Chung J W, Bernhardt R, Pyun J C
Korea Institute for Science and Technology Europe (KIST Europe fGmbH), Stuhlsatzenhausweg 97, 66123 Saarbruecken, Germany.
J Immunol Methods. 2006 Apr 20;311(1-2):178-88. doi: 10.1016/j.jim.2006.02.003. Epub 2006 Mar 6.
A sequential analysis method for the analysis of two analytes was developed using a surface plasmon resonance (SPR) biosensor. A sample with both analytes was introduced into the single sensing region and then each analyte was analyzed sequentially. Two detection models were devised for the samples with the following composition: (1) one target analyte resulting in a sensor response without any label and the other analyte with only additional label, (2) both target analytes requiring additional labels for detection. A standard curve for each model was prepared and applied for sequential analysis of anti-bovine serum albumin (anti-BSA) antibodies and horseradish peroxidase (HRP). The errors of the sequential analysis of Models 1 and 2 were found to be less than 6%, and this method was therefore acceptable for application. No cross-reaction arising from non-specific binding among the participating antigens and antibodies was shown to occur in Models 1 and 2. For optimization of the analyte binding capacity of immunoaffinity (IA), the concentration ratio of the molecular recognition element at the immobilization step was adjusted. Subsequently, from the measurement of the maximum sensor response (R(max)), optimization of the analyte binding capacity could be made. Using Model 2, the feasibility of sequential analysis was demonstrated by detecting levels of human chorionic gonadotropin (hCG) and human albumin (hA) in healthy human urine, since both proteins are known to be related to abortion and preterm delivery during early pregnancy.
利用表面等离子体共振(SPR)生物传感器开发了一种用于分析两种分析物的顺序分析方法。将含有两种分析物的样品引入单个传感区域,然后依次分析每种分析物。针对具有以下组成的样品设计了两种检测模型:(1)一种目标分析物在无任何标记的情况下产生传感器响应,另一种分析物仅带有额外标记;(2)两种目标分析物都需要额外标记才能进行检测。为每个模型制备了标准曲线,并将其应用于抗牛血清白蛋白(anti-BSA)抗体和辣根过氧化物酶(HRP)的顺序分析。发现模型1和模型2顺序分析的误差小于6%,因此该方法可接受应用。在模型1和模型2中未显示出参与抗原和抗体之间非特异性结合产生的交叉反应。为了优化免疫亲和(IA)的分析物结合能力,调整了固定步骤中分子识别元件的浓度比。随后,通过测量最大传感器响应(R(max)),可以实现分析物结合能力的优化。使用模型2,通过检测健康人尿液中人绒毛膜促性腺激素(hCG)和人白蛋白(hA)的水平,证明了顺序分析的可行性,因为已知这两种蛋白质都与早期妊娠期间的流产和早产有关。