Improvement of a diffusion-based microfluidic chemotaxis assay through stable formation of a chemical gradient
Graphical abstract
Introduction
Chemotaxis is a movement of cells or organisms in response to chemicals, whereby the cells are attracted (positive chemotaxis) or repelled (negative chemotaxis) by substances exhibiting chemical properties (Adler, 1966, Bray et al., 1998, Celani and Vergassola, 2010). Chemotaxis provides fundamental and important information in a broad range of biological phenomena including disease pathogenesis, biofilms, bioremediation, and even carbon cycling in the ocean (Jeong et al., 2014, Kim et al., 2010, Ottemann and Lowenthal, 2002, Seymour et al., 2010). In biophysical research, it represents a powerful model system to understand how cells and organisms sense and respond to chemoeffectors (Ahmed et al., 2010, Mao et al., 2003).
For decades, traditional in vitro chemotaxis assays including micropipette assays, diffusion chambers, Boyden chambers, Zigmond chambers, and Dunn chambers have been developed to investigate how various factors act individually or collectively to regulate cellular movement by creating a spatial concentration gradient of compounds of interest (Xu et al., 2014). However, these techniques have limitations in the precise control of chemical gradients, poor sensitivity, and low reproducibility. In the last decade, microfluidic techniques have been applied to generate, monitor, and quantify the chemical gradient with high accuracy (Ahmed et al., 2010, Hwang et al., 2016, Jeong et al., 2016, Li and Lin, 2011, Sim et al., 2017, Takayama et al., 2001, Weibel and Whitesides, 2006). The techniques are classified into two major categories: (1) continuous flow-based and (2) static diffusion-based system.
A continuous flow-based method employs a laminar flow and diffusion-based mixing to generate chemo-effector gradients, being capable of forming various types of chemical gradient profiles, such as linear, ramp, parabolic, etc. (Dertinger et al., 2001, Englert et al., 2009, Jeon et al., 2009, Jeong et al., 2015, Jeong et al., 2010, Mao et al., 2003, You and Bai, 2017). However, these methods are often conducted on a hydrogel media to minimize the shear force and consequential external distortion of bacterial movement from the fluid flows (Cheng et al., 2007). The hydrogel matrix still restricts the motility of bacteria. In addition, heterogeneous pore size distribution of the hydrogel leads to a nonreproducible formation of chemical gradients (Huang et al., 2009).
As complementary, a static diffusion-based gradient method for bacterial chemotaxis analysis (Diao et al., 2006) has been proposed to innovate the unpredictable effect of random convection and low-throughput of the traditional static pipette (Irimia, 2010). It utilizes chemical diffusion through a channel-patterned nitrocellulose membrane to generate chemical gradients in the gradient channel located between the source and sink channel with no external apparatus (Abhyankar et al., 2006). However, this platform consists of four layers for sample loading, fluidic channel, glass substrate, and housing, making it hard to be widely used for biologists due to lack of usability. Hydrogel-incorporated gradient platforms have been developed for rapid and user-friendly biological analysis (Jeong et al., 2011, Kothapalli et al., 2011, Saadi et al., 2007). The device employs hydrogel matrix as a diffusion channel to accomplish flow-free conditions that solely relies on diffusion. Moreover, the platform is able to form non-linear gradients by manipulating channel geometry of gel matrix (Mosadegh et al., 2007). However, it is still difficult to fabricate the hydrogel matrix and the quality control of hydrogel matrix is intrinsically poor, resulting in low reliability of chemical gradients. Meanwhile, liquid-liquid interface diffusion-based platforms have emerged by virtue of good usability. It generates a liquid-liquid interface between source and sink channel and the diffusion occurs through the interface (Paliwal et al., 2007). In spite of good usability and throughput, however, it allows cross-flow between the two channels, leading to substantial experimental bias in chemotaxis analysis of motile living microorganisms. We previously reported a pump-less microfluidic platform for bacterial chemotaxis analysis based on a static diffusion-based method (Jeong et al., 2013). It operates with a cross flow-minimizing narrow liquid-liquid junction channel between two reservoirs working as a diffusion-occurring interface. We can monitor in situ the dynamic changes of the bacterial population by pure bacterial motility in response to the concentrations of chemoeffectors. In this method, however, the narrow junction channel solely determines the diffusion rate under the same polar concentrations, and the cross-sectional area of the junction channel is the only parameter for determining the rate of diffusion. It requires a highly uniform distribution of the junction channel height to minimize batch-to-batch variations of experiments. Although silicon reactive ion etching (RIE) is useful to control the height of junction channels in the previously proposed fabrication method, height control with narrow dimension error is still difficult to achieve through direct etching of a large silicon substrate due to low etch rate by crystallinity and microloading effect-induced low etching uniformity.
Here, we propose a new fabrication method for improving the experimental reproducibility of bacterial chemotaxis analysis on the diffusion-based chemical gradient through static liquid-liquid interfaces. Plasma-enhanced chemical vapor deposition (PECVD) of a silicon oxide layer and RIE etching process have been adopted instead of direct etching of silicon wafer (Si-RIE) to obtain a highly uniform distribution of junction channel height. A higher etch rate of SiO2 over Si minimizes the nonuniformity of the height of junction channel because of overcoming limited diffusion of etchant gas into narrow trenches (microloading effect) (Hedlund et al., 1994). Uniform height distribution of the devices determines the variations of the rate of diffusion since it simply relies on the cross-sectional area in this system. We inspected the height distribution of junction channel and compared with the previous process. The coefficient of variation (C.V.) has been decreased over 10-fold from 5.69% to 0.42%. Time-dependent evolution of chemical gradient profiles were monitored using fluorescent signals, and the results showed significantly reduced C.V.s in early diffusion time. For comparison with previous results, we performed chemotaxis analysis with Pseudomonas aeruginosa PAO1 and chemoeffectors. Chemotaxis indexes of two chemoeffectors and a negative control strongly agreed with previous values; however, we note that the variations of the chemotaxis indexes were significantly reduced.
Section snippets
Preparation of bacteria and chemicals
P. aeruginosa PAO1 (wild-type strain) was electroporated with plasmid pMRP9-1, which expresses green fluorescent protein (GFP) at high levels, and grown in Luria-Bertani (LB) medium supplemented with carbenicillin (200 μg/ml) for recombinant selection and retention. The P. aeruginosa strain was used for all experiments. The bacteria solution was prepared by culturing the strain in LB medium with carbenicilin in a 37 °C shaking incubator with its rpm of 270, followed by switching the media with
Design of a microfluidic device
Our previous study reported unique microfluidic design to generate a liquid-liquid interface that prevents flow instability along with the diffusion of chemoeffectors toward bacteria (Jeong et al., 2013). The detailed design scheme is illustrated in Fig. 2A. The bacteria injection channel is connected to the chemo-effector injection channel by facing a narrow junction. Diffusion occurs through the narrow junction from chemo-effector channel to bacteria injection channel. The junction is
Conclusions
This study reports an alternative microfabrication technique, using PECVD and RIE, for the diffusion-based chemotaxis analysis device to improve the reliability and reproducibility of chemical gradient formation. The achieved 0.54% C.V. of the junction channel height significantly increases the spatiotemporal accuracy of chemical concentration by a factor of two compared to that of the Si-RIE process. The C.V.s of chemical concentration in SOeMC are analyzed to be around half that of SeMC until
Conflict of interest
Author declares that there is no conflict of interest.
Acknowledgments
This research was supported by Korea Institute of Industrial Technology and Global Research Laboratory (GRL) Program through the National Research Foundation of Korea (NRF), which is funded by the Ministry of Science and ICT (NRF-2015K1A1A2033054).
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