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Based on the input of specifications of experts in the field (entomologists, mosquito control offices), the scientific process of detection (ecosystem of the mosquitoes, state of the samples containing pathogen antigens, safety,…) we were able to generate the 3D coordinates of a trapping device with the help of computation and 3D modeling software. The trap was subsequently generated through the 3D printing process. The prototype model tested for egress of sample of mosquitoes (n=200) showed a 2% rate of escape (98% retention rate). However, capture using the Biogent® pheromone bag was not efficient as no mosquitoes were captured after 24h of exposure. This second aspect needs to be improved, by changing attraction systems including CO2 generation.
The fusion protein we designed contains the silica-binding peptide (Si4), the cellulose-binding domain of cellulose-binding protein A (CBPa), and the B domain of staphylococcal protein A (BpA). It is a 25 kDa protein (Fig. 1).
Figure 1. Schematic representation of the C2 fusion protein. The C2 fusion protein is composed of the silica-binding peptide (Si4, in red), the cellulose-binding domain of Clostridium cellulovorans cellulose-binding protein A (CBPa, in green), the B domain of staphylococcal protein A (BpA, in blue.
Once we received the sequence encoding for this protein (named construction C1 or C2, size 921bp, with a C-ter or N-ter His-Tag respectively), we amplified it by PCR by using specific primers (For, Rev, see PCR protocol) (Fig. 2) and a Taq polymerase without exonuclease activity. In lanes 1 and 4 we see that a PCR product was amplified with the expected size. As negative controls, neither amplification was possible with a single primer (lanes 2, 3, 5, 6), nor in the absence of primers (lane 7) or DNA template (lane 8).
In order to have more DNA, we cloned it into TOPO vector (Fig. 3A), and transformed competent bacteria Escherichia coli TOP10, resulting in white clones (Fig. 3B). After bacteria culture and plasmid DNA extraction, we verified the presence of an insert by using Xba I and Hind III restriction enzymes (data not shown). After that, insert was extracted from the gel, and ligated into digested and dephosphorylated pET43.1a, the expression vector (Fig. 4A). We repeated the procedure, and we proved that our vector contained the insert by electrophoresis (Fig. 4B). Sequencing confirmed that it was the correct sequence.
Once checked, we cloned our construct into the Escherichia coli BL21(DE3) strain, a specific dedicated strain to produce high amounts of desired proteins under a T7 promoter. Bacteria were grown on large scale (4 l), and we made a growth curve (Fig. 5). Protein expression was induced with IPTG overnight at 15°C. Protein purification was achieved using the HisTag. Owing to the intrinsic affinity of C2 for cellulose, we had to revert to a polystyrene column for purification to work. We eluted our protein using a gradient of imidazole-containing buffer, and two peaks were detected (Fig. 6). We checked the presence of proteins in the fractions by SDS-PAGE. We clearly noted the appearance of bands at about 25 kDa, the expected size of our fusion protein (24 967 Da), but also at about 50 kDa (Fig. 7). We hypothesized that it could be monomers (25 kDa) and dimers (50 kDa). Indeed, since Si4 of C2 is able to condense silicic acid, it could potentially form dimers via Si-O bonds.
After determining the concentration of each fraction by Bradford assay, we tested the efficiency of our protein to bind to cellulose and to catalyze the biosilification reaction. Unfortunately, the described methods to the last component, i.e. to test the ability of our protein to bind to antibodies, require high amounts of antibodies (hundreds of micrograms), making the experiment too expensive to perform. form dimers via Si-O bonds.
We first tested the ability of our protein to bind to cellulose. To do that, we used several types of cellulose: Avicell, Sigmacell, and carboxymethyl-cellulose. As described by Goldstein et al1, we mixed cellulose with an excess of competitor non-specific protein (BSA), and with or without our protein of interest (Fig. 8A). After washing and centrifugation, we harvested proteins from supernatant and the cellulose-based pellet in order to analyze them by SDS-PAGE. We clearly noted that the 25 kDa and 50 kDa proteins were retained by cellulose, instead of the non-specific BSA (Fig. 8B). Indeed, data showed that almost no monomer remained in the supernatant after the second wash, but the pellet contained most of the protein. However, some dimers seem to remain in the second washing supernatant because the initial protein concentration was too high: the binding sites were saturated. The pellet also contains a lot of the dimers. As control, we observed that BSA remained in the supernatant and didn’t bind to cellulose. Therefore, we can conclude that our protein binds to cellulose.
Then, we investigated whether our protein was able to catalyze the biosilification reaction. To do that, we drew inspiration for the 2011 Minnesota iGEM team and their work about Si4 to evaluate the silification process. First, we used a source of silicic acid, the tetraethyl orthosilicate (TEOS), which is an inactive form of silicic acid. By activating it in acidic conditions, we released the free silicic acid (Fig. 9A). After incubation with or without our fusion protein, we determined the quantity of free silicic acid by a spectrophotometric method, since biosilification process consumes silicic acid to form silica (Fig. 9B). We clearly observed a precipitation into the test tube, instead of the negative control (Fig. 10A). By quantifying it by molybdate assay using a standard curve (Fig. 10B), we deduced the corresponding mass of silicic acid left after silification: 33 µg. Before silification, the concentration was 208 µg/ml. The fusion protein led to the production of 175 µg of silica after 2 hours. Therefore, the silification yield after two hours is up to 84% with the protein whereas the yield without the protein is 0% (Fig. 10C). We concluded that our protein worked.
Taken together, our results suggest that our fusion protein is able to bind to cellulose and to catalyze biosilification.
Using the modeling approach described in the Protocols section (Patch mechanical properties modeling), we assumed that silica could increase by 48% the Young’s modulus and by 75% the shear modulus of the patch. Thus, our patch would be as rigid as plastics after silification. However, we have to be cautious about our model since we assumed that our protein is linear, which is not the case. Moreover, the rule of mixtures can be applied only when the two materials have the same Poisson’s ratio, but we do not have any evidence of this for C2 and silified C2. Additionnaly, we assumed that all integrated proteins are silified, but we only observed 84% yield, thus generating two states in the system.
Composite patches were obtained with a mix of cellulose and silica gel, either mechanically mixed or produced in the one pot experiment . The resulting composite patches are easier to handle than those with cellulose alone or a mix of cellulose and water. The former resist to manipulation whereas the latter break when they are manipulated.
At the time of this writing, we have sent the patches to the iGEM TU Delft 2016 team to be characterized, by electron microscopy.
Our patch aims at detecting mosquito-borne pathogen antigens. Since the composite patch-protein was not completely assembled, we characterized the efficiency of our detection method by using commercial membranes of PVDF or nitrocellulose. The detection method we designed was based on the conjugation of antigens with the HRP, and the capture of these conjugated antigens by specific antibodies. We revealed interactions by incubating membranes with the HRP’s substrate. First, we tested whether our detection method was working by using single purified viral protein of yellow fever virus (YFVp). By incubating coated membranes with conjugated HRP-BSA, single EZ, or non conjugated YFVp, we didn’t observe any signal (Fig. 11). However, in presence of conjugated HRP-YFVp, a dark spot appeared (Fig. 11). Thus showing that we were able to detect YFVp by this immunodetection technique. Then, in the presence of an excess of non-specific proteins such as BSA, we showed that we maintained the specificity of our detection method (data not shown). To determine whether mosquito proteins can interfere with the specific interaction between viral proteins and specific antibodies, we coated PVDF membranes with CHIKV-specific antibodies, and we conjugated CHIKV envelope protein in presence of an excess of mosquito proteins (from non infected mosquitoes). Then, we incubated coated membranes with conjugated mosquito proteins in the presence or absence of CHIKV envelope protein. We noted a basal level of interaction between the CHIKV-specific antibody 3E4 and mosquito proteins (Fig. 12). However, we noted an important increase of signal when CHIKV envelope protein is present in the mixture. It is obvious that we have to improve the specificity of our detection method in the presence of mosquito lysate. However, these results showed that our detection method worked. We plan to determine the sensitivity of the method by using different amounts of CHIKV envelope proteins in the mixture. Finally, when patches became available, we repeated the experiment on the composite patches (cellulose-silica + fusion protein). By replacing the membrane by the patch, we observed the presence of signal when CHIKV envelope protein is present, but non-specific interactions are clearly visible (Fig. 13). We can explain this observation by the fact that it was difficult to wash patches since they are brittle, Moreover, heterogeneity of degradation between the patches contributed to the fact that we cannot come to a conclusion (signal intensity was measured by mean intensity in regions of interests). In parallel, we did the same experiment to detect YFV envelope protein into infected mosquitoes (day 11 post-infection). As previously, no conclusion can be drawn.
Using similar approaches as in the trap design, a prototype for an analysis station has been 3D printed. It allows us to visualize the analysis process and ergonomy. Sample throughput in the system remains to be tested.
With collaborations, public education, public opinion, polling, we were able to generate a scenario that encompasses the use of our Mos(kit)o device in the real world. Open science vs Start-up model From our meet-ups, discussion with other teams, and our own concern for the transition from Open Science to a possible start-up, we were able to generate two document tools that summarize and inform about these issues.
