Like every year, we share our findings with the iGEM community in the hope that future teams can benefit from our work. miRADAR provides three contributions: software for designing toehold switches activated by miRNA, a part collection accompanied by a model to implement threshold-dependent signal output, and an algorithm to design logic circuits with toehold switches.

An improved toehold switch design software for miRNA

Our project involved designing toehold switches for MS-specific miRNAs. To design these switches, we initially used the SwitchMi Designer made by iGEM team UParis BME 2021, which is a software tool that designs toehold switches activated by miRNA. Upon further research, we found that the toehold switches designed by the SwitchMi tool only partially hybridise with the desired miRNAs which leads to a reduced signal output. Full hybridisation of the miRNA ensures the largest difference in minimal free energy (MFE) between the native secondary structure of a toehold switch and the hybridised structure. Partial hybridisation leads to a smaller difference in MFE, meaning that the toehold switch is less likely to convert to the hybridised structure, since this conversion is less energetically favourable. We therefore improved the software tool by ensuring that the designed toehold switches fully anneal to the miRNA, resulting in improved signal output. This was done by adding a fixed requirement in the code of the software that takes the total length of the miRNA into account, while keeping the key features of the tool the same. Additionally, the conserved region in the toehold was changed to the B series toehold region designed by Pardee et al. (2016) as these toehold switches have been optimised for shorter (mi)RNA.¹ By decreasing the number of user inputs, we also obtained a program that is more user-friendly. Moreover, we have experimentally validated the output of this improved software tool in vitro. Future iGEM teams that want to design toehold switches for miRNA in diagnostic tools and other applications can find the software, which requires Python (version 3.10.12), in our GitHub.

A novel toolkit for threshold-dependent signal output in silico and in vitro

In our project, we needed to distinguish between levels of miRNA associated with healthy individuals and people with MS. We used Toehold-Mediated Strand Displacement (TMSD), which creates a sharp transition in the signal output of the system when the input miRNA is present above a certain threshold concentration. We designed a part collection consisting of four parts (BBa\_K5106015-18) that were tested in vitro. The output of this system is a fluorescent signal, designed by Wang et al. (2023), which allows the user to characterise the TMSD output by measuring the fluorescence.² The system is very versatile and applicable to any iGEM team that requires RNA-biosensors with a binary output. The RNA sequences needed for this system can be easily designed or adapted based on a desired input sequence, and the threshold between ON and OFF signals can be altered by simply changing the concentration of one of the components. This versatility could establish TMSD as a standard threshold system tool for cell-free systems. Simultaneously, we built a model that can optimise TMSD properties like the input concentrations and the reaction parameters, which can guide sequence design. We encourage future iGEM teams to further optimise and expand our part collection, together with the accompanying model, and to implement a threshold system for their (diagnostic) projects. The model is available as MATLAB scripts in our GitHub, and the threshold system is available from the parts registry.

A new optimisation algorithm for logic gate circuit design with toehold switches

To detect specific combinations of miRNAs, we needed to design a logic circuit that generates a single output only when the required miRNAs are present. Therefore, we designed an algorithm that finds the optimal logic gate circuit based on a set of disease-specific miRNAs. The importance of these disease-specific miRNAs varies. Some can be critical for diagnosing MS, others may suggest a potential MS diagnosis. As such, our logic circuit designs can include both AND and OR gates to accurately reflect this. The algorithm allows the user to design the optimal circuit, completely in silico. The optimal logic circuit we found for MS-specific miRNAs could not be tested in the lab due to time constraints. However, in parallel with searching for circuit designs, we made a continuous ODE model of a single toehold switch and the logic gates. This model was then fitted against experimental data from a toehold switch generated by our toehold switch design software and a previously reported AND gate we reconstructed.³ The resulting analysis helped us to understand sources of leakiness and the overall dynamics of the parts. Our code can serve as a useful tool for future iGEM teams that want to include logic gates in their projects and evaluate their performance. To our knowledge, this is a new algorithm that designs simple logic circuits and can be customised for any specific set of miRNAs. This algorithm could also serve as the basis for an extended algorithm that is able to design more complex logic circuits. The code is available in Python on our GitHub.

(1)

Pardee, K.; Green, A. A.; Takahashi, M. K.; Braff, D.; Lambert, G.; Lee, J. W.; Ferrante, T.; Ma, D.; Donghia, N.; Fan, M.; Daringer, N. M.; Bosch, I.; Dudley, D. M.; O’Connor, D. H.; Gehrke, L.; Collins, J. J. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components. Cell 2016, 165 (5), 1255–1266. https://doi.org/10.1016/j.cell.2016.04.059.

(2)

Wang, T.; Simmel, F. C. Switchable Fluorescent Light-Up Aptamers Based on Riboswitch Architectures. Angewandte Chemie International Edition 2023, 62 (41), e202302858. https://doi.org/10.1002/anie.202302858.

(3)

Green, A. A.; Kim, J.; Ma, D.; Silver, P. A.; Collins, J. J.; Yin, P. Complex Cellular Logic Computation Using Ribocomputing Devices. Nature 2017, 548 (7665), 117–121. https://doi.org/10.1038/nature23271.