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Karpov OA, Stotland A, Raedschelders K, Chazarin B, Ai L, Murray CI, Van Eyk JE. Proteomics of the heart. Physiol Rev 2024; 104:931-982. [PMID: 38300522 DOI: 10.1152/physrev.00026.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 12/25/2023] [Accepted: 01/14/2024] [Indexed: 02/02/2024] Open
Abstract
Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.
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Affiliation(s)
- Oleg A Karpov
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Aleksandr Stotland
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Koen Raedschelders
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Blandine Chazarin
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Lizhuo Ai
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
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2
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López-Valverde L, Vázquez-Mosquera ME, Colón-Mejeras C, Bravo SB, Barbosa-Gouveia S, Álvarez JV, Sánchez-Martínez R, López-Mendoza M, López-Rodríguez M, Villacorta-Argüelles E, Goicoechea-Diezhandino MA, Guerrero-Márquez FJ, Ortolano S, Leao-Teles E, Hermida-Ameijeiras Á, Couce ML. Characterization of the plasma proteomic profile of Fabry disease: Potential sex- and clinical phenotype-specific biomarkers. Transl Res 2024; 269:47-63. [PMID: 38395389 DOI: 10.1016/j.trsl.2024.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/25/2024] [Accepted: 02/20/2024] [Indexed: 02/25/2024]
Abstract
Fabry disease (FD) is a X-linked rare lysosomal storage disorder caused by deficient α-galactosidase A (α-GalA) activity. Early diagnosis and the prediction of disease course are complicated by the clinical heterogeneity of FD, as well as by the frequently inconclusive biochemical and genetic test results that do not correlate with clinical course. We sought to identify potential biomarkers of FD to better understand the underlying pathophysiology and clinical phenotypes. We compared the plasma proteomes of 50 FD patients and 50 matched healthy controls using DDA and SWATH-MS. The >30 proteins that were differentially expressed between the 2 groups included proteins implicated in processes such as inflammation, heme and haemoglobin metabolism, oxidative stress, coagulation, complement cascade, glucose and lipid metabolism, and glycocalyx formation. Stratification by sex revealed that certain proteins were differentially expressed in a sex-dependent manner. Apolipoprotein A-IV was upregulated in FD patients with complications, especially those with chronic kidney disease, and apolipoprotein C-III and fetuin-A were identified as possible markers of FD with left ventricular hypertrophy. All these proteins had a greater capacity to identify the presence of complications in FD patients than lyso-GB3, with apolipoprotein A-IV standing out as being more sensitive and effective in differentiating the presence and absence of chronic kidney disease in FD patients than renal markers such as creatinine, glomerular filtration rate and microalbuminuria. Identification of these potential biomarkers can help further our understanding of the pathophysiological processes that underlie the heterogeneous clinical manifestations associated with FD.
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Affiliation(s)
- Laura López-Valverde
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - María E Vázquez-Mosquera
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - Cristóbal Colón-Mejeras
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - Susana B Bravo
- Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Proteomic Platform, University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - Sofía Barbosa-Gouveia
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - J Víctor Álvarez
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain
| | - Rosario Sánchez-Martínez
- Internal Medicine Department, Alicante General University Hospital-Alicante Institute of Health and Biomedical Research (ISABIAL), Pintor Baeza 12, Alicante 03010, Spain
| | - Manuel López-Mendoza
- Department of Nephrology, Hospital Universitario Virgen del Rocío, Manuel Siurot s/n, Sevilla 41013, Spain
| | - Mónica López-Rodríguez
- Internal Medicine Department, Hospital Universitario Ramón y Cajal, IRYCIS, Colmenar Viejo, Madrid 28034, Spain; Faculty of Medicine and Health Sciences, Universidad de Alcalá (UAH), Av. de Madrid, Alcalá de Henares 28871, Spain
| | - Eduardo Villacorta-Argüelles
- Department of Cardiology, Complejo Asistencial Universitario de Salamanca, P°. de San Vicente 58, Salamanca 37007, Spain
| | | | - Francisco J Guerrero-Márquez
- Department of Cardiology, Internal Medicine Service, Hospital de la Serranía, San Pedro, Ronda, Málaga 29400, Spain
| | - Saida Ortolano
- Rare Diseases and Pediatric Medicine Research Group, Galicia Sur Health Research Institute-SERGAS-UVIGO, Clara Campoamor 341, Vigo 36213, Spain
| | - Elisa Leao-Teles
- Centro de Referência de Doenças Hereditárias do Metabolismo, Centro Hospitalar Universitário de São João, Prof. Hernâni Monteiro, Porto 4200-319, Portugal
| | - Álvaro Hermida-Ameijeiras
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain.
| | - María L Couce
- Unit of Diagnosis and Treatment of Congenital Metabolic Diseases. RICORS-SAMID, CIBERER. University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain; Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, Choupana s/n, Santiago de Compostela, A Coruña 15706, Spain.
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3
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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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4
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Turner NP. Playing pin-the-tail-on-the-protein in extracellular vesicle (EV) proteomics. Proteomics 2024:e2400074. [PMID: 38899939 DOI: 10.1002/pmic.202400074] [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: 03/15/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 06/21/2024]
Abstract
Extracellular vesicles (EVs) are anucleate particles enclosed by a lipid bilayer that are released from cells via exocytosis or direct budding from the plasma membrane. They contain an array of important molecular cargo such as proteins, nucleic acids, and lipids, and can transfer these cargoes to recipient cells as a means of intercellular communication. One of the overarching paradigms in the field of EV research is that EV cargo should reflect the biological state of the cell of origin. The true relationship or extent of this correlation is confounded by many factors, including the numerous ways one can isolate or enrich EVs, overlap in the biophysical properties of different classes of EVs, and analytical limitations. This presents a challenge to research aimed at detecting low-abundant EV-encapsulated nucleic acids or proteins in biofluids for biomarker research and underpins technical obstacles in the confident assessment of the proteomic landscape of EVs that may be affected by sample-type specific or disease-associated proteoforms. Improving our understanding of EV biogenesis, cargo loading, and developments in top-down proteomics may guide us towards advanced approaches for selective EV and molecular cargo enrichment, which could aid EV diagnostics and therapeutics research.
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Affiliation(s)
- Natalie P Turner
- Faculty of Health, Queensland University of Technology, Kelvin Grove, Australia
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5
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Wettstein R, Hugener J, Gillet L, Hernández-Armenta Y, Henggeler A, Xu J, van Gerwen J, Wollweber F, Arter M, Aebersold R, Beltrao P, Pilhofer M, Matos J. Waves of regulated protein expression and phosphorylation rewire the proteome to drive gametogenesis in budding yeast. Dev Cell 2024:S1534-5807(24)00343-5. [PMID: 38906138 DOI: 10.1016/j.devcel.2024.05.025] [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: 09/24/2023] [Revised: 02/25/2024] [Accepted: 05/20/2024] [Indexed: 06/23/2024]
Abstract
Sexually reproducing eukaryotes employ a developmentally regulated cell division program-meiosis-to generate haploid gametes from diploid germ cells. To understand how gametes arise, we generated a proteomic census encompassing the entire meiotic program of budding yeast. We found that concerted waves of protein expression and phosphorylation modify nearly all cellular pathways to support meiotic entry, meiotic progression, and gamete morphogenesis. Leveraging this comprehensive resource, we pinpointed dynamic changes in mitochondrial components and showed that phosphorylation of the FoF1-ATP synthase complex is required for efficient gametogenesis. Furthermore, using cryoET as an orthogonal approach to visualize mitochondria, we uncovered highly ordered filament arrays of Ald4ALDH2, a conserved aldehyde dehydrogenase that is highly expressed and phosphorylated during meiosis. Notably, phosphorylation-resistant mutants failed to accumulate filaments, suggesting that phosphorylation regulates context-specific Ald4ALDH2 polymerization. Overall, this proteomic census constitutes a broad resource to guide the exploration of the unique sequence of events underpinning gametogenesis.
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Affiliation(s)
- Rahel Wettstein
- Max Perutz Laboratories, University of Vienna, 1030 Vienna, Austria; Institute of Biochemistry, ETH Zürich, 8093 Zürich, Switzerland
| | - Jannik Hugener
- Max Perutz Laboratories, University of Vienna, 1030 Vienna, Austria; Institute of Biochemistry, ETH Zürich, 8093 Zürich, Switzerland; Institute of Molecular Biology and Biophysics, ETH Zürich, 8093 Zürich, Switzerland
| | - Ludovic Gillet
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Yi Hernández-Armenta
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK
| | - Adrian Henggeler
- Max Perutz Laboratories, University of Vienna, 1030 Vienna, Austria; Institute of Biochemistry, ETH Zürich, 8093 Zürich, Switzerland
| | - Jingwei Xu
- Institute of Molecular Biology and Biophysics, ETH Zürich, 8093 Zürich, Switzerland
| | - Julian van Gerwen
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Florian Wollweber
- Institute of Molecular Biology and Biophysics, ETH Zürich, 8093 Zürich, Switzerland
| | - Meret Arter
- Institute of Biochemistry, ETH Zürich, 8093 Zürich, Switzerland
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Pedro Beltrao
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK.
| | - Martin Pilhofer
- Institute of Molecular Biology and Biophysics, ETH Zürich, 8093 Zürich, Switzerland.
| | - Joao Matos
- Max Perutz Laboratories, University of Vienna, 1030 Vienna, Austria; Institute of Biochemistry, ETH Zürich, 8093 Zürich, Switzerland.
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6
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He Y, Hou P, Long Z, Zheng Y, Tang C, Jones E, Diao X, Zhu M. Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry. Drug Metab Dispos 2024; 52:634-643. [PMID: 38830773 DOI: 10.1124/dmd.124.001661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/24/2024] [Accepted: 03/28/2024] [Indexed: 06/05/2024] Open
Abstract
Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.
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Affiliation(s)
- Yifei He
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Pengyi Hou
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Zhimin Long
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Yuandong Zheng
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Chongzhuang Tang
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Elliott Jones
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Xingxing Diao
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
| | - Mingshe Zhu
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People's Republic of China (Y.H., Y.Z., X.D.); University of the Chinese Academy of Sciences, Beijing, People's Republic of China (Y.H., X.D.); Sciex, Beijing, People's Republic of China (P.H., Z.L.); XenoFinder Co., Ltd., Suzhou, People's Republic of China (C.T., M.Z.); AB Sciex LLC, Framingham, Massachusetts (E.J.); and MassDefect Technologies, Princeton, New Jersey (M.Z.)
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7
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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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8
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Pelaz SG, Flores-Hernández R, Vujic T, Schvartz D, Álvarez-Vázquez A, Ding Y, García-Vicente L, Belloso A, Talaverón R, Sánchez JC, Tabernero A. A proteomic approach supports the clinical relevance of TAT-Cx43 266-283 in glioblastoma. Transl Res 2024; 272:95-110. [PMID: 38876188 DOI: 10.1016/j.trsl.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/18/2024] [Accepted: 06/01/2024] [Indexed: 06/16/2024]
Abstract
Glioblastoma (GBM) is the most frequent and aggressive primary brain cancer. The Src inhibitor, TAT-Cx43266-283, exerts antitumor effects in in vitro and in vivo models of GBM. Because addressing the mechanism of action is essential to translate these results to a clinical setting, in this study we carried out an unbiased proteomic approach. Data-independent acquisition mass spectrometry proteomics allowed the identification of 190 proteins whose abundance was modified by TAT-Cx43266-283. Our results were consistent with the inhibition of Src as the mechanism of action of TAT-Cx43266-283 and unveiled antitumor effectors, such as p120 catenin. Changes in the abundance of several proteins suggested that TAT-Cx43266-283 may also impact the brain microenvironment. Importantly, the proteins whose abundance was reduced by TAT-Cx43266-283 correlated with an improved GBM patient survival in clinical datasets and none of the proteins whose abundance was increased by TAT-Cx43266-283 correlated with shorter survival, supporting its use in clinical trials.
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Affiliation(s)
- Sara G Pelaz
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain.
| | - Raquel Flores-Hernández
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | - Tatjana Vujic
- Department of Medicine, University of Geneva, 1211, Geneva, Switzerland; University Center of Legal Medicine, Lausanne-Geneva, Lausanne University Hospital and University of Lausanne, Geneva University Hospital and University of Geneva, Lausanne Geneva, Switzerland
| | - Domitille Schvartz
- Department of Medicine, University of Geneva, 1211, Geneva, Switzerland; University of Geneva, Faculty of Medicine, Proteomics Core Facility, Geneva, Switzerland
| | - Andrea Álvarez-Vázquez
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | - Yuxin Ding
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | - Laura García-Vicente
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | - Aitana Belloso
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | - Rocío Talaverón
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain
| | | | - Arantxa Tabernero
- Instituto de Neurociencias de Castilla y León (INCYL), Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Calle Pintor Fernando Gallego 1, Salamanca, 37007, Spain.
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9
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Kumsab J, Yingchutrakul Y, Simanon N, Jankam C, Sonthirod C, Tangphatsornruang S, Butkinaree C. Comparative Proteomic Analysis of Ridge Gourd Seed ( Luffa acutangula (L.) Roxb.) during Artificial Aging. ACS OMEGA 2024; 9:24739-24750. [PMID: 38882140 PMCID: PMC11171090 DOI: 10.1021/acsomega.4c01270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/15/2024] [Accepted: 05/23/2024] [Indexed: 06/18/2024]
Abstract
Seed aging is a complicated process influenced by environmental conditions, impacting biochemical processes in seeds and causing deterioration that results in reduced viability and vigor. In this study, we investigated the seed aging process of ridge gourd, which is one of the most exported commercial seeds in Thailand using sequential window acquisition of all theoretical fragment ion spectra mass spectrometry. A total of 855 proteins were identified among the two groups (0 d/15 d and 0 d/30 d). The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of differentially expressed proteins revealed that in ridge gourd seeds, the aging process altered the abundance of proteins related to the oxidative stress response, nutrient reservoir, and metabolism pathway. The most identified DEPs were mitochondrial proteins, ubiquitin-proteasome system proteins, ribosomal proteins, carbohydrate metabolism-related proteins, and stress response-related proteins. This study also presented the involvement of aconitase and glutathione pathway-associated enzymes in seed aging, with aconitase and total glutathione being determined as possible suggestive biomarkers for aged ridge gourd seeds. This acquired knowledge has the potential to considerably improve growing methods and seed preservation techniques, enhancing seed storage and maintenance.
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Affiliation(s)
- Jakkaphan Kumsab
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Yodying Yingchutrakul
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Nattapon Simanon
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Chonchawan Jankam
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Chutima Sonthirod
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Sithichoke Tangphatsornruang
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Chutikarn Butkinaree
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
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10
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Lewis JM, Jebeli L, Coulon PML, Lay CE, Scott NE. Glycoproteomic and proteomic analysis of Burkholderia cenocepacia reveals glycosylation events within FliF and MotB are dispensable for motility. Microbiol Spectr 2024; 12:e0034624. [PMID: 38709084 DOI: 10.1128/spectrum.00346-24] [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: 02/10/2024] [Accepted: 04/16/2024] [Indexed: 05/07/2024] Open
Abstract
Across the Burkholderia genus O-linked protein glycosylation is highly conserved. While the inhibition of glycosylation has been shown to be detrimental for virulence in Burkholderia cepacia complex species, such as Burkholderia cenocepacia, little is known about how specific glycosylation sites impact protein functionality. Within this study, we sought to improve our understanding of the breadth, dynamics, and requirement for glycosylation across the B. cenocepacia O-glycoproteome. Assessing the B. cenocepacia glycoproteome across different culture media using complementary glycoproteomic approaches, we increase the known glycoproteome to 141 glycoproteins. Leveraging this repertoire of glycoproteins, we quantitively assessed the glycoproteome of B. cenocepacia using Data-Independent Acquisition (DIA) revealing the B. cenocepacia glycoproteome is largely stable across conditions with most glycoproteins constitutively expressed. Examination of how the absence of glycosylation impacts the glycoproteome reveals that the protein abundance of only five glycoproteins (BCAL1086, BCAL2974, BCAL0525, BCAM0505, and BCAL0127) are altered by the loss of glycosylation. Assessing ΔfliF (ΔBCAL0525), ΔmotB (ΔBCAL0127), and ΔBCAM0505 strains, we demonstrate the loss of FliF, and to a lesser extent MotB, mirror the proteomic effects observed in the absence of glycosylation in ΔpglL. While both MotB and FliF are essential for motility, we find loss of glycosylation sites in MotB or FliF does not impact motility supporting these sites are dispensable for function. Combined this work broadens our understanding of the B. cenocepacia glycoproteome supporting that the loss of glycoproteins in the absence of glycosylation is not an indicator of the requirement for glycosylation for protein function. IMPORTANCE Burkholderia cenocepacia is an opportunistic pathogen of concern within the Cystic Fibrosis community. Despite a greater appreciation of the unique physiology of B. cenocepacia gained over the last 20 years a complete understanding of the proteome and especially the O-glycoproteome, is lacking. In this study, we utilize systems biology approaches to expand the known B. cenocepacia glycoproteome as well as track the dynamics of glycoproteins across growth phases, culturing media and in response to the loss of glycosylation. We show that the glycoproteome of B. cenocepacia is largely stable across conditions and that the loss of glycosylation only impacts five glycoproteins including the motility associated proteins FliF and MotB. Examination of MotB and FliF shows, while these proteins are essential for motility, glycosylation is dispensable. Combined this work supports that B. cenocepacia glycosylation can be dispensable for protein function and may influence protein properties beyond stability.
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Affiliation(s)
- Jessica M Lewis
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Leila Jebeli
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Pauline M L Coulon
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Catrina E Lay
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
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11
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Adnane M, de Almeida AM, Chapwanya A. Unveiling the power of proteomics in advancing tropical animal health and production. Trop Anim Health Prod 2024; 56:182. [PMID: 38825622 DOI: 10.1007/s11250-024-04037-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 05/20/2024] [Indexed: 06/04/2024]
Abstract
Proteomics, the large-scale study of proteins in biological systems has emerged as a pivotal tool in the field of animal and veterinary sciences, mainly for investigating local and rustic breeds. Proteomics provides valuable insights into biological processes underlying animal growth, reproduction, health, and disease. In this review, we highlight the key proteomics technologies, methodologies, and their applications in domestic animals, particularly in the tropical context. We also discuss advances in proteomics research, including integration of multi-omics data, single-cell proteomics, and proteogenomics, all of which are promising for improving animal health, adaptation, welfare, and productivity. However, proteomics research in domestic animals faces challenges, such as sample preparation variation, data quality control, privacy and ethical considerations relating to animal welfare. We also provide recommendations for overcoming these challenges, emphasizing the importance of following best practices in sample preparation, data quality control, and ethical compliance. We therefore aim for this review to harness the full potential of proteomics in advancing our understanding of animal biology and ultimately improve animal health and productivity in local breeds of diverse animal species in a tropical context.
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Affiliation(s)
- Mounir Adnane
- Department of Biomedicine, Institute of Veterinary Sciences, University of Tiaret, Tiaret, 14000, Algeria.
| | - André M de Almeida
- LEAF-Linking Landscape, Environment, Agriculture and Food Research Center, Associate Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa, 1349-017, Portugal
| | - Aspinas Chapwanya
- Department of Clinical Sciences, Ross University School of Veterinary Medicine, Basseterre, 00265, Saint Kitts and Nevis
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12
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Munro V, Kelly V, Messner CB, Kustatscher G. Cellular control of protein levels: A systems biology perspective. Proteomics 2024; 24:e2200220. [PMID: 38012370 DOI: 10.1002/pmic.202200220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 11/13/2023] [Accepted: 11/15/2023] [Indexed: 11/29/2023]
Abstract
How cells regulate protein levels is a central question of biology. Over the past decades, molecular biology research has provided profound insights into the mechanisms and the molecular machinery governing each step of the gene expression process, from transcription to protein degradation. Recent advances in transcriptomics and proteomics have complemented our understanding of these fundamental cellular processes with a quantitative, systems-level perspective. Multi-omic studies revealed significant quantitative, kinetic and functional differences between the genome, transcriptome and proteome. While protein levels often correlate with mRNA levels, quantitative investigations have demonstrated a substantial impact of translation and protein degradation on protein expression control. In addition, protein-level regulation appears to play a crucial role in buffering protein abundances against undesirable mRNA expression variation. These findings have practical implications for many fields, including gene function prediction and precision medicine.
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Affiliation(s)
- Victoria Munro
- Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK
| | - Van Kelly
- Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK
| | - Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK
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13
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D'Ermo G, Audebert S, Camoin L, Planer-Friedrich B, Casiot-Marouani C, Delpoux S, Lebrun R, Guiral M, Schoepp-Cothenet B. Quantitative proteomics reveals the Sox system's role in sulphur and arsenic metabolism of phototroph Halorhodospira halophila. Environ Microbiol 2024; 26:e16655. [PMID: 38897608 DOI: 10.1111/1462-2920.16655] [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: 02/08/2024] [Accepted: 05/07/2024] [Indexed: 06/21/2024]
Abstract
The metabolic process of purple sulphur bacteria's anoxygenic photosynthesis has been primarily studied in Allochromatium vinosum, a member of the Chromatiaceae family. However, the metabolic processes of purple sulphur bacteria from the Ectothiorhodospiraceae and Halorhodospiraceae families remain unexplored. We have analysed the proteome of Halorhodospira halophila, a member of the Halorhodospiraceae family, which was cultivated with various sulphur compounds. This analysis allowed us to reconstruct the first comprehensive sulphur-oxidative photosynthetic network for this family. Some members of the Ectothiorhodospiraceae family have been shown to use arsenite as a photosynthetic electron donor. Therefore, we analysed the proteome response of Halorhodospira halophila when grown under arsenite and sulphide conditions. Our analyses using ion chromatography-inductively coupled plasma mass spectrometry showed that thioarsenates are chemically formed under these conditions. However, they are more extensively generated and converted in the presence of bacteria, suggesting a biological process. Our quantitative proteomics revealed that the SoxAXYZB system, typically dedicated to thiosulphate oxidation, is overproduced under these growth conditions. Additionally, two electron carriers, cytochrome c551/c5 and HiPIP III, are also overproduced. Electron paramagnetic resonance spectroscopy suggested that these transporters participate in the reduction of the photosynthetic Reaction Centre. These results support the idea of a chemically and biologically formed thioarsenate being oxidized by the Sox system, with cytochrome c551/c5 and HiPIP III directing electrons towards the Reaction Centre.
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Affiliation(s)
- Giulia D'Ermo
- Aix-Marseille Université, CNRS, BIP-UMR 7281, Marseille, France
| | - Stéphane Audebert
- Aix-Marseille Université, Inserm, CNRS, Institut Paoli-Calmettes, CRCM, Marseille Protéomique, Marseille, France
| | - Luc Camoin
- Aix-Marseille Université, Inserm, CNRS, Institut Paoli-Calmettes, CRCM, Marseille Protéomique, Marseille, France
| | - Britta Planer-Friedrich
- Environmental Geochemistry, Bayreuth Centre for Ecology and Environmental Research (BAYCEER), University of Bayreuth, Bayreuth, Germany
| | | | - Sophie Delpoux
- Laboratoire HydroSciences Montpellier, Univ. Montpellier, CNRS, IRD, Montpellier, France
| | - Régine Lebrun
- Aix-Marseille Université, CNRS, IMM-FR3479, Marseille Protéomique, Marseille, France
| | - Marianne Guiral
- Aix-Marseille Université, CNRS, BIP-UMR 7281, Marseille, France
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14
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Padhye BD, Nawaz U, Hains PG, Reddel RR, Robinson PJ, Zhong Q, Poulos RC. Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities. Pediatr Blood Cancer 2024; 71:e30980. [PMID: 38556739 DOI: 10.1002/pbc.30980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/13/2024] [Accepted: 03/14/2024] [Indexed: 04/02/2024]
Abstract
Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.
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Affiliation(s)
- Bhavna D Padhye
- Cancer Centre for Children, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Kids Research, Children's Cancer Research Unit, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Urwah Nawaz
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Peter G Hains
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Roger R Reddel
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Phillip J Robinson
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Qing Zhong
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Rebecca C Poulos
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
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15
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Kulsange SE, Sharma M, Sonawane B, Jaiswal MR, Kulkarni MJ, Santhakumari B. SWATH-MS reveals that bisphenol A and its analogs regulate pathways leading to disruption in insulin signaling and fatty acid metabolism. Food Chem Toxicol 2024; 188:114667. [PMID: 38653447 DOI: 10.1016/j.fct.2024.114667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 03/24/2024] [Accepted: 04/14/2024] [Indexed: 04/25/2024]
Abstract
Bisphenol A (BPA) is an endocrine-disrupting chemical (EDC), associated with obesity and insulin resistance. The FDA prohibited the use of BPA-based polycarbonate resins in infant formula packaging; thus, its analogs, viz. Bisphenol S (BPS) and Bisphenol F (BPF) were considered alternatives in epoxy resins, plastics, and food cans. As these analogs might evoke a similar response, we investigated the role of Bisphenols (BPA, BPF, and BPS), on insulin signaling in CHO-HIRc-myc-GLUT4eGFP cells at environmentally relevant concentrations of 2 nM and 200 nM. Insulin signaling demonstrated that Bisphenols reduced phosphorylation of IR and AKT2, GLUT4 translocation, and glucose uptake. This was accompanied by increased oxidative stress. Furthermore, SWATH-MS-based proteomics of 3T3-L1 cells demonstrated that Bisphenol-treated cells regulate proteins in insulin resistance, adipogenesis, and fatty acid metabolism pathways differently. All three Bisphenols induced differentially expressed proteins enriched similar pathways, although their abundance differed for each Bisphenol. This might be due to their varying toxicity level, structural differences, and estrogen-mimetic activity. This study has important implications in addressing health concerns related to EDCs. Given that the analogs of BPA are considered alternatives to BPA, the findings of this study suggest they are equally potent in altering fatty acid metabolism and inducing insulin resistance.
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Affiliation(s)
- Shabda E Kulsange
- Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Monika Sharma
- Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Babasaheb Sonawane
- Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Meera R Jaiswal
- Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Mahesh J Kulkarni
- Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
| | - B Santhakumari
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India; Centre for Material Characterization, CSIR-National Chemical Laboratory, Pune 411008, India.
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16
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Hernández-Avilés C, Ramírez-Agámez L, Weintraub ST, Scoggin CF, Davis BW, Raudsepp T, Varner DD, Love CC. Proteomic analysis of sperm from fertile stallions and subfertile stallions due to impaired acrosomal exocytosis. Sci Rep 2024; 14:12446. [PMID: 38816557 PMCID: PMC11139894 DOI: 10.1038/s41598-024-63410-3] [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: 03/29/2024] [Accepted: 05/28/2024] [Indexed: 06/01/2024] Open
Abstract
Thoroughbred stallions that carry a double-homozygous genotype A/A-A/A for SNPs rs397316122 and rs69101140 in exon 5 of the FKBP6 gene (chr13; EquCab3.0) are uniquely subfertile due to impaired acrosomal exocytosis (IAE). In this study, the sperm proteome in frozen/thawed semen from subfertile Thoroughbred stallions was studied and compared to that of frozen/thawed sperm from fertile Thoroughbred stallions. A total of 2,220 proteins was identified, of which 140 proteins were found to be differentially abundant in sperm from the subfertile stallions compared to that of fertile stallions (83 less and 57 more abundant). Proteins of differential abundance in sperm from the subfertile stallions were mainly overrepresented in the "metabolism" and the "metabolism of lipids" pathways. One of these proteins, arylsulfatase F (ARSF), was studied by immunofluorescence. A lower proportion of sperm displaying ARSF signal at the acrosome region was observed in sperm from subfertile Thoroughbred stallions. In addition, heterologous zona pellucida binding assays revealed that sperm from subfertile Thoroughbred stallions bound at a lower proportion to zonae pellucidae than sperm from fertile Thoroughbred stallions. In conclusion, a group of differential abundance proteins, including some of acrosome origin, were identified in sperm from subfertile stallions with acrosome dysfunction.
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Affiliation(s)
- Camilo Hernández-Avilés
- Equine Fertility Laboratory, Department of Large Animal Clinical Sciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, 500 Raymond Stotzer Parkway, College Station, TX, 77843, USA.
| | - Luisa Ramírez-Agámez
- Equine Fertility Laboratory, Department of Large Animal Clinical Sciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, 500 Raymond Stotzer Parkway, College Station, TX, 77843, USA
| | - Susan T Weintraub
- Department of Biochemistry and Structural Biology, The University of Texas Health Science Center, San Antonio, TX, USA
| | - Charles F Scoggin
- LeBlanc Reproduction Center, Rood & Riddle Equine Hospital, Lexington, KY, USA
| | - Brian W Davis
- Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Terje Raudsepp
- Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Dickson D Varner
- Equine Fertility Laboratory, Department of Large Animal Clinical Sciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, 500 Raymond Stotzer Parkway, College Station, TX, 77843, USA
| | - Charles C Love
- Equine Fertility Laboratory, Department of Large Animal Clinical Sciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, 500 Raymond Stotzer Parkway, College Station, TX, 77843, USA
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17
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Duan H, Ning Z, Zhang A, Figeys D. Spectral entropy as a measure of the metaproteome complexity. Proteomics 2024:e2300570. [PMID: 38794877 DOI: 10.1002/pmic.202300570] [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: 03/20/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite the anticipated proteomic diversity, observed complexities of microbiome samples are often lower than expected. Two main factors contribute to this discrepancy: limitations in mass spectrometry's detection sensitivity and bioinformatics challenges in metaproteomics identification. This study introduces a novel approach to evaluating sample complexity directly at the full mass spectrum (MS1) level rather than relying on peptide identifications. When analyzing under identical mass spectrometry conditions, microbiome samples displayed significantly higher complexity, as evidenced by the spectral entropy and peptide candidate entropy, compared to single-species samples. The research provides solid evidence for the complexity of microbiome in proteomics indicating the optimization potential of the bioinformatics workflow.
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Affiliation(s)
- Haonan Duan
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Zhibin Ning
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Ailing Zhang
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Daniel Figeys
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
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18
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Kesmen E, Nezih Kök A, Ateş O, Şenol O. Investigating the pathogenesis of vitreous in postmortem COVID patients via untargeted metabolomics based bioinformatics model. Leg Med (Tokyo) 2024; 70:102461. [PMID: 38815416 DOI: 10.1016/j.legalmed.2024.102461] [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: 01/30/2024] [Revised: 05/01/2024] [Accepted: 05/15/2024] [Indexed: 06/01/2024]
Abstract
SARS-CoV-2 virus has become a worldwide pandemic causing millions of death. This severe disaster lead to a immense panic and stress all over the world. Several studies were dedicated to understand its mechanism, pathogenesis and spreading characteristics. By this way, scientists try to develop different therapy and diagnose strategies. For these reasons, several metabolomics, proteomics and genomics studies were also carried out to improve knowledge in this newly identified virus. In this study, we are aimed to explain the pathogenesis of SARS-CoV-2 exposure on postmortem COVID (+) patients via untargeted metabolomics analysis. To carry out this study, a Data Independent Acquisition SWATH method is optimized and performed. Vitreous samples were analyzed in both MS1 and MS2 ESI(+) mode. An orthogonal Partial Least Square Discriminant Analysis were performed for classification. It was observed that lipid metabolism, several amino acids and oxidative stress biomarkers were strongly affected due to high inflammation and possible cytokine storm.
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Affiliation(s)
- Elif Kesmen
- Erzurum Branch Office, The Ministry of Justice Council of Forensic Medicine, Erzurum, Turkey
| | - Ahmet Nezih Kök
- Atatürk University, Faculty of Medicine, Department of Forensic Science, 25240 Erzurum, Turkey
| | - Orhan Ateş
- Atatürk University, Faculty of Medicine, Department of Ophtalmology, 25240 Erzurum, Turkey
| | - Onur Şenol
- Atatürk University, Faculty of Pharmacy, Department of Analytical Chemistry, 25240 Erzurum, Turkey.
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19
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Rosenberger G, Li W, Turunen M, He J, Subramaniam PS, Pampou S, Griffin AT, Karan C, Kerwin P, Murray D, Honig B, Liu Y, Califano A. Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nat Commun 2024; 15:3909. [PMID: 38724493 PMCID: PMC11082183 DOI: 10.1038/s41467-024-47957-3] [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: 03/18/2023] [Accepted: 04/16/2024] [Indexed: 05/12/2024] Open
Abstract
Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.
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Affiliation(s)
- George Rosenberger
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Mikko Turunen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jing He
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Prem S Subramaniam
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sergey Pampou
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Aaron T Griffin
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Medical Scientist Training Program, Columbia University Irving Medical Center, New York, NY, USA
| | - Charles Karan
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Patrick Kerwin
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Diana Murray
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Barry Honig
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA.
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA.
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
- Chan Zuckerberg Biohub New York, New York, NY, USA.
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20
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Gent L, Chiappetta ME, Hesketh S, Palmowski P, Porter A, Bonicelli A, Schwalbe EC, Procopio N. Bone Proteomics Method Optimization for Forensic Investigations. J Proteome Res 2024; 23:1844-1858. [PMID: 38621258 PMCID: PMC11077585 DOI: 10.1021/acs.jproteome.4c00151] [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: 02/28/2024] [Revised: 03/30/2024] [Accepted: 04/03/2024] [Indexed: 04/17/2024]
Abstract
The application of proteomic analysis to forensic skeletal remains has gained significant interest in improving biological and chronological estimations in medico-legal investigations. To enhance the applicability of these analyses to forensic casework, it is crucial to maximize throughput and proteome recovery while minimizing interoperator variability and laboratory-induced post-translational protein modifications (PTMs). This work compared different workflows for extracting, purifying, and analyzing bone proteins using liquid chromatography with tandem mass spectrometry (LC-MS)/MS including an in-StageTip protocol previously optimized for forensic applications and two protocols using novel suspension-trap technology (S-Trap) and different lysis solutions. This study also compared data-dependent acquisition (DDA) with data-independent acquisition (DIA). By testing all of the workflows on 30 human cortical tibiae samples, S-Trap workflows resulted in increased proteome recovery with both lysis solutions tested and in decreased levels of induced deamidations, and the DIA mode resulted in greater sensitivity and window of identification for the identification of lower-abundance proteins, especially when open-source software was utilized for data processing in both modes. The newly developed S-Trap protocol is, therefore, suitable for forensic bone proteomic workflows and, particularly when paired with DIA mode, can offer improved proteomic outcomes and increased reproducibility, showcasing its potential in forensic proteomics and contributing to achieving standardization in bone proteomic analyses for forensic applications.
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Affiliation(s)
- Luke Gent
- School
of Law and Policing, Research Centre for Field Archaeology and Forensic
Taphonomy, University of Central Lancashire, Preston PR1 2HE, United Kingdom
| | - Maria Elena Chiappetta
- School
of Law and Policing, Research Centre for Field Archaeology and Forensic
Taphonomy, University of Central Lancashire, Preston PR1 2HE, United Kingdom
- Department
of Biology, Ecology and Earth Sciences (DiBEST), University of Calabria, Arcavacata
di Rende 87036, Italy
| | - Stuart Hesketh
- School
of Medicine, University of Central Lancashire, Preston PR1 2HE, United Kingdom
| | - Pawel Palmowski
- NUPPA
Facility, Medical School, Newcastle University, Newcastle Upon Tyne NE1
7RU, United Kingdom
| | - Andrew Porter
- NUPPA
Facility, Medical School, Newcastle University, Newcastle Upon Tyne NE1
7RU, United Kingdom
| | - Andrea Bonicelli
- School
of Law and Policing, Research Centre for Field Archaeology and Forensic
Taphonomy, University of Central Lancashire, Preston PR1 2HE, United Kingdom
| | - Edward C. Schwalbe
- Department
of Applied Sciences, Northumbria University, Newcastle Upon Tyne NE1
8ST, United Kingdom
| | - Noemi Procopio
- School
of Law and Policing, Research Centre for Field Archaeology and Forensic
Taphonomy, University of Central Lancashire, Preston PR1 2HE, United Kingdom
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21
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Ha A, Khoo A, Ignatchenko V, Khan S, Waas M, Vesprini D, Liu SK, Nyalwidhe JO, Semmes OJ, Boutros PC, Kislinger T. Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine. J Proteome Res 2024; 23:1768-1778. [PMID: 38580319 PMCID: PMC11077481 DOI: 10.1021/acs.jproteome.4c00009] [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: 01/04/2024] [Revised: 03/02/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.
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Affiliation(s)
- Annie Ha
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Amanda Khoo
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Vladimir Ignatchenko
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Shahbaz Khan
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Matthew Waas
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Danny Vesprini
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Stanley K. Liu
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Julius O. Nyalwidhe
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Oliver John Semmes
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Paul C. Boutros
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
- Department
of Urology, University of California, Los
Angeles, Los Angeles, California 90095, United States
- Institute
for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095, United States
- Eli
and Edythe Broad Stem Cell Research Center, University of California, Los
Angeles, California 90095, United States
- Broad
Stem Cell Research Center, University of
California, Los Angeles, California 90095, United States
- Jonsson
Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024, United States
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
| | - Thomas Kislinger
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
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22
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Sun Z, Ning Z, Figeys D. The Landscape and Perspectives of the Human Gut Metaproteomics. Mol Cell Proteomics 2024; 23:100763. [PMID: 38608842 PMCID: PMC11098955 DOI: 10.1016/j.mcpro.2024.100763] [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: 11/14/2023] [Revised: 02/26/2024] [Accepted: 04/09/2024] [Indexed: 04/14/2024] Open
Abstract
The human gut microbiome is closely associated with human health and diseases. Metaproteomics has emerged as a valuable tool for studying the functionality of the gut microbiome by analyzing the entire proteins present in microbial communities. Recent advancements in liquid chromatography and tandem mass spectrometry (LC-MS/MS) techniques have expanded the detection range of metaproteomics. However, the overall coverage of the proteome in metaproteomics is still limited. While metagenomics studies have revealed substantial microbial diversity and functional potential of the human gut microbiome, few studies have summarized and studied the human gut microbiome landscape revealed with metaproteomics. In this article, we present the current landscape of human gut metaproteomics studies by re-analyzing the identification results from 15 published studies. We quantified the limited proteome coverage in metaproteomics and revealed a high proportion of annotation coverage of metaproteomics-identified proteins. We conducted a preliminary comparison between the metaproteomics view and the metagenomics view of the human gut microbiome, identifying key areas of consistency and divergence. Based on the current landscape of human gut metaproteomics, we discuss the feasibility of using metaproteomics to study functionally unknown proteins and propose a whole workflow peptide-centric analysis. Additionally, we suggest enhancing metaproteomics analysis by refining taxonomic classification and calculating confidence scores, as well as developing tools for analyzing the interaction between taxonomy and function.
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Affiliation(s)
- Zhongzhi Sun
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Zhibin Ning
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Daniel Figeys
- School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
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23
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Wang C, Feng G, Zhao J, Xu Y, Li Y, Wang L, Wang M, Liu M, Wang Y, Mu H, Zhou C. Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics. Proteomics Clin Appl 2024; 18:e2300047. [PMID: 38215274 DOI: 10.1002/prca.202300047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 11/03/2023] [Accepted: 11/22/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection. METHODS The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA). RESULTS A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis. CONCLUSIONS Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.
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Affiliation(s)
- Ce Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Gang Feng
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Jie Zhao
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Xu
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Li
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Lin Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Meng Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Miao Liu
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Yilin Wang
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Hong Mu
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Chunlei Zhou
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
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24
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Bell RJ, Hage DS, Dodds ED. Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry by Matrix-Assisted Laser Desorption Ionization. Anal Chem 2024; 96:6584-6587. [PMID: 38619932 DOI: 10.1021/acs.analchem.3c05601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Two-dimensional Fourier transform ion cyclotron resonance (2D FTICR) mass spectrometry is a developing form of data-independent acquisition that allows for the simultaneous fragmentation and correlation of fragment ions to their precursors across a range of m/z values. The modern usage of 2D FTICR is performed using electrospray ionization (ESI) as the dried droplet preparation for matrix-assisted laser desorption ionization (MALDI) does not produce a consistent packet of ions over a number of scans. This work uses pneumatic spray techniques from mass spectrometry imaging to create a homogeneous surface for use with MALDI as an ionization source for 2D FTICR. A mixture of peptides and matrix was deposited onto a glass slide using an HTX pneumatic sprayer. MALDI was then used to ionize the peptide mixture for use with a standard 2D FTICR pulse sequence. The generated 2D spectrum reveals comparable structural information to spectra collected in a 1D experiment. Artifacts observed in the collected 2D MALDI spectra do not significantly differ from those expected from 2D ESI spectra.
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Affiliation(s)
- Richard J Bell
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska 68588-0304, United States
| | - David S Hage
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska 68588-0304, United States
| | - Eric D Dodds
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska 68588-0304, United States
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25
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Zhong X, Li Q, Polacco BJ, Patil T, Marley A, Foussard H, Khare P, Vartak R, Xu J, DiBerto JF, Roth BL, Eckhardt M, Zastrow MV, Krogan NJ, Hüttenhain R. A proximity proteomics pipeline with improved reproducibility and throughput. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.04.11.536358. [PMID: 37090610 PMCID: PMC10120663 DOI: 10.1101/2023.04.11.536358] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Proximity labeling (PL) through biotinylation coupled with mass spectrometry (MS) has emerged as a powerful technique for capturing spatial proteomes within living cells. Large-scale sample processing for proximity proteomics requires a workflow that minimizes hands-on time while enhancing quantitative reproducibility. Here, we present a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. By combining this pipeline with an optimized quantitative MS acquisition method based on data-independent acquisition (DIA), we not only significantly increased sample throughput but also improved the reproducibility of protein identification and quantification. We applied this pipeline to delineate subcellular proteomes across various cellular compartments, including endosomes, late endosomes/lysosomes, the Golgi apparatus, and the plasma membrane. Moreover, employing 5HT2A serotonin receptor as a model, we investigated temporal changes of proximal interaction networks induced by the receptor's activation with serotonin. Finally, to demonstrate the applicability of our PL pipeline across multiple experimental conditions, we further modified the PL pipeline for reduced sample input amounts to accommodate CRISPR-based gene knockout, and assessed the dynamics of the 5HT2A network in response to the perturbation of selected proximal interactors. Importantly, the presented PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, increasing both throughput and reproducibility of standard protocols.
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Affiliation(s)
- Xiaofang Zhong
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Qiongyu Li
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Benjamin J Polacco
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Trupti Patil
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Aaron Marley
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94158, USA
| | - Helene Foussard
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Prachi Khare
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Rasika Vartak
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jiewei Xu
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jeffrey F DiBerto
- Department of Pharmacology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bryan L Roth
- Department of Pharmacology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Manon Eckhardt
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Mark Von Zastrow
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94158, USA
| | - Nevan J Krogan
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ruth Hüttenhain
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA
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26
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Schrader JM, Xu F, Agostinucci KJ, DaSilva NA, Van Nostrand WE. Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats. Sci Rep 2024; 14:8441. [PMID: 38600214 PMCID: PMC11006668 DOI: 10.1038/s41598-024-59013-7] [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: 11/18/2023] [Accepted: 04/05/2024] [Indexed: 04/12/2024] Open
Abstract
Cerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer's disease (AD). While it is known that vascular fibrillar amyloid β (Aβ) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-β1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-β1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.
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Affiliation(s)
- Joseph M Schrader
- Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, 130 Flagg Road, Kingston, Rhode Island, 02881, USA
| | - Feng Xu
- Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, 130 Flagg Road, Kingston, Rhode Island, 02881, USA
| | - Kevin J Agostinucci
- Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, 130 Flagg Road, Kingston, Rhode Island, 02881, USA
| | - Nicholas A DaSilva
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, 02912, USA
| | - William E Van Nostrand
- Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, 130 Flagg Road, Kingston, Rhode Island, 02881, USA.
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Basharat AR, Xiong X, Xu T, Zang Y, Sun L, Liu X. TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588302. [PMID: 38645171 PMCID: PMC11030422 DOI: 10.1101/2024.04.05.588302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the last decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.
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Affiliation(s)
- Abdul Rehman Basharat
- Department of BioHealth Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA
| | - Xingzhao Xiong
- Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Tian Xu
- Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA
| | - Yong Zang
- Department of Biostatistics and Health Data Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA
| | - Xiaowen Liu
- Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA
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Goetze S, van Drogen A, Albinus JB, Fort KL, Gandhi T, Robbiani D, Laforte V, Reiter L, Levesque MP, Xuan Y, Wollscheid B. Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA. Clin Proteomics 2024; 21:26. [PMID: 38565978 PMCID: PMC10988896 DOI: 10.1186/s12014-024-09478-5] [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: 10/31/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring. METHODS Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides. RESULTS We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making. CONCLUSIONS Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.
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Affiliation(s)
- Sandra Goetze
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
- ETH PHRT Swiss Multi-Omics Center (SMOC), Zurich, Switzerland.
| | - Audrey van Drogen
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
- ETH PHRT Swiss Multi-Omics Center (SMOC), Zurich, Switzerland
| | - Jonas B Albinus
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Kyle L Fort
- Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany
| | | | | | | | | | - Mitchell P Levesque
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Yue Xuan
- Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany
| | - Bernd Wollscheid
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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Manda V, Pavelka J, Lau E. Proteomics applications in next generation induced pluripotent stem cell models. Expert Rev Proteomics 2024; 21:217-228. [PMID: 38511670 PMCID: PMC11065590 DOI: 10.1080/14789450.2024.2334033] [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: 06/14/2023] [Accepted: 03/08/2024] [Indexed: 03/22/2024]
Abstract
INTRODUCTION Induced pluripotent stem (iPS) cell technology has transformed biomedical research. New opportunities now exist to create new organoids, microtissues, and body-on-a-chip systems for basic biology investigations and clinical translations. AREAS COVERED We discuss the utility of proteomics for attaining an unbiased view into protein expression changes during iPS cell differentiation, cell maturation, and tissue generation. The ability to discover cell-type specific protein markers during the differentiation and maturation of iPS-derived cells has led to new strategies to improve cell production yield and fidelity. In parallel, proteomic characterization of iPS-derived organoids is helping to realize the goal of bridging in vitro and in vivo systems. EXPERT OPINIONS We discuss some current challenges of proteomics in iPS cell research and future directions, including the integration of proteomic and transcriptomic data for systems-level analysis.
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Affiliation(s)
- Vyshnavi Manda
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Jay Pavelka
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Edward Lau
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
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Korchak JA, Jeffery ED, Bandyopadhyay S, Jordan BT, Lehe M, Watts EF, Fenix A, Wilhelm M, Sheynkman GM. IS-PRM-based peptide targeting informed by long-read sequencing for alternative proteome detection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.01.587549. [PMID: 38617311 PMCID: PMC11014528 DOI: 10.1101/2024.04.01.587549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of pre-defined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (LR RNAseq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNAseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This LR RNA seq-informed Tomahto targeted approach, called LRP-IS-PRM, is a new modality for generating protein-level evidence of alternative isoforms - a critical first step in designing functional studies and eventually clinical assays.
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Affiliation(s)
- Jennifer A. Korchak
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Erin D. Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Saikat Bandyopadhyay
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ben T. Jordan
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - Micah Lehe
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Emily F. Watts
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Aidan Fenix
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich (TUM), D-85354 Freising, Germany
| | - Gloria M. Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA, USA
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31
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Njoku K, Pierce A, Chiasserini D, Geary B, Campbell AE, Kelsall J, Reed R, Geifman N, Whetton AD, Crosbie EJ. Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery. EBioMedicine 2024; 102:105064. [PMID: 38513301 PMCID: PMC10960138 DOI: 10.1016/j.ebiom.2024.105064] [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: 12/13/2022] [Revised: 02/16/2024] [Accepted: 03/04/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. METHODS Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. FINDINGS A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. INTERPRETATION Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. FUNDING Cancer Research UK, Blood Cancer UK, National Institute for Health Research.
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Affiliation(s)
- Kelechi Njoku
- Division of Cancer Sciences, University of Manchester, School of Medical Sciences, Faculty of Biology, Medicine and Health, 5th Floor Research, St Mary's Hospital, Road, Manchester, M13 9WL, UK; Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; Department of Clinical Oncology, Christie NHS Foundation Trust, Manchester, UK.
| | - Andrew Pierce
- North Wales Medical School, Bangor University, Bangor, Gwynedd, LL57 2DG, UK
| | - Davide Chiasserini
- Department of Medicine and Surgery, Section of Physiology and Biochemistry, University of Perugia, 06132, Perugia, Italy
| | - Bethany Geary
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dow Street, Dundee, DD1 5EH, UK
| | - Amy E Campbell
- Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Janet Kelsall
- Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Rachel Reed
- Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Nophar Geifman
- School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, GU2 7XH, UK
| | - Anthony D Whetton
- Veterinary Health Innovation Engine, School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, GU2 7XH, UK
| | - Emma J Crosbie
- Division of Cancer Sciences, University of Manchester, School of Medical Sciences, Faculty of Biology, Medicine and Health, 5th Floor Research, St Mary's Hospital, Road, Manchester, M13 9WL, UK.
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32
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Li Y, Liu X, Wang Y, Liu Z, Ye M, Wang H. [Deciphering cellular processes responding to lethality of 17 β-estradiol by quantitative phosphoproteomics]. Se Pu 2024; 42:333-344. [PMID: 38566422 PMCID: PMC10988567 DOI: 10.3724/sp.j.1123.2023.04025] [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: 04/25/2023] [Indexed: 04/04/2024] Open
Abstract
17β-Estradiol (E2), an important endocrine hormone in the mammalian body, participates in the regulation of the physiological functions of the reproductive system, mammary glands, bone, and cardiovascular system, among others. Paradoxically, despite the physiological actions of endogenous E2 (0.2-1.0 nmol/L), numerous clinical and experimental studies have demonstrated that high-dose E2 treatment can cause tumor regression and exert pro-apoptotic actions in multiple cell types; however, the underlying mechanism remains undescribed. In particular, little information of the cellular processes responding to the lethality of E2 is available. In the present study, we attempted to characterize the cellular processes responding to high-dose (μmol/L) E2 treatment using quantitative phosphoproteomics to obtain a better understanding of the regulatory mechanism of E2-induced cell death. First, the cell phenotype induced by high-dose E2 was determined by performing Cell Counting Kit-8 assay (CCK8), cell cytotoxicity analysis by trypan blue staining, and microscopic imaging on HeLa cells treated with 1-10 μmol/L E2 or dimethyl sulfoxide (DMSO) for 1-3 d. E2 inhibited cell proliferation and induced cell death in a dose- and time-dependent manner. Compared with the DMSO-treated HeLa cells, the cells treated with 5 μmol/L E2 for 2 d demonstrated >74% growth inhibition and approximately 50% cell death. Thus, these cells were used for quantitative phosphoproteomic analysis. Next, a solid-phase extraction (SPE)-based immobilized titanium ion affinity chromatography (Ti4+-IMAC) phosphopeptide-enrichment method coupled with data-independent acquisition (DIA)-based quantitative proteomics was employed for the in-depth screening of high-dose E2-regulated phosphorylation sites to investigate the intracellular processes responding to high-dose E2 treatment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified over 10000 phosphorylation sites regulated by E2 and DMSO in HeLa cells. In comparison with the DMSO-treated cells, the cells treated with 5 μmol/L E2 showed 537 upregulated phosphorylation sites and 387 downregulated phosphorylation sites, with a threshold of p<0.01 and |log2(fold change)|≥1. A total of 924 phosphorylation sites on 599 proteins were significantly regulated by high-dose E2, and these sites were subjected to enrichment analysis. In addition, 453 differently regulated phosphorylation sites on 325 proteins were identified only in the E2- or DMSO-treated cell samples. These phosphorylation sites may be phosphorylated or dephosphorylated in response to high-dose E2 stimulation and were subjected to parallel enrichment analyses. Taken together, 1218 phosphorylation sites on 741 proteins were significantly regulated by high-dose E2 treatment. The functional phosphoproteins in these two groups were then analyzed using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) to determine the biological processes in which they participate and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Consistent with the cell-phenotype data, cell cycle-related proteins were highly enriched in the two groups of E2-regulated phosphoproteins (p<0.05), indicating that high-dose E2 treatment can regulate cell proliferation. In addition, E2-regulated phosphoproteins were highly enriched in the cellular processes of ribosome biogenesis, nucleocytoplasmic transport, and messenger ribonucleic acid (mRNA) processing/splicing (p<0.05), indicating that the activation of these processes may contribute to high-dose E2-induced cell death. These results further confirm that high-dose E2 treatment inhibits protein translation and induces cell death. Furthermore, the significant upregulation of multiple phosphorylation sites associated with epidermal growth factor receptor (EGFR) and mitogen-activated protein kinases (MAPKs) MAPK1, MAPK4, and MAPK14 by high-dose E2 indicates that the EGFR and MAPK signaling pathways are likely involved in the regulation of E2-induced cell death. These phosphorylation sites likely play vital roles in E2-induced cell death in HeLa cells. Overall, our phosphoproteomic data could be a valuable resource for uncovering the regulatory mechanisms of E2 in the micromolar range.
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Affiliation(s)
- Yanan Li
- 1. School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- 2. State Key Laboratory of Environmental Chemistry and Eco-toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Xiaoyan Liu
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Yan Wang
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Zhen Liu
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Mingliang Ye
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Hailin Wang
- 1. School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- 2. State Key Laboratory of Environmental Chemistry and Eco-toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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Skawinski CLS, Shah PS. I'm Walking into Spiderwebs: Making Sense of Protein-Protein Interaction Data. J Proteome Res 2024. [PMID: 38556766 DOI: 10.1021/acs.jproteome.3c00892] [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: 04/02/2024]
Abstract
Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.
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Affiliation(s)
- Chase L S Skawinski
- Department of Chemical Engineering, University of California, Davis 95616, California, United States
| | - Priya S Shah
- Department of Chemical Engineering, University of California, Davis 95616, California, United States
- Department of Microbiology and Molecular Genetics, University of California, Davis 95616, California, United States
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Feás X, Alonso-Sampedro M, Bravo SB, Vidal C. Peeking into the Stingers: A Comprehensive SWATH-MS Study of the European Hornet Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae) Venom Sac Extracts. Int J Mol Sci 2024; 25:3798. [PMID: 38612607 PMCID: PMC11011553 DOI: 10.3390/ijms25073798] [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: 03/02/2024] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024] Open
Abstract
This study aimed to investigate the venom sac extracts (VSEs) of the European hornet (EH) Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae), focusing on the differences between stinging females, gynes (G), and workers (W), at the protein level. Using a quantitative "Sequential Window Acquisition of all Theoretical Fragment Ion Mass Spectra" (SWATH-MS) analysis, we identified and quantified a total of 240 proteins. Notably, within the group, 45.8% (n = 110) showed significant differential expression between VSE-G and VSE-W. In this set, 57.3% (n = 63) were upregulated and 42.7% (n = 47) downregulated in the G. Additionally, the two-hundred quantified proteins from the class Insecta belong to sixteen different species, six of them to the Hymenoptera/Apidae lineage, comprising seven proteins with known potential allergenicity. Thus, phospholipase A1 (Vesp v 1), phospholipase A1 verutoxin 2b (VT-2b), hyaluronidase A (Vesp v 2A), hyaluronidase B (Vesp v 2B), and venom allergen 5 (Vesp v 5) were significantly downregulated in the G, and vitellogenin (Vesp v 6) was upregulated. Overall, 46% of the VSE proteins showed differential expression, with a majority being upregulated in G. Data are available via ProteomeXchange with identifier PXD047955. These findings shed light on the proteomic differences in VSE between EH castes, potentially contributing to our understanding of their behavior and offering insights for allergy research.
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Affiliation(s)
- Xesús Feás
- Academy of Veterinary Sciences of Galicia, 15707 Santiago de Compostela, Spain;
- Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Hospital Clínico, 15706 Santiago de Compostela, Spain; (M.A.-S.); (S.B.B.)
| | - Manuela Alonso-Sampedro
- Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Hospital Clínico, 15706 Santiago de Compostela, Spain; (M.A.-S.); (S.B.B.)
- Research Methods Group (RESMET), Health Research Institute of Santiago de Compostela (IDIS), University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS-ISCIII/RD21/0016/0022), University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
| | - Susana Belén Bravo
- Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Hospital Clínico, 15706 Santiago de Compostela, Spain; (M.A.-S.); (S.B.B.)
- Proteomic Unit, Health Research Institute of Santiago de Compostela (IDIS), University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
| | - Carmen Vidal
- Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Hospital Clínico, 15706 Santiago de Compostela, Spain; (M.A.-S.); (S.B.B.)
- Research Methods Group (RESMET), Health Research Institute of Santiago de Compostela (IDIS), University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS-ISCIII/RD21/0016/0022), University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Allergy Department, University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Department of Psychiatry, Radiology, Public Health, Nursing and Medicine, Faculty of Medicine, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, Spain
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Carvalho SB, Profit L, Krishnan S, Gomes RA, Alexandre BM, Clavier S, Hoffman M, Brower K, Gomes-Alves P. SWATH-MS as a strategy for CHO host cell protein identification and quantification supporting the characterization of mAb purification platforms. J Biotechnol 2024; 384:1-11. [PMID: 38340900 DOI: 10.1016/j.jbiotec.2024.02.001] [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: 10/18/2023] [Revised: 01/17/2024] [Accepted: 02/05/2024] [Indexed: 02/12/2024]
Abstract
Host cell proteins (HCPs) are process-related impurities expressed by the host cells during biotherapeutics' manufacturing, such as monoclonal antibodies (mAbs). Some challenging HCPs evade clearance during the downstream processing and can be co-purified with the molecule of interest, which may impact product stability, efficacy, and safety. Therefore, HCP content is a critical quality attribute to monitor and quantify across the bioprocess. Here we explored a mass spectrometry (MS)-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, as an orthogonal method to traditional ELISA. The SWATH workflow was applied for high-throughput individual HCP identification and quantification, supporting characterization of a mAb purification platform. The design space of HCP clearance of two polishing resins was evaluated through a design of experiment study. Absolute quantification of high-risk HCPs was achieved (reaching 1.8 and 4.2 ppm limits of quantification, for HCP A and B respectively) using HCP-specific synthetic heavy labeled peptide calibration curves. Profiling of other HCPs was also possible using an average calibration curve (using labeled peptides from different HCPs). The SWATH approach is a powerful tool for HCP assessment during bioprocess development enabling simultaneous monitoring and quantification of different individual HCPs and improving process understanding of their clearance.
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Affiliation(s)
- Sofia B Carvalho
- iBET, Instituto de Biologia Experimental e Tecnológica, Apartado 12, Oeiras 2780-901, Portugal; ITQB-NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Av. Da República, Oeiras 2780-157, Portugal
| | - Ludivine Profit
- Mammalian Platform, Global CMC Development, Sanofi R&D, Vitry-sur-Seine, France
| | - Sushmitha Krishnan
- Mammalian Platform, Global CMC Development, Sanofi R&D, Framingham, MA, USA
| | - Ricardo A Gomes
- iBET, Instituto de Biologia Experimental e Tecnológica, Apartado 12, Oeiras 2780-901, Portugal; ITQB-NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Av. Da República, Oeiras 2780-157, Portugal
| | - Bruno M Alexandre
- iBET, Instituto de Biologia Experimental e Tecnológica, Apartado 12, Oeiras 2780-901, Portugal; ITQB-NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Av. Da República, Oeiras 2780-157, Portugal
| | - Severine Clavier
- BioAnalytics, Global CMC Development, Sanofi R&D, Vitry-sur-Seine, France
| | - Michael Hoffman
- Mammalian Platform, Global CMC Development, Sanofi R&D, Framingham, MA, USA
| | - Kevin Brower
- Mammalian Platform, Global CMC Development, Sanofi R&D, Framingham, MA, USA.
| | - Patrícia Gomes-Alves
- iBET, Instituto de Biologia Experimental e Tecnológica, Apartado 12, Oeiras 2780-901, Portugal; ITQB-NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Av. Da República, Oeiras 2780-157, Portugal.
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36
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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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37
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Suo Y, Du D, Chen C, Zhu H, Wang X, Song N, Lu D, Yang Y, Li J, Wang J, Luo Z, Zhou B, Luo C, Zhou H. Uncovering PROTAC Sensitivity and Efficacy by Multidimensional Proteome Profiling: A Case for STAT3. J Med Chem 2024. [PMID: 38466231 DOI: 10.1021/acs.jmedchem.3c02371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Proteolysis-targeting chimera (PROTAC) is a powerful technology that can effectively trigger the degradation of target proteins. The intricate interplay among various factors leads to a heterogeneous drug response, bringing about significant challenges in comprehending drug mechanisms. Our study applied data-independent acquisition-based mass spectrometry to multidimensional proteome profiling of PROTAC (DIA-MPP) to uncover the efficacy and sensitivity of the PROTAC compound. We profiled the signal transducer and activator of transcription 3 (STAT3) PROTAC degrader in six leukemia and lymphoma cell lines under multiple conditions, demonstrating the pharmacodynamic properties and downstream biological responses. Through comparison between sensitive and insensitive cell lines, we revealed that STAT1 can be regarded as a biomarker for STAT3 PROTAC degrader, which was validated in cells, patient-derived organoids, and mouse models. These results set an example for a comprehensive description of the multidimensional PROTAC pharmacodynamic response and PROTAC drug sensitivity biomarker exploration.
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Affiliation(s)
- Yuying Suo
- University of Chinese Academy of Sciences, NO.19A Yuquan Road, Beijing 100049, P. R. China
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China
| | - Daohai Du
- Drug Discovery and Design Center, the Center for Chemical Biology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Chao Chen
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
- Shandong Laboratory of Yantai Drug Discovery, Bohai Rim Advanced Research Institute for Drug Discovery, Yantai, Shandong 264117, China
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Hongwen Zhu
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China
| | - Xiongjun Wang
- Precise Genome Engineering Center, School of Life Sciences, Guangzhou University, Guangzhou 510006, China
| | - Nixue Song
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China
| | - Dayun Lu
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China
| | - Yaxi Yang
- University of Chinese Academy of Sciences, NO.19A Yuquan Road, Beijing 100049, P. R. China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- Shandong Laboratory of Yantai Drug Discovery, Bohai Rim Advanced Research Institute for Drug Discovery, Yantai, Shandong 264117, China
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Jiacheng Li
- Drug Discovery and Design Center, the Center for Chemical Biology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Jun Wang
- Drug Discovery and Design Center, the Center for Chemical Biology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Zhongyuan Luo
- Drug Discovery and Design Center, the Center for Chemical Biology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Bing Zhou
- University of Chinese Academy of Sciences, NO.19A Yuquan Road, Beijing 100049, P. R. China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- Shandong Laboratory of Yantai Drug Discovery, Bohai Rim Advanced Research Institute for Drug Discovery, Yantai, Shandong 264117, China
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Cheng Luo
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528437, China
- Drug Discovery and Design Center, the Center for Chemical Biology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Hu Zhou
- University of Chinese Academy of Sciences, NO.19A Yuquan Road, Beijing 100049, P. R. China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China
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38
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Hsiao Y, Zhang H, Li GX, Deng Y, Yu F, Kahrood HV, Steele JR, Schittenhelm RB, Nesvizhskii AI. Analysis and visualization of quantitative proteomics data using FragPipe-Analyst. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.05.583643. [PMID: 38496650 PMCID: PMC10942459 DOI: 10.1101/2024.03.05.583643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.
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Affiliation(s)
- Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Haijian Zhang
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yamei Deng
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hossein Valipour Kahrood
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
- Monash Genomics & Bioinformatics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Joel R. Steele
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ralf B. Schittenhelm
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Alexey I. Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
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39
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Bhushan V, Nita-Lazar A. Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology. J Proteome Res 2024. [PMID: 38451675 DOI: 10.1021/acs.jproteome.3c00839] [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: 03/08/2024]
Abstract
The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.
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Affiliation(s)
- Vanya Bhushan
- Functional Cellular Networks Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Aleksandra Nita-Lazar
- Functional Cellular Networks Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
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40
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Li L, Lu X, Dai P, Ma H. DIA-Based Quantitative Proteomics in the Flower Buds of Two Malus sieversii (Ledeb.) M. Roem Subtypes at Different Overwintering Stages. Int J Mol Sci 2024; 25:2964. [PMID: 38474210 DOI: 10.3390/ijms25052964] [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: 01/29/2024] [Revised: 02/29/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
Malus sieversii is considered the ancestor of the modern cultivated apple, with a high value for apple tolerance breeding. Despite studies on the temperature adaptability of M. sieversii carried out at a physiological response and the genome level, information on the proteome changes of M. sieversii during dormancy is limited, especially about the M. sieversii subtypes. In this study, a DIA-based approach was employed to screen and identify differential proteins involved in three overwintering periods of flower buds in two M. sieversii subtypes (Malus sieversii f. luteolus, GL; Malus sieversii f. aromaticus, HC) with different overwintering adaptabilities. The proteomic analysis revealed that the number of the down-regulated differential expression proteins (DEPs) was obviously higher than that of the up-regulated DEPs in the HC vs. GL groups, especially at the dormancy stage and dormancy-release stage. Through functional classification of those DEPs, the majority of the DEPs in the HC vs. GL groups were associated with protein processing in the endoplasmic reticulum, oxidative phosphorylation, starch and sucrose metabolism and ribosomes. Through WGCNA analysis, tricarboxylic acid cycle and pyruvate metabolism were highly correlated with the overwintering stages; oxidative phosphorylation and starch and sucrose metabolism were highly correlated with the Malus sieversii subtypes. This result suggests that the down-regulation of DEPs, which are predominantly enriched in these pathways, could potentially contribute to the lower cold tolerance observed in HC during overwintering stage.
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Affiliation(s)
- Lijie Li
- College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China
| | - Xiaochen Lu
- College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China
| | - Ping Dai
- College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China
| | - Huaiyu Ma
- College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China
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41
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Clouthier KL, Taylor AC, Xuhuai J, Liu Y, Parker S, Van Eyk J, Reddy S. A Noninvasive Circulating Signature of Combined Right Ventricular Pressure and Volume Overload in Tetralogy of Fallot/Pulmonary Atresia/Major Aortopulmonary Collateral Arteries. World J Pediatr Congenit Heart Surg 2024; 15:162-173. [PMID: 38128927 DOI: 10.1177/21501351231213626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Background: Despite surgical advances, children with tetralogy of Fallot/pulmonary atresia/major aortopulmonary collaterals (TOF/PA/MAPCAs) are subject to chronic right ventricular (RV) pressure and volume overload. Current diagnostic tools do not identify adverse myocardial remodeling and cannot predict progression to RV failure. We sought to identify a noninvasive, circulating signature of the systemic response to right heart stress to follow disease progression. Methods: Longitudinal data were collected from patients with TOF/PA/MAPCAs (N = 5) at the time of (1) early RV pressure overload and (2) late RV pressure and volume overload. Plasma protein and microRNA expression were evaluated using high-throughput data-independent mass spectroscopy and Agilent miR Microarray, respectively. Results: At the time of early RV pressure overload, median patient age was 0.34 years (0.02-9.37), with systemic RV pressures, moderate-severe hypertrophy, and preserved systolic function. Late RV pressure and volume overload occurred at a median age of 4.08 years (1.51-10.83), with moderate RV hypertrophy and dilation, and low normal RV function; 277 proteins were significantly dysregulated (log2FC ≥0.6/≤-0.6, FDR≤0.05), predicting downregulation in lipid transport (apolipoproteins), fibrinolytic system, and extracellular matrix structural proteins (talin 1, profilin 1); and upregulation in the respiratory burst. Increasing RV size and decreasing RV function correlated with decreasing structural protein expression. Similarly, miR expression predicted downregulation of extracellular matrix-receptor interactions and upregulation in collagen synthesis. Conclusion: To our knowledge, we show for the first time a noninvasive protein and miR signature reflecting the systemic response to adverse RV myocardial remodeling in TOF/PA/MAPCAs which could be used to follow disease progression.
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Affiliation(s)
- Katie L Clouthier
- Department of Pediatrics (Cardiology), Stanford University, Palo Alto, CA, USA
| | - Anne C Taylor
- Department of Pediatrics (Cardiology), Stanford University, Palo Alto, CA, USA
| | - Ji Xuhuai
- Human Immune Monitoring Center and Functional Genomics Facility, Stanford University, Palo Alto, CA, USA
| | - Yuhan Liu
- Department of Medicine (Quantitative Science Unit), Stanford University, Palo Alto, CA, USA
| | - Sarah Parker
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer Van Eyk
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sushma Reddy
- Department of Pediatrics (Cardiology), Stanford University, Palo Alto, CA, USA
- Cardiovascular Institute, Stanford University, Los Angeles, CA, USA
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42
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Bhimani K, Peresadina A, Vozniuk D, Kertész-Farkas A. Exact p-value calculation for XCorr scoring of high-resolution MS/MS data. Proteomics 2024; 24:e2300145. [PMID: 37726251 DOI: 10.1002/pmic.202300145] [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: 03/18/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/21/2023]
Abstract
Exact p-value (XPV)-based methods for dot product-like score functions-such as the XCorr score implemented in Tide, SEQUEST, Comet or shared peak count-based scoring in MSGF+ and ASPV-provide a fairly good calibration for peptide-spectrum-match (PSM) scoring in database searching-based MS/MS spectrum data identification. Unfortunately, standard XPV methods, in practice, cannot handle high-resolution fragmentation data produced by state-of-the-art mass spectrometers because having smaller bins increases the number of fragment matches that are assigned to incorrect bins and scored improperly. In this article, we present an extension of the XPV method, called the high-resolution exact p-value (HR-XPV) method, which can be used to calibrate PSM scores of high-resolution MS/MS spectra obtained with dot product-like scoring such as the XCorr. The HR-XPV carries remainder masses throughout the fragmentation, allowing them to greatly increase the number of fragments that are properly assigned to the correct bin and, thus, taking advantage of high-resolution data. Using four mass spectrometry data sets, our experimental results demonstrate that HR-XPV produces well-calibrated scores, which in turn results in more trusted spectrum annotations at any false discovery rate level.
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Affiliation(s)
- Kishankumar Bhimani
- Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow, Russian Federation
| | - Arina Peresadina
- Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow, Russian Federation
| | - Dmitrii Vozniuk
- Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow, Russian Federation
| | - Attila Kertész-Farkas
- Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow, Russian Federation
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43
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Hu E, Yang T, Cai L, Ouyang J, Wang F, Li Z, Wang Y, Xing X, Liu X. Proteomic Analysis Identifies GSN as a Noninvasive Circulating Serum Biomarker for Predicting Early Recurrence of Hepatocellular Carcinoma. J Proteome Res 2024; 23:1062-1074. [PMID: 38373391 DOI: 10.1021/acs.jproteome.3c00813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Hepatocellular carcinoma (HCC) is susceptible to early recurrence, but it lacks effective predictive biomarkers. In this study, we retrospectively selected 179 individuals as a discovery cohort (126 HCC patients and 53 liver cirrhosis (LC) patients) for screening candidate serum biomarkers of early recurrence based on data independent acquisition-mass spectrometry strategy. And then, the candidate biomarkers were validated in an additional independent cohort with 192 individuals (142 HCC patients and 50 LC patients) using parallel reaction monitoring targeted quantitative techniques (PXD047852). Eventually, we validated that gelsolin (GSN) concentrations were significantly lower in HCC than in LC (p < 0.0001), patients with low GSN concentrations had a poor prognosis (p < 0.0001), and GSN concentrations were significantly lower in early recurrence HCC than in late recurrence HCC (p < 0.0001). These trends were also observed in alpha-fetoprotein (AFP)-negative HCC patients. The area under the curve of machine-learning-based predictive model (GSN and microvascular invasion) for predicting early recurrence risk reached 0.803 (95% confidence interval (CI): 0.786-0.820) and maintained the same efficacy in AFP-negative patients. In conclusion, GSN is a novel serum biomarker for early recurrence of HCC. The model could provide timely warning to HCC patients at high risk of recurrence.
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Affiliation(s)
- En Hu
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Tao Yang
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Linsheng Cai
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Jiahe Ouyang
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Fei Wang
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Zongman Li
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Yingchao Wang
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Xiaohua Xing
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - Xiaolong Liu
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
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44
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White MEH, Sinn LR, Jones DM, de Folter J, Aulakh SK, Wang Z, Flynn HR, Krüger L, Tober-Lau P, Demichev V, Kurth F, Mülleder M, Blanchard V, Messner CB, Ralser M. Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics. Nat Biomed Eng 2024; 8:233-247. [PMID: 37474612 DOI: 10.1038/s41551-023-01067-5] [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: 07/19/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.
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Affiliation(s)
- Matthew E H White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ludwig R Sinn
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - D Marc Jones
- Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
| | - Joost de Folter
- Software Engineering and Artificial Intelligence Technology Platform, The Francis Crick Institute, London, UK
| | - Simran Kaur Aulakh
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ziyue Wang
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Helen R Flynn
- Mass Spectrometry Proteomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Lynn Krüger
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Pinkus Tober-Lau
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vadim Demichev
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Florian Kurth
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High-throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Véronique Blanchard
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Christoph B Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Precision Proteomic Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland.
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
- Max Planck Institute for Molecular Genetics, Berlin, Germany.
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45
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Tan TCJ, Spanos C, Tollervey D. Improved detection and consistency of RNA-interacting proteomes using DIA SILAC. Nucleic Acids Res 2024; 52:e21. [PMID: 38197237 PMCID: PMC10899761 DOI: 10.1093/nar/gkad1249] [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: 09/15/2023] [Revised: 12/14/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024] Open
Abstract
The RNA-interacting proteome is commonly characterized by UV-crosslinking followed by RNA purification, with protein recovery quantified using SILAC labeling followed by data-dependent acquisition (DDA) of proteomic data. However, the low efficiency of UV-crosslinking, combined with limited sensitivity of the DDA approach often restricts detection to relatively abundant proteins, necessitating multiple mass spec injections of fractionated peptides for each biological sample. Here we report an application of data-independent acquisition (DIA) with SILAC in a total RNA-associated protein purification (TRAPP) UV-crosslinking experiment. This gave 15% greater protein detection and lower inter-replicate variation relative to the same biological materials analyzed using DDA, while allowing single-shot analysis of the sample. As proof of concept, we determined the effects of arsenite treatment on the RNA-bound proteome of HEK293T cells. The DIA dataset yielded similar GO term enrichment for RNA-binding proteins involved in cellular stress responses to the DDA dataset while detecting extra proteins unseen by DDA. Overall, the DIA SILAC approach improved detection of proteins over conventional DDA SILAC for generating RNA-interactome datasets, at a lower cost due to reduced machine time. Analyses are described for TRAPP data, but the approach is suitable for proteomic analyses following essentially any RNA-binding protein enrichment technique.
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Affiliation(s)
- Thomas C J Tan
- Wellcome Centre for Cell Biology and Institute of Cell Biology, School of Biological Sciences, University of Edinburgh. Edinburgh EH9 3BF, Scotland, UK
| | - Christos Spanos
- Wellcome Centre for Cell Biology and Institute of Cell Biology, School of Biological Sciences, University of Edinburgh. Edinburgh EH9 3BF, Scotland, UK
| | - David Tollervey
- Wellcome Centre for Cell Biology and Institute of Cell Biology, School of Biological Sciences, University of Edinburgh. Edinburgh EH9 3BF, Scotland, UK
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46
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Hadjineophytou C, Loh E, Koomey M, Scott NE. Combining FAIMS based glycoproteomics and DIA proteomics reveals widespread proteome alterations in response to glycosylation occupancy changes in Neisseria gonorrhoeae. Proteomics 2024:e2300496. [PMID: 38361220 DOI: 10.1002/pmic.202300496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 02/01/2024] [Accepted: 02/06/2024] [Indexed: 02/17/2024]
Abstract
Protein glycosylation is increasingly recognized as a common protein modification across bacterial species. Within the Neisseria genus O-linked protein glycosylation is conserved yet closely related Neisseria species express O-oligosaccharyltransferases (PglOs) with distinct targeting activities. Within this work, we explore the targeting capacity of different PglOs using Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) fractionation and Data-Independent Acquisition (DIA) to allow the characterization of the impact of changes in glycosylation on the proteome of Neisseria gonorrhoeae. We demonstrate FAIMS expands the known glycoproteome of wild type N. gonorrhoeae MS11 and enables differences in glycosylation to be assessed across strains expressing different pglO allelic chimeras with unique substrate targeting activities. Combining glycoproteomic insights with DIA proteomics, we demonstrate that alterations within pglO alleles have widespread impacts on the proteome of N. gonorrhoeae. Examination of peptides known to be targeted by glycosylation using DIA analysis supports alterations in glycosylation occupancy occurs independently of changes in protein levels and that the occupancy of glycosylation is generally low on most glycoproteins. This work thus expands our understanding of the N. gonorrhoeae glycoproteome and the roles that pglO allelic variation may play in governing genus-level protein glycosylation.
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Affiliation(s)
- Chris Hadjineophytou
- Department of Biosciences, Section for Genetics and Evolutionary Biology, University of Oslo, Oslo, Norway
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
- Clinical Microbiology, BioClinicum, Karolinska University Hospital, Solna, Sweden
| | - Edmund Loh
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
- Clinical Microbiology, BioClinicum, Karolinska University Hospital, Solna, Sweden
| | - Michael Koomey
- Department of Biosciences, Section for Genetics and Evolutionary Biology, University of Oslo, Oslo, Norway
- Department of Biosciences, Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
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47
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Tomioka R, Tomioka A, Ogata K, Chan HJ, Chen LY, Guzman UH, Xuan Y, Olsen JV, Chen YJ, Ishihama Y. Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:386-396. [PMID: 38287222 DOI: 10.1021/jasms.3c00448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
To improve the coverage in bottom-up proteomics, S-aminoethylation of cysteine residues (AE-Cys) was carried out with 2-bromoethylamine, followed by cleavage with lysyl endopeptidase (Lys-C) or Lys-C/trypsin. A model study with bovine serum albumin showed that the C-terminal side of AE-Cys was successfully cleaved by Lys-C. The frequency of side reactions at amino acids other than Cys was less than that in the case of carbamidomethylation of Cys with iodoacetamide. Proteomic analysis of A549 cell extracts in the data-dependent acquisition mode after AE-Cys modification afforded a greater number of identified protein groups, especially membrane proteins. In addition, label-free quantification of proteins in mouse nonsmall cell lung cancer (NSCLC) tissue in the data-independent acquisition mode after AE-Cys modification showed improved NSCLC pathway coverage and greater reproducibility. Furthermore, the AE-Cys method could identify an epidermal growth factor receptor peptide containing the T790 M mutation site, a well-established lung-cancer-related mutation site that has evaded conventional bottom-up methods. Finally, AE-Cys was found to fully mimic Lys in terms of collision-induced dissociation fragmentation, ion mobility separation, and cleavage by Lys-C/trypsin, except for sulfoxide formation during sample preparation.
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Affiliation(s)
- Ryota Tomioka
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Biopharmaceutical Research Division, Shionogi & Co., Ltd., Toyonaka 561-0825, Osaka, Japan
| | - Ayana Tomioka
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Kosuke Ogata
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Hsin-Ju Chan
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Li-Yu Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Ulises H Guzman
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
| | - Yue Xuan
- Thermo Fisher Scientific GmbH, Bremen 28199, Germany
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Laboratory of Clinical and Analytical Chemistry, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki 567-0085, Osaka, Japan
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48
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Pade LR, Lombard-Banek C, Li J, Nemes P. Dilute to Enrich for Deeper Proteomics: A Yolk-Depleted Carrier for Limited Populations of Embryonic (Frog) Cells. J Proteome Res 2024; 23:692-703. [PMID: 37994825 PMCID: PMC10872351 DOI: 10.1021/acs.jproteome.3c00541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Abundant proteins challenge deep mass spectrometry (MS) analysis of the proteome. Yolk, the source of food in many developing vertebrate embryos, complicates chemical separation and interferes with detection. We report here a strategy that enhances bottom-up proteomics in yolk-laden specimens by diluting the interferences using a yolk-depleted carrier (YODEC) proteome via isobaric multiplexing quantification. This method was tested on embryos of the South African Clawed Frog (Xenopus laevis), where a >90% yolk proteome content challenges deep proteomics. As a proof of concept, we isolated neural and epidermal fated cell clones from the embryo by dissection or fluorescence-activated cell sorting. Compared with the standard multiplexing carrier approach, YODEC more than doubled the detectable X. laevis proteome, identifying 5,218 proteins from D11 cell clones dissected from the embryo. Ca. ∼80% of the proteins were quantified without dropouts in any of the analytical channels. YODEC with high-pH fractionation quantified 3,133 proteins from ∼8,000 V11 cells that were sorted from ca. 2 embryos (1.5 μg total, or 150 ng yolk-free proteome), marking a 15-fold improvement in proteome coverage vs the standard proteomics approach. About 60% of these proteins were only quantifiable by YODEC, including molecular adaptors, transporters, translation, and transcription factors. While this study was tailored to limited populations of Xenopus cells, we anticipate the approach of "dilute to enrich" using a depleted carrier proteome to be adaptable to other biological models in which abundant proteins challenge deep MS proteomics.
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Affiliation(s)
- Leena R. Pade
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Camille Lombard-Banek
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Jie Li
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
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49
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Major G, Simcock J, Kumar A, Kleffmann T, Woodfield TBF, Lim KS. Comprehensive Matrisome Profiling of Human Adipose Tissue for Soft Tissue Reconstruction. Adv Biol (Weinh) 2024; 8:e2300448. [PMID: 37953659 DOI: 10.1002/adbi.202300448] [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: 08/25/2023] [Revised: 10/14/2023] [Indexed: 11/14/2023]
Abstract
For effective translation of research from tissue engineering and regenerative medicine domains, the cell-instructive extracellular matrix (ECM) of specific tissues must be accurately realized. As adipose tissue is gaining traction as a biomaterial for soft tissue reconstruction, with highly variable clinical outcomes obtained, a quantitative investigation of the adipose tissue matrisome is overdue. In this study, the human adipose tissue matrisome is profiled using quantitative sequential windowed acquisition of all theoretical fragment ion spectra - mass spectrometry (SWATH-MS) proteomics across a cohort of 13 fat-grafting patients, to provide characterization of ECM proteins within the tissue, and to understand human population variation. There are considerable differences in the expression of matrisome proteins across the patient cohort, with age and lipoaspirate collection technique contributing to the greatest variation across the core matrisome. A high abundance of basement membrane proteins (collagen IV and heparan sulfate proteoglycan) is detected, as well as fibrillar collagens I and II, reflecting the hierarchical structure of the tissue. This study provides a comprehensive proteomic evaluation of the adipose tissue matrisome and contributes to an enhanced understanding of the influence of the matrisome in adipose-related pathologies by providing a healthy reference cohort and details an experimental pipeline that can be further exploited for future biomaterial development.
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Affiliation(s)
- Gretel Major
- Department of Orthopaedic Surgery and Musculoskeletal Medicine, Centre for Bioengineering & Nanomedicine, University of Otago, Christchurch, 8011, New Zealand
| | - Jeremy Simcock
- Department of Surgery, University of Otago, Christchurch, 8011, New Zealand
| | - Abhishek Kumar
- Centre for Protein Research, Research Infrastructure Centre, University of Otago, Dunedin, 9054, New Zealand
| | - Torsten Kleffmann
- Centre for Protein Research, Research Infrastructure Centre, University of Otago, Dunedin, 9054, New Zealand
| | - Tim B F Woodfield
- Department of Orthopaedic Surgery and Musculoskeletal Medicine, Centre for Bioengineering & Nanomedicine, University of Otago, Christchurch, 8011, New Zealand
| | - Khoon S Lim
- Department of Orthopaedic Surgery and Musculoskeletal Medicine, Centre for Bioengineering & Nanomedicine, University of Otago, Christchurch, 8011, New Zealand
- Light-Activated Biomaterials Group, School of Medical Science, University of Sydney, Sydney, NSW, 2006, Australia
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50
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Shajari E, Gagné D, Malick M, Roy P, Noël JF, Gagnon H, Brunet MA, Delisle M, Boisvert FM, Beaulieu JF. Application of SWATH Mass Spectrometry and Machine Learning in the Diagnosis of Inflammatory Bowel Disease Based on the Stool Proteome. Biomedicines 2024; 12:333. [PMID: 38397935 PMCID: PMC10886680 DOI: 10.3390/biomedicines12020333] [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: 12/07/2023] [Revised: 01/17/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
Inflammatory bowel disease (IBD) flare-ups exhibit symptoms that are similar to other diseases and conditions, making diagnosis and treatment complicated. Currently, the gold standard for diagnosing and monitoring IBD is colonoscopy and biopsy, which are invasive and uncomfortable procedures, and the fecal calprotectin test, which is not sufficiently accurate. Therefore, it is necessary to develop an alternative method. In this study, our aim was to provide proof of concept for the application of Sequential Window Acquisition of All Theoretical Mass Spectra-Mass spectrometry (SWATH-MS) and machine learning to develop a non-invasive and accurate predictive model using the stool proteome to distinguish between active IBD patients and symptomatic non-IBD patients. Proteome profiles of 123 samples were obtained and data processing procedures were optimized to select an appropriate pipeline. The differentially abundant analysis identified 48 proteins. Utilizing correlation-based feature selection (Cfs), 7 proteins were selected for proceeding steps. To identify the most appropriate predictive machine learning model, five of the most popular methods, including support vector machines (SVMs), random forests, logistic regression, naive Bayes, and k-nearest neighbors (KNN), were assessed. The generated model was validated by implementing the algorithm on 45 prospective unseen datasets; the results showed a sensitivity of 96% and a specificity of 76%, indicating its performance. In conclusion, this study illustrates the effectiveness of utilizing the stool proteome obtained through SWATH-MS in accurately diagnosing active IBD via a machine learning model.
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Affiliation(s)
- Elmira Shajari
- Laboratory of Intestinal Physiopathology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - David Gagné
- Laboratory of Intestinal Physiopathology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Allumiqs, 975 Rue Léon-Trépanier, Sherbrooke, QC J1G 5J6, Canada
| | - Mandy Malick
- Laboratory of Intestinal Physiopathology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Patricia Roy
- Laboratory of Intestinal Physiopathology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | | | - Hugo Gagnon
- Allumiqs, 975 Rue Léon-Trépanier, Sherbrooke, QC J1G 5J6, Canada
| | - Marie A. Brunet
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Pediatrics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Maxime Delisle
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - François-Michel Boisvert
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Jean-François Beaulieu
- Laboratory of Intestinal Physiopathology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
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