Vol.2, No.10, 1138-1147 (2010) Natural Science
http://dx.doi.org/10.4236/ns.2010.210141
Copyright © 2010 SciRes. OPEN ACCESS
Correlated mutations in the four influenza proteins
essential for viral RNA synthesis, host adaptation,
and virulence: NP, PA, PB1, and PB2
Wei Hu
Department of Computer Science, Houghton College, Houghton, USA; wei.hu@houghton.edu.
Received 12 July 2010; revised 20 August 2010; accepted 23 August 2010.
ABSTRACT
The NP, PA, PB1, and PB2 proteins of influenza
viruses together are responsible for the tran-
scription and replication of viral RNA, and the
latter three proteins comprise the viral poly-
merase. Two recent reports indicated that the
mutation at site 627 of PB2 plays a key role in
host range and increased virulence of influenza
viruses, and could be compensated by multiple
mutations at other sites of PB2, suggesting the
association of this mutation with those at other
sites. The objective of this study was to analyze
the co-mutated sites within and between these
important proteins of influenza. With mutual
information, a set of statistically significant co-
mutated position pairs (P value = 0) in NP, PA,
PB1, and PB2 of avian, human, pandemic 2009
H1N1, and swine influenza were identified,
based on which several highly connected net-
works of correlated sites in NP, PA, PB1, and
PB2 were discovered. These correlation net-
works further illustrated the inner functional
dependence of the four proteins that are critical
for host adaptation and pathogenicity. Mutual
information was also applied to quantify the
correlation of sites within each individual pro-
tein and between proteins. In general, the inter
protein correlation of the four proteins was
stronger than the intra protein correlation. Fi-
nally, the correlation patterns of the four pro-
teins of pandemic 2009 H1N1 were found to be
closer to those of avian and human than to
swine influenza, thus rendering a novel insight
into the interaction of the four proteins of the
pandemic 2009 H1N1 virus when compared to
avian, human, and swine influenza and how the
origin of these four proteins might affect the
correlation patterns uncovered in this analysis.
Keywords: Co-mutation; Entropy; Influenza;
Mutation; Mutual Information; Pandemic 2009 H1N1;
Polymerase
1. INTRODUCTION
There are eight single-stranded RNA gene segments in
the influenza A virus, which are present as ribonucleo-
protein complexes (vRNPs) with nucleoprotein (NP) and
polymerase within the virus particle. The viral poly-
merase itself is a heterotrimer composed of two basic
subunits PB1 and PB2, and one acidic subunit PA, which
catalyzes the transcription of viral RNA (vRNA) to
mRNA and the replication of vRNA to complementary
RNA (cRNA). The primary function of NP is to assem-
ble the RNA gene segments into a helical nucleocapsid
to provide structural support in vRNPs. After infection,
vRNPs are transported into the nucleus where the tran-
scription and replication of the viral genome take place,
which means it is the vRNP, rather than the vRNA, that
is utilized as the template for transcription and replica-
tion. Moreover, NP could also function as a multifunc-
tional key adaptor for interactions between virus and
host cell [1,2].
The influenza polymerase also plays an important role
in host adaptation and pathogenicity, and mutations at
sites 627,701, and 714 in PB2, 615 in PA, and 319 in NP
could result in enhanced polymerase activity to facilitate
cross species transmission and virulence [3]. A focal
poultry outbreak in Manipur, India in 2007 was caused
by a unique influenza A (H5N1) virus that contained two
unique amino acid mutations, K116R and I411M, in the
PB2 protein [4]. Additionally, several other mutations in
PA, PB1, and PB2 were also shown to influence the po-
lymerase activity [5-12]. Furthermore, the interaction of
NP and PB2 with Importin α1 was found to be a deter-
minant of host range as well [13].
The well-known mutation E627K in PB2 is a deter-
minant marker for host shifts between avian and human
W. Hu / Natural Science 2 (2010) 1138-1147
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viruses and increased virulence. However, accumulating
evidence demonstrated that the mutation at position 627
in PB2 could be compensated by multiple mutations at
other sites of PB2 [14,15], implying that mutations in
proteins tend to co-occur at different sites to compensate
each other in order to maintain the structural and func-
tional constraints. To extend our knowledge of the co-
mutations in the proteins of influenza, this study em-
ployed entropy and mutual information to analyze co-
varying sites in NP, PA, PB1, and PB2 and to uncover a
set of statistical significant co-mutated sites to reveal and
quantify the interactions of these proteins that play a key
role in the life cycle of the influenza viruses.
Information theory including entropy and mutual in-
formation (MI) enjoyed wide applications in sequence
analysis. Mutual information was employed to identify
groups of covariant mutations in the sequences of HIV-1
protease and to distinguish the correlated amino acid
polymorphisms resulting from neutral mutations and
those induced by multi-drug resistance [16]. With en-
tropy, a simple informational index was proposed in [17]
to reveal the patterns of synonymous codon usage bias.
Further, mutual information was utilized in the construc-
tion of site transition network based on 4064 HA1 of
A/H3N1 sequences from 1968 to 2008, which was able
to model the evolutionary path of the influenza virus and
to predict seven possible HA mutations for the next an-
tigenic drift in the 2009-2010 season [18]. Recently, en-
tropy and mutual information were also applied to in-
dentify critical positions and co-mutated positions on
HA for predicting the antigenic variants [19]. In another
report, sequence data of 1032 complete genomes of in-
fluenza A virus (H3N2) during 1968-2006 were used to
construct networks of genomic co-occurrence to describe
H3N2 virus evolutionary patterns and dynamics. It sug-
gested that amino acid substitutions corresponding to
nucleotide co-changes cluster preferentially in known
antigenic regions of HA [20].
To investigate the co-mutations in the proteins of in-
fluenza, three separate tasks were performed in this
study. The first task was to uncover the variation and
co-variation patterns of proteins NP, PA, PB1, and PB2
by the entropy and mutual information computed from
their concatenated amino acid sequences. The distribu-
tions of entropy and MI obtained reflected the unique
sequence characteristics of each protein of avian, human,
pandemic 2009 H1N1, and swine influenza viruses,
based on which a comparative analysis could be con-
ducted to reveal the variation signature of each influenza
species. The second task was to zoom in onto each posi-
tion pairs in the four proteins to identify a set of statisti-
cally significant co-mutated residue pairs (P value = 0),
from which several networks of highly correlated sites
could be inferred. These correlated pairs and networks of
correlated sites presented, at a different scale, finer in-
formation about the co-variation of these four proteins
than that from task one. In a sense, the correlation in-
formation obtained from task two was pair dependent,
i.e., it was about pairs. The third task was to mine the
association of these four proteins with a pair independent
approach, where the locations of pairs with positive MI
values were counted according to each protein or to each
functional domain in a protein as described in [21]. The
strength of association was measured by the averaged
counts of correlated pairs located within each protein or
between proteins.
2. MATERIALS AND METHODS
2.1. Sequence Data
The protein sequences of influenza A virus employed
in this study were downloaded from the Influenza Virus
Resource of the National Center for Biotechnology In-
formation (NCBI). All the NP, PA, PB1, and PB2 protein
sequences from the same isolates were concatenated into
single sequences, and there were 1520 such concatenated
sequences of avian viruses, 1928 of human viruses, 164
of pandemic 2009 H1N1, and 232 of swine viruses.
These concatenated sequences, rather than the individual
protein sequences, were used in our analysis. All the se-
quences utilized in the study were aligned with MAFFT
[22].
2.2. Entropy and Mutual Information
In information theory [23,24], entropy is a measure of the
uncertainty associated with a random variable. Let x be a
discrete random variable that has a set of possible values
123
{,, ,}
n
aaa awith probabilities123
,,, n
pp ppwhere
the entropy H of
x
is
ii i
H
xplogp
The mutual information of two random variables is a
quantity that measures the mutual dependence of the two
variables or the average amount of information that
x
conveys about y, which can defined as

I
x,y HxHyHx,y
where H(x) is the entropy of x, and H(x,y) is the joint
entropy of x and y. I (x, y) = 0 if and only if x and y are
independent random variables.
In the current study, each of the N columns in a multi-
ple sequence alignment of a set of influenza protein se-
quences of length N is considered as a discrete random
variable i
x
(1 i N) that takes on one of the 20 (n =
20) amino acid types with some probability. H(i
x
) has
its minimum value 0 if all the amino acids at position i
are the same, and achieves its maximum if all the 20
W. Hu / Natural Science 2 (2010) 1138-1147
Copyright © 2010 SciRes. OPEN ACCESS
1140
amino acid types appear with equal probability at posi-
tion i, which can be verified by the Lagrange multiplier
technique. A position of high entropy means that the
amino acids are often varied at this position. While H
(i
x
) measures the genetic diversity at position i in our
current study, I (i
x
,
j
y) measures the correlation be-
tween amino acid substitutions at positions i and j.
2.3. Mutual Information Evaluation
In order to assess the significance of the mutual in-
formation value of two positions in a multiple sequence
alignment, it is necessary to show that this value is sig-
nificantly higher than that based on random sequences.
For each pair of positions in a multiple protein sequence
alignment, we randomly permuted the amino acids from
different sequences at the two positions and calculated
the mutual information of these random sequences. This
procedure was repeated 1000 times. The P value was
calculated as the percentage of the mutual information
values of the permuted sequences that were higher than
those of the original sequences.
3. RESULTS
3.1. Entropy and Mutual Information of NP,
PA, PB1, and PB2
To gain a global view of the sequence variation and
co-variation of these four proteins, the entropy and mu-
tual information of their concatenated sequences were
calculated (Figure 1). The entropy distributions revealed
that the swine influenza had the highest overall sequence
variation and the pandemic 2009 had the least variation,
with avian and human influenza being in the middle.
Within each individual influenza species, it appeared
that PA had the highest entropy average among the four
proteins, with the exception of pandemic 2009 H1N1
(Table 1). Mutual information measures the correlation
of the amino acids at two sites in a multiple sequence
alignment. Therefore, to offer the information of how
each site co-mutated with all other sites within each in-
dividual protein and between proteins, for each site, all
the MI values associated with this site were summed
(Figure 1).
These MI values represented the association between
one site and all other sites in the four proteins. The pat-
terns of MI distributions were quite different from those
of entropy, where the ranking of the overall average MI
values was swine (5.9533), human (3.6590), avian (0.
8298), and pandemic 2009 H1N1 (0.0165), suggesting
that variation and co-variation were two distinct meas-
urements of protein sequence changes. The most co-
varying protein in each influenza species was PA in
avian, PB1 in human, PA in pandemic 2009 H1N1, and
PA in swine (Table 1).
3.2. Highly Correlated Sites in NP, PA, PB1,
and PB2
In order to provide more detailed information about
the highly correlated sites, top 50 MI sites in the con-
catenated sequences from the four proteins of each in-
fluenza species were selected from the sites in Figure 1.
Among the top 50 MI sites (Figure 2), there were sev-
eral sites that were shared between two different influ-
enza species indicating their significant correlation. These
top 50 MI sites represented their correlation in a pair
independent manner. Next, top 30 MI co-mutated resi-
due pairs of highest MI values (P value = 0) from each
influenza species were identified (Table 2), and a collec-
tion of highly connected networks of co-varying sites in
the four proteins were established based on these 30 sta-
tistically significant pairs. There were two avian, one
human, two pandemic 2009 H1N1, and one swine cor-
relation networks (Figure 3). All these networks from
various influenza species exhibited their preferred con-
nectivity among the four proteins. In the two avian net-
works, one had only sites from PA and PB1, and the
other contained only those from NP, PB1, and PB2. The
human network had PA, PB1, and PB2 sites, where the
most connected sites were PA_32, PB1_61, and PB1_63.
In the two pandemic 2009 networks, the first had sites
selected from all four proteins, while the second had
only sites from PA, PB1, and PB2. The swine network
had sites from all four proteins, where the most con-
nected sites were PA_580 and PB2_661. These top 30
MI residue pairs and networks of associated sites pre-
sented their correlation in a pair dependent manner.
PB2_627 is a key site for host switches and virulence,
which is also the most extensively studied site. Never-
theless, only avian viruses had it as one of their top 50
MI sites (Figure 2). To find those sites that related to
PB2_627, a set of sites that had high MI values with
Table 1. Averaged entropy and MI of the four proteins.
Entropy NP PA PB1 PB2 Overall Average
Avian 0.04070.04990.0351 0.0426 0.0420
Human 0.04760.05100.0448 0.0471 0.0476
Pandemic 2009 0.00400.00460.0039 0.0050 0.0044
Swine 0.08840.10560.0751 0.0911 0.0900
MI NP PA PB1 PB2 Overall Average
Avian 0.75600.93870.7888 0.8358 0.8298
Human 3.38193.81604.1865 3.2518 3.6590
Pandemic 2009 0.01370.01890.0157 0.0177 0.0165
Swine 4.73587.57615.4241 6.0774 5.9533
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Figure 1.Entropy and MI of the four proteins.
PB2_627 (P value = 0) were included in Table 3, where
the MI ranks were based on the MI values of all possible
pairs. In swine, PB2_627 appeared to interact exclusively
with sites in PA and PB2, while in avian, PB2_ 627 cor-
related with those in NP, PA, PB1, and PB2. The connec-
tivity of PB2_627 with other sites in NP, PA, PB1 and
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Figure 2. Top 50 MI sites from the four proteins.
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Figure 3. Networks of correlated sites from the four proteins that had high MI values (all with P value = 0).
Table 2. Top 30 MI site pairs from the four proteins (all with P value = 0).
Top 30 pairs in avian
(NP_14,NP_384) (NP_133,NP_149) (NP_133,NP_384) (NP_149,NP_384) (NP_149,PB1_293) (NP_149,PB1_636)
(NP_149,PB2_64) (NP_384,PB1_636) (NP_384,PB1_741) (NP_113,PB1_293) (NP_384,PB2_64) (PA_317,PA_388)
(PA_317,PA_463) (PA_317,PB1_97) (PA_317,PB1_212) (PA_317,PB1_225) (PA_388,PA_463) (PA_388,PB1_212)
(PA_388,PB1_255) (PA_463,PB1_212) (PA_463,PB1_255) (PA_531,PA_659) (PA_607,PB1_169) (PA_607,PB1_169)
(PB1_97,PB1_212) (PB1_97,PB1_255) (PB1_212,PB1_255)(PB1_293,PB1_636)(PB1_293,PB1_741) (PB1_709,PB2_478)
Top 30 pairs in human
(PA_324,PA_325) (PA_324,PB1_634) (PA_325,PA_580) (PA_325,PB1_612) (PA_325,PB1_634) (PA_536,PB1_612)
(PA_536,PB1_632) (PA_580,PB1_612) (PA_602,PB1_100) (PA_602,PB1_632) (PA_602,PB1_634) (PA_602,PB2_559)
(PB1_100,PB1_277) (PB1_100,PB1_634) (PB1_100,PB1_682)(PB1_161,PB1_632) (PB1_161,PB2_227) (PB1_293,PB1_612)
(PB1_293,PB1_643) (PB1_324,PB1_643) (PB1_545,PB1_632)(PB1_602,PB1_718) (PB1_602,PB2_682) (PB1_612,PB1_634)
(PB1_612,PB1_682) (PB1_632,PB1_634) (PB1_632,PB1_682)(PB1_632,PB2_227) (PB1_667,PB2_355) (PB1_718,PB2_682)
Top 30 pairs in 2009 H1N1
(NP_157,PA_89) (NP_181,PA_37) (NP_181,PA_525) (NP_353,PA_68) (NP_353,PB1_359) (PA_37,PA_525)
(PA_68,PB2_471) (PA_89,PB1_124) (PA_89,PB1_632) (PA_89,PB2_526) (PA_169,PB2_649) (PA_262,PB2_677)
(PA_483,PA_646) (PA_483,PB1_171) (PA_483,PB1_368) (PA_525,PB1_124) (PA_525,PB1_632) (PA_646,PB1_171)
(PA_646,PB1_622) (PA_646,PB2_368) (PB1_124,PB1_359)(PB1_124,PB1_632)(PB1_124,PB2_526) (PB1_171,PB1_622)
(PB1_171,PB2_368) (PB1_359,PB1_632) (PB1_359,PB2_526)(PB1_622,PB2_368) (PB1_632,PB2_526) (PB2_109,PB2_588)
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Top 30 pairs in swine
(NP_182,PA_120) (NP_361,NP_375) (NP_361,NP_430) (NP_375,PA_659) (PA_120,PA_580) (PA_120,PB1_92)
(PA_120,PB2_195) (PA_324,PA_401) (PA_324,PA_580) (PA_324,PB2_453) (PA_324,PB2_661) (PA_401,PA_580)
(PA_401,PA_659) (PA_401,PB2_661) (PA_531,PA_580) (PA_531,PA_659) (PA_531,PB2_66) (PA_580,PA_611)
(PA_580,PA_659) (PA_580,PB1_92) (PA_580,PB2_64) (PA_580,PB2_195) (PA_580,PB2_661) (PA_611,PB2_66)
(PB1_92,PB2_195) (PB2_184,PB2_243) (PB2_184,PB2_265)(PB2_243,PB2_265)(PB2_453,PB2_661) (PB2_475,PB2_627)
Table 3. Pearson correlation coefficients of the pair counts between different influenza species in Figures 4 and 5.
(Avian, Human) (Avian,2009 H1N1)(Avian, Swine)(Human,2009 H1N1)(Human, Swine) (2009 H1N1, Swine)
Averaged counts in proteins 0.986644 0.852749 0.974158 0.893431 0.977686 0.78265
Averaged counts in domains 0.63857 0.3873 0.8716 0.7614 0.3893 0.0976
PB2 in human and pandemic 2009 H1N1 viruses was
weak, and therefore no such sites were included in this
report.
3.3. Correlation within Each Individual
Protein and between Proteins
The correlated residue pairs that had a positive MI
value were counted according to their location in the
four proteins (Figure 4). In general, the inter protein
correlation from (NP, PA), (NP, PB1), (NP, PB2), (PA,
PB1), (PA, PB2), (PB1, PB2) was stronger than the intra
protein correlation (NP, NP), (PA, PA), (PB1, PB1) and
(PB2, PB2), with (NP, NP) correlation being the weakest.
Figure 4 also indicated that the correlation between PA
and PB2 was the strongest in avian, human, and pan-
demic 2009 H1N1, and the correlations of PA and PB2,
PA and PB1, and PB1 and PB2 were the strongest in
swine. Similarly, Figure 5 showed that the correlation of
nuclear localization signals (NLS) of PB2 was the
strongest in avian, human, and pandemic 2009 H1N1,
and the correlation of the RNA cap binding domain of
PB2 was the strongest in swine. To further quantify the
correlation of these four proteins, the averaged counts of
positions in the functional domains of the four proteins
that had a positive MI value with other positions were
calculated, based on the domain boundary information
given in [21] (Figure 5). Comprehensive phylogenetic
analysis suggested that the genes of 2009 pandemic
H1N1 were derived from avian (PB2 and PA), human
H3N2 (PB1), classical swine (HA, NP and NS), and
Figure 4. Averaged correlated pair counts in each individual protein and between proteins.
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Figure 5. Averaged counts of sites in the functional domains of the four proteins that had a positive MI value with other sites.
Table 4. Sites from the four proteins of avian and swine influenza that had high MI values with PB2_627.
Avian Sites MI Rank P value Avian Sites MI Rank P value Swine Sites MI Rank P value
PA_258 163 0.0 PB1_667 332 0.0 PB2_485 21 0.0
PB2_451 207 0.0 NP_211 395 0.0 PB2_199 242 0.0
PA_626 210 0.0 PB2_339 396 0.0 PA_580 331 0.0
PA_596 220 0.0 NP_390 414 0.0 PA_401 338 0.0
PB1_292 226 0.0 PA_445 421 0.0 PA_314 364 0.0
NP_353 256 0.0 PB2_543 424 0.0 PB2_64 412 0.0
PB2_649 262 0.0 NP_178 428 0.0 PA_615 472 0.0
PB2_368 299 0.0 PB2_147 434 0.0 PA_324 473 0.0
PB1_632 307 0.0 PA_399 449 0.0
PB1_196 323 0.0 PB1_255 491 0.0
PB2_390 331 0.0
Eurasian avian-like swine H1N1 (NA and M) lineages
[25]. With Pearson correlation coefficients (Table 4),
both Figures 4 and 5 consistently illustrated that the
correlation patterns of pandemic 2009 H1N1 were mo-
re similar to those of avian and human influenza than to
swine, thus offering a new insight into the interaction
of the four proteins of the pandemic 2009 H1N1 virus
when compared with avian, human, and swine influ-
enza and how the origin of these four proteins might
contribute to the correlation patterns revealed in this
analysis.
4. DISCUSSION
Development of our knowledge about the molecular
mechanism of host range restriction and the adaptation
of influenza viruses to a new host species remains a cen-
tral topic in flu research. The four proteins NP, PA, PB1,
and PB2 are crucial components in viral RNA synthesis,
and are also implicated in host adaptation and patho-
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1146
genicity. Therefore, clear revelation of the function and
action of these four proteins is required. Sequence sur-
vey implied that the common host shift markers in the
proteins of avian or swine influenza are not present in
the pandemic 2009 H1N1 virus. Moreover, introduction
of known virulence markers into 2009 H1N1 does not
increase its virulence [26,27]. The combination of its
pandemic potential and absence of traditional host
markers has remained a source for concern and justifies
the search for its own host markers outside of the space
of classical host markers [28,29].
The PB2 of 2009 H1N1 had a glutamic acid at posi-
tion 627, reflecting its avian origin. Typically avian vi-
ruses have a glutamic acid (E) at position 627, while
human viruses usually have a lysine (K) at this position.
Additionally, the presence of a glutamic acid at position
627 in PB2 contributed to the cold sensitivity of poly-
merase derived from avian viruses in mammalian cells
[3]. However, the clinical experience in 2009 demon-
strated that this novel virus was able to transmit and rep-
licate in humans efficiently. A natural assumption was
that some amino acids at other sites in PB2 might be
responsible for its efficiency in reproduction and trans-
mission. It turned out that two amino acids, serine (S) at
site 590 and arginine (R) at site 591, in PB2, termed SR
polymorphism, compensate the lack of amino acid lysine
at site 627 in PB2 [15].
Although our mutual information analysis illustrated
the connectivity was low between PB2_627, PB2_591,
PB2_590, and other sites in pandemic 2009 H1N1, this
study discovered three sites correlating with PB2_590,
which were NP_480 (MI = 0.0219, P value = 0.033, MI
rank = 370), PB1_359 (MI = 0.0060, P value = 0.338,
MI rank = 611), and PB1_124 (MI = 0.0011, P value =
0.0, MI rank = 1093). With the same approach, associa-
tions with other critical sites such as PB2_701 and
PB2_271 could also be detected.
Host range and virulence of influenza viruses are mul-
tigenically determined through interactions between the
proteins involved, which could be, in part, elucidated
with identification of mutations and co-mutations that
might confer increased pathogenicity or transmissibility.
The absence of familiar host switch markers in 2009
H1N1 added a new dimension in this effort, and moti-
vated the extensive search for other mutations or strate-
gies that influenza viruses evolved to develop and adapt.
To move this direction, this report revealed and quanti-
fied the interactions of NP, PA, PB1, and PB2 of avian,
human, pandemic 2009 H1N1, and swine influenza, and
identified a collection of statistically significant co-
varying sites, not only in each individual protein but also
between proteins, for further investigation of their inte-
grative biological relevance experimentally.
5. ACKNOWLEDGEMENT
We thank Houghton College for its financial support.
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