BME494s2013 Project Team1: Difference between revisions
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We used a model of the natural Lac operon to understand how changing the parameter values changes the behavior of the system. By changing the initial concentration of input (IPTG in this case), we were able to estimate the threshold that produces an "on" state in the system. | We used a model of the natural Lac operon to understand how changing the parameter values changes the behavior of the system. By changing the initial concentration of input (IPTG in this case), we were able to estimate the threshold that produces an "on" state in the system. | ||
Initially, the code had the concentration at 0.32 which is seen in the β-galactoside (Bgal concentration) vs. time plot (Figure 1). This value was changed again to 0.25 in determining the threshold that produces this "on" state (Figure 2). After proceeding to go up and down with these a values, a threshold was indeed found where the concentration of IPTG is about 0.064 (Figure 3). | Initially, the code had the concentration at 0.32 which is seen in the β-galactoside (Bgal concentration) vs. time plot (Figure 1). This value was changed again to 0.25 in determining the threshold that produces this "on" state (Figure 2). After proceeding to go up and down with these a values, a threshold was indeed found where the output concentration of IPTG was sustained and is about 0.064 (Figure 3). | ||
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Because the rate at which β-galactosidase is being produced must interact with the degradation rate of β-galactosidase, the production starts to cap off at around time = 100 with an approaching βgal concentration of about 4.52 x 10<sup>-4</sup> as seen in the original model. As the initial concentration of IPTG goes down (say 0.25), this time goes down to about 80 with the output decreasing (3.08 x 10<sup>-4</sup>) as the input decreases. Even at this point however, the output of IPTG is still not quite sustained although a pattern is evident. As soon as the concentration gets down to around 0.064, visible equilibrium is seen between production and degradation at a concentration of about 2.56 x 10<sup>-5</sup> and thus a threshold is found. | |||
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This model assumes that IPTG stays constant over time although realistically IPTG would of course fluctuate or run out as time would go on. Some more terms/variables are taken into account as well: | |||
{| border="1" class="wikitable" | |||
|+ '''Terms We were Concerned with when Considered in Matlab Model''' | |||
! Variable | |||
! Description | |||
|- | |||
! μ | |||
| Dilution of input IPTG or [IPTG]/cell volume, with IPTG diffusion | |||
|- | |||
! γ<sub>β</sub> | |||
| Degradation of βgal protein (the β-galactosidase) concentration that is being produced | |||
|- | |||
! α<sub>M</sub> | |||
| Production rate that M (the mRNA) is being transcribed | |||
|- | |||
! α<sub>β</sub> | |||
| Production rate that βgal (the β-galactosidase) is being translated | |||
|- | |||
! cell (= 1) | |||
| Bacterial cell volume of 1 | |||
|} | |||
<!-- Continue this paragraph by explaining how you interacted with the MatLab model. Include two or more images showing different output curves that were generated when you altered the IPTG concentration --> | <!-- Continue this paragraph by explaining how you interacted with the MatLab model. Include two or more images showing different output curves that were generated when you altered the IPTG concentration --> |
Revision as of 16:40, 28 April 2013
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Overview & PurposeSarah
Background
"Only LacZ and LacY appear to be necessary for lactose catabolism" [3].
Design: Our genetic circuitJulia Our gene switchParts<tab>pSB1A3-1 is a high copy number plasmid. The replication origin is a pUC19-derived pMB1 (copy number of 100-300 per cell). The terminators bracketing pSB1A3 MCS are designed to prevent transcription from inside the MCS from reading out into the vector.
Building: Assembly schemeThe assembly strategy employed in the design of this device is a Type IIS assembly strategy. The steps and procedures involved in this single-pot assembly are described below. MutagenesisOne of the parts chosen by our group contains a BsmBI cut site, which would disrupt the digestion and ligation process further along the assembly strategy. In order to counteract this, the part is subjected to mutagenesis to alter a selected base pair within the DNA to eliminate the BsmBI cut site while keeping the integrity of the coding sequence intact. This site-directed base substitution is performed using two primers with centrally located substitution sites to alter the selected base pair on a methylated plasmid. After the part has completed the mutagenesis, the DNA sequence (which is linear at this point in time) undergoes in vitro recombination reaction. The host cell then "circularizes" the mutated part DNA and digests the original methylated plasmid. If the methylation of the original plasmid is skipped, an additional purification step would be necessary to extract the mutated plasmid.[5]
PCRPCR, or polymerase chain reaction, is then used to amplify the DNA sequences and create modular fragments for ease of assembly. A DNA fragment is combined with its forward and reverse primers, nucleotides, and DNA polymerase. This mixture is then inserted into a thermal cycler, which cycles the internal temperature with predetermined values. These changes in temperature cause the DNA to separate, the primers to pair with their respective DNA strands, the DNA polymerase to activate, and a new DNA strand to be formed. The thermal cycling procedure, listed below, is continued until the specified fragment is amplified sufficiently for use. Thermal Cycling
Digestion and ligation reactionThe Type IIS assembly strategy employs a single-pot assembly, wherein digestion and ligation occur in tandem. To prevent the futile digestion/ligation loop that could result from this assembly strategy, the BsmBI restriction enzyme is used. BsmBI is useful in this scenario because its binding site is remote from its cutting site. In the digestion and ligation reaction, BsmBI binds to its binding site, CGTCTC, and cuts at a location further along the DNA strand. This creates a 4 base pair "sticky overhang." Complementary "sticky overhangs" then pair up and are connected by the ligase. The thermal cycling procedure used in the digestion and ligation reaction is shown below. Thermal Cycling
Parts and primersThe following table lists the BioBricks used in the construction of the Sweet Cyan device. The individual parts can be found with a simple search of the part IDs at the Parts Registry.
Testing: Modeling and GFP imaging
A lac switch modelWe used a previously published synthetic switch, developed by Ceroni et al.[6], to understand how our system could potentially be modeled and simulated. The graphic to the left depicts the relationships between the parameters of the lac operon switch described by Ceroni using a network diagram illustration. The parameters shown in the illustration relate to cell processes and could be used in forming a cohesive mathematical model of the cell's operation. In order to approximate the behavior of this set-up, a mathematical model can be developed based upon the relationships between the processes found in the cell. These relationships can be expressed in mathematical terms using numbers that relate to the system, including creation or decay rates, concentrations, or various constants. The actual values for these parameters can be sourced from experimentation, literature, or a predefined steady-state. If a model is well-defined and the necessary parameters known, a person may use the model to ascertain the state of a cell at a given point in time. For example, if an experimenter wanted to know the decay of the GFP protein molecules at a given point in time in a single cell, the following equation could be written using the notation found in the table below. Decay = G × λG/L The formula takes the concentration of the GFP protein in molecules per cell ("G") and multiplies it by the protein degradation rate in minutes-1 ("λG/L"). This results in a decay value for GPF in molecules per minute per cell. The Ceroni et al. model and the network diagram illustration use the table of variables and parameters seen below in their representation of the lac switch. The variables related to a particular cell process are located near to that process in the network diagram illustration.
An interactive modelWe used a model of the natural Lac operon to understand how changing the parameter values changes the behavior of the system. By changing the initial concentration of input (IPTG in this case), we were able to estimate the threshold that produces an "on" state in the system. Initially, the code had the concentration at 0.32 which is seen in the β-galactoside (Bgal concentration) vs. time plot (Figure 1). This value was changed again to 0.25 in determining the threshold that produces this "on" state (Figure 2). After proceeding to go up and down with these a values, a threshold was indeed found where the output concentration of IPTG was sustained and is about 0.064 (Figure 3).
Collecting imperical values to improve the modelSarah
Stakeholder Assessment
SUPPORTS & UNDERSTANDS Public and laymen knowledge of E. coli may consist of only what they hear in the news, which often relates to food contamination scares; for this reason, stakeholders of the device itself may not support its production if they believe that widespread stigma may prevent successful marketing and sales campaigns.
Our Team
Works Cited |