Our software, Circular DNA Design, generates a list of DNA sequences tailored to GotCha mechanism, but customisable according to the user's choice of target miRNA detected.
To develop the software tool, we followed the classic six phases of the software development life cycle: requirement analysis, design, coding, testing, deployment, and maintenance. For more information, see Model)
Initially, our team tried to use existing circular DNA sequences in scientific journals while only replacing the MicroRNA binding site of the circular DNA sequence with the complementary DNA sequences of our target micro-RNAs. However, we were faced with the challenge that there were way too many stem-loops in the predicted DNA structures in this scenario, making the DNA sequence unsuitable for use as the loops may intefere with amplification by polymerase. Despite this, we could not find any softwares out there that generates circular DNA sequences.Therefore, after much consultation with esteemed professors such as Dr. Yao Bo (Human Practices), and graduate seniors such as Chen Kuan-Lin (Human Practices), we came to a decision to design our own circular DNA sequence as a model called Circular DNA Sequence Design, which can be found on Github here. Through online DNA secondary structure prediction websites such as UNAFold, Kinefold, and RNAstructure, we have validated our code and therefore used it to generate our circular DNA probe sequences for capture of both our micro-RNA biomarkers in order to tailor our circular DNA for our project. For more information, please refer to Parts. We believe that our software can provide a new direction in microRNA detection.
When there is a segment of three or more complementary base pairs in a single DNA strand, there is a high probability of forming stem-loops.
With GC bases in particular, two base pairs are enough to form an unstable loop. the above can be ignored in our code design because of low probability.
To ensure GotCha will capture our selected miRNAs as expected and at the same time not detach easily, the Immobilisation Probe and miRNA have to bind accurately to binding sites on the circular DNA probe. Therefore, we designed our Circular DNA sequence such that there are no more than two complementary base pairs with Immobilisation Probe and miRNA. This ensures high accuracy in binding of Immobilisation and microRNA to their respective binding sites.
We created a software named "Circular DNA Sequence Design".
We used python language to create our software. Our main principle in this design software is that we used a unit of 3 nucleotides at a time to check if there are complementary bases read in the opposite direction. If there are complementary bases, the sequence of 3 nucleotides will be abandoned. If not, the code will continue to check for the next 3 nucleotides until the total length of circular DNA is reached.
Upon testing our software, we confirmed that the outputs are of the correct desired length without complementary binding to MicroRNAs and probe sequences at inappropriate places.
After which, we used UNAFold, Kinefold, RNAstructure DNA prediction websites to verify the secondary structures and thermostabilities of our output sequences.
In the process of testing the software, we made improvements to the code along the way. We changed the input from the complementary miRNA sequence of choice to the miRNA sequence itself, and a few other improvements to the interface.
Deployment and Maintenance
The software is deployed and maintained on a Linux server. This server allows us to maintain the database and make necessary changes on the website.
As the rolling circle amplification mechanism is growing in popularity in the field of synthetic biology and diagnostics, we see the great potential our model can bring to the table in these relevant fields (for more information, see Contribution). In the future, we aim to continue improving our model towards an even more user-friendly software. We recognise that albeit the cut in time our model brings to the process of circular DNA sequence generation, it still lacks the built-in ability to predict DNA structures and value of free-energy, therefore troubling users to manually take an extra step in checking through another website. Therefore, we hope that in the future, this modeling system can be further built on to increase user convenience and provide an efficient platform for both aspiring students such as fellow iGEMers as well as professionals in the field in DNA sequence synthesis.