Revolutionizing Nipah virus vaccinology: insights into subunit vaccine development strategies and immunological advances

Abstract

The Nipah virus (NiV), a zoonotic virus in the Henipavirus genus of the Paramyxoviridae family, emerged in Malaysia in 1998 and later spread globally. Diseased patients may have a 40- 70% chance of fatality depending on the severity and early medication. The recent outbreak of NiV was reported in Kerala (India) by a new strain of MCL-19-H-1134 isolate. Currently, no vaccines are available, highlighting the critical need for a conclusive remedy. Our study aims to develop a subunit vaccine against the NiV by analyzing its proteome. NiV genome and proteome sequences were obtained from the NCBI database. A phylogenetic tree was constructed based on genome alignment. T-cell, helper T-cell, and B-cell epitopes were predicted from the protein sequences using NetCTL-1.2, NetMHCIIPan-4.1, and IEDB servers, respectively. High-affinity epitopes for human receptors were selected to construct a multi-epitope vaccine (MEV). These epitopes' antigenicity, toxicity, and allergenicity were evaluated using VaxiJen, AllergenFP-v.1.0, and AllergenFP algorithms. Molecular interactions with specific receptors were analyzed using PyRx and ClusPro. Amino acid interactions were visualized and analyzed using PyMOL and LigPlot. Immuno-simulation was conducted using C-ImmSim to assess the immune response elicited by the MEV. Finally, the vaccine cDNA was inserted into the pET28a(+) expression vector using SnapGene tool for in silico cloning in an E. coli host. The potential for an imminent outbreak cannot be overlooked. A subunit vaccine is more cost-effective and time-efficient. With additional in vitro and in vivo validation, this vaccine could become a superior preventive measure against NiV disease.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00246-9.

Keywords: Immune simulation; In-silico cloning; Multi epitope; Nipah virus; Subunit vaccine; Toll-like receptor 3.

Fig. 1

A flow chart showing the methodology applied to identify the peptide epitope and its interaction with specific receptors

Fig. 2

Phylogenetic tree of selected NiV strains

Fig. 3

Linear RNA genome of NiV MCL-19-H-1134 isolates 2023 strain

Fig. 4

B-cell epitope prediction by IEDB server. The line above the threshold (yellow) represents B-cell epitope and the line below the threshold (green) does not. Average: 0.582 Minimum: 0.261 Maximum: 0.729 Center position: 4 Threshold: 0.500

Fig. 5

Population conservancy analysis of epitope RETDLVHLE, KNLSVPAKD, and AIPFTPKNL across different countries of the world

Fig. 6

Interaction of RETDLVHLE with HLA DP and amino acid interaction is visualized through Ligplot software

Fig. 7

Interaction of RETDLVHLE with HLA DQ and amino acid interaction is visualized through Ligplot software

Fig. 8

Interaction of AIPFTPKNL with HLA C and amino acid interaction is visualized through Ligplot software

Fig. 9

Interaction of YRSIEGSR with HLA DR and amino acid interaction is visualized through Ligplot software

Fig. 10

Interaction of KNLSVPAKD with HLA DP and amino acid interaction is visualized through Ligplot software

Fig. 11

NiV vaccine immune simulation. (a) Antigen and immunoglobulins (b) Concentration of cytokines and interleukins. D in the inset plot is danger signal. (c) Plasma B lymphocytes count sub-divided per isotype (d) CD4 T-helper lymphocytes count. The plot shows total and memory counts. (e) CD8 T-cytotoxic lymphocytes count. Total and memory shown. (f) Natural Killer cells (total count). (g) Dendritic cells; The curves show the total number broken down to active, resting, internalized and presenting the ag. (h) Plasma B lymphocytes count sub-divided per isotype (i) B lymphocytes population per entity-state (j) CD8 T-cytotoxic lymphocytes count per entity-state (k) CD4 T-helper lymphocytes count sub-divided per entity-state (l) MA population per state

Fig. 12

Structure prediction and validation of MEV candidate. (a) Tertiary structure od MEV. (b) Schematic representation of MEV formulation. (c, d) Secondary structure and topology of MEV candidate predicted by PDBsum server. (e) Ramachandran plot of MEV tertiary structure

Fig. 13

Molecular docking of MEV. (a) MEV-MHC class I complex. (b) MEV-MHC class II complex

Fig. 14

(a) Amino acid residue interaction between MHC-I (chain D) and vaccine (chain C). (b, c) Amino acid interaction between MHC-II (chain D, B) and vaccine (chain C). (d) Ramachandran plot of MEV-MHCI complex tertiary structure. (e) Ramachandran plot of MEV-MHC-II complex tertiary structure

Fig. 15

In silico cloning of formulated vaccine in pET28a(+)