1. Ultrasensitive dynamic light scattering immunosensing platform for NT-proBNP detection using boronate affinity amplification.
- Author
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Hu J, Ding L, Chen J, Fu J, Zhu K, Guo Q, Huang X, and Xiong Y
- Subjects
- Antibodies, Monoclonal chemistry, Humans, Limit of Detection, Magnetite Nanoparticles chemistry, Biosensing Techniques methods, Boronic Acids chemistry, Dynamic Light Scattering methods, Immunoassay methods, Natriuretic Peptide, Brain blood, Peptide Fragments blood
- Abstract
Herein, we reported a new dynamic light scattering (DLS) immunosensing technology for the rapid and sensitive detection of glycoprotein N-terminal pro-brain natriuretic peptide (NT-proBNP). In this design, the boronate affinity recognition based on the interaction of boronic acid ligands and cis-diols was introduced to amplify the nanoparticle aggregation to enable highly sensitive DLS transduction, thereby lowering the limit of detection (LOD) of the methodology. After covalently coupling with antibodies, magnetic nanoparticles (MNPs) were employed as the nanoprobes to selectively capture trace amount of NT-proBNP from complex samples and facilitate DLS signal transduction. Meanwhile, silica nanoparticles modified with phenylboronic acid (SiO
2 @PBA) were designed as the crosslinking agent to bridge the aggregation of MNPs in the presence of target NT-proBNP. Owing to the multivalent and fast affinity recognition between NT-proBNP containing cis-diols and SiO2 @PBA, the developed DLS immunosensor exhibited charming advantages over traditional immunoassays, including ultrahigh sensitivity with an LOD of 7.4 fg mL-1 , fast response time (< 20 min), and small sample consumption (1 μL). The DLS immunosensor was further characterized with good selectivity, accuracy, precision, reproducibility, and practicability. Collectively, this work demonstrated the promising application of the designed boronate affinity amplified-DLS immunosensor for field or point-of-care testing of cis-diol-containing molecules., (© 2022. The Author(s).)- Published
- 2022
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