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Mehta S, Bernt M, Chambers M, Fahrner M, Föll MC, Gruening B, Horro C, Johnson JE, Loux V, Rajczewski AT, Schilling O, Vandenbrouck Y, Gustafsson OJR, Thang WCM, Hyde C, Price G, Jagtap PD, Griffin TJ. A Galaxy of informatics resources for MS-based proteomics. Expert Rev Proteomics 2023; 20:251-266. [PMID: 37787106 DOI: 10.1080/14789450.2023.2265062] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 09/06/2023] [Indexed: 10/04/2023]
Abstract
INTRODUCTION Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software. AREAS COVERED The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses. EXPERT OPINION The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.
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Affiliation(s)
- Subina Mehta
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Matthias Bernt
- Helmholtz Centre for Environmental Research - UFZ, Department Computational Biology, Leipzig, Germany
| | | | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Bjoern Gruening
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Carlos Horro
- Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - James E Johnson
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Valentin Loux
- Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France
- Université Paris-Saclay, INRAE, BioinfOmics, MIGALE bioinformatics facility, Jouy-en-Josas, France
| | - Andrew T Rajczewski
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - W C Mike Thang
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Cameron Hyde
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Sippy Downs, University of the Sunshine Coast, Australia
| | - Gareth Price
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Pratik D Jagtap
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Timothy J Griffin
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
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Fu Q, Murray CI, Karpov OA, Van Eyk JE. Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis. Mass Spectrom Rev 2023; 42:873-886. [PMID: 34786750 DOI: 10.1002/mas.21750] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 10/11/2021] [Accepted: 10/27/2021] [Indexed: 06/13/2023]
Abstract
Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.
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Affiliation(s)
- Qin Fu
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Oleg A Karpov
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
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Mehta S, Carvalho VM, Rajczewski AT, Pible O, Grüning BA, Johnson JE, Wagner R, Armengaud J, Griffin TJ, Jagtap PD. Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations. Viruses 2022; 14:2205. [PMID: 36298760 PMCID: PMC9609567 DOI: 10.3390/v14102205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/05/2022] Open
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in a major health crisis worldwide with its continuously emerging new strains, resulting in new viral variants that drive "waves" of infection. PCR or antigen detection assays have been routinely used to detect clinical infections; however, the emergence of these newer strains has presented challenges in detection. One of the alternatives has been to detect and characterize variant-specific peptide sequences from viral proteins using mass spectrometry (MS)-based methods. MS methods can potentially help in both diagnostics and vaccine development by understanding the dynamic changes in the viral proteome associated with specific strains and infection waves. In this study, we developed an accessible, flexible, and shareable bioinformatics workflow that was implemented in the Galaxy Platform to detect variant-specific peptide sequences from MS data derived from the clinical samples. We demonstrated the utility of the workflow by characterizing published clinical data from across the world during various pandemic waves. Our analysis identified six SARS-CoV-2 variant-specific peptides suitable for confident detection by MS in commonly collected clinical samples.
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Affiliation(s)
- Subina Mehta
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Andrew T. Rajczewski
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Olivier Pible
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, 30200 Bagnols-sur-Cèze, France
| | - Björn A. Grüning
- Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany
| | - James E. Johnson
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
| | - Reid Wagner
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jean Armengaud
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, 30200 Bagnols-sur-Cèze, France
| | - Timothy J. Griffin
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Pratik D. Jagtap
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
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Lee H, Kim SI. Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases. Int J Mol Sci 2022; 23:ijms23042187. [PMID: 35216306 PMCID: PMC8878692 DOI: 10.3390/ijms23042187] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 02/11/2022] [Accepted: 02/14/2022] [Indexed: 01/27/2023] Open
Abstract
Rapid and precise diagnostic methods are required to control emerging infectious diseases effectively. Human body fluids are attractive clinical samples for discovering diagnostic targets because they reflect the clinical statuses of patients and most of them can be obtained with minimally invasive sampling processes. Body fluids are good reservoirs for infectious parasites, bacteria, and viruses. Therefore, recent clinical proteomics methods have focused on body fluids when aiming to discover human- or pathogen-originated diagnostic markers. Cutting-edge liquid chromatography-mass spectrometry (LC-MS)-based proteomics has been applied in this regard; it is considered one of the most sensitive and specific proteomics approaches. Here, the clinical characteristics of each body fluid, recent tandem mass spectroscopy (MS/MS) data-acquisition methods, and applications of body fluids for proteomics regarding infectious diseases (including the coronavirus disease of 2019 [COVID-19]), are summarized and discussed.
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Affiliation(s)
- Hayoung Lee
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Korea;
- Bio-Analytical Science Division, University of Science and Technology (UST), Daejeon 34113, Korea
| | - Seung Il Kim
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Korea;
- Bio-Analytical Science Division, University of Science and Technology (UST), Daejeon 34113, Korea
- Correspondence:
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Do T, Guran R, Adam V, Zitka O. Use of MALDI-TOF mass spectrometry for virus identification: a review. Analyst 2022; 147:3131-3154. [DOI: 10.1039/d2an00431c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The possibilities of virus identification, including SARS-CoV-2, by MALDI-TOF mass spectrometry are discussed in this review.
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Affiliation(s)
- Tomas Do
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
| | - Roman Guran
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
| | - Vojtech Adam
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
| | - Ondrej Zitka
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
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Guest PC, Zahedipour F, Majeed M, Jamialahmadi T, Sahebkar A. Multiplex Technologies in COVID-19 Research, Diagnostics, and Prognostics: Battling the Pandemic. Methods Mol Biol 2022; 2511:3-20. [PMID: 35838948 DOI: 10.1007/978-1-0716-2395-4_1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Due to continuous technical developments and new insights into the high complexity of infectious diseases such as COVID-19, there is an increasing need for multiplex biomarkers to aid clinical management and support the development of new drugs and vaccines. COVID-19 disease requires rapid diagnosis and stratification to enable the most appropriate treatment course for the best possible outcomes for patients. In addition, these tests should be rapid, specific, and sensitive. They should rule out other potential causes of illness with simultaneous testing for other diseases. Elevated levels of specific biomarkers can be used to establish severity risks of chronic diseases so that patients can be provided the proper medication at the right time. This review describes the state-of-the-art technologies in proteomics, transcriptomics, and metabolomics, for multiplex biomarker approaches in COVID-19 research.
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Affiliation(s)
- Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Fatemeh Zahedipour
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Tannaz Jamialahmadi
- Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Nutrition, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
- School of Medicine, The University of Western Australia, Perth, Australia.
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Abstract
In this article of EBioMedicine, Santosh Renuse and colleagues1 show the relevance of combining immunoaffinity capture with targeted mass spectrometry measurement to detect SARS-CoV-2 nucleocapsid proteins in nasopharyngeal swab samples. The COVID-19 pandemic has confirmed the need to improve the toolbox available to diagnose respiratory infections. Rapid, reliable, and highly specific detection is essential if we are to mount immediate preventive and therapeutic responses. This report stands out from previous studies as it implements immunocapture along with robust validation for a large cohort of subjects. The results presented show that mass spectrometry is definitively at a crossroads for large-scale clinical applications.
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Affiliation(s)
- Jean Armengaud
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, 30200 Bagnols-sur-Cèze, France..
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