Quantifying antibody binding on protein microarrays using microarray nonlinear calibration

We present a microarray nonlinear calibration (MiNC) method for quantifying antibody binding to the surface of protein microarrays that significantly increases the linear dynamic range and reduces assay variation compared with traditional approaches. A serological analysis of guinea pig Mycobacteriu...

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Main Authors: Xiaobo Yu, Garrick Wallstrom, Dewey Mitchell Magee, Ji Qiu, D. Eliseo A. Mendoza, Jie Wang, Xiaofang Bian, Morgan Graves, Joshua LaBaer
Format: Article
Language:English
Published: Taylor & Francis Group 2013-05-01
Series:BioTechniques
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Online Access:https://www.future-science.com/doi/10.2144/000114028
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author Xiaobo Yu
Garrick Wallstrom
Dewey Mitchell Magee
Ji Qiu
D. Eliseo A. Mendoza
Jie Wang
Xiaofang Bian
Morgan Graves
Joshua LaBaer
author_facet Xiaobo Yu
Garrick Wallstrom
Dewey Mitchell Magee
Ji Qiu
D. Eliseo A. Mendoza
Jie Wang
Xiaofang Bian
Morgan Graves
Joshua LaBaer
author_sort Xiaobo Yu
collection DOAJ
description We present a microarray nonlinear calibration (MiNC) method for quantifying antibody binding to the surface of protein microarrays that significantly increases the linear dynamic range and reduces assay variation compared with traditional approaches. A serological analysis of guinea pig Mycobacterium tuberculosis models showed that a larger number of putative antigen targets were identified with MiNC, which is consistent with the improved assay performance of protein microarrays. MiNC has the potential to be employed in biomedical research using multiplex antibody assays that need quantitation, including the discovery of antibody biomarkers, clinical diagnostics with multi-antibody signatures, and construction of immune mathematical models.
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publishDate 2013-05-01
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series BioTechniques
spelling doaj-art-a3953415c7a04f4d8a725e432d431a4e2025-08-20T02:26:03ZengTaylor & Francis GroupBioTechniques0736-62051940-98182013-05-0154525726410.2144/000114028Quantifying antibody binding on protein microarrays using microarray nonlinear calibrationXiaobo Yu0Garrick Wallstrom1Dewey Mitchell Magee2Ji Qiu3D. Eliseo A. Mendoza4Jie Wang5Xiaofang Bian6Morgan Graves7Joshua LaBaer81Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, ArizonaWe present a microarray nonlinear calibration (MiNC) method for quantifying antibody binding to the surface of protein microarrays that significantly increases the linear dynamic range and reduces assay variation compared with traditional approaches. A serological analysis of guinea pig Mycobacterium tuberculosis models showed that a larger number of putative antigen targets were identified with MiNC, which is consistent with the improved assay performance of protein microarrays. MiNC has the potential to be employed in biomedical research using multiplex antibody assays that need quantitation, including the discovery of antibody biomarkers, clinical diagnostics with multi-antibody signatures, and construction of immune mathematical models.https://www.future-science.com/doi/10.2144/000114028microarray nonlinear calibrationnucleic acid programmable protein arraysnn vitro transcription/translationtuberculosis
spellingShingle Xiaobo Yu
Garrick Wallstrom
Dewey Mitchell Magee
Ji Qiu
D. Eliseo A. Mendoza
Jie Wang
Xiaofang Bian
Morgan Graves
Joshua LaBaer
Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
BioTechniques
microarray nonlinear calibration
nucleic acid programmable protein arrays
nn vitro transcription/translation
tuberculosis
title Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
title_full Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
title_fullStr Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
title_full_unstemmed Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
title_short Quantifying antibody binding on protein microarrays using microarray nonlinear calibration
title_sort quantifying antibody binding on protein microarrays using microarray nonlinear calibration
topic microarray nonlinear calibration
nucleic acid programmable protein arrays
nn vitro transcription/translation
tuberculosis
url https://www.future-science.com/doi/10.2144/000114028
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