Difference between revisions of "Team:NUS Singapore-A/Hardware"
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<p>The first problem is that while there is a rapidly-growing interest in using optogenetics for biomanufacturing<sup>[1]</sup>, development of custom tools to support the research of optogenetic circuits cannot match this pace, and is insufficient to meet user needs<sup>[2]</sup>. An example of the most current hardware tools available is a modified Tecan microplate reader, which provides controlled illumination on top of its usual measurement capabilities<sup>[3]</sup>. Such an approach is costly and requires specialized knowledge of the microplate reader model. Another example would be the open-source light exposure tool constructed for a 24-well plate<sup>[4]</sup>. To our team, it seemed that scaling-up in optogenetic research (Figure 1) was not well-supported by current hardware solutions, which only cater to microwell plates.</p> | <p>The first problem is that while there is a rapidly-growing interest in using optogenetics for biomanufacturing<sup>[1]</sup>, development of custom tools to support the research of optogenetic circuits cannot match this pace, and is insufficient to meet user needs<sup>[2]</sup>. An example of the most current hardware tools available is a modified Tecan microplate reader, which provides controlled illumination on top of its usual measurement capabilities<sup>[3]</sup>. Such an approach is costly and requires specialized knowledge of the microplate reader model. Another example would be the open-source light exposure tool constructed for a 24-well plate<sup>[4]</sup>. To our team, it seemed that scaling-up in optogenetic research (Figure 1) was not well-supported by current hardware solutions, which only cater to microwell plates.</p> | ||
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<img src="https://static.igem.org/mediawiki/2018/thumb/b/b3/T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Small.png/800px-T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Small.png"> | <img src="https://static.igem.org/mediawiki/2018/thumb/b/b3/T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Small.png/800px-T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Small.png"> | ||
<figcaption><b>Figure 1.</b> Scaling-up in optogenetics research - from the microplate to small-scale bioreactor</figcaption> | <figcaption><b>Figure 1.</b> Scaling-up in optogenetics research - from the microplate to small-scale bioreactor</figcaption> | ||
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<img src="https://static.igem.org/mediawiki/2018/thumb/a/ac/T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21.png/800px-T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21.png"> | <img src="https://static.igem.org/mediawiki/2018/thumb/a/ac/T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21.png/800px-T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21.png"> | ||
<figcaption><b>Figure 2</b>. PDF-LA!.</figcaption> | <figcaption><b>Figure 2</b>. PDF-LA!.</figcaption> | ||
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<img src="https://static.igem.org/mediawiki/2018/0/00/T--NUS_Singapore-A--Hardware_Bioreactor_Assembly_HLR_White.png"> | <img src="https://static.igem.org/mediawiki/2018/0/00/T--NUS_Singapore-A--Hardware_Bioreactor_Assembly_HLR_White.png"> | ||
<figcaption><b>Figure 3</b>. Light Wait.</figcaption> | <figcaption><b>Figure 3</b>. Light Wait.</figcaption> | ||
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<img src="https://static.igem.org/mediawiki/2018/thumb/b/bc/T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Big.png/800px-T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Big.png"> | <img src="https://static.igem.org/mediawiki/2018/thumb/b/bc/T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Big.png/800px-T--NUS_Singapore-A--Hardware_Overview_Scaling_Up_Big.png"> | ||
<figcaption><b>Figure 4</b>. The components in Figure 1 (bottom right-hand corner) are still dwarfed by an industrial bioreactor.</figcaption> | <figcaption><b>Figure 4</b>. The components in Figure 1 (bottom right-hand corner) are still dwarfed by an industrial bioreactor.</figcaption> | ||
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<p>The second problem is that although a proof-of-concept already exists for optogenetic biomanufacturing, the process can be further optimized to bring the vision of an industrial-scale optogenetic bioreactor closer to reality. <br><br> | <p>The second problem is that although a proof-of-concept already exists for optogenetic biomanufacturing, the process can be further optimized to bring the vision of an industrial-scale optogenetic bioreactor closer to reality. <br><br> | ||
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<h2>Product Demonstration</h2> | <h2>Product Demonstration</h2> | ||
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| + | <i><b>Figure 5</b>. Showcase of </i>PDF-LA!<i>.</i> | ||
| − | <video src="https://static.igem.org/mediawiki/2018/8/8d/T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21_Snazzy.mp4 | + | <br><br> |
| − | <i><b>Figure | + | <div class="video-landscape"> |
| + | <video src="https://static.igem.org/mediawiki/2018/8/8d/T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21_Snazzy.mp4" controls></video> | ||
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| + | <i><b>Figure 6</b>. With </i>PDF-LA!<i>, you’ll be light-years ahead of the competition! At the very least, you can program your own snazzy light show and be the envy of other optogenetics researchers.</i> | ||
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| − | <p>The utility and functionality of <i>PDF-LA!</i> was validated by user feedback. We also used it when characterizing the behaviour of EL222 in repressible and inducible systems, thus producing what you see on our Results page.</p> | + | <p>The utility and functionality of <i>PDF-LA!</i> was validated by user feedback. We also used it when characterizing the behaviour of EL222 in repressible and inducible systems, thus producing what you see on our <a href="https://2018.igem.org/Team:NUS_Singapore-A/Results">Results</a> page.</p> |
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<h3>Possible Configurations</h3> | <h3>Possible Configurations</h3> | ||
| − | <p><i>DF-LA!</i> was designed with modularity and flexibility as fundamental guiding principles. Many configurations are possible (Figure | + | <p><i>DF-LA!</i> was designed with modularity and flexibility as fundamental guiding principles. Many configurations are possible (Figure 7), enabling researchers to customize their experimental setups to a greater degree.</p><br> |
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| − | <i><b>Figure | + | <video src=" https://static.igem.org/mediawiki/2018/0/09/T--NUS_Singapore-A--Hardware_Overview_PDF-LA%21_Possible_Configurations.mp4" controls></video> |
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| + | <i><b>Figure 7</b>. Examples of possible configurations.</i> | ||
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<p><i>P-LA!</i> comprises a tech holder and a lighting plate.</p> | <p><i>P-LA!</i> comprises a tech holder and a lighting plate.</p> | ||
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<figcaption><b>Figure 4</b>Picture of tech holder and lighting plate</figcaption> | <figcaption><b>Figure 4</b>Picture of tech holder and lighting plate</figcaption> | ||
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<p><i>Light Wait</i> supports optogenetic research, especially in optogenetic biomanufacturing, by allowing researchers to scale up to a 500 ml working volume bioreactor.</p> | <p><i>Light Wait</i> supports optogenetic research, especially in optogenetic biomanufacturing, by allowing researchers to scale up to a 500 ml working volume bioreactor.</p> | ||
| + | <h2>Product Demonstration</h2> | ||
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| − | + | <video src="https://static.igem.org/mediawiki/2018/e/e3/T--NUS_Singapore-A--Hardware_pump_bioreactor.mp4" controls>Bioreactor Backup Video</video> | |
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<p><i>Light Wait</i> was validated through a series of experiments which first proved each component’s functionality, and then the functionality of the whole system when all the components were assembled. </p> | <p><i>Light Wait</i> was validated through a series of experiments which first proved each component’s functionality, and then the functionality of the whole system when all the components were assembled. </p> | ||
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| + | <h3>Experimental Plans</h3> | ||
| + | <p>The overnight culture for the experiment was obtained by inoculating the E. coli strain top 10 from glycerol stock that stored in -80 °C freezer. Cells harboring blue light repressible RFP (fused with YbaQ degradation tag) expression plasmid Brep-RFP-YbaQ were grown in Luria-Bertani (LB) broth medium supplemented with Kanamycin (Km) (50 μg/mL) at 37˚C with shaking speed at 225 RPM. Before starting the experiment, the overnight culture was refreshed in LB with kanamycin in shaking incubator. The cell density (absorbance at 600 nm) and red fluorescence protein (RFP) expression (excitation and emission wavelengths at 535 nm and 600 nm respectively) were measured using microplate reader (H1, Biotek, USA). The optogenetic bioreactor, Light Wait was housed in a large shaking incubator, the temperature was maintained at 37˚C and shaking speed was set at 225 RPM. The refreshed cell culture was mixed with fresh LB to make a total volume of 500 ml in the bioreactor chamber. Cell samples were drawn from the bioreactor at different time point to obtain different OD600 and RFP. The calibration of bioreactor OD and RFP sensors was done by comparing the data against the readings acquired from microplate reader. During the cell growth phase (OD600 less than 0.6), bioreactor’s build-in blue light was shone to repress the RFP expression. The blue light would be turned off automatically by the computer when the OD600 exceed 0.6, and subsequently the RFP could be expressed (production phase). Blue light would be turned on again once RFP reading reaches 900, this would stop RFP expression.</p> | ||
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| + | <h3>Experimental Results</h3> | ||
| + | <p>Please visit <a href="https://2018.igem.org/Team:NUS_Singapore-A/Results"><u>Results:Cell-Machine Interface</u></a> for the outcomes of our experimental plans.</p> | ||
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| − | + | <button class="accordion">HOW IT WORKS</button> | |
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| − | < | + | <h3>Operation</h3> |
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<p>This operation guide assumes that all components have been assembled and programmed. Ensure that this has been completed before operation, else results may vary. For instructions on how to set up and operate each component of <i>Light Wait</i>, please refer to our dedicated component pages.</p> | <p>This operation guide assumes that all components have been assembled and programmed. Ensure that this has been completed before operation, else results may vary. For instructions on how to set up and operate each component of <i>Light Wait</i>, please refer to our dedicated component pages.</p> | ||
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<li>Place <i>Light Wait</i> in a shaking incubator unit as shown in our Product Demonstration. Take care to ensure that all wires and tubing are slack and of sufficient length, else they may become disconnected during operation. </li> | <li>Place <i>Light Wait</i> in a shaking incubator unit as shown in our Product Demonstration. Take care to ensure that all wires and tubing are slack and of sufficient length, else they may become disconnected during operation. </li> | ||
<li>Fill and cover the fermentation chamber. </li> | <li>Fill and cover the fermentation chamber. </li> | ||
| − | <li>Connect the pump, 2-in-1 sensor, and the fermentation chamber with the silicone tubings in a loop as shown below (Figure | + | <li>Connect the pump, 2-in-1 sensor, and the fermentation chamber with the silicone tubings in a loop as shown below (Figure 8). The remaining 2 small tubes are for introducing more media, and an air pump. </li> |
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| − | <img src=" | + | <img src="https://static.igem.org/mediawiki/2018/0/00/T--NUS_Singapore-A--Hardware_Bioreactor_Assembly_HLR_White.png"> |
| − | <figcaption><b>Figure | + | <figcaption><b>Figure 8</b>. Illustration of how the pump, sensor, and fermentation chamber should be connected by silicone tubing.</figcaption> |
</figure> | </figure> | ||
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| − | <li>Turn on the AC adapters for the pump and the LEDs in the fermentation chamber. | + | <li>Turn on the AC adapters for the pump and the LEDs in the fermentation chamber. The pump should begin to rotate and the LEDs should light up. Connect the Arduino controlling the 2-in-1 sensor to your PC. Load the code for the 2-in-1 sensor and open the Serial Monitor to check that the sensor is collecting data. </li> |
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<li>After verifying that all the components are working to your satisfaction, close the shaking incubator door. </li> | <li>After verifying that all the components are working to your satisfaction, close the shaking incubator door. </li> | ||
| − | <li>When the OD reaches your target levels, the LEDs in the fermentation chamber will turn off. The green LED in the 2-in-1 sensor will also turn off, and the red LED will turn on | + | <li>When the OD reaches your target levels, the LEDs in the fermentation chamber will turn off. The green LED in the 2-in-1 sensor will also turn off, and the red LED will turn on.</li> |
<li>When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are stressed, the LEDs in the fermentation chamber will turn on again.</li> | <li>When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are stressed, the LEDs in the fermentation chamber will turn on again.</li> | ||
<li>When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are NOT stressed, the LEDs in the fermentation chamber will turn off again.</li> | <li>When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are NOT stressed, the LEDs in the fermentation chamber will turn off again.</li> | ||
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| + | <p><i>Light Wait</i> comprises a peristaltic pump, a 2-in-1 OD and fluorescence sensor, and a fermentation chamber.</p> | ||
| − | < | + | <h4>Click on the picture of the component to be taken to its dedicated page!</h4> |
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| − | + | <a href="https://2018.igem.org/Team:NUS_Singapore-A/Hardware/Pump"><img src="https://static.igem.org/mediawiki/2018/8/8d/T--NUS_Singapore-A--The_Real_Peristaltic_Pump.png" style="max-width: 100%; display: inline-block;"></a> | |
| + | <figcaption><b>Pump</b></figcaption> | ||
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| − | < | + | <a href="https://2018.igem.org/Team:NUS_Singapore-A/Hardware/Sensor"><img src="https://static.igem.org/mediawiki/2018/3/35/T--NUS_Singapore-A--The_Real_Sensor.png" style="max-width: 100%; display: inline-block;"></a> |
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| − | < | + | <a href="https://2018.igem.org/Team:NUS_Singapore-A/Hardware/CoJar"><img src="https://static.igem.org/mediawiki/2018/4/47/T--NUS_Singapore-A--The_Real_Cookie_Jar.png" style="max-width: 100%; display: inline-block;"></a> |
| − | + | <figcaption><b>Fermentation Jar</b></figcaption> | |
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</figure> | </figure> | ||
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| − | < | + | <br><h2>References</h2><br> |
| − | < | + | <div class="reference"> |
| − | < | + | [1] Zhao, E. M., Zhang, Y., Mehl, J., Park, H., Lalwani, M. A., Toettcher, J. E., & Avalos, J. L. (2018). Optogenetic regulation of engineered cellular metabolism for microbial chemical production. <i>Nature</i>, 555(7698), 683.<br><br> |
| − | < | + | [2] Wang, H., & Yang, Y. (2017). Mini Photobioreactors for in Vivo Real-Time Characterization and Evolutionary Tuning of Bacterial Optogenetic Circuit. <i>ACS Synthetic Biology</i>, 6(9), 1793-1796. <br><br> |
| + | [3] Wang, H., & Yang, Y. (2017). Mini Photobioreactors for in Vivo Real-Time Characterization and Evolutionary Tuning of Bacterial Optogenetic Circuit. <i>ACS Synthetic Biology</i>, 6(9), 1793-1796. <br><br> | ||
| + | [4] Gerhardt, K. P., Olson, E. J., Castillo-Hair, S. M., Hartsough, L. A., Landry, B. P., Ekness, F., . . . Tabor, J. J. (2016). An open-hardware platform for optogenetics and photobiology. <i>Scientific Reports</i>, 6(1).<br><br> | ||
| + | [5] Delvigne, F., & Noorman, H. (2017). Scale-up/Scale-down of microbial bioprocesses: A modern light on an old issue. <i>Microbial Biotechnology</i>, 10(4), 685-687.<br><br> | ||
| + | [6] Zhao, E. M., Zhang, Y., Mehl, J., Park, H., Lalwani, M. A., Toettcher, J. E., & Avalos, J. L. (2018). Optogenetic regulation of engineered cellular metabolism for microbial chemical production. <i>Nature</i>, 555(7698), 683.<br><br> | ||
| + | [7] Lalwani, M. A., Zhao, E. M., & Avalos, J. L. (2018). Current and future modalities of dynamic control in metabolic engineering. <i>Current Opinion in Biotechnology</i>, 52, 56-65. <br><br> | ||
| + | [8] Ceroni, F., Boo, A., Furini, S., Gorochowski, T. E., Borkowski, O., Ladak, Y. N., ... & Ellis, T. (2018). Burden-driven feedback control of gene expression. <i>Nature Methods</i>, 15(5), 387. | ||
| + | [9] Milias-Argeitis, A., Rullan, M., Aoki, S. K., Buchmann, P., & Khammash, M. (2016). Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth. <i>Nature Communications</i>, 7(1).<br><br> | ||
</div></div> | </div></div> | ||
Latest revision as of 03:23, 8 December 2018
Introduction
Our hardware team developed two sets of hardware to address two problems in synthetic biology, and complement the work of the wet lab team to complete our optogenetic biomanufacturing platform. These two problems are: the lack of tools to help optogenetic researchers scale up their research, and the need to continue optimizing optogenetic biomanufacturing.
The first problem is that while there is a rapidly-growing interest in using optogenetics for biomanufacturing[1], development of custom tools to support the research of optogenetic circuits cannot match this pace, and is insufficient to meet user needs[2]. An example of the most current hardware tools available is a modified Tecan microplate reader, which provides controlled illumination on top of its usual measurement capabilities[3]. Such an approach is costly and requires specialized knowledge of the microplate reader model. Another example would be the open-source light exposure tool constructed for a 24-well plate[4]. To our team, it seemed that scaling-up in optogenetic research (Figure 1) was not well-supported by current hardware solutions, which only cater to microwell plates.
Yet, the biomanufacturing industry is expected to deliver products to the market, in high volumes, at high quality, and at competitive prices[5]. If we are ever to bring our optogenetic biomanufacturing platform to an industrial scale, it is necessary to bridge the gap between the microplate and the industrial bioreactor, and adapt our cells for actual large-scale bioreactor conditions. We thus designed a suite of three devices, called PDF-LA!, which enables the characterization of optogenetic circuits at different scales - 12-well Plate, petri Dish, and conical Flask (Figure 2).
We also created a bench-top optogenetic bioreactor, Light Wait.
It is our vision that these devices will empower optogenetic researchers to make great leaps forward in their research, although we acknowledge that there is a still-greater leap between our humble bioreactor and an industrial bioreactor (Figure 4). For now, it is enough for us to have taken the first few steps.
The second problem is that although a proof-of-concept already exists for optogenetic biomanufacturing, the process can be further optimized to bring the vision of an industrial-scale optogenetic bioreactor closer to reality.
For some background, Zhao et al. have increased yield of isobutanol from yeast by using a blue light repressible system in a simple bioreactor, showing the potential of optogenetics in biomanufacturing[6]. However, they did not optimize the duration or intensity of blue light, instead shining blue light periodically. Reportedly, the team is considering adding biosensors that can automatically switch the light source on and off, so as to improve efficiency[7]. We decided to try tackling this challenge. In the process, we discovered that dynamic regulation is a good method for optimizing biomanufacturing, because prioritization of growth and production can be achieved simultaneously. We distilled this observation from both literature[8] and our Human Practices activities. Dynamic regulation can be achieved through computer-assisted feedback control, and we found that Argeitis et. al developed automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth[9]. So far this is the most recent and sophisticated feedback system for optogenetics. However, after examining his method, we found that while his feedback control system was closed-loop, his physical system was open. Measurement samples were discarded as waste. This is not advantageous to biomanufacturing, as this will lead to much product being wasted, lowering effective yield.
To solve this, we combined the insights and design features from these two systems (Zhao and Argeitis) to create an automated, closed-loop feedback control system for Light Wait.
PDF-LA!
Plate-Dish-Flask Light Apparatus (PDF-LA!) supports optogenetic research by allowing researchers to investigate cells cultured in 12-well plates, petri dishes, and Erlenmeyer flasks.
Product Demonstration
Figure 5. Showcase of PDF-LA!.
Figure 6. With PDF-LA!, you’ll be light-years ahead of the competition! At the very least, you can program your own snazzy light show and be the envy of other optogenetics researchers.
The utility and functionality of PDF-LA! was validated by user feedback. We also used it when characterizing the behaviour of EL222 in repressible and inducible systems, thus producing what you see on our Results page.
Operation
This operation guide assumes that all electronics have been assembled and programmed. Ensure that this has been completed before operation, else results may vary. Instructions may be found on our dedicated page for PDF-LA!.
- Place your container into the required holder. If using an Erlenmeyer flask, first rest the flask on D-LA!, then place the flask adapter over the flask to form F-LA!. Keeping a firm grip on F-LA!, pull the flask upwards sharply to ensure a tight fit.
- Connect the AC adapter to the Arduino and wall socket.
- Turn on the wall switch controlling the AC adapter.
The devices should light up as shown in the product demonstration video above.
Possible Configurations
DF-LA! was designed with modularity and flexibility as fundamental guiding principles. Many configurations are possible (Figure 7), enabling researchers to customize their experimental setups to a greater degree.
Figure 7. Examples of possible configurations.
P-LA! comprises a tech holder and a lighting plate.
Collectively, a single unit of DF-LA! comprises a tech holder, a petri dish illumination column, and a flask adapter.
Presenting, PDF-LA!.
Click on the picture below to visit its dedicated page.
Light Wait
Light Wait supports optogenetic research, especially in optogenetic biomanufacturing, by allowing researchers to scale up to a 500 ml working volume bioreactor.
Product Demonstration
Light Wait was validated through a series of experiments which first proved each component’s functionality, and then the functionality of the whole system when all the components were assembled.
Experimental Plans
The overnight culture for the experiment was obtained by inoculating the E. coli strain top 10 from glycerol stock that stored in -80 °C freezer. Cells harboring blue light repressible RFP (fused with YbaQ degradation tag) expression plasmid Brep-RFP-YbaQ were grown in Luria-Bertani (LB) broth medium supplemented with Kanamycin (Km) (50 μg/mL) at 37˚C with shaking speed at 225 RPM. Before starting the experiment, the overnight culture was refreshed in LB with kanamycin in shaking incubator. The cell density (absorbance at 600 nm) and red fluorescence protein (RFP) expression (excitation and emission wavelengths at 535 nm and 600 nm respectively) were measured using microplate reader (H1, Biotek, USA). The optogenetic bioreactor, Light Wait was housed in a large shaking incubator, the temperature was maintained at 37˚C and shaking speed was set at 225 RPM. The refreshed cell culture was mixed with fresh LB to make a total volume of 500 ml in the bioreactor chamber. Cell samples were drawn from the bioreactor at different time point to obtain different OD600 and RFP. The calibration of bioreactor OD and RFP sensors was done by comparing the data against the readings acquired from microplate reader. During the cell growth phase (OD600 less than 0.6), bioreactor’s build-in blue light was shone to repress the RFP expression. The blue light would be turned off automatically by the computer when the OD600 exceed 0.6, and subsequently the RFP could be expressed (production phase). Blue light would be turned on again once RFP reading reaches 900, this would stop RFP expression.
Experimental Results
Please visit Results:Cell-Machine Interface for the outcomes of our experimental plans.
Operation
This operation guide assumes that all components have been assembled and programmed. Ensure that this has been completed before operation, else results may vary. For instructions on how to set up and operate each component of Light Wait, please refer to our dedicated component pages.
- Place Light Wait in a shaking incubator unit as shown in our Product Demonstration. Take care to ensure that all wires and tubing are slack and of sufficient length, else they may become disconnected during operation.
- Fill and cover the fermentation chamber.
- Connect the pump, 2-in-1 sensor, and the fermentation chamber with the silicone tubings in a loop as shown below (Figure 8). The remaining 2 small tubes are for introducing more media, and an air pump.
- Turn on the AC adapters for the pump and the LEDs in the fermentation chamber. The pump should begin to rotate and the LEDs should light up. Connect the Arduino controlling the 2-in-1 sensor to your PC. Load the code for the 2-in-1 sensor and open the Serial Monitor to check that the sensor is collecting data.
- After verifying that all the components are working to your satisfaction, close the shaking incubator door.
- When the OD reaches your target levels, the LEDs in the fermentation chamber will turn off. The green LED in the 2-in-1 sensor will also turn off, and the red LED will turn on.
- When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are stressed, the LEDs in the fermentation chamber will turn on again.
- When the fluorescence from the stress reporter reaches your predetermined value indicating that the cells are NOT stressed, the LEDs in the fermentation chamber will turn off again.
- Steps 7-8 will repeat indefinitely, unless you power the system off.
Light Wait comprises a peristaltic pump, a 2-in-1 OD and fluorescence sensor, and a fermentation chamber.
Click on the picture of the component to be taken to its dedicated page!
References
[2] Wang, H., & Yang, Y. (2017). Mini Photobioreactors for in Vivo Real-Time Characterization and Evolutionary Tuning of Bacterial Optogenetic Circuit. ACS Synthetic Biology, 6(9), 1793-1796.
[3] Wang, H., & Yang, Y. (2017). Mini Photobioreactors for in Vivo Real-Time Characterization and Evolutionary Tuning of Bacterial Optogenetic Circuit. ACS Synthetic Biology, 6(9), 1793-1796.
[4] Gerhardt, K. P., Olson, E. J., Castillo-Hair, S. M., Hartsough, L. A., Landry, B. P., Ekness, F., . . . Tabor, J. J. (2016). An open-hardware platform for optogenetics and photobiology. Scientific Reports, 6(1).
[5] Delvigne, F., & Noorman, H. (2017). Scale-up/Scale-down of microbial bioprocesses: A modern light on an old issue. Microbial Biotechnology, 10(4), 685-687.
[6] Zhao, E. M., Zhang, Y., Mehl, J., Park, H., Lalwani, M. A., Toettcher, J. E., & Avalos, J. L. (2018). Optogenetic regulation of engineered cellular metabolism for microbial chemical production. Nature, 555(7698), 683.
[7] Lalwani, M. A., Zhao, E. M., & Avalos, J. L. (2018). Current and future modalities of dynamic control in metabolic engineering. Current Opinion in Biotechnology, 52, 56-65.
[8] Ceroni, F., Boo, A., Furini, S., Gorochowski, T. E., Borkowski, O., Ladak, Y. N., ... & Ellis, T. (2018). Burden-driven feedback control of gene expression. Nature Methods, 15(5), 387. [9] Milias-Argeitis, A., Rullan, M., Aoki, S. K., Buchmann, P., & Khammash, M. (2016). Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth. Nature Communications, 7(1).
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We’re using synthetic biology to change the way the world thinks and functions.
We’re a little disruptive, dangerous and maybe a tad too bold. But the world needs some shaking up every now and then, and we think we’re just the right people for that.
Together we’re going to engineer biology and create something awesome.
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