Revision as of 20:11, 20 September 2015

Single-chain variable fragment (Anti-HER2)

Introduction:

ScFv (Single-Chain Variable Fragment)

Fig.1 Single-chain variable fragment and A coding gene of scFv (anti-VEGF)

ScFv (single-chain variable fragment) is a fusion protein containing light (VL) and heavy (VH) variable domains connected by a short peptide linker (Fig. 1) The peptide linker (GGSSRSSSSGGGGSGGGG) is rich in glycine and serine which makes it flexible.

Features of scFv:

1. Specific：Though remove of the constant regions , scFv still maintain the specificity of the original immunoglobulin.

2. Efficient：ScFv is smaller than the entire antibody, so that the loading of production to E. coli is lower.

HER2

Human epidermal growth factor 2, abbreviated as Her2 or EtbB2, belongs to the ErbB receptor tyrosine kinase fam ily, which is composed of four plasma membrane-bound receptor tyrosine kinases including the other three receptors, epidermal growth factor receptor(EGFR), erbB-3 (neuregulin-binding), and erbB-4

1.Herceptin inhibition
Herceptin works by binding to the HER2 receptors on the surface of breast cancer cells, preventing them from transforming the cell growth signals and slow or cease the growth of the breast cancer. Moreover, Herceptin flags the HER2 receptors and strikes these receptors by the assistance of the immune system.
2.HER2 activation
HER2 is one of the members in the human epidermal growth factor receptor family. HER2 can heterodimerize with any other three receptors in the ErbB family to form the dimerization, which consequently results in the autophosphorylation and initials the signaling pathway. When the amplification or overexpression of the HER2 gene occurs, it may cause the development and progression of certain types of the breast cancer.

Fig. 3. (1.) Herceptin inhibition mechanism (2.) HER2 activation mechanism

Reference:
1.http://www.biooncology.com/biological-pathways/her-signaling
2.http://www.cellsignal.com/contents/science-pathway-research-tyrosine-kinase/erbb-her-signaling-pathway/pathways-erbb
3.[ ]Mark M. Moasser , The oncogene HER2; Its signaling and transforming functions and its role in human cancer pathogenesis, Oncogene. Author manuscript; available in PMC 2011 January 14.

ErbB receptor family

Which are typical cell membrane receptor tyrosine kinases that are activated following ligand binding and receptor dimerization. Especially Her2 lacks a ligand, and its structure resembles a ligand-activated state and favors dimerization. The formation of dimers leads to activation of the intrinsic tyrosine kinase domain and subsequent phosphorylation on specific tyrosine residues, which serve as docking sites for a variety of molecules. Recruitment of these molecules leads to the activation of different downstream signaling cascades, including the MAPK proliferation pathway and/or the PI3K/Akt pro-survival pathway. Inappropriate signaling may occur as a result of receptor overexpression or dysregulation of receptor activation, which may lead to Increased/uncontrolled cell proliferation, decreased apoptosis (programmed cell death), enhanced cancer cell motility, and angiogenesis

The oncogene amplify or overexpress play an important role in development and progression of aggressive types of breast cancer. Her2 amplifications are seen in breast, ovarian, bladder, Non-small-cell lung carcinoma, as well as several other tumor types.HER2 proteins have been shown to form clusters in cell membranes that may play a role in tumorigenesis.

Display scFv on the cell surface of E. coli

To display the antibody outside the E. coli, we used Lipoprotein-Outer membrane protein A (Lpp-OmpA). According to the paper reference [1], We chose the first 9 amino acid of Lpp, and the 46~159 amino acid of OmpA.
In order to change the scFv parts easily, we added a NcoI restriction site between OmpA and scFv so that we can change various scFv DNA sequence using the NcoI restriction enzyme.
The Fig.2 showed how we combine Lpp-OmpA-N and scFv together, first we use restriction enzyme NcoI to digest the upstream and downstream parts. After ligate two digest product, there are no M site in Lpp-OmpA-N-scFv.

Fig.2 The combination of Ompa-N-scfv

Fig.3 Ompa-N-scfv

See this composite part:BBa_K1694015
Reference:
[1]Improving tumor targeting and therapeutic potential of Salmonella VNP20009 by displaying cell surface CEA-specific antibodies, Michal Bereta, Andrew Hayhurst, Mariusz Gajda, Paulina Chorobik, Marta Targosz, Janusz Marcinkiewicz, Howard L. Kaufman (2007)

Experiment:

Fig.4 The PCR result of the scFv. The DNA sequence length of scFv are around 700~800 bp, so the PCR products should appear at 900～1000 bp.

After receiving the DNA sequences from the gene synthesis company, we recombined each scFv gene to PSB1C3 backbones and conducted a PCR experiment to check the size of each of the scFvs. The DNA sequence length of the scFvs are around 600~800 bp. In this PCR experiment, the scFv products size should be near at 850~1050 bp. The Fig. showed the correct size of the scFv, and proved that we successful ligated the scFv sequence onto an ideal backbone.

Fig.5scFv(Anti-HER2)

Application of the part:

1. Co-transform (Two plasmids)

This year we want to provide a customized platform. We provide two libraries of Pcon+RBS+OmpA-scFv and Pcons+RBS+Fluorescence+Ter into E. coli. Therefore, our customers can choose any scfv and any fluorescence protein. Our team will then co-transform the two plasmids, which helps us tailor our product to the wishes of our customers.

(1) Parts:

Fig.5 Co-transform (Two plasmids)

Pcons+RBS+Lpp-OmpA-N+Anti-EGFR

Fig.7 Pcons+RBS+RFP+Ter

Fig.8 Pcons+RBS+GFP+Ter

(2) Cell staining experiment:

After cloning the part of anti-HER2, we were able to co-transform anti-HER2 with different fluorescence protein into our E. coli.
The next step was to prove that our co-transformed product have successfully displayed scFv of anti-HER2 and expressed fluorescence protein.
To prove this, we conducted the cell staining experiment by using the co-transformed E. coli to detect the HER2 in the cancer cell line.

(3) Staining results：

Fig.9 As results,there is no red fluorescent E. coli stick on the cell’s surface as there is no specific scFv displayed around the E.coli.

There are red fluorescent anti-HER2 E. coli stick on the cell’s surfaces as the anti-HER2 probes on E. coli successfully detect and bind with HER2.

Fig.11 As results,there is no green fluorescent E. coli stick on the cell’s surface as there is no specific scFv displayed around the E.coli.

There are green fluorescent anti-HER2 E. coli stick on the cell’s surfaces as the anti-HER2 probes on E. coli successfully detect and bind with HER2.

2. 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 fluorescence 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 fluorescence protein. 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.

(1) Parts:

Fig.13 Transformation of single plasmid

Pcons+RBS+Lpp-OmpA-N+Anti-HER2+RBS+RFP+Ter

Pcons+RBS+Lpp-OmpA-N+Anti-HER2+RBS+GFP+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-HER2. To prove this, we have decided to undergo the cell staining experiment by using our E. coli to detect the HER2 in the SKOV-3 cancer cell lines. SKOV-3 is a kind of epithelial cell that expressed markers such as HER2.

(3) Staining results：

Fig.16 As results,there is no red fluorescent E. coli stick on the cell’s surface as there is no specific scFv displayed around the E. coli.

There are red fluorescent anti-HER2 E. coli stick on the cell’s surface as the anti-HER2 probes on E. coli successfully detect and bind with HER2.

Fig.18 As results,there is no green fluorescent E. coli stick on the cell’s surface as there is no specific scFv displayed around the E. coli.

There are green fluorescent anti-HER2 E. coli stick on the cell’s surface as the anti-HER2 probes on E. coli successfully detect and bind with HER2.

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-EGFR E. coli stick on the cell’s surface as the anti-EGFR probes on E. coli successfully detect and bind with EGFR.

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 (Fig.1) (Fig.2) (Fig.3). Thus, we get the optimum protein production time Compared with the simulated protein production rate of time, our experiment data quite fit the simulation.

Co-transform

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 18 hours. Thus, we can know that the E. Cotector can have maximum efficiency at this point.

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 15 hours. Thus, we can know that the E. Cotector can have maximum efficiency at this point.

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 15 hours. Thus, we can know that the E. Cotector can have maximum efficiency at this point.

Sequence and Features