title: An improved method for estimating antibody titers in microneutralization assay using green fluorescent protein.
abstract: Viruses that express reporter genes upon infection have been recently used to evaluate neutralizing antibody responses, where a lack of reporter expression indicates specific virus inhibition. The traditional model-based methods using standard outcome of percent neutralization could be applied to the data from the assays to estimate antibody titers. However, the data produced are sometimes irregular, which can yield meaningless outcomes of percent neutralization that do not fit the typical curves for immunoassays, making automated or semi-high throughput antibody titer estimation unreliable. We developed a type of new outcomes model, which is biologically meaningful and fits typical immunoassay curves well. Our simulation study indicates that the new response approach outperforms the traditional response approach regardless of the data variability. The proposed new response approach can be used in similar assays for other disease models.
authors.affiliation: a Department of Biostatistics and Computational Biology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Hongmei
authors.initials: H
authors.lastname: Yang
authors.affiliation: b Department of Microbiology and Immunology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Steven F
authors.initials: SF
authors.lastname: Baker
authors.affiliation: b Department of Microbiology and Immunology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Mario E
authors.initials: ME
authors.lastname: González
authors.affiliation: b Department of Microbiology and Immunology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: David J
authors.initials: DJ
authors.lastname: Topham
authors.affiliation: b Department of Microbiology and Immunology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Luis
authors.initials: L
authors.lastname: Martínez-Sobrido
authors.affiliation: b Department of Microbiology and Immunology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Zand
authors.affiliation: a Department of Biostatistics and Computational Biology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Jeanne
authors.initials: J
authors.lastname: Holden-Wiltse
authors.affiliation: a Department of Biostatistics and Computational Biology , University of Rochester Medical Center , Rochester , New York , USA.
authors.forename: Hulin
authors.initials: H
authors.lastname: Wu
mesh_terms: D057134:Antibodies, Neutralizing / Q000032:analysis; D000914:Antibodies, Viral / Q000032:analysis; D049452:Green Fluorescent Proteins / Q000737:chemistry*; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000032:analysis; D015233:Models, Statistical; D009010:Monte Carlo Method; D009500:Neutralization Tests / Q000379:methods*
chemical_list: D057134:Antibodies, Neutralizing; D000914:Antibodies, Viral; D019267:Hemagglutinin Glycoproteins, Influenza Virus; D049452:Green Fluorescent Proteins
keywords: Antibody-mediated virus inhibition; four-parameter logistic regression; green fluorescent protein (GFP); hemagglutinin (HA); influenza virus; microneutralization assay; neutralizing antibodies; nonlinear maximization