Difference between revisions of "Part:BBa K1694033"
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[[File:PROBGFP.png|600px|thumb|center|'''Fig.4''' P<sub>cons</sub>+B0034+Lpp-OmpA-N+scFv(Anti-VEGF)+B0030+GFP+J61048]] | [[File:PROBGFP.png|600px|thumb|center|'''Fig.4''' P<sub>cons</sub>+B0034+Lpp-OmpA-N+scFv(Anti-VEGF)+B0030+GFP+J61048]] | ||
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Revision as of 06:11, 22 September 2015
Pcons+B0034+Lpp-OmpA-N+scFv(Anti-VEGF)+B0030+GFP+J61048
Introduction:
Transformation of single plasmid
To prove that our scFv can actually bind on to the antigen on cancer cells, we connected each scFv with a different fluorescent protein. Therefore we could use fluorescence microscope to clearly observe if the E. coli has produced scFv proteins. Currently,we built three different scFv connected with their respectively fluorescent protein, which are anti-VEGF+GFP, anti-EGFR+RFP, anti-HER2+BFP. When applied on cell staining, we can identify the antigen distribution on cancer cells by observing the fluorescence. Furthermore, if we use the three scFv simultaneously, we can also detect multiple markers.
Experiment
1.Cloning
After assemble the DNA sequences from the basic parts, we recombined each Pcons+B0034+Lpp-OmpA-N+scFv(Anti-VEGF)+B0030+GFP+J61048 gene to pSB1C3 backbones and conducted a PCR experiment to check the size of each of the parts. The DNA sequence length of the these parts are around 2000~2200 bp. In this PCR experiment, the PCR products size should be near at 2200~2400 bp. The Fig.3 showed the correct size of this part, and proved that we successful ligated the sequence onto an ideal backbone.
2. Transformation of single plasmid
(1) Cell staining experiment:
After creating the part of scFv and transforming them into our E. coli, we were going to prove that our detectors have successfully displayed scFv of anti-VEGF. To prove this, we have decided to undergo the cell staining experiment by using our E. coli to detect the VEGF in the SKOV-3 cancer cell lines. SKOV-3 is a kind of epithelial cell that expressed markers such as VEGF.
(2) Staining results:
Modeling
In the modeling part, we discover optimum protein production time by using the genetic algorithm in Matlab.
We want to characterize the actual kinetics of this Hill-function based model that accurately reflects protein production time.
When we have the simulated protein production rate, the graph of protein production versus time can be drawn. Thus, we get the optimum protein production time Compared with the simulated protein production rate of time, our experiment data quite fit the simulation.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12INCOMPATIBLE WITH RFC[12]Illegal NheI site found at 7
Illegal NheI site found at 30 - 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25INCOMPATIBLE WITH RFC[25]Illegal NgoMIV site found at 451
Illegal NgoMIV site found at 2013 - 1000INCOMPATIBLE WITH RFC[1000]Illegal BsaI.rc site found at 1929