1
|
Fedorov II, Protasov SA, Tarasova IA, Gorshkov MV. Ultrafast Proteomics. BIOCHEMISTRY. BIOKHIMIIA 2024; 89:1349-1361. [PMID: 39245450 DOI: 10.1134/s0006297924080017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 09/10/2024]
Abstract
Current stage of proteomic research in the field of biology, medicine, development of new drugs, population screening, or personalized approaches to therapy dictates the need to analyze large sets of samples within the reasonable experimental time. Until recently, mass spectrometry measurements in proteomics were characterized as unique in identifying and quantifying cellular protein composition, but low throughput, requiring many hours to analyze a single sample. This was in conflict with the dynamics of changes in biological systems at the whole cellular proteome level upon the influence of external and internal factors. Thus, low speed of the whole proteome analysis has become the main factor limiting developments in functional proteomics, where it is necessary to annotate intracellular processes not only in a wide range of conditions, but also over a long period of time. Enormous level of heterogeneity of tissue cells or tumors, even of the same type, dictates the need to analyze biological systems at the level of individual cells. These studies involve obtaining molecular characteristics for tens, if not hundreds of thousands of individual cells, including their whole proteome profiles. Development of mass spectrometry technologies providing high resolution and mass measurement accuracy, predictive chromatography, new methods for peptide separation by ion mobility and processing of proteomic data based on artificial intelligence algorithms have opened a way for significant, if not radical, increase in the throughput of whole proteome analysis and led to implementation of the novel concept of ultrafast proteomics. Work done just in the last few years has demonstrated the proteome-wide analysis throughput of several hundred samples per day at a depth of several thousand proteins, levels unimaginable three or four years ago. The review examines background of these developments, as well as modern methods and approaches that implement ultrafast analysis of the entire proteome.
Collapse
Affiliation(s)
- Ivan I Fedorov
- Moscow Institute of Physics and Technology (National University), Dolgoprudny, Moscow Region, 141700, Russia
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Sergey A Protasov
- Moscow Institute of Physics and Technology (National University), Dolgoprudny, Moscow Region, 141700, Russia
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Irina A Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia.
| |
Collapse
|
2
|
Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| |
Collapse
|
3
|
Sing JC, Charkow J, AlHigaylan M, Horecka I, Xu L, Röst HL. MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization. J Proteome Res 2024. [PMID: 38684072 DOI: 10.1021/acs.jproteome.4c00026] [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: 05/02/2024]
Abstract
With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m/z, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.
Collapse
Affiliation(s)
- Justin C Sing
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| | - Joshua Charkow
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| | - Mohammed AlHigaylan
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| | - Ira Horecka
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| | - Leon Xu
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| | - Hannes L Röst
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario M5G 1A8, Canada
| |
Collapse
|
4
|
Alves MF, Katchborian-Neto A, Bueno PCP, Carnevale-Neto F, Casoti R, Ferreira MS, Murgu M, de Paula ACC, Dias DF, Soares MG, Chagas-Paula DA. LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case. RSC Adv 2024; 14:10481-10498. [PMID: 38567345 PMCID: PMC10985591 DOI: 10.1039/d4ra01384k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.
Collapse
Affiliation(s)
- Matheus Fernandes Alves
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Albert Katchborian-Neto
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Paula Carolina Pires Bueno
- Leibniz Institute of Vegetable and Ornamental Crops (IGZ) Theodor-Echtermeyer-Weg 1 14979 Großbeeren Germany
| | - Fausto Carnevale-Neto
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington 850 Republican Street Seattle Washington 98109 USA
| | - Rosana Casoti
- Antibiotics Department, Federal University of Pernambuco 50670-901 Recife Pernambuco Brazil
| | - Miller Santos Ferreira
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Michael Murgu
- Waters Corporation Alameda Tocantins 125, Alphaville 06455-020 São Paulo Brazil
| | | | - Danielle Ferreira Dias
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Marisi Gomes Soares
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | | |
Collapse
|
5
|
White MEH, Sinn LR, Jones DM, de Folter J, Aulakh SK, Wang Z, Flynn HR, Krüger L, Tober-Lau P, Demichev V, Kurth F, Mülleder M, Blanchard V, Messner CB, Ralser M. Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics. Nat Biomed Eng 2024; 8:233-247. [PMID: 37474612 DOI: 10.1038/s41551-023-01067-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.
Collapse
Affiliation(s)
- Matthew E H White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ludwig R Sinn
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - D Marc Jones
- Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
| | - Joost de Folter
- Software Engineering and Artificial Intelligence Technology Platform, The Francis Crick Institute, London, UK
| | - Simran Kaur Aulakh
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ziyue Wang
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Helen R Flynn
- Mass Spectrometry Proteomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Lynn Krüger
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Pinkus Tober-Lau
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vadim Demichev
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Florian Kurth
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High-throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Véronique Blanchard
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Christoph B Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Precision Proteomic Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland.
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
- Max Planck Institute for Molecular Genetics, Berlin, Germany.
| |
Collapse
|
6
|
Steigerwald S, Sinha A, Fort KL, Zeng WF, Niu L, Wichmann C, Kreutzmann A, Mourad D, Aizikov K, Grinfeld D, Makarov A, Mann M, Meier F. Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis. Mol Cell Proteomics 2024; 23:100713. [PMID: 38184013 PMCID: PMC10851225 DOI: 10.1016/j.mcpro.2024.100713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 01/08/2024] Open
Abstract
Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.
Collapse
Affiliation(s)
- Sophia Steigerwald
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ankit Sinha
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Kyle L Fort
- Thermo Fisher Scientific (GmbH), Bremen, Germany
| | - Wen-Feng Zeng
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lili Niu
- Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Christoph Wichmann
- Department Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | | | | | | | | | - Matthias Mann
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Florian Meier
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Functional Proteomics, Jena University Hospital, Jena, Germany.
| |
Collapse
|
7
|
Schulze B, Heffernan AL, Gomez Ramos MJ, Thomas KV, Kaserzon SL. Influence of extraction windows for data-independent acquisition on feature annotation during suspect screening. CHEMOSPHERE 2024; 349:140697. [PMID: 37972864 DOI: 10.1016/j.chemosphere.2023.140697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/08/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
Non-target analysis (NTA) using high-resolution mass spectrometry is becoming a useful approach to screen for suspect and unknown chemicals. For comprehensive analyses, data-independent acquisition (DIA), like Sequential Windowed Acquisition of all THeoretical Mass Spectra (SWATH-MS) on Sciex instruments, is necessary, usually followed by library matching for feature annotation. The choice of parameters, such as acquisition window number and size, may influence the comprehensiveness of the suspect features detected. The goal of this study was to assess how mass spectrometric DIA settings may influence the ability to obtain confident annotations and identifications of features in environmental (river water, passive sample extract (PSE)), wastewater (unpreserved and acidified) and biological (urine) sample matrices. Each matrix was analysed using 11 different MS methods, with 5-15 variable size acquisition windows. True positive (TP) annotation (i.e., matching experimental and library spectra) rates were constant for PSE (40%) and highest for urine (18%), wastewater (34% and 36%, unpreserved and acidified, respectively) and river water (8%) when using higher numbers of windows (15). The number of annotated features was highest for PSE (12%) and urine (8.5%) when using more acquisition windows (9 and 14, respectively). Less complex matrices (based on average total ion chromatogram intensities) like river water, unpreserved and acidified wastewater have higher annotation rates (7.5%, 8% and 13.2%, respectively) when using less acquisition windows (5-6), indicating matrix dependency of optimum settings. Library scores varied widely for correct (scores between 6 and 100) as well as incorrect annotations (scores between 2 and 100), making it hard to define specific ideal cut-off values. Results highlight the need for properly curated libraries and careful optimization of SWATH-MS and other DIA methods for each individual matrix, finding the best ratio of total annotations to true positive, (i.e., correct) annotations to achieve best NTA results.
Collapse
Affiliation(s)
- Bastian Schulze
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia.
| | - Amy L Heffernan
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
| | - Maria Jose Gomez Ramos
- Chemistry and Physics Department, University of Almeria, Agrifood Campus of International Excellence (ceiA3), 04120, Almería, Spain
| | - Kevin V Thomas
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
| | - Sarit L Kaserzon
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
| |
Collapse
|
8
|
Lou R, Shui W. Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023. Mol Cell Proteomics 2024; 23:100712. [PMID: 38182042 PMCID: PMC10847697 DOI: 10.1016/j.mcpro.2024.100712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/27/2023] [Accepted: 01/02/2024] [Indexed: 01/07/2024] Open
Abstract
Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.
Collapse
Affiliation(s)
- Ronghui Lou
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
| |
Collapse
|
9
|
Chatterjee S, Zaia J. Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples. MASS SPECTROMETRY REVIEWS 2024; 43:193-229. [PMID: 36177493 PMCID: PMC9538640 DOI: 10.1002/mas.21813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 05/12/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.
Collapse
Affiliation(s)
- Sayantani Chatterjee
- Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Joseph Zaia
- Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University School of Medicine, Boston, Massachusetts, USA
- Bioinformatics Program, Boston University School of Medicine, Boston, Massachusetts, USA
| |
Collapse
|
10
|
Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. MASS SPECTROMETRY REVIEWS 2023; 42:2324-2348. [PMID: 35645145 DOI: 10.1002/mas.21781] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/17/2021] [Accepted: 01/21/2022] [Indexed: 06/15/2023]
Abstract
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
Collapse
Affiliation(s)
| | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
| |
Collapse
|
11
|
Karaaslan Z, Şengül-Yediel B, Yüceer-Korkmaz H, Şanlı E, Gezen-Ak D, Dursun E, Timirci-Kahraman Ö, Baykal AT, Yılmaz V, Türkoğlu R, Kürtüncü M, Gündüz T, Gürsoy-Özdemir Y, Tüzün E, İsmail Küçükali C. Chloride intracellular channel protein-1 (CLIC1) antibody in multiple sclerosis patients with predominant optic nerve and spinal cord involvement. Mult Scler Relat Disord 2023; 78:104940. [PMID: 37603930 DOI: 10.1016/j.msard.2023.104940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 07/31/2023] [Accepted: 08/12/2023] [Indexed: 08/23/2023]
Abstract
INTRODUCTION Antibodies to cell surface proteins of astrocytes have been described in chronic inflammatory demyelinating disorders (CIDD) of the central nervous system including multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Our aim was to identify novel anti-astrocyte autoantibodies in relapsing remitting MS (RRMS) patients presenting predominantly with spinal cord and optic nerve attacks (MS-SCON). METHODS Sera of 29 MS-SCON patients and 36 healthy controls were screened with indirect immunofluorescence to identify IgG reacting with human astrocyte cultures. Putative target autoantigens were investigated with immunoprecipitation (IP) and liquid chromatography-mass/mass spectrometry (LC-MS/MS) studies using cultured human astrocytes. Validation of LC-MS/MS results was carried out by IP and ELISA. RESULTS Antibodies to astrocytic cell surface antigens were detected in 5 MS-SCON patients by immunocytochemistry. LC-MS/MS analysis identified chloride intracellular channel protein-1 (CLIC1) as the single common membrane antigen in 2 patients with MS-SCON. IP experiments performed with the commercial CLIC1 antibody confirmed CLIC1-antibody. Home made ELISA using recombinant CLIC1 protein as the target antigen identified CLIC1 antibodies in 9/29 MS-SCON and 3/15 relapsing inflammatory optic neuritis (RION) patients but in none of the 30 NMOSD patients, 36 RRMS patients with only one or no myelitis/optic neuritis attacks and 36 healthy controls. Patients with CLIC1-antibodies showed trends towards exhibiting reduced disability scores. CONCLUSION CLIC1-antibody was identified for the first time in MS and RION patients, confirming once again anti-astrocytic autoimmunity in CIDD. CLIC1-antibody may potentially be utilized as a diagnostic biomarker for differentiation of MS from NMOSD.
Collapse
Affiliation(s)
- Zerrin Karaaslan
- Institute of Graduate Studies in HealthySciences, Istanbul University, Istanbul, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Büşra Şengül-Yediel
- Department of Neuroscience, Institute of Neurological Sciences, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Hande Yüceer-Korkmaz
- Institute of Graduate Studies in HealthySciences, Istanbul University, Istanbul, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Elif Şanlı
- Institute of Graduate Studies in HealthySciences, Istanbul University, Istanbul, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Duygu Gezen-Ak
- Department of Neuroscience, Institute of Neurological Sciences, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Erdinç Dursun
- Department of Neuroscience, Institute of Neurological Sciences, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Özlem Timirci-Kahraman
- Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Ahmet Tarık Baykal
- Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Vuslat Yılmaz
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Recai Türkoğlu
- Department of Neurology, Istanbul Haydarpasa Numune Training and Research Hospital, Istanbul, Turkey
| | - Murat Kürtüncü
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
| | - Tuncay Gündüz
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
| | | | - Erdem Tüzün
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Cem İsmail Küçükali
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey.
| |
Collapse
|
12
|
He Q, Zhong CQ, Li X, Guo H, Li Y, Gao M, Yu R, Liu X, Zhang F, Guo D, Ye F, Guo T, Shuai J, Han J. Dear-DIA XMBD: Deep Autoencoder Enables Deconvolution of Data-Independent Acquisition Proteomics. RESEARCH (WASHINGTON, D.C.) 2023; 6:0179. [PMID: 37377457 PMCID: PMC10292580 DOI: 10.34133/research.0179] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 06/01/2023] [Indexed: 06/29/2023]
Abstract
Data-independent acquisition (DIA) technology for protein identification from mass spectrometry and related algorithms is developing rapidly. The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition data represents a promising direction. In this paper, we proposed an untargeted analysis method, Dear-DIAXMBD, for direct analysis of DIA data. Dear-DIAXMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms, then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes, and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides and between fragments and peptides. We show that Dear-DIAXMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms. Dear-DIAXMBD is publicly available at https://github.com/jianweishuai/Dear-DIA-XMBD.
Collapse
Affiliation(s)
- Qingzu He
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research,
Xiamen University, Xiamen 361005, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) and Wenzhou Institute,
University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| | - Chuan-Qi Zhong
- School of Life Sciences,
Xiamen University, Xiamen 361102, China
- State Key Laboratory of Cellular Stress Biology,
Innovation Center for Cell Signaling Network, Xiamen 361102, China
| | - Xiang Li
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research,
Xiamen University, Xiamen 361005, China
- State Key Laboratory of Cellular Stress Biology,
Innovation Center for Cell Signaling Network, Xiamen 361102, China
| | - Huan Guo
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research,
Xiamen University, Xiamen 361005, China
| | - Yiming Li
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research,
Xiamen University, Xiamen 361005, China
| | - Mingxuan Gao
- Department of Computer Science,
Xiamen University, Xiamen 361005, China
| | - Rongshan Yu
- Department of Computer Science,
Xiamen University, Xiamen 361005, China
- National Institute for Data Science in Health and Medicine, School of Medicine,
Xiamen University, Xiamen 361102, China
| | - Xianming Liu
- Bruker (Beijing) Scientific Technology Co. Ltd., Beijing, China
| | - Fangfei Zhang
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences,
Westlake University, 18 Shilongshan Road, Hangzhou 310024, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, China
| | - Donghui Guo
- Department of Electronic Engineering,
Xiamen University, Xiamen 361005, China
| | - Fangfu Ye
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) and Wenzhou Institute,
University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| | - Tiannan Guo
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences,
Westlake University, 18 Shilongshan Road, Hangzhou 310024, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, China
- Westlake Omics Ltd., Yunmeng Road 1, Hangzhou, China
| | - Jianwei Shuai
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research,
Xiamen University, Xiamen 361005, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) and Wenzhou Institute,
University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
- State Key Laboratory of Cellular Stress Biology,
Innovation Center for Cell Signaling Network, Xiamen 361102, China
- National Institute for Data Science in Health and Medicine, School of Medicine,
Xiamen University, Xiamen 361102, China
| | - Jiahuai Han
- School of Life Sciences,
Xiamen University, Xiamen 361102, China
- State Key Laboratory of Cellular Stress Biology,
Innovation Center for Cell Signaling Network, Xiamen 361102, China
- National Institute for Data Science in Health and Medicine, School of Medicine,
Xiamen University, Xiamen 361102, China
| |
Collapse
|
13
|
Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
Collapse
Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| |
Collapse
|
14
|
Yang Y, Yang L, Zheng M, Cao D, Liu G. Data acquisition methods for non-targeted screening in environmental analysis. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
|
15
|
Kiris I, Kukula-Koch W, Karayel-Basar M, Gurel B, Coskun J, Baykal AT. Proteomic alterations in the cerebellum and hippocampus in an Alzheimer's disease mouse model: Alleviating effect of palmatine. Biomed Pharmacother 2023; 158:114111. [PMID: 36502756 DOI: 10.1016/j.biopha.2022.114111] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/28/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease (AD) is one of the most prevalent diseases that lead to memory deficiencies, severe behavioral abnormalities, and ultimately death. The need for more appropriate treatment of AD continues, and remains a sought-after goal. Previous studies showed palmatine (PAL), an isoquinoline alkaloid, might have the potential for combating AD because of its in vitro and in vivo activities. In this study, we aimed to assess PAL's therapeutic potential and gain insights into the working mechanism on protein level in the AD mouse model brain, for the first time. To this end, PAL was administered to 12-month-old 5xFAD mice at two doses after its successful isolation from the Siberian barberry shrub. PAL (10 mg/kg) showed statistically significant improvement in the memory and learning phase on the Morris water maze test. The PAL's ability to pass through the blood-brain barrier was verified via Multiple Reaction Monitoring (MRM). Label-free proteomics analysis revealed PAL administration led to changes most prominently in the cerebellum, followed by the hippocampus, but none in the cortex. Most of the differentially expressed proteins in PAL compared to the 5xFAD control group (ALZ) were the opposite of those in ALZ in comparison to healthy Alzheimer's littermates (ALM) group. HS105, HS12A, and RL12 were detected as hub proteins in the cerebellum. Collectively, here we present PAL as a potential therapeutic candidate owing to its alleviating effect in 5xFAD mice on not only cognitive impairment but also proteomes in the cerebellum and hippocampus.
Collapse
Affiliation(s)
- Irem Kiris
- Department of Biochemistry and Molecular Biology, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Wirginia Kukula-Koch
- Department of Pharmacognosy with Medicinal Plants Garden, Medical University of Lublin, Lublin, Poland
| | - Merve Karayel-Basar
- Department of Biochemistry and Molecular Biology, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Busra Gurel
- Sabanci University Nanotechnology Research and Application Center, SUNUM, Istanbul, Turkey
| | - Julide Coskun
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Ahmet Tarik Baykal
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
| |
Collapse
|
16
|
Skowronek P, Krohs F, Lubeck M, Wallmann G, Itang ECM, Koval P, Wahle M, Thielert M, Meier F, Willems S, Raether O, Mann M. Synchro-PASEF Allows Precursor-Specific Fragment Ion Extraction and Interference Removal in Data-Independent Acquisition. Mol Cell Proteomics 2023; 22:100489. [PMID: 36566012 PMCID: PMC9868879 DOI: 10.1016/j.mcpro.2022.100489] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/12/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
Data-independent acquisition (DIA) methods have become increasingly popular in mass spectrometry-based proteomics because they enable continuous acquisition of fragment spectra for all precursors simultaneously. However, these advantages come with the challenge of correctly reconstructing the precursor-fragment relationships in these highly convoluted spectra for reliable identification and quantification. Here, we introduce a scan mode for the combination of trapped ion mobility spectrometry with parallel accumulation-serial fragmentation (PASEF) that seamlessly and continuously follows the natural shape of the ion cloud in ion mobility and peptide precursor mass dimensions. Termed synchro-PASEF, it increases the detected fragment ion current several-fold at sub-second cycle times. Consecutive quadrupole selection windows move synchronously through the mass and ion mobility range. In this process, the quadrupole slices through the peptide precursors, which separates fragment ion signals of each precursor into adjacent synchro-PASEF scans. This precisely defines precursor-fragment relationships in ion mobility and mass dimensions and effectively deconvolutes the DIA fragment space. Importantly, the partitioned parts of the fragment ion transitions provide a further dimension of specificity via a lock-and-key mechanism. This is also advantageous for quantification, where signals from interfering precursors in the DIA selection window do not affect all partitions of the fragment ion, allowing to retain only the specific parts for quantification. Overall, we establish the defining features of synchro-PASEF and explore its potential for proteomic analyses.
Collapse
Affiliation(s)
- Patricia Skowronek
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Florian Krohs
- Research and Development, Bruker Daltonics GmbH & Co KG, Bremen, Germany
| | - Markus Lubeck
- Research and Development, Bruker Daltonics GmbH & Co KG, Bremen, Germany
| | - Georg Wallmann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ericka C M Itang
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Polina Koval
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Biomedicine and Neuroscience, Kyiv Academic University, Kyiv, Ukraine
| | - Maria Wahle
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Marvin Thielert
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Florian Meier
- Functional Proteomics, Jena University Hospital, Jena, Germany
| | - Sander Willems
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Research and Development, Bruker Belgium nv., Kontich, Belgium.
| | - Oliver Raether
- Research and Development, Bruker Daltonics GmbH & Co KG, Bremen, Germany.
| | - Matthias Mann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Proteomics, NNF Center for Protein Research, Copenhagen, Denmark.
| |
Collapse
|
17
|
Yang Y, Qiao L. Data-independent acquisition proteomics methods for analyzing post-translational modifications. Proteomics 2022; 23:e2200046. [PMID: 36036492 DOI: 10.1002/pmic.202200046] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 08/20/2022] [Accepted: 08/23/2022] [Indexed: 11/06/2022]
Abstract
Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, i.e., detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| |
Collapse
|
18
|
Rojas Echeverri JC, Volke D, Milkovska-Stamenova S, Hoffmann R. Evaluating Peptide Fragment Ion Detection Using Traveling Wave Ion Mobility Spectrometry with Signal-Enhanced MS E (SEMS E). Anal Chem 2022; 94:10930-10941. [PMID: 35904512 DOI: 10.1021/acs.analchem.2c00461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The inherent poor sampling of fragment ions in time-of-flight mass analyzers was recently improved for data-dependent acquisition (DDA) by considering their drift times in traveling wave ion mobility spectrometry (TWIMS). Here, we extend this TWIMS-DDA approach to the data-independent acquisition (DIA) mode MSE to improve the signal intensities of fragment ions by providing improved ion beam sampling efficiency, which we termed therefore signal-enhanced MSE (SEMSE). The theoretical expectation that SEMSE improves the number of identified peptides, the number of quantifiable peptides, and the lower limit of quantitation in wideband DIA was evaluated on an electrospray ionisation-ion mobility spectrometry-quadrupole-time-of-flight-MS (ESI-IMS-Q-TOF-MS) (Synapt G2-Si) in comparison to five established TWIMS-DDA and TWIMS-MSE methods with respect to the number of peptide identifications, the spectral quality of supporting peptide spectra matches, and (most importantly) fragment ion signal sensitivity. A comparison of the fragment signals clearly indicated that SEMSE provides 6.8- to 11.5-fold larger peak areas than established MSE techniques. While this clearly shows the advantages of SEMSE, the inherent limitations of the current software tools do not allow using all benefits in routine analyses. As the simultaneous fragmentation of co-eluting peptides limited peptide identification, DDA and MSE data sets were integrated using Skyline.
Collapse
Affiliation(s)
- Juan Camilo Rojas Echeverri
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Universität Leipzig, 04103 Leipzig, Germany.,Center for Biotechnology and Biomedicine, Universität Leipzig, 04103 Leipzig, Germany
| | - Daniela Volke
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Universität Leipzig, 04103 Leipzig, Germany.,Center for Biotechnology and Biomedicine, Universität Leipzig, 04103 Leipzig, Germany
| | - Sanja Milkovska-Stamenova
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Universität Leipzig, 04103 Leipzig, Germany.,Center for Biotechnology and Biomedicine, Universität Leipzig, 04103 Leipzig, Germany
| | - Ralf Hoffmann
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Universität Leipzig, 04103 Leipzig, Germany.,Center for Biotechnology and Biomedicine, Universität Leipzig, 04103 Leipzig, Germany
| |
Collapse
|
19
|
Mendes ML, Dittmar G. Targeted proteomics on its way to discovery. Proteomics 2022; 22:e2100330. [PMID: 35816345 DOI: 10.1002/pmic.202100330] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 06/20/2022] [Accepted: 06/27/2022] [Indexed: 11/06/2022]
Abstract
For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This changed with the recent advances in highly multiplexed analysis. While discovery proteomics still pushes higher numbers of identified and quantified proteins, the advances in targeted proteomics rose to cover large parts of less complex proteomes or proteomes with low protein detection counts due to dynamic range restrictions, like the blood proteome. These new developments will impact, especially on the field of biomarker discovery and the possibility of using targeted proteomics for diagnostic purposes. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Marta L Mendes
- Proteomics of cellular signalling, Department of Infection and Immunity, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Gunnar Dittmar
- Proteomics of cellular signalling, Department of Infection and Immunity, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg.,Department of Life Sciences and Medicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
| |
Collapse
|
20
|
Kaeslin J, Zenobi R. Resolving isobaric interferences in direct infusion tandem mass spectrometry. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2022; 36:e9266. [PMID: 35124854 PMCID: PMC9286799 DOI: 10.1002/rcm.9266] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 06/14/2023]
Abstract
RATIONALE The co-fragmentation of precursors in direct infusion (DI) tandem high-resolution mass spectrometry (HRMS) can complicate the fragment spectra and consequently lead to false hits during compound identification. METHODS The method herein described, termed IQAROS (incremental quadrupole acquisition to resolve overlapping spectra), modulates the intensities of precursors and fragments by stepwise movement of the quadrupole isolation window over the mass-to-charge (m/z) range of the precursors. The modulated signals are then deconvoluted by a linear regression model to reconstruct the fragment spectra with less interference. The hardware to demonstrate the use of IQAROS was an orbitrap with electrospray ionization (ESI) or secondary electrospray ionization (SESI), although the method can also be applied to other ionization techniques or mass analyzers. RESULTS Assessing the performance of IQAROS with isobaric standards revealed that the reconstructed fragment spectra match with spectra acquired from the pure standards and that more compounds were correctly identified compared with the classical approach with the quadrupole centered at the m/z value of the precursor of interest. Moreover, the strength of IQAROS is exemplified by the identification of two isobaric biomarkers directly from a breath sample with SESI-HRMS. CONCLUSIONS With IQAROS, cleaner fragment spectra of co-fragmenting isobars during DI-HRMS analysis can be obtained. IQAROS can easily be set up by the standard graphical user interface of the instrument. Therefore, it facilitates the characterization of features of interest in samples analyzed by DI-HRMS, for example, in high-throughput or real-time metabolomics.
Collapse
Affiliation(s)
- Jérôme Kaeslin
- Department of Chemistry and Applied BiosciencesETH ZürichZürichSwitzerland
| | - Renato Zenobi
- Department of Chemistry and Applied BiosciencesETH ZürichZürichSwitzerland
| |
Collapse
|
21
|
Van Puyvelde B, Daled S, Willems S, Gabriels R, Gonzalez de Peredo A, Chaoui K, Mouton-Barbosa E, Bouyssié D, Boonen K, Hughes CJ, Gethings LA, Perez-Riverol Y, Bloomfield N, Tate S, Schiltz O, Martens L, Deforce D, Dhaenens M. A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics. Sci Data 2022; 9:126. [PMID: 35354825 PMCID: PMC8967878 DOI: 10.1038/s41597-022-01216-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 02/23/2022] [Indexed: 12/23/2022] Open
Abstract
In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735).
Collapse
Affiliation(s)
- Bart Van Puyvelde
- ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium
| | - Simon Daled
- ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium
| | - Sander Willems
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, VIB, 9000, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9000, Ghent, Belgium
| | - Anne Gonzalez de Peredo
- Institut de Pharmacologie et de Biologie Structural (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Karima Chaoui
- Institut de Pharmacologie et de Biologie Structural (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Emmanuelle Mouton-Barbosa
- Institut de Pharmacologie et de Biologie Structural (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - David Bouyssié
- Institut de Pharmacologie et de Biologie Structural (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Kurt Boonen
- VITO Health, Mol, Belgium
- Centre for Proteomics, University of Antwerpen, Antwerp, Belgium
| | | | | | - Yasset Perez-Riverol
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | | | | | - Odile Schiltz
- Institut de Pharmacologie et de Biologie Structural (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, 9000, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9000, Ghent, Belgium
| | - Dieter Deforce
- ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium
| | - Maarten Dhaenens
- ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.
| |
Collapse
|
22
|
Nontargeted Screening Using Gas Chromatography-Atmospheric Pressure Ionization Mass Spectrometry: Recent Trends and Emerging Potential. Molecules 2021; 26:molecules26226911. [PMID: 34834002 PMCID: PMC8624013 DOI: 10.3390/molecules26226911] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 11/10/2021] [Accepted: 11/12/2021] [Indexed: 01/02/2023] Open
Abstract
Gas chromatography–high-resolution mass spectrometry (GC–HRMS) is a powerful nontargeted screening technique that promises to accelerate the identification of environmental pollutants. Currently, most GC–HRMS instruments are equipped with electron ionization (EI), but atmospheric pressure ionization (API) ion sources have attracted renewed interest because: (i) collisional cooling at atmospheric pressure minimizes fragmentation, resulting in an increased yield of molecular ions for elemental composition determination and improved detection limits; (ii) a wide range of sophisticated tandem (ion mobility) mass spectrometers can be easily adapted for operation with GC–API; and (iii) the conditions of an atmospheric pressure ion source can promote structure diagnostic ion–molecule reactions that are otherwise difficult to perform using conventional GC–MS instrumentation. This literature review addresses the merits of GC–API for nontargeted screening while summarizing recent applications using various GC–API techniques. One perceived drawback of GC–API is the paucity of spectral libraries that can be used to guide structure elucidation. Herein, novel data acquisition, deconvolution and spectral prediction tools will be reviewed. With continued development, it is anticipated that API may eventually supplant EI as the de facto GC–MS ion source used to identify unknowns.
Collapse
|
23
|
Borràs E, Pastor O, Sabidó E. Use of Linear Ion Traps in Data-Independent Acquisition Methods Benefits Low-Input Proteomics. Anal Chem 2021; 93:11649-11653. [PMID: 34404205 DOI: 10.1021/acs.analchem.1c01885] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The need for a better understanding of cellular heterogeneity has pushed mass spectrometry technologies to the analysis of single-cell and single-cell-type proteomes, although several challenges still limit their widespread implementation. Among the efforts toward single-cell and low-input analyses, there is the adoption of data-independent acquisition methods to increase analytical sensitivity. Here, we revisited the use of linear ion traps mass analyzers in data-independent acquisition methods and demonstrate their benefits to boost peptide and protein identifications in low-input proteomes.
Collapse
Affiliation(s)
- Eva Borràs
- Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain.,Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Olga Pastor
- Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain.,Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Eduard Sabidó
- Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain.,Universitat Pompeu Fabra, 08003 Barcelona, Spain
| |
Collapse
|
24
|
Kiris I, Skalicka-Wozniak K, Basar MK, Sahin B, Gurel B, Baykal AT. Molecular Effects of Pteryxin and Scopoletin in the 5xFAD Alzheimer's Disease Mouse Model. Curr Med Chem 2021; 29:2937-2950. [PMID: 34455957 DOI: 10.2174/0929867328666210827152914] [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] [Received: 04/27/2021] [Revised: 07/06/2021] [Accepted: 07/11/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is one of the most prevalent diseases with rapidly increasing numbers, but there is still no medication to treat or stop the disease. Previous data on coumarins suggests that scopoletin may have potential benefits in AD. OBJECTIVE Evaluate the therapeutic potential of the coumarins with natural origin - scopoletin and pteryxin in a 5xFAD mouse model of AD Methods: Both compounds were administered at two doses to 12-month-old mice, which represent severe AD pathology. The effects of coumarins were assessed on cognition in mouse experiments. Changes in the overall brain proteome were evaluated using LC-MS/MS analyses. RESULTS The Morris water maze test implicated that a higher dose of pteryxin (16 mg/kg) significantly improved learning, and the proteome analysis showed pronounced changes of specific proteins upon pteryxin administration. The amyloid-β precursor protein, glial fibrillary acid protein, and apolipoprotein E protein which are highly associated with AD, were among the differentially expressed proteins at the higher dose of the pteryxin. CONCLUSION Overall, pteryxin may be evaluated further as a disease-modifying agent in AD pathology in the late stages of AD.
Collapse
Affiliation(s)
- Irem Kiris
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul. Turkey
| | | | - Merve Karayel Basar
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul. Turkey
| | - Betul Sahin
- Acibadem Labmed Clinical Laboratories, R&D Center, Istanbul. Turkey
| | - Busra Gurel
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul. Turkey
| | - Ahmet Tarik Baykal
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul. Turkey
| |
Collapse
|
25
|
Meier F, Park MA, Mann M. Trapped Ion Mobility Spectrometry and Parallel Accumulation-Serial Fragmentation in Proteomics. Mol Cell Proteomics 2021; 20:100138. [PMID: 34416385 PMCID: PMC8453224 DOI: 10.1016/j.mcpro.2021.100138] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 08/05/2021] [Accepted: 08/11/2021] [Indexed: 12/14/2022] Open
Abstract
Recent advances in efficiency and ease of implementation have rekindled interest in ion mobility spectrometry, a technique that separates gas phase ions by their size and shape and that can be hybridized with conventional LC and MS. Here, we review the recent development of trapped ion mobility spectrometry (TIMS) coupled to TOF mass analysis. In particular, the parallel accumulation-serial fragmentation (PASEF) operation mode offers unique advantages in terms of sequencing speed and sensitivity. Its defining feature is that it synchronizes the release of ions from the TIMS device with the downstream selection of precursors for fragmentation in a TIMS quadrupole TOF configuration. As ions are compressed into narrow ion mobility peaks, the number of peptide fragment ion spectra obtained in data-dependent or targeted analyses can be increased by an order of magnitude without compromising sensitivity. Taking advantage of the correlation between ion mobility and mass, the PASEF principle also multiplies the efficiency of data-independent acquisition. This makes the technology well suited for rapid proteome profiling, an increasingly important attribute in clinical proteomics, as well as for ultrasensitive measurements down to single cells. The speed and accuracy of TIMS and PASEF also enable precise measurements of collisional cross section values at the scale of more than a million data points and the development of neural networks capable of predicting them based only on peptide sequences. Peptide collisional cross section values can differ for isobaric sequences or positional isomers of post-translational modifications. This additional information may be leveraged in real time to direct data acquisition or in postprocessing to increase confidence in peptide identifications. These developments make TIMS quadrupole TOF PASEF a powerful and expandable platform for proteomics and beyond.
Collapse
Affiliation(s)
- Florian Meier
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Functional Proteomics, Jena University Hospital, Jena, Germany.
| | - Melvin A Park
- Bruker Daltonics Inc, Billerica, Massachusetts, USA.
| | - Matthias Mann
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
| |
Collapse
|
26
|
Paris J, Morgan TE, Marzullo BP, Wootton CA, Barrow MP, O'Hara J, O'Connor PB. Two-Dimensional Mass Spectrometry Analysis of IgG1 Antibodies. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1716-1724. [PMID: 34152763 DOI: 10.1021/jasms.1c00096] [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: 06/13/2023]
Abstract
Two-dimensional mass spectrometry (2DMS) is a new, and theoretically ideal, data-independent analysis tool, which allows the characterization of a complex mixture and was used in the bottom-up analysis of IgG1 for the identification of post-translational modifications. The new peak picking algorithm allows the distinction between chimeric peaks in proteomics. In this application, the processing of 2DMS data correlates fragments to their corresponding precursors, with fragments from precursors which are <0.1 m/z at m/z 840 easily resolved, without the need for quadrupole or chromatographic separation.
Collapse
Affiliation(s)
- Johanna Paris
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Tomos E Morgan
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Bryan P Marzullo
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| | | | - Mark P Barrow
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - John O'Hara
- UCB, 216 Bath Road, Slough SL1 3WE, United Kingdom
| | - Peter B O'Connor
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| |
Collapse
|
27
|
Yang P, Li H, Zhang J, Xu X. Research progress on biomarkers of pulmonary embolism. CLINICAL RESPIRATORY JOURNAL 2021; 15:1046-1055. [PMID: 34214256 DOI: 10.1111/crj.13414] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/16/2021] [Accepted: 06/29/2021] [Indexed: 01/05/2023]
Abstract
OBJECTIVES To present a review on the traditional and new biomarkers of pulmonary embolism (PE). DATA SOURCE A systematic search has been carried out using keywords as PE, biomarker, diagnosis and risk stratification. RESULTS The results of this work have been structured into three parts: first, conventional biomarkers for vascular, cardiac and inflammation, including static markers and dynamic markers for measuring the time course; next, a review of new biomarkers in recent years, such as RNAs and markers obtained through proteomics and mass spectrometry; finally, use of new detection methods to directly detect the activity of existing markers, such as the determination of coagulation factor II and plasmin activities based on the proteolytic activation of an engineered zymogen. CONCLUSIONS This work summarized the characteristics of current traditional biomarkers for clinical diagnosis and risk stratification of PE, as well as a series of newly discovered biomarkers obtained through various clinical experimental methods.
Collapse
Affiliation(s)
- Pengbo Yang
- Department of Laboratory Medicine, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, Beijing, China
| | - Hexin Li
- Clinical Biobank, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, Beijing, China
| | - Junhua Zhang
- The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaomao Xu
- Department of Respiratory and Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Chinese Academy of Medical Sciences, Beijing, China
| |
Collapse
|
28
|
Affiliation(s)
- Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, MA, USA.
- Barnett Institute, Northeastern University, Boston, MA, USA.
| |
Collapse
|
29
|
Messner CB, Demichev V, Bloomfield N, Yu JSL, White M, Kreidl M, Egger AS, Freiwald A, Ivosev G, Wasim F, Zelezniak A, Jürgens L, Suttorp N, Sander LE, Kurth F, Lilley KS, Mülleder M, Tate S, Ralser M. Ultra-fast proteomics with Scanning SWATH. Nat Biotechnol 2021; 39:846-854. [PMID: 33767396 PMCID: PMC7611254 DOI: 10.1038/s41587-021-00860-4] [Citation(s) in RCA: 130] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/18/2021] [Indexed: 01/31/2023]
Abstract
Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min-1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5-5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.
Collapse
Affiliation(s)
- Christoph B Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vadim Demichev
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK
| | | | - Jason S L Yu
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Matthew White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Marco Kreidl
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Anna-Sophia Egger
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Anja Freiwald
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Core Facility - High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | | | | | - Aleksej Zelezniak
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Linda Jürgens
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Norbert Suttorp
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Leif Erik Sander
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Florian Kurth
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine & I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kathryn S Lilley
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge, UK
| | - Michael Mülleder
- Core Facility - High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
| |
Collapse
|
30
|
Kiris I, Basar MK, Sahin B, Gurel B, Coskun J, Mroczek T, Baykal AT. Evaluation of the Therapeutic Effect of Lycoramine on Alzheimer's Disease in Mouse Model. Curr Med Chem 2021; 28:3449-3473. [PMID: 33200692 DOI: 10.2174/0929867327999201116193126] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 08/31/2020] [Accepted: 09/04/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Alzheimer's disease is one of the leading health problems characterized by the accumulation of Aβ and hyperphosphorylated tau that account for the senile plaque formations causing extensive cognitive decline. Many of the clinical diagnoses of Alzheimer's disease are made in the late stages, when the pathological changes have already progressed. OBJECTIVE The objective of this study is to evaluate the promising therapeutic effects of a natural compound, lycoramine, which has been shown to have therapeutic potential in several studies and to understand its mechanism of action on the molecular level via differential protein expression analyses. METHODS Lycoramine and galantamine, an FDA approved drug used in the treatment of mild to moderate AD, were administered to 12 month-old 5xFAD mice. Effects of the compounds were investigated by Morris water maze, immunohistochemistry and label- free differential protein expression analyses. RESULTS Here we demonstrated the reversal of cognitive decline via behavioral testing and the clearance of Aβ plaques. Proteomics analysis provided in-depth information on the statistically significant protein perturbations in the cortex, hippocampus and cerebellum sections to hypothesize the possible clearance mechanisms of the plaque formation and the molecular mechanism of the reversal of cognitive decline in a transgenic mouse model. Bioinformatics analyses showed altered molecular pathways that can be linked with the reversal of cognitive decline observed after lycoramine administration but not with galantamine. CONCLUSION Lycoramine shows therapeutic potential to halt and reverse cognitive decline at the late stages of disease progression, and holds great promise for the treatment of Alzheimer's disease.
Collapse
Affiliation(s)
- Irem Kiris
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Merve Karayel Basar
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Betul Sahin
- Acibadem Labmed Clinical Laboratories, R&D Center, Istanbul, Turkey
| | - Busra Gurel
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Julide Coskun
- Acibadem Labmed Clinical Laboratories, R&D Center, Istanbul, Turkey
| | - Tomasz Mroczek
- Department of Pharmacognosy, Medical University of Lublin, Lublin, Poland
| | - Ahmet Tarik Baykal
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| |
Collapse
|
31
|
Ryu J, Thomas SN. Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer. Molecules 2021; 26:molecules26092674. [PMID: 34063568 PMCID: PMC8125593 DOI: 10.3390/molecules26092674] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 04/29/2021] [Accepted: 05/01/2021] [Indexed: 12/11/2022] Open
Abstract
Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.
Collapse
|
32
|
Nambiar S, Clynick B, How BS, King A, Walters EH, Goh NS, Corte TJ, Trengove R, Tan D, Moodley Y. There is detectable variation in the lipidomic profile between stable and progressive patients with idiopathic pulmonary fibrosis (IPF). Respir Res 2021; 22:105. [PMID: 33836757 PMCID: PMC8033725 DOI: 10.1186/s12931-021-01682-3] [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] [Received: 10/16/2020] [Accepted: 03/11/2021] [Indexed: 01/10/2023] Open
Abstract
Background Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease characterized by fibrosis and progressive loss of lung function. The pathophysiological pathways involved in IPF are not well understood. Abnormal lipid metabolism has been described in various other chronic lung diseases including asthma and chronic obstructive pulmonary disease (COPD). However, its potential role in IPF pathogenesis remains unclear. Methods In this study, we used ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to characterize lipid changes in plasma derived from IPF patients with stable and progressive disease. We further applied a data-independent acquisition (DIA) technique called SONAR, to improve the specificity of lipid identification. Results Statistical modelling showed variable discrimination between the stable and progressive subjects, revealing differences in the detection of triglycerides (TG) and phosphatidylcholines (PC) between progressors and stable IPF groups, which was further confirmed by mass spectrometry imaging (MSI) in IPF tissue. Conclusion This is the first study to characterise lipid metabolism between stable and progressive IPF, with results suggesting disparities in the circulating lipidome with disease progression.
Collapse
Affiliation(s)
- Shabarinath Nambiar
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia
| | - Britt Clynick
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia. .,Institute for Respiratory Health, Nedlands, WA, Australia.
| | - Bong S How
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia.,Metabolomics Australia, Murdoch University, Murdoch, WA, Australia
| | - Adam King
- Scientific Operations, Waters Corporation, Stamford Avenue, Wilmslow, SK9 4AX, UK
| | - E Haydn Walters
- Alfred Hospital, Melbourne, VIC, Australia.,University of Tasmania, Hobart, TAS, Australia.,University of Melbourne, Parkville, VIC, Australia.,Royal Hobart Hospital, Hobart, TAS, Australia
| | - Nicole S Goh
- Austin Hospital, Heidelberg, VIC, Australia.,Institute of Breathing and Sleep, Heidelberg, VIC, Australia
| | - Tamera J Corte
- University of Sydney, Camperdown, NSW, Australia.,Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Robert Trengove
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia.,Metabolomics Australia, Murdoch University, Murdoch, WA, Australia
| | - Dino Tan
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia.,Institute for Respiratory Health, Nedlands, WA, Australia
| | - Yuben Moodley
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia.,Institute for Respiratory Health, Nedlands, WA, Australia.,Fiona Stanley Hospital, Murdoch, WA, Australia
| |
Collapse
|
33
|
Xu Y, Song X, Wang D, Wang Y, Li P, Li J. Proteomic insights into synaptic signaling in the brain: the past, present and future. Mol Brain 2021; 14:37. [PMID: 33596935 PMCID: PMC7888154 DOI: 10.1186/s13041-021-00750-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/09/2021] [Indexed: 12/29/2022] Open
Abstract
Chemical synapses in the brain connect neurons to form neural circuits, providing the structural and functional bases for neural communication. Disrupted synaptic signaling is closely related to a variety of neurological and psychiatric disorders. In the past two decades, proteomics has blossomed as a versatile tool in biological and biomedical research, rendering a wealth of information toward decoding the molecular machinery of life. There is enormous interest in employing proteomic approaches for the study of synapses, and substantial progress has been made. Here, we review the findings of proteomic studies of chemical synapses in the brain, with special attention paid to the key players in synaptic signaling, i.e., the synaptic protein complexes and their post-translational modifications. Looking toward the future, we discuss the technological advances in proteomics such as data-independent acquisition mass spectrometry (DIA-MS), cross-linking in combination with mass spectrometry (CXMS), and proximity proteomics, along with their potential to untangle the mystery of how the brain functions at the molecular level. Last but not least, we introduce the newly developed synaptomic methods. These methods and their successful applications marked the beginnings of the synaptomics era.
Collapse
Affiliation(s)
- Yalan Xu
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China
| | - Xiuyue Song
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China
| | - Dong Wang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China
| | - Yin Wang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China
| | - Peifeng Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China
| | - Jing Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Medical College, Qingdao University, Qingdao, 266021, China.
| |
Collapse
|
34
|
Schreckenbach SA, Simmons D, Ladak A, Mullin L, Muir DCG, Simpson MJ, Jobst KJ. Data-Independent Identification of Suspected Organic Pollutants Using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry. Anal Chem 2021; 93:1498-1506. [PMID: 33355455 DOI: 10.1021/acs.analchem.0c03733] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The identity of an unknown environmental pollutant is reflected by the mass and dissociation chemistry of its (quasi)molecular ion. Gas chromatography-atmospheric pressure chemical ionization-mass spectrometry (GC-APCI-MS) increases the yield of molecular ions (compared to conventional electron ionization) by collisional cooling. Scanning quadrupole data-independent acquisition (SQDIA) permits unbiased, unattended selection of (quasi)molecular ions and acquisition of structure-diagnostic collision-induced dissociation mass spectra, while minimizing interferences, by sequentially cycling a quadrupole isolation window through the m/z range. This study reports on the development of a suspect screening method based on industrial compounds with bioaccumulation potential. A comparison of false and correct identifications in a mixed standard containing 30 analytes suggests that SQDIA results in a markedly lower false-positive rate than standard DIA: 5 for SQDIA and 82 for DIA. Electronic waste dust was analyzed using GC and quadrupole time-of-flight MS with APCI and SQDIA acquisition. A total of 52 brominated, chlorinated, and organophosphorus compounds were identified by suspect screening; 15 unique elemental compositions were identified using nontargeted screening; 17 compounds were confirmed using standards and others identified to confidence levels 2, 3, or 4. SQDIA reduced false-positive identifications, compared to experiments without quadrupole isolation. False positives also varied by class: 20% for Br, 37% for Cl, 75% for P, and >99% for all other classes. The structure proposal of a previously reported halogenated compound was revisited. The results underline the utility of GC-SQDIA experiments that provide information on both the (quasi)molecular ions and its dissociation products for a more confident structural assignment.
Collapse
Affiliation(s)
- Sophia A Schreckenbach
- Department of Chemistry, University of Toronto, Toronto, Ontario, M1C 1A4, Canada.,Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario M1C 1A4, Canada
| | - Denina Simmons
- Depertment of Biology, University of Ontario Institute of Technology, Oshawa, Ontario L1G 0C5, Canada
| | - Adam Ladak
- Waters Corporation, Milford, Massachusetts 01757, United States
| | - Lauren Mullin
- Waters Corporation, Milford, Massachusetts 01757, United States
| | - Derek C G Muir
- Environment and Climate Change Canada, Burlington, Ontario ON L7S 1A1, Canada
| | - Myrna J Simpson
- Department of Chemistry, University of Toronto, Toronto, Ontario, M1C 1A4, Canada.,Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario M1C 1A4, Canada
| | - Karl J Jobst
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland A1B 3X7, Canada
| |
Collapse
|
35
|
Buric F, Zrimec J, Zelezniak A. Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra. PATTERNS (NEW YORK, N.Y.) 2020; 1:100137. [PMID: 33336195 PMCID: PMC7733873 DOI: 10.1016/j.patter.2020.100137] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 09/14/2020] [Accepted: 10/12/2020] [Indexed: 11/26/2022]
Abstract
High-throughput data-independent acquisition (DIA) is the method of choice for quantitative proteomics, combining the best practices of targeted and shotgun approaches. The resultant DIA spectra are, however, highly convolved and with no direct precursor-fragment correspondence, complicating biological sample analysis. Here, we present CANDIA (canonical decomposition of data-independent-acquired spectra), a GPU-powered unsupervised multiway factor analysis framework that deconvolves multispectral scans to individual analyte spectra, chromatographic profiles, and sample abundances, using parallel factor analysis. The deconvolved spectra can be annotated with traditional database search engines or used as high-quality input for de novo sequencing methods. We demonstrate that spectral libraries generated with CANDIA substantially reduce the false discovery rate underlying the validation of spectral quantification. CANDIA covers up to 33 times more total ion current than library-based approaches, which typically use less than 5% of total recorded ions, thus allowing quantification and identification of signals from unexplored DIA spectra. Conventional DIA spectral libraries cover less than 3% of a scan's total ion count CANDIA deconvolves peptide signals by leveraging all scan data CANDIA uses GPUs to enable tensor algebra on massive DIA mass spectrometry data CANDIA output enables high-confidence and precise quantitative proteomics
The latest high-throughput mass spectrometry-based technologies can record virtually all molecules from complex biological samples, providing a holistic picture of proteomes in cells and tissues and enabling an evaluation of the overall status of a person's health. However, current best practices are still only scratching the surface of the wealth of available information obtained from the massive proteome datasets, and efficient novel data-driven strategies are needed. Powered by advances in GPU hardware and open-source machine-learning frameworks, we developed a data-driven approach, CANDIA, which disassembles highly complex proteomics data into the elementary molecular signatures of the proteins in biological samples. Our work provides a performant and adaptable solution that complements existing mass spectrometry techniques. As the central mathematical methods are generic, other scientific fields that are dealing with highly convolved datasets will benefit from this work.
Collapse
Affiliation(s)
- Filip Buric
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden
| | - Jan Zrimec
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden
| | - Aleksej Zelezniak
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden.,Science for Life Laboratory, Tomtebodavägen 23a, Stockholm 171 65, Sweden
| |
Collapse
|
36
|
An assessment of quality assurance/quality control efforts in high resolution mass spectrometry non-target workflows for analysis of environmental samples. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.116063] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
|
37
|
Whetton AD, Preston GW, Abubeker S, Geifman N. Proteomics and Informatics for Understanding Phases and Identifying Biomarkers in COVID-19 Disease. J Proteome Res 2020; 19:4219-4232. [PMID: 32657586 PMCID: PMC7384384 DOI: 10.1021/acs.jproteome.0c00326] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Indexed: 02/07/2023]
Abstract
The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that fuller definitions of patient status, trajectory, sequelae, and responses to therapy are now required. There is accumulating evidence-from studies of both COVID-19 and the related disease SARS-that protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase), and the inflammatory response (e.g., C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. To be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g., using mass spectrometry) but also informatics approaches via which to derive actionable information from large data sets. Here we review applications of proteomics to COVID-19 and SARS and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.
Collapse
Affiliation(s)
- Anthony D. Whetton
- Stoller
Biomarker Discovery Centre, Faculty of Biology Medicine and Health
(FBMH), University of Manchester, Manchester M20 4GJ, United Kingdom
- Stem
Cell and Leukaemia Proteomics Laboratory, Manchester Cancer Research
Centre, University of Manchester, Manchester M13 9PL, United Kingdom
- Manchester
National Institute for Health Biomedical Research Centre, Manchester M13 9WL, United Kingdom
| | - George W. Preston
- Stoller
Biomarker Discovery Centre, Faculty of Biology Medicine and Health
(FBMH), University of Manchester, Manchester M20 4GJ, United Kingdom
- Stem
Cell and Leukaemia Proteomics Laboratory, Manchester Cancer Research
Centre, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Semira Abubeker
- Stoller
Biomarker Discovery Centre, Faculty of Biology Medicine and Health
(FBMH), University of Manchester, Manchester M20 4GJ, United Kingdom
- Stem
Cell and Leukaemia Proteomics Laboratory, Manchester Cancer Research
Centre, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Nophar Geifman
- Centre
for Health Informatics, FBMH, University
of Manchester, Manchester M13 9PL, United Kingdom
| |
Collapse
|
38
|
Akgun E, Tuzuner MB, Sahin B, Kilercik M, Kulah C, Cakiroglu HN, Serteser M, Unsal I, Baykal AT. Proteins associated with neutrophil degranulation are upregulated in nasopharyngeal swabs from SARS-CoV-2 patients. PLoS One 2020; 15:e0240012. [PMID: 33079950 PMCID: PMC7575075 DOI: 10.1371/journal.pone.0240012] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/17/2020] [Indexed: 12/21/2022] Open
Abstract
COVID-19 or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared throughout the World and currently affected more than 9 million people and caused the death of around 470,000 patients. The novel strain of the coronavirus disease is transmittable at a devastating rate with a high rate of severe hospitalization even more so for the elderly population. Naso-oro-pharyngeal swab samples as the first step towards detecting suspected infection of SARS-CoV-2 provides a non-invasive method for PCR testing at a high confidence rate. Furthermore, proteomics analysis of PCR positive and negative naso-oropharyngeal samples provides information on the molecular level which highlights disease pathology. Samples from 15 PCR positive cases and 15 PCR negative cases were analyzed with nanoLC-MS/MS to identify the differentially expressed proteins. Proteomic analyses identified 207 proteins across the sample set and 17 of them were statistically significant. Protein-protein interaction analyses emphasized pathways like Neutrophil degranulation, Innate Immune System, Antimicrobial Peptides. Neutrophil Elastase (ELANE), Azurocidin (AZU1), Myeloperoxidase (MPO), Myeloblastin (PRTN3), Cathepsin G (CTSG) and Transcobalamine-1 (TCN1) were found to be significantly altered in naso-oropharyngeal samples of SARS-CoV-2 patients. The identified proteins are linked to alteration in the innate immune system specifically via neutrophil degranulation and NETosis.
Collapse
Affiliation(s)
- Emel Akgun
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | | | - Betul Sahin
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Meltem Kilercik
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Canan Kulah
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | | | - Mustafa Serteser
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Ibrahim Unsal
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Ahmet Tarik Baykal
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| |
Collapse
|
39
|
Krasny L, Huang PH. Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology. Mol Omics 2020; 17:29-42. [PMID: 33034323 DOI: 10.1039/d0mo00072h] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Data-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic methodology that generates permanent digital proteome maps offering highly reproducible retrospective analysis of cellular and tissue specimens. The adoption of this technology has ushered a new wave of oncology studies across a wide range of applications including its use in molecular classification, oncogenic pathway analysis, drug and biomarker discovery and unravelling mechanisms of therapy response and resistance. In this review, we provide an overview of the experimental workflows commonly used in DIA-MS, including its current strengths and limitations versus conventional data-dependent acquisition mass spectrometry (DDA-MS). We further summarise a number of key studies to illustrate the power of this technology when applied to different facets of oncology. Finally we offer a perspective of the latest innovations in DIA-MS technology and machine learning-based algorithms necessary for driving the development of high-throughput, in-depth and reproducible proteomic assays that are compatible with clinical diagnostic workflows, which will ultimately enable the delivery of precision cancer medicine to achieve optimal patient outcomes.
Collapse
Affiliation(s)
- Lukas Krasny
- Division of Molecular Pathology, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.
| | | |
Collapse
|
40
|
Pino LK, Just SC, MacCoss MJ, Searle BC. Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries. Mol Cell Proteomics 2020; 19:1088-1103. [PMID: 32312845 PMCID: PMC7338082 DOI: 10.1074/mcp.p119.001913] [Citation(s) in RCA: 135] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 04/14/2020] [Indexed: 11/06/2022] Open
Abstract
Data independent acquisition (DIA) is an attractive alternative to standard shotgun proteomics methods for quantitative experiments. However, most DIA methods require collecting exhaustive, sample-specific spectrum libraries with data dependent acquisition (DDA) to detect and quantify peptides. In addition to working with non-human samples, studies of splice junctions, sequence variants, or simply working with small sample yields can make developing DDA-based spectrum libraries impractical. Here we illustrate how to acquire, queue, and validate DIA data without spectrum libraries, and provide a workflow to efficiently generate DIA-only chromatogram libraries using gas-phase fractionation (GPF). We present best-practice methods for collecting DIA data using Orbitrap-based instruments and develop an understanding for why DIA using an Orbitrap mass spectrometer should be approached differently than when using time-of-flight instruments. Finally, we discuss several methods for analyzing DIA data without libraries.
Collapse
Affiliation(s)
- Lindsay K Pino
- Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Seth C Just
- Proteome Software, Inc. Portland, Oregon, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Brian C Searle
- Institute for Systems Biology, Seattle, Washington, USA.
| |
Collapse
|
41
|
Raetz M, Bonner R, Hopfgartner G. SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis. Metabolomics 2020; 16:71. [PMID: 32504120 DOI: 10.1007/s11306-020-01692-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 05/29/2020] [Indexed: 12/19/2022]
Abstract
INTRODUCTION While liquid chromatography coupled to mass spectrometric detection in the selected reaction monitoring detection mode offers the best quantification sensitivity for omics, the number of target analytes is limited, must be predefined and specific methods developed. Data independent acquisition (DIA), including SWATH using quadrupole time of flight or orbitrap mass spectrometers and generic acquisition methods, has emerged as a powerful alternative technique for quantitative and qualitative analyses since it can cover a wide range of analytes without predefinition. OBJECTIVES Here we review the current state of DIA, SWATH-MS and highlight novel acquisition strategies for metabolomics and lipidomics and opportunities for data analysis tools. METHOD Different databases were searched for papers that report developments and applications of DIA and in particular SWATH-MS in metabolomics and lipidomics. RESULTS DIA methods generate digital sample records that can be mined retrospectively as further knowledge is gained and, with standardized acquisition schemes, used in multiple studies. The different chemical spaces of metabolites and lipids require different specificities, hence different acquisition and data processing approaches must be considered for their analysis. CONCLUSIONS Although the hardware and acquisition modes are well defined for SWATH-MS, a major challenge for routine use remains the lack of appropriate software tools capable of handling large datasets and large numbers of analytes.
Collapse
Affiliation(s)
- Michel Raetz
- Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, 24 Quai Ernest Ansermet, CH-1211, Geneva, Switzerland
| | - Ron Bonner
- Ron Bonner Consulting, Newmarket, ON, L3Y 3C7, Canada
| | - Gérard Hopfgartner
- Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, 24 Quai Ernest Ansermet, CH-1211, Geneva, Switzerland.
| |
Collapse
|
42
|
Zhang F, Ge W, Ruan G, Cai X, Guo T. Data‐Independent Acquisition Mass Spectrometry‐Based Proteomics and Software Tools: A Glimpse in 2020. Proteomics 2020; 20:e1900276. [DOI: 10.1002/pmic.201900276] [Citation(s) in RCA: 116] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/27/2020] [Indexed: 01/02/2023]
Affiliation(s)
- Fangfei Zhang
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Weigang Ge
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Guan Ruan
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Xue Cai
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Tiannan Guo
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| |
Collapse
|
43
|
Kaufmann A, Maden K, Walker S. Partially overlapping sequential window acquisition of all theoretical mass spectra: A methodology to improve the spectra quality of veterinary drugs present at low concentrations in highly complex biological matrices. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2020; 34:e8638. [PMID: 31659800 DOI: 10.1002/rcm.8638] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 09/24/2019] [Accepted: 10/15/2019] [Indexed: 06/10/2023]
Abstract
RATIONALE Residues of veterinary drugs in food matrices have to be detected, identified and confirmed at low concentrations. Data-independent acquisition (DIA) methods such as the sequential window acquisition of all theoretical spectra (SWATH) permit the extraction of relatively clean spectra out of complex matrices. Such spectra can be significantly improved by using a modified SWATH algorithm which provides several times narrower mass isolation windows without affecting the cycle time. METHODS A quadrupole-time-of-flight mass spectrometer was operated in a partially overlapping SWATH mode. Unlike in conventional SWATH, acquisition sequences are not identically repeated, but each sequence is initiated with a mass intercept (mass shift). Pearson correlation is used to assign HRMS-resolved product ions to the precursor mass of interest. Trace analytes (veterinary drugs) in a complex matrix extract (bovine liver) were investigated. RESULTS Utilizing identical cycle times, the partially overlapping SWATH mode produced for the investigated small molecules a significantly higher selectivity than the conventional SWATH acquisition mode. The acquisition strategy enables long ion accumulation times and therefore the required high sensitivity of detection. The study investigates the quality of the obtained product ion spectra and compares it with that in conventional acquisition modes. CONCLUSIONS The modified SWATH mode permits high duty cycles in combination with narrow virtual mass windows. The technique is a further step toward harvesting a HRMS product ion spectrum out of a data-independent acquisition which moves closer towards the quality of a dedicated precursor unit isolation product ion spectrum.
Collapse
Affiliation(s)
- Anton Kaufmann
- Official Food Control Authority, Fehrenstrasse 15, 8032, Zürich, Switzerland
| | - Kathryn Maden
- Official Food Control Authority, Fehrenstrasse 15, 8032, Zürich, Switzerland
| | - Stephan Walker
- Official Food Control Authority, Fehrenstrasse 15, 8032, Zürich, Switzerland
| |
Collapse
|
44
|
|
45
|
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.
Collapse
Affiliation(s)
- Zainab Noor
- Department of Molecular Sciences, Macquarie University, Sydney, Australia
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, Australia.
| |
Collapse
|
46
|
King A, Baginski M, Morikawa Y, Rainville PD, Gethings LA, Wilson ID, Plumb RS. Application of a Novel Mass Spectral Data Acquisition Approach to Lipidomic Analysis of Liver Extracts from Sitaxentan-Treated Liver-Humanized PXB Mice. J Proteome Res 2019; 18:4055-4064. [DOI: 10.1021/acs.jproteome.9b00334] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Adam King
- Waters Corporation, Stamford Avenue, Wilmslow SK9 4AX, U.K
| | - Matthew Baginski
- PhoenixBio USA Corporation, 65 Broadway, Suite 605, New York, New York 10006, United States
| | - Yoshio Morikawa
- PhoenixBio USA Corporation, 65 Broadway, Suite 605, New York, New York 10006, United States
| | - Paul D. Rainville
- Waters Corporation, 34 Maple Street, Milford, Massachusetts 01757, United States
| | | | - Ian D. Wilson
- Department of Surgery and Cancer, Imperial College, Exhibition Road, South Kensington, London SW7 2AZ, U.K
| | - Robert S. Plumb
- Waters Corporation, 34 Maple Street, Milford, Massachusetts 01757, United States
| |
Collapse
|
47
|
Li W, Chi H, Salovska B, Wu C, Sun L, Rosenberger G, Liu Y. Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:1396-1405. [PMID: 31147889 DOI: 10.1007/s13361-019-02243-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2019] [Revised: 04/28/2019] [Accepted: 04/28/2019] [Indexed: 06/09/2023]
Abstract
Due to the technical advances of mass spectrometers, particularly increased scanning speed and higher MS/MS resolution, the use of data-independent acquisition mass spectrometry (DIA-MS) became more popular, which enables high reproducibility in both proteomic identification and quantification. The current DIA-MS methods normally cover a wide mass range, with the aim to target and identify as many peptides and proteins as possible and therefore frequently generate MS/MS spectra of high complexity. In this report, we assessed the performance and benefits of using small windows with, e.g., 5-m/z width across the peptide elution time. We further devised a new DIA method named RTwinDIA that schedules the small isolation windows in different retention time blocks, taking advantage of the fact that larger peptides are normally eluting later in reversed phase chromatography. We assessed the direct proteomic identification by using shotgun database searching tools such as MaxQuant and pFind, and also Spectronaut with an external comprehensive spectral library of human proteins. We conclude that algorithms like pFind have potential in directly analyzing DIA data acquired with small windows, and that the instrumental time and DIA cycle time, if prioritized to be spent on small windows rather than on covering a broad mass range by large windows, will improve the direct proteome coverage for new biological samples and increase the quantitative precision. These results further provide perspectives for the future convergence between DDA and DIA on faster MS analyzers.
Collapse
Affiliation(s)
- Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA
| | - Hao Chi
- Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China
| | - Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA
- Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic
| | - Chongde Wu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA
| | | | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA.
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06520, USA.
| |
Collapse
|
48
|
Amodei D, Egertson J, MacLean BX, Johnson R, Merrihew GE, Keller A, Marsh D, Vitek O, Mallick P, MacCoss MJ. Improving Precursor Selectivity in Data-Independent Acquisition Using Overlapping Windows. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:669-684. [PMID: 30671891 PMCID: PMC6445824 DOI: 10.1007/s13361-018-2122-8] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 12/03/2018] [Accepted: 12/05/2018] [Indexed: 05/22/2023]
Abstract
A major goal of proteomics research is the accurate and sensitive identification and quantification of a broad range of proteins within a sample. Data-independent acquisition (DIA) approaches that acquire MS/MS spectra independently of precursor information have been developed to overcome the reproducibility challenges of data-dependent acquisition and the limited breadth of targeted proteomics strategies. Typical DIA implementations use wide MS/MS isolation windows to acquire comprehensive fragment ion data. However, wide isolation windows produce highly chimeric spectra, limiting the achievable sensitivity and accuracy of quantification and identification. Here, we present a DIA strategy in which spectra are collected with overlapping (rather than adjacent or random) windows and then computationally demultiplexed. This approach improves precursor selectivity by nearly a factor of 2, without incurring any loss in mass range, mass resolution, chromatographic resolution, scan speed, or other key acquisition parameters. We demonstrate a 64% improvement in sensitivity and a 17% improvement in peptides detected in a 6-protein bovine mix spiked into a yeast background. To confirm the method's applicability to a realistic biological experiment, we also analyze the regulation of the proteasome in yeast grown in rapamycin and show that DIA experiments with overlapping windows can help elucidate its adaptation toward the degradation of oxidatively damaged proteins. Our integrated computational and experimental DIA strategy is compatible with any DIA-capable instrument. The computational demultiplexing algorithm required to analyze the data has been made available as part of the open-source proteomics software tools Skyline and msconvert (Proteowizard), making it easy to apply as part of standard proteomics workflows. Graphical Abstract.
Collapse
Affiliation(s)
- Dario Amodei
- Department of Radiology, Stanford University, 3155 Porter Drive, Palo Alto, CA USA
| | - Jarrett Egertson
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Brendan X. MacLean
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Richard Johnson
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Gennifer E. Merrihew
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Austin Keller
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Don Marsh
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| | - Olga Vitek
- College of Computer and Information Science, Northeastern University, 440 Huntington Ave, Boston, MA USA
| | - Parag Mallick
- Department of Radiology, Stanford University, 3155 Porter Drive, Palo Alto, CA USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA USA
| |
Collapse
|
49
|
Chalkley RJ, MacCoss MJ, Jaffe JD, Röst HL. Initial Guidelines for Manuscripts Employing Data-independent Acquisition Mass Spectrometry for Proteomic Analysis. Mol Cell Proteomics 2019; 18:1-2. [PMID: 30602589 PMCID: PMC6317474 DOI: 10.1074/mcp.e118.001286] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Robert J Chalkley
- From the ‡Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143;.
| | - Michael J MacCoss
- ¶Department of Genome Sciences, University of Washington, Seattle, Washington 98195
| | - Jacob D Jaffe
- ‖Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
| | - Hannes L Röst
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| |
Collapse
|
50
|
Deutsch EW, Perez-Riverol Y, Chalkley RJ, Wilhelm M, Tate S, Sachsenberg T, Walzer M, Käll L, Delanghe B, Böcker S, Schymanski EL, Wilmes P, Dorfer V, Kuster B, Volders PJ, Jehmlich N, Vissers JP, Wolan DW, Wang AY, Mendoza L, Shofstahl J, Dowsey AW, Griss J, Salek RM, Neumann S, Binz PA, Lam H, Vizcaíno JA, Bandeira N, Röst H. Expanding the Use of Spectral Libraries in Proteomics. J Proteome Res 2018; 17:4051-4060. [PMID: 30270626 PMCID: PMC6443480 DOI: 10.1021/acs.jproteome.8b00485] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.
Collapse
Affiliation(s)
- Eric W. Deutsch
- Institute for Systems Biology, Seattle, Washington, 98109, United States
| | - Yasset Perez-Riverol
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Robert J. Chalkley
- University of California San Francisco, San Francisco, 94158, California, United States
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, 85354, Germany
| | | | - Timo Sachsenberg
- Department of Computer Science, Center for Bioinformatics, University of Tübingen, Sand 14, Tübingen, 72076, Germany
| | - Mathias Walzer
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Lukas Käll
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH − Royal Institute of Technology, Stockholm 114 28, Sweden
| | - Bernard Delanghe
- Thermo Fisher Scientific Bremen, Hanna-Kunath Str. 11, 28199 Bremen, Germany
| | - Sebastian Böcker
- Chair for Bioinformatics, Friedrich-Schiller-University Jena, 07743 Jena, Germany
| | - Emma L. Schymanski
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 avenue du Swing, L-4367 Belvaux, Luxembourg
| | - Paul Wilmes
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 avenue du Swing, L-4367 Belvaux, Luxembourg
| | - Viktoria Dorfer
- University of Applied Sciences Upper Austria, Bioinformatics Research Group, Hagenberg, 4232, Austria
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, 85354, Germany
- Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich, Freising, 85354, Germany
| | | | - Nico Jehmlich
- Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | | | - Dennis W. Wolan
- Department of Molecular Medicine, The Scripps Research Institute, 92037, La Jolla, California, United States
| | - Ana Y. Wang
- Department of Molecular Medicine, The Scripps Research Institute, 92037, La Jolla, California, United States
| | - Luis Mendoza
- Institute for Systems Biology, Seattle, Washington, 98109, United States
| | - Jim Shofstahl
- Thermo Fisher Scientific, 355 River Oaks Parkway San Jose, CA 95134
| | - Andrew W. Dowsey
- Department of Population Health Sciences and Bristol Veterinary School, Faculty of Health Sciences, University of Bristol, Bristol BS9 1BN, UK
| | - Johannes Griss
- Division of Immunology, Allergy and Infectious Diseases, Department of Dermatology, Medical University of Vienna, Währinger Gürtel 18-20, Vienna 1090, Austria
| | - Reza M. Salek
- The International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372 Lyon CEDEX 08, France
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, 06120 Halle, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, 04103 Leipzig, Germany
| | - Pierre-Alain Binz
- Clinical Chemistry Service, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland
| | - Henry Lam
- Department of Chemical and Biological Engineering, the Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Nuno Bandeira
- Center for Computational Mass Spectrometry, Department of Computer Science and Engineering, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, 92093-0404, USA
| | - Hannes Röst
- The Donnelly Centre, University of Toronto, 160 College St., Toronto, ON, M5S 3E1, Canada
| |
Collapse
|