Our Software Tool
Introduction
Following the design of COVID mRNA vaccines, there is an increased number of academic and industrial studies that are based on mRNA-based regulation. This type of regulation has also appeared in various IGEM projects. Thus, we decided to develop a user-friendly website with a software tool for the automatic generation of switch modules in the 5’-UTR of an mRNA for cell-specific translation. We aimed to develop a flexible tool that can be used by any kind of user and to adjust to different applications.
In our tool, the user provides the gene he wishes to express and can either provide a trigger molecule or simply select a cell type (including cancer tissue) in which the protein needs to be expressed. If the user did not provide the trigger, our software will find an mRNA molecule that strongly differentiates between the desired cell type to the other cells based on its expression characters and other properties such as unique cancer mutations.
The user can choose to run a default version or to adjust advanced parameters according to specific needs. Then, based on our models and algorithms, the software generates an optimized switch sequence. The switch is designed to enable translation only in the targeted cells and to prevent translation in the non-targeted cells, depending on the presence of the selected trigger molecule. In addition, the software can optimize the gene of interest based on translation models. Eventually, the user receives a detailed report with several options of proposed molecules for differential translation.
In the rest of this page, we provide a detailed description of our software tool.
Welcome Page
Our welcome page contains two links:
- Switch generator – links to switch design web page.
- Visit our wiki – links to our IGEM 2022 wiki website.
Welcome page
Web Interface Parameters
- Switch generator page – This page contains the different parameters the model receives, giving the user different levels of freedom.
- Email: email address to send the design report.
- Choose an organism: The model supports two different types of organisms, each organism triggers a different kind model optimized for it. Therefore, some features are different between each category.
- Have a Known Trigger? – The users check this box in case they already know the wanted trigger to use the Toehold sequence.
- Have a known mRNA to be used as Trigger? – The users check this box in case they want to use an algorithm for finding the best trigger inside given mRNA.
- Advanced options contain different parameter the users can change in case they need more complex designs.
- Stem Size: The size of the stem in the Toehold sequence.
- Hairpin side: The size of hairpin in the Toehold sequence.
- Trigger outside of stem: The trigger has two parts: outside the stem, part of the stem. By determining this proportion, the user can control the ON and OFF Ration as this feature implies this directly.
- Prioritize expression levels: Each sequence receives 3 scores: On Ration and OFF ration (determine by our regressor ), Metric score. This selection box let the users decide by which metric the sequences should be sorted by.
- Optimize translation: Should the pipeline use an algorithm for gene optimization.
- Perform Uridine depletion: Should the pipeline use an algorithm for gene Uridine depletion.
- Avoid pseudoknots: The pipeline by default avoids pseudoknots, letting the users disable this feature.
- Perform reading frame and stop codon check: The pipeline by default avoids inserting start and stop codons in the sequences and check the reading frame, The users can disable this feature.
Web interface parameters
Different Models
For each organism we have different model with slightly different parameters, the Web interface changes accordingly.
Prokaryotes
The model for the prokaryotic is generating a sequence with fixed structure. Structure based on Pardee's "Series B" design [1]. Selecting prokaryote lock the Trigger and mRNA checkboxes, while selecting know trigger. Advanced options contain only Triger out side of stem.
Prokaryotes web interface
Eukaryotes
When the user choose to work on eukaryotes, they can choose from three options:
- Inserting known trigger
- Insert mRNA, an algorithm determines the best trigger inside
- Choose Cancer Type, an algorithm chooses the best mRNA and the best trigger inside
Eurokaryotes web interface
Results Report
After the user submits a job, our algorithms will do their job and a detailed PDF will be sent to the user's email after approximately 20 minutes. The report conatins 5 different suggested toeholds along with:
- The toehold sequence
- A predicted secondary structure
- Metric score
- True/False if kissing hairpins is predicted to occur
- On prediction rank by our regressor
- Off prediction rank by our regressor
In addition, if the user chose to optimize the gene of interest, the PDF contains a second page with the optimized sequence.
References
- Keith Pardee, Alexander A. Green, Melissa K. Takahashi, Dana Braff, Guillaume Lambert, Jeong Wook Lee, Tom Ferrante, Duo Ma, Nina Donghia, Melina Fan, Nichole M. Daringer, Irene Bosch, Dawn M. Dudley, David H. O’Connor, Lee Gehrke, James J. Collins, Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components, Cell, Volume 165, Issue 5, 2016, Pages 1255-1266, ISSN 0092-8674