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使用基于硫代碳菁-甘氨酸的荧光传感器阵列进行蛋白质鉴别。

Protein Discrimination Using a Fluorescence-Based Sensor Array of Thiacarbocyanine-GUMBOS.

作者信息

Pérez Rocío L, Cong Mingyan, Vaughan Stephanie R, Ayala Caitlan E, Galpothdeniya Waduge Indika S, Mathaga John K, Warner Isiah M

机构信息

Chemistry Department, Louisiana State University, Baton Rouge, Lousiana 70803, United States.

出版信息

ACS Sens. 2020 Aug 28;5(8):2422-2429. doi: 10.1021/acssensors.0c00484. Epub 2020 Aug 3.

Abstract

Sensitive and selective detection of proteins from complex samples has gained substantial interest within the scientific community. Early and precise detection of key proteins plays an important role in potential clinical diagnosis, treatment of different diseases, and proteomic research. In the study reported here, six different compounds belonging to a group of uniform materials based on organic salts (GUMBOS) have been synthesized using three thiacarbocyanine (TC) dyes and employed as fluorescent sensors. Fluorescence properties of micro- and nanoaggregates of these TC-based GUMBOS formed in phosphate buffer solutions are studied in the absence and presence of seven proteins. Fluorescence response patterns of these TC-based GUMBOS were analyzed by linear discriminant analysis (LDA). The constructed LDA model allowed discrimination of these seven proteins at various concentrations with 100% accuracy. The sensing and discrimination abilities of these TC-based GUMBOS were further evaluated in mixtures of two major proteins, i.e., human serum albumin and hemoglobin. Fluorescence response patterns of these mixtures were analyzed by LDA. This model allowed discrimination of various mixtures with 100% accuracy. Moreover, spiked urine samples were prepared and the responses of these sensors were collected and analyzed by LDA. Remarkably, discrimination of these seven proteins was also achieved with 100% accuracy.

摘要

从复杂样品中灵敏且选择性地检测蛋白质已引起科学界的广泛关注。关键蛋白质的早期精确检测在潜在临床诊断、不同疾病的治疗以及蛋白质组学研究中发挥着重要作用。在本文报道的研究中,使用三种硫代碳菁(TC)染料合成了六种属于基于有机盐的统一材料组(GUMBOS)的不同化合物,并将其用作荧光传感器。研究了在磷酸盐缓冲溶液中形成的这些基于TC的GUMBOS的微米和纳米聚集体在不存在和存在七种蛋白质的情况下的荧光特性。通过线性判别分析(LDA)分析了这些基于TC的GUMBOS的荧光响应模式。构建的LDA模型能够以100%的准确率区分不同浓度的这七种蛋白质。在两种主要蛋白质,即人血清白蛋白和血红蛋白的混合物中进一步评估了这些基于TC的GUMBOS的传感和区分能力。通过LDA分析了这些混合物的荧光响应模式。该模型能够以100%的准确率区分各种混合物。此外,制备了加标尿液样品,并收集了这些传感器的响应并通过LDA进行分析。值得注意的是,同样以100%的准确率实现了对这七种蛋白质的区分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/979b/7460578/db6fdb088494/se0c00484_0001.jpg

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