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Chen H, Li S, Wang J, He S, Wang D, Qian Z, Hu D, Qi F, Hu K, Luo C, Wang J. Simultaneous measurement of the antibody responses against SARS-CoV-2 and its multiple variants by a phage display mediated immuno-multiplex quantitative PCR-based assay. Front Microbiol 2022; 13:968036. [PMID: 36071962 PMCID: PMC9441900 DOI: 10.3389/fmicb.2022.968036] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 07/18/2022] [Indexed: 11/14/2022] Open
Abstract
To combat the continued pandemic of COVID-19, multiplex serological assays have been developed to comprehensively monitor the humoral immune response and help to design new vaccination protocols to different SARS-CoV-2 variants. However, multiplex beads and stably transfected cell lines require stringent production and storage conditions, and assays based on flow cytometry is time-consuming and its application is therefore restricted. Here, we describe a phage display system to distinguish the differences of immune response to antigenic domains of multiple SARS-CoV-2 variants simultaneously. Compared with linear peptides, the recombinant antigens displayed on the phage surface have shown some function that requires the correct folding to form a stable structure, and the binding efficiency between the recombinant phage and existing antibodies is reduced by mutations on antigens known to be important for antigen–antibody interaction. By using Phage display mediated immuno-multiplex quantitative PCR (Pi-mqPCR), the binding efficiency between the antibody and antigens of different SARS-CoV-2 variants can be measured in one amplification reaction. Overall, these data show that this assay is a valuable tool to evaluate the humoral response to the same antigen of different SARS-CoV-2 variants or antigens of different pathogens. Combined with high-throughput DNA sequencing technology, this phage display system can be further applied in monitoring humoral immune response in a large population before and after vaccination.
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Affiliation(s)
- Hanyi Chen
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Shen Li
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Jiali Wang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Siqi He
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Dong Wang
- School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhaohui Qian
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dandan Hu
- Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Fangfang Qi
- Department of Anatomy and Neurobiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Keping Hu
- The Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Andes Antibody Technology Hengshui LL Company, Hengshui City, China
| | - Chenyi Luo
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
- Shenzhen Research Institute, Beijing University of Chinese Medicine, Shenzhen, China
- *Correspondence: Chenyi Luo,
| | - Jianxun Wang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
- Shenzhen Research Institute, Beijing University of Chinese Medicine, Shenzhen, China
- Jianxun Wang,
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Garcia L, Woudenberg T, Rosado J, Dyer AH, Donnadieu F, Planas D, Bruel T, Schwartz O, Prazuck T, Velay A, Fafi-Kremer S, Batten I, Reddy C, Connolly E, McElheron M, Kennelly SP, Bourke NM, White MT, Pelleau S. Kinetics of the SARS-CoV-2 Antibody Avidity Response Following Infection and Vaccination. Viruses 2022; 14:1491. [PMID: 35891471 PMCID: PMC9321390 DOI: 10.3390/v14071491] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 06/29/2022] [Accepted: 07/06/2022] [Indexed: 12/04/2022] Open
Abstract
Serological assays capable of measuring antibody responses induced by previous infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been critical tools in the response to the COVID-19 pandemic. In this study, we use bead-based multiplex assays to measure IgG and IgA antibodies and IgG avidity to five SARS-CoV-2 antigens (Spike (S), receptor-binding domain (RBD), Nucleocapsid (N), S subunit 2, and Membrane-Envelope fusion (ME)). These assays were performed in several cohorts of healthcare workers and nursing home residents, who were followed for up to eleven months after SARS-CoV-2 infection or up to six months after vaccination. Our results show distinct kinetic patterns of antibody quantity (IgG and IgA) and avidity. While IgG and IgA antibody levels waned over time, with IgA antibody levels waning more rapidly, avidity increased with time after infection or vaccination. These contrasting kinetic patterns allow for the estimation of time since previous SARS-CoV-2 infection. Including avidity measurements in addition to antibody levels in a classification algorithm for estimating time since infection led to a substantial improvement in accuracy, from 62% to 78%. The inclusion of antibody avidity in panels of serological assays can yield valuable information for improving serosurveillance during SARS-CoV-2 epidemics.
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Affiliation(s)
- Laura Garcia
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
| | - Tom Woudenberg
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
| | - Jason Rosado
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
| | - Adam H. Dyer
- Tallaght University Hospital, Tallaght, D24 NR0A Dublin, Ireland; (A.H.D.); (S.P.K.)
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Françoise Donnadieu
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
| | - Delphine Planas
- Virus & Immunity Unit, Department of Virology, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (D.P.); (T.B.); (O.S.)
| | - Timothée Bruel
- Virus & Immunity Unit, Department of Virology, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (D.P.); (T.B.); (O.S.)
| | - Olivier Schwartz
- Virus & Immunity Unit, Department of Virology, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (D.P.); (T.B.); (O.S.)
| | - Thierry Prazuck
- CHR d’Orléans, Service de Maladies Infectieuses, 45100 Orléans, France;
| | - Aurélie Velay
- CHU de Strasbourg, Laboratoire de Virologie, CEDEX, 67091 Strasbourg, France; (A.V.); (S.F.-K.)
- Unité Mixte de Recherche Scientifique Immuno-Rhumathologie Moléculaire (IRM UMR-S) 1109, Strasbourg University, Institut National de la Santé et de la Recherche Médicale (INSERM), CEDEX, 67084 Strasbourg, France
| | - Samira Fafi-Kremer
- CHU de Strasbourg, Laboratoire de Virologie, CEDEX, 67091 Strasbourg, France; (A.V.); (S.F.-K.)
- Unité Mixte de Recherche Scientifique Immuno-Rhumathologie Moléculaire (IRM UMR-S) 1109, Strasbourg University, Institut National de la Santé et de la Recherche Médicale (INSERM), CEDEX, 67084 Strasbourg, France
| | - Isabella Batten
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Conor Reddy
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Emma Connolly
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Matt McElheron
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Sean P. Kennelly
- Tallaght University Hospital, Tallaght, D24 NR0A Dublin, Ireland; (A.H.D.); (S.P.K.)
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Nollaig M. Bourke
- Department of Medical Gerontology, School of Medicine, Trinity College Dublin, D02 PN40 Dublin, Ireland; (I.B.); (C.R.); (E.C.); (M.M.); (N.M.B.)
| | - Michael T. White
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
| | - Stéphane Pelleau
- Infectious Diseases Epidemiology and Analytics Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, 75015 Paris, France; (L.G.); (T.W.); (J.R.); (F.D.)
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