MultiSero: An Open-Source Multiplex-ELISA Platform for Measuring Antibody Responses to Infection.

Autor: Byrum JR; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Waltari E; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Janson O; 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., Guo SM; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Folkesson J; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Chhun BB; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Vinden J; Infectious Diseases and Immunity Graduate Program, University of California, Berkeley, CA 94720-3370, USA., Ivanov IE; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Forst ML; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA.; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA., Li H; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA., Larson AG; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA., Blackmon L; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Liu Z; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Wu W; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Ahyong V; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Tato CM; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., McCutcheon KM; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Hoh R; Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA., Kelly JD; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA., Martin JN; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA., Peluso MJ; Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA., Henrich TJ; Division of Experimental Medicine, University of California, San Francisco, CA 94110, USA., Deeks SG; Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA., Prakash M; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA.; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA., Greenhouse B; 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., Mehta SB; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA., Pak JE; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA.
Jazyk: angličtina
Zdroj: Pathogens (Basel, Switzerland) [Pathogens] 2023 May 02; Vol. 12 (5). Date of Electronic Publication: 2023 May 02.
DOI: 10.3390/pathogens12050671
Abstrakt: 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.
Databáze: MEDLINE