1
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Habeck T, Brown KA, Des Soye B, Lantz C, Zhou M, Alam N, Hossain MA, Jung W, Keener JE, Volny M, Wilson JW, Ying Y, Agar JN, Danis PO, Ge Y, Kelleher NL, Li H, Loo JA, Marty MT, Paša-Tolić L, Sandoval W, Lermyte F. Top-down mass spectrometry of native proteoforms and their complexes: a community study. Nat Methods 2024:10.1038/s41592-024-02279-6. [PMID: 38744918 DOI: 10.1038/s41592-024-02279-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 04/10/2024] [Indexed: 05/16/2024]
Abstract
The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.
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Affiliation(s)
- Tanja Habeck
- Technische Universität Darmstadt, Darmstadt, Germany
| | - Kyle A Brown
- University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Mowei Zhou
- Pacific Northwest National Laboratory, Richland, WA, USA
- Zhejiang University, Zhejiang, China
| | | | | | | | | | | | - Jesse W Wilson
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yujia Ying
- Sun Yat-sen University, Guangzhou, China
| | - Jeffrey N Agar
- Northeastern University, Boston, MA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Paul O Danis
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Ying Ge
- University of Wisconsin-Madison, Madison, WI, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Neil L Kelleher
- Northwestern University, Evanston, IL, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Huilin Li
- Sun Yat-sen University, Guangzhou, China
| | - Joseph A Loo
- University of California, Los Angeles, CA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | | | - Ljiljana Paša-Tolić
- Pacific Northwest National Laboratory, Richland, WA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
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2
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Barnidge D, Troske D, North S, Wallis G, Perkins M, Harding S. Endogenous monoclonal immunoglobulins analyzed using the EXENT® solution and LC-MS. J Mass Spectrom Adv Clin Lab 2024; 32:31-40. [PMID: 38405412 PMCID: PMC10891330 DOI: 10.1016/j.jmsacl.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/27/2024] Open
Abstract
Introduction The EXENT® Solution, a fully automated system, is a recent advancement for identifying and quantifying monoclonal immunoglobulins in serum. It combines immunoprecipitation with MALDI-TOF mass spectrometry. Compared to gel-based methods, like SPEP and IFE, it has demonstrated the ability to detect monoclonal immunoglobulins in serum at lower levels. In this study, samples that tested negative using EXENT® were reflexed to LC-MS to determine if the more sensitive LC-MS method could identify monoclonal immunoglobulins missed by EXENT®. Objectives To assess whether monoclonal immunoglobulins that are not detected by EXENT® can be detected by LC-MS using a low flow LC system coupled to a Q-TOF mass spectrometer. Methods Samples obtained from patients confirmed to have multiple myeloma (MM) were diluted with pooled polyclonal human serum and analyzed using EXENT®. If a specific monoclonal immunoglobulin was not detected by EXENT®, the sample was then subjected to analysis by LC-MS. For the LC-MS analysis, the sample eluate, obtained after the MALDI-TOF MS spotting step, was collected and transferred to an autosampler tray for subsequent analysis using LC-MS. Conclusion LC-MS has the capability to detect monoclonal immunoglobulins that are no longer detected by EXENT®. Reflexing samples to LC-MS for analysis does not involve additional sample handling, allowing for a faster time-to-result compared to current approaches, such as Next-Generation Sequencing, Next-Generation Flow, and clonotypic peptide methods. Notably, LC-MS offers equivalent sensitivity in detecting these specific monoclonal immunoglobulins.
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Affiliation(s)
- David Barnidge
- The Binding Site, Part of ThermoFisher Scientific Research and Development Laboratory, 3777 40th Ave NW, Rochester, MN 55906, United States
| | - Derek Troske
- The Binding Site, Part of ThermoFisher Scientific Research and Development Laboratory, 3777 40th Ave NW, Rochester, MN 55906, United States
| | - Simon North
- The Binding Site, Part of ThermoFisher Scientific, The Binding Site Group Ltd, 8 Calthorpe Road Edgbaston, Birmingham, UK
| | - Gregg Wallis
- The Binding Site, Part of ThermoFisher Scientific, The Binding Site Group Ltd, 8 Calthorpe Road Edgbaston, Birmingham, UK
| | - Mark Perkins
- The Binding Site, Part of ThermoFisher Scientific, The Binding Site Group Ltd, 8 Calthorpe Road Edgbaston, Birmingham, UK
| | - Stephen Harding
- The Binding Site, Part of ThermoFisher Scientific, The Binding Site Group Ltd, 8 Calthorpe Road Edgbaston, Birmingham, UK
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3
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Harvey SR, Gadkari VV, Ruotolo BT, Russell DH, Wysocki VH, Zhou M. Expanding Native Mass Spectrometry to the Masses. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:646-652. [PMID: 38303101 DOI: 10.1021/jasms.3c00352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
At the 33rd ASMS Sanibel Meeting, on Membrane Proteins and Their Complexes, a morning roundtable discussion was held discussing the current challenges facing the field of native mass spectrometry and approaches to expanding the field to nonexperts. This Commentary summarizes the discussion and current initiatives to address these challenges.
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Affiliation(s)
- Sophie R Harvey
- Department of Chemistry and Biochemistry, Native Mass Spectrometry Guided Structural Biology Center, The Ohio State University, Columbus, Ohio, 43210, United States
| | - Varun V Gadkari
- Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Brandon T Ruotolo
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - David H Russell
- Department of Chemistry, Texas A&M University, College Station, Texas 77844, United States
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry, Native Mass Spectrometry Guided Structural Biology Center, The Ohio State University, Columbus, Ohio, 43210, United States
| | - Mowei Zhou
- Department of Chemistry, Zhejiang University, Hangzhou, Zhejiang 310058, China
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4
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Jeong K, Kaulich PT, Jung W, Kim J, Tholey A, Kohlbacher O. Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics. Proteomics 2024; 24:e2300068. [PMID: 37997224 DOI: 10.1002/pmic.202300068] [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: 04/26/2023] [Revised: 11/09/2023] [Accepted: 11/13/2023] [Indexed: 11/25/2023]
Abstract
Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.
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Affiliation(s)
- Kyowon Jeong
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Philipp T Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Wonhyeuk Jung
- Department of Cell Biology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jihyung Kim
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Oliver Kohlbacher
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
- Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany
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5
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Villacob RA, Feizi N, Beno SC, Solouki T. Collision-Induced Unfolding, Tandem MS, Bottom-up Proteomics, and Interactomics for Identification of Protein Complexes in Native Surface Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:13-30. [PMID: 38095581 DOI: 10.1021/jasms.3c00261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
Endogenously occurring salts and nonvolatile matrix components in untreated biological surfaces can suppress protein ionization and promote adduct formation, challenging protein identification. Characterization of labile proteins within biological specimens is particularly demanding because additional purification or sample treatment steps can be time-intensive and can disrupt noncovalent interactions. It is demonstrated that the combined use of collision-induced unfolding, tandem mass spectrometry, and bottom-up proteomics improves protein characterization in native surface mass spectrometry (NSMS). This multiprong analysis is achieved by acquiring NSMS, MS/MS, ion mobility (IM), and bottom-up proteomics data from a single surface extracted sample. The validity of this multiprong approach was confirmed by the successful characterization of nine surface-deposited proteins, with molecular weights ranging from 8 to 147 kDa, in two separate mixtures. Bottom-up proteomics provided a list of proteins to match against observed proteins in NSMS and their detected subunits in tandem MS. The method was applied to characterize endogenous proteins from untreated chicken liver samples. The subcapsular liver sampling for NSMS analysis allowed for the detection of endogenous proteins with molecular weights of up to ∼220 kDa. Moreover, using IM-MS, collision cross sections and collision-induced unfolding pathways of enzymatic proteins and protein complexes of up to 145 kDa were obtained.
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Affiliation(s)
- Raul A Villacob
- Department of Chemistry and Biochemistry, Baylor University, Waco, Texas 76798, United States
| | - Neda Feizi
- Department of Chemistry and Biochemistry, Baylor University, Waco, Texas 76798, United States
| | - Sarah C Beno
- Department of Chemistry and Biochemistry, Baylor University, Waco, Texas 76798, United States
| | - Touradj Solouki
- Department of Chemistry and Biochemistry, Baylor University, Waco, Texas 76798, United States
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6
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Lermyte F, Habeck T, Brown K, Des Soye B, Lantz C, Zhou M, Alam N, Hossain MA, Jung W, Keener J, Volny M, Wilson J, Ying Y, Agar J, Danis P, Ge Y, Kelleher N, Li H, Loo J, Marty M, Pasa-Tolic L, Sandoval W. Top-down mass spectrometry of native proteoforms and their complexes: A community study. RESEARCH SQUARE 2023:rs.3.rs-3228472. [PMID: 37674709 PMCID: PMC10479449 DOI: 10.21203/rs.3.rs-3228472/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
The combination of native electrospray ionisation with top-down fragmentation in mass spectrometry allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and co-factors. While this approach is powerful, both native mass spectrometry and top-down mass spectrometry are not yet well standardised, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics (CTDP) initiated a study to develop and test protocols for native mass spectrometry combined with top-down fragmentation of proteins and protein complexes across eleven instruments in nine laboratories. The outcomes are summarised in this report to provide robust benchmarks and a valuable entry point for the scientific community.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | - Jeffrey Agar
- Department of Chemistry and Chemical Biology, Northeastern University
| | | | - Ying Ge
- University of Wisconsin-Madison
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7
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Phung W, Bakalarski CE, Hinkle TB, Sandoval W, Marty MT. UniDec Processing Pipeline for Rapid Analysis of Biotherapeutic Mass Spectrometry Data. Anal Chem 2023; 95:11491-11498. [PMID: 37478487 DOI: 10.1021/acs.analchem.3c02010] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2023]
Abstract
Recent advances in native mass spectrometry (MS) and denatured intact protein MS have made these techniques essential for biotherapeutic characterization. As MS analysis has increased in throughput and scale, new data analysis workflows are needed to provide rapid quantitation from large datasets. Here, we describe the UniDec processing pipeline (UPP) for the analysis of batched biotherapeutic intact MS data. UPP is built into the UniDec software package, which provides fast processing, deconvolution, and peak detection. The user and programming interfaces for UPP read a spreadsheet that contains the data file names, deconvolution parameters, and quantitation settings. After iterating through the spreadsheet and analyzing each file, it returns a spreadsheet of results and HTML reports. We demonstrate the use of UPP to measure the correct pairing percentage on a set of bispecific antibody data and to measure drug-to-antibody ratios from antibody-drug conjugates. Moreover, because the software is free and open-source, users can easily build on this platform to create customized workflows and calculations. Thus, UPP provides a flexible workflow that can be deployed in diverse settings and for a wide range of biotherapeutic applications.
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Affiliation(s)
- Wilson Phung
- Microchemistry, Proteomics, and Lipidomics Department, Genentech, Inc., South San Francisco, California 94080, United States
| | - Corey E Bakalarski
- Microchemistry, Proteomics, and Lipidomics Department, Genentech, Inc., South San Francisco, California 94080, United States
| | - Trent B Hinkle
- Microchemistry, Proteomics, and Lipidomics Department, Genentech, Inc., South San Francisco, California 94080, United States
| | - Wendy Sandoval
- Microchemistry, Proteomics, and Lipidomics Department, Genentech, Inc., South San Francisco, California 94080, United States
| | - Michael T Marty
- Department of Chemistry and Biochemistry and the Bio5 Institute, University of Arizona, Tucson, Arizona 85721, United States
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8
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Keating AR, Wesdemiotis C. Rapid and simple determination of average molecular weight and composition of synthetic polymers via electrospray ionization-mass spectrometry and a Bayesian universal charge deconvolution. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2023; 37:e9478. [PMID: 36669764 DOI: 10.1002/rcm.9478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 01/17/2023] [Accepted: 01/18/2023] [Indexed: 06/17/2023]
Abstract
RATIONALE Simple, affordable, and rapid methods for identifying the molecular weight (MW) distribution and macromolecular composition of polymeric materials are limited. Current tools require extensive solvent consumption, linear calibrations, and expensive consumables. A simple method for the determination of average MW (Mn , Mw ) and chain end groups is demonstrated for synthetic homopolymer standards using direct injection electrospray ionization-mass spectrometry (ESI-MS) and an open-sourced charge deconvolution (CDC) algorithm. METHODS Five homopolymer standards in the 1-7 kDa MW range were analyzed using direct-injection ESI-MS on a quadrupole/time-of-flight mass spectrometer. The samples investigated, viz. two poly(ethylene oxide) (PEO) and two poly(styrene sulfonic acid) (PSS) standards with narrow polydispersity and one poly(d,l-alanine) (pAla) standard with undefined polydispersity, were chosen to illustrate challenges with ESI-MS quantitation. Using the UniDec program, weight average MWs (Mw ) obtained from the charge-deconvoluted spectra were compared to the reported Mw data of the standards from size exclusion chromatography (SEC) measurements. RESULTS The MW data derived for the PSS, PEO, and pAla standards agreed well with the corresponding reported Mw or MW range values. The method was able to provide MW, degree of polymerization (DP), and polydispersity index (PDI) information for polymers with narrow (PSS, PEO) as well as broader (pAla) molecular weight distribution; this feature provides an advantage over MW analysis via matrix-assisted laser desorption/ionization (MALDI) for ESI-compatible materials. PSS standards differing in average MW by only a few repeat units could be confidently distinguished. Additionally, the oligomeric resolution observed for all samples studied unveiled chain-end information not available through chromatographic analysis. CONCLUSIONS Overall, the free and easy-to-use UniDec CDC algorithm provides a simple, alternative method to measuring MW and DP for polymeric materials without high solvent consumption, expensive ionization sources, or calibration curves. Information about the masses of individual oligomers and the possibility to further characterize these oligomers using tandem mass spectrometry and/or ion mobility techniques constitutes additional benefits of this approach vis-à-vis traditional MW and PDI elucidation through SEC.
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Affiliation(s)
- Addie R Keating
- Department of Chemistry, The University of Akron, Akron, Ohio, USA
| | - Chrys Wesdemiotis
- Department of Chemistry, The University of Akron, Akron, Ohio, USA
- School of Polymer Science and Polymer Engineering, The University of Akron, Akron, Ohio, USA
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9
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Villacob RA, Egbejiogu BC, Feizi N, Hogan C, Murray KK, Solouki T. Native Mass Spectrometry and Collision-Induced Unfolding of Laser-Ablated Proteins. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:2215-2225. [PMID: 36346890 DOI: 10.1021/jasms.2c00184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Infrared laser ablation sample transfer (LAST) was used to collect samples from solid surfaces for mass spectrometry under native spray conditions. Native mass spectrometry was utilized to probe the charge states and collision-induced unfolding (CIU) characteristics of bovine serum albumin (BSA), bovine hemoglobin (BHb), and jack-bean concanavalin A (ConA) via direct injection electrospray, after liquid extraction surface sampling, and after LAST. Each protein was deposited from solution on solid surfaces and laser-ablated for off-line analysis or sampled for online analysis. It was found that the protein ion gas-phase charge-state distributions were comparable for direct infusion, liquid extraction, and laser ablation experiments. Moreover, calculated average collision cross section (CCS) values from direct injection, liquid extraction, and laser ablation experiments were consistent with previously reported literature values. Additionally, an equivalent number of mobility features and conformational turnovers were identified from unfolding pathways from all three methods for all charge states of each protein analyzed in this work. The presented work suggests that laser ablation yields intact proteins (BSA, BHb, and ConA), is compatible with native mass spectrometry, and could be suitable for spatially resolved interrogation of unfolding pathways of proteins.
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Affiliation(s)
| | | | - Neda Feizi
- Baylor University, Waco, Texas 76706, United States
| | - Cole Hogan
- Baylor University, Waco, Texas 76706, United States
| | - Kermit K Murray
- Louisiana State University, Baton Rouge, Louisiana 70803, United States
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10
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Marty MT. Fundamentals: How Do We Calculate Mass, Error, and Uncertainty in Native Mass Spectrometry? JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:1807-1812. [PMID: 36130030 DOI: 10.1021/jasms.2c00218] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mass spectrometry (MS) is uniquely powerful for measuring the mass of intact proteins and other biomolecules. New applications have expanded intact protein analysis into biopharmaceuticals, native MS, and top-down proteomics, all of which have driven the need for more automated data-processing pipelines. However, key metrics in the field are often not precisely defined. For example, there are different views on how to calculate uncertainty from spectra. This Critical Insight will explore the different definitions of mass, error, and uncertainty. It will discuss situations where different definitions may be more suitable and provide recommendations for best practices. Targeting both beginners and experts, the goal of the discussion is to provide a common foundation of terminology, enhance statistical rigor, and improve automation of data analysis.
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Affiliation(s)
- Michael T Marty
- Department of Chemistry and Biochemistry and Bio5 Institute, University of Arizona, Tucson, Arizona 85721, United States
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11
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Boiko DA, Kozlov KS, Burykina JV, Ilyushenkova VV, Ananikov VP. Fully Automated Unconstrained Analysis of High-Resolution Mass Spectrometry Data with Machine Learning. J Am Chem Soc 2022; 144:14590-14606. [PMID: 35939718 DOI: 10.1021/jacs.2c03631] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Mass spectrometry (MS) is a convenient, highly sensitive, and reliable method for the analysis of complex mixtures, which is vital for materials science, life sciences fields such as metabolomics and proteomics, and mechanistic research in chemistry. Although it is one of the most powerful methods for individual compound detection, complete signal assignment in complex mixtures is still a great challenge. The unconstrained formula-generating algorithm, covering the entire spectra and revealing components, is a "dream tool" for researchers. We present the framework for efficient MS data interpretation, describing a novel approach for detailed analysis based on deisotoping performed by gradient-boosted decision trees and a neural network that generates molecular formulas from the fine isotopic structure, approaching the long-standing inverse spectral problem. The methods were successfully tested on three examples: fragment ion analysis in protein sequencing for proteomics, analysis of the natural samples for life sciences, and study of the cross-coupling catalytic system for chemistry.
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Affiliation(s)
- Daniil A Boiko
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow 119991, Russia
| | - Konstantin S Kozlov
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow 119991, Russia
| | - Julia V Burykina
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow 119991, Russia
| | - Valentina V Ilyushenkova
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow 119991, Russia
| | - Valentine P Ananikov
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow 119991, Russia
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12
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Jeong K, Babović M, Gorshkov V, Kim J, Jensen ON, Kohlbacher O. FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts. Nat Commun 2022; 13:4407. [PMID: 35906205 PMCID: PMC9338294 DOI: 10.1038/s41467-022-31922-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 07/07/2022] [Indexed: 11/17/2022] Open
Abstract
The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.
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Affiliation(s)
- Kyowon Jeong
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Sand 14, 72076, Tübingen, Germany.
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany.
| | - Maša Babović
- Department of Biochemistry & Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Odense, Denmark
| | - Vladimir Gorshkov
- Department of Biochemistry & Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Odense, Denmark
| | - Jihyung Kim
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Sand 14, 72076, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany
| | - Ole N Jensen
- Department of Biochemistry & Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Odense, Denmark
| | - Oliver Kohlbacher
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Sand 14, 72076, Tübingen, Germany.
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany.
- Translational Bioinformatics, University Hospital Tübingen, Hoppe-Seyler-Str. 9, 72076, Tübingen, Germany.
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13
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Lusci G, Pivetta T, Carucci C, Parsons DF, Salis A, Monduzzi M. BSA fragmentation specifically induced by added electrolytes: An electrospray ionization mass spectrometry investigation. Colloids Surf B Biointerfaces 2022; 218:112726. [PMID: 35914467 DOI: 10.1016/j.colsurfb.2022.112726] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/16/2022] [Accepted: 07/24/2022] [Indexed: 10/16/2022]
Abstract
Biointerfaces are significantly affected by electrolytes according to the Hofmeister series. This work reports a systematic investigation on the effect of different metal chlorides, sodium and potassium bromides, iodides and thiocyanates, on the ESI/MS spectra of bovine serum albumin (BSA) in aqueous solution at pH = 2.7. The concentration of each salt was varied to maximize the quality of the ESI/MS spectrum, in terms of peak intensity and bell-shaped profile. The ESI/MS spectra of BSA in the absence and in the presence of salts showed a main protein pattern characterized by the expected mass of 66.5 kDa, except the case of BSA/RbCl (mass 65.3 kDa). In all systems we observed an additional pattern, characterized by at least three peaks with low intensity, whose deconvolution led to suggest the formation of a BSA fragment with a mass of 19.2 kDa. Only NaCl increased the intensity of the peaks of the main BSA pattern, while minimizing that of the fragment. NaCl addition seems to play a crucial role in stabilizing the BSA ionized interface against hydrolysis of peptide bonds, through different synergistic mechanisms. To quantify the observed specific electrolyte effects, two "Hofmeister" parameters (Hs and Ps) are proposed. They are obtained using the ratio of (BSA-Salt)/BSA peak intensities for both the BSA main pattern and for its fragment. SYNOPSIS: NaCl stabilizes BSA ion and almost prevents fragmentation due to denaturing pH.
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Affiliation(s)
- Gloria Lusci
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy
| | - Tiziana Pivetta
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy
| | - Cristina Carucci
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy; Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande Interfase (CSGI), via della Lastruccia 3, 50019, Sesto Fiorentino (FI), Italy. Unità Operativa University of Cagliari, Cittadella Universitaria, SS 554 bivio Sestu, 09042 Monserrato (CA), Italy
| | - Drew Francis Parsons
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy; Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande Interfase (CSGI), via della Lastruccia 3, 50019, Sesto Fiorentino (FI), Italy. Unità Operativa University of Cagliari, Cittadella Universitaria, SS 554 bivio Sestu, 09042 Monserrato (CA), Italy.
| | - Andrea Salis
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy; Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande Interfase (CSGI), via della Lastruccia 3, 50019, Sesto Fiorentino (FI), Italy. Unità Operativa University of Cagliari, Cittadella Universitaria, SS 554 bivio Sestu, 09042 Monserrato (CA), Italy.
| | - Maura Monduzzi
- Dept. Chemical and Geological Science, University of Cagliari, Cittadella Universitaria, S.S. 554 bivio Sestu, 09042 Monserrato, Cagliari, Italy; Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande Interfase (CSGI), via della Lastruccia 3, 50019, Sesto Fiorentino (FI), Italy. Unità Operativa University of Cagliari, Cittadella Universitaria, SS 554 bivio Sestu, 09042 Monserrato (CA), Italy.
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14
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Abstract
Native mass spectrometry (MS) is aimed at preserving and determining the native structure, composition, and stoichiometry of biomolecules and their complexes from solution after they are transferred into the gas phase. Major improvements in native MS instrumentation and experimental methods over the past few decades have led to a concomitant increase in the complexity and heterogeneity of samples that can be analyzed, including protein-ligand complexes, protein complexes with multiple coexisting stoichiometries, and membrane protein-lipid assemblies. Heterogeneous features of these biomolecular samples can be important for understanding structure and function. However, sample heterogeneity can make assignment of ion mass, charge, composition, and structure very challenging due to the overlap of tens or even hundreds of peaks in the mass spectrum. In this review, we cover data analysis, experimental, and instrumental advances and strategies aimed at solving this problem, with an in-depth discussion of theoretical and practical aspects of the use of available deconvolution algorithms and tools. We also reflect upon current challenges and provide a view of the future of this exciting field.
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Affiliation(s)
- Amber D. Rolland
- Department of Chemistry and Biochemistry, 1253 University of Oregon, Eugene, OR, USA 97403-1253
| | - James S. Prell
- Department of Chemistry and Biochemistry, 1253 University of Oregon, Eugene, OR, USA 97403-1253
- Materials Science Institute, 1252 University of Oregon, Eugene, OR, USA 97403-1252
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15
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Abstract
Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of─among others─biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein-ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.
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Affiliation(s)
- Sem Tamara
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584
CH Utrecht, The Netherlands
- Netherlands
Proteomics Center, Padualaan
8, 3584 CH Utrecht, The Netherlands
| | - Maurits A. den Boer
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584
CH Utrecht, The Netherlands
- Netherlands
Proteomics Center, Padualaan
8, 3584 CH Utrecht, The Netherlands
| | - Albert J. R. Heck
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584
CH Utrecht, The Netherlands
- Netherlands
Proteomics Center, Padualaan
8, 3584 CH Utrecht, The Netherlands
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16
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Abstract
Intact protein, top-down, and native mass spectrometry (MS) generally requires the deconvolution of electrospray ionization (ESI) mass spectra to assign the mass of components from their charge state distribution. For small, well-resolved proteins, the charge can usually be assigned based on the isotope distribution. However, it can be challenging to determine charge states with larger proteins that lack isotopic resolution, in complex mass spectra with overlapping charge states, and in native spectra that show adduction. To overcome these challenges, UniDec uses Bayesian deconvolution to assign charge states and to create a zero-charge mass distribution. UniDec is fast, user-friendly, and includes a range of advanced tools to assist in intact protein, top-down, and native MS data analysis. This chapter provides a step-by-step protocol and an in-depth explanation of the UniDec algorithm, and highlights the parameters that affect the deconvolution. It also covers advanced data analysis tools, such as macromolecular mass defect analysis and tools for assigning potential PTMs and bound ligands. Overall, this chapter provides users with a deeper understanding of UniDec, which will enhance the quality of deconvolutions and allow for more intricate MS experiments.
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Affiliation(s)
- Marius M Kostelic
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA
| | - Michael T Marty
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA.
- Bio5 Institute, University of Arizona, Tucson, AZ, USA.
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17
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Abstract
Iron-sulfur clusters constitute a large and widely distributed group of protein cofactors that play key roles in a wide range of metabolic processes. The inherent reactivity of iron-sulfur clusters toward small molecules, for example, O2, NO, or free Fe, makes them ideal for sensing changes in the cellular environment. Nondenaturing, or native, MS is unique in its ability to preserve the noncovalent interactions of many (if not all) species, including stable intermediates, while providing accurate mass measurements in both thermodynamic and kinetic experimental regimes. Here, we provide practical guidance for the study of iron-sulfur proteins by native MS, illustrated by examples where it has been used to unambiguously determine the type of cluster coordinated to the protein framework. We also describe the use of time-resolved native MS to follow the kinetics of cluster conversion, allowing the elucidation of the precise series of molecular events for all species involved. Finally, we provide advice on a unique approach to a typical thermodynamic titration, uncovering early, quasi-stable, intermediates in the reaction of a cluster with nitric oxide, resulting in cluster nitrosylation.
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Affiliation(s)
- Jason C Crack
- Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, UK
| | - Nick E Le Brun
- Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, UK.
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18
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Marty MT. Nanodiscs and Mass Spectrometry: Making Membranes Fly. INTERNATIONAL JOURNAL OF MASS SPECTROMETRY 2020; 458:116436. [PMID: 33100891 PMCID: PMC7584149 DOI: 10.1016/j.ijms.2020.116436] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Cells are surrounded by a protective lipid bilayer membrane, and membrane proteins in the bilayer control the flow of chemicals, information, and energy across this barrier. Many therapeutics target membrane proteins, and some directly target the lipid membrane itself. However, interactions within biological membranes are challenging to study due to their heterogeneity and insolubility. Mass spectrometry (MS) has become a powerful technique for studying membrane proteins, especially how membrane proteins interact with their surrounding lipid environment. Although detergent micelles are the most common membrane mimetic, nanodiscs are emerging as a promising platform for MS. Nanodiscs, nanoscale lipid bilayers encircled by two scaffold proteins, provide a controllable lipid bilayer for solubilizing membrane proteins. This Young Scientist Perspective focuses on native MS of intact nanodiscs and highlights the unique experiments enabled by making membranes fly, including studying membrane protein-lipid interactions and exploring the specificity of fragile transmembrane peptide complexes. It will also explore current challenges and future perspectives for interfacing nanodiscs with MS.
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Affiliation(s)
- Michael T Marty
- Department of Chemistry and Biochemistry and Bio5 Institute, University of Arizona, Tucson, AZ 85721
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19
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Barth M, Schmidt C. Native mass spectrometry-A valuable tool in structural biology. JOURNAL OF MASS SPECTROMETRY : JMS 2020; 55:e4578. [PMID: 32662584 DOI: 10.1002/jms.4578] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 05/18/2020] [Accepted: 05/19/2020] [Indexed: 05/16/2023]
Abstract
Proteins and the complexes they form with their ligands are the players of cellular action. Their function is directly linked with their structure making the structural analysis of protein-ligand complexes essential. Classical techniques of structural biology include X-ray crystallography, nuclear magnetic resonance spectroscopy and recently distinguished cryo-electron microscopy. However, protein-ligand complexes are often dynamic and heterogeneous and consequently challenging for these techniques. Alternative approaches are therefore needed and gained importance during the last decades. One alternative is native mass spectrometry, which is the analysis of intact protein complexes in the gas phase. To achieve this, sample preparation and instrument conditions have to be optimised. Native mass spectrometry then reveals stoichiometry, protein interactions and topology of protein assemblies. Advanced techniques such as ion mobility and high-resolution mass spectrometry further add to the range of applications and deliver information on shape and microheterogeneity of the complexes. In this tutorial, we explain the basics of native mass spectrometry including sample requirements, instrument modifications and interpretation of native mass spectra. We further discuss the developments of native mass spectrometry and provide example spectra and applications.
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Affiliation(s)
- Marie Barth
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Institute for Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Carla Schmidt
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Institute for Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Halle, Germany
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20
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Peris-Díaz MD, Guran R, Zitka O, Adam V, Krężel A. Mass Spectrometry-Based Structural Analysis of Cysteine-Rich Metal-Binding Sites in Proteins with MetaOdysseus R Software. J Proteome Res 2020; 20:776-785. [PMID: 32924499 PMCID: PMC7786378 DOI: 10.1021/acs.jproteome.0c00651] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
![]()
Identification
of metal-binding sites in proteins and understanding
metal-coupled protein folding mechanisms are aspects of high importance
for the structure-to-function relationship. Mass spectrometry (MS)
has brought a powerful adjunct perspective to structural biology,
obtaining from metal-to-protein stoichiometry to quaternary structure
information. Currently, the different experimental and/or instrumental
setups usually require the use of multiple data analysis software,
and in some cases, they lack some of the main data analysis steps
(MS processing, scoring, identification). Here, we present a comprehensive
data analysis pipeline that addresses charge-state deconvolution,
statistical scoring, and mass assignment for native MS, bottom-up,
and native top-down with emphasis on metal–protein complexes.
We have evaluated all of the approaches using assemblies of increasing
complexity, including free and chemically labeled proteins, from low-
to high-resolution MS. In all cases, the results have been compared
with common software and proved how MetaOdysseus outperformed them.
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Affiliation(s)
- Manuel David Peris-Díaz
- Department of Chemical Biology, Faculty of Biotechnology, University of Wrocław, F. Joliot-Curie 14a, 50-383 Wrocław, Poland
| | - Roman Guran
- Department of Chemistry and Biochemistry, Mendel University in Brno, Zemedelska 1, 613 00 Brno, Czech Republic.,Central European Institute of Technology, Brno University of Technology, Purkynova 123, 612 00 Brno, Czech Republic
| | - Ondrej Zitka
- Department of Chemistry and Biochemistry, Mendel University in Brno, Zemedelska 1, 613 00 Brno, Czech Republic.,Central European Institute of Technology, Brno University of Technology, Purkynova 123, 612 00 Brno, Czech Republic
| | - Vojtech Adam
- Department of Chemistry and Biochemistry, Mendel University in Brno, Zemedelska 1, 613 00 Brno, Czech Republic.,Central European Institute of Technology, Brno University of Technology, Purkynova 123, 612 00 Brno, Czech Republic
| | - Artur Krężel
- Department of Chemical Biology, Faculty of Biotechnology, University of Wrocław, F. Joliot-Curie 14a, 50-383 Wrocław, Poland
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21
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Wu Z, Roberts DS, Melby JA, Wenger K, Wetzel M, Gu Y, Ramanathan SG, Bayne EF, Liu X, Sun R, Ong IM, McIlwain SJ, Ge Y. MASH Explorer: A Universal Software Environment for Top-Down Proteomics. J Proteome Res 2020; 19:3867-3876. [PMID: 32786689 DOI: 10.1021/acs.jproteome.0c00469] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Top-down mass spectrometry (MS)-based proteomics enable a comprehensive analysis of proteoforms with molecular specificity to achieve a proteome-wide understanding of protein functions. However, the lack of a universal software for top-down proteomics is becoming increasingly recognized as a major barrier, especially for newcomers. Here, we have developed MASH Explorer, a universal, comprehensive, and user-friendly software environment for top-down proteomics. MASH Explorer integrates multiple spectral deconvolution and database search algorithms into a single, universal platform which can process top-down proteomics data from various vendor formats, for the first time. It addresses the urgent need in the rapidly growing top-down proteomics community and is freely available to all users worldwide. With the critical need and tremendous support from the community, we envision that this MASH Explorer software package will play an integral role in advancing top-down proteomics to realize its full potential for biomedical research.
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Affiliation(s)
- Zhijie Wu
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - David S Roberts
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Jake A Melby
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Kent Wenger
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Molly Wetzel
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Yiwen Gu
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | | | - Elizabeth F Bayne
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Xiaowen Liu
- Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, United States.,Center for Computational Biology and Bioinformatics, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, United States
| | - Ruixiang Sun
- National Institute of Biological Sciences, Beijing, 102206, China
| | - Irene M Ong
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Sean J McIlwain
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
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