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Bons J, Hunter CL, Chupalov R, Causon J, Antonoplis A, Rose J, MacLean B, Schilling B. Localization and Quantification of Post-Translational Modifications of Proteins Using Electron Activated Dissociation Fragmentation on a Fast-Acquisition Time-of-Flight Mass Spectrometer. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2199-2210. [PMID: 37694881 PMCID: PMC11157679 DOI: 10.1021/jasms.3c00144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Protein post-translational modifications (PTMs) are crucial and dynamic players in a large variety of cellular processes and signaling. Proteomic technologies have emerged as the method of choice to profile PTMs. However, these analyses remain challenging due to potential low PTM stoichiometry, the presence of multiple PTMs per proteolytic peptide, PTM site localization of isobaric peptides, and neutral losses. Collision-induced dissociation (CID) is commonly used to characterize PTMs, but the application of collision energy can lead to neutral losses and incomplete peptide sequencing for labile PTM groups. In this study, we assessed the performance of an alternative fragmentation, electron activated dissociation (EAD), to characterize, site localize, and quantify peptides with labile modifications in comparison to CID, both operated on a recently introduced fast-scanning quadrupole-time-of-flight (QqTOF) mass spectrometer. We analyzed biologically relevant phosphorylated, succinylated, malonylated, and acetylated synthetic peptides using targeted parallel reaction monitoring (PRM or MRMHR) assays. We report that electron-based fragmentation preserves the malonyl group from neutral losses. The novel tunable EAD kinetic energy maintained labile modification integrity and provided better peptide sequence coverage with strong PTM-site localization fragment ions. Activation of a novel trap-and-release technology significantly improves the duty cycle and provided significant MS/MS sensitivity gains by an average of 6-11-fold for EAD analyses. Evaluation of the quantitative EAD PRM workflows revealed high reproducibility with coefficients of variation of ∼2-7%, as well as very good linearity and quantification accuracy. This novel workflow combining EAD and trap-and-release technology provides high sensitivity, alternative fragmentation information to achieve confident PTM characterization and quantification.
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Affiliation(s)
- Joanna Bons
- Buck Institute for Research on Aging, Novato, California 94947, United States
| | | | - Rita Chupalov
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | | | | | - Jacob Rose
- Buck Institute for Research on Aging, Novato, California 94947, United States
| | - Brendan MacLean
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, California 94947, United States
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Zhou W, Li W, Wang S, Salovska B, Hu Z, Tao B, Di Y, Punyamurtula U, Turk BE, Sessa WC, Liu Y. An optogenetic-phosphoproteomic study reveals dynamic Akt1 signaling profiles in endothelial cells. Nat Commun 2023; 14:3803. [PMID: 37365174 PMCID: PMC10293293 DOI: 10.1038/s41467-023-39514-1] [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: 07/08/2022] [Accepted: 06/07/2023] [Indexed: 06/28/2023] Open
Abstract
The serine/threonine kinase AKT is a central node in cell signaling. While aberrant AKT activation underlies the development of a variety of human diseases, how different patterns of AKT-dependent phosphorylation dictate downstream signaling and phenotypic outcomes remains largely enigmatic. Herein, we perform a systems-level analysis that integrates methodological advances in optogenetics, mass spectrometry-based phosphoproteomics, and bioinformatics to elucidate how different intensity, duration, and pattern of Akt1 stimulation lead to distinct temporal phosphorylation profiles in vascular endothelial cells. Through the analysis of ~35,000 phosphorylation sites across multiple conditions precisely controlled by light stimulation, we identify a series of signaling circuits activated downstream of Akt1 and interrogate how Akt1 signaling integrates with growth factor signaling in endothelial cells. Furthermore, our results categorize kinase substrates that are preferably activated by oscillating, transient, and sustained Akt1 signals. We validate a list of phosphorylation sites that covaried with Akt1 phosphorylation across experimental conditions as potential Akt1 substrates. Our resulting dataset provides a rich resource for future studies on AKT signaling and dynamics.
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Affiliation(s)
- Wenping Zhou
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Department of Cell Biology, Yale University School of Medicine, New Haven, CT, 06511, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Wenxue Li
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, 06516, USA
| | - Shisheng Wang
- Department of Pulmonary and Critical Care Medicine, and Proteomics-Metabolomics Analysis Platform, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Barbora Salovska
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, 06516, USA
| | - Zhenyi Hu
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, 06516, USA
| | - Bo Tao
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Yi Di
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, 06516, USA
| | - Ujwal Punyamurtula
- Master of Biotechnology ScM Program, Brown University, Providence, RI, 02912, USA
| | - Benjamin E Turk
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - William C Sessa
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, 06520, USA.
| | - Yansheng Liu
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, 06516, USA.
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Di Y, Li W, Salovska B, Ba Q, Hu Z, Wang S, Liu Y. A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology. BIOPHYSICS REPORTS 2023; 9:82-98. [PMID: 37753060 PMCID: PMC10518521 DOI: 10.52601/bpr.2023.230007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 04/28/2023] [Indexed: 09/28/2023] Open
Abstract
Phosphorylation is one of the most important post-translational modifications (PTMs) of proteins, governing critical protein functions. Most human proteins have been shown to undergo phosphorylation, and phosphoproteomic studies have been widely applied due to recent advancements in high-resolution mass spectrometry technology. Although the experimental workflow for phosphoproteomics has been well-established, it would be useful to optimize and summarize a detailed, feasible protocol that combines phosphoproteomics and data-independent acquisition (DIA), along with follow-up data analysis procedures due to the recent instrumental and bioinformatic advances in measuring and understanding tens of thousands of site-specific phosphorylation events in a single experiment. Here, we describe an optimized Phos-DIA protocol, from sample preparation to bioinformatic analysis, along with practical considerations and experimental configurations for each step. The protocol is designed to be robust and applicable for both small-scale phosphoproteomic analysis and large-scale quantification of hundreds of samples for studies in systems biology and systems medicine.
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Affiliation(s)
- Yi Di
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Wenxue Li
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Barbora Salovska
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Qian Ba
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
- Current address: Laboratory Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China
| | - Zhenyi Hu
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Shisheng Wang
- Department of Pulmonary and Critical Care Medicine, and Proteomics-Metabolomics Analysis Platform, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yansheng Liu
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA
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Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform. Mol Cell Proteomics 2023; 22:100491. [PMID: 36603806 PMCID: PMC9944986 DOI: 10.1016/j.mcpro.2022.100491] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/10/2022] [Accepted: 12/20/2022] [Indexed: 01/04/2023] Open
Abstract
Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.
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Salovska B, Liu Y. Post-translational modification and phenotype. Proteomics 2023; 23:e2200535. [PMID: 36799530 DOI: 10.1002/pmic.202200535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 01/02/2023] [Indexed: 02/18/2023]
Affiliation(s)
- Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, Connecticut, USA
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, Connecticut, USA.,Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut, USA
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Li W, Salovska B, Fornasiero EF, Liu Y. Toward a hypothesis-free understanding of how phosphorylation dynamically impacts protein turnover. Proteomics 2023; 23:e2100387. [PMID: 36422574 PMCID: PMC10964180 DOI: 10.1002/pmic.202100387] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/16/2022] [Accepted: 11/18/2022] [Indexed: 11/25/2022]
Abstract
The turnover measurement of proteins and proteoforms has been largely facilitated by workflows coupling metabolic labeling with mass spectrometry (MS), including dynamic stable isotope labeling by amino acids in cell culture (dynamic SILAC) or pulsed SILAC (pSILAC). Very recent studies including ours have integrated themeasurement of post-translational modifications (PTMs) at the proteome level (i.e., phosphoproteomics) with pSILAC experiments in steady state systems, exploring the link between PTMs and turnover at the proteome-scale. An open question in the field is how to exactly interpret these complex datasets in a biological perspective. Here, we present a novel pSILAC phosphoproteomic dataset which was obtained during a dynamic process of cell starvation using data-independent acquisition MS (DIA-MS). To provide an unbiased "hypothesis-free" analysis framework, we developed a strategy to interrogate how phosphorylation dynamically impacts protein turnover across the time series data. With this strategy, we discovered a complex relationship between phosphorylation and protein turnover that was previously underexplored. Our results further revealed a link between phosphorylation stoichiometry with the turnover of phosphorylated peptidoforms. Moreover, our results suggested that phosphoproteomic turnover diversity cannot directly explain the abundance regulation of phosphorylation during cell starvation, underscoring the importance of future studies addressing PTM site-resolved protein turnover.
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Affiliation(s)
- Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Eugenio F. Fornasiero
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, 37073, Göttingen, Germany
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA
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Yang Y, Qiao L. Data-independent acquisition proteomics methods for analyzing post-translational modifications. Proteomics 2022; 23:e2200046. [PMID: 36036492 DOI: 10.1002/pmic.202200046] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 08/20/2022] [Accepted: 08/23/2022] [Indexed: 11/06/2022]
Abstract
Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, i.e., detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
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