Microscale Bioseparations Laboratory and Biomedical Engineering Department, Rochester Institute of Technology, Rochester, NY 14623, USA.
Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA.
Biosensors (Basel). 2020 Oct 19;10(10):148. doi: 10.3390/bios10100148.
The increased concern regarding emerging pathogens and antibiotic resistance has drawn interest in the development of rapid and robust microfluidic techniques to analyze microorganisms. The novel parameter known as the electrokinetic equilibrium condition (EEEC) was presented in recent studies, providing an approach to analyze microparticles in microchannels employing unique electrokinetic (EK) signatures. While the EEEC shows great promise, current estimation approaches can be time-consuming or heavily user-dependent for accurate values. The present contribution aims to analyze existing approaches for estimating this parameter and modify the process into an accurate yet simple technique for estimating the EK behavior of microorganisms in insulator-based microfluidic devices. The technique presented here yields the parameter called the electrokinetic equilibrium condition (eEEEC) which works well as a value for initial approximations of trapping conditions in insulator-based EK (iEK) microfluidic systems. A total of six types of microorganisms were analyzed in this study (three bacteria and three bacteriophages). The proposed approach estimated eEEEC values employing images of trapped microorganisms, yielding high reproducibility (SD 5.0-8.8%). Furthermore, stable trapping voltages (sTVs) were estimated from eEEEC values for distinct channel designs to test that this parameter is system-independent and good agreement was obtained when comparing estimated sTVs vs. experimental values (SD 0.3-19.6%). The encouraging results from this work were used to generate an EK library of data, available on our laboratory website. The data in this library can be used to design tailored iEK microfluidic devices for the analysis of microorganisms.
人们越来越关注新出现的病原体和抗生素耐药性，这促使人们热衷于开发快速而强大的微流控技术来分析微生物。最近的研究提出了一个新的参数，称为电动平衡条件（EEEC），为在微通道中分析微粒提供了一种利用独特电动（EK）特征的方法。虽然 EEEC 显示出巨大的潜力，但目前的估计方法可能需要大量时间或高度依赖用户才能获得准确的值。本研究旨在分析现有的 EEEC 估计方法，并将该过程修改为一种准确而简单的技术，用于估计基于绝缘体的微流控装置中微生物的 EK 行为。这里提出的技术产生了一个称为电动平衡条件（eEEEC）的参数，它可以很好地作为基于绝缘体的电动（iEK）微流控系统中捕获条件的初始近似值。本研究共分析了六种类型的微生物（三种细菌和三种噬菌体）。该方法通过捕获微生物的图像来估计 eEEEC 值，具有较高的重现性（SD 5.0-8.8%）。此外，还从 eEEEC 值估计了不同通道设计的稳定捕获电压（sTV），以测试该参数是否与系统无关，并在比较估计的 sTV 与实验值时获得了良好的一致性（SD 0.3-19.6%）。这项工作的令人鼓舞的结果被用来生成一个可在我们的实验室网站上获得的 EK 数据库。该库中的数据可用于设计针对微生物分析的定制化 iEK 微流控装置。
