Difference between revisions of "Team:BostonU/Design"

To obtain our system of well characterized mammalian digital and analog promoters, we divided our work space into three technical aims:

To complete these goals we made use of the three class of plasmids: a constitutive guide RNA expressing vector driven by a, a guide RNA operator reporter vector driven by a minimal CMV, and a constitutive dCas9-VPR complex. dCas9, like its sister system Cas9, works by using CRISPR’s targeting system and a guide RNA to find specific section of the genome. Where they differ is in how the proteins interact with the genome. While Cas9 has a nuclease that can cleave the DNA, dCas9’s nuclease was catalytically inhibited. This results in a protein that can be localized to a region of DNA but cannot interact with it. When fused, however, to the VPR, a strong activating complexation of transcription regulators, the dCas9 becomes an activating complex that can drive the production of a gene.

In our work, those genes of interest were fluorescent proteins. The benefit of using fluorescent proteins is that they are easily assayable. The two assaying techniques used throughout are research were flow cytometry and fluorescent microscopy (the latter courtesy of Worcester Polytechnic Institute’s iGEM Team). In both cases, however, the process to assay began the same. Plasmids were transiently transfected into HEK293FT cells from E.coli.

We began our work by developing the digital promoter library. Before moving into experimentation, we made several design constraints. The first being that our system had to be orthogonal to the human genome. The motivation behind this was two-fold. Primarily, it stems from our testing in human cells and the need for true cellular response. The second, however, is more far removed from the competition. We as a lab feel our work could have long reaching effects in therapeutics and immunotherapy, and thus we want to begin optimizing our system with that in mind.

Once we have determined our system is orthogonal to the human genome, we needed to ascertain if our system had clear activated and basal state changes when dCas9-VPR is added. This behavior needed to maintained over multiple genes interest. Finally, our system need mutual orthogonality. Because ultimately we intend to transfect gene circuits and operators into a single cell, we must be sure that there will be no cross talk between state outputs of the circuits.

After establishing the digital library, we moved to expand into our full analog library. We did this using two main hypotheses: the multimerization of binding sites would increase expression and the mutation of binding sites would decrease expression. In the case of the former, the multimerization would recruit a greater number of dCas9-VPR’s upstream of the minimal promoter. In the case of the former, mutations should decrease the binding affinity of the dCas9-VPR. In addition to those parameters, we also increased the distance between binding sites on the multimerized plasmids in another attempt to increase expression. Once the library was expanded out into the analog domain, we begun integrating our library into genetic logic circuits. The motivation behind doing this was is once again two fold (catching a theme here… wink… wink...Gemini). First, genetic circuits represent one of synthetic biology’s most powerful tools. Circuits have become integral in our search for better immunotherapy procedures. Also, genetic circuits grant a scientist a greater capacity to mimic naturally cellular behavior for synthetic operations.

There were two distinct class of circuits we aimed to develop. The first is a combinatorial digital logic circuit. These circuits are defined by their binary outputs as well as their ignorance towards input order. In a biological context, a binary output would be the expression or absence of expression of a gene of interest. The second type of circuit is the combinatorial analog logic circuit. These circuit are defined by their analog output of a single gene as well as their ignorance towards input order. In a biological context, this behavior can be modelled by increasing the expression of gene as one shifts from a given logical state to another logical state.

Each design parameter mentioned above required its own distinct set of experiments to prove our system could achieve them. Ultimately, we were able to prove that Gemini could fulfill all design parameters. The evidence of this can be seen under our Proof of Concept.