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| − | <h1>Modeling</h1> | + | <h1>Aalto-Helsinki<br> |
| | + | <small>Bioworks</small></h1> |
| | + | <img src="https://static.igem.org/mediawiki/2014/d/dc/Aalto_Helsinki_Logov_Oma.png" class="img-responsive omalogo center-block"> |
| | <p class="bigsplashtext"> | | <p class="bigsplashtext"> |
| − | Before bringing all the parts together in the lab, we built our switch in the mathematical world. | + | Figuring out how to combine business with science. |
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| − | <div class="link" id=" Intro"></div> | + | <div class="link" id="Abstract"></div> |
| − | | + | <h2>Aalto-Helsinki Bioworks<br> |
| − | <h2 class="kakspaddingbottom">Introduction</h2> | + | <small>A Synthetic Biology Startup with a Three-Channel Gene Switch</small></h2> |
| | | | |
| | + | <h3>Project Description</h3> |
| | <p> | | <p> |
| − | To get an idea of how our gene circuit would work in an ideal situation, we explored the structure and dynamics of our system by creating a mathematical model of the reaction kinetics and a simulation that can be controlled in real time. We started working with the mathematical model without any detailed information about the system. We derived the differential equations to demonstrate how blue light and the changes in phosphorylated $YF1$ and $FixJ$ concentrations would affect the production of our three target proteins. We labeled them simply $A$, $B$ and $C$, because the system is intended to be used with any three genes encoding the proteins of choice. | + | We have engineered a three-channel switch that is controlled with the intensity of blue light. By utilizing the mechanisms of the lambda repressor, we are able to switch between the expressions of three different genes with a short delay. This kind of mechanism provides a nearly real-time control over genes, which could provide advantages in variety of industrial bioprocesses. |
| | </p> | | </p> |
| − |
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| | <p> | | <p> |
| − | Using our equations we constructed a simulation showing the effects of red and blue light on our system in real time. The user can control the input of both lights to see how they affect the production of proteins $A$, $B$ and $C$. We experimented with different values for all constants and via trial-and-error iteration we arrived to a visualized simulation that can be used to demonstrate the intended function of our system. This is an idealization. Based on present and future measurement data, the parameters can be adjusted to better the dynamics of our system. | + | Inspired by the principles of open source software, we introduce an Open Source business model implemented around our switch. We want to encourage future companies to create Open Source based solutions and to empower customers to participate in the product development. Open Source model’s transparency as well as lower degree of protection raises trust and continuity and benefits larger community. |
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| − | <div class="update Intro"></div>
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| − | <div class="link" id="Math"></div>
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| − |
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| − | <h2>Mathematical Model</h2>
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| − |
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| − | <h3 class="kakspaddingtop">Assumptions</h3>
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| − |
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| | <p> | | <p> |
| − | We assumed that the species identified in our gene circuit are the only ones that affect the overall concentrations inside the bacteria. We further assumed that binding of $CI$ to $O_R$ operator site does not impact the overall $CI$ concentration and that the amount of $CI$ bound to the $O_R$ sites was proportional to $CI$ concentration. The model is also strictly deterministic and doesn’t take any noise into account. The phosphorylation, decay, binding and production of proteins are assumed to be linear functions of concentration. We further assumed that the phosphorylation of $FixJ$ by phosphorylated $YF1$ would not involve phosphate transfer between the reacting molecules. | + | We want to share our experiences and insights in biotech entrepreneurship and address the difficulties that students and newcomers may face in the early stages of building a synthetic biology startup. |
| | </p> | | </p> |
| − | | + | |
| − | <p>
| + | |
| − | The first model was constructed before our lab work had even begun and it contains many harsh simplifications. Our aim was to get a general picture of how the system could work in ideal conditions and how stable it was.
| + | <a href="http://youtu.be/tlc7MPY9SE8"><img src="https://static.igem.org/mediawiki/2014/ 7/ 79/ Aaltohelsinki_pitc_capture.png" class="img-responsive smallerimg"></img></ a> |
| − | </p>
| + | |
| − | | + | Our pitch video on August 6th, Summer of Startups Demo Day. |
| − | <h3>Equations for Dynamics</h3>
| + | </p> |
| − | | + | </div> |
| − | <p>
| + | |
| − | Based on the assumptions made before, we arrived at following differential equations to describe the idealized dynamics of our system:
| + | |
| − | | + | |
| − | </p>
| + | |
| − | | + | |
| − | <div class="row modelimg"> | + | |
| − | | + | |
| − | <img src="https://static.igem.org/mediawiki/2014/ 0/ 0a/ Aalto_Helsinki_Equations.png" class="img-responsive"></img> | + | |
| − | </div>
| + | |
| − | </div>
| + | |
| − | | + | |
| − | | + | |
| − | \begin{eqnarray*}
| + | |
| − | & & \frac{d[YF1]}{dt} = P_1Rbs_{YF1} + DP_1[YF1]_{phos} - (Deg_{YF1}+I_B)[YF1] \\ \quad \\
| + | |
| − | & & \frac{d[YF1]_{phos}}{dt} = I_B[YF1] - (Deg_{\text{YF1}} + DP_1)[YF1]_{phos} \\
| + | |
| − | \
| + | |
| − | & & \frac{d[FixJ]}{dt} = P_1Rbs_{FixJ} + DP_2[FixJ]_{phos} - (C_{phos}[YF1]_{phos} + Deg_{FixJ})[FixJ] \\
| + | |
| − | \\
| + | |
| − | & & \frac{d[FixJ]_{phos}}{dt} = C_{phos}[YF1]_{phos}[FixJ] - (DP_2[FixJ]_{phos} + Deg_{FixJ}[FixJ]) \\
| + | |
| − | \\
| + | |
| − | & & \frac{d[CI]}{dt} = P_2Rbs_{CI} - Deg_{CI}[CI] \\
| + | |
| − | \\
| + | |
| − | & & \frac{d[TetR]}{dt} = P_ARbs_{TetR_A} + P_BRbs_{TetR_B} - Deg_{TetR}[TetR]
| + | |
| − | \end{eqnarray*}
| + | |
| − | </p>
| + | |
| − | | + | |
| − | <div class="row row-eq-height">
| + | |
| − | <div class="center-block">
| + | |
| − | <ul> | + | |
| − | <h4 class="nopaddingtop">Legend</h4>
| + | |
| − | <li><strong>$[YF1]$</strong> = concentration of $YF1$ protein</li>
| + | |
| − | <li><strong>$[YF1]_{phos}$</strong> = concentration of phosphorylated $YF1$ protein</li>
| + | |
| − | <li><strong>$[FixJ]$</strong> = concentration of $FixJ$ protein</li>
| + | |
| − | <li><strong>$[FixJ]_{phos}$</strong> = concentration of phosphorylated $FixJ$ protein</li>
| + | |
| − | <li><strong>$[CI]$</strong> = concentration of $CI$ protein</li>
| + | |
| − | <li><strong>$[TetR]$</strong> = concentration of $TetR$ protein</li>
| + | |
| − | <li><strong>$P_1$</strong> = relative strength of the first promoter in gene circuit</li>
| + | |
| − | <li><strong>$P_2$</strong> = relative strength of the $FixK_2$ promoter</li>
| + | |
| − | <li><strong>$P_A$</strong> = relative strength of the $P_R$ promoter, codes gene $A$</li>
| + | |
| − | <li><strong>$P_B$</strong> = relative strength of the $P_{RM}$ promoter, codes gene $B$</li>
| + | |
| − | <li><strong>$P_C$</strong> = relative strength of the promoter coding gene $C$
| + | |
| − | <li><strong>$Rbs$</strong> = relative strengths of ribosome binding sites</li>
| + | |
| − | <li><strong>$Deg$</strong> = degradation coefficient</li>
| + | |
| − | <li><strong>$C_{phos}$</strong> = phosphorylation coefficient</li>
| + | |
| − | <li><strong>$DP$</strong> = de-phosphorylation coefficient</li>
| + | |
| − | </ul>
| + | |
| − | </div>
| + | |
| | </div> | | </div> |
| − | <br><br>
| + | <img src="https://static.igem.org/mediawiki/2014/7/7e/Aalto_Helsinki_Logot_Oma.png" class="img-responsive center-block omalogot"> |
| − | <p> | + | |
| − | These equations describe the essential proteins our system ($YF1$, $FixJ$, Phosphorylated $YF1$, Phosphorylated $FixJ$, $CI$, $TetR$). Proteins are produced with rates that depend on the strength of respective promoter and ribosome binding site, and also when phosphorylated protein (denoted with $phos$) is dephosphorylated back to its original form. The concentration of all proteins reduces by degradation and its depends on the concentration of protein in question.
| + | |
| − | </p>
| + | |
| | | | |
| − | <h3>Rate Coefficients</h3>
| + | </article> |
| | + | <article class="abg-pcb"> |
| | | | |
| − | <p> | + | <h2>The Story of Aalto-Helsinki Bioworks</h2> |
| − | $P_1$, $P_2$, $P_A$ and $P_B$ denote the relative strengths of the promoters. $Rbs$s are the relative strengths of ribosome binding sites, which both affect the mRNA translation rate linearly. Each protein has its own degradation coefficient (denoted $Deg$). $I_B$ is the combined effect of blue light that affects the phosphorylation of $YF1$. The phosphorylation of $FixJ$ is assumed to depend on phosphorylation coefficient $C_{phos}$ and the concentration of phosphorylated $YF1$. The dephosphorylation here depends on the respective dephosphorylation coefficient $DP$(1&2 for $YF1$ and $FixJ$). Later on, we found out that non-phosphorylated YF1 acts as a phosphatase on FixJ. However, these effects are not taken into account in our model. | + | <div class="row"> |
| − | </p>
| + | <div class="col-md-6 text-col-left"> |
| − | | + | <p> |
| − | <h3 class="nopaddingbottom">Equations for Promoter Activities</h3>
| + | We are Aalto-Helsinki Bioworks, the first-ever Finnish iGEM Team and one of the four teams in the new Entrepreneurship Track. Our <a href="https://2014.igem.org/Team:Aalto-Helsinki/Team">team</a> consists of nine students from Aalto University and the University of Helsinki and we are combining our interdisciplinary forces to develop something new and fascinating. We want to put Finland on the map of synthetic biology and improve undergraduate research opportunities in our universities. |
| − | | + | </p> |
| − | <div class="row modelimg">
| + | <p> |
| − | <div class="img-center"> | + | We have <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research">designed</a> a three-channel gene switch that would make it possible to control three user-defined genes with blue light intensity. We are using <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research#yf1-title">YF1</a> as our light receptor protein and the signal is mediated to lambda repressor protein (CI) production via phosphorylation pathway. The concentration of the CI protein defines the gene that should be active at a time. The secret behind this function is our modified version of the <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research#lambda-title">lambda repressor</a> mechanism. |
| − | <img src="https://static.igem.org/mediawiki/2014/a/a0/Aalto_Helsinki_Promoters.png" class="img-responsive"></img> | + | </p> |
| | + | <p> |
| | + | We constructed a mathematical <a href="https://2014.igem.org/Team:Aalto-Helsinki/Modeling">model</a> that simulates the interactions of the molecules and function of the gene switch we designed. This revealed interesting phenomena in the dynamics of our system which helps us to better understand the capabilities and limitations of the gene switch. We also made an <a href="http://igem-qsf.github.io/SimCircus/WebUI/">interactive simulation</a> available to everybody to best illustrate how our idea actually works. |
| | + | </p> |
| | + | <p> |
| | + | To control the amount of blue light on our cell cultures, we created the <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research#ledrig-title">LED rig</a> device. This enabled us to perform diverse experiments in order to characterize our light response element. These <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research#Results">results</a> show that our light response element is able to regulate the downstream gene expression precisely. In addition, the response time is in a ten-minute-scale, which enables constant and nearly real-time control over bacterial cultures. In addition, we hypothesize that this system is also applicable to bioreactors, which would enable higher level of control in industrial bioprocesses. However, our fully functional prototype is still under ongoing development. |
| | + | </p> |
| | + | <p> |
| | + | We have developed an open approach to <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business">biotech business</a> inspired by the business models for open source software. Following the Open Source philosophy, we will distribute open Aalto-Helsinki Bioworks technologies for free to everybody - as long as they share the improvements made on the technology. Therefore, we empower our users to participate in product development. Our <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business#canvas-title">business model</a> is based on hardware and wide range of services offered to our customers. |
| | + | </p> |
| | + | <p> |
| | + | During the summer we participated in Aalto Entrepreneurship Society’s <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business#Sos">Summer of Startups 2014</a> incubator programme to learn the essential entrepreneurial skills, such as pitching, investor relations, customer-driven development and <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business#pitch-title">explaining</a> the science for general audience. See our Demo Day video for details. |
| | + | </p> |
| | + | <p> |
| | + | iGEM is an international experience and as the first Finnish team, we went to find advice and experience around the globe. We contributed to the iGEM community by building a <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation#Seekers">BioBrick Seeker</a> tool which makes it easy to find parts of your interest in the 2014 BioBrick distribution. This tool has been used by iGEM teams all over the world! We also did a lot of <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation#Interteam">cooperation</a>, including filling out surveys and having skype conversations and live meetings with current and previous iGEM teams from France, Colombia, Switzerland, USA and the Netherlands. We even made a <a href="http://www.youtube.com/embed/icPgP3OOVOQ?rel=0">video</a> together with ETH Zürich team to Colombia team’s challenge. |
| | + | </p> |
| | + | <p> |
| | + | We wanted to <a href="https://2014.igem.org/Team:Aalto-Helsinki/Outreach">raise awareness</a> about synthetic biology in Finland and also showcase researchers’ work to young people and undergraduate students. Therefore, we have been reaching out to general public, especially young people via <a href="https://2014.igem.org/Team:Aalto-Helsinki/Outreach#SoMe">social media</a>, including <a href="http://www.facebook.com/AaltoHelsinki">Facebook</a>, <a href="http://twitter.com/AaltoHelsinki">Twitter</a>, <a href="http://www.youtube.com/channel/UCEZliqjLu86CRpQlk57FfSw">Youtube</a>, <a href="http://www.flickr.com/photos/aaltohelsinki/">Flickr</a> and our own blog. We’ve shared stories, pictures, videos and experiences to our followers. In addition, we have been featured in radio interviews and articles on magazines and webzines. We also made a silly game: <a href="https://2014.igem.org/Team:Aalto-Helsinki/Flappycoli">Flappy Coli</a>. We have a public team webpage, <a href="http://2014.aaltohelsinki.com/">aaltohelsinki.com</a>, where you can find the latest stories of Aalto Helsinki also in the future. We lifted some of the highlights of this project on a <a href="https://2014.igem.org/Team:Aalto-Helsinki/Journal#Timeline">timeline</a>: the story of Aalto-Helsinki Bioworks is there for you to see! |
| | + | </p> |
| | + | </div> |
| | + | <div class="col-md-6 img-100"> |
| | + | <img src="https://static.igem.org/mediawiki/2014/a/a2/Aalto_Helsinki_Banner.png" class="img-responsive"> |
| | </div> | | </div> |
| | </div> | | </div> |
| | | | |
| − | <p class="modellatex">
| |
| − | \begin{eqnarray*}
| |
| − | & & P_2 = C_{P_2}N_1[CI] \\
| |
| − | \\
| |
| − | & & P_A =
| |
| − | \begin{cases}
| |
| − | C_{P_A}N_1[CI] \quad \text{if} \quad N_1[CI] \leq 1 \\
| |
| − | 0 \quad \text{if} \quad N_1[CI] > 1
| |
| − | \end{cases} \\
| |
| − | \\
| |
| − | & & P_B =
| |
| − | \begin{cases}
| |
| − | C_{P_B}N[CI] \quad \text{if} \quad N_1[CI] < 1 \\
| |
| − | C_{P_B}(1-(N_1[CI] - 1)) \quad \text{if} \quad 1 \leq N_1[CI] < 2 \\
| |
| − | 0 \quad \text{if} \quad N_1[CI] \geq 2
| |
| − | \end{cases} \\
| |
| − | \\
| |
| − | & & P_C =
| |
| − | \begin{cases}
| |
| − | C_{P_A}(1-N_2[TetR]) \quad \text{if} \quad N_2[TetR] \leq 1 \\
| |
| − | 0 \quad \text{if} \quad N_2[TetR] > 1
| |
| − | \end{cases}
| |
| − | \end{eqnarray*}
| |
| − | </p>
| |
| − | <h3 class="nopaddingtop">Promoter Coefficients</h3>
| |
| − |
| |
| − | <p>
| |
| − | Here the $C_{P_n}$s denote the respective promoter's maximum activity. The $N_1$ and $N_2$ in front of $CI$ and $TetR$ concentrations are normalization coefficients, which are needed to map the values of $[CI]$ to the interval $(0,3)$ and values of $[TetR]$ to the interval $(0,1)$. This way, when multiplied by the promoters' maximum activity values, we get values in the interval $(0, C_{P_n})$ The functions definitions must also change so that they never take negative values, which would make no sense when it refers to promoter activity. We have simplified the model so that the promoters’ activity only depend on $[CI]$ and $[FixJ]$.
| |
| − | </p>
| |
| | | | |
| | </article> | | </article> |
| − | <div class="update Math"></div>
| |
| − | <div class="update Simulation"></div>
| |
| | <article> | | <article> |
| − | <div class="link" id="Simulation"></div>
| |
| | | | |
| − | <h2>Simulation</h2> | + | <h2 class="kakspaddingbot">Accomplishments</h2> |
| | + | <ul> |
| | + | <li>Best undergraduate wiki 2014</li> |
| | + | <li>Poster</li> |
| | + | <li>Presentation at the Giant Jamboree in Boston</li> |
| | + | <li>Background research, design and the creation of a <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research">Three-Channel Gene Switch</a></li> |
| | + | <li>Submission of <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research#Parts">three new BioBricks and two new primers to the Registry</a></li> |
| | + | <li>Creation of <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business#Plan">an Open Source business model and a business plan</a> for Synthetic Biology Entrepreneurship</li> |
| | + | <li>Logo and brand design</li> |
| | + | <li><a href="http://youtu.be/tlc7MPY9SE8">Pitch</a> to an audience of 1000+ people</li> |
| | + | <li>Participation in the <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business#Sos">Summer of Startups</a>, a startup incubator program</li> |
| | + | <li>Connecting with <a href="https://2014.igem.org/Team:Aalto-Helsinki/Outreach">investors and general public</a></li> |
| | + | <li>Received 45 000€ in <a href="https://2014.igem.org/Team:Aalto-Helsinki/Team#Sponsors">funding</a></li> |
| | + | <li>Drawing attention <a href="https://2014.igem.org/Team:Aalto-Helsinki/Outreach#Media">in the media</a></li> |
| | + | <li>BioBrick and Team <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation#Seekers">Seekers</a></li> |
| | + | <li>Collaboration with other <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation#Interteam">iGEM teams</a></li> |
| | + | <li>Participation in the <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation#Interlab">Measurement Interlab Study</a></li> |
| | + | </ul> |
| | | | |
| − | <h3 class="kakspaddingtop">Overview </h3>
| + | </article> |
| | + | <article> |
| | | | |
| − | <p> | + | <h2>Categories</h2> |
| − | Based on our mathematical model, we created an interactive simulation and a graphical user interface for it. This visualization, although idealized, is suitable for demonstrating the intended functioning of our gene circuit and the gene switch system. We included two sliders, one for red and one for blue light. With these, the user can see the effect of the light intensity to the simulated bacterial culture in real time. Proteins $A$, $B$ and $C$ are represented by GFP, RFP and BFP (green, red and blue fluorescent protein) and therefore the bacteria change color when lights’ intensities are changed.
| + | |
| − | <p/>
| + | |
| − | | + | |
| − | <h3>Lights </h3>
| + | |
| | | | |
| | <p> | | <p> |
| − | In our system, the communication between user and the bacteria happens via illuminating the culture with blue and red light. Blue light phosphorylates the $YF1$-protein, which is the key to controlling the production of $A$, $B$ and $C$ proteins inside the bacteria. In the simulation, this is represented by change in the $I_B$ parameter from the mathematical model. This takes values between 0 and 1, and the rest of the system behaves as described previously. | + | Our wiki has seven different categories in addition to this main page. On each of them you can just scroll through the content until you're finished reading. Everything about the subject can be found on one page, additional material is provided when possible and pages discussing similar topics are linked to each other. A submenu will also appear when you start scrolling through the other pages: see the top of the page as you advance in the wiki! |
| | </p> | | </p> |
| − | <p> | + | <div class="row row-eq-height"> |
| − | Our original design also had a transcription intensity switch, controlled by red light. Due to time constrains, this wasn't yet implemented in our gene circuit. In the simulation, we added a second user controlled parameter in front of every promoter. This takes values between 0 and 1, representing the zero production state and the production at maximum promoter activity. With this, the user has control of all desired protein concentrations. The assumed mechanism is idealized and has a linear effect on the activity. | + | <div class="col-md-4 bg feat feat-left bg-team"> |
| − | </p>
| + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Team"> |
| − | | + | <div class="feattext-container-tall"> |
| − | <h3>Runge-Kutta Method </h3>
| + | <div class ="feattext-cell"> |
| − | | + | <p class="feattext-p"> |
| − | <p>
| + | <big><big><big>Team</big></big></big><br> |
| − | The dynamics of our system were approximated and computed using 4th order Runge-Kutta method (RK4) for the differential equations in our mathematical model. The point of this method is to approximate the function in question by it's derivatives without having to solve the function itself. The starting values of each concentration are assumed to be zero, so $y(0) = 0$. The simulation computes the next datapoint adding the derivative times a timestep $h$ to previous concentrations. The method uses a mean value of different derivatives (the different k's below) during timestep $h$ to get a more accurate approximation. | + | We are a team of nine Finnish students and we've gotten amazing support during this project. |
| − | </p>
| + | </p> |
| − | | + | </div> |
| − | <div class="row modelimg"> | + | </div> |
| − | <div class="img-center"> | + | </a> |
| − | <img src="https://static.igem.org/mediawiki/2014/6/63/Aalto_Helsinki_IGEM_rungekutta.png" class="img-responsive"></img> | + | </div> |
| | + | <div class="col-md-4 bg feat feat-center bg-business"> |
| | + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Business"> |
| | + | <div class="feattext-container-tall"> |
| | + | <div class ="feattext-cell"> |
| | + | <p class="feattext-p"> |
| | + | <big><big><big>Business</big></big></big><br> |
| | + | We explored the possibilities of biotech and synthetic biology business. |
| | + | </p> |
| | + | </div> |
| | + | </div> |
| | + | </a> |
| | + | </div> |
| | + | <div class="col-md-4 bg feat feat-right bg-research"> |
| | + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Research"> |
| | + | <div class="feattext-container-tall"> |
| | + | <div class ="feattext-cell"> |
| | + | <p class="feattext-p"> |
| | + | <big><big><big>Research</big></big></big><br> |
| | + | We engineered a three-channel switch that can be controlled with the intensity of blue light. |
| | + | </p> |
| | + | </div> |
| | + | </div> |
| | + | </a> |
| | </div> | | </div> |
| | </div> | | </div> |
| | | | |
| − | <p class="modellatex"> | + | <div class="row row-eq-height"> |
| − | \begin{eqnarray*} | + | <div class="col-md-6 bg feat feat-left bg-modeling"> |
| − | & & y' = f(t,y(t)), \quad y(t_0) = y_0 \\
| + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Modeling"> |
| − | \\
| + | <div class="feattext-container-tall"> |
| − | \\
| + | <div class ="feattext-cell"> |
| − | & & y_{n+1} = y_n + \frac{h}{6}(k_1 + 2k_2 + 2k_3 + k_4) \\
| + | <p class="feattext-p"> |
| − | & & t_{n+1} = t_n + h
| + | <big><big><big>Modeling</big></big></big><br> |
| − | \\
| + | We made mathematic models of the interactions behind our gene switch. |
| − | \\
| + | </p> |
| − | & & k_1 = f(t_n,y_n) \\
| + | </div> |
| − | & & k_2 = f(t_n +\frac{h}{2}, y_n + \frac{h}{2}k_1) \\
| + | </div> |
| − | & & k_3 = f(t_n + \frac{h}{2}, y_n + \frac{h}{2}k_2) \\
| + | </a> |
| − | & & k_4 = f(t_n + \frac{h}{2}, y_n +hk_3)
| + | </div> |
| − | \end{eqnarray*}
| + | <div class="col-md-6 bg feat feat-right bg-cooperation"> |
| − | </p>
| + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Cooperation"> |
| − | | + | <div class="feattext-container-tall"> |
| − | <h3 class="nopaddingtop">Software Implementation</h3>
| + | <div class ="feattext-cell"> |
| − | | + | <p class="feattext-p"> |
| − | <p>
| + | <big><big><big>Cooperation</big></big></big><br> |
| − | A computational model was created based on our mathematical model and the RK4 approximation. We made a real-time visualisation script to illustrate the dynamics in a simple and clear graphic UI. We added two light switches so that the user can have an impact on our simulation in real time. This all was then further developed into a presentable, user-friendly form that is accessible from our website. The simulation itself was created using Python and translated into Javascript for web implementation.
| + | We got to know other iGEM teams and developed tools for everyone to use. |
| − | </p>
| + | </p> |
| − | | + | </div> |
| − | | + | </div> |
| − | <div class="img-center"> | + | </a> |
| − | <a href="http://igem-qsf.github.io/SimCircus/WebUI/" target="_blank"><img src="https://static.igem.org/mediawiki/2014/0/03/Aalto_Helsinki_Simulation.png" class="img-responsive"></a> | + | |
| − | | + | |
| − | Here is a screenshot of the simulation. You can adjust the amount of the red and blue light and see how it affects the bacteria. You can also see how active each gene (A, B, C) is. | + | |
| − | </p> | + | |
| | </div> | | </div> |
| | </div> | | </div> |
| − | | + | <div class="row row-eq-height"> |
| − | | + | <div class="col-md-6 bg feat feat-left bg-outreach"> |
| − | <p> | + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/ Outreach"> |
| − | To demonstrate our work for the general public in an event, <a href="https://2014.igem.org/Team:Aalto-Helsinki/ Business#Sos"> Summer of Startups Demo Day< /a> , we used the < a href=" http://igem- qsf.github.io/ SimCircus/ WebUI/"> simulation</ a> to show our system in action. It can be accessed with a web browser and shows an animated bacterial plate with adjustable light intensity sliders to remotely control the bacteria. The proteins the bacteria produce in this simulation are colors, so you can see how the changes in light intensity correlate to the color of the colonies on the plate. The simulation also has a nice graph that shows the protein levels in real time so you can see more clearly what's going on in the cell. | + | <div class="feattext-container-tall"> |
| − | </p>
| + | <div class ="feattext-cell"> |
| − | | + | <p class="feattext-p"> |
| − | <p>
| + | <big><big><big>Outreach</big></big></big><br> |
| − | All the code (including the Python simulation with more detailed graphs) is available at the project's <a href="http://github.com/iGEM-QSF/SimCircus">GitHub page.</a>
| + | We spread the word about iGEM and synthetic biology especially in Finland. |
| − | </p>
| + | </p> |
| − | </article>
| + | </div> |
| − | | + | </div> |
| − | <div class="update Simulation"></div> | + | </a> |
| − | <div class="update Discussion"></div> | + | </div> |
| − | | + | <div class=" col-md-6 bg feat feat-right bg-journal"> |
| − | <article>
| + | <a href="https://2014.igem.org/Team:Aalto-Helsinki/Journal"> |
| − | <div class=" link" id=" Discussion"></ div> | + | <div class=" feattext-container-tall"> |
| − | | + | <div class =" feattext-cell" > |
| − | <h2 class="ykspaddingbottom">Discussion</h2>
| + | <p class="feattext-p"> |
| − | | + | <big><big><big>Journal</big></big></big><br> |
| − | <p>
| + | We documented the project well. |
| − | Our model doesn’t take any noise into consideration. Therefore all interactions produce smooth, good-looking curves. On the other hand, the clear graphics generated by the simulation are easily interpretable, so even someone not familiar with science can clearly see what's going on in our system.
| + | </p> |
| − | </p>
| + | </div> |
| − | | + | </div> |
| − | <p>
| + | </a> |
| − | So far we have also used arbitrary parameters, simplified reaction pathways and reaction equations. The parameters were acquired by estimation and empirical testing. Full experimental data wasn't available when the simulation was created, so derivation of differential equations by using the law of mass-action was not possible. All reaction mechanisms are our own estimations of what's going on inside the bacteria and the system.
| + | </div> |
| − | </p>
| + | </div> |
| − | | + | <div class="cpright"> |
| − | <p>
| + | <p class ="kuvateksti"> |
| − | Some unexpected observations were made after running the simulation several times. We noticed that when activating all the promoters while the $CI$ concentration was zero, both proteins $A$ and $C$ were produced simultaneously instead of just the anticipated $A$. When $TetR$ is further produced by the activation of $P_R$ promoter, $C$ production is repressed and the concentration drops back to zero. Secondly, when blue light intensity is set to a level that corresponds to the maximum concentration of either $A$ or $B$, the promoter activity adjustable using the red light and it should only affect the said concentration. Again, when lowering the activity enough, we noticed that a spike in production of protein $C$ appeared again. This seemed to be caused by the lowered concentration of $TetR$ that allowed a leak in $P_C$ promoter. We had no idea that a $C$ spike would appear based on the theoretical model of our gene circuit, so this phenomenon was discovered early thanks to our simulation. | + | <a href="http://i- see-faces. deviantart. com/">Photos © Tanja Maria</a> |
| − | </p> | + | </p> |
| − | | + | </div> |
| − | <p> | + | |
| − | We also noticed that going from directly producing the protein $A$ to protein $C$, or reversely, from $C$ to $A$ is virtually impossible without producing some protein $B$ along the way. We thus concluded that our Gene Switch is not entirely orthogonal between the three channels. The possible interactions with other products with protein $B$ are needed to be taken under consideration when designing applications that only use genes $A$ and $C$. | + | |
| − | </p>
| + | |
| − | | + | |
| − | <p>
| + | |
| − | Upon later research, we found out the actual mechanism with which $FixJ$ was phosphorylated. In contrast to our model, the phosphate is actually transmitted from $YF1$ to $FixJ$. In their paper, Möglich et al. (2009, reference in research section) showed that in a two-step reaction, $FixL$ first undergoes autophosphorylation and then transfers the phosphate to its cognate, noncovalently bound, response regulator $FixJ$. The $YF1$ protein is a derivative of $FixL$ with different sensory domain, so it behaves the same way in this reaction. This wasn't however implemented in our model.
| + | |
| − | </p>
| + | |
| − | | + | |
| | <p> | | <p> |
| − | In it's current state the simulation gives a good idea on how the system should work. Making it realistic and accurate requires measuring the appropriate parameters, research on appropriate scientific publications, and tuning. Still, this version is ideal for demonstration of our idea, bringing the visual UI a significant marketing value. | + | If you find yourself lost (or simply don't know where to start looking for what you'd want to find), <a href="https://static.igem.org/mediawiki/2014/7/73/Aalto_Helsinki_Wiki_Sitemap.png" target="_blank">here's a sitemap to help with the task</a>! |
| | </p> | | </p> |
| | | | |
| | </article> | | </article> |
| − | <div class="update Simulation"></div>
| |
| | </div> | | </div> |
| | </body> | | </body> |
