In Silico-Based Vaccine Design Against Hepatopancreatic Microsporidiosis in Shrimp
DOI:
https://doi.org/10.48048/tis.2022.2679Keywords:
Enterocytozoon hepatopenaei, Hepatopancreatic microsporidiosis, Vaccine, Epitopes, MD SimulationAbstract
Enterocytozoon hepatopenaei (EHP) is a spore-forming intracellular parasite that produces an economically devastating disease in farmed shrimp called hepatopancreatic microsporidiosis (HPM), known to slow the growth of hosts in aquaculture. Spore wall proteins are implicated in the recognition of host cells in microsporidia. Many parasites have been demonstrated to detect heparin, a glycosaminoglycan (GAG) molecule present on cell surfaces, as a host. The sequencing and characterization of several EHP strains started to reveal information regarding pathogen biology, pathogenicity, and spore wall proteins must bind to the shrimp cell surface to infect it, and failure to do so results in ineffective infection. Despite these devastating complications, there is still no cure or vaccine for the parasites. In this regard, an immunoinformatics method was used to generate an epitope-based vaccine against this pathogen. The immunodominant T-cell and B-cell epitopes were identified using the spore wall proteins of EHP. The final constructed vaccine sequence was developed to be immunogenic, non-allergenic as well as have better solubility. Molecular dynamics simulation revealed significant binding stability and structural compactness. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher CAI value, which was then included in the cloning vector pET2+ (a). Altogether, our outcomes imply that the proposed peptide vaccine may be a good option for HPM prophylaxis.
HIGHLIGHTS
- Hepatopancreatic microsporidiosis (HPM) is known to slow the growth of shrimp
- There are approved drugs or vaccines to control this disease
- In-silico approach and immunoinformatics has some advantage previously in fishes
- The design vaccine candidate would have some advantages to combat the disease for sustainable shrimp production
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N Ghaffari, A Sanchez-Flores, R Doan, KD Garcia-Orozco, PL Chen, A Ochoa-Leyva, AA Lopez-Zavala, JS Carrasco, C Hong and LG Brieba. Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture. Sci. Rep. 2014; 4, 7081.
U Lele and S Goswami. The food and agriculture organization of the United Nations. Food and Agriculture Organization, Québec, Canada, 2021, p. 630-706.
K Chayaburakul, G Nash, P Pratanpipat, S Sriurairatana and B Withyachumnarnkul. Multiple pathogens found in growth-retarded black tiger shrimp Penaeus monodon cultivated in Thailand. Dis. Aquat. Organisms 2004; 60, 89-96.
KF Tang, CR Pantoja, RM Redman, JE Han, LH Tran and DV Lightner. Development of in situ hybridization and PCR assays for the detection of Enterocytozoon hepatopenaei (EHP), a microsporidian parasite infecting penaeid shrimp. J. Invertebr. Pathol. 2015; 130, 37-41.
DJ Aldama-Cano, P Sanguanrut, N Munkongwongsiri, JC Ibarra-Gámez, O Itsathitphaisarn, R Vanichviriyakit, TW Flegel, K Sritunyalucksana and S Thitamadee. Bioassay for spore polar tube extrusion of shrimp Enterocytozoon hepatopenaei (EHP). Aquaculture 2018; 490, 156-61.
T Chaijarasphong, N Munkongwongsiri, GD Stentiford, DJ Aldama-Cano, K Thansa, TW Flegel, K Sritunyalucksana and O Itsathitphaisarn. The shrimp microsporidian Enterocytozoon hepatopenaei (EHP): Biology, pathology, diagnostics and control. J. Invertebr. Pathol. 2021; 186, 107458.
KFJ Tang, JE Han, LF Aranguren, B White-Noble, MM Schmidt, P Piamsomboon, E Risdiana and B Hanggono. Dense populations of the microsporidian Enterocytozoon hepatopenaei (EHP) in feces of penaeus vannamei exhibiting white feces syndrome and pathways of their transmission to healthy shrimp. J. Invertebr. Pathol. 2016; 140, 1-7.
Q Lv, L Wang, Y Fan, X Meng, K Liu, B Zhou, J Chen, G Pan, M Long and Z Zhou. Identification and characterization a novel polar tube protein (NbPTP6) from the microsporidian Nosema bombycis. Parasites Vectors. 2020; 13, 475.
JR Hayman, TR Southern and TE Nash. Role of sulfated glycans in adherence of the microsporidian Encephalitozoon intestinalis to host cells in vitro. Infect. Immun. 2005; 73, 841-8.
P Jaroenlak, DW Boakye, R Vanichviriyakit, BAP Williams, K Sritunyalucksana and O Itsathitphaisarn. Identification, characterization and heparin binding capacity of a spore-wall, virulence protein from the shrimp microsporidian, Enterocytozoon hepatopenaei (EHP). Parasites Vectors 2018; 11, 177.
JE Muñoz-Medina, CJ Sánchez-Vallejo, A Méndez-Tenorio, IE Monroy-Muñoz, J Angeles-Martínez, AS Coy-Arechavaleta, CE Santacruz-Tinoco, J González-Ibarra, YM Anguiano-Hernández and CR González-Bonilla. In Silico identification of highly conserved epitopes of influenza A H1N1, H2N2, H3N2, and H5N1 with diagnostic and vaccination potential. BioMed Res. Int. 2015; 2015, 813047.
MT Ali, MM Morshed and F Hassan. A computational approach for designing a universal epitope-based peptide vaccine against nipah virus. Interdiscipl. Sci. 2015; 7, 177-85.
S Anwar, JT Mourosi, MF Khan and MJ Hosen. Prediction of epitope-based peptide vaccine against the chikungunya virus by immuno-informatics approach. Curr. Pharmaceut. Biotechnol. 2020; 21, 325-40.
R Dash, R Das, M Junaid, MF Akash, A Islam and SZ Hosen. In silico-based vaccine design against Ebola virus glycoprotein. Comput. Biol. Chem. Adv. Appl. 2017; 10, 11-28.
J Shi, J Zhang, S Li, J Sun, Y Teng, M Wu, J Li, Y Li, N Hu, H Wang and H Yunzhang. Epitope-based vaccine target screening against highly pathogenic MERS-CoV: An in silico approach applied to emerging infectious diseases. PLoS One 2015; 10, e0144475.
R Mahendran, S Jeyabaskar, G Sitharaman, RD Michael and AV Paul. Computer-aided vaccine designing approach against fish pathogens edwardsiella tarda and flavobacterium columnare using bioinformatics softwares. Drug Des. Dev. Ther. 2016; 10, 1703-14.
UP Pereira, SC Soares, J Blom, CA Leal, RT Ramos, LC Guimarães, LC Oliveira, SS Almeida, SS Hassan and AR Santos. In silico prediction of conserved vaccine targets in streptococcus agalactiae strains isolated from fish, cattle, and human samples. Genet. Mol. Res. 2013; 12, 2902-12.
A Pumchan, S Krobthong, S Roytrakul, O Sawatdichaikul, H Kondo, I Hirono, N Areechon and S Unajak. Novel chimeric multiepitope vaccine for streptococcosis disease in nile tilapia (Oreochromis niloticus Linn.). Sci. Rep. 2020; 10, 603.
A Madonia, C Melchiorri, S Bonamano, M Marcelli, C Bulfon, F Castiglione, M Galeotti, D Volpatti, F Mosca, T Pietro-Giorgio and N Romano. Computational modeling of immune system of the fish for a more effective vaccination in aquaculture. Bioinformatics 2017; 33, 3065-71.
A Joshi, DC Pathak, MA Mannan and V Kaushik. In-silico designing of epitope-based vaccine against the seven banded grouper nervous necrosis virus affecting fish species. Netw. Model. Anal. Health Informat. Biol. 2021; 10, 37.
A Garg and D Gupta. VirulentPred: A SVM based prediction method for virulent proteins in bacterial pathogens. BMC Bioinformatics 2008; 9, 62.
IA Doytchinova and DR Flower. VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics 2007; 8, 4.
B Farhood, M Najafi and K Mortezaee. CD8 + cytotoxic T lymphocytes in cancer immunotherapy: A review. J. Cell. Physiol. 2019; 234, 8509-21.
JJ Calis, M Maybeno, JA Greenbaum, D Weiskopf, ADD Silva, A Sette, C Keşmir and B Peters. Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput. Biol. 2013; 9, e1003266.
S Gupta, P Kapoor, K Chaudhary, A Gautam, R Kumar and GP Raghava. In silico approach for predicting toxicity of peptides and proteins. PLoS One 2013; 8, e73957.
I Dimitrov, DR Flower and I Doytchinova. AllerTOP--a server for in silico prediction of allergens. BMC Bioinformatics 2013; 14, S4.
Z Nain, F Abdulla, MM Rahman, MM Karim, MSA Khan, SB Sayed, S Mahmud, SMR Rahman, MM Sheam, Z Haque and UK Adhikari. Proteome-wide screening for designing a multi-epitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches. J. Biomol. Struct. Dynam. 2020; 38, 4850-67.
B Manavalan, RG Govindaraj, TH Shin, MO Kim and G Lee. iBCE-EL: A new ensemble learning framework for improved linear b-cell epitope prediction. Front. Immunol. 2018; 9, 1695.
H Dorosti, M Eslami, M Negahdaripour, MB Ghoshoon, A Gholami, R Heidari, A Dehshahri, N Erfani, N Nezafat and Y Ghasemi. Vaccinomics approach for developing multi-epitope peptide pneumococcal vaccine. J. Biomol. Struct. Dynam. 2019; 37, 3524-35.
Z Nain, MM Karim, MK Sen and UK Adhikari. Structural basis and designing of peptide vaccine using PE-PGRS family protein of mycobacterium ulcerans-an integrated vaccinomics approach. Mol. Immunol. 2020; 120, 146-63.
J Olejnik, AJ Hume and E Mühlberger. Toll-like receptor 4 in acute viral infection: Too much of a good thing. PLoS Pathogens 2018; 14, e1007390.
RK Pandey, TK Bhatt and VK Prajapati. Novel immunoinformatics approaches to design multi-epitope subunit vaccine for malaria by investigating anopheles salivary protein. Sci. Rep. 2018; 8, 1125.
A Shanmugam, S Rajoria, AL George, A Mittelman, R Suriano and RK Tiwari. Synthetic toll like receptor-4 (TLR-4) agonist peptides as a novel class of adjuvants. PLoS One 2012; 7, e30839.
M Hasan, S Islam, S Chakraborty, AH Mustafa, KF Azim, ZF Joy, MN Hossain, SH Foysal and MN Hasan. Contriving a chimeric polyvalent vaccine to prevent infections caused by herpes simplex virus (type-1 and type-2): An exploratory immunoinformatic approach. J. Biomol. Struct. Dynam. 2020; 38, 2898-915.
GS Abdellrazeq, LM Fry, MM Elnaggar, JP Bannantine, DA Schneider, WM Chamberlin, AHA Mahmoud, KT Park, V Hulubei and WC Davis, Simultaneous cognate epitope recognition by bovine CD4 and CD8 T cells is essential for primary expansion of antigen-specific cytotoxic T-cells following ex vivo stimulation with a candidate Mycobacterium avium subsp. paratuberculosis peptide vaccine. Vaccine 2020; 38, 2016-25.
M Wilkins, E Gasteiger, A Bairoch, JC Sanchez, K Williams, R Appel and D Hochstrasser. Protein identification and analysis tools in the ExPASy server. The Proteomics Protocols Handbook. Humana Press, New Jersey, 2008, p. 571-607.
CN Magnan, M Zeller, MA Kayala, A Vigil, A Randall, PL Felgner and P Baldi. High-throughput prediction of protein antigenicity using protein microarray data. Bioinformatics 2010; 26, 2936-43.
C Geourjon and G Deléage SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Comput. Appl. Biosci. 1995; 11, 681-4.
DW Buchan, F Minneci, TC Nugent, K Bryson and DT Jones. Scalable web services for the PSIPRED protein analysis workbench. Nucleic Acids Res. 2013; 41, W349-57.
J Xu, M McPartlon and J Li. Improved protein structure prediction by deep learning irrespective of co-evolution information. Nat. Mach. Intell. 2021; 3, 601-9.
T Nugent, D Cozzetto and DT Jones. Evaluation of predictions in the CASP10 model refinement category. Proteins 2014; 82, 98-111.
WL DeLano. PyMOL: An open-source molecular graphics tool. Adv. Biol. Chem. 2002; 8, 1-9.
M Wiederstein and MJ Sippl. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007; 35, W407-10.
DB Craig and AA Dombkowski. Disulfide by design 2.0: A web-based tool for disulfide engineering in proteins. BMC Bioinformatics 2013; 14, 346.
D Kozakov, DR Hall, B Xia, KA Porter, D Padhorny, C Yueh, D Beglov and S Vajda: The ClusPro web server for protein-protein docking. Nat. Protocol. 2017; 12, 255-78.
S Pokhrel, TA Bouback, A Samad, SM Nur, R Alam, M Abdullah-Al-Mamun, Z Nain, RR Imon, MEK Talukder, MMI Tareq, MS Hossen, TM Karpiński, F Ahammad, I Qadri and MS Rahman.Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2. Int. J. Biol. Macromol. 2021; 191, 1114-25.
TA Bouback, S Pokhrel, A Albeshri, AM Aljohani, A Samad, R Alam, MS Hossen, K Al-Ghamdi, MEK Talukder, F Ahammad, I Qadri and J Simal-Gandara. Pharmacophore-based virtual screening, quantum mechanics calculations, and molecular dynamics simulation approaches identified potential natural antiviral drug candidates against MERS-CoV S1-NTD. Molecules 2021; 26, 4961.
A Grote, K Hiller, M Scheer, R Münch, B Nörtemann, DC Hempel and D Jahn. JCat: A novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Res. 2005; 33, W526-31.
MF Goldberg, EK Roeske, LN Ward, T Pengo, T Dileepan, DI Kotov and MK Jenkins. Salmonella persist in activated macrophages in T cell-sparse granulomas but are contained by surrounding CXCR3 ligand-positioned Th1 cells. Immunity 2018; 49, 1090-102.
W Li, MD Joshi, S Singhania, KH Ramsey and AK Murthy. Peptide vaccine: Progress and challenges. Vaccines 2014; 2, 515-36.
KF Bol, EH Aarntzen, JM Pots, MAO Nordkamp, MWVD Rakt, NM Scharenborg, AJD Boer, TGV Oorschot, SA Croockewit and WA Blokx. Prophylactic vaccines are potent activators of monocyte-derived dendritic cells and drive effective anti-tumor responses in melanoma patients at the cost of toxicity. Canc. Immunother. 2016; 65, 327-39.
S Shamriz, H Ofoghi and N Moazami. Effect of linker length and residues on the structure and stability of a fusion protein with malaria vaccine application. Comput. Biol. Med. 2016; 76, 24-9.
SR Bonam, CD Partidos, SKM Halmuthur and S Muller. An overview of novel adjuvants designed for improving vaccine efficacy. Trends Pharmacol. Sci. 2017; 38, 771-93.
N Khatoon, RK Pandey and VK Prajapati. Exploring leishmania secretory proteins to design B and T cell multi-epitope subunit vaccine using immunoinformatics approach. Sci. Rep. 2017; 7, 8285.
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