Freeze-drying

For our application, it was important that we made the storage conditions of our bacteria as easy as possible. We came up with he idea of freeze-drying our bacteria to see if they would survive that. Since our ML-I Biolab did not contain a freeze-drying setup, we had to make one ourselves. We did this in one of the fumehoods in the biolab and we attempted to freeze-dry six different types of sample (Table 3). Three for each of the different conditions also tested previously (no expression, A120 and Z1-A120-Z2) and these .same three, but with 100 mM threhalose added. This is a sugar which protects the bacterial membrane during freeze-drying^[10], and was therefore meant to be used in the samples for a positive control. However, even after running the setup for over 8h, some samples did not sublimate unfortunately. And since this setup required us to refill the cold trap with liquid nitrogen every couple of hours, we could not leave it overnight. Therefore, only two of the samples, Wt and Z1-A120-Z2, were dried relatively well. These were then reconstituted and subseqeuntly assayed using CCK8. Using the calibration curve made for this assay, the OD₆₀₀ values were calculated from the measured OD₄₅₀ values. These were then divided by 0.5, the original OD600 at which the samples were made, to obtain the final survival rate of the bacteria.

Sample	Success?
No expression	Yes
No expression + 100 mM trehalose	No
A120	No
A120 + 100 mM trehalose	No
Z1-A120-Z2	Yes
Z1-A120-Z2 + 100 mM trehalose	No

Molecular Dynamics simulation

Introduction

Molecular dynamics (MD) simulations are commonly used to see how proteins or other molecules move over time. This can contribute to the understanding of molecular systems, which cannot be seen with the eye or even with the best microscopes. In our application of forming a hydrogel with Elastin-Like Polypeptides (ELPs), it can be useful to see how the ELPs will behave at different temperatures. Above a certain transition temperature (Tt), there is a disruption in the thermal energy of the water molecules around the ELPs, which causes the water molecules to move away from the ELPs. This makes room for interactions between the ELPs. It has been found that there will be conformational changes in another ELP sequence when the temperature rises above Tt, which makes them more ordered and increases the hydrophobicity^[11].

It is interesting to see how this applies to our own ELP. The MD simulation will give a better understanding of the differences in the structure below and above the T_t and it will help with understanding how the ELP actually looks like. We will analyze different properties of the proteins, like the secondary structure formation, compactness, and the surface area that is accessible for the solvent, to see how the conformation differs at specific temperatures below and above the Tt.

Methods

MD simulations are typically computationally expensive. This made it necessary to shorten our ELP sequence to make the computational time manageable. We chose to shorten the hydrophobic parts to I_[10] instead of I_[60] and to shorten the hydrophilic part to A_[50] instead of A_[120] or A_[100], as shown in Figure 19. The leucine zippers stay the same. In this length reduction, the proportions are not the same as in the original ELP. However, we wanted to make sure that the hydrophobic parts were not shorter than the leucine zippers. This maintains a greater distance between the Leucine zippers and the hydrophilic part, and it prevents unrealistic folding. The hydrophilic part is kept long since this part gives the ELP its length and it might be interesting to see how this part behaves during the folding. The choices made for this might affect the outcome, but the combination of regions is still the same and the difference between the temperatures can still be compared.

Figure 19: ELP construct used for the MD simulation. In this construct, the hydrophobic VPGIG parts are repeated 10 times instead of 60 times and the hydrophilic part in the middle is repeated 10 times instead of 24 or 20 times. At the ends, the two different leucine zippers are located, which remain the same.

A generalized born implicit solvent is used to fold the protein. In an implicit solvent, the solvent (in this case water) molecules are not individually modeled, but with an approximation of the mean force from the solvent on the protein. Different theories can be used for this, and we chose to use the generalized born model. Implicit solvents are faster than an explicit solvent with simulated water molecules and more detailed than a simulation in vacuum[12]. The MD simulation is performed at temperatures 3 °C, 15 °C, 25 °C, and 37 °C, since the transition temperature was found to be 20 °C in the conducted UV-VIS experiments. The simulations are run in triplet to reduce the chance of coincidence in the results. This is necessary, since the initial velocities are chosen by the NAMD software and thus differ every time. Different velocities can cause differences in the final stable conformations, which can affect the results of the analytical methods.

Just like in López Barreiro et al., first energy minimalization is done for 20 000 time steps. Then, Langevin dynamics is used with Generalized Born implicit solvent. The simulation step was 2 fs with a simulation time of 50 ns. The cutoff distance is 18 Å, the switch distance 16 Å^[13].

The results are analyzed with Root Mean Square Distance (RMSD), Radius of Gyration and relative shape anisotropy, Ratio of Secondary Structures, and Solvent Accessible Surface Area (SASA) to show the different behaviors of the ELP at different temperatures. They are calculated with the MDTraj Python library. For the analysis, the analysis methods are calculated for the 1000 frames of the last 5 ns, which has a stable conformation at all temperatures. Even when the conformation is stable, there are still some small differences. These differences are taken into account with this distribution of the results of the last 5 ns.

Results

In Figure 20, a video is shown from one of the simulations at 25°C. Not all videos are included, since the process is comparable for the other simulations, especially when comparing them by eye. Some frames of those simulations can be found in the file below. When comparing the simulations at the four temperatures, they all start with folding at the ends of the ELP. This was expected since those parts are the most hydrophobic. Some of the simulations also show the folding of the ELP in the middle at the more hydrophilic part. However, there is no clear relationship between temperature and this folding behavior, so it is probably caused by luck in the simulation.

Figure 20: Video with one of the MD simulations at 25°C. The red residues represent the Leucine zipper, the blue residues are the hydrophobic part, and the light-blue residues are the hydrophilic part.

RMSD plots are made for each of the three simulations at the four temperatures. They are made for the complete 50 ns, but also for the last 5 ns to show how stable the conformation is related to frame 9000 (45 ns). This is important since there can still be a lot of changes in the structure while the moved distance of the atoms stays the same. Since there are a lot of figures made, they are not visualized here. However, they can be found on the wiki of the TU Eindhoven 2023 team.

For all of the measurements, the equilibrium seems to be reached. When looking at the plots of the last 5 ns, most RMSD plots have a variability of a maximum of 1 nm. Only the third simulation at 37 °C has a slightly larger difference. An RMSD of 0 describes a stable conformation, but there are always some small deviations. So it can be said that an RMSD of 0.25 nm has a high stability, but also 0.2-0.5 nm will give a high stability^[14]. With this information and when looking at the course of the curves, it can still be concluded that the conformations are relatively stable since the RMSD is still very small.

In Figures 21a, b, and c, the boxplots for the secondary structure analysis of the individual simulations are shown. This shows some variability between the simulations of a single temperature, but also overlapping deviations. This happens especially for the α-helix and β-sheet plots. The simulation results are taken together for each temperature to make them easier to analyze, which is shown in Figure 21d, e, and f.

Figure 21: Secondary structure analysis with a, b, and c for respectively the coils, α-helices, and β-sheets three individual simulations for each of the four temperatures and d, e, and f the overall results with the different simulations per temperature taken together.

Overall, almost no secondary structures seem to be formed. The rate of the coils is much higher than the rates for alpha-helices and beta-sheets. It is possible that more secondary structures make the ELP more stable, but that it is stuck in a local minimum. This can be proved with more simulations and some other simulation techniques.

When comparing the boxplots of the different temperatures, there does not seem to be a convincing difference in the secondary structure formation. There are some small differences in the medians and distributions, but there is no clear relation between those differences. We can thus conclude that there is no difference in the secondary structure between the temperatures.

The radius of gyration results of the individual simulations are shown in Figure 22a. The individual simulation results of 3 and 37°C show large differences in the results. This can be caused by the different velocities that are chosen for the single simulations. Since the individual simulations of 3 and 37°C differ a lot, the total boxplot in Figure 22b shows a large distribution of the results.

Figure 22: Radius of gyration results with a three individual simulations for each of the four temperatures and b the overall results with the different simulations per temperature taken together.

There is a clear difference between the radius of gyration at 15 °C and 25 °C, which are just below and just above the transition temperature. When looking at the median at 37 °C, also these results show a lower radius of gyration than 15 °C. At 3 °C, the radius of gyration is for two of the simulations very low compared to the other temperatures. When looking at the final conformations of the simulations, this can be caused by the shape of the stable configurations. When the shape is more cylindrical instead of spherical, which seems especially the case for the simulations at 15°C, the radius of gyration will increase. As mentioned in the methods section, we also computed the relative shape anisotropy.

Figure 23: Relative shape anisotropy results with a three individual simulations for each of the four temperatures and b the overall results with the different simulations per temperature taken together.

In Figure 23a, the relative shape anisotropy is shown for the individual simulations. There is clearly a difference in the shape between the different simulations, also in those with the same temperature. For example 25°C, which has a clear variability between the simulations. Some of the differences were already expected after the analysis of the radius of gyration. The second simulation at 3°C is clearly less spherical than the other two simulations at that temperature. Overall, when looking at Figure 23b, the shape of the ELP at 15°C is less spherical than at 25°C. Because of the large variabilities between the measurements at 3 and 37°C, it cannot be concluded how this is affected at lower and higher temperatures.

This analysis suggests that there is a difference in the compactness of the ELP below and above the transition temperature. Below the transition temperature, the ELP is less compact. At a temperature above the transition temperature, the ELP will become more hydrophobic with fewer solvent molecules around it. This makes the folded ELP more compact, but also more likely to induce interactions with other ELPs. However, for harder conclusions with the role of solvent molecules included, explicit simulations are needed.

In Figure 24a, the individual results show some deviations between the simulations at specific temperatures, especially at 3 and 37 °C. When taking the individual simulations together for each temperature in Figure 24b, some small deviations are shown. SASA at 25 °C seems to be lower than SASA at 15 °C, while the median SASA at 3 °C is also lower than the rest of the temperatures, but with a large deviation. The results for 37 °C also have a large deviation, with a median higher than the median of 15 °C. When comparing the results with the relative shape anisotropy, there is a relationship between more spherical simulation results and a lower SASA. There seems to be a smaller difference than the difference found in the radius of gyration and the anisotropy, which might be because ends that stick out probably have more effect on SASA than the relative shape anisotropy.

The conclusion will be that there is a small but significant difference in SASA at 15 and 25 °C, but that SASA at 37°C becomes higher again. So there is a small effect of the transition temperature on SASA, but not as clear as the radius of gyration. It was expected that SASA would become much lower when passing the transition temperature^[11], but in our ELPs it seems more subtle. This might thus be caused by the ends of the ELP that stick out of the spherical shape of the folded ELP.

Conclusion

In the analysis of the MD simulation of a shortened version of our ELP, different analysis methods were applied. These bring us to the conclusion that the shape of the folded ELP will be altered when increasing the temperature. At a higher temperature, the results suggest a more compact ELP with a more spherical shape. When the temperature increases even more to 37°C, the difference compared to 15°C will decrease. A temperature of 3°C generally results in more compact conformations but with a large variability between the simulations. The explanation for the more compact ELP at higher temperatures is that the residues become more hydrophobic and thus have more interactions with each other. When multiple ELPs are brought together, it is expected that this property results in increased interactions between the ELPs, especially between the hydrophobic ends and between the Leucine zippers.

The radius of gyration and relative shape anisotropy shows the most convincing difference between temperatures below and above the transition temperature, while the secondary structure analysis did not find a clear difference. For SASA, there seems to be a difference, but it is not as clear as the radius of gyration and relative shape anisotropy. For more convincing results, it would probably be better to use explicit solvent simulations and to perform more simulations at more temperatures. However, this and other more extensive experiments on the ELP interactions will be done in further research.

References

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