Novel approach to porcine epidemic diarrhea vaccine development by reverse vaccinology

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Woarawut Oniam
Suang Rungpragayphan
Busaba Powthongchin
Perayot Pamonsinlapatham

Abstract

Porcine epidemic diarrhea (PED) affects most swine, causing severe diarrhea and rapid death. The mortality rate of piglets reaches up to 80%-100%, which affects the pig industry. This study aimed to develop a PED vaccine using reverse vaccinology applying bioinformatic tools and evaluate epitope-based vaccines in an animal model. The genome of PED virus (PEDV)-CBR1 was retrieved and used, following the prediction of open reading frames (ORFs) by ORF finder. Consequently, protein localization was predicted by the iLoc-Virus program. Target proteins were subjected to adhesin-like prediction followed by B-cell epitope prediction. Finally, three epitope-based vaccines were synthesized and injected in an animal model, and the mucosal antibody response was measured. The candidate vaccine can stimulate mucosal antibodies in different mucosal organs. In conclusion, reverse vaccinology can be applied in PED cases by using different bioinformatic tools and proofing in the animal model.

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Health sciences

References

Alexander, J., del Guercio, M. F., Maewal, A., Qiao, L., Fikes, J., Chesnut, R. W., Paulson, J., Bundle, D. R., DeFrees, S., and Sette, A. (2000). Linear PADRE T helper epitope and carbohydrate B cell epitope conjugates induce specific high titer IgG antibody responses. The Journal of Immunology, 164(3), 1625-1633.

Bouvet, J. P., Decroix, N., and Pamonsinlapatham, P. (2002). Stimulation of local antibody production: Parenteral or mucosal vaccination? Trends in Immunology, 23(4), 209-213.

Bruno, L., Cortese, M., Rappuoli, R., and Merola, M. (2015). Lessons from reverse vaccinology for viral vaccine design. Current Opinion in Virology, 11, 89-97.

Chen, J., Liu, H., Yang, J., and Chou, K. C. (2007). Prediction of linear B-cell epitopes using amino acid pair antigenicity scale. Amino Acids, 33(3), 423-428.

Cheun-Arom, T., Temeeyasen, G., Srijangwad, A., Tripipat, T., Sangmalee, S., Vui, D. T., Chuanasa, T., Tantituvanont, A., and Nilubol, D. (2015). Complete genome sequences of two genetically distinct variants of porcine epidemic diarrhea virus in the eastern region of Thailand. Genome Announcements, 3(3). e00634-15.

Decroix, N., Pamonsinlapatham, P., Quan, C. P., and Bouvet, J. P. (2003). Impairment by mucosal adjuvants and cross-reactivity with variant peptides of the mucosal immunity induced by injection of the fusion peptide PADRE-ELDKWA. Clinical and Vaccine Immunology, 10(6), 1103-1108.

El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008). Predicting flexible length linear B-cell epitopes. In Proceedings of the Computational Systems Bioinformatics Conference, pp. 121-132. California, USA.

Gerdts, V., and Zakhartchouk, A. (2017). Vaccines for porcine epidemic diarrhea virus and other swine coronaviruses. Veterinary Microbiology, 206, 45-51.

Hwang, W., Lei, W., Katritsis, N. M., MacMahon, M., Chapman, K., and Han, N. (2021). Current and prospective computational approaches and challenges for developing COVID-19 vaccines. Advanced Drug Delivery Reviews, 172(4), 249-274.

Jung, K., Saif, L. J., and Wang, Q. (2020). Porcine epidemic diarrhea virus (PEDV): An update on etiology, transmission, pathogenesis, and prevention and control. Virus Research, 286, 198045.

Lassmann, T., and Sonnhammer, E. L. L. (2006). Kalign, kalignvu and mumsa: Web servers for multiple sequence alignment. Nucleic Acids Research, 34(2), 596-599.

Lee, C. (2015). Porcine epidemic diarrhea virus: An emerging and re-emerging epizootic swine virus. Virology Journal, 12, 193.

Lee, S. H., Yang, D. K., Kim, H. H., and Cho, I. S. (2018). Efficacy of inactivated variant porcine epidemic diarrhea virus vaccines in growing pigs. Clinical and Experimental Vaccine Research, 7(1), 61-69.

Li, M., Wang, Y., Sun, Y., Cui, H., Zhu, S. J., and Qiu, H. J. (2020). Mucosal vaccines: Strategies and challenges. Immunology Letters, 217(52), 116-125.

Lian, Y., Ge, M., and Pan, X. M. (2014). EPMLR: Sequence-based linear B-cell epitope prediction method using multiple linear regression. BMC Bioinformatics, 15(1), 414.

Rappuoli, R., Bottomley, M. J., D’Oro, U., Finco, O., and De Gregorio, E. (2016). Reverse vaccinology 2.0: Human immunology instructs vaccine antigen design. Journal of Experimental medicine, 213(4), 469-481.

Sachdeva, G., Kumar, K., Jain, P., and Ramachandran, S. (2005). SPAAN: A software program for prediction of adhesins and adhesin-like proteins using neural networks. Bioinformatics, 21(4), 483-491.

Saha, S., and Raghava, G. P. S. (2006). Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins, 65(1), 40-48.

Shibata, I., Ono, M., and Mori, M. (2001). Passive protection against porcine epidemic diarrhea (PED) virus in piglets by colostrum from immunized cows. Journal of Veterinary Medical Science, 63(6), 655-658.

Singh, H., Ansari, H. R., and Raghava, G. P. S. (2013). Improved method for linear B-cell epitope prediction using antigen’s primary sequence. PLOS One, 8(5), e62216.

Song, D., Moon, H., and Kang, B. (2015). Porcine epidemic diarrhea: A review of current epidemiology and available vaccines. Clinical and Experimental Vaccine Research, 4(2), 166-176.

Song, D. S., Oh, J. S., Kang, B. K., Yang, J. S., Moon, H. J., Yoo, H. S., Jang, Y. S., and Park, B. K. (2007). Oral efficacy of Vero cell attenuated porcine epidemic diarrhea virus DR13 strain. Research in Veterinary Science, 82(1), 134-140.

Sweredoski, M. J., and Baldi, P. (2009). COBEpro: A novel system for predicting continuous B-cell epitopes. Protein Engineering, Design and Selection, 22(3), 113-120.

Temeeyasen, G., Srijangwad, A., Tripipat, T., Tipsombatboon, P., Piriyapongsa, J., Phoolcharoen, W., Chuanasa, T., Tantituvanont, A., and Nilubol, D. (2014). Genetic diversity of ORF3 and spike genes of porcine epidemic diarrhea virus in Thailand. Infection, Genetics and Evolution, 21, 205-213.

Xiao, X., Wu, Z. C., and Chou, K. C. (2011). iLoc-Virus: A multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites. Journal of Theoretical Biology, 284(1), 42-51.

Yang, D. K., Kim, H. H., Lee, S. H., Yoon, S. S., Park, J. W., and Cho, I. S. (2018). Isolation and characterization of a new porcine epidemic diarrhea virus variant that occurred in Korea in 2014. Journal of Veterinary Science, 19(1), 71-78.

Yao, B., Zhang, L., Liang, S., and Zhang, C. (2012). SVMTriP: A method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity. PLOS One, 7(9), e45152.