Microfluidic phenotyping methods have been of vital importance for cellular characterization, especially for evaluating single cells. In order to study the deformability of a single cell, we devised and tested a tunable microfluidic chip-based method. A pneumatic polymer polydimethylsiloxane (PDMS) membrane was designed and fabricated abutting a single-cell trapping structure, so the cell could be squeezed controllably in a lateral direction. Cell contour changes under increasing pressure were recorded, enabling the deformation degree of different types of single cell to be analyzed and compared using computer vision. This provides a new perspective for studying mechanical properties of cells at the single cell level.

  • A microfluidic chip with pneumatic PDMS membrane was proposed to achieve tunable lateral deformation of single cells.

  • Controllable cell squeezing was realized to study the deformation degree of single cells.

  • Computer vision was applied to exact cell contours and the deformation degrees of two cell types were compared.

The single-cell study is of vital importance for understanding the mechanism of cell behaviors, such as invasion, migration, and diffusion of malignant tumor cells,1,2 in which cell mechanical properties3 have emerged as a label-free characteristic of cell phenotyping. Cell mechanical properties, including deformability, recoverability, and cell stiffness, have been investigated for cell recognition,4,5 disease diagnosis,6 cell biophysical study, and so on. Conventional methods, such as atomic force microscopy (AFM),7–11 micropipetting,12–14 and optical stretching15–19 have been widely used for measuring cell deformation when subjected to external forces, giving precise characterization of the mechanical properties of cells. However, the need for skilled operators and the high costs of these techniques still limit their widespread use.

Recently, microfluidic technology has developed rapidly. This has led to the adoption of two techniques as mainstream microfluidic strategies for cell mechanical phenotyping: contactless hydro-stretching deformability cytometry, and contact constriction deformability cytometry. Compared to conventional methods, the constriction of microfluidic channels20–26 allows gentle pressures to squeeze the cells by physical contact with the inner wall of the microchannel, avoiding cell damage.

By measuring the passage time and deformation degree of cells under the external forces in the constricted microchannel, the mechanical properties of cells can be further evaluated and compared. Abkarian et al.27 designed a microfluidic system composed of 64 narrow channels to measure the passage time of white blood cells, and used a high-speed imaging system to study the deformability of different types of these cells. Urbanska et al.28 studied the mechanical properties of different cells by measuring cell area, contour, roundness, and shape variables when cells flowed through a constricted channel. However, cell deformation is usually fixed to a certain degree or range when the constriction channel is fabricated, which limits the study of the cell mechanics.

In order to achieve various degrees of deformation within a single chip, a constriction microchannel with tunable channel dimension is one potential solution. Previous reports discussed tunable polymer polydimethylsiloxane (PDMS) microfluidic chips for microbead and cell screening29,30 and tunable microfluidic channels for cell capture.31 In this paper, we propose a tunable microfluidic chip with a pneumatic PDMS membrane, fabricated to abut a single-cell trapping structure. The tunable chip enables controllable lateral compression on the single cell by adjusting the air pressure.

First, the lateral displacements of the PDMS membrane were verified and optimized by finite element method (FEM) simulation. The single-cell trapping structure was then integrated with the tunable PDMS membrane to perform single-cell squeezing. The whole device was in a single layer and could be photographed in real time using a high-speed camera, making it straightforward to measure cell deformation. The U-net neural network automatically measured and analyzed the cell contour changes under successive increases in applied pressure. The deformation of different types of cell was compared, showing the potential of the proposed system to automatically and efficiently study single-cell mechanical properties.

A schematic of the microfluidic chip and system setup is shown in Fig. 1. Compressed dry air was introduced as a pressure source, which was adjusted precisely by a pressure-regulating controller (MFCS-EZ, Fluigent, France). The cell suspension was injected into the chip through the inlet of the liquid channel, and the compressed air source was connected to the inlet of the dead-end dry channel to deform the PDMS membrane. In each experiment, a PC and the pressure controller adjusted the working pressure on different channels. The pressure controller contained a pressure sensor for measurements in real time. The microfluidic chip was mounted on an inverted optical microscope (IX53, Olympus, Japan) with a 40× phase contrast objective lens, which allowed a sufficient field of view for observing the deformation of single cells. A high-speed camera (Mini UX50, FASTCAM, Japan) captured images from the microscope.

FIG. 1.

Schematic of the microfluidic system.

FIG. 1.

Schematic of the microfluidic system.

Close modal

The microfluidic chip consisted of a liquid and an air microchannel, with widths of 60 μm and 200 μm, respectively. The height of the microchannels was 20 μm. The microfluidic chip was fabricated by the PDMS soft lithography process.32 The PDMS mold was fabricated on the silicon substrate with SU-8 2015. The PDMS base and curing agent were mixed at volume ratios of 25:1,33 20:1 and 10:1 to make the PDMS layer sufficiently easy to deform; the different ratios of base and curing agent resulted in different elastic moduli. The uncured PDMS mixture was then poured on the molded wafer, degassed in a vacuum chamber, and baked in an oven at 90 °C for 1 h to further cure the PDMS. The cross-linked PDMS was cut into individual chips and punched with inlet and outlet holes. The PDMS channel layer was air plasma treated, then irreversibly bonded to a glass slide and baked at 80 °C for 1 h to reinforce the bonding strength.

The EJ human bladder carcinoma cell line and the hCMEC/D3 human endothelial cell line were used in the cell squeezing experiments. The EJ cells were cultured in 1640 medium at a concentration of approximately 1 × 105 cells/mL in the cell incubator at 37 °C with 5% CO2. After cell adhesion and growth for 48 h, the adherent cells were suspended using 1 mL trypsin-EDTA solution (Biosharp). Then, EJ cells were collected using centrifugation and resuspended in 1640 medium for the experiments. The hCMEC/D3 cells were cultured in ECM medium at a cell concentration of 1 × 105 cells/mL in a cell culture incubator at 37 °C and 5% CO2. After 72 hours of cell adhesion and growth, the adherent cells were suspended with 1 mL of trypsin-EDTA solution (Biosharp). Cells were then collected and resuspended in ECM medium for the experiments.

The behavior of the tunable PDMS membrane was simulated using a simplified microfluidic structure. Figure 2(a) shows a schematic of the microfluidic chip with a tunable PDMS membrane. Two dead-end T-shaped microchannels (air channels) were placed symmetrically either side of a straight microchannel (liquid channel), forming a “sandwich” of channels (air-liquid-air) so that the pressure in the air channels could squeeze the liquid channel. The air and liquid channels were separated by a PDMS membrane. When pressure was applied to the air, the dead-end air channels were forced to expand and deform, reducing the diameter of the liquid channel. To predict the degree of deformation of the PDMS membrane under various air pressures, finite element method (FEM) simulation (COMSOL Multiphysics 5.6) was introduced.23Figure 2(b) shows the simulation results for stress and strain added to a 10 μm PDMS membrane under 2 bar air pressure.

FIG. 2.

Numerical simulations of PDMS membranes. (a) Schematic of tunable PDMS membrane. (b) FEM simulation of the stress and deformation of a PDMS membrane, 10 μm thick. (c) The displacement of a 20 μm-thick PDMS membrane under a series of pressures. (d) The displacement of a 10 μm-thick PDMS membrane under a series of pressures. (e) The maximum displacement of PDMS membranes with different thicknesses under varying pressure. (f) The maximum displacement of 10 μm thick PDMS membranes with different PDMS base:curing agent mix ratios.

FIG. 2.

Numerical simulations of PDMS membranes. (a) Schematic of tunable PDMS membrane. (b) FEM simulation of the stress and deformation of a PDMS membrane, 10 μm thick. (c) The displacement of a 20 μm-thick PDMS membrane under a series of pressures. (d) The displacement of a 10 μm-thick PDMS membrane under a series of pressures. (e) The maximum displacement of PDMS membranes with different thicknesses under varying pressure. (f) The maximum displacement of 10 μm thick PDMS membranes with different PDMS base:curing agent mix ratios.

Close modal

The maximum displacement of membranes of 10 μm to 20 μm was investigated. Figures 2(c) and 2(d) show the position displacement curves of PDMS membranes of 20 μm and 10 μm thickness respectively under increasing pressure. Figure 2(e) shows the degree of deformation for different membrane thicknesses under constant pressure. As expected, a larger displacement was obtained with a thinner membrane.

The deformation of PDMS membranes with different elastic moduli was investigated. The moduli were varied by adjusting the ratio of PDMS base to curing agent. Ratios of 25:1 and 10:1 were used, resulting in elastic moduli of 0.20 MPa and 0.75 MPa respectively. Figure 2(f) presents the results. A 10 μm thick membrane made with a mix ratio of 25:1 (smaller elastic modulus) showed a larger maximum displacement under the same pressure.

A tunable “sandwich” microfluidic chip was fabricated. External air pressures between 0 bar and 1.5 bar were introduced into the air channels to deform the PDMS membrane so that it squeezed the liquid channel. To better characterize the contour of the liquid channel under squeezing, red ink was injected into the liquid channel, and microscopic images were taken by a high-speed camera. Figure 3(a) shows the images of the deformable microchannel under air pressure of 0 bar to 1.4 bar. As the added pressure increased, the liquid channel shrank until it was fully closed at the middle of the channel. The Java image processing program ImageJ was employed to quantify the maximum deformation of the membrane by extracting the boundary of the deformable liquid channel. The same was done for different PDMS mix ratios (25:1 and 20:1) and membrane thicknesses (10 μm, 15 μm, and 20 μm), as shown in Figs. 3(b) and 3(c). It is clear that the 10 μm-thick membrane with a 25:1 PDMS mix ratio exhibited the maximum deformation, which corresponded well to the results of the FEM simulation. However, it is also worth noting that there was a non-linear deformation range when the applied pressure was below ∼0.6 bar, which was due to the compressibility of air in the sample reservoir that may have counteracted the applied pressures. The maximum deformation shows a linear trend when the pressure is greater than 0.6 bar, which corresponds to the simulation results.

FIG. 3.

(a) Microscopic images of the deformable microchannel under increasing air pressure. The white scale bar at bottom right is 100 μm. (b) Comparison of maximum deformation of different membrane thicknesses with a PDMS mix ratio of 25:1 and (c) 20:1.

FIG. 3.

(a) Microscopic images of the deformable microchannel under increasing air pressure. The white scale bar at bottom right is 100 μm. (b) Comparison of maximum deformation of different membrane thicknesses with a PDMS mix ratio of 25:1 and (c) 20:1.

Close modal

Therefore, in order to realize controllable deformation within the microfluidic chip, for subsequent experiments a PDMS membrane was selected at 10 μm thick and a PDMS mix ratio of 25:1.

According to the simulation and experimental results for the deformable PDMS membrane, the lateral deformation of the microchannel can be well-tuned by adjusting the added air pressure. The tunable PDMS membrane was then integrated with a single-cell trapping structure to investigate single-cell deformation under a series of squeezing conditions. The layout of the microfluidic chip is shown in Fig. 4(a). Single-cell trapping was realized by the hydrodynamic principle.34 A bypass channel with a relatively high initial flow resistance was designed in parallel with the semicircular single-cell trapping structure so that a single cell was more likely to flow straight into the trapping structure. Once the trapping structure was blocked by a single cell, subsequent cells flowed into the bypass channel. A dead-end air channel was fabricated at the side of the single-cell trapping structure to squeeze the single cell in the trapping structure. As shown in Fig. 4(b), after cell trapping, the air channel was pressurized in order to deform the PDMS membrane. Images of the squeezed cells were captured in real time by the high-speed camera and analyzed using computer vision. Figures 4(c) and 4(d) show microscopic images of a single cell in the microfluidic chip before and after squeezing, respectively.

FIG. 4.

(a) Layout of the microfluidic chip for single-cell deformation study with a hydrodynamic trapping structure. (b) Schematic of single-cell trapping and squeezing. (c) Microscopic image of a single cell trapped in the structure and (d) deformed as pressure was applied to the structure.

FIG. 4.

(a) Layout of the microfluidic chip for single-cell deformation study with a hydrodynamic trapping structure. (b) Schematic of single-cell trapping and squeezing. (c) Microscopic image of a single cell trapped in the structure and (d) deformed as pressure was applied to the structure.

Close modal

The contours of the squeezed cell were studied by sequential analysis. Automatic cell contour extraction is usually achieved by image processing to improve accuracy and efficiency. However, the cell and channel wall had overlapping contours. The Attention U-Net neural network was applied to segment the cells from the channel background, as shown in Fig. 5(a). The cells were manually segmented using LabelMe software to generate data labels. The single-cell images were normalized and inputted into the Attention U-net for data training. The Attention U-Net neural network was trained on the TensorFlow-based Keras framework.35,36 A stochastic gradient descent (SGD) optimizer was employed during training, with the initial learning rate set to 1 × 10-3, and the network trained for 200 epochs. Training was done using 90% of the dataset, and the remaining 10% was used for validating all the input data. As shown in Fig. 5(b), the segmented image has an intersection over union (IOU) of 0.85, so the trained neural network can be applied for accurate extraction of single-cell contour in the microfluidic channel. The segmented cell contour was then applied for analysis of cell deformability by extracting the cell’s short axis length and long axis length using the fitEllipse algorithm in OpenCV. Furthermore, to verify the feasibility of the proposed method for cell deformation study, two types of cell, a cancer cell line (EJ) and a human endothelial cell line (hCMEC/D3) were measured and their cell contours analyzed under increasing pressure. As shown in Fig. 5(c), 30 groups of single-cell deformation experiments were carried out on EJ and hCMEC/D3 cells. The extracted deformation degree (long axis length divided by short axis length) of EJ cells and hCMEC/D3 cells were plotted against applied pressure. As the pressure increased, the EJ cells deformed more, and increasingly so, compared with the hCMEC/D3 cells, due to cancer cells being less rigid than normal cells.37,38

FIG. 5.

(a) Diagram of the Attention U-Net segmentation model. (b) Original images of single-cell deformation and segmented images with extracted contour. The scale bar is 15 μm. (c) Deformation degree of single EJ cells and hCMEC/D3 cells as pressure increases (N = 30).

FIG. 5.

(a) Diagram of the Attention U-Net segmentation model. (b) Original images of single-cell deformation and segmented images with extracted contour. The scale bar is 15 μm. (c) Deformation degree of single EJ cells and hCMEC/D3 cells as pressure increases (N = 30).

Close modal

Thus, by analyzing the deformation degree of single cells under increasing pressure, the mechanical properties of different types of cells could be evaluated and compared using a single-chip design.

In this paper, a tunable microfluidic chip with a deformable PDMS membrane was proposed to squeeze single cells laterally and study their deformation degree. The feasibility of the proposed method was first verified by FEM simulation. A device was fabricated and experimental tests conducted. By integrating a deformable PDMS membrane at the side of the single-cell trapping structure, a series of tunable, lateral squeezes were applied to a single cell. The images of a single cell under squeezing were analyzed by extracting the cell contour using computer vision, and a characteristic curve of single-cell deformation degree was efficiently obtained. The deformation degree curves for two different types of cell (EJ cells and hCMEC/D3 cells) were obtained, indicating the feasibility of the proposed method for cell deformation studies on different cells with a single chip design. The proposed method for controllable single-cell squeezing and efficient acquisition of single-cell deformation degree can potentially be applied for studying mechanical properties of various types of cell, as well as studies on dynamic cell morphology at single-cell level.

The authors gratefully acknowledge financial support from National Key R&D Program of China (2018YFE0118700), the National Natural Science Foundation of China (NSFC No. 62174119), the 111 Project (B07014), and the Foundation for Talent Scientists of Nanchang Institute for Micro-technology of Tianjin University. Quanning Li, Xuejiao Chen, Bohua Liu, and Chongling Sun are thanked for the help with device fabrication.

The authors have no conflicts of interest to declare.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Ruiyun Zhang received her B.E. degree in engineering from China Agriculture University, Beijing, China, in 2020. She is currently pursuing the master’s degree at State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, China. Her current research interests include tunable microfluid chips.

Xuexin Duan received a Ph.D. degree from the University of Twente, Netherlands in 2010. After postdoctoral studies at Yale University, he moved to Tianjin University, Tianjin, China. Currently, he is a full professor at the State Key Laboratory of Precision Measuring Technology and Instruments, Department of Precision Instrument Engineering of Tianjin University. His research concerns MEMS/NEMS devices, microsystems, and microfluidics, and their interfaces with chemistry, biology, medicine, and environmental science.

Shuaihua Zhang received the B.S. degree from Northeastern University, Qinhuangdao, China, in 2019. He is currently working toward a Ph.D. degree at Tianjin University, Tianjin, China. His research interests include biosensors, microfluidics fluorescence and impedance flow cytometry, droplet technology, and acoustic actuators.

Wenlan Guo received her M.S. in food science from Tianjin University in 2013. She is currently an engineer at the School of Precision Instruments and Opto-Electronics Engineering, Tianjin University. Her research interests include Physical Vapor Deposition based various materials, and Semiconductor package processing.

Chen Sun received his B.S. degree in optical information science and technology from Nanjing University of Science and Technology, in 2006, and his M.S. degree in optics from Tianjin University in 2015. He is currently an engineer at the School of Precision Instruments and Opto-Electronics Engineering, Tianjin University. His research interests include wet processing of silicon-based materials and structures, photomechanics, and digital image processing.

Ziyu Han received a Ph.D. degree from Tianjin University, China in 2022. Currently, he is a postdoctoral fellow at the College of Precision Instrument and Opto-Electronics Engineering, Tianjin University. His research concerns microfluidic impedance cytometry, nanofluidic devices, biosensing microsystems and platforms.