Bovine serum albumin as a molecular sensor for the discrimination of complex metabolite samples.
Bovine serum albumin as a molecular sensor for the discrimination of complex metabolite samples.
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DOI：
10.1016/j.aca.2014.01.058
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发表时间：
2014-03
影响因子：
6.2
通讯作者：
Timothy Hamerly;Joshua Heinemann;Monika Tokmina-Lukaszewska;E. Lusczek;K. Mulier;G. Beilman;B. Bothner
中科院分区：
文献类型：
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作者：
Timothy Hamerly;Joshua Heinemann;Monika Tokmina-Lukaszewska;E. Lusczek;K. Mulier;G. Beilman;B. Bothner
探讨了血清白蛋白（SA）作为一种广泛适用的分子传感器的潜力，以建立一种快速分析复杂代谢物样品的方法。SA是一种在血液中以高浓度存在的蛋白质，其运输多种化合物，包括脂肪酸、激素和药物。牛直系同源物（BSA）作为分子传感器的有效性进行了测试，通过分析池的小分子结合的蛋白质后，简单的培养与复杂的流体的生物来源。作为初步测试，三种红葡萄酒很容易区分。用四种白色葡萄酒作进一步分析也显示出明显的分离。在使用尿液进行的第二次分析中，将失血性休克动物与一组经口给药的对照动物分开。时间过程分析表明，也可以使用该测定法跟踪损伤恢复。这一发现意义重大，因为目前还没有预测休克发作的方法或生物标志物。样品的比较是基于BSA选择性结合的化合物的液相色谱质谱（LCMS）分析。蛋白质选择后的样品分析显示，通过主成分分析（PCA），复杂性显著降低，组的分离清晰。这些结果显示了使用运载蛋白作为分子传感器用于筛选复杂样品而不需要样品组成或浓度的先验知识的潜力，并且可以简化生物标志物的阐明。
The potential for using serum albumin (SA) as a broadly applicable molecular sensor was explored in an effort to develop a method for rapid analysis of complex metabolite samples. SA is a protein present at high concentration in blood, which transports a diverse set of compounds including fatty acids, hormones, and drugs. The effectiveness of the bovine ortholog (BSA) as a molecular sensor was tested by analyzing the pool of small molecules bound to the protein after a brief incubation with complex fluids of biological origin. As an initial test, three varietals of red wine were readily distinguished. Further analysis using four varietals of white wine also showed clear separation. In a second analysis using urine, animals in hemorrhagic shock were separated from a group of comparably treated controls. A time course analysis showed that recovery from injury could also be followed using the assay. This finding is significant as there currently is no method or biomarker for predicting the onset of shock. Comparison of samples was based on liquid chromatography mass spectrometry (LCMS) analysis of compounds selectively bound by BSA. Analysis of the samples after protein selection revealed a significant reduction in complexity and clear separation of groups by Principle Component Analysis (PCA). These results show the potential for using cargo-carrying proteins as molecular sensors for screening complex samples without the need for prior knowledge of sample composition or concentration and may streamline elucidation of biomarkers.