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An Immunoinformatics-Based Study of Mycobacterium tuberculosis Region of Difference-2 Uncharacterized Protein (Rv1987) as a Potential Subunit Vaccine Candidate for Preliminary Ex Vivo Analysis

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Abstract

Mycobacterium tuberculosis (Mtb) is the pathogen that causes tuberculosis and develops resistance to many of the existing drugs. The sole licensed TB vaccine, BCG, is unable to provide a comprehensive defense. So, it is crucial to maintain the immunological response to eliminate tuberculosis. Our previous in silico study reported five uncharacterized proteins as potential vaccine antigens. In this article, we considered the uncharacterized Mtb H37Rv regions of difference (RD-2) Rv1987 protein as a promising vaccine candidate. The vaccine quality of the protein was analyzed using reverse vaccinology and immunoinformatics-based quality-checking parameters followed by an ex vivo preliminary investigation. In silico analysis of Rv1987 protein predicted it as surface localized, secretory, single helix, antigenic, non-allergenic, and non-homologous to the host protein. Immunoinformatics analysis of Rv1987 by CD4 + and CD8 + T-cells via MHC-I and MHC-II binding affinity and presence of B-cell epitope predicted its immunogenicity. The docked complex analysis of the 3D model structure of the protein with immune cell receptor TLR-4 revealed the protein’s capability for potential interaction. Furthermore, the target protein-encoded gene Rv1987 was cloned, over-expressed, purified, and analyzed by mass spectrometry (MS) to report the target peptides. The qRT-PCR gene expression analysis shows that it is capable of activating macrophages and significantly increasing the production of a number of key cytokines (TNF-α, IL-1β, and IL-10). Our in-silico analysis and ex vivo preliminary investigations revealed the immunogenic potential of the target protein. These findings suggest that the Rv1987 be undertaken as a potent subunit vaccine antigen and that further animal model immuno-modulation studies would boost the novel TB vaccine discovery and/or BCG vaccine supplement pipeline.

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Abbreviations

RD:

Region of difference

MDR:

Multidrug-resistant

XDR:

Extreme drug-resistant

MTBC:

Mycobacterium tuberculosis Complex bacteria (MTBC)

MD:

Molecular dynamics

Mtb :

Mycobacterium tuberculosis

BCG:

Bacille Calmette-Guérin

WHO:

World Health Organization

RMSD:

Root mean square deviations

TLR:

Tool-like receptors

MHC:

Major histocompatibility complex

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Acknowledgements

The authors would like to acknowledge the Bioinformatics, Immunology, and Plant Molecular Biology laboratory facilities of School of Biotechnology, KIIT Deemed to be University, Bhubaneswar, for completion of the research work. In addition, the authors would like to acknowledge KIIT Deemed to be University, Odisha, India, and Ethiopia Federal Democratic Republic Ministry of Education Addis Ababa and National Veterinary Institute, Debre Zeit, Ethiopia, for providing the financial support to conduct the PhD research work.

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  1. School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India

    Aregitu Mekuriaw Arega, Ajit Kumar Dhal, Kali Prasad Pattanaik, Sasmita Nayak & Rajani Kanta Mahapatra

  2. National Veterinary Institute, Debre Zeit, Ethiopia

    Aregitu Mekuriaw Arega

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Contributions

AMA contributed to performing and analyzing the in silico and wet lab experiments as well as writing the manuscript. AKD performed the MD simulation and data analysis of the results. KPP contributes towards the MTT assay and cytokine analysis of the identified vaccine candidate. SN provided the chemicals and Petri plates and co-supervised the study. RKM conceived the project, supervised the whole study, and corrected the manuscript.

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Correspondence to Rajani Kanta Mahapatra.

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Arega, A.M., Dhal, A.K., Pattanaik, K.P. et al. An Immunoinformatics-Based Study of Mycobacterium tuberculosis Region of Difference-2 Uncharacterized Protein (Rv1987) as a Potential Subunit Vaccine Candidate for Preliminary Ex Vivo Analysis. Appl Biochem Biotechnol 196, 2367–2395 (2024). https://doi.org/10.1007/s12010-023-04658-9

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