1
|
Bielow C, Hoffmann N, Jimenez-Morales D, Van Den Bossche T, Vizcaíno JA, Tabb DL, Bittremieux W, Walzer M. Communicating Mass Spectrometry Quality Information in mzQC with Python, R, and Java. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1875-1882. [PMID: 38918936 PMCID: PMC11311537 DOI: 10.1021/jasms.4c00174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/07/2024] [Accepted: 06/11/2024] [Indexed: 06/27/2024]
Abstract
Mass spectrometry is a powerful technique for analyzing molecules in complex biological samples. However, inter- and intralaboratory variability and bias can affect the data due to various factors, including sample handling and preparation, instrument calibration and performance, and data acquisition and processing. To address this issue, the Quality Control (QC) working group of the Human Proteome Organization's Proteomics Standards Initiative has established the standard mzQC file format for reporting and exchanging information relating to data quality. mzQC is based on the JavaScript Object Notation (JSON) format and provides a lightweight yet versatile file format that can be easily implemented in software. Here, we present open-source software libraries to process mzQC data in three programming languages: Python, using pymzqc; R, using rmzqc; and Java, using jmzqc. The libraries follow a common data model and provide shared functionalities, including the (de)serialization and validation of mzQC files. We demonstrate use of the software libraries in a workflow for extracting, analyzing, and visualizing QC metrics from different sources. Additionally, we show how these libraries can be integrated with each other, with existing software tools, and in automated workflows for the QC of mass spectrometry data. All software libraries are available as open source under the MS-Quality-Hub organization on GitHub (https://github.com/MS-Quality-Hub).
Collapse
Affiliation(s)
- Chris Bielow
- Bioinformatics
Solution Center, Institut für Mathematik und Informatik, Freie Universität Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - Nils Hoffmann
- Institute
for Bio- and Geosciences (IBG-5), Forschungszentrum Jülich
GmbH, 52428 Jülich, Germany
| | - David Jimenez-Morales
- Department
of Medicine, Stanford University School
of Medicine, Stanford, California 94305, United States
| | - Tim Van Den Bossche
- Department
of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium
- VIB-UGent
Center for Medical Biotechnology, VIB, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium
| | - Juan Antonio Vizcaíno
- European
Molecular Biology Laboratory, EMBL-European
Bioinformatics Institute (EMBL-EBI),
Hinxton, Cambridge CB10 1SD, United Kingdom
| | - David L. Tabb
- European
Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen 9713 AV, The Netherlands
| | - Wout Bittremieux
- Department
of Computer Science, University of Antwerp, Antwerpen 2020, Belgium
| | - Mathias Walzer
- European
Molecular Biology Laboratory, EMBL-European
Bioinformatics Institute (EMBL-EBI),
Hinxton, Cambridge CB10 1SD, United Kingdom
| |
Collapse
|
2
|
Henke AN, Chilukuri S, Langan LM, Brooks BW. Reporting and reproducibility: Proteomics of fish models in environmental toxicology and ecotoxicology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168455. [PMID: 37979845 DOI: 10.1016/j.scitotenv.2023.168455] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/20/2023]
Abstract
Environmental toxicology and ecotoxicology research efforts are employing proteomics with fish models as New Approach Methodologies, along with in silico, in vitro and other omics techniques to elucidate hazards of toxicants and toxins. We performed a critical review of toxicology studies with fish models using proteomics and reported fundamental parameters across experimental design, sample preparation, mass spectrometry, and bioinformatics of fish, which represent alternative vertebrate models in environmental toxicology, and routinely studied animals in ecotoxicology. We observed inconsistencies in reporting and methodologies among experimental designs, sample preparations, data acquisitions and bioinformatics, which can affect reproducibility of experimental results. We identified a distinct need to develop reporting guidelines for proteomics use in environmental toxicology and ecotoxicology, increased QA/QC throughout studies, and method optimization with an emphasis on reducing inconsistencies among studies. Several recommendations are offered as logical steps to advance development and application of this emerging research area to understand chemical hazards to public health and the environment.
Collapse
Affiliation(s)
- Abigail N Henke
- Department of Biology, Baylor University Waco, TX, USA; Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University Waco, TX, USA
| | | | - Laura M Langan
- Department of Environmental Science, Baylor University Waco, TX, USA; Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University Waco, TX, USA.
| | - Bryan W Brooks
- Department of Environmental Science, Baylor University Waco, TX, USA; Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University Waco, TX, USA.
| |
Collapse
|
3
|
Tian S, Zhan D, Yu Y, Wang Y, Liu M, Tan S, Li Y, Song L, Qin Z, Li X, Liu Y, Li Y, Ji S, Wang S, Zheng Y, He F, Qin J, Ding C. Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics. Genome Biol 2023; 24:202. [PMID: 37674236 PMCID: PMC10483797 DOI: 10.1186/s13059-023-03048-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 08/23/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. RESULTS Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics. CONCLUSION Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.
Collapse
Affiliation(s)
- Sha Tian
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Dongdong Zhan
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Ying Yu
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Yunzhi Wang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Mingwei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Subei Tan
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Yan Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Lei Song
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Zhaoyu Qin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Xianju Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Yang Liu
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Yao Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Shuhui Ji
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Shanshan Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.
| | - Fuchu He
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
| | - Jun Qin
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
| | - Chen Ding
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.
| |
Collapse
|
4
|
Lu S, Lu H, Zheng T, Yuan H, Du H, Gao Y, Liu Y, Pan X, Zhang W, Fu S, Sun Z, Jin J, He QY, Chen Y, Zhang G. A multi-omics dataset of human transcriptome and proteome stable reference. Sci Data 2023; 10:455. [PMID: 37443183 PMCID: PMC10344951 DOI: 10.1038/s41597-023-02359-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023] Open
Abstract
The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine.
Collapse
Affiliation(s)
- Shaohua Lu
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China.
- Sino-French Hoffmann Institute, School of Basic Medical Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China.
| | - Hong Lu
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China
| | - Tingkai Zheng
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China
| | - Huiming Yuan
- CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian, China
| | - Hongli Du
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Youhe Gao
- Department of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal University, Beijing, China
| | - Yongtao Liu
- Department of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal University, Beijing, China
| | - Xuanzhen Pan
- Department of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal University, Beijing, China
| | - Wenlu Zhang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Shuying Fu
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Zhenghua Sun
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China
| | - Jingjie Jin
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China
| | - Qing-Yu He
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China
| | - Yang Chen
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China.
| | - Gong Zhang
- Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan University, Guangzhou, China.
| |
Collapse
|
5
|
Deutsch EW, Vizcaíno JA, Jones AR, Binz PA, Lam H, Klein J, Bittremieux W, Perez-Riverol Y, Tabb DL, Walzer M, Ricard-Blum S, Hermjakob H, Neumann S, Mak TD, Kawano S, Mendoza L, Van Den Bossche T, Gabriels R, Bandeira N, Carver J, Pullman B, Sun Z, Hoffmann N, Shofstahl J, Zhu Y, Licata L, Quaglia F, Tosatto SCE, Orchard SE. Proteomics Standards Initiative at Twenty Years: Current Activities and Future Work. J Proteome Res 2023; 22:287-301. [PMID: 36626722 PMCID: PMC9903322 DOI: 10.1021/acs.jproteome.2c00637] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Indexed: 01/11/2023]
Abstract
The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.
Collapse
Affiliation(s)
- Eric W. Deutsch
- Institute
for Systems Biology, Seattle, Washington 98109, United States
| | - Juan Antonio Vizcaíno
- European
Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Andrew R. Jones
- Institute
of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Pierre-Alain Binz
- Clinical
Chemistry Service, Lausanne University Hospital, 1011 976 Lausanne, Switzerland
| | - Henry Lam
- Department
of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, P. R. China.
| | - Joshua Klein
- Program for
Bioinformatics, Boston University, Boston, Massachusetts 02215, United States
| | - Wout Bittremieux
- Skaggs
School
of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States
- Department
of Computer Science, University of Antwerp, 2020 Antwerpen, Belgium
| | - Yasset Perez-Riverol
- European
Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - David L. Tabb
- SA MRC
Centre for TB Research, DST/NRF Centre of Excellence for Biomedical
TB Research, Division of Molecular Biology and Human Genetics, Faculty
of Medicine and Health Sciences, Stellenbosch
University, Cape Town 7602, South Africa
| | - Mathias Walzer
- European
Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Sylvie Ricard-Blum
- Univ.
Lyon, Université Lyon 1, ICBMS, UMR 5246, 69622 Villeurbanne, France
| | - Henning Hermjakob
- European
Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Steffen Neumann
- Bioinformatics
and Scientific Data, Leibniz Institute of
Plant Biochemistry, 06120 Halle, Germany
- German
Centre for Integrative Biodiversity Research (iDiv), 04103 Halle-Jena-Leipzig, Germany
| | - Tytus D. Mak
- Mass Spectrometry
Data Center, National Institute of Standards
and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United
States
| | - Shin Kawano
- Database
Center for Life Science, Joint Support Center for Data Science Research, Research Organization of Information and Systems, Chiba 277-0871, Japan
- Faculty
of Contemporary Society, Toyama University
of International Studies, Toyama 930-1292, Japan
- School
of Frontier Engineering, Kitasato University, Sagamihara 252-0373, Japan
| | - Luis Mendoza
- Institute
for Systems Biology, Seattle, Washington 98109, United States
| | - Tim Van Den Bossche
- VIB-UGent
Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department
of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, 9052 Ghent, Belgium
| | - Ralf Gabriels
- VIB-UGent
Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department
of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, 9052 Ghent, Belgium
| | - Nuno Bandeira
- Skaggs
School
of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States
- Center
for Computational Mass Spectrometry, Department of Computer Science
and Engineering, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego 92093-0404, United States
| | - Jeremy Carver
- Center
for Computational Mass Spectrometry, Department of Computer Science
and Engineering, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego 92093-0404, United States
| | - Benjamin Pullman
- Center
for Computational Mass Spectrometry, Department of Computer Science
and Engineering, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego 92093-0404, United States
| | - Zhi Sun
- Institute
for Systems Biology, Seattle, Washington 98109, United States
| | - Nils Hoffmann
- Institute
for Bio- and Geosciences (IBG-5), Forschungszentrum
Jülich GmbH, 52428 Jülich, Germany
| | - Jim Shofstahl
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Yunping Zhu
- National
Center for Protein Sciences (Beijing), Beijing
Institute of Lifeomics, #38, Life Science Park, Changping District, Beijing 102206, China
| | - Luana Licata
- Fondazione
Human Technopole, 20157 Milan, Italy
- Department
of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Federica Quaglia
- Institute
of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR-IBIOM), 70126 Bari, Italy
- Department
of Biomedical Sciences, University of Padova, 35131 Padova, Italy
| | | | - Sandra E. Orchard
- European
Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| |
Collapse
|
6
|
Lombard-Banek C, Pohl KI, Kwee EJ, Elliott JT, Schiel JE. A Sensitive and Controlled Data-Independent Acquisition Method for Proteomic Analysis of Cell Therapies. J Proteome Res 2022; 21:1229-1239. [PMID: 35404046 PMCID: PMC9087334 DOI: 10.1021/acs.jproteome.1c00887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Indexed: 11/29/2022]
Abstract
Mass spectrometry (MS)-based proteomic measurements are uniquely poised to impact the development of cell and gene therapies. With the adoption of rigorous instrumental performance qualifications (PQs), large-scale proteomics can move from a research to a manufacturing control tool. Especially suited, data-independent acquisition (DIA) approaches have distinctive qualities to extend multiattribute method (MAM) principles to characterize the proteome of cell therapies. Here, we describe the development of a DIA method for the sensitive identification and quantification of proteins on a Q-TOF instrument. Using the improved acquisition parameters, we defined a control strategy and highlighted some metrics to improve the reproducibility of SWATH acquisition-based proteomic measurements. Finally, we applied the method to analyze the proteome of Jurkat cells that here serves as a model for human T-cells. Raw and processed data were deposited in PRIDE (PXD029780).
Collapse
Affiliation(s)
- Camille Lombard-Banek
- National
Institute of Standards and Technology, Material and Measurements Laboratory, Gaithersburg, Maryland 20899, United States
- Institute
for Bioscience and Bioengineering Research, Rockville, Maryland 20850, United States
| | | | - Edward J. Kwee
- National
Institute of Standards and Technology, Material and Measurements Laboratory, Gaithersburg, Maryland 20899, United States
| | - John T. Elliott
- National
Institute of Standards and Technology, Material and Measurements Laboratory, Gaithersburg, Maryland 20899, United States
| | - John E. Schiel
- National
Institute of Standards and Technology, Material and Measurements Laboratory, Gaithersburg, Maryland 20899, United States
- Institute
for Bioscience and Bioengineering Research, Rockville, Maryland 20850, United States
| |
Collapse
|
7
|
Łącki MK, Startek MP, Brehmer S, Distler U, Tenzer S. OpenTIMS, TimsPy, and TimsR: Open and Easy Access to timsTOF Raw Data. J Proteome Res 2021; 20:2122-2129. [PMID: 33724840 DOI: 10.1021/acs.jproteome.0c00962] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The Bruker timsTOF Pro is an instrument that couples trapped ion mobility spectrometry (TIMS) to high-resolution time-of-flight (TOF) mass spectrometry (MS). For proteomics, lipidomics, and metabolomics applications, the instrument is typically interfaced with a liquid chromatography (LC) system. The resulting LC-TIMS-MS data sets are, in general, several gigabytes in size and are stored in the proprietary Bruker Tims data format (TDF). The raw data can be accessed using proprietary binaries in C, C++, and Python on Windows and Linux operating systems. Here we introduce a suite of computer programs for data accession, including OpenTIMS, TimsR, and TimsPy. OpenTIMS is a C++ library capable of reading Bruker TDF files. It opens up Bruker's proprietary codebase. TimsPy and TimsR build on top of OpenTIMS, enabling swift and user-friendly data access to the raw data with Python and R. Both programs are available under a GPL3 license on all major platforms, extending the possibility to interact with timsTOF data to macOS. Additionally, OpenTIMS is capable of translating Bruker data into HDF5 files that can be easily analyzed from Python with the vaex module. OpenTIMS and TimsPy therefore provide easy and quick access to Bruker timsTOF raw data.
Collapse
Affiliation(s)
- Mateusz K Łącki
- Institute of Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, 55131 Mainz, Germany
| | - Michał P Startek
- Department of Mathematics, Informatics, and Mechanics, University of Warsaw, 02-097 Warsaw, Poland
| | | | - Ute Distler
- Institute of Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, 55131 Mainz, Germany
| | - Stefan Tenzer
- Institute of Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, 55131 Mainz, Germany
| |
Collapse
|
8
|
Maia T, Staes A, Plasman K, Pauwels J, Boucher K, Argentini A, Martens L, Montoye T, Gevaert K, Impens F. Simple Peptide Quantification Approach for MS-Based Proteomics Quality Control. ACS OMEGA 2020; 5:6754-6762. [PMID: 32258910 PMCID: PMC7114614 DOI: 10.1021/acsomega.0c00080] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 03/04/2020] [Indexed: 06/11/2023]
Abstract
Despite its growing popularity and use, bottom-up proteomics remains a complex analytical methodology. Its general workflow consists of three main steps: sample preparation, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), and computational data analysis. Quality assessment of the different steps and components of this workflow is instrumental to identify technical flaws and avoid loss of precious measurement time and sample material. However, assessment of the extent of sample losses along with the sample preparation protocol, in particular, after proteolytic digestion, is not yet routinely implemented because of the lack of an accurate and straightforward method to quantify peptides. Here, we report on the use of a microfluidic UV/visible spectrophotometer to quantify MS-ready peptides directly in the MS-loading solvent, consuming only 2 μL of sample. We compared the performance of the microfluidic spectrophotometer with a standard device and determined the optimal sample amount for LC-MS/MS analysis on a Q Exactive HF mass spectrometer using a dilution series of a commercial K562 cell digest. A careful evaluation of selected LC and MS parameters allowed us to define 3 μg as an optimal peptide amount to be injected into this particular LC-MS/MS system. Finally, using tryptic digests from human HEK293T cells and showing that injecting equal peptide amounts, rather than approximate ones, result in less variable LC-MS/MS and protein quantification data. The obtained quality improvement together with easy implementation of the approach makes it possible to routinely quantify MS-ready peptides as a next step in daily proteomics quality control.
Collapse
Affiliation(s)
- Teresa
Mendes Maia
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- VIB
Proteomics Core, Albert
Baertsoenkaai 3, Ghent 9000, Belgium
| | - An Staes
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- VIB
Proteomics Core, Albert
Baertsoenkaai 3, Ghent 9000, Belgium
| | - Kim Plasman
- Alzheimer
Research Foundation, Kalkhoevestraat 1, Waregem 8790, Belgium
| | - Jarne Pauwels
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- VIB
Proteomics Core, Albert
Baertsoenkaai 3, Ghent 9000, Belgium
| | - Katie Boucher
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- VIB
Proteomics Core, Albert
Baertsoenkaai 3, Ghent 9000, Belgium
| | - Andrea Argentini
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Ghent 9000, Belgium
| | - Lennart Martens
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Ghent 9000, Belgium
| | - Tony Montoye
- Business
Development Management, VIB, Ghent 9000, Belgium
| | - Kris Gevaert
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
| | - Francis Impens
- VIB
Center for Medical Biotechnology, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- Department
of Biomolecular Medicine, Ghent University, Albert Baertsoenkaai 3, Ghent 9000, Belgium
- VIB
Proteomics Core, Albert
Baertsoenkaai 3, Ghent 9000, Belgium
| |
Collapse
|
9
|
Lombard-Banek C, Schiel JE. Mass Spectrometry Advances and Perspectives for the Characterization of Emerging Adoptive Cell Therapies. Molecules 2020; 25:E1396. [PMID: 32204371 PMCID: PMC7144572 DOI: 10.3390/molecules25061396] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 03/06/2020] [Accepted: 03/11/2020] [Indexed: 12/12/2022] Open
Abstract
Adoptive cell therapy is an emerging anti-cancer modality, whereby the patient's own immune cells are engineered to express T-cell receptor (TCR) or chimeric antigen receptor (CAR). CAR-T cell therapies have advanced the furthest, with recent approvals of two treatments by the Food and Drug Administration of Kymriah (trisagenlecleucel) and Yescarta (axicabtagene ciloleucel). Recent developments in proteomic analysis by mass spectrometry (MS) make this technology uniquely suited to enable the comprehensive identification and quantification of the relevant biochemical architecture of CAR-T cell therapies and fulfill current unmet needs for CAR-T product knowledge. These advances include improved sample preparation methods, enhanced separation technologies, and extension of MS-based proteomic to single cells. Innovative technologies such as proteomic analysis of raw material quality attributes (MQA) and final product quality attributes (PQA) may provide insights that could ultimately fuel development strategies and lead to broad implementation.
Collapse
Affiliation(s)
- Camille Lombard-Banek
- National Institute of Standards and Technology, Gaithersburg, MD 20899, USA;
- Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| | - John E. Schiel
- National Institute of Standards and Technology, Gaithersburg, MD 20899, USA;
- Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| |
Collapse
|
10
|
Jarnuczak AF, Ternent T, Vizcaíno JA. Quantitative Proteomics Data in the Public Domain: Challenges and Opportunities. Methods Mol Biol 2019; 1977:217-235. [PMID: 30980331 DOI: 10.1007/978-1-4939-9232-4_14] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Mass spectrometry based proteomics is no longer only a qualitative discipline, and can be successfully employed to obtain a truly multidimensional view of the proteome. In particular, systematic protein expression profiling is now a routine part of many studies in the field and beyond. The large growth in the number of quantitative studies is accompanied by a trend to share publicly the associated analysis results and the underlying raw data. This trend, established and strongly supported by public repositories such as the PRIDE database at the European Bioinformatics Institute, opens up enormous possibilities to explore the data beyond the original publications, for instance by reusing, reanalyzing, and performing different flavors of meta-analysis studies. To help researchers and scientists realize about this potential, here we describe the mainstream public proteomics resources containing quantitative proteomics data, including the processed analysis results and/or the underlying raw data. We then present and discuss the most important points to consider when attempting to (re)use proteomics data in the public domain. We conclude by highlighting potential pitfalls of (re)using quantitative data and discuss some of our own experiences in this context.
Collapse
Affiliation(s)
- Andrew F Jarnuczak
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Tobias Ternent
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
| |
Collapse
|
11
|
Bittremieux W, Tabb DL, Impens F, Staes A, Timmerman E, Martens L, Laukens K. Quality control in mass spectrometry-based proteomics. MASS SPECTROMETRY REVIEWS 2018; 37:697-711. [PMID: 28802010 DOI: 10.1002/mas.21544] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2017] [Revised: 07/24/2017] [Accepted: 07/24/2017] [Indexed: 05/21/2023]
Abstract
Mass spectrometry is a highly complex analytical technique and mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining accurate and reproducible results. Therefore, a comprehensive and systematic approach to quality control is an essential requirement to inspire confidence in the generated results. A typical mass spectrometry experiment consists of multiple different phases including the sample preparation, liquid chromatography, mass spectrometry, and bioinformatics stages. We review potential sources of variability that can impact the results of a mass spectrometry experiment occurring in all of these steps, and we discuss how to monitor and remedy the negative influences on the experimental results. Furthermore, we describe how specialized quality control samples of varying sample complexity can be incorporated into the experimental workflow and how they can be used to rigorously assess detailed aspects of the instrument performance.
Collapse
Affiliation(s)
- Wout Bittremieux
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Research Center Antwerp (Biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| | - David L Tabb
- Division of Molecular Biology and Human Genetics, Stellenbosch University Faculty of Medicine and Health Sciences, Tygerberg Hospital, Cape Town, South Africa
| | - Francis Impens
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - An Staes
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - Evy Timmerman
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Zwijnaarde, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Research Center Antwerp (Biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| |
Collapse
|
12
|
Chiva C, Olivella R, Borràs E, Espadas G, Pastor O, Solé A, Sabidó E. QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories. PLoS One 2018; 13:e0189209. [PMID: 29324744 PMCID: PMC5764250 DOI: 10.1371/journal.pone.0189209] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 11/21/2017] [Indexed: 01/03/2023] Open
Abstract
The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0.
Collapse
Affiliation(s)
- Cristina Chiva
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Roger Olivella
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Eva Borràs
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Guadalupe Espadas
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Olga Pastor
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Amanda Solé
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
| | - Eduard Sabidó
- Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona
- Universitat Pompeu Fabra (UPF), Barcelona, Barcelona
- * E-mail:
| |
Collapse
|
13
|
Deutsch EW, Orchard S, Binz PA, Bittremieux W, Eisenacher M, Hermjakob H, Kawano S, Lam H, Mayer G, Menschaert G, Perez-Riverol Y, Salek RM, Tabb DL, Tenzer S, Vizcaíno JA, Walzer M, Jones AR. Proteomics Standards Initiative: Fifteen Years of Progress and Future Work. J Proteome Res 2017; 16:4288-4298. [PMID: 28849660 PMCID: PMC5715286 DOI: 10.1021/acs.jproteome.7b00370] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Indexed: 12/21/2022]
Abstract
The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.
Collapse
Affiliation(s)
- Eric W. Deutsch
- Institute
for Systems Biology, Seattle, Washington 98109, United States
| | - Sandra Orchard
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Pierre-Alain Binz
- CHUV
Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland
| | - Wout Bittremieux
- Department
of Mathematics and Computer Science, University
of Antwerp, Middelheimlaan
1, 2020 Antwerp, Belgium
| | - Martin Eisenacher
- Medizinisches
Proteom Center (MPC), Ruhr-Universität
Bochum, D-44801 Bochum, Germany
| | - Henning Hermjakob
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
- State
Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing
Institute of Radiation Medicine, National
Center for Protein Sciences, Beijing, Beijing 102206, China
| | - Shin Kawano
- Database
Center for Life Science, Joint Support Center for Data Science Research,
Research Organization of Information and Systems, Kashiwa, Chiba 277-0871, Japan
| | - Henry Lam
- Division
of Biomedical Engineering, The Hong Kong
University of Science and Technology, Clear Water Bay, Hong Kong, P. R. China
- Department
of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, P. R. China
| | - Gerhard Mayer
- Medizinisches
Proteom Center (MPC), Ruhr-Universität
Bochum, D-44801 Bochum, Germany
| | - Gerben Menschaert
- Lab of Bioinformatics
and Computational Genomics (BioBix), Faculty of Bioscience Engineering, Ghent University, 9000 Ghent, Belgium
| | - Yasset Perez-Riverol
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Reza M. Salek
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - David L. Tabb
- SA
MRC Centre
for TB Research, DST/NRF Centre of Excellence for Biomedical TB Research,
Division of Molecular Biology and Human Genetics, Faculty of Medicine
and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Stefan Tenzer
- Institute
for Immunology, University Medical Center
of the Johannes-Gutenberg University Mainz, 55131 Mainz, Germany
| | - Juan Antonio Vizcaíno
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Mathias Walzer
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Andrew R. Jones
- Institute
of Integrative Biology, University of Liverpool, South Wirral L64 4AY, United Kingdom
| |
Collapse
|
14
|
Tay AP, Geoghegan V, Yagoub D, Wilkins MR, Hart-Smith G. MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data. J Proteome Res 2017; 17:359-373. [DOI: 10.1021/acs.jproteome.7b00601] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Aidan P. Tay
- NSW
Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Vincent Geoghegan
- Centre
for Immunology and Infection, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Daniel Yagoub
- NSW
Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Marc R. Wilkins
- NSW
Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Gene Hart-Smith
- NSW
Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| |
Collapse
|
15
|
Pfeuffer J, Sachsenberg T, Alka O, Walzer M, Fillbrunn A, Nilse L, Schilling O, Reinert K, Kohlbacher O. OpenMS – A platform for reproducible analysis of mass spectrometry data. J Biotechnol 2017; 261:142-148. [DOI: 10.1016/j.jbiotec.2017.05.016] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 05/17/2017] [Accepted: 05/22/2017] [Indexed: 10/19/2022]
|
16
|
Roos A, Thompson R, Horvath R, Lochmüller H, Sickmann A. Intersection of Proteomics and Genomics to "Solve the Unsolved" in Rare Disorders such as Neurodegenerative and Neuromuscular Diseases. Proteomics Clin Appl 2017; 12. [PMID: 29059504 DOI: 10.1002/prca.201700073] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 07/30/2017] [Indexed: 01/10/2023]
Abstract
Despite recent rapid advances in sequencing technologies, a significant proportion of patients with rare genetic disorders do not receive a genetic diagnosis after exhaustive testing, and even fewer have a potential therapeutic target identified. Taking rare neuromuscular and neurodegenerative disorders as a paradigm that can be extended to other rare Mendelian disorders, this viewpoint explores the opportunities that are brought about by the integration of genomics and proteomics, as well as the limitations and remaining challenges of this newly emerging field of proteogenomics. The relevance of combining proteomic findings with genetic results for diagnosis and gene discovery is illustrated, highlighting the insights the combined analysis provides into the underlying biology and aetiology as well as the limitations of the experimental techniques. A final discussion focuses on the importance of mechanisms to enable the sharing, reuse, and analysis of source experimental data and describes some of the international initiatives that are making progress in this area.
Collapse
Affiliation(s)
- Andreas Roos
- John Walton Muscular Dystrophy Research Centre, International Centre for Life, Institute of Genetic Medicine, Newcastle upon Tyne, England, UK.,Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany
| | - Rachel Thompson
- John Walton Muscular Dystrophy Research Centre, International Centre for Life, Institute of Genetic Medicine, Newcastle upon Tyne, England, UK
| | - Rita Horvath
- John Walton Muscular Dystrophy Research Centre, International Centre for Life, Institute of Genetic Medicine, Newcastle upon Tyne, England, UK
| | - Hanns Lochmüller
- John Walton Muscular Dystrophy Research Centre, International Centre for Life, Institute of Genetic Medicine, Newcastle upon Tyne, England, UK
| | - Albert Sickmann
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany.,Department of Chemistry, College of Physical Sciences, University of Aberdeen, Aberdeen, Scotland, UK.,Medizinisches Proteom-Center (MPC), Ruhr-Universitat Bochum, Bochum, Germany
| |
Collapse
|