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Byrum JR, Waltari E, Janson O, Guo SM, Folkesson J, Chhun BB, Vinden J, Ivanov IE, Forst ML, Li H, Larson AG, Blackmon L, Liu Z, Wu W, Ahyong V, Tato CM, McCutcheon KM, Hoh R, Kelly JD, Martin JN, Peluso MJ, Henrich TJ, Deeks SG, Prakash M, Greenhouse B, Mehta SB, Pak JE. MultiSero: An Open-Source Multiplex-ELISA Platform for Measuring Antibody Responses to Infection. Pathogens 2023; 12:671. [PMID: 37242341 PMCID: PMC10221076 DOI: 10.3390/pathogens12050671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/24/2023] [Accepted: 04/27/2023] [Indexed: 05/28/2023] Open
Abstract
A multiplexed enzyme-linked immunosorbent assay (ELISA) that simultaneously measures antibody binding to multiple antigens can extend the impact of serosurveillance studies, particularly if the assay approaches the simplicity, robustness, and accuracy of a conventional single-antigen ELISA. Here, we report on the development of multiSero, an open-source multiplex ELISA platform for measuring antibody responses to viral infection. Our assay consists of three parts: (1) an ELISA against an array of proteins in a 96-well format; (2) automated imaging of each well of the ELISA array using an open-source plate reader; and (3) automated measurement of optical densities for each protein within the array using an open-source analysis pipeline. We validated the platform by comparing antibody binding to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antigens in 217 human sera samples, showing high sensitivity (0.978), specificity (0.977), positive predictive value (0.978), and negative predictive value (0.977) for classifying seropositivity, a high correlation of multiSero determined antibody titers with commercially available SARS-CoV-2 antibody tests, and antigen-specific changes in antibody titer dynamics upon vaccination. The open-source format and accessibility of our multiSero platform can contribute to the adoption of multiplexed ELISA arrays for serosurveillance studies, for SARS-CoV-2 and other pathogens of significance.
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Affiliation(s)
- Janie R. Byrum
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Eric Waltari
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Owen Janson
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
- EPPIcenter Program, University of California, San Francisco, CA 94143, USA
| | - Syuan-Ming Guo
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Jenny Folkesson
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Bryant B. Chhun
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Joanna Vinden
- Infectious Diseases and Immunity Graduate Program, University of California, Berkeley, CA 94720-3370, USA
| | - Ivan E. Ivanov
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Marcus L. Forst
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Hongquan Li
- Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Adam G. Larson
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Lena Blackmon
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Ziwen Liu
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Wesley Wu
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Vida Ahyong
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Cristina M. Tato
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | | | - Rebecca Hoh
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - J. Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Jeffrey N. Martin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Michael J. Peluso
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - Timothy J. Henrich
- Division of Experimental Medicine, University of California, San Francisco, CA 94110, USA
| | - Steven G. Deeks
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - Manu Prakash
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Bryan Greenhouse
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
- EPPIcenter Program, University of California, San Francisco, CA 94143, USA
| | - Shalin B. Mehta
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - John E. Pak
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
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Jørgensen MM, Sloth JK, Bæk R. Optimization of High-Throughput Multiplexed Phenotyping of Extracellular Vesicles Performed in 96-Well Microtiter Plates. Polymers (Basel) 2021; 13:polym13142368. [PMID: 34301125 PMCID: PMC8309600 DOI: 10.3390/polym13142368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/02/2021] [Accepted: 07/08/2021] [Indexed: 12/25/2022] Open
Abstract
Extracellular vesicles (EVs) are promising biomarkers for several diseases, however, no simple and robust methods exist to characterize EVs in a clinical setting. The EV Array analysis is based on a protein microarray platform, where antibodies are printed onto a solid surface that enables the capture of small EVs (sEVs) by their surface or surface-associated proteins. The EV Array analysis was transferred to an easily handled microtiter plate (MTP) format and a range of optimization experiments were performed within this study. The optimization was performed in a comprehensive analytical setup where the focus was on the selection of additives added to spotting-, blocking-, and incubation buffers as well as the storage of printed antibody arrays under different temperatures from one day to 12 weeks. After ending the analysis, the stability of the fluorescent signal was investigated at different storage conditions for up to eight weeks. The various parameters and conditions tested within this study were shown to have a high influence on each other. The reactivity of the spots was found to be preserved for up to 12 weeks when stored at room temperature and using blocking procedure IV in combination with trehalose in the spotting buffer. Similar preservation could be obtained using glycerol or sciSPOT D1 in the spotting buffers, but only if stored at 4 °C after blocking procedure I. Conclusively, it was found that immediate scanning of the MTPs after analysis was not critical if stored dried, in the dark, and at room temperature. The findings in this study highlight the necessity of performing optimization experiments when transferring an established analysis to a new technological platform.
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Affiliation(s)
- Malene Møller Jørgensen
- Department of Clinical Immunology, Aalborg University Hospital, 9000 Aalborg, Denmark; (J.K.S.); (R.B.)
- Department of Clinical Medicine, Aalborg University, 9000 Aalborg, Denmark
- Correspondence:
| | - Jenni Kathrine Sloth
- Department of Clinical Immunology, Aalborg University Hospital, 9000 Aalborg, Denmark; (J.K.S.); (R.B.)
| | - Rikke Bæk
- Department of Clinical Immunology, Aalborg University Hospital, 9000 Aalborg, Denmark; (J.K.S.); (R.B.)
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Byrum JR, Waltari E, Janson O, Guo SM, Folkesson J, Chhun BB, Vinden J, Ivanov IE, Forst ML, Li H, Larson AG, Wu W, Tato CM, McCutcheon KM, Peluso MJ, Henrich TJ, Deeks SG, Prakash M, Greenhouse B, Pak JE, Mehta SB. multiSero: open multiplex-ELISA platform for analyzing antibody responses to SARS-CoV-2 infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021. [PMID: 34013298 PMCID: PMC8132273 DOI: 10.1101/2021.05.07.21249238] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Serology has provided valuable diagnostic and epidemiological data on antibody responses to SARS-CoV-2 in diverse patient cohorts. Deployment of high content, multiplex serology platforms across the world, including in low and medium income countries, can accelerate longitudinal epidemiological surveys. Here we report multiSero, an open platform to enable multiplex serology with up to 48 antigens in a 96-well format. The platform consists of three components: ELISA-array of printed proteins, a commercial or home-built plate reader, and modular python software for automated analysis (pysero). We validate the platform by comparing antibody titers against the SARS-CoV-2 Spike, receptor binding domain (RBD), and nucleocapsid (N) in 114 sera from COVID-19 positive individuals and 87 pre-pandemic COVID-19 negative sera. We report data with both a commercial plate reader and an inexpensive, open plate reader (nautilus). Receiver operating characteristic (ROC) analysis of classification with single antigens shows that Spike and RBD classify positive and negative sera with the highest sensitivity at a given specificity. The platform distinguished positive sera from negative sera when the reactivity of the sera was equivalent to the binding of 1 ng mL−1 RBD-specific monoclonal antibody. We developed normalization and classification methods to pool antibody responses from multiple antigens and multiple experiments. Our results demonstrate a performant and accessible pipeline for multiplexed ELISA ready for multiple applications, including serosurveillance, identification of viral proteins that elicit antibody responses, differential diagnosis of circulating pathogens, and immune responses to vaccines.
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