Team:Rio UFRJ Brazil/Design
Design
A rational approach for designing diagnostic antigens
Multi-epitope proteins (MEP) have been usually explored for the production of vaccines (some past iGEM teams such as (AFCM-Egypt 2020) and (Slovenia 2018) have used them in their projects with this goal). However, their potential to be explored as promising antibody probes for serodiagnostic uses is still emerging.
There are already some studies proposing using this approach for the diagnostics of different pathogens such as Toxoplasma gondii and Trypanossoma cruzi [1,2]. Regarding arboviral infections such as Dengue, there are two important studies conducted by Anandarao and collaborators, in which the researchers designed MEPs for capturing anti-Dengue IgG and IgM antibodies [3,4]. Those studies have shown that using this strategy has many advantages:
Despite the fact that the Dengue MEPs studies argue that an increase in specificity can be achieved using this approach, they have not evaluated experimentally the possibility of their antigens to cross-react with antibodies induced during other arboviral infections such as Zika and Yellow Fever.
Since cross-reaction is a known problem as explained on the Project description page, we decided to propose a new strategy for diagnostic antigen design, based on the Design, Build, Test, and Learn cycle. Since Dengue is a relevant public health burden in our country Brazil, we decided to test our strategy for developing an antigen for this arbovirose detection.
Beginning with an initial Dengue epitope pool (used by AnandaRao and collaborators [3,4]), we ran sequence and structural alignments between those epitopes and their corresponding sequence in Zika and Yellow fever proteome in order to select the ones with the least chance of cross-reaction. After epitope selection, we also chose the best linker to join them and the order in which they should be combined. For evaluating protein structure and its ability to bind to antibodies, we used modeling tools such as PSIPRED and Cluspro, besides analyzing exposed epitope regions through a hydrophobicity plot.
Since we identified some differences between the sequence of those epitopes published in those studies when comparing to Brazilian strains sequences, we also decided to design a mutated MEP, in which some residues were replaced. This way we could evaluate if those differences could cause some kind of impact on antibody recognition. For details about epitope selection, chosen residues for mutation, and protein design, check the (Engineering Page).The whole pipeline we used is summarized below.
There are already some studies proposing using this approach for the diagnostics of different pathogens such as Toxoplasma gondii and Trypanossoma cruzi [1,2]. Regarding arboviral infections such as Dengue, there are two important studies conducted by Anandarao and collaborators, in which the researchers designed MEPs for capturing anti-Dengue IgG and IgM antibodies [3,4]. Those studies have shown that using this strategy has many advantages:
- It is a safer alternative than producing whole viruses antigens, which are produced in tissue culture and, depending on the Biosafety level of the pathogens, may require specialized laboratory infrastructure for manipulation [4].
- It might lower production costs since MEPs can be produced in cheaper expression platforms such as bacterial chassis [4].
- It enables careful and balanced choice of specific epitopes and a higher epitope density [1,4].
- It is more sensible in terms of signal than using single recombinant or synthetic peptides. Although a solution constituted of a peptide mixture might increase the sensitivity, still, there would be costs associated with the production and purification of each of them separately. Expressing all those epitopes at once using a ME protein contributes to lowering those costs [1].
Despite the fact that the Dengue MEPs studies argue that an increase in specificity can be achieved using this approach, they have not evaluated experimentally the possibility of their antigens to cross-react with antibodies induced during other arboviral infections such as Zika and Yellow Fever.
Since cross-reaction is a known problem as explained on the Project description page, we decided to propose a new strategy for diagnostic antigen design, based on the Design, Build, Test, and Learn cycle. Since Dengue is a relevant public health burden in our country Brazil, we decided to test our strategy for developing an antigen for this arbovirose detection.
Beginning with an initial Dengue epitope pool (used by AnandaRao and collaborators [3,4]), we ran sequence and structural alignments between those epitopes and their corresponding sequence in Zika and Yellow fever proteome in order to select the ones with the least chance of cross-reaction. After epitope selection, we also chose the best linker to join them and the order in which they should be combined. For evaluating protein structure and its ability to bind to antibodies, we used modeling tools such as PSIPRED and Cluspro, besides analyzing exposed epitope regions through a hydrophobicity plot.
Since we identified some differences between the sequence of those epitopes published in those studies when comparing to Brazilian strains sequences, we also decided to design a mutated MEP, in which some residues were replaced. This way we could evaluate if those differences could cause some kind of impact on antibody recognition. For details about epitope selection, chosen residues for mutation, and protein design, check the (Engineering Page).The whole pipeline we used is summarized below.
Choosing an expression system
In the end, we used two proteins: DME-C, with the chosen epitopes with their unchanged sequences, and DME-BR, which contains some mutations highlighted in Figure 2, in order to make the sequence more identical to the conserved Dengue Brazilian strain proteome.
In order to allow purification, we have added a 6 histidine tag at the carboxyl-terminus so we could use a metal chelate affinity chromatography. This type of downstream method is commonly used for heterologous protein purification and can yield up to 95% purity [5]. The final DME-C and DME-BR sequences are shown below (Table 1).
In order to allow purification, we have added a 6 histidine tag at the carboxyl-terminus so we could use a metal chelate affinity chromatography. This type of downstream method is commonly used for heterologous protein purification and can yield up to 95% purity [5]. The final DME-C and DME-BR sequences are shown below (Table 1).
Since we used only linear B-cell epitopes, whose recognition did not depend on post-translational modifications, we decided to express both DME-C and DME-BR in Escherichia coli using a pET plasmid.
The pET plasmid family is commonly used for high-level expression of recombinant protein in E. coli strains that have a lysogenised DE3 phage fragment encoding the T7 RNA polymerase in their genome such as BL21(DE3) [6]. In this vector, the target gene expression is regulated by a T7 promoter (recognized by the T7 RNA polymerase) and an adjacent lac operator sequence, which helps to prevent leaked expression. The ribosome binding site (RBS) corresponds to the Shine–Dalgarno sequence from the capsid protein of T7, which is highly efficient [6,7]. In addition, this vector family uses the T7 terminator, which encodes an RNA sequence that forms a stem-loop responsible for the transcription interruption [8].
Because of those features, this vector was the one chosen by us (Figure 3).
We initially were having questions regarding which pET vector to use, specifically regarding which selection marker to use, ampicillin or kanamycin. After consulting Professor Marcius Almeida from UFRJ, a specialist in recombinant protein expression, we decided to use pET-28a(+) (Figure 2), since according to him, industrially, kanamycin is preferable because of ampicillin degradation with time (Check the (Human Practices) Page for more information).
Regarding the host, we chose the BL21(DE3) E. coli strain, commonly used with pET vectors for recombinant protein expression. As mentioned before, it has a lysogenised DE3, which is a lambda phage derivative and carries a DNA fragment with the lacI gene, the lacUV5 promoter, and the gene for T7 RNA polymerase [7]. Since the lacUV5 promoter inducible by isopropyl-β-D-thiogalactopyranoside (IPTG), in the presence of this molecule, the T7 RNA polymerase is expressed, thus inducing the target gene in the pET vector expression [6,7].
We decided to order at Genscript both DME-C and DME-BR synthesis already cloned in the pET-28a(+), using NcoI restriction site at the 5’ sequence end and BamHI restriction site at the 3’ end. The sequences were codon-optimized for expression in E. coli using the Genscript online tool, avoiding NcoI, BamHI, EcoRI, SpeI, XbaI, and PstI restriction sites inside the coding sequence in order to make the sequence compatible with Biobrick Assembly.
We decided to order at Genscript both DME-C and DME-BR synthesis already cloned in the pET-28a(+), using NcoI restriction site at the 5’ sequence end and BamHI restriction site at the 3’ end. The sequences were codon-optimized for expression in E. coli using the Genscript online tool, avoiding NcoI, BamHI, EcoRI, SpeI, XbaI, and PstI restriction sites inside the coding sequence in order to make the sequence compatible with Biobrick Assembly.
References
1- Camussone C, Gonzalez Verónica, Belluzo María S., Pujato N, Ribone María E., Lagier CM, et al. Comparison of recombinant trypanosoma cruzi peptide mixtures versus multiepitope chimeric proteins as sensitizing antigens for immunodiagnosis. Clinical and Vaccine Immunology. 2009;16(6):899–905.
2- Hajissa K, Zakaria R, Suppian R, Mohamed Z. Design and evaluation of a recombinant multi-epitope antigen for serodiagnosis of Toxoplasma gondii infection in humans. Parasites & Vectors. 2015;8(1).
3- AnandaRao R, Swaminathan S, Fernando S, Jana AM, Khanna N. A custom-designed recombinant multiepitope protein as a dengue diagnostic reagent. Protein Expression and Purification. 2005;41(1):136–47.
4- AnandaRao R, Swaminathan S, Fernando S, Jana AM, Khanna N. Recombinant multiepitope protein for early detection of dengue infections. Clinical and Vaccine Immunology. 2006;13(1):59–67.
5- Hengen PN. Purification of his-tag fusion proteins from escherichia coli. Trends in Biochemical Sciences. 1995;20(7):285–6.
6- Shilling PJ, Mirzadeh K, Cumming AJ, Widesheim M, Köck Z, Daley DO. Improved designs for pet expression plasmids increase protein production yield in escherichia coli. Communications Biology. 2020;3(1).
7- Novagen. pET System Manual. 8th ed. Novagen; 1999. Available at: < https://research.fredhutch.org/content/dam/stripe/hahn/methods/biochem/pet >
8- Macdonald LE, Durbin RK, Dunn JJ, McAllister WT. Characterization of two types of termination signal for bacteriophage T7 RNA polymerase. Journal of Molecular Biology. 1994;238(2):145–58.
2- Hajissa K, Zakaria R, Suppian R, Mohamed Z. Design and evaluation of a recombinant multi-epitope antigen for serodiagnosis of Toxoplasma gondii infection in humans. Parasites & Vectors. 2015;8(1).
3- AnandaRao R, Swaminathan S, Fernando S, Jana AM, Khanna N. A custom-designed recombinant multiepitope protein as a dengue diagnostic reagent. Protein Expression and Purification. 2005;41(1):136–47.
4- AnandaRao R, Swaminathan S, Fernando S, Jana AM, Khanna N. Recombinant multiepitope protein for early detection of dengue infections. Clinical and Vaccine Immunology. 2006;13(1):59–67.
5- Hengen PN. Purification of his-tag fusion proteins from escherichia coli. Trends in Biochemical Sciences. 1995;20(7):285–6.
6- Shilling PJ, Mirzadeh K, Cumming AJ, Widesheim M, Köck Z, Daley DO. Improved designs for pet expression plasmids increase protein production yield in escherichia coli. Communications Biology. 2020;3(1).
7- Novagen. pET System Manual. 8th ed. Novagen; 1999. Available at: < https://research.fredhutch.org/content/dam/stripe/hahn/methods/biochem/pet >
8- Macdonald LE, Durbin RK, Dunn JJ, McAllister WT. Characterization of two types of termination signal for bacteriophage T7 RNA polymerase. Journal of Molecular Biology. 1994;238(2):145–58.
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