Biotechnological
Communication
Biosci. Biotech. Res. Comm. 9(2):
Design and in silico analysis of pentavalent chimeric antigen against three enteropathogenic bacteria: enterotoxigenic E. coli, enterohemorragic E. coli and Shigella
Abbas Hajizade1, Firouz Ebrahimi*2, Jafar Amani3, and Ayoob Arpanaei4,
Ali Hatef Salmanian*5
1Applied Biotechnology Research Centre, Baqiyatallah University of Medical Sciences, Tehran, Iran, 2Biology Research Centre, Faculty of Basic Sciences, Imam Hossein University, Tehran, Iran,
3Applied Microbiology Research Centre, Baqiyatallah University of Medical Sciences, Tehran, Iran,
4Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
5Plant biotechnology Department, National Institute for Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran,
ABSTRACT
Astonishing improvements in information technology, in combination with the valuable experimental data gathered during the past decades, has revolutionized vaccine design strategies. On the other hand, the development of genetic engineering methods has enabled us to design and produce new chimeric proteins for many different purposes, including immunization. In this study we took the advan- tages of these improvements to develop an efficacious vaccine against three important enteropathogenic bacteria: enterotoixigenic E. coli (ETEC), enterohemorragic E. coli (EHEC), and Shigella. To do this, appropriate immunogens, including subunit B of heat labile toxin and mutated STa toxin from ETEC; EspA and Stx B from EHEC; and the
KEY WORDS: CHIMERIC ANTIGEN, IN SILICO ANALYSIS, CANDIDATE VACCINE DESIGN, ETEC, EHEC, SHIGELLA
ARTICLE INFORMATION:
*Corresponding Author: Salman@nigeb.ac.ir, febrhimi@ihu.ac.ir Received 31st May, 2016
Accepted after revision 25th June, 2016 BBRC Print ISSN:
Thomson Reuters ISI SCI Indexed Journal NAAS Journal Score : 3.48
© A Society of Science and Nature Publication, 2016. All rights225 reserved.
Online Contents Available at: http//www.bbrc.in/
Abbas Hajizade et al.
INTRODUCTION
Information technology has revolutionized almost all fields of sciences and technologies, including vaccinol- ogy and vaccine development strategies (Lund 2005). There are many authentic software and programs that could serve as powerful tools for rational designe of new vaccines. There are such tools in almost all steps of a vaccine design project, from determination of a hypo- thetical immunogen structure (Pollastri and Mclysaght 2005, Yang, Yan et al. 2015) to the evaluation of its inter- action with cells and molecules of immune system (Saha and Raghava 2004, EL‐Manzalawy, Dobbs et al. 2008). By applying these tools, the time and costs of a vac- cine development project will be dramatically reduced. Indeed, we proceed through a project clearly, and as a result, we are able to manipulate the project more effi- ciently. Having hypothetical antigens of a pathogen, it is possible to evaluate the effectiveness of these anti- gens as candidate vaccines and choose the most potent ones for in vivo analysis, (Davies and Flower 2007 and Sharma, et al. 2016).
By doing more researches and gathering more experi- mental data, in combination with development of new algorithms and software, the science of computational vaccinology will be developed, so that it is not out of reach to stand on a point where we have the ability to design a multivalent efficacious immunogen (against several pathogens) (Pinheiro, Martins et al. 2011). The process, despite being new, is already used in an increas- ing manner for evaluating the effectiveness of differ- ent antigens or proposed chimeric antigens as candidate vaccines.
On the other hand, the development of genetic engi- neering methods has enabled us to design new chimeric proteins that carry more than one epitope from one or more pathogen, as a candidate vaccine against these pathogens. Chimeric antigens could be designed to carry different epitopes, so it is postulated that they can elicit immune responses against all included antigens (Ahlers et al. 2001). A striking advantage of these vaccines is the fact that “working on one protein (i.e. chimeric pro- tein) is preferable than working on several proteins”; it reduces the cost and time greatly.
Annually, there are more than 800,000 deaths from diarrheal diseases, more than AIDS, malaria, and mea- sles combined (Liu, Johnson et al. 2012). The diseases accounts for 1 in 9 child deaths worldwide and are the second leading cause of death in children under 5. Enter- opathogenic bacteria are of the main causative agents of diarrhea. Shigella species, ETEC, and EHEC are among the most important bacteria that cause the disease.
Enteropathogenic bacteria cause diarrhea all over the world. Despite all improvements in hygene standards,
the problem is still remained. Indeed, phenomena like national disasters, including earthquickes and floods, create a situation that the disease can cause severe health problems. This suggests that there is a great need for developing efficacious vaccines against these pathogens. In the present study, bioinformatics tools were used for designing a chimeric antigen as a can- didate vaccine against three enteropathogenic bacteria: enterotoixigenic E. coli (ETEC), enterohemorragic E. coli (EHEC), and Shigella. ETEC is a major cause of diarrhea in children under 5 in developing world and in travel- ers to these areas (Svennerholm and Tobias 2008, Taxt, 2016). EHEC, the pathogenic subgroup of Shiga toxin
There have been many designated chimeric pro- teins against each of mentioned pathogens. To our best knowledge, it is the first report on a chimeric vaccine that may protects against these three pathogens. In this study, we designed a chimeric protein consisting of five different antigens (LTB and STa from ETEC,
METHODS
IMMUNOGEN SELECTION AND SEQUENCE RETRIEVAL
Through the literature search and review, appropriate immunogens for each pathogen were selected. Multiple alignment softwares were used to select more prevalent and consensus sequences. Sequences and structures of the desired immunogens were adopted from UniProt (www.uniprot.org).
CONSTRUCTION OF DESIGN
The order of the selected sequences was optimized for obtaining the best 3D structure and immunogenic prop- erties. Having closer secondary and tertiary structures to the individual proteins, and also a high antigenic-
ity of the final structure were our priorities in lining up the antigens in the chimeric structure. For a good sepa- ration, the rigid helical linker (EAAAK) with different repeats were tested to obtain a good separation of the selected antigenic domains.
PREDICTION OF THE PROTEIN’S SECONDARY STRUCTURE
Several online programs, including GOR IV and V methods
TERTIARY STRUCTURE PREDICTION, VALIDATION, AND REFINEMENT OF THE CHIMERIC PROTEIN
Online
All predicted protein structures have some errors (Hooft, Vriend et al. 1996), so it’s inevitable to validate the predicted models. To overcome to this problem, the best 3D model, in which the different domains were separated and exposed and had a significant score, was selected and processed by ProSA (https://prosa.services. came.sbg.ac.at/prosa) (Wiederstein and Sippl 2007) pro- gram. Indeed, via Rampage, Ramachandran diagram was plotted to determine the overall
ANALYSIS OF THE
All
Abbas Hajizade et al.
Expasy’s ProtParam tool at http://us.expasy.org/tools/ protparam.html.
PREDICTION OF ANTIGENIC B- AND
BCPred analysis tool (www.imtech.res.in/raghava/bcep- red/) was used for the prediction of linear
CODON OPTIMIZATION AND MRNA
STRUCTURE PREDICTION
After confirming the efficacy of the chimeric protein as a candidate vaccine, the protein sequence was
For efficient translation, the final structure of the mRNA should be at the right form and energy level. Unavailable ribosome binding site (RBS) and some unfa- vorable secondary structures, such as long
Abbas Hajizade et al.
RESULTS
IMMUNOGEN SELECTION AND SEQUENCE RETRIEVAL
By the literature review and according to the previ- ous studies and investigations, StxB and EspA from EHEC, LTB and modified form of STa from ETEC, and
SYNTHETIC CONSTRUCT DESIGN
The potential orders of the antigens in the final struc- ture were evaluated by two different methods: the over- all antigenicity of the final structure and by comparing the similarity between secondary and tertiary structures of the each antigen alone and in the chimeric form. Moreover, placing the antigens of the same pathogen near together was important. The overall antigenicity of the various combinations of fragments was calculated by VaxiJen. Then, the ones of low antigenicity were removed and those of high antigenicity (higher than 7.2, when the threshold was 0.4) were selected for fur- ther analysis. The selected combinations were compared according to the similarity of secondary and tertiary structures’ of the individual antigens when they are alone and when they are incorporated in the chimeric antigen. The results show that the best results are met when the order of antigens is as follow:
of the chimeric antigen were 0.7389 and 0.847915 when analyzed by VaxiJen and ANTIGENpro (http://scratch. proteomics.ics.uci.edu/), respectively.
For effective separation between domains, an alpha
PREDICTION OF THE PROTEIN’S SECONDARY STRUCTURE
Several methods were exploited for the prediction of sec- ondary structure of the chimeric protein. As a control, the secondary structures of all individual antigens were either retrieved from PDB database (in the case of LTB and StxB) or predicted by different methods (all antigens). The frequency of the major types of secondary structure (alpha helix, extended strands, and random coils) in each individual antigen was compared with these structures in the chimeric antigen (Table 1). As it has been shown in table 1, different programs present different values.
By analyzing the predicted results we came to the conclusion that the prediction of the structures by the GORIV has been done more exact, so the method, which is an information
According to GOR IV, 56.47% of the secondary struc- ture types are alpha helix, 12.02% are extended strands, and 31.51% are random coiled. PredictProtein results show that the solvent accessibility composition (core/ surface ratio) for the chimeric protein was estimated to be acceptable: 60.79% of the residues were exposed with more than 16% of their surfaces.
FIGURE 1. The order of the antigens in the chimeric protein.
Abbas Hajizade et al.
Table 1: Predicted secondary structures of chimeric protein and each fragment by different programs.
*nd: not determined
TERTIARY STRUCTURE PREDICTION AND THE MODEL VALIDATION AND REFINEMENT
The tertiary structure prediction was performed by Rap- torx, DISTILL, and
confidence of the model (the
Figure 3 represents the predicted tertiary structure of the chimeric antigen by
Further analysis of the predicted 3D model was car- ried out by
FIGURE 2. Shematic view of the results for secondary structure prediction of the chimeric pro- tein. Blue color stands for helices, purple stands for random coils, and red stands for extended strands.
Abbas Hajizade et al.
FIGURE 3. Predicted tertiary structure of the chimeric protein by
Ramachandran plot analysis of the
The
PREDICTION OF ANTIGENIC B- AND
Prediction of continuous
The continuous
Prediction of discontinuous
Prediction by DiscoTope server, that predicts discontinu- ous B cell epitopes from protein three dimensional struc- tures, showed that there are many potent conformational
Abbas Hajizade et al.
FIGURE 4. Tertiary protein validation by ProSA program
Indeed, the prediction of conformational epitopes was done by ElliPro. ElliPro, which is based on the geometri- cal properties of protein structure, allows the prediction of epitopes in a given protein structure or sequence. Table 3 represents the results of conformational epitope prediction by ElliPro.
Prediction of
SYFPEITHI, a database compromising more than 7000 peptide sequences known to bind
For the prediction of
(Sturniolo, Bono et al. 1999). Analysis showed that there are many potent MHC
CODON OPTIMIZATION AND MRNA
STRUCTURE PREDICTION
The
47.76.Since the ideal percentage range of GC content is between 30% to 70% and there are not any peaks
Abbas Hajizade et al.
FIGURE 5. Ramachandran plot analysis of the predicted model by
outside of these ranges (figure 6B), it is expected that the transcriptional and translational efficiency won’t be affected. Rare codon analysis was carried out by codon frequency distribution (CFD) graph plotting. By this, the quantities of rare codons present in the sequence were identified (figure 6C). The value of CFD for the codon with the highest usage frequency for a given amino acid in the desired expression organism is set 100. The CFD value of less than 30 is determined as
Prediction of mRNA secondary structure was car- ried out by mfold server to analyze both stability and the status of ribosome binding site (RBS). The predicted structure showed that the mRNA is stable enough to be expressed in E. coli (ΔG = −418.8 kcal/mol) and the ribo-
Table 2: Physicochemical parameters of the SEISL synthetic peptide.
Abbas Hajizade et al.
Table 2: Continuous
FIGURE 6. Conformational
Abbas Hajizade et al.
Table 3: Predicted conformational
Table 4:
122D V I D Y I N D P 27
255 D V N K S A Q L L 26
166 T T V V N N S Q L 24
175 E I Q Q M S N T L 23
461 T I N D K I L S Y 23
21 T V K V A G K E Y 22
65 E V Q F N N D A E 22
482 I T F K S G A T F 22
519 L T E T K I D K L 22
18 D T F T V K V A G 21
55 S T C E S G S G F 21
106 D V Q S S T D K N 20
192 D V Q S L Q Y R T 20
some binding site is accessible for translational machi- nary.
DISCUSSION
Annually, there are more than 800,000 deaths from diarrheal diseases, more than AIDS, malaria, and mea- sles combined (Liu, Johnson et al. 2012). The diseases accounts for 1 in 9 child deaths worldwide and are the second leading cause of death in children under five. The disease is mainly caused by microbial pathogens,
although malnutrition and some illnesses can cause GI, too (Rodríguez, Cervantes et al. 2011, Oriá, et al. 2016).
Parasitic, viral and bacterial pathogens can cause the disease. Although viruses are the main diarrha- genic agents, however, enteropathogenic bacteria are very important, especially in regions with low hygiene standards. Diarrhagenic E. coli, Shigella species, Campi- lobacer jejuni, Vibrio cholera, and Bacterioides fragilis are the main bacterial causative of diarrhea in humans (Guarner, Khan et al. 2012). Shigella species, ETEC, and EHEC are among the most important bacteria that cause the disease. Vaccination is a good strategy for fighting against the diseases. There are many efficient candidate vaccines against each mentioned pathogens, however, there hasn’t been any vaccine that can protect against all three pathogens. Chimeric antigens, which are a com- bination of several antigens or antigen epitopes, have been proved to be efficient against several bacterial dis- eases. By having different antigens in one construct, the downstream processes, and consequently, the produc- tion time and costs will be largely diminished. Here we chose this strategy for designing of a vaccine, which simultaneously can immunize against three pathogens. The most important step in chimeric vaccine design is the selection of appropriate immunogens.
For this, we tried to choose the most immunodomi- nant immunogen(s) of each pathogen for incorpo- rating to the final antigen. In the case of ETEC, since pathogenic strains of the bacteria produce at least one of these two toxins, heat labile (LT) and/or heat stable (STa) (Qadri, Das et al. 2000), both toxins were selected for induction an immunity response against all pathogenic ETEC strains. LT is a member of AB5 fam-
Abbas Hajizade et al.
FIGURE 7. A. The distribution of codon usage frequency along the length of the chimeric SESL protein. CAI of the sequence was calculated 0.84, so the probability of high level protein expression in E. coli has been increased. B. GC percent curve of the optimized sequence. All the peaks are located in the allowed region (30- 70%). C. The percentage distribution of codons in computed codon quality groups. 96% of codons have a CFD value more than 50% and there are not any codons with CFD values of less than 30.
Abbas Hajizade et al.
FIGURE 8. mRNA secondary structure predicted for seisl gene by mfold server (the most stable structure is presented here.
ily toxins(Sixma, Pronk et al. 1991, Sixma, Kalk et al. 1993). While the A subunit has the enzymatic activity alone, the B subunit is not poisonous lonely, however, it is able to efficiently stimulate the immune system
[14].Stable toxin type a (STa), which is a
It has been shown that a point mutation in the cata- lytic site of the toxin will diminish the toxicity of the molecule, however the mutated toxin has the ability to induce the immune responses (Taxt, Aasland et al. 2010, Zeinalzadeh, Salmanian et al. 2013). Having these find- ings, we chose the B subunit of LT and a mutant form of STa for immunization against all pathogenic ETEC strains. In the case of EHEC, as mentioned earlier, dif- ferent combinations of EHEC virolence factors can be
chosen for incorporating into a chimeric antigen. We selected the
late the human immune responses (Li, Frey et al. 2000). In the case of shigella, Ipa (insertion plasmid antigen) proteins, which are found in all Shigella species and are required for the entry of the pathogen into the host cells, are a good choice. Induction of mutation into Ipa genes cause the pathogen to lose the capability of invading host cells (Ménard, Sansonetti et al. 1993), so target- ing these proteins can prevent the pathogen to invade cells. There are four major Ipa proteins: IpaA, IpaB, IpaC, and IpaD. There have been many vaccine formulations that have used a combination of these proteins. Here, the
The selection of an appropriate peptide linker could act as a bridge and connect individual components together and play a crucial role in final structure of the chimeric antigen. An ideal linker should connect the immunogens in such a way that they become completely separated in the final folded state of the chimeric pro- tein. Linkers with
It is of a great importance that the major structural elements of each individual antigen be similar to the relevant structures in the chimeric antigen. For exam- ining this issue, five different secondary structure pre- diction methods (Psipred, PORTER, GORIV, GORV, and SSpro) were exploited. By comparing the calculated data from different methods with the data retrieved from PDB, we came to the conclusion that GOR IV (Garnier-
There are two main methods for in silico tertiary structure prediction of proteins: abinitio methods, which seek to build
Abbas Hajizade et al.
scratch”, i.e., based on physical principles rather than (directly) on previously solved structures; and compara- tive protein modeling, which uses previously solved structures as starting points, or templates. There are many useful programs developed according to these strategies. Here we used the hierarchical method,
The physiochemical analysis of the chimeric protein shows that the protein is a positively charged in physi- ological conditions and it could be expressed in differ- ent expression systems. Indeed, the results show that the protein is relatively stable.
The overall antigenicity of the chimeric antigen is the most important factor for a protein to be considered as a candidate vaccine. Being identified by humoral and cellular immunity systems’ components is an essen- tial factor for a potent immunogen. Antigenic proteins are recognized by immune systems through antigenic determinants or epitopes.
Abbas Hajizade et al.
Having a
ACKNOWLEDGEMENT
This research was carried out as a part of the Ph.D the- sis of Abbas Hajizade. The authors thank Applied Bio- technology Research Centre, Baqiyatallah University of Medical Sciences, for the warm and kind support.
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