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Klingelhuber F, Frendo-Cumbo S, Omar-Hmeadi M, Massier L, Kakimoto P, Taylor AJ, Couchet M, Ribicic S, Wabitsch M, Messias AC, Iuso A, Müller TD, Rydén M, Mejhert N, Krahmer N. A spatiotemporal proteomic map of human adipogenesis. Nat Metab 2024; 6:861-879. [PMID: 38565923 PMCID: PMC11132986 DOI: 10.1038/s42255-024-01025-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
White adipocytes function as major energy reservoirs in humans by storing substantial amounts of triglycerides, and their dysfunction is associated with metabolic disorders; however, the mechanisms underlying cellular specialization during adipogenesis remain unknown. Here, we generate a spatiotemporal proteomic atlas of human adipogenesis, which elucidates cellular remodelling as well as the spatial reorganization of metabolic pathways to optimize cells for lipid accumulation and highlights the coordinated regulation of protein localization and abundance during adipocyte formation. We identify compartment-specific regulation of protein levels and localization changes of metabolic enzymes to reprogramme branched-chain amino acids and one-carbon metabolism to provide building blocks and reduction equivalents. Additionally, we identify C19orf12 as a differentiation-induced adipocyte lipid droplet protein that interacts with the translocase of the outer membrane complex of lipid droplet-associated mitochondria and regulates adipocyte lipid storage by determining the capacity of mitochondria to metabolize fatty acids. Overall, our study provides a comprehensive resource for understanding human adipogenesis and for future discoveries in the field.
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Affiliation(s)
- Felix Klingelhuber
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Scott Frendo-Cumbo
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Muhmmad Omar-Hmeadi
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Lucas Massier
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Pamela Kakimoto
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Austin J Taylor
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Morgane Couchet
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Sara Ribicic
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Martin Wabitsch
- Center for Rare Endocrine Diseases, Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, Ulm University Medical Centre, Ulm, Germany
| | - Ana C Messias
- Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Zentrum München, Neuherberg, Germany
- Bavarian NMR Centre, Department of Bioscience, School of Natural Sciences, Technical University of Munich, Garching, Germany
| | - Arcangela Iuso
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Human Genetics, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Timo D Müller
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Walther-Straub Institute for Pharmacology and Toxicology, Ludwig-Maximilians-University Munich (LMU), Munich, Germany
| | - Mikael Rydén
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
- Endocrinology unit, Karolinska University Hospital, Huddinge, Stockholm, Sweden
| | - Niklas Mejhert
- Department of Medicine (H7), Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Natalie Krahmer
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Neuherberg, Germany.
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2
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Silva Barbosa AC, Pfister KE, Chiba T, Bons J, Rose JP, Burton JB, King CD, O'Broin A, Young V, Zhang B, Sivakama B, Schmidt AV, Uhlean R, Oda A, Schilling B, Goetzman ES, Sims-Lucas S. Dicarboxylic Acid Dietary Supplementation Protects against AKI. J Am Soc Nephrol 2024; 35:135-148. [PMID: 38044490 PMCID: PMC10843194 DOI: 10.1681/asn.0000000000000266] [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: 03/17/2023] [Accepted: 10/20/2023] [Indexed: 12/05/2023] Open
Abstract
SIGNIFICANCE STATEMENT In this study, we demonstrate that a common, low-cost compound known as octanedioic acid (DC 8 ) can protect mice from kidney damage typically caused by ischemia-reperfusion injury or the chemotherapy drug cisplatin. This compound seems to enhance peroxisomal activity, which is responsible for breaking down fats, without adversely affecting mitochondrial function. DC 8 is not only affordable and easy to administer but also effective. These encouraging findings suggest that DC 8 could potentially be used to assist patients who are at risk of experiencing this type of kidney damage. BACKGROUND Proximal tubules are rich in peroxisomes, which are damaged during AKI. Previous studies demonstrated that increasing peroxisomal fatty acid oxidation (FAO) is renoprotective, but no therapy has emerged to leverage this mechanism. METHODS Mice were fed with either a control diet or a diet enriched with dicarboxylic acids, which are peroxisome-specific FAO substrates, then subjected to either ischemia-reperfusion injury-AKI or cisplatin-AKI models. Biochemical, histologic, genetic, and proteomic analyses were performed. RESULTS Both octanedioic acid (DC 8 ) and dodecanedioic acid (DC 12 ) prevented the rise of AKI markers in mice that were exposed to renal injury. Proteomics analysis demonstrated that DC 8 preserved the peroxisomal and mitochondrial proteomes while inducing extensive remodeling of the lysine succinylome. This latter finding indicates that DC 8 is chain shortened to the anaplerotic substrate succinate and that peroxisomal FAO was increased by DC 8 . CONCLUSIONS DC 8 supplementation protects kidney mitochondria and peroxisomes and increases peroxisomal FAO, thereby protecting against AKI.
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Affiliation(s)
- Anne C. Silva Barbosa
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Katherine E. Pfister
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Takuto Chiba
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joanna Bons
- Buck Institute for Research on Aging, Novato, California
| | - Jacob P. Rose
- Buck Institute for Research on Aging, Novato, California
| | | | | | - Amy O'Broin
- Buck Institute for Research on Aging, Novato, California
| | - Victoria Young
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Bob Zhang
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Bharathi Sivakama
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alexandra V. Schmidt
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Rebecca Uhlean
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Akira Oda
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | - Eric S. Goetzman
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sunder Sims-Lucas
- Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania
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3
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Alexandrov T, Saez‐Rodriguez J, Saka SK. Enablers and challenges of spatial omics, a melting pot of technologies. Mol Syst Biol 2023; 19:e10571. [PMID: 37842805 PMCID: PMC10632737 DOI: 10.15252/msb.202110571] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 07/31/2023] [Accepted: 08/03/2023] [Indexed: 10/17/2023] Open
Abstract
Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.
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Affiliation(s)
- Theodore Alexandrov
- Structural and Computational Biology UnitEuropean Molecular Biology LaboratoryHeidelbergGermany
- Molecular Medicine Partnership UnitEuropean Molecular Biology LaboratoryHeidelbergGermany
- BioInnovation InstituteCopenhagenDenmark
| | - Julio Saez‐Rodriguez
- Molecular Medicine Partnership UnitEuropean Molecular Biology LaboratoryHeidelbergGermany
- Faculty of Medicine and Heidelberg University Hospital, Institute for Computational BiomedicineHeidelberg UniversityHeidelbergGermany
| | - Sinem K Saka
- Genome Biology UnitEuropean Molecular Biology LaboratoryHeidelbergGermany
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4
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Abstract
The biology of a cell, whether it is a unicellular organism or part of a multicellular network, is influenced by cell type, temporal changes in cell state, and the cell's environment. Spatial cues play a critical role in the regulation of microbial pathogenesis strategies. Information about where the pathogen is-in a tissue or in proximity to a host cell-regulates gene expression and the compartmentalization of gene products in the microbe and the host. Our understanding of host and pathogen identity has bloomed with the accessibility of transcriptomics and proteomics techniques. A missing piece of the puzzle has been our ability to evaluate global transcript and protein expression in the context of the subcellular niche, primary cell, or native tissue environment during infection. This barrier is now lower with the advent of new spatial omics techniques to understand how location regulates cellular functions. This review will discuss how recent advances in spatial proteomics and transcriptomics approaches can address outstanding questions in microbial pathogenesis.
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Affiliation(s)
- Samantha Lempke
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Dana May
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Sarah E. Ewald
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
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5
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Kotliar IB. Proteomics Update and Perspectives from the Proteomics in Cell Biology and Disease Mechanisms Conference. Chembiochem 2023; 24:e202200626. [PMID: 36703596 PMCID: PMC10077886 DOI: 10.1002/cbic.202200626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Indexed: 01/28/2023]
Abstract
Proteomics, or the large-scale study of proteomes, has benefitted from many recent advances in chemical biology, mass spectrometry, and machine learning. The Proteomics in Cell Biology and Disease Mechanisms conference showcased the synergy between these elements and the vast range of biological questions that proteomics can now help us to answer.
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Affiliation(s)
- Ilana B Kotliar
- Laboratory of Chemical Biology and Signal Transduction, The Rockefeller University, 1230 York Ave., New York, NY 10065, USA
- Tri-Institutional PhD Program in Chemical Biology, New York, NY 10065, USA
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6
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Genome-Wide Investigation of Apyrase (APY) Genes in Peanut ( Arachis hypogaea L.) and Functional Characterization of a Pod-Abundant Expression Promoter AhAPY2-1p. Int J Mol Sci 2023; 24:ijms24054622. [PMID: 36902052 PMCID: PMC10003104 DOI: 10.3390/ijms24054622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/05/2023] [Accepted: 01/12/2023] [Indexed: 03/06/2023] Open
Abstract
Peanut (Arachis hypogaea L.) is an important food and feed crop worldwide and is affected by various biotic and abiotic stresses. The cellular ATP levels decrease significantly during stress as ATP molecules move to extracellular spaces, resulting in increased ROS production and cell apoptosis. Apyrases (APYs) are the nucleoside phosphatase (NPTs) superfamily members and play an important role in regulating cellular ATP levels under stress. We identified 17 APY homologs in A. hypogaea (AhAPYs), and their phylogenetic relationships, conserved motifs, putative miRNAs targeting different AhAPYs, cis-regulatory elements, etc., were studied in detail. The transcriptome expression data were used to observe the expression patterns in different tissues and under stress conditions. We found that the AhAPY2-1 gene showed abundant expression in the pericarp. As the pericarp is a key defense organ against environmental stress and promoters are the key elements regulating gene expression, we functionally characterized the AhAPY2-1 promoter for its possible use in future breeding programs. The functional characterization of AhAPY2-1P in transgenic Arabidopsis plants showed that it effectively regulated GUS gene expression in the pericarp. GUS expression was also detected in flowers of transgenic Arabidopsis plants. Overall, these results strongly suggest that APYs are an important future research subject for peanut and other crops, and AhPAY2-1P can be used to drive the resistance-related genes in a pericarp-specific manner to enhance the defensive abilities of the pericarp.
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7
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Burton JB, Silva-Barbosa A, Bons J, Rose J, Pfister K, Simona F, Gandhi T, Reiter L, Bernhardt O, Hunter CL, Goetzman ES, Sims-Lucas S, Schilling B. Substantial Downregulation of Mitochondrial and Peroxisomal Proteins during Acute Kidney Injury revealed by Data-Independent Acquisition Proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.26.530107. [PMID: 36865241 PMCID: PMC9980295 DOI: 10.1101/2023.02.26.530107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A fast-acquisition rate ZenoTOF 7600 mass spectrometer was introduced for data-independent acquisition (DIA) for comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3,945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured mice exhibited severely declined health. The comprehensive and sensitive kidney-specific DIA assays highlighted here feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome and will serve as useful tools for developing novel therapeutics to remediate kidney function.
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8
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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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9
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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: 1] [Impact Index Per Article: 1.0] [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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10
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Albarnaz JD, Weekes MP. Proteomic analysis of antiviral innate immunity. Curr Opin Virol 2023; 58:101291. [PMID: 36529073 DOI: 10.1016/j.coviro.2022.101291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/03/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022]
Abstract
The capacity of host cells to detect and restrict an infecting virus rests on an array of cell-autonomous antiviral effectors and innate immune receptors that can trigger inflammatory processes at tissue and organismal levels. Dynamic changes in protein abundance, subcellular localisation, post-translational modifications and interactions with other biomolecules govern these processes. Proteomics is therefore an ideal experimental tool to discover novel mechanisms of host antiviral immunity. Additional information can be gleaned both about host and virus by systematic analysis of viral immune evasion strategies. In this review, we summarise recent advances in proteomic technologies and their application to antiviral innate immunity.
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Affiliation(s)
- Jonas D Albarnaz
- Cambridge Institute for Medical Research, University of Cambridge, Hills Road, CB2 0XY Cambridge, UK
| | - Michael P Weekes
- Cambridge Institute for Medical Research, University of Cambridge, Hills Road, CB2 0XY Cambridge, UK.
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11
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Davies SW, Gamache MH, Howe-Kerr LI, Kriefall NG, Baker AC, Banaszak AT, Bay LK, Bellantuono AJ, Bhattacharya D, Chan CX, Claar DC, Coffroth MA, Cunning R, Davy SK, del Campo J, Díaz-Almeyda EM, Frommlet JC, Fuess LE, González-Pech RA, Goulet TL, Hoadley KD, Howells EJ, Hume BCC, Kemp DW, Kenkel CD, Kitchen SA, LaJeunesse TC, Lin S, McIlroy SE, McMinds R, Nitschke MR, Oakley CA, Peixoto RS, Prada C, Putnam HM, Quigley K, Reich HG, Reimer JD, Rodriguez-Lanetty M, Rosales SM, Saad OS, Sampayo EM, Santos SR, Shoguchi E, Smith EG, Stat M, Stephens TG, Strader ME, Suggett DJ, Swain TD, Tran C, Traylor-Knowles N, Voolstra CR, Warner ME, Weis VM, Wright RM, Xiang T, Yamashita H, Ziegler M, Correa AMS, Parkinson JE. Building consensus around the assessment and interpretation of Symbiodiniaceae diversity. PeerJ 2023; 11:e15023. [PMID: 37151292 PMCID: PMC10162043 DOI: 10.7717/peerj.15023] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 02/17/2023] [Indexed: 05/09/2023] Open
Abstract
Within microeukaryotes, genetic variation and functional variation sometimes accumulate more quickly than morphological differences. To understand the evolutionary history and ecology of such lineages, it is key to examine diversity at multiple levels of organization. In the dinoflagellate family Symbiodiniaceae, which can form endosymbioses with cnidarians (e.g., corals, octocorals, sea anemones, jellyfish), other marine invertebrates (e.g., sponges, molluscs, flatworms), and protists (e.g., foraminifera), molecular data have been used extensively over the past three decades to describe phenotypes and to make evolutionary and ecological inferences. Despite advances in Symbiodiniaceae genomics, a lack of consensus among researchers with respect to interpreting genetic data has slowed progress in the field and acted as a barrier to reconciling observations. Here, we identify key challenges regarding the assessment and interpretation of Symbiodiniaceae genetic diversity across three levels: species, populations, and communities. We summarize areas of agreement and highlight techniques and approaches that are broadly accepted. In areas where debate remains, we identify unresolved issues and discuss technologies and approaches that can help to fill knowledge gaps related to genetic and phenotypic diversity. We also discuss ways to stimulate progress, in particular by fostering a more inclusive and collaborative research community. We hope that this perspective will inspire and accelerate coral reef science by serving as a resource to those designing experiments, publishing research, and applying for funding related to Symbiodiniaceae and their symbiotic partnerships.
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Affiliation(s)
- Sarah W. Davies
- Department of Biology, Boston University, Boston, MA, United States
| | - Matthew H. Gamache
- Department of Integrative Biology, University of South Florida, Tampa, FL, United States
| | | | | | - Andrew C. Baker
- Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL, United States
| | - Anastazia T. Banaszak
- Unidad Académica de Sistemas Arrecifales, Universidad Nacional Autónoma de México, Puerto Morelos, Mexico
| | - Line Kolind Bay
- Australian Institute of Marine Science, Townsville, Australia
| | - Anthony J. Bellantuono
- Department of Biological Sciences, Florida International University, Miami, FL, United States
| | - Debashish Bhattacharya
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States
| | - Cheong Xin Chan
- Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia
| | - Danielle C. Claar
- Nearshore Habitat Program, Washington State Department of Natural Resources, Olympia, WA, USA
| | | | - Ross Cunning
- Daniel P. Haerther Center for Conservation and Research, John G. Shedd Aquarium, Chicago, IL, United States
| | - Simon K. Davy
- School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Javier del Campo
- Institut de Biologia Evolutiva (CSIC - Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
| | | | - Jörg C. Frommlet
- Centre for Environmental and Marine Studies, Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal
| | - Lauren E. Fuess
- Department of Biology, Texas State University, San Marcos, TX, United States
| | - Raúl A. González-Pech
- Department of Integrative Biology, University of South Florida, Tampa, FL, United States
- Department of Biology, Pennsylvania State University, State College, PA, United States
| | - Tamar L. Goulet
- Department of Biology, University of Mississippi, University, MS, United States
| | - Kenneth D. Hoadley
- Department of Biological Sciences, University of Alabama—Tuscaloosa, Tuscaloosa, AL, United States
| | - Emily J. Howells
- National Marine Science Centre, Faculty of Science and Engineering, Southern Cross University, Coffs Harbour, NSW, Australia
| | | | - Dustin W. Kemp
- Department of Biology, University of Alabama—Birmingham, Birmingham, Al, United States
| | - Carly D. Kenkel
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, United States
| | - Sheila A. Kitchen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
| | - Todd C. LaJeunesse
- Department of Biology, Pennsylvania State University, University Park, PA, United States
| | - Senjie Lin
- Department of Marine Sciences, University of Connecticut, Mansfield, CT, United States
| | - Shelby E. McIlroy
- Swire Institute of Marine Science, School of Biological Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Ryan McMinds
- Center for Global Health and Infectious Disease Research, University of South Florida, Tampa, FL, United States
| | | | - Clinton A. Oakley
- School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Raquel S. Peixoto
- Red Sea Research Center (RSRC), Division of Biological and Environmental Science and Engineering (BESE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Carlos Prada
- Department of Biological Sciences, University of Rhode Island, Kingston, RI, United States
| | - Hollie M. Putnam
- Department of Biological Sciences, University of Rhode Island, Kingston, RI, United States
| | | | - Hannah G. Reich
- Department of Biological Sciences, University of Rhode Island, Kingston, RI, United States
| | - James Davis Reimer
- Department of Biology, Chemistry and Marine Sciences, Faculty of Science, University of the Ryukyus, Nishihara, Okinawa, Japan
| | | | - Stephanie M. Rosales
- The Cooperative Institute For Marine and Atmospheric Studies, Miami, FL, United States
| | - Osama S. Saad
- Department of Biological Oceanography, Red Sea University, Port-Sudan, Sudan
| | - Eugenia M. Sampayo
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD, Australia
| | - Scott R. Santos
- Department of Biological Sciences, University at Buffalo, Buffalo, NY, United States
| | - Eiichi Shoguchi
- Marine Genomics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Edward G. Smith
- School of Life Sciences, University of Warwick, Coventry, UK
| | - Michael Stat
- School of Environmental and Life Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - Timothy G. Stephens
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States
| | - Marie E. Strader
- Department of Biology, Texas A&M University, College Station, TX, United States
| | - David J. Suggett
- Red Sea Research Center (RSRC), Division of Biological and Environmental Science and Engineering (BESE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Climate Change Cluster, University of Technology Sydney, Ultimo, NSW, Australia
| | - Timothy D. Swain
- Department of Marine and Environmental Science, Nova Southeastern University, Dania Beach, FL, United States
| | - Cawa Tran
- Department of Biology, University of San Diego, San Diego, CA, United States
| | - Nikki Traylor-Knowles
- Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL, United States
| | | | - Mark E. Warner
- School of Marine Science and Policy, University of Delaware, Lewes, DE, United States
| | - Virginia M. Weis
- Department of Integrative Biology, Oregon State University, Corvallis, OR, United States
| | - Rachel M. Wright
- Department of Biological Sciences, Southern Methodist University, Dallas, TX, United States
| | - Tingting Xiang
- School of Life Sciences, University of Warwick, Coventry, UK
| | - Hiroshi Yamashita
- Fisheries Technology Institute, Japan Fisheries Research and Education Agency, Ishigaki, Okinawa, Japan
| | - Maren Ziegler
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen (Germany), Giessen, Germany
| | | | - John Everett Parkinson
- Department of Integrative Biology, University of South Florida, Tampa, FL, United States
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12
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Das H, Zografakis A, Oeljeklaus S, Warscheid B. Analysis of Yeast Peroxisomes via Spatial Proteomics. Methods Mol Biol 2023; 2643:13-31. [PMID: 36952175 DOI: 10.1007/978-1-0716-3048-8_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Peroxisomes are ubiquitous organelles with essential functions in numerous cellular processes such as lipid metabolism, detoxification of reactive oxygen species, and signaling. Knowledge of the peroxisomal proteome including multi-localized proteins and, most importantly, changes of its composition induced by altering cellular conditions or impaired peroxisome biogenesis and function is of paramount importance for a holistic view on peroxisomes and their diverse functions in a cellular context. In this chapter, we provide a spatial proteomics protocol specifically tailored to the analysis of the peroxisomal proteome of baker's yeast that enables the definition of the peroxisomal proteome under distinct conditions and to monitor dynamic changes of the proteome including the relocation of individual proteins to a different cellular compartment. The protocol comprises subcellular fractionation by differential centrifugation followed by Nycodenz density gradient centrifugation of a crude peroxisomal fraction, quantitative mass spectrometric measurements of subcellular and density gradient fractions, and advanced computational data analysis, resulting in the establishment of organellar maps on a global scale.
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Affiliation(s)
- Hirak Das
- Biochemistry II, Theodor Boveri-Institute, University of Würzburg, Würzburg, Germany
| | - Alexandros Zografakis
- Biochemistry II, Theodor Boveri-Institute, University of Würzburg, Würzburg, Germany
| | - Silke Oeljeklaus
- Biochemistry II, Theodor Boveri-Institute, University of Würzburg, Würzburg, Germany.
| | - Bettina Warscheid
- Biochemistry II, Theodor Boveri-Institute, University of Würzburg, Würzburg, Germany.
- CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany.
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13
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Mou M, Pan Z, Lu M, Sun H, Wang Y, Luo Y, Zhu F. Application of Machine Learning in Spatial Proteomics. J Chem Inf Model 2022; 62:5875-5895. [PMID: 36378082 DOI: 10.1021/acs.jcim.2c01161] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Spatial proteomics is an interdisciplinary field that investigates the localization and dynamics of proteins, and it has gained extensive attention in recent years, especially the subcellular proteomics. Numerous evidence indicate that the subcellular localization of proteins is associated with various cellular processes and disease progression. Mass spectrometry (MS)-based and imaging-based experimental approaches have been developed to acquire large-scale spatial proteomic data. To allow the reliable analysis of increasingly complex spatial proteomics data, machine learning (ML) methods have been widely used in both MS-based and imaging-based spatial proteomic data analysis pipelines. Here, we comprehensively survey the applications of ML in spatial proteomics from following aspects: (1) data resources for spatial proteome are comprehensively introduced; (2) the roles of different ML algorithms in data analysis pipelines are elaborated; (3) successful applications of spatial proteomics and several analytical tools integrating ML methods are presented; (4) challenges existing in modern ML-based spatial proteomics studies are discussed. This review provides guidelines for researchers seeking to apply ML methods to analyze spatial proteomic data and can facilitate insightful understanding of cell biology as well as the future research in medical and drug discovery communities.
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Affiliation(s)
- Minjie Mou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ziqi Pan
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Mingkun Lu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Huaicheng Sun
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yunxia Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yongchao Luo
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
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14
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Leger MM, Stairs C. Eukaryotic evolution: Spatial proteomics sheds light on mitochondrial reduction. Curr Biol 2022; 32:R1308-R1311. [PMID: 36473440 DOI: 10.1016/j.cub.2022.10.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Multi-organelle spatial proteomics has revolutionized animal cell biology, but its use in protists has so far been limited. A new study delivers the first such proteome of a free-living protist, uncovering a previously overlooked function of highly reduced mitochondria.
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Affiliation(s)
- Michelle M Leger
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), Pg. Marítim de la Barceloneta 37-49, 08003 Barcelona, Spain.
| | - Courtney Stairs
- Microbiology Research Group, Department of Biology, Lund University, Sölvegatan 35, 223 62 Lund, Sweden.
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15
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Crook OM, Lilley KS, Gatto L, Kirk PD. Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics. Ann Appl Stat 2022; 16:22-aoas1603. [PMID: 36507469 PMCID: PMC7613899 DOI: 10.1214/22-aoas1603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Understanding sub-cellular protein localisation is an essential component in the analysis of context specific protein function. Recent advances in quantitative mass-spectrometry (MS) have led to high resolution mapping of thousands of proteins to sub-cellular locations within the cell. Novel modelling considerations to capture the complex nature of these data are thus necessary. We approach analysis of spatial proteomics data in a non-parametric Bayesian framework, using K-component mixtures of Gaussian process regression models. The Gaussian process regression model accounts for correlation structure within a sub-cellular niche, with each mixture component capturing the distinct correlation structure observed within each niche. The availability of marker proteins (i.e. proteins with a priori known labelled locations) motivates a semi-supervised learning approach to inform the Gaussian process hyperparameters. We moreover provide an efficient Hamiltonian-within-Gibbs sampler for our model. Furthermore, we reduce the computational burden associated with inversion of covariance matrices by exploiting the structure in the covariance matrix. A tensor decomposition of our covariance matrices allows extended Trench and Durbin algorithms to be applied to reduce the computational complexity of inversion and hence accelerate computation. We provide detailed case-studies on Drosophila embryos and mouse pluripotent embryonic stem cells to illustrate the benefit of semi-supervised functional Bayesian modelling of the data.
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16
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Low TY, Chen YJ, Ishihama Y, Chung MCM, Cordwell S, Poon TCW, Kwon HJ. The Second Asia-Oceania Human Proteome Organization (AOHUPO) Online Education Series on the Renaissance of Clinical Proteomics: Biomarkers, Imaging and Therapeutics. Mol Cell Proteomics 2022; 21:100436. [PMID: 36309314 PMCID: PMC9700300 DOI: 10.1016/j.mcpro.2022.100436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022] Open
Abstract
In 2021, the Asia-Oceania Human Proteome Organization (AOHUPO) initiated a new endeavor named the AOHUPO Online Education Series with the aim to promote scientific education and collaboration, exchange of ideas and culture among the young scientists in the AO region. Following the warm participation, the AOHUPO organized the second series in 2022, with the theme "The Renaissance of Clinical Proteomics: Biomarkers, Imaging and Therapeutics". This time, the second AOHUPO Online Education Series was hosted by the UKM Medical Molecular Biology Institute (UMBI) affiliated to the National University of Malaysia (UKM) in Kuala Lumpur, Malaysia on three consecutive Fridays (11th, 18th and 25th of March). More than 300 participants coming from 29 countries/regions registered for this 3-days event. This event provided an amalgamation of six prominent speakers and all participants whose interests lay mainly in applying MS-based and non-MS-based proteomics for clinical investigation.
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Affiliation(s)
- Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Max Ching Ming Chung
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Stuart Cordwell
- School of Life and Environmental Sciences and Sydney Mass Spectrometry, The University of Sydney, Sydney, Australia
| | - Terence Chuen Wai Poon
- Pilot Laboratory, Proteomics Core, Institute of Translational Medicine, Centre for Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Ho Jeong Kwon
- Chemical Genomics Leader Research Initiative, Department of Biotechnology, Yonsei University, Seoul, South Korea,For correspondence: Ho Jeong Kwon
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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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Arslan T, Pan Y, Mermelekas G, Vesterlund M, Orre LM, Lehtiö J. SubCellBarCode: integrated workflow for robust spatial proteomics by mass spectrometry. Nat Protoc 2022; 17:1832-1867. [PMID: 35732783 DOI: 10.1038/s41596-022-00699-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 03/18/2022] [Indexed: 11/09/2022]
Abstract
The molecular functions of a protein are defined by its inherent properties in relation to its environment and interaction network. Within a cell, this environment and network are defined by the subcellular location of the protein. Consequently, it is crucial to know the localization of a protein to fully understand its functions. Recently, we have developed a mass spectrometry- (MS) and bioinformatics-based pipeline to generate a proteome-wide resource for protein subcellular localization across multiple human cancer cell lines ( www.subcellbarcode.org ). Here, we present a detailed wet-lab protocol spanning from subcellular fractionation to MS-sample preparation and analysis. A key feature of this protocol is that it includes all generated cell fractions without discarding any material during the fractionation process. We also describe the subsequent quantitative MS-data analysis, machine learning-based classification, differential localization analysis and visualization of the output. For broad applicability, we evaluated the pipeline by using MS data generated by two different peptide pre-fractionation approaches, namely high-resolution isoelectric focusing and high-pH reverse-phase fractionation, as well as direct analysis without pre-fractionation by using long-gradient liquid chromatography-MS. Moreover, an R package covering the dry-lab part of the method was developed and made available through Bioconductor. The method is straightforward and robust, and the entire protocol, from cell harvest to classification output, can be performed within 1-2 weeks. The protocol enables accurate classification of proteins to 15 compartments and 4 neighborhoods, visualization of the output data and differential localization analysis including treatment-induced protein relocalization, condition-dependent localization or cell type-specific localization. The SubCellBarCode package is freely available at https://bioconductor.org/packages/devel/bioc/html/SubCellBarCode.html .
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Affiliation(s)
- Taner Arslan
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Yanbo Pan
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Georgios Mermelekas
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Mattias Vesterlund
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden
| | - Lukas M Orre
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden.
| | - Janne Lehtiö
- Department of Oncology and Pathology, Karolinska Institutet, Science for Life Laboratory, Solna, Sweden.
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19
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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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20
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Burton JB, Carruthers NJ, Hou Z, Matherly LH, Stemmer PM. Pattern Analysis of Organellar Maps for Interpretation of Proteomic Data. Proteomes 2022; 10:18. [PMID: 35645376 PMCID: PMC9149908 DOI: 10.3390/proteomes10020018] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/07/2022] [Accepted: 05/17/2022] [Indexed: 12/13/2022] Open
Abstract
Localization of organelle proteins by isotope tagging (LOPIT) maps are a coordinate-directed representation of proteome data that can aid in biological interpretation. Analysis of organellar association for proteins as displayed using LOPIT is evaluated and interpreted for two types of proteomic data sets. First, test and control group protein abundances and fold change data obtained in a proximity labeling experiment are plotted on a LOPIT map to evaluate the likelihood of true protein interactions. Selection of true positives based on co-localization of proteins in the organellar space is shown to be consistent with carboxylase enrichment which serves as a positive control for biotinylation in streptavidin affinity selected proteome data sets. The mapping in organellar space facilitates discrimination between the test and control groups and aids in identification of proteins of interest. The same representation of proteins in organellar space is used in the analysis of extracellular vesicle proteomes for which protein abundance and fold change data are evaluated. Vesicular protein organellar localization patterns provide information about the subcellular origin of the proteins in the samples which are isolates from the extracellular milieu. The organellar localization patterns are indicative of the provenance of the vesicular proteome origin and allow discrimination between proteomes prepared using different enrichment methods. The patterns in LOPIT displays are easy to understand and compare which aids in the biological interpretation of proteome data.
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Affiliation(s)
- Jordan B. Burton
- Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA;
| | | | - Zhanjun Hou
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48202, USA; (Z.H.); (L.H.M.)
| | - Larry H. Matherly
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48202, USA; (Z.H.); (L.H.M.)
| | - Paul M. Stemmer
- Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA;
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21
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Dionne U, Gingras AC. Proximity-Dependent Biotinylation Approaches to Explore the Dynamic Compartmentalized Proteome. Front Mol Biosci 2022; 9:852911. [PMID: 35309513 PMCID: PMC8930824 DOI: 10.3389/fmolb.2022.852911] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 02/07/2022] [Indexed: 12/12/2022] Open
Abstract
In recent years, proximity-dependent biotinylation approaches, including BioID, APEX, and their derivatives, have been widely used to define the compositions of organelles and other structures in cultured cells and model organisms. The associations between specific proteins and given compartments are regulated by several post-translational modifications (PTMs); however, these effects have not been systematically investigated using proximity proteomics. Here, we discuss the progress made in this field and how proximity-dependent biotinylation strategies could elucidate the contributions of PTMs, such as phosphorylation, to the compartmentalization of proteins.
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Affiliation(s)
- Ugo Dionne
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Anne-Claude Gingras
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- *Correspondence: Anne-Claude Gingras,
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22
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Hooper CM, Castleden IR, Tanz SK, Grasso SV, Millar AH. Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1346:67-89. [PMID: 35113396 DOI: 10.1007/978-3-030-80352-0_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
In eukaryotic organisms, subcellular protein location is critical in defining protein function and understanding sub-functionalization of gene families. Some proteins have defined locations, whereas others have low specificity targeting and complex accumulation patterns. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining evidence from different approaches, the strengths and weaknesses of different technologies can be estimated, and a location consensus can be built. The Subcellular Location of Proteins in Arabidopsis database ( http://suba.live/ ) combines experimental data sets that have been reported in the literature and is analyzing these data to provide useful tools for biologists to interpret their own data. Foremost among these tools is a consensus classifier (SUBAcon) that computes a proposed location for all proteins based on balancing the experimental evidence and predictions. Further tools analyze sets of proteins to define the abundance of cellular structures. Extending these types of resources to plant crop species has been complex due to polyploidy, gene family expansion and contraction, and the movement of pathways and processes within cells across the plant kingdom. The Crop Proteins of Annotated Location database ( http://crop-pal.org/ ) has developed a range of subcellular location resources including a species-specific voting consensus for 12 plant crop species that offers collated evidence and filters for current crop proteomes akin to SUBA. Comprehensive cross-species comparison of these data shows that the sub-cellular proteomes (subcellulomes) depend only to some degree on phylogenetic relationship and are more conserved in major biosynthesis than in metabolic pathways. Together SUBA and cropPAL created reference subcellulomes for plants as well as species-specific subcellulomes for cross-species data mining. These data collections are increasingly used by the research community to provide a subcellular protein location layer, inform models of compartmented cell function and protein-protein interaction network, guide future molecular crop breeding strategies, or simply answer a specific question-where is my protein of interest inside the cell?
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Affiliation(s)
- Cornelia M Hooper
- The Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia
| | - Ian R Castleden
- The Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia
| | - Sandra K Tanz
- The Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia
| | - Sally V Grasso
- The Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia
| | - A Harvey Millar
- The Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia.
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23
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Abstract
To absolutely and relatively quantitate the alteration of a posttranslationally modified (PTM) proteome in response to a specific internal or external signal, a 15N-stable isotope labeling in Arabidopsis (SILIA) protocol has been integrated into the 4C quantitative PTM proteomics, named as SILIA-based 4C quantitative PTM proteomics (S4Quap). The isotope metabolic labeling produces both forward (F) and reciprocal (R) mixings of either 14N/15N-coded tissues or the 14N/15N-coded total cellular proteins. Plant protein is isolated using a urea-based extraction buffer (UEB). The presence of 8 M urea, 2% polyvinylpolypyrrolidone (PVPP), and 5 mM ascorbic acid allows to instantly denature protein, remove the phenolic compounds, and curb the oxidation by free radicals once plant cells are broken. The total cellular proteins are routinely processed into peptides by trypsin. The PTM peptide yield of affinity enrichment and preparation is 0.1-0.2% in general. Ion exchange chromatographic fractionation prepares the PTM peptides for LC-MS/MS analysis. The collected mass spectrograms are subjected to a target-decoy sequence analysis using various search engines. The computational programs are subsequently applied to analyze the ratios of the extracted ion chromatogram (XIC) of the 14N/15N isotope-coded PTM peptide ions and to perform the statistical evaluation of the quantitation results. The Student t-test values of ratios of quantifiable 14N/15N-coded PTM peptides are normally corrected using a Benjamini-Hochberg (BH) multiple hypothesis test to select the significantly regulated PTM peptide groups (BH-FDR < 5%). Consequently, the highly selected prospect candidate(s) of PTM proteins are confirmed and validated using biochemical, molecular, cellular, and transgenic plant analysis.
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Affiliation(s)
- Emily Oi Ying Wong
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, SAR, China.,Shenzhen Research Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China
| | - Ning Li
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, SAR, China. .,Shenzhen Research Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China.
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24
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Christopher JA, Geladaki A, Dawson CS, Vennard OL, Lilley KS. SUBCELLULAR TRANSCRIPTOMICS & PROTEOMICS: A COMPARATIVE METHODS REVIEW. Mol Cell Proteomics 2021; 21:100186. [PMID: 34922010 PMCID: PMC8864473 DOI: 10.1016/j.mcpro.2021.100186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [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. Subcellular information of protein and RNA give insights into molecular function. This review discusses strategies available to measure subcellular information. Hybridization of methods shows promise for exploring the composition of organelles. Advances are aiding understanding of the organisation and dynamics of cells.
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Affiliation(s)
- Josie A Christopher
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
| | - Aikaterini Geladaki
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK; Department of Genetics, University of Cambridge, 20 Downing Place, Cambridge, CB2 3EJ, UK
| | - Charlotte S Dawson
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
| | - Owen L Vennard
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK; Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK.
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25
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Ahmed R, Augustine R, Valera E, Ganguli A, Mesaeli N, Ahmad IS, Bashir R, Hasan A. Spatial mapping of cancer tissues by OMICS technologies. Biochim Biophys Acta Rev Cancer 2021; 1877:188663. [PMID: 34861353 DOI: 10.1016/j.bbcan.2021.188663] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 11/15/2021] [Accepted: 11/26/2021] [Indexed: 12/14/2022]
Abstract
Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, number of different biomolecules that can be detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.
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Affiliation(s)
- Rashid Ahmed
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar; Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA
| | - Robin Augustine
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar
| | - Enrique Valera
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA
| | - Anurup Ganguli
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA
| | - Nasrin Mesaeli
- Department of Biochemistry, Weill Cornell Medicine in Qatar, Qatar Foundation, Doha, Qatar
| | - Irfan S Ahmad
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA
| | - Rashid Bashir
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, IL, USA; Department of Bioengineering, University of Illinois at Urbana Champaign, IL, USA; Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
| | - Anwarul Hasan
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar; Biomedical Research Center (BRC), Qatar University, Doha 2713, Qatar.
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26
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Kershaw CJ, Nelson MG, Lui J, Bates CP, Jennings MD, Hubbard SJ, Ashe MP, Grant CM. Integrated multi-omics reveals common properties underlying stress granule and P-body formation. RNA Biol 2021; 18:655-673. [PMID: 34672913 PMCID: PMC8782181 DOI: 10.1080/15476286.2021.1976986] [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] [Indexed: 12/30/2022] Open
Abstract
Non-membrane-bound compartments such as P-bodies (PBs) and stress granules (SGs) play important roles in the regulation of gene expression following environmental stresses. We have systematically and quantitatively determined the protein and mRNA composition of PBs and SGs formed before and after nutrient stress. We find that high molecular weight (HMW) complexes exist prior to glucose depletion that we propose may act as seeds for further condensation of proteins forming mature PBs and SGs. We identify an enrichment of proteins with low complexity and RNA binding domains, as well as long, structured mRNAs that are poorly translated following nutrient stress. Many proteins and mRNAs are shared between PBs and SGs including several multivalent RNA binding proteins that promote condensate interactions during liquid-liquid phase separation. We uncover numerous common protein and RNA components across PBs and SGs that support a complex interaction profile during the maturation of these biological condensates. These interaction networks represent a tuneable response to stress, highlighting previously unrecognized condensate heterogeneity. These studies therefore provide an integrated and quantitative understanding of the dynamic nature of key biological condensates.
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Affiliation(s)
- Christopher J Kershaw
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Michael G Nelson
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Jennifer Lui
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Christian P Bates
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Martin D Jennings
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Simon J Hubbard
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Mark P Ashe
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
| | - Chris M Grant
- University of Manchester School of Biological Science, The University of Manchester Faculty of Biology Medicine and Health, Manchester, UK
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27
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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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28
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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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29
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Ayagama T, Bose SJ, Capel RA, Priestman DA, Berridge G, Fischer R, Galione A, Platt FM, Kramer H, Burton RA. A modified density gradient proteomic-based method to analyze endolysosomal proteins in cardiac tissue. iScience 2021; 24:102949. [PMID: 34466782 PMCID: PMC8384914 DOI: 10.1016/j.isci.2021.102949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 03/04/2021] [Accepted: 08/02/2021] [Indexed: 11/22/2022] Open
Abstract
The importance of lysosomes in cardiac physiology and pathology is well established, and evidence for roles in calcium signaling is emerging. We describe a label-free proteomics method suitable for small cardiac tissue biopsies based on density-separated fractionation, which allows study of endolysosomal (EL) proteins. Density gradient fractions corresponding to tissue lysate; sarcoplasmic reticulum (SR), mitochondria (Mito) (1.3 g/mL); and EL with negligible contamination from SR or Mito (1.04 g/mL) were analyzed using Western blot, enzyme activity assay, and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis (adapted discontinuous Percoll and sucrose differential density gradient). Kyoto Encyclopedia of Genes and Genomes, Reactome, Panther, and Gene Ontology pathway analysis showed good coverage of RAB proteins and lysosomal cathepsins (including cardiac-specific cathepsin D) in the purified EL fraction. Significant EL proteins recovered included catalytic activity proteins. We thus present a comprehensive protocol and data set of guinea pig atrial EL organelle proteomics using techniques also applicable for non-cardiac tissue.
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Affiliation(s)
- Thamali Ayagama
- University of Oxford, Department of Pharmacology, Oxford, OX1 3QT UK
| | - Samuel J. Bose
- University of Oxford, Department of Pharmacology, Oxford, OX1 3QT UK
| | - Rebecca A. Capel
- University of Oxford, Department of Pharmacology, Oxford, OX1 3QT UK
| | | | - Georgina Berridge
- Target Discovery Institute, University of Oxford, Oxford, OX3 7FZ UK
| | - Roman Fischer
- Target Discovery Institute, University of Oxford, Oxford, OX3 7FZ UK
| | - Antony Galione
- University of Oxford, Department of Pharmacology, Oxford, OX1 3QT UK
| | - Frances M. Platt
- University of Oxford, Department of Pharmacology, Oxford, OX1 3QT UK
| | - Holger Kramer
- Biological Mass Spectrometry and Proteomics Facility, MRC London Institute of Medical Sciences, Imperial College London, London, W12 0NN UK
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30
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Abstract
Lysosomes are the main degradative organelles of almost all eukaryotic cells. They fulfil a crucial function in cellular homeostasis, and impairments in lysosomal function are connected to a continuously increasing number of pathological conditions. In recent years, lysosomes are furthermore emerging as control centers of cellular metabolism, and major regulators of cellular signaling were shown to be activated at the lysosomal surface. To date, >300 proteins were demonstrated to be located in/at the lysosome, and the lysosomal proteome and interactome is constantly growing. For the identification of these proteins, and their involvement in cellular mechanisms or disease progression, mass spectrometry (MS)-based proteomics has proven its worth in a large number of studies. In this review, we are recapitulating the application of MS-based approaches for the investigation of the lysosomal proteome, and their application to a diverse set of research questions. Numerous strategies were applied for the enrichment of lysosomes or lysosomal proteins and their identification by MS-based methods. This allowed for the characterization of the lysosomal proteome, the investigation of lysosome-related disorders, the utilization of lysosomal proteins as biomarkers for diseases, and the characterization of lysosome-related cellular mechanisms. While these >60 studies provide a comprehensive picture of the lysosomal proteome across several model organisms and pathological conditions, various proteomics approaches have not been applied to lysosomes yet, and a large number of questions are still left unanswered.
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Affiliation(s)
- Pathma Muthukottiappan
- Institute for Biochemistry and Molecular Biology, Medical Faculty, Rheinische Friedrich-Wilhelms-University of Bonn, Nussallee 11, 53115 Bonn, Germany.
| | - Dominic Winter
- Institute for Biochemistry and Molecular Biology, Medical Faculty, Rheinische Friedrich-Wilhelms-University of Bonn, Nussallee 11, 53115 Bonn, Germany.
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31
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Low TY, Syafruddin SE, Mohtar MA, Vellaichamy A, A Rahman NS, Pung YF, Tan CSH. Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions. Cell Mol Life Sci 2021; 78:5325-5339. [PMID: 34046695 PMCID: PMC8159249 DOI: 10.1007/s00018-021-03856-0] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/03/2021] [Accepted: 05/14/2021] [Indexed: 02/07/2023]
Abstract
Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.
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Affiliation(s)
- Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Jalan Yaacob Latiff, Bandar Tun Razak, 56000, Kuala Lumpur, Malaysia.
| | - Saiful Effendi Syafruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Jalan Yaacob Latiff, Bandar Tun Razak, 56000, Kuala Lumpur, Malaysia
| | - M Aiman Mohtar
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Jalan Yaacob Latiff, Bandar Tun Razak, 56000, Kuala Lumpur, Malaysia
| | | | - Nisa Syakila A Rahman
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Jalan Yaacob Latiff, Bandar Tun Razak, 56000, Kuala Lumpur, Malaysia
| | - Yuh-Fen Pung
- Division of Biomedical Science, University of Nottingham Malaysia, 43500, Semenyih, Malaysia
| | - Chris Soon Heng Tan
- Department of Chemistry, College of Science , Southern University of Science and Technology, Shenzhen, 518055, China.
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32
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Mehta D, Krahmer J, Uhrig RG. Closing the protein gap in plant chronobiology. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 106:1509-1522. [PMID: 33783885 DOI: 10.1111/tpj.15254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/19/2021] [Accepted: 03/23/2021] [Indexed: 06/12/2023]
Abstract
Our modern understanding of diel cell regulation in plants stems from foundational work in the late 1990s that analysed the dynamics of selected genes and mutants in Arabidopsis thaliana. The subsequent rise of transcriptomics technologies such as microarrays and RNA sequencing has substantially increased our understanding of anticipatory (circadian) and reactive (light- or dark-triggered) diel events in plants. However, it is also becoming clear that gene expression data fail to capture critical events in diel regulation that can only be explained by studying protein-level dynamics. Over the past decade, mass spectrometry technologies and quantitative proteomic workflows have significantly advanced, finally allowing scientists to characterise diel protein regulation at high throughput. Initial proteomic investigations suggest that the diel transcriptome and proteome generally lack synchrony and that the timing of daily regulatory events in plants is impacted by multiple levels of protein regulation (e.g., post-translational modifications [PTMs] and protein-protein interactions [PPIs]). Here, we highlight and summarise how the use of quantitative proteomics to elucidate diel plant cell regulation has advanced our understanding of these processes. We argue that this new understanding, coupled with the extraordinary developments in mass spectrometry technologies, demands greater focus on protein-level regulation of, and by, the circadian clock. This includes hitherto unexplored diel dynamics of protein turnover, PTMs, protein subcellular localisation and PPIs that can be masked by simple transcript- and protein-level changes. Finally, we propose new directions for how the latest advancements in quantitative proteomics can be utilised to answer outstanding questions in plant chronobiology.
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Affiliation(s)
- Devang Mehta
- Department of Biological Sciences, University of Alberta, Edmonton, Canada
| | - Johanna Krahmer
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - R Glen Uhrig
- Department of Biological Sciences, University of Alberta, Edmonton, Canada
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33
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Horváthová L, Žárský V, Pánek T, Derelle R, Pyrih J, Motyčková A, Klápšťová V, Vinopalová M, Marková L, Voleman L, Klimeš V, Petrů M, Vaitová Z, Čepička I, Hryzáková K, Harant K, Gray MW, Chami M, Guilvout I, Francetic O, Franz Lang B, Vlček Č, Tsaousis AD, Eliáš M, Doležal P. Analysis of diverse eukaryotes suggests the existence of an ancestral mitochondrial apparatus derived from the bacterial type II secretion system. Nat Commun 2021; 12:2947. [PMID: 34011950 PMCID: PMC8134430 DOI: 10.1038/s41467-021-23046-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 03/22/2021] [Indexed: 12/14/2022] Open
Abstract
The type 2 secretion system (T2SS) is present in some Gram-negative eubacteria and used to secrete proteins across the outer membrane. Here we report that certain representative heteroloboseans, jakobids, malawimonads and hemimastigotes unexpectedly possess homologues of core T2SS components. We show that at least some of them are present in mitochondria, and their behaviour in biochemical assays is consistent with the presence of a mitochondrial T2SS-derived system (miT2SS). We additionally identified 23 protein families co-occurring with miT2SS in eukaryotes. Seven of these proteins could be directly linked to the core miT2SS by functional data and/or sequence features, whereas others may represent different parts of a broader functional pathway, possibly also involving the peroxisome. Its distribution in eukaryotes and phylogenetic evidence together indicate that the miT2SS-centred pathway is an ancestral eukaryotic trait. Our findings thus have direct implications for the functional properties of the early mitochondrion. Bacteria use the type 2 secretion system to secrete enzymes and toxins across the outer membrane to the environment. Here the authors analyse the T2SS pathway in three protist lineages and suggest that the early mitochondrion may have been capable of secreting proteins into the cytosol.
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Affiliation(s)
- Lenka Horváthová
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Vojtěch Žárský
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Tomáš Pánek
- Faculty of Science, Department of Biology and Ecology, University of Ostrava, Ostrava, Czech Republic.,Faculty of Science, Department of Zoology, Charles University, Prague 2, Czech Republic
| | - Romain Derelle
- School of Biosciences, University of Birmingham, Edgbaston, UK
| | - Jan Pyrih
- Laboratory of Molecular & Evolutionary Parasitology, RAPID group, School of Biosciences, University of Kent, Canterbury, UK.,Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Alžběta Motyčková
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Veronika Klápšťová
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Martina Vinopalová
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Lenka Marková
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Luboš Voleman
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Vladimír Klimeš
- Faculty of Science, Department of Biology and Ecology, University of Ostrava, Ostrava, Czech Republic
| | - Markéta Petrů
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Zuzana Vaitová
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic
| | - Ivan Čepička
- Faculty of Science, Department of Zoology, Charles University, Prague 2, Czech Republic
| | - Klára Hryzáková
- Faculty of Science, Department of Genetics and Microbiology, Charles University, Prague 2, Czech Republic
| | - Karel Harant
- Faculty of Science, Proteomic core facility, Charles University, BIOCEV, Vestec, Czech Republic
| | - Michael W Gray
- Department of Biochemistry and Molecular Biology and Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada
| | - Mohamed Chami
- Center for Cellular Imaging and NanoAnalytics, University of Basel, Basel, Switzerland
| | - Ingrid Guilvout
- Biochemistry of Macromolecular Interactions Unit, Department of Structural Biology and Chemistry, Institut Pasteur, CNRS UMR3528, Paris, France
| | - Olivera Francetic
- Biochemistry of Macromolecular Interactions Unit, Department of Structural Biology and Chemistry, Institut Pasteur, CNRS UMR3528, Paris, France
| | - B Franz Lang
- Robert Cedergren Centre for Bioinformatics and Genomics, Département de Biochimie, Université de Montréal, Montreal, QC, Canada
| | - Čestmír Vlček
- Institute of Molecular Genetics, Czech Academy of Sciences, Prague 4, Czech Republic
| | - Anastasios D Tsaousis
- Laboratory of Molecular & Evolutionary Parasitology, RAPID group, School of Biosciences, University of Kent, Canterbury, UK
| | - Marek Eliáš
- Faculty of Science, Department of Biology and Ecology, University of Ostrava, Ostrava, Czech Republic.
| | - Pavel Doležal
- Faculty of Science, Department of Parasitology, Charles University, BIOCEV, Vestec, Czech Republic.
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Sheridan E, Vercellino S, Cursi L, Adumeau L, Behan JA, Dawson KA. Understanding intracellular nanoparticle trafficking fates through spatiotemporally resolved magnetic nanoparticle recovery. NANOSCALE ADVANCES 2021; 3:2397-2410. [PMID: 36134166 PMCID: PMC9419038 DOI: 10.1039/d0na01035a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 02/21/2021] [Indexed: 05/08/2023]
Abstract
The field of nanomedicine has the potential to be a game-changer in global health, with possible applications in prevention, diagnostics, and therapeutics. However, despite extensive research focus and funding, the forecasted explosion of novel nanomedicines is yet to materialize. We believe that clinical translation is ultimately hampered by a lack of understanding of how nanoparticles really interact with biological systems. When placed in a biological environment, nanoparticles adsorb a biomolecular layer that defines their biological identity. The challenge for bionanoscience is therefore to understand the evolution of the interactions of the nanoparticle-biomolecules complex as the nanoparticle is trafficked through the intracellular environment. However, to progress on this route, scientists face major challenges associated with isolation of specific intracellular compartments for analysis, complicated by the diversity of trafficking events happening simultaneously and the lack of synchronization between individual events. In this perspective article, we reflect on how magnetic nanoparticles can help to tackle some of these challenges as part of an overall workflow and act as a useful platform to investigate the bionano interactions within the cell that contribute to this nanoscale decision making. We discuss both established and emerging techniques for the magnetic extraction of nanoparticles and how they can potentially be used as tools to study the intracellular journey of nanomaterials inside the cell, and their potential to probe nanoscale decision-making events. We outline the inherent limitations of these techniques when investigating particular bio-nano interactions along with proposed strategies to improve both specificity and resolution. We conclude by describing how the integration of magnetic nanoparticle recovery with sophisticated analysis at the single-particle level could be applied to resolve key questions for this field in the future.
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Affiliation(s)
- Emily Sheridan
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
| | - Silvia Vercellino
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Biomolecular and Biomedical Science, University College Dublin Belfield Dublin 4 Ireland
| | - Lorenzo Cursi
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
| | - Laurent Adumeau
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
| | - James A Behan
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
| | - Kenneth A Dawson
- Centre for BioNano Interactions, School of Chemistry, University College Dublin Belfield Dublin 4 Ireland
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35
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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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36
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Liu M, Hu J, Zhang A, Dai Y, Chen W, He Y, Zhang H, Zheng X, Zhang Z. Auxilin-like protein MoSwa2 promotes effector secretion and virulence as a clathrin uncoating factor in the rice blast fungus Magnaporthe oryzae. THE NEW PHYTOLOGIST 2021; 230:720-736. [PMID: 33423301 PMCID: PMC8048681 DOI: 10.1111/nph.17181] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 01/04/2021] [Indexed: 05/03/2023]
Abstract
Plant pathogens exploit the extracellular matrix (ECM) to inhibit host immunity during their interactions with the host. The formation of ECM involves a series of continuous steps of vesicular transport events. To understand how such vesicle trafficking impacts ECM and virulence in the rice blast fungus Magnaporthe oryzae, we characterised MoSwa2, a previously identified actin-regulating kinase MoArk1 interacting protein, as an orthologue of the auxilin-like clathrin uncoating factor Swa2 of the budding yeast Saccharomyces cerevisiae. We found that MoSwa2 functions as an uncoating factor of the coat protein complex II (COPII) via an interaction with the COPII subunit MoSec24-2. Loss of MoSwa2 led to a deficiency in the secretion of extracellular proteins, resulting in both restricted growth of invasive hyphae and reduced inhibition of host immunity. Additionally, extracellular fluid (ECF) proteome analysis revealed that MoSwa2-regulated extracellular proteins include many redox proteins such as the berberine bridge enzyme-like (BBE-like) protein MoSef1. We further found that MoSef1 functions as an apoplastic virulent factor that inhibits the host immune response. Our studies revealed a novel function of a COPII uncoating factor in vesicular transport that is critical in the suppression of host immunity and pathogenicity of M. oryzae.
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Affiliation(s)
- Muxing Liu
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
- The Key Laboratory of Plant ImmunityNanjing Agricultural UniversityNanjing210095China
| | - Jiexiong Hu
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Ao Zhang
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Ying Dai
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Weizhong Chen
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Yanglan He
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Haifeng Zhang
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Xiaobo Zheng
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
| | - Zhengguang Zhang
- Department of Plant PathologyCollege of Plant ProtectionNanjing Agricultural UniversityKey Laboratory of Integrated Management of Crop Diseases and PestsMinistry of EducationNanjing210095China
- The Key Laboratory of Plant ImmunityNanjing Agricultural UniversityNanjing210095China
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37
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Abstract
The elucidation of the subcellular localization of proteins is very important in order to deeply understand their functions. In fact, proteins activities are strictly correlated to the cellular compartment and microenvironment in which they are present.In recent years, several effective and reliable proteomics techniques and computational methods have been developed and implemented in order to identify the proteins subcellular localization. This process is often time-consuming and expensive, but the recent technological and bioinformatics progress allowed the development of more accurate and simple workflows to determine the localization, interactions, and functions of proteins.In the following chapter, a brief introduction on the importance of knowing subcellular localization of proteins will be presented. Then, sample preparation protocols, proteomic methods, data analysis strategies, and software for the prediction of proteins localization will be presented and discussed. Finally, the more recent and advanced spatial proteomics techniques will be shown.
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Affiliation(s)
- Elettra Barberis
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Diseases, CAAD, University of Piemonte Orientale, Novara, Italy
| | - Emilio Marengo
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Alessandria, Italy
- Center for Translational Research on Autoimmune and Allergic Diseases, CAAD, University of Piemonte Orientale, Novara, Italy
| | - Marcello Manfredi
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
- Center for Translational Research on Autoimmune and Allergic Diseases, CAAD, University of Piemonte Orientale, Novara, Italy.
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38
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Hermann C, Karamchand L, Blackburn JM, Soares NC. Cell Envelope Proteomics of Mycobacteria. J Proteome Res 2020; 20:94-109. [PMID: 33140963 DOI: 10.1021/acs.jproteome.0c00650] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The World Health Organization (WHO) estimates that Mycobacterium tuberculosis, the most pathogenic mycobacterium species to humans, has infected up to a quarter of the world's population, with the occurrence of multidrug-resistant strains on the rise. Research into the detailed composition of the cell envelope proteome in mycobacteria over the last 20 years has formed a key part of the efforts to understand host-pathogen interactions and to control the current tuberculosis epidemic. This is due to the great importance of the cell envelope proteome during infection and during the development of antibiotic resistance as well as the search of surface-exposed proteins that could be targeted by therapeutics and vaccines. A variety of experimental approaches and mycobacterial species have been used in proteomic studies thus far. Here we provide for the first time an extensive summary of the different approaches to isolate the mycobacterial cell envelope, highlight some of the limitations of the studies performed thus far, and comment on how the recent advances in membrane proteomics in other fields might be translated into the field of mycobacteria to provide deeper coverage.
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Affiliation(s)
- Clemens Hermann
- Department of Integrative Biomedical Sciences, Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa
| | - Leshern Karamchand
- National Research Council Canada, Nanotechnology Research Centre, Biomedical Nanotechnologies, 11421 Saskatchewan Drive NW, Edmonton, Alberta T6G 2M9, Canada
| | - Jonathan M Blackburn
- Department of Integrative Biomedical Sciences, Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa
| | - Nelson C Soares
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah 27272, United Arab Emirates.,College of Pharmacy, Department of Medicinal Chemistry, University of Sharjah, Sharjah 27272, United Arab Emirates
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39
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Crook OM, Geladaki A, Nightingale DJH, Vennard OL, Lilley KS, Gatto L, Kirk PDW. A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection. PLoS Comput Biol 2020; 16:e1008288. [PMID: 33166281 PMCID: PMC7707549 DOI: 10.1371/journal.pcbi.1008288] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 12/01/2020] [Accepted: 08/25/2020] [Indexed: 01/13/2023] Open
Abstract
The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein's sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insufficient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyperLOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identified in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins trafficking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches.
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Affiliation(s)
- Oliver M. Crook
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, Cambridge, UK
| | - Aikaterini Geladaki
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Genetics, Universtiy of Cambridge, Cambridge, UK
| | - Daniel J. H. Nightingale
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Owen L. Vennard
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, Cambridge, UK
| | - Kathryn S. Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, Cambridge, UK
| | - Laurent Gatto
- de Duve Institute, UCLouvain, 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, UK
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40
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Mann M. The Origins of Organellar Mapping by Protein Correlation Profiling. Proteomics 2020; 20:e1900330. [PMID: 32744740 DOI: 10.1002/pmic.201900330] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 07/27/2020] [Indexed: 11/09/2022]
Abstract
Cells have a rich inner structure that is commonly explored by microscopy. Classical biochemical methods that break apart the cells and fractionate them along a gradient have now gotten a new lease on life through modern methods of mass spectrometry-based proteomics. Their common principle is to comprehensively measure all the proteins in each of the fractions. The resulting quantitative profile then associates thousands of proteins to their cellular homes. Here, the author recounts how protein correlation profiling, the first such technique, was conceived and how it was applied to answer intricate cell biological questions.
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Affiliation(s)
- Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152, Martinsried, Germany.,Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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41
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Zecha J, Lee CY, Bayer FP, Meng C, Grass V, Zerweck J, Schnatbaum K, Michler T, Pichlmair A, Ludwig C, Kuster B. Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing. Mol Cell Proteomics 2020; 19:1503-1522. [PMID: 32591346 PMCID: PMC7780043 DOI: 10.1074/mcp.ra120.002164] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 06/26/2020] [Indexed: 12/14/2022] Open
Abstract
As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.
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Affiliation(s)
- Jana Zecha
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Chien-Yun Lee
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Florian P Bayer
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Chen Meng
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany
| | - Vincent Grass
- Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany; German Center for Infection Research (DZIF), Munich partner site, Germany
| | | | | | - Thomas Michler
- Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andreas Pichlmair
- Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany; German Center for Infection Research (DZIF), Munich partner site, Germany
| | - Christina Ludwig
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany.
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany.
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42
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Borner GHH. Organellar Maps Through Proteomic Profiling - A Conceptual Guide. Mol Cell Proteomics 2020; 19:1076-1087. [PMID: 32345598 PMCID: PMC7338086 DOI: 10.1074/mcp.r120.001971] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 04/27/2020] [Indexed: 11/29/2022] Open
Abstract
Protein subcellular localization is an essential and highly regulated determinant of protein function. Major advances in mass spectrometry and imaging have allowed the development of powerful spatial proteomics approaches for determining protein localization at the whole cell scale. Here, a brief overview of current methods is presented, followed by a detailed discussion of organellar mapping through proteomic profiling. This relatively simple yet flexible approach is rapidly gaining popularity, because of its ability to capture the localizations of thousands of proteins in a single experiment. It can be used to generate high-resolution cell maps, and as a tool for monitoring protein localization dynamics. This review highlights the strengths and limitations of the approach and provides guidance to designing and interpreting profiling experiments.
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Affiliation(s)
- Georg H H Borner
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany.
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43
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Kennedy MA, Hofstadter WA, Cristea IM. TRANSPIRE: A Computational Pipeline to Elucidate Intracellular Protein Movements from Spatial Proteomics Data Sets. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:1422-1439. [PMID: 32401031 PMCID: PMC7737664 DOI: 10.1021/jasms.0c00033] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Protein localization is paramount to protein function, and the intracellular movement of proteins underlies the regulation of numerous cellular processes. Given advances in spatial proteomics, the investigation of protein localization at a global scale has become attainable. Also becoming apparent is the need for dedicated analytical frameworks that allow the discovery of global intracellular protein movement events. Here, we describe TRANSPIRE, a computational pipeline that facilitates TRanslocation ANalysis of SPatIal pRotEomics data sets. TRANSPIRE leverages synthetic translocation profiles generated from organelle marker proteins to train a probabilistic Gaussian process classifier that predicts changes in protein distribution. This output is then integrated with information regarding co-translocating proteins and complexes and enriched gene ontology associations to discern the putative regulation and function of movement. We validate TRANSPIRE performance for predicting nuclear-cytoplasmic shuttling events. Analyzing an existing data set of nuclear and cytoplasmic proteomes during Kaposi Sarcoma-associated herpesvirus (KSHV)-induced cellular mRNA decay, we confirm that TRANSPIRE readily discerns expected translocations of RNA binding proteins. We next investigate protein translocations during infection with human cytomegalovirus (HCMV), a β-herpesvirus known to induce global organelle remodeling. We find that HCMV infection induces broad changes in protein localization, with over 800 proteins predicted to translocate during virus replication. Evident are protein movements related to HCMV modulation of host defense, metabolism, cellular trafficking, and Wnt signaling. For example, the low-density lipoprotein receptor (LDLR) translocates to the lysosome early in infection in conjunction with its degradation, which we validate by targeted mass spectrometry. Using microscopy, we also validate the translocation of the multifunctional kinase DAPK3, a movement that may contribute to HCMV activation of Wnt signaling.
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Affiliation(s)
- Michelle A Kennedy
- Department of Molecular Biology, Princeton University, Washington Road, Princeton, New Jersey 08544, United States
| | - William A Hofstadter
- Department of Molecular Biology, Princeton University, Washington Road, Princeton, New Jersey 08544, United States
| | - Ileana M Cristea
- Department of Molecular Biology, Princeton University, Washington Road, Princeton, New Jersey 08544, United States
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44
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Crook OM, Smith T, Elzek M, Lilley KS. Moving Profiling Spatial Proteomics Beyond Discrete Classification. Proteomics 2020; 20:e1900392. [PMID: 32558233 DOI: 10.1002/pmic.201900392] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/18/2020] [Indexed: 12/12/2022]
Abstract
The spatial subcellular proteome is a dynamic environment; one that can be perturbed by molecular cues and regulated by post-translational modifications. Compartmentalization of this environment and management of these biomolecular dynamics allows for an array of ancillary protein functions. Profiling spatial proteomics has proved to be a powerful technique in identifying the primary subcellular localization of proteins. The approach has also been refashioned to study multi-localization and localization dynamics. Here, the analytical approaches that have been applied to spatial proteomics thus far are critiqued, and challenges particularly associated with multi-localization and dynamic relocalization is identified. To meet some of the current limitations in analytical processing, it is suggested that Bayesian modeling has clear benefits over the methods applied to date and should be favored whenever possible. Careful consideration of the limitations and challenges, and development of robust statistical frameworks, will ensure that profiling spatial proteomics remains a valuable technique as its utility is expanded.
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Affiliation(s)
- Oliver M Crook
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Tom Smith
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Mohamed Elzek
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
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45
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Budayeva HG, Kirkpatrick DS. Monitoring protein communities and their responses to therapeutics. Nat Rev Drug Discov 2020; 19:414-426. [PMID: 32139903 DOI: 10.1038/s41573-020-0063-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2020] [Indexed: 12/19/2022]
Abstract
Most therapeutics are designed to alter the activities of proteins. From metabolic enzymes to cell surface receptors, connecting the function of a protein to a cellular phenotype, to the activity of a drug and to a clinical outcome represents key mechanistic milestones during drug development. Yet, even for therapeutics with exquisite specificity, the sequence of events following target engagement can be complex. Interconnected communities of structural, metabolic and signalling proteins modulate diverse downstream effects that manifest as interindividual differences in efficacy, adverse effects and resistance to therapy. Recent advances in mass spectrometry proteomics have made it possible to decipher these complex relationships and to understand how factors such as genotype, cell type, local environment and external perturbations influence them. In this Review, we explore how proteomic technologies are expanding our understanding of protein communities and their responses to large- and small-molecule therapeutics.
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Affiliation(s)
- Hanna G Budayeva
- Department of Microchemistry, Proteomics and Lipidomics, Genentech, South San Francisco, CA, USA
| | - Donald S Kirkpatrick
- Department of Microchemistry, Proteomics and Lipidomics, Genentech, South San Francisco, CA, USA.
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46
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Lundberg E, Borner GHH. Spatial proteomics: a powerful discovery tool for cell biology. Nat Rev Mol Cell Biol 2020; 20:285-302. [PMID: 30659282 DOI: 10.1038/s41580-018-0094-y] [Citation(s) in RCA: 264] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Protein subcellular localization is tightly controlled and intimately linked to protein function in health and disease. Capturing the spatial proteome - that is, the localizations of proteins and their dynamics at the subcellular level - is therefore essential for a complete understanding of cell biology. Owing to substantial advances in microscopy, mass spectrometry and machine learning applications for data analysis, the field is now mature for proteome-wide investigations of spatial cellular regulation. Studies of the human proteome have begun to reveal a complex architecture, including single-cell variations, dynamic protein translocations, changing interaction networks and proteins localizing to multiple compartments. Furthermore, several studies have successfully harnessed the power of comparative spatial proteomics as a discovery tool to unravel disease mechanisms. We are at the beginning of an era in which spatial proteomics finally integrates with cell biology and medical research, thereby paving the way for unbiased systems-level insights into cellular processes. Here, we discuss current methods for spatial proteomics using imaging or mass spectrometry and specifically highlight global comparative applications. The aim of this Review is to survey the state of the field and also to encourage more cell biologists to apply spatial proteomics approaches.
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Affiliation(s)
- Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden. .,Department of Genetics, Stanford University, Stanford, CA, USA. .,Chan Zuckerberg Biohub, San Francisco, CA, USA.
| | - Georg H H Borner
- Max Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Martinsried, Germany.
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47
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Advances and applications of stable isotope labeling-based methods for proteome relative quantitation. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115815] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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48
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Dayon L, Affolter M. Progress and pitfalls of using isobaric mass tags for proteome profiling. Expert Rev Proteomics 2020; 17:149-161. [PMID: 32067523 DOI: 10.1080/14789450.2020.1731309] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne, Switzerland
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A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Syst 2020; 10:133-155.e6. [PMID: 32027860 PMCID: PMC7042714 DOI: 10.1016/j.cels.2020.01.001] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 11/08/2019] [Accepted: 01/10/2020] [Indexed: 12/19/2022]
Abstract
Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins. In proteomic studies, these have been treated as independent entities, disregarding their higher-level organization into complexes that affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell-state-specific changes in the physical arrangement of protein complexes concurrently for thousands of proteins and hundreds of complexes. Applying this technique to a comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and suggest a model of nuclear pore complex disassembly, which we validate by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc. Global quantification of assembly state changes in the mitotic proteome Improved performance over thermostability measurement of proteome states Discovery of a mitotic disassembly intermediate of the nuclear pore complex Introduction of SECexplorer-cc, a publicly available online platform
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50
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Le T, Žárský V, Nývltová E, Rada P, Harant K, Vancová M, Verner Z, Hrdý I, Tachezy J. Anaerobic peroxisomes in Mastigamoeba balamuthi. Proc Natl Acad Sci U S A 2020; 117:2065-2075. [PMID: 31932444 PMCID: PMC6994998 DOI: 10.1073/pnas.1909755117] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The adaptation of eukaryotic cells to anaerobic conditions is reflected by substantial changes to mitochondrial metabolism and functional reduction. Hydrogenosomes belong among the most modified mitochondrial derivative and generate molecular hydrogen concomitant with ATP synthesis. The reduction of mitochondria is frequently associated with loss of peroxisomes, which compartmentalize pathways that generate reactive oxygen species (ROS) and thus protect against cellular damage. The biogenesis and function of peroxisomes are tightly coupled with mitochondria. These organelles share fission machinery components, oxidative metabolism pathways, ROS scavenging activities, and some metabolites. The loss of peroxisomes in eukaryotes with reduced mitochondria is thus not unexpected. Surprisingly, we identified peroxisomes in the anaerobic, hydrogenosome-bearing protist Mastigamoeba balamuthi We found a conserved set of peroxin (Pex) proteins that are required for protein import, peroxisomal growth, and division. Key membrane-associated Pexs (MbPex3, MbPex11, and MbPex14) were visualized in numerous vesicles distinct from hydrogenosomes, the endoplasmic reticulum (ER), and Golgi complex. Proteomic analysis of cellular fractions and prediction of peroxisomal targeting signals (PTS1/PTS2) identified 51 putative peroxisomal matrix proteins. Expression of selected proteins in Saccharomyces cerevisiae revealed specific targeting to peroxisomes. The matrix proteins identified included components of acyl-CoA and carbohydrate metabolism and pyrimidine and CoA biosynthesis, whereas no components related to either β-oxidation or catalase were present. In conclusion, we identified a subclass of peroxisomes, named "anaerobic" peroxisomes that shift the current paradigm and turn attention to the reductive evolution of peroxisomes in anaerobic organisms.
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Affiliation(s)
- Tien Le
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Vojtěch Žárský
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Eva Nývltová
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Petr Rada
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Karel Harant
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Marie Vancová
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, 370 05 České Budějovice, Czech Republic
| | - Zdeněk Verner
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Ivan Hrdý
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic
| | - Jan Tachezy
- Department of Parasitology, Faculty of Science, BIOCEV, Charles University, 25242 Vestec, Czech Republic;
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