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Singin Ö, Astapenka A, Costina V, Kühl S, Bonekamp N, Drews O, Islinger M. Analysis of the Mouse Hepatic Peroxisome Proteome-Identification of Novel Protein Constituents Using a Semi-Quantitative SWATH-MS Approach. Cells 2024; 13:176. [PMID: 38247867 PMCID: PMC10814758 DOI: 10.3390/cells13020176] [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: 12/21/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024] Open
Abstract
Ongoing technical and bioinformatics improvements in mass spectrometry (MS) allow for the identifying and quantifying of the enrichment of increasingly less-abundant proteins in individual fractions. Accordingly, this study reassessed the proteome of mouse liver peroxisomes by the parallel isolation of peroxisomes from a mitochondria- and a microsome-enriched prefraction, combining density-gradient centrifugation with a semi-quantitative SWATH-MS proteomics approach to unveil novel peroxisomal or peroxisome-associated proteins. In total, 1071 proteins were identified using MS and assessed in terms of their distribution in either high-density peroxisomal or low-density gradient fractions, containing the bulk of organelle material. Combining the data from both fractionation approaches allowed for the identification of specific protein profiles characteristic of mitochondria, the ER and peroxisomes. Among the proteins significantly enriched in the peroxisomal cluster were several novel peroxisomal candidates. Five of those were validated by colocalization in peroxisomes, using confocal microscopy. The peroxisomal import of HTATIP2 and PAFAH2, which contain a peroxisome-targeting sequence 1 (PTS1), could be confirmed by overexpression in HepG2 cells. The candidates SAR1B and PDCD6, which are known ER-exit-site proteins, did not directly colocalize with peroxisomes, but resided at ER sites, which frequently surrounded peroxisomes. Hence, both proteins might concentrate at presumably co-purified peroxisome-ER membrane contacts. Intriguingly, the fifth candidate, OCIA domain-containing protein 1, was previously described as decreasing mitochondrial network formation. In this work, we confirmed its peroxisomal localization and further observed a reduction in peroxisome numbers in response to OCIAD1 overexpression. Hence, OCIAD1 appears to be a novel protein, which has an impact on both mitochondrial and peroxisomal maintenance.
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Affiliation(s)
- Öznur Singin
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Artur Astapenka
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Victor Costina
- Institute of Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (V.C.); (O.D.)
| | - Sandra Kühl
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Nina Bonekamp
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
| | - Oliver Drews
- Institute of Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (V.C.); (O.D.)
- Biomedical Mass Spectrometry, Center for Medical Research, Johannes Kepler University Linz, 4020 Linz, Austria
| | - Markus Islinger
- Neuroanatomy, Mannheim Center for Translational Neuroscience, Medical Faculty Mannheim, Heidelberg University, D-68167 Mannheim, Germany; (Ö.S.); (A.A.); (S.K.); (N.B.)
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2
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Xu S, Suttapitugsakul S, Tong M, Wu R. Systematic analysis of the impact of phosphorylation and O-GlcNAcylation on protein subcellular localization. Cell Rep 2023; 42:112796. [PMID: 37453062 PMCID: PMC10530397 DOI: 10.1016/j.celrep.2023.112796] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 05/02/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
The subcellular localization of proteins is critical for their functions in eukaryotic cells and is tightly correlated with protein modifications. Here, we comprehensively investigate the nuclear-cytoplasmic distributions of the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins to dissect the correlation between protein distribution and modifications. Phosphorylated and O-GlcNAcylated proteins have overall higher nuclear distributions than non-modified ones. Different distributions among the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins are associated with protein size, structure, and function, as well as local environment and adjacent residues around modification sites. Moreover, we perform site-mutagenesis experiments using phosphomimetic and phospho-null mutants of two proteins to validate the proteomic results. Additionally, the effects of the OGT/OGA inhibition on glycoprotein distribution are systematically investigated, and the distribution changes of glycoproteins are related to their abundance changes under the inhibitions. Systematic investigation of the relationship between protein modification and localization advances our understanding of protein functions.
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Affiliation(s)
- Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Suttipong Suttapitugsakul
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ming Tong
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ronghu Wu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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3
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Nishiura M, Hori Y, Umeno M, Kikuchi K. Visualization of multiple localizations of GLUT4 by fluorescent probes of PYP-tag with designed unnatural warhead. Chem Sci 2023; 14:5925-5935. [PMID: 37293637 PMCID: PMC10246691 DOI: 10.1039/d3sc00724c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/08/2023] [Indexed: 06/10/2023] Open
Abstract
Within a cell, multiple copies of the same protein coexist in different pathways and behave differently. Being able to individually analyze the constant actions of proteins in a cell is crucial to know the pathways through which they pass and which physiological functions they are deeply involved in. However, until now, it has been difficult to distinguish protein copies with distinct translocation properties by fluorescence labeling with different colors in living cells. In this study, we have created an unnatural ligand with an unprecedented protein-tag labeling property in living cells and overcome the above-mentioned problem. Of special interest is that some fluorescent probes with the ligand can selectively and efficiently label intracellular proteins without binding to cell-surface proteins, even if the proteins are present on the cell membrane. We also developed a cell-membrane impermeable fluorescent probe that selectively labels cell-surface proteins without labeling of intracellular proteins. These localization-selective properties enabled us to visually discriminate two kinetically distinct glucose transporter 4 (GLUT4) molecules that show different multiple subcellular localization and translocation dynamics in live cells. Taking advantage of the probes, we revealed that N-glycosylation of GLUT4 influences intracellular localization. Furthermore, we were able to visually distinguish active GLUT4 molecules that underwent membrane translocation at least twice within an hour from those that remained intracellularly, discovering previously unrecognized dynamic behaviors of GLUT4. This technology provides not only a valuable tool for study on multiple localization and dynamics of proteins but also important information on diseases caused by protein translocation dysfunction.
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Affiliation(s)
- Miyako Nishiura
- Department of Applied Chemistry, Graduate School of Engineering, and Division of Applied Chemistry, Osaka University Suita Osaka 565-0871 Japan
| | - Yuichiro Hori
- Department of Chemistry, Faculty of Science, Kyushu University Fukuoka Fukuoka 819-0395 Japan
| | - Maho Umeno
- Department of Applied Chemistry, Graduate School of Engineering, and Division of Applied Chemistry, Osaka University Suita Osaka 565-0871 Japan
| | - Kazuya Kikuchi
- Department of Applied Chemistry, Graduate School of Engineering, and Division of Applied Chemistry, Osaka University Suita Osaka 565-0871 Japan
- Immunology Frontier Research Center, Osaka University Suita Osaka 565-0871 Japan
- Quantum Information and Quantum Biology Division, Osaka University Suita Osaka 565-0871 Japan
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4
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Zhang L, Liang X, Takáč T, Komis G, Li X, Zhang Y, Ovečka M, Chen Y, Šamaj J. Spatial proteomics of vesicular trafficking: coupling mass spectrometry and imaging approaches in membrane biology. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:250-269. [PMID: 36204821 PMCID: PMC9884029 DOI: 10.1111/pbi.13929] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/14/2022] [Accepted: 09/08/2022] [Indexed: 06/16/2023]
Abstract
In plants, membrane compartmentalization requires vesicle trafficking for communication among distinct organelles. Membrane proteins involved in vesicle trafficking are highly dynamic and can respond rapidly to changes in the environment and to cellular signals. Capturing their localization and dynamics is thus essential for understanding the mechanisms underlying vesicular trafficking pathways. Quantitative mass spectrometry and imaging approaches allow a system-wide dissection of the vesicular proteome, the characterization of ligand-receptor pairs and the determination of secretory, endocytic, recycling and vacuolar trafficking pathways. In this review, we highlight major proteomics and imaging methods employed to determine the location, distribution and abundance of proteins within given trafficking routes. We focus in particular on methodologies for the elucidation of vesicle protein dynamics and interactions and their connections to downstream signalling outputs. Finally, we assess their biological applications in exploring different cellular and subcellular processes.
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Affiliation(s)
- Liang Zhang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological SciencesChina Agricultural UniversityBeijingChina
- College of Life ScienceHenan Normal UniversityXinxiangChina
| | - Xinlin Liang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological SciencesChina Agricultural UniversityBeijingChina
| | - Tomáš Takáč
- Department of Biotechnology, Faculty of SciencePalacky University OlomoucOlomoucCzech Republic
| | - George Komis
- Department of Cell Biology, Centre of the Region Hana for Biotechnological and Agricultural Research, Faculty of SciencePalacky University OlomoucOlomoucCzech Republic
| | - Xiaojuan Li
- College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Yuan Zhang
- College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Miroslav Ovečka
- Department of Biotechnology, Faculty of SciencePalacky University OlomoucOlomoucCzech Republic
| | - Yanmei Chen
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological SciencesChina Agricultural UniversityBeijingChina
| | - Jozef Šamaj
- Department of Biotechnology, Faculty of SciencePalacky University OlomoucOlomoucCzech Republic
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5
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Crook OM, Davies CTR, Breckels LM, Christopher JA, Gatto L, Kirk PDW, Lilley KS. Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE. Nat Commun 2022; 13:5948. [PMID: 36216816 PMCID: PMC9550814 DOI: 10.1038/s41467-022-33570-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 09/20/2022] [Indexed: 11/08/2022] Open
Abstract
The steady-state localisation of proteins provides vital insight into their function. These localisations are context specific with proteins translocating between different subcellular niches upon perturbation of the subcellular environment. Differential localisation, that is a change in the steady-state subcellular location of a protein, provides a step towards mechanistic insight of subcellular protein dynamics. High-accuracy high-throughput mass spectrometry-based methods now exist to map the steady-state localisation and re-localisation of proteins. Here, we describe a principled Bayesian approach, BANDLE, that uses these data to compute the probability that a protein differentially localises upon cellular perturbation. Extensive simulation studies demonstrate that BANDLE reduces the number of both type I and type II errors compared to existing approaches. Application of BANDLE to several datasets recovers well-studied translocations. In an application to cytomegalovirus infection, we obtain insights into the rewiring of the host proteome. Integration of other high-throughput datasets allows us to provide the functional context of these data.
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Affiliation(s)
- Oliver M Crook
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK.
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, CB2 0AW, UK.
| | - Colin T R Davies
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, CB2 0AW, UK
- Mechanistic Biology and Profiling, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Lisa M Breckels
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, CB2 0AW, UK
| | - Josie A Christopher
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, CB2 0AW, UK
| | - Laurent Gatto
- de Duve Institute, Université catholique de Louvain, Avenue Hippocrate 75, 1200, Brussels, Belgium
| | - Paul D W Kirk
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK.
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, CB2 0AW, UK.
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6
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Spatial Proteomics Reveals Differences in the Cellular Architecture of Antibody-Producing CHO and Plasma Cell-Derived Cells. Mol Cell Proteomics 2022; 21:100278. [PMID: 35934186 PMCID: PMC9562429 DOI: 10.1016/j.mcpro.2022.100278] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 07/28/2022] [Accepted: 07/30/2022] [Indexed: 01/18/2023] Open
Abstract
Most of the recombinant biotherapeutics employed today to combat severe illnesses, for example, various types of cancer or autoimmune diseases, are produced by Chinese hamster ovary (CHO) cells. To meet the growing demand of these pharmaceuticals, CHO cells are under constant development in order to enhance their stability and productivity. The last decades saw a shift from empirical cell line optimization toward rational cell engineering using a growing number of large omics datasets to alter cell physiology on various levels. Especially proteomics workflows reached new levels in proteome coverage and data quality because of advances in high-resolution mass spectrometry instrumentation. One type of workflow concentrates on spatial proteomics by usage of subcellular fractionation of organelles with subsequent shotgun mass spectrometry proteomics and machine learning algorithms to determine the subcellular localization of large portions of the cellular proteome at a certain time point. Here, we present the first subcellular spatial proteome of a CHO-K1 cell line producing high titers of recombinant antibody in comparison to the spatial proteome of an antibody-producing plasma cell-derived myeloma cell line. Both cell lines show colocalization of immunoglobulin G chains with chaperones and proteins associated in protein glycosylation within the endoplasmic reticulum compartment. However, we report differences in the localization of proteins associated to vesicle-mediated transport, transcription, and translation, which may affect antibody production in both cell lines. Furthermore, pairing subcellular localization data with protein expression data revealed elevated protein masses for organelles in the secretory pathway in plasma cell-derived MPC-11 (Merwin plasma cell tumor-11) cells. Our study highlights the potential of subcellular spatial proteomics combined with protein expression as potent workflow to identify characteristics of highly efficient recombinant protein-expressing cell lines. Data are available via ProteomeXchange with identifier PXD029115.
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8
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Braccia C, Christopher JA, Crook OM, Breckels LM, Queiroz RML, Liessi N, Tomati V, Capurro V, Bandiera T, Baldassari S, Pedemonte N, Lilley KS, Armirotti A. CFTR Rescue by Lumacaftor (VX-809) Induces an Extensive Reorganization of Mitochondria in the Cystic Fibrosis Bronchial Epithelium. Cells 2022; 11:1938. [PMID: 35741067 PMCID: PMC9222197 DOI: 10.3390/cells11121938] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/07/2022] [Accepted: 06/12/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Cystic Fibrosis (CF) is a genetic disorder affecting around 1 in every 3000 newborns. In the most common mutation, F508del, the defective anion channel, CFTR, is prevented from reaching the plasma membrane (PM) by the quality check control of the cell. Little is known about how CFTR pharmacological rescue impacts the cell proteome. METHODS We used high-resolution mass spectrometry, differential ultracentrifugation, machine learning and bioinformatics to investigate both changes in the expression and localization of the human bronchial epithelium CF model (F508del-CFTR CFBE41o-) proteome following treatment with VX-809 (Lumacaftor), a drug able to improve the trafficking of CFTR. RESULTS The data suggested no stark changes in protein expression, yet subtle localization changes of proteins of the mitochondria and peroxisomes were detected. We then used high-content confocal microscopy to further investigate the morphological and compositional changes of peroxisomes and mitochondria under these conditions, as well as in patient-derived primary cells. We profiled several thousand proteins and we determined the subcellular localization data for around 5000 of them using the LOPIT-DC spatial proteomics protocol. CONCLUSIONS We observed that treatment with VX-809 induces extensive structural and functional remodelling of mitochondria and peroxisomes that resemble the phenotype of healthy cells. Our data suggest additional rescue mechanisms of VX-809 beyond the correction of aberrant folding of F508del-CFTR and subsequent trafficking to the PM.
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Affiliation(s)
- Clarissa Braccia
- D3 PharmaChemistry, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; (C.B.); (T.B.)
| | - Josie A. Christopher
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK; (J.A.C.); (O.M.C.); (L.M.B.); (R.M.L.Q.)
| | - Oliver M. Crook
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK; (J.A.C.); (O.M.C.); (L.M.B.); (R.M.L.Q.)
- Department of Statistics, University of Oxford, 29 St Giles’, Oxford OX1 3LB, UK
| | - Lisa M. Breckels
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK; (J.A.C.); (O.M.C.); (L.M.B.); (R.M.L.Q.)
| | - Rayner M. L. Queiroz
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK; (J.A.C.); (O.M.C.); (L.M.B.); (R.M.L.Q.)
| | - Nara Liessi
- Analytical Chemistry Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy;
| | - Valeria Tomati
- UOC Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy; (V.T.); (V.C.); (S.B.)
| | - Valeria Capurro
- UOC Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy; (V.T.); (V.C.); (S.B.)
| | - Tiziano Bandiera
- D3 PharmaChemistry, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; (C.B.); (T.B.)
| | - Simona Baldassari
- UOC Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy; (V.T.); (V.C.); (S.B.)
| | - Nicoletta Pedemonte
- UOC Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy; (V.T.); (V.C.); (S.B.)
| | - Kathryn S. Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK; (J.A.C.); (O.M.C.); (L.M.B.); (R.M.L.Q.)
| | - Andrea Armirotti
- Analytical Chemistry Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy;
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Spatial and temporal proteomics reveals the distinct distributions and dynamics of O-GlcNAcylated proteins. Cell Rep 2022; 39:110946. [PMID: 35705054 PMCID: PMC9244862 DOI: 10.1016/j.celrep.2022.110946] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/28/2022] [Accepted: 05/23/2022] [Indexed: 11/30/2022] Open
Abstract
Protein O-GlcNAcylation plays critical roles in many cellular events, and its dysregulation is related to multiple diseases. Integrating bioorthogonal chemistry and multiplexed proteomics, we systematically and site specifically study the distributions and dynamics of protein O-GlcNAcylation in the nucleus and the cytoplasm of human cells. The results demonstrate that O-GlcNAcylated proteins with different functions have distinct distribution patterns. The distributions vary site specifically, indicating that different glycoforms of the same protein may have different distributions. Moreover, we comprehensively analyze the dynamics of O-GlcNAcylated and non-modified proteins in these two compartments, respectively, and the half-lives of glycoproteins in different compartments are markedly different, with the median half-life in the cytoplasm being much longer. In addition, glycoproteins in the nucleus are more dramatically stabilized than those in the cytoplasm under the O-GlcNAcase inhibition. The comprehensive spatial and temporal analyses of protein O-GlcNAcylation provide valuable information and advance our understanding of this important modification. Xu et al. systematically and site specifically study the distribution and dynamics of O-GlcNAcylated proteins in the nucleus and the cytoplasm. O-GlcNAcylated proteins with different functions have distinct distribution patterns. The half-lives of glycoproteins in the two cellular compartments are markedly different, with the much longer median half-life in the cytoplasm.
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Moore DF, Sleat DE, Lobel P. A Method to Estimate the Distribution of Proteins across Multiple Compartments Using Data from Quantitative Proteomics Subcellular Fractionation Experiments. J Proteome Res 2022; 21:1371-1381. [PMID: 35522998 DOI: 10.1021/acs.jproteome.1c00781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Knowledge of cellular location is key to understanding the biological function of proteins. One commonly used large-scale method to assign cellular locations is subcellular fractionation, followed by quantitative mass spectrometry to identify proteins and estimate their relative distribution among centrifugation fractions. In most of such subcellular proteomics studies, each protein is assigned to a single cellular location by comparing its distribution to those of a set of single-compartment reference proteins. However, in many cases, proteins reside in multiple compartments. To accurately determine the localization of such proteins, we previously introduced constrained proportional assignment (CPA), a method that assigns each protein a fractional residence over all reference compartments (Jadot Mol. Cell Proteomics 2017, 16(2), 194-212. 10.1074/mcp.M116.064527). In this Article, we describe the principles underlying CPA, as well as data transformations to improve accuracy of assignment of proteins and protein isoforms, and a suite of R-based programs to implement CPA and related procedures for analysis of subcellular proteomics data. We include a demonstration data set that used isobaric-labeling mass spectrometry to analyze rat liver fractions. In addition, we describe how these programs can be readily modified by users to accommodate a wide variety of experimental designs and methods for protein quantitation.
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Affiliation(s)
- Dirk F Moore
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health and Rutgers Cancer Institute of New Jersey, 683 Hoes Lane West, Piscataway, New Jersey 08854, United States
| | - David E Sleat
- Center for Advanced Biotechnology and Medicine and Department of Biochemistry and Molecular Biology, Rutgers Biomedical and Health Sciences, 679 Hoes Lane West, Piscataway, New Jersey 08854, United States
| | - Peter Lobel
- Center for Advanced Biotechnology and Medicine and Department of Biochemistry and Molecular Biology, Rutgers Biomedical and Health Sciences, 679 Hoes Lane West, Piscataway, New Jersey 08854, United States
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11
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Christopher JA, Geladaki A, Dawson CS, Vennard OL, Lilley KS. Subcellular Transcriptomics and Proteomics: A Comparative Methods Review. Mol Cell Proteomics 2022; 21:100186. [PMID: 34922010 PMCID: PMC8864473 DOI: 10.1016/j.mcpro.2021.100186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 11/16/2021] [Accepted: 12/13/2021] [Indexed: 12/23/2022] Open
Abstract
The internal environment of cells is molecularly crowded, which requires spatial organization via subcellular compartmentalization. These compartments harbor specific conditions for molecules to perform their biological functions, such as coordination of the cell cycle, cell survival, and growth. This compartmentalization is also not static, with molecules trafficking between these subcellular neighborhoods to carry out their functions. For example, some biomolecules are multifunctional, requiring an environment with differing conditions or interacting partners, and others traffic to export such molecules. Aberrant localization of proteins or RNA species has been linked to many pathological conditions, such as neurological, cancer, and pulmonary diseases. Differential expression studies in transcriptomics and proteomics are relatively common, but the majority have overlooked the importance of subcellular information. In addition, subcellular transcriptomics and proteomics data do not always colocate because of the biochemical processes that occur during and after translation, highlighting the complementary nature of these fields. In this review, we discuss and directly compare the current methods in spatial proteomics and transcriptomics, which include sequencing- and imaging-based strategies, to give the reader an overview of the current tools available. We also discuss current limitations of these strategies as well as future developments in the field of spatial -omics.
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Affiliation(s)
- Josie A Christopher
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Aikaterini Geladaki
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK; Department of Genetics, University of Cambridge, Cambridge, UK
| | - Charlotte S Dawson
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Owen L Vennard
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Kathryn S Lilley
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK.
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12
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Mulvey CM, Breckels LM, Crook OM, Sanders DJ, Ribeiro ALR, Geladaki A, Christoforou A, Britovšek NK, Hurrell T, Deery MJ, Gatto L, Smith AM, Lilley KS. Spatiotemporal proteomic profiling of the pro-inflammatory response to lipopolysaccharide in the THP-1 human leukaemia cell line. Nat Commun 2021; 12:5773. [PMID: 34599159 PMCID: PMC8486773 DOI: 10.1038/s41467-021-26000-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 09/07/2021] [Indexed: 02/07/2023] Open
Abstract
Protein localisation and translocation between intracellular compartments underlie almost all physiological processes. The hyperLOPIT proteomics platform combines mass spectrometry with state-of-the-art machine learning to map the subcellular location of thousands of proteins simultaneously. We combine global proteome analysis with hyperLOPIT in a fully Bayesian framework to elucidate spatiotemporal proteomic changes during a lipopolysaccharide (LPS)-induced inflammatory response. We report a highly dynamic proteome in terms of both protein abundance and subcellular localisation, with alterations in the interferon response, endo-lysosomal system, plasma membrane reorganisation and cell migration. Proteins not previously associated with an LPS response were found to relocalise upon stimulation, the functional consequences of which are still unclear. By quantifying proteome-wide uncertainty through Bayesian modelling, a necessary role for protein relocalisation and the importance of taking a holistic overview of the LPS-driven immune response has been revealed. The data are showcased as an interactive application freely available for the scientific community.
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Affiliation(s)
- Claire M Mulvey
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Lisa M Breckels
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | - Oliver M Crook
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
- MRC Biostatistics Unit, Cambridge Institute for Public Health, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK
| | - David J Sanders
- Department of Microbial Diseases, Eastman Dental Institute, University College London, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK
| | - Andre L R Ribeiro
- Department of Microbial Diseases, Eastman Dental Institute, University College London, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK
| | - Aikaterini Geladaki
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | | | - Nina Kočevar Britovšek
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
- Lek d.d., Kolodvorska 27, Mengeš, 1234, Slovenia
| | - Tracey Hurrell
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | - Michael J Deery
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | - Laurent Gatto
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
- de Duve Institute, UCLouvain, Avenue Hippocrate 75, Brussels, 1200, Belgium
| | - Andrew M Smith
- Department of Microbial Diseases, Eastman Dental Institute, University College London, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK.
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK.
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13
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Lyu Z, Genereux JC. Methodologies for Measuring Protein Trafficking across Cellular Membranes. Chempluschem 2021; 86:1397-1415. [PMID: 34636167 DOI: 10.1002/cplu.202100304] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/19/2021] [Indexed: 12/11/2022]
Abstract
Nearly all proteins are synthesized in the cytosol. The majority of this proteome must be trafficked elsewhere, such as to membranes, to subcellular compartments, or outside of the cell. Proper trafficking of nascent protein is necessary for protein folding, maturation, quality control and cellular and organismal health. To better understand cellular biology, molecular and chemical technologies to properly characterize protein trafficking (and mistrafficking) have been developed and applied. Herein, we take a biochemical perspective to review technologies that enable spatial and temporal measurement of protein distribution, focusing on both the most widely adopted methodologies and exciting emerging approaches.
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Affiliation(s)
- Ziqi Lyu
- Department of Chemistry, University of California, Riverside, 501 Big Springs Road, 92521, Riverside, CA, USA
| | - Joseph C Genereux
- Department of Chemistry, University of California, Riverside, 501 Big Springs Road, 92521, Riverside, CA, USA
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14
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Pino L, Schilling B. Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics. Expert Rev Proteomics 2021; 18:757-765. [PMID: 34496693 PMCID: PMC8650568 DOI: 10.1080/14789450.2021.1976149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 08/31/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Proteins are highly dynamic and their biological function is controlled by not only temporal abundance changes but also via regulated protein-protein interaction networks, which respond to internal and external perturbations. A wealth of novel analytical reagents and workflows allow studying spatiotemporal protein environments with great granularity while maintaining high throughput and ease of analysis. AREAS COVERED We review technology advances for measuring protein-protein proximity interactions with an emphasis on proximity labeling, and briefly summarize other spatiotemporal approaches including protein localization, and their dynamic changes over time, specifically in human cells and mammalian tissues. We focus especially on novel technologies and workflows emerging within the past 5 years. This includes enrichment-based techniques (proximity labeling and crosslinking), separation-based techniques (organelle fractionation and size exclusion chromatography), and finally sorting-based techniques (laser capture microdissection and mass spectrometry imaging). EXPERT OPINION Spatiotemporal proteomics is a key step in assessing biological complexity, understanding refined regulatory mechanisms, and forming protein complexes and networks. Studying protein dynamics across space and time holds promise for gaining deep insights into how protein networks may be perturbed during disease and aging processes, and offer potential avenues for therapeutic interventions, drug discovery, and biomarker development.
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Affiliation(s)
- Lindsay Pino
- University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, California, CA 94945, USA
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15
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Christopher JA, Stadler C, Martin CE, Morgenstern M, Pan Y, Betsinger CN, Rattray DG, Mahdessian D, Gingras AC, Warscheid B, Lehtiö J, Cristea IM, Foster LJ, Emili A, Lilley KS. Subcellular proteomics. NATURE REVIEWS. METHODS PRIMERS 2021; 1:32. [PMID: 34549195 PMCID: PMC8451152 DOI: 10.1038/s43586-021-00029-y] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/15/2021] [Indexed: 12/11/2022]
Abstract
The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.
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Affiliation(s)
- Josie A. Christopher
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Charlotte Stadler
- Department of Protein Sciences, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Claire E. Martin
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Marcel Morgenstern
- Institute of Biology II, Biochemistry and Functional Proteomics, Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Yanbo Pan
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Cora N. Betsinger
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - David G. Rattray
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Diana Mahdessian
- Department of Protein Sciences, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Anne-Claude Gingras
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Bettina Warscheid
- Institute of Biology II, Biochemistry and Functional Proteomics, Faculty of Biology, University of Freiburg, Freiburg, Germany
- BIOSS and CIBSS Signaling Research Centers, University of Freiburg, Freiburg, Germany
| | - Janne Lehtiö
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Ileana M. Cristea
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Leonard J. Foster
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrew Emili
- Center for Network Systems Biology, Boston University, Boston, MA, USA
| | - Kathryn S. Lilley
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Cambridge, UK
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16
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Affiliation(s)
- Georg H H Borner
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, 82152, Germany
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17
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Shin JJH, Crook OM, Borgeaud AC, Cattin-Ortolá J, Peak-Chew SY, Breckels LM, Gillingham AK, Chadwick J, Lilley KS, Munro S. Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers. Nat Commun 2020; 11:5987. [PMID: 33239640 PMCID: PMC7689464 DOI: 10.1038/s41467-020-19840-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 10/27/2020] [Indexed: 02/07/2023] Open
Abstract
Intracellular traffic between compartments of the secretory and endocytic pathways is mediated by vesicle-based carriers. The proteomes of carriers destined for many organelles are ill-defined because the vesicular intermediates are transient, low-abundance and difficult to purify. Here, we combine vesicle relocalisation with organelle proteomics and Bayesian analysis to define the content of different endosome-derived vesicles destined for the trans-Golgi network (TGN). The golgin coiled-coil proteins golgin-97 and GCC88, shown previously to capture endosome-derived vesicles at the TGN, were individually relocalised to mitochondria and the content of the subsequently re-routed vesicles was determined by organelle proteomics. Our findings reveal 45 integral and 51 peripheral membrane proteins re-routed by golgin-97, evidence for a distinct class of vesicles shared by golgin-97 and GCC88, and various cargoes specific to individual golgins. These results illustrate a general strategy for analysing intracellular sub-proteomes by combining acute cellular re-wiring with high-resolution spatial proteomics.
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Affiliation(s)
- John J H Shin
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK.
| | - Oliver M Crook
- The Milner Therapeutics Institute, University of Cambridge, Cambridge, CB2 0AW, UK
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Alicia C Borgeaud
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Jérôme Cattin-Ortolá
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Sew Y Peak-Chew
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Lisa M Breckels
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | - Alison K Gillingham
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Jessica Chadwick
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Kathryn S Lilley
- The Milner Therapeutics Institute, University of Cambridge, Cambridge, CB2 0AW, UK
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK
| | - Sean Munro
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK.
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