The authors would like to acknowledge Lloyd Ung for constructive input in early versions of this technique, Dr. Jeremy Agresti for pressure cap design tips, and Dr. Dongping Qi for his help in fabricating the pressure cap. We are grateful to the laboratories of M. Teitell and P. Gunaratne for providing a variety of cell samples for testing. We are grateful to the National Science Foundation (CAREER Award DBI-1254185), the UCLA Jonsson Comprehensive Cancer Center, and the UCLA Clinical and Translational Science Institute for supporting this work.

1. Microfluidic Device Design
NOTE: The device design has four basic functional regions: entry port, cell filter, constriction array, and exit port (Figure 1). The overall design can be applied to a wide array of cell types, with minor adjustments to dimensions. Provided here are a few basic design recommendations along with device parameters that are effective for a selection of both primary and immortalized cells.
<ol>
	<li>Select the width of constriction array channels (Figure 1B) to be approximately 30-50% of the average cell diameter; this constriction-to-cell size ratio results in significant cell deformation but minimal clogging. Given a cell type that has not previously been tested, it is prudent to design a range of constriction widths from ~30-50% the cell diameter to find the optimum width. As with many types of microfluidic devices, over 120 device master molds can be patterned on a single 4 inch silicon wafer, enabling an array of different device designs to be fabricated in a single fabrication process.</li>
	<li>Select the channel height to be at least 50% of the cell diameter; this ensures the cell is confined in 2&#160;dimensions. To prevent channel collapse during bonding, ensure that the channel aspect ratio is no less than 1:10 (height:width) throughout the device. For channels that must exceed this aspect ratio, add support posts to prevent collapse. Space support posts at a distance that is at least twice the cell diameter as to not impede cell flow.</li>
	<li>Include a filter at the entry ports to remove debris and disaggregate cell clusters (Figure 1B). Adjust the size and spacing of the filter posts so that the distance separating the posts is approximately equal to one cell diameter. 
	NOTE: The lower limit of feature size is set by the resolution at which the lithography mask is printed. Ensure that all features are within the resolution limit specified by the mask supplier.</li>
</ol>
2. Supplies and Preparation
NOTE: Before commencing any experiment, the following items must be prepared. A schematic of the entire setup is given in Figure 1.
<ol>
	<li>Fabricate the device master using standard techniques for lithographic micromachining14,15. Verify the height of the patterned features using a profilometer. 
	NOTE: While masters can be easily fabricated in a cleanroom facility, some labs have developed inexpensive lithography methods for use in a semi-clean environment16,17.</li>
	<li>Prepare the air source for pressure-driven flow, using a tank of compressed air and sequence of air regulators and fittings (Figure 1A).
	<ol>
		<li>Set up an air supply tank and manual regulator. 
		NOTE: A composition of 5% CO2 in air maintains a similar environment as a typical cell culture incubator, but other gas mixtures can also be used.</li>
		<li>Set up an electronically controlled pressure regulator in-line with the manual regulator. Use an electro-pneumatic converter to regulate and maintain a stable pressure drop across the channels, with pressure fluctuations of less than 2 kPa. Use the simple code written in LabVIEW (Supplementary Information) to input the desired pressure. 
		NOTE: The electro-pneumatic converter uses an internal feedback loop to adjust the valve outlet pressure to match the specified pressure across the microfluidic device.</li>
		<li>Set up a pressurized chamber to drive flow of the cell suspension. Assemble a cell suspension chamber out of a standard flow cytometer tube and a machined cap that creates a pressure-tight seal on the tube. 
		NOTE: The pressure chamber cap contains two orifices: an inlet that connects to the compressed air tank, and an outlet through which cells flow from the pressurized chamber into the device (Figure 2).</li>
	</ol>
	</li>
	<li>Set up an inverted microscope fitted with a camera that has an acquisition rate of at least 100 frames per sec&#160;to capture images of the cells flowing through the constriction array. Interface the camera with a video capture card and a computer.</li>
	<li>Prepare a stock surfactant solution of 10% w/w Pluronic F-127 in phosphate buffered saline (PBS) as adding a small amount of F127 to the cell media solution will help to minimize cell adhesion to the PDMS walls. To prepare the F127 solution, vortex and heat gently at 37 &#176;C&#160;to dissolve the F127. Prior to use, pass the solution through a 0.2 &#181;m syringe filter and store at room temperature. Prepare the surfactant solution in advance as vortexing and filtering will generate bubbles that will persist for more than 24 hr.</li>
</ol>
3. Microfluidic Device Fabrication
<ol>
	<li>Fabricate PDMS block with microfluidic channels.
	<ol>
		<li>Mix PDMS thoroughly at a ratio of 1:10 (w/w) curing agent to base.</li>
		<li>Pour the mixture over the device master (Step 2.1). Degas in a bell jar with applied vacuum until the entrapped bubbles disappear, or for about 10-20 min. 
		NOTE: After this time, there may still be bubbles at the air-PDMS interface, which is normal; these will typically dissipate during baking. It is most critical to ensure that there are no remaining bubbles adjacent to the channels.</li>
		<li>Bake the degassed device at 65 &#176;C&#160;for 4 hr. To prevent channels from collapsing, bake the device overnight to further crosslink the PDMS for a device with a higher elastic modulus that is more resistant to channel collapse. However, note that extended baking also embrittles the PDMS and may lead to cracking when punching holes (Step 3.3).</li>
	</ol>
	</li>
	<li>Remove microfluidic devices from the master mold. Cut individual microfluidic devices out of the PDMS block with a razor blade and remove the device from the master. Start by gently lifting off one corner of the device; slow and gentle peeling, as opposed to lifting the PDMS block straight up, reduces the stress on both the PDMS and the master.</li>
	<li>Punch holes in the PDMS device to create connection ports for access between tubing and microchannels. Create holes using a biopsy punch, and&#160;punch from the channel side through to the exterior side of the device. 
	NOTE: A biopsy punch with a 0.75 mm bore size creates holes that interface perfectly with polyetheretherketone (PEEK) tubing (outer diameter = 1/32&#8221; or 0.79 mm) or polyethylene tubing (PE-20, outer diameter = 0.043&#8221; or 1.09 mm). Use a ring light to help visualize holes in devices with shallow channels18. Be sure the biopsy punch is sharp; after repeated use the cutting edge dulls and the biopsy punch should be discarded and replaced.</li>
	<li>Rinse the PDMS device with isopropanol (HPLC grade) to remove dust and lodged chunks of PDMS. Make sure the punched holes are clear of debris by directing a steady stream of pure isopropanol from a squeeze bottle through the holes. Blow dry with filtered air. After cleaning, place PDMS blocks with channels face up in a clean Petri dish to maintain device cleanliness. If required, store devices in this form until bonding.</li>
	<li>Clean the glass substrate by rinsing with methanol (HPLC grade), blow dry with filtered air, and place on&#160;a 200 &#176;C&#160;hotplate&#160;for 5-10 min to ensure the glass is completely clean and dry before plasma treatment. 
	NOTE: The glass substrate forms the bottom of each channel. Typically a glass slide suffices, since a 10X&#160;or 20X&#160;objective is ideal for imaging multiple channels in parallel. For higher resolution imaging, bond the device to a coverslip (#1.5 thickness).</li>
	<li>Bond the PDMS device to the glass substrate.
	<ol>
		<li>Oxygen plasma treat the channel side of the PDMS block and 1&#160;side of a glass slide. 
		NOTE: With a hand-held discharge unit, use a treatment time of 1 min, but optimize the treatment time for each oxygen plasma apparatus.</li>
		<li>Place the channel side of the PDMS on top of the treated side of the glass immediately after treatment.</li>
		<li>Hold together with light pressure for ~10 sec to promote bonding. Bake the entire device at an elevated temperature (60-80&#160;&#176;C) for at least 15 min to improve bond strength.</li>
	</ol>
	</li>
</ol>
4. Deforming Cells through Constricted Channels
<ol>
	<li>Inspect the microfluidic device under a microscope. Ensure that the channels are not collapsed or broken and that both inlet and outlet holes connect directly into the device channels by using a low-power objective (10X). Designate defective devices by scoring the surface of the PDMS with a razor blade and do not use them for experiments.</li>
	<li>Prepare the cell culture samples to be assayed. Culture cells using standard conditions.
	<ol>
		<li>For example, culture HL-60 cells in RPMI-1640 medium supplemented with 1% penicillin-streptomycin solution and 10% fetal bovine serum in 5% CO2 incubator at 37 &#176;C.</li>
		<li>For adherent cells, harvest them by trypsinization and resuspend in fresh growth medium. Use a standard trypsinization protocol; for example, add ~0.5 ml&#160;trypsin to a flask with 25 cm2 culture area, and resuspend in ~30 ml&#160;fresh medium. Differentiate HL-60 cells into neutrophil-type cells by all-trans retinoic (ATRA) at a final concentration of 5 &#181;M per 1 x 105 cells/ml as previously described19,20.</li>
		<li>Centrifuge the cells at 300 x g for 3 min, carefully aspirate the supernatant and resuspend cells to the appropriate final density in fresh culture medium with 0.1% v/v F-127.</li>
	</ol>
	</li>
	<li>Count the cells using a Coulter counter, hemacytometer, or flow cytometer. Adjust the cell suspension to a density of 1 x 106 to 5 x 106 cells/ml. Once the suspension density is set, supplement with approximately 0.1% v/v F-127. 
	NOTE: The cell density and surfactant concentration may need to be modified depending on the particular cell systems; Table 1&#160;provides a record of previously used concentrations of cells and F-127 for different cell types.</li>
	<li>Place cell suspension in a flow cytometer tube and connect to the pressure cap. Before connecting the tubing to the microfluidic device, adjust the pressure to about 14-21 kPa and flush until the cell suspension emerges from the tip of the tubing. This will help to minimize air bubbles in the tubing and device.</li>
	<li>Insert the tip of the tubing containing the cell suspension into the device inlet. If the device is bonded to a coverslip, place the device on a flat, solid surface such as the microscope stage before connecting the tubing; the coverslip is fragile and may otherwise break.</li>
	<li>Insert a piece of tubing into the exit port and route it into an empty tube for waste collection such as an empty Falcon tube taped to the side of the microscope stage. For consistency in the overall fluidic resistance of the device between experiments, ensure that the inlet and outlet tubing is of the same diameter and approximately the same length for each experiment.</li>
	<li>Gently ramp up the pressure to about 28 kPa or until cells flow through the channels. Position the device so that multiple channels are in the field of view and are perpendicular to the bottom of the screen. If the camera is limited by data size, acquire multiple videos to generate a sufficient number of independent data points. Adjust the frame rate as necessary for the desired data output. To capture changes in cell shape, use high speed imaging at 300 frames per sec&#160;(fps); to measure transit times of cells, use frame rates of approximately 100 fps.</li>
</ol>
5. Data Analysis
<ol>
	<li>Open the file Master_script.m (Downloadable Supplemental File) and run the program.</li>
	<li>Select the first video to be analyzed from the Windows Explorer window that appears. Specify the frame rate for the selected video and press enter. 
	NOTE: A figure will appear that prompts the user to select a rectangular cropping window for the first video.</li>
	<li>Select a window that encompasses all the channels from left to right and intersects the channels just above the first bulb of the array of channels at the top and bottom (Figure 3).</li>
	<li>Select the constriction regions from the cropped image. Pay special attention to maintain a fixed pixel distance between the top and bottom window boundary for every video selected. 
	NOTE: The top window edge specifies the topmost constriction and bottom window edge specifies the bottommost constriction (Figure 4); intermediate constrictions are approximated from this user input. Next, the algorithm displays the segmentation of cells for the first 50 frames of each video (Figure 5).</li>
	<li>Monitor the top left image (Figure 5A) closely to determine if the algorithm is accurately locating cells; a binarized image is superimposed on the source video to demonstrate the location of identified cells. 
	NOTE: The different windows, (Figures 5B-5D) are for code diagnosis and demonstrate the video frames after specific image processing operations.</li>
	<li>Select the next video to be processed from the Windows Explorer window. 
	NOTE: The algorithm will repeat steps 5.2-5.5 for each video selected.</li>
	<li>Select cancel once all desired videos have been added via the Windows Explorer window to instruct the function that the video list is complete. 
	NOTE: The algorithm will perform the remaining operations without user intervention. This will take approximately 1-2 hr&#160;depending on the number of videos processed and computer performance. Upon completion, the algorithm will produce a histogram of the transit time data and save the data in the directory as a MATLAB .mat file and a Microsoft Excel .xls file.</li>
</ol>

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The authors have no conflicts of interest to disclose.

Here we provide a comprehensive experimental procedure for analyzing the deformation of cells transiting through constricted microfluidic channels using pressure-driven flow. A MATLAB script enables automated data processing (Supplemental Material); an updated version of the code is maintained (<a href="http://www.ibp.ucla.edu/research/rowat" target="_blank">www.ibp.ucla.edu/research/rowat</a>). More broadly, the techniques presented here can be adapted in many cell-based microfluidic assays, including the effect of cytoskeletal and nuclear stiffening agents24,23 as well as assaying the deformability of cancer cell types4,5. Taken together with higher resolution microscopy to image subcellular deformations, this method provides a powerful approach to study cell mechanical properties and alterations that occur in physiological and pathological conditions.
Automatic Cell Processing Algorithm
The acquired movies can be analyzed with little user intervention using a MATLAB script. The algorithm is outlined in Figure 7, and the set of MATLAB functions is provided in the Supplementary Information. In brief, the user is instructed to select all the videos to analyze; crop each video for the region of interest; and specify a frame rate for the set of videos; thereafter, the software automatically processes video data to determine the transit time of each cell for each constriction. There are certain requirements for the script to operate: cells should flow from the top of the frame to the bottom of the frame in the video; the microfluidic device position and the lighting conditions should not change appreciably over the duration of the video; and videos should be in .avi format. Importantly, the tracking algorithm includes cells that both enter and passage in the time window of a single video recording, which is approximately 8 sec. Therefore, any objects that have a longer transit time are excluded from the analysis. By performing background subtraction, objects that are present throughout the entire video are removed from the analysis. The code also implements a lower size cutoff, which may be set by the user. The size cutoff for the video analysis was 5 pixels, equivalent to a cell diameter of 2.7 &#181;m.
Since the high-speed video data files can be sizable (~500 MB), the program is computationally intensive. Code is most efficiently run using a desktop computer with at least 6 GB of RAM and a 64-bit chipset with either a local hard drive with at least a 1 TB capacity or interfaced with a large external hard drive or data server with a USB 3.0, FireWire, or Ethernet connection. Data is output in a histogram format for rapid visualization of results; it is also tabulated as data that is stored in a MATLAB (.mat) data file and in an Excel spreadsheet.
The code that is presented provides a simple way to compare cell populations by analysis of the transit time for cells to passage through each constriction. For more detailed analysis, the code could be extended to investigate other parameters including cell size, aspect ratio, as well as relaxation timescale. Previous studies reveal only a weak dependence of cell size on transit time6.
Device-related Pitfalls
Occluded channels are a major hindrance in any flow experiment. Cell adhesion to the device walls will impair the flow of cells through the constricted channels: cells may be observed to smear out along the channel walls. To prevent adhesion, proper surface treatment with F-127 is essential.
The surface properties of PDMS change with time after plasma treatment, which renders the PDMS temporarily hydrophilic25,26. Over the course of one week, hydrophilic PDMS surfaces slowly degenerate to their natural hydrophobic surface energy; this can challenge the removal of air bubbles through the channels. Devices should thus be used within seven days of plasma treatment. Most importantly, the time between plasma treatment and the deformability assay should be consistent across all experiments.
While we have successfully distinguished transit times between distinct cell types using devices fabricated with a glass floor and three PDMS walls, devices can also be fabricated so they have uniform surface properties on all four channel walls27. The PDMS device can be bonded to a glass substrate spincoated with a thin PDMS layer: mix curing agent to base at a ratio of 1:5 (w/w), pour onto the device mold, and cure for 20 min at 65 &#176;C. Meanwhile, spincoat a thin layer of 1:20 (w/w) curing agent to base onto the glass substrate; bake at 85 &#176;C for 4 min. Place the PDMS device on the PDMS-coated slide, and finish baking overnight to complete bonding. This method is also valuable if a plasma machine for glass-PDMS bonding is not available.
Cell-related pitfalls. 
hen preparing the cell suspension, the density of cells is critical: if the cell density is too low, cell transit events will be infrequent; if the cell density is too high, there will be multiple cells passaging a single channel simultaneously, the pressure drop across a single cell will not be consistent, and it will be difficult to delineate individual cells with an automated script.
While experiments are typically performed within 30 min&#160;of cell suspensions being prepared, cells can settle to the bottom of the pressure chamber over longer times of &#62;30 min. To avoid settling over longer time periods, the pressure chamber and connecting tubing can be periodically rotated. For longer experiments, a small magnetic stir bar can be added to the cell suspension, with a stir plate positioned beneath the pressure chamber to agitate the cells and prevent settling.

Changes in cell shape are critical in numerous biological contexts. For example, erythrocytes and leukocytes deform through capillaries that are smaller than their own diameter1. In metastasis, cancer cells must deform through narrow interstitial gaps as well as tortuous vasculature and lymphatic networks to seed at secondary sites2. To probe the physical behavior of individual cells, microfluidic devices present an ideal platform that can be customized to study a range of cell behaviors including their ability to migrate through narrow gaps3 and to passively deform through micron-scale constrictions3-9. Polydimethylsiloxane (PDMS) microfluidic devices are optically transparent, enabling cell deformations to be visualized using light microscopy and analyzed using basic image processing tools. Moreover, arrays of constrictions can be precisely defined, enabling analysis of multiple cells simultaneously with a throughput that exceeds many existing techniques10,11.
Here we present a detailed experimental protocol for probing cell deformability using the &#8216;Cell Deformer&#8217; PDMS microfluidic device. The device is designed so that cells passage through sequential constrictions; this geometry is common in physiological contexts, such as the pulmonary capillary bed12. To gauge cell deformability, transit time provides a convenient metric that is easily measured as the time required for an individual cell to transit through a single constriction4,6. To maintain a constant pressure drop across the constricted channels during cell transit, we use pressure-driven flow. Our protocol includes detailed instructions on device design and fabrication, device operation by pressure-driven flow, preparation and imaging of cells, as well as image processing to measure the time for cells to deform through a series of constrictions. We include both device designs and vision data processing code as supplemental files. As a representative sample of data, we show cell transit time through a series of constrictions as a function of the number of constrictions passaged. Analysis of the timescale for cells to transit though narrow constrictions of a microfluidic device can reveal differences in the deformability of a variety of cell types4,5,13. The device demonstrated here uniquely surveys cell transit through a series of micron-scale constrictions; this design emulates the tortuous path that cells experience in circulation and also enables probing additional physical characteristics of the cells such as relaxation time.

<table><tbody><tr><td>Pluronic F-127 Block Copolymer Surfactant&amp;nbsp;</td><td>Fisher Scientific&amp;nbsp;</td><td>8409400</td><td>Produced by BASF, also available through Sigma</td></tr><tr><td>PDMS base and crosslinker</td><td>Essex Brownell</td><td>DC-184-1.1</td><td>Product commonly named Sylgard 184 Elastomer</td></tr><tr><td>Oxygen plasma discharge unit</td><td>Enercon</td><td>Dyne-A-Mite 3D Treater</td><td></td></tr><tr><td>Biopsy Punch, Harris Uni-Core (0.75 mm)</td><td>Ted Pella, Inc.</td><td>15072</td><td></td></tr><tr><td>Fingertight Ferrule, 1/32&quot;</td><td>Upchurch Scientific</td><td>UP-F-113</td><td></td></tr><tr><td>Fingertight III Fitting, 10-32</td><td>Upchurch Scientific</td><td>UP-F-300X</td><td></td></tr><tr><td>Polyetheretherketone (PEEK) tubing, outer diameter = 1/32&quot;or 0.79 mm</td><td>Valco</td><td>TPK.515-25M</td><td></td></tr><tr><td>Polyethylene (PE-20) tubing, 0.043&quot; or 1.09 mm</td><td>Becton Dickinson</td><td>427406</td><td></td></tr><tr><td>Pressure regulator</td><td>Airgas or Praxair</td><td></td><td></td></tr><tr><td>Polyurethane tubing, 5/32&amp;rdquo; OD</td><td>McMaster Carr</td><td>5648K284</td><td></td></tr><tr><td>Push-to-connect fittings</td><td>McMaster Carr</td><td>5111K91</td><td></td></tr><tr><td>Voltage to Pressure (E/P) Electropneumatic Converter</td><td>Omega</td><td>IP413-020</td><td></td></tr><tr><td>16-bit, 250 kS/S, 80 Analog Inputs Multifunction DAQ</td><td>National Instruments</td><td>NI PCI 6225-779295-01</td><td></td></tr><tr><td>Analog Connector Block-Screw Terminal</td><td>National Instruments</td><td>SCB-68-776844-01</td><td></td></tr><tr><td>LabView System Design Software</td><td>National Instruments</td><td></td><td></td></tr><tr><td>MATLAB Software</td><td>The MathWorks, Inc.</td><td>MATLAB R2012a</td><td>Code requires the Image Processing Toolbox</td></tr><tr><td>Shielded Cable</td><td>National Instruments</td><td>SHC68-68</td><td></td></tr></tbody></table>

a microfluidic technique to probe cell deformability

Here we detail the design, fabrication, and use of a microfluidic device to evaluate the deformability of a large number of individual cells in an efficient manner. Typically, data for ~102 cells can be acquired within a 1 hr experiment. An automated image analysis program enables efficient post-experiment analysis of image data, enabling processing to be complete within a few hours. Our device geometry is unique in that cells must deform through a series of micron-scale constrictions, thereby enabling the initial deformation and time-dependent relaxation of individual cells to be assayed. The applicability of this method to human promyelocytic leukemia (HL-60) cells is demonstrated. Driving cells to deform through micron-scale constrictions using pressure-driven flow, we observe that human promyelocytic (HL-60) cells momentarily occlude the first constriction for a median time of 9.3 msec before passaging more quickly through the subsequent constrictions with a median transit time of 4.0 msec per constriction. By contrast, all-trans retinoic acid-treated (neutrophil-type) HL-60 cells occlude the first constriction for only 4.3 msec before passaging through the subsequent constrictions with a median transit time of 3.3 msec. This method can provide insight into the viscoelastic nature of cells, and ultimately reveal the molecular origins of this behavior.

To investigate the deformability of different cell types, human myeloid leukemia cells (HL-60), differentiated neutrophil cells, mouse lymphocyte cells, and human ovarian cancer cell lines (OVCAR8, HEYA8) are evaluated using the &#8216;Cell Deformer&#8217; microfluidic technique. Representative results for the transit time of HL-60 and neutrophil-type HL-60 cells show the timescale for a single cell to transit through a series of constrictions, as shown in Figure 6. Transit time is measured for a population of individual cells at each 7 &#181;m constriction in a series of 7 constrictions at a driving pressure of 28 kPa (Figure 6).
As shown in Figure 6, HL-60 cells temporarily occlude the first constriction for a median time of 9.3 msec before passaging through the subsequent constrictions. By contrast, neutrophil-type HL-60 cells occlude the first constriction for only 4.3 msec before passaging. The shorter transit time of the HL-60 cells is consistent with their reduced elastic and viscous moduli, as determined by atomic force microscopy21 and micropipette aspiration22. These results are also consistent with the reduced levels of the mechanoregulating protein, lamin A, which determine transit times of cells through micron-scale gaps23. Once through the first constriction, cells transit more quickly through the remaining constrictions, from 2 to 7, with a median transit time of 4.0 msec for the HL-60 cells and 3.3 msec for the neutrophil-type cells (Figure 6). While the HL-60 cells still exhibit slightly longer but significant transit times (C2-C7, p = 1.7E-9), the distribution of transit times for constrictions 2-7 are nearly identical for each cell type. The observation of the longer transit time required for the first constriction may reflect that the viscoelastic cells do not fully relax to their initial shape on these ~msec timescales. This behavior may also be explained by irreversible structural changes that develop within the cell, and facilitate their transit through the subsequent micron-scale gaps. Importantly, by comparing transit time among cell populations, even for the first constriction, can reveal differences in their deformability23.
<img alt="Figure 1" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig1highres.jpg" width="500" /> 
Figure 1. Schematic illustration of the experimental setup. A.&#160;&#8216;Cell Deformer&#8217; device in the experimental setup showing the peripheral connections. B.&#160;The device design has 4&#160;functional regions: entry port, cell filter, constriction array, and exit port. Architecture of the microfluidic device showing its main features; inset shows a transmitted light image of the constricted channels. Scale, 10 &#181;m.
<img alt="Figure 2" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig2highres.jpg" width="500" /> 
Figure 2. Engineering drawings for a custom cap to pressurize cell media contained in a flow cytometer tube.
<img alt="Figure 3" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig3highres.jpg" width="500" /> 
Figure 3. Demonstration of how to select the region of interest for video frame cropping.
<img alt="Figure 4" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig4highres.jpg" width="500" /> 
Figure 4. Demonstration of how to select constriction locations.
<img alt="Figure 5" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig5highres.jpg" width="500" /> 
Figure 5. Observation window used to verify that the algorithm properly identifies cell locations as they process through the constriction array. A. Binarized image is superimposed on the source video to show the location of the cells. B. Difference image; C. Bottom hat filtered image; D. Median filtered.
<img alt="Figure 6" fo:content-width="5in" src="/files/ftp_upload/51474/51474fig6highres.jpg" width="500" /> 
Figure 6. Representative transit time measurements as a function of constriction number. A. HL-60 cells exhibit a longer transit time through the first constriction than B. ATRA-treated HL-60 (neutrophil-type) cells. A comparison of the transformed passage time (log10) through the first constriction as evaluated using the nonparametric Mann-Whitney test reveals the difference is significant, p = 1.47E-5. Cells typically transit through the first constriction more slowly than the subsequent constrictions. Data is shown here for cells transiting through 7 &#956;m-wide constrictions at a driving pressure of 28 kPa. Cell density, mean cell diameter, and surfactant concentration are given in Table 1. HL-60, N = 77; ATRA-treated HL-60, N = 97. Results were replicated in independent experiments over the course of 3&#160;different days.
<img alt="Figure 7" fo:content-width="4.5in" src="/files/ftp_upload/51474/51474fig7highres.jpg" width="500" /> 
Figure 7. Overview of the MATLAB script for measuring the transit time. The first loop requires user intervention and observation for the first 50 frames for each video. After the first loop, the entire program will run without user intervention and automatically compiles and plots population data.
<table border="0" cellpadding="0" cellspacing="0" width="582">
	<tbody>
		<tr height="68">
			<td height="68" style="height:68px;width:139px;">Cell Type</td>
			<td style="width:87px;">Channel Height (&#181;m)</td>
			<td style="width:93px;">Channel constriction (&#181;m)</td>
			<td style="width:63px;">Mean Cell Diameter (&#181;m)</td>
			<td style="width:99px;">Cell Concentration (cells/ml)</td>
			<td style="width:103px;">Surfactant Concentration (vol%)</td>
		</tr>
		<tr height="17">
			<td height="17" style="height:17px;width:139px;">HL-60</td>
			<td align="right">10.2</td>
			<td>5, 7, 9</td>
			<td align="right">14</td>
			<td>~1 x 106</td>
			<td>F127: 0.1</td>
		</tr>
		<tr height="34">
			<td height="34" style="height:34px;width:139px;">Neutrophil-type HL-60</td>
			<td align="right">10.2</td>
			<td>5, 7, 9</td>
			<td align="right">14</td>
			<td>~1 x 106</td>
			<td>F127: 0.1</td>
		</tr>
		<tr height="17">
			<td height="17" style="height:17px;width:139px;">OVCAR8&#160;</td>
			<td align="right">10.2</td>
			<td>7, 9</td>
			<td align="right">16</td>
			<td>~5 x 106</td>
			<td>F127: 0.1</td>
		</tr>
		<tr height="17">
			<td height="17" style="height:17px;width:139px;">HEYA8</td>
			<td align="right">10.2</td>
			<td>7, 9</td>
			<td align="right">17</td>
			<td>~5 x 106</td>
			<td>F127: 0.1</td>
		</tr>
		<tr height="17">
			<td height="17" style="height:17px;width:139px;">Mouse lymphocyte</td>
			<td align="right">5.5</td>
			<td>3, 5</td>
			<td align="right">8</td>
			<td>~3 x 106</td>
			<td>F127: 0.33</td>
		</tr>
	</tbody>
</table>
Table 1. Previously studied cell systems and their operating conditions.

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A Microfluidic Technique to Probe Cell Deformability

We demonstrate a microfluidics-based assay to measure the timescale for cells to transit through a sequence of micron-scale constrictions.

Here we detail the design, fabrication, and use of a microfluidic device to evaluate the deformability of a large number of individual cells in an ...

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11.2K Views.  University of California, Los Angeles. We demonstrate a microfluidics-based assay to measure the timescale for cells to transit through a sequence of micron-scale constrictions.

Video: A Microfluidic Technique to Probe Cell Deformability

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

Live Cell Imaging during Mechanical Stretch

There is currently a significant interest in understanding how cells and tissues respond to mechanical stimuli, but current approaches are limited in their capability for measuring responses in real time in live cells or viable tissue. A protocol was developed with the use of a cell actuator to distend live cells grown on or tissues attached to an elastic substrate while imaging with confocal and atomic force microscopy (AFM). Preliminary studies show that tonic stretching of human bronchial epithelial cells caused a significant increase in the production of mitochondrial superoxide. Moreover, using this protocol, alveolar epithelial cells were stretched and imaged, which showed direct damage to the epithelial cells by overdistention simulating one form of lung injury in vitro. A protocol to conduct AFM nano-indentation on stretched cells is also provided.

A novel imaging protocol was developed using a custom motor-driven mechanical actuator to allow the measurement of real time responses to mechanical strain in live cells. Relevant to mechanobiology, the system can apply strains up to 20% while allowing near real-time imaging with confocal or atomic force microscopy.

There is currently a significant interest in understanding how cells and tissues respond to mechanical stimuli, but current approaches are limited in ...

Measurement of the Compressibility of Cell and Nucleus Based on Acoustofluidic Microdevice

Cell mechanics play an important role in tumor metastasis, malignant transformation of cells, and radiosensitivity. During these processes, studying the mechanical properties of the cells is often challenging. Conventional measurement methods based on contact such as compression or stretching are prone to cause cell damage, affecting measurement accuracy and subsequent cell culture. Measurements in adherent state can also affect accuracy, especially after irradiation since ionizing radiation will flatten cells and enhance adhesion. Here, a cell mechanics measurement system based on acoustofluidic method has been developed. The cell compressibility can be obtained by recording the cell motion trajectory under the action of the acoustic force, which can realize fast and non-destructive measurement in suspended state. This paper reports in detail the protocols for chip design, sample preparation, trajectory recording, parameter extraction and analysis. The compressibility of different types of tumor cells was measured based on this method. Measurement of the compressibility of nucleus was also achieved by adjusting the resonance frequency of the piezoelectric ceramic and the width of the microchannel. Combined with the molecular level verification of immunofluorescence experiments, the cell compressibility before and after drug-induced epithelial to mesenchymal transition (EMT) were compared. Further, the change of cell compressibility after X-ray irradiation with different doses was revealed. The cell mechanics measurement method proposed in this paper is universal and flexible and has broad application prospects in scientific research and clinical practice.

Here a protocol is presented to build a fast and non-destructive system for measuring cell or nucleus compressibility based on acoustofluidic microdevice. Changes in mechanical properties of tumor cells after epithelial-mesenchymal transition or ionizing radiation were investigated, demonstrating the application prospect of this method in scientific research and clinical practice.

Cell mechanics play an important role in tumor metastasis, malignant transformation of cells, and radiosensitivity. During these processes, studying the ...

Cancer Research

Stiffness Measurement of Soft Silicone Substrates for Mechanobiology Studies Using a Widefield Fluorescence Microscope

Soft tissues in the human body typically have stiffness in the kilopascal (kPa) range. Accordingly, silicone and hydrogel flexible substrates have been proven to be useful substrates for culturing cells in a physical microenvironment that partially mimics in vivo conditions. Here, we present a simple protocol for characterizing the Young's moduli of isotropic linear elastic substrates typically used for mechanobiology studies. The protocol consists of preparing a soft silicone substrate on a Petri dish or stiff silicone, coating the top surface of the silicone substrate with fluorescent beads, using a millimeter-scale sphere to indent the top surface (by gravity), imaging the fluorescent beads on the indented silicone surface using a fluorescence microscope, and analyzing the resultant images to calculate the Young's modulus of the silicone substrate. Coupling the substrate's top surface with a moduli extracellular matrix protein (in addition to the fluorescent beads) allows the silicone substrate to be readily used for cell plating and subsequent studies using traction force microscopy experiments. The use of stiff silicone, instead of a Petri dish, as the base of the soft silicone, enables the use of mechanobiology studies involving external stretch. A specific advantage of this protocol is that a widefield fluorescence microscope, which is commonly available in many labs, is the major equipment necessary for this procedure. We demonstrate this protocol by measuring the Young's modulus of soft silicone substrates of different elastic moduli.

Substrates with stiffness in the kilopascal-range are useful to study the response of cells to physiologically relevant micro-environment stiffness. Using just a widefield fluorescence microscope, the Young's modulus of soft silicone gels can be determined using an indentation with a suitable sphere.

Soft tissues in the human body typically have stiffness in the kilopascal (kPa) range. Accordingly, silicone and hydrogel flexible substrates have been ...

Measuring Deformability and Red Cell Heterogeneity in Blood by Ektacytometry

Decreased red cell deformability is characteristic of several disorders. In some cases, the extent of defective deformability can predict severity of disease or occurrence of serious complications. Ektacytometry uses laser diffraction viscometry to measure the deformability of red blood cells subject to either increasing shear stress or an osmotic gradient at a constant value of applied shear stress. However, direct deformability measurements are difficult to interpret when measuring heterogenous blood that is characterized by the presence of both rigid and deformable red cells. This is due to the inability of rigid cells to properly align in response to shear stress and results in a distorted diffraction pattern marked by an exaggerated decrease in apparent deformability. Measurement of the degree of distortion provides an indicator of the heterogeneity of the erythrocytes in blood. In sickle cell anemia, this is correlated with the percentage of rigid cells, which reflects the hemoglobin concentration and hemoglobin composition of the erythrocytes. In addition to measuring deformability, osmotic gradient ektacytometry provides information about the osmotic fragility and hydration status of erythrocytes. These parameters also reflect the hemoglobin composition of red blood cells from sickle cell patients. Ektacytometry measures deformability in populations of red cells and does not, therefore, provide information on the deformability or mechanical properties of individual erythrocytes. Regardless, the goal of the techniques described herein is to provide a convenient and reliable method for measuring the deformability and cellular heterogeneity of blood. These techniques may be useful for monitoring temporal changes, as well as disease progression and response to therapeutic intervention in several disorders. Sickle cell anemia is one well-characterized example. Other potential disorders where measurements of red cell deformability and/or heterogeneity are of interest include blood storage, diabetes, Plasmodium infection, iron deficiency, and the hemolytic anemias due to membrane defects.

Here we present techniques to measure red cell deformability and cellular heterogeneity by ektacytometry. These techniques are applicable to general investigations of red cell deformability and specific investigations of blood diseases characterized by the presence of both rigid and deformable red cells in circulation, such as sickle cell anemia.

Decreased red cell deformability is characteristic of several disorders. In some cases, the extent of defective deformability can predict severity of ...

Immunology and Infection

A Microfluidic Platform for Stimulating Chondrocytes with Dynamic Compression

Mechanical stimuli are known to modulate biological functions of cells and tissues. Recent studies have suggested that compressive stress alters growth plate cartilage architecture and results in growth modulation of long bones of children. To determine the role of compressive stress in bone growth, we created a microfluidic device actuated by pneumatic pressure, to dynamically (or statically) compress growth plate chondrocytes embedded in alginate hydrogel cylinders. In this article, we describe detailed methods for fabricating and characterizing this device. The advantages of our protocol are: 1) Five different magnitudes of compressive stress can be generated on five technical replicates in a single platform, 2) It is easy to visualize cell morphology via a conventional light microscope, 3) Cells can be rapidly isolated from the device after compression to facilitate downstream assays, and 4) The platform can be applied to study mechanobiology of any cell type that can grow in hydrogels.

This article provides detailed methods for fabricating and characterizing a pneumatically actuating microfluidic device for chondrocyte compression.

Mechanical stimuli are known to modulate biological functions of cells and tissues. Recent studies have suggested that compressive stress alters growth ...

Control of Cell Adhesion using Hydrogel Patterning Techniques for Applications in Traction Force Microscopy

Traction force microscopy (TFM) is the main method used in mechanobiology to measure cell forces. Commonly this is being used for cells adhering to flat soft substrates that deform under cell traction (2D-TFM). TFM relies on the use of linear elastic materials, such as polydimethylsiloxane (PDMS) or polyacrylamide (PA). For 2D-TFM on PA, the difficulty in achieving high throughput results mainly from the large variability of cell shapes and tractions, calling for standardization. We present a protocol to rapidly and efficiently fabricate micropatterned PA hydrogels for 2D-TFM studies. The micropatterns are first created by maskless photolithography using near-UV light where extracellular matrix proteins bind only to the micropatterned regions, while the rest of the surface remains non-adhesive for cells. The micropatterning of extracellular matrix proteins is due to the presence of active aldehyde groups, resulting in adhesive regions of different shapes to accommodate either single cells or groups of cells. For TFM measurements, we use PA hydrogels of different elasticity by varying the amounts of acrylamide and bis-acrylamide and tracking the displacement of embedded fluorescent beads to reconstruct cell traction fields with regularized Fourier Transform Traction Cytometry (FTTC).
To further achieve precise recording of cell forces, we describe the use of a controlled dose of patterned light to release cell tractions in defined regions for single cells or groups of cells. We call this method local UV illumination traction force microscopy (LUVI-TFM). With enzymatic treatment, all cells are detached from the sample simultaneously, whereas with LUVI-TFM traction forces of cells in different regions of the sample can be recorded in sequence. We demonstrate the applicability of this protocol (i) to study cell traction forces as a function of controlled adhesion to the substrate, and (ii) to achieve a greater number of experimental observations from the same sample.

Near-UV lithography and traction force microscopy are combined to measure cellular forces on micropatterned hydrogels. The targeted light-induced release of single cells enables a high number of measurements on the same sample.

Traction force microscopy (TFM) is the main method used in mechanobiology to measure cell forces. Commonly this is being used for cells adhering to flat ...

Simplified, High-throughput Analysis of Single-cell Contractility using Micropatterned Elastomers

Cellular contractile force generation is a fundamental trait shared by virtually all cells. These contractile forces are crucial to proper development, function at both the cellular and tissue levels,and regulate the mechanical systems in the body. Numerous biological processes are force-dependent, including motility, adhesion, and division of single-cells, as well as contraction and relaxation of organs such as the heart, bladder, lungs, intestines, and uterus. Given its importance in maintaining proper physiological function, cellular contractility can also drive disease processes when exaggerated or disrupted. Asthma, hypertension, preterm labor, fibrotic scarring, and underactive bladder are all examples of mechanically driven disease processes that could potentially be alleviated with proper control of cellular contractile force. Here, we present a comprehensive protocol for utilizing a novel microplate-based contractility assay technology known as fluorescently labeled elastomeric contractible surfaces (FLECS), that provides simplified and intuitive analysis of single-cell contractility in a massively scaled manner. Herein, we provide a step-wise protocol for obtaining two six-point dose-response curves describing the effects of two contractile inhibitors on the contraction of primary human bladder smooth muscle cells in a simple procedure utilizing just a single FLECS assay microplate, to demonstrate proper technique to users of the method. Using FLECS Technology, all researchers with basic biological laboratories and fluorescent microscopy systems gain access to studying this fundamental but difficult-to-quantify functional cell phenotype, effectively lowering the entry barrier into the field of force biology and phenotypic screening of contractile cell force.

This work presents a flexible protocol for utilizing fluorescently labeled elastomeric contractible surfaces (FLECS) Technology in microwell format for simplified, hands-off quantification of single-cell contractile forces based on visualized displacements of fluorescent protein micropatterns.

Cellular contractile force generation is a fundamental trait shared by virtually all cells. These contractile forces are crucial to proper development, ...

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements

Cellular mechanical properties are involved in a wide variety of biological processes and diseases, ranging from stem cell differentiation to cancer metastasis. Conventional methods for measuring these properties, such as atomic force microscopy (AFM) and micropipette aspiration (MA), capture rich information, reflecting a cell's full viscoelastic response; however, these methods are limited by very low throughput. High-throughput approaches, such as real-time deformability cytometry (RT-DC), can only measure limited mechanical information, as they are often restricted to single-parameter readouts that only reflect a cell's elastic properties. In contrast to these methods, mechano-node-pore sensing (mechano-NPS) is a flexible, label-free microfluidic platform that bridges the gap in achieving multi-parameter viscoelastic measurements of a cell with moderate throughput. A direct current (DC) measurement is used to monitor cells as they transit a microfluidic channel, tracking their size and velocity before, during, and after they are forced through a narrow constriction. This information (i.e., size and velocity) is used to quantify each cell's transverse deformation, resistance to deformation, and recovery from deformation. In general, this electronics-based microfluidic platform provides multiple viscoelastic cell properties, and thus a more complete picture of a cell's mechanical state. Because it requires minimal sample preparation, utilizes a straightforward electronic measurement (in contrast to a high-speed camera), and takes advantage of standard soft lithography fabrication, the implementation of this platform is simple, accessible, and adaptable to downstream analysis. This platform's flexibility, utility, and sensitivity have provided unique mechanical information on a diverse range of cells, with the potential for many more applications in basic science and clinical diagnostics.

Presented here is a method to mechanically phenotype single cells using an electronics-based microfluidic platform called mechano-node-pore sensing (mechano-NPS). This platform maintains moderate throughput of 1-10 cells/s while measuring both the elastic and viscous biophysical properties of cells.

Cellular mechanical properties are involved in a wide variety of biological processes and diseases, ranging from stem cell differentiation to cancer ...

Mechanical Fatigue Testing of RBCs by Amplitude-Modulated Electrodeformation

Amplitude-Modulated Electrodeformation to Evaluate Mechanical Fatigue of Biological Cells

Red blood cells (RBCs) are known for their remarkable deformability. They repeatedly undergo considerable deformation when passing through the microcirculation. Reduced deformability is seen in physiologically aged RBCs. Existing techniques to measure cell deformability cannot easily be used for measuring fatigue, the gradual degradation in cell membranes caused by cyclic loads. We present a protocol to evaluate mechanical degradation in RBCs from cyclic shear stresses using amplitude shift keying (ASK) modulation-based electrodeformation in a microfluidic channel. Briefly, the interdigitated electrodes in the microfluidic channel are excited with a low voltage alternating current at radio frequencies using a signal generator. RBCs in suspension respond to the electric field and exhibit positive dielectrophoresis (DEP), which moves cells to the electrode edges. Cells are then stretched due to the electrical forces exerted on the two cell halves, resulting in uniaxial stretching, known as electrodeformation. The level of shear stress and the resultant deformation can be easily adjusted by changing the amplitude of the excitation wave. This enables quantifications of nonlinear deformability of RBCs in response to small and large deformations at high throughput. Modifying the excitation wave with the ASK strategy induces cyclic electrodeformation with programmable loading rates and frequencies. This provides a convenient way for the characterization of RBC fatigue. Our ASK-modulated electrodeformation approach enables, for the first time, a direct measurement of RBC fatigue from cyclic loads. It can be used as a tool for general biomechanical testing, for analyses of cell deformability and fatigue in other cell types and diseased conditions, and can also be combined with strategies to control the microenvironment of cells, such as oxygen tension and biological and chemical cues.

Author Spotlight: Studying Biomechanics of Circulating Cells by Modulating Their Electrodeformation Behavior 

Presented here is a protocol for mechanical fatigue testing in the case of human red blood cells using an amplitude-modulated electrodeformation approach. This general approach can be used to measure the systematic changes in morphological and biomechanical characteristics of biological cells in a suspension from cyclic deformation.