Contribution
Hardware Contribution: 3D Printing
Fig. 1. The designed structure of our filtering device
The filter tube is covered by filter paper, which is used to prevent bacterial leakage. We designed filter paper caps to fix the filter paper caps for further prevention of bacterial leakage. The caps have similar sizes to the tube’s opening, as indicated in Fig. 7, so when caps are locked on the tube with filter papers, the filter would be an isolated space. To prevent branches or stones from breaking the filter papers, we added filter webs outside the filter papers’ cabs and designed filter webs’ caps to fix the webs on the tube. The caps’ design and 3D printing are documented for future iGEM teams to reference when developing prototypes for their implementation device.
Fig. 2. The design of the cap for the filter
We chose to use Acrylonitrile Butadiene Styrene (ABS) as the material of the 3D-printed caps because it is acid, base, and heat resistant, especially to phosphoric acid, which eutrophic water has a high concentration of. Therefore, when placed into the reservoirs, the caps made out of abs can keep the filter papers intact and prevent bacteria leakage.
How do we design the caps?
Here is a video about how we utilize 3D-printed caps in the design.
For more information about the hardware, please visit our Hardware Page.
Model Contribution
Our model was built to explain the results from the proof of concept experiment of the designed part organophosphorus hydrolase (OPH), in which the ability of optimized conditions for OPH to hydrolyze paraoxon (a form of organic phosphate pollutant) into p-nitrophenol (pNP) was tested. Due to the fact that the OPH construct (Part: BBa_K4271001) we engineered was recently published, there are limited resources regarding this variant of OPH. Among these studies on this OPH, there was no research that provides quantitative analysis for this OPH. Therefore we contributed to this OPH part by fitting our experimental data with our model to evaluate the rate reaction constants of this OPH quantitatively. We constructed this model using Enzyme Kinetics. On this basis, there are three reactions concerning OPH. One of them is the reversible reaction of paraoxon PXN binding with OPH, forming the complex OPH::PXN. The reaction rate constants for this reaction are kOPH_PXN_f and kOPH_PXN_r, denoting the forward and reverse reactions, respectively. The rest of the reactions are hydrolysis and degradation; their reaction rate constants are khydro, and kdOPH respectively. We used data collected in the experimentation of the OPH function under different concentrations of IPTG induction and fitted them with the model we constructed and yielded the values summarized in the table below.
Fig. 3. Proposed reaction rate constants
We then used these constants to simulate a pNP curve for any other experimental data. The curve was plotted with the data and proved that our proposed kinetics are reasonable.
Fig. 4. pNP simulation curve
For more information about the model, please visit our Dry Lab (Model) Page.
Wet Lab Contribution
In order to detect the degree of paraoxon degradation by our target protein OPH into p-nitrophenol (pNP), we designed a biosensor based on the existing part: superfolder GFP coding sequence (Part: BBa_I746916 ). Our construct design (BBa_4271008) was based on a research paper published in Nucleic Acids Research (Jha, Ramesh K., et al.). The pNP sensor indicates the amount of pNP produced during OPH hydrolysis via GFP fluorescence.
Fig. 5. The linear map of our pNP sensor plasmid
Our sensor plasmid includes a dual-directional pobA/R promoter, pNP RBS, sfGFP, pobR operator, pNPmut1-1, and two double terminators that are composed of RrrnB1 terminator and T7 terminator
Fig. 6. Theoretical function of our biosensor upon IPTG induction (created by BioRender):
Our biosensor contains an enzyme plasmid and a sensor plasmid that would enhance GFP expression, thereby indicating the amount of paraoxon detoxified by OPH
After cultivating normal E.coli colonies and E.coli engineered with the biosensor in the absence and presence of pNP, the result we acquired from the experiment was not consistent with the data published in the paper (Jha et al., 2016). The observed differences between the levels of GFP fluorescence before and after adding 125 µM of pNP were not significant enough to prove the effectiveness of the biosensor.
Groups Fluorescence
DH5alpha
24870
DH5alpha + pNP
20650
DH5alpha-sensor
46867
DH5alpha-sensor + pNP
50783
Fig. 7. GFP fluorescence level of DH5 alpha and DH5 alpha with biosensor in the absence/presence of pNP
Since the genetic organization and sequence of our pNP sensor is identical to the plasmid design in the research paper, we concluded that there might be an error in the biosensor design. We believe this discovery would benefit and contribute to future research related to the application of the pNP biosensor.
For more information about the pNP biosensor design and experiments, please visit our Engineering Success Page .
References
Ramesh K. Jha, Theresa L. Kern, Youngchang Kim, Christine Tesar, Robert Jedrzejczak, Andrzej Joachimiak, Charlie E. M. Strauss, A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription factor, Nucleic Acids Research, Volume 44, Issue 17, 30 September 2016, Pages 8490–8500, https://doi.org/10.1093/nar/gkw687