Team:Washington/Optogenetics

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==<i>Optogenetics: A hands-free approach to protein regulation</i>==
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[[File:Washington_Multichromatic_Peppers.png|border|180px|right|thumb|An image of two peppers by shining red and green light on bacteria with light receptors.[3]]]
<h1 id='Background'>Background </h1>
<h1 id='Background'>Background </h1>
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Bacterial metabolic pathways constitute a foundation on which to build biological processes that perform useful tasks such as the production of drugs or biofuels, or the degradation of harmful compounds. Often, to achieve optimal efficiencies, substantial tuning of expression levels of each component of the pathway must be carried out. The burgeoning field of optogenetics affords researchers the ability to control gene expression with light. In addition to being cheap and readily available, control of gene expression with light has a number of advantages over standard chemical methods of gene control. Among these are the ability to finely tune induction levels through changes in intensity, as well as the ability to quickly and completely remove the input.  Further, many light induced expression systems are reversible depending on the wavelength used for illumination. Thus one of the goals of the 2012 iGEM team is to develop a light inducible system which we hoped to apply to the tuning of multiple metabolic pathways.
 
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Bacterial metabolic pathways constitute a foundation on which to build biological processes that perform useful tasks such as the production of drugs, biofuels, or the degradation of harmful compounds. Often, to achieve an optimally tuned system, expression levels of each component must be varied over a wide range. The burgeoning field of optogenetics affords researchers the ability to control gene expression with light. In addition to being low cost,  controlling of gene expression with light has a number of advantages over standard chemical methods of gene control. Among these are the ability to finely tune induction levels through changes in intensity, as well as the ability to quickly and completely remove the input. Further, many light-induced expression systems are reversible depending on the wavelength used for illumination. Thus one of the goals of the 2012 iGEM team is to implement a light inducible system which we hoped to apply to the tuning of multiple metabolic pathways. In addition, we wanted to make the tools to control optogenetic systems readily available and easier to access.
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<h1 id='Methods'>Methods<html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
 
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'''Characterization of a light inducible protein expression system for the tuning of biological pathways
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'''
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<h1 id='App'>Our App: E. colight<html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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<center>[http://www.youtube.com/watch?v=8h4RbDjTDYg <b><font size='4'>See our app in action!</font></b>]</center>
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[[File:UWiGEM2012QR_size6.png‎|link=https://play.google.com/store/apps/details?id=com.UWIgem.test2d|left|text-top|alt=App QR Code|frame|We developed an [https://play.google.com/store/apps/details?id=com.UWIgem.test2d app for the Android OS] that allows up to control gene expression with light.]][[Image:Lightapp.png|150px|right]]
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At the beginning of our project we wanted to make a system for high-specificity light control without the common problems such systems came with: High cost, difficult assembly, and very little reproducibility. With these goals in mind, we worked with Max Gelb to create E. colight.
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[[File:Optogenetics diagram 1.png|700px]]
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E. colight was designed entirely from scratch in order to illuminate bacterial cultures with different types of light. The light source is on as either blue, green, or red. In the app, any given color of light can be shone between 0 and 60,000 milliseconds, which will illuminate the culture accordingly. Intensity of the light can be adjusted between 0 and 100%. All three colors are individually controllable, making high-specificity multichromatic tuning very easy.
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Chromatic tuning is based off light-induced protein interactions. The most basic of these systems is a monochromatic system, in which a specific wavelength of light changes a protein's conformation temporarily, causing it to interact differently with its environment. Our system's protein was a fusion the genes CcaR and CcaS with a chromophore, and changed conformation in response to green light (λ=535nm), and red light (λ=672nm). When stimulated by green light, the protein exhibits improved autophosphorylation, and the phosphorylated protein binds to promoter region P<sub>cpcG2</sub> and activates the downstream gene. Red light, on the other hand, changes the protein conformation such that it resists phosphorylation, thus not binding to the promoter and not allowing gene expression. Any gene placed after the promoter can be theoretically controlled by the exposure of λ=535nm and λ=637nm light to the system.
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Unfortunately, light-induced protein interactions require a lot of work to characterize. In the past, experiments have involved elaborate set-ups like light masks, or specific-wavelength lasers. When beginning our experiment, we set out to engineer a system that would produce light both modular in position and in color. The result was a tablet app, e. colitune(light), described in detail in the following section.
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The app has two settings which allow it to control bacterial cultures: One is its petri dish setting, which is a single light source made for a petri dish with an 8.5mm diameter. The other is a 96-well plate, which means it has '''''96 individually-controllable light sources''''', which lends the potential to run huge numbers of tests in tandem. The size of both the wells and the petri dish is flexible and can be adjusted between 0 and 100% of its original size.
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'''E. colight
 
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'''
 
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The current swath of tools available to illuminate bacterial cultures in a controlled manner often necessitate the purchase of specialized equipment or materials. Further, devices must often be both constructed, and fully characterized by the researcher prior to conducting any experiments to ensure reproducibility. To circumvent these problems, we sought to develop a tablet based application for the Android platform which affords a fully customizable method for illumination of bacterial plate cultures inexpensively and reproducibly.<div style="clear:both;"></div>
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<h1 id='Methods'>Methods<html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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[[File:Picture1 wtf alex.png|thumb|right|400px|The basic operation of our light system.]]
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===Characterization of a light inducible protein expression system for the tuning of biological pathways===
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Chromatic tuning is based on light-induced protein interactions. The most basic of these systems is a monochromatic system, in which a specific wavelength of light changes a protein's conformation temporarily, causing it to interact differently with its environment. Our system involves the use of a photoreceptor CcaS attached to a chromophore and CcaR, a response regulator. The chromophore, when illuminated with green light (λ=535nm) will undergo a conformational change leading to autophosphorylation of the photoreceptor CcaS. Increased autophosphorylation leads to activation of the response regulator via phosphorylation. The activated response regulator will then bind to the promoter P<sub>cpcG2</sub>, activating transcription and producing beta-galactosidase. Beta-galactosidase will cleave the S-gal, creating a black precipitate and allowing us to know visually that our light sensor is working. Red light (λ=672nm), on the other hand, changes the protein conformation such that it resists phosphorylation, thus not binding to the promoter and not allowing gene expression. Any gene placed after the promoter can be theoretically controlled by the exposure of λ=535nm and λ=637nm light to the system.
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In recent years, tablet computers have become increasingly ubiquitous. Each year sees the release of many new tablets, including some that are relatively cheap. Further, many tablets operate on the Android platform, allowing us to develop a freely available app with many features we believe will be useful for future optogenetics studies.
 
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[[File:AMOLED diagram.png|thumb|left|top|300px|AMOLED displays have organic cathode layers that provide high-intensity light when stimulated by a TFT array.]]After a bit of research we decided to install our app on the Samsung Galaxy Tab 7.7. The benefits of this tablet were its relative cheapness (approximately $300), and its type of display. The Samsung Galaxy Tab 7.7 uses a Super AMOLED (Active-Matrix Organic Light-Emitting Diode) display, which emits brighter and more intense light than LCD displays used on other tablets. [AMOLED_diagram.png] Contrast is also elevated under an AMOLED display, as the color black is represented by turning an LED off, instead of the dark-grey substitute LCD displays use. The downside to AMOLED displays is that the organic material in the screen decays over the course of years, which causes uneven color shifts and imprints in the screen, but we decided that the benefits of the AMOLED display outweighed this detriment. The app was programmed by Max Gelb.
 
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'''E.colight app feature list:
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[[File:Picture 2.png|thumb|left|400px|By inserting the light system into ''E. coli'', we can test its functionality by measuring pigment density.]]
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'''[[File:App+Plate-in-action.jpeg|right|thumb|text-top|200px|An example petri dish on top of the working app.]]
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A blue light sensor (Lov_Tap BBa_K191003) was found in the registry and transformed to be used as one of our main components to create a functioning blue light sensor, activated at 470 nm wavelengths of light. The part taken from the registry was joined with a TetR inverter, since originally the blue light sensor repressed gene expression. The newly added TetR inverter then suppressed the regulator that came with Lov_Tap, allowing transcription to occur under stimulation of blue light. We also included sfGFP which is our readout protein, allowing the used to know whether or not the light sensor was properly functioning.  Near the end, once we had all the pieces we did a Gibson assembly to join our pieces. At that time we noticed that our blue light sensor had a point mutation that needed to be fixed. The point mutation was then fixed through several PCRs that retrieved two parts of the sensor without the mutation. Once those two parts were obtained, they were then fused together in the Gibson assembly along with being Gibson assembled together with the inverter and sfGFP. Future iGEM projects could be focused around detaching sfGFP as the output protein and attaching the light sensor to other parts of the e.coli gene, allowing light illuminated control of genetic pathways.
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* Petri Dish / 96 Well Plate Formats available
 
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* Red, Blue, and Green light available
 
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* Intensity of light delivered can be modulated by:
 
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* Frequency of Flashing
 
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* Changing light intensity
 
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* Well sizes can be changed (in 96 well plate format only)
 
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===Building Optogenetic Tools===
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The current swath of tools available to illuminate bacterial cultures in a controlled manner often necessitate the purchase of specialized equipment or materials. Further, devices must often be both constructed, and fully characterized by the researcher prior to conducting any experiments to ensure reproducibility. To circumvent these problems, we sought to develop an application whose accessibility played off of modern technological conveniences. In recent years, mobile technology has become increasingly ubiquitous. Each year sees the release of many new tablets, phones, and small computers, including some that are relatively cheap. Tablets are excellently-sized, cost-effective tools for use with bacterial cultures.
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'''Experimental Description
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[[File:AMOLED diagram.png|thumb|left|top|250px|AMOLED displays have organic cathode layers that provide high-intensity light when stimulated by a TFT array.[1]]]After a bit of research we decided to install our app on the Samsung Galaxy Tab 7.7. We chose the tablet because of it's relatively low cost and because of the brightness and contrast of the display. The Samsung Galaxy Tab 7.7 uses a Super AMOLED (Active-Matrix Organic Light-Emitting Diode) display, which emits brighter and more intense light than LCD displays used on other tablets. Contrast is also elevated under an AMOLED display, as the color black is represented by turning an LED off, instead of the dark-grey substitute LCD displays use. The downside to AMOLED displays is that the organic material in the screen decays over the course of years, which causes uneven color shifts and imprints in the screen, but we decided that the benefits of the AMOLED display outweighed this detriment. The app was programmed by Max Gelb.[[File:App+Plate-in-action.jpeg|right|thumb|text-top|200px|An example petri dish on top of the working app.]]
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'''
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[[File:AppUW.png|left|thumb|text-bottom|200px|The UW logo, made by flashing mixtures of light fast enough to trick the human eye, as well as cameras.]]E. coli (Strain JT2, derivative of RU1012, gift from Tabor lab, Tabor. et al, J. Mol. Biol. 2011: 405, 315–324) was transformed with pJT122 and pJT106b. We tested strains that contain the green light sensor, with a lacZ output. In short, when exposed to green light, the strains should make lacZ, and in red light, they should not. In order to test both the light sensing system and the app, we carried out the following experiments. These experiments include bacteria density gradient, red light inhibition confirmation on green light sensor bacteria, and tablet light leak. Experimental protocols are available on our protocols page.
 
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For the bacteria density gradient experiment, we grew an overnight culture of JT2 cells transformed with pJT122 and pJT106b overnight in buffered LB. Cultures were grown in tubes wrapped with aluminum foil to ensure no activation by light occurred during growth. We then diluted the cultures in a 1:5 serial dilution to a final dilution of X. After planted on the 96-well plate in a row, the bacteria were shined continuously by tablet green light mode. The experiment was carried in 37 C incubator and the period is 15-hour long, which we concluded from long-time repeated tests. The result showed obvious gradient on the darkness of spots in the wells and illustrated the bacteria gradient can control the pigment produced.
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Our solution was to design and build a software application for use on tablet devices that is able to shine light of different frequencies in different conformations (i.e. 96 well plate, petri dish) to enable controlled and reproducible characterization and testing of optogenetic pathways. The application that we designed can generate different wavelengths of light. To use the application we simply chose well or plates, and then chose wait time between flashes of colors in milliseconds of wait time and color intensities of each color from 0-100. The bacteria can then be grown overnight on top of the app. The app is currently available in the google play store for free and provides a convenient way for anyone interested in biological sciences to test their optogenetic systems. Because iGEM teams and labs will have a set budget, we hope that this tool becomes useful to all that want to pursue science.
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From the Tabor paper, we found red light could inhibit the pigment production process. So we followed the ~2-inch petri dish mixture protocol indicated in web page and set control experiment up. We set one plate in green light, one in red light, and one covered with aluminium foil, all of which placed in 37 C incubator. After 15-hour wait and quantification, the result showed the lowest intensity in red light and higher one in green light. Then the red light inhibition system in this JT2 bacteria is confirmed.
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===Experimental Description===
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E. coli was transformed with pJT122 and pJT106b, which contained the lacZ gene, the green light sensor, and the system's chromophores.[3] In order to characterize the genes, we put them through three experiments: An assay of pigment concentration based on bacterial concentration, an assay of pigment concentration based on absorbed light, and a test of light leakage between wells.
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During the control test on one 96-well plate between green light and red light comparison, we found the certain green project area was lighter than some wells far away from the red light. After several repeated tests, we were sure that this was not a coincident, but a tablet light leak. Since the light projected from tablet was not vertically on each well and the 96-well plate had no smooth surface, the light would reflect and spread among wells, which lead to light leak. In general, two solutions were come up: one is to use smaller area of light in each well, which is one of the function you can see in the app now;  the other is to use a rubber gasket between plate and tablet to decrease light amount and reflection. The tests confirmed the rubber gasket is a good way to solve the light leak by tablet.
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[[File:Washington_Concentration_Gradient.png|left|thumb|350px|In the bacterial concentration assay, as the amount of E. coli in a well increased, so too did the expression of lacZ.]]For the assay based on bacterial concentration, we grew an overnight culture of JT2 cells transformed with pJT122 and pJT106b overnight in buffered LB. Cultures were grown in tubes wrapped with aluminum foil to ensure no light interfered with gene expression during growth. We then diluted the cultures in a 1:5 serial dilution in a row on a 96-well plate, and exposed them only to green light from E. colight for a 15-hour incubation. As seen in the picture to the right, the cells visibly demonstrated an increase in pigment production (a sign of increased lacZ activity).[[File:09192012 cropped scaled.png|border|250px|right|thumb|lacZ is downregulated by red light in our modified bacteria. Layout of plates, from left to right: constant illumination under red light, green light, or grown in the dark.]][[File:09192012 cropped measurements plot.png|right|thumb|250px|Image analysis of the petri dishes above. The x axis indicates treatment (red light, green light, or darkness). The y axis indicates darkness. Red-treated cells are much lighter than the other treatments, indicating red light downregulation of lacZ expresion.]]
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Three typical experiments are all stated in Result section.
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In order to test the functionality of the green light activator and red light repressor, we plated the same cells onto three petri dishes. One petri dish was incubated in green light, one in red light, and one in total darkness for 15 hours. The dish exposed to red light demonstrated very strong downregulation, while the dish exposed to green light showed strong upregulation.
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When performing characterization tests on 96-well plates, we found that bacteria over a predominantly-green well but near predominantly-red wells had drastically decreased gene expression compared to predominantly-green wells that weren't near red light. After repeating trials, we decided this was due to light leaking from one well to another. An LED spreads light in all directions, unlike a laser which focuses only in a single area. This leak was causing the green light sensors to switch conformation and repress gene output, which meant that our tuning could lead to imprecise results. In order to compensate for this, we added a feature to the app, and made use of a rubber gasket. Hoping to keep our tools all electronic, we added a well-size modulator to the app in order to increase the gap spaces between wells and hopefully decrease the amount of light that moved from its generative well to another well. The rubber gasket was our physical fix, and simply involved placing a 96-well rubber cover on top of the app so that only light moving upwards would pass though.
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In order to make more precise comparisons between data, we used ImageJ to quantify lacZ expression. In ImageJ, the images were converted to grayscale, and the average black pixel density was calculated for each plate or well. The quantified data gives a more careful look at our results, and adds details to results that cannot be told apart by the naked eye.
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<h1 id='Results'>Results Summary <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
<h1 id='Results'>Results Summary <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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[[File:20120927 big dots cropped experimentwells resized.png|border|350px|left|thumb|Plate Experiment: Columns 1-5: constant exposure to green light. Columns 6-7: flashing red light. Columns 8-12: constant exposure to green light. Rows are replicates.]]When originally characterizing the light sensor, we found that bacteria left in darkness turned the controlled gene on equal to or more than the green light-illuminated plate. This is possibly because P<sub>cpcG2</sub> is leaky, or possibly because the natural conformation of the green light sensor is its upregulation form. Either way, our tests demonstrated that only the red light repressor was truly functional. When dealing with light leakage, we found that even decreasing the size of the light source didn't help as much as simply covering the light with the rubber stop.[[File:20120927 big dots cropped experimentwells firstroi ddply plot.png|border|350px|right|thumb|Image analysis of the plate experiment. The y axis is well darkness and the x axis is distance from the center of the plate. 0 is columns 6 and 7, 1 is 5 and 8, and so on. Wells closest to the center (red light, reduces lacZ expression) are lighter than wells that are farther away, indicating weaker gene expression.]]
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The finished app was capable of flashing  series of blue, green, or red light, or none at all, for an amount of time up to [maximum wait time]. Despite originally intending to compensate for light intensity with this, we learned that programming intensity of light was easy, so the app comes with both for easier tuning.
 
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The app is currently able to use two culture formats. One is a 96-well plate, which contains 96 separately-controllable light sources. The other is a standard petri dish, which acts as a single light source. During testing, we found that light had a tendency to leak  between wells of a  96-well plate despite the spacing between wells and the LEDs on the app. To somewhat compensate for this, an option for well size was added that allows the wells to be adjusted between 1 and 100% of their normal size. This limits leakiness between wells while still allowing for strong induction.
 
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We wanted to characterize the multichromatic system put together by Tabor et. al. In order to confirm the functionality of our light sensor we did a series of experiments. Our first experiment involved simply plating our bacteria onto three plates and then growing them under illumination of different colors of light or no light at all in the case of the control. We see that there is a clear difference between the plates. On the left, when the plate was grown on red light, there was complete repression of the reporter gene, therefore a white plate. In the middle, the plate was grown under illumination of green light and showed increased gene expression afterwards. The control plate which was grown in aluminum foil shows high levels of gene expression; higher than what should be expected of under normal conditions. There should be intermediary amounts of transcription, somewhere between the gene being turned on and being off. However, due to a leaky promoter transcription occurs via the response regulator more often than is expected. In order to make a better comparison between the three different plates, they were quantified through the use of imageJ. The average pixel density was taken for each plate and then graphed. The quantified data gives a more careful look at our results that are not instantly apparent by visually just looking at it. By looking at the quantified data it’s apparent that grown in the dark, there appears to be more gene expression. What should be expected of this system is that there should be the least amount of gene expression under red light, which was accomplished, mediary amounts for the control plate and maximum gene expression when grown under red light. Due to our results, we have concluded that the system works well under red light repression, since red light is able to almost completely halt gene expression.
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As a proof of concept of both the light sensor and E. colight, we created a gradient of gene expression by making use of the light leakage. In two rows of a 96-well plate, we programmed all the well lights to display green constantly except for two lights in the middle, which periodically flashed red. The red light-induced downregulation of gene expression was demonstrated as the least amount of visible pigment was in the center of the gradient, and the greatest amount was at the ends. The well images were also put into ImageJ, which measured the average pixel value of each culture, as is shown in the graph on the right. The large uncertainty in the data is caused by uneven bacterial spreads in the agar, which can be solved by using soft agar.
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[[File:09192012 cropped scaled.png]]
 
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[[File:09192012 cropped measurements plot.png]]
 
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In order to create some kind of gradient for the multichromatic system, we decided to use a 96 well plate and the app. There are rows with constant green light excitation, two rows in the middle that flash and end rows that have constant green light on. The plate is darkest on either end with a gradient that lightens up as it gets closer to the middle, where red and green light flash, inducing intermediary amounts of gene expression. Ideally there should only be lighter colors of wells in columns 6 and 7. However, there appears to be some leakiness with the utilization of the light app as some of this light has managed to leak to other wells, which creates a sort of gradient with darkest wells on either side and becoming lighter towards the middle. Pipetting error also affects the data as some of the wells have more colonies than others which leads to higher pixel values even if gene expression may not necessarily be higher. Using soft agar can help resolve this problem in the future. The quantified data above was made by using ImageJ and measuring average pixel value of each plate. Generally there is a gradient of increased pixel value as the well is further away from the red light. Both replicates show similar results, even though replicate one has slightly ,more dramatic increases while replicate one appears to have a steadier rise. Because of leakiness, some of the flashing red light that was supposed to be confined to wells 6 and 7 have leaked over to nearby wells, causing some gene repression even when there shouldn’t necessarily have been any. However the results show that gene repression is extremely sensitive to red light and a gradient can be created from various levels of red light relatively easily. That being said, gene control isn’t completely “on” or “off” but also holds the benefit of having various levels of “on” and “off”.
 
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[[File:20120927 big dots cropped experimentwells resized.png]]
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[[File:20120927 big dots cropped experimentwells firstroi ddply plot.png|750px]]
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<h1 id='Future'>Future Directions<html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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<h1 id='Future'>Future Directions <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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We believe that light inducible gene expression represents a field that could be of great interest to synthetic biologists, and the iGEM community.  The work we carried out this summer has laid a foundation on which we hope future teams can build, but there is much more than can be done.  To that end, we are currently trying to standardize more the light sensors, and submit them to the registry so that they are readily available for all interested teams in the future. The light sensor used in this year's research appears to have a rather leaky promoter in our hands, leading to more transcription than we would normally expect in dark conditions. We think that the E.colight app developed over the summer could be used to address this problem.  In 96 well plate experiments we noticed what appeared to be leakiness between wells.  In order to carry out experiments using liquid cultures in the future, we may need to modify the assay plates.  We are currently exploring a variety of options to accomplish this. For example, a suggestion was made to use a rubber adaptor with appropriately placed holes that would fit under a 96 well plate.  Currently, the blue light sensor has not been characterized, and the only confirmation of a working sensor available right now are the sequencing files. We hope to continue to work with this sensor, testing and characterizing the sensor and seeking to fix any problems with the light sensor if problems are to be found. We hope to accomplish this kind of testing within the next couple of weeks. We would also like to work with the light sensors that we currently have in order to increase control of genetic pathways. The light sensors can also be attached to different genes in order to control production of certain substrates. Finally, Taking current light sensors available and applying them to e.coli is another aspiration of the Washington iGEM team.
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[[File:UWiGEM2012QR_size6.png‎|link=https://play.google.com/store/apps/details?id=com.UWIgem.test2d|right|text-top|alt=App QR Code|frame|[https://play.google.com/store/apps/details?id=com.UWIgem.test2d The app is available on Google Play for any software using Android OS.]]]Currently the app is available on google play and can be downloaded by any android. However, in the future we want to get this app onto the apple app store so that it can also be used by apple users as well. It is preferable however to use the app that was used for our testing because of the way that the app displays light, allowing for more pure color versus the retina display which filters light so there is less of a pure concentration of the wavelength of light desired. We want to work more with Tabor’s multichromatic system, improving the light sensor available so that we can biobrick them later and have those pieces readily available for use. We suspect that a big problem with the light sensor right now is the leaky promoter, which leads to more transcription than we would normally expect in dark conditions. The promoter should be modified accordingly, either by fixing any present mutation or choosing to use a new promoter entirely for various reasons. Also to improve characterization of the sensor itself, in the future soft agar should be used which will allow more sufficient spread of bacteria, which should minimize differences in bacteria colonies in each well, allowing better data collection with imageJ. There also appears to be some leakiness between wells that should be addressed more appropriately in the future. A suggestion was made to use a rubber stopper with holes in it on top of the app to try to minimize leakiness of light between different wells.We also want to work with different light sensors to improve functioning and to use light sensors to promote various gene expression of different proteins.
 
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Citations
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The main idea of creating a light activated system would be to control gene transcription, either producing a wanted substrate or breaking substrates down. One of the ways we would like to work with our light systems in the future is to optimize it to control metabolism or production of needed substrates in e.coli. Doing that will allow us to optimally control the growth of our bacteria, only allowing it to grow under a certain wavelength of light and metabolism being repressed in the absent of light and slowed down without the right wavelength of light illuminating the bacteria. That way, if someone becomes contaminated with the bacteria and goes out into the environment, the bacteria will ideally not be able to thrive there. Therefore, by preventing bacteria growth through optimized gene control we can prevent the spread of bacteria therefore protecting the environment from potential contamination with mutant strains.
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Levskaya, A. et al. Synthetic biology: Engineering Escherichia coli to see light. Nature 438, 441–442 (2005).
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Tabor, J. J., Levskaya, A. & Voigt, C. a Multichromatic control of gene expression in Escherichia coli. Journal of molecular biology 405, 315–24 (2011).
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The app is readily available and can be downloaded onto any android OS system through the Google play store. Currently we have access to the tablet system with the app on it so we will want to use this app to further test our bacteria in the future to validate for functionality and to control genetic expression.
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<h1 id='Parts'>Parts Submitted <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
<h1 id='Parts'>Parts Submitted <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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[http://partsregistry.org/wiki/index.php?title=Part:BBa_K892800 BBa_K892800 '''LovTAP with reporter gene''']
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LovTAP system, with inverter and sfGFP output.
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<h1 id='Sources'>Sources <html><a href="#Background"><font size="3">[Top]</font></a></html></h1>
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[1]http://upload.wikimedia.org/wikipedia/commons/9/96/AMOLED_en.svg
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<br>
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[2]Levskaya, A. et al. Synthetic biology: Engineering Escherichia coli to see light. Nature 438, 441–442 (2005).
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<br>
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[3]Tabor, J. J., Levskaya, A. & Voigt, C. a Multichromatic control of gene expression in Escherichia coli. Journal of molecular biology 405, 315–24 (2011).

Latest revision as of 03:59, 4 October 2012

Optogenetics: A hands-free approach to protein regulation

An image of two peppers by shining red and green light on bacteria with light receptors.[3]

Background

Bacterial metabolic pathways constitute a foundation on which to build biological processes that perform useful tasks such as the production of drugs, biofuels, or the degradation of harmful compounds. Often, to achieve an optimally tuned system, expression levels of each component must be varied over a wide range. The burgeoning field of optogenetics affords researchers the ability to control gene expression with light. In addition to being low cost, controlling of gene expression with light has a number of advantages over standard chemical methods of gene control. Among these are the ability to finely tune induction levels through changes in intensity, as well as the ability to quickly and completely remove the input. Further, many light-induced expression systems are reversible depending on the wavelength used for illumination. Thus one of the goals of the 2012 iGEM team is to implement a light inducible system which we hoped to apply to the tuning of multiple metabolic pathways. In addition, we wanted to make the tools to control optogenetic systems readily available and easier to access.


Our App: E. colight[Top]

[http://www.youtube.com/watch?v=8h4RbDjTDYg See our app in action!]
App QR Code
We developed an app for the Android OS that allows up to control gene expression with light.
Lightapp.png

At the beginning of our project we wanted to make a system for high-specificity light control without the common problems such systems came with: High cost, difficult assembly, and very little reproducibility. With these goals in mind, we worked with Max Gelb to create E. colight.

E. colight was designed entirely from scratch in order to illuminate bacterial cultures with different types of light. The light source is on as either blue, green, or red. In the app, any given color of light can be shone between 0 and 60,000 milliseconds, which will illuminate the culture accordingly. Intensity of the light can be adjusted between 0 and 100%. All three colors are individually controllable, making high-specificity multichromatic tuning very easy.

The app has two settings which allow it to control bacterial cultures: One is its petri dish setting, which is a single light source made for a petri dish with an 8.5mm diameter. The other is a 96-well plate, which means it has 96 individually-controllable light sources, which lends the potential to run huge numbers of tests in tandem. The size of both the wells and the petri dish is flexible and can be adjusted between 0 and 100% of its original size.


Methods[Top]

The basic operation of our light system.

Characterization of a light inducible protein expression system for the tuning of biological pathways

Chromatic tuning is based on light-induced protein interactions. The most basic of these systems is a monochromatic system, in which a specific wavelength of light changes a protein's conformation temporarily, causing it to interact differently with its environment. Our system involves the use of a photoreceptor CcaS attached to a chromophore and CcaR, a response regulator. The chromophore, when illuminated with green light (λ=535nm) will undergo a conformational change leading to autophosphorylation of the photoreceptor CcaS. Increased autophosphorylation leads to activation of the response regulator via phosphorylation. The activated response regulator will then bind to the promoter PcpcG2, activating transcription and producing beta-galactosidase. Beta-galactosidase will cleave the S-gal, creating a black precipitate and allowing us to know visually that our light sensor is working. Red light (λ=672nm), on the other hand, changes the protein conformation such that it resists phosphorylation, thus not binding to the promoter and not allowing gene expression. Any gene placed after the promoter can be theoretically controlled by the exposure of λ=535nm and λ=637nm light to the system.


By inserting the light system into E. coli, we can test its functionality by measuring pigment density.

A blue light sensor (Lov_Tap BBa_K191003) was found in the registry and transformed to be used as one of our main components to create a functioning blue light sensor, activated at 470 nm wavelengths of light. The part taken from the registry was joined with a TetR inverter, since originally the blue light sensor repressed gene expression. The newly added TetR inverter then suppressed the regulator that came with Lov_Tap, allowing transcription to occur under stimulation of blue light. We also included sfGFP which is our readout protein, allowing the used to know whether or not the light sensor was properly functioning. Near the end, once we had all the pieces we did a Gibson assembly to join our pieces. At that time we noticed that our blue light sensor had a point mutation that needed to be fixed. The point mutation was then fixed through several PCRs that retrieved two parts of the sensor without the mutation. Once those two parts were obtained, they were then fused together in the Gibson assembly along with being Gibson assembled together with the inverter and sfGFP. Future iGEM projects could be focused around detaching sfGFP as the output protein and attaching the light sensor to other parts of the e.coli gene, allowing light illuminated control of genetic pathways.


Building Optogenetic Tools

The current swath of tools available to illuminate bacterial cultures in a controlled manner often necessitate the purchase of specialized equipment or materials. Further, devices must often be both constructed, and fully characterized by the researcher prior to conducting any experiments to ensure reproducibility. To circumvent these problems, we sought to develop an application whose accessibility played off of modern technological conveniences. In recent years, mobile technology has become increasingly ubiquitous. Each year sees the release of many new tablets, phones, and small computers, including some that are relatively cheap. Tablets are excellently-sized, cost-effective tools for use with bacterial cultures.

AMOLED displays have organic cathode layers that provide high-intensity light when stimulated by a TFT array.[1]
After a bit of research we decided to install our app on the Samsung Galaxy Tab 7.7. We chose the tablet because of it's relatively low cost and because of the brightness and contrast of the display. The Samsung Galaxy Tab 7.7 uses a Super AMOLED (Active-Matrix Organic Light-Emitting Diode) display, which emits brighter and more intense light than LCD displays used on other tablets. Contrast is also elevated under an AMOLED display, as the color black is represented by turning an LED off, instead of the dark-grey substitute LCD displays use. The downside to AMOLED displays is that the organic material in the screen decays over the course of years, which causes uneven color shifts and imprints in the screen, but we decided that the benefits of the AMOLED display outweighed this detriment. The app was programmed by Max Gelb.
An example petri dish on top of the working app.


Our solution was to design and build a software application for use on tablet devices that is able to shine light of different frequencies in different conformations (i.e. 96 well plate, petri dish) to enable controlled and reproducible characterization and testing of optogenetic pathways. The application that we designed can generate different wavelengths of light. To use the application we simply chose well or plates, and then chose wait time between flashes of colors in milliseconds of wait time and color intensities of each color from 0-100. The bacteria can then be grown overnight on top of the app. The app is currently available in the google play store for free and provides a convenient way for anyone interested in biological sciences to test their optogenetic systems. Because iGEM teams and labs will have a set budget, we hope that this tool becomes useful to all that want to pursue science.

Experimental Description

E. coli was transformed with pJT122 and pJT106b, which contained the lacZ gene, the green light sensor, and the system's chromophores.[3] In order to characterize the genes, we put them through three experiments: An assay of pigment concentration based on bacterial concentration, an assay of pigment concentration based on absorbed light, and a test of light leakage between wells.

In the bacterial concentration assay, as the amount of E. coli in a well increased, so too did the expression of lacZ.
For the assay based on bacterial concentration, we grew an overnight culture of JT2 cells transformed with pJT122 and pJT106b overnight in buffered LB. Cultures were grown in tubes wrapped with aluminum foil to ensure no light interfered with gene expression during growth. We then diluted the cultures in a 1:5 serial dilution in a row on a 96-well plate, and exposed them only to green light from E. colight for a 15-hour incubation. As seen in the picture to the right, the cells visibly demonstrated an increase in pigment production (a sign of increased lacZ activity).
lacZ is downregulated by red light in our modified bacteria. Layout of plates, from left to right: constant illumination under red light, green light, or grown in the dark.
Image analysis of the petri dishes above. The x axis indicates treatment (red light, green light, or darkness). The y axis indicates darkness. Red-treated cells are much lighter than the other treatments, indicating red light downregulation of lacZ expresion.


In order to test the functionality of the green light activator and red light repressor, we plated the same cells onto three petri dishes. One petri dish was incubated in green light, one in red light, and one in total darkness for 15 hours. The dish exposed to red light demonstrated very strong downregulation, while the dish exposed to green light showed strong upregulation.

When performing characterization tests on 96-well plates, we found that bacteria over a predominantly-green well but near predominantly-red wells had drastically decreased gene expression compared to predominantly-green wells that weren't near red light. After repeating trials, we decided this was due to light leaking from one well to another. An LED spreads light in all directions, unlike a laser which focuses only in a single area. This leak was causing the green light sensors to switch conformation and repress gene output, which meant that our tuning could lead to imprecise results. In order to compensate for this, we added a feature to the app, and made use of a rubber gasket. Hoping to keep our tools all electronic, we added a well-size modulator to the app in order to increase the gap spaces between wells and hopefully decrease the amount of light that moved from its generative well to another well. The rubber gasket was our physical fix, and simply involved placing a 96-well rubber cover on top of the app so that only light moving upwards would pass though.

In order to make more precise comparisons between data, we used ImageJ to quantify lacZ expression. In ImageJ, the images were converted to grayscale, and the average black pixel density was calculated for each plate or well. The quantified data gives a more careful look at our results, and adds details to results that cannot be told apart by the naked eye.


Results Summary [Top]

Plate Experiment: Columns 1-5: constant exposure to green light. Columns 6-7: flashing red light. Columns 8-12: constant exposure to green light. Rows are replicates.
When originally characterizing the light sensor, we found that bacteria left in darkness turned the controlled gene on equal to or more than the green light-illuminated plate. This is possibly because PcpcG2 is leaky, or possibly because the natural conformation of the green light sensor is its upregulation form. Either way, our tests demonstrated that only the red light repressor was truly functional. When dealing with light leakage, we found that even decreasing the size of the light source didn't help as much as simply covering the light with the rubber stop.
Image analysis of the plate experiment. The y axis is well darkness and the x axis is distance from the center of the plate. 0 is columns 6 and 7, 1 is 5 and 8, and so on. Wells closest to the center (red light, reduces lacZ expression) are lighter than wells that are farther away, indicating weaker gene expression.


As a proof of concept of both the light sensor and E. colight, we created a gradient of gene expression by making use of the light leakage. In two rows of a 96-well plate, we programmed all the well lights to display green constantly except for two lights in the middle, which periodically flashed red. The red light-induced downregulation of gene expression was demonstrated as the least amount of visible pigment was in the center of the gradient, and the greatest amount was at the ends. The well images were also put into ImageJ, which measured the average pixel value of each culture, as is shown in the graph on the right. The large uncertainty in the data is caused by uneven bacterial spreads in the agar, which can be solved by using soft agar.


Future Directions[Top]

We believe that light inducible gene expression represents a field that could be of great interest to synthetic biologists, and the iGEM community. The work we carried out this summer has laid a foundation on which we hope future teams can build, but there is much more than can be done. To that end, we are currently trying to standardize more the light sensors, and submit them to the registry so that they are readily available for all interested teams in the future. The light sensor used in this year's research appears to have a rather leaky promoter in our hands, leading to more transcription than we would normally expect in dark conditions. We think that the E.colight app developed over the summer could be used to address this problem. In 96 well plate experiments we noticed what appeared to be leakiness between wells. In order to carry out experiments using liquid cultures in the future, we may need to modify the assay plates. We are currently exploring a variety of options to accomplish this. For example, a suggestion was made to use a rubber adaptor with appropriately placed holes that would fit under a 96 well plate. Currently, the blue light sensor has not been characterized, and the only confirmation of a working sensor available right now are the sequencing files. We hope to continue to work with this sensor, testing and characterizing the sensor and seeking to fix any problems with the light sensor if problems are to be found. We hope to accomplish this kind of testing within the next couple of weeks. We would also like to work with the light sensors that we currently have in order to increase control of genetic pathways. The light sensors can also be attached to different genes in order to control production of certain substrates. Finally, Taking current light sensors available and applying them to e.coli is another aspiration of the Washington iGEM team.


The main idea of creating a light activated system would be to control gene transcription, either producing a wanted substrate or breaking substrates down. One of the ways we would like to work with our light systems in the future is to optimize it to control metabolism or production of needed substrates in e.coli. Doing that will allow us to optimally control the growth of our bacteria, only allowing it to grow under a certain wavelength of light and metabolism being repressed in the absent of light and slowed down without the right wavelength of light illuminating the bacteria. That way, if someone becomes contaminated with the bacteria and goes out into the environment, the bacteria will ideally not be able to thrive there. Therefore, by preventing bacteria growth through optimized gene control we can prevent the spread of bacteria therefore protecting the environment from potential contamination with mutant strains.


The app is readily available and can be downloaded onto any android OS system through the Google play store. Currently we have access to the tablet system with the app on it so we will want to use this app to further test our bacteria in the future to validate for functionality and to control genetic expression.


Parts Submitted [Top]

[http://partsregistry.org/wiki/index.php?title=Part:BBa_K892800 BBa_K892800 LovTAP with reporter gene]

LovTAP system, with inverter and sfGFP output.

Sources [Top]

[1]http://upload.wikimedia.org/wikipedia/commons/9/96/AMOLED_en.svg
[2]Levskaya, A. et al. Synthetic biology: Engineering Escherichia coli to see light. Nature 438, 441–442 (2005).
[3]Tabor, J. J., Levskaya, A. & Voigt, C. a Multichromatic control of gene expression in Escherichia coli. Journal of molecular biology 405, 315–24 (2011).

Retrieved from "http://2012.igem.org/Team:Washington/Optogenetics"