Toehold Design

Toehold Analysis

| Troubleshooting

| Our solution

Therefore, the frustrating specialization of machine learning tools led us to develop our own software tool, as previously mentioned, to analyze the sequences. For this purpose, Nupack and ViennaRNA statistical models were utilized, making our software modeling tool compatible with both Windows and Linux devices, providing results from two different packages for comparison and finally generalizing the function of the model, making it possible for future iGEM teams to use it. Various values of the sequences’ properties were calculated:

  • ~delta-G free energy of the toehold switch sequence.
  • ~Frequency of the mfe (minimum free energy) structure of every toehold sequence.
  • ~delta-G free energy of the RBS-Linker of every toehold switch sequence.
  • ~Perfect matches: number of paired nucleotides between toehold sequence and miRNA. This part of the software has 2 outputs for ViennaRNA: 1) the number of the nucleotides, 2) the percentage of paired nucleotides compared to the predicted nucleotides in the design process.
  • ~delta-G binding of the toehold switch sequence.
  • ~Concentration dependency plot for every toehold sequence: plot that shows the relative concentrations of the complex miRNA-toehold, toehold and miRNA sequences.
  • ~PostScript images (.ps files) that depicts the complex of the toehold switch and miRNA binding.
  • ~Scalable Vector Graphics (.svg files) that depict the secondary structure of every toehold switch sequence.
  • ~Pair probability matrix: matrix containing the probabilities of pairs between two sequences.
  • ~Sampled structures values.
  • ~Partition function: algorithm for nucleic acid secondary structure including pseudoknots.


Corresponding miRNAPart's Name on the RegistryFree Energy of the Toehold (kcal/mol)ΔG Binding Energy (kcal/mol)ΔG RBS-Linker Energy (kcal/mol)

Corresponding miRNAPart's Name on the RegistryPerfect_matches (percentage % number of bases binded)Design (paired + unpaired)
hsa-miR-143-3pBBa_K3727001(1,0 20)20
BBa_K3727000(1,0 20)20
BBa_K3727002(0,95 20)18
BBa_K3727003(0,95 20)18
hsa-miR-30e-5p BBa_K3727005(1,0 19)19
BBa_K3727004(1,0 19)19
BBa_K3727007(1,0 20)20
BBa_K3727006(1,0 20)20
BBa_K3727009(1,0 21)21
BBa_K3727008(1,0 21)21
BBa_K3727011(1,0 18)18
BBa_K3727010(1,0 18)18
hsa-miR-1246 BBa_K3727012(1,0 20)19
BBa_K3727013(1,0 20)19
BBa_K3727014(1,0 19)18
BBa_K3727015(1,0 19)18

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Final Dry Lab Results

After the evaluation process completion, the following toehold sequences were selected and ordered to be tested in iGEM Thessaloniki lab:
1-st Generation2-nd Generation

Concerning the generations (as previously mentioned) the results were surprisingly conclusive. The 1-st generation of toeholds didn’t satisfy the necessary thermodynamic conditions in order for the fluorescence to be a declarative factor of either the presence or the absence of any miRNA sequences. The 2-nd generation on the other hand, did satisfy all these conditions and was selected as the ideal group of toeholds to be used for the diagnostic tool. These results were later confirmed by our wet lab’s experiments.

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Engineering Success
Proof of Concept

Mass Reaction Kinetics

In this particular genre of mathematical modeling, the products of the reactions taking place within the biological system depend on the concentrations of the reacting elements. The modeling of such systems requires solving ordinary differential equations (ODEs), which correlate the concentrations of the reacting elements to those of the products. In our case, the solution of the ODEs was performed using MATLAB.

The system under study consists of our synthetic sequence, that is toehold switch, and its corresponding miRNA sequence. The miRNA sequence works as a trigger for the translation of the reporter gene to be initiated; a procedure that is suppressed if the synthetic sequence doesn’t interact with the trigger RNA.

The parameters used to describe the reaction rates of this particular system were taken from the team iGEM SASTRA Thanjavur 2019, since they studied the system toehold switch – miRNA as well.

| Interaction of the toehold switch with the corresponding miRNA

The initial model, which is the first step towards the study of the system, consists of four differential equations. Essentially, it concerns exclusively the interaction of the toehold switch with the corresponding miRNA and it refers to the final form of the complex suitable for translation. The reciprocity of the reactions of the system requires using two rates for each reaction, which are not identical since thermodynamically the molecules being bound to each other are favored. In order for the proper study to be done, another transitional situation is added between the closed hairpin and the linear arrangement of the complex. (as implemented by iGEM SASTRA Thanjavur 2019 and iGEM CLBS-UK 2017)

The diagram below demonstrates the Concetration of the Closed Toehold Switch (CTS), miRNA, Partially Bound Toehold Switch (PBTS) and Open Toehold Switch over time.

| Transfer process of DNA, translation process of the reporter gene and decay process of all the molecules of the system

The second model concerns the transfer process of DNA (which results to the initial form of the RNA synthetic molecules), the translation process of the reporter gene (in our case GFP) and finally the decay process (which includes all the molecules of the system: closed toehold switch, miRNA, open toehold switch). This model aims to the quantification of the concentration of the fluorescence protein and to the representation of the reaction occurring within the cell-free system for better accuracy to be achieved during the experiments.

The diagram below shows the concentration of the Closed Toehold Switch, Open Toehold Switch, miRNA and GFP. The initial concentration of miRNA is the same as DNA of Toehold Switch , 100nM.

| Quantification of fluorescence

The next and final step of the modeling is the quantification of the fluorescence provided by the system. As our system approaches with great accuracy the one of iGEM SASTRA Thanjavur’s 2019, we are allowed to use the parameters of their system for the measuring of fluorescence. In this last system, the maturity and decay of the GFP molecule are studied as well as the scaling factor, which represents the fluorescence’s quantity.

The diagram of the third model represents the intensity of the fluorescence that should be detected after a 2 hours period when the initial concentration of miRNA is 1,10,100 and 1000 nM.

See also:

SASTRA Thanjavur 2019 Model
CLBS-UK 2017 Model

Wet Lab Experiments Design

In order to organize our experiments, we used Benchling, an online platform that combines many of the necessary tools for the design and simulation of the experiments.

We used Benchling throughout the design of our experiments, for keeping notes of the lab work we conducted each day and keeping our results organized, creating and writing our protocols, visualizing our sequences and plasmids and finally, for performing sequence alignments. For our protocols and notebooks, you can check the pages Experiments and Notebook, respectively. However, the most important procedure that this tool came in handy for, was cloning. Specifically, we needed a tool for the simulation of the reactions involved in cloning, such as restriction digestions and ligation, to better design these experiments.

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Wet Lab Notebook

First of all, we used Benchling to create interactive maps of our g-Blocks and vector. After that, we used the digest tool to run a virtual digestion of each part to ensure that these sequences were compatible with the cloning method we selected -that is BioBrick Assembly. In the following figure, there is the map of the vector we used, as shown in Benchling.

Through the simulation of the digests, we wanted to ensure that there are no restriction sites of the selected enzymes (EcoRI and PstI) within our sequences, except for BioBrick prefix and suffix, respectively. This tool, also, helped us to predict the electrophoresis results, after the digestion of the vector. This was important because as it is clear in the image below, the two bands -the linearized vector and its insert- are of similar length and their lanes are very close and difficult to distinct. This led us to run the gel for a longer time than usually recommended.
For the simulation of the assembly of our parts with the vector, we used the Assembly Wizard tool. With this tool, we were able to select the vector’s backbone and our part, by picking the regions between the restriction sites and automatically create a new plasmid. This procedure could give us insights into the ligation of the two parts and mistakes in the design and orientation of the sequences that could impede the cloning procedure. Although we tested all the parts, here we attached only an example of a virtual plasmid created by the Assembly Wizard.

This was, also, of great importance, since we tried cloning many times without success. Having our assembly method tested, we made sure that there was no problem with the design of our parts and this made troubleshooting these experiments much easier.

Finally, we used Benchling’s alignment tool, to compare the results we got after the sequencing of the parts we were working with, with their initial sequence and determine if there were any mutations that would alter or hinder their function. For example, we used this procedure for iGEM Thessaly 2019 parts. You can find more information about it in our “Lab Book: iGEM Thessaly 2019 Parts”:

Wet Lab Notebook

Modeling the Device

Concerning our fluorometer device, we decided to model the hardware and mechanical part with CAD designs, which enable a bottom-to-top construction of the device.
  • Fig.1 Temperature Controller
  • Fig.2 3D CAD Design

A more analytical explanation of the desings is hosted on our Hardware page: