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Everything's under Control: Maximizing Biosensor Performance through Negative Control Probe Selection

delete2025-02-03
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J
Joseph Bucukovski
B
Benjamin L. Miller *
DOI:10.1021/acs.analchem.4c05854delete
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Abstract

Abstract

En 中文
The rapid rise of label-free biosensing technologies has led to multiple creative strategies for the detection of macromolecules in complex biological solutions for disease state monitoring, drug discovery, and basic science research. A challenge with these techniques is that assays conducted in complex media such as serum suffer from nonspecific binding of matrix constituents. In label-free biosensors, it is virtually impossible to distinguish these nonspecific interactions without the use of a reference (negative control) probe. Only with reference subtraction can the specific binding signal be faithfully reported. To date, this has been a sparsely studied area in the biosensing field. Here, we report an FDA-inspired framework for optimum control probe selection and a systematic analysis for determining the optimal negative control probe given two monoclonal antibody capture probes on photonic ring resonator sensors. Briefly, while the differences in assay performance for IL-17A and CRP were found to be subtle, the best-scoring reference control based on the bioanalytical parameters of linearity, accuracy, and selectivity differed for each analyte. In the IL-17A assay, BSA scored the highest at 83%, while mouse IgG1 isotype control antibody placed a close second with 75%. With respect to the CRP assay, the rat IgG1 isotype control antibody scored the highest at 95%, while anti-FITC scored the second highest at 89%. These results suggest that although isotype-matching to the capture antibody may be tempting, the best on-chip reference control must be optimized on a case-by-case basis using the framework we report.
Keywords:
CONCENTRATION GRADIENTS
LABEL-FREE
SILICON
BINDING

Journal

Analytical Chemistry cover
Analytical Chemistry
IF:
6.7
Papers:
4.7W
Citations:
15.9W

Organization

U
Univ Rochester
Scholars:
1.1K
Papers: 936
Citations: 267