A computational study of single cells trapping inside a microfluidic channel

Amelia Ahmad Khalili1and Mohd Ridzuan Ahmad1,2

1Dept. of Mechatronic and Robotic,

Faculty of Electrical Eng., Universiti Teknologi Malaysia 81310 Skudai, Johor, Malaysia

2 Institute of Ibnu Sina, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. amelia.ahmadkhalili@gmail.com and ridzuan@fke.utm.my

Abstract—The purpose of this paper is to present the simulation results from a computational model of cell-like object flow in a microfluidic device. This work is important because computational models are needed to design miniaturized biomedical devices which leverage microfluidics technology. Microfluidic devices are important for the single cell analysis such as cell adhesion and single cell electrical properties studies which could lead to many significant applications including early disease diagnosis. The aims of this study are to trap a single cell-like object in the micro-well and to obtain the optimized micro-channel water flow rate and micro-well suction rate using finite element analysis. This study presents numerical solutions from the finite element analysis simulation using ABAQUS-FEA software to analyze the effects of suction rate and depth of the micro-well for a single cell trapping in a microfluidic device. According to the simulation results, a single cell-like object able to be trap into the micro-well with the optimized well’s depth and suitable micro-channel’s flow rate and micro-well’s holes suction rate.

Keywords-component; single cell, finite element, microfluidic, cell trapping

I. INTRODUCTION Conventional biological studies are usually carried out

with large cell populations thus preventing assessment of individual cell. The measurement of population based study can only reflect the average values summed over the responses of many cells. Accessing the information inherent to single cells will allow us to resolve such heterogeneity and eventually improve our understanding of enduring problems in molecular biology, cancer diagnostics, pathology and therapy. The analysis of single cells with a sufficient number of cells to elucidate process heterogeneities is necessary to obtain more precise information, to obtain statistically meaningful data and thus, reveal the properties of individual cells and cell-to-cell differences [1].

Microfluidic platforms have become an important tool for

single cell analysis as they allow constructing fluidic

channels in dimensions adapted to a specific cell size and provide fluidic tools for cell analysis with minimal dilution errors [4-8]. Microfluidics could overcome difficulties or challenges in traditional assays in medical diagnosis and have the ability to handle small sample sizes and thus minimized the use of valuable reagents in the analysis. The major advantages of micro fabricated systems for cell study are the ability to design cellular microenvironments, precisely control fluid flows, and to reduce the time and cost of cell culture experimentations.

Microfluidic devices using hydrodynamic flows exhibit

numerous advantages such as non-marker labeling, short detection time and high reproducibility based on simple and robust experimental procedure [2]. The size-based approach is relatively less invasive because it does not require any chemical or biological interactions between the cells and the device. Single cells trap should not only allow spatial localization of single cells, but also create micro-reaction chambers, where reactions with stimuli can take place [4] and manipulations could be performed.

Computational Fluid Dynamics (CFD) modeling is an

invaluable tool that has been applied only relatively recently in the area of micro scale cell culture that enables a better understanding of the role of the hydrodynamic environment and the factors that modulate it. CFD is now enabling us to understand the implications of fluid flow and transport on cell function thus provides important insights into the design and optimization of microfluidic cell culture chip [3]. CFD simulations have been performed to estimate the properties of the system during cell-trapping and releasing [9].

This study presents development of the single cell

trapping in the microfluidic finite element model using hydrodynamic manipulation techniques. In this paper, we discuss the simulation of the single cell-like object trapping inside water in the channel. The single cell-like object trapping was carried out by manipulating the flow rate of channel fluid flow and micro-well suction and the geometry of the trap-hole. According to the simulation results, a single

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cell-like object able to be be trapped into the micro-well with the optimized well’s depth and suitable suction rate.

II. THE IDEA AND CONCEPT OF THE MODEL The single cell trapping microfluidic device and the

concept for the individual cell trapping are schematically illustrated in Figure 1.

Figure 1: Schematic of the idea and concept design of single cell trapping microfluidic device

The device will consist of parallel micro-wells which have a dimension that could only fit a single cell. There will be suction holes in the base of the micro-well to introduce the suction force that will guide and trap a single cell into the micro-well. Cells will be introduced into the device through the inlet with appropriate flow rate. Cells that enter the device will be directed through the channel by controlling the flow rate of channel’s inlet and outlet. A single cell will be directed to each micro-well by applying an appropriate suction force through the suction holes. The excess and remaining cells will be directed out through the channel’s outlet by injecting cell’s culture medium.

III. SIMULATION SETUP

The channel was designed with one micro-well to trap a single cell-like object with a curved edge of micro-well. This is because in our previous analysis, a sharp edge curve was found to damage the cell-like object surface (data not shown). The analysis was carried out using finite element ABAQUS-FEA analysis software which able to perform multi-physics analysis. At first, the simulation analysis was carried out using the parameters in micro dimension properties. However due to time consumed for the simulation to converge is too long (data not shown), the parameters was appropriately scaled into meter dimension with the ratio of 1 m is proportional to 1μm. The advantage of dimension scaling is that a simulation works could be carried out in a reasonable simulation times [10]. The approach to represents a nano scale model by giving nanometer dimensions to the geometry and using the material property values identical to the scale model suffers from two major drawbacks. Firstly, the simulation will face a very small incremental time steps which would make real time simulation prohibitively expensive if not impossible and secondly, using properties with nanometer dimensions will create numerical issues in finite element programs [10].

Water micro-channel was modeled as 3D Eulerian

explicit EC3DR and an 8-node linear eulerian brick element was used. The micro-channel width and depth was 5 µm and the length is 25 µm. The initial dimension of the micro-well is 5 µm in length, width and depth. There are 2 rectangle suction holes in the micro-well with the size of 0.5 µm and 1 µm of width and length, respectively. Properties of water were assigned with density, speed of sound and viscosity.

Figure 2: The assembly of experimental setup of water micro-channel with three cell-like objects. Arrows shows the direction of the water flow.

The cell-like object was model as 3D standard solid deformable C3D8R and an 8-node linear brick 3D stress was used. Properties of cell-like object were assigned with Young’s modulus, Poisson’s ratio and density of yeast cell. Both the water channel and cell-like object was meshed using hexahedron mesh type. The dimension of the ellipse shape cell-like object is 5 µm in diameter. Figure 2 shows the assembly of both water channel and three of cell-like objects. The cell-like object was placed in three different parallel places in the water channel. Zero pressure and no-flow boundary condition was applied to the walls of

Inlet outlet

Suction

(A) (B) (C)

Inlet outlet

suction suction suction

Inlet outlet

suction

suction

suction

cell

outlet Inlet

suction suction suction

cell

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channel. Inflow and outflow velocity of 0.3 - 0.6 µms-1 was applied to the inlet and outlet of the channel, respectively and the suction velocity of each suction hole in the micro-well was set from 0.6 to 2 µms-1. The depth of the micro-well was set from 3-5 µm. The interaction between objects and water was set as rough tangential behavior.

IV. RESULTS AND DISCUSSION

The initial analysis was carried out with the flow rate of inlet and outlet of 0.3 µms-1and suction rate of 0.6 µms-1. This suction rate was found not enough to trap the cell-like object. All three objects were found to assemble and floating together on the micro-well without entering the well (Fig. 3a). The suction rate was increased to 1 µms-1 while the inlet-outlet flow rate remained as in previous analysis. However, the force was still not enough to trap the cell-like objects; as the objects pass through the micro-well without entering it (Fig. 3b). Increasing the suction rate to 1.5 µms-1 able to trap the cell-like objects when the inlet-outlet flow rate was 0.3 µms-1. However, more than one object were found to be trapped in the micro-well (Fig. 3c). The aim for this analysis is to trap a single cell-like object into the micro-well; therefore 1.5 µms-1 suction rate is not suitable for the purpose of single-cell trapping.

Figure 3: a; Analysis with main channel flow of 0.3 ms-1 and suction of 0.6 ms-1. b; Analysis with main channel flow of 0.3 ms-1 and suction of 1ms-1. c; Analysis with main channel flow of 0.3 ms-1 and suction of 1.5m-s. d; Analysis with a less trap-hole depth, main channel flow of 0.3 ms-1 and suction of 1.5 ms-1. f; Analysis with a less trap-hole depth, main channel flow of 0.3ms-1 and suction of 2 ms-1. g; Analysis with a less trap-hole depth, main channel flow of 0.6 ms-1 and suction of 1.5 ms-1.

The depth of micro-well was decreased from 5 µm into 3.5 µm for the subsequent analysis to allow only a single cell-like object to be trapped. With the inlet-outlet flow 0.3µms-1 and suction of 1.5 µms-1, one object was able to be trapped inside the micro-channel; however the cell-like object was floating up and did not enter to the base of the micro-well (Fig. 3d). By maintaining the inlet-outlet flow rate, suction rate 2.0 µms-1 was found to be sufficient to trap a single cell-like object into the micro-well (Fig.3e). Increasing the inlet and outlet flow rate to 0.6 µms-1 and maintaining the suction rate to 2.0 µms-1 caused the trapped object to be floating up in the micro-well; therefore the model was not suitable for efficient single cell-like object trapping (Fig. 3f).

V. CONCLUSION This study presents the model of single cell trapping

inside a microfluidic device using finite element software. A single cell-like object was able to be trapped into the micro-well by manipulating the channel’s inlet-outlet flow rate and micro-well’s suction holes flow rate and modifying the depth of the micro-well. The optimized condition to trap a single cell-like object is 0.3 µms-1 of the inlet-outlet flow rate and 2 µms-1 of suction rate and 3.5 µm of micro-well depth.

ACKNOWLEDGMENT

We would like to express our appreciation towards Ministry of Higher Education Malaysia (MOHE) grant no. 78677 (FRGS) and Universiti Teknologi Malaysia, grant nos. 77973 (NAS) and 02H34 (GUP) for funding this project and for their endless support.

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