Photoluminescence–Electrochemiluminescence Dual-Mode Sensor Arrays for Histidine and Its Metabolite Discrimination and Disease Identification

电化学发光 化学 代谢物 咪唑 组氨酸 光致发光 组合化学 色谱法 检出限 生物化学 光电子学 氨基酸 材料科学
作者
Manping Qian,Yonghao Liu,Haonan Huo,Meng Li,Chengxiao Zhang,Honglan Qi
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:96 (1): 446-454 被引量:15
标识
DOI:10.1021/acs.analchem.3c04507
摘要

Histidine (His) and its metabolite analysis is significant due to their vital roles in the diagnosis of diseases. In practical applications, simple and effective detection and discrimination of these metabolic species are still a great challenge due to their highly similar structures. Herein, photoluminescence (PL)-electrochemiluminescence (ECL) dual-mode sensor arrays consisting of a series of sensing elements were proposed for simultaneous quantitation and accurate discrimination of His and its four key metabolites (including histamine, imidazole-4-acetic acid, N-acetylhistamine, and imidazole propionate). The sensing elements of these sensor arrays were constructed by employing two solvent iridium(III) complexes ([Ir(pbz)2(DMSO)Cl] and [Ir(ppy)2(DMSO)Cl], pbz = 3-(2-pyridyl)benzoic acid, ppy = 2-phenylpyridine) with excellent PL and ECL performances as cross-responsive sensing units. Based on diverse coordination abilities of the two complexes with the imidazole group of the five targets, PL and ECL responses of each sensing unit can be enhanced to various degrees, which generate unique fingerprint patterns for the corresponding targets. Through principal component analysis, the multifarious patterns (two-, three-, and four-element sensor arrays) can be transformed into simple visualization modes, from which His and its four key metabolites can be effectively discriminated against each other. Moreover, the quantitation of an individual metabolic species at different concentrations and the recognition of the mixtures with different ratios were also accurately achieved. Notably, His and its four key metabolites in urine can also be successfully discriminated by the as-fabricated sensor arrays, and the patients with kidney diseases can be identified clearly, providing a promising way for disease diagnosis.
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