Results

Project Achievements

Wet-lab Results

We successfully:

1. affinity selected DARPins binding to AIP1 via ribosome display (sequences)
2. expressed GFP
3. expressed DARPins
4. synthesised DARPins in vitro
5. designed and cloned a bioreporter for quorum sensing
6. collaborated with Dresden to assess how a DARPin would diffuse through their hydrogel
7. synthesised our own DARPins with the BioXP machine from Codex DNA

Dry-lab Results

1. Designed successfully DARPins
2. Modelled DARPin-AIP binding in silico via CABS-dock
3. Modelled DARPin-AIP binding in silicovia Mdock-PEP
4. Compared modelling of DARPin-AIP binding
5. Modelled diffusion and binding of DARPin and AIP in biofilm

GFP AND DARPIN PRODUCTION

GFP expression

GFP was expressed from the pET28a-sfGFP plasmid provided by Norman Adlung. This GFP was used for the ribosome display in order to have a positive control and proving that the GFP-targeting DARPin binds the GFP during ribosome display. Additionally, this experiment confirms that the pET28a-sfGFP plasmid expresses GFP, because this plasmid with a different promoter will be used for the bioreporter.

Mainly the GFP was present in the GFP supernatant deeming the GFP expression as successful. This experiment confirmed the GFP expression as successful at 28 kDA. The pET28a-sfGFP plasmid will be later used for the bioreporter and expression of the GFP from the plasmid is necessary to retrieve a positive signal in case of AIP binding. This experiment confirmed that we can use this plasmid for the establishment of our bioreporter, but we also retrieved GFP, which we will use as the positive control during our ribosome display.
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GFP-targeting DARPin Expression

We decided to express the GFP-targeting DARPin for our collaboration with TU Dresden. We wanted to assess how our DARPin would pass through their hydrogel for a combined treatment. We decided to use the GFP-targeting DARPin, because for our positive control we had a confirmed target. The GFP-targeting DARPin was first aimed to be expressed via cloning in the GFP-targeting DARPin gene with an additional His- and Avi-tag into the pET42b-HF-BE3 plasmid. The cloning of the gene into the plasmid was successful and colonies were observed. The GFP-targeting DARPin expression was further induced with IPTG and purified (Figure 2).

The GFP-targeting DARPin was mainly present in the pellet and not in the soluble fraction. The best results were present for induction of the GFP-targeting DARPin expression at 20 °C overnight. However, expression and extraction could not be improved. Therefore, we decided to proceed with in vitro transcription and translation of the protein due to the time constraint for our collaboration with TU Dresden.
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GFP-targeting DARPin in vitro synthesis

The GFP-targeting DARPin for the TU Dresden collaboration was in vitro transcribed and translated after the extraction was not successful and due to the time constraint we considered other possibilities. The GFP-targeting DARPin was synthesised and dry-freezed before it was sent to the TU Dresden team.
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Predicting the Structure of the AIP-binding DARPin

Design of DARPin Library

Our original DARPin library was planned to have a size of 1024, however due to limited funding it was not possible to design a library in this size and the DARPin library was limited to a size of 42 DARPins. The N-cap and C-cap were optimised according to previous publications and fixed (Hansen et al., 2017; Schilling et al., 2014). It was decided to only randomise eight positions in the internal repeats due to previous publications (Hansen et al., 2017; Schilling et al., 2014; Seeger et al., 2013). For more information about the design, please refer to the modelling page.

During the modelling and prediction of the structure of AIP and the DARPins the library was confirmed to be very diverse, because out of the ten predicted DARPins all of them interacted at different bindings indicating variability in the library. For more information, please refer to the modelling page.

Structure Prediction & Protein-Peptide Docking

AlphaFold2 was used to predict the structure of our DARPins. Ten of the DARPins were randomly selected and their binding predicted both via CABS-dock and MDockPeP. These algorithms were used to score the interaction between both and generally predict high domains of interaction. These algorithms were particularly useful, because they take the input sequences without previous assumptions of binding sites. All ten selected DARPins were observed to interact with AIP according to the modelling results and additionally, the modelling predicted that the DARPins between position 11 and 140 would interact with the AIPs between position 1 to 8. However, a general trend was observed that predicted that AIP will most likely bind between the last amino acids of the N-cap until the first amino acids of the C-cap with highest probability of binding between the first and third internal repeats. For more information upon the modelling results please refer to the Model page.

Diffusion Modelling

TU Dresden modelled how their phages and growth factors would pass through their hydrogel of their product Wunderband. Both of us focused on chronic wounds; therefore, we came together and collaborated on using their model to assess how DARPins pass through the biofilm and bind AIP. The model was very advantageous in order to discuss the implementation of our product. According to the model 30 µM of DARPins would be applied and they would have a half-life of 10 hours. This would give us the information that the DARPins should be applied every ~10 hours. For more information upon the diffusion modelling and also the implementation check the appropriate wiki pages.

Results from Ribosome Display

We performed in total three ribosome display experiments. Two of them were affinity selecting our 42 DARPins against the biotinylated AIP1 target, while one of them was affinity selecting our GFP-targeting DARPin against GFP. For the ribosome display containing the GFP-targeting DARPin we added additionally a small aliquot of DARPin #12. This would confirm that the GFP-targeting DARPin would bind the GFP target in higher quantities.

Based on the results from the sequencing, we were successful in the ribosome display with our GFP binding DARPin. The sequence logo for our GFP DARPin and the retrieved sequence from the binding assay can be seen in the figure 3. It shows that the sequence found to be bound was actually the GFP DARPin and not the added DARPin #12. We show here that the ribosome display can be used for future experiments, and could be used as an easy tool to find the right DARPin sequence for the target signalling molecule.

We also saw some affinity of sequencing of the AIP binding DARPins. We could retrieve from the sequencing data the same N-cap and beginning of the DARPin sequence. However, unfortunately, due to time restrictions, we couldn't show any specific DARPin that showed great affinity against our AIP. More time for testing and re-runs of the ribosome display would be needed to confirm the exact DARPin sequence that bound the best.

Synthesis of DARPins

We designed the DARPin library ourselves and also synthesised the DARPins in collaboration with Codex DNA by using their BioXPTM machine. For this we uploaded 32 of our DARPins and assessed how successful DNA synthesis of these were before we synthesised them in the BioXP™ machine. The whole machine run for DNA synthesis took around 15 hours (Figure 4).

The synthesised fragments were run on a gel to observe the expected size of 815 bp and after that were gel extracted to have no additional fragments interfering with the latter ribosome display (Figure 5).
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The DNA synthesis via the BioXPTM machine was successful and the created DARPin DNA could be successfully used for the latter in vitro transcription and translation for ribosome display.

Building and Testing the Bioreporter

Bioreporter Design

The bioreporter was built in BL21 E. coli and designed to contain both the AgrA and AgrC genes, which are responsible to sense AIP in S. epidermidis. Both these genes were under expression of pBAD, which is a constitutive promoter and expression of both of them would be constant. Additionally, the plasmid of the bioreporter contained GFP, which was under control of the inducible P2 promoter, which would only be expressed in the presence of AIP. This system would therefore cause a green fluorescent signal in the presence of AIP and meaning that if the DARPin would bind to AIP the green fluorescent signal would be decreased.

During the assembly of our bioreporter we had initial trouble fitting in the bioreporter part 1, which contained both of the promoters. Therefore, we decided to elongate the part and add more base pairs between the promoters to also avoid later steric hindrance of the promoters. After both the parts of the bioreporter were added into the pET28a-sfGFP plasmid another PCR of both bioreporter parts was performed to confirm the presence of both parts (Figure 6).

The bioreporter was assumed to be functional after this PCR for the reason of performing restriction cloning, which would align the parts in the direct direction. The final test of the functional bioreporter shall be done with the addition of AIP.
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Bioreporter Test

To test the bioreporter, our aim was to test the GFP intensity of the bioreporter cells when they were induced with AIP's, and then if we had time, test if the signal would be lower in case DARPins were present in the environment. Unfortunately, we only had time to test the bioreporter with AIP inducement.

For the testing we wanted to know if different concentrations of AIP's would affect the GFP signal, or if it would be the same as long as the threshold of inducement had been achieved. The exact amount of AIP molecules needed to activate the P2 promoter has not been measured as far as we know in literature. However, we had done some estimations of the needed concentration for our modelling work, and for this we chose to see if high concentration would yield high intensity. We ordered the AIP's directly from Genescript as purified protein. The AIP's were dissolvable in DMSO, however, we ran into some trouble of not all protein dissolving in the DMSO when we were preparing the dilutions. Due to this we had only some type of estimates of the concentrations but renamed them to high and low concentrations of the AIP's. The lower concentration should be somewhere around 250nM, however, this is unfortunately not tested due to lack of equipment available. The amount of each tested AIP's can be seen below in table 1.

The cells were grown up to 1.2 OD600, we added 5 µL of culture to 200 µL of LB media, which equals 4.8*106 cells in the beginning. After that we induced 3 wells with each concentration and measured the OD600 and GFP intensity at both 470 and 511nm wavelength. The measurements were done with the BioTek Synergy H1 Plate Reader, and the measurements were taken for 10 hour every 20 min.

As blank we had LB media with kanamycin to avoid contamination growth, and as negative control, we had the same expression cells as for the bioreporter, but these ones included the GFP DARPin expression cassette. The set up on our 96 well plate can be seen in table 2.

Table 2. 96 well plate set up for GFP and OD600 measuring

The results of the growth and fluorescence can be seen below in table 3. All wells started nicely from the same OD600 which was the aim. And the blanks where there are no cells showed low to almost no growth. The small OD600 can be due to some contamination during the pipetting work or just the reader calibration. It is also good that the growth is the same for both our bioreporter cells and for the negative control cells, as they were the same strain. And based on these results, the transformation of the bioreporter into the cells shows no defect in the growth. A closer look at the growth and fluorescence signal overtime can be seen in graph 1, for one of the wells with our bioreporter cells which was induced with 50uL of AIP's of the lower concentration. The GFP intensity can be seen in graph 2. It is quite clear that the concentration of AIP's did not change the GFP output signal. It was also seen that the bioreporter cells which were not induced with AIP's still showed also some GFP intensity.

Table 3. Synergy reads of max OD600 and GFP fluorescence intensity over 10 hours

We can conclude that there should still be some changes done to the setup of the promoters in the bioreporter. It seems that the P2 promoter might be active even if it hasn't been induced, or then the strong constitutive pBAD promoter has something to do with the expression of GFP. However, it seems not likely as it is about 70 bp downstream from the GFP encoding gene, and the pBAD promoter is inserted to start transcription in the opposite direction. Future testing of inserting just the P2 promoter in the plasmid prior to the GFP gene would be needed to figure out what might be the cause of the false GFP signal.
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Future Tests

Possible future tests definitely involve the fine-tuning of our bioreporter in order to ensure the level of AIP that is required for our bioreporter to respond. Furthermore, the bioreporter should be used in combination with the best performing DARPin to ensure that the DARPin blocks the fluorescent signal. This last test could not be performed due to time limitation, but due to the results from the collaboration with TU Dresden we already have potential testable DARPin concentrations.

Additionally, potential high affinity DARPins are now known to bind to AIP. However, the library can always be improved. The ribosome display could be repeated by altering the Tween concentrations to make the selection more harsh and find the best affinity binder out of the ones we isolated from the first round of ribosome display. In addition to repeating ribosome display we can specifically model the wet-lab results to retrieve results about the binding in silico.

In addition to testing the final DARPin with the bioreporter and analyse it in silico, we should also test its behaviour on an actual S. epidermidis biofilm. For this we plan to grow an S. epidermidis biofilm and measure its biofilm biomass with crystal violet. We assume that the biofilm biomass might decrease with the addition of the DARPin, because more bacteria would stay planktonic (Cruz et al., 2018). We could also analyse the biofilm build-up and in which way it changes when the DARPin is added. This could be done via FISH (Fluorescence in situ hybridization). FISH has previously been proposed as a tool to diagnose biofilms with and it would be interesting to know in which way the phenotype of the biofilm changes with the addition of DARPins as well as quantify the biofilm in an exact measurement (Moter and Göbel, 2000). After the DARPin has been analysed for it's functionality it would be beneficial to analyse it's stability on different surfaces most importantly skin. Therefore, it would be ideal to move on to in vivo experiments with animal models or utilise organoids.

References

1. Cruz, C.D., Shah, S. and Tammela, P. (2018)
   Defining conditions for biofilm inhibition and eradication assays for Gram-positive clinical reference strains
   BMC microbiology, 18(1), pp.1-9
   Google Scholar
2. Moter, A. and Göbel, U.B. (2000)
   Fluorescence in situ hybridization (FISH) for direct visualization of microorganisms
   Journal of microbiological methods, 41(2), pp.85-112
   Google Scholar