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<p style = "font-size:260%; color:#0071A7; text-align:center;">Developing a Digital Parts Library</p> | <p style = "font-size:260%; color:#0071A7; text-align:center;">Developing a Digital Parts Library</p> | ||
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<p style = "font-size:150%; padding:5px 150px 10px 150px; color:#0071A7;">The first phase of our project was to develop a library of digital parts. Our journey began with finding the guide RNA sequences we would use in our work. We generated over one thousand 20 base guide RNA sequences in silico using a random sequence generator.</p> | <p style = "font-size:150%; padding:5px 150px 10px 150px; color:#0071A7;">The first phase of our project was to develop a library of digital parts. Our journey began with finding the guide RNA sequences we would use in our work. We generated over one thousand 20 base guide RNA sequences in silico using a random sequence generator.</p> |
Revision as of 20:00, 15 October 2016
Developing a Digital Parts Library
The first phase of our project was to develop a library of digital parts. Our journey began with finding the guide RNA sequences we would use in our work. We generated over one thousand 20 base guide RNA sequences in silico using a random sequence generator.
It was critical these guide RNA sequences be orthogonal to the human genome because we wanted to test our system in HEK293FT cells and prevent off target activation in the host genome. To test for orthogonality, we entered the sequences into the CRISPR Optimized Design tool developed by the Feng Zhang lab. We selected the top 18 sequences, which had an orthogonality score of 98% or higher, to synthesize and use in our research.
We synthesized these guide RNA sequences through IDT and cloned each one into guide RNA expressing vectors and guide RNA operator pairs. To act as controls for our experiments, we also cloned the guide RNA sequences Tre and UAS into guide RNA expressing vectors and guide RNA operator pairs. These 20 initial operators expressed an iRFP gene.
We transiently transfected and ran through a flow cytometer our paired gRNA expression vectors and gRNA operator reporters and dCas9-VPR to test their expression behaviors. We wanted to see high activated states coupled with low basal expression, a true digital system. The screen of this can be seen below.
Based on this screen, we decided to proceed with guide 1, guide 3, guide 8, and guide 13 for all future experiments. Next, we needed to prove that our parts could drive a diverse library of genes of interest. To complete this, we replaced the iRFP in our guide RNA operator reporters with a GFP, a BFP, and an mRuby protein. The results from these test can be seen in the matrix below.
In all cases, there was low basal expression and strong activation, proving that our system not only behaves digitally, but that it could also do so over multiple genes.
Finally, our system needed to be mutually orthogonal to prevent significant undesired crosstalk. If there was off target gene activation between operators, then we could not transfect multiple operator-expression pairs and obtain predictable results. We performed an orthogonality transfection with the GFP driven operators from our library. The experiment was designed such that every guide RNA expressing vector would be paired with each guide RNA operator reporter vector. We predicted significant GFP fluorescence when the guide RNA expressing vector has the same guide RNA sequence as the guide RNA operator reporter vector, and no significant expression elsewhere. The results of the experiment can be seen in the matrix below.
The diagonal down the matrix demonstrates that there is mutual orthogonality between the guides in our system. With this matrix, we proved that we developed a digital parts library.
Our final test was to compare the relative strength of our parts to a CMV, a strong mammalian promoter, to determine the relative strength of our system. This would also allow for a better interpretation of where our parts fit into the grand scheme of synthetic biology. The graph below shows the results from this experiment.
While our parts expressed well, they did not have a higher expression than the CMV. This was not particularly surprising. But it did raise the question, would we ever be able to show higher activity with a minimal CMV in our system than with a full CMV?
Our next step was to expand to a functioning analog library...
Expanding to an Analog Parts Library
The next step in developing our library was to expand into the analog domain. We are more specifically referring to an array of quantized levels of expression that on a macroscopic scale appear analog, similar to a Riemann Sum of an analog signal.
To create this “quantized-analog” pattern, we had two driving hypotheses: multimerize the operators to increase expression and mutate the operators to decrease expression.
The conceptualization behind multimerizing, or adding multiple binding sites for the dCas9, harkens to previous work done with TAL effectors and Zinc Finger motifs. By adding additional binding sites, we expect to recruit more dCas-VPR transactivators to the operator vector, increasing expression and producing a synergistic effect. Additionally, we varied the space between binding sites. The motivation behind this was that we wanted space for the dCas9-VPR to bind effectively. The results for these experiments for each of the four guides in our library can be seen in the graphs below.
In general, increasing the number of binding sites also increased the expression of the operator reporter. Additionally, with only minor variations from this trend, increasing the space between binding sites also increased expression. This set of experiments proves that multimerization is an effective technique to increase gene activity.
We also compared the relative strength a CMV from the Registry to one of our multimerized operators, consisting of three binding sites for guide RNA 13. CMVs are known among mammalian synthetic biologists as being a strong constitutive promoter. The data from this comparison can be seen below.
As the graph demonstrates, our triple multimerized operator containing a minimal CMV had greater expression than the full CMV. This proves that our system produces additional varied levels of gene activation as well as have some temporal inducibility.
After we completed cloning and assaying our multimerized operator reporters we sequentially mutated every base in our twenty base guide RNA sequences, beginning at the five prime end. Every adenosine was mutated to a cytosine and vice versa and every guanine was mutated to a thymine and vice versa. This produced a complete shift from purines to pyrimidines of the opposite DNA base pair. In addition to these single base mutations, we also clustered 2 and 3 point mutations around base 1 and base 11 in the guide. The results of this screen can be seen below.
Though the data did not produce the decreasing step function we had expected, there were some results of extreme interest. The mutations on bases 4 through base 7 produced a distinguishable downward trend. Moreover, mutations at base 10 and base 11 produced nearly a fivefold decrease in expression when compared to the non-mutated operator. From our multi point mutations, the data did not represent any significant or controllable changes in expression. Therefore, we have decided to not move forward with multi-point mutations.
With this experiment we have proven that we have developed an analog parts library. We have a system than can range from five times below normal expression to five times above normal expression under a minimal promoter, out competing a strong full promoter. Now, what can we accomplish with our library of both digital and analog parts?
An answer lies in Genetic Logic Circuits...
Integration into Genetic Logic Circuits
As we move to combat more and more complicated problems in synthetic biology, we must create more and more advanced tools. As synthetic biologists, one route we can take is to develop genetic logic circuits to produce the computational tools needed to complete our research.
There are several possible variants of genetic logic circuits. We chose to use combinatorial logic circuits because it is only the absence or presence of inputs, not the order, that determines the output.
By definition, these inputs shift the logical state of our circuits. To build our circuits, the guide RNA target sequences were placed between heterospecific recombination sites unique to Cre and Flp tyrosine recombinases. When a recombinase is introduced, it excises the region between the heterospecific sites, changing which guide RNA is expressed through the constitutive promoter that drives the circuit. This process is unidirectional in time, meaning that state changes are irreversible.
We performed numerous experiments of increasing complexity to prove that our library could be used in a wide variety of circuits to achieve digital and analog outputs. All of our experiments used the same gene circuit.
The circuit constitutively expresses guide RNA 3 in the first state, guide RNA 1 in the second state, guide RNA 8 in the third state, and finally guide RNA 13 in the final state. This image will appear in conjunction with every experiment below as a reminder.
Experiment 1: Activation
The ability to control gene activation is a fundamental characteristic of genetic logic. To test if our system could hold up to such behavior, we set up an AND gate experiment that could only produce an output in the presence of both signals (Cre and Flp). We transfected our logic circuit and a guide RNA operator containing a g13 target site and a BFP reporter into HEK293FT cells. With this design, we expected that there would be strong BFP expression in state 4 but no significant fluorescence in states 1, 2, or 3. As the graph below demonstrates, we succeeded in proving our system could control gene activation via an AND gate.
Experiment 2: Repression
Another fundamental characteristic of genetic logic circuits is the ability to control gene repression. A NOR gate will only express a gene in the absence of signals. We developed a NOR gate circuit and transfected it into our HEK cells along with a guide RNA operator containing a g3 target site and a GFP reporter. We expected to see significant GFP expression only in state 1 and no significant expression in the other three states. As the graph below demonstrates, we succeeded in proving our system could work effectively in a NOR gate to repress a desired gene.
We experimentally collaborated with Worcester Polytechnic Institute’s iGEM team to validate the results of our circuit using fluorescent microscopy. The microscope images can be seen below.
The fluorescent microscopy images validated our flow cytometry analysis by showing significant GFP expression in the first state and no significant GFP expression in the other three states.
Experiment 3: Complexation of Basic Gates
After proving our library’s ability to perform fundamental circuits behaviors, we developed more complex behaviors. We combined our AND and NOR gates to develop our “Complexation Circuit”. We expected to see GFP expression in the absence of signals in our first state, no significant fluorescence in our second and third states, and BFP expression in the presence of both signals in our fourth state. To perform this experiment, we transfected our circuit and the operators from our previous AND and NOR gate experiments into HEK cells and assayed fluorescence using our flow cytometers. As the results below show, our “Complexation Circuit” functions as expected, proving our circuits capacity to perform more complex functions than fundamental computation.
Experiment 4: Line Decoders
For our final digital output circuit, we developed a line decoder. A line decoder is when each logical state has its own output, a quintessential circuit behavior. We created four distinct line decoders with each state producing a different fluorescent protein (BFP, GFP, iRFP, and mRuby) in each decoder. The results of these four trials can be seen below with the operators used in the experiment stated:
g3- BFP g1- GFP g8-iRFP g13- mRuby
g3- iRFP g1- mRuby g8- BFP g13- GFP
g3- mRuby g1- BFP g8- GFP g13-iRFP
g3- GFP g1- iRFP g8- mRuby g13- BFP
In each line decoder, there is only significant protein fluorescence in its predicted state, proving that our library is fully capable of performing in complex systems composed of two inputs and four outputs.
Experiment 5: Analog Logic
Once we were able to prove our system could produce digital output, we tested to see if we could also produce a circuit that could provide analog outputs. As a reminder, an analog output circuit has the same gene of interest expressed at different levels for a given logical state. In our circuit, state 1 paired with a triple multimerized operator reporter with a g3 target site. State 2 paired with a single binding site operator with a g1 target site. State 3 paired with the double multimerized operator reporter with a g8 target site. Finally, state 4 paired with a mutant operator with a g13 target site. All of these operators contained a GFP reporter and were transfected with the genetic logic circuit and their accompanied expression vectors and dCas9-VPR. We predicted that the order of expression, from highest to lowest, would be state 1, state 3, state 2, and finally state 4. The results of the experiment can be seen in the graphic below.
While there are some discrepancies between the expected results and the actual results, (specifically the expression level of state 3), we can say that this experiment effectively proves that the Gemini library of parts can be used to produce an analog response from a combinatorial circuit.