Comprehensive analysis of genetic and evolutionary features of the hepatitis E virus

Abstract

BackgroundThe hepatitis E virus (HEV) is the causative pathogen of hepatitis E, a global public health concern. HEV comprises 8 genotypes with a wide host range and geographic distribution. This study aims to determine the genetic factors influencing the molecular adaptive changes of HEV open reading frames (ORFs) and estimate the HEV origin and evolutionary history.ResultsSequences of HEV strains isolated between 1982 and 2017 were retrieved and multiple analyses were performed to determine overall codon usage patterns, effects of natural selection and/or mutation pressure and host influence on the evolution of HEV ORFs. Besides, Bayesian Coalescent Markov Chain Monte Carlo (MCMC) Analysis was performed to estimate the spatial-temporal evolution of HEV. The results indicated an A/C nucleotide bias and ORF-dependent codon usage bias affected mainly by natural selection. The adaptation of HEV ORFs to their hosts was also ORF-dependent, with ORF1 and ORF2 sharing an almost similar adaptation profile to the different hosts. The discriminant analysis based on the adaptation index suggested that ORF1 and ORF3 could play a pivotal role in viral host tropism.ConclusionIn this study, we estimate that the common ancestor of the modern HEV strains emerged ~ 6000 years ago, in the period following the domestication of pigs. Then, natural selection played the major role in the evolution of the codon usage of HEV ORFs. The significant adaptation of ORF1 of genotype 1 to humans, makes ORF1 an evolutionary indicator of HEV host speciation, and could explain the epidemic character of genotype 1 strains in humans.

Codon usage analysis of zoonotic coronaviruses reveals lower adaptation to humans by SARS-CoV-2

“…Because the genetic code is redundant in most organisms, during the adaptation to their hosts, viruses can modify codon usage therefore protein synthesis efficiency while maintaining the amino acid sequences, leading to changes in viral replication ( Chen et al, 2020 ). Effective number of codons (ENC) and codon adaptation index (CAI) analyses are frequently used to evaluate the codon usage patterns of viruses ( Baha et al, 2019 ; Belalov and Lukashev, 2013 ; Khandia et al, 2019 ; Li et al, 2018b ; Stoletzki and Eyre-Walker, 2007 ; Zhang et al, 2019 ). Between them, ENC values are measurements of codon preference ( Comeron and Aguadé, 1998 ), while CAI is an indirect measurement of the likely expression efficiency of viral genes in the host ( Carbone et al, 2003 ; Chen et al, 2020 ).…”

A comparative genomics-based study of positive strand RNA viruses emphasizing on SARS-CoV-2 utilizing dinucleotide signature, codon usage and codon context analyses

“…The human ribosomal protein coding genes were used as reference for measuring CAI. CAI is of great importance for estimating translational efficiency and predicting cellular protein levels ( Baha et al, 2019 ). SCUO ranges from 0 to 1, and represents the synonymous codon usage bias ( Wan et al, 2004b ) which is mainly based on Shannon Information theory explaining entropy of codon sequences of genes ( Behura and Severson, 2012 ).…”

“…Codon pair utilization bias present in each of the different organisms can be better explored through this parameter to infer on phylogeny ( Moura et al, 2011 ). Codon context analysis was carried out using the software ANACONDA 2 to generate the frequency table of codon pair context ( Baha et al, 2019 ), and followed by subsequent statistical analysis, to identify preferred set of codon pairs in a coding sequence ( Nasrullah et al, 2015 ; Pal et al, 2015 ). Along with codon context analysis, the codon pair ratio or CP R was also calculated for each viral genome to find out how many codon pairs have been utilized in coding the different coding sequences relative to the number of codon pairs combinations that are feasible ( Pal et al, 2015 ).…”

Mechanism of Cross-Species Transmission, Adaptive Evolution and Pathogenesis of Hepatitis E Virus

“…When the ORFs were analyzed separately, ORF1 and ORF3 were demonstrated to more efficiently separate the HEV strains into anthropotropic and enzootic genotypes, suggesting their evolutionary role in host species tropism [ 157 , 158 , 162 ]. Consistent with the broad host range of enzootic HEV genotypes, the HVR of ORF1 in HEV-3 and HEV-4 is around two-fold more heterogenous than that in HEV-1 [ 162 ], and the analysis of the relative synonymous codon usage values of ORF3s showed that the HEV strains were grouped into only two clusters consisting of the HEV-1 and HEV-2 strains (anthropotropic genotypes), and a cluster of the remaining strains (HEV-3–8, enzootic genotypes) [ 158 ]. On the other hand, ORF2 was previously thought to be the viral determinant of host tropism, since it encodes the capsid (the only structural protein) that possibly binds to unknown host cell receptors [ 141 , 163 , 164 , 165 ].…”

“…The common ancestor of the modern HEV strains emerged approximately 6800 years ago, following the domestication of pigs and intensification of agriculture. Domestication caused adaptive changes in the common ancestor leading to the emergence of both human-restricted (HEV-1 and HEV-2) and zoonotic (HEV-3 and HEV-4) strains [ 158 ]. An analysis performed before the identification of the wild boar- and camel-derived genotypes (HEV-5 to HEV-8) indicated that the ancestor of all Orthohepevirus A was enzootic [ 169 ].…”