Revision as of 07:22, 22 September 2015

Pcons+B0034+Lpp-OmpA-N+scFv(Anti-HER2)+B0034+amilCP+B0015

Introduction

To observe that our scFv can bind onto the cancer cells, we connected each scFv with different chromoprotein. Color proteins are commonly used as reporter gene for observation. However, chromoproteins can be conveniently observed by naked eye without the help of instruments. Therefore, when we conducted cell staining experiment, we can observe the binding distribution by color right after the experiments have finished.

Experiment

1.Cloning

Fig.2 The PCR result of the Pcons+B0034+Lpp-OmpA-N+scFv+B0034+amilCP+B0015. The DNA sequence length is around 2000~2100 bp, so the PCR products should appear at 2200~2300 bp.

After assemble the DNA sequences from the basic parts, we recombined each Pcons+B0034+Lpp-OmpA-N+scFv+B0034+amilCP+B0015 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 2000~2100 bp. In this PCR experiment, the PCR products size should be near at 2200~2300 bp. The Fig.3 showed the correct size of this part, and proved that we successful ligated the sequence onto an ideal backbone.

Fig.3 Pcons+RBS+OmpA-scFv(Anti-HER2)+RBS+amilCP+Ter

2.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.

Fig.20 As results,there is no blue chromoprotein E. coli stick on the cell’s surface as there is no specific scFv displayed around the E. coli.

Fig.21 There are blue chromoprotein anti-VEGF E. coli stick on the cell’s surface as the anti-VEGF probes on E. coli successfully detect and bind with VEGF.

Modeling

In the modeling part, we discover optimum protein expression time by using the genetic algorithm (GA) in Matlab.
We want to characterize the actual kinetics of this Hill-function based model that accurately reflects protein expression time.
By using the differential function which was derived from these optimum parameters which were calculated by GA can help us to simulate the optimum protein expression. When we have the simulated protein expression rate, the graph of protein expression versus time can be drawn.Thus, we can find the optimum protein expression time. However, the simulated protein expression curve is slower than the experimental curve by one hour. Therefore, to find the most exact optimum protein expression time, we infer that subtracting one hour of the optimum protein expression time would be correct.

From this graph, the orange curve is the simulated protein expression. The blue curve is our experimental data. By comparing the orange curve and the blue curve, the blue curve quite fit the simulation. The orange curve reaches peak after growing about 11 hours.Thus, we can know that the E.Cotector can have maximum efficiency at this point.

Sequence and Features