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Citation: Pallavi S, Vijai S, M Arshad (2008) Modeling of RNA Secondary Structure of Non Structural Gene and Evolutionary
Stability of the Influenza Virus Through In Silico Methods. J Proteomics Bioinform 1: 219-226.
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Copyright: © 2008 Pallavi S, etal. This is an open-access article distributed under the terms of the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and
source are credited.
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Abstract
An influenza virus is an important pathogen causing disease in the birds and further transmits to humans
globally. The genome of Influenza virus encodes highly conserved non structural gene (NS1), which is thermodynamically
stable in the evolution. Total 32 NS1 nucleotide sequences of Influenza A virus H5N1 strain varied
from 831 to 875 bp were used to construct the phylogeny and nine major clades were obtained. The computational
tool was used to model the RNA secondary structure of nine different strains of Influenza A virus. The
thermodynamic free energy ranges between -222.90 to-251.10 Kcal/mol of the NS which may provide new insight
to understand the evolutionary stability and pathogenesis of Influenza virus.
Keywords
Influenza Avirus; NS1; RNA secondary structure; free energy; evolution
Introduction
An outbreak of avian influenza A virus of the H5N1
subtype was spread to poultry in Asian countries. The transmission
of influenza virus from birds to humans in Hong
Kong with outbreaks H5N1 strains of avian influenza A
virus Hiorrimoton et al (2005) and highly pathogenic influenza
A virus H5N1 was identified among the poultry in republic
of Korea Fouchier et al (2005). An outbreak of highly
pathogenic avian influenza (HPAI) H5N1 virus was reported
from India in 2006. Phylogenetic analyses revealed that
Indian isolates were grouped in the mixed-migratory bird
sub-lineage of the Eurasian lineage. In the phylogeny analysis
viruses were probably introduced to India from China via
Europe because they share a direct ancestral relationship
with the Indian isolates Kamal et al (2007).
Influenza viruses are pleomorphic RNA viruses belonging
to the Orthomyxoviridae family. The genome of influenza virus is segmented and consists of single stranded negative
sense RNA; it encodes the 8 structural proteins and
non structural gene (NS1). The Influenza virus proteins such
as two surface proteins hemagglutinin (HA) and neuraminidase
(NA)Fouchier et al (2005) and other proteins like
three RNA polymerase (PA, PB1 and PB2). Nucleoprotein
(NP) and matrix protein (M1 and M2) also play role in the
cell cycle. The non structural gene (NS1) provides evolutionary
stability and replication of Influenza virus Wan et al
(2007).
Several reports are available on the role of NS of the
Influenza virus. The avian influenza virus NS encoding protein
induces the apoptosis in the human Lam et al (2008).
The NS protein contributes in the pathogenesis and small
fragment have deleted from the NS gene that have been
reported as the attenuated vaccine for the chickens Zhu et al (2008). The influenza virus subtype H5N1 has raised
concerns of a possible human pandemic threat because of
its high virulence and mutation rate Landon et al (2008).
Highly pathogenic H5N1 influenza viruses have become
endemic in poultry populations throughout Southeast Asia
and continue to infect humans with a greater than 50% case
fatality rate Neumann et al (2007).
The phylogenetic and proteome analysis of influenza A
virus subtype H5N1 have been earlier reported. The study
furnish a understanding of the whole proteome function, gene
regulation and may be also supportive to vaccine and antiviral
drug target to inhibit the functioning of influenza at the
specific position of predicted motifs Somvanshi a, et al
(2008). The antigenic epitopes were also reported in two
highly virulence surface proteins HA and NA of influenza A
virus. The host specific epitopes and conserved epitopes
have been identified. These results could help in development
of immunodiagnostic kit and also designing of vaccine
candidate Somvanshi b, et al (2008).
There are limited reports available on RNA secondary
structure of the NS in influenza virus. This conformational
shift may consequences for splicing regulation of segment
mRNA. This study suggest that besides changes at the protein
level, changes in RNA secondary structure should be
seriously considered when attempting to explain influenza
virus evolution Gultyaev et al (2007).
A varied number of bioinformatics tools were reported
to generate the RNA secondary structure of viral gene like
RNAdraw, RNAfold, Mfold etc. MFold uses the nearest
neighbor energy rules to calculate the energy of the RNA
secondary structure. RNA structure plays an important role
in the life cycle of RNA viruses. Many functional viral RNA
structure are known and evolution of virus RNA genome is
subjected to various structure constrains Simmonds et al
(2004). In the present study, we have predicted the secondary
structure of non structural gene of Influenza A virus
subtype H5N1. The free energy of the module of non structural
gene may predict the evolutionary stability of different
host specific strains of Influenza A virus.
Material and Methods
Selection of Sequence Data Set
The complete nucleotide sequences of non-structural
proteins from different goose, chicken, turkey, swine, swan
and duck of Influenza A virus H5N1 strains were retrieved
from the biological database such as National Centre for
Biotechnology Information NCBI) cited at http://www.ncbi.nlm.nih.gov.
Construction and Analysis of Phylogenetic Tree
All the sequences were aligned with Clustal X2. The
computed alignment was manually checked and corrected.
Pair-wise evolutionary distances were computed using the
Jukes and Cantor equation implemented in the MEGA 3.1
program and a phylogenetic tree was constructed by neighbor-
joining method which comprise DNA weight matrix for
nucleotide. Bootstrapped values of 100 were sampled to
determine a measure of support for each node on the consensus
tree.
RNA Secondary Structure Prediction
Prediction of the possible folding of the non structural
protein of influenza virus was done with the online MFold
package. The most widely used algorithms for RNA secondary
structure prediction, which are based on a search
for the minimal free energy state Zuker (1989).The genetic
algorithm (GA) simulates the natural folding pathway which
takes place during RNA synthesis. This is not only enables
new stems added to growing RNA chain but also allows
structures to be removed at later stages of the simulation if
other pairings are found to be more favourable. The GA
also allows the prediction of certain tertiary interactions,
including RNA pseudoknots. The minimum free energy was
obtained from the secondary structure of RNA.
Results and Discussion
The size of non structural gene diverge from 831 to 875
bp was used to construct the phylogenetic relationship. All
the 32 strains of influenza A virus subtype H5N1 were isolated
from a diverse series of animal hosts like Goose,
Chicken, Turkey, Swine, Swan and Duck. In this investigation,
nine major clades were obtained from the six host strains
of influenza A virus (Fig. 1). The four major clades in the
phylogenetic tree based on the surface HA and NA proteins
of influenza A virus H5N1 has been reported Somvanshi
a et al (2008).
The RNA secondary structure of NS gene of influenza
A virus showed the lowest free energy -251.10 Kcal/mol
from the host swine. The highest free energy in the analysis
of the duck strain was -221.70 Kcal/mol. The free energy
value of all these NS of different strains of influenza A virus
was given (Table 1 ). The prediction of evolutionarily conserved
RNA structures important for elucidating the potential
functions of RNA sequences and the mechanisms by which these functions are exerted but it also lies at the core
of RNA gene prediction. An accurate prediction of the conserved
RNA structure needs a high-quality sequence alignment
and an evolutionary tree relating several evolutionarily
related sequences.
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Figure 1: Unrooted phylogenetic tree based on NS1 gene of different strains of Influenza A virus H5N1. The bar represents
0.001 base changes per site.
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Table 1: The thermodynamic free gibbs energy (ä G) of Influenza A virus H5N1
nonstructural gene (NS1).
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Computational tool was used to model the RNA
secondary structure in coding region of hepatitis C virus
(HCV) includes thermodynamic prediction, calculation of
free energy on folding, and a newly developed method to
scan sequences for covariant sites and associated secondary
structures using a parsimony-based algorithm. Total six
evolutionary conserve stem-loop structures in the NS5Bencoding
region and two in the core gene. The virus most
closely relate to HCV, GB virus-B (GBV-B) also showed
evidence for similar internal base pairing in its coding region,
although predictions of secondary structures were limited
by the absence of comparative sequence data for this
virus Tuplin et al (2002).
The secondary structure RNA non structural gene
of influenza A virus provides stability of the genome during
evolution and adaptation in the infection to various hosts.
This gene is highly conserved in the genome of influenza A
virus and slight variation in the size. The confirmation of
secondary structure was assorted due to mutation in the
NS gene. The mutation of the NS region possibly will be
reducing the pathogenesis of influenza virus. The secondary
structure of RNA of NS of influenza A virus was given
(Fig. 2A-2I). In 2001 and 2003, two influenza A virus H5N1,
A/swine/Fujian/1/01 (SW/FJ/01) and A/swine/Fujian/1/03
(SW/FJ/03) isolated from pigs in Fujian Province, southern
China was studied. Both the virus were genetically similar,
although the NS gene of the SW/FJ/03 virus has a 15-nucleotide deletion at coding positions 612 to 626. The small fragment
deleted from the NS gene that have used as the attenuated
vaccine for the chickens Zhu et al (2008). Secondary
structure models exhibited three pairs of small subunit
ribosomal RNA molecules. These are the 16S rRNA
from E. coli cytoplasmic and Z. mays chloroplast ribosomes,
the 18S rRNA from S. cerevisiae and X. laevis cytoplasmic
ribosomes, and the 12S rRNA from human and mouse
mitochondrial ribosomes. The model supports the concept
that secondary structure of ribosomal RNA has been extensively
conserved throughout the evolution Zwieb et al
(1981).
The 5S rRNA gene from Sphingobium
chungbukense DJ77 was identified. The secondary structure
of the 199-base-long RNA was proposed. The twobase-
long D loop was the shortest among all of the known
5S rRNAs. The U19-U64 non-canonical pair in the helix II
region was uniquely found in strain DJ77 among all of the
sphingomonads Kwon and Kim (2007). The nucleotide sequence
of Pinus silvestyris 5S rRNA was determined using
two independent methods and compared with other plant
5S rRNAs. It shows more than 90% sequence homology
with gymnosperm 5S RNAs. The free energy (delta G)
analysis of 5S rRNAs from gymnosperms, angiosperms and
the other higher plants revealed that the free energy of this
ribosomal RNA decreases with evolutionMashkova et al
(1990).
Hepatitis C virus (HCV) possesses extensive RNA secondary
structure in the core and NS5B-encoding regions of
the genome. A program was developed
(STRUCTUR_DIST) that analyses multiple RNA-folding
patterns predicted by MFOLD to determine the evolutionary
conservation of predicted stem–loop structures by a new
method, to analyze frequencies of covariant sites in predicted
RNA folding between HCV genotypes Tuplin et al
(2004).
RNA secondary structure prediction was combined with
comparative sequence analysis to construct models of folding
for the distal 380 nucleotides of the 3‘-untranslated region
(3‘-UTR) of yellow fever virus (YFV). A number of
structural elements that are thermodynamically stable, conserved
in shape, and confirmed by compensatory mutations
were revealed. At the same time structural polymorphisms
were observed among strains of YFV. The observation of a
strong association between secondary structure of the 3‘-
UTR and virulence of YFV may help elucidate the molecular
mechanisms of virus attenuation and lead to new strategies
of vaccine development directed towards rational modification
of secondary structure of the 3‘-UTR. In this study,
the free energy value of pathogenic YFV was higher and
non pathogenic YFV was lower Proutski et al (1997).
In conclusion, this study was carried out for the modeling
of RNA secondary structure and phylogenetic analysis
of influenza A virus H5N1. The prediction of RNA structure
in conjunction with structure known to exist within the
virus untranslated region may facilitate further understanding
of virus translation, replication and packaging. The free
energy of the conserved NS gene may help to understand
the stability of influenza A virus through out the evolution.
Acknowledgement
The authors are thankful to Indian Council of Medical
Research, New Delhi for providing financial support and
also appreciate critical suggestions provided by Mr.
Indramani and Mr. D. K. Chaudhary during the preparation
of manuscript.
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