Difference between revisions of "Team:IIT Delhi/Photobleaching"

 
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             <h2 class="h2font">Deterministic Model</h2>
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             <h2 class="h2font">Photobleaching</h2>
  
 
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  </p>
 
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<h2 id="pfont" style = "text-align : left; ">
 
<h2 id="pfont" style = "text-align : left; ">
<left>The biological networks are highly nonlinear and exhibit interesting phenotypical behaviour for certain operating conditions. One of such behaviour is the limit cycle in the
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<left><u id="pfont">Characterization of Rate of Photobleaching of Wild Type GFP (BBa_E0040)</u><br><br>
 
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mathematical sense, which shows a sustained oscillations of protein levels in the cell. It
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is quite interesting as well important to look for topologies which can produce such oscillations for different amplitude, oscillation and shape. Here, we have used a theoretical framework to begin with, for identifying topology based on following theorem.<br/><br>
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Theorem:1 (Hasting et. al.) Consider a system  ̇x = f(x), which is of ring in nature, and f is a monotone
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function and in the form<br/><br>
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<img src = "https://static.igem.org/mediawiki/2017/a/ad/T--IIT_Delhi--Deterform_1.jpg" style='border:3px solid #000000' width = "95%"><br><br>
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Then, if the Jacobian of f and x has no repeated eigenvalues and has any eigenvalue
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Photobleaching is the phenomenon of irreversible damage to the fluorophore, such that after certain number of electronic transitions on absorption of photons, it cannot fluoresce anymore. This hinders the ability to continuously image a sample over a long period of time, thus acting as a bottleneck to the characterization pipeline. Therefore, it is of paramount importance to understand and characterize the bleaching effect so that an optimum time gap between successive images could be chosen. This would ensure that the fluorophores do not bleach and at the same time we don’t have to compromise on the amount of collected data due to the time gap.<br/><br>
with positive real parts, then the system must have a consistent periodic orbit.<br/><br>
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To design a squarewave oscillator, we used the theorem to idenify the biological system
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which can satisfy such condition. One of classical example is Repressillator (Elowitz et
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al) or 5n1 ring oscillator (Murray et al). This kind of oscillator is based on negative
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feedback with delay and able to produce stable limit cycle computationally and as well as
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experimentally. However, these oscillators are more of a phaselag oscillator matching the
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sinusoidal umbrella behavior. As philosophy behind our work is to design
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square wave, we exploit the system parameters to produce relaxation oscillations. The
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relaxation oscillator typically works on the principle of level of concentration, where once
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the level is reached it relaxes there for some additional time and falls back to another
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level and resides there for some till it jumps back (slowly). The time evolution of such
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trajectories portray a square wave-ish in state-space.<br/><br>
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The dynamical model of the five node oscillator can be written as;<br/><br>
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Here, we characterized the photobleaching effect in wildtype GFP (E0040), which was the reporter in our oscillator using fluorescent microscopy with the etaluma Lumascope 500 microscope. Cells expressing GFP under the PhlF repressible promoter (BBa_K2525016) in the absence of PhlF, so that it constitutively expressed GFP. Cells were loaded in microfluidic chambers and droplet encapsulation was performed to capture a small number of cells. This droplet was continuously exposed to light corresponding to the excitation wavelength of GFP (~485 nm) and the emission was captured continuously as well. ImageJ was used to analyze the images, to obtain the rate of photobleaching as shown in Fig 1. Where we have fitted an exponential curve to the total intensity over time. It is known that photobleaching has a first order decay. We obtain a photobleaching rate of 0.002 per second (7.2 per hour).<br><br>
<img src = "https://static.igem.org/mediawiki/2017/3/38/T--IIT_Delhi--Deterform_2.jpg" style='border:3px solid #000000' width = "80%"><br><br>
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where i ∈ [0 = 5, 1, 2, 3, 4, 5], xmi is the mRNA concentration level, xpi is the protein
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<img src = "https://static.igem.org/mediawiki/2017/c/c6/T--IIT_Delhi--Results_Photobleach.png" style='border:3px solid #000000' width = "95%"><br><br>
transcription level, βm0 is the leaky expression, βmi is the production rate of mRNA, βpi
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is the production rate of protein, γmi is the degradation/dilution of mRNA and γpi is
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the degradation/dilution of protein for ith protein. The simulation results of the model
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presented in Fig. below. It is evident the such system can exhibit a oscillation resembling a
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squarewave.<br/><br>
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<img src = "https://static.igem.org/mediawiki/2017/5/5b/T--IIT_Delhi--Fig_2_.jpg" style='border:3px solid #000000' width = "90%"><br><br>
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As the dynamical model comprises of two time-scale, one can use the singular perturbation analysis to reduce the model in to smaller one, i.e. 5th order, as discussed earlier.
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Total Intensity in the encapsulated droplet over time. Since photobleaching is known to be a first order process, we have fitted an exponential curve to the data. The high R-squared value implies a good fit of the exponential model to the data. The rate of photobleaching turns out to be 0.002 per second (7.2 per hour)<br/><br>
  
The simpler version of the model, where multiple constants product are clubbed into one,
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A timelapse gif of the image is as shown below. Photobleaching over time can be clearly seen as time progresses (notice the time stamp). <br/><br>
can be reproduced as follows,<br><br>
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<center><img src = "https://static.igem.org/mediawiki/2017/0/00/T--IIT_Delhi--Results_Photobleach_GIF.gif" style='border:3px solid #000000' width = "80%" ></center><br><br>
<img src = "https://static.igem.org/mediawiki/2017/d/df/T--IIT_Delhi--Deterform_3.jpg" style='border:3px solid #000000' width = "70%"><br><br>
+
  
where αi can be considered as the protein production rate constant and γ as the degra-
 
dation constant. The simulation of 5th order comes model presented in FigX is almost
 
  
identical to the simulation for full order model. Both of the model can exhibit sustained
 
square wave like response of arbitrary initial conditions.<br/></left><br>
 
  
<img src = "https://static.igem.org/mediawiki/2017/a/af/T--IIT_Delhi--Fig_1_.jpg" style='border:3px solid #000000' width = "90%"><br><br>
 
  
 
</h2>
 
</h2>

Latest revision as of 22:18, 1 November 2017

iGEM IIT Delhi


Photobleaching

                                                                                                                                                                                                                 

Characterization of Rate of Photobleaching of Wild Type GFP (BBa_E0040)

Photobleaching is the phenomenon of irreversible damage to the fluorophore, such that after certain number of electronic transitions on absorption of photons, it cannot fluoresce anymore. This hinders the ability to continuously image a sample over a long period of time, thus acting as a bottleneck to the characterization pipeline. Therefore, it is of paramount importance to understand and characterize the bleaching effect so that an optimum time gap between successive images could be chosen. This would ensure that the fluorophores do not bleach and at the same time we don’t have to compromise on the amount of collected data due to the time gap.

Here, we characterized the photobleaching effect in wildtype GFP (E0040), which was the reporter in our oscillator using fluorescent microscopy with the etaluma Lumascope 500 microscope. Cells expressing GFP under the PhlF repressible promoter (BBa_K2525016) in the absence of PhlF, so that it constitutively expressed GFP. Cells were loaded in microfluidic chambers and droplet encapsulation was performed to capture a small number of cells. This droplet was continuously exposed to light corresponding to the excitation wavelength of GFP (~485 nm) and the emission was captured continuously as well. ImageJ was used to analyze the images, to obtain the rate of photobleaching as shown in Fig 1. Where we have fitted an exponential curve to the total intensity over time. It is known that photobleaching has a first order decay. We obtain a photobleaching rate of 0.002 per second (7.2 per hour).



Total Intensity in the encapsulated droplet over time. Since photobleaching is known to be a first order process, we have fitted an exponential curve to the data. The high R-squared value implies a good fit of the exponential model to the data. The rate of photobleaching turns out to be 0.002 per second (7.2 per hour)

A timelapse gif of the image is as shown below. Photobleaching over time can be clearly seen as time progresses (notice the time stamp).






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