Multicolor detection of biothiols: machine learning-empowered plasmonic patterns recognition based on anti-etching of gold nanorods
摘要
Biothiols play pivotal roles in maintaining cellular redox homeostasis, where even minor concentration fluctuations can critically affect physiological health. Their structural similarity and dynamic interconversion, however, make the accurate detection of individual species and their metabolic ratios particularly challenging. To address these challenges, we propose a robust multicolorimetric probe based on gold nanorod anti-etching, capable of rapid, sensitive, and reproducible detection and discrimination of multiple ratios of biothiols using a single signal reporter. The modulation of the aspect ratio of AuNRs allows for rapid and visual differentiation of key biothiols—homocysteine (HCY), cysteine (CYS), glutathione (GSH), cystine (CYSS), and glutathione disulfide (GSSG)—as well as enables simultaneous monitoring of their metabolic ratios. The sensing mechanism is governed by a single-electron transfer process between N-bromosuccinimide (NBS) and biothiols, leading to an anti-etching effect that suppresses AuNR oxidation. Linear Discriminant Analysis (LDA) and Partial Least Squares Regression (PLSR) provided qualitative and quantitative evaluations over a wide concentration range (0.1–50 µmol L− 1), yielding detection limits of 0.5–1.3 µmol L− 1 for individual biothiols. Furthermore, linear responses were obtained for biologically relevant biothiol ratios, with detection limits of 0.1–1.8 µmol L− 1. Also, the assay demonstrated excellent reproducibility in real serum samples, with relative standard deviations (RSD% or CV%) of 2.58, 1.03, 1.18, 1.95, and 2.18% for HCY, CYS, GSH, CYSS, and GSSG, respectively, all accompanied with an appropriate recovery percentage. Thus, this AuNR-based multicolorimetric system serves as a practical platform for probing biothiol metabolism and redox balance in clinical evaluation of oxidative stress-associated disorders.
Graphical abstract