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Bayne EF, Buck KM, Towler AG, Zhu Y, Pergande MR, Zhou T, Price S, Rossler KJ, Morales-Tirado V, Lloyd S, Wang F, He Y, Tian Y, Ge Y. High-Throughput Extracellular Matrix Proteomics of Human Lungs Enabled by Photocleavable Surfactant and diaPASEF. J Proteome Res 2024; 23:2908-2918. [PMID: 38315831 DOI: 10.1021/acs.jproteome.3c00532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
The extracellular matrix (ECM) is a complex assembly of proteins that provide interstitial scaffolding and elastic recoil for human lungs. The pulmonary extracellular matrix is increasingly recognized as an independent bioactive entity, by creating biochemical and mechanical signals that influence disease pathogenesis, making it an attractive therapeutic target. However, the pulmonary ECM proteome ("matrisome") remains challenging to analyze by mass spectrometry due to its inherent biophysical properties and relatively low abundance. Here, we introduce a strategy designed for rapid and efficient characterization of the human pulmonary ECM using the photocleavable surfactant Azo. We coupled this approach with trapped ion mobility MS with diaPASEF to maximize the depth of matrisome coverage. Using this strategy, we identify nearly 400 unique matrisome proteins with excellent reproducibility that are known to be important in lung biology, including key core matrisome proteins.
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Affiliation(s)
- Elizabeth F Bayne
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Kevin M Buck
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Anna G Towler
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Yanlong Zhu
- 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
| | - Melissa R Pergande
- 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
| | - Tianhua Zhou
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Scott Price
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Kalina J Rossler
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
- Molecular and Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Vanessa Morales-Tirado
- Discovery Immunology, Pharmacology and Pathology, AbbVie Bioresearch Center, Worcester, Massachusetts 01605, United States
| | - Sarah Lloyd
- Discovery Immunology, Pharmacology and Pathology, AbbVie, Inc., North Chicago, Illinois 60064, United States
| | - Fei Wang
- Quantitative Translational & ADME Science, AbbVie Bioresearch Center, Worcester, Massachusetts 01605, United States
| | - Yupeng He
- Discovery Immunology, Pharmacology and Pathology, AbbVie, Inc., North Chicago, Illinois 60064, United States
| | - Yu Tian
- Quantitative Translational & ADME Science, AbbVie Bioresearch Center, Worcester, Massachusetts 01605, United States
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, 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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2
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Fröhlich K, Fahrner M, Brombacher E, Seredynska A, Maldacker M, Kreutz C, Schmidt A, Schilling O. Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics. Mol Cell Proteomics 2024; 23:100800. [PMID: 38880244 PMCID: PMC11380018 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 06/08/2024] [Accepted: 06/13/2024] [Indexed: 06/18/2024] Open
Abstract
Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given m/z range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.
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Affiliation(s)
- Klemens Fröhlich
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Eva Brombacher
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Freiburg, Germany
| | - Alexander Schmidt
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany.
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3
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Hadpech S, Thongboonkerd V. Proteomic investigations of dengue virus infection: key discoveries over the last 10 years. Expert Rev Proteomics 2024; 21:281-295. [PMID: 39049185 DOI: 10.1080/14789450.2024.2383580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 07/12/2024] [Indexed: 07/27/2024]
Abstract
INTRODUCTION Dengue virus (DENV) infection remains one of the most significant infectious diseases in humans. Several efforts have been made to address its molecular mechanisms. Over the last 10 years, proteomics has been widely applied to investigate various aspects of DENV infection. AREAS COVERED In this review, we briefly introduce common proteomics approaches using various mass spectrometric modalities followed by summarizing all the discoveries obtained from proteomic investigations of DENV infection over the last 10 years. These include the data on DENV-vector interactions and host responses to address the DENV biology and disease mechanisms. Moreover, applications of proteomics to disease prevention, diagnosis, vaccine design, development of anti-DENV agents and other new treatment strategies are discussed. EXPERT OPINION Despite efforts on disease prevention, DENV infection is still a significant global healthcare burden that affects the general population. As summarized herein, proteomic technologies with high-throughput capabilities have provided more in-depth details of protein dynamics during DENV infection. More extensive applications of proteomics and other powerful research tools would provide a promise to better cope and prevent this mosquito-borne infectious disease.
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Affiliation(s)
- Sudarat Hadpech
- Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
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Zhang G, Ding Y, Zhang H, Wei D, Liu Y, Sun J, Xie Z, Tao WA, Zhu Y. Assessment of urine sample collection and processing variables for extracellular vesicle-based proteomics. Analyst 2024; 149:3416-3424. [PMID: 38716512 DOI: 10.1039/d4an00296b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Extracellular vesicles (EVs) in urine are a promising source for developing non-invasive biomarkers. However, urine concentration and content are highly variable and dynamic, and actual urine collection and handling often is nonideal. Furthermore, patients such as those with prostate diseases have challenges in sample collection due to difficulties in holding urine at designated time points. Here, we simulated the actual situation of clinical sample collection to examine the stability of EVs in urine under different circumstances, including urine collection time and temporary storage temperature, as well as daily urine sampling under different diet conditions. EVs were isolated using functionalized EVtrap magnetic beads and characterized by nanoparticle tracking analysis (NTA), western blotting, electron microscopy, and mass spectrometry (MS). EVs in urine remained relatively stable during temporary storage for 6 hours at room temperature and for 12 hours at 4 °C, while significant fluctuations were observed in EV amounts from urine samples collected at different time points from the same individuals, especially under certain diets. Sample normalization with creatinine reduced the coefficient of variation (CV) values among EV samples from 17% to approximately 6% and facilitated downstream MS analyses. Finally, based on the results, we applied them to evaluate potential biomarker panels in prostate cancer by data-independent acquisition (DIA) MS, presenting the recommendation that can facilitate biomarker discovery with nonideal handling conditions.
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Affiliation(s)
- Guiyuan Zhang
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
- Bell Mountain Molecular MedTech Institute, Nanjing 210032, China
- EVLiXiR Biotech, Nanjing 210032, China
| | - Yajie Ding
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Hao Zhang
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
- EVLiXiR Biotech, Nanjing 210032, China
| | - Dong Wei
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
- Bell Mountain Molecular MedTech Institute, Nanjing 210032, China
| | - Yufeng Liu
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
- Bell Mountain Molecular MedTech Institute, Nanjing 210032, China
| | - Jie Sun
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Zhuoying Xie
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
| | - W Andy Tao
- Departments of Chemistry and Biochemistry, Purdue University, West Lafayette, Indiana 47907, USA
| | - Yefei Zhu
- School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China.
- Laboratory Medicine Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing 210011, China
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5
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Wang C, Feng G, Zhao J, Xu Y, Li Y, Wang L, Wang M, Liu M, Wang Y, Mu H, Zhou C. Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics. Proteomics Clin Appl 2024; 18:e2300047. [PMID: 38215274 DOI: 10.1002/prca.202300047] [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: 04/27/2023] [Revised: 11/03/2023] [Accepted: 11/22/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection. METHODS The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA). RESULTS A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis. CONCLUSIONS Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.
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Affiliation(s)
- Ce Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Gang Feng
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Jie Zhao
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Xu
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Li
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Lin Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Meng Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Miao Liu
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Yilin Wang
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Hong Mu
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Chunlei Zhou
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
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Lou R, Shui W. Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023. Mol Cell Proteomics 2024; 23:100712. [PMID: 38182042 PMCID: PMC10847697 DOI: 10.1016/j.mcpro.2024.100712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/27/2023] [Accepted: 01/02/2024] [Indexed: 01/07/2024] Open
Abstract
Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.
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Affiliation(s)
- Ronghui Lou
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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Na S, Paek E. Demystifying PTM Identification Using MODplus: Best Practices and Pitfalls. Methods Mol Biol 2024; 2836:37-55. [PMID: 38995534 DOI: 10.1007/978-1-0716-4007-4_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Tandem mass spectrometry (MS/MS) facilitates the rapid identification of posttranslational modifications (PTMs), which play a pivotal role in regulating numerous biological processes. This chapter explores recent advancements that expand the types of detectable PTMs and enhance the speed of the PTM searches. We also delve into computational challenges associated with searching for a multitude of PTMs simultaneously. The latter section introduces an automated procedure to identify an extensive range of PTMs using MODplus, a free PTM analysis software tool. We guide the reader through the preparation of the modification search, the determination of optional search parameters, the execution of the search, and the analysis of results, exemplified by a case study using specific MS/MS dataset.
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Affiliation(s)
- Seungjin Na
- Digital Omics Research Center, Korea Basic Science Institute, Cheongju, South Korea
| | - Eunok Paek
- Department of Computer Science, Hanyang University, Seoul, South Korea.
- Department of Artificial Intelligence, Hanyang University, Seoul, South Korea.
- Institute for Artificial Intelligence Research, Hanyang University, Seoul, South Korea.
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Deng B, Vanagas L, Alonso AM, Angel SO. Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery. Pathogens 2023; 13:33. [PMID: 38251340 PMCID: PMC10821451 DOI: 10.3390/pathogens13010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.
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Affiliation(s)
- Bin Deng
- Department of Biology and VBRN Proteomics Facility, University of Vermont, Burlington, VT 05405, USA
| | - Laura Vanagas
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Andres M. Alonso
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Sergio O. Angel
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
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Wen C, Wu X, Lin G, Yan W, Gan G, Xu X, Chen XY, Chen X, Liu X, Fu G, Zhong CQ. Evaluation of DDA Library-Free Strategies for Phosphoproteomics and Ubiquitinomics Data-Independent Acquisition Data. J Proteome Res 2023. [PMID: 37256709 DOI: 10.1021/acs.jproteome.2c00735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Phosphoproteomics and ubiquitinomics data-independent acquisition (DIA) mass spectrometry (MS) data is typically analyzed by using a data-dependent acquisition (DDA) spectral library. The performance of various library-free strategies for analyzing phosphoproteomics and ubiquitinomics DIA MS data has not been evaluated. In this study, we systematically compare four commonly used DDA library-free approaches including Spectronaut's directDIA, DIA-Umpire, DIA-MSFragger, and in silico-predicted library for analysis of phosphoproteomics SWATH, DIA, and diaPASEF data as well as ubiquitinomics diaPASEF data. Spectronaut's directDIA shows the highest sensitivity for phosphopeptide detection not only in synthetic phosphopeptide samples but also in phosphoproteomics SWATH-MS and DIA data from real biological samples, when compared to the other three library-free strategies. For phosphoproteomics diaPASEF data, Spectronaut's directDIA and the in silico-predicted library based on DIA-NN identify almost the same number of phosphopeptides as a project-specific DDA spectral library. However, only about 30% of the total phosphopeptides are commonly identified, suggesting that the library-free strategies for phospho-diaPASEF data need further improvement in terms of sensitivity. For ubiquitinomics diaPASEF data, the in silico-predicted library performs the best among the four workflows and detects ∼50% more K-GG peptides than a project-specific DDA spectral library. Our results demonstrate that Spectronaut's directDIA is suitable for the analysis of phosphoproteomics SWATH-MS and DIA MS data, while the in silico-predicted library based on DIA-NN shows substantial advantages for ubiquitinomics diaPASEF MS data.
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Affiliation(s)
- Chengwen Wen
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Xiurong Wu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Guanzhong Lin
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Wei Yan
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Guohong Gan
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Xiao Xu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Xiang-Yu Chen
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Xi Chen
- SpecAlly Life Technology Co., Ltd., Wuhan 430074, Hubei, China
| | - Xianming Liu
- Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200030, China
| | - Guo Fu
- School of Medicine, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
| | - Chuan-Qi Zhong
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361005, Fujian, China
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Allgoewer K, Wu S, Choi H, Vogel C. Re-mining serum proteomics data reveals extensive post-translational modifications upon Zika and dengue infection. Mol Omics 2023; 19:308-320. [PMID: 36810580 PMCID: PMC10175154 DOI: 10.1039/d2mo00258b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Zika virus (ZIKV) and dengue virus (DENV) are two closely related flaviviruses with similar symptoms. However, due to the implications of ZIKV infections for pregnancy outcomes, understanding differences in their molecular impact on the host is of high interest. Viral infections change the host proteome, including post-translational modifications. As modifications are diverse and of low abundance, they typically require additional sample processing which is not feasible for large cohort studies. Therefore, we tested the potential of next-generation proteomics data in its ability to prioritize specific modifications for later analysis. We re-mined published mass spectra from 122 serum samples from ZIKV and DENV patients for the presence of phosphorylated, methylated, oxidized, glycosylated/glycated, sulfated, and carboxylated peptides. We identified 246 modified peptides with significantly differential abundance in ZIKV and DENV patients. Amongst these, methionine-oxidized peptides from apolipoproteins and glycosylated peptides from immunoglobulin proteins were more abundant in ZIKV patient serum and generate hypotheses on the potential roles of the modification in the infection. The results demonstrate how data-independent acquisition techniques can help prioritize future analyses of peptide modifications.
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Affiliation(s)
- Kristina Allgoewer
- New York University, Department of Biology, Center for Genomics and Systems Biology, New York, NY, USA.
- Humboldt University, Department of Biology, Berlin, Germany
| | - Shaohuan Wu
- New York University, Department of Biology, Center for Genomics and Systems Biology, New York, NY, USA.
| | - Hyungwon Choi
- Department of Medicine, Yong Loo Lin School of Medicine, National University, Singapore, Singapore
| | - Christine Vogel
- New York University, Department of Biology, Center for Genomics and Systems Biology, New York, NY, USA.
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