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.
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