1. An enzymatic reaction-based SERS saliva analysis microporous array chip for chiral differentiation and high-throughput detection of D-amino acids.
- Author
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Lu F, Li L, Shen K, Qian Y, Zhang P, Yang Y, Zhu Q, Huang Y, Yan C, and Wei W
- Subjects
- Humans, Porosity, Limit of Detection, D-Amino-Acid Oxidase, Proline chemistry, Proline analysis, Stereoisomerism, Alanine chemistry, Alanine analysis, Alanine analogs & derivatives, Hydrogen Peroxide chemistry, Hydrogen Peroxide analysis, Boronic Acids chemistry, Silicon chemistry, Amino Acids analysis, Amino Acids chemistry, Metal Nanoparticles chemistry, High-Throughput Screening Assays methods, Saliva chemistry, Spectrum Analysis, Raman methods, Gold chemistry
- Abstract
A Raman-active boronate modified surface-enhanced Raman scattering (SERS) microporous array chip based on the enzymatic reaction was constructed for reliable, sensitive, and quantitative monitoring of D-Proline (D-Pro) and D-Alanine (D-Ala) in saliva. Initially, 3-mercaptophenylboronic acid (3-MPBA) was bonded to Au-coated Si nanocrown arrays (Au/SiNCA) via Au-S bonding. Following this, H
2 O2 obtained from D-amino acid oxidase (DAAO)-specific catalyzed D-amino acids (D-AAs) further reduced 3-MPBA to 3-hydroxythiophenol (3-HTP) with a new Raman peak at 882 cm-1 . Meanwhile, the original characteristic peak at 998 cm-1 remained unchanged. Therefore, the I882 /I998 ratio increased with increasing content of D-AAs in the sample to be tested, allowing D-AAs to be quantitatively detected. The Au/SiNCA with large-area periodic crown structure prepared provided numerous, uniform "hot spots," and the microporous array chip with 16 detection units was employed as the platform for SERS analysis, realizing high-throughput, high sensitivity, high specificity and high-reliability quantitative detection of D-AAs (D-Pro and D-Ala). The limits of detection (LOD) were down to 10.1 µM and 13.7 µM throughout the linear range of 20-500 µM. The good results of the saliva detection suggested that this SERS sensor could rapidly differentiate between early-stage gastric cancer patients and healthy individuals., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)- Published
- 2024
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