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Differential Mobility Cytometry Kelong Wang, Ximena Solis-Wever, Charmaine Aguas, Yan Liu, Peng Li, and Dimitri Pappas* Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-1061 A new cell analysis method, differential mobility cytometry (DMC), was developed to monitor cells spatially and temporally or to separate cells based on affinity interactions. DMC combines an oscillation system with opentubular capillary cell affinity chromatography (OT-CAC), although any separation volume (capillaries, channels, etc.) can be used. This unique separation approach uses oscillating flow and differential imaging to analyze cells as they retard and adhere to an affinity surface. Three main factors of the oscillation system were studied: the pump speed, oscillation frequency, and cell velocity at different oscillation speeds. The optimized oscillation frequency and intensity were determined. Cell-surface interactions were used to estimate the number of bonds formed during cell capture. An average of 200 bonds (standard deviation of 150 bonds) were formed during cell capture. The variability was due to differences in cellcapture times (0.8 ( 0.6 s). Cells expressing the target protein on the surface oscillated slower and were captured by the corresponding ligand on the capillary surface. Cells were detected by differential imaging of a charge-coupled device camera. DMC measurements were optimized with respect to the camera frame difference. Cells were observed to slow as they reached the surface and could be observed to sway in the oscillating flow as they were tethered to the surface by a capture antibody. With the advantage of high cell-capture efficiency and temporally monitoring cell adhesion by the differential mobility of cells, DMC has proven to be a useful tool in cell analysis for basic biological studies and biomedical research. A new cell analysis method, differential mobility cytometry (DMC), is described in this paper. DMC combines the functions of separating target cells and monitoring cell adhesion with high temporal resolution. DMC uses affinity cell capture to separate cells. A differential imaging system is used to discriminate between captured and mobile cells. The broad field of cell separation shows great importance in disease detection and treatment, such as the detection of cancer and acquired immune deficiency syndrome (AIDS).1,2 Purified and enriched target cells after separation can be used for further study such as analysis of the genomics and proteomics of the malignant cells. Cell adhesion plays a critical role in many essentially biological functions including migration, * Corresponding author. E-mail:
[email protected]. (1) Du, Z.; Cheng, K. H.; Vaughn, M. W.; Collie, N. L.; Gollahon, L. S. Biomed. Microdevices 2007, 9, 35–42. (2) Cheng, X.; Irimia, D.; Dixon, M.; Sekine, K.; Demirci, U.; Zamir, L.; Tompkins, R. G.; Rodriguez, R.; Toner, M. Lab Chip 2007, 7, 170–178.
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immune system activation, tissue formation, and wound healing. Understanding the cell-adhesion process elucidates many biological processes such as the immune system inflammation reaction and the activation and deactivation of immune cells.3,4 DMC, which is capable of simultaneous cell-separation and cell-adhesion studies, will be a convenient cell analysis tool with simple operation, low cost, high throughput, and multiparameter detection. Cell separation is typically based on either cell-surface molecules or internal properties. Internal properties include the cell density, cell size, or electrical conductivity, while cell-surface marker techniques include separations based on cell-surface antigens, such as fluorescence-activated cell sorting (FACS) and magnetic-activated cell sorting, using labels to establish the specificity of the separation.5,6 In the case of dielectrophoresis, both internal and external properties can be used in the separation.7 Internal-property-based methods have the advantages of time efficiency, low cost, and minimized disturbance from chemicals; the limit is that there must be a significant difference between the cell size, density, dielectric potential, buoyancy, or other parameters. Field-flow techniques take advantage of the physical differences of particles for separation, such as the sedimentation speed.8,9 In an optimal case, a gravitational split-flow thin channel (G-SPLITT) system sorted myeloma and spleen cells, because of a sufficient difference in size.10 A size-based microfluidic crossflow device was reported to separate white blood cells (WBCs) from whole blood with retention of 98% of the WBCs.11 A threechannel microfluidic device showed the ability of separating myocytes and nonmyocytes from the neonatal rat myocardium.12 Capillary electrophoresis has also been used to separate bacteria and viruses based on internal properties.13-15 Dielectrophoretic activity of cells in the presence of electric fields was used (3) Rico, F.; Roca-Cusachs, P.; Sunyer, R.; Farre´, R.; Navajas, D. J. Mol. Recognit. 2007, 20, 459–466. (4) Gunzer, M. Ernst Schering Found. Symp. Proc. 2007, 3, 97–137. (5) Fu, A. Y.; Spence, C.; Scherer, A.; Arnold, F. H.; Quake, S. R. Nat. Biotechnol. 1999, 17, 1109–1111. (6) Schmitz, B.; Radbruch, A.; Kummel, T.; Wickenhauser, C.; Korb, H.; Hansmann, M. L.; Thiele, J.; Fischer, R. Eur. J. Haematol. 1994, 52, 267– 275. (7) Vahey, M. D.; Voldman, J. Anal. Chem. 2008, 80, 3135–3143. (8) Giddings, J. C. Science 1993, 260, 1456–1465. (9) Springston, S. R.; Myers, M. N.; Giddings, J. C. Anal. Chem. 1987, 59, 344–350. (10) Benincasa, M.-A.; Moore, L. R.; Williams, S.; Potic, E.; Carpino, F.; Zborowski, M. Anal. Chem. 2005, 77, 5294–5301. (11) VanDelinder, V.; Groisman, A. Anal. Chem. 2007, 79, 2023–2030. (12) Murthy, S. K.; Sethu, P.; Vunjak-Novakovic, G.; Toner, M.; Radisic, M. Biomed. Microdevices 2006, 8, 231–237. (13) Lantz, A. W.; Bao, Y.; Armstrong, D. W. Anal. Chem. 2007, 79, 1720– 1724. (14) Hjerten, S.; Elenbring, K.; Kilar, F.; Liao, J.; Chen, A. J.; Siebert, C. J.; Zhu, M. J. Chromatogr. 1987, 403, 47–61. 10.1021/ac900277y CCC: $40.75 2009 American Chemical Society Published on Web 03/30/2009
to separate cancer cells from blood and from CD34+ hematopoietic stem cells, as well as to segregate different human cell types.16-18 Vahey and Voldman have reported the separation of nonviable from viable cells of the budding yeast Saccharomyces cerevisiae with the isodielectric separation method, which is based on electrically distinguishable phenotypes.7 Antibody- or aptamer-based cell-surface molecule techniques have been widely used in cell separation and analysis on different substrates including microchips, capillaries, hollow fibers, and flow cells.19-32 Currently, microfluidic techniques have made rapid progress with chip- or array-based cell separations and analyses because of the ease of use of poly(dimethylsiloxane) (PDMS) in soft lithography.33 Easily fabricated PDMS is increasingly being implemented in cell culture and chip-based analysis devices.34 While PDMS has greatly accommodated researchers, several disadvantages, such as protein absorption and water evaporation, restrict its application in cell analysis.35 To overcome these disadvantages, silicon and glass chips can be used, but the fabrication is much more complex and costly than making a PDMS chip.33 Cell affinity chromatography exploits differences in cell-surface macromolecules. When mixtures of cells are passed through an affinity column, target cells are captured by the corresponding (15) Desai, M. J.; Armstrong, D. W. Microbiol. Mol. Biol. Rev. 2003, 67, 38– 51. (16) Gascoyne, P. R. C.; Wang, X.-B.; Huang, Y.; Becker, F. F. IEEE Trans. Ind. Appl. 1997, 33, 670–678. (17) Wang, X.-B.; Yang, J.; Huang, Y.; Vykoukal, J.; Becker, F. F.; Gascoyne, P. R. C. Anal. Chem. 2000, 72, 832–839. (18) Das, C. M.; Becker, F.; Vernon, S.; Noshari, J.; Joyce, C.; Gascoyne, P. R. C. Anal. Chem. 2005, 77, 2708–2719. (19) Nagrath, S.; Sequist, L. V.; Maheswaran, S.; Bell, D. W.; Irimia, D.; Ulkus, L.; Smith, M. R.; Kwak, E. L.; Digumarthy, S.; Muzikansky, A.; Ryan, P.; Balis, U. J.; Tompkins, R. G.; Haber, D. A.; Toner, M. Nature (London) 2007, 450, 1235–1239. (20) Delehanty, J. B.; Ligler, F. S. Anal. Chem. 2002, 74, 5681–5687. (21) Herr, J. K.; Smith, J. E.; Medley, C. D.; Shangguan, D.; Tan, W. Anal. Chem. 2006, 78, 2918–2924. (22) Belov, L.; Huang, P.; Barber, N.; Mulligan, S. P.; Christopherson, R. I. Proteomics 2003, 3, 2147–2154. (23) Belov, L.; Huang, P.; Chrisp, J. S.; Mulligan, S. P.; Christopherson, R. I. J. Immunol. Methods 2005, 305, 10–19. (24) Belov, L.; Mulligan, S. P.; Barber, N.; Woolfson, A.; Scott, M.; Stoner, K.; Chrisp, J. S.; Sewell, W. A.; Bradstock, K. F.; Bendall, L.; Psovici, D. S.; Thomas, M.; Erber, W.; Huang, P.; Sartor, M.; Young, G. A. R.; Wiley, J. S.; Juneja, S.; Wierda, W. G.; Green, A. R.; Keating, J. K.; Christopherson, R. I. Br. J. Hamaetol. 2006, 135, 184–197. (25) Ellmark, P.; Belov, L.; Huang, P.; Lee, C. S.; Solomon, M. J.; Morgan, D. K.; Christopherson, R. I. Proteomics 2006, 6, 1791–1802. (26) Woolfson, A.; Stegging, J.; Tom, B. D. M.; Stoner, K. J.; Gilks, W. R.; Kreil, D. P.; Mulligan, S. P.; Belov, L.; Chrisp, J.; Errington, W.; Wildfire, A.; Erber, W. N.; Bower, M.; Gazzard, B.; Christopherson, R. I.; Scott, M. A. Blood 2005, 106, 1003–1007. (27) Zhang, C. X.; Liu, H. P.; Tang, Z. M.; He, N. Y.; Lu, Z. H. Electrophoresis 2003, 24, 3279–3283. (28) Yang, Y.; Zhang, C.; Tang, Z.; Zhang, X.; Lu, Z. Clin. Chem. 2005, 51, 910–911. (29) Wang, K.; Marshall, M. K.; Garza, G.; Pappas, D. Anal. Chem. 2008, 80, 2118–2124. (30) Wang, K.; Cometti, B.; Pappas, D. Anal. Chim. Acta 2007, 601, 1–9. (31) Nordon, R. E.; Shu, A.; Camacho, F.; Milthorpe, B. K. Cytometry, Part A 2004, 57A, 39–44. (32) Nordon, R. E.; Haylock, D. N.; Gaudry, L.; Schindhelm, K. Cytometry 1996, 24, 340–347. (33) El-Ali, J.; Sorger, P. K.; Jensen, K. F. Nature (London) 2006, 442, 403– 411. (34) Liu, K.; Dang, D.; Bayer, K.; Harrington, T.; Pappas, D. Langmuir 2008, 24, 5955–5960. (35) Mukhopadhyay, R. Anal. Chem. 2007, 79, 3248–3253.
ligands. This column typically is packed with ligand-coated beads, porous supports, or membranes or operated in an open-tubular approach with a piece of capillary modified with antibody.29,36-44 Cell affinity chromatography is characterized by high specificity, low cost, and simple operation. In our previous work, an opentubular cell affinity chromatography (OT-CAC) method was demonstrated to efficiently separate B and T lymphocytes from lysed blood with single and tandem capillaries. Using a piece of capillary, OT-CAC drastically simplified the device-making process of cell separation. The purity of CD4+ cells separated in antiCD4 capillaries was 88%. Anti-CD4 and anti-CD19 capillaries in tandem separated CD4+ T lymphocytes and CD19+ B lymphocytes from lysed blood with high purity.29 For further details regarding the current cell-separation methods, the reader is referred to several excellent reviews.33,45-47 Other groups have studied the cell-adhesion theory including the size of an adherent cell, the force on association and dissociation, and the ligand-receptor equilibrium.48-51 The mechanism of cell adhesion has been successfully studied by atomic force microscopy (AFM).3,52-54 In general, one cell is attached on the AFM cantilever first; then it is positioned above the other cell; after a predefined time interval to allow establishment of cell adhesion, the force spectra for cells can be recorded by retracting the cantilever until the contact between the cells is broken. With the AFM-based single-cell force spectroscopy method, not only the overall cell adhesion but also the properties of single adhesionreceptor-ligand interactions can be studied.55 Single-cell transit times of blood cell populations have been tested by the microfluidics-based “biophysical” flow cytometry technique.56 (36) Hertz, C. M.; Graves, D. J.; Lauffenburger, D. A. Biotechnol. Bioeng. 1985, 27, 603–612. (37) Brewster, J. D. J. Microbiol. Methods 2003, 55, 287–293. (38) Ujam, L. B.; Clemmitt, R. H.; Clarke, S. A.; Brooks, R. A.; Rushton, N.; Chase, H. A. Biotechnol. Bioeng. 2003, 83, 554–566. (39) Kumar, A.; Plieva, F. M.; Galeav, I. Y.; Mattiasson, B. J. Immunol. Methods 2003, 283, 185–194. (40) Dainiak, M. B.; Plieva, F. M.; Galaev, I. Y.; Hatti-Kaul, R.; Mattiasson, B. J. Biotechnol. Prog. 2005, 21, 644–649. (41) Kumar, A.; Rodriguez-Caballero, A.; Plieva, F. M.; Galaev, I. Y.; Nandakumar, K. S.; Kamihira, M.; Holmdahl, R.; Orfao, A.; Mattiasson, B. J. Mol. Recognit. 2005, 18, 84–93. (42) Dainiak, M. B.; Kumar, A.; Galaev, I. Y.; Mattiasson, B. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 849–854. (43) Dainiak, M. B.; Galaev, I. Y.; Mattiasson, B. J. Chromatogr., A 2006, 1123, 145–150. (44) Higuchi, A.; Iizuka, A.; Gomei, Y.; Miyazaki, T.; Sakurai, M.; Matsuoka, Y.; Natori, S. H. J. Biomed. Mater. Res. 2006, 78A, 491–499. (45) Andersson, H.; van den Berg, A. Sens. Actuators, B 2003, 92, 315–325. (46) Pappas, D.; Wang, K. Anal. Chim. Acta 2007, 601, 26–35. (47) Chen, P.; Feng, X. J.; Du, W.; Liu, B. F. Front Biosci. 2008, 13, 2464–483. (48) Orsello, C. E.; Lauffenburger, D. A.; Hammer, D. A. Trends Biotechnol. 2001, 19, 310–316. (49) Tees, D. F. J.; Goetz, D. J. News Physiol. Sci. 2003, 18, 186–190. (50) Hammer, D. A.; Lauffenburger, D. A. Biophys. J. 1987, 52, 475–487. (51) Prashant, K. S.; Gibcus, M. J.; van der Mei, H. C.; Busscher, H. J. Appl. Environ. Microbiol. 2005, 71, 3668–3673. (52) Benoit, M.; Gabriel, D.; Gerisch, G.; Gaub, H. E. Nat. Cell Biol. 2000, 2, 313–317. (53) Roca-Cusachs, P.; Almendros, I.; Sunyer, R.; Gavara, N.; Farre´, R.; Navajas, D. Biophys. J. 2006, 91, 3508–3518. (54) Zhang, X.; Wojcikiewicz, E. P.; Moy, V. T. Exp. Biol. Med. 2006, 231, 1306– 1312. (55) Helenius, J.; Heisenberg, C.-P.; Gaub, H. E.; Muller, D. J. J. Cell Sci. 2008, 121, 1785–1791. (56) Rosenbluth, M. J.; Lam, W. A.; Fletcher, D. A. Lab Chip 2008, 8, 1062– 1070.
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Figure 1. DMC. (A) Cells suspended in an oscillating flow in a separation channel (i) reach the surface via sedimentation (ii). The capture process results in the formation of affinity bonds, immobilizing the cell (iii, green). (B) Concept of mobility measurements. Green cells are bound, and white cells move in the fluid stream. In frame C, the unbound cells have moved some distance from their original position. The difference of frames B and C produce image D, where only mobile cells are identified, leading to label-free detection of bound cells.
While many cell-separation methods benefit from the high specificity, none of the methods accomplished cell separation while monitoring the target cell mobility and cell capture temporally. In this paper, DMC has been developed to separate cells and monitor cell adhesion spatially and temporally. DMC combines an oscillation system and affinity separation to fulfill both separation and adhesion monitoring functions at the same time. In the oscillation system, cells expressing the target protein on the surface oscillated slower and eventually were captured by the corresponding ligand on the capillary surface. The cell-adhesion process is analyzed by the cell mobility difference. Time-lapsed imaging and differential processing of the charge-coupled device (CCD) camera images discriminated between stationary and moving cells in oscillating flow. Cell-surface adhesion, cell-capture efficiency, and the temporal resolution of the system were studied. Using this new approach to cell separations, many long-term cellcapture processes can be determined, such as gravitational settling in laminar flow or the affect of antigen density on cell capture. DMC CONSIDERATIONS Cell capture using antibody-antigen or ligand-receptor binding depends on several factors. As cells reach the surface in DMC columns by gravitational settling (Figure 1), a collision or interaction with the surface occurs and affinity bonds are formed. The number of affinity bonds formed (B*) is estimated using Lauffenburger’s formula36 B* ) BAcτc
(1)
where B is the number of antigens per unit area on the cell surface, Ac is the collision area between the cell and the surface, and τc is the collision duration. In traditional flow methods where the direction of flow is constant (or when no flow is present), cells settle to the surface and interact for a given interaction time. When oscillating flow is present, the cell can interact multiple times on the same surface and observation areas, allowing for longer-term cell-adhesion studies to be conducted. Cells travel along the fluid axis but move between fluid lamina through sedimentation. One of the key advantages of using oscillating flow is that the cells in the channel have adequate time 3336
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Figure 2. Oscillation generator used to generate flow. The peristaltic roller compresses the tubing (sealed on the distal end), producing oscillations in the capillary separation channel. If both plates were used, the pulse frequency was doubled. The peristaltic roller pulls fluid away from the capillary, and the pulse is created as the roller releases the tubing and the fluid returns in the direction of the capillary.
to approach the affinity surface via sedimentation. If continuous flow is used, the cells may leave the channel (regardless of the channel length) before interacting with the surface. One potential drawback of this technique is that mobility differences are measured in parabolic, laminar flow. Therefore, cells near the affinity surface will travel slower than those suspended near the center of the fluid stream. Cells near the surface will be slow, but if the affinity bonds are not formed, the cell will continue to roll or slide and will therefore have a mobility that is distinguishable from cells captured by affinity bonds. The depth of field of the imaging system (see the Experimental Section) can be adjusted so that only cells near the surface are measured, significantly reducing the effect of differences in the flow velocity due to parabolic flow. Because cells move between fluid lamina via gravitational settling, there is therefore a settling time (measured to be 5 min for human T lymphocytes (HuT 78) in an anti-CD4 capillary; Figure 4) required to capture cells in the channel. Cells that reach the surface can then attach (if antigen-antibody bonds are formed), deflect off of the surface, and re-enter the bulk fluid or roll along the surface until affinity bonds are formed. EXPERIMENTAL SECTION Chemical and Reagents. Fetal bovine serum (FBS), bovine serum albumin (BSA), and biotinylated BSA were purchased from Sigma-Aldrich. Neutravidin was purchased from Pierce. Biotinylated mouse antihuman CD4 was purchased from Ebioscience, and biotinylated mouse antihuman CD71 was purchased from Becton-Dickinson. Calcein AM and propidium iodide (PI) were obtained from Invitrogen (Molecular Probes) and used according to the manufacturer’s directions. Sterile phosphate-buffered saline (PBS; pH ) 7.4) was purchased from Invitrogen. The CD71 antigen density was determined using mouse antihuman CD71 conjugated to fluorescein (anti-CD71-FITC, Ebioscience) and calibrated antigen binding capacity beads (Quantum Simply Cellular antimouse IgG beads, Bangs Laboratories). Anti-CD71FITC-stained beads and cells were measured using a flow cytometer (FACSCalibur, Becton-Dickinson).
Figure 3. Differential imaging of mobile and immobile cells. Frame no. 1199 of a movie sequence of oscillating cells (A). Frame no. 1206 of the same sequence; unbound cells have moved from their original position (B). The difference image of the two frames reveals moving cells circled in red for clarity (C). Each cell is approximately 15 µm.
The antigen density was determined by the ratio of the antibody binding capacity and the cell surface area (determined by microscopy). The Quantum Simply Cellular beads used in this study were coated with known amounts of antimouse IgG (Fc specific). The beads were incubated with a titrated amount of mouse antihuman antibodies conjugated to fluorescein and analyzed by flow cytometry. A calibration curve of fluorescence as a function of IgG antibodies bound to the beads was constructed according to the manufacturer’s protocols. Cell samples were then tested and the number of antibodies calculated using the calibration curve. This method eliminates the need to determine the fluorophore-to-antibody ratio. The antigen density was determined by dividing the total number of antibodies on the cell by the surface area (the cell was assumed to be a sphere for these calculations). The error in these measurements was due to a combination of the variability of the cell antigen density size. Cell Lines and Cell Culture. HuT 78, Jurkat, and B lymphocyte (RPMI 8226) transformed cell lines were purchased from the American type Culture Collection. The HuT 78 cells are CD3+, CD4+, and CD71+; RPMI 8226 B cells are CD71+, CD4-, and CD19-; Jurkat cells are CD3+, CD71+, and CD4-. Cells were cultured in a flask with a RPMI 1640 medium (VWR Scientific) supplemented with 10% FBS (Sigma-Aldrich, Inc.) and 20 mL/L antibiotic (penicillin-streptomycin solution stabilized, SigmaAldrich, Inc.). The incubator was set to 37 °C and 5% CO2. Cells were subcultured by replacing part of the cell suspension with fresh medium one or two times each week. Before analysis, cells were moved into 1.5 mL centrifuge tubes, centrifuged at 4500 rpm for 4 min, and resuspended with 3% BSA in PBS. The cell density varied between 105 and 106 cells/mL for analysis. Cells were injected into the capillary by a syringe pump and a 29-gauge syringe. Capillaries with inner diameters of 200 µm were purchased from Polymicro Technologies, LLC. The polyimide coating was burned off to facilitate microscopic imaging. Capillary Cell Affinity Chromatography. Details of the opentubular capillary affinity chromatography method were described elsewhere.29 In short, a 29-gauge needle and antibody-modified capillary were connected by a piece of 30-gauge Teflon tubing (Small Parts). The cell sample and buffer loading speed were controlled by the syringe pump (Kd Scientific). Flavell’s protocol was modified by substituting streptavidin with neutravidin to coat antibody on the inner surface of the capillary.57 Antibodies were linked to the glass surface with a sandwich strategy: (i) biotin-conjugated albumin was coated onto the inner wall of the capillary; (ii) neutravidin was coated over the first layer, forming a uniform coating of the protein on the surface; (iii) (57) Jing, R.; Bolshakov, V. I.; Flavell, A. J. Nat. Protoc. 2007, 2, 168–177. (58) Reneman, R. S.; Arts, T.; Hoeks, A. P. G. J. Vasc. Res. 2006, 43, 251–269.
monoclonal mouse antihuman IgG antibodies conjugated to biotin were used to create surfaces for cell capture. Capillaries were then stored in a refrigerator at 4 °C. The entire process required less than 1 h for a batch of capillary columns. The reagent loading volume is 3 µL for a capillary of 10 cm length and 200 µm inner diameter. To minimize nonspecific binding, 3% BSA in PBS was used as the carrier fluid. Either shear flow or bubbles were used to elute cells retained in the column. Recovered cells were collected into 1.5 mL centrifuge tubes (VWR Scientific) containing PBS. Oscillation System. The oscillation generation system was made by a peristaltic pump (VWR, Cat. no. 54856-070), a homemade oscillation generator (Figure 2), a thick silicone tubing (peristaltic tubing) filled with buffer to transfer oscillation, an opentubular affinity capillary connected with the thick tubing by a thin tubing, and a T-shape connector. The third port of the T-shape connector was for sample injection. The other side of the thick peristaltic pump tubing was sealed or connected with a washing buffer. The oscillation generator was fixed on the variable-flow peristaltic pump to generate oscillation. Using both plates on the oscillation generator doubled the pulsed frequency to 6 pulses/ revolution. In this paper, only one plate on the oscillation generator was adjusted by squeezing the thick tubing to form 3 pulses in a revolution of the roller. The roller rotates counterclockwise. The pump oscillates by squeezing the peristaltic tubing between the poles on the roller and the compression plates. The roller moves in the reverse direction (i.e., away from the capillary inlet). The solution is pulled away from the capillary inlet during this portion of the pump cycle. As the peristaltic roller releases the tubing, the fluid flows toward the capillary inlet, generating a pulse. The peristaltic tubing furthest from the separation channel is sealed (for oscillation) or connected with a rinsing buffer (for flushing the system between experiments). The flow rate and oscillation frequency can be independently adjusted in this system. The flow rate is controlled by moving the adjustable plate to squeeze the peristaltic tubing. In addition, using peristaltic tubing of different diameter also affects the flow rate. The oscillation frequency is controlled by the revolution speed of the peristaltic roller and whether one or both plates are used (Figure 2 shows only the top plate in the working position). If both plates are used, then the pulse frequency is double the pump rotation frequency. The forward and reverse velocities under different experimental conditions were determined by analyzing the distance traveled by 10 cells or beads as a function of time. The velocities reported are therefore an average across the channel diameter. Differential Imaging. An inverted microscope (IX71, Olympus) was used to obtain all of the images and videos of the DMC columns. A 0.10 NA, 4× objective was used for white light imaging, and a 0.25 NA, 10× objective was used for fluorescence imaging. Analytical Chemistry, Vol. 81, No. 9, May 1, 2009
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Figure 4. Normalized B and T cell attachment in an anti-CD4 capillary at different oscillation speeds (pulses/min): (A) 13.3; (B) 20.7; (C) 26.7. A higher oscillating frequency diminished the nonspecific binding, while target cell capture was not affected: (9) T cells; (b) B cells. Error bars represent the standard deviation of the mean cell number. The absolute number of the cells imaged in parts A-C of Figure 4 respectively are 18 ( 7 B cells, 88 ( 52 T cells; 2 ( 1.7 B cells, 20 ( 4 T cells; and 2 ( 2 B cells, 81 ( 56 T cells.
The depths of field for the 4× and 10× objectives are 50 and 8 µm, respectively. The imaged cells were located on the bottom wall of the capillary closest to the inverted microscope objective. Because gravitational settling is the major source of cell-wall interaction, most cells were located on the bottom portion of the capillary wall. Images and videos were recorded using a 12-bit, cooled CCD camera (Orca-285, Hamamatsu, Japan) using the manufacturer’s software. Image analysis was performed in ImageJ (version 1.33, National Institutes of Health). Videos were compressed and then analyzed by ImageJ. Before separation of the mixture of B and T cells, B cells were prestained by Calcein AM. The purity of the recovery was tested by flow cytometry by detecting the fluorescence of Calcein in B cells. The cell viability was determined using a 5 µg/mL solution of PI and tested by a flow cytometer. All experiments were performed in triplicate, and all errors reported represent the standard deviation of these three measurements. DMC Measurements. In the oscillation system, different cell types have different oscillation speeds based on the affinity between the antigen on the cell surface and the antibody on the capillary wall. Target cells oscillated slower and were captured finally by the corresponding ligand on the capillary surface. From image frames in a time interval, the mobility difference of cells can be calculated (Figure 1) to represent the cell position difference by which the attached cells and unattached cells can be recognized and the cell attaching process can be studied with high temporal resolution. If the difference between two frames is taken, the image background and immobilized cells are subtracted 3338
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out, and only moving cells are imaged. Figure 3 shows the concept of DMC. A zoomed-in portion of a camera frame is shown for clarity. The first frame (no. 1199 of a particular movie sequence) and second frame (no. 1206) are from a video of CD4+ HuT 78 cells oscillating in an anti-CD4 capillary. The two frames were subtracted from each other to reveal the differential image shown in Figure 3. The seven-frame difference (time interval 0.78 s) resulted in an observable change in the cell position for mobile cells. White spots in Figure 3C represent the cells with position changes (moving cells). The intensity of these spots represents the cell mobility difference. Safety Precautions. HuT 78, Jurkat, and RPMI 8226 B cell lines are rated at a biosafety level of 1. Universal precautions for blood-borne pathogens were followed for all cell lines. All personnel were trained in a blood-borne pathogen program and used appropriate personal protective equipment (gloves, laboratory coats, etc.). All materials were disinfected with 10% bleach when necessary. All materials used for cell cultures and cell-related tests were deposited in biohazard containers and autoclaved prior to disposal. A laminar-flow biosafety cabinet appropriate for the required biosafety level was used when handling cell cultures to maintain culture sterility and minimize exposure risk. RESULTS Oscillation System Study. Because cells oscillate under push-pull flow conditions, the flow rate of the oscillation pump must be characterized to allow for cell adhesion while minimizing nonspecific binding. Three main factors of the oscillation system
were studied: the pump revolution speed and pulse frequency, cell velocities at different pump speeds, and the effect of the oscillation frequency on target cells and interference cell attachment. The pulse frequency range of this system is from 4.5 to 64.8 pulses/min. The relationship between the oscillation frequency and the pump speed is shown in the Supporting Information (Figure S-2). The clockwise and counterclockwise pump speeds are the same for any given pump setting (Supporting Information, Table S-1). As seen in the Supporting Information, the current oscillation system, while simple to construct, does have a degree of hysteresis and variability in the cell velocity. The relative standard deviations in the cell velocity for the forward and reverse speeds (Figure S-2) are 62% and 53%, respectively. The variability in the cell velocity is due, in part, to the different velocity profiles in the capillary channel rather than pump oscillation. The standard deviation of the pump speed (Table S-1) is 4% on average between pump speeds. By using a smaller depth of focus to image cells only near the surface, the cell-to-cell variability in the velocity will be smaller. Near the surface, the deviation in the cell velocity is smaller although still significant because cells interacting with affinity molecules will be slower than cells that do not interact with the surface. It should be noted that the variability in the pulse intensity is smaller than the variability of cell-surface interactions. A second-generation pump that will be hysteresis-free and provide better pulse-to-pulse repeatability is currently being designed and will be described in detail at a later date. The cell velocities between different oscillation frequencies and continuous loading at 0.04 mL/h were compared. For measurement of the cell velocity, see the Supporting Information. At 0.04 mL/h continuous loading, the forward and reverse cell velocities were 0.14 ± 0.06 and 0.07 ± 0.01 mm/s, respectively. The relationship between the cell attachment number and oscillation time was tested with target T cells and interfering B cells at different oscillation frequencies. The target cells were CD4+ and matched the antibody in the separation channel, while the CD4B cells served as a test of interference and nonspecific binding. In this test, B and T cells were oscillated in an anti-CD4-coated capillary separately, and the captured cell number at one spot was monitored during oscillation. While normalized cell concentrations (see the Supporting Information for normalization methods) are used, the absolute numbers of cells imaged in parts A-C of Figure 4 respectively are 18 ± 7 B cells, 88 ± 52 T cells; 2 ± 1.7 B cells, 20 ± 4 T cells; and 2 ± 2 B cells, 81 ± 56 T cells. The large difference in the cell number in this case reflects differences in loading cell concentrations. The normalization methods used for Figure 4 remove the contribution of different input concentrations to the measurement error. The number of attached T cells reached a plateau after 5-10 min. At high oscillation frequency (Figure 4C), it took a longer time to reach the plateau than at low oscillation frequency. At a lower oscillation frequency (Figure 4A), more B cells were attached to the anti-CD4 capillary. The nonspecific binding is higher at lower oscillation frequency than that at higher frequency because of the longer time needed for a cell to nonspecifically bind to the surface (instead of the strong antibody-antigen bond formed by the target cell and the surface). On the basis of this
Figure 5. Frame difference optimization in DMC: (A) Differential images of a moving cell with increasing frame difference (1-5 frames). (B) Effect of the frame difference on the cell mobility image intensity. As the frame difference increases, overlap between the new and original cell position diminishes, resulting in a greater difference between the two image frames. The unit of mobility difference is arbitrary units (au); error bars represent the standard deviation.
test, an optimized oscillation time of 10 min and an oscillation frequency of 20.7 pulses/min were used. DMC: Frame Difference Optimization. Figure 5A shows the mobility differences measured in different frame differences (intervals) in a 4× objective video. The signal intensity (mobility difference) increased with the frame difference increase. With small frame differences, the cell has not moved significantly from the starting position, and the difference image is essentially a crescent shape of narrow width. As the cell travels further from the starting point, the crescent expands and the moving cell is observed. Figure 5B shows the cell mobility signal intensity increased from around 300 at a 1-frame difference to 1400 at a 6-frame interval. The mobility intensity is determined by the integrated intensity of the cells in the difference image (the integration eliminates the need to accurately size the objects because the image background is zero). Seven moving cells were identified by visual inspection of the CCD image stream (movie), and those cells were subsequently analyzed by the differential imaging approach. The average differential image intensity for moving cells reaches a plateau at 6 frames for the flow rate used in this study. DMC: Monitoring T Cell Adhesion and B Cell Movement. During oscillation, the B lymphocytes kept moving and T lymphocytes slowed down and attached on the antibody-modified capillary surface. Figure 6 shows an index figure, which is an average of 6 images from frame no. 583 to no. 588 (in a 10 × objective) of the particular movie used in this study. The time interval of these images is 0.6 s. The adhesions of three T lymphocytes, A-C, and a mobile B lymphocyte, D, were analyzed by DMC. A piece of cell debris labeled E affected the signal intensity when a fixed-position window was used to analyze cell D (see the Supporting Information). Figure 7A is the mobility difference of T cell A oscillating from 2.4 to 4.1 s. The mobility Analytical Chemistry, Vol. 81, No. 9, May 1, 2009
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Figure 6. Average of 6 frames of a B lymphocyte and T lymphocyte mixture oscillating at 64.8 s. A-C are three attached T cells during oscillation, D is an unattached B lymphocyte, and E is a piece of cell debris. The white squares are analyzing windows. The black square for cell C is an improper analyzing window. With both a white light lamp and a mercury lamp on, Calcein AM prestained B cells are bright and T cells are dark in this figure.
difference of cell A decreased from around 45 000 to 3000 corresponding to the cell adhering to the capillary surface. At 2.7 s, the small trough on the mobility difference curve represents the cell slowing down quickly. That is presumably because several antibody-antigen bonds were formed but the affinity was not strong enough to fully stop the cell. The flat region of the mobility curve represents cell rolling, where bonds are broken and formed as the cell moves along the surface. As the bonds continue to be formed, the cell slows and finally stops moving at 3.8 s. In contrast, HuT 78 cells oscillating in a capillary with a mismatched capillary (coated with anti-CD19 antibodies) exhibited higher mobility differences (Figure 7B). In this case, cells near the surface were not retained by the antibody and were able to continue to oscillate, albeit at a slower mobility than cells in the center of the channel. The adhesion processes for two more T lymphocytes, cells B and C from Figure 6, were also analyzed by DMC. The mobility differences over time were calculated to determine the mobility difference curve (Figure 8A; also see the Supporting Information for details of cell B). Cell C (Figure 8B) rocked back and forth in its anchor point on the surface several times and was attached on the capillary surface after 66.4 s. The effect of the image analysis window size/shape is discussed in the Supporting Information. After two oscillations at 61.7 and 64.4 s, cell C slowed down and attached on the capillary. On the mobility difference curve, there were two peaks at which the mobility difference intensities were 11 000 and 7000. The mobility difference decreased to 1300 at 66.4 s, indicating that cell C had adhered on the capillary surface at that time. Not only is the DMC sensitive to the cell immobilization, but it also can detect cell gentle movement such as wagging. Not all of the attached cells are immobile on the antibody-coated capillary surface. Cell B, which was attached on the capillary surface, swung back and forth in every pulse. Figure 8A shows that the mobility difference of cell B varied from more than 10 000, which represents the cell position change, to near 2000, which represents cell immobile. Two peaks in the interval of 6 s from 58.5 to 64.5 s 3340
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Figure 7. (A) One T lymphocyte (cell A in Figure 6) mobility difference changing during the adhesion process. The initial decrease in mobility (marked by an arrow) is due to the cell interacting with the surface and decelerating. Approximately 25 bonds are formed during this initial capture process. After a brief period, the cell continues to slow as more bonds are formed with the surface, until the cell stops entirely. (B) Three typical HuT 78 cells in a mismatched capillary (antiCD19), showing a large mobility even for cells at the surface of the capillary.
indicate that the cell wagging frequency is 20 pulses/min, which agrees with the frequency of oscillation (20.7 pulses/min). At 58.5 s, 61.17, and 64.5 s, the peak values are 6000, 12 900, and 9900, respectively. Slight variations in the distances between the poles on the roller and the hose on the current oscillation generator led to different pressures on the cells in the capillary; therefore, the cell mobility difference changed. In the future, a precision-machined roller will eliminate this pulse difference. One moving B lymphocyte (cell D) was analyzed by DMC to demonstrate the ability of the technique to detect moving cells. The mobility difference curve (Figure S-4 in the Supporting Information) using a fixed-position window can detect the cell moving in (at 61.7, 64.4, and 65.0 s) and out (at 60.4 and 61.1 s) of the analyzing window. When cell D moved out of the analyzing window, the mobility differences were lower than 2000, and when cell D moved back into the analyzing window, the mobility differences were higher than 8000. A sliding analysis window could also be used, where the region of interest on the image moved
Table 1. Cell Capture in Anti-CD71 Capillaries and Antigen Expression cell capture (%) cell line
2 min
10 min
antigen densitya (µm-2)
HuT 78 Jurkat T
92 ± 7 9±3
95 ± 7 25 ± 7
660 ± 90 160 ± 12
a
Figure 8. Observation of movement (wagging) of attached cells. One attached cell wagging under oscillating flow (cell B in Figure 6), showing a movement frequency corresponding to the oscillation frequency (A). A second anchored cell, also rocking on the surface, finally comes to a complete stop as more antigen-antibody bonds are formed between the cell and the surface (B).
with the cell (see the Supporting Information). With a sliding window in the interval of 60.4-67.7 s, the mobility differences of cell D were all higher than 7500. Both analyzing windows showed the same trend of the mobility difference curves. Because cells oscillate back and forth in the carrier fluid, there will be two points in each oscillation cycle where even the moving cells appear to be at rest. At each flow reversal, suspended cells and cells rolling along the separation channel surface will stop and reverse direction. During this brief velocity change, the mobility of all cells will appear to be near zero. In order to avoid this artifact, image differences during these points of the oscillation cycle were discarded. DISCUSSION Cell Capture in Oscillating Flow. Using Lauffenburger’s model of cell adhesion, the capture time determined by DMC can be used to estimate the number of bonds formed in the capture process, regardless of the flow rate in the channel. In this study, the mean time for cell capture was 0.8 ± 0.6 s with a frame rate difference (temporal resolution) of 0.1 s. The standard deviation of 0.6 s is due to the random nature of cell interactions with the surface and not the experimental precision, which is currently limited by pulse-to-pulse differences. Normally, a larger frame rate difference is used for smaller data files and less processing if only
b
Measured by flow cytometry. b Represents standard deviation.
free or bound cells are to be detected. However, a smaller frame difference, resulting in higher temporal resolution, can be specified for adhesion studies. Because the raw movie files are retained, frame selection can be changed depending on the experimental need. Using eq 1 and the cell-capture time, the mean number of bonds formed during cell capture can be estimated. The cell contact area with the affinity surface (Ac) can be estimated to be 2 µm2.36 The CD4 antigen density for the HuT 78 cell line used in this study was measured by flow cytometry to be 125 antigens/µm2. Using the mean capture time, the number of bonds formed during cell capture was estimated to be 200 ± 150 bonds/cell. The variation in this bond number is due primarily to the random nature of cell collision and capture rather than the error in antigen expression measurement or cell size measurement (10% and 7%, respectively). In the fastest cell capture (measured at the highest DMC resolution to be 0.1 s), the number of bonds formed during cell capture was 25 bonds (Figure 7A). In this case, the number of bonds was insufficient to fully immobilize the cell, which continued to roll until the cell stopped completely. In the slowest cell-capture cases (1.3 s), approximately 325 bonds were formed, resulting in complete immobilization (no swaying). In comparison, cell capture using two similarly sized cell types (with different antigen densities) showed a similar relationship between antigen density and capture. HuT 78 cells captured in anti-CD71 capillaries showed little swaying behavior (i.e., rigid capture), with a mean capture time of 0.32 ± 0.01 s (n ) 3 for these analyses). This capture time corresponded to 430 ± 15 bonds with an antigen density of 660 antigens/µm2. Jurkat cells, which were determined to have an antigen density of 60 antigens/ µm2 for these tests, exhibited a more random capture time with swaying behavior present for most cells. The mean capture time for Jurkat cells was 0.40 ± 0.20 s, corresponding to 39 ± 26 bonds formed during capture. The differences in the surface antigen density and cell capture were also measured (Table 1). Flow cytometry was used to determine the differences in the antigen expression of HuT 78 and RPMI 8226 cultured cells. Anti-CD71-coated capillaries were then tested for cell capture for both cell types. At both 2 and 10 min after injection, more HuT 78 cells were captured than Jurkat cells. As a control, using a mismatched capillary (HuT 78 cells in an anti-CD19 capillary) showed no cell capture at both oscillation times. At both 2 and 10 min, the percentage of cells that were captured in anti-CD71 capillaries follows the trend of the antigen expression. Differences in cell size and settling time, albeit small, contribute to the differences between the antigen expression and capture ratio. Effect of the Radial Position. Changes in the radial position will result in slower mobility of cells, regardless of whether Analytical Chemistry, Vol. 81, No. 9, May 1, 2009
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antigen-antibody bonds are formed. In order to discern if cells are indeed being captured by antigen-antibody bonds or are simply settling and stopping on the cell surface, HuT 78 cells were oscillated in an anti-CD19 column and mobility differences were recorded over a 20-min period. At any time in the separation, fewer than two HuT 78 cells were retained in the capillary. Mobility values of 11 000-18 000 were measured for cells on and near the surface at the slowest end of the oscillation cycle (Figure 7B). Cells near the surface but lacking antigen-antibody bonds to retard their movement had larger mobilities than CD4+ T cells measured in anti-CD4 capillaries (Figures 7A and 8). Therefore, while the radial position does affect the velocity, unbound cells that reach the surface have a higher mobility than cells that are captured by antigen-antibody bonds. DMC Temporal Resolution. The camera recording speed, the frame differences, and the mobility difference acquisition method affect the resolution of DMC. The relationship between frame differences and the mobility difference intensity is shown in Figure 5A. Less frame difference results in higher temporal resolution but lower signal intensity, and vice versa. Therefore, an optimized frame difference should be tested to get a proper temporal resolution with high signal intensity (or signal-to-noise ratio). Even at the optimum frame difference for these experiments, the temporal response is less than 1 s, which is more than adequate for long-term cell monitoring. The mobility difference acquisition methods include discrete and continuous acquisition with the CCD camera. In continuous acquisition, the CCD camera acquires at the maximum frame rate and a rolling differential image (i.e., 6 frame difference that is translated every frame) is generated. In discrete acquisition, an image is acquired every 6 frames (i.e., frames 1, 7, 13, 20, etc.). Continuous acquisition produces a high-resolution mobility difference curve. The discrete data acquisition greatly simplifies the data processing but compromises the temporal resolution of DMC to a degree. For example, in Figure 7, the mobility difference curve was made by a continuous acquisition method with a frame difference of 5. Frame nos. 19-24 were used to measure the mobility difference at 2.4 s and then frame nos. 20-25 for time 2.5 s, and so on. In this way, the cell movement in the adhesion process was monitored with a temporal resolution of 0.1 s. In the video, the cell slowed down at 2.5 s, attached on the surface at 3.1 s, and then swung to the right; it fully stopped after 3.7 s. The mobility difference curve showed these adhesion stages clearly. From 2.5 to 2.7 s, the mobility difference decreased from 47 000 to 28 000, which was from the sharp velocity decrease. The swaying of the cell on the surface was shown by a mobility difference decline from 25 000 to 2500 gradually. When a discrete acquisition method is used to acquire the mobility difference curve in the same time interval, there will be only three mobility differences that can be calculated: 44 800 at 2.4 s, 25 200 at 3.1 s, and 7600 at 3.7 s. In this case, the trend of cell adhesion still can be shown from the decreasing of the mobility difference, but some of the changes in cell movement were not observed in the discrete mobility difference curve. Mobility Difference Measurement. The shape, size, and position (either fixed-position or sliding) of the analyzing window contribute to the mobility intensity. In this work, the height of the analyzing window is the diameter of the cell, which can 3342
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minimize the interference arising from other particles, and its width is 4 times the height, which was optimized based on the frame difference. The size of the window affecting the mobility difference is straightforward. The different shapes of analyzing windows in the same area were used to analyze cell C shown in Figure 5. With correctly sized analyzing windows, the cell-adhesion process can be detected by the mobility difference change (as verified by visual observation of the time-lapsed image sequence). With an improperly sized window, the mobility difference intensity was affected by other cells entering the window (see the Supporting Information). Even though cell movement was detected by correctly and incorrectly sized windows, the final deceleration and adhesion of the cell in question was not detected by the incorrectly sized analyzing window. When a sliding analyzing window is used, there is a better discrimination between moving and stationary or wagging cells, and the effect of debris or other cells/particles is minimized. CONCLUSION DMC has proven to be an effective method for studying cell separation and cell adhesion with high temporal resolution. By combining affinity separations under oscillating conditions with differential imaging, DMC has the advantage of separating and analyzing at the same time without sample pretreatment. To obtain accurate cell mobility information with DMC, several conditions must be optimized including the frame difference and the dimensions of the analyzing window. The temporal resolution was determined by the recording the speed of the digital camera and the mobility difference data acquisition method. Continuous acquisition results in higher temporal resolution than discrete acquisition, at the expense of the data processing workload. In DMC, normally three main moving patterns of cells can be detected: the unattached cells (in flow or rolling along the separation surface), attached cells (immobilized), and attached cells (wagging/rocking). The qualitative detection of cell adhesion was presented in this paper. The quantitative DMC method to monitor the different cell-adhesion stages can be fulfilled in the future by normalizing mobility differences by the area of analyzing window so that the mobility differences of cells of different sizes can be compared. With the normalized mobility difference intensity, thresholds can be set to evaluate the cell moving pattern such as sliding, floating, wagging, and so on. These two improvements will make the DMC a robust method for analyzing cell adhesion and other cell-adhesion-related studies. DMC can also be used for long-term cell observations, particularly in the cases where a cell-surface marker evolves over time. An excellent example of this, which is currently in progress and will be published in the future, is monitoring the externalization of phosphotidyl serine in apoptotic cells using Annexin-V-coated separation channels. Currently, glass capillaries are used in DMC because of their ease of use. However, for added cell analysis capabilities, microfluidic devices based on PDMS are being developed. Moving to a PDMS channel is critical for longer-term cell monitoring because gas exchange in the glass capillaries is not as efficient as that in PDMS devices. DMC is a new technique, and therefore the potential uses are large and varied. The technique is capable of long-term cell observations, affinity separations, and adhesion-surface interac-
tion studies. DMC could be applied to the study of biofouling, antibody/aptamer screening, and adhesion of successive cell layers used in coculture, as well as other cytometric applications. DMC is also amenable to multiparameter detection, such as the incorporation of fluorescence microscopy of attached or mobile cells. ACKNOWLEDGMENT This work was supported by startup funds from Texas Tech University. Scott Heimstra of the TTU Department of Chemistry and Biochemistry Machine Shop is acknowledged for his consult-
ing and fabrication of the oscillation generator. C.A and X.S.-W. were supported by the University Research Fellows program. SUPPORTING INFORMATION AVAILABLE Additional data and a movie of oscillating T and B lymphocytes. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review December 1, 2008. Accepted March 18, 2009. AC900277Y
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