A comparative genomic approach to decipher the mutations associated with Nipah viral human isolates from southeast Asia

Norine  Norbert Dsouza; Selvaa Kumar Chellasamy

doi:10.18502/ijm.v16i1.14879

Norine Norbert Dsouza Department of Bioinformatics, School of Biotechnology and Bioinformatics, Sector 15, CBD Belapur, Navi Mumbai, Maharashtra, India
Selvaa Kumar Chellasamy Department of Bioinformatics, School of Biotechnology and Bioinformatics, Sector 15, CBD Belapur, Navi Mumbai, Maharashtra, India

DOI: https://doi.org/10.18502/ijm.v16i1.14879

Keywords: Nipah virus; Phylogeny; Synonymous mutations; Mutations; Host-pathogen interaction

Abstract

Background and Objectives: Multiple outbreaks over two decades and a high mortality rate have emphasized the Nipah virus (NiV) as a priority research area. The study focuses on identifying the mutational landscape in sequences from NiV human isolates from different geographical regions.

Materials and Methods: Thirty-seven NiV genomes of human samples from Malaysia, Bangladesh, and India were subject- ed to phylogeny and metagenomic analysis to decipher the genome variability using MEGA11 software and the meta-CATS web server. Using the Single-Likelihood Ancestor Counting method, the synonymous and nonsynonymous mutations among NiV genes were identified. Further, the nonsynonymous variations were used to identify mutations in all the NiV proteins. Results: The NiV isolates were categorized into NiV-M, NiV-B, and NiV-I clades based on phylogenetic analysis. Metag- enomic analysis revealed 1636 variations in the noncoding and coding regions of the genomes of the three clades of NiV. Further analysis of nonsynonymous mutations showed the phosphoprotein to be highly mutating, whereas the matrix protein was stable.

Conclusion: Deciphering the mutation pattern using a comparative genomics approach for human isolates provided valuable insight into the stability of NiV proteins which can be further used for understanding variations in host-pathogen interaction and developing effective therapeutic measures.