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Zhou M, Lantz C, Brown KA, Ge Y, Paša-Tolić L, Loo JA, Lermyte F. Higher-order structural characterisation of native proteins and complexes by top-down mass spectrometry. Chem Sci 2020; 11:12918-12936. [PMID: 34094482 PMCID: PMC8163214 DOI: 10.1039/d0sc04392c] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 10/05/2020] [Indexed: 12/11/2022] Open
Abstract
In biology, it can be argued that if the genome contains the script for a cell's life cycle, then the proteome constitutes an ensemble cast of actors that brings these instructions to life. Their interactions with each other, co-factors, ligands, substrates, and so on, are key to understanding nearly any biological process. Mass spectrometry is well established as the method of choice to determine protein primary structure and location of post-translational modifications. In recent years, top-down fragmentation of intact proteins has been increasingly combined with ionisation of noncovalent assemblies under non-denaturing conditions, i.e., native mass spectrometry. Sequence, post-translational modifications, ligand/metal binding, protein folding, and complex stoichiometry can thus all be probed directly. Here, we review recent developments in this new and exciting field of research. While this work is written primarily from a mass spectrometry perspective, it is targeted to all bioanalytical scientists who are interested in applying these methods to their own biochemistry and chemical biology research.
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Affiliation(s)
- Mowei Zhou
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory Richland WA 99354 USA
| | - Carter Lantz
- Department of Chemistry and Biochemistry, Department of Biological Chemistry, University of California-Los Angeles Los Angeles CA 90095 USA
| | - Kyle A Brown
- Department of Chemistry, University of Wisconsin-Madison Madison WI 53706 USA
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison Madison WI 53706 USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison Madison WI 53706 USA
| | - Ljiljana Paša-Tolić
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory Richland WA 99354 USA
| | - Joseph A Loo
- Department of Chemistry and Biochemistry, Department of Biological Chemistry, University of California-Los Angeles Los Angeles CA 90095 USA
| | - Frederik Lermyte
- Department of Chemistry, Institute of Chemistry and Biochemistry, Technical University of Darmstadt 64287 Darmstadt Germany
- Mass Spectrometry Laboratory, MolSys Research Unit, University of Liège 4000 Liège Belgium
- School of Engineering, University of Warwick Coventry CV4 7AL UK
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Ciach MA, Miasojedow B, Skoraczyński G, Majewski S, Startek M, Valkenborg D, Gambin A. Masserstein: Linear regression of mass spectra by optimal transport. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2020:e8956. [PMID: 32996651 DOI: 10.1002/rcm.8956] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/31/2020] [Accepted: 09/25/2020] [Indexed: 06/11/2023]
Abstract
RATIONALE The linear regression of mass spectra is a computational problem defined as fitting a linear combination of reference spectra to an experimental one. It is typically used to estimate the relative quantities of selected ions. In this work, we study this problem in an abstract setting to develop new approaches applicable to a diverse range of experiments. METHODS To overcome the sensitivity of the ordinary least-squares regression to measurement inaccuracies, we base our methods on a non-conventional spectral dissimilarity measure, known as the Wasserstein or the Earth Mover's distance. This distance is based on the notion of the cost of transporting signal between mass spectra, which renders it naturally robust to measurement inaccuracies in the mass domain. RESULTS Using a data set of 200 mass spectra, we show that our approach is capable of estimating ion proportions accurately without extensive preprocessing of spectra required by other methods. The conclusions are further substantiated using data sets simulated in a way that mimics most of the measurement inaccuracies occurring in real experiments. CONCLUSIONS We have developed a linear regression algorithm based on the notion of the cost of transporting signal between spectra. Our implementation is available in a Python 3 package called masserstein, which is freely available at https://github.com/mciach/masserstein.
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Affiliation(s)
- Michał Aleksander Ciach
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
- Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
| | - Błażej Miasojedow
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Grzegorz Skoraczyński
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Szymon Majewski
- Institute of Mathematics, Polish Academy of Sciences, Warsaw, Poland
| | - Michał Startek
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Dirk Valkenborg
- Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
| | - Anna Gambin
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
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Affiliation(s)
- Mateusz K. Łącki
- Institute of Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, Mainz 55131, Germany
| | - Dirk Valkenborg
- Data Science Institute, Hasselt University, BE3500 Hasselt, Belgium
- Interuniversity Institute of Biostatistics and Statistical Bioinformatics, Hasselt University, BE3500 Hasselt, Belgium
- Center for Proteomics, University of Antwerp, 2000 Antwerp, Belgium
- Applied Bio and Molecular Systems, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
| | - Michał P. Startek
- Department of Mathematics, Informatics, and Mechanics, University of Warsaw, 02-097 Warsaw, Poland
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Basharat AR, Ning X, Liu X. EnvCNN: A Convolutional Neural Network Model for Evaluating Isotopic Envelopes in Top-Down Mass-Spectral Deconvolution. Anal Chem 2020; 92:7778-7785. [PMID: 32356965 PMCID: PMC7341906 DOI: 10.1021/acs.analchem.0c00903] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Top-down mass spectrometry has become the main method for intact proteoform identification, characterization, and quantitation. Because of the complexity of top-down mass spectrometry data, spectral deconvolution is an indispensable step in spectral data analysis, which groups spectral peaks into isotopic envelopes and extracts monoisotopic masses of precursor or fragment ions. The performance of spectral deconvolution methods relies heavily on their scoring functions, which distinguish correct envelopes from incorrect ones. A good scoring function increases the accuracy of deconvoluted masses reported from mass spectra. In this paper, we present EnvCNN, a convolutional neural network-based model for evaluating isotopic envelopes. We show that the model outperforms other scoring functions in distinguishing correct envelopes from incorrect ones and that it increases the number of identifications and improves the statistical significance of identifications in top-down spectral interpretation.
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Affiliation(s)
- Abdul Rehman Basharat
- School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, 46202, USA
| | - Xia Ning
- Department of Biomedical Informatics and Department of Computer Science and Engineering, Ohio State University, Columbus, Ohio, 43210, USA
| | - Xiaowen Liu
- School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
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Zhong J, Sun Y, Xie M, Peng W, Zhang C, Wu FX, Wang J. Proteoform characterization based on top-down mass spectrometry. Brief Bioinform 2020; 22:1729-1750. [PMID: 32118252 DOI: 10.1093/bib/bbaa015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 01/23/2020] [Indexed: 12/16/2022] Open
Abstract
Proteins are dominant executors of living processes. Compared to genetic variations, changes in the molecular structure and state of a protein (i.e. proteoforms) are more directly related to pathological changes in diseases. Characterizing proteoforms involves identifying and locating primary structure alterations (PSAs) in proteoforms, which is of practical importance for the advancement of the medical profession. With the development of mass spectrometry (MS) technology, the characterization of proteoforms based on top-down MS technology has become possible. This type of method is relatively new and faces many challenges. Since the proteoform identification is the most important process in characterizing proteoforms, we comprehensively review the existing proteoform identification methods in this study. Before identifying proteoforms, the spectra need to be preprocessed, and protein sequence databases can be filtered to speed up the identification. Therefore, we also summarize some popular deconvolution algorithms, various filtering algorithms for improving the proteoform identification performance and various scoring methods for localizing proteoforms. Moreover, commonly used methods were evaluated and compared in this review. We believe our review could help researchers better understand the current state of the development in this field and design new efficient algorithms for the proteoform characterization.
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Affiliation(s)
- Jiancheng Zhong
- College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China
| | - Yusui Sun
- College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China
| | - Minzhu Xie
- College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China
| | - Wei Peng
- Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Chushu Zhang
- College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China
| | - Fang-Xiang Wu
- College of Engineering and the Department of Computer Science at University of Saskatchewan, Saskatoon, Canada
| | - Jianxin Wang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering at Central South University, Changsha, Hunan, China
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Williams JP, Morrison LJ, Brown JM, Beckman JS, Voinov VG, Lermyte F. Top-Down Characterization of Denatured Proteins and Native Protein Complexes Using Electron Capture Dissociation Implemented within a Modified Ion Mobility-Mass Spectrometer. Anal Chem 2020; 92:3674-3681. [PMID: 31999103 DOI: 10.1021/acs.analchem.9b04763] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Electron-based fragmentation methods have revolutionized biomolecular mass spectrometry, in particular native and top-down protein analysis. Here, we report the use of a new electromagnetostatic cell to perform electron capture dissociation (ECD) within a quadrupole/ion mobility/time-of-flight mass spectrometer. This cell was installed between the ion mobility and time-of-flight regions of the instrument, and fragmentation was fast enough to be compatible with mobility separation. The instrument was already fitted with electron transfer dissociation (ETD) between the quadrupole and mobility regions prior to modification. We show excellent fragmentation efficiency for denatured peptides and proteins without the need to trap ions in the gas phase. Additionally, we demonstrate native top-down backbone fragmentation of noncovalent protein complexes, leading to comparable sequence coverage to what was achieved using the instrument's existing ETD capabilities. Limited collisional ion activation of the hemoglobin tetramer before ECD was reflected in the observed fragmentation pattern, and complementary ion mobility measurements prior to ECD provided orthogonal evidence of monomer unfolding within this complex. The approach demonstrated here provides a powerful platform for both top-down proteomics and mass spectrometry-based structural biology studies.
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Affiliation(s)
- Jonathan P Williams
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Lindsay J Morrison
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Jeffery M Brown
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Joseph S Beckman
- e-MSion Inc., 2121 NE Jack London Drive, Corvallis, Oregon 97330, United States.,Linus Pauling Institute and the Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon 97331, United States
| | - Valery G Voinov
- e-MSion Inc., 2121 NE Jack London Drive, Corvallis, Oregon 97330, United States.,Linus Pauling Institute and the Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon 97331, United States
| | - Frederik Lermyte
- School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom.,Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
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