Team:TEC COSTA RICA/Proof Of Concept
Proof of Concept
To demonstrate the relevance of our project and validate its viability, we chose a software tool and a multidimensional characterization of the genetic suicide circuit. These are the proofs of concept for our circuit, our conceptual framework and overall take on sequential logic.
Wet Lab
While experimental characterization is essential for a complete synthetic gene circuit design to be
validated, we explored alternative approaches to sidepass COVID-19 related limitations.
Firstly, in our architecture we detailed the use of our parts for related functions, making
our approach feasible at least from a theoretical standpoint. Extensive mathematical modelling for
the optimization and characterization of our counter circuit has been done as well, its results
being reported in the {mathematical model} page. Furthermore, an experimental characterization
design for the full circuit was also developed in order to demonstrate its feasibility. Finally, we
were able to design and perform some experiments to characterize our most novel device, the counter
system, rooted in a fluorescence assay along with in silico modelling, whose results are detailed in
{Wet-lab}.
Software
As mentioned before, the proposed {software framework} is a guide meant to be implemented in a
software tool. Therefore, our proof of concept for the software framework and -by extension- for our
conceptual framework, is our software: a python library for the exploration of circuit
architectures. This is our specific conceptualization on the abstractions presented
by the conceptual and software framework. The objective of the software is the design of genetic
circuits that fulfill complex functions which follow sequential logic, and the exploration of
architecture alternatives for each specific functionality.
We implemented the four stages of the software framework: {generation, evaluation, action and
analysis} through a python script that generates circuits, processes each state change to generate
the child architectures and feeds them to a database.
Furthermore, the software follows a sequential approach facilitated by its base on the framework,
and portrays some of the characteristics previously covered for sequential logic:
- It facilitates traceability for the circuit's behavior by both storing all of the states as well as their corresponding inputs; this way the progression of states is easily visualized and data such as the activated promoter or potential inducers is linked to the state.
- It allows data storage by including parts that modify the DNA sequence.
- As it is based on the {processing workflow}, the circuit's behavior is simulated by reiterating the analysis for the time-ordered progression of states.
- The software generates all possible alternative states, as a state is generated per functional part.
- Multipurpose circuits, where multiple states and fates are achieved using few parts and inputs, can be easily designed or filtered.
- Furthermore, it facilitates troubleshooting for real life applications since, when an in vitro. or in vivo. problem emerges, easy tests (e.g. sequencing) can be performed that, together with the methodology and results, can be matched to the stored information and trace back the issue.
- The user interface allows the analysis of biological behaviour as decision making networks.
- The software, as an implementation of sequential logic, analyzes and develops biological behavior and processes in a highly straightforward form.
- A guided design is facilitated through the use of filters to generate and analyze circuits.
The software is also proposed to be highly modular, in order to be used in different areas and easily modifiable. To achieve this, we implemented the use of filters for generation and analysis that assist specific applications. Even further, the script was thoroughly documented to facilitate its application and modification.
You can see more about how our software works, its scope and the results we obtained on our Software.