1
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Pradita T, Chen YJ, Su TH, Chang KH, Chen PJ, Chen YJ. Data Independent Acquisition Mass Spectrometry Enhanced Personalized Glycosylation Profiling of Haptoglobin in Hepatocellular Carcinoma. J Proteome Res 2024. [PMID: 38994555 DOI: 10.1021/acs.jproteome.4c00227] [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: 07/13/2024]
Abstract
Aberrant glycosylation has gained significant interest for biomarker discovery. However, low detectability, complex glycan structures, and heterogeneity present challenges in glycoprotein assay development. Using haptoglobin (Hp) as a model, we developed an integrated platform combining functionalized magnetic nanoparticles and zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) for highly specific glycopeptide enrichment, followed by a data-independent acquisition (DIA) strategy to establish a deep cancer-specific Hp-glycosylation profile in hepatitis B virus (HBV, n = 5) and hepatocellular carcinoma (HCC, n = 5) patients. The DIA strategy established one of the deepest Hp-glycosylation landscapes (1029 glycopeptides, 130 glycans) across serum samples, including 54 glycopeptides exclusively detected in HCC patients. Additionally, single-shot DIA searches against a DIA-based spectral library outperformed the DDA approach by 2-3-fold glycopeptide coverage across patients. Among the four N-glycan sites on Hp (N-184, N-207, N-211, N-241), the total glycan type distribution revealed significantly enhanced detection of combined fucosylated-sialylated glycans, which were the most dominant glycoforms identified in HCC patients. Quantitation analysis revealed 48 glycopeptides significantly enriched in HCC (p < 0.05), including a hybrid monosialylated triantennary glycopeptide on the N-184 site with nearly none-to-all elevation to differentiate HCC from the HBV group (HCC/HBV ratio: 2462 ± 766, p < 0.05). In summary, DIA-MS presents an unbiased and comprehensive alternative for targeted glycoproteomics to guide discovery and validation of glyco-biomarkers.
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Affiliation(s)
- Tiara Pradita
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
| | - Yi-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan
| | - Tung-Hung Su
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan
- Hepatitis Research Center, National Taiwan University Hospital, Taipei 100, Taiwan
| | - Kun-Hao Chang
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan
- Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
- Department of Chemistry, National Tsing-Hua University, Hsinchu 300, Taiwan
| | - Pei-Jer Chen
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan
- Hepatitis Research Center, National Taiwan University Hospital, Taipei 100, Taiwan
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei 100, Taiwan
- Department of Medical Research, National Taiwan University Hospital, Taipei 100, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 106, Taiwan
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2
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Humphries EM, Xavier D, Ashman K, Hains PG, Robinson PJ. High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH. J Proteome Res 2024; 23:2355-2366. [PMID: 38819404 DOI: 10.1021/acs.jproteome.4c00010] [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: 06/01/2024]
Abstract
High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 μg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.
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Affiliation(s)
- Erin M Humphries
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Keith Ashman
- Sciex, 96 Ricketts Road,Mount Waverley, Victoria 3149, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
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3
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Aguilan JT, Lim J, Racine-Brzostek S, Fischer J, Silvescu C, Cornett S, Nieves E, Mendu DR, Aliste CM, Semple S, Angeletti R, Weiss LM, Cole A, Prystowsky M, Pullman J, Sidoli S. Effect of dynamic exclusion and the use of FAIMS, DIA and MALDI-mass spectrometry imaging with ion mobility on amyloid protein identification. Clin Proteomics 2024; 21:47. [PMID: 38961380 PMCID: PMC11223398 DOI: 10.1186/s12014-024-09500-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/26/2024] [Indexed: 07/05/2024] Open
Abstract
Amyloidosis is a disease characterized by local and systemic extracellular deposition of amyloid protein fibrils where its excessive accumulation in tissues and resistance to degradation can lead to organ failure. Diagnosis is challenging because of approximately 36 different amyloid protein subtypes. Imaging methods like immunohistochemistry and the use of Congo red staining of amyloid proteins for laser capture microdissection combined with liquid chromatography tandem mass spectrometry (LMD/LC-MS/MS) are two diagnostic methods currently used depending on the expertise of the pathology laboratory. Here, we demonstrate a streamlined in situ amyloid peptide spatial mapping by Matrix Assisted Laser Desorption Ionization-Mass Spectrometry Imaging (MALDI-MSI) combined with Trapped Ion Mobility Spectrometry for potential transthyretin (ATTR) amyloidosis subtyping. While we utilized the standard LMD/LC-MS/MS workflow for amyloid subtyping of 31 specimens from different organs, we also evaluated the potential introduction in the MS workflow variations in data acquisition parameters like dynamic exclusion, or testing Data Dependent Acquisition combined with High-Field Asymmetric Waveform Ion Mobility Spectrometry (DDA FAIMS) versus Data Independent Acquisition (DIA) for enhanced amyloid protein identification at shorter acquisition times. We also demonstrate the use of Mascot's Error Tolerant Search and PEAKS de novo sequencing for the sequence variant analysis of amyloidosis specimens.
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Affiliation(s)
- Jennifer T Aguilan
- Laboratory for Macromolecular Analysis and Proteomics Facility, Albert Einstein College of Medicine, New York, 10461, USA
- Department of Pathology, Albert Einstein College of Medicine, New York, 10461, USA
- Montefiore Medical Center, Moses and Weiler Campus, New York, 10461, USA
| | - Jihyeon Lim
- Janssen Research and Development, Malvern, PA, USA
| | | | | | | | | | - Edward Nieves
- Laboratory for Macromolecular Analysis and Proteomics Facility, Albert Einstein College of Medicine, New York, 10461, USA
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Damodara Rao Mendu
- Clinical Chemistry Laboratory, Mount Sinai School of Medicine, New York, USA
| | - Carlos-Madrid Aliste
- Laboratory for Macromolecular Analysis and Proteomics Facility, Albert Einstein College of Medicine, New York, 10461, USA
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, New York, 10461, USA
| | | | - Ruth Angeletti
- Laboratory for Macromolecular Analysis and Proteomics Facility, Albert Einstein College of Medicine, New York, 10461, USA
| | - Louis M Weiss
- Department of Pathology, Albert Einstein College of Medicine, New York, 10461, USA
- Montefiore Medical Center, Moses and Weiler Campus, New York, 10461, USA
| | - Adam Cole
- Montefiore Medical Center, Moses and Weiler Campus, New York, 10461, USA
| | - Michael Prystowsky
- Department of Pathology, Albert Einstein College of Medicine, New York, 10461, USA
- Montefiore Medical Center, Moses and Weiler Campus, New York, 10461, USA
| | - James Pullman
- Montefiore Medical Center, Moses and Weiler Campus, New York, 10461, USA
| | - Simone Sidoli
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
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4
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Pham TV, Henneman AA, Truong NX, Jimenez CR. msproteomics sitereport: reporting DIA-MS phosphoproteomics experiments at site level with ease. Bioinformatics 2024; 40:btae432. [PMID: 38944032 DOI: 10.1093/bioinformatics/btae432] [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] [Received: 12/24/2023] [Revised: 06/07/2024] [Accepted: 06/28/2024] [Indexed: 07/01/2024] Open
Abstract
SUMMARY Identification and quantification of phosphorylation sites are essential for biological interpretation of a phosphoproteomics experiment. For data independent acquisition mass spectrometry-based (DIA-MS) phosphoproteomics, extracting a site-level report from the output of current processing software is not straightforward as multiple peptides might contribute to a single site, multiple phosphorylation sites can occur on the same peptides, and protein isoforms complicate site specification. Currently only limited support is available from a commercial software package via a platform-specific solution with a rather simple site quantification method. Here, we present sitereport, a software tool implemented in an extendable Python package called msproteomics to report phosphosites and phosphopeptides from a DIA-MS phosphoproteomics experiment with a proven quantification method called MaxLFQ. We demonstrate the use of sitereport for downstream data analysis at site level, allowing benchmarking different DIA-MS processing software tools. AVAILABILITY AND IMPLEMENTATION sitereport is available as a command line tool in the Python package msproteomics, released under the Apache License 2.0 and available from the Python Package Index (PyPI) at https://pypi.org/project/msproteomics and GitHub at https://github.com/tvpham/msproteomics.
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Affiliation(s)
- Thang V Pham
- Amsterdam UMC location Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Medical Oncology, De Boelelaan 1117, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Alex A Henneman
- Amsterdam UMC location Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Medical Oncology, De Boelelaan 1117, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Nam X Truong
- Thuyloi University, Faculty of Computer Science and Engineering, 175 Tay Son, Hanoi, Vietnam
| | - Connie R Jimenez
- Amsterdam UMC location Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Medical Oncology, De Boelelaan 1117, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
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5
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Oliinyk D, Will A, Schneidmadel FR, Böhme M, Rinke J, Hochhaus A, Ernst T, Hahn N, Geis C, Lubeck M, Raether O, Humphrey SJ, Meier F. µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics. Mol Syst Biol 2024:10.1038/s44320-024-00050-9. [PMID: 38907068 DOI: 10.1038/s44320-024-00050-9] [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: 08/25/2023] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 06/23/2024] Open
Abstract
Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.
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Affiliation(s)
- Denys Oliinyk
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Andreas Will
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Felix R Schneidmadel
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Maximilian Böhme
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Jenny Rinke
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Andreas Hochhaus
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Thomas Ernst
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Nina Hahn
- Section of Translational Neuroimmunology, Department of Neurology, Jena University Hospital, 07747, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, 07747, Jena, Germany
| | - Christian Geis
- Section of Translational Neuroimmunology, Department of Neurology, Jena University Hospital, 07747, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, 07747, Jena, Germany
| | - Markus Lubeck
- Bruker Daltonics GmbH & Co. KG, 28359, Bremen, Germany
| | | | - Sean J Humphrey
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, 3052, Victoria, Australia.
| | - Florian Meier
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany.
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany.
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6
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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 2024:100800. [PMID: 38880244 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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 mass-to-charge 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, 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, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of 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, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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7
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Wu C, Zhang S, Hou C, Byers S, Ma J. In-Depth Endogenous Phosphopeptidomics of Serum with Zirconium(IV)-Grafted Mesoporous Silica Enrichment. Anal Chem 2024; 96:8254-8262. [PMID: 38728223 PMCID: PMC11140682 DOI: 10.1021/acs.analchem.3c02150] [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] [Received: 05/17/2023] [Revised: 03/21/2024] [Accepted: 04/22/2024] [Indexed: 05/12/2024]
Abstract
Detection of endogenous peptides, especially those with modifications (such as phosphorylation) in biofluids, can serve as an indicator of intracellular pathophysiology. Although great progress has been made in phosphoproteomics in recent years, endogenous phosphopeptidomics has largely lagged behind. One main hurdle in endogenous phosphopeptidomics analysis is the coexistence of proteins and highly abundant nonmodified peptides in complex matrices. In this study, we developed an approach using zirconium(IV)-grafted mesoporous beads to enrich phosphopeptides, followed by analysis with a high resolution nanoRPLC-MS/MS system. The bifunctional material was first tested with digests of standard phosphoproteins and HeLa cell lysates, with excellent enrichment performance achieved. Given the size exclusion nature, the beads were directly applied for endogenous phosphopeptidomic analysis of serum samples from pancreatic ductal adenocarcinoma (PDAC) patients and controls. In total, 329 endogenous phosphopeptides (containing 113 high confidence sites) were identified across samples, by far the largest endogenous phosphopeptide data set cataloged to date. In addition, the method was readily applied for phosphoproteomics of the same set of samples, with 172 phosphopeptides identified and significant changes in dozens of phosphopeptides observed. Given the simplicity and robustness of the proposed method, we envision that it can be readily used for comprehensive phosphorylation studies of serum and other biofluid samples.
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Affiliation(s)
- Ci Wu
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington D.C. 20007, United States
- School
of Chemistry and Chemical Engineering, Liaoning
Normal University, Dalian 116029, China
| | - Shen Zhang
- Clinical
Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha 410000, China
| | - Chunyan Hou
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington D.C. 20007, United States
| | - Stephen Byers
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington D.C. 20007, United States
| | - Junfeng Ma
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington D.C. 20007, United States
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8
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Lancaster NM, Sinitcyn P, Forny P, Peters-Clarke TM, Fecher C, Smith AJ, Shishkova E, Arrey TN, Pashkova A, Robinson ML, Arp N, Fan J, Hansen J, Galmozzi A, Serrano LR, Rojas J, Gasch AP, Westphall MS, Stewart H, Hock C, Damoc E, Pagliarini DJ, Zabrouskov V, Coon JJ. Fast and Deep Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.21.568149. [PMID: 38045259 PMCID: PMC10690147 DOI: 10.1101/2023.11.21.568149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology was benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We applied this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detected 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of novel phosphorylation events relevant to mitochondrial and brain biology.
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9
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Rrustemi T, Meyer K, Roske Y, Uyar B, Akalin A, Imami K, Ishihama Y, Daumke O, Selbach M. Pathogenic mutations of human phosphorylation sites affect protein-protein interactions. Nat Commun 2024; 15:3146. [PMID: 38605029 PMCID: PMC11009412 DOI: 10.1038/s41467-024-46794-8] [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: 08/09/2023] [Accepted: 03/11/2024] [Indexed: 04/13/2024] Open
Abstract
Despite their lack of a defined 3D structure, intrinsically disordered regions (IDRs) of proteins play important biological roles. Many IDRs contain short linear motifs (SLiMs) that mediate protein-protein interactions (PPIs), which can be regulated by post-translational modifications like phosphorylation. 20% of pathogenic missense mutations are found in IDRs, and understanding how such mutations affect PPIs is essential for unraveling disease mechanisms. Here, we employ peptide-based interaction proteomics to investigate 36 disease-associated mutations affecting phosphorylation sites. Our results unveil significant differences in interactomes between phosphorylated and non-phosphorylated peptides, often due to disrupted phosphorylation-dependent SLiMs. We focused on a mutation of a serine phosphorylation site in the transcription factor GATAD1, which causes dilated cardiomyopathy. We find that this phosphorylation site mediates interaction with 14-3-3 family proteins. Follow-up experiments reveal the structural basis of this interaction and suggest that 14-3-3 binding affects GATAD1 nucleocytoplasmic transport by masking a nuclear localisation signal. Our results demonstrate that pathogenic mutations of human phosphorylation sites can significantly impact protein-protein interactions, offering insights into potential molecular mechanisms underlying pathogenesis.
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Affiliation(s)
| | - Katrina Meyer
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
- Max Planck Institute for Molecular Genetics, Ihnestraße 63, 14195, Berlin, Germany
| | - Yvette Roske
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Bora Uyar
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Altuna Akalin
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Koshi Imami
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Kanagawa, Japan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan
| | - Oliver Daumke
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
- Freie Universität Berlin, Institute of Chemistry and Biochemistry, Takustraße 6, Berlin, Germany
| | - Matthias Selbach
- Max Delbrück Center (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany.
- Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany.
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10
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Yang Y, Fang Q. Prediction of glycopeptide fragment mass spectra by deep learning. Nat Commun 2024; 15:2448. [PMID: 38503734 PMCID: PMC10951270 DOI: 10.1038/s41467-024-46771-1] [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: 09/13/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024] Open
Abstract
Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.
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Affiliation(s)
- Yi Yang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
| | - Qun Fang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
- Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
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11
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Bashyal A, Brodbelt JS. Uncommon posttranslational modifications in proteomics: ADP-ribosylation, tyrosine nitration, and tyrosine sulfation. MASS SPECTROMETRY REVIEWS 2024; 43:289-326. [PMID: 36165040 PMCID: PMC10040477 DOI: 10.1002/mas.21811] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
Posttranslational modifications (PTMs) are covalent modifications of proteins that modulate the structure and functions of proteins and regulate biological processes. The development of various mass spectrometry-based proteomics workflows has facilitated the identification of hundreds of PTMs and aided the understanding of biological significance in a high throughput manner. Improvements in sample preparation and PTM enrichment techniques, instrumentation for liquid chromatography-tandem mass spectrometry (LC-MS/MS), and advanced data analysis tools enhance the specificity and sensitivity of PTM identification. Highly prevalent PTMs like phosphorylation, glycosylation, acetylation, ubiquitinylation, and methylation are extensively studied. However, the functions and impact of less abundant PTMs are not as well understood and underscore the need for analytical methods that aim to characterize these PTMs. This review focuses on the advancement and analytical challenges associated with the characterization of three less common but biologically relevant PTMs, specifically, adenosine diphosphate-ribosylation, tyrosine sulfation, and tyrosine nitration. The advantages and disadvantages of various enrichment, separation, and MS/MS techniques utilized to identify and localize these PTMs are described.
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Affiliation(s)
- Aarti Bashyal
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA
| | - Jennifer S Brodbelt
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA
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12
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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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13
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Chen NY, Lin CW, Lai TY, Wu CY, Liao PC, Hsu TL, Wong CH. Increased expression of SSEA-4 on TKI-resistant non-small cell lung cancer with EGFR-T790M mutation. Proc Natl Acad Sci U S A 2024; 121:e2313397121. [PMID: 38252815 PMCID: PMC10835044 DOI: 10.1073/pnas.2313397121] [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: 09/04/2023] [Accepted: 12/22/2023] [Indexed: 01/24/2024] Open
Abstract
Non-small cell lung cancer (NSCLC), a major life-threatening disease accounting for 85% of all lung cancer cases, has been treated with tyrosine kinase inhibitors (TKIs), but often resulted in drug resistance, and approximately 60% of TKI-resistant cases are due to acquired secondary (epithelial growth factor receptor) EGFR-T790M mutation. To identify alternative targets for TKI-resistant NSCLC with EGFR-T790M mutation, we found that the three globo-series glycosphingolipids are increasingly expressed on this type of NSCLC cell lines, and among them, the increase of stage-specific embryonic antigen-4 (SSEA-4) expression is the most significant. Compared to TKI-sensitive cell lines, SSEA-4 and the key enzyme β3GalT5 responsible for the synthesis of SSEA3 are more expressed in TKI-resistant NSCLC cell lines with EGFR-T790M mutation, and the expression levels strongly correlate with poor survival in patients with EGFR mutation. In addition, we demonstrated that a SSEA-4 targeted monoclonal antibody, especially the homogeneous glycoform with well-defined Fc glycan designed to improve effective functions, is highly effective against this subpopulation of NSCLC in cell-based and animal studies. These findings provide a direction for the prediction of tumor recurrence and treatment of TKI-resistant NSCLC with EGFR-T790M mutation.
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Affiliation(s)
- Nai-Yu Chen
- Genomics Research Center, Academia Sinica, Taipei11529, Taiwan
- Institute of Microbiology and Immunology, National Yang-Ming University, Taipei11221, Taiwan
| | - Chih-Wei Lin
- Institute of Biochemistry and Molecular Biology, China Medical University, Taichung406040, Taiwan
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung406040, Taiwan
| | - Ting-Yen Lai
- Genomics Research Center, Academia Sinica, Taipei11529, Taiwan
| | - Chung-Yi Wu
- Genomics Research Center, Academia Sinica, Taipei11529, Taiwan
| | - Pei-Chi Liao
- Institute of Biochemistry and Molecular Biology, China Medical University, Taichung406040, Taiwan
| | - Tsui-Ling Hsu
- Genomics Research Center, Academia Sinica, Taipei11529, Taiwan
| | - Chi-Huey Wong
- Genomics Research Center, Academia Sinica, Taipei11529, Taiwan
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA92037
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14
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郭 淑, 张 择, 赵 晋, 袁 进, 孙 世. [Role of Histone Modifications in Acute Kidney Injury Progressing to Chronic Kidney Disease]. SICHUAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF SICHUAN UNIVERSITY. MEDICAL SCIENCE EDITION 2023; 54:1080-1084. [PMID: 38162077 PMCID: PMC10752784 DOI: 10.12182/20231160506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Indexed: 01/03/2024]
Abstract
Acute kidney injury (AKI), a clinical syndrome caused by various factors, is characterized by a rapid decline in kidney function in a short period of time. AKI affects the short-term prognosis of patients and may also induce chronic kidney disease (CKD). However, the current treatment options for AKI mainly focus on symptom management. Specific therapeutic measures available for the prevention of transition from AKI to CKD are very limited in number. Histones are basic proteins that intricately bind the DNA in chromosomes. After translation, histones undergo various modifications on their amino-terminal tails, such as methylation, acetylation, phosphorylation, ubiquitination, and lactylation, collectively forming the "histone code", which affects the expression of genes mainly by regulating the elastic structure of chromatin or recruiting specific proteins. Extensive research conducted in recent years on histone post-translational modifications (PTMs) has also sparked continuous interest in their association with the AKI-to-CKD transition. Therefore, this paper highlights the significant role of PTMs in the process of AKI developing and progressing to CKD, with a view to finding new approaches to preventing the progression of AKI to CKD.
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Affiliation(s)
- 淑娴 郭
- 空军军医大学第一附属医院 肾脏内科 (西安 710032)Department of Nephrology, The First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - 择阳 张
- 空军军医大学第一附属医院 肾脏内科 (西安 710032)Department of Nephrology, The First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - 晋 赵
- 空军军医大学第一附属医院 肾脏内科 (西安 710032)Department of Nephrology, The First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - 进国 袁
- 空军军医大学第一附属医院 肾脏内科 (西安 710032)Department of Nephrology, The First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - 世仁 孙
- 空军军医大学第一附属医院 肾脏内科 (西安 710032)Department of Nephrology, The First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
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15
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Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. MASS SPECTROMETRY REVIEWS 2023; 42:2324-2348. [PMID: 35645145 DOI: 10.1002/mas.21781] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/17/2021] [Accepted: 01/21/2022] [Indexed: 06/15/2023]
Abstract
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
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Affiliation(s)
| | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
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16
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Hay BN, Akinlaja MO, Baker TC, Houfani AA, Stacey RG, Foster LJ. Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities. Proteomics 2023; 23:e2200278. [PMID: 37144656 DOI: 10.1002/pmic.202200278] [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: 10/28/2022] [Revised: 04/03/2023] [Accepted: 04/14/2023] [Indexed: 05/06/2023]
Abstract
Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.
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Affiliation(s)
- Brenna N Hay
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Mopelola O Akinlaja
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Teesha C Baker
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Aicha Asma Houfani
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - R Greg Stacey
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Leonard J Foster
- Michael Smith Laboratories and Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, BC, Canada
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17
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Huang D, Leng Y, Zhang X, Xing M, Ying W, Gao X. Serial and multi-level proteome analysis for microscale protein samples. J Proteomics 2023; 288:104993. [PMID: 37619946 DOI: 10.1016/j.jprot.2023.104993] [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: 04/05/2023] [Revised: 07/26/2023] [Accepted: 08/04/2023] [Indexed: 08/26/2023]
Abstract
Post-translational modifications (PTMs), such as phosphorylation and ubiquitination, play key roles in signal transduction and protein homeostasis. The crosstalk of PTMs greatly expands the components of proteome and protein functions. Multi-level proteome analysis, which involves proteome investigations of total lysate and PTMs in this context, provides a comprehensive approach to explore the PTM crosstalk of a biological system under diverse disturbances. However, multi-level proteome practice remains technically challenging. Here we intended to build a strategy for multi-level proteome analysis, in which we focus on the serial profiling the total proteome, ubiquitinome and phosphoproteome from the microscale of starting material. We started by evaluating five common lysis buffers and found that the sodium deoxycholate buffer provided the best overall performance. We then developed an approach for serial enrichment and profiling of the multi-level proteome. To expand the depth of identification, we customized the variable windows to perform data-independent acquisition (DIA) sequencing for each proteome. In total, we identified 6465 proteins, ∼20,000 GlyGly sites (class 1), and ∼ 19,000 phosphosites (class 1) sequentially using 1 mg of HeLa digest by three DIA measurements. We applied this strategy to analyze MG132-treated HeLa cells and observed the crosstalk between ubiquitination and phosphorylation. Our method can be referenced for other multi-level proteome studies with microscale samples. SIGNIFICANCE: Lysis buffer containing sodium deoxycholate provided the best overall performance in multi-level proteome analysis. One step of ubiquitination enrichment before phosphorylation enrichment does not reduce the reproducibility of phosphoproteome. Customized isolation windows were established for DIA analysis on each level of proteome. Combined the serial enrichment approach and the customized single-shot DIA method enabled the multi-level proteome of microscale protein samples.
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Affiliation(s)
- Dongying Huang
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yeye Leng
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Xiangye Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Meining Xing
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Wantao Ying
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China.
| | - Xiaoxia Gao
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China.
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18
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Yu F, Teo GC, Kong AT, Fröhlich K, Li GX, Demichev V, Nesvizhskii AI. Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform. Nat Commun 2023; 14:4154. [PMID: 37438352 PMCID: PMC10338508 DOI: 10.1038/s41467-023-39869-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/28/2023] [Indexed: 07/14/2023] Open
Abstract
Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
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Affiliation(s)
- Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Andy T Kong
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Klemens Fröhlich
- Proteomics Core Facility, Biozentrum, University of Basel, Basel, Switzerland
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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19
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Martínez-Val A, Fort K, Koenig C, Van der Hoeven L, Franciosa G, Moehring T, Ishihama Y, Chen YJ, Makarov A, Xuan Y, Olsen JV. Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids. Nat Commun 2023; 14:3599. [PMID: 37328457 PMCID: PMC10276052 DOI: 10.1038/s41467-023-39347-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/06/2023] [Indexed: 06/18/2023] Open
Abstract
Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.
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Affiliation(s)
- Ana Martínez-Val
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Kyle Fort
- Thermo Fisher Scientific, Bremen, Germany
| | - Claire Koenig
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Leander Van der Hoeven
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Giulia Franciosa
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | | | | | | | | | - Yue Xuan
- Thermo Fisher Scientific, Bremen, Germany.
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
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20
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Hamza GM, Miele E, Wojchowski DM, Toran P, Worsfold CR, Anthonymuthu TS, Bergo VB, Zhang AX, Silva JC. Affi-BAMS™: A Robust Targeted Proteomics Microarray Platform to Measure Histone Post-Translational Modifications. Int J Mol Sci 2023; 24:10060. [PMID: 37373206 DOI: 10.3390/ijms241210060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 06/08/2023] [Accepted: 06/11/2023] [Indexed: 06/29/2023] Open
Abstract
For targeted protein panels, the ability to specifically assay post-translational modifications (PTMs) in a quantitative, sensitive, and straightforward manner would substantially advance biological and pharmacological studies. The present study highlights the effectiveness of the Affi-BAMS™ epitope-directed affinity bead capture/MALDI MS platform for quantitatively defining complex PTM marks of H3 and H4 histones. Using H3 and H4 histone peptides and isotopically labelled derivatives, this affinity bead and MALDI MS platform achieves a range of >3 orders of magnitude with a technical precision CV of <5%. Using nuclear cellular lysates, Affi-BAMS PTM-peptide capture resolves heterogeneous histone N-terminal PTMs with as little as 100 µg of starting material. In an HDAC inhibitor and MCF7 cell line model, the ability to monitor dynamic histone H3 acetylation and methylation events is further demonstrated (including SILAC quantification). Affi-BAMS (and its capacity for the multiplexing of samples and target PTM-proteins) thus provides a uniquely efficient and effective approach for analyzing dynamic epigenetic histone marks, which is critical for the regulation of chromatin structure and gene expression.
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Affiliation(s)
- Ghaith M Hamza
- Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Boston, MA 02451, USA
- Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
| | - Eric Miele
- Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Boston, MA 02451, USA
| | - Don M Wojchowski
- Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
| | - Paul Toran
- Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
| | | | | | | | - Andrew X Zhang
- Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Boston, MA 02451, USA
| | - Jeffrey C Silva
- Adeptrix Corporation, Beverly, MA 01915, USA
- Cell Signaling Technology, Danvers, MA 01915, USA
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21
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Wu X, Liu YK, Iliuk AB, Tao WA. Mass spectrometry-based phosphoproteomics in clinical applications. Trends Analyt Chem 2023; 163:117066. [PMID: 37215489 PMCID: PMC10195102 DOI: 10.1016/j.trac.2023.117066] [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] [Indexed: 05/24/2023]
Abstract
Protein phosphorylation is an essential post-translational modification that regulates many aspects of cellular physiology, and dysregulation of pivotal phosphorylation events is often responsible for disease onset and progression. Clinical analysis on disease-relevant phosphoproteins, while quite challenging, provides unique information for precision medicine and targeted therapy. Among various approaches, mass spectrometry (MS)-centered characterization features discovery-driven, high-throughput and in-depth identification of phosphorylation events. This review highlights advances in sample preparation and instrument in MS-based phosphoproteomics and recent clinical applications. We emphasize the preeminent data-independent acquisition method in MS as one of the most promising future directions and biofluid-derived extracellular vesicles as an intriguing source of the phosphoproteome for liquid biopsy.
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Affiliation(s)
- Xiaofeng Wu
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Yi-Kai Liu
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
| | - Anton B. Iliuk
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
- Tymora Analytical Operations, West Lafayette, IN, USA
| | - W. Andy Tao
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
- Tymora Analytical Operations, West Lafayette, IN, USA
- Center for Cancer Research, Purdue University, West Lafayette, IN, USA
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22
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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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23
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Li X, Huang Y, Zheng K, Yu G, Wang Q, Gu L, Li J, Wang H, Zhang W, Sun Y, Li C. Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer. BIOPHYSICS REPORTS 2023; 9:67-81. [PMID: 37753059 PMCID: PMC10518519 DOI: 10.52601/bpr.2022.210048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 11/18/2022] [Indexed: 02/19/2023] Open
Abstract
Mass spectrometry (MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Data-independent acquisition (DIA) mode is considered to perform better than data-dependent acquisition (DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft (MiniPDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients. Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases. Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer (CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and MiniPDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.
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Affiliation(s)
- Xumiao Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yiming Huang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kuo Zheng
- Colorectal Surgery Department, Changhai Hospital, Naval Medical University, Shanghai 200433, China
| | - Guanyu Yu
- Colorectal Surgery Department, Changhai Hospital, Naval Medical University, Shanghai 200433, China
| | - Qinqin Wang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Lei Gu
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jingquan Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hui Wang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Wei Zhang
- Colorectal Surgery Department, Changhai Hospital, Naval Medical University, Shanghai 200433, China
| | - Yidi Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chen Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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24
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Franciosa G, Locard-Paulet M, Jensen LJ, Olsen JV. Recent advances in kinase signaling network profiling by mass spectrometry. Curr Opin Chem Biol 2023; 73:102260. [PMID: 36657259 DOI: 10.1016/j.cbpa.2022.102260] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 01/19/2023]
Abstract
Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.
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Affiliation(s)
- Giulia Franciosa
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marie Locard-Paulet
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lars J Jensen
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesper V Olsen
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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25
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Hadisurya M, Lee ZC, Luo Z, Zhang G, Ding Y, Zhang H, Iliuk AB, Pili R, Boris RS, Tao WA. Data-independent acquisition phosphoproteomics of urinary extracellular vesicles enables renal cell carcinoma grade differentiation. Mol Cell Proteomics 2023; 22:100536. [PMID: 36997065 PMCID: PMC10165457 DOI: 10.1016/j.mcpro.2023.100536] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 03/01/2023] [Accepted: 03/24/2023] [Indexed: 03/31/2023] Open
Abstract
Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated (GPF) library, direct DIA (library-free), forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease (CKD), and healthy control (HC) individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2,584 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.
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26
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Bons J, Rose J, Zhang R, Burton JB, Carrico C, Verdin E, Schilling B. In-depth analysis of the Sirtuin 5-regulated mouse brain malonylome and succinylome using library-free data-independent acquisitions. Proteomics 2023; 23:e2100371. [PMID: 36479818 PMCID: PMC10363399 DOI: 10.1002/pmic.202100371] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/29/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022]
Abstract
Post-translational modifications (PTMs) dynamically regulate proteins and biological pathways, typically through the combined effects of multiple PTMs. Lysine residues are targeted for various PTMs, including malonylation and succinylation. However, PTMs offer specific challenges to mass spectrometry-based proteomics during data acquisition and processing. Thus, novel and innovative workflows using data-independent acquisition (DIA) ensure confident PTM identification, precise site localization, and accurate and robust label-free quantification. In this study, we present a powerful approach that combines antibody-based enrichment with comprehensive DIA acquisitions and spectral library-free data processing using directDIA (Spectronaut). Identical DIA data can be used to generate spectral libraries and comprehensively identify and quantify PTMs, reducing the amount of enriched sample and acquisition time needed, while offering a fully automated workflow. We analyzed brains from wild-type and Sirtuin 5 (SIRT5)-knock-out mice, and discovered and quantified 466 malonylated and 2211 succinylated peptides. SIRT5 regulation remodeled the acylomes by targeting 164 malonylated and 578 succinylated sites. Affected pathways included carbohydrate and lipid metabolisms, synaptic vesicle cycle, and neurodegenerative diseases. We found 48 common SIRT5-regulated malonylation and succinylation sites, suggesting potential PTM crosstalk. This innovative and efficient workflow offers deeper insights into the mouse brain lysine malonylome and succinylome.
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Affiliation(s)
- Joanna Bons
- Buck Institute for Research on Aging, Novato, California, USA
| | - Jacob Rose
- Buck Institute for Research on Aging, Novato, California, USA
| | - Ran Zhang
- Buck Institute for Research on Aging, Novato, California, USA
| | - Jordan B Burton
- Buck Institute for Research on Aging, Novato, California, USA
| | | | - Eric Verdin
- Buck Institute for Research on Aging, Novato, California, USA
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27
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Zhao J, Yang Y, Xu H, Zheng J, Shen C, Chen T, Wang T, Wang B, Yi J, Zhao D, Wu E, Qin Q, Xia L, Qiao L. Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota. NPJ Biofilms Microbiomes 2023; 9:4. [PMID: 36693863 PMCID: PMC9873935 DOI: 10.1038/s41522-023-00373-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.
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Affiliation(s)
- Jinzhi Zhao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Yi Yang
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China.,ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311200, Hangzhou, China
| | - Hua Xu
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China
| | - Jianxujie Zheng
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Chengpin Shen
- Shanghai Omicsolution Co., Ltd, 201100, Shanghai, China
| | - Tian Chen
- Changhai Hospital, The Naval Military Medical University, 200433, Shanghai, China
| | - Tao Wang
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China
| | - Bing Wang
- College of Food Science and Technology, Shanghai Ocean University, 201306, Shanghai, China
| | - Jia Yi
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Dan Zhao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Enhui Wu
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Qin Qin
- Changhai Hospital, The Naval Military Medical University, 200433, Shanghai, China.
| | - Li Xia
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China.
| | - Liang Qiao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China.
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28
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Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways. Molecules 2023; 28:molecules28031143. [PMID: 36770810 PMCID: PMC9919559 DOI: 10.3390/molecules28031143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 01/12/2023] [Accepted: 01/18/2023] [Indexed: 01/26/2023] Open
Abstract
Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)-also known as multiple reaction monitoring (MRM)-and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.
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29
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Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics. Nat Commun 2023; 14:94. [PMID: 36609502 PMCID: PMC9822986 DOI: 10.1038/s41467-022-35740-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 12/20/2022] [Indexed: 01/07/2023] Open
Abstract
A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.
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30
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Bersching K, Michna T, Tenzer S, Jacob S. Data-Independent Acquisition (DIA) Is Superior for High Precision Phospho-Peptide Quantification in Magnaporthe oryzae. J Fungi (Basel) 2022; 9:jof9010063. [PMID: 36675884 PMCID: PMC9863866 DOI: 10.3390/jof9010063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/16/2022] [Accepted: 12/21/2022] [Indexed: 01/04/2023] Open
Abstract
The dynamic interplay of signaling networks in most major cellular processes is characterized by the orchestration of reversible protein phosphorylation. Consequently, analytic methods such as quantitative phospho-peptidomics have been pushed forward from a highly specialized edge-technique to a powerful and versatile platform for comprehensively analyzing the phosphorylation profile of living organisms. Despite enormous progress in instrumentation and bioinformatics, a high number of missing values caused by the experimental procedure remains a major problem, due to either a random phospho-peptide enrichment selectivity or borderline signal intensities, which both cause the exclusion for fragmentation using the commonly applied data dependent acquisition (DDA) mode. Consequently, an incomplete dataset reduces confidence in the subsequent statistical bioinformatic processing. Here, we successfully applied data independent acquisition (DIA) by using the filamentous fungus Magnaporthe oryzae as a model organism, and could prove that while maintaining data quality (such as phosphosite and peptide sequence confidence), the data completeness increases dramatically. Since the method presented here reduces the LC-MS/MS analysis from 3 h to 1 h and increases the number of phosphosites identified up to 10-fold in contrast to published studies in Magnaporthe oryzae, we provide a refined methodology and a sophisticated resource for investigation of signaling processes in filamentous fungi.
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Affiliation(s)
- Katharina Bersching
- Institute of Biotechnology and Drug Research gGmbH (IBWF), Hanns-Dieter-Hüsch-Weg 17, 55131 Mainz, Germany
| | - Thomas Michna
- Institute for Immunology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Stefan Tenzer
- Institute for Immunology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
- Helmholtz-Institute for Translational Oncology Mainz (HI-TRON), 55131 Mainz, Germany
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Stefan Jacob
- Institute of Biotechnology and Drug Research gGmbH (IBWF), Hanns-Dieter-Hüsch-Weg 17, 55131 Mainz, Germany
- Correspondence:
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31
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Dueñas ME, Peltier‐Heap RE, Leveridge M, Annan RS, Büttner FH, Trost M. Advances in high-throughput mass spectrometry in drug discovery. EMBO Mol Med 2022; 15:e14850. [PMID: 36515561 PMCID: PMC9832828 DOI: 10.15252/emmm.202114850] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/03/2022] [Accepted: 10/07/2022] [Indexed: 12/15/2022] Open
Abstract
High-throughput (HT) screening drug discovery, during which thousands or millions of compounds are screened, remains the key methodology for identifying active chemical matter in early drug discovery pipelines. Recent technological developments in mass spectrometry (MS) and automation have revolutionized the application of MS for use in HT screens. These methods allow the targeting of unlabelled biomolecules in HT assays, thereby expanding the breadth of targets for which HT assays can be developed compared to traditional approaches. Moreover, these label-free MS assays are often cheaper, faster, and more physiologically relevant than competing assay technologies. In this review, we will describe current MS techniques used in drug discovery and explain their advantages and disadvantages. We will highlight the power of mass spectrometry in label-free in vitro assays, and its application for setting up multiplexed cellular phenotypic assays, providing an exciting new tool for screening compounds in cell lines, and even primary cells. Finally, we will give an outlook on how technological advances will increase the future use and the capabilities of mass spectrometry in drug discovery.
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Affiliation(s)
- Maria Emilia Dueñas
- Laboratory for Biomedical Mass Spectrometry, Biosciences InstituteNewcastle UniversityNewcastle‐upon‐TyneUK
| | - Rachel E Peltier‐Heap
- Discovery Analytical, Screening Profiling and Mechanistic Biology, GSK R&DStevenageUK
| | - Melanie Leveridge
- Discovery Analytical, Screening Profiling and Mechanistic Biology, GSK R&DStevenageUK
| | - Roland S Annan
- Discovery Analytical, Screening Profiling and Mechanistic Biology, GSK R&DStevenageUK
| | - Frank H Büttner
- Drug Discovery Sciences, High Throughput BiologyBoehringer Ingelheim Pharma GmbH&CoKGBiberachGermany
| | - Matthias Trost
- Laboratory for Biomedical Mass Spectrometry, Biosciences InstituteNewcastle UniversityNewcastle‐upon‐TyneUK
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32
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Shen CY, Chang WH, Chen YJ, Weng CW, Regmi P, Kier MKK, Su KY, Chang GC, Chen JS, Chen YJ, Yu SL. Tissue Proteogenomic Landscape Reveals the Role of Uncharacterized SEL1L3 in Progression and Immunotherapy Response in Lung Adenocarcinoma. J Proteome Res 2022; 22:1056-1070. [PMID: 36349894 DOI: 10.1021/acs.jproteome.2c00382] [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: 11/10/2022]
Abstract
The fundamental pursuit to complete the human proteome atlas and the unmet clinical needs in lung adenocarcinoma have prompted us to study the functional role of uncharacterized proteins and explore their implications in cancer biology. In this study, we characterized SEL1L3, a previously uncharacterized protein encoded from chromosome 4 as a dysregulated protein in lung adenocarcinoma from the large-scale tissue proteogenomics data set established using the cohort of Taiwan Cancer Moonshot. SEL1L3 was expressed in abundance in the tumor parts compared with paired adjacent normal tissues in 90% of the lung adenocarcinoma patients in our cohorts. Moreover, survival analysis revealed the association of SEL1L3 with better clinical outcomes. Intriguingly, silencing of SEL1L3 imposed a reduction in cell viability and activation of ER stress response pathways, indicating a role of SEL1L3 in the regulation of cell stress. Furthermore, the immune profiles of patients with higher SEL1L3 expression were corroborated with its active role in immunophenotype and favorable clinical outcomes in lung adenocarcinoma. Taken together, our study revealed that SEL1L3 might play a vital role in the regulation of cell stress, interaction with cancer cells and the immune microenvironment. Our research findings provide promising insights for further investigation of its molecular signaling network and also suggest SEL1L3 as a potential emerging adjuvant for immunotherapy in lung adenocarcinoma.
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Affiliation(s)
- Chi-Ya Shen
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei10048, Taiwan
| | - Wen-Hsin Chang
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, University of California─Davis, Davis, California95616, United States.,Division of Nephrology, Department of Internal Medicine, University of California─Davis, Davis, California95616, United States
| | - Yi-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei11529, Taiwan
| | - Chia-Wei Weng
- Institute of Medicine, Chung Shan Medical University, Taichung40201, Taiwan
| | - Prabha Regmi
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei10048, Taiwan
| | - Mickiela K K Kier
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei10048, Taiwan
| | - Kang-Yi Su
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei10048, Taiwan.,Department of Laboratory Medicine, National Taiwan University Hospital, Taipei10002, Taiwan
| | - Gee-Chen Chang
- Division of Pulmonary Medicine, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung40201, Taiwan
| | - Jin-Shing Chen
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei10002, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei11529, Taiwan
| | - Sung-Liang Yu
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei10048, Taiwan.,Department of Laboratory Medicine, National Taiwan University Hospital, Taipei10002, Taiwan.,Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei10051, Taiwan.,Graduate Institute of Pathology, College of Medicine, National Taiwan University, Taipei10051, Taiwan.,Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei10002, Taiwan
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33
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Kar FM, Vogel C, Hochwagen A. Meiotic DNA breaks activate a streamlined phospho-signaling response that largely avoids protein-level changes. Life Sci Alliance 2022; 5:e202201454. [PMID: 36271494 PMCID: PMC9438802 DOI: 10.26508/lsa.202201454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 08/15/2022] [Accepted: 08/19/2022] [Indexed: 11/24/2022] Open
Abstract
Meiotic cells introduce a numerous programmed DNA breaks into their genome to stimulate meiotic recombination and ensure controlled chromosome inheritance and fertility. A checkpoint network involving key kinases and phosphatases coordinates the repair of these DNA breaks, but the precise phosphorylation targets remain poorly understood. It is also unknown whether meiotic DNA breaks change gene expression akin to the canonical DNA-damage response. To address these questions, we analyzed the meiotic DNA break response in Saccharomyces cerevisiae using multiple systems-level approaches. We identified 332 DNA break-dependent phosphorylation sites, vastly expanding the number of known events during meiotic prophase. Less than half of these events occurred in recognition motifs for the known meiotic checkpoint kinases Mec1 (ATR), Tel1 (ATM), and Mek1 (CHK2), suggesting that additional kinases contribute to the meiotic DNA-break response. We detected a clear transcriptional program but detected only very few changes in protein levels. We attribute this dichotomy to a decrease in transcript levels after meiotic entry that dampens the effects of break-induced transcription sufficiently to cause only minimal changes in the meiotic proteome.
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Affiliation(s)
- Funda M Kar
- Department of Biology, New York University, New York City, NY, USA
| | - Christine Vogel
- Department of Biology, New York University, New York City, NY, USA
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34
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Gong Y, Behera G, Erber L, Luo A, Chen Y. HypDB: A functionally annotated web-based database of the proline hydroxylation proteome. PLoS Biol 2022; 20:e3001757. [PMID: 36026437 PMCID: PMC9455854 DOI: 10.1371/journal.pbio.3001757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 09/08/2022] [Accepted: 07/13/2022] [Indexed: 01/16/2023] Open
Abstract
Proline hydroxylation (Hyp) regulates protein structure, stability, and protein-protein interaction. It is widely involved in diverse metabolic and physiological pathways in cells and diseases. To reveal functional features of the Hyp proteome, we integrated various data sources for deep proteome profiling of the Hyp proteome in humans and developed HypDB (https://www.HypDB.site), an annotated database and web server for Hyp proteome. HypDB provides site-specific evidence of modification based on extensive LC-MS analysis and literature mining with 14,413 nonredundant Hyp sites on 5,165 human proteins including 3,383 Class I and 4,335 Class II sites. Annotation analysis revealed significant enrichment of Hyp on key functional domains and tissue-specific distribution of Hyp abundance across 26 types of human organs and fluids and 6 cell lines. The network connectivity analysis further revealed a critical role of Hyp in mediating protein-protein interactions. Moreover, the spectral library generated by HypDB enabled data-independent analysis (DIA) of clinical tissues and the identification of novel Hyp biomarkers in lung cancer and kidney cancer. Taken together, our integrated analysis of human proteome with publicly accessible HypDB revealed functional diversity of Hyp substrates and provides a quantitative data source to characterize Hyp in pathways and diseases.
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Affiliation(s)
- Yao Gong
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
- Bioinformatics and Computational Biology Program, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
| | - Gaurav Behera
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
| | - Luke Erber
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
| | - Ang Luo
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
| | - Yue Chen
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
- Bioinformatics and Computational Biology Program, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America
- * E-mail:
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35
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Chan H, Chen L, Chiu H, Chen Y. Membrane proteomic profiling enhances drug target detection. J CHIN CHEM SOC-TAIP 2022. [DOI: 10.1002/jccs.202200265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Hsin‐Ju Chan
- Institute of Chemistry, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
| | - Li‐Yu Chen
- Institute of Chemistry, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
| | - Huan‐Chi Chiu
- Institute of Chemistry, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
| | - Yu‐Ju Chen
- Institute of Chemistry, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
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36
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Duan L, Scheidemantle G, Lodge M, Cummings MJ, Pham E, Wang X, Kennedy A, Liu X. Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis. Metabolomics 2022; 18:55. [PMID: 35842862 DOI: 10.1007/s11306-022-01913-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 06/27/2022] [Indexed: 10/17/2022]
Abstract
INTRODUCTION Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow. OBJECTIVES To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis. METHODS Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer. RESULTS DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition. CONCLUSION The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.
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Affiliation(s)
- Likun Duan
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Grace Scheidemantle
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Mareca Lodge
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Magdalina J Cummings
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27695, USA
- The Comparative Medicine Institute, North Carolina State University, Raleigh, NC, 27695, USA
| | - Eva Pham
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Xiaoqiu Wang
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27695, USA
- The Comparative Medicine Institute, North Carolina State University, Raleigh, NC, 27695, USA
| | - Arion Kennedy
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Xiaojing Liu
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, 27695, USA.
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37
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Xiao J, Lu S, Wang X, Liang M, Dong C, Zhang X, Qiu M, Ou C, Zeng X, Lan Y, Hu L, Tan L, Peng T, Zhang Q, Long F. Serum Proteomic Analysis Identifies SAA1, FGA, SAP, and CETP as New Biomarkers for Eosinophilic Granulomatosis With Polyangiitis. Front Immunol 2022; 13:866035. [PMID: 35757752 PMCID: PMC9226334 DOI: 10.3389/fimmu.2022.866035] [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: 01/30/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Background Eosinophilic granulomatosis with polyangiitis (EGPA) is characterized by asthma-like attacks in its early stage, which is easily misdiagnosed as severe asthma. Therefore, new biomarkers for the early diagnosis of EGPA are needed, especially for differentiating the diagnosis of asthma. Objectives To identify serum biomarkers that can be used for early diagnosis of EGPA and to distinguish EGPA from severe asthma. Method Data-independent acquisition (DIA) analysis was performed to identify 45 healthy controls (HC), severe asthma (S-A), and EGPA patients in a cohort to screen biomarkers for early diagnosis of EGPA and to differentiate asthma diagnosis. Subsequently, parallel reaction monitoring (PRM) analysis was applied to a validation cohort of 71 HC, S-A, and EGPA patients. Result Four candidate biomarkers were identified from DIA and PRM analysis-i.e., serum amyloid A1 (SAA1), fibrinogen-α (FGA), and serum amyloid P component (SAP)-and were upregulated in the EGPA group, while cholesteryl ester transfer protein (CETP) was downregulated in the EGPA group compared with the S-A group. Receiver operating characteristics analysis shows that, as biomarkers for early diagnosis of EGPA, the combination of SAA1, FGA, and SAP has an area under the curve (AUC) of 0.947, a sensitivity of 82.35%, and a specificity of 100%. The combination of SAA1, FGA, SAP, and CETP as biomarkers for differential diagnosis of asthma had an AUC of 0.921, a sensitivity of 78.13%, and a specificity of 100%, which were all larger than single markers. Moreover, SAA1, FGA, and SAP were positively and CETP was negatively correlated with eosinophil count. Conclusion DIA-PRM combined analysis screened and validated four previously unexplored but potentially useful biomarkers for early diagnosis of EGPA and differential diagnosis of asthma.
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Affiliation(s)
- Jing Xiao
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Shaohua Lu
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Xufei Wang
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Mengdi Liang
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Cong Dong
- Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaoxian Zhang
- Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Minzhi Qiu
- Health Management Center, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; the First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China
| | - Changxing Ou
- Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaoyin Zeng
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Yanting Lan
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Longbo Hu
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Long Tan
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Tao Peng
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China.,Guangdong South China Vaccine Co., Ltd, Guangzhou, China
| | - Qingling Zhang
- Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Fei Long
- Sino-French Hoffmann Institute, State Key Laboratory of Respiratory Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
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Koenig C, Martinez-Val A, Franciosa G, Olsen JV. Optimal analytical strategies for sensitive and quantitative phosphoproteomics using TMT-based multiplexing. Proteomics 2022; 22:e2100245. [PMID: 35713889 DOI: 10.1002/pmic.202100245] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/28/2022] [Accepted: 06/01/2022] [Indexed: 11/10/2022]
Abstract
In large-scale quantitative mass spectrometry (MS)-based phosphoproteomics, isobaric labeling with tandem mass tags (TMTs) coupled with offline high-pH reversed-phase peptide chromatographic fractionation maximizes depth of coverage. To investigate to what extent limited sample amounts affect sensitivity and dynamic range of the analysis due to sample losses, we benchmarked TMT-based fractionation strategies against single-shot label-free quantification with spectral library-free data independent acquisition (LFQ-DIA), for different peptide input per sample. To systematically examine how peptide input amounts influence TMT-fractionation approaches in a phosphoproteomics workflow, we compared two different high-pH reversed-phase fractionation strategies, microflow (MF) and stage-tip fractionation (STF), while scaling the peptide input amount down from 12.5 to 1 μg per sample. Our results indicate that, for input amounts higher than 5 μg per sample, TMT labeling, followed by microflow fractionation (MF) and phospho-enrichment, achieves the deepest phosphoproteome coverage, even compared to single shot direct-DIA analysis. Conversely, STF of enriched phosphopeptides (STF) is optimal for lower amounts, below 5 μg/peptide per sample. As a result, we provide a decision tree to help phosphoproteomics users to choose the best workflow as a function of sample amount.
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Affiliation(s)
- Claire Koenig
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Ana Martinez-Val
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Giulia Franciosa
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
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Yang X, Wang N, Ren S, Hu Y, Wang H, Ji A, Cao L, Li M, Liu J, Wang H. Phosphorylation regulation of cardiac proteins in Babesia microti infected mice in an effort to restore heart function. Parasit Vectors 2022; 15:98. [PMID: 35313969 PMCID: PMC8935697 DOI: 10.1186/s13071-022-05233-7] [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: 01/11/2022] [Accepted: 03/03/2022] [Indexed: 11/10/2022] Open
Abstract
Background Babesia is a common protozoan parasite that infects red blood cells. In mice infected with Babesia microti, the red blood cells were lysed, resulting in decreased oxygen-carrying capacity. To compensate for low blood oxygen levels, stress on the heart was greatly increased. Babesiosis induces a variety of pathologies; meanwhile, heart tissues initiate self-repair responses to babesiosis-induced tissue damage to restore heart function. Methods To discover the molecular mechanisms of the damage and self-repair in the heart after B. microti infection in mice, we investigated the changes in protein expression and phosphorylation modification levels in heart tissues at 0, 5, 8, 11, and 19 days post-infection using data-independent acquisition (DIA) quantitative proteomics. Results The numbers of global proteins we identified were 1934, 1966, 1984, 1989, and 1955 and of phosphopeptides were 5118, 5133, 5130, 5133, and 5140 at 0, 5, 8, 11, and 19 days, respectively, in heart cells after infection with B. microti. The results showed that after B. microti infection the differentially expressed proteins in mice mainly include fibrinogen α (Fgα), fibrinogen β (Fgβ), Serpina1b, Serpina1c, cathepsin Z, cytochrome c oxidases (COXs), RPS11, and RPS20. The proteins with phosphorylation changes mainly include 20-kDa light chain of myosin II (MLC20), myosin light chain kinase (MLCK), mitogen-activated protein kinase 14 (MAPK14), and Akt1. These proteins were mainly involved in coagulation processes, cell apoptosis, oxidative phosphorylation, and ribosomes. Conclusions The coagulation cascade-related proteins, apoptosis-related proteins, oxidative phosphorylation-related proteins, and other types of proteins are all involved in the damage and self-repair process in the heart after B. microti infection. These results offer a wealth of new targets for further exploration into the causes of heart disease induced by Babesia infection and are of great significance for novel drug development and new opportunities for targeted therapies. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s13071-022-05233-7.
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Affiliation(s)
- Xiaohong Yang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.,Department of Pathogenic Biology, College of Basic Medicine, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Ningmei Wang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Shuguang Ren
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.,The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yuhong Hu
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.,Instrumental Analysis Center, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Han Wang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Aimeng Ji
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Lihui Cao
- Animal Disease Control Center of Zhengding County, Shijiazhuang, Hebei, China
| | - Mengxue Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Jingze Liu
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.
| | - Hui Wang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.
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40
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Zhang B, Li S, Shui W. Post-Translational Modifications of G Protein–Coupled Receptors Revealed by Proteomics and Structural Biology. Front Chem 2022; 10:843502. [PMID: 35355784 PMCID: PMC8960047 DOI: 10.3389/fchem.2022.843502] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 02/16/2022] [Indexed: 01/20/2023] Open
Abstract
G protein–coupled receptors (GPCRs) are a protein superfamily comprising >800 members that regulate numerous cellular and physiologic responses. GPCRs represent the largest class of therapeutic targets with implications in various diseases. Although advances in GPCR structural and pharmacological research have significantly improved our knowledge of GPCR signaling mechanisms, mapping diverse post-translational modifications (PTMs) of GPCR proteins and understanding their regulatory roles have received much less attention. Mass spectrometry-based proteomics has become the most popular technology for profiling protein PTMs in a systematic manner. Herein we provide an overview of PTM types, locations, crosstalk and dynamic regulation for different GPCRs that are characterized using proteomic and/or biochemical approaches. Our main focus is on glycosylation, phosphorylation, ubiquitination and palmitoylation that are known to modulate receptor folding, biosynthesis, trafficking, dimerization and signaling. Furthermore, we discuss the locations of specific PTM sites in the structure of a given GPCR and its signaling complex to highlight the importance of PTM regulation in the molecular basis of GPCRs, which may shed new light on structure-based drug discovery.
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Affiliation(s)
- Bingjie Zhang
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Shanshan Li
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- *Correspondence: Wenqing Shui,
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41
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Li J, Fan C, Yao Y, Liu Z, Li F, Jiang B. Highly efficient enrichment of intact phosphoproteins by a cadmium ion‐based co‐precipitation strategy. J Sep Sci 2022; 45:1336-1344. [DOI: 10.1002/jssc.202100892] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/19/2022] [Accepted: 01/25/2022] [Indexed: 11/08/2022]
Affiliation(s)
- Jiangfeng Li
- School of Basic Medical Sciences, Academy of Medical Science Zhengzhou University Zhengzhou China
| | - Chongyuan Fan
- School of Basic Medical Sciences, Academy of Medical Science Zhengzhou University Zhengzhou China
| | - Yating Yao
- School of Basic Medical Sciences, Academy of Medical Science Zhengzhou University Zhengzhou China
| | - Zhaochen Liu
- The First Affiliated Hospital of Zhengzhou University Zhengzhou University Zhengzhou China
| | - Fangfang Li
- School of Basic Medical Sciences, Academy of Medical Science Zhengzhou University Zhengzhou China
| | - Binghua Jiang
- School of Basic Medical Sciences, Academy of Medical Science Zhengzhou University Zhengzhou China
- Department of Pathology, Anatomy and Cell Biology Thomas Jefferson University Philadelphia PA19107 USA
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42
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Yang F, Jia G, Guo J, Liu Y, Wang C. Quantitative Chemoproteomic Profiling with Data-Independent Acquisition-Based Mass Spectrometry. J Am Chem Soc 2022; 144:901-911. [PMID: 34986311 DOI: 10.1021/jacs.1c11053] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Activity-based protein profiling (ABPP) has emerged as a powerful and versatile tool to enable annotation of protein functions and discovery of targets of bioactive ligands in complex biological systems. It utilizes chemical probes to covalently label functional sites in proteins so that they can be enriched for mass spectrometry (MS)-based quantitative proteomics analysis. However, the semistochastic nature of data-dependent acquisition and high cost associated with isotopically encoded quantification reagents compromise the power of ABPP in multidimensional analysis and high-throughput screening, when a large number of samples need to be quantified in parallel. Here, we combine the data-independent acquisition (DIA) MS with ABPP to develop an efficient label-free quantitative chemical proteomic method, DIA-ABPP, with good reproducibility and high accuracy for high-throughput quantification. We demonstrated the power of DIA-ABPP for comprehensive profiling of functional cysteineome in three distinct applications, including dose-dependent quantification of cysteines' sensitivity toward a reactive metabolite, screening of ligandable cysteines with a covalent fragment library, and profiling of cysteinome fluctuation in circadian clock cycles. DIA-ABPP will open new opportunities for in-depth and multidimensional profiling of functional proteomes and interactions with bioactive small molecules in complex biological systems.
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Affiliation(s)
- Fan Yang
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Guogeng Jia
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Jiuzhou Guo
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Yuan Liu
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Chu Wang
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.,Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
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Gebreyesus ST, Siyal AA, Kitata RB, Chen ESW, Enkhbayar B, Angata T, Lin KI, Chen YJ, Tu HL. Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry. Nat Commun 2022; 13:37. [PMID: 35013269 PMCID: PMC8748772 DOI: 10.1038/s41467-021-27778-4] [Citation(s) in RCA: 83] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 11/24/2021] [Indexed: 12/27/2022] Open
Abstract
Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan
| | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan
- Department of Chemistry, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | | | | | - Bayarmaa Enkhbayar
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan
- Institute of Biological Chemistry, Academia Sinica, Taipei, 11529, Taiwan
| | - Takashi Angata
- Institute of Biological Chemistry, Academia Sinica, Taipei, 11529, Taiwan
| | - Kuo-I Lin
- Genomics Research Center, Academia Sinica, Taipei, 11529, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan.
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, 10617, Taiwan.
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan.
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, 10617, Taiwan.
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44
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Siyal AA, Chen ESW, Chan HJ, Kitata RB, Yang JC, Tu HL, Chen YJ. Sample Size-Comparable Spectral Library Enhances Data-Independent Acquisition-Based Proteome Coverage of Low-Input Cells. Anal Chem 2021; 93:17003-17011. [PMID: 34904835 DOI: 10.1021/acs.analchem.1c03477] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Despite advancements of data-independent acquisition mass spectrometry (DIA-MS) to provide comprehensive and reproducible proteome profiling, its utility in very low-input samples is limited. Due to different proteome complexities and corresponding peptide ion abundances, the conventional LC-MS/MS acquisition and widely used large-scale DIA libraries may not be suitable for the micro-nanogram samples. In this study, we report a sample size-comparable library-based DIA approach to enhance the proteome coverage of low-input nanoscale samples (i.e., nanogram cells, ∼5-50 cells). By constructing sample size-comparable libraries, 2380 and 3586 protein groups were identified from as low as 0.75 (∼5 cells) and 1.5 ng (∼10 cells), respectively, highlighting one of the highest proteome coverage with good reproducibility (86%-99% in triplicate results). For the 0.75 ng sample (∼5 cells), significantly superior identification (2380 proteins) was achieved by small-size library-based DIA, compared to 1908, 1749, and 107 proteins identified from medium-size and large-size libraries and a lung cancer resource spectral library, respectively. A similar trend was observed using a different instrument and data analysis pipeline, indicating the generalized conclusion of the approach. Furthermore, the small-size library uniquely identified 518 (22%) proteins in the low-abundant region and spans over a 5-order dynamic range. Spectral similarity analysis revealed that the fragmentation ion pattern in the DIA-MS/MS spectra of the dataset and spectral library play crucial roles for mapping low abundant proteins. With these spectral libraries made freely available, the optimized library-based DIA strategy and DIA digital map will advance quantitative proteomics applications for mass-limited samples.
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Affiliation(s)
- Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University, Hsinchu 300, Taiwan
| | - Eric Sheng-Wen Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Research Center for Cancer Biology, China Medical University, Taichung 40402, Taiwan
| | - Hsin-Ju Chan
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan
| | | | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan.,Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan
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Lou R, Liu W, Li R, Li S, He X, Shui W. DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation. Nat Commun 2021; 12:6685. [PMID: 34795227 PMCID: PMC8602247 DOI: 10.1038/s41467-021-26979-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 10/26/2021] [Indexed: 12/27/2022] Open
Abstract
Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining heavily relies on a spectral library that in most cases is built on DDA analysis of the same sample. Construction of this project-specific DDA library impairs the analytical throughput, limits the proteome coverage, and increases the sample size for DIA phosphoproteomics. Herein we introduce a deep neural network, DeepPhospho, which conceptually differs from previous deep learning models to achieve accurate predictions of LC-MS/MS data for phosphopeptides. By leveraging in silico libraries generated by DeepPhospho, we establish a DIA workflow for phosphoproteome profiling which involves DIA data acquisition and data mining with DeepPhospho predicted libraries, thus circumventing the need of DDA library construction. Our DeepPhospho-empowered workflow substantially expands the phosphoproteome coverage while maintaining high quantification performance, which leads to the discovery of more signaling pathways and regulated kinases in an EGF signaling study than the DDA library-based approach. DeepPhospho is provided as a web server as well as an offline app to facilitate user access to model training, predictions and library generation.
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Affiliation(s)
- Ronghui Lou
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Weizhen Liu
- School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Rongjie Li
- School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Shanshan Li
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
| | - Xuming He
- School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai, 201210, China.
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
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Gerritsen JS, White FM. Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells. Expert Rev Proteomics 2021; 18:661-674. [PMID: 34468274 PMCID: PMC8628306 DOI: 10.1080/14789450.2021.1976152] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Many pathologies, including cancer, have been associated with aberrant phosphorylation-mediated signaling networks that drive altered cell proliferation, migration, metabolic regulation, and can lead to systemic inflammation. Phosphoproteomics, the large-scale analysis of protein phosphorylation sites, has emerged as a powerful tool to define signaling network regulation and dysregulation in normal and pathological conditions. AREAS COVERED We provide an overview of methodology for global phosphoproteomics as well as enrichment of specific subsets of the phosphoproteome, including phosphotyrosine and phospho-motif enrichment of kinase substrates. We review quantitative methods, advantages and limitations of different mass spectrometry acquisition formats, and computational approaches to extract biological insight from phosphoproteomics data. Throughout, we discuss various applications and their challenges in implementation. EXPERT OPINION Over the past 20 years the field of phosphoproteomics has advanced to enable deep biological and clinical insight through the quantitative analysis of signaling networks. Future areas of development include Clinical Laboratory Improvement Amendments (CLIA)-approved methods for analysis of clinical samples, continued improvements in sensitivity to enable analysis of small numbers of rare cells and tissue microarrays, and computational methods to integrate data resulting from multiple systems-level quantitative analytical methods.
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Affiliation(s)
- Jacqueline S Gerritsen
- Koch Institute for Integrative Cancer Research; Center for Precision Cancer Medicine; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, U.S.A
| | - Forest M White
- Koch Institute for Integrative Cancer Research; Center for Precision Cancer Medicine; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, U.S.A
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