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Chen ZZ, Dufresne J, Bowden P, Miao M, Marshall JG. Extraction of naturally occurring peptides versus the tryptic digestion of proteins from fetal versus adult bovine serum for LC-ESI-MS/MS. Anal Biochem 2024; 689:115497. [PMID: 38461948 DOI: 10.1016/j.ab.2024.115497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 02/23/2024] [Accepted: 02/25/2024] [Indexed: 03/12/2024]
Abstract
The naturally occurring peptides and digested proteins of fetal versus adult bovine serum were compared by LC-ESI-MS/MS after correction against noise from blank injections and random MS/MS spectra as statistical controls. Serum peptides were extracted by differential precipitation with mixtures of acetonitrile and water. Serum proteins were separated by partition chromatography over quaternary amine resin followed by tryptic digestion. The rigorous X!TANDEM goodness of fit algorithm that has a low error rate as demonstrated by low FDR q-values (q ≤ 0.01) showed qualitative and quantitative agreement with the SEQUEST cross correlation algorithm on 12,052 protein gene symbols. Tryptic digestion provided a quantitative identification of the serum proteins where observation frequency reflected known high abundance. In contrast, the naturally occurring peptides reflected the cleavage of common serum proteins such as C4A, C3, FGB, HPX, A2M but also proteins in lower concentration such as F13A1, IK, collagens and protocadherins. Proteins associated with cellular growth and development such as actins (ACT), ribosomal proteins like Ribosomal protein S6 (RPS6), synthetic enzymes and extracellular matrix factors were enriched in fetal calf serum. In contrast to the large literature from cord blood, IgG light chains were absent from fetal serum as observed by LC-ESI-MS/MS and confirmed by ELISA.
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Affiliation(s)
- Zhuo Zhen Chen
- Research Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Toronto Metropolitan University, Canada.
| | - Jaimie Dufresne
- Research Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Toronto Metropolitan University, Canada.
| | - Peter Bowden
- Research Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Toronto Metropolitan University, Canada.
| | - Ming Miao
- Research Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Toronto Metropolitan University, Canada.
| | - John G Marshall
- Research Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Toronto Metropolitan University, Canada.
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Urbiola-Salvador V, Lima de Souza S, Macur K, Czaplewska P, Chen Z. Plasma Proteomics Elucidated a Protein Signature in COVID-19 Patients with Comorbidities and Early-Diagnosis Biomarkers. Biomedicines 2024; 12:840. [PMID: 38672194 PMCID: PMC11048573 DOI: 10.3390/biomedicines12040840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 04/03/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024] Open
Abstract
Despite great scientific efforts, deep understanding of coronavirus-19 disease (COVID-19) immunopathology and clinical biomarkers remains a challenge. Pre-existing comorbidities increase the mortality rate and aggravate the exacerbated immune response against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, which can result in more severe symptoms as well as long-COVID and post-COVID complications. In this study, we applied proteomics analysis of plasma samples from 28 patients with SARS-CoV-2, with and without pre-existing comorbidities, as well as their corresponding controls to determine the systemic protein changes caused by the SARS-CoV-2 infection. As a result, the protein signature shared amongst COVID-19 patients with comorbidities was revealed to be characterized by alterations in the coagulation and complement pathways, acute-phase response proteins, tissue damage and remodeling, as well as cholesterol metabolism. These altered proteins may play a relevant role in COVID-19 pathophysiology. Moreover, several novel potential biomarkers for early diagnosis of the SARS-CoV-2 infection were detected, such as increased levels of keratin K22E, extracellular matrix protein-1 (ECM1), and acute-phase response protein α-2-antiplasmin (A2AP). Importantly, elevated A2AP may contribute to persistent clotting complications associated with the long-COVID syndrome in patients with comorbidities. This study provides new insights into COVID-19 pathogenesis and proposes novel potential biomarkers for early diagnosis that could be facilitated for clinical application by further validation studies.
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Affiliation(s)
- Víctor Urbiola-Salvador
- Intercollegiate Faculty of Biotechnology of University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, 80-307 Gdańsk, Poland;
| | - Suiane Lima de Souza
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland;
| | - Katarzyna Macur
- Laboratory of Mass Spectrometry-Core Facility Laboratories, Intercollegiate Faculty of Biotechnology University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, 80-309 Gdańsk, Poland; (K.M.); (P.C.)
| | - Paulina Czaplewska
- Laboratory of Mass Spectrometry-Core Facility Laboratories, Intercollegiate Faculty of Biotechnology University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, 80-309 Gdańsk, Poland; (K.M.); (P.C.)
| | - Zhi Chen
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland;
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3
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Fredolini C, Dodig-Crnković T, Bendes A, Dahl L, Dale M, Albrecht V, Mattsson C, Thomas CE, Torinsson Naluai Å, Gisslen M, Beck O, Roxhed N, Schwenk JM. Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections. Commun Med (Lond) 2024; 4:55. [PMID: 38565620 PMCID: PMC10987641 DOI: 10.1038/s43856-024-00480-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 03/07/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored. METHODS Our study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information. RESULTS Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors. CONCLUSIONS Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.
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Affiliation(s)
- Claudia Fredolini
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
- Affinity Proteomics Unit, SciLifeLab Infrastructure, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Tea Dodig-Crnković
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Annika Bendes
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Leo Dahl
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Matilda Dale
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
- Affinity Proteomics Unit, SciLifeLab Infrastructure, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Vincent Albrecht
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Cecilia Mattsson
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
- Affinity Proteomics Unit, SciLifeLab Infrastructure, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Cecilia E Thomas
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden
| | - Åsa Torinsson Naluai
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, 405 30, Gothenburg, Sweden
| | - Magnus Gisslen
- Department of Infectious Diseases, The Sahlgrenska Academy at University of Gothenburg, 405 30, Gothenburg, Sweden
- Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
- Public Health Agency of Sweden, 171 65, Solna, Sweden
| | - Olof Beck
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Niclas Roxhed
- MedTechLabs, BioClinicum, Karolinska University Hospital, 171 64, Solna, Sweden.
- Department of Micro and Nanosystems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology Stockholm, 100 44, Stockholm, Sweden.
| | - Jochen M Schwenk
- Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 171 65, Solna, Sweden.
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Anandakrishnan N, Yi Z, Sun Z, Liu T, Haydak J, Eddy S, Jayaraman P, DeFronzo S, Saha A, Sun Q, Yang D, Mendoza A, Mosoyan G, Wen HH, Schaub JA, Fu J, Kehrer T, Menon R, Otto EA, Godfrey B, Suarez-Farinas M, Leffters S, Twumasi A, Meliambro K, Charney AW, García-Sastre A, Campbell KN, Gusella GL, He JC, Miorin L, Nadkarni GN, Wisnivesky J, Li H, Kretzler M, Coca SG, Chan L, Zhang W, Azeloglu EU. Integrated multiomics implicates dysregulation of ECM and cell adhesion pathways as drivers of severe COVID-associated kidney injury. medRxiv 2024:2024.03.18.24304401. [PMID: 38562892 PMCID: PMC10984064 DOI: 10.1101/2024.03.18.24304401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
COVID-19 has been a significant public health concern for the last four years; however, little is known about the mechanisms that lead to severe COVID-associated kidney injury. In this multicenter study, we combined quantitative deep urinary proteomics and machine learning to predict severe acute outcomes in hospitalized COVID-19 patients. Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrated predictive power for both discovery and validation set with 87% and 79% accuracy, respectively. These predictive urinary biomarkers were recapitulated in non-COVID acute kidney injury revealing overlapping injury mechanisms. We further combined orthogonal multiomics datasets to understand the mechanisms that drive severe COVID-associated kidney injury. Functional overlap and network analysis of urinary proteomics, plasma proteomics and urine sediment single-cell RNA sequencing showed that extracellular matrix and autophagy-associated pathways were uniquely impacted in severe COVID-19. Differentially abundant proteins associated with these pathways exhibited high expression in cells in the juxtamedullary nephron, endothelial cells, and podocytes, indicating that these kidney cell types could be potential targets. Further, single-cell transcriptomic analysis of kidney organoids infected with SARS-CoV-2 revealed dysregulation of extracellular matrix organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters showed significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Collectively, these data suggest that extracellular matrix degradation and adhesion-associated mechanisms could be a main driver of COVID-associated kidney injury and severe outcomes.
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5
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Zou Y, Pronker MF, Damen JMA, Heck AJR, Reiding KR. Genotype-dependent N-glycosylation and newly exposed O-glycosylation affect plasmin-induced cleavage of histidine-rich glycoprotein (HRG). J Biol Chem 2024; 300:105683. [PMID: 38272220 PMCID: PMC10882129 DOI: 10.1016/j.jbc.2024.105683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 01/02/2024] [Accepted: 01/11/2024] [Indexed: 01/27/2024] Open
Abstract
Histidine-rich glycoprotein (HRG) is an abundant plasma protein harboring at least three N-glycosylation sites. HRG integrates many biological processes, such as coagulation, antiangiogenic activity, and pathogen clearance. Importantly, HRG is known to exhibit five genetic variants with minor allele frequencies of more than 10%. Among them, Pro204Ser can induce a fourth N-glycosylation site (Asn202). Considerable efforts have been made to reveal the biological function of HRG, whereas data on HRG glycosylation are scarcer. To close this knowledge gap, we used C18-based LC-MS/MS to study the glycosylation characteristics of six HRG samples from different sources. We used endogenous HRG purified from human plasma and compared its glycosylation to that of the recombinant HRG produced in Chinese hamster ovary cells or human embryonic kidney 293 cells, targeting distinct genotypic isoforms. In endogenous plasma HRG, every N-glycosylation site was occupied predominantly with a sialylated diantennary complex-type glycan. In contrast, in the recombinant HRGs, all glycans showed different antennarities, sialylation, and core fucosylation, as well as the presence of oligomannose glycans, LacdiNAcs, and antennary fucosylation. Furthermore, we observed two previously unreported O-glycosylation sites in HRG on residues Thr273 and Thr274. These sites together showed more than 90% glycan occupancy in all HRG samples studied. To investigate the potential relevance of HRG glycosylation, we assessed the plasmin-induced cleavage of HRG under various conditions. These analyses revealed that the sialylation of the N- and O-glycans as well as the genotype-dependent N-glycosylation significantly influenced the kinetics and specificity of plasmin-induced cleavage of HRG.
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Affiliation(s)
- Yang Zou
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Matti F Pronker
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - J Mirjam A Damen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Karli R Reiding
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands.
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6
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Pushalkar S, Wu S, Maity S, Pressler M, Rendleman J, Vitrinel B, Jeffery L, Abdelhadi R, Chen M, Ross T, Carlock M, Choi H, Vogel C. Complex changes in serum protein levels in COVID-19 convalescents. Sci Rep 2024; 14:4479. [PMID: 38396092 PMCID: PMC10891133 DOI: 10.1038/s41598-024-54534-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.
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Affiliation(s)
- Smruti Pushalkar
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
| | - Shaohuan Wu
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Shuvadeep Maity
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Birla Institute of Technology and Science-Pilani (BITS Pilani), Hyderabad, India
| | - Matthew Pressler
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Justin Rendleman
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Burcu Vitrinel
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Lauren Jeffery
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Ryah Abdelhadi
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Mechi Chen
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Ted Ross
- Cleveland Clinic Florida Research & Innovation Center, Port St. Lucie, FL, USA
| | - Michael Carlock
- Cleveland Clinic Florida Research & Innovation Center, Port St. Lucie, FL, USA
| | - Hyungwon Choi
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christine Vogel
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
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Mahin A, Soman SP, Modi PK, Raju R, Keshava Prasad TS, Abhinand CS. Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases. J Neurovirol 2024; 30:57-70. [PMID: 38167982 DOI: 10.1007/s13365-023-01191-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 11/22/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024]
Abstract
In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.
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Affiliation(s)
- Althaf Mahin
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Sreelakshmi Pathappillil Soman
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Prashant Kumar Modi
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Rajesh Raju
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to Be University), Mangalore, Karnataka, 575018, India.
| | | | - Chandran S Abhinand
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India.
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8
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Rajoria S, Kavuru SR, Pyda HS, Bihani S, Borishetty D, Biswas D, Prajapati J, Paladi H, Srivastava S. CoVProt: Toward a Mass Spectrometry Data Portal for COVID-19 Proteomics Research and Development. OMICS 2024; 28:24-31. [PMID: 38193774 DOI: 10.1089/omi.2023.0274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc globally. Beyond the pandemic, the long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in multiple organ systems are yet to be deciphered. This calls for continued systems science research. Moreover, the host response to SARS-CoV-2 varies person-to-person and gives rise to different degrees of morbidity and mortality. Mass spectrometry (MS) has been a proven asset in studies of the SARS-CoV-2 from an omics systems science lens. To strengthen the proteomics research dedicated to COVID-19, we introduce here a web-based portal, CoVProt. The portal is work in progress and aims for a comprehensive curation of MS-based proteomics data of COVID-19 clinical samples for deep proteomic investigations, data visualization, and easy data accessibility for life sciences innovations and planetary health research community. Currently, CoVProt contains information on 2725 different proteins and 37,125 different peptides from six data sets covering a total of 202 clinical samples. Moreover, all pertinent data sets extracted from the literature have been reanalyzed using a common analysis pipeline developed by combining multiple tools. Going forward, we anticipate that the CoVProt portal will also provide access to the clinical parameters of the patients. The CoVProt (v1.0) portal addresses an existing significant gap to study COVID-19 host proteomics, which, to the best of our knowledge, is the first effort in this direction. We believe that CoVProt is poised to make contributions as a community resource for proteomic applications and aims to broadly support clinical studies to facilitate the discovery of COVID-19 biomarkers and therapeutics with translational potential.
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Affiliation(s)
- Sakshi Rajoria
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Sai Rohith Kavuru
- Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA Deemed to be University, Thanjavur, India
| | - Hari Sundar Pyda
- Department of Chemical Engineering, Institute of Chemical Technology, Mumbai- Indian Oil Odisha Campus, Bhubaneswar, India
| | - Surbhi Bihani
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Dhanush Borishetty
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Deeptrup Biswas
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Jeel Prajapati
- Department of Biotechnology and Bioengineering, Institute of Advanced Research, Gandhinagar, India
| | - Harshith Paladi
- Department of Computer Science, School of Computing, SASTRA Deemed to be University, Thanjavur, India
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
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9
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Bondt A, Hoek M, Dingess K, Tamara S, de Graaf B, Peng W, den Boer MA, Damen M, Zwart C, Barendregt A, van Rijswijck DMH, Schulte D, Grobben M, Tejjani K, van Rijswijk J, Völlmy F, Snijder J, Fortini F, Papi A, Volta CA, Campo G, Contoli M, van Gils MJ, Spadaro S, Rizzo P, Heck AJR. Into the Dark Serum Proteome: Personalized Features of IgG1 and IgA1 Repertoires in Severe COVID-19 Patients. Mol Cell Proteomics 2024; 23:100690. [PMID: 38065436 PMCID: PMC10784693 DOI: 10.1016/j.mcpro.2023.100690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 12/30/2023] Open
Abstract
Serum proteomics has matured and is now able to monitor hundreds of proteins quantitatively in large cohorts of patients. However, the fine characteristics of some of the most dominant proteins in serum, the immunoglobulins, are in these studies often ignored, due to their vast, and highly personalized, diversity in sequences. Here, we focus exclusively on these personalized features in the serum proteome and distinctively chose to study individual samples from a low diversity population: elderly donors infected by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). By using mass spectrometry-based methods, immunoglobulin IgG1 and IgA1 clonal repertoires were monitored quantitatively and longitudinally in more than 50 individual serum samples obtained from 17 Corona virus disease 2019 patients admitted to intensive care units. These clonal profiles were used to examine how each patient reacted to a severe SARS-CoV-2 infection. All 17 donors revealed unique polyclonal repertoires and substantial changes over time, with several new clones appearing following the infection, in a few cases leading to a few, very high, abundant clones dominating their repertoire. Several of these clones were de novo sequenced through combinations of top-down, middle-down, and bottom-up proteomics approaches. This revealed sequence features in line with sequences deposited in the SARS-CoV-specific antibody database. In other patients, the serological Ig profiles revealed the treatment with tocilizumab, that subsequently dominated their serological IgG1 repertoire. Tocilizumab clearance could be monitored, and a half-life of approximately 6 days was established. Overall, our longitudinal monitoring of IgG1 and IgA1 repertoires of individual donors reveals that antibody responses are highly personalized traits of each patient, affected by the disease and the chosen clinical treatment. The impact of these observations argues for a more personalized and longitudinal approach in patients' diagnostics, both in serum proteomics as well as in monitoring immune responses.
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Affiliation(s)
- Albert Bondt
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Max Hoek
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Kelly Dingess
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Sem Tamara
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Bastiaan de Graaf
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Weiwei Peng
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Maurits A den Boer
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Mirjam Damen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Ceri Zwart
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Arjan Barendregt
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Danique M H van Rijswijck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Douwe Schulte
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Marloes Grobben
- Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Khadija Tejjani
- Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jacqueline van Rijswijk
- Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Franziska Völlmy
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Joost Snijder
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | | | - Alberto Papi
- Respiratory Section, Department of Translational Medicine, University of Ferrara, Ferrara, Italy; Respiratory Disease Unit, Azienda Ospedaliero-Universitaria di Ferrara, Ferrara, Italy
| | - Carlo Alberto Volta
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy; Intensive Care Unit, Azienda Ospedaliero-Universitaria di Ferrara, Ferrara, Italy
| | - Gianluca Campo
- Cardiology Unit, Azienda Ospedaliero-Universitaria di Ferrara, University of Ferrara, Ferrara, Italy
| | - Marco Contoli
- Respiratory Section, Department of Translational Medicine, University of Ferrara, Ferrara, Italy; Respiratory Disease Unit, Azienda Ospedaliero-Universitaria di Ferrara, Ferrara, Italy
| | - Marit J van Gils
- Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Savino Spadaro
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy; Intensive Care Unit, Azienda Ospedaliero-Universitaria di Ferrara, Ferrara, Italy
| | - Paola Rizzo
- Maria Cecilia Hospital, GVM Care & Research, Cotignola, Italy; Department of Translational Medicine and Laboratory for Technology of Advanced Therapies (LTTA), University of Ferrara, Ferrara, Italy
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands.
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10
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Oskam N, den Boer MA, Lukassen MV, Ooijevaar-de Heer P, Veth TS, van Mierlo G, Lai SH, Derksen NIL, Yin V, Streutker M, Franc V, Šiborová M, Damen MJA, Kos D, Barendregt A, Bondt A, van Goudoever JB, de Haas CJC, Aerts PC, Muts RM, Rooijakkers SHM, Vidarsson G, Rispens T, Heck AJR. CD5L is a canonical component of circulatory IgM. Proc Natl Acad Sci U S A 2023; 120:e2311265120. [PMID: 38055740 PMCID: PMC10723121 DOI: 10.1073/pnas.2311265120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/07/2023] [Indexed: 12/08/2023] Open
Abstract
Immunoglobulin M (IgM) is an evolutionary conserved key component of humoral immunity, and the first antibody isotype to emerge during an immune response. IgM is a large (1 MDa), multimeric protein, for which both hexameric and pentameric structures have been described, the latter additionally containing a joining (J) chain. Using a combination of single-particle mass spectrometry and mass photometry, proteomics, and immunochemical assays, we here demonstrate that circulatory (serum) IgM exclusively exists as a complex of J-chain-containing pentamers covalently bound to the small (36 kDa) protein CD5 antigen-like (CD5L, also called apoptosis inhibitor of macrophage). In sharp contrast, secretory IgM in saliva and milk is principally devoid of CD5L. Unlike IgM itself, CD5L is not produced by B cells, implying that it associates with IgM in the extracellular space. We demonstrate that CD5L integration has functional implications, i.e., it diminishes IgM binding to two of its receptors, the FcαµR and the polymeric Immunoglobulin receptor. On the other hand, binding to FcµR as well as complement activation via C1q seem unaffected by CD5L integration. Taken together, we redefine the composition of circulatory IgM as a J-chain containing pentamer, always in complex with CD5L.
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Affiliation(s)
- Nienke Oskam
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Maurits A. den Boer
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Marie V. Lukassen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Pleuni Ooijevaar-de Heer
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Tim S. Veth
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Gerard van Mierlo
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Szu-Hsueh Lai
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Ninotska I. L. Derksen
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Victor Yin
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Marij Streutker
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Vojtech Franc
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Marta Šiborová
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Mirjam J. A. Damen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Dorien Kos
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Arjan Barendregt
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Albert Bondt
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
| | - Johannes B. van Goudoever
- Amsterdam University Medical Center, Vrije Universiteit, University of Amsterdam, Emma Children's Hospital, Amsterdam1105 AZ, the Netherlands
| | - Carla J. C. de Haas
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht3584 CX, the Netherlands
| | - Piet C. Aerts
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht3584 CX, the Netherlands
| | - Remy M. Muts
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht3584 CX, the Netherlands
| | - Suzan H. M. Rooijakkers
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht3584 CX, the Netherlands
| | - Gestur Vidarsson
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
- Sanquin Research and Landsteiner Laboratory, Department of Experimental Immunohematology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Theo Rispens
- Sanquin Research and Landsteiner Laboratory, Department of Immunopathology, Amsterdam University Medical Center, Amsterdam1066 CX, the Netherlands
| | - Albert J. R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht3584 CH, the Netherlands
- Netherlands Proteomics Center, Utrecht3584 CH, the Netherlands
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11
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Mundt F, Albrechtsen NJW, Mann SP, Treit P, Ghodgaonkar-Steger M, O’Flaherty M, Raijmakers R, Vizcaíno JA, Heck AJ, Mann M. Foresight in clinical proteomics: current status, ethical considerations, and future perspectives. Open Res Eur 2023; 3:59. [PMID: 37645494 PMCID: PMC10446044 DOI: 10.12688/openreseurope.15810.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/26/2023] [Indexed: 08/31/2023]
Abstract
With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.
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Affiliation(s)
- Filip Mundt
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicolai J. Wewer Albrechtsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, University Hospital, Bispebjerg Hospital, Bispebjerg, Denmark
| | | | - Peter Treit
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
| | | | - Martina O’Flaherty
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Reinout Raijmakers
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Albert J.R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
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12
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Basak I, Harfoot R, Palmer JE, Kumar A, Quiñones-Mateu ME, Schweitzer L, Hughes SM. Neuroproteomic Analysis after SARS-CoV-2 Infection Reveals Overrepresented Neurodegeneration Pathways and Disrupted Metabolic Pathways. Biomolecules 2023; 13:1597. [PMID: 38002279 PMCID: PMC10669333 DOI: 10.3390/biom13111597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/19/2023] [Accepted: 10/26/2023] [Indexed: 11/26/2023] Open
Abstract
Besides respiratory illness, SARS-CoV-2, the causative agent of COVID-19, leads to neurological symptoms. The molecular mechanisms leading to neuropathology after SARS-CoV-2 infection are sparsely explored. SARS-CoV-2 enters human cells via different receptors, including ACE-2, TMPRSS2, and TMEM106B. In this study, we used a human-induced pluripotent stem cell-derived neuronal model, which expresses ACE-2, TMPRSS2, TMEM106B, and other possible SARS-CoV-2 receptors, to evaluate its susceptibility to SARS-CoV-2 infection. The neurons were exposed to SARS-CoV-2, followed by RT-qPCR, immunocytochemistry, and proteomic analyses of the infected neurons. Our findings showed that SARS-CoV-2 infects neurons at a lower rate than other human cells; however, the virus could not replicate or produce infectious virions in this neuronal model. Despite the aborted SARS-CoV-2 replication, the infected neuronal nuclei showed irregular morphology compared to other human cells. Since cytokine storm is a significant effect of SARS-CoV-2 infection in COVID-19 patients, in addition to the direct neuronal infection, the neurons were treated with pre-conditioned media from SARS-CoV-2-infected lung cells, and the neuroproteomic changes were investigated. The limited SARS-CoV-2 infection in the neurons and the neurons treated with the pre-conditioned media showed changes in the neuroproteomic profile, particularly affecting mitochondrial proteins and apoptotic and metabolic pathways, which may lead to the development of neurological complications. The findings from our study uncover a possible mechanism behind SARS-CoV-2-mediated neuropathology that might contribute to the lingering effects of the virus on the human brain.
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Affiliation(s)
- Indranil Basak
- Brain Health Research Centre, Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand
| | - Rhodri Harfoot
- Department of Microbiology and Immunology, University of Otago, Dunedin 9016, New Zealand (M.E.Q.-M.)
| | - Jennifer E. Palmer
- Brain Health Research Centre, Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand
| | - Abhishek Kumar
- Centre for Protein Research, University of Otago, Dunedin 9016, New Zealand
| | - Miguel E. Quiñones-Mateu
- Department of Microbiology and Immunology, University of Otago, Dunedin 9016, New Zealand (M.E.Q.-M.)
| | - Lucia Schweitzer
- Brain Health Research Centre, Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand
| | - Stephanie M. Hughes
- Brain Health Research Centre, Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand
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13
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Babačić H, Christ W, Araújo JE, Mermelekas G, Sharma N, Tynell J, García M, Varnaite R, Asgeirsson H, Glans H, Lehtiö J, Gredmark-Russ S, Klingström J, Pernemalm M. Comprehensive proteomics and meta-analysis of COVID-19 host response. Nat Commun 2023; 14:5921. [PMID: 37739942 PMCID: PMC10516886 DOI: 10.1038/s41467-023-41159-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 08/24/2023] [Indexed: 09/24/2023] Open
Abstract
COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.
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Affiliation(s)
- Haris Babačić
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden.
| | - Wanda Christ
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - José Eduardo Araújo
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Georgios Mermelekas
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Nidhi Sharma
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Janne Tynell
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Marina García
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Renata Varnaite
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Hilmir Asgeirsson
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
- Unit of Infectious Diseases, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Hedvig Glans
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Janne Lehtiö
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Sara Gredmark-Russ
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
- The Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå, Sweden
| | - Jonas Klingström
- Centre for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
- Division of Molecular Medicine and Virology (MMV), Department of Biomedical and Clinical Sciences (BKV), Linköping University, Linköping, Sweden
| | - Maria Pernemalm
- Science for Life Laboratory and Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden.
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14
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Ali H, Naseem A, Siddiqui ZI. SARS-CoV-2 Syncytium under the Radar: Molecular Insights of the Spike-Induced Syncytia and Potential Strategies to Limit SARS-CoV-2 Replication. J Clin Med 2023; 12:6079. [PMID: 37763019 PMCID: PMC10531702 DOI: 10.3390/jcm12186079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 09/14/2023] [Accepted: 09/17/2023] [Indexed: 09/29/2023] Open
Abstract
SARS-CoV-2 infection induces non-physiological syncytia when its spike fusogenic protein on the surface of the host cells interacts with the ACE2 receptor on adjacent cells. Spike-induced syncytia are beneficial for virus replication, transmission, and immune evasion, and contribute to the progression of COVID-19. In this review, we highlight the properties of viral fusion proteins, mainly the SARS-CoV-2 spike, and the involvement of the host factors in the fusion process. We also highlight the possible use of anti-fusogenic factors as an antiviral for the development of therapeutics against newly emerging SARS-CoV-2 variants and how the fusogenic property of the spike could be exploited for biomedical applications.
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Affiliation(s)
- Hashim Ali
- Department of Pathology, University of Cambridge, Addenbrookes Hospital, Cambridge CB2 0QQ, UK
| | - Asma Naseem
- Infection, Immunity and Inflammation Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, London WC1N 1DZ, UK
| | - Zaheenul Islam Siddiqui
- Diabetes and Obesity Research Center, NYU Grossman Long Island School of Medicine, New York, NY 11501, USA
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15
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Schweizer L, Schaller T, Zwiebel M, Karayel Ö, Müller‐Reif JB, Zeng W, Dintner S, Nordmann TM, Hirschbühl K, Märkl B, Claus R, Mann M. Quantitative multiorgan proteomics of fatal COVID-19 uncovers tissue-specific effects beyond inflammation. EMBO Mol Med 2023; 15:e17459. [PMID: 37519267 PMCID: PMC10493576 DOI: 10.15252/emmm.202317459] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 07/11/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023] Open
Abstract
SARS-CoV-2 may directly and indirectly damage lung tissue and other host organs, but there are few system-wide, untargeted studies of these effects on the human body. Here, we developed a parallelized mass spectrometry (MS) proteomics workflow enabling the rapid, quantitative analysis of hundreds of virus-infected FFPE tissues. The first layer of response to SARS-CoV-2 in all tissues was dominated by circulating inflammatory molecules. Beyond systemic inflammation, we differentiated between systemic and true tissue-specific effects to reflect distinct COVID-19-associated damage patterns. Proteomic changes in the lungs resembled those of diffuse alveolar damage (DAD) in non-COVID-19 patients. Extensive organ-specific changes were also evident in the kidneys, liver, and lymphatic and vascular systems. Secondary inflammatory effects in the brain were related to rearrangements in neurotransmitter receptors and myelin degradation. These MS-proteomics-derived results contribute substantially to our understanding of COVID-19 pathomechanisms and suggest strategies for organ-specific therapeutic interventions.
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Affiliation(s)
- Lisa Schweizer
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Tina Schaller
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Maximilian Zwiebel
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Özge Karayel
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Present address:
Department of Physiological ChemistryGenentechSouth San FranciscoUSA
| | | | - Wen‐Feng Zeng
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | | | - Thierry M Nordmann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Klaus Hirschbühl
- Hematology and Oncology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Bruno Märkl
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Rainer Claus
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
- Hematology and Oncology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Matthias Mann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
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16
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Hernández-Caravaca I, Moros-Nicolás C, González-Brusi L, Romero de Ávila MJ, De Paco Matallana C, Pelegrín P, Castaño-Molina MÁ, Díaz-Meca L, Sánchez-Romero J, Martínez-Alarcón L, Avilés M, Izquierdo-Rico MJ. Colostrum Features of Active and Recovered COVID-19 Patients Revealed Using Next-Generation Proteomics Technique, SWATH-MS. Children (Basel) 2023; 10:1423. [PMID: 37628421 PMCID: PMC10453012 DOI: 10.3390/children10081423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/15/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023]
Abstract
Colostrum performs nutritional, anti-inflammatory and anti-infective functions and promotes immune system formation and organ development. The new coronavirus, SARS-CoV-2, has generated concerns about viral transmission through human milk, with a lack of evidence about human milk's protective effects against the infection. This study aimed at analyzing presence of the virus and at identifying the protein expression profile of human colostrum in active and COVID-19-recovered patients. Colostrum samples were collected from women with COVID-19 (n = 3), women recently recovered from the infection (n = 4), and non-infected women (n = 5). The samples were analyzed by means of RT-qPCR to determine presence of the virus and using SWATH-MS for proteomic analysis. Proteomic results were then analyzed using bioinformatic methods. The viral tests were negative for SARS-CoV-2 in the colostrum from COVID-19 patients. The proteomic analysis identified 301 common proteins in all samples analyzed. Nineteen proteins were upregulated and 7 were downregulated in the COVID-19 group versus the control samples, whereas 18 were upregulated and 7 were downregulated when comparing the COVID-19 group to the recovered group. Eleven proteins were biomarkers of active COVID-19 infection. Ten were upregulated: ACTN1, CD36, FAM3B, GPRC5B, IGHA2, IGK, PLTP, RAC1, SDCBP and SERPINF1, and one was downregulated: PSAP. These proteins are mainly related to immunity, inflammatory response and protein transport. In conclusion, the results of this study suggest that colostrum is not a vehicle for mother-to-child SARS-CoV-2 transmission. Moreover, the colostrum's proteome of active and recuperated patients indicate that it could provide immune benefits to infants.
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Affiliation(s)
- Iván Hernández-Caravaca
- Department of Community Nursing, Preventive Medicine and Public Health and History of Science, Campus de Sant Vicent del Raspeig, University of Alicante, 03690 Alicante, Spain;
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
| | - Carla Moros-Nicolás
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain;
| | - Leopoldo González-Brusi
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain;
| | - Mª José Romero de Ávila
- Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain;
| | - Catalina De Paco Matallana
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Servicio de Obstetricia y Ginecología, Hospital Clínico Universitario Virgen de la Arrixaca, 30120 Murcia, Spain;
| | - Pablo Pelegrín
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Bioquímica y Biología Molecular “B” e Inmunología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain
| | - María Ángeles Castaño-Molina
- Servicio de Obstetricia y Ginecología, Hospital Clínico Universitario Virgen de la Arrixaca, 30120 Murcia, Spain;
- Departamento de Enfermería, Facultad de Enfermería, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain
| | - Lucía Díaz-Meca
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Servicio de Obstetricia y Ginecología, Hospital Clínico Universitario Virgen de la Arrixaca, 30120 Murcia, Spain;
| | - Javier Sánchez-Romero
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Servicio de Obstetricia y Ginecología, Hospital Clínico Universitario Virgen de la Arrixaca, 30120 Murcia, Spain;
| | - Laura Martínez-Alarcón
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Enfermería, Facultad de Enfermería, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain
- Unit, Department of Surgery, Virgen de la Arrixaca University Hospital, 30120 Murcia, Spain
| | - Manuel Avilés
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain;
| | - Mª José Izquierdo-Rico
- Instituto Murciano de Investigación Biosanitaria Pascual Parrilla (IMIB), Campus de Ciencias de la Salud, 30120 Murcia, Spain; (C.M.-N.); (L.G.-B.); (C.D.P.M.); (P.P.); (L.D.-M.); (L.M.-A.); (M.A.)
- Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Murcia, Campus Mare Nostrum (CMN), 30120 Murcia, Spain;
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Burnap SA, Ortega-Prieto AM, Jimenez-Guardeño JM, Ali H, Takov K, Fish M, Shankar-Hari M, Giacca M, Malim MH, Mayr M. Cross-Linking Mass Spectrometry Uncovers Interactions Between High-Density Lipoproteins and the SARS-CoV-2 Spike Glycoprotein. Mol Cell Proteomics 2023; 22:100600. [PMID: 37343697 PMCID: PMC10279469 DOI: 10.1016/j.mcpro.2023.100600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 06/06/2023] [Accepted: 06/07/2023] [Indexed: 06/23/2023] Open
Abstract
High-density lipoprotein (HDL) levels are reduced in patients with coronavirus disease 2019 (COVID-19), and the extent of this reduction is associated with poor clinical outcomes. While lipoproteins are known to play a key role during the life cycle of the hepatitis C virus, their influence on coronavirus (CoV) infections is poorly understood. In this study, we utilize cross-linking mass spectrometry (XL-MS) to determine circulating protein interactors of the severe acute respiratory syndrome (SARS)-CoV-2 spike glycoprotein. XL-MS of plasma isolated from patients with COVID-19 uncovered HDL protein interaction networks, dominated by acute-phase serum amyloid proteins, whereby serum amyloid A2 was shown to bind to apolipoprotein (Apo) D. XL-MS on isolated HDL confirmed ApoD to interact with SARS-CoV-2 spike but not SARS-CoV-1 spike. Other direct interactions of SARS-CoV-2 spike upon HDL included ApoA1 and ApoC3. The interaction between ApoD and spike was further validated in cells using immunoprecipitation-MS, which uncovered a novel interaction between both ApoD and spike with membrane-associated progesterone receptor component 1. Mechanistically, XL-MS coupled with data-driven structural modeling determined that ApoD may interact within the receptor-binding domain of the spike. However, ApoD overexpression in multiple cell-based assays had no effect upon viral replication or infectivity. Thus, SARS-CoV-2 spike can bind to apolipoproteins on HDL, but these interactions do not appear to alter infectivity.
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Affiliation(s)
- Sean A Burnap
- Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, Oxford, UK; The Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford, UK; King's College London British Heart Foundation Centre, School of Cardiovascular Medicine and Sciences, London, UK.
| | - Ana Maria Ortega-Prieto
- Department of Infectious Diseases, School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Jose M Jimenez-Guardeño
- Department of Infectious Diseases, School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Hashim Ali
- King's College London British Heart Foundation Centre, School of Cardiovascular Medicine and Sciences, London, UK; Division of Virology, Department of Pathology, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Kaloyan Takov
- King's College London British Heart Foundation Centre, School of Cardiovascular Medicine and Sciences, London, UK
| | - Matthew Fish
- Department of Infectious Diseases, School of Immunology and Microbial Sciences, King's College London, London, UK; Department of Intensive Care Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Manu Shankar-Hari
- Centre for Inflammation Research, Institute of Regeneration and Repair, University of Edinburgh, Edinburgh, UK; Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK
| | - Mauro Giacca
- King's College London British Heart Foundation Centre, School of Cardiovascular Medicine and Sciences, London, UK
| | - Michael H Malim
- Department of Infectious Diseases, School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Manuel Mayr
- King's College London British Heart Foundation Centre, School of Cardiovascular Medicine and Sciences, London, UK.
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18
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Zhang B, Han H, Zhao X, Li AN, Wang Y, Yuan W, Yang Z, Li MD. An HBV susceptibility variant of KNG1 modulates the therapeutic effects of interferons α and λ1 in HBV infection by promoting MAVS lysosomal degradation. EBioMedicine 2023; 94:104694. [PMID: 37442062 PMCID: PMC10435766 DOI: 10.1016/j.ebiom.2023.104694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Hepatitis B virus (HBV) infection is one of the main causes of hepatocellular carcinoma (HCC). The relationship between HBV infection and the host genome as well as their underlying mechanisms remain largely unknown. METHODS In this study, we performed a whole-genome exon sequencing analysis of 300 sib-pairs of Chinese HBV-infected families with the goal of identifying variants and genes involved in HBV infection. A site-direct mutant plasmid was used to investigate the function of SNP rs76438938 in KNG1. The functional and mechanical studies of KNG1 were conducted with in vitro liver cell lines and a hydrodynamic injection model in vivo. The impact of KNG1 on HBV infection therapy was determined in hepatocytes treated with IFN-α/λ1. FINDINGS Our whole-exon association study of 300 families with hepatitis B infection found that SNP rs76438938 in KNG1 significantly increased the risk for HBV infection, and the rs76438938-T allele was found to promote HBV replication by increasing the stability of KNG1 mRNA. By competitively binding HSP90A with MAVS, KNG1 can inhibit the expression of types I and III IFNs by promoting MAVS lysosomal degradation. Such suppression of IFN expression and promotion of HBV replication by Kng1 were further demonstrated with an animal model in vivo. Lastly, we showed that the rs76438938-C allele can improve the therapeutic effect of IFN-α and -λ1 in HBV infection. INTERPRETATION This study identified a SNP, rs76438938, in a newly discovered host gene, KNG1, for its involvement in HBV infection and treatment effect through modulating the cellular antiviral process. FUNDING This study was supported in part by the Independent Task of State Key Laboratory for Diagnosis and Treatment of Infectious Diseases of the First Affiliated Hospital of Zhejiang University, the China Precision Medicine Initiative (2016YFC0906300), and the Research Center for Air Pollution and Health of Zhejiang University.
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Affiliation(s)
- Bin Zhang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haijun Han
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Zhao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Andria N Li
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yan Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenji Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongli Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China.
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19
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Rajoria S, Halder A, Tarnekar I, Pal P, Bansal P, Srivastava S. Detection of Mutant Peptides of SARS-CoV-2 Variants by LC/MS in the DDA Approach Using an In-House Database. J Proteome Res 2023; 22:1816-1827. [PMID: 37093804 PMCID: PMC10152398 DOI: 10.1021/acs.jproteome.2c00819] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Indexed: 04/25/2023]
Abstract
Equipped with a dramatically high mutation rate, which happens to be a signature of RNA viruses, SARS-CoV-2 trampled across the globe infecting individuals of all ages and ethnicities. As the variants of concern (VOC) loomed large, definitive detection of SARS-CoV-2 strains became a matter of utmost importance in epidemiological and clinical research. Besides, unveiling the disease pathogenesis at the molecular level and deciphering the therapeutic targets became key priorities since the emergence of the pandemic. Mass spectrometry has been largely used in this regard. A critical part of mass spectrometric analyses is the proteome database required for the identification of peptides. Presently, the mutational information on proteins available on SARS-CoV-2 databases cannot be used to analyze data extracted from mass spectrometers. Hence, we developed the novel Mutant Peptide Database (MPD) for the mass spectrometry (MS)-based identification of mutated peptides, which contains information from 11 proteins of SARS-CoV-2 from a total of 21,549 SARS-CoV-2 variants across different regions of India. The database was validated using clinical samples, and its applicability was also demonstrated with the mutated peptides extracted from the literature. We believe that MPD will support broad-spectrum MS-based studies like viral detection, disease pathogenesis, and therapeutics with respect to SARS-CoV-2 and its variants.
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Affiliation(s)
- Sakshi Rajoria
- Department of Biosciences and Bioengineering,
Indian Institute of Technology Bombay, Mumbai 400076,
India
| | - Ankit Halder
- Department of Biosciences and Bioengineering,
Indian Institute of Technology Bombay, Mumbai 400076,
India
| | - Ishita Tarnekar
- Thadomal Shahani Engineering
College, P.G. Kher Marg T.P.S III, Bandra West, Mumbai 400050,
India
| | - Pracheta Pal
- Department of Life Sciences, Presidency
University, 86/1 College Street, Kolkata 700073, West Bengal,
India
| | - Prakhar Bansal
- Department of Electrical Engineering,
Indian Institute of Technology Bombay, Mumbai 400076,
India
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering,
Indian Institute of Technology Bombay, Mumbai 400076,
India
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20
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Völkel S, Tarawneh TS, Sacher L, Bhagwat AM, Karim I, Mack HID, Wiesmann T, Beutel B, Hoyer J, Keller C, Renz H, Burchert A, Neubauer A, Graumann J, Skevaki C, Mack EKM. Serum proteomics hint at an early T-cell response and modulation of SARS-CoV-2-related pathogenic pathways in COVID-19-ARDS treated with Ruxolitinib. Front Med (Lausanne) 2023; 10:1176427. [PMID: 37293294 PMCID: PMC10244732 DOI: 10.3389/fmed.2023.1176427] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/24/2023] [Indexed: 06/10/2023] Open
Abstract
Background Acute respiratory distress syndrome (ARDS) in corona virus disease 19 (COVID-19) is triggered by hyperinflammation, thus providing a rationale for immunosuppressive treatments. The Janus kinase inhibitor Ruxolitinib (Ruxo) has shown efficacy in severe and critical COVID-19. In this study, we hypothesized that Ruxo's mode of action in this condition is reflected by changes in the peripheral blood proteome. Methods This study included 11 COVID-19 patients, who were treated at our center's Intensive Care Unit (ICU). All patients received standard-of-care treatment and n = 8 patients with ARDS received Ruxo in addition. Blood samples were collected before (day 0) and on days 1, 6, and 10 of Ruxo treatment or, respectively, ICU admission. Serum proteomes were analyzed by mass spectrometry (MS) and cytometric bead array. Results Linear modeling of MS data yielded 27 significantly differentially regulated proteins on day 1, 69 on day 6 and 72 on day 10. Only five factors (IGLV10-54, PSMB1, PGLYRP1, APOA5, WARS1) were regulated both concordantly and significantly over time. Overrepresentation analysis revealed biological processes involving T-cells only on day 1, while a humoral immune response and complement activation were detected at day 6 and day 10. Pathway enrichment analysis identified the NRF2-pathway early under Ruxo treatment and Network map of SARS-CoV-2 signaling and Statin inhibition of cholesterol production at later time points. Conclusion Our results indicate that the mechanism of action of Ruxo in COVID-19-ARDS can be related to both known effects of this drug as a modulator of T-cells and the SARS-CoV-2-infection.
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Affiliation(s)
- Sara Völkel
- Institute of Laboratory Medicine, Philipps-University Marburg, Marburg, Germany
| | - Thomas S. Tarawneh
- Department of Hematology, Oncology and Immunology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Laura Sacher
- Institute of Laboratory Medicine, Philipps-University Marburg, Marburg, Germany
| | - Aditya M. Bhagwat
- Institute of Translational Proteomics, Philipps-University Marburg, Marburg, Germany
| | - Ihab Karim
- Department of Hematology, Oncology and Immunology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Hildegard I. D. Mack
- Institute for Biomedical Aging Research, Leopold-Franzens-Universität Innsbruck, Innsbruck, Austria
| | - Thomas Wiesmann
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, Diakonie-Klinikum Schwäbisch Hall, Schwäbisch Hall, Germany
| | - Björn Beutel
- Department of Pulmonary and Critical Care Medicine, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
- German Center for Lung Research (DZL), Member of the Universities of Gießen and Marburg Lung Center, Gießen, Germany
| | - Joachim Hoyer
- Department of Nephrology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Christian Keller
- Institute of Virology, Philipps-University Marburg, Marburg, Germany
| | - Harald Renz
- Institute of Laboratory Medicine, Philipps-University Marburg, Marburg, Germany
- German Center for Lung Research (DZL), Member of the Universities of Gießen and Marburg Lung Center, Gießen, Germany
| | - Andreas Burchert
- Department of Hematology, Oncology and Immunology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Andreas Neubauer
- Department of Hematology, Oncology and Immunology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Johannes Graumann
- Institute of Translational Proteomics, Philipps-University Marburg, Marburg, Germany
- Biomolecular Mass Spectrometry, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Chrysanthi Skevaki
- Institute of Laboratory Medicine, Philipps-University Marburg, Marburg, Germany
- German Center for Lung Research (DZL), Member of the Universities of Gießen and Marburg Lung Center, Gießen, Germany
| | - Elisabeth K. M. Mack
- Department of Hematology, Oncology and Immunology, University Hospital Gießen and Marburg, Philipps-University Marburg, Marburg, Germany
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21
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Bader JM, Albrecht V, Mann M. MS-based proteomics of body fluids: The end of the beginning. Mol Cell Proteomics 2023:100577. [PMID: 37209816 PMCID: PMC10388585 DOI: 10.1016/j.mcpro.2023.100577] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/07/2023] [Accepted: 05/11/2023] [Indexed: 05/22/2023] Open
Abstract
Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification and quantification making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In a previous review we described technological and conceptual limitations that had held back success (Geyer et al., 2017). We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. They are also required for machine learning or deep learning. Shorter gradients, new scan modes and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multi-protein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter into regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.
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Affiliation(s)
- Jakob M Bader
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Vincent Albrecht
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany; Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
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22
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Siegel PM, Barta BA, Orlean L, Steenbuck ID, Cosenza-Contreras M, Wengenmayer T, Trummer G, Wolf D, Westermann D, Schilling O, Diehl P. The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study. J Transl Med 2023; 21:319. [PMID: 37173738 PMCID: PMC10176307 DOI: 10.1186/s12967-023-04174-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 04/30/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is applied in patients with refractory hemodynamic failure. Exposure of blood components to high shear stress and the large extracorporeal surfaces in the ECMO circuit trigger a complex inflammatory response syndrome and coagulopathy which are believed to worsen the already poor prognosis of these patients. Mass spectrometry-based proteomics allow a detailed characterization of the serum proteome as it provides the identity and concentration of large numbers of individual proteins at the same time. In this study, we aimed to characterize the serum proteome of patients receiving VA-ECMO. METHODS Serum samples were collected on day 1 and day 3 after initiation of VA-ECMO. Samples underwent immunoaffinity based depletion for the 14 most abundant serum proteins, in-solution digestion and PreOmics clean-up. A spectral library was built with multiple measurements of a master-mix sample using variable mass windows. Individual samples were measured in data independent acquisition (DIA) mode. Raw files were analyzed by DIA-neural network. Unique proteins were log transformed and quantile normalized. Differential expression analysis was conducted with the LIMMA-R package. ROAST was applied to generate gene ontology enrichment analyses. RESULTS Fourteen VA-ECMO patients and six healthy controls were recruited. Seven patients survived. Three hundred and fifty-one unique proteins were identified. One hundred and thirty-seven proteins were differentially expressed between VA-ECMO patients and controls. One hundred and forty-five proteins were differentially expressed on day 3 compared to day 1. Many of the differentially expressed proteins were involved in coagulation and the inflammatory response. The serum proteomes of survivors and non-survivors on day 3 differed from each other according to partial least-squares discriminant analysis (PLS-DA) and 48 proteins were differentially expressed. Many of these proteins have also been ascribed to processes in coagulation and inflammation (e.g., Factor IX, Protein-C, Kallikrein, SERPINA10, SEMA4B, Complement C3, Complement Factor D and MASP-1). CONCLUSION The serum proteome of VA-ECMO patients displays major changes compared to controls and changes from day 1 until day 3. Many changes in the serum proteome are related to inflammation and coagulation. Survivors and non-survivors can be differentiated according to their serum proteomes using PLS-DA analysis on day 3. Our results build the basis for future studies using mass-spectrometry based serum proteomics as a tool to identify novel prognostic biomarkers. TRIAL REGISTRATION DRKS00011106.
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Affiliation(s)
- Patrick Malcolm Siegel
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Bálint András Barta
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Lukas Orlean
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ines Derya Steenbuck
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Miguel Cosenza-Contreras
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Tobias Wengenmayer
- Interdisciplinary Medical Intensive Care (IMIT), Medical Center, University of Freiburg, Freiburg, Germany
| | - Georg Trummer
- Department of Cardiovascular Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Dennis Wolf
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dirk Westermann
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Philipp Diehl
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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23
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Toomer KH, Gerber GF, Zhang Y, Daou L, Tushek M, Hooper JE, Francischetti IMB. SARS-CoV-2 infection results in upregulation of Plasminogen Activator Inhibitor-1 and Neuroserpin in the lungs, and an increase in fibrinolysis inhibitors associated with disease severity. EJHaem 2023; 4:324-338. [PMID: 37206290 PMCID: PMC10188457 DOI: 10.1002/jha2.654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/14/2023] [Accepted: 01/21/2023] [Indexed: 05/21/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection results in coagulation activation although it is usually not associated with consumption coagulopathy. D-dimers are also commonly elevated despite systemic hypofibrinolysis. To understand these unusual features of coronavirus disease 2019 (COVID-19) coagulopathy, 64 adult patients with SARS-CoV-2 infection (36 moderate and 28 severe) and 16 controls were studied. We evaluated the repertoire of plasma protease inhibitors (Serpins, Kunitz, Kazal, Cystatin-like) targeting the fibrinolytic system: Plasminogen Activator Inhibitor-1 (PAI-1), Tissue Plasminogen Activator/Plasminogen Activator Inhibitor-1 complex (t-PA/PAI-1), α-2-Antiplasmin, Plasmin-α2-Antiplasmin Complex, Thrombin-activatable Fibrinolysis Inhibitor (TAFI)/TAFIa, Protease Nexin-1 (PN-1), and Neuroserpin (the main t-PA inhibitor of the central nervous system). Inhibitors of the common (Antithrombin, Thrombin-antithrombin complex, Protein Z [PZ]/PZ inhibitor, Heparin Cofactor II, and α2-Macroglobulin), Protein C ([PC], Protein C inhibitor, and Protein S), contact (Kallistatin, Protease Nexin-2/Amyloid Beta Precursor Protein, and α-1-Antitrypsin), and complement (C1-Inhibitor) pathways, in addition to Factor XIII, Histidine-rich glycoprotein (HRG) and Vaspin were also investigated by enzyme-linked immunosorbent assay. The association of these markers with disease severity was evaluated by logistic regression. Pulmonary expression of PAI-1 and Neuroserpin in the lungs from eight post-mortem cases was assessed by immunohistochemistry. Results show that six patients (10%) developed thrombotic events, and mortality was 11%. There was no significant reduction in plasma anticoagulants, in keeping with a compensated state. However, an increase in fibrinolysis inhibitors (PAI-1, Neuroserpin, PN-1, PAP, and t-PA/PAI-1) was consistently observed, while HRG was reduced. Furthermore, these markers were associated with moderate and/or severe disease. Notably, immunostains demonstrated overexpression of PAI-1 in epithelial cells, macrophages, and endothelial cells of fatal COVID-19, while Neuroserpin was found in intraalveolar macrophages only. These results imply that the lungs in SARS-CoV-2 infection provide anti-fibrinolytic activity resulting in a shift toward a local and systemic hypofibrinolytic state predisposing to (immuno)thrombosis, often in a background of compensated disseminated intravascular coagulation.
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Affiliation(s)
- Kevin H. Toomer
- Department of PathologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Gloria F. Gerber
- Division of HematologyDepartment of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Yifan Zhang
- Department of BiostatisticsJohns Hopkins University Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Laetitia Daou
- Department of PathologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Michael Tushek
- Department of PathologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Jody E. Hooper
- Department of PathologyStanford University School of MedicinePalo AltoCaliforniaUSA
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24
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Woo J, Zhang Q. A Streamlined High-Throughput Plasma Proteomics Platform for Clinical Proteomics with Improved Proteome Coverage, Reproducibility, and Robustness. J Am Soc Mass Spectrom 2023; 34:754-762. [PMID: 36975161 PMCID: PMC10080683 DOI: 10.1021/jasms.3c00022] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 06/18/2023]
Abstract
Mass spectrometry-based clinical proteomics requires high throughput, reproducibility, robustness, and comprehensive coverage to serve the needs of clinical diagnosis, prognosis, and personalized medicine. Oftentimes these requirements are contradictory to each other. We report the development of a streamlined High-Throughput Plasma Proteomics (sHTPP) platform for untargeted profiling of the blood plasma proteome, which includes 96-well plates and simplified procedures for sample preparation, disposable trap column for peptide loading, robust liquid chromatographic system for separation, data-independent acquisition in tandem mass spectrometry, and DIA-NN, FragPipe, and in-house peptide spectral library-based data analysis. Using the optimized platform at a throughput of 60 samples per day, over 600 protein groups including 57 FDA-approved biomarkers can be consistently identified from whole human plasma, and more than 85% of the detected proteins have 100% completeness in quantitative values across 300 samples. The balance achieved between proteome coverage, throughput, and reproducibility of this sHTPP platform makes it promising in clinical settings, where a large number of samples are to be measured quickly and reliably to support various needs of clinical medicine.
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Affiliation(s)
- Jongmin Woo
- Center
for Translational Biomedical Research, University
of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, North Carolina 28081, United States
| | - Qibin Zhang
- Center
for Translational Biomedical Research, University
of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, North Carolina 28081, United States
- Department
of Chemistry & Biochemistry, University
of North Carolina at Greensboro, Greensboro, North Carolina 27402, United States
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25
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Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
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Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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26
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Rylski B, Schilling O, Czerny M. Acute aortic dissection: evidence, uncertainties, and future therapies. Eur Heart J 2023; 44:813-821. [PMID: 36540036 DOI: 10.1093/eurheartj/ehac757] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 10/27/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Remarkable progress has become especially apparent in aortic medicine in the last few decades, leading to essential changes in how thoracic aortic dissection is understood and treated. This state-of-the-art review article addresses the mechanisms of acute aortic dissection, explaining the role of its primary entry location, proximal, and distal dissection extension in their clinical presentation and impact on the decision-making process towards the best treatment approach. The latest evidence on novel treatment methods for acute aortic syndromes is presented, and the diverse dissection classification systems that remain uncertain are discussed, which reveals the need for shared terminology and more clarity. Finally, future aspects are discussed in treating acute aortic dissection, such as the endovascular treatment of aortic dissection Type A and biomarkers for acute aortic syndromes.
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Affiliation(s)
- Bartosz Rylski
- Department of Cardiovascular Surgery, Heart Centre Freiburg University, Hugstetter Str. 55, 79106 Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany
| | - Oliver Schilling
- Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany.,Institute for Surgical Pathology, Hugstetter Str. 55, 79106 Freiburg, Germany
| | - Martin Czerny
- Department of Cardiovascular Surgery, Heart Centre Freiburg University, Hugstetter Str. 55, 79106 Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany
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27
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Sahin AT, Yurtseven A, Dadmand S, Ozcan G, Akarlar BA, Kucuk NEO, Senturk A, Ergonul O, Can F, Tuncbag N, Ozlu N. Plasma proteomics identify potential severity biomarkers from COVID-19 associated network. Proteomics Clin Appl 2023; 17:e2200070. [PMID: 36217943 PMCID: PMC9874836 DOI: 10.1002/prca.202200070] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/27/2022] [Accepted: 10/07/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE Coronavirus disease 2019 (COVID-19) continues to threaten public health globally. Severe acute respiratory coronavirus type 2 (SARS-CoV-2) infection-dependent alterations in the host cell signaling network may unveil potential target proteins and pathways for therapeutic strategies. In this study, we aim to define early severity biomarkers and monitor altered pathways in the course of SARS-CoV-2 infection. EXPERIMENTAL DESIGN We systematically analyzed plasma proteomes of COVID-19 patients from Turkey by using mass spectrometry. Different severity grades (moderate, severe, and critical) and periods of disease (early, inflammatory, and recovery) are monitored. Significant alterations in protein expressions are used to reconstruct the COVID-19 associated network that was further extended to connect viral and host proteins. RESULTS Across all COVID-19 patients, 111 differentially expressed proteins were found, of which 28 proteins were unique to our study mainly enriching in immunoglobulin production. By monitoring different severity grades and periods of disease, CLEC3B, MST1, and ITIH2 were identified as potential early predictors of COVID-19 severity. Most importantly, we extended the COVID-19 associated network with viral proteins and showed the connectedness of viral proteins with human proteins. The most connected viral protein ORF8, which has a role in immune evasion, targets many host proteins tightly connected to the deregulated human plasma proteins. CONCLUSIONS AND CLINICAL RELEVANCE Plasma proteomes from critical patients are intrinsically clustered in a distinct group than severe and moderate patients. Importantly, we did not recover any grouping based on the infection period, suggesting their distinct proteome even in the recovery phase. The new potential early severity markers can be further studied for their value in the clinics to monitor COVID-19 prognosis. Beyond the list of plasma proteins, our disease-associated network unravels altered pathways, and the possible therapeutic targets in SARS-CoV-2 infection by connecting human and viral proteins. Follow-up studies on the disease associated network that we propose here will be useful to determine molecular details of viral perturbation and to address how the infection affects human physiology.
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Affiliation(s)
- Ayse Tugce Sahin
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey.,Graduate School of Science and Engineering, Koc University, Istanbul, Turkey
| | - Ali Yurtseven
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey.,Graduate School of Science and Engineering, Koc University, Istanbul, Turkey
| | - Sina Dadmand
- Graduate School of Science and Engineering, Koc University, Istanbul, Turkey.,Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey
| | - Gulin Ozcan
- Koc University Research Center for Translational Medicine (KUTTAM), Istanbul, Turkey.,Graduate School of Health Sciences, Koc University, Istanbul, Turkey
| | - Busra A Akarlar
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey.,Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey
| | - Nazli Ezgi Ozkan Kucuk
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey.,Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey
| | - Aydanur Senturk
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey
| | - Onder Ergonul
- Graduate School of Health Sciences, Koc University, Istanbul, Turkey.,Koc University Is Bank Research Center for Infectious Diseases (KUISCID), Istanbul, Turkey
| | - Fusun Can
- Graduate School of Health Sciences, Koc University, Istanbul, Turkey.,Department of Infectious Diseases, School of Medicine, Koc University, Istanbul, Turkey
| | - Nurcan Tuncbag
- Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey.,Department of Medical Microbiology, School of Medicine, Koc University, Istanbul, Turkey.,Department of Medical Biology, School of Medicine, Koc University, Istanbul, Turkey
| | - Nurhan Ozlu
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey.,Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey.,Department of Medical Biology, School of Medicine, Koc University, Istanbul, Turkey
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28
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Horlacher M, Oleshko S, Hu Y, Ghanbari M, Cantini G, Schinke P, Vergara EE, Bittner F, Mueller NS, Ohler U, Moyon L, Marsico A. A computational map of the human-SARS-CoV-2 protein-RNA interactome predicted at single-nucleotide resolution. NAR Genom Bioinform 2023; 5:lqad010. [PMID: 36814457 PMCID: PMC9940458 DOI: 10.1093/nargab/lqad010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 01/10/2023] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
RNA-binding proteins (RBPs) are critical host factors for viral infection, however, large scale experimental investigation of the binding landscape of human RBPs to viral RNAs is costly and further complicated due to sequence variation between viral strains. To fill this gap, we investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP-viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments on more than 100 human RBPs. We evaluated conservation of RBP binding between six other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of mutations from 11 variants of concern on protein-RNA interaction, identifying a set of gain- and loss-of-binding events, as well as predicted the regulatory impact of putative future mutations. Lastly, we linked RBPs to functional, OMICs and COVID-19 patient data from other studies, and identified MBNL1, FTO and FXR2 RBPs as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and open new avenues for therapeutic intervention.
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Affiliation(s)
- Marc Horlacher
- Computational Health Center, Helmholtz Center Munich, Munich, Germany
| | - Svitlana Oleshko
- Computational Health Center, Helmholtz Center Munich, Munich, Germany
| | - Yue Hu
- Computational Health Center, Helmholtz Center Munich, Munich, Germany,Informatics 12 Chair of Bioinformatics, Technical University Munich, Garching, Germany
| | - Mahsa Ghanbari
- Institutes of Biology and Computer Science, Humboldt University, Berlin, Germany,Max Delbruck Center, Computational Regulatory Genomics, Berlin, Germany
| | - Giulia Cantini
- Computational Health Center, Helmholtz Center Munich, Munich, Germany
| | - Patrick Schinke
- Computational Health Center, Helmholtz Center Munich, Munich, Germany
| | | | | | | | - Uwe Ohler
- Institutes of Biology and Computer Science, Humboldt University, Berlin, Germany,Max Delbruck Center, Computational Regulatory Genomics, Berlin, Germany
| | - Lambert Moyon
- To whom correspondence should be addressed. Tel: +49 89318749193;
| | - Annalisa Marsico
- Correspondence may also be addressed to Annalisa Marsico. Tel: +49 89318743073;
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29
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Mun DG, Budhraja R, Bhat FA, Zenka RM, Johnson KL, Moghekar A, Pandey A. Four-dimensional proteomics analysis of human cerebrospinal fluid with trapped ion mobility spectrometry using PASEF. Proteomics 2023; 23:e2200507. [PMID: 36752121 DOI: 10.1002/pmic.202200507] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 02/09/2023]
Abstract
A quadrupole time-of-flight mass spectrometer coupled with a trapped ion mobility spectrometry (timsTOF) operated in parallel accumulation-serial fragmentation (PASEF) mode has recently emerged as a platform capable of providing four-dimensional (4D) features comprising of elution time, collision cross section (CCS), mass-to-charge ratio, and intensity of peptides. The PASEF mode provides ∼100% ion sampling efficiency both in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes without sacrificing sensitivity. In addition, targeted measurements using PASEF integrated parallel reaction monitoring (PRM) mode have also been described. However, only limited number of studies have used timsTOF for analysis of clinical samples. Although Orbitrap mass spectrometers have been used for biomarker discovery from cerebrospinal fluid (CSF) in a variety of neurological diseases, these Orbitrap-derived datasets cannot readily be applied for driving experiments on timsTOF mass spectrometers. We generated a catalog of peptides and proteins in human CSF in DDA mode on a timsTOF mass spectrometer and used these data to build a spectral library. This strategy allowed us to use elution times and ion mobility values from the spectral library to design PRM experiments for quantifying previously discovered biomarkers from CSF samples in Alzheimer's disease. When the same samples were analyzed using a DIA approach combined with a spectral library search, a higher number of proteins were identified than in a library-free approach. Overall, we have established a spectral library of CSF as a resource and demonstrated its utility for PRM and DIA studies, which should facilitate studies of neurological disorders.
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Affiliation(s)
- Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Firdous A Bhat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Roman M Zenka
- Proteomics Core, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Abhay Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.,Manipal Academy of Higher Education, Manipal, Karnataka, India.,Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
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30
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Bauer A, Pachl E, Hellmuth JC, Kneidinger N, Heydarian M, Frankenberger M, Stubbe HC, Ryffel B, Petrera A, Hauck SM, Behr J, Kaiser R, Scherer C, Deng L, Teupser D, Ahmidi N, Muenchhoff M, Schubert B, Hilgendorff A. Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients. Biochim Biophys Acta Mol Basis Dis 2023; 1869:166592. [PMID: 36328146 PMCID: PMC9622026 DOI: 10.1016/j.bbadis.2022.166592] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 10/27/2022] [Accepted: 10/27/2022] [Indexed: 11/05/2022]
Abstract
SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Previous studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited. We addressed the gap of existing knowledge with regard to a differentiated understanding of disease dynamics in SARS-CoV-2 infection while specifically considering disease stage and severity. We biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of the individualized disease phase assignment, proteome analysis revealed a severity dependent general type-2-centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response characterizing severe disease was successfully validated in a second cohort. Together with the regulation of proteins related to SARS-CoV-2-specific symptoms identified by proteome screening, we not only confirmed results from previous studies but provide novel information for biomarker and therapy development.
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Affiliation(s)
- Alina Bauer
- Helmholtz Zentrum München, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany
| | - Elisabeth Pachl
- Helmholtz Zentrum München, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany,Fraunhofer IKS, Fraunhofer Institute for Cognitive Systems IKS, 80686 Munich, Germany
| | - Johannes C. Hellmuth
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany,German Cancer Consortium (DKTK), Munich, Germany,COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany
| | - Nikolaus Kneidinger
- Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Member of the German Center for Lung Research (DZL), Munich, Germany,Department of Medicine V, University Hospital, LMU Munich, Member of the German Center for Lung Research (DZL), Munich, Germany
| | | | - Marion Frankenberger
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany
| | - Hans C. Stubbe
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany,Department of Medicine II, University Hospital, LMU Munich, Munich, Germany
| | - Bernhard Ryffel
- Laboratory of Experimental and Molecular Immunology and Neurogenetics (INEM), UMR 7355 CNRS-University of Orleans and Artimmune, Orléans, France
| | - Agnese Petrera
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, Munich, Germany
| | - Stefanie M. Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, Munich, Germany
| | - Jürgen Behr
- Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Member of the German Center for Lung Research (DZL), Munich, Germany,Department of Medicine V, University Hospital, LMU Munich, Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Rainer Kaiser
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany,Medizinische Klinik und Poliklinik I, University Hospital, LMU Munich, Munich, Germany,DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Clemens Scherer
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany,Medizinische Klinik und Poliklinik I, University Hospital, LMU Munich, Munich, Germany,DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Li Deng
- Helmholtz Zentrum München, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany,Institute of Virology, Technical University of Munich, 81675 Munich, Germany
| | - Daniel Teupser
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Narges Ahmidi
- Fraunhofer IKS, Fraunhofer Institute for Cognitive Systems IKS, 80686 Munich, Germany
| | - Maximilian Muenchhoff
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany,Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany,German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Benjamin Schubert
- Helmholtz Zentrum München, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany,Department of Mathematics, Technical University of Munich, 85748 Garching bei München, Germany
| | - Anne Hilgendorff
- Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Member of the German Center for Lung Research (DZL), Munich, Germany; Center for Comprehensive Developmental Care (CDeC(LMU)) at the Interdisciplinary Social Pediatric Center (iSPZ), LMU Hospital, Munich, Germany.
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31
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Liang X, Sun R, Wang J, Zhou K, Li J, Chen S, Lyu M, Li S, Xue Z, Shi Y, Xie Y, Zhang Q, Yi X, Pan J, Wang D, Xu J, Zhu H, Zhu G, Zhu J, Zhu Y, Zheng Y, Shen B, Guo T. Proteomics Investigation of Diverse Serological Patterns in COVID-19. Mol Cell Proteomics 2023; 22:100493. [PMID: 36621767 PMCID: PMC9814280 DOI: 10.1016/j.mcpro.2023.100493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/23/2022] [Accepted: 01/03/2023] [Indexed: 01/07/2023] Open
Abstract
Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.
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Affiliation(s)
- Xiao Liang
- Fudan University, Shanghai, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Rui Sun
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Jing Wang
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Kai Zhou
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Jun Li
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Shiyong Chen
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Mengge Lyu
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Sainan Li
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Zhangzhi Xue
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Yingqiu Shi
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Yuting Xie
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Qiushi Zhang
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd, Hangzhou, Zhejiang, China
| | - Xiao Yi
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd, Hangzhou, Zhejiang, China
| | - Juan Pan
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Donglian Wang
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Jiaqin Xu
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Hongguo Zhu
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Guangjun Zhu
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Jiansheng Zhu
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Yi Zhu
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China; Westlake Omics (Hangzhou) Biotechnology Co., Ltd, Hangzhou, Zhejiang, China
| | - Yufen Zheng
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China.
| | - Bo Shen
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, Zhejiang, China.
| | - Tiannan Guo
- Fudan University, Shanghai, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China; Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China.
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32
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Ye X, Cui X, Zhang L, Wu Q, Sui X, He A, Zhang X, Xu R, Tian R. Combination of automated sample preparation and micro-flow LC-MS for high-throughput plasma proteomics. Clin Proteomics 2023; 20:3. [PMID: 36611134 PMCID: PMC9824974 DOI: 10.1186/s12014-022-09390-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/27/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis. METHODS We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC-MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups. RESULTS This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC-MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers. CONCLUSIONS This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups.
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Affiliation(s)
- Xueting Ye
- grid.440218.b0000 0004 1759 7210The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, 518020 China ,grid.258164.c0000 0004 1790 3548The First Affiliated Hospital, Jinan University, Guangzhou, 510632 China ,grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
| | - Xiaozhen Cui
- grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
| | - Luobin Zhang
- grid.440218.b0000 0004 1759 7210The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, 518020 China
| | - Qiong Wu
- grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
| | - Xintong Sui
- grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
| | - An He
- grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
| | - Xinyou Zhang
- grid.440218.b0000 0004 1759 7210The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, 518020 China
| | - Ruilian Xu
- grid.440218.b0000 0004 1759 7210The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, 518020 China
| | - Ruijun Tian
- grid.263817.90000 0004 1773 1790Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, 518055 China
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Nieman DC, Woo J, Sakaguchi CA, Omar AM, Tang Y, Davis K, Pecorelli A, Valacchi G, Zhang Q. Astaxanthin supplementation counters exercise-induced decreases in immune-related plasma proteins. Front Nutr 2023; 10:1143385. [PMID: 37025615 PMCID: PMC10070989 DOI: 10.3389/fnut.2023.1143385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 02/23/2023] [Indexed: 04/08/2023] Open
Abstract
Objectives Astaxanthin is a dark red keto-carotenoid found in aquatic animals such as salmon and shrimp, and algae (Haematococcus pluvialis). Astaxanthin has a unique molecular structure that may facilitate anti-oxidative, immunomodulatory, and anti-inflammatory effects during physiological stress. The primary objective of this study was to examine the efficacy of 4-week ingestion of astaxanthin in moderating exercise-induced inflammation and immune dysfunction using a multi-omics approach. Methods This study employed a randomized, double blind, placebo controlled, crossover design with two 4-week supplementation periods and a 2-week washout period. Study participants were randomized to astaxanthin and placebo trials, with supplements ingested daily for 4 weeks prior to running 2.25 h at close to 70%VO2max (including 30 min of 10% downhill running). After the washout period, participants repeated all procedures using the counterbalanced supplement. The astaxanthin capsule contained 8 mg of algae astaxanthin. Six blood samples were collected before and after supplementation (overnight fasted state), immediately post-exercise, and at 1.5, 3, and 24 h-post-exercise. Plasma aliquots were assayed using untargeted proteomics, and targeted oxylipin and cytokine panels. Results The 2.25 h running bout induced significant muscle soreness, muscle damage, and inflammation. Astaxanthin supplementation had no effect on exercise-induced muscle soreness, muscle damage, and increases in six plasma cytokines and 42 oxylipins. Notably, astaxanthin supplementation countered exercise-induced decreases in 82 plasma proteins (during 24 h recovery). Biological process analysis revealed that most of these proteins were involved in immune-related functions such as defense responses, complement activation, and humoral immune system responses. Twenty plasma immunoglobulins were identified that differed significantly between the astaxanthin and placebo trials. Plasma levels of IgM decreased significantly post-exercise but recovered after the 24 h post-exercise recovery period in the astaxanthin but not the placebo trial. Discussion These data support that 4-week astaxanthin versus placebo supplementation did not counter exercise-induced increases in plasma cytokines and oxylipins but was linked to normalization of post-exercise plasma levels of numerous immune-related proteins including immunoglobulins within 24 h. Short-term astaxanthin supplementation (8 mg/day during a 4-week period) provided immune support for runners engaging in a vigorous 2.25 h running bout and uniquely countered decreases in plasma immunoglobulin levels.
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Affiliation(s)
- David C. Nieman
- Human Performance Laboratory, Appalachian State University, Kannapolis, NC, United States
- *Correspondence: David C. Nieman,
| | - Jongmin Woo
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, Kannapolis, NC, United States
| | - Camila A. Sakaguchi
- Human Performance Laboratory, Appalachian State University, Kannapolis, NC, United States
| | - Ashraf M. Omar
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, Kannapolis, NC, United States
| | - Yang Tang
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, Kannapolis, NC, United States
| | - Kierstin Davis
- Human Performance Laboratory, Appalachian State University, Kannapolis, NC, United States
| | - Alessandra Pecorelli
- Department of Food Bioprocessing and Nutrition Sciences, Plants for Human Health Institute, North Carolina State University, Kannapolis, NC, United States
| | - Giuseppe Valacchi
- Department of Food Bioprocessing and Nutrition Sciences, Plants for Human Health Institute, North Carolina State University, Kannapolis, NC, United States
- Department of Environmental Sciences and Prevention, University of Ferrara, Ferrara, Italy
| | - Qibin Zhang
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, Kannapolis, NC, United States
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Jeon K, Kim Y, Kang SK, Park U, Kim J, Park N, Koh J, Shim MS, Kim M, Rhee YJ, Jeong H, Lee S, Park D, Lim J, Kim H, Ha NY, Jo HY, Kim SC, Lee JH, Shon J, Kim H, Jeon YK, Choi YS, Kim HY, Lee WW, Choi M, Park HY, Park WY, Kim YS, Cho NH. Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia. Front Immunol 2023; 14:1101808. [PMID: 36776879 PMCID: PMC9911526 DOI: 10.3389/fimmu.2023.1101808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/09/2023] [Indexed: 01/28/2023] Open
Abstract
Introduction Despite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive. Methods Here, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients. Results Differential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients. Discussion Aberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression.
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Affiliation(s)
- Kyeongseok Jeon
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yuri Kim
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Shin Kwang Kang
- Department of Thoracic and Cardiovascular Surgery, Chungnam National University School of Medicine, Deajon, Republic of Korea
| | - Uni Park
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jayoun Kim
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nanhee Park
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jaemoon Koh
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Man-Shik Shim
- Department of Thoracic and Cardiovascular Surgery, Chungnam National University School of Medicine, Deajon, Republic of Korea
| | - Minsoo Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Youn Ju Rhee
- Department of Thoracic and Cardiovascular Surgery, Chungnam National University School of Medicine, Deajon, Republic of Korea
| | - Hyeongseok Jeong
- Department of Internal Medicine, Chungnam National University School of Medicine, Deajon, Republic of Korea
| | | | | | - Jinyoung Lim
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
| | - Hyunsu Kim
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
| | - Na-Young Ha
- Chungnam National University Hospital, Biomedical Research Institute, Deajon, Republic of Korea
| | - Hye-Yeong Jo
- Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Sang Cheol Kim
- Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Ju-Hee Lee
- Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Jiwon Shon
- Department of Biohealth Regulatory Science, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea
| | - Hoon Kim
- Department of Biohealth Regulatory Science, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea.,Biopharmaceutical Convergence Major, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea
| | - Yoon Kyung Jeon
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Youn-Soo Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hye Young Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Won-Woo Lee
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Murim Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hyun-Young Park
- Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Woong-Yang Park
- Geninus Inc., Seoul, Republic of Korea.,Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
| | - Yeon-Sook Kim
- Department of Internal Medicine, Chungnam National University School of Medicine, Deajon, Republic of Korea
| | - Nam-Hyuk Cho
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Endemic Diseases, Medical Research Center, Seoul National University, Seoul, Republic of Korea.,Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Republic of Korea.,Wide River Institute of Immunology, Seoul National University, Hongcheon, Gangwon-do, Republic of Korea
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Gong R, Luo H, Long G, Xu J, Huang C, Zhou X, Shang Y, Zhang D. Integrative proteomic profiling of lung tissues and blood in acute respiratory distress syndrome. Front Immunol 2023; 14:1158951. [PMID: 37197655 PMCID: PMC10184823 DOI: 10.3389/fimmu.2023.1158951] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 04/20/2023] [Indexed: 05/19/2023] Open
Abstract
Introduction Acute respiratory distress syndrome and acute lung injury (ARDS/ALI) still lack a recognized diagnostic test and pharmacologic treatments that target the underlying pathology. Methods To explore the sensitive non-invasive biomarkers associated with pathological changes in the lung of direct ARDS/ALI, we performed an integrative proteomic analysis of lung and blood samples from lipopolysaccharide (LPS)-induced ARDS mice and COVID-19-related ARDS patients. The common differentially expressed proteins (DEPs) were identified based on combined proteomic analysis of serum and lung samples in direct ARDS mice model. The clinical value of the common DEPs was validated in lung and plasma proteomics in cases of COVID-19-related ARDS. Results We identified 368 DEPs in serum and 504 in lung samples from LPS-induced ARDS mice. Gene ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEPs in lung tissues were primarily enriched in pathways, including IL-17 and B cell receptor signaling pathways, and the response to stimuli. In contrast, DEPs in the serum were mostly involved in metabolic pathways and cellular processes. Through network analysis of protein-protein interactions (PPI), we identified diverse clusters of DEPs in the lung and serum samples. We further identified 50 commonly upregulated and 10 commonly downregulated DEPs in the lung and serum samples. Internal validation with a parallel-reacted monitor (PRM) and external validation in the Gene Expression Omnibus (GEO) datasets further showed these confirmed DEPs. We then validated these proteins in the proteomics of patients with ARDS and identified six proteins (HP, LTA4H, S100A9, SAA1, SAA2, and SERPINA3) with good clinical diagnostic and prognostic value. Discussion These proteins can be viewed as sensitive and non-invasive biomarkers associated with lung pathological changes in the blood and could potentially serve as targets for the early detection and treatment of direct ARDS especially in hyperinflammatory subphenotype.
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Affiliation(s)
- Rui Gong
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China (USTC), Hefei, Anhui, China
- Center for Translational Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
| | - Hong Luo
- Center for Translational Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
| | - Gangyu Long
- Center for Translational Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
| | - Jiqian Xu
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
| | - Chaolin Huang
- Center for Translational Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
| | - Xin Zhou
- SpecAlly Life Technology Co., Ltd, Wuhan, Hubei, China
| | - You Shang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China (USTC), Hefei, Anhui, China
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
- *Correspondence: Dingyu Zhang, ; You Shang,
| | - Dingyu Zhang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China (USTC), Hefei, Anhui, China
- Center for Translational Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, China
- *Correspondence: Dingyu Zhang, ; You Shang,
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Rajoria S, Nair D, Suvarna K, Pai MGJ, Salkar A, Palanivel V, Verma A, Barpanda A, Awasthi G, Doshi H, Dhara V, Burli A, Agrawal S, Shrivastav O, Shastri J, Srivastava S. Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai. Adv Exp Med Biol 2023; 1412:175-195. [PMID: 37378767 DOI: 10.1007/978-3-031-28012-2_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.
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Affiliation(s)
- Sakshi Rajoria
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Divya Nair
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Kruthi Suvarna
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Medha Gayathri J Pai
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Akanksha Salkar
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Viswanthram Palanivel
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Ayushi Verma
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Abhilash Barpanda
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Gaurav Awasthi
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Hastyn Doshi
- Department of Computer Science, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Vivek Dhara
- Department of Mechanical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Ananya Burli
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Sachee Agrawal
- Kasturba Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra, India
| | - Om Shrivastav
- Kasturba Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra, India
| | - Jayanthi Shastri
- Kasturba Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra, India
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India.
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Gallo V, Gentile R, Antonini G, Iacobelli S, Nobrega C, Silva CS, Sarmento H, Cotter J, Canto-Gomes J, Palha J, Peixoto P, Barreira-Silva P, Sousa JC, Correia-Neves M, Formigo M, Vieira N, Cunha PG, Roque S, Gentile R, Antonini G, Iacobelli S. Increased Gal-3BP plasma levels in hospitalized patients infected with SARS-CoV-2. Clin Exp Med 2023; 23:151-155. [PMID: 35076790 PMCID: PMC8787969 DOI: 10.1007/s10238-021-00788-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 12/17/2021] [Indexed: 12/20/2022]
Abstract
Coronavirus disease 2019 (COVID-19) has quickly turned into a health, financial and societal problem globally. The complex pathogenesis of severe acute respiratory syndrome coronavirus centers on the unpredictable clinical progression of the disease, which may evolve abruptly and results in critical and life-threatening clinical complications. Effective laboratory biomarkers that can classify patients according to risk of progression to severe disease are essential for ensuring timely treatment. Gal-3BP is a human secreted protein with innate immune functions, which is upregulated in viral infections, promotes inflammation and has been shown to induce IL-6 expression. In this study, Gal-3BP plasma levels were measured retrospectively in a cohort of 84 hospitalized COVID-19 patients. These were classified as having either "non-severe" or "severe" disease. Compared to healthy controls, Gal-3BP plasma levels were markedly increased in COVID-19 patients (P < 0.0001). Moreover, the levels were higher in severe than in non-severe patients (P < 0.05). As expected, patients with severe disease had plasma levels of IL-6 higher than patients with non-severe disease (P < 0.01). In non-severe disease patients, Gal-3BP levels collected at a late stage (13.3 + 5.7 days after the first positive PCR result) were significantly lower than those collected at an early stage (4.2 + 2.9 days form the first positive PCR result). Larger prospective analyses are needed to strength our understanding of the prognostic utility of Gal-3BP in COVID-19 patients.
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Affiliation(s)
- Valentina Gallo
- Department of Sciences, Roma Tre University, Rome, Italy ,Biostructures and Biosystems National Institute (INBB), Rome, Italy
| | | | | | - Giovanni Antonini
- Department of Sciences, Roma Tre University, Rome, Italy. .,Biostructures and Biosystems National Institute (INBB), Rome, Italy.
| | - Stefano Iacobelli
- Biostructures and Biosystems National Institute (INBB), Rome, Italy ,MediaPharma Srl, Chieti, Italy
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Li C, Yue L, Ju Y, Wang J, Chen M, Lu H, Liu S, Liu T, Wang J, Hu X, Tuohetaerbaike B, Wen H, Zhang W, Xu S, Jiang C, Chen F. Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan. Microbiol Spectr 2022; 10:e0127022. [PMID: 36314975 PMCID: PMC9784772 DOI: 10.1128/spectrum.01270-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/07/2022] [Indexed: 12/24/2022] Open
Abstract
The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of "coagulation" and "immune response" in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in "coagulation" and "immune response". Importantly, we identified 7 "coagulation system"- and 9 "immune response"-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 "coagulation system"- and 5 "immune response"-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.
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Affiliation(s)
- Cuidan Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
| | - Liya Yue
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
| | - Yingjiao Ju
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jie Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Mengfan Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hao Lu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Sitong Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Tao Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jing Wang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Xin Hu
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Bahetibieke Tuohetaerbaike
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Hao Wen
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Wenbao Zhang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Sihong Xu
- Division II of In Vitro Diagnostics for Infectious Diseases, Institute for In Vitro Diagnostics Control, National Institutes for Food and Drug Control, Beijing, China
| | - Chunlai Jiang
- National Engineering Laboratory for AIDS Vaccine, School of Life Science, Jilin University, Changchun, China
| | - Fei Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
- Beijing Key Laboratory of Genome and Precision Medicine Technologies, Beijing, China
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Torun F, Virreira Winter S, Doll S, Riese FM, Vorobyev A, Mueller-Reif JB, Geyer PE, Strauss MT. Transparent Exploration of Machine Learning for Biomarker Discovery from Proteomics and Omics Data. J Proteome Res 2022; 22:359-367. [PMID: 36426751 PMCID: PMC9903317 DOI: 10.1021/acs.jproteome.2c00473] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy; still, they are lacking for most diseases. Mass spectrometry (MS)-based proteomics is a powerful technology for biomarker discovery but requires sophisticated bioinformatics to identify robust patterns. Machine learning (ML) has become a promising tool for this purpose. However, it is sometimes applied in an opaque manner and generally requires specialized knowledge. To enable easy access to ML for biomarker discovery without any programming or bioinformatics skills, we developed "OmicLearn" (http://OmicLearn.org), an open-source browser-based ML tool using the latest advances in the Python ML ecosystem. Data matrices from omics experiments are easily uploaded to an online or a locally installed web server. OmicLearn enables rapid exploration of the suitability of various ML algorithms for the experimental data sets. It fosters open science via transparent assessment of state-of-the-art algorithms in a standardized format for proteomics and other omics sciences.
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Affiliation(s)
| | | | - Sophia Doll
- OmicEra
Diagnostics GmbH, 82152 Planegg, Germany
| | | | | | | | | | - Maximilian T. Strauss
- Novo
Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark,
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He B, Huang Z, Huang C, Nice EC. Clinical applications of plasma proteomics and peptidomics: Towards precision medicine. Proteomics Clin Appl 2022; 16:e2100097. [PMID: 35490333 DOI: 10.1002/prca.202100097] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/16/2022] [Accepted: 04/28/2022] [Indexed: 02/05/2023]
Abstract
In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.
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Affiliation(s)
- Bo He
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, P. R. China
| | - Zhao Huang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, P. R. China
| | - Canhua Huang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, P. R. China.,Department of Pharmacology, and Provincial Key Laboratory of Pathophysiology in Ningbo University School of Medicine, Ningbo, Zhejiang, China
| | - Edouard C Nice
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia
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Adiguzel Y, Shoenfeld Y. Shared 6mer Peptides of Human and Omicron (21K and 21L) at SARS-CoV-2 Mutation Sites. Antibodies (Basel) 2022; 11. [PMID: 36412834 DOI: 10.3390/antib11040068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/18/2022] [Accepted: 10/21/2022] [Indexed: 12/14/2022] Open
Abstract
We investigated the short sequences involving Omicron 21K and Omicron 21L variants to reveal any possible molecular mimicry-associated autoimmunity risks and changes in those. We first identified common 6mers of the viral and human protein sequences present for both the mutant (Omicron) and nonmutant (SARS-CoV-2) versions of the same viral sequence and then predicted the binding affinities of those sequences to the HLA supertype representatives. We evaluated change in the potential autoimmunity risk, through comparative assessment of the nonmutant and mutant viral sequences and their similar human peptides with common 6mers and affinities to the same HLA allele. This change is the lost and the new, or de novo, autoimmunity risk, associated with the mutations in the Omicron 21K and Omicron 21L variants. Accordingly, e.g., the affinity of virus-similar sequences of the Ig heavy chain junction regions shifted from the HLA-B*15:01 to the HLA-A*01:01 allele at the mutant sequences. Additionally, peptides of different human proteins sharing 6mers with SARS-CoV-2 proteins at the mutation sites of interest and with affinities to the HLA-B*07:02 allele, such as the respective SARS-CoV-2 sequences, were lost. Among all, any possible molecular mimicry-associated novel risk appeared to be prominent in HLA-A*24:02 and HLA-B*27:05 serotypes upon infection with Omicron 21L. Associated disease, pathway, and tissue expression data supported possible new risks for the HLA-B*27:05 and HLA-A*01:01 serotypes, while the risks for the HLA-B*07:02 serotypes could have been lost or diminished, and those for the HLA-A*03:01 serotypes could have been retained, for the individuals infected with Omicron variants under study. These are likely to affect the complications related to cross-reactions influencing the relevant HLA serotypes upon infection with Omicron 21K and Omicron 21L.
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Saheb Sharif-Askari N, Soares NC, Mohamed HA, Saheb Sharif-Askari F, Alsayed HAH, Al-Hroub H, Salameh L, Osman RS, Mahboub B, Hamid Q, Semreen MH, Halwani R. Saliva metabolomic profile of COVID-19 patients associates with disease severity. Metabolomics 2022; 18:81. [PMID: 36271948 PMCID: PMC9589589 DOI: 10.1007/s11306-022-01936-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 09/27/2022] [Indexed: 01/08/2023]
Abstract
INTRODUCTION Coronavirus disease 2019 (COVID-19) is strongly linked to dysregulation of various molecular, cellular, and physiological processes that change abundance of different biomolecules including metabolites that may be ultimately used as biomarkers for disease progression and severity. It is important at early stage to readily distinguish those patients that are likely to progress to moderate and severe stages. OBJECTIVES This study aimed to investigate the utility of saliva and plasma metabolomic profiles as a potential parameter for risk stratifying COVID-19 patients. METHOD LC-MS/MS-based untargeted metabolomics were used to profile the changes in saliva and plasma metabolomic profiles of COVID-19 patients with different severities. RESULTS Saliva and plasma metabolites were screened in 62 COVID-19 patients and 18 non-infected controls. The COVID-19 group included 16 severe, 15 moderate, 16 mild, and 15 asymptomatic cases. Thirty-six differential metabolites were detected in COVID-19 versus control comparisons. SARS-CoV-2 induced metabolic derangement differed with infection severity. The metabolic changes were identified in saliva and plasma, however, saliva showed higher intensity of metabolic changes. Levels of saliva metabolites such as sphingosine and kynurenine were significantly different between COVID-19 infected and non-infected individuals; while linoleic acid and Alpha-ketoisovaleric acid were specifically increased in severe compared to non-severe patients. As expected, the two prognostic biomarkers of C-reactive protein and D-dimer were negatively correlated with sphingosine and 5-Aminolevulinic acid, and positively correlated with L-Tryptophan and L-Kynurenine. CONCLUSION Saliva disease-specific and severity-specific metabolite could be employed as potential COVID-19 diagnostic and prognostic biomarkers.
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Affiliation(s)
- Narjes Saheb Sharif-Askari
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
| | - Nelson Cruz Soares
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
- grid.412789.10000 0004 4686 5317Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah, UAE
| | - Hajer A. Mohamed
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
- grid.412789.10000 0004 4686 5317Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah, UAE
| | - Fatemeh Saheb Sharif-Askari
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
| | | | - Hamza Al-Hroub
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
| | - Laila Salameh
- grid.414167.10000 0004 1757 0894Rashid Hospital, Dubai Health Authority, Dubai, UAE
- grid.412789.10000 0004 4686 5317Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE
| | - Rufaida Satti Osman
- grid.414167.10000 0004 1757 0894Rashid Hospital, Dubai Health Authority, Dubai, UAE
| | - Bassam Mahboub
- grid.414167.10000 0004 1757 0894Rashid Hospital, Dubai Health Authority, Dubai, UAE
- grid.412789.10000 0004 4686 5317Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE
| | - Qutayba Hamid
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
- grid.412789.10000 0004 4686 5317Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE
- grid.14709.3b0000 0004 1936 8649Meakins-Christie Laboratories, McGill University, Montreal, QC Canada
| | - Mohammad H. Semreen
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
- grid.412789.10000 0004 4686 5317College of Pharmacy, University of Sharjah, Sharjah, UAE
| | - Rabih Halwani
- grid.412789.10000 0004 4686 5317Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE
- grid.412789.10000 0004 4686 5317Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE
- grid.56302.320000 0004 1773 5396Prince Abdullah Ben Khaled Celiac Disease Research Chair, Department of Pediatrics, Faculty of Medicine, King Saud University, Riyadh, Saudi Arabia
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Tierney AL, Alali WM, Scott T, Rees-Unwin KS, Clark SJ, Unwin RD. Levels of soluble complement regulators predict severity of COVID-19 symptoms. Front Immunol 2022; 13:1032331. [PMID: 36330526 PMCID: PMC9624227 DOI: 10.3389/fimmu.2022.1032331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 09/26/2022] [Indexed: 12/15/2022] Open
Abstract
The SARS-CoV-2 virus continues to cause significant morbidity and mortality worldwide from COVID-19. One of the major challenges of patient management is the broad range of symptoms observed. While the majority of individuals experience relatively mild disease, a significant minority of patients require hospitalisation, with COVID-19 still proving fatal for some. As such, there remains a desperate need to better understand what drives this severe disease, both in terms of the underlying biology, but also to potentially predict at diagnosis which patients are likely to require further interventions, thus enabling better outcomes for both patients and healthcare systems. Several lines of evidence have pointed to dysregulation of the complement cascade as a major factor in severe COVID-19 outcomes. How this is underpinned mechanistically is not known. Here, we have focussed on the role of the soluble complement regulators Complement Factor H (FH), its splice variant Factor H-like 1 (FHL-1) and five Factor H-Related proteins (FHR1-5). Using a targeted mass spectrometry approach, we quantified these proteins in a cohort of 188 plasma samples from controls and SARS-CoV-2 patients taken at diagnosis. This analysis revealed significant elevations in all FHR proteins, but not FH, in patients with more severe disease, particularly FHR2 and FHR5 (FHR2: 1.97-fold, p<0.0001; FHR5: 2.4-fold, p<0.0001). Furthermore, for a subset of 77 SARS-CoV-2 +ve patients we also analysed time course samples taken approximately 28 days post-diagnosis. Here, we see complement regulator levels drop in all individuals with asymptomatic or mild disease, but regulators remain high in those with more severe outcomes, with elevations in FHR2 over baseline levels in this group. These data support the hypothesis that elevation of circulating levels of the FHR family of proteins could predict disease severity in COVID-19 patients, and that the duration of elevation (or lack of immune activation resolution) may be partly responsible for driving poor outcomes in COVID-19.
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Affiliation(s)
- Anna L. Tierney
- Division of Cardiovascular Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Stoller Biomarker Discovery Centre and Division of Cancer Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Wajd Mohammed Alali
- Stoller Biomarker Discovery Centre and Division of Cancer Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Thomas Scott
- Stoller Biomarker Discovery Centre and Division of Cancer Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Karen S. Rees-Unwin
- Stoller Biomarker Discovery Centre and Division of Cancer Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | | | - Simon J. Clark
- Institute for Opthalmic Research is based at Eberhard Karls University of Tubingen, Tubingen, BW, Germany
- University Eye Clinic, Eberhard Karls University of Tubingen, Tubingen, BW, Germany
- Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, United Kingdom
| | - Richard D. Unwin
- Stoller Biomarker Discovery Centre and Division of Cancer Sciences, School of Medicine, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
- *Correspondence: Richard D. Unwin,
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Abstract
Plasma and serum are rich sources of proteins that are commonly used for clinical proteome profiling and biomarkers discovery. However, high-throughput plasma proteome profiling and quantitative analysis using mass spectrometry are challenging because of the large dynamic range of protein abundance and complexity. To overcome these challenges, we developed a convenient high-throughput workflow of depleted plasma using the 4D-Proteomics feature of the Bruker timsTOF Pro mass spectrometer with data-dependent (PASEF) and data-independent acquisition (diaPASEF) method that can potentially be used in a clinical proteome profiling and biomarker discoveries. This workflow is robust, optimal for high throughput, high proteome depth, and is reproducible. In our sample preparation steps, we used immuno-depletion steps to remove high-abundance plasma proteins, and without any further cleanup steps, we can use depleted plasma samples directly for enzymatic digestion. Immuno-depletion steps and 4D-Proteomics features of timsTOF Pro increase the plasma proteome depth, and accuracy with the identification of >800 protein groups.
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Affiliation(s)
- Rajesh Kumar Soni
- Proteomics and Macromolecular Crystallography Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, NY, USA.
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Naryzhny S, Ronzhina N, Zorina E, Kabachenko F, Klopov N, Zgoda V. Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers. Int J Mol Sci 2022; 23:ijms231911113. [PMID: 36232415 PMCID: PMC9569744 DOI: 10.3390/ijms231911113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/16/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.
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Affiliation(s)
- Stanislav Naryzhny
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
- Correspondence: ; Tel.: +7-911-176-4453
| | - Natalia Ronzhina
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
| | - Elena Zorina
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
| | - Fedor Kabachenko
- Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
| | - Nikolay Klopov
- Petersburg Institute of Nuclear Physics (PNPI) of National Research Center “Kurchatov Institute”, 188300 Gatchina, Russia
| | - Victor Zgoda
- Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia
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Nishibori M. Novel aspects of sepsis pathophysiology: NETs, plasma glycoproteins, endotheliopathy and COVID-19. J Pharmacol Sci 2022; 150:9-20. [PMID: 35926948 DOI: 10.1016/j.jphs.2022.06.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/02/2022] [Accepted: 06/07/2022] [Indexed: 12/13/2022] Open
Abstract
In 2016, sepsis was newly defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis remains one of the crucial medical problems to be solved worldwide. Although the world health organization has made sepsis a global health priority, there remain no specific and effective therapy for sepsis so far. Indeed, over the previous decades almost all attempts to develop novel drugs have failed. This may be partly ascribable to the multifactorial complexity of the septic cascade and the resultant difficulties of identifying drug targets. In addition, there might still be missing links among dysregulated host responses in vital organs. In this review article, recent advances in understanding of the complex pathophysiology of sepsis are summarized, with a focus on neutrophil extracellular traps (NETs), the significant role of NETs in thrombosis/embolism, and the functional roles of plasma proteins, histidine-rich glycoprotein (HRG) and inter-alpha-inhibitor proteins (IAIPs). The specific plasma proteins that are markedly decreased in the acute phase of sepsis may play important roles in the regulation of blood cells, vascular endothelial cells and coagulation. The accumulating evidence may provide us with insights into a novel aspect of the pathophysiology of sepsis and septic ARDS, including that in COVID-19.
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Shahinian JH, Hauser-stadler CB, Walter T, Discher P, Steenbuck ID, Schilling O, Czerny M. Acute, Chronic, and Treated Aortic Diseases Present Distinguishable Serum Proteome Fingerprints with Protein Profiles That Correlate with Disease Severity. Biomedicines 2022; 10:2103. [PMID: 36140204 PMCID: PMC9495769 DOI: 10.3390/biomedicines10092103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/14/2022] [Accepted: 08/22/2022] [Indexed: 11/16/2022] Open
Abstract
Aortic diseases are a rare but potentially life-threatening condition. We present a serum proteomic study for a spectrum of aortic diseases including thoracic aortic aneurysms (n = 11), chronic dissections (n = 9), acute aortic dissections (n = 11), and surgically treated dissections (n = 19) as well as healthy controls (n = 10) and patients of coronary heart disease (n = 10) to represent non-aortic cardiovascular disease. In total, we identified and quantified 425 proteins across all 70 samples. The different aortic diseases represented distinguishable proteome profiles. We identified protein clusters that positively or negatively correlate with disease severity, including increase of cytosolic tissue leakage proteins and decrease of components of the coagulation and complement system. Further, we identified a serum proteome fingerprint of acute aortic dissections, consisting, among others, of enriched inflammatory markers such as C-reactive protein and members of the S100 protein family. The study underlines the applicability of serum proteomics for the investigation of aortic diseases and highlights the possibility to establish disease-specific prognostic markers.
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Gao J, He J, Zhang F, Xiao Q, Cai X, Yi X, Zheng S, Zhang Y, Wang D, Zhu G, Wang J, Shen B, Ralser M, Guo T, Zhu Y. Integration of protein context improves protein-based COVID-19 patient stratification. Clin Proteomics 2022; 19:31. [PMID: 35953823 PMCID: PMC9366758 DOI: 10.1186/s12014-022-09370-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 07/30/2022] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19. METHODS We performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort. RESULTS Besides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type. CONCLUSION Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.
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Affiliation(s)
- Jinlong Gao
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Jiale He
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Fangfei Zhang
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Qi Xiao
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Xue Cai
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Xiao Yi
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Siqi Zheng
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Ying Zhang
- grid.268099.c0000 0001 0348 3990Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang China
| | - Donglian Wang
- grid.268099.c0000 0001 0348 3990Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang China
| | - Guangjun Zhu
- grid.268099.c0000 0001 0348 3990Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang China
| | - Jing Wang
- grid.268099.c0000 0001 0348 3990Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang China
| | - Bo Shen
- grid.268099.c0000 0001 0348 3990Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang China
| | - Markus Ralser
- grid.451388.30000 0004 1795 1830Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK ,grid.6363.00000 0001 2218 4662Department of Biochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Tiannan Guo
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Yi Zhu
- grid.494629.40000 0004 8008 9315Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
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Richard VR, Gaither C, Popp R, Chaplygina D, Brzhozovskiy A, Kononikhin A, Mohammed Y, Zahedi RP, Nikolaev EN, Borchers CH. Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning. Mol Cell Proteomics 2022; 21:100277. [PMID: 35931319 PMCID: PMC9345792 DOI: 10.1016/j.mcpro.2022.100277] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 07/05/2022] [Accepted: 07/27/2022] [Indexed: 01/18/2023] Open
Abstract
The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.
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Key Words
- acd, acid citrate dextrose
- acn, acetonitrile
- auc, area under the receiver operating characteristic curve
- bqc19, biobanque quebecoise de la covid-19
- bsa, bovine serum albumin covid-19
- cptac, clinical proteomic tumor analysis consortium
- dtt, dithiothreitol
- fa, formic acid
- fdr, false discovery rate
- icu, intensive care unit
- lc/mrm-ms, liquid chromatography/multiple reaction monitoring mass spectrometry
- lc-ms, liquid chromatography-mass spectrometry
- lloq, lower limit of quantitation
- lysopc, lysophosphatidylcholine
- maldi, matrix-assisted laser desorption ionization
- meoh, methanol
- ms, mass spectrometry
- pbs, phosphatase buffered saline
- pcr, polymerase chain reaction
- pitc, phenylisothiocyanate
- qc, quality control
- rp-uhplc, reversed phase ultrahigh performance liquid chromatography
- sis, stable-isotope-labeled internal standard
- spe, solid-phase extraction
- svm, support vector machine
- trishcl, tris (hydroxymethyl) aminomethane hydrochloride
- uniprot, the universal protein resource
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Affiliation(s)
- Vincent R. Richard
- Segal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada
| | | | | | - Daria Chaplygina
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Alexander Brzhozovskiy
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Alexey Kononikhin
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands,Genome BC Proteomics Centre, University of Victoria, Victoria, Canada
| | - René P. Zahedi
- Segal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada,Manitoba Centre for Proteomics & Systems Biology, John Buhler Research Centre, University of Manitoba, Winnipeg, Canada,Department of Internal Medicine, University of Manitoba, Winnipeg, Canada
| | - Evgeny N. Nikolaev
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Christoph H. Borchers
- Segal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada,Gerald Bronfman Department of Oncology, Division of Experimental Medicine, Lady Davis Institute for Medical Research, McGill University, Montreal, Canada,Department of Pathology, McGill University, Montreal, Canada,For correspondence: Christoph H. Borchers
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