|
1
|
Roberts DS, Loo JA, Tsybin YO, Liu X, Wu S, Chamot-Rooke J, Agar JN, Paša-Tolić L, Smith LM, Ge Y. Top-down proteomics. NATURE REVIEWS. METHODS PRIMERS 2024; 4:38. [PMID: 39006170 PMCID: PMC11242913 DOI: 10.1038/s43586-024-00318-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/24/2024] [Indexed: 07/16/2024]
Abstract
Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.
Collapse
Affiliation(s)
- David S Roberts
- Department of Chemistry, Stanford University, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Joseph A Loo
- Department of Chemistry and Biochemistry, Department of Biological Chemistry, University of California - Los Angeles, Los Angeles, CA, USA
| | | | - Xiaowen Liu
- Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA
| | - Si Wu
- Department of Chemistry and Biochemistry, The University of Alabama, Tuscaloosa, AL, USA
| | | | - Jeffrey N Agar
- Departments of Chemistry and Chemical Biology and Pharmaceutical Sciences, Northeastern University, Boston, MA, USA
| | - Ljiljana Paša-Tolić
- Environmental and Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin, Madison, WI, USA
| | - Ying Ge
- Department of Chemistry, University of Wisconsin, Madison, WI, USA
- Department of Cell and Regenerative Biology, Human Proteomics Program, University of Wisconsin - Madison, Madison, WI, USA
| |
Collapse
|
|
2
|
Choi IK, Abeysinghe E, Coulter E, Marru S, Pierce M, Liu X. TopPIC Gateway: A Web Gateway for Top-Down Mass Spectrometry Data Interpretation. PEARC20 : PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING 2020 : CATCH THE WAVE : JULY 27-31, 2020, PORTLAND, OR VIRTUAL CONFERENCE. PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING (CONFERENCE) (2020 : ONLINE) 2020; 2020:461-464. [PMID: 35615582 PMCID: PMC9128478 DOI: 10.1145/3311790.3400853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Top-down mass spectrometry-based proteomics has become the method of choice for identifying and quantifying intact proteoforms in biological samples. We present a web-based gateway for TopPIC suite, a widely used software suite consisting of four software tools for top-down mass spectrometry data interpretation: TopFD, TopPIC, TopMG, and TopDiff. The gateway enables the community to use heterogeneous collection of computing resources that includes high performance computing clusters at Indiana University and virtual clusters on XSEDE's Jetstream Cloud resource for top-down mass spectral data analysis using TopPIC suite. The gateway will be a useful resource for proteomics researchers and students who have limited access to high-performance computing resources or who are not familiar with interacting with server-side supercomputers.
Collapse
Affiliation(s)
- In Kwon Choi
- Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis
| | - Eroma Abeysinghe
- Cyberinfrastructure Integration Research Center, Indiana University
| | - Eric Coulter
- Cyberinfrastructure Integration Research Center, Indiana University
| | - Suresh Marru
- Cyberinfrastructure Integration Research Center, Indiana University
| | - Marlon Pierce
- Cyberinfrastructure Integration Research Center, Indiana University
| | - Xiaowen Liu
- Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis
| |
Collapse
|
|
3
|
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.
Collapse
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
| |
Collapse
|
|
4
|
Schaffer LV, Millikin RJ, Miller RM, Anderson LC, Fellers RT, Ge Y, Kelleher NL, LeDuc RD, Liu X, Payne SH, Sun L, Thomas PM, Tucholski T, Wang Z, Wu S, Wu Z, Yu D, Shortreed MR, Smith LM. Identification and Quantification of Proteoforms by Mass Spectrometry. Proteomics 2019; 19:e1800361. [PMID: 31050378 PMCID: PMC6602557 DOI: 10.1002/pmic.201800361] [Citation(s) in RCA: 128] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 04/07/2019] [Indexed: 12/29/2022]
Abstract
A proteoform is a defined form of a protein derived from a given gene with a specific amino acid sequence and localized post-translational modifications. In top-down proteomic analyses, proteoforms are identified and quantified through mass spectrometric analysis of intact proteins. Recent technological developments have enabled comprehensive proteoform analyses in complex samples, and an increasing number of laboratories are adopting top-down proteomic workflows. In this review, some recent advances are outlined and current challenges and future directions for the field are discussed.
Collapse
Affiliation(s)
- Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Robert J Millikin
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Rachel M Miller
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Lissa C Anderson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, FL, 32310, USA
| | - Ryan T Fellers
- Proteomics Center of Excellence, Northwestern University, Evanston, IL, 60208, USA
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Cell and Regenerative Biology and Human Proteomics Program, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Neil L Kelleher
- Proteomics Center of Excellence, Northwestern University, Evanston, IL, 60208, USA
- Department of Chemistry and Molecular Biosciences and the Division of Hematology and Oncology, Northwestern University, Evanston, IL, 60208, USA
| | - Richard D LeDuc
- Proteomics Center of Excellence, Northwestern University, Evanston, IL, 60208, USA
| | - Xiaowen Liu
- Department of BioHealth Informatics, Indiana University-Purdue University, Indianapolis, IN, 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, UT, 84602
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA
| | - Paul M Thomas
- Proteomics Center of Excellence, Northwestern University, Evanston, IL, 60208, USA
| | - Trisha Tucholski
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Zhe Wang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Zhijie Wu
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Dahang Yu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| |
Collapse
|