Laboratory of Advanced Microfluidic Systems  
  Culturing Cells in a Microfluidic Differential Oxygenator  
Monitoring and controlling the dissolved oxygen (DO) concentration in medium are critical for biological culture and tissue engineering applications. Cellular growth, especially biofilm formation, involves the complex correlations of growth environment and cell-cell communications among cellular species. For cellular growth analysis, including the single cells/small cell clusters monitoring, precise control of the cellular environment is clearly desirable.We have achieved the culture of anaerobic and aerobic species within a disposable multilayer elasteromic microfluidic device with an integrated differential oxygenator (Fig. 1). A gas-filled microchannel network functioning as an oxygen-nitrogen mixer generates differential oxygen concentration. To demonstrate the general utility of the platform for both aerobic and anaerobic culture, three bacteria with differential oxygen requirements (E. coli, A. viscosus, and F. nucleatum), as well as a model mammalian cell line (murine embryonic fibroblast cells (3T3)), were cultured. Results showed differential cellular growth response verses DO concentrations, ranging from 0 ppm (anaerobic) to 42 ppm (fully saturated). Microfluidic oxygenator chips, representing a robust and low-cost method to regulate DO levels in culture, are anticipated to be of wide appeal not only to cancer researchers, but also to public health laboratories for bacteria that are difficult to culture using established microbiology protocols.

Figure 1. Fabricated microfluidic oxygenator The device consists of two PDMS layers (gas and medium) containing molded microchannels. The multiplexor and O2 gradient generator in contained in the gas layer, while the DO sensors are contained in the medium channels.
  Mathematical Analysis of Oxygen Transfer in a Microfluidic Oxygenator  
For successful cell culture in microfluidic devices, precise control of the microenvironment, including gas transfer between the cells and the surrounding medium, is exceptionally important. The work is motivated by a PDMS microfluidic oxygenator chip for mammalian cell culture suggesting that the speed of the oxygen transfer may vary depending on the thickness of a PDMS membrane or the height of a fluid channel. In this work, a model is presented to describe the oxygen transfer dynamics in the PDMS microfluidic oxygenator chip for mammalian cell culture (Fig. 2). Theoretical studies were carried out to evaluate the oxygen profile within the multilayer device, consisting of a gas reservoir, a PDMS membrane, a fluid channel containing growth media, and a cell culture layer. The corresponding semi-analytical solution was derived to evaluate dissolved oxygen concentration within the heterogeneous materials, and was found to be in good agreement with the numerical solution. Additionally, a separate analytical solution was obtained to investigate the oxygen pressure drop (OPD) along the cell layer due to oxygen uptake of cells, with experimental validation of the OPD model carried out using human umbilical vein endothelial cells cultured in a PDMS microfluidic oxygenator. Within the theoretical framework, the effects of several microfluidic oxygenator design parameters were studied, including cell type and critical device dimensions.

Figure 2 . (a) Photograph and (b) cross-section schematic diagram of a device for oxygen pressure drop (OPD) validation. (c) HUVECs were cultured along microchannels with different cell coverages to measure the corresponding OPD.
  Applying Lagrangian Modeling to the Design of Microfluidic Devices for Cell Biology  
In this work, we show how computational fluid dynamics can be applied to the design of efficient hydrodynamic cell traps in microfluidic devices (Fig. 3). Modeled hydrodynamic trap designs included a large, multiple-aperture “C-type” sieve for trapping hundreds of cells, flat single-aperture arrays for single cells, and “U-type” hydrodynamic structures with one or two apertures to confine small clusters of cells (10–15 cells per trap). Using 3T3 cells as a model system, the motion of each individual cell was calculated using a one-way coupled Lagrangian method. The cell was assumed to be a solid sphere, and interactions with other cells were only considered when a cell sedimented in the trap. The ordinary differential equations were solved along the cell trajectory for the three components of the velocity and location vector by using the Rosenbrock method based on an adaptive time-stepping technique. Validation of the predictive value of modeling, using 3T3 cells flowed through microfluidic devices containing “U-type sieves” under the simulation flow parameters, showed excellent agreement between experiment and simulation with respect to cell number per trap and the uniformity of cell distribution within individual microchambers. For applications such as on-chip cell culture or high-throughput screening of cell populations within a lab-on-a-chip environment, Lagrangian simulations have the potential to greatly simplify the design process.

Figure 3. Cell isolation and patterning using sieve microstructures. (a) Experiments on cell capture. (b) Simulated flow field. (c) Simulation cell capture by sieves.
  A Digitally Controllable Mixing Module Array      
A Microfluidic system is defined as a system composed of one or more of the various microfluidic devices. Micropump, microvalve, micromixer, microneedle and microfluidic flow sensor are some of the key microfluidic devices. In the past decades, researchers have contributed to both of the implementation and theoretical analyses on each device. With the superior performance of the maturing microfluidic devices, the integration of microfluidic devices becomes the next challenge of the microfluidic technology. In this work, our goal is to develop different individual micro-devices with compatible fabrication and devise strategies to integrate as a system to perform more complicated fluidic operations.
Operation of the vortex micropump is based on the energy conversion of a rotating impeller to fluid movement, in which the impeller rotation is driven by a mini-size motor. It can provide sufficient flow rate (2.45 ml/min) and hydraulic driving pressure (7.1 kPa) for most microfluidic applications. Additionally, an active aquatic micromixer can encourage a significant mixing is based on the mechanical vibration (frequency: 0.9 kHz) generated by the piezoelectric ceramic. Integrating these basic devices, we successfully developed a microfluidic mixing system capable of mixing activation (mixing time: <5 s) and deactivation (restoring time: 1.5 min). In the mixing chamber, additional micro-pillars were fabricated in the mixing chamber to increase the chaos level of vibration. A tesla valve that eliminates backward flow by increasing the back pressure of the inactive pump channels was also designed and built along each pumping channel. Discretized fluid supply can be performed by swapping the activation of either micropump, meaning that the proportion between two inlet fluids is adjustable with different pumping duty cycles. Therefore, this system supports continuous supply of fully mixed solutions with accurate defined compositions. We have successfully developed the polymer-based vortex micropump, active micromixer and tesla microvalve, as well as their integration as a microfluidic system capable of delivering discrete fluid masses and mixing solutions (Fig. 4). All the devices and systems in this work are portable (without bulky accessories) and can be driven by conventional batteries. Due to the planar geometry and compatible fabrication process of vortex micropump, active micromixers and tesla microvalve, a digitally controllable mixing system on a biocompatible polymer substrate can be potentially integrated to perform complex sample preparation, chemical analyses, fluid delivery, DNA detection, etc. In essence, we have demonstrated a technology that can be extended to build large-scale integrated microfluidic systems.

Figure. 4 Photograph of an array of digitally controllable microfluidic mixing modules.



Laboratory of Advanced Microfluidic Systems | Department of Mechanical and Biomedical Engineering | City University of Hong Kong
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