Team:BostonU/Model

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MODELING

Initially, there was not a defined relationship between the concentration of DNA added to the cell-free batches we made and protein expression. The maximum amount of DNA that our in-house cell free can handle was also undefined. Part of this is due to the variety in capabilities of a particular ‘batch’ of cell-free, even if the same protocol is used. Modeling this relationship allows us to maximize expression when performing experiments that use many different pieces of interacting DNA; such as in later tests where a plasmid containing a toehold switch driving a recombinase interacts with a reporter plasmid.

 

We collected data on the fluorescence from a plasmid containing constitutive deGFP. The plasmid was added to the cell free reaction at 10 nM, 20 nM, 30 nM, and 40 nM. There was also a reaction with no DNA. The resulting data can be seen in Figure 1.

 

Figure 1.This figure shows fluorescence from constitutive deGFP plasmids at 10 nM, 20 nM, 30 nM, and 40 nM concentrations as well as a reaction containing no DNA.

 

Initially we planned on modeling this capacity with a single logistic curve. The results of this initial model are shown in figure 2.

 

Figure 2.Model of cell free saturation from Figure 1 data based off of a single logistic curve.

After looking at the data more closely, we determined that a more complex curve was required and fit a bell shaped dose response curve. A bell shaped dose response curve is the sum of two dose response curves. Here, low concentrations of DNA stimulate gene expression while high concentrations inhibit gene expression.

 

Figure 3.Adapted model of cell free saturation from Figure 1 data using a double dosage response curve.

 

 

From this information, we see that the maximal levels of expression are achieved around 20 nM concentrations of DNA. In the future, when possible we aim to achieve the highest levels of expression by adding no more than 20 nM concentrations of total DNA in the system. For example, when testing plasmid toehold deGFP expression in response to a plasmid trigger, we had to ensure that we did not oversaturate our cell free system. We tuned the concentrations and volumes of these plasmids added in response to the results from this model.

 

We believe that the activity shown by our model may be a result of molecular activity of the cell-free machinery. This has been dubbed 'burn-out' by some researchers and it is when the amount of DNA that is added to a cell-free system is so great that it overwhelms one or more key proteins within the transcription translation pathway. There is not currently any available literature on this subject, but as the use of bacterial cell-free systems becomes more common we expected this issue to be studied in further depth.