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Bohn T, Balbuena E, Ulus H, Iddir M, Wang G, Crook N, Eroglu A. Carotenoids in Health as Studied by Omics-Related Endpoints. Adv Nutr 2023; 14:1538-1578. [PMID: 37678712 PMCID: PMC10721521 DOI: 10.1016/j.advnut.2023.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/25/2023] [Accepted: 09/01/2023] [Indexed: 09/09/2023] Open
Abstract
Carotenoids have been associated with risk reduction for several chronic diseases, including the association of their dietary intake/circulating levels with reduced incidence of obesity, type 2 diabetes, certain types of cancer, and even lower total mortality. In addition to some carotenoids constituting vitamin A precursors, they are implicated in potential antioxidant effects and pathways related to inflammation and oxidative stress, including transcription factors such as nuclear factor κB and nuclear factor erythroid 2-related factor 2. Carotenoids and metabolites may also interact with nuclear receptors, mainly retinoic acid receptor/retinoid X receptor and peroxisome proliferator-activated receptors, which play a role in the immune system and cellular differentiation. Therefore, a large number of downstream targets are likely influenced by carotenoids, including but not limited to genes and proteins implicated in oxidative stress and inflammation, antioxidation, and cellular differentiation processes. Furthermore, recent studies also propose an association between carotenoid intake and gut microbiota. While all these endpoints could be individually assessed, a more complete/integrative way to determine a multitude of health-related aspects of carotenoids includes (multi)omics-related techniques, especially transcriptomics, proteomics, lipidomics, and metabolomics, as well as metagenomics, measured in a variety of biospecimens including plasma, urine, stool, white blood cells, or other tissue cellular extracts. In this review, we highlight the use of omics technologies to assess health-related effects of carotenoids in mammalian organisms and models.
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Affiliation(s)
- Torsten Bohn
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Emilio Balbuena
- Department of Molecular and Structural Biochemistry, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States; Plants for Human Health Institute, North Carolina Research Campus, North Carolina State University, Kannapolis, NC, United States
| | - Hande Ulus
- Plants for Human Health Institute, North Carolina Research Campus, North Carolina State University, Kannapolis, NC, United States
| | - Mohammed Iddir
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Genan Wang
- Department of Chemical and Biomolecular Engineering, College of Engineering, North Carolina State University, Raleigh, NC, United States
| | - Nathan Crook
- Department of Chemical and Biomolecular Engineering, College of Engineering, North Carolina State University, Raleigh, NC, United States
| | - Abdulkerim Eroglu
- Department of Molecular and Structural Biochemistry, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States; Plants for Human Health Institute, North Carolina Research Campus, North Carolina State University, Kannapolis, NC, United States.
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2
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Huttenhower C, Finn RD, McHardy AC. Challenges and opportunities in sharing microbiome data and analyses. Nat Microbiol 2023; 8:1960-1970. [PMID: 37783751 DOI: 10.1038/s41564-023-01484-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 08/28/2023] [Indexed: 10/04/2023]
Abstract
Microbiome data, metadata and analytical workflows have become 'big' in terms of volume and complexity. Although the infrastructure and technologies to share data have been established, the interdisciplinary and multi-omic nature of the field can make resources difficult to identify and use. Following best practices for data deposition requires substantial effort, with sometimes little obvious reward. Gaps remain where microbiome-specific resources for data sharing or reproducibility do not yet exist. We outline available best practices, challenges to their adoption and opportunities in data sharing in microbiome research. We showcase examples of best practices and advocate for their enforcement and incentivization for data sharing. This includes recognition of data curation and sharing endeavours by individuals, institutions, journals and funders. Opportunities for progress include enabling microbiome-specific databases to incorporate future methods for data analysis, integration and reuse.
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Affiliation(s)
- Curtis Huttenhower
- Harvard Chan Microbiome in Public Health Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Departments of Biostatistics and Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Alice Carolyn McHardy
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.
- Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.
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3
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Wu L, Hoque A, Lam H. Spectroscape enables real-time query and visualization of a spectral archive in proteomics. Nat Commun 2023; 14:6267. [PMID: 37805652 PMCID: PMC10560257 DOI: 10.1038/s41467-023-42006-x] [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: 05/26/2023] [Accepted: 09/26/2023] [Indexed: 10/09/2023] Open
Abstract
In proteomics, spectral archives organize the enormous amounts of publicly available peptide tandem mass spectra by similarity, offering opportunities for error correction and novel discoveries. Here we adapt an indexing algorithm developed by Facebook for organizing online multimedia resources to tandem mass spectra and achieve practically instantaneous retrieval and clustering of approximate nearest neighbors in a large spectral archive. An interactive web-based graphical user interface enables the user to view a query spectrum in its clustered neighborhood, which facilitates contextual validation of peptide identifications and exploration of the dark proteome.
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Affiliation(s)
- Long Wu
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
- Department of Electrical and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - Ayman Hoque
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - Henry Lam
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.
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4
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Prokai L, Zaman K, Prokai-Tatrai K. Mass spectrometry-based retina proteomics. MASS SPECTROMETRY REVIEWS 2023; 42:1032-1062. [PMID: 35670041 PMCID: PMC9730434 DOI: 10.1002/mas.21786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.
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Affiliation(s)
- Laszlo Prokai
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Khadiza Zaman
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Katalin Prokai-Tatrai
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
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5
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Mohammed Y, Goodlett D, Borchers CH. Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics. Methods Mol Biol 2023; 2628:557-577. [PMID: 36781806 DOI: 10.1007/978-1-0716-2978-9_32] [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
In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.
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Affiliation(s)
- Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, ZA, Netherlands. .,University of Victoria - Genome BC Proteomics Centre, Victoria, BC, Canada. .,Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada.
| | - David Goodlett
- University of Victoria - Genome BC Proteomics Centre, Victoria, BC, Canada.,Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada.,University of Gdansk, International Centre for Cancer Vaccine Science, Gdansk, Poland
| | - Christoph H Borchers
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.,Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC, Canada.,Division of Experimental Medicine, McGill University, Montreal, QC, Canada.,Department of Pathology, McGill University, Montreal, QC, Canada
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6
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Rehfeldt TG, Krawczyk K, Echers SG, Marcatili P, Palczynski P, Röttger R, Schwämmle V. Variability analysis of LC-MS experimental factors and their impact on machine learning. Gigascience 2022; 12:giad096. [PMID: 37983748 PMCID: PMC10659119 DOI: 10.1093/gigascience/giad096] [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: 04/12/2023] [Revised: 08/23/2023] [Accepted: 10/11/2023] [Indexed: 11/22/2023] Open
Abstract
BACKGROUND Machine learning (ML) technologies, especially deep learning (DL), have gained increasing attention in predictive mass spectrometry (MS) for enhancing the data-processing pipeline from raw data analysis to end-user predictions and rescoring. ML models need large-scale datasets for training and repurposing, which can be obtained from a range of public data repositories. However, applying ML to public MS datasets on larger scales is challenging, as they vary widely in terms of data acquisition methods, biological systems, and experimental designs. RESULTS We aim to facilitate ML efforts in MS data by conducting a systematic analysis of the potential sources of variability in public MS repositories. We also examine how these factors affect ML performance and perform a comprehensive transfer learning to evaluate the benefits of current best practice methods in the field for transfer learning. CONCLUSIONS Our findings show significantly higher levels of homogeneity within a project than between projects, which indicates that it is important to construct datasets most closely resembling future test cases, as transferability is severely limited for unseen datasets. We also found that transfer learning, although it did increase model performance, did not increase model performance compared to a non-pretrained model.
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Affiliation(s)
- Tobias Greisager Rehfeldt
- Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark
| | - Konrad Krawczyk
- Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark
| | | | - Paolo Marcatili
- Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Pawel Palczynski
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark
| | - Richard Röttger
- Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark
| | - Veit Schwämmle
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark
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Knoot CJ, Wantuch PL, Robinson LS, Rosen DA, Scott NE, Harding CM. Discovery and characterization of a new class of O-linking oligosaccharyltransferases from the Moraxellaceae family. Glycobiology 2022; 33:57-74. [PMID: 36239418 PMCID: PMC9829042 DOI: 10.1093/glycob/cwac070] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 01/12/2023] Open
Abstract
Bacterial protein glycosylation is commonly mediated by oligosaccharyltransferases (OTases) that transfer oligosaccharides en bloc from preassembled lipid-linked precursors to acceptor proteins. Natively, O-linking OTases usually transfer a single repeat unit of the O-antigen or capsular polysaccharide to the side chains of serine or threonine on acceptor proteins. Three major families of bacterial O-linking OTases have been described: PglL, PglS, and TfpO. TfpO is limited to transferring short oligosaccharides both in its native context and when heterologously expressed in glycoengineered Escherichia coli. On the other hand, PglL and PglS can transfer long-chain polysaccharides when expressed in glycoengineered E. coli. Herein, we describe the discovery and functional characterization of a novel family of bacterial O-linking OTases termed TfpM from Moraxellaceae bacteria. TfpM proteins are similar in size and sequence to TfpO enzymes but can transfer long-chain polysaccharides to acceptor proteins. Phylogenetic analyses demonstrate that TfpM proteins cluster in distinct clades from known bacterial OTases. Using a representative TfpM enzyme from Moraxella osloensis, we determined that TfpM glycosylates a C-terminal threonine of its cognate pilin-like protein and identified the minimal sequon required for glycosylation. We further demonstrated that TfpM has broad substrate tolerance and can transfer diverse glycans including those with glucose, galactose, or 2-N-acetyl sugars at the reducing end. Last, we find that a TfpM-derived bioconjugate is immunogenic and elicits serotype-specific polysaccharide IgG responses in mice. The glycan substrate promiscuity of TfpM and identification of the minimal TfpM sequon renders this enzyme a valuable additional tool for expanding the glycoengineering toolbox.
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Affiliation(s)
- Cory J Knoot
- Omniose, 4340 Duncan Ave, Suite 202, St. Louis, MO 63110, USA
| | - Paeton L Wantuch
- Department of Pediatrics, Division of Infectious Diseases, Washington University School of Medicine, 4990 Children’s Place, St. Louis, MO 63110, USA
| | | | - David A Rosen
- Department of Pediatrics, Division of Infectious Diseases, Washington University School of Medicine, 4990 Children’s Place, St. Louis, MO 63110, USA,Department of Molecular Microbiology, Washington University School of Medicine, 660 Euclid Ave, St. Louis, MO 63110, USA
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC 3010, Australia
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8
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Perez-Riverol Y. Proteomic repository data submission, dissemination, and reuse: key messages. Expert Rev Proteomics 2022; 19:297-310. [PMID: 36529941 PMCID: PMC7614296 DOI: 10.1080/14789450.2022.2160324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
INTRODUCTION The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public. AREAS COVERED Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed. EXPERT OPINION The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.
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Affiliation(s)
- Yasset Perez-Riverol
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
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9
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Harney DJ, Larance M. Annotated Protein Database Using Known Cleavage Sites for Rapid Detection of Secreted Proteins. J Proteome Res 2022; 21:965-974. [DOI: 10.1021/acs.jproteome.1c00806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Dylan J. Harney
- Charles Perkins Centre and School of Life and Environmental Sciences, University of Sydney, 2006 Sydney, Australia
| | - Mark Larance
- Charles Perkins Centre and School of Life and Environmental Sciences, University of Sydney, 2006 Sydney, Australia
- Charles Perkins Centre and School of Medical Sciences, University of Sydney, 2006 Sydney, Australia
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10
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La Ferlita A, Alaimo S, Ferro A, Pulvirenti A. Pathway Analysis for Cancer Research and Precision Oncology Applications. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1361:143-161. [DOI: 10.1007/978-3-030-91836-1_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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11
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Sharma D, Sharma A, Singh B, Kumar S, Verma S. Neglected scrub typhus: An updated review with a focus on omics technologies. ASIAN PAC J TROP MED 2022. [DOI: 10.4103/1995-7645.364003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
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12
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Ma C, Zeng W, Meng Q, Wang C, Peng Y. Identification of partial denitrification granulation enhanced by low C/N ratio in the aspect of metabolomics and quorum sensing. CHEMOSPHERE 2022; 286:131895. [PMID: 34435576 DOI: 10.1016/j.chemosphere.2021.131895] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 07/18/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
Partial denitrification granular sludge (PDGS) and denitrification granular sludge (DGS) play an important role in nitrogen removal from wastewater. However, the inherent cause of aggregation capacity related to the ratio of COD to nitrogen (COD/N) is still unclear. In this study, metabolomics analysis was combined with microbiological analyses, granular performance and extracellular polymeric substances (EPS) structure to explore the granulation mechanism at different influent COD/N ratios. The results showed that the higher COD/N ratio selectively enhanced the gluconeogenesis pathway, purine and pyrimidine metabolism pathway, resulting in more extracellular polysaccharide (PS) excretion and floc sludge. The absence of carbon source weakened tricarboxylic acid cycle (TCA) reaction, resulting in NAD+ and ADP decrease, nitrite accumulation and change of microbial community structure. The amino acids biosynthesis pathway was enhanced under low COD/N ratio, which promoted the hydrophobicity of EPS. PDGS had stronger Acyl-homoserine lactones (AHLs)-based quorum sensing (QS) than DGS during the operational period. CO8-HSL, C8-HSL and C6-HSL, as the main form of AHLs, played a dominating role in DGS and PDGS. Batch tests illustrated that adding AHLs obviously improved the synthesis of the amino acids, threonine (Thr), tryptophan (Trp), methionine (Met) and glycine (Gly). Dosing AHLs regulated PS synthesis only at a high COD/N ratio. The glucose-6P, glycerate-3p and UDP-Glc were up-regulated only in DSG, which increased the hydrophilic groups in EPS. The results not only provided the new insights into the metabolism of denitrifying granular sludge, but also indicated the application potential of the technologies regarding start-up and operation of granule sludge.
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Affiliation(s)
- Chenyang Ma
- National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Department of Environmental Engineering, Beijing University of Technology, Beijing, 100124, China
| | - Wei Zeng
- National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Department of Environmental Engineering, Beijing University of Technology, Beijing, 100124, China.
| | - Qingan Meng
- National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Department of Environmental Engineering, Beijing University of Technology, Beijing, 100124, China
| | - Chunyan Wang
- National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Department of Environmental Engineering, Beijing University of Technology, Beijing, 100124, China
| | - Yongzhen Peng
- National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Department of Environmental Engineering, Beijing University of Technology, Beijing, 100124, China
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A proteomics sample metadata representation for multiomics integration and big data analysis. Nat Commun 2021; 12:5854. [PMID: 34615866 PMCID: PMC8494749 DOI: 10.1038/s41467-021-26111-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 09/16/2021] [Indexed: 11/08/2022] Open
Abstract
The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.
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14
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Kulyyassov A, Fresnais M, Longuespée R. Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives. Proteomics 2021; 21:e2100153. [PMID: 34591362 DOI: 10.1002/pmic.202100153] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/08/2021] [Accepted: 09/24/2021] [Indexed: 12/25/2022]
Abstract
Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.
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Affiliation(s)
| | - Margaux Fresnais
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
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15
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Methods for Proteomic Analyses of Mycobacteria. Methods Mol Biol 2021. [PMID: 34235669 DOI: 10.1007/978-1-0716-1460-0_23] [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: 09/12/2023]
Abstract
The use of proteomic technologies to characterize and study the proteome of mycobacteria has provided important information in terms of function, diversity, protein-protein interactions, and host-pathogen interactions in Mycobacterium spp. There are many different mass spectrometry methodologies that can be applied to proteomics studies of mycobacteria and microorganisms in general. Sample processing and appropriate study design are critical to generating high-quality data regardless of the mass spectrometry method applied. Appropriate study design relies on statistical rigor and data curation using bioinformatics approaches that are widely applicable regardless of the organism or system studied. Sample processing, on the other hand, is often a niched process specific to the physiology of the organism or system under investigation. Therefore, in this chapter, we will provide protocols for processing mycobacterial protein samples for the specific application of Top-down and Bottom-up proteomic analyses.
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16
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da Silva EMG, Santos LGC, de Oliveira FS, Freitas FCDP, Parreira VDSC, dos Santos HG, Tavares R, Carvalho PC, Neves-Ferreira AGDC, Haibara AS, de Araujo-Souza PS, Dias AAM, Passetti F. Proteogenomics Reveals Orthologous Alternatively Spliced Proteoforms in the Same Human and Mouse Brain Regions with Differential Abundance in an Alzheimer's Disease Mouse Model. Cells 2021; 10:1583. [PMID: 34201730 PMCID: PMC8303486 DOI: 10.3390/cells10071583] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/12/2021] [Accepted: 06/18/2021] [Indexed: 01/19/2023] Open
Abstract
Alternative splicing (AS) may increase the number of proteoforms produced by a gene. Alzheimer's disease (AD) is a neurodegenerative disease with well-characterized AS proteoforms. In this study, we used a proteogenomics strategy to build a customized protein sequence database and identify orthologous AS proteoforms between humans and mice on publicly available shotgun proteomics (MS/MS) data of the corpus callosum (CC) and olfactory bulb (OB). Identical proteotypic peptides of six orthologous AS proteoforms were found in both species: PKM1 (gene PKM/Pkm), STXBP1a (gene STXBP1/Stxbp1), Isoform 3 (gene HNRNPK/Hnrnpk), LCRMP-1 (gene CRMP1/Crmp1), SP3 (gene CADM1/Cadm1), and PKCβII (gene PRKCB/Prkcb). These AS variants were also detected at the transcript level by publicly available RNA-Seq data and experimentally validated by RT-qPCR. Additionally, PKM1 and STXBP1a were detected at higher abundances in a publicly available MS/MS dataset of the AD mouse model APP/PS1 than its wild type. These data corroborate other reports, which suggest that PKM1 and STXBP1a AS proteoforms might play a role in amyloid-like aggregate formation. To the best of our knowledge, this report is the first to describe PKM1 and STXBP1a overexpression in the OB of an AD mouse model. We hope that our strategy may be of use in future human neurodegenerative studies using mouse models.
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Affiliation(s)
- Esdras Matheus Gomes da Silva
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
- Laboratory of Toxinology, Oswaldo Cruz Institute (FIOCRUZ), Av. Brazil 4365, Manguinhos, Rio de Janeiro, RJ 21040-900, Brazil;
| | - Letícia Graziela Costa Santos
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
| | - Flávia Santiago de Oliveira
- Laboratório de Inflamação e Câncer, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Avenida Presidente Antônio Carlos 6627, Pampulha, Belo Horizonte, MG 31270-901, Brazil; (F.S.d.O.); (A.A.M.D.)
| | - Flávia Cristina de Paula Freitas
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
| | - Vinícius da Silva Coutinho Parreira
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
| | - Hellen Geremias dos Santos
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
| | - Raphael Tavares
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Avenida Presidente Antônio Carlos 6627, Pampulha, Belo Horizonte, MG 31270-901, Brazil;
| | - Paulo Costa Carvalho
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
| | | | - Andrea Siqueira Haibara
- Departamento de Fisiologia e Biofísica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Avenida Presidente Antônio Carlos 6627, Pampulha, Belo Horizonte, MG 31270-901, Brazil;
| | - Patrícia Savio de Araujo-Souza
- Laboratory of Immunogenetics and Histocompatibility, Department of Genetics, Universidade Federal do Paraná, Av. Cel. Francisco H. dos Santos 100, Jardim das Américas, Curitiba, PR 81530-980, Brazil;
| | - Adriana Abalen Martins Dias
- Laboratório de Inflamação e Câncer, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Avenida Presidente Antônio Carlos 6627, Pampulha, Belo Horizonte, MG 31270-901, Brazil; (F.S.d.O.); (A.A.M.D.)
| | - Fabio Passetti
- Instituto Carlos Chagas, FIOCRUZ, Rua Professor Algacyr Munhoz Mader 3775, Cidade Industrial De Curitiba, Curitiba, PR 81310-020, Brazil; (E.M.G.d.S.); (L.G.C.S.); (F.C.d.P.F.); (V.d.S.C.P.); (H.G.d.S.); (P.C.C.)
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17
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Damm M, Hempel BF, Süssmuth RD. Old World Vipers-A Review about Snake Venom Proteomics of Viperinae and Their Variations. Toxins (Basel) 2021; 13:toxins13060427. [PMID: 34204565 PMCID: PMC8235416 DOI: 10.3390/toxins13060427] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/11/2021] [Accepted: 06/16/2021] [Indexed: 12/12/2022] Open
Abstract
Fine-tuned by millions of years of evolution, snake venoms have frightened but also fascinated humanity and nowadays they constitute potential resources for drug development, therapeutics and antivenoms. The continuous progress of mass spectrometry techniques and latest advances in proteomics workflows enabled toxinologists to decipher venoms by modern omics technologies, so-called ‘venomics’. A tremendous upsurge reporting on snake venom proteomes could be observed. Within this review we focus on the highly venomous and widely distributed subfamily of Viperinae (Serpentes: Viperidae). A detailed public literature database search was performed (2003–2020) and we extensively reviewed all compositional venom studies of the so-called Old-World Vipers. In total, 54 studies resulted in 89 venom proteomes. The Viperinae venoms are dominated by four major, four secondary, six minor and several rare toxin families and peptides, respectively. The multitude of different venomics approaches complicates the comparison of venom composition datasets and therefore we differentiated between non-quantitative and three groups of quantitative workflows. The resulting direct comparisons within these groups show remarkable differences on the intra- and interspecies level across genera with a focus on regional differences. In summary, the present compilation is the first comprehensive up-to-date database on Viperinae venom proteomes and differentiating between analytical methods and workflows.
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Affiliation(s)
- Maik Damm
- Department of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany;
| | - Benjamin-Florian Hempel
- BIH Center for Regenerative Therapies, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, (BCRT), 10117 Berlin, Germany;
| | - Roderich D. Süssmuth
- Department of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany;
- Correspondence: ; Tel.: +49-(0)30-314-24205
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18
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Schindell BG, Allardice M, Lockman S, Kindrachuk J. Integrating Proteomics for Facilitating Drug Identification and Repurposing During an Emerging Virus Pandemic. ACS Infect Dis 2021; 7:1303-1316. [PMID: 33319978 DOI: 10.1021/acsinfecdis.0c00579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has disrupted global healthcare and economic systems throughout 2020 with no clear end in sight. While the pandemic continues to have deleterious effects across the globe, mechanisms for disrupting disease transmission have relied on behavioral controls (e.g., social distancing, masks, and hygiene) as there are currently no vaccines approved for use and limited therapeutic options. As this pandemic has demonstrated our vulnerability to newly emerging viruses, there has been strong interest in utilizing proteomics approaches to identify targets for repurposed drugs as novel therapeutic candidates that could be fast-tracked for human use. Building on a previous discussion on the combination of proteomics technologies with clinical data for combating emerging viruses, we discuss how these technologies are being employed for COVID-19 and the current state of knowledge regarding repurposed drugs in these efforts.
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Affiliation(s)
- Brayden G. Schindell
- Laboratory of Emerging and Re-Emerging Viruses, Department of Medical Microbiology & Infectious Diseases, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Meagan Allardice
- Laboratory of Emerging and Re-Emerging Viruses, Department of Medical Microbiology & Infectious Diseases, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Sandhini Lockman
- Regenerative Medicine Program, Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Jason Kindrachuk
- Laboratory of Emerging and Re-Emerging Viruses, Department of Medical Microbiology & Infectious Diseases, University of Manitoba, Winnipeg R3T 2N2, Canada
- Vaccine and Infectious Disease Organization−International Vaccine Centre (VIDO-InterVac, University of Saskatchewan, Saskatoon S7N 5E3, Canada
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19
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Borges Lima D, Dupré M, Mariano Santos MD, Carvalho PC, Chamot-Rooke J. DiagnoTop: A Computational Pipeline for Discriminating Bacterial Pathogens without Database Search. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1295-1299. [PMID: 33856212 DOI: 10.1021/jasms.1c00014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Pathogen identification is crucial to confirm bacterial infections and guide antimicrobial therapy. Although MALDI-TOF mass spectrometry (MS) serves as foundation for tools that enable rapid microbial identification, some bacteria remain challenging to identify. We recently showed that top-down proteomics (TDP) could be used to discriminate closely related enterobacterial pathogens (Escherichia coli, Shigella, and Salmonella) that are indistinguishable with tools rooted in the MALDI-TOF MS approach. Current TDP diagnostic relies on the identification of specific proteoforms for each species through a database search. However, microbial proteomes are often poorly annotated, which complicates the large-scale identification of proteoforms and leads to many unidentified high-quality mass spectra. Here, we describe a new computational pipeline called DiagnoTop that lists discriminative spectral clusters found in TDP data sets that can be used for microbial diagnostics without database search. Applied to our enterobacterial TDP data sets, DiagnoTop could easily shortlist high-quality discriminative spectral clusters, leading to increased diagnostic power. This pipeline opens new perspectives in clinical microbiology and biomarker discovery using TDP.
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Affiliation(s)
- Diogo Borges Lima
- Mass Spectrometry for Biology Unit, CNRS USR2000, Institut Pasteur, Paris 75015, France
| | - Mathieu Dupré
- Mass Spectrometry for Biology Unit, CNRS USR2000, Institut Pasteur, Paris 75015, France
| | - Marlon Dias Mariano Santos
- Laboratory for Structural and Computational Proteomics, Carlos Chagas Institute Fiocruz, Paraná, Curitiba CIC 81350-010, Brazil
| | - Paulo Costa Carvalho
- Laboratory for Structural and Computational Proteomics, Carlos Chagas Institute Fiocruz, Paraná, Curitiba CIC 81350-010, Brazil
| | - Julia Chamot-Rooke
- Mass Spectrometry for Biology Unit, CNRS USR2000, Institut Pasteur, Paris 75015, France
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20
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Weber SR, Zhao Y, Gates C, Ma J, da Veiga Leprevost F, Basrur V, Nesvizhskii AI, Gardner TW, Sundstrom JM. Proteomic Analyses of Vitreous in Proliferative Diabetic Retinopathy: Prior Studies and Future Outlook. J Clin Med 2021; 10:jcm10112309. [PMID: 34070658 PMCID: PMC8199452 DOI: 10.3390/jcm10112309] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 05/20/2021] [Accepted: 05/22/2021] [Indexed: 11/16/2022] Open
Abstract
Vitreous fluid is becoming an increasingly popular medium for the study of retinal disease. Numerous studies have demonstrated that proteomic analysis of the vitreous from patients with proliferative diabetic retinopathy yields valuable molecular information regarding known and novel proteins and pathways involved in this disease. However, there is no standardized methodology for vitreous proteomic studies. Here, we share a suggested protocol for such studies and outline the various experimental and analytic methods that are currently available. We also review prior mass spectrometry-based proteomic studies of the vitreous from patients with proliferative diabetic retinopathy, discuss common pitfalls of these studies, and propose next steps for moving the field forward.
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Affiliation(s)
- Sarah R. Weber
- Department of Ophthalmology, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033, USA; (S.R.W.); (Y.Z.)
- Kellogg Eye Center, University of Michigan Medical School, 1000 Wall Street, Ann Arbor, MI 48105, USA;
| | - Yuanjun Zhao
- Department of Ophthalmology, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033, USA; (S.R.W.); (Y.Z.)
| | - Christopher Gates
- Bioinformatics Core, Biomedical Research Core Facilities, University of Michigan Medical School, 2800 Plymouth Road, Ann Arbor, MI 48109, USA;
| | - Jingqun Ma
- Department of Pathology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA;
| | - Felipe da Veiga Leprevost
- Department of Pathology, University of Michigan Medical School, 1301 Catherine Street, Ann Arbor, MI 48109, USA; (F.d.V.L.); (V.B.); (A.I.N.)
| | - Venkatesha Basrur
- Department of Pathology, University of Michigan Medical School, 1301 Catherine Street, Ann Arbor, MI 48109, USA; (F.d.V.L.); (V.B.); (A.I.N.)
| | - Alexey I. Nesvizhskii
- Department of Pathology, University of Michigan Medical School, 1301 Catherine Street, Ann Arbor, MI 48109, USA; (F.d.V.L.); (V.B.); (A.I.N.)
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave, Ann Arbor, MI 48109, USA
| | - Thomas W. Gardner
- Kellogg Eye Center, University of Michigan Medical School, 1000 Wall Street, Ann Arbor, MI 48105, USA;
| | - Jeffrey M. Sundstrom
- Department of Ophthalmology, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033, USA; (S.R.W.); (Y.Z.)
- Kellogg Eye Center, University of Michigan Medical School, 1000 Wall Street, Ann Arbor, MI 48105, USA;
- Correspondence: ; Tel.: +1-717-531-6774
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21
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Enhancing the chondrogenic potential of chondrogenic progenitor cells by deleting RAB5C. iScience 2021; 24:102464. [PMID: 34013174 PMCID: PMC8113995 DOI: 10.1016/j.isci.2021.102464] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 02/24/2021] [Accepted: 04/21/2021] [Indexed: 11/21/2022] Open
Abstract
Osteoarthritis (OA) is the most prevalent chronic joint disease that affects a large proportion of the elderly population. Chondrogenic progenitor cells (CPCs) reside in late-stage OA cartilage tissue, producing a fibrocartilaginous extracellular matrix; these cells can be manipulated in vitro to deposit proteins of healthy articular cartilage. CPCs are under the control of SOX9 and RUNX2. In our earlier studies, we showed that a knockdown of RUNX2 enhanced the chondrogenic potential of CPCs. Here we demonstrate that CPCs carrying a knockout of RAB5C, a protein involved in endosomal trafficking, exhibited elevated expression of multiple chondrogenic markers, including the SOX trio, and increased COL2 deposition, whereas no changes in COL1 deposition were observed. We report RAB5C as an attractive target for future therapeutic approaches designed to increase the COL2 content in the diseased joint.
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22
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Tolani P, Gupta S, Yadav K, Aggarwal S, Yadav AK. Big data, integrative omics and network biology. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2021; 127:127-160. [PMID: 34340766 DOI: 10.1016/bs.apcsb.2021.03.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other metabolic activities of a cell. These networks regulate signal perception and processing that drives biological functions. The biological complexity cannot be fully captured by a single -omics discipline. The holistic study of an organism-in health, perturbation, exposure to environment and disease, is studied under systems biology. The bottom-up molecular approaches (genes, mRNA, protein, metabolite, etc.) have laid the foundation of current biological knowledge covering the horizon from viruses, bacteria, fungi, plants and animals. Yet, these techniques provide a rather myopic view of biology at the molecular level. To understand how the interconnected molecular components are formed and rewired in disease or exposure to environmental stimuli is the holy grail of modern biology. The omics era was heralded by the genomics revolution but advanced sequencing techniques are now also ubiquitous in transcriptomics, proteomics, metabolomics and lipidomics. Multi-omics data analysis and integration techniques are driving the quest for deeper insights into how the different layers of biomolecules talk to each other in diverse contexts.
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Affiliation(s)
- Priya Tolani
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India
| | - Srishti Gupta
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India; School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Kirti Yadav
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India; Department of Pharmaceutical Biotechnology, Delhi Pharmaceutical Sciences and Research University, New Delhi, India
| | - Suruchi Aggarwal
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India; Department of Molecular Biology and Biotechnology, Cotton University, Guwahati, Assam, India
| | - Amit Kumar Yadav
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India.
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23
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Sengupta A, Naresh G, Mishra A, Parashar D, Narad P. Proteome analysis using machine learning approaches and its applications to diseases. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2021; 127:161-216. [PMID: 34340767 DOI: 10.1016/bs.apcsb.2021.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.
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Affiliation(s)
- Abhishek Sengupta
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India
| | - G Naresh
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India
| | - Astha Mishra
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India
| | - Diksha Parashar
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India
| | - Priyanka Narad
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India.
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24
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Bhowmick P, Roome S, Borchers CH, Goodlett DR, Mohammed Y. An Update on MRMAssayDB: A Comprehensive Resource for Targeted Proteomics Assays in the Community. J Proteome Res 2021; 20:2105-2115. [PMID: 33683131 PMCID: PMC8041396 DOI: 10.1021/acs.jproteome.0c00961] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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Precise multiplexed
quantification of proteins in biological samples
can be achieved by targeted proteomics using multiple or parallel
reaction monitoring (MRM/PRM). Combined with internal standards, the
method achieves very good repeatability and reproducibility enabling
excellent protein quantification and allowing longitudinal and cohort
studies. A laborious part of performing such experiments lies in the
preparation steps dedicated to the development and validation of individual
protein assays. Several public repositories host information on targeted
proteomics assays, including NCI’s Clinical Proteomic Tumor
Analysis Consortium assay portals, PeptideAtlas SRM Experiment Library,
SRMAtlas, PanoramaWeb, and PeptideTracker, with all offering varying
levels of details. We introduced MRMAssayDB in 2018 as an integrated
resource for targeted proteomics assays. The Web-based application
maps and links the assays from the repositories, includes comprehensive
up-to-date protein and sequence annotations, and provides multiple
visualization options on the peptide and protein level. We have extended
MRMAssayDB with more assays and extensive annotations. Currently it
contains >828 000 assays covering >51 000 proteins
from
94 organisms, of which >17 000 proteins are present in >2400
biological pathways, and >48 000 mapping to >21 000
Gene Ontology terms. This is an increase of about four times the number
of assays since introduction. We have expanded annotations of interaction,
biological pathways, and disease associations. A newly added visualization
module for coupled molecular structural annotation browsing allows
the user to interactively examine peptide sequence and any known PTMs
and disease mutations, and map all to available protein 3D structures.
Because of its integrative approach, MRMAssayDB enables a holistic
view of suitable proteotypic peptides and commonly used transitions
in empirical data. Availability: http://mrmassaydb.proteincentre.com.
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Affiliation(s)
- Pallab Bhowmick
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada.,University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | - Simon Roome
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada.,University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | - Christoph H Borchers
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada.,Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, Quebec H3T 1E2, Canada.,Department of Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Nobel Street, Moscow 121205, Russia
| | - David R Goodlett
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada.,University of Victoria, Victoria, British Columbia V8P 5C2, Canada.,University of Gdansk, International Centre for Cancer Vaccine Science, 80-309 Gdansk, Poland
| | - Yassene Mohammed
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada.,University of Victoria, Victoria, British Columbia V8P 5C2, Canada.,Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, Netherlands
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25
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Improving Exposure Assessment Using Non-Targeted and Suspect Screening: The ISO/IEC 17025: 2017 Quality Standard as a Guideline. J Xenobiot 2021; 11:1-15. [PMID: 33530331 PMCID: PMC7838891 DOI: 10.3390/jox11010001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/13/2021] [Accepted: 01/21/2021] [Indexed: 01/27/2023] Open
Abstract
The recent advances of novel methodologies such as non-targeted and suspect screening based on high-resolution mass spectrometry (HRMS) have paved the way to a new paradigm for exposure assessment. These methodologies allow to profile simultaneously thousands of small unknown molecules present in environmental and biological samples, and therefore hold great promises in order to identify more efficiently hazardous contaminants potentially associated with increased risks of developing adverse health outcomes. In order to further explore the potential of these methodologies and push the transition from research applications towards regulatory purposes, robust harmonized quality standards have to be implemented. Here, we discuss the feasibility of using ISO/IEC 17025: 2017 as a guideline to implement non-targeted and suspect screening methodologies in laboratories, whether it is for accreditation purposes or not. More specifically, we identified and then discussed how specificities of non-targeted HRMS methodology can be accounted for in order to comply with the specific items of ISO/IEC 17025: 2017. We also discussed other specificities of HRMS methodologies (e.g., need for digital storage capacity) that are so far not included in the ISO/IEC 17025 requirements but should be considered. This works aims to fuel and expand the discussion in order to subsidize new opportunities of harmonization for non-targeted and suspect screening.
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26
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Role of Bioinformatics in Biological Sciences. Adv Bioinformatics 2021. [DOI: 10.1007/978-981-33-6191-1_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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27
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Freire MS, Oliveira NG, Lima SMF, Porto WF, Martins DCM, Silva ON, Chaves SB, Sousa MV, Ricart CAO, Castro MS, Fontes W, Franco OL, Rezende TMB. IL-4 absence triggers distinct pathways in apical periodontitis development. J Proteomics 2020; 233:104080. [PMID: 33338687 DOI: 10.1016/j.jprot.2020.104080] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/17/2020] [Accepted: 12/12/2020] [Indexed: 12/18/2022]
Abstract
Dental pulp is a specialized tissue able to respond to infectious processes. Nevertheless, infection progress and root canal colonization trigger an immune-inflammatory response in tooth-surrounding tissues, leading to apical periodontitis and bone tissue destruction, further contributing to tooth loss. In order to shed some light on the effects of IL-4 on periradicular pathology development modulation, microtomographic, histological and proteomic analyses were performed using 60 mice, 30 wild type and 30 IL-4-/-. For that, 5 animals were used for microtomographic and histological analysis, and another 5 for proteomic analysis for 0, 7 and 21 days with/without pulp exposure. The periapical lesions were established in WT and IL-4-/- mice without statistical differences in their volume, and the value of p < 0.05 was adopted as significant in microtomographic and histological analyses. Regarding histological analysis, IL-4-/- mice show aggravation of pulp inflammation compared to WT. By using proteomic analysis, we have identified 32 proteins with increased abundance and 218 proteins with decreased abundance in WT animals after 21 days of pulp exposure, compared to IL-4-/- animals. However, IL-4-/- mice demonstrated faster development of apical periodontitis. These animals developed a compensatory mechanism to overcome IL-4 absence, putatively based on the identification of upregulated proteins related to immune system signaling pathways. Significance: IL-4 might play a protective role in diseases involving bone destruction and its activity may contribute to host protection, mainly due to its antiosteoclastogenic action.
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Affiliation(s)
- Mirna S Freire
- Programa de Pós-Graduação em Biotecnologia e Biodiversidade, Universidade de Brasília, Brasília, DF, Brazil; Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Curso de Odontologia, Centro Universitário do Planalto Central Apparecido dos Santos, UNICEPLAC, Brasília, DF, Brazil
| | - Nelson G Oliveira
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil
| | - Stella M F Lima
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Curso de Odontologia, Universidade Católica de Brasília, UCB, Brasília, DF, Brazil
| | - William F Porto
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Porto Reports, Brasília, DF, Brazil
| | - Danilo C M Martins
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Programa de Pós-Graduação em Ciências da Saúde, Faculdade de Ciências da Saúde, Universidade de Brasília, UnB, Brasília, DF, Brazil
| | - Osmar N Silva
- Programa de Pós-graduacao em Ciências Farmacêuticas. Centro Universitário de Anápolis - UniEVANGELICA, Anápolis, GO, Brazil
| | - Sacha B Chaves
- Departamento de nanotecnologia, Universidade de Brasília, Brazil
| | - Marcelo V Sousa
- Laboratório de Bioquímica e Química de Proteínas, Departamento de Biologia Celular, Universidade de Brasília, Brazil
| | - Carlos A O Ricart
- Laboratório de Bioquímica e Química de Proteínas, Departamento de Biologia Celular, Universidade de Brasília, Brazil
| | - Mariana S Castro
- Laboratório de Bioquímica e Química de Proteínas, Departamento de Biologia Celular, Universidade de Brasília, Brazil
| | - Wagner Fontes
- Laboratório de Bioquímica e Química de Proteínas, Departamento de Biologia Celular, Universidade de Brasília, Brazil
| | - Octavio L Franco
- Programa de Pós-Graduação em Biotecnologia e Biodiversidade, Universidade de Brasília, Brasília, DF, Brazil; Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Programa de Pós-Graduação em Ciências da Saúde, Faculdade de Ciências da Saúde, Universidade de Brasília, UnB, Brasília, DF, Brazil; Programa de Pós-Graduação em Patologia Molecular, Universidade de Brasília, Brasília, DF, Brazil.
| | - Taia M B Rezende
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil; Curso de Odontologia, Universidade Católica de Brasília, UCB, Brasília, DF, Brazil; Programa de Pós-Graduação em Ciências da Saúde, Faculdade de Ciências da Saúde, Universidade de Brasília, UnB, Brasília, DF, Brazil.
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Weis C, Jutzeler C, Borgwardt K. Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review. Clin Microbiol Infect 2020; 26:1310-1317. [DOI: 10.1016/j.cmi.2020.03.014] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/05/2020] [Accepted: 03/13/2020] [Indexed: 01/12/2023]
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29
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Do QT, Huang TE, Liu YC, Tai JH, Chen SH. Identification of Cytosolic Protein Targets of Catechol Estrogens in Breast Cancer Cells Using a Click Chemistry-Based Workflow. J Proteome Res 2020; 20:624-633. [PMID: 32951420 DOI: 10.1021/acs.jproteome.0c00578] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Catechol estrogens (CEs) are known to be toxic metabolites and the initiators of the oncogenesis of breast cancers via forming covalent adducts with DNAs. CEs shall also react with proteins, but their cellular protein targets remain unexplored. Here, we reported the identification of protein targets of CEs in the soluble cytosol of estrogen-sensitive breast cancer cells by multiple comparative proteomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with an improved click chemistry-based workflow. Multiple comparative proteomics composed of an experimental pair (probe versus solvent) and two control pairs (solvent versus solvent and probe versus solvent without enrichment) were studied using stable isotope dimethyl labeling. The use of 4-hydroxyethynylestradiol (4OHEE2) probe with an amide-free linker coupled with on-bead digestion and redigestion of the proteins cleaved from the beads was shown to greatly improve the recovery and identification of CE-adducted peptides. A total of 310 protein targets and 40 adduction sites were repeatedly (n ≥ 2) identified with D/H (probe/solvent) ratio >4 versus only one identified with D/H >4 from the two control pairs, suggesting that our workflow imposes only a very low background. Meanwhile, multiple comparative D/H ratios revealed that CEs may downregulate many target proteins involved in the metabolism or detoxification, suggesting a negative correlation between CE-induced adduction and expression of proteins acting on the alleviation of stress-induced cellular damages. The reported method and data will provide opportunities to study the progression of estrogen metabolism-derived diseases and biomarkers.
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Affiliation(s)
- Quynh-Trang Do
- Department of Chemistry, National Cheng Kung University, Tainan 701, Taiwan
| | - Ting-En Huang
- Department of Chemistry, National Cheng Kung University, Tainan 701, Taiwan
| | - Yi-Chen Liu
- Department of Chemistry, National Cheng Kung University, Tainan 701, Taiwan
| | - Jung-Hsiang Tai
- Division of Infectious Diseases and Immunology, Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan
| | - Shu-Hui Chen
- Department of Chemistry, National Cheng Kung University, Tainan 701, Taiwan
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30
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Shamsaei B, Chojnacki S, Pilarczyk M, Najafabadi M, Niu W, Chen C, Ross K, Matlock A, Muhlich J, Chutipongtanate S, Zheng J, Turner J, Vidović D, Jaffe J, MacCoss M, Wu C, Pillai A, Ma'ayan A, Schürer S, Kouril M, Medvedovic M, Meller J. piNET: a versatile web platform for downstream analysis and visualization of proteomics data. Nucleic Acids Res 2020; 48:W85-W93. [PMID: 32469073 PMCID: PMC7319557 DOI: 10.1093/nar/gkaa436] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 04/29/2020] [Accepted: 05/27/2020] [Indexed: 02/03/2023] Open
Abstract
Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. Several interconnected workflows can be used to generate: (i) interactive graphs and tables providing comprehensive annotation and mapping between peptides and proteins with PTM sites; (ii) high resolution and interactive visualization for enzyme-substrate networks, including kinases and their phospho-peptide targets; (iii) mapping and visualization of LINCS signature connectivity for chemical inhibitors or genetic knockdown of enzymes upstream of their target PTM sites. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool. The Apache Lucene indexing is used for fast mapping of peptides into UniProt entries for the human, mouse and other commonly used model organism proteomes. PTM-centric network analyses combine PhosphoSitePlus, iPTMnet and SIGNOR databases of validated enzyme-substrate relationships, for kinase networks augmented by DeepPhos predictions and sequence-based mapping of PhosphoSitePlus consensus motifs. Concordant LINCS signatures are mapped using iLINCS. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. The server is available at http://pinet-server.org, and it is free and open to all users without login requirement.
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Affiliation(s)
- Behrouz Shamsaei
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA
| | - Szymon Chojnacki
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA
| | - Marcin Pilarczyk
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA
| | - Mehdi Najafabadi
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA
| | - Wen Niu
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA
| | - Chuming Chen
- Center for Bioinformatics & Computational Biology; University of Delaware, USA
| | - Karen Ross
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, USA
| | - Andrea Matlock
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, USA
| | - Jeremy Muhlich
- Department of Systems Biology, Harvard Medical School, USA
| | - Somchai Chutipongtanate
- Department of Cancer Biology, University of Cincinnati College of Medicine, USA.,Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand
| | - Jie Zheng
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, USA
| | - John Turner
- Department of Pharmacology, Miller School of Medicine, Sylvester Comprehensive Cancer Center, Center for Computational Science, University of Miami, Miami, USA
| | - Dušica Vidović
- Department of Pharmacology, Miller School of Medicine, Sylvester Comprehensive Cancer Center, Center for Computational Science, University of Miami, Miami, USA
| | - Jake Jaffe
- Broad Institute of MIT and Harvard & Inzen Therapeutics, USA
| | - Michael MacCoss
- Department of Genome Sciences, University of Washington, USA
| | - Cathy Wu
- Center for Bioinformatics & Computational Biology; University of Delaware, USA.,Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, USA
| | - Ajay Pillai
- Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Avi Ma'ayan
- Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, USA
| | - Stephan Schürer
- Department of Pharmacology, Miller School of Medicine, Sylvester Comprehensive Cancer Center, Center for Computational Science, University of Miami, Miami, USA
| | - Michal Kouril
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, USA
| | - Mario Medvedovic
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA.,Department of Biomedical Informatics, University of Cincinnati College of Medicine, USA
| | - Jarek Meller
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, USA.,Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, USA.,Department of Electrical Engineering and Computer Science, University of Cincinnati, USA
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31
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Santiago PB, Charneau S, Mandacaru SC, Bentes KLDS, Bastos IMD, de Sousa MV, Ricart CAO, de Araújo CN, Santana JM. Proteomic Mapping of Multifunctional Complexes Within Triatomine Saliva. Front Cell Infect Microbiol 2020; 10:459. [PMID: 32984079 PMCID: PMC7492717 DOI: 10.3389/fcimb.2020.00459] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 07/27/2020] [Indexed: 11/26/2022] Open
Abstract
Triatomines are hematophagous insects that transmit Trypanosoma cruzi, the etiological agent of Chagas disease. This neglected tropical disease represents a global health issue as it is spreading worldwide. The saliva of Triatominae contains miscellaneous proteins crucial for blood feeding acquisition, counteracting host's hemostasis while performing vasodilatory, anti-platelet and anti-coagulant activities, besides modulating inflammation and immune responses. Since a set of biological processes are mediated by protein complexes, here, the sialocomplexomes (salivary protein complexes) of five species of Triatominae were studied to explore the protein-protein interaction networks. Salivary multiprotein complexes from Triatoma infestans, Triatoma dimidiata, Dipetalogaster maxima, Rhodnius prolixus, and Rhodnius neglectus were investigated by Blue-Native- polyacrylamide gel electrophoresis coupled with liquid chromatography tandem mass spectrometry. More than 70 protein groups, uncovering the landscape of the Triatominae salivary interactome, were revealed. Triabin, actin, thioredoxin peroxidase and an uncharacterized protein were identified in sialocomplexes of the five species, while hexamerin, heat shock protein and histone were identified in sialocomplexes of four species. Salivary proteins related to triatomine immunity as well as those required during blood feeding process such as apyrases, antigen 5, procalins, and nitrophorins compose different complexes. Furthermore, unique proteins for each triatomine species were revealed. This study represents the first Triatominae sialocomplexome reference to date and shows that the approach used is a reliable tool for the analysis of Triatominae salivary proteins assembled into complexes.
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Affiliation(s)
- Paula Beatriz Santiago
- Pathogen-Host Interface Laboratory, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Sébastien Charneau
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Samuel Coelho Mandacaru
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Kaio Luís da Silva Bentes
- Pathogen-Host Interface Laboratory, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | | | - Marcelo Valle de Sousa
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Carlos André O Ricart
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Carla Nunes de Araújo
- Pathogen-Host Interface Laboratory, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
| | - Jaime Martins Santana
- Pathogen-Host Interface Laboratory, Department of Cell Biology, The University of Brasilia, Brasilia, Brazil
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32
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Tahir M, Arshid S, Fontes B, S. Castro M, Sidoli S, Schwämmle V, Luz IS, Roepstorff P, Fontes W. Phosphoproteomic Analysis of Rat Neutrophils Shows the Effect of Intestinal Ischemia/Reperfusion and Preconditioning on Kinases and Phosphatases. Int J Mol Sci 2020; 21:ijms21165799. [PMID: 32823483 PMCID: PMC7460855 DOI: 10.3390/ijms21165799] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 03/11/2020] [Accepted: 04/17/2020] [Indexed: 01/02/2023] Open
Abstract
Intestinal ischemia reperfusion injury (iIRI) is a severe clinical condition presenting high morbidity and mortality worldwide. Some of the systemic consequences of IRI can be prevented by applying ischemic preconditioning (IPC), a series of short ischemia/reperfusion events preceding the major ischemia. Although neutrophils are key players in the pathophysiology of ischemic injuries, neither the dysregulation presented by these cells in iIRI nor the protective effect of iIPC have their regulation mechanisms fully understood. Protein phosphorylation, as well as the regulation of the respective phosphatases and kinases are responsible for regulating a large number of cellular functions in the inflammatory response. Moreover, in previous work we found hydrolases and transferases to be modulated in iIR and iIPC, suggesting the possible involvement of phosphatases and kinases in the process. Therefore, in the present study, we analyzed the phosphoproteome of neutrophils from rats submitted to mesenteric ischemia and reperfusion, either submitted or not to IPC, compared to quiescent controls and sham laparotomy. Proteomic analysis was performed by multi-step enrichment of phosphopeptides, isobaric labeling, and LC-MS/MS analysis. Bioinformatics was used to determine phosphosite and phosphopeptide abundance and clustering, as well as kinases and phosphatases sites and domains. We found that most of the phosphorylation-regulated proteins are involved in apoptosis and migration, and most of the regulatory kinases belong to CAMK and CMGC families. An interesting finding revealed groups of proteins that are modulated by iIR, but such modulation can be prevented by iIPC. Among the regulated proteins related to the iIPC protective effect, Vamp8 and Inpp5d/Ship are discussed as possible candidates for control of the iIR damage.
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Affiliation(s)
- Muhammad Tahir
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia 70910-900, Brazil; (M.T.); (S.A.); (M.S.C.); (I.S.L.)
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark; (S.S.); (V.S.); (P.R.)
| | - Samina Arshid
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia 70910-900, Brazil; (M.T.); (S.A.); (M.S.C.); (I.S.L.)
- Laboratory of Surgical Physiopathology (LIM-62), Faculty of Medicine, University of São Paulo, São Paulo 01246903, Brazil;
| | - Belchor Fontes
- Laboratory of Surgical Physiopathology (LIM-62), Faculty of Medicine, University of São Paulo, São Paulo 01246903, Brazil;
| | - Mariana S. Castro
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia 70910-900, Brazil; (M.T.); (S.A.); (M.S.C.); (I.S.L.)
| | - Simone Sidoli
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark; (S.S.); (V.S.); (P.R.)
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Veit Schwämmle
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark; (S.S.); (V.S.); (P.R.)
| | - Isabelle S. Luz
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia 70910-900, Brazil; (M.T.); (S.A.); (M.S.C.); (I.S.L.)
| | - Peter Roepstorff
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark; (S.S.); (V.S.); (P.R.)
| | - Wagner Fontes
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia 70910-900, Brazil; (M.T.); (S.A.); (M.S.C.); (I.S.L.)
- Correspondence:
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33
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Sulakhe D, D'Souza M, Wang S, Balasubramanian S, Athri P, Xie B, Canzar S, Agam G, Gilliam TC, Maltsev N. Exploring the functional impact of alternative splicing on human protein isoforms using available annotation sources. Brief Bioinform 2020; 20:1754-1768. [PMID: 29931155 DOI: 10.1093/bib/bby047] [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] [Received: 01/19/2018] [Revised: 05/02/2018] [Indexed: 12/30/2022] Open
Abstract
In recent years, the emphasis of scientific inquiry has shifted from whole-genome analyses to an understanding of cellular responses specific to tissue, developmental stage or environmental conditions. One of the central mechanisms underlying the diversity and adaptability of the contextual responses is alternative splicing (AS). It enables a single gene to encode multiple isoforms with distinct biological functions. However, to date, the functions of the vast majority of differentially spliced protein isoforms are not known. Integration of genomic, proteomic, functional, phenotypic and contextual information is essential for supporting isoform-based modeling and analysis. Such integrative proteogenomics approaches promise to provide insights into the functions of the alternatively spliced protein isoforms and provide high-confidence hypotheses to be validated experimentally. This manuscript provides a survey of the public databases supporting isoform-based biology. It also presents an overview of the potential global impact of AS on the human canonical gene functions, molecular interactions and cellular pathways.
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Affiliation(s)
- Dinanath Sulakhe
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Computation Institute, University of Chicago, 5735 S. Ellis Avenue, Chicago, IL, USA
| | - Mark D'Souza
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA
| | - Sheng Wang
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Toyota Technological Institute at Chicago, 6045 S. Kenwood Avenue, Chicago, IL, USA
| | - Sandhya Balasubramanian
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Genentech, Inc. 1 DNA Way, Mail Stop: 35-6J, South San Francisco, CA, USA
| | - Prashanth Athri
- Department of Computer Science and Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, Kasavanahalli, Carmelaram P.O., Bengaluru, Karnataka, India
| | - Bingqing Xie
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA
| | - Stefan Canzar
- Toyota Technological Institute at Chicago, 6045 S. Kenwood Avenue, Chicago, IL, USA.,Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gady Agam
- Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA
| | - T Conrad Gilliam
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Computation Institute, University of Chicago, 5735 S. Ellis Avenue, Chicago, IL, USA
| | - Natalia Maltsev
- Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, USA.,Computation Institute, University of Chicago, 5735 S. Ellis Avenue, Chicago, IL, USA
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34
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Cipollo JF, Parsons LM. Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships. MASS SPECTROMETRY REVIEWS 2020; 39:371-409. [PMID: 32350911 PMCID: PMC7318305 DOI: 10.1002/mas.21629] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 04/01/2020] [Accepted: 04/05/2020] [Indexed: 05/21/2023]
Abstract
The advancement of viral glycomics has paralleled that of the mass spectrometry glycomics toolbox. In some regard the glycoproteins studied have provided the impetus for this advancement. Viral proteins are often highly glycosylated, especially those targeted by the host immune system. Glycosylation tends to be dynamic over time as viruses propagate in host populations leading to increased number of and/or "movement" of glycosylation sites in response to the immune system and other pressures. This relationship can lead to highly glycosylated, difficult to analyze glycoproteins that challenge the capabilities of modern mass spectrometry. In this review, we briefly discuss five general areas where glycosylation is important in the viral niche and how mass spectrometry has been used to reveal key information regarding structure-function relationships between viral glycoproteins and host cells. We describe the recent past and current glycomics toolbox used in these analyses and give examples of how the requirement to analyze these complex glycoproteins has provided the incentive for some advances seen in glycomics mass spectrometry. A general overview of viral glycomics, special cases, mass spectrometry methods and work-flows, informatics and complementary chemical techniques currently used are discussed. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.
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Affiliation(s)
- John F. Cipollo
- Center for Biologics Evaluation and Research, Food and Drug AdministrationSilver SpringMaryland
| | - Lisa M. Parsons
- Center for Biologics Evaluation and Research, Food and Drug AdministrationSilver SpringMaryland
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35
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de Sousa Neto IV, Tibana RA, da Silva LGDO, de Lira EM, do Prado GPG, de Almeida JA, Franco OL, Durigan JLQ, Adesida AB, de Sousa MV, Ricart CAO, Damascena HL, Castro MS, Fontes W, Prestes J, Marqueti RDC. Paternal Resistance Training Modulates Calcaneal Tendon Proteome in the Offspring Exposed to High-Fat Diet. Front Cell Dev Biol 2020; 8:380. [PMID: 32656202 PMCID: PMC7325979 DOI: 10.3389/fcell.2020.00380] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 04/27/2020] [Indexed: 12/27/2022] Open
Abstract
The increase in high-energy dietary intakes is a well-known risk factor for many diseases, and can also negatively impact the tendon. Ancestral lifestyle can mitigate the metabolic harmful effects of offspring exposed to high-fat diet (HF). However, the influence of paternal exercise on molecular pathways associated to offspring tendon remodeling remains to be determined. We investigated the effects of 8 weeks of paternal resistance training (RT) on offspring tendon proteome exposed to standard diet or HF diet. Wistar rats were randomly divided into two groups: sedentary fathers and trained fathers (8 weeks, three times per week, with 8–12 dynamic movements per climb in a stair climbing apparatus). The offspring were obtained by mating with sedentary females. Upon weaning, male offspring were divided into four groups (five animals per group): offspring from sedentary fathers were exposed either to control diet (SFO-C), or to high-fat diet (SFO-HF); offspring from trained fathers were exposed to control diet (TFO-C) or to a high-fat diet (TFO-HF). The Nano-LC-MS/MS analysis revealed 383 regulated proteins among offspring groups. HF diet induced a decrease of abundance in tendon proteins related to extracellular matrix organization, transport, immune response and translation. On the other hand, the changes in the offspring tendon proteome in response to paternal RT were more pronounced when the offspring were exposed to HF diet, resulting in positive regulation of proteins essential for the maintenance of tendon integrity. Most of the modulated proteins are associated to biological pathways related to tendon protection and damage recovery, such as extracellular matrix organization and transport. The present study demonstrated that the father’s lifestyle could be crucial for tendon homeostasis in the first generation. Our results provide important insights into the molecular mechanisms involved in paternal intergenerational effects and potential protective outcomes of paternal RT.
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Affiliation(s)
- Ivo Vieira de Sousa Neto
- Laboratory of Molecular Analysis, Graduate Program of Sciences and Technology of Health, Universidade de Brasília, Distrito Federal, Brazil
| | - Ramires Alsamir Tibana
- Graduate Program of Physical Education, Universidade Católica de Brasília, Distrito Federal, Brazil.,Graduate Program in Health Sciences, Universidade Federal do Mato Grosso, Cuiabá, Brazil
| | | | - Eliene Martins de Lira
- Laboratory of Molecular Analysis, Graduate Program of Sciences and Technology of Health, Universidade de Brasília, Distrito Federal, Brazil
| | - Gleyce Pires Gonçalves do Prado
- Laboratory of Molecular Analysis, Graduate Program of Sciences and Technology of Health, Universidade de Brasília, Distrito Federal, Brazil
| | - Jeeser Alves de Almeida
- Graduate Program in Health and Development in the Midwest Region, Faculty of Medicine, Universidade Federal do Mato Grosso do Sul, Campo Grande, Brazil.,Research in Exercise and Nutrition in Health and Sports Performance-PENSARE, Graduate Program in Movement Sciences, Universidade Federal do Mato Grosso do Sul, Campo Grande, Brazil
| | - Octavio Luiz Franco
- Center for Proteomic and Biochemical Analyses, Graduate Program in Genomic Sciences and Biotechnology, Universidade Católicade Brasília, Distrito Federal, Brazil.,S-Inova Biotech, Graduate Program in Biotechnology, Universidade Católica Dom Bosco, Campo Grande, Brazil
| | - João Luiz Quaglioti Durigan
- Laboratory of Molecular Analysis, Graduate Program of Sciences and Technology of Health, Universidade de Brasília, Distrito Federal, Brazil
| | - Adetola B Adesida
- University of Alberta, Divisions of Orthopaedic Surgery and Surgical Research, Edmonton, AB, Canada
| | - Marcelo Valle de Sousa
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biological Sciences, Universidade de Brasília, Distrito Federal, Brazil
| | - Carlos André Ornelas Ricart
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biological Sciences, Universidade de Brasília, Distrito Federal, Brazil
| | - Hylane Luiz Damascena
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biological Sciences, Universidade de Brasília, Distrito Federal, Brazil
| | - Mariana S Castro
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biological Sciences, Universidade de Brasília, Distrito Federal, Brazil
| | - Wagner Fontes
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biological Sciences, Universidade de Brasília, Distrito Federal, Brazil
| | - Jonato Prestes
- Graduate Program of Physical Education, Universidade Católica de Brasília, Distrito Federal, Brazil
| | - Rita de Cassia Marqueti
- Laboratory of Molecular Analysis, Graduate Program of Sciences and Technology of Health, Universidade de Brasília, Distrito Federal, Brazil
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36
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Vasconcellos AF, Mandacaru SC, de Oliveira AS, Fontes W, Melo RM, de Sousa MV, Resende RO, Charneau S. Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus. Parasit Vectors 2020; 13:297. [PMID: 32522239 PMCID: PMC7285477 DOI: 10.1186/s13071-020-04167-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 06/02/2020] [Indexed: 12/25/2022] Open
Abstract
Background Mayaro virus (MAYV) is responsible for a mosquito-borne tropical disease with clinical symptoms similar to dengue or chikungunya virus fevers. In addition to the recent territorial expansion of MAYV, this virus may be responsible for an increasing number of outbreaks. Currently, no vaccine is available. Aedes aegypti is promiscuous in its viral transmission and thus an interesting model to understand MAYV-vector interactions. While the life-cycle of MAYV is known, the mechanisms by which this arbovirus affects mosquito host cells are not clearly understood. Methods After defining the best conditions for cell culture harvesting using the highest virus titer, Ae. aegypti Aag-2 cells were infected with a Brazilian MAYV isolate at a MOI of 1 in order to perform a comparative proteomic analysis of MAYV-infected Aag-2 cells by using a label-free semi-quantitative bottom-up proteomic analysis. Time-course analyses were performed at 12 and 48 h post-infection (hpi). After spectrum alignment between the triplicates of each time point and changes of the relative abundance level calculation, the identified proteins were annotated and using Gene Ontology database and protein pathways were annotated using the Kyoto Encyclopedia of Genes and Genomes. Results After three reproducible biological replicates, the total proteome analysis allowed for the identification of 5330 peptides and the mapping of 459, 376 and 251 protein groups, at time 0, 12 hpi and 48 hpi, respectively. A total of 161 mosquito proteins were found to be differentially abundant during the time-course, mostly related to host cell processes, including redox metabolism, translation, energy metabolism, and host cell defense. MAYV infection also increased host protein expression implicated in viral replication. Conclusions To our knowledge, this first proteomic time-course analysis of MAYV-infected mosquito cells sheds light on the molecular basis of the viral infection process and host cell response during the first 48 hpi. Our data highlight several mosquito proteins modulated by the virus, revealing that MAYV manipulates mosquito cell metabolism for its propagation.![]()
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Affiliation(s)
- Anna Fernanda Vasconcellos
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil.,Laboratory of Virology, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Samuel Coelho Mandacaru
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Athos Silva de Oliveira
- Laboratory of Virology, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Wagner Fontes
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Reynaldo Magalhães Melo
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Marcelo Valle de Sousa
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil
| | - Renato Oliveira Resende
- Laboratory of Virology, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil.
| | - Sébastien Charneau
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia, Brasilia, DF, 70910-900, Brazil.
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Moriya Y, Kawano S, Okuda S, Watanabe Y, Matsumoto M, Takami T, Kobayashi D, Yamanouchi Y, Araki N, Yoshizawa AC, Tabata T, Iwasaki M, Sugiyama N, Tanaka S, Goto S, Ishihama Y. The jPOST environment: an integrated proteomics data repository and database. Nucleic Acids Res 2020; 47:D1218-D1224. [PMID: 30295851 PMCID: PMC6324006 DOI: 10.1093/nar/gky899] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 09/24/2018] [Indexed: 01/13/2023] Open
Abstract
Rapid progress is being made in mass spectrometry (MS)-based proteomics, yielding an increasing number of larger datasets with higher quality and higher throughput. To integrate proteomics datasets generated from various projects and institutions, we launched a project named jPOST (Japan ProteOme STandard Repository/Database, https://jpostdb.org/) in 2015. Its proteomics data repository, jPOSTrepo, began operations in 2016 and has accepted more than 10 TB of MS-based proteomics datasets in the past two years. In addition, we have developed a new proteomics database named jPOSTdb in which the published raw datasets in jPOSTrepo are reanalyzed using standardized protocol. jPOSTdb provides viewers showing the frequency of detected post-translational modifications, the co-occurrence of phosphorylation sites on a peptide and peptide sharing among proteoforms. jPOSTdb also provides basic statistical analysis tools to compare proteomics datasets.
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Affiliation(s)
- Yuki Moriya
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa 277-0871, Japan
| | - Shin Kawano
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa 277-0871, Japan
| | - Shujiro Okuda
- Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8510, Japan
| | - Yu Watanabe
- Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8510, Japan
| | - Masaki Matsumoto
- Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan
| | - Tomoyo Takami
- Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan
| | - Daiki Kobayashi
- Graduate School of Medical Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto 860-8556, Japan
| | - Yoshinori Yamanouchi
- Graduate School of Medical Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto 860-8556, Japan.,Kumamoto University Hospital, Kumamoto 860-8556, Japan
| | - Norie Araki
- Graduate School of Medical Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto 860-8556, Japan
| | - Akiyasu C Yoshizawa
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Tsuyoshi Tabata
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan.,Center for iPS Cell Research and Application, Kyoto University, Kyoto 606-8507, Japan
| | - Mio Iwasaki
- Center for iPS Cell Research and Application, Kyoto University, Kyoto 606-8507, Japan
| | - Naoyuki Sugiyama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | | | - Susumu Goto
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa 277-0871, Japan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
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38
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Ambrosino L, Colantuono C, Diretto G, Fiore A, Chiusano ML. Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era. PLANTS 2020; 9:plants9050591. [PMID: 32384671 PMCID: PMC7285221 DOI: 10.3390/plants9050591] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 04/24/2020] [Accepted: 04/29/2020] [Indexed: 12/13/2022]
Abstract
Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.
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Affiliation(s)
- Luca Ambrosino
- Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici (Na), Italy; (L.A.); (C.C.)
- Department of Research Infrastructures for Marine Biological Resources (RIMAR), 80121 Naples, Italy
| | - Chiara Colantuono
- Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici (Na), Italy; (L.A.); (C.C.)
- Department of Research Infrastructures for Marine Biological Resources (RIMAR), 80121 Naples, Italy
| | - Gianfranco Diretto
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), 00123 Rome, Italy; (G.D.); (A.F.)
| | - Alessia Fiore
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), 00123 Rome, Italy; (G.D.); (A.F.)
| | - Maria Luisa Chiusano
- Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici (Na), Italy; (L.A.); (C.C.)
- Department of Research Infrastructures for Marine Biological Resources (RIMAR), 80121 Naples, Italy
- Correspondence: ; Tel.: +39-081-253-9492
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39
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Verheggen K, Raeder H, Berven FS, Martens L, Barsnes H, Vaudel M. Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows. MASS SPECTROMETRY REVIEWS 2020; 39:292-306. [PMID: 28902424 DOI: 10.1002/mas.21543] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Accepted: 07/05/2017] [Indexed: 06/07/2023]
Abstract
Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines.
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Affiliation(s)
- Kenneth Verheggen
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biochemistry, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Helge Raeder
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Frode S Berven
- Proteomics Unit, Department of Biomedicine, University of Bergen, Norway
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biochemistry, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Harald Barsnes
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
- Proteomics Unit, Department of Biomedicine, University of Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway
| | - Marc Vaudel
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
- Proteomics Unit, Department of Biomedicine, University of Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
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40
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Hu GM, Secario MK, Chen CM. SeQuery: an interactive graph database for visualizing the GPCR superfamily. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2019:5522636. [PMID: 31236561 PMCID: PMC6591535 DOI: 10.1093/database/baz073] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/28/2019] [Accepted: 05/16/2019] [Indexed: 01/01/2023]
Abstract
The rate at which new protein and gene sequences are being discovered has grown explosively in the omics era, which has increasingly complicated the efficient characterization and analysis of their biological properties. In this study, we propose a web-based graphical database tool, SeQuery, for intuitively visualizing proteome/genome networks by integrating the sequential, structural and functional information of sequences. As a demonstration of our tool’s effectiveness, we constructed a graph database of G protein-coupled receptor (GPCR) sequences by integrating data from the UniProt, GPCRdb and RCSB PDB databases. Our tool attempts to achieve two goals: (i) given the sequence of a query protein, correctly and efficiently identify whether the protein is a GPCR, and, if so, define its sequential and functional roles in the GPCR superfamily; and (ii) present a panoramic view of the GPCR superfamily and its network centralities that allows users to explore the superfamily at various resolutions. Such a bottom-up-to-top-down view can provide the users with a comprehensive understanding of the GPCR superfamily through interactive navigation of the graph database. A test of SeQuery with the GPCR2841 dataset shows that it correctly identifies 99 out of 100 queried protein sequences. The developed tool is readily applicable to other biological networks, and we aim to expand SeQuery by including additional biological databases in the near future.
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Affiliation(s)
- Geng-Ming Hu
- Department of Physics, National Taiwan Normal University, 88 Sec. 4 Ting-Chou Rd., Taipei 11677, Taiwan
| | - M K Secario
- Department of Physics, National Taiwan Normal University, 88 Sec. 4 Ting-Chou Rd., Taipei 11677, Taiwan.,Department of Applied Chemistry, National Chiao Tung University, 1001 Ta Hsueh Rd., Hsinchu 300, Taiwan
| | - Chi-Ming Chen
- Department of Physics, National Taiwan Normal University, 88 Sec. 4 Ting-Chou Rd., Taipei 11677, Taiwan
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41
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Gelman H, Dines JN, Berg J, Berger AH, Brnich S, Hisama FM, James RG, Rubin AF, Shendure J, Shirts B, Fowler DM, Starita LM. Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation. Genome Med 2019; 11:85. [PMID: 31862013 PMCID: PMC6925490 DOI: 10.1186/s13073-019-0698-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 11/20/2019] [Indexed: 01/31/2023] Open
Abstract
Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.
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Affiliation(s)
- Hannah Gelman
- Department of Genome Sciences, University of Washington School of Medicine, 15th Avenue NE, Seattle, WA, 98195, USA
- Current affiliation: Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, S Columbian Way, Seattle, WA, 98108, USA
| | - Jennifer N Dines
- Department of Genome Sciences, University of Washington School of Medicine, 15th Avenue NE, Seattle, WA, 98195, USA
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Current affiliation: Adaptive Biotechnologies, Eastlake Avenue E, Seattle, WA, 98102, USA
| | - Jonathan Berg
- Department of Genetics, University of North Carolina at Chapel Hill,, Mason Farm Road, Chapel Hill, NC, 27514, USA
| | - Alice H Berger
- Human Biology Division, Fred Hutchinson Cancer Research Center, Fairview Avenue, Seattle, WA, 98109, USA
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA
| | - Sarah Brnich
- Department of Genetics, University of North Carolina at Chapel Hill,, Mason Farm Road, Chapel Hill, NC, 27514, USA
| | - Fuki M Hisama
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA
| | - Richard G James
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA
- Department of Pediatrics, University of Washington School of Medicine, NE Pacific Street, Seattle, WA, 98195, USA
- Center for Immunity and Immunotherapies, Seattle Children, Research Institute, Ninth Avenue, Seattle, WA, 98145, USA
| | - Alan F Rubin
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Royal Parade, Parkville, VIC, 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, 3010, Australia
- Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, Grattan Street, Melbourne, VIC, 3000, Australia
| | - Jay Shendure
- Department of Genome Sciences, University of Washington School of Medicine, 15th Avenue NE, Seattle, WA, 98195, USA
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA
- Howard Hughes Medical Institute, Pacific Street, Seattle, WA, 98195, USA
| | - Brian Shirts
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA
- Department of Laboratory Medicine, University of Washington School of Medicine, NE Pacific Street, Seattle, WA, 98195, USA
| | - Douglas M Fowler
- Department of Genome Sciences, University of Washington School of Medicine, 15th Avenue NE, Seattle, WA, 98195, USA.
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA.
- Department of Bioengineering, University of Washington, 15th Avenue NE, Seattle, WA, 98195, USA.
| | - Lea M Starita
- Department of Genome Sciences, University of Washington School of Medicine, 15th Avenue NE, Seattle, WA, 98195, USA.
- Brotman Baty Institute for Precision Medicine, NE Pacific Street, Seattle, WA, 98195, USA.
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42
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Hulstaert N, Shofstahl J, Sachsenberg T, Walzer M, Barsnes H, Martens L, Perez-Riverol Y. ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. J Proteome Res 2019; 19:537-542. [PMID: 31755270 DOI: 10.1021/acs.jproteome.9b00328] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The field of computational proteomics is approaching the big data age, driven both by a continuous growth in the number of samples analyzed per experiment as well as by the growing amount of data obtained in each analytical run. In order to process these large amounts of data, it is increasingly necessary to use elastic compute resources such as Linux-based cluster environments and cloud infrastructures. Unfortunately, the vast majority of cross-platform proteomics tools are not able to operate directly on the proprietary formats generated by the diverse mass spectrometers. Here, we present ThermoRawFileParser, an open-source, cross-platform tool that converts Thermo RAW files into open file formats such as MGF and the HUPO-PSI standard file format mzML. To ensure the broadest possible availability and to increase integration capabilities with popular workflow systems such as Galaxy or Nextflow, we have also built Conda package and BioContainers container around ThermoRawFileParser. In addition, we implemented a user-friendly interface (ThermoRawFileParserGUI) for those users not familiar with command-line tools. Finally, we performed a benchmark of ThermoRawFileParser and msconvert to verify that the converted mzML files contain reliable quantitative results.
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Affiliation(s)
- Niels Hulstaert
- VIB-UGent Center for Medical Biotechnology, VIB , Ghent B-9000 , Belgium.,Department of Biomolecular Medicine , Ghent University , Ghent B-9000 , Belgium
| | - Jim Shofstahl
- Thermo Fisher Scientific , 355 River Oaks Parkway , San Jose , California 95134 , United States
| | - Timo Sachsenberg
- Applied Bioinformatics, Department for Computer Science , University of Tuebingen , Sand 14 , 72076 Tuebingen , Germany
| | - Mathias Walzer
- European Molecular Biology Laboratory , European Bioinformatics Institute (EMBL-EBI) , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , United Kingdom
| | - Harald Barsnes
- Computational Biology Unit (CBU), Department of Informatics , University of Bergen , Bergen 5020 , Norway.,Proteomics Unit (PROBE), Department of Biomedicine , University of Bergen , Bergen 5020 , Norway
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB , Ghent B-9000 , Belgium.,Department of Biomolecular Medicine , Ghent University , Ghent B-9000 , Belgium
| | - Yasset Perez-Riverol
- European Molecular Biology Laboratory , European Bioinformatics Institute (EMBL-EBI) , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , United Kingdom
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Elguoshy A, Hirao Y, Yamamoto K, Xu B, Kinoshita N, Mitsui T, Yamamoto T. Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM. J Proteome Res 2019; 18:4197-4205. [PMID: 31646870 DOI: 10.1021/acs.jproteome.9b00355] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.
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Affiliation(s)
- Amr Elguoshy
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan.,Graduate School of Science and Technology , Niigata University , Niigata 950-2181 , Japan.,Biotechnology Department, Faculty of Agriculture , Al-Azhar University , Cairo 11651 , Egypt
| | - Yoshitoshi Hirao
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan
| | - Keiko Yamamoto
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan
| | - Bo Xu
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan
| | - Naohiko Kinoshita
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan.,Department of Health Informatics , Niigata University of Health and Welfare , Niigata 950-3102 , Japan
| | - Toshiaki Mitsui
- Graduate School of Science and Technology , Niigata University , Niigata 950-2181 , Japan
| | - Tadashi Yamamoto
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences , Niigata University , Niigata 950-2181 , Japan.,Department of Clinical Laboratory , Shinrakuen Hospital , Niigata 950-2087 , Japan
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44
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Noor Z, Ranganathan S. Bioinformatics approaches for improving seminal plasma proteome analysis. Theriogenology 2019; 137:43-49. [PMID: 31186128 DOI: 10.1016/j.theriogenology.2019.05.036] [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: 10/26/2022]
Abstract
Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.
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Affiliation(s)
- Zainab Noor
- Department of Molecular Sciences, Macquarie University, Sydney, Australia
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, Australia.
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45
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Chen SH, Li CW. Detection and Characterization of Catechol Quinone-Derived Protein Adducts Using Biomolecular Mass Spectrometry. Front Chem 2019; 7:571. [PMID: 31497592 PMCID: PMC6712063 DOI: 10.3389/fchem.2019.00571] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Accepted: 07/29/2019] [Indexed: 12/14/2022] Open
Abstract
The catechol quinone (CQ) motif is present in many biologically relevant molecules throughout endogenous metabolic products, foods, drugs, and environmental pollutants. The CQ derivatives may undergo Michael addition, and has been shown to yield covalent bonds with nucleophilic sites of cysteine, lysine, or histidine residue of proteins. The CQ-adducted proteins may exhibit cytotoxicity or biological functions different from their un-adducted forms. Identification, characterization, and quantification of relevant protein targets are essential but challenging goals. Mass spectrometry (MS) is well-suited for the analysis of proteins and protein modifications. Technical development of bottom-up proteomics has greatly advanced the field of biomolecular MS, including protein adductomics. This mini-review focuses on the use of biomolecular MS in (1) structural and functional characterization of CQ adduction on standards of proteins, (2) identification of endogenous adduction targets, and (3) quantification of adducted blood proteins as exposure index. The reactivity and outcome of CQ adduction are discussed with emphases on endogenous species, such as dopamine and catechol estrogens. Limitations and advancements in sample preparation, MS instrumentation, and software to facilitate protein adductomics are also discussed.
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Affiliation(s)
- Shu-Hui Chen
- Department of Chemistry, National Cheng Kung University, Tainan, Taiwan
| | - Chun-Wei Li
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
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46
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Schmidt T, Samaras P, Frejno M, Gessulat S, Barnert M, Kienegger H, Krcmar H, Schlegl J, Ehrlich HC, Aiche S, Kuster B, Wilhelm M. ProteomicsDB. Nucleic Acids Res 2019; 46:D1271-D1281. [PMID: 29106664 PMCID: PMC5753189 DOI: 10.1093/nar/gkx1029] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 10/22/2017] [Indexed: 01/01/2023] Open
Abstract
ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC–MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein–protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically.
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Affiliation(s)
- Tobias Schmidt
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Patroklos Samaras
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Martin Frejno
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Siegfried Gessulat
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany.,Innovation Center Network, SAP SE, Potsdam 14469, Germany
| | - Maximilian Barnert
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | - Harald Kienegger
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | - Helmut Krcmar
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | | | | | - Stephan Aiche
- Innovation Center Network, SAP SE, Potsdam 14469, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany.,Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
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47
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Brademan DR, Riley NM, Kwiecien NW, Coon JJ. Interactive Peptide Spectral Annotator: A Versatile Web-based Tool for Proteomic Applications. Mol Cell Proteomics 2019; 18:S193-S201. [PMID: 31088857 PMCID: PMC6692776 DOI: 10.1074/mcp.tir118.001209] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 03/21/2019] [Indexed: 11/06/2022] Open
Abstract
Here we present IPSA, an innovative web-based spectrum annotator that visualizes and characterizes peptide tandem mass spectra. A tool for the scientific community, IPSA can visualize peptides collected using a wide variety of experimental and instrumental configurations. Annotated spectra are customizable via a selection of interactive features and can be exported as editable scalable vector graphics to aid in the production of publication-quality figures. Single spectra can be analyzed through provided web forms, whereas data for multiple peptide spectral matches can be uploaded using the Proteomics Standards Initiative file formats mzTab, mzIdentML, and mzML. Alternatively, peptide identifications and spectral data can be provided using generic file formats. IPSA provides supports for annotating spectra collecting using negative-mode ionization and facilitates the characterization of experimental MS/MS performance through the optional export of fragment ion statistics from one to many peptide spectral matches. This resource is made freely accessible at http://interactivepeptidespectralannotator.com, whereas the source code and user guides are available at https://github.com/coongroup/IPSA for private hosting or custom implementations.
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Affiliation(s)
- Dain R Brademan
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706; Genome Center of Wisconsin, Madison, WI 53706
| | - Nicholas M Riley
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706; Genome Center of Wisconsin, Madison, WI 53706
| | - Nicholas W Kwiecien
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706; Genome Center of Wisconsin, Madison, WI 53706
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706; Morgridge Institute for Research, Madison, WI 53715; Genome Center of Wisconsin, Madison, WI 53706; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53706.
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48
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Abstract
The amount of omics data in the public domain is increasing every year. Modern science has become a data-intensive discipline. Innovative solutions for data management, data sharing, and for discovering novel datasets are therefore increasingly required. In 2016, we released the first version of the Omics Discovery Index (OmicsDI) as a light-weight system to aggregate datasets across multiple public omics data resources. OmicsDI aggregates genomics, transcriptomics, proteomics, metabolomics and multiomics datasets, as well as computational models of biological processes. Here, we propose a set of novel metrics to quantify the attention and impact of biomedical datasets. A complete framework (now integrated into OmicsDI) has been implemented in order to provide and evaluate those metrics. Finally, we propose a set of recommendations for authors, journals and data resources to promote an optimal quantification of the impact of datasets. Increasing amount of public omics data are important and valuable resources for the research community. Here, the authors develop a set of metrics to quantify the attention and impact of biomedical datasets and integrate them into the framework of Omics Discovery Index (OmicsDI).
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49
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Blonder N, Orsburn BC, Blonder J, Gonzalez CA. Visual mass-spec share (vMS-Share): a new public web-based mass spectrometry visualization and data mining repository. ACTA ACUST UNITED AC 2019; 12. [PMID: 31274965 DOI: 10.4172/0974-276x.1000495] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Herein we introduce the Visual Mass-Spec Share (vMS-Share), a new public mass spectrometric (MS) repository and data mining website/resource freely accessible at https://vmsshare.nist.gov. vMS-Share is a web-based application developed for instant visualization of raw MS data with integrated display of metadata optimized for the sharing of proteomics and metabolomics experimental results. Each MS-based identification is linked to a given experiment and the entire experimental data can then be viewed using the link associated with a given peptide and/or small molecule. Interactive and user-friendly visualizations are provided to the user via variety of easily accessible search filters.
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Affiliation(s)
- Niksa Blonder
- Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8380, United States
| | | | - Josip Blonder
- Cancer Research Technology Program, Antibody Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, United States
| | - Carlos A Gonzalez
- Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8380, United States
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50
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Figeac N, Mohamed AD, Sun C, Schönfelder M, Matallanas D, Garcia-Munoz A, Missiaglia E, Collie-Duguid E, De Mello V, Pobbati AV, Pruller J, Jaka O, Harridge SDR, Hong W, Shipley J, Vargesson N, Zammit PS, Wackerhage H. VGLL3 operates via TEAD1, TEAD3 and TEAD4 to influence myogenesis in skeletal muscle. J Cell Sci 2019; 132:jcs.225946. [PMID: 31138678 PMCID: PMC6633393 DOI: 10.1242/jcs.225946] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 05/03/2019] [Indexed: 12/21/2022] Open
Abstract
VGLL proteins are transcriptional co-factors that bind TEAD family transcription factors to regulate events ranging from wing development in fly, to muscle fibre composition and immune function in mice. Here, we characterise Vgll3 in skeletal muscle. We found that mouse Vgll3 was expressed at low levels in healthy muscle but that its levels increased during hypertrophy or regeneration; in humans, VGLL3 was highly expressed in tissues from patients with various muscle diseases, such as in dystrophic muscle and alveolar rhabdomyosarcoma. Interaction proteomics revealed that VGLL3 bound TEAD1, TEAD3 and TEAD4 in myoblasts and/or myotubes. However, there was no interaction with proteins from major regulatory systems such as the Hippo kinase cascade, unlike what is found for the TEAD co-factors YAP (encoded by YAP1) and TAZ (encoded by WWTR1). Vgll3 overexpression reduced the activity of the Hippo negative-feedback loop, affecting expression of muscle-regulating genes including Myf5, Pitx2 and Pitx3, and genes encoding certain Wnts and IGFBPs. VGLL3 mainly repressed gene expression, regulating similar genes to those regulated by YAP and TAZ. siRNA-mediated Vgll3 knockdown suppressed myoblast proliferation, whereas Vgll3 overexpression strongly promoted myogenic differentiation. However, skeletal muscle was overtly normal in Vgll3-null mice, presumably due to feedback signalling and/or redundancy. This work identifies VGLL3 as a transcriptional co-factor operating with the Hippo signal transduction network to control myogenesis. Summary: VGLL3 interacts with TEAD transcription factors to direct expression of crucial muscle regulatory genes and contribute to the control of skeletal myogenesis.
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Affiliation(s)
- Nicolas Figeac
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK
| | - Abdalla D Mohamed
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK.,Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Munich/Neuherberg, Germany
| | - Congshan Sun
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK.,Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Martin Schönfelder
- Faculty of Sport and Health Sciences, Technical University of Munich, Georg-Brauchle-Ring 60, 80992 Munich, Germany
| | - David Matallanas
- Systems Biology Ireland, Conway Institute, Belfield; Dublin 4, Ireland
| | | | - Edoardo Missiaglia
- Institute of Pathology, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
| | - Elaina Collie-Duguid
- University of Aberdeen, Centre for Genome Enabled Biology and Medicine, 23 St Machar Drive, Aberdeen AB24 3RY, UK
| | - Vanessa De Mello
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Ajaybabu V Pobbati
- Institute of Molecular and Cell Biology, A-STAR, 61 Biopolis Drive, Singapore 138673, Singapore
| | - Johanna Pruller
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK
| | - Oihane Jaka
- Centre for Human and Applied Physiological Sciences, King's College London, London SE1 1UL, UK
| | - Stephen D R Harridge
- Centre for Human and Applied Physiological Sciences, King's College London, London SE1 1UL, UK
| | - Wanjin Hong
- Institute of Molecular and Cell Biology, A-STAR, 61 Biopolis Drive, Singapore 138673, Singapore
| | - Janet Shipley
- Sarcoma Molecular Pathology Team, Divisions of Molecular Pathology and Cancer Therapeutics, Institute of Cancer Research, Surrey, SM2 5NG, UK
| | - Neil Vargesson
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Peter S Zammit
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK
| | - Henning Wackerhage
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK .,Faculty of Sport and Health Sciences, Technical University of Munich, Georg-Brauchle-Ring 60, 80992 Munich, Germany
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