP interaction were then predicted through three different docking programs including ClusPro, ZDOCK and HADDOCK. Furthermore, the most likely complex structure of Lys49 PLA2-CRISP was inferred by molecular dynamic (MD) simulations with GROMACS software. The techniques used and results obtained from this study strengthen the understanding of snake venom protein interactions and pave the way for the study of animal venom complexity.
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30
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Munteanu CVA, Chirițoiu GN, Chirițoiu M, Ghenea S, Petrescu AJ, Petrescu ȘM. Affinity proteomics and deglycoproteomics uncover novel EDEM2 endogenous substrates and an integrative ERAD network. Mol Cell Proteomics 2021; 20:100125. [PMID: 34332121 PMCID: PMC8455867 DOI: 10.1016/j.mcpro.2021.100125] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 07/09/2021] [Accepted: 07/25/2021] [Indexed: 02/08/2023] Open
Abstract
Various pathologies result from disruptions to or stress of endoplasmic reticulum (ER) homeostasis, such as Parkinson's disease and most neurodegenerative illnesses, diabetes, pulmonary fibrosis, viral infections and cancers. A critical process in maintaining ER homeostasis is the selection of misfolded proteins by the ER quality-control system (ERQC) for destruction via ER-associated degradation (ERAD). One key protein proposed to act during the first steps of misfolded glycoprotein degradation is the ER degradation-enhancing α-mannosidase-like protein 2 (EDEM2). Therefore, characterization of the EDEM2 associated proteome is of great interest. We took advantage of using melanoma cells overexpressing EDEM2 as a cancer model system, to start documenting at the deglycoproteome level (N-glycosites identification) the emerging link between ER homeostasis and cancer progression. The dataset created for identifying the EDEM2 glyco-clients carrying high mannose/hybrid N-glycans provides a comprehensive N-glycosites analysis mapping over 1000 N-glycosites on more than 600 melanoma glycoproteins. To identify EDEM2-associated proteins we used affinity-proteomics and proteome-wide analysis of sucrose density fractionation in an integrative workflow. Using intensity and spectral count-based quantification, we identify seven new EDEM2 partners, all of which are involved in ERQC and ERAD. Moreover, we defined novel endogenous candidates for EDEM2-dependent ERAD by combining deglycoproteomics, SILAC-based proteomics, and biochemical methods. These included tumor antigens and several ER-transiting endogenous melanoma proteins, including ITGA1 and PCDH2, the expression of which was negatively correlated with that of EDEM2. Tumor antigens are key in the antigen presentation process, whilst ITGA1 and PCDH2 are involved in melanoma metastasis and invasion. EDEM2 could therefore have a regulatory role in melanoma through the modulation of these glycoproteins degradation and trafficking. The data presented herein suggest that EDEM2 is involved in ER homeostasis to a greater extent than previously suggested.
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Affiliation(s)
- Cristian V A Munteanu
- Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania
| | - Gabriela N Chirițoiu
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania
| | - Marioara Chirițoiu
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania
| | - Simona Ghenea
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania
| | - Andrei-Jose Petrescu
- Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania
| | - Ștefana M Petrescu
- Department of Molecular Cell Biology, Institute of Biochemistry, Splaiul Independenței 296, 060031, Bucharest, Romania.
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31
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Hu Y, Park N, Seo KS, Park JY, Somarathne RP, Olivier AK, Fitzkee NC, Thornton JA. Pneumococcal surface adhesion A protein (PsaA) interacts with human Annexin A2 on airway epithelial cells. Virulence 2021; 12:1841-1854. [PMID: 34233589 PMCID: PMC8274441 DOI: 10.1080/21505594.2021.1947176] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
Abstract
Streptococcus pneumoniae (pneumococcus) is a normal colonizer of the human nasopharynx capable of causing serious invasive disease. Since colonization of the nasopharynx is a prerequisite for progression to invasive diseases, the development of future protein-based vaccines requires an understanding of the intimate interaction of bacterial adhesins with host receptors. In this study, we identified that pneumococcal surface adhesin A (PsaA), a highly conserved pneumococcal protein known to play an important role in colonization of pneumococcus, can interact with Annexin A2 (ANXA2) on Detroit 562 nasopharyngeal epithelial cells. Lentiviral expression of ANXA2 in HEK 293 T/17 cells, which normally express minimal ANXA2, significantly increased pneumococcal adhesion. Blocking of ANXA2 with recombinant PsaA negatively impacted pneumococcal adherence to ANXA2-transduced HEK cells. These results suggest that ANXA2 is an important host cellular receptor for pneumococcal colonization.
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Affiliation(s)
- Yoonsung Hu
- Department of Biological Sciences, Mississippi State University, Mississippi State, USA
| | - Nogi Park
- Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, USA
| | - Keun Seok Seo
- Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, USA
| | - Joo Youn Park
- Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, USA
| | - Radha P Somarathne
- Department of Chemistry, Mississippi State University, Mississippi State, USA
| | - Alicia K Olivier
- Department of Population and Pathobiology, College of Veterinary Medicine, Mississippi State University, MS, USA
| | - Nicholas C Fitzkee
- Department of Chemistry, Mississippi State University, Mississippi State, USA
| | - Justin A Thornton
- Department of Biological Sciences, Mississippi State University, Mississippi State, USA
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32
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Drew K, Wallingford JB, Marcotte EM. hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies. Mol Syst Biol 2021; 17:e10016. [PMID: 33973408 PMCID: PMC8111494 DOI: 10.15252/msb.202010016] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 04/08/2021] [Accepted: 04/09/2021] [Indexed: 12/30/2022] Open
Abstract
A general principle of biology is the self-assembly of proteins into functional complexes. Characterizing their composition is, therefore, required for our understanding of cellular functions. Unfortunately, we lack knowledge of the comprehensive set of identities of protein complexes in human cells. To address this gap, we developed a machine learning framework to identify protein complexes in over 15,000 mass spectrometry experiments which resulted in the identification of nearly 7,000 physical assemblies. We show our resource, hu.MAP 2.0, is more accurate and comprehensive than previous state of the art high-throughput protein complex resources and gives rise to many new hypotheses, including for 274 completely uncharacterized proteins. Further, we identify 253 promiscuous proteins that participate in multiple complexes pointing to possible moonlighting roles. We have made hu.MAP 2.0 easily searchable in a web interface (http://humap2.proteincomplexes.org/), which will be a valuable resource for researchers across a broad range of interests including systems biology, structural biology, and molecular explanations of disease.
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Affiliation(s)
- Kevin Drew
- Department of Molecular BiosciencesCenter for Systems and Synthetic BiologyUniversity of TexasAustinTXUSA
- Present address:
Department of Biological SciencesUniversity of Illinois at ChicagoChicagoILUSA
| | - John B Wallingford
- Department of Molecular BiosciencesCenter for Systems and Synthetic BiologyUniversity of TexasAustinTXUSA
| | - Edward M Marcotte
- Department of Molecular BiosciencesCenter for Systems and Synthetic BiologyUniversity of TexasAustinTXUSA
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33
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PCprophet: a framework for protein complex prediction and differential analysis using proteomic data. Nat Methods 2021; 18:520-527. [PMID: 33859439 DOI: 10.1038/s41592-021-01107-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 03/03/2021] [Indexed: 02/02/2023]
Abstract
Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein profiles have shown promise. However, most approaches for interpreting cofractionation datasets to yield complex composition and rearrangements between samples depend considerably on protein-protein interaction inference. We introduce PCprophet, a toolkit built on size exclusion chromatography-sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data to predict protein complexes and characterize their changes across experimental conditions. We demonstrate improved performance of PCprophet over state-of-the-art approaches and introduce a Bayesian approach to analyze altered protein-protein interactions across conditions. We provide both command-line and graphical interfaces to support the application of PCprophet to any cofractionation MS dataset, independent of separation or quantitative liquid chromatography-MS workflow, for the detection and quantitative tracking of protein complexes and their physiological dynamics.
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34
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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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35
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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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36
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Lee Y, Szymanski DB. Multimerization variants as potential drivers of neofunctionalization. SCIENCE ADVANCES 2021; 7:eabf0984. [PMID: 33771868 PMCID: PMC7997512 DOI: 10.1126/sciadv.abf0984] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 01/29/2021] [Indexed: 05/05/2023]
Abstract
Whole-genome duplications are common during evolution, creating genetic redundancy that can enable cellular innovations. Novel protein-protein interactions provide a route to diversified gene functions, but, at present, there is limited proteome-scale knowledge on the extent to which variability in protein complex formation drives neofunctionalization. Here, we used protein correlation profiling to test for variability in apparent mass among thousands of orthologous proteins isolated from diverse species and cell types. Variants in protein complex size were unexpectedly common, in some cases appearing after relatively recent whole-genome duplications or an allopolyploidy event. In other instances, variants such as those in the carbonic anhydrase orthologous group reflected the neofunctionalization of ancient paralogs that have been preserved in extant species. Our results demonstrate that homo- and heteromer formation have the potential to drive neofunctionalization in diverse classes of enzymes, signaling, and structural proteins.
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Affiliation(s)
- Youngwoo Lee
- Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Daniel B Szymanski
- Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA.
- Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
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37
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Klann K, Tascher G, Münch C. Virus systems biology: Proteomics profiling of dynamic protein networks during infection. Adv Virus Res 2021; 109:1-29. [PMID: 33934824 DOI: 10.1016/bs.aivir.2020.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The host cell proteome undergoes a variety of dynamic changes during viral infection, elicited by the virus itself or host cell defense mechanisms. Studying these changes on a global scale by integrating functional and physical interactions within protein networks during infection is an important tool to understand pathology. Indeed, proteomics studies dissecting protein signaling cascades and interaction networks upon infection showed how global information can significantly improve understanding of disease mechanisms of diverse viral infections. Here, we summarize and give examples of different experimental designs, proteomics approaches and bioinformatics analyses that allow profiling proteome changes and host-pathogen interactions to gain a molecular systems view of viral infection.
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Affiliation(s)
- Kevin Klann
- Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany
| | - Georg Tascher
- Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany
| | - Christian Münch
- Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany; Frankfurt Cancer Institute, Frankfurt am Main, Germany; Cardio-Pulmonary Institute, Frankfurt am Main, Germany.
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38
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Lee J, Oh S, Bhattacharya S, Zhang Y, Florens L, Washburn MP, Workman JL. The plasticity of the pyruvate dehydrogenase complex confers a labile structure that is associated with its catalytic activity. PLoS One 2020; 15:e0243489. [PMID: 33370314 PMCID: PMC7769281 DOI: 10.1371/journal.pone.0243489] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 11/21/2020] [Indexed: 12/04/2022] Open
Abstract
The pyruvate dehydrogenase complex (PDC) is a multienzyme complex that plays a key role in energy metabolism by converting pyruvate to acetyl-CoA. An increase of nuclear PDC has been shown to be correlated with an increase of histone acetylation that requires acetyl-CoA. PDC has been reported to form a ~ 10 MDa macromolecular machine that is proficient in performing sequential catalytic reactions via its three components. In this study, we show that the PDC displays size versatility in an ionic strength-dependent manner using size exclusion chromatography of yeast cell extracts. Biochemical analysis in combination with mass spectrometry indicates that yeast PDC (yPDC) is a salt-labile complex that dissociates into sub-megadalton individual components even under physiological ionic strength. Interestingly, we find that each oligomeric component of yPDC displays a larger size than previously believed. In addition, we show that the mammalian PDC also displays this uncommon characteristic of salt-lability, although it has a somewhat different profile compared to yeast. We show that the activity of yPDC is reduced in higher ionic strength. Our results indicate that the structure of PDC may not always maintain its ~ 10 MDa organization, but is rather variable. We propose that the flexible nature of PDC may allow modulation of its activity.
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Affiliation(s)
- Jaehyoun Lee
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
| | - Seunghee Oh
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
| | - Saikat Bhattacharya
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
| | - Ying Zhang
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
| | - Laurence Florens
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
| | - Michael P. Washburn
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas, United States of America
| | - Jerry L. Workman
- Stowers Institute for Medical Research, Kansas City, Missouri, United States of America
- * E-mail:
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39
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Rosenberger G, Heusel M, Bludau I, Collins BC, Martelli C, Williams EG, Xue P, Liu Y, Aebersold R, Califano A. SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles. Cell Syst 2020; 11:589-607.e8. [PMID: 33333029 PMCID: PMC8034988 DOI: 10.1016/j.cels.2020.11.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 08/25/2020] [Accepted: 11/17/2020] [Indexed: 12/29/2022]
Abstract
Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper's transparent peer review process is included in the Supplemental Information.
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Affiliation(s)
| | - Moritz Heusel
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Isabell Bludau
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Ben C Collins
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Claudia Martelli
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Evan G Williams
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Peng Xue
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland; Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven CT, USA; Department of Pharmacology, Yale University School of Medicine, New Haven CT, USA
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland; Faculty of Science, University of Zürich, Zürich, Switzerland.
| | - Andrea Califano
- Department of Systems Biology, Columbia University, New York NY, USA; Department of Biomedical Informatics, Columbia University, New York NY, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York NY, USA; J.P. Sulzberger Columbia Genome Center, Columbia University, New York NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University, New York NY, USA; Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York NY, USA.
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40
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Ross AB, Langer JD, Jovanovic M. Proteome Turnover in the Spotlight: Approaches, Applications, and Perspectives. Mol Cell Proteomics 2020; 20:100016. [PMID: 33556866 PMCID: PMC7950106 DOI: 10.1074/mcp.r120.002190] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 11/25/2020] [Accepted: 11/30/2020] [Indexed: 01/17/2023] Open
Abstract
In all cells, proteins are continuously synthesized and degraded to maintain protein homeostasis and modify gene expression levels in response to stimuli. Collectively, the processes of protein synthesis and degradation are referred to as protein turnover. At a steady state, protein turnover is constant to maintain protein homeostasis, but in dynamic responses, proteins change their rates of synthesis and degradation to adjust their proteomes to internal or external stimuli. Thus, probing the kinetics and dynamics of protein turnover lends insight into how cells regulate essential processes such as growth, differentiation, and stress response. Here, we outline historical and current approaches to measuring the kinetics of protein turnover on a proteome-wide scale in both steady-state and dynamic systems, with an emphasis on metabolic tracing using stable isotope-labeled amino acids. We highlight important considerations for designing proteome turnover experiments, key biological findings regarding the conserved principles of proteome turnover regulation, and future perspectives for both technological and biological investigation.
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Affiliation(s)
- Alison Barbara Ross
- Department of Biological Sciences, Columbia University, New York, New York, USA
| | - Julian David Langer
- Proteomics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany; Proteomics, Max Planck Institute for Brain Research, Frankfurt am Main, Germany.
| | - Marko Jovanovic
- Department of Biological Sciences, Columbia University, New York, New York, USA.
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41
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Peck Justice SA, Barron MP, Qi GD, Wijeratne HRS, Victorino JF, Simpson ER, Vilseck JZ, Wijeratne AB, Mosley AL. Mutant thermal proteome profiling for characterization of missense protein variants and their associated phenotypes within the proteome. J Biol Chem 2020; 295:16219-16238. [PMID: 32878984 PMCID: PMC7705321 DOI: 10.1074/jbc.ra120.014576] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 08/17/2020] [Indexed: 12/20/2022] Open
Abstract
Temperature-sensitive (TS) missense mutants have been foundational for characterization of essential gene function. However, an unbiased approach for analysis of biochemical and biophysical changes in TS missense mutants within the context of their functional proteomes is lacking. We applied MS-based thermal proteome profiling (TPP) to investigate the proteome-wide effects of missense mutations in an application that we refer to as mutant thermal proteome profiling (mTPP). This study characterized global impacts of temperature sensitivity-inducing missense mutations in two different subunits of the 26S proteasome. The majority of alterations identified by RNA-Seq and global proteomics were similar between the mutants, which could suggest that a similar functional disruption is occurring in both missense variants. Results from mTPP, however, provide unique insights into the mechanisms that contribute to the TS phenotype in each mutant, revealing distinct changes that were not obtained using only steady-state transcriptome and proteome analyses. Computationally, multisite λ-dynamics simulations add clear support for mTPP experimental findings. This work shows that mTPP is a precise approach to measure changes in missense mutant-containing proteomes without the requirement for large amounts of starting material, specific antibodies against proteins of interest, and/or genetic manipulation of the biological system. Although experiments were performed under permissive conditions, mTPP provided insights into the underlying protein stability changes that cause dramatic cellular phenotypes observed at nonpermissive temperatures. Overall, mTPP provides unique mechanistic insights into missense mutation dysfunction and connection of genotype to phenotype in a rapid, nonbiased fashion.
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Affiliation(s)
- Sarah A Peck Justice
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Monica P Barron
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Guihong D Qi
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - H R Sagara Wijeratne
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - José F Victorino
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ed R Simpson
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of BioHealth Informatics, School of Informatics and Computing, Indiana University-Purdue University, Indianapolis, Indiana, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jonah Z Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Aruna B Wijeratne
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA.
| | - Amber L Mosley
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
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42
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Zablotskii V, Polyakova T, Dejneka A. Modulation of the Cell Membrane Potential and Intracellular Protein Transport by High Magnetic Fields. Bioelectromagnetics 2020; 42:27-36. [PMID: 33179821 DOI: 10.1002/bem.22309] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/16/2020] [Accepted: 10/22/2020] [Indexed: 01/26/2023]
Abstract
To explore cellular responses to high magnetic fields (HMF), we present a model of the interactions of cells with a homogeneous HMF that accounts for the magnetic force exerted on paramagnetic/diamagnetic species. There are various chemical species inside a living cell, many of which may have large concentration gradients. Thus, when an HMF is applied to a cell, the concentration-gradient magnetic forces act on paramagnetic or diamagnetic species and can either assist or oppose large particle movement through the cytoplasm. We demonstrate possibilities for changing the machinery in living cells with HMFs and predict two new mechanisms for modulating cellular functions with HMFs via (i) changes in the membrane potential and (ii) magnetically assisted intracellular diffusiophoresis of large proteins. By deriving a generalized form for the Nernst equation, we find that an HMF can change the membrane potential of the cell and thus have a significant impact on the properties and biological functionality of cells. The elaborated model provides a universal framework encompassing current studies on controlling cell functions by high static magnetic fields. Bioelectromagnetics. 2021;42:27-36. © 2020 Bioelectromagnetics Society.
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Affiliation(s)
- Vitalii Zablotskii
- Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic
| | - Tatyana Polyakova
- Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic
| | - Alexandr Dejneka
- Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic
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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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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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McWhite CD, Papoulas O, Drew K, Cox RM, June V, Dong OX, Kwon T, Wan C, Salmi ML, Roux SJ, Browning KS, Chen ZJ, Ronald PC, Marcotte EM. A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies. Cell 2020; 181:460-474.e14. [PMID: 32191846 PMCID: PMC7297045 DOI: 10.1016/j.cell.2020.02.049] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 01/08/2020] [Accepted: 02/21/2020] [Indexed: 01/11/2023]
Abstract
Plants are foundational for global ecological and economic systems, but most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. By using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified previously unknown interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical for agriculture. We also observed plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers a cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.
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Affiliation(s)
- Claire D McWhite
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Kevin Drew
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Rachael M Cox
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Viviana June
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Oliver Xiaoou Dong
- Department of Plant Pathology and The Genome Center, University of California, Davis, Davis, CA 95616, USA; Joint Bioenergy Institute, Emeryville, CA 94608, USA
| | - Taejoon Kwon
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Ulju-gun, Ulsan 44919, Republic of Korea
| | - Cuihong Wan
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA; Hubei Key Lab of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, No. 152 Luoyu Road, Wuhan 430079, P.R. China
| | - Mari L Salmi
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Stanley J Roux
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Karen S Browning
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Z Jeffrey Chen
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Pamela C Ronald
- Department of Plant Pathology and The Genome Center, University of California, Davis, Davis, CA 95616, USA; Joint Bioenergy Institute, Emeryville, CA 94608, USA
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA.
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Caudron-Herger M, Wassmer E, Nasa I, Schultz AS, Seiler J, Kettenbach AN, Diederichs S. Identification, quantification and bioinformatic analysis of RNA-dependent proteins by RNase treatment and density gradient ultracentrifugation using R-DeeP. Nat Protoc 2020; 15:1338-1370. [PMID: 32094787 PMCID: PMC7212772 DOI: 10.1038/s41596-019-0261-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 10/29/2019] [Indexed: 12/14/2022]
Abstract
Analysis of RNA-protein complexes is central to understanding the molecular circuitry governing cellular processes. In recent years, several proteome-wide studies have been dedicated to the identification of RNA-binding proteins. Here, we describe in detail R-DeeP, an approach built on RNA dependence, defined as the ability of a protein to engage in protein complexes only in the presence of RNA, involving direct or indirect interaction with RNA. This approach provides-for the first time, to our knowledge-quantitative information on the fraction of a protein associated with RNA-protein complexes. R-DeeP is independent of any potentially biased purification procedures. It is based on cellular lysate fractionation by density gradient ultracentrifugation and subsequent analysis by proteome-wide mass spectrometry (MS) or individual western blotting. The comparison of lysates with and without previous RNase treatment enables the identification of differences in the apparent molecular weight and, hence, the size of the complexes. In combination with information from databases of protein-protein complexes, R-DeeP facilitates the computational reconstruction of protein complexes from proteins migrating in the same fraction. In addition, we developed a pipeline for the statistical analysis of the MS dataset to automatically identify RNA-dependent proteins (proteins whose interactome depends on RNA). With this protocol, the individual analysis of proteins of interest by western blotting can be completed within 1-2 weeks. For proteome-wide studies, additional time is needed for the integration of the proteomic and statistical analyses. In the future, R-DeeP can be extended to other fractionation techniques, such as chromatography.
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Affiliation(s)
- Maiwen Caudron-Herger
- Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Elsa Wassmer
- Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Isha Nasa
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Astrid-Solveig Schultz
- Division of Cancer Research, Department of Thoracic Surgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK)-Partner Site Freiburg, Freiburg, Germany
| | - Jeanette Seiler
- Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Arminja N Kettenbach
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Sven Diederichs
- Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Division of Cancer Research, Department of Thoracic Surgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK)-Partner Site Freiburg, Freiburg, Germany.
- National Center for Tumor Diseases (NCT)-Partner Site Heidelberg, Heidelberg, Germany.
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47
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de Souza N, Picotti P. Mass spectrometry analysis of the structural proteome. Curr Opin Struct Biol 2020; 60:57-65. [DOI: 10.1016/j.sbi.2019.10.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 10/16/2019] [Indexed: 01/01/2023]
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48
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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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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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50
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Protein Complex Identification and quantitative complexome by CN-PAGE. Sci Rep 2019; 9:11523. [PMID: 31395906 PMCID: PMC6687828 DOI: 10.1038/s41598-019-47829-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 07/24/2019] [Indexed: 02/07/2023] Open
Abstract
The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system.
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