INTEGRATED MICROBIOREACTOR FOR CULTURE AND ANALYSIS OF BACTERIA, ALGAE AND YEAST (BAY)

Steve C.C. Shih1,2*, Sam H. Au1,2, and Aaron R. Wheeler1,2,3 1Donnelly Center for Cellular and Biomolecular Research (University of Toronto), CANADA

2Institute of Biomaterials and Biomedical Engineering (University of Toronto), CANADA 3Department of Chemistry (University of Toronto), CANADA

ABSTRACT

We introduce a micro-scale bioreactor for automated culture and density analysis of microorganisms (bacteria, algae and yeast) using digital microfluidics (DMF). Organisms were grown for up to 5 days and cell densities were determined by measuring absorbance, and growth profiles were shown to be comparable to those generated in macro-scale systems. For downstream analysis, we evaluated the compatibility of two processes on the same device: a fluorescent viability assay of yeast and genetic transformation of bacteria. These results suggest that DMF may be a useful new tool in automated culture and analysis of microorganisms for a wide range of applications. KEYWORDS: digital microfluidics, microorganism, bacteria, algae, yeast, cell culture, absorbance, optical density, EWOD INTRODUCTION

Microorganisms such as bacteria, algae, and yeast are important for a wide range of applications. For example, bacteria and yeast are used extensively for protein production [1], and genomics [2], and algae is a potential source of biofuel production [3]. These applications often require huge quantities of organisms and reagents, but smaller aliquots are typically grown to screen for optimal growth and analyte production conditions. Such systems typically involve microwell plates, test tubes, shake flasks, or stirred tank bioreactors, with working volumes of hundreds of microliters to liters. A common method for monitoring growth profiles is to measure the absorbance of the culture at a specific wavelength. As biomass accumulates, the absorbance increases in a predictable manner, related to the density of cells in suspension.

Here, we introduce a microbioreactor relying on digital microfluidics (DMF). In DMF, fluid droplets are controlled in parallel on an open surface by applying electrical potentials to an array of electrodes coated with a hydrophobic insulator [4]. There is only one report of the use of DMF with microorganisms – Son and Garrell [5] demonstrated that droplets containing yeast could be moved on a DMF system. In the present work we have built on these preliminary results, demonstrating a system capable of automated growth and density analysis of several different types of microorganisms. To validate the new technique, the growth characteristics of bacteria, algae, and yeast were measured and compared to those of microorganisms grown and analyzed using conventional macroscale techniques. Furthermore, a viability assay and a genetic transformation were implemented on-chip illustrate how the platform can be integrated with down-stream analyses.

EXPERIMENTAL Growth curve generation

The parameters for each type of culture are listed in Table 1. To generate growth curves, microbial cultures were initialized by inoculating culture fluid into fresh media. Mother drops containing bacteria, algae, or yeast were then grown with automated semi-continuous mixing. For absorbance measurements, three ~7 µL daughter droplets were dispensed from the mother drop onto the sample region and were driven to the L-shaped electrodes at designated intervals (see Table 1). The microbioreactors were then positioned onto the tops of transparent 96 well-plates and inserted into a PHERAstar microplate reader (BMG Labtech, Durham, NC) for absorbance measurements at 600 nm for bacteria/yeast and 660 nm for algae. The absorbances were collected using a well-scanning program, in which 8 separate measurements were collected from pre-determined spots in a ~2.25 mm2 area. The absorbances of the three daughter droplets were averaged together and were background-corrected by subtracting the average absorbance measured from droplets containing only media on the same devices. After measuring the optical densities, the daughter droplets were translated by DMF actuation back to the reactor region where they were re-combined with the mother drop for continued culture.

Table 1. Parameters used for microfluidic culture and analysis of bacteria, algae, and yeast

E. coli S. cerevisiae C. cryptica Growth Media

LB broth YPD broth f/2 supplemented with biotin and cyanocobalamin

Temperature (°C) 37 30 14 Mixing Frequency (min) 2.5 2.5 120 Absorbance Measurement Frequency (h)

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978-0-9798064-3-8/µTAS 2010/$20©2010 CBMS 1334 14th International Conference onMiniaturized Systems for Chemistry and Life Sciences

3 - 7 October 2010, Groningen, The Netherlands

Cell Death Assays The viability of S. cerevisiae yeast grown in BAY microbioreactors was assayed using the nucleic acid dye Ethidium

homodimer-1 (EthD-1). Prior to operation, a 20 µL mixture of 2 µM EthD-1 in PBS supplemented with 0.05% F68 was added to one reservoir and another mixture of 2 µM EthD-1 in PBS supplemented with 0.05% F68 and 0.05% (v/v) Triton X-100 was added to another. Yeast were then inoculated and incubated at 30°C with automated mixing for 4 hours before the assay was started. The assay was completed by dispensing daughter droplets from the mother drop, combined with equal sized droplets dispensed from the reservoirs and mixed in the sample region by actuation 10 times. The microbioreactor was then incubated at 30°C for 1 hour and then visualized for fluorescence over a square sample electrode. Transformation

E. coli bacteria were transformed in a BAY microbioreactor with a pTriEx vector encoding yellow fluorescent protein (YFP) and ampicillin resistance. Prior to operation, a 20 µL mixture of 200 ng plasmid DNA and 0.20 M CaCl2 in LB broth without antibiotic supplemented with 0.05% F68 was added to a reservoir. Bacteria (without ampicillin resistance) were then inoculated as described above and incubated at 37°C with automated mixing for 1 hour before transformation. After confirming that the cultures were at early to mid-log phase densities (as above), the microbioreactor was placed on ice for 5 minutes, after which a daughter droplet was combined with an equal volume droplet dispensed from the reservoir and mixed in the sample region by actuation 10 times. The microbioreactor was chilled on ice for 1 hour, rapidly heated on a hot plate at 42°C for 50 seconds and then cooled on ice for an additional 1 minute. The microbioreactor was incubated at 37°C for 1 hour with automated mixing after which the droplet containing transformed bacteria was spread on an LB agar plate containing ampicillin at 100 mg/L and incubated overnight at 37°C to allow colony formation. RESULTS AND DISCUSSION

The BAY microreactor is shown in Figure 1. As shown, it comprises a reactor region mated to a sample and a reservoir region. Each of the three rows includes an L-shaped electrode which defines a transparent window for absorbance measurements. Figure 2 is a series of pictures from a movie demonstrating a mixing sequence of the mother culture between adjacent electrodes and in addition the dispensing of three daughter droplets from the mother culture. The daughter droplets were driven onto L-shaped electrodes for absorbance analysis using a well plate reader.

 

Figure 1: Schematic of the Digital Microfluidic Device Design for the BAY microreactor

Figure 2: Sequence of images from a movie of the BAY microreactor in action: mixing and density measurement

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Figure 3 shows the growth curve of bacteria, algae, and yeast cultured in the BAY microreactor, as well as an analogous curve generated using conventional methods. To generate growth curves, cultures were initialized by inoculating culture fluid into fresh media. Mother drops containing bacteria, algae, or yeast were then grown with automated semi-continuous mixing. The growth rates of the bacteria on the macro- and micro-scale were similar (P=0.08); this was also true for algae and yeast.

For downstream analysis, we evaluated the compatibility

of two processes on the same device: a fluorescent viability assay of yeast and genetic transformation of bacteria. Figure 4a-c are representative images collected in the viability assay, and Figure 4d shows an image of bacteria transformed with a YFP reporter gene. In the latter, droplets containing the bacteria were spread on an ampicillin agar plate for imaging.

CONCLUSION

In conclusion, we present a DMF-driven platform for the integrated growth and cell density analysis of microorganisms. This new technique may be beneficial for microbial applications that require miniaturization or parallelization in highly customizable formats.

ACKNOWLEDGEMENTS We thank Kevin Truong (E.coli), Igot Stagjlar (S.

cerevisiae), William Ryu (cold room), Evan Mills and Dawn Edmonds (assistance with bacteria and yeast culture) and Ken Patel and Pam Lane (algae culture). SCC and SHA thank NSERC and ARW thanks the CRC for Canada Research Chair. REFERENCES [1] G. P. L. Cereghino and J. M. Cregg, Applications of yeast in biotechnology: protein production and genetic

analysis, Current Opinion in Biotechnology, 10, 422-427, (1999). [2] E. V. Koonin and M. Y. Galperin, Prokaryotic genomes: the emerging paradigm of genome-based microbiology,

Current Opinion in Genetics & Development, 7, 757-763, (1997). [3] Y. Chisti, Biodiesel from microalgae, Trends Biotechnology, 26, 126-131, (2008). [4] M. Abdelgawad, A.R. Wheeler, The digital revolution: A new paradigm for microfluidics, Advanced Materials 21,

920-925 (2009). [5] S. Son and R. Garrell, Transport of live yeast and zebrafish embryo on a droplet (digital) microfluidic platform, Lab

on a chip, 9, 2398-2401, (2009). CONTACT *Steve Shih, tel: +1-416-946-5702; steve.shih@utoronto.ca

Figure 4: Downstream analysis using BAY: Images of yeast viability assay (a-c) and bacterial

transformation (d)

(a) (b) (c)

Figure 3: Growth curve for (a) bacteria (E.coli), (b) algae (C. Cryptica), and (c) yeast (S.cerevisiae): Bacteria, algae, and yeast were grown in macroscale (circles) or in BAY microbioreactors (triangles). Samples were evaluated in

triplicate and error bars represent one standard deviation

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