Presented here is the first continuous separation of microparticles and cells of similar characteristics employing linear and nonlinear electrokinetic phenomena in an insulator-based electrokinetic (iEK) system. By utilizing devices with insulating features, which distort the electric field distribution, it is possible to combine linear and nonlinear EK phenomena, resulting in highly effective separation schemes that leverage the new advancements in nonlinear electrophoresis. This work combines mathematical modeling and experimentation to separate four distinct binary mixtures of particles and cells. A computational model with COMSOL Multiphysics was used to predict the retention times (tR,p) of the particles and cells in iEK devices. Then, the experimental separations were carried out using the conditions identified with the model, where the experimental retention time (tR,e) of the particles and cells was measured. A total of four distinct separations of binary mixtures were performed by increasing the level of difficulty. For the first separation, two types of polystyrene microparticles, selected to mimic Escherichia coli and Saccharomyces cerevisiae cells, were separated. By leveraging the knowledge gathered from the first separation, a mixture of cells of distinct domains and significant size differences, E. coli and S. cerevisiae, was successfully separated. The third separation also featured cells of different domains but closer in size: Bacillus cereus versus S. cerevisiae. The last separation included cells in the same domain and genus, B. cereus versus Bacillus subtilis. Separation results were evaluated in terms of number of plates (N) and separation resolution (Rs), where Rs values for all separations were above 1.5, illustrating complete separations. Experimental results were in agreement with modeling results in terms of retention times, with deviations in the 6–27% range, while the variation between repetitions was between 2 and 18%, demonstrating good reproducibility. This report is the first prediction of the retention time of cells in iEK systems.
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Determination of the Empirical Electrokinetic Equilibrium Condition of Microorganisms in Microfluidic Devices
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 empirical 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.
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- Award ID(s):
- 1705895
- NSF-PAR ID:
- 10289175
- Date Published:
- Journal Name:
- Biosensors
- Volume:
- 10
- Issue:
- 10
- ISSN:
- 2079-6374
- Page Range / eLocation ID:
- 148
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/bios10100148
