Difference between revisions of "Part:BBa K4271001"

Revision as of 12:00, 7 October 2022 (view source) EthanClarke (Talk | contribs) ← Older edit		Revision as of 12:05, 7 October 2022 (view source) EthanClarke (Talk | contribs) Newer edit →
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	<td> 0.2323266987 </td>		<td> 0.2323266987 </td>
	<td> 0.3905284832 </td>		<td> 0.3905284832 </td>
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−	<td>Replicate 3</td>
−	<td> 35.8 </td>
−	<td> 64.2 </td>
	<td> <img src="https://static.igem.wiki/teams/4271/wiki/3.jpg" width=40% style="border: 1px solid black;"> </td>		<td> <img src="https://static.igem.wiki/teams/4271/wiki/3.jpg" width=40% style="border: 1px solid black;"> </td>
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Revision as of 12:05, 7 October 2022

T7 Promoter + Lac operator + RBS + OPH + T7 terminator

This sequence is responsible for the regulation and expression of the OPH gene. The T7 promoter, transcribed by only the T7 RNA polymerase, identifies the sequence downstream and enables fast and effective transcription. We further designed a lac operon, so that upon IPTG induction, the lacI repressor protein will be detached from the lacI gene, leading to the transcription and translation of our target oph gene. The ribosome binding site (RBS) is where the ribosome bind on the mRNA for translation. This RBS is taken from the pET22B vector. OPH a gene that encodes organophosphate hydrolase, paraoxon, a type of organic phosphate and insecticide. The product of the paraoxon degradation, pNP, will be detected to evaluate the efficacy of the gene. The T7 terminator identifies the end of the transcription sequence.

Engineering

Build:

Synthetic oph gene we used in this study is derived from the opd (organophosphate degradation) gene in Agrobacterium tumefaciens and performed with codon usage optimization for E. coli heteroexpression. We digested the oph gene with BamHI and HindIII, subcloned it to pET22b vectors that underwent the same restriction enzyme digestion, then transformed the recombinant into E. coli DH5α. The transformation was conducted by plasmid extraction through mini-prep.

We later confirmed the insertion of our oph gene into the enzyme plasmid by enzyme digestion, cutting the recombinant DNA with BamHI and HindIII respectively, and observing the same band sizes of 6.5 kilobases after gel electrophoresis (left). We later digested our pET22b::OPH again with both BamHI and HindIII, two of resulting DNA bands include the 1071 base-long oph and the 5479 base-long pET22b vector (right). Finally, the plasmid was transformed into the competent cells E.coli BL21(DE3) via heat shock, which we later used to examine the level of paraoxon degradation by our enzyme plasmid.

Test:

To confirm the efficiency of our pNP sensor in determining the amount of pNP produced, we measure the GFP fluorescence of E. coli BL21 (DE3) with and without pNP sensor in the presence and absence of pNP.

Analysis of Result:

The result we acquired from the experiment is not consistent with the data previously published (Jha, Ramesh K., et al.). The difference in the level of GFP fluorescence with and without adding 125 µM of pNP is not significant enough to prove the effectiveness of our pNP sensor (Jha, Ramesh K., et al.). Given that the genetic organization and sequence of our pNP sensor is identical to the plasmid design in the research paper, we went back to further examine and check the pNP sensor design. As a result, we discovered the lack of commonly used RBS sequence in front of pNPmut1-1 in the sensor plasmid, from which we inferred that the poor transcription of pNPmut1-1 might be the reason behind the relatively weak and undetectable green fluorescence signals. In Redesign, we are planning to insert RBS by flanking 4 bases apart from the start codon of pNPmut1-1 in the pNP sensor backbone to further observe if GFP expression will increase in the presence of the same amount of pNP.

	(Absorbance at 410nm - background data)/ OD600	(Supernatant Absorbance at 410nm - background data)/ OD600
1. BL2(DE3) (negative control)	0	0
2. BL2(DE3) +paraoxon (experimental)	0.2323266987	0.3905284832
3. BL2(DE3) +pNP (positive control)	8.905950096	9.966890595
4. PET::OPH +IPTG induction (negative control)	0	0
5. PET::OPH +paraoxon +IPTG induction (experimental)	6.720481928	6.916144578
6. PET::OPH +pNP +IPTG induction (positive control)	11.83912249	12.51005484

The results met our expectations as the pNP concentration increased over time, showing that paraoxon is being degraded by the E.coli BL21(DE3) steadily. However, pNP concentration seems to increase rapidly only in the first 5 hours of observation, after which it proceeds to grow steadily, which demonstrates that the enzyme reaches optimal activity after 5 hours of culture. We later measured the pNP concentration under exposure of different concentrations of IPTG. We discovered that the concentration of pNP reaches a maximum amount when around 250 μM of IPTG is introduced into E.coli BL21(DE3) engineered with OPH. We also inferred from the data that after pNP concentration reaches a maximum at 250μM of IPTG induction, the amount of pNP will not increase as the concentration of IPTG increases.

Model

Due to the recently published nature of the OPH we used, 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 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 reaction respectively. The rest of the reactions are hydrolysis and degradation; their reaction rate constants are khydro, and kdOPH respectively. We used data collected from different IPTG concentrations and fitted them with the model we constructed and yielded the values summarized in the table below.

Then we 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.

References:

Jha, Ramesh K., et al. “A Microbial Sensor for Organophosphate Hydrolysis Exploiting an Engineered Specificity Switch in a Transcription Factor.” Nucleic Acids Research, vol. 44, no. 17, 2016, pp. 8490–500. Crossref, https://doi.org/10.1093/nar/gkw687.

Sequence and Features