Part:BBa_K4734005
RBHS iGEM Designed Epitope for T. Gondii
Usage and Biology
Our project primarily functions based on being able to use the functional epitopes of the tyrosine-rich oocyst wall protein (TrOWP2) derived from Toxoplasma Gondii to produce an immunological response from the cat, thus preventing future toxoplasmosis and reducing shedding of the parasite into the environment. The peptides that comprise linear B-cell epitopes can be used in place of antigens when producing antibody responses via immunization. As such, we can attach an epitope peptide sequence to our phage-based vaccine in order to effectively immunize the cat. To better understand and determine the locations of these epitopes, we used several web-based software in order to predict, as well as visualize the location of the antigen’s epitope region.
Three web based computational epitope prediction tools were used. Bepriped, then ABCpred and SVMTriP software’s were used to determine, and then additionally validate the sequence of the epitope from the given wall protein antigen sequence we found. Bepried was used in the initial determination of the epitope sequence. As protein structures contain approximately the same amount of hydrophilic and hydrophobic residues, as well as comparing scales for surface accessibility, flexibility, and β-propensity, multi algorithmic programs such as those run by the IEDB’s Bepried can be used to determine the potential epitope region based on the hydrogen bond driven secondary structure characteristics of the amino acid from the sequence. We were able to get an initial prediction of 18 potential peptides in varying locations from the antigen sequence:
In order to become more specific in determining the epitope region, as well as to validate which of the potential peptide regions were most likely to be the functional epitope, we turned to two additional web-based software’s in ABCpred and SVMtrip. These models, primarily developed on the basis of machine learning algorithms, consist of artificial neural networks utilizing positive data training models, though for ABCpred specifically random peptides were used as negative data. Such ML base systems have been found to, in certain instances, produce greater accuracy than propensity scales, while others show little improvement, however the difference in training data does allow this as an effective method to additional validate the results. We determined a 15 amino acid long peptide sequence that shared high confidence intervals and properties from all three servers of Bepried, ABCpred, and SVMtrip, with confidence intervals stated at .555, .94, and 1 from each server respectively.
Using the newfound sequence FKCAEGTTETIDGDCKRLKQFPP, Alpha Fold via the collabfold web server was used to produce 3D protein models that we could then use for additional analysis of the epitope’s properties based on the structure. Below is the predicted 3D structure for the epitope from the amino acid sequence:
Using the 3D structure and PDB file, we were able to utilize the web-based computational mapping server FTMap in order to determine binding hotspots that could additionally be used for binding studies to help further validate the effectiveness of the epitope. FTMap has greater accuracy than classical mapping methods, being developed as computational analogues of X-ray crystallography experiments, using 16 probes to determine binding hotspots. This is particularly relevant as epitope mapping in experimental settings can often be carried out via x ray crystallography. Once regions that are capable of binding several probed (Consensus sites, CSs) are determined, being a fundamental property of the protein structure, sequences that are easily susceptible to bound and unbound interactions can be later used to help determine likelihood of antigen bonding. Below are the locations shown to be hot spots for binding in the protein structure, as well as locations in the sequences for unbound structures.
The following protocol can be followed to insert the epitope on the phage:
Extend the annealed duplex as follows (mix in the given order) H2O: 119 µl 10X NEBuffer 2: 20μl annealed duplex: 50μl 10 mM dNTP's: 8μl Klenow fragment (NEB #M0210 ) (5 Units/µl ): 3μl Total: 200 µl Incubate at 37°C for 10 minutes, then 65°C for 15 minutes. Save 4 µl for later analysis (Step 5).
The extended duplex is then cut using EagI and either, KpnI or Acc65I. We favor digestion as follows:
Extension reaction: 196 µl
H2O: 158 μl
10X NEBuffer 2: 40 μl
EagI-HF (NEB #R3505 ) (10 Units/µl ): 5 μl
KpnI (NEB #R0142 ) (10 Units/µl ): 6 μl
Total: 400 µl
Extension reaction: 196 µl H2O: 154 μl 10X NEBuffer 4: 40 μl EagI-HF (NEB #R3505 ) (10 Units/µl ): 5 μl KpnI-HF (NEB #R3142 ) (10 Units/µl ): 5 μl Total: 400 µl Incubate at 37°C for 3–5 hours.* Purify the DNA by phenol/chloroform extraction, chloroform extraction and ethanol precipitation.
- EagI-HF is not recommended for > 1 hour digestions.
The ligated phage can then be transformed in F+ bacteria.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000COMPATIBLE WITH RFC[1000]
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