Skip to main content

The potential of a dielectrophoresis activated cell sorter (DACS) as a next generation cell sorter

Abstract

Originally introduced by H. A. Pohl in 1951, dielectrophoretic (DEP) force has been used as a striking tool for biological particle manipulation (or separation) for the last few decades. In particular, dielectrophoresis activated cell sorters (DACSes) have been developed for applications in various biomedical fields. These applications include cell replacement therapy, drug screening and medical diagnostics. Since a DACS does not require a specific bio-marker, it is able to function as a biological particle sorting tool with numerous configurations for various cells [e.g. red blood cells (RBCs), white blood cells (WBCs), circulating tumor cells, leukemia cells, breast cancer cells, bacterial cells, yeast cells and sperm cells]. This article explores current DACS capabilities worldwide, and it also looks at recent developments intended to overcome particular limitations. First, the basic theories are reviewed. Then, representative DACSes based on DEP trapping, traveling wave DEP systems, DEP field-flow fractionation and DEP barriers are introduced, and the strong and weak points of each DACS are discussed. Finally, for the purposes of commercialization, prerequisites regarding throughput, efficiency and recovery rates are discussed in detail through comparisons with commercial cell sorters (e.g. fluorescent activated and magnetic activated cell sorters).

Background

Since dielectrophoresis was first reported by H. A. Pohl in 1951, it has been employed as a biological particle manipulating tool in various fields (e.g. cell replacement therapy, drug screening, medical diagnostics, particle filtration and microfluidics) [110]. Dielectrophoretic (DEP) phenomena occur when micro/nano-particles in a medium are exposed to a non-uniform electric field, causing polarization for particular particles according to their dielectric property [11, 12]. DEP force is classified into two types according to correlations of the dielectric properties of the particles and medium. Positive DEP (p-DEP) force pulls particles toward a higher electric gradient, and negative DEP (n-DEP) force repels particles away from the higher electric gradient. Therefore, various target cells with different dielectric properties can be manipulated by controlling the medium properties or the input voltage condition. In order to manipulate biological particles, consequently, various dielectrophoresis-based techniques, including DEP trapping, DEP field-flow fractionation (DEP-FFF), traveling wave DEP (TwDEP) force and DEP barrier, are performed within a micro fluid channel [1321]. DEP trapping techniques are mainly used to isolate particles within a still fluid utilizing p-DEP force [2225]. The TwDEP force, DEP-FFF and DEP barrier techniques are realized via angled or vertical electrode pairs, and they are generally implemented with n-DEP force within the micro channel with fluidic flow [2632]. The latter techniques have a striking advantage in terms of throughput since the continuous loading of target cells along the fluidic flow allows for continuous cell separation. Therefore, there have been many studies on the separation of various biological particles, including blood cells [red blood cells (RBCs) and white blood cells (WBCs)], cancer cells [circulating tumor cells (CTCs), leukemia cells and breast cancer cells], submicron particles (bacteria, yeast cells), spermatozoa, stem cells, protein and DNA. Dielectrophoresis activated cell sorters (DACSes) differ from conventional fluorescent activated cell sorters (FACSes) and magnetic activated cell sorters (MACSes) in that they do not require the additional financial and time expenditure necessary for immune-labeling [3338]. In addition, DACSes achieve high separation efficiency owing to the continuous separation in the micro fluid channel. Nevertheless, there are still big hurdles to be overcome with respect to their low throughputs and recovery rates.

In this article, therefore, we explore current DACS capabilities worldwide and look at recent developments intended to overcome particular limitations. First, the basic theories are reviewed. Then, the configurations and characteristics of four representative DACSes are compared, and the strong and weak points of each DACS are discussed. Finally, a commercialization strategy is suggested.

Theory

Dielectrophoresis is a phenomenon that occurs in a non-uniform electric field as a result of polarization, as shown in Fig. 1. DEP force is generated by the interaction between the induced dipoles and a non-uniform electric field [11, 12]. The magnitude and direction of the DEP force is determined by the intrinsic dielectric properties of the particles and the medium. As mentioned, the characteristics of DEP force differ from those of other cell sorters that require an antibody antigen reaction. The magnitude and direction of the DEP force is expressed with the below equation [11, 12, 39].

Fig. 1
figure 1

Schematic diagram of dielectrophoresis. a a particle in a non-uniform electric field experiencing positive DEP force and negative DEP force, b a particle experiencing DEP trapping, c a particle in an electric field with a phase gradient (traveling wave dielectrophoresis), d target and non-target particles experiencing DEP-FFF, e a particle experiencing DEP barrier

$$\varvec{F}_{\text{DEP}} = 2\pi r^{3} \varepsilon_{m} \varepsilon_{0} {\text{Re}}\left[ {f_{CM} } \right]\nabla \left| {\varvec{E}_{rms} } \right|^{2}$$
(1)

where r indicates the radius of the target particle, ε m and ε 0 are the permittivity of the medium and the vacuum state, the term Re[f CM ] indicates the real parts of f CM . f CM is the Clausius–Mossotti (CM) factor, and E rms is the root-mean-square of the electric field. Researchers transform Eq. 1 as necessary to various forms according to technique. For example, in the case of TwDEP force (Fig. 1c), the magnitude of the acting force on a particle can be expressed as [16, 17].

$$\varvec{F}_{TWD} = - \frac{{4\pi \varepsilon_{m} \varepsilon_{0} r^{3} {\text{Im}}\left( {f_{CM} } \right)\varvec{E}^{2} }}{{4\left( {w + g} \right)}}$$
(2)

where the term Im[f CM ] indicates the imaginary part, w is the width of the electrode, and g is the spacing between each electrode. Also, the force of the DEP barrier (Fig. 1e), which is generated between top and bottom electrodes, can be approximated as [19, 40].

$$F_{DEP} = \frac{27}{32}\pi^{2} \varepsilon_{m} {\text{Re}}\left[ {f_{CM} } \right]r^{3} \frac{{U^{2} }}{{a^{3} }}\left[ {1 + O\left( {\frac{{r^{2} }}{{a^{2} }}} \right)} \right]$$
(3)

where U is the applied root-mean-square voltage, and a is the channel height, which is the same as the spacing between the top and bottom electrode pair.

The direction of DEP force depends on the sign of the CM factor in Eq. 1, and it is defined as.

$$f_{CM} = \frac{{\varepsilon_{p}^{*} - \varepsilon_{m}^{*} }}{{\varepsilon_{p}^{*} + 2\varepsilon_{m}^{*} }}$$
(4)
$$\varepsilon _{i}^{*} = \varepsilon _{0} \varepsilon _{i} - j\frac{{\sigma _{i} }}{\omega },where,i = m,p$$
(5)

where \(\varepsilon _{p}^{*}\) and \(\varepsilon _{m}^{*}\) denote the complex permittivity of the particle and the medium, j is the imaginary vector \((j = \sqrt { - 1} )\), σ i is the conductivity of i, and ω is the angular frequency (ω = 2πf) of the applied AC electric field. In the case of Re[f CM ] > 0, particles in a non-uniform AC electric field move toward the higher electric field, and this is called p-DEP force. The blue arrow in Fig. 1a indicates its direction. In the case of Re[f CM ] < 0, particles in an electric field are repelled from the higher electric field, and this is called n-DEP force. The red arrow in Fig. 1a indicates its direction. Hence, the input frequency is an important factor. In particular, the condition in which the frequency at the CM factor is zero is called cross-over frequency. This is expressed as [41, 42].

$$f_{CO} \approx \frac{{\sigma_{m} }}{{\sqrt 2 \pi rC_{mem} }}$$
(6)

where σ m is the medium conductivity, and C mem is the capacitance per unit area of the cell plasma membrane. In other words, when an application employs n-DEP force, the input frequency should be selected properly to ensure that Re[f CM ] < 0. Consequently, DEP force-based cell manipulating tools in the microfluidics can be designed based on the above equations.

DEP trapping

Dielectrophoretic trapping is an application suitable for dealing with submicron particles such as bacteria and viruses. Its concept is shown in Fig. 1b. In order to separate submicron particles, DEP trapping generally harnesses p-DEP force in a still fluid. Suehiro et al. [13] implemented a DEP impedance measurement (DEPIM) employing p-DEP to trap suspended biological cells [e.g. Escherichia coli (E. coli) and Serratia marcescens (Serratia)]. They trapped target cells within a still fluid and washed the non-target cells after agglutinating the target cells by antigen–antibody reaction. Also, they employed interdigitated patterned electrode arrays and trapped target cells spaced between electrodes deposited in parallel. Lapizco-Encinas et al. [43] presented insulator-based (electrodeless) dielectrophoresis (iDEP) to separate live and dead E. coli. In their paper, p-DEP and n-DEP force were selective1y utilized. Since dead cells show much lower DEP mobility than live cells, dielectrophoresis is a more appropriate technique than those using other electrokinetic phenomena. Their DACS was designed to have numerous micron-sized posts, as shown in Fig. 2 (i.e. extruded electrodes). Although DEP trapping is a useful tool to differentiate target particles, it has limitations. Rather than separating biological particles continuously, DEP tapping is a one-shot method. In addition, DEP trapping requires flushing to collect trapped target cells (or wash un-trapped non-target cells). These limitations cause low throughput and recovery rates in DEP tapping-based DACSes. In order to overcome these limitations, transporting techniques (TwDEP force) and particle sorting in a continuous flow (e.g. DEP-FFF) have been proposed [16, 4446].

Fig. 2
figure 2

DEP trapping configuration by Lapizco-Encinas et al. [43]. a Top view of the DACS, b the electric lines being squeezed between the insulating posts

Traveling wave dielectrophoresis

Unlike other DACS techniques, traveling wave dielectrophoresis utilizes an AC electric field with a phase gradient. It is suitable for separating micron-sized particles such as blood cells. The phase shifts induce particle transportation along or against the direction of the travelling wave. For cell separation, it is a more adequate method than DEP trapping because the phase shifts enable particle motion even in a still fluid. Morgan et al. [16] introduced TwDEP force-based cell sorting by employing a multilayered electrode on a large area to achieve high throughput. Although they separated the components of whole blood, the large area of the configuration caused a resistance increase at the microelectrode. Therefore, Choi et al. proposed a unique multilayered bus bar design to deliver an improved TwDEP force-based DACS, as shown in Fig. 3. They exploited a quadrature phase (0°, 90°, 180° and 270°) with four microelectrode tracks. In addition, in order to implement size-based particle sorting, a microelectrode track was designed with gradually increasing gaps from 10 to 40 μm. Consequently, they demonstrated separation feasibility by fractionating four different diametric latex particles (i.e. 3, 6, 10 and 20 μm) successfully. In order to break through the limitations of conventional DACSes, Cheng et al. [47] proposed a transformed cell sorting device employing two different electrode arrays that generated TwDEP force, as shown in Fig. 4. They achieved an approximate fourfold velocity increase by using a focusing mechanism that employed TwDEP force within a continuous flow. Conclusively, they showed that a TwDEP system could achieve a higher throughput than DEP trapping. However, since it required complicated electrode structures, they had difficulty in improving the recovery rate and reproducibility.

Fig. 3
figure 3

The proposed electrode with three layers by Choi et al. [17]. a Schematic view of the high-throughput gradient TwDEP device, b three layers of the TwDEP device

Fig. 4
figure 4

Schematic diagram of TwDEP force-based cell sorter by Cheng et al. [47]. a Top view of electrode arrangement, b side view of electrode structure, c images of TwDEP focusing electrodes, TwDEP sorting electrodes and packaged chip

DEP field flow fractionation

The working principle of the DEP field-flow fractionation is shown in Fig. 1d. DEP-FFF is an outstanding technique because it was originally proposed to separate biological particles within a continuous fluidic flow. In other words, a DACS that harnesses DEP-FFF is able to perform continuous cell separation with the unceasing injection of target particles. Particle movement in the microchannel depends on three acting forces—DEP force, hydrodynamic force, and gravity. Particles passing through the main channel can experience sedimentation and levitation due to the gravity and n-DEP force, respectively. When the DEP force is stronger than gravity, the particles levitate diagonally rather than vertically due to the hydrodynamic force of the fluidic flow. Since DEP force depends on dielectric properties and the radius of the particles, multiple particle types with different sizes or dielectric properties can be fractionated. A detailed analysis concerning the acting force for different particles with DEP-FFF was implemented by Gascoyne et al. and Wang et al. [8, 48]. Lewpiriyawong et al. [49] fabricated a PDMS-based micro-device utilizing DEP-FFF, and they demonstrated simulation studies. They selected an AgPDMS composite as their electrode material. In order to select the proper input voltage, they implemented a separation test under various voltage conditions (0, 25, 50 and 55 V) with latex polystyrene microspheres (5, 10 and 15 μm), as shown in Fig. 5. Since the AgPDMS caused voltage drops, they were able to select a higher voltage than in the simulation analysis. Consequently, they demonstrated size-dependent particle sorting within a continuous microfluidic flow. Piacentini et al. [50] performed the size-based separation of platelets from red blood cells, as shown in Fig. 6. In the same manner as that used by Lewpiriyawong et al. 48 they investigated the trajectory in the microchannel through a numerical simulation. Their device employed a “liquid electrode” defined by Demierre et al. [46] which is a kind of planar electrode deposited at the bottom of the empty zone positioned vertically from the main channel. They achieved striking results, with a recovery rate of over 98 %. On the other hand, Gupta et al. developed a device named ApoStream® to separate circulating tumor cells (CTCs) from normal and healthy blood cells in a microfluidic flow [47, 51]. They not only separated various CTCs (e.g. SKOV3 and MDA-MB-231), but also confirmed the viability of the completely separated cells. As a result, the viability of the cancer cells fractionated by Apostream® (see Fig. 7) was greater than 97.1 %, and the throughput was reported as 5000 cells/s. Also, Apostream® has come close to being commercialized, and the device has been utilized in research fields. Recent news regarding its commercialization is continually being reported on their website (ApoCell).

Fig. 5
figure 5

Video clip of particle levitation according to input voltage (10 μm particle at a 0 V, b 25 V, c 55 V, and 15 μm particle at d 0 V, e 25 V and f 50 V) by Lewpiriyawong et al. [49]

Fig. 6
figure 6

Trajectory of RBCs and PLTs in the device and graphical representation of trajectory between simulation and experiment by Piacentini et al. [50]

Fig. 7
figure 7

Schematic diagram of the Apostream® by Gupta et al. [44]

DEP barrier

Another way to exploit a continuous flow is to generate a dielectrophoretic barrier to hinder cell movement at the main channel. Generally, top–bottom patterned electrodes are deposited to generate n-DEP force and consequently deflect target particles toward a target area. When the DEP force between the top and bottom electrodes (electrode pair) is sufficient, the angled electrode pair enables the deflection of the target particles along the electrode pair. DACSes harnessing DEP barrier always install repeated electrode pairs to guarantee high separation efficiency. This technique is convenient since it does not forcibly translocate but just switches the direction of the particles in the channel, though not against the fluidic flow. In addition, the DEP barrier technique has advantages in terms of size-based target particle selection because changes in the channel depth (distance between top and bottom electrodes) can control the magnitude of the DEP barrier under the same input conditions (input voltage and frequency), as shown in Eq. 3. Durr et al. [19] introduced a DACS that harnessed DEP barrier, as shown in Fig. 8. They reported an electrode pair as a 3-D deflector array. They analyzed the threshold velocity for particle size according to voltage variation, as well as an electric field in a numerical simulation. As shown in Fig. 9, Kim et al. [52] presented a multi-target DACS (MT-DACS), and they separated multiple biological particles (MC1061 strain of E. coli) harnessing the same mechanism. They confirmed their separation results using flow cytometry. Since three kinds of particles were selected as target cells, three outlets and two kinds of angled electrode groups with different angles were fabricated. Compared to single pass DACSes, they achieved a 1000-fold overall enrichment of the separated target cells. In addition, they found that there was no detectable cross-contamination near the outlet channels. Kim et al. [53] proposed a novel DACS with a vertically arrayed micro channel to harness gravity with cantilever type electrode arrays. Since the proposed DACS harnessed gravity to shunt the injected cells, they did not require an additional flow generator such as micro syringe pump (or other micro-device), which is utilized by almost DACSes. Also, for high throughput, which is a weak point in current DACSes, they designed a meso-sized channel (L × W×H = 2 mm × 0.5 mm × 25 mm) that differed from conventional micro-devices. They injected a mixture including three kinds of particles (10, 25 and 50 μm), and they investigated the sedimentation patterns of each colony. Consequently, they achieved a high separation efficiency of 94.7 %. Lee et al. [54] designed a simplified DACS to obtain high reliability. Their DACS consisted of a meso-sized channel (15 mm × 40 mm × 0.2 mm) encompassed by two plates that were as a patterned top–bottom electrode to generate DEP barrier as shown in Fig. 10. In the case of conventional DACSes, the large number of components complicates the assembly procedure. Hence they insisted that complex structures could cause a leaking phenomenon between components and reduce reproducibility and reliability. They determined the proper input condition based on a numerical simulation and demonstrated a separation test with K562 cells (cancer cells found in bone marrow). In the experiments, the DACS achieved a separation efficiency of 94.74 %, a throughput of 17,000 cells/min and a recovery rate of 49.42 %.

Fig. 8
figure 8

Schematic diagram of DACS harnessing DEP barrier by Durr et al. [19]

Fig. 9
figure 9

Experimental setup a and optically captured images b at the crossroads by Kim et al. [52]

Fig. 10
figure 10

Simplified DACS configuration and video clip of separation process by Lee et al. [54]. a Deflected K562 cells above the DEP barrier, b K562 cells sinks beyond boundary line

Comparative analysis with a commercial cell sorter

FACSes and MACSes are representative commercial cell sorters. FACSes show high separation efficiencies of over 97 %, throughputs of 10,000 cells/s and recovery rates of over 55 % [5557]. MACSes show similar performance characteristics—separation efficiencies of over 90 %, throughputs of 1010 cells/h and recovery rates near 50 % [5860]. The results do not include the time-consuming labeling process that takes over an hour. The aforementioned DACS employing DEP-FFF and DEP barrier immediately achieved competitive results when compared to FACSes and MACSes in terms of separation efficiency. However, the throughput and recovery rate are still not at commercial levels. Even though Hu et al. [40] reported a striking throughput employing dielectrophoresis at over 10,000 cells/s, similar to that of a FACS, their sorter required a specific marker and a labeling process as prerequisites, which are also required for FACSes and MACSes. Consequently, it can be said that a DACS without immune-labelling cannot produce the levels of performance in terms of efficiency, throughput and recovery rate when compared to FACSes and MACSes. Nevertheless, a DACS employing the intrinsic dielectric material properties of a particle obtained a high separation efficiency and high recovery rate without the labeling process. Once a high throughput can be achieved through an optimization process (e.g. employing a modular system consisting of a few of the same features as those used by MACSes, applying a higher flow rate and so on), DACSes will be sufficiently competitive with FACSes and MACSes.

Conclusion and prospects

In this review article, DEP theory and various transformed equations broadly used in DACSes were introduced. Particle sorting techniques were classified into four types—DEP trapping, DEP field-flow fractionation (DEP-FFF), traveling wave dielectrophoresis and DEP barrier. According to target particles and objects, it was shown that the appropriate technique must be selected. Even though DEP trapping techniques are outstanding with respect to isolating submicron particles such as viruses and bacteria, they still have limitations in separating micro particles when compared to other techniques. This is because DEP trapping techniques are generally performed within a still fluid, and this prohibits the increase of throughput. Throughput is a very important factor for commercialization. Although research has stressed high efficiency, throughput and recovery rate have not been dealt with in depth because almost all DACSes have failed to obtain throughputs and recovery rates that have already been achieved by commercialized tools such as FACSes and MACSes. In order to meet the prerequisites for commercialization, exceedingly high separation efficiencies, throughputs and recovery rates must be achieved. Considering commercialization, therefore, DACS techniques within a continuous flow (DACSes based on TwDEP force, DEP-FFF and DEP barrier) have been widely studied to achieve the desired throughputs and recovery rates. However, success has not yet been achieved since the DACSes reported thus far have not only used micro-sized channels with low flow rates, but also complicated configurations. Therefore, the channel and the flow rate should be maximized for high throughput. In addition separation device configurations need to be simplified to enable high recovery rates. Furthermore, innovative electrode shapes and channel configurations must be implemented to obtain the high separation efficiencies. When high separation efficiencies, throughputs and recovery rates are guaranteed, DACSes will be able to open a new era in the fields listed below since they will not require immune-labelling related pre- and post-processes before and after separation.

  • Tissue engineering to rebuild damaged organs.

  • Stem cell separation for cell replacement treatment.

  • In vitro fertilization or intracytoplasmic sperm injection; superior sperm selection.

References

  1. Tsutsui Hideaki, Ho Chih-Ming (2009) Cell separation by non-inertial force fields in microfluidic systems. Mech Res Commun 36(1):92–103

    Article  MATH  Google Scholar 

  2. Franke Thomas A, Wixforth Achim (2008) Microfluidics for miniaturized laboratories on a chip. ChemPhysChem 9(15):2140–2156

    Article  Google Scholar 

  3. Kersaudy-Kerhoas M, Dhariwal R, Desmulliez MPY (2008) Recent advances in microparticle continuous separation. IET Nanobiotechnol 2(1):1–13

    Article  Google Scholar 

  4. Khoshmanesh Khashayar et al (2011) “Dielectrophoretic platforms for bio-microfluidic systems. Biosens Bioelectron 26(5):1800–1814

    Article  Google Scholar 

  5. Zhang C et al (2010) Dielectrophoresis for manipulation of micro/nano particles in microfluidic systems. Anal Bioanal Chem 396(1):401–420

    Article  Google Scholar 

  6. Qian Cheng et al (2014) “Dielectrophoresis for bioparticle manipulation. Int J Mol Sci 15(10):18281–18309

    Article  Google Scholar 

  7. Lapizco-Encinas Blanca H, Rito-Palomares Marco (2007) Dielectrophoresis for the manipulation of nanobioparticles. Electrophoresis 28(24):4521–4538

    Article  Google Scholar 

  8. Gascoyne Peter RC, Vykoukal Jody (2002) Particle separation by dielectrophoresis. Electrophoresis 23(13):1973

    Article  Google Scholar 

  9. Kadaksham J, Singh P, Aubry N (2003) Particle separation using dielectrophoresis. ASME 2003 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers

  10. Hawkins BG et al (2007) Continuous-flow particle separation by 3D insulative dielectrophoresis using coherently shaped, dc-biased, ac electric fields. Anal Chem 79(19):7291–7300

    Article  Google Scholar 

  11. Pohl Herbert A (1951) The motion and precipitation of suspensoids in divergent electric fields. J Appl Phys 22(7):869–871

    Article  Google Scholar 

  12. Pohl HA, Pohl HA (1978) Dielectrophoresis: the behavior of neutral matter in nonuniform electric fields, vol 80. Cambridge University Press, Cambridge

    Google Scholar 

  13. Suehiro Junya et al (2003) Selective detection of specific bacteria using dielectrophoretic impedance measurement method combined with an antigen–antibody reaction. J Electrost 58(3):229–246

    Article  Google Scholar 

  14. Grilli Simonetta, Ferraro Pietro (2008) Dielectrophoretic trapping of suspended particles by selective pyroelectric effect in lithium niobate crystals. Appl Phys Lett 92(23):232902

    Article  Google Scholar 

  15. Müller T et al (1996) High frequency electric fields for trapping of viruses. Biotechnol Tech 10(4):221–226

    Article  Google Scholar 

  16. Morgan H et al (1997) Large-area travelling-wave dielectrophoresis particle separator. J Micromech Microeng 7(2):65

    Article  Google Scholar 

  17. Choi Eunpyo, Kim Byungkyu, Park Jungyul (2009) High-throughput microparticle separation using gradient traveling wave dielectrophoresis. J Micromech Microeng 19(12):125014

    Article  Google Scholar 

  18. Markx Gerard H, Rousselet Juliette, Pethig Ronald (1997) DEP-FFF: field-flow fractionation using non-uniform electric fields. J Liq Chromatogr Relat Technol 20(16-17):2857–2872

    Article  Google Scholar 

  19. Dürr M et al (2003) Microdevices for manipulation and accumulation of micro-and nanoparticles by dielectrophoresis. Electrophoresis 24(4):722–731

    Article  Google Scholar 

  20. Kentsch J et al (2003) Microdevices for separation, accumulation, and analysis of biological micro-and nanoparticles. IEE Proceedings-Nanobiotechnology. vol 150. No. 2. IET Digital Library

  21. Chen DF, Du H, Li WH (2006) A 3D paired microelectrode array for accumulation and separation of microparticles. J Micromech Microeng 16(7):1162

    Article  Google Scholar 

  22. Müller T et al (1995) High-frequency electric-field trap for micron and submicron particles. Il Nuovo Cimento D 17(4):425–432

    Article  Google Scholar 

  23. Thomas Rupert S, Morgan Hywel, Green Nicolas G (2009) Negative DEP traps for single cell immobilisation. Lab Chip 9(11):1534–1540

    Article  Google Scholar 

  24. Zhao Y, Yi UC, Cho SK (2007) Microparticle concentration and separation by traveling-wave dielectrophoresis (twDEP) for digital microfluidics. Microelectromech Syst J 16(6):1472–1481

    Article  Google Scholar 

  25. Zhao Y, Yi UC, Cho SK (2007) Highly efficient in-droplet particle concentration and separation by twDEP and EWOD for digital microfluidics. Micro Electro Mech Syst, MEMS. IEEE 20th International Conference on. IEEE

  26. Choi Sungyoung, Park Je-Kyun (2007) Continuous hydrophoretic separation and sizing of microparticles using slanted obstacles in a microchannel. Lab Chip 7(7):890–897

    Article  Google Scholar 

  27. Huang Y et al (1997) Introducing dielectrophoresis as a new force field for field-flow fractionation. Biophys J 73(2):1118–1129

    Article  Google Scholar 

  28. Huang Y et al (1999) The removal of human breast cancer cells from hematopoietic CD34+ stem cells by dielectrophoretic field-flow-fractionation. J Hematother Stem Cell Res 8(5):481–490

    Article  Google Scholar 

  29. Peng H et al (2006) Dielectrophoresis field flow fractionation of single-walled carbon nanotubes. J Am Chem Soc 128(26):8396–8397

    Article  Google Scholar 

  30. Park J et al (2005) An efficient cell separation system using 3D-asymmetric microelectrodes. Lab Chip 5(11):1264–1270

    Article  Google Scholar 

  31. An J et al (2009) Separation of malignant human breast cancer epithelial cells from healthy epithelial cells using an advanced dielectrophoresis-activated cell sorter (DACS). Anal Bioanal Chem 394(3):801–809

    Article  Google Scholar 

  32. Lee D et al (2013) A negative dielectrophoresis and gravity-driven flow-based high-throughput and high-efficiency cell-sorting system. J Lab Autom: 2211068213498385

  33. Nicoletti I et al (1991) A rapid and simple method for measuring thymocyte apoptosis by propidium iodide staining and flow cytometry. J Immunol Meth 139(2):271–279

    Article  Google Scholar 

  34. Applegate R, Robert, et al (2004) Optical trapping, manipulation, and sorting of cells and colloids in microfluidic systems with diode laser bars. Opt Expr 12(19):4390–4398

    Article  Google Scholar 

  35. Jr Applegate, Robert W et al (2006) Microfluidic sorting system based on optical waveguide integration and diode laser bar trapping. Lab Chip 6(3):422–426

    Article  Google Scholar 

  36. Miltenyi S et al (1990) High gradient magnetic cell separation with MACS. Cytometry 11(2):231–238

    Article  Google Scholar 

  37. He Z et al (2012) Isolation of human male germ-line stem cells using enzymatic digestion and magnetic-activated cell sorting Germline Development. Springer, New York, pp 45–57

    Google Scholar 

  38. Seidl J, Knuechel R, Kunz-Schughart LA (1999) Evaluation of membrane physiology following fluorescence activated or magnetic cell separation. Cytometry 36(2):102–111

    Article  Google Scholar 

  39. Hywel M, Green Nicolas G (2003) AC electrokinetics: colloids and nanoparticles. No. 2. Research Studies Press

  40. Hu X et al (2005) Marker-specific sorting of rare cells using dielectrophoresis. Proc Natl Acad Sci USA 102(44):15757–15761

    Article  Google Scholar 

  41. Shim S et al (2013) Dielectrophoresis has broad applicability to marker-free isolation of tumor cells from blood by microfluidic systems. Biomicrofluidics 7(1):011808

    Article  Google Scholar 

  42. Gascoyne PR et al (2013) Correlations between the dielectric properties and exterior morphology of cells revealed by dielectrophoretic field-flow fractionation. Electrophoresis 34(7):1042–1050

    Article  Google Scholar 

  43. Lapizco-Encinas BH et al (2005) An insulator-based (electrodeless) dielectrophoretic concentrator for microbes in water. J Microbiol Meth 62(3):317–326

    Article  Google Scholar 

  44. Gupta V et al (2012) ApoStream™, a new dielectrophoretic device for antibody independent isolation and recovery of viable cancer cells from blood. Biomicrofluidics 6(2):024133

    Article  Google Scholar 

  45. Gascoyne Peter, Satayavivad Jutamaad, Ruchirawat Mathuros (2004) Microfluidic approaches to malaria detection. Acta Trop 89(3):357–369

    Article  Google Scholar 

  46. Demierre N et al (2007) Characterization and optimization of liquid electrodes for lateral dielectrophoresis. Lab Chip 7(3):355–365

    Article  Google Scholar 

  47. Cheng, I-Fang, Cheng-Che Chung, and Hsien-Chang Chang. “High-throughput electrokinetic bioparticle focusing based on a travelling-wave dielectrophoretic field.” Microfluidics and nanofluidics 10.3 (2011): 649-660

  48. Wang XB et al (2000) Cell separation by dielectrophoretic field-flow-fractionation. Anal Chem 72(4):832–839

  49. Lewpiriyawong Nuttawut, Yang C, Lam YC (2010) “Continuous sorting and separation of microparticles by size using AC dielectrophoresis in a PDMS microfluidic device with 3-D conducting PDMS composite electrodes.”. Electrophoresis 31(15):2622–2631

  50. Piacentini N et al (2011) Separation of platelets from other blood cells in continuous-flow by dielectrophoresis field-flow-fractionation. Biomicrofluidics 5(3):034122

    Article  MathSciNet  Google Scholar 

  51. Varadhachary G et al (2013) ApoStream™, a new dielectrophoretic device for antibody-independent isolation and recovery of circulating tumor cells from blood of patients with metastatic pancreatic adenocarcinoma. Cancer Res 73(8):1449

    Article  Google Scholar 

  52. Kim U et al (2008) Multitarget dielectrophoresis activated cell sorter. Anal Chem 80(22):8656–8661

    Article  Google Scholar 

  53. Kim Y et al (2011) Cantilever-type electrode array-based high-throughput microparticle sorting platform driven by gravitation and negative dielectrophoretic force. J Micromech Microeng 21(1):015015

    Article  Google Scholar 

  54. Lee D et al (2016) Negative dielectrophoretic force based cell sorter with simplified structure for high reliability. Int J Precis Eng Manuf 17(2):1–5

    Google Scholar 

  55. Wolff A et al (2003) Integrating advanced functionality in a microfabricated high-throughput fluorescent-activated cell sorter. Lab Chip 3(1):22–27

    Article  Google Scholar 

  56. Ferrari Belinda C, Oregaard G, Sørensen SJ (2004) Recovery of GFP-labeled bacteria for culturing and molecular analysis after cell sorting using a benchtop flow cytometer. Microb Ecol 48(2):239–245

    Article  Google Scholar 

  57. Soeth E et al (1996) The detection of disseminated tumor cells in bone marrow from colorectal-cancer patients by a cytokeratin-20-specific nested reverse-transcriptase-polymerase-chain reaction is related to the stage of disease. Int J Cancer 69(4):278–282

    Article  Google Scholar 

  58. Büsch J et al (1994) Enrichment of fetal cells from maternal blood by high gradient magnetic cell sorting (double MACS) for PCR-based genetic analysis. Prenat Diagn 14(12):1129–1140

    Article  Google Scholar 

  59. Schmitz B et al (1994) Magnetic activated cell sorting (MACS)—a new immunomagnetic method for megakaryocytic cell isolation: comparison of different separation techniques. Eur J Haematol 52(5):267–275

    Article  MathSciNet  Google Scholar 

  60. Adams Jonathan D, Kim U, Tom Soh H (2008) Multitarget magnetic activated cell sorter. Proc Natl Acad Sci 105(47):18165–18170

    Article  Google Scholar 

Download references

Authors’ contributions

DL carried out the research work and wrote the manuscript. BH carried out a survey of dielectrohporesis-based particle sorting systems. BK supervised all research work. All authors read and approved the final manuscript.

Authors’ information

Dongkyu Lee received his B.S. and M.S. degrees from Korea Aerospace University in 2012 and 2014, respectively, and is now a Ph.D. candidate at Korea Aerospace University. His current research interests include microelectromechanical systems (MEMS) for bio particle sorting systems.

Bohyun Hwang received his B.S. degree from Korea Aerospace University in 2015, and is now in a Master’s course at Korea Aerospace University. His current research interests include the development of cell sorting systems based on dielectrophoresis.

Byungkyu Kim received his Ph.D. in mechanical engineering from the University of Wisconsin, Madison, in 1997. From 1997 to 2000, he was a technical staff member at the Center for X-ray Lithography (CXrL) at the University of Wisconsin where he developed a computer code for the thermal modeling of a mask membrane and wafer during beam exposure. From 2000 to 2005, he worked for the Microsystem Center at KIST as a principal research scientist. He was in charge of developing the microrobot for a microcapsule-type endoscope. Currently, he is a professor in the School of Aerospace and Mechanical Engineering at Korea Aerospace University. His research interests include microelectromechanical systems (MEMS) for cell separation.

Acknowledgements

This research was supported by the Bio & Medical Technology Development Program (NRF-2005-2000206) and the Basic Science Research Program (NRF-2015R1D1A01057714) of the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology.

Competing interests

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Byungkyu Kim.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, D., Hwang, B. & Kim, B. The potential of a dielectrophoresis activated cell sorter (DACS) as a next generation cell sorter. Micro and Nano Syst Lett 4, 2 (2016). https://doi.org/10.1186/s40486-016-0028-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40486-016-0028-4

Keywords