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Guo Y, Cupp‐Sutton KA, Zhao Z, Anjum S, Wu S. Multidimensional Separations in Top-Down Proteomics. ANALYTICAL SCIENCE ADVANCES 2023; 4:181-203. [PMID: 38188188 PMCID: PMC10769458 DOI: 10.1002/ansa.202300016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/21/2023] [Accepted: 05/01/2023] [Indexed: 01/09/2024]
Abstract
Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.
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Affiliation(s)
- Yanting Guo
- Department of Chemistry and BiochemistryUniversity of OklahomaOklahomaNormanUSA
| | | | - Zhitao Zhao
- Department of Chemistry and BiochemistryUniversity of OklahomaOklahomaNormanUSA
| | - Samin Anjum
- Department of Chemistry and BiochemistryUniversity of OklahomaOklahomaNormanUSA
| | - Si Wu
- Department of Chemistry and BiochemistryUniversity of OklahomaOklahomaNormanUSA
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Kline JT, Belford MW, Huang J, Greer JB, Bergen D, Fellers RT, Greer SM, Horn DM, Zabrouskov V, Huguet R, Boeser CL, Durbin KR, Fornelli L. Improved Label-Free Quantification of Intact Proteoforms Using Field Asymmetric Ion Mobility Spectrometry. Anal Chem 2023; 95:9090-9096. [PMID: 37252723 PMCID: PMC11149911 DOI: 10.1021/acs.analchem.3c01534] [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] [Indexed: 05/31/2023]
Abstract
The high-throughput quantification of intact proteoforms using a label-free approach is typically performed on proteins in the 0-30 kDa mass range extracted from whole cell or tissue lysates. Unfortunately, even when high-resolution separation of proteoforms is achieved by either high-performance liquid chromatography or capillary electrophoresis, the number of proteoforms that can be identified and quantified is inevitably limited by the inherent sample complexity. Here, we benchmark label-free quantification of proteoforms of Escherichia coli by applying gas-phase fractionation (GPF) via field asymmetric ion mobility spectrometry (FAIMS). Recent advances in Orbitrap instrumentation have enabled the acquisition of high-quality intact and fragmentation mass spectra without the need for averaging time-domain transients prior to Fourier transform. The resulting speed improvements allowed for the application of multiple FAIMS compensation voltages in the same liquid chromatography-tandem mass spectrometry experiment without increasing the overall data acquisition cycle. As a result, the application of FAIMS to label-free quantification based on intact mass spectra substantially increases the number of both identified and quantified proteoforms without penalizing quantification accuracy in comparison to traditional label-free experiments that do not adopt GPF.
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Affiliation(s)
- Jake T. Kline
- Department of Biology, University of Oklahoma, Norman, Oklahoma 73019, United States
| | | | - Jingjing Huang
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Joseph B. Greer
- Proteinaceous, Inc., Evanston, Illinois 60208, United States
| | - David Bergen
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Ryan T. Fellers
- Proteinaceous, Inc., Evanston, Illinois 60208, United States
| | | | - David M. Horn
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Romain Huguet
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | | | - Luca Fornelli
- Department of Biology, University of Oklahoma, Norman, Oklahoma 73019, United States
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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