simultaneous on-chip dc dielectrophoretic cell separation and quantitative separation performance...

Simultaneous On-Chip DC Dielectrophoretic Cell Separation andQuantitative Separation Performance CharacterizationJiashu Sun,†,‡ Yandong Gao,† Richard J. Isaacs,§ Kimberly C. Boelte,∥ P. Charles Lin,∥,⊥

Erik M. Boczko,*,§ and Deyu Li*,†

†Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee 37235-1592, United States‡CAS Key Lab for Biological Effects of Nanomaterials and Nanosafety, National Center for NanoScience and Technology, Beijing, PRChina, 100190§Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee 37232, United States∥Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States⊥Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, United States

*S Supporting Information

ABSTRACT: Through integration of a MOSFET-based microfluidic Coulter counter with a dc-dielectrophoretic cell sorter, wedemonstrate simultaneous on-chip cell separation and sizing with three different samples including 1) binary mixtures ofpolystyrene beads, 2) yeast cells of continuous size distribution, and 3) mixtures of 4T1 tumor cells and murine bone marrowcells. For cells with continuous size distribution, it is found that the receiver operator characteristic analysis is an ideal method tocharacterize the separation performance. The characterization results indicate that dc-DEP separation performance degrades asthe sorting throughput (cell sorting rate) increases, which provides insights into the design and operation of size-basedmicrofluidic cell separation.

Microfluidic cell separation has attracted significantattention because of its important applications in

different microfluidic based assays. Different schemes havebeen developed to separate cells according to their size, density,and/or dielectric property.1,2 Size-based microfluidic cellseparation techniques, in particular, have attracted a lot ofinterest because the most commonly used conventional cellseparation techniques, centrifugation and microfiltration,separate cells by size.In the past decade, various size-based microfluidic cell

separation schemes have been developed,3−18 which, in general,can be classified into two categories: passive separation andactive separation.3,4 Passive separation usually involvesmanipulation of cells in a laminar flow field or filtration witharrays of different size microsieves.5−8 For example, using thedeterministic lateral displacement of cells in a laminar flow fieldcomposed of periodic flow pattern generated with staggeredmicropost arrays, Davis et al. demonstrated separation of white

blood cells from red blood cells and plasma.5 With massivelyparallel microsieves, Mohamed et al. showed that culturedneuroblastoma cells could be filtered out from other smallerwhole blood cells.6 Active cell separation techniques involveexternal force fields acting on cells. For example, several reportshave been published to show that both alternating current (ac)and direct current (dc) dielectrophoretic (DEP) forces couldbe used to sort particles and cells by size.9−14 In addition,optical, acoustic, and magnetic forces have all been integratedwith microfluidic circuits to realize size-based cell-separa-tion.15−18

As pointed out in two recent reviews,1,2 most microfluidicseparation research published so far has been concerned withproof-of-concept demonstration, often with user-defined binary

Received: December 3, 2011Accepted: January 9, 2012Published: January 9, 2012

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mixtures or preconditioned biological samples. For size-basedseparation, the binary mixture of particles is often composed ofparticles or cells of significant size difference.19,20 Theseparation performance of the binary mixture of different sizecells or particles has often been verified qualitatively by visualobservation.21 More quantitative characterization has beendone with Coulter counters post separation, which requiressample transfer from the microfluidic chip to the Coultercounter, involving additional complication during the transferprocess.8,17 A real-time postseparation analyzing system canprovide quantitative analyses of how well the separationperformance is and how the separation performance varies asa function of sorting throughput, which can provide insightsinto the device design and the best operation protocol. Moreimportantly, real biological samples often contain cells ofcontinuous size distribution, and, therefore, the parametersused for simple binary mixtures may not be adequate tocharacterize the separation performance for complex biologicalsamples.Here we present a microfluidic chip with integrated dc-DEP

size-based cell separation and sizing functions to performsimultaneous cell separation and performance characterization.Experiments have been performed with three different samples,binary mixtures of 1.97 and 4.84 μm-diameter polystyrenebeads, yeast cells with continuous size distribution, andmixtures of 4T1 tumor and bone marrow cells. For sampleswith continuous cell size distribution, we adopted the receiveroperator characteristic (ROC) analysis22 to quantitativelycharacterize the separation performance. ROC analysis is thenatural choice to quantify the separation of two populationdistributions, which can help to assess the size-based separationperformance as a function of operational parameters such as thesorting throughput in terms of cell sorting rate. The analysisresult provides insights for design and operation optimizationof size-based cell sorting schemes.

■ EXPERIMENTAL METHODSDesign of the dc-DEP Cell Sorters. DEP force is

proportional to the gradient of the square of the magnitudeof the electric field intensity.23−26 To create an electric fieldintensity gradient, oil droplets and square hurdles have beenused to induce a nonuniform electric field in microfluidicchannels.19−21 In the current design, we choose to use a 60degree triangle hurdle as shown in Figure 1 based on thefollowing two considerations: (1) with a sharper trianglehurdle, the induced electric field intensity gradient is stronger,which will lead to larger difference of the DEP force ondifferent size particles; (2) the design, with a shorter narrowregion than those with an oil droplet or a square hurdle,significantly reduces the duration that cells/particles experiencestrong electric fields. This is important for separation of fragilecells that cannot survive high electric field intensity for anextended period.In the operation, cells/particles are fed into the microfluidic

sorter through branch B2, in which they are squeezed to flowalong the left wall of the triangle hurdle by the buffer flowing inbranch B1. The electroosmostic flow in the channels is drivenby electric potentials applied to the boundary of each branch.The electric field intensity gradient in branch B1 and B2 is verysmall so the DEP effect is negligible before the cell/particletranslocates the triangle hurdle, where the cell/particleexperiences a strong DEP force generated by the highlynonuniform electric field in the transverse direction. The

interaction of particles/cells with the nonuniform electric fieldwould induce a negative DEP force, and this induced negativeDEP force would point away from the triangle surface and pushthe particle/cell away from the triangle hurdle. Different sizecells/particles experience different DEP forces, with larger DEPforces on larger cells/particles, which push them further awayfrom the triangle hurdle than smaller ones. As a result, differentsize cells/particles will be deflected to different branches (B3and B4) after they traverse the tip of the triangle hurdle.For separation of binary mixtures of polystyrene beads or

yeast cells of continuous size distribution, the dimensions of thehorizontal driving channel (branch B1) and the tilted inputchannel (branch B2) are 5.5 mm long and 300 μm wide and 3.5mm long and 60 μm wide, respectively. The 60 degree trianglehurdle forms a narrow gap of 20 μm wide with the top wall,which is connected to branch B3 (1.5 mm long and 450 μmwide) and B4 (1.5 mm long and 300 μm wide). Both branch B3and B4 are connected to the sizing section through two L-shapechannels (branch B3 and B4) of 100 μm wide. All channels are15 μm in height.To separate the mixture of 4T1 tumor cells and murine bone

marrow cells over a broad range of sizes, we enlarge theseparation regime and branch B2, through which the cells arefed into the microfluidic devices. Now the narrowest gapbetween the triangle hurdle and the top channel wall is 30 μm× 50 μm for length and depth and branch B2 has a dimensionof 80 μm × 50 μm for width and depth. Moreover, toinvestigate the cell entrance effect on separation performance,we also introduce an arc-shaped left wall right before theseparation hurdle, in comparison with the straight wall of thetriangle hurdle. All channels are 50 μm in height.

Integration of the Cell Sorter and the MOSFET-BasedCoulter Counter. To realize simultaneous on-chip cellseparation and sizing, the above-described cell separationcircuit is integrated with MOSFET-based microfluidic Coultercounters27−29 as depicted in Figure 1. The sizing sectionconsists of a pair of mirror-symmetric microfluidic circuits, eachof which is a MOSFET-based microfluidic Coulter counter withtwo large microchannels sandwiching a small sensing channel.The sensing channels are 50 μm long, 15 μm wide forpolystyrene particles and yeast sizing, and 50 μm long, 30 μmwide for mammalian cell sizing. The MOSFET-based Coulter

Figure 1. Schematic of the microfluidic channel layout with theseparation and the characterization section.

Analytical Chemistry Article

dx.doi.org/10.1021/ac203212g | Anal. Chem. 2012, 84, 2017−20242018

counter amplifies the percentage modulation of the resistancepulse from the translocation of cells/particles through the smallsensing channel, which can be used to measure the size of thecells/particles.27−29 In the MOSFET-based Coulter counter,the electrical potential downstream of the sensing channel isconnected to the gate of a MOSFET through a verticalmicrochannel (4 mm long and 110 μm wide) connected to wellW5 and W6, respectively. Well W3 is 1.5 mm above thehorizontal channel (branch B3) to provide an additional port toset the electrical potential in the fluidic circuit. The tiltedconnection branch between well W3 and the horizontalchannel is 2 mm long and 800 μm wide. The horizontalbranch B7 is 6 mm long and 500 μm wide. The mirror-symmetric MOSFET-based Coulter counter at the bottom hasthe same dimensions. All channels are 15 μm in height forpolystyrene particles and yeast separation and sizing and 50 μmin height for mammalian cell separation and sizing.Experimental Procedure. The microfluidic devices are

fabricated using standard soft-lithography techniques andassembled by bonding the PDMS layer to a glass substratepost oxygen plasma treatment.30 In the experiment withpolystyrene beads and yeast cells, a buffer solution (composedof 10 mM sodium chloride and 10 mM phosphate, pH 7.2) wasloaded into the eight wells of the microfluidic device. Platinumelectrodes were submerged into each well to connect the fluidiccircuits to the external electronic circuit. Binary mixtures ofpolystyrene beads (1.97 and 4.84 μm in diameter) or yeastcolony were then loaded into well W2. Two DC power supplies(Keithley 6487, Keithley Instruments Inc.) were used toprovide 120 and 110 V to well W1 and W2, respectively, tointroduce electroosmotic flow. Two relatively low voltages wereapplied to well W3 (10 V) and W4 (20 V) by another twopower supplies (Agilent E-3612A, Agilent Technologies). Anadditional power supply (Agilent E-3617A, Agilent Technolo-gies) was used to supply a constant source-drain bias (0.15 V)to induce the MOSFET drain current. A negative voltage

ranging from −8 V to −18 V was applied to well W7 or W8 toensure that the MOSFET (2N7000 N-channel FET, FairchildSemiconductor) worked in the subthreshold regime. TheMOSFET drain current was measured by a current preamplifier(Keithley 428, Keithley Instruments Inc.), which wasconditioned by a low-pass filter (SR 560, Stanford ResearchSystems) with a cutoff frequency of 100 Hz and a 50/60 Hznoise eliminator (Hum bug noise eliminator, Quest ScientificInstruments Inc.) before it was fed into the digital dataacquisition system. The ground terminals of the power supplies,the current preamplifier, low-pass filter, and the digital dataacquisition system were all connected to the same ground line.In this manner, the fluidic and electric circuits were commonlygrounded. In some experiments, the particle motion wasmonitored using an inverted optical microscope (Nikon EclipseTE-2000U, Nikon Corp.) and recorded by a CCD camera(Nikon digital sight DS-U1, Nikon Corp.). The frame rate wasset to be 9.8 frames per second.Similarly, in the experiment with mammalian cells, DMEM

medium, a commonly used medium for culturing mammaliancells, was first filled into the microfluidic device, followed byloading 4T1 tumor and bone marrow cell mixtures into wellW2. The separation of 4T1 tumor and bone marrow cells wasperformed with the applied voltages of 150 V to well W1, 100 Vto well W2, 15.1 V to well W3, 34.7 V to well W4, −12.51 V towell W7, and −66.2 V to well W8.

■ RESULTS AND DISCUSSION

Separation of Binary Polystyrene Beads. Since quite afew microfluidic separation schemes are demonstrated withbinary mixtures, we first applied the device to sort a binarymixture of polystyrene beads (1.97 and 4.84 μm in diameter)and quantitatively characterize the separation performance. Theseparation was conducted at two different throughputs withbead sorting rates of 0.485 beads/s and 0.778 beads/s,respectively, by altering the bead concentration (6.5 × 106

Figure 2. (a) The binary mixture (1.97 and 4.84 μm in diameter polystyrene beads) separation images from superimposing 1 min consecutiveimages of the moving beads at a high bead sorting rate −0.778 beads/s. (b) The separation images at a lower bead sorting rate −0.485 beads/s underthe same experimental conditions. (c) The MOSFET drain current of the upper sensing channel containing mostly 4.84 μm polystyrene beads (withone 1.97 μm bead). (d) The MOSFET drain current of the lower sensing channel containing mostly 1.97 μm polystyrene beads (with one 4.84 μmbead).



beads/mL and 1 × 107 beads/mL) in the binary bead mixture.The trajectories of the moving beads at different bead sortingrates were obtained by superimposing multiple consecutiveimage frames within 1 min using Adobe Photoshop CS3(Adobe Systems) (Figure 2a,b). The figures show that after themixture of 1.97 and 4.84 μm diameter polystyrene beads flowthrough the narrow gap between the triangle hurdle and thechannel wall, the single stream of beads mixture splits intomultiple streams and are collected into two branches (B3 andB4). Most 4.84 μm polystyrene beads flow into branch B3,while most 1.97 μm polystyrene beads flow into branch B4.Even though Figure 2a,b qualitatively shows that our design

of the dc-DEP scheme can separate the beads effectively, it isdifficult to determine quantitatively how well the separation is.The integrated MOSFET-based microfluidic Coulter counters,however, can provide quantitative data of the separationperformance. Our previous studies27−29 show that theMOSFET-based microfluidic Coulter counter can detect beador cell volume with a high sensitivity, and the MOSFET-draincurrent modulation is directly proportional to the volume ratioof the bead/cell to the sensing channel. Figure 2c,d showssnapshots of the measured MOSFET drain current of the upper(Figure 2c) and lower sensing channels (Figure 2d) as afunction of time. Figure 2c indicates that while most beads flowinto the upper branch B3 are 4.84 μm-diameter beads, there area small number of 1.97 μm-diameter beads also entering thebranch. A similar observation is true for beads entering thelower branch B4, which indicates that the separation is not100%. By counting the number of 1.97 and 4.84 μm beads thattranslocate through each sensing channel over an extended timeperiod, the separation efficiency or purity of the separatedbeads can be obtained. The characterization results are shownin Table 1, which indicate that as the bead sorting rate

decreases from 0.778 to 0.485 beads/s, the purity of the beadsin the upper and lower branch increases from 89.16% to97.35% and from 97.82% to 99.03%, respectively (see theSupporting Information for a confidence analysis). Thecharacterization results show that the separation performancedegrades as the bead sorting rate increases. One possibleexplanation for this finding is that for a higher bead sorting rate,multiple beads can translocate the triangle hurdle at the sametime, resulting in undesirable bead deflection and degradedseparation performance, which we speculate might come frombead−bead or bead-DEP field interactions.10 It is reasonable toimagine that when two beads are close to each other andtranslocate the DEP field at the same time, the bead mightaffect the DEP field and there could be sensible bead−beadinteractions, as discussed in the literature.14 These interactionsmight have a negative effect on the separation result.

Separation and Characterization of Yeast Cells. Forbinary mixtures of beads and cells, it is straightforward to usethe percentage of one type of beads/cells in a population as theparameter to characterize the separation performance. How-ever, for real biological samples, the cells are often ofcontinuous size distribution, and, therefore, it is necessary toconstruct new parameters to characterize the separationperformance. To address this issue, we applied the device toseparate yeast cells (S. cerevisiae strain CEN.PK 113-7D) of acontinuous size distribution under five different sorting rates(0.37 cells/s, 0.9 cells/s, 1.79 cells/s, 2.3 cells/s, and 3.4 cells/s)by adjusting the cell concentration in the buffer (2 × 106 cells/mL, 5 × 106 cells/mL, 1 × 107 cells/mL, 1.5 × 107 cells/mL,and 2 × 107 cells/mL). The volume of each separated yeast cellwas simultaneously acquired by the MOSFET-based micro-fluidic Coulter counters with a lower detection limit of 0.675μm3. It is worth noting that the signal of Coulter counters is notsensitive to cell shape changes but mainly decided by thevolume of each cell. In fact, it has been pointed out31 thatcompared to a sphere of the same volume, an ellipsoid ofrevolution with an axial ratio of 4 to 1 would give rise to a pulsedifference of merely 3%.We chose to work on yeast cells also because of the

important applications of size-based cell separation in yeastbased biological assays and engineering. Currently, because ofthe inherent asymmetry in yeast growth and division, asynchronous cell population (e.g., prepared with a babymachine) decays rapidly and loses cell cycle synchrony after3 cell cycles. It has been shown theoretically that size-basedfiltration could maintain population synchrony for over 30cycles of mitotic divisions as opposed to the current best of 3,32

which is certain to impact studies of cell cycle and cell cycledependent gene regulation as well as industrial applications inwhich product recovery from micro-organisms is cell cycledependent.33

In the experiment, the trajectories of yeast cells separated atdifferent sorting rates were obtained by superimposingconsecutive images, as shown in Figure 3 (a-c). At a lowsorting rate (0.37 cells/s), we observed that larger cells tendedto be deflected into the upper branch while smaller ones tendedto enter the lower branch. As the cell sorting rate increased, wenoticed that the separation performance degraded, as indicatedby more smaller cells entering the upper branch and morelarger cells entering the lower branch. The quantitativecharacterization of each cell volume in each branch isperformed with the downstream MOSFET-based Coultercounter. To obtain more accurate volume data, a calibrationrun with more than two hundred 4.84 μm diameter polystyrenebeads was done to obtain a reference MOSFET drain currentmodulation.29 This is acceptable because the MOSFET-draincurrent modulation is directly proportional to the volume of thecells, as discussed in our previous publications about MOSFET-based microfluidic Coulter counters.27−29 Histograms ofseparated cell volume distributions in the upper and thelower branches for different cell sorting rates are drawn inFigure 3 (d-f) with the statistical analysis results shown in Table2. The number of cells in the histogram plots refers to the totalnumber of cells in both the upper and lower branches. Figure 3(d-f) and Table 2 clearly indicate that the sorting performancedegrades as the cell sorting rate increases.Even though the detailed size distribution and the average

volume of the separated cells present a good picture of howwell the separation performance is, it is desirable to have a

Table 1. Separation Efficiency of the Microfluidic SorterDetermined by the Integrated MOSFET-Based MicrofluidicCoulter Counter

high sorting rate (0.778beads/s)

low sorting rate (0.485beads/s)

upper lower upper lower

time (s) 1500 570 2550 810# of 4.84 μm beads 288 7 257 3# of 1.97 μm beads 35 314 7 306

purity (%) 89.16 97.82 97.35 99.03



single quantitative parameter to characterize the cell separationperformance. We find that the receiver operator characteristic(ROC) method, a powerful approach in statistical analysis,provides an ideal parameter to quantitatively characterize theseparation performance.22 To assess the separation perform-ance, it is necessary to determine to what extent the two sizedistributions overlap with each other, which can be describedelegantly with a parameter, fractional separation, from an ROCanalysis (for details see the Supporting Information).The ROC analysis and resulted fractional separation for

different cell sorting rates have been calculated and shown inFigure 4 and also listed in Table 2. For the ROC analysis,specificity and sensitivity are defined by a threshold position inthe two size distributions being analyzed. The curve in Figure4a is generated by calculating the sensitivity and specificity asthe threshold swept through the two size distributions, with thedotted line representing the values if the two distributionscompletely overlapped. The fractional separation of twodistributions is defined as two times the area under the ROCcurve minus one. Figure 4a shows the ROC curves and thecalculated fractional separation for each cell sorting rate, andFigure 4b plots the fractional separation versus the sorting rate.Along each point of the empiric ROC curve calculated from theyeast separation data (Table 2), a 95% confidence interval forthe sensitivity can be calculated using the Wilson Score methodwith continuity correction.34 This procedure results in thegeneration of error bars in Figure 4b, in which the fractionalseparation for different cell sorting rates is bounded by thelower and the upper confidence limit. Figure 4 indicates that

the fractional separation is 95% at a cell sorting rate of 0.37cells/s, which drops to 55% as the cell sorting rate increases to3.4 cells/s. It is worth noting that the fractional separationdrops rapidly as the cell sorting rate increases from 0.37 to 1.79cells/s, after which the fractional separation only reducesmarginally. Similar to the polystyrene bead case, we speculatethat enhanced cell−cell interaction and cell-electrical fieldinteraction might be responsible for the degraded performanceat higher cell sorting rate. It is difficult to further reduce the cellsorting rate in the experiment because less and less cells can betested in a reasonable time frame to achieve a statisticallymeaningful analysis. However, we expect that the fractional

Figure 3. (a-c) The traces of yeast cells by superimposing 30 s consecutive images of the moving yeast at three different cell sorting rates. (d-f) Thecorresponding histograms of percentage size distributions of yeast cells for the upper branch and the lower branch.

Table 2. Volumes of the Separated Yeast Cells in the Upperand the Lower Wells Determined by the MOSFET-BasedMicrofluidic Coulter Counter

average volume(μm3)

concentration(cells/mL)

sorting rate(cells/s) upper lower

fractionalseparation

2 × 106 0.37 80.04 38.32 95%5 × 106 0.9 77.99 44.42 78%1 × 107 1.79 70.27 44.77 63%1.5 × 107 2.3 65.19 45.52 56%2 × 107 3.4 65.04 45.6 55%

Figure 4. (a) The ROC curves and the calculated fractional separation(FS) for different cell sorting rates. (b) The logistic fit of the FS versusthe cell sorting rate.



separation will approach unity in an asymptotic manner as thecell sorting rate reduces.Arc Design for Separation and Characterization of

Murine Breast Cancer Cells (4T1) and Murine BoneMarrow Cells. While size-based yeast cell separation is ofimportant practical significance, more biomedically relevant cellseparation is on mammalian cells. Therefore, it is of greatinterest to characterize the performance of size-basedseparation of mammalian cells. To test the present separationand characterization scheme for mammalian cells, we appliedthe device to separate and characterize binary mixtures ofmurine breast cancer cells (4T1) and murine bone marrowcells. The device dimension and operation conditions aremodified from those for polystyrene beads and yeast cells, asdiscussed in the Experimental Methods section. Since themammalian cells tended to deposit on the substrate surfaceover time, we used a higher concentration of cells to obtainstatistically meaningful results in a short time period. In theexperiment, we used a mixture with a cell concentration of 3 ×107 cells/mL, which led to a cell sorting rate of 2.37 cells/s.Test runs showed that as a result of these channel dimension

modifications, the buffer from branch B1 could not push thecells well against the left wall of the triangle hurdle, leading topoor cell separation (Figure 5a). This is because for better dc-DEP separation, cells need to enter the separation region alongthe same flow streamline so different DEP forces can separatethem. To compensate for this negative effect of the larger sizeof branch B2, we modified the profile of the left wall of thetriangle hurdle by introducing an arc wall (the designed radiusof the arc structure is 180 μm) to ensure that all cells enter theDEP cell separation region at approximately the same position,as shown in Figure 5b.Figure 5b shows the traces of the 4T1 and bone marrow cells

from superimposing 5.7 s consecutive images. As expected, the4T1 cells, which are larger than the bone marrow cells, aredeflected into the upper branch (B3), while the smaller bonemarrow cells flow into the lower branch (B4). Size character-

ization with the downstream microfluidic Coulter counteryields the cell size distribution based on calibration results frommore than 200 of 9.77 μm-diameter polystyrene beads. Thehistogram of percentage size distributions (Figure 5c) showsthat for the two separate cell populations, there is an overlap inthe size range of 8−15 μm. The ROC analysis, as shown inFigure 5d, yields an 87% fractional separation.For comparison, we have also characterized the size

distribution of 356 4T1 tumor cells and 302 murine bonemarrow cells, respectively, with detailed distributions plotted inthe Supporting Information (Figure S-2). The average diameterof the 4T1 cells is 17.63 μm with a standard deviation of 3.04μm, while the average diameter for the bone marrow cells is8.08 μm with a standard deviation of 1.39 μm. Given that thesize distribution of both the 4T1 and bone marrow cellsapproximately follows normal distribution around the averagecell size, it is interesting that the separated cell population in theupper channel shows a size distribution with double peaks. Atpresent, we could not explain the observed double peaksconclusively. One possible reason could be that the bonemarrow cells could stick together as twins or triplets, whichhave larger sizes and flow into the upper channel. Anotherpotential reason is that some bone marrow cells stick to the4T1 cells and shift the distribution of the 4T1 cells. Thesespeculations are based on our observation that mammalian cellstend to stick together in the experiments. However, to drawsolid conclusions, much more extensive experiments need to bedone. Given the main scope of this paper is to demonstrate thesimultaneous on-chip cell sorting and size characterization andto introduce the ROC analysis to characterize the separationperformance for samples with continuous size distribution, weleave the thorough understanding of the observed double peaksin separated cell population to future research.

Further Discussion. As mentioned in the introduction,microfluidic cell separation has attracted significant attention inthe past decade, and a significant amount of efforts have beendevoted to develop various microfluidic separation techniques

Figure 5. (a-b) The traces of 4T1 breast cancer cells and bone marrow cells via superimposing 5.7 s consecutive images of the moving cells around atriangle (a) and an arc hurdle (b), respectively. (c) The histograms of percentage size distributions for the upper and lower branches. (d) The ROCseparation curve for 4T1 and bone marrow cells, yielding an 87% fractional separation.



including dc-DEP continuous flow separation. The presentedresearch, with integrated microfluidic Coulter counters to sizeeach cell flowing through the sorter, provides an accuratequantitative characterization of the separation performance as afunction of the separation throughput or cell sorting rate. TheROC analysis provides an effective approach to characterize theoverlap between separated cell distributions. These data lead toa new understanding of microfluidic cell separation. While thesizing fluidic circuit can be readily integrated with other size-based microfluidic cell separation schemes, here we brieflycompare the obtained results with other dc-DEP basedmicrofluidic cell separation as this is the separation schemewe adopted in this paper.First of all, as mentioned in the introduction, most published

microfluidic cell separation studies mainly focused ondemonstration of the separation mechanism, only withqualitative, superimposed phase contrast or fluorescent imagesto show the separation of binary particles of significant sizedifference.19−21,35−38 More recent studies tend to present atleast some quantitative analysis of the separation performance.For example, using dc-DEP separation, Zhu et al.39 separated 1and 5 μm polystyrene beads and 3 μm polystyrene beads and4−8 μm yeast cells. Quantitative characterization is onlyprovided for the beads and cell mixture by observing thecollection wells through phase contrast imaging. Thepercentage separation is beyond 90%. However, there is nocharacterization of the size distribution of yeast cells in the twowells and no separation performance as a function of theseparation throughput. Therefore, the presented separationperformance as a function of separation throughput, enabled bythe quantitative characterization and ROC analysis for yeastcolony with a continuous size distribution, provides newinsights into the operation of dc-DEP based cell separation.The MOSFET-based microfluidic Coulter counter circuit,

with the current design parameter and without any furtheroptimization, could have a characterization throughput wellbeyond tens of cells/s. In fact, with further design optimizationsuch as reducing the sensing channel length, together withbetter noise elimination techniques, the characterizationthroughput can easily reach thousands of cells per second. Inthat case, the limitation of the throughput will be mainly fluidicsuch as the maximum flow velocity that cells can survive. Giventhe potential to significantly increase the throughput of theMOSFET-based Coulter counter and the fact that cellseparation performance degrades as the sorting throughputincreases, we do not expect any limitation from the character-ization throughput of the MOSFET-based Coulter counter.

■ SUMMARYIn a summary, we show that by combining a dc-DEP cell sorterand MOSFET-based Coulter counters, simultaneous on-chipsize-based cell separation and quantitative separation perform-ance characterization can be achieved. With the new design ofdc-DEP cell separation, we can significantly reduce the durationduring which cells are exposed to strong electric fields. Inaddition, an arc shape design of the triangle hurdle wall can beintroduced to force the cells to enter the cell separation regionfrom approximately the same position, which is necessary for agood separation result. The integrated MOSFET-based micro-fluidic Coulter counter presents quantitative characterization ofthe size distribution of the separated cells. Results show that fordc-DEP cell separation, the separation performance degrades asthe cell sorting rate increases. For cells with continuous size

distribution, we find that fractional separation, a singleparameter from the ROC analysis, presents an ideal quantitativeparameter reflecting the cell separation performance.

■ ASSOCIATED CONTENT*S Supporting InformationText and Figures S-1 and S-2. This material is available free ofcharge via the Internet at http://pubs.acs.org.

■ AUTHOR INFORMATIONCorresponding Author*E-mail: [email protected] (E.M.B.), [email protected] (D.L.).

■ ACKNOWLEDGMENTSJ.S. and D.L. acknowledge financial support from NSF (CBET-0643583). E.M.B. and R.J.I. were partially supported from NIHR01GM090207.

■ REFERENCES(1) Pamme, N. Lab Chip 2007, 7, 1644−1659.(2) Tsutsui, H.; Ho, C. M. Mech. Res. Commun. 2009, 36, 92−103.(3) Erickson, D.; Li, D. Q. Anal. Chim. Acta 2004, 507, 11−26.(4) Ohno, K.; Tachikawa, K.; Manz, A. Electrophoresis 2008, 29,4443−4453.(5) Davis, J. A.; Inglis, D. W.; Morton, K. J.; Lawrence, D. A.; Huang,L. R.; Chou, S. Y.; Sturm, J. C.; Austin, R. H. Proc. Natl. Acad. Sci.U.S.A. 2006, 103, 14779−14784.(6) Mohamed, H.; McCurdy, L. D.; Szarowski, D. H.; Duva, S.;Turner, J. N.; Caggana, M. IEEE Trans. Nanobiosci. 2004, 3, 251−256.(7) Taylor, J.; Ren, C. L.; Stubley, G. D. Biotechnol. Prog. 2008, 24,981−991.(8) Di Carlo, D.; Edd, J. F.; Irimia, D.; Tompkins, R. G.; Toner, M.Anal. Chem. 2008, 80, 2204−2011.(9) Choi, S.; Park, J. K. Lab Chip 2005, 5, 1161−1167.(10) Doh, I.; Cho, Y. H. Sens. Actuators, A 2005, 121, 59−65.(11) Li, Y. L.; Kaler, K. V. I. S. Anal. Chim. Acta 2004, 507, 151−161.(12) Yang, J.; Huang, Y.; Wang, X. B.; Becker, F. F.; Gascoyne, P. R.C. Anal. Chem. 1999, 71, 911−918.(13) Vykoukal, J.; Vykoukal, D. M.; Freyberg, S.; Alt, E. U.;Gascoyne, P. R. C. Lab Chip 2008, 8, 1386−1393.(14) Kralj, J. G.; Lis, M. T. W.; Schmidt, M. A.; Jensen, K. F. Anal.Chem. 2006, 78, 5019−5025.(15) Grier, D. G. Nature 2003, 424, 810−816.(16) Shi, J.; Huang, H.; Stratton, Z.; Huang, Y.; Huang, T. J. LabChip 2009, 9, 3354−3359.(17) Petersson, F.; Aberg, L.; Sward-Nilsson, A. M.; Laurell, T. Anal.Chem. 2007, 79, 5117−5123.(18) Han, K. H.; Frazier, A. B. IEE Proc. Nanobiotechnol. 2006, 153,67−73.(19) Barbulovic-Nad, I.; Xuan, X. C.; Lee, J. S. H.; Li, D. Q. Lab Chip2006, 6, 274−279.(20) Kang, K. H.; Kang, Y.; Xuan, X.; Li, D. Electrophoresis 2006, 27,694−702.(21) Kang, Y.; Li, D.; Kalams, S. A.; Eid, J. E. Biomed. Microdevices2008, 10, 243−249.(22) Lasko, T. A.; Bhagwat, J. G.; Zou, K. H.; Ohno-Machado, L. J.Biomed. Informatics 2005, 38, 404−415.(23) Pohl, H. A. Dielectrophoresis: the behavior of neutral matter innonuniform electric fields; Cambridge University Press: Cambridge,New York, 1978.(24) Probstein, R. F. Physicochemical hydrodynamics: an introduction,2nd ed.; John Wiley & Sons: New York, 1994.(25) Jones, T. B. Electromechanics of particles; Cambridge UniversityPress: Cambridge; New York, 1995.(26) Morgan, H.; Green, N. G. AC electrokinetics: colloids andnanoparticles; Research Studies Press: Philadelphia, PA, 2003.



http://pubs.acs.org

mailto:[email protected]



(27) Xu, D.; Kang, Y.; Sridhar, M.; Hmelo, A. B.; Feldman, L. C.; Li,D.; Li, D. Appl. Phys. Lett. 2007, 91, 013901.(28) Sridhar, M.; Xu, D. Y.; Kang, Y. J.; Hmelo, A. B.; Feldman, L. C.;Li, D. Q.; Li, D. Y. J. Appl. Phys. 2008, 103, 104701.(29) Sun, J.; Stowers, C. C.; Boczko, E. M.; Li, D. Lab Chip 2010, 10,2986−2993.(30) Sun, J. S.; Vajandar, S. K.; Xu, D. Y.; Kang, Y. J.; Hu, G. Q.; Li,D. Q.; Li, D. Y. Microfluid. Nanofluid. 2009, 6, 589−598.(31) Kubitschek, H. E. In Methods in Microbiology; Ribbons, R. W.,Norris, J. R., Eds.; Academic: London, 1969; p 503.(32) Stowers, C. C.; Robertson, J. B.; Ban, H. J.; Tanner, R. D.;Boczko, E. M. Appl. Biochem. Biotechnol. 2009, 156, 489−505.(33) Stowers, C.; Hackworth, D.; Mischaikow, K.; Gedeon, T.;Boczko, E. J. Biomed. Sci. Eng. 2010, 3, 987−1001.(34) Newcombe, R. G. Stat. Med. 1998, 17, 857−872.(35) Fiedler, S.; Shirley, S. G.; Schnelle, T.; Fuhr, G. Anal. Chem.1998, 70, 1909−1915.(36) Shafiee, H.; Sano, M. B.; Henslee, E. A.; Caldwell, J. L.; Davalos,R. V. Lab Chip 2010, 10, 438−445.(37) Beech, J. P.; Jonsson, P.; Tegenfeldt, J. O. Lab Chip 2009, 9,2698−2706.(38) Hawkins, B. G.; Ezekiel Smith, A.; Syed, Y. A.; Kirby, B. J. Anal.Chem. 2007, 79, 7291−7300.(39) Zhu, J.; Canter, R. C.; Keten, G.; Vedantam, P.; Tzeng, T.-R. J.;Xuan, X. Microfluid. Nanofluid. 2011, 11, 743−752.



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