School of Dentistry, Dental Research Institute, University of California, Los Angeles, CA, USA.
Biosens Bioelectron. 2011 Dec 15;30(1):174-9. doi: 10.1016/j.bios.2011.09.014. Epub 2011 Sep 20.
The sensitivity and detection time of an aptamer based biosensor for detecting botulinum neurotoxin (BoNT) depend upon the formation of proper tertiary architecture of aptamer, which closely correlates with the combinatorial effects of multiple types of ions and their concentrations presented in the buffer. Finding the optimal conditions for four different ions at 12 different concentrations, 20,736 possible combinations, by brute force is an extremely laborious and time-consuming task. Here, we introduce a feedback system control (FSC) scheme that can rapidly identify the best combination of components to form the optimal aptamer structure binding to a target molecule. In this study, rapid identification of optimized ionic combinations for electrochemical aptasensor of BoNT type A (BoNT/A) detection has been achieved. Only about 10 iterations with about 50 tests in each iteration are needed to identify the optimal ionic concentration out of the 20,736 possibilities. The most exciting finding was that a very short detection time and high sensitivity could be achieved with the optimized combinational ion buffer. Only a 5-min detection time, compared with hours or even days, was needed for aptamer-based BoNT/A detection with a limit of detection of 40 pg/ml. The methodologies described here can be applied to other multi-parameter chemical systems, which should significantly improve the rate of parameter optimization.
基于适体的生物传感器检测肉毒神经毒素(BoNT)的灵敏度和检测时间取决于适体形成适当的三级结构,这与缓冲液中存在的多种类型离子及其浓度的组合效应密切相关。通过暴力搜索在 12 种不同浓度下的四种不同离子的最佳条件,20,736 种可能的组合,这是一项极其费力和耗时的任务。在这里,我们引入了一种反馈系统控制(FSC)方案,该方案可以快速识别形成最佳适体结构与目标分子结合的最佳组件组合。在这项研究中,实现了快速识别用于检测 A 型肉毒神经毒素(BoNT/A)的电化学适体传感器的最佳离子组合。仅需要大约 10 次迭代,每次迭代大约 50 次测试,就可以从 20,736 种可能性中确定最佳离子浓度。最令人兴奋的发现是,使用优化的组合离子缓冲液可以实现非常短的检测时间和高灵敏度。与基于适体的 BoNT/A 检测的数小时甚至数天相比,仅需 5 分钟的检测时间,检测限为 40 pg/ml。此处描述的方法可以应用于其他多参数化学系统,这应该会显著提高参数优化的速度。