Expression and Epitope Prediction of the Sirohydrochlorin Cobaltochelatase Isolated from a Local Strain of Mycobacterium Tuberculosis

Ahyar Ahmad, Abdul Karim, Rugaiyah A. Arfah, Rosana Agus, Rusdina Bte Ladju, Najdah Hidayah, Muhammad N. Massi, Astutiati Nurhasanah, Harningsih Karim, Irda Handayani, Rizal Irfandi

Abstract


The efficacy of the BCG vaccine, a widely recognized tuberculosis vaccine, has shown varying degrees of effectiveness, ranging from 0% to 80%. Sirohydrochlorin cobaltochelatase (CbiX), found in Mycobacterium tuberculosis, plays a crucial role in the bacteria metabolism, making it a promising target for future vaccine and drug development. Although several studies had been published regarding its role in M. tuberculosis vitamin B-12 metabolism, the potentials of CbiX protein as a vaccine candidate had not been widely discussed nor explored. This study focuses on the cloning and expression of the Rv0259c gene obtained from a clinical isolate of M. tuberculosis, as well as the exploration of CbiX protein epitopes. The Rv0259c gene was isolated by PCR, cloned into the pGEM®-TEasy vector, and subsequently sub-cloned into the pTrcHisA expression vector. Sanger sequencing, followed by BLASTN and BLASTX analyses, confirmed the presence of the CbiX protein-encoding gene. The amino acid sequence was predicted using BioEdit v.7.0.11, and a three-dimensional (3D) model was generated using SwissModel. Exploration for both B and T-cell epitopes was conducted using IEDB Ellipro, MHCI, and MHCII tools, revealing highly immunogenic epitopes, indicating the potential of CbiX as a vaccine candidate. Alignment using MAFFT between the putative amino acid sequence and CbiX proteins available in the NCBI database identified an amino acid variation (A182), situated outside the B-cell epitopes but within the T-cell epitopes. In silicoanalysis of HLA allele frequency predicted vaccine coverage of 86.14%±10.77%, with two significant epitope cores identified: AASAHPHVT and RRVAVASFL (both highly antigenic and showing high-frequency HLA allele binding), suggesting the protein might be a potential antigen for a future vaccine candidate.

 

Doi: 10.28991/ESJ-2024-08-04-07

Full Text: PDF


Keywords


CbiX; Cloning; Expression; Mycobacterium tuberculosis; Rv0259c; B-cell-epitope; T-cell-epitope.

References


WHO. (2022). Global Tuberculosis Report 2022. World Health Organisation (WHO), Geneva, Switzerland. Available online: https://www.who.int/publications/i/item/9789240061729 (accessed on July 2024).

Gordon, S. V., & Parish, T. (2018). Microbe profile: Mycobacterium tuberculosis: Humanity’s deadly microbial foe. Microbiology (United Kingdom), 164(4), 437–439. doi:10.1099/mic.0.000601.

Sibuea, F., Hardhana, B., Widiantini, W. (2022). Indonesian Health Profile. Kementerian Kesehatan Republik Indonesia, Jakarta, Indonesia. Available online: https://www.kemkes.go.id/id/profil-kesehatan-indonesia-(accessed on July 2024) (In Indonesian).

Tornheim, J. A., & Dooley, K. E. (2017). Tuberculosis Associated with HIV Infection. Microbiology Spectrum, 5(1). doi:10.1128/microbiolspec.tnmi7-0028-2016.

Christof, C., Nußbaumer-Streit, B., & Gartlehner, G. (2020). WHO-Leitlinie: Prävention und Kontrolle von Tuberkulose-Infektionen. Das Gesundheitswesen, 82(11), 885–889. doi:10.1055/a-1241-4321. (In German).

Kuan, R., Muskat, K., Peters, B., & Lindestam Arlehamn, C. S. (2020). Is mapping the BCG vaccine-induced immune responses the key to improving the efficacy against tuberculosis? Journal of Internal Medicine, 288(6), 651–660. doi:10.1111/joim.13191.

Li, J., Zhao, A., Tang, J., Wang, G., Shi, Y., Zhan, L., & Qin, C. (2020). Tuberculosis vaccine development: from classic to clinical candidates. European Journal of Clinical Microbiology and Infectious Diseases, 39(8), 1405–1425. doi:10.1007/s10096-020-03843-6.

Wang, R., Fan, X., Jiang, Y., Li, G., Li, M., Zhao, X., Luan, X., Deng, Y., Chen, Z., Liu, H., & Wan, K. (2023). Immunogenicity and efficacy analyses of EPC002, ECA006, and EPCP009 protein subunit combinations as tuberculosis vaccine candidates. Vaccine, 41(26), 3836–3846. doi:10.1016/j.vaccine.2023.04.003.

Zhang, Y., Xu, J. C., Hu, Z. D., & Fan, X. Y. (2023). Advances in protein subunit vaccines against tuberculosis. Frontiers in Immunology, 14. doi:10.3389/fimmu.2023.1238586.

Naidu, A., Nayak, S. S., Lulu S, S., & Sundararajan, V. (2023). Advances in computational frameworks in the fight against TB: The way forward. Frontiers in Pharmacology, 14. doi:10.3389/fphar.2023.1152915.

Minias, A., Minias, P., Czubat, B., & Dziadek, J. (2018). Purifying selective pressure suggests the functionality of a vitamin B12 biosynthesis pathway in a global population of mycobacterium tuberculosis. Genome Biology and Evolution, 10(9), 2326–2337. doi:10.1093/gbe/evy153.

Modlin, S. J., Elghraoui, A., Gunasekaran, D., Zlotnicki, A. M., Dillon, N. A., Dhillon, N., Kuo, N., Robinhold, C., Chan, C. K., Baughn, A. D., & Valafar, F. (2021). Structure-Aware Mycobacterium tuberculosis Functional Annotation Uncloaks Resistance, Metabolic, and Virulence Genes. MSystems, 6(6). doi:10.1128/msystems.00673-21.

Kumar, A. (2008). Computational Annotation for Hypothetical Proteins of Mycobacterium Tuberculosis. Journal of Computer Science & Systems Biology, 01(01). doi:10.4172/jcsb.1000004.

Machtel, P., Bąkowska-Żywicka, K., & Żywicki, M. (2016). Emerging applications of riboswitches – from antibacterial targets to molecular tools. Journal of Applied Genetics, 57(4), 531–541. doi:10.1007/s13353-016-0341-x.

Ahmad, A., Agus, R., Massi, M. N., Handayani, I., & Karim, H. (2019). Cloning and characterization of Rv1980c gene encoding MPT64 Protein from Mycobacterium tuberculosis as a new candidate vaccine of tuberculosis. Journal of Physics: Conference Series, 1341(3), 032010. doi:10.1088/1742-6596/1341/3/032010.

Ye, J., Coulouris, G., Zaretskaya, I., Cutcutache, I., Rozen, S., & Madden, T. L. (2012). Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics, 13(134), 134. doi:10.1186/1471-2105-13-134.

Ahmad, A., Agus, R., Massi, M. N., Natzir, R., Madhyastha, R., Madhyastha, H. K., & Maruyama, M. (2018). Cloning and expression of MPT83 gene from Mycobacterium tuberculosis in E. coli BL21 as vaccine candidate of tuberculosis: A preliminary study. Journal of Genetic Engineering and Biotechnology, 16(2), 335–340. doi:10.1016/j.jgeb.2018.04.001.

Ahmad, A., Agus, R., Hidayah, N., Massi, M. N., Nurhasanah, A., & Karim, H. (2023). Cloning And Expression Of MPT83 Plus MPT64 Fusion Protein From Mycobacterium tuberculosis In Escherichia coli BL21 (DE3) Strain As Vaccine Candidate Of Tuberculosis. Rasayan Journal of Chemistry, 16(1), 297–306. doi:10.31788/RJC.2023.1618092.

Sambrook, J. and Russell, D.W. (2001) Molecular Cloning: A Laboratory Manual. (3rd Ed.). Cold Spring Harbor Laboratory Press, New York, United States.

Promega. (2015). pGEM®-T and pGEM®-T Easy Vector Systems. Promega, Madison, United States. Available online: https://worldwide.promega.com/products/pcr/pcr-cloning/pgem-t-easy-vector-systems/?catNum=A1360 (accessed on June 2024).

Hall, T. A. (1999). BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/ NT. Nucleic Acids Symposium Series, 41(41), 95–98.

Zhang, Z., Schwartz, S., Wagner, L., & Miller, W. (2000). A greedy algorithm for aligning DNA sequences. Journal of Computational Biology, 7(1–2), 203–214. doi:10.1089/10665270050081478.

Altschul, S. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389–3402. doi:10.1093/nar/25.17.3389.

Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., De Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., & Schwede, T. (2018). SWISS-MODEL: Homology modelling of protein structures and complexes. Nucleic Acids Research, 46(W1), W296–W303. doi:10.1093/nar/gky427.

Fujishiro, T., Shimada, Y., Nakamura, R., & Ooi, M. (2019). Structure of sirohydrochlorin ferrochelatase SirB: The last of the structures of the class II chelatase family. Dalton Transactions, 48(18), 6083–6090. doi:10.1039/c8dt04727h.

Berman, H. M. (2000). The Protein Data Bank. Nucleic Acids Research, 28(1), 235–242. doi:10.1093/nar/28.1.235.

Karimah, N., Sulfianti, A., & Nurhasanah, A. (2022). A bioinformatic approach towards designing a human papillomavirus vaccine based on L1 capsid protein sequence of HPV45. Indian Journal of Biochemistry and Biophysics, 59(9), 927–935. doi:10.56042/ijbb.v59i9.62010.

Ponomarenko, J., Bui, H. H., Li, W., Fusseder, N., Bourne, P. E., Sette, A., & Peters, B. (2008). ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 9. doi:10.1186/1471-2105-9-514.

Fleri, W. (2013) T Cell Epitopes - MHC Class I Binding Prediction Tools Description (IEDB), Durham, United Kingdom. Available online: https://help.iedb.org/hc/en-us/articles/114094151691-T-Cell-Epitopes-MHC-Class-I-Binding-Prediction-Tools-Description (accessed July 2024).

Reynisson, B., Alvarez, B., Paul, S., Peters, B., & Nielsen, M. (2020). NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Research, 48(W1), W449–W454. doi:10.1093/nar/gkaa379.

Hoof, I., Peters, B., Sidney, J., Pedersen, L. E., Sette, A., Lund, O., Buus, S., & Nielsen, M. (2009). NetMHCpan, a method for MHC class i binding prediction beyond humans. Immunogenetics, 61(1), 1–13. doi:10.1007/s00251-008-0341-z.

Jensen, K. K., Andreatta, M., Marcatili, P., Buus, S., Greenbaum, J. A., Yan, Z., Sette, A., Peters, B., & Nielsen, M. (2018). Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology, 154(3), 394–406. doi:10.1111/imm.12889.

Fleri, W. (2013) T Cell Epitopes - MHC Class II Binding Prediction Tools Description (IEDB), Durham, United Kingdom. Available online: https://help.iedb.org/hc/en-us/articles/114094151731-T-Cell-Epitopes-MHC-Class-II-Binding-Prediction-Tools-Description (accessed July 2024).

Doytchinova, I. A., & Flower, D. R. (2007). VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 8(4). doi:10.1186/1471-2105-8-4.

Bui, H. H., Sidney, J., Dinh, K., Southwood, S., Newman, M. J., & Sette, A. (2006). Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics, 7(153). doi:10.1186/1471-2105-7-153.

Sulfianti, A., Karimah, N., & Nurhasanah, A. (2023). In silico analysis of HLA-1 and HLA-2 recognition of a designed recombinant human papillomavirus vaccine based on L1 protein HPV subtype 45. Journal of Genetic Engineering and Biotechnology, 21(1), 167. doi:10.1186/s43141-023-00593-8.

Katoh, K., Rozewicki, J., & Yamada, K. D. (2017). MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Briefings in Bioinformatics, 20(4), 1160–1166. doi:10.1093/bib/bbx108.

Mariani, V., Biasini, M., Barbato, A., & Schwede, T. (2013). IDDT: A local superposition-free score for comparing protein structures and models using distance difference tests. Bioinformatics, 29(21), 2722–2728. doi:10.1093/bioinformatics/btt473.

Studer, G., Rempfer, C., Waterhouse, A. M., Gumienny, R., Haas, J., & Schwede, T. (2020). QMEANDisCo—distance constraints applied on model quality estimation. Bioinformatics, 36(6), 1765–1771. doi:10.1093/bioinformatics/btz828.

Cun, Y., Li, C., Shi, L., Sun, M., Dai, S., Sun, L., Shi, L., & Yao, Y. (2021). COVID-19 coronavirus vaccine T cell epitope prediction analysis based on distributions of HLA class I loci (HLA-A, -B, -C) across global populations. Human Vaccines and Immunotherapeutics, 17(4), 1097–1108. doi:10.1080/21645515.2020.1823777.

Minias, A., Gąsior, F., Brzostek, A., Jagielski, T., & Dziadek, J. (2021). Cobalamin is present in cells of non-tuberculous mycobacteria, but not in Mycobacterium tuberculosis. Scientific Reports, 11(1), 12267. doi:10.1038/s41598-021-91430-w.


Full Text: PDF

DOI: 10.28991/ESJ-2024-08-04-07

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Ahyar Ahmad, Abdul Karim, Rugaiyah Arfah, Rosana Agus, Rusdina Bte Ladju, Najdah Hidayah, Muhammad Nasrum Massi, Astutiati Nurhasanah, Harningsih Karim, Irda Handayani, Rizal Irfandi