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Gain-Scanning for Protein Microarray Assays.

  • Academic Journal
  • Feng F; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.
    Ataca ST; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.
    Ran M; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.
    Wang Y; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.
    Breen M; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.
    Kepler TB; Department of Microbiology, Boston University School of Medicine, 700 Albany Street, Boston, Massachusetts 02118, United States.; Department of Mathematics & Statistics, Boston University, Boston, Massachusetts 02118, United States.
  • Journal of proteome research [J Proteome Res] 2020 Jul 02; Vol. 19 (7), pp. 2664-2675. Date of Electronic Publication: 2020 Jan 23.
  • English
  • Protein microarrays consist of known proteins spotted onto solid substrates and are used to perform highly multivariate assessments of protein-binding interactions. Human protein arrays are routinely applied to pathogen detection, immune response biomarker profiling, and antibody specificity profiling. Here, we describe and demonstrate a new data processing procedure, gain-scan, in which data were acquired under multiple photomultiplier tube (PMT) settings, followed by data fitting with a power function model to estimate the incident light signals of the array spots. Data acquisition under multiple PMT settings solves the difficulty of determining the single optimal PMT gain setting and allows us to maximize the detection of low-intensity signals while avoiding the saturation of high-intensity ones at the same time. The gain-scan data acquisition and fitting also significantly lower the variances over the detectable range of signals and improve the linear data normalization. The performance of the proposed procedure was verified by analyzing the profiling data of both the human polyclonal serum samples and the monoclonal antibody samples with both technical replicates and biological replicates. We showed that the multigain power function was an appropriate model for describing data acquired under multiple PMT settings. The gain-scan fitting alone or in combination with the linear normalization could effectively reduce the technical variability of the array data and lead to better sample separability and more sensitive differential analysis.
Additional Information
Publisher: American Chemical Society Country of Publication: United States NLM ID: 101128775 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-3907 (Electronic) Linking ISSN: 15353893 NLM ISO Abbreviation: J Proteome Res Subsets: MEDLINE
Original Publication: Washington, D.C. : American Chemical Society, c2002-
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U19 AI117892 United States AI NIAID NIH HHS; U19 AI117905 United States AI NIAID NIH HHS
Keywords: ProtoArray*; data acquisition*; data analysis*; feature identification*; intra-array and inter-array variability*; photomultiplier gain*; protein microarray*
Date Created: 20200114 Date Completed: 20210617 Latest Revision: 20210617
20220902
PMC7783788
10.1021/acs.jproteome.9b00892
31928020

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