Team:UIUC Illinois/Software/Evolvalvability

From 2014.igem.org

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<h2> Having trouble with finding the best enzymes for your cut sites? </h2>
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<h2> Do you fear that your plasmid will be lost by mutation? </h2>
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   <h2>Here is our <font color= "red">cutsultant</font> software that will potentially suggest you the optimal enzyme! </h2>
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   <h2>Here is our <font color= "red">EvoTracer</font> software that will predict mutational tolerance of plasmid </h2>
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<h2> in K12 E.Coli strain!! </h2>
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<p><b>Description:</b>
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<p><b><p style="font-size:15px">Description:</p></b></p>
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Currently there are few websites that give you only cut sites, however we heard that many synthetic biologists struggle with obtaining optimized enzymes
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<p><p style="font-size:15px">The basis is how evolution depends on both mutational rate on a single organism and the selection of organisms within a group in terms of who receives certain mutations. There are many steps that must be accounted in order to proximate more accurately. This is why we must be modular in our approach. As a preliminary step, and due to the specificity of the data we will be using, we specifically choose a common strain of E. coli which is K12.</p>
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Cutsultant is a python script created to expedite the process of finding restriction enzymes that produce the most optimal digestions. Using Biopython's restriction enzyme package, as well as user-inputted sequences and available restriction enzymes Cutsultant can use one or two sequences (typically a plasmid and/or a plasmid with an insert) and generate lists of enzymes that produce an optimal cut based on a a few parameters, such as number of cuts, minimum band length, maximum band length, and differentiability of bands. </p>
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<p><b><p style="font-size:15px">Overall Plan:</p></b></p>
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<p><p style="font-size:15px">The first thing that must be done is to account for the probability of mutational change on one organism.</p>
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<br>
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<p><b><p style="font-size:15px">1. Single base pair mutation:</p></b></p>
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<p><p style="font-size:15px">Find polymerase error rate for our organisms. (1/6000 per generation) Using the length of nucelotide sequence, we can find
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the probability of a nucleotide experiencing an error.</p> 
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<p><p style="font-size:15px">Pr(Mutation at Nucleotide at location N) = f(error rate and size)</p></p>
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<br>
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<p><b><p style="font-size:15px">2. Rate of experiencing error of single base:</p></b></p>
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<p><p style="font-size:15px">Find the transition & transversion matrix parameter for K12 strain.</p></p>
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<p><b><p style="font-size:15px">3. The probability that, if the single base experiences an error and if the error causes it to change into a different base, the change will cause another change in amino acid expression</p></b></p>
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  <p><b><p style="font-size:15px">Additional Constraints</p></b></p>
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<p style="font-size:15px">Synthetic biology devices commonly impose a burden on their host organisms that is at odds with their long-term survival.<br>
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Metabolic toll of constructing additional RNAs and proteins.<br>
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Heterologous genetic parts that interfere with the efficient operation of native cellular processes.<br>
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<br>
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Genetic reliability is defined in terms of an evolutionary half-life : the number of cell doublings over which 50% of the total function of an engineered device persists in a cell population.<br>
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<br>
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Mutations usually cause the evolutionary meltdown of circuits with 3-6 days.<br>
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<br>
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Slowing down evolution:<br>
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Choose DNA sequences that are less prone to mutations.<br>
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Manipulate the organisms copying and repair mechanisms.</p><br>
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<p style="font-size:15px">Overlap the sequence encoding genetic parts with information for some activity that is required for cell survival, so that some mutations are no longer favored by selection<br>
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<br>
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Eliminate unnecessary components from the organisms genome or utilize an orthogonal gene expression or signaling system (with the goal of reducing genetic and metabolic cost)</p><br>
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Latest revision as of 03:49, 18 October 2014


Do you fear that your plasmid will be lost by mutation?

Here is our EvoTracer software that will predict mutational tolerance of plasmid

in K12 E.Coli strain!!

Description:

The basis is how evolution depends on both mutational rate on a single organism and the selection of organisms within a group in terms of who receives certain mutations. There are many steps that must be accounted in order to proximate more accurately. This is why we must be modular in our approach. As a preliminary step, and due to the specificity of the data we will be using, we specifically choose a common strain of E. coli which is K12.

Overall Plan:

The first thing that must be done is to account for the probability of mutational change on one organism.


1. Single base pair mutation:

Find polymerase error rate for our organisms. (1/6000 per generation) Using the length of nucelotide sequence, we can find the probability of a nucleotide experiencing an error.

Pr(Mutation at Nucleotide at location N) = f(error rate and size)


2. Rate of experiencing error of single base:

Find the transition & transversion matrix parameter for K12 strain.


3. The probability that, if the single base experiences an error and if the error causes it to change into a different base, the change will cause another change in amino acid expression

Additional Constraints

Synthetic biology devices commonly impose a burden on their host organisms that is at odds with their long-term survival.

Metabolic toll of constructing additional RNAs and proteins.

Heterologous genetic parts that interfere with the efficient operation of native cellular processes.

Genetic reliability is defined in terms of an evolutionary half-life : the number of cell doublings over which 50% of the total function of an engineered device persists in a cell population.

Mutations usually cause the evolutionary meltdown of circuits with 3-6 days.

Slowing down evolution:
Choose DNA sequences that are less prone to mutations.
Manipulate the organisms copying and repair mechanisms.


Overlap the sequence encoding genetic parts with information for some activity that is required for cell survival, so that some mutations are no longer favored by selection

Eliminate unnecessary components from the organisms genome or utilize an orthogonal gene expression or signaling system (with the goal of reducing genetic and metabolic cost)



The Institute for Genomic Biology
Biosystems Design, South wing, 2nd floor
University of Illinois at Urbana-Champaign
1206 West Gregory Drive
61801 Urbana, Illinois
illinoisigem@gmail.com
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