Expression and Purification of Recombinant Envelope (rE) Protein of Dengue Virus in Escherichia coli BL21(DE3) with Computational Insights
Abstract
Dengue Hemorrhagic Fever (DHF) caused by the Dengue Virus has become an endemic problem in countries with tropical and subtropical climates, thus categorizing it as a global challenge. One molecular biology approach for DHF prevention is through vaccination. A protein-based recombinant vaccine approach can be employed by utilizing the Envelope protein (E) of the Dengue Virus, as this protein is an ideal target as a vaccine candidate. This study optimized the gene sequence of recombinant Envelope (rE) coding for the recombinant Envelope protein (rE), followed by in silico testing of protein characteristics and structure modeling. The obtained results revealed that the rE protein exhibited instability index, aliphatic index, and isoelectric point values of 32.14, 75.08, and 7.17, respectively. The Ramachandran plot analysis indicated that 95.4% of amino acid residues were within the allowed region, while 4.7% were within the disallowed region, demonstrating the accuracy of the in silico protein modeling for rE. Consequently, the in silico testing results demonstrated that the rE protein possessed a stable and high-quality structure. The rE gene was then inserted into the pET-15b vector plasmid for subsequent expression using the Escherichia coli BL21(DE3) expression host system. Positive Escherichia coli colonies carrying the rE gene were induced with 1 mM IPTG. The expression results were analyzed using SDS-PAGE, followed by purification using a Ni-NTA column, and further analyzed by SDS-PAGE and western blot. The research findings demonstrated the successful insertion of the recombinant pET-15b-rE plasmid into E. coli BL21(DE3). The rE protein, with a size of 50.68 kDa, was successfully expressed in Escherichia coli BL21(DE3), as evidenced by the SDS-PAGE analysis showing a band within the 50-60 kDa range. In conclusion, this study successfully achieved the expression and purification of the recombinant Envelope protein (rE) of Dengue Virus in Escherichia coli BL21(DE3).
References
Arumugam, B., Palanisamy, U. D., Chua, K. H., & Kuppusamy, U. R. (2020). Amelioration of hyperglycemia-induced oxidative damage in ARPE-19 cells by myricetin derivatives isolated from Syzygium malaccense. Journal of Functional Foods, 67, 103844. https://doi.org/10.1016/j.jff.2020.103844
Brinkman, J. E., & Sharma, S. (2023). Physiology, Metabolic Alkalosis.
Chan, W. T., Verma, C. S., Lane, D. P., & Gan, S. K. E. (2013). A comparison and optimization of methods and factors affecting the transformation of Escherichia coli. Bioscience Reports, 33(6). https://doi.org/10.1042/BSR20130098
Diamond, M. S., & Pierson, T. C. (2015). Molecular Insight into Dengue Virus Pathogenesis and Its Implications for Disease Control. In Cell (Vol. 162, Issue 3, pp. 488–492). Cell Press. https://doi.org/10.1016/j.cell.2015.07.005
Doytchinova, I. A., & Flower, D. R. (2007). VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 8(1), 4. https://doi.org/10.1186/1471-2105-8-4
Fahimi, H., Sadeghizadeh, M., & Mohammadipour, M. (2016). In silico analysis of an envelope domain III-based multivalent fusion protein as a potential dengue vaccine candidate . Clinical and Experimental Vaccine Research, 5(1), 41. https://doi.org/10.7774/cevr.2016.5.1.41
Gamage, D. G., Gunaratne, A., Periyannan, G. R., & Russell, T. G. (2019). Applicability of Instability Index for In vitro Protein Stability Prediction. Protein & Peptide Letters, 26(5), 339–347. https://doi.org/10.2174/0929866526666190228144219
Ghosh, A., & Dar, L. (2015). Dengue vaccines: Challenges, development, current status and prospects. In Indian Journal of Medical Microbiology (Vol. 33, Issue 1, pp. 3–15). Wolters Kluwer Medknow Publications. https://doi.org/10.4103/0255-0857.148369
Halstead, S. B. (2016). Critique of world health organization recommendation of a dengue vaccine. In Journal of Infectious Diseases (Vol. 214, Issue 12, pp. 1793–1795). Oxford University Press. https://doi.org/10.1093/infdis/jiw340
Hardani, M., Ramadhian, M. R., & Wahyudo, R. (n.d.). DENV-5: Ancaman Serotipe Baru Virus Dengue DENV-5: New Emerging Dengue Virus Serotype.
Hasan, S., Jamdar, S. F., Alalowi, M., & Al Ageel Al Beaiji, S. M. (2016). Dengue virus: A global human threat: Review of literature. In Journal of International Society of Preventive and Community Dentistry (Vol. 6, Issue 1, pp. 1–6). Wolters Kluwer (UK) Ltd. https://doi.org/10.4103/2231-0762.175416
Imai, N., & Ferguson, N. M. (2018). Targeting vaccinations for the licensed dengue vaccine: Considerations for serosurvey design. PLoS ONE, 13(6). https://doi.org/10.1371/journal.pone.0199450
Jansen, R., Bussemaker, H. J., & Gerstein, M. (2003). Revisiting the codon adaptation index from a whole-genome perspective: Analyzing the relationship between gene expression and codon occurrence in yeast using a variety of models. Nucleic Acids Research, 31(8), 2242–2251. https://doi.org/10.1093/nar/gkg306
Lovell, S. C., Davis, I. W., Arendall, W. B., de Bakker, P. I. W., Word, J. M., Prisant, M. G., Richardson, J. S., & Richardson, D. C. (2003). Structure validation by Cα geometry: ϕ,ψ and Cβ deviation. Proteins: Structure, Function, and Bioinformatics, 50(3), 437–450. https://doi.org/10.1002/prot.10286
Made Susila Utama, I., Lukman, N., Sukmawati, D. D., Alisjahbana, B., Alam, A., Murniati, D., Made Gede Dwi Lingga Utama, I., Puspitasari, D., Kosasih, H., Laksono, I., Karyana, M., Karyanti, M. R., Hapsari, M. M. D. E. A. H., Meutia, N., Jason Liang, C., Wulan, W. N., Lau, C. Y., & Parwati, K. T. M. (2019). Dengue viral infection in Indonesia: Epidemiology, diagnostic challenges, and mutations from an observational cohort study. PLoS Neglected Tropical Diseases, 13(10). https://doi.org/10.1371/journal.pntd.0007785
Medeiros, A. S., Costa, D. M. P., Branco, M. S. D., Sousa, D. M. C., Monteiro, J. D., Galväo, S. P. M., Azevedo, P. R. M., Fernandes, J. V., Jeronimo, S. M. B., & Araújo, J. M. G. (2018). Dengue virus in Aedes aegypti and Aedes albopictus in urban areas in the state of Rio Grande do Norte, Brazil: Importance of virological and entomological surveillance. PLoS ONE, 13(3). https://doi.org/10.1371/journal.pone.0194108
Murugesan, A., & Manoharan, M. (2019). Dengue virus. In Emerging and Reemerging Viral Pathogens: Volume 1: Fundamental and Basic Virology Aspects of Human, Animal and Plant Pathogens (pp. 281–359). Elsevier. https://doi.org/10.1016/B978-0-12-819400-3.00016-8
Nehete, J., Bhambar, R., Narkhede, M., & Gawali, S. (2013). Natural proteins: Sources, isolation, characterization and applications. In Pharmacognosy Reviews (Vol. 7, Issue 14, pp. 107–116). https://doi.org/10.4103/0973-7847.120508
Pollet, J., Chen, W. H., & Strych, U. (2021). Recombinant protein vaccines, a proven approach against coronavirus pandemics. In Advanced Drug Delivery Reviews (Vol. 170, pp. 71–82). Elsevier B.V. https://doi.org/10.1016/j.addr.2021.01.001
Puigbò, P., Bravo, I. G., & Garcia-Vallvé, S. (2008). E-CAI: A novel server to estimate an expected value of Codon Adaptation Index (eCAI). BMC Bioinformatics, 9. https://doi.org/10.1186/1471-2105-9-65
Roy, A., Kucukural, A., & Zhang, Y. (2010). I-TASSER: A unified platform for automated protein structure and function prediction. Nature Protocols, 5(4), 725–738. https://doi.org/10.1038/nprot.2010.5
Sabir, M. J., Al-Saud, N. B. S., & Hassan, S. M. (2021). Dengue and human health: A global scenario of its occurrence, diagnosis and therapeutics. In Saudi Journal of Biological Sciences (Vol. 28, Issue 9, pp. 5074–5080). Elsevier B.V. https://doi.org/10.1016/j.sjbs.2021.05.023
Sambrook and Russel, 2006. (n.d.).
Seo, S., Choi, J., Park, S., & Ahn, J. (2021). Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions. BMC Bioinformatics, 22(1). https://doi.org/10.1186/s12859-021-04466-0
Sharp, P. M., & Li, W.-H. (1987). The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Research, 15(3), 1281–1295. https://doi.org/10.1093/nar/15.3.1281
Sørensen, H. P., & Mortensen, K. K. (2005). Advanced genetic strategies for recombinant protein expression in Escherichia coli. Journal of Biotechnology, 115(2), 113–128. https://doi.org/10.1016/j.jbiotec.2004.08.004
Thomas, S. J., & Yoon, I. K. (2019). A review of Dengvaxia®: development to deployment. Human Vaccines and Immunotherapeutics, 15(10), 2295–2314. https://doi.org/10.1080/21645515.2019.1658503
Tokmakov, A. A., Kurotani, A., & Sato, K. I. (2021). Protein pI and Intracellular Localization. In Frontiers in Molecular Biosciences (Vol. 8). Frontiers Media S.A. https://doi.org/10.3389/fmolb.2021.775736
Wibowo, B., & Dokter, P. (n.d.). HUBUNGAN INFEKSI DENGUE SEKUNDER DENGAN DERAJAT KEPARAHAN INFEKSI DENGUE.
Wibowo, S., Costa, J., Baratto, M. C., Pogni, R., Widyarti, S., Sabarudin, A., Matsuo, K., & Sumitro, S. B. (2022). Quantification and Improvement of the Dynamics of Human Serum Albumin and Glycated Human Serum Albumin with Astaxanthin/Astaxanthin-Metal Ion Complexes: Physico-Chemical and Computational Approaches. International Journal of Molecular Sciences, 23(9), 4771. https://doi.org/10.3390/ijms23094771
Wibowo, S., Widyarti, S., Sabarudin, A., Soeatmadji, D. W., & Sumitro, S. B. (2021). DFT and molecular dynamics studies of astaxanthin-metal ions (Cu2+ and Zn2+) complex to prevent glycated human serum albumin from possible unfolding. Heliyon, 7(3), e06548. https://doi.org/10.1016/j.heliyon.2021.e06548
Widyarti, S., Wibowo, S., Sabarudin, A., Abhirama, I., & Sumitro, S. B. (2023). Dysfunctional energy and future perspective of low dose H2O2 as protective agent in neurodegenerative disease. Heliyon, 9(7), e18123. https://doi.org/10.1016/j.heliyon.2023.e18123
Yadav, D. K., Yadav, N., & Khurana, S. M. P. (2013). Vaccines: Present Status and Applications. In Animal Biotechnology: Models in Discovery and Translation (pp. 491–508). Elsevier Inc. https://doi.org/10.1016/B978-0-12-416002-6.00026-2
Yao, B., Zhang, L., Liang, S., & 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). https://doi.org/10.1371/journal.pone.0045152