Mini Photobioreactors for in Vivo Real-Time Characterization and

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Mini photobioreactors for in vivo, real time characterization and evolutionary tuning of bacterial optogenetic circuit Hsinkai Wang, and YA-TANG YANG ACS Synth. Biol., Just Accepted Manuscript • Publication Date (Web): 22 May 2017 Downloaded from http://pubs.acs.org on May 27, 2017

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ACS Synthetic Biology

Mini photobioreactors for in vivo, real time characterization and evolutionary tuning of bacterial optogenetic circuit Hsinkai Wang1 and Ya-Tang Yang1* 1

Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan, R.O.C.

Abstract The current standard protocols for characterizing the optogenetic circuit of bacterial cells using flow cytometry in light tubes and light exposure of culture plates are tedious, laborintensive, and cumbersome. In this work, we engineer a bioreactor with working volume of ~10 mL for in vivo real-time optogenetic characterization of E. coli with a CcaS-CcaR lightsensing system. In the bioreactor, optical density measurements, reporter protein fluorescence detection, and light input stimuli are provided by four light-emitting diode sources and two photodetectors. Once calibrated, the device can cultivate microbial cells and record their growth and gene expression without human intervention. We measure gene expression during cell growth with different organic substrates (glucose, succinate, acetate, pyruvate) as carbon sources in minimal medium and demonstrate evolutionary tuning of the optogenetic circuit by serial dilution passages. Keywords: bioreactor, optogenetics, two component system, adaptive laboratory evolution

*

Correspondence and requests for materials should be addressed to Y. T. Y. (email: [email protected]).

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I. Introduction Unlike chemical effectors, light is a very convenient way to characterize the responses of a genetic circuit. Several parameters, such as wavelength, duration, and waveform, of illumination intensity can be precisely controlled and delivered to the sample to control gene expression. Several light-switchable promotor systems with excitation light ranging from visible to near-infrared have been created in Escherichia coli1-6 and yeasts.7-9 Through these efforts, photoreceptors with diverse spectral properties have been used to control a wide range of cellular processes. To keep up with the pace of such development, several researchers have endeavored to develop custom tools for optogenetic circuits.10-13 Moglich et al.10 modified a Tecan microplate reader and added light illumination, but their approach requires sophisticated knowledge to hack the existing software and is costly (a Tecan microplate reader costs ~$40,000). Attempting to provide a low-cost solution to this problem, Tabor and colleagues constructed a light tube array, as a light-emitting diode-based device, to characterize the optogenetic circuit in 64 shaking incubated cultures, and demonstrated its applications in bacteria, yeasts, and mammalian cells.11-13 However, this light tube array can be best regarded as a light exposure tool and requires a flow cytometer to characterize the cell properties. In a typical run, cells are exposed with prescribed duration of light exposure and harvested at a fixed period of time, mixed with antibiotic, and placed in ice to stop metabolic process. Each step will nevertheless introduce errors. Therefore, the device lacks in vivo realtime measuring capability to simultaneously record microbial growth data such as optical density and gene expression such as reporter protein fluorescence. Here we extend previous work14-16 and demonstrate a low-cost mini photobioreactor that can measure in vivo real-time gene expression in conjunction with optical density data with high temporal resolution (~12 min or less) by meticulously embedding all light sources, detectors, and other functionalities


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such fluidic mixing. Once calibrated, the device can run by itself during the course of bacterial cultivation with minimal human intervention.

II. Experimental setup The bioreactor developed here is modified from a previously reported design.14 The experimental setup is shown in Figure 1(a). We construct a tube holder for a culture vial with a working volume of ~10 mL that sits on top on an electronic fan attached with a magnet. A magnetic stirring bar is placed inside the tube for fluid mixing. The tube holder has four openings drilled for LED light sources and photodetectors to measure optical density and fluorescence, respectively. Two LED sources with wavelengths of 520 nm and 625 nm in strip format (3M) are mounted on the tube holder for illumination for cells. For optical density measurements, two of the openings are positioned at an angle of 135° to maximize the detection of scattered light. An LED light source with wavelength of 940 nm and a photodetector (ST-2L2B; Kodenshi) are mounted on each tube holder and connected to the circuits. For fluorescence measurements, two of the openings are positioned at an angle of 90° and designed to hold the excitation filter (FGB25; Thorlabs Inc.) and emission filter (FGL530; Thorlabs Inc.) for GFP, and an LED light source with wavelength of 470 nm and a photodetector (ST1KLA; Kodenshi) are also mounted. (For the excitation, FGB25 is a bandpass filter with pass band from 315 nm to 445 nm. At 470 nm, the transmission is 15%. For the emission, FGL530 is a long pass filter with cut-on wavelength 530 nm.) A circuit is built to measure the voltage across the photodetectors with bias resistors. All of the LEDs and an electronic fan for magnetic stirring are powered by a Darlington pair chip (ULN2803APG; Toshiba). The continuous illumination of bacterial cultures to activate gene expression is briefly interrupted every 12 min for measurements of optical density and fluorescence with the magnetic stirring unit switched off. All of these operations are orchestrated by an Arduino 2 ACS Paragon Plus Environment


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microcontroller board (Arduino Inc.) After performing a calibration to convert voltage readings to optical density (at wavelength 600 nm) and fluorescence in a plate reader (Synergy H1 Hybrid; Biotek), the tube holder is placed in a temperature-controlled incubator (ES 20; Biosan) at 37°C and covered with an optical blackboard. To test the bioreactor, we chose CcaS-CcaR, a two-component system from cyanobacteria Synechocystis sp. PCC 6803.5 Two plasmids (pSR43.6 and pSR58.6; Addgene Inc.) harboring the CcaS-CcaR lightsensing system were used to transform E. coli BW29655 strain,5 (Δ(araD-araB), ΔlacZ, Δ (envZ-ompR)), and a large stock of culture was prepared with antibiotics chloramphenicol and spectinomycin and stored at −80°C with addition of glycerol. The basic on-and-off operation of the optogenetic circuit was verified by turning the light illumination on and off, and measuring the reported protein fluorescence reflecting gene expression. We also used red light to deactivate the circuit and measured the gene expression, finding little difference from the expression obtained in the dark condition. Regarding the day to day reproducibility, the error, defined as the ratio of the standard deviation to the mean value, for the growth rate and fluorescence measurements (GFP fluorescence level divided by optical density) under light illumination was 10.9% and 10.7% from five replicate run, respectively.

III. Results and discussion We used our bioreactor to measure gene expression when cells were allowed to grow on various organic substrates as carbon and energy sources, to elucidate the interdependence of the growth rate and the level of gene expression. We chose glucose, pyruvate, succinate, and acetate as substrates, because the cell growth with these substrates has been wellcharacterized both theoretically and experimentally.17-18 Figure 1(d) and 1(e) show the optical density and fluorescence measurements versus time. The optogenetic circuits were turned on after light illumination for all substrates examined. The growth rate trends, except for 3 ACS Paragon Plus Environment

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pyruvate, were consistent with calculations by flux balance analysis.18 The gene expression for acetate and succinate was found to be higher and delayed compared with that for glucose and pyruvate. A similar delay was previously observed for a blue light-sensing system with similar optical density ranges and sampling during the course of bacterial cultivation.4 One plausible explanation for highest gene expression level is that for the acetate, the growth rate is lowest among all carbon sources and therefore more cellular sources are allocated for ribosomes for protein production.19 Therefore, more cellular resource is allocated to protein production. To demonstrate robust operation of our device, we employed the bioreactor for evolutionary tuning of the optogenetic circuit by carrying out sequential serial dilution passages. Ten-milliliter cultures were grown each day at 37°C (cells grow by 100-fold each day, corresponding to log2 100 = 6.6 generations). After 1 day of growth, the cells were diluted 1:100 in a tube with fresh medium. Samples were frozen (−80°C) every day with addition of glycerol. In total, we ran five replicate evolution experiments for 9 days with light illumination. As the optogenetic circuit expresses wasteful (unnecessary) protein and causes reduced fitness, evolution favors cells with lower levels of protein expression. In the language of the cost-benefit theory proposed by Dekel and Alon,20 the expression of the reporter protein has no benefit for fitness (growth rate), but has a cost through the consumption of cellular resources. During the course of evolution, we expect that the gene expression level will monotonically decrease over time. This is exactly what we observed. The fitness and gene expression (quantified as GFP fluorescence divided by optical density at the end of each day) are displayed in Figures 2(a) and 2(b), respectively. In both figures, the data were normalized by the corresponding values on Day 1. At the end of the experiment, the fitness had increased by 21±0.33% and the gene expression had decreased on average by 49±9.3% in the five replicate runs. The interdependence of the growth rate and the gene 4 ACS Paragon Plus Environment


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expression level is displayed in Figure 2(d). A general decreasing trend was observed, consistent with the tradeoff between fitness and gene expression level. One plausible explanation on the genetic level for the optimization is due to mutations in all the genes encoded for light sensing two component system. This could be due to, for example, mutations in the promotor region of ccaS protein to down regulate the ccaS protein.5,19 It should be noted that evolution experiments are very tedious to perform with a light tube array. Each run for 9 days with a temporal resolution of 12 minutes per data point using the previously reported light tube array would require ~1000 manual runs in the flow cytometer. In addition, for microplates with a typical working volume of ~100 µl, there would be insignificant numbers of mutation events for mutants with high fitness (a typical spontaneous mutation rate of ~10-9 1/bp/generation and 109 cells/mL provides an average of ~0.1 mutation events/day/bp).

IV. Conclusion In conclusion, we have developed a mini photobioreactor and demonstrated its usage in characterizing the bacterial optogenetic circuit. The device enables in vivo real-time measurement of gene expression and is very suitable for growth-related experiments to elucidate the interdependence between growth and optogenetic gene expression. The evolutionary tuning reported here can be extended for optically-controlled metabolism21 or antibiotic resistance4 using a light-sensing promoter system. For example, Möglich and coworkers demonstrate optical control for the antibiotic resistance marker chloramphenicol acetyl transferase (CAT).4 Incubation in constant blue light induces CAT expression and confers antibiotic resistance to chloramphenicol. Currently, one bioreactor can be constructed under $300 with most of the cost from custom machined parts. Furthermore, the $300 components cost will drop even more with access to 3D printer. These low costs make our 5 ACS Paragon Plus Environment

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devices practical for large scale experiments. Moreover, our bioreactor can be individually set up to run separate experimental conditions, and micropumps can be added to enable chemostat operation.14-16 Currently, the upper limits of OD and fluorescence detection are ~0.66 and 7600 fluorescence unit, respectively. (The fluorescence unit is referred back to the plate reader used in calibration.) The lower limit of OD detection is ~0.05 and the lower limit of fluorescence is 60 fluorescence unit. Extension to even lower OD requires more sophisticated background cancellation scheme while the extension to lower fluorescence requires low noise photodetector. Extension to anaerobic operation is also straightforward by placing the bioreactor in an anaerobic chamber and replacing the GFP reporter with a fluorescent protein that can work in anaerobic conditions.22

Acknowledgements: Y. T. Y. would like to acknowledge funding support from the Ministry of Science and Technology under grant numbers MOST 105-2221-E-007-MY3 and MOST 105-2622-8-007-009.

Supporting information Additional notes, experimental setup, figures, and tables. This material is available free of charge via the Internet at http://pubs.acs.org. Author information: Author Address: Department of Electrical Engineering, National Tsing-Hua University, Hsinchu 30013, Taiwan, R.O.C.

Author Contributions: H. W. contributed to bioreactor development and experimental measurement. Y. T. Y. contributed to the initial idea, the experiment design and manuscript preparation. 6 ACS Paragon Plus Environment


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Note:

The authors declare no competing financial interests.

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Figure 1. Operation of the mini photobioreactor and growth with different organic substrates. (a) The mini photbioreactor in the shaker incubator. The device consists of the tube holder with culture vial. (b) The tube holder with light illumination. Upper and lower panel shows bioreactor under green and red light illumination, respectively. (c) The CCaS CCaR light sensing promoter system. (d) Growth data with different organic substrates. Optical density versus time is displayed for growth under glucose, pyruvate, succinate, and acetate as carbon and energy source in minimal medium. The data in the exponential phase allows extraction of growth rate. (e) Gene expression level versus time. The gene expression level represented by GFP fluorescence divided by optical density is plotted against time in unit of the cell generation. Growth under succinate and acetate shows smaller delay than those under glucose and pyruvate. Time is rescaled using measured cell generation time tcell. The cell generation time is related to the growth rate α by tcell = log 2=0.693/ α for each substrate. An averaged green light intensity of 5.5 W/m2 is used here to activate the optogenetic circuit.



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Figure 2. Evolutionary tuning of optogenetic circuits (a) Sequential serial passages in the bioreactor with optogenetic circuit activated under light illumination (b) The measured fitness over time. The increase of fitness over 9 days of evolution is displayed for five replicate runs. The fitness is defined as the growth rate normalized to the growth rate of first day. (c) The gene expression level change. The gene expression shows an over all decrease over the time course of the evolution. (d) The interdependence of growth rate and gene expression level. All the gene expression level represented by GFP fluorescence level divided by optical density is plotted again the corresponding growth rate. A trend line from linear regression of all the data points is also shown. An averaged green light intensity of 5.5 W/m2 is used here to activate the optogenetic circuit for all experiments.


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