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\begin{document}

\title{Reconstruction of molecular evolution of human influenza A H1N1/2009
virus in Iran and neighboring countries}



\author[1]{Nima Ghalekhani}%
\author[2]{Saied Bokaie}%
\author[3]{Sana Eybpoosh}%
\author[2]{Hesameddin  Akbarein}%
\author[4]{Hamid Sharifi}%
\affil[1]{2.	HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences}%
\affil[2]{1.	Divisions of Epidemiology \& Zoonoses, Department of Food Hygiene and Quality Control, Faculty of Veterinary Medicine, University of Tehran, Iran}%
\affil[3]{3.	Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran}%
\affil[4]{2.	HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\selectlanguage{english}
\begin{abstract}
Background In this study, the time and path of transmission of H1N1
serotype influenza A viruses in Iran and neighboring countries have been
investigated by using Bayesian phylogeography analysis on the sequences
extracted from the gene bank. Methods We obtained all hemagglutinin (HA)
and neuraminidase (NA) nucleotide sequences of influenza H1N1 available
up to December 25, 2020, from Iran and its neighboring countries (i.e.,
Pakistan, Afghanistan, Turkmenistan, Armenia, Azerbaijan, Turkey, and
Iraq). We also performed a Bayesian Markov chain Monte Carlo method to
infer the evolutionary dynamic and the most recent common ancestor for
the HA and NA sequences. Results Based on the extracted sequences, the
age of emergence of H1N1 influenza virus serotype was older in Iran
compared to neighboring countries, and Tehran had a key role and
epicenter of transmission to other cities within Iran. The mean time of
the most recent common ancestor of H1N1 viruses was 1989 (95\% HPD:
1980-1994) for HA and NA as well. Conclusions Along with ordinary
measures like resource management, diagnostic approaches, and
preparedness to fight against viruses that were in place, continuous
monitoring, and screening of H1N1 serotype influenza virus in the
country, especially by implementation of feasible, effective, and
innovative measures at border line should be initiated and identified
gaps and shortage that should be a priority for virus control. It is
also important for countries to have a regional monitoring program in
addition to internal monitoring programs, as well as to start a virus
molecular care program.%
\end{abstract}%



\sloppy


\textbf{Reconstruction of molecular evolution of human influenza A
H1N1/2009 virus in Iran and neighboring countries}

Running Title: Molecular evolution of A H1N1 virus in Iran and neighbors

Nima Ghalekhani\textsuperscript{1,2}, Saied Bokaie\textsuperscript{1},
Sana Eybpoosh\textsuperscript{3}*, Hesameddin
Akbarein\textsuperscript{1}, Hamid Sharifi\textsuperscript{2}

\begin{enumerate}
\tightlist
\item
  Divisions of Epidemiology \& Zoonoses, Department of Food Hygiene and
  Quality Control, Faculty of Veterinary Medicine, University of Tehran,
  Iran
\item
  HIV/STI Surveillance Research Center, and WHO Collaborating Center for
  HIV Surveillance, Institute for Futures Studies in Health, Kerman
  University of Medical Sciences, Kerman, Iran
\item
  Department of Epidemiology and Biostatistics, Research Centre for
  Emerging and Reemerging Infectious Diseases, Pasteur Institute of
  Iran, Tehran, Iran
\end{enumerate}

Corresponding Author: Sana Eybpoosh

E-mail: sana.eybpoosh@gmail.com

\textbf{Acknowledgment}

We wish to acknowledge to Institute for Futures Studies in Health,
Kerman University of Medical Sciences, Kerman, Iran, especially Reza
Sheikhzadeh (IT Manager) for his kind collaboration to access server
computer to conduct computational analysis.



\textbf{Abstract}

\textbf{Background}

In this study, the time and path of transmission of H1N1 serotype
influenza A viruses in Iran and neighboring countries have been
investigated by using Bayesian phylogeography analysis on the sequences
extracted from the gene bank.

\textbf{Methods}

We obtained all hemagglutinin (HA) and neuraminidase (NA) nucleotide
sequences of influenza H1N1 available up to December 25, 2020, from Iran
and its neighboring countries (i.e., Pakistan, Afghanistan,
Turkmenistan, Armenia, Azerbaijan, Turkey, and Iraq). We also performed
a Bayesian Markov chain Monte Carlo method to infer the evolutionary
dynamic and the most recent common ancestor for the HA and NA sequences.

\textbf{Results}

Based on the extracted sequences, the age of emergence of H1N1 influenza
virus serotype was older in Iran compared to neighboring countries, and
Tehran had a key role and epicenter of transmission to other cities
within Iran. The mean time of the most recent common ancestor of H1N1
viruses was 1989 (95\% HPD: 1980-1994) for HA and NA as well.

\textbf{Conclusions}

Along with ordinary measures like resource management, diagnostic
approaches, and preparedness to fight against viruses that were in
place, continuous monitoring, and screening of H1N1 serotype influenza
virus in the country, especially by implementation of feasible,
effective, and innovative measures at border line should be initiated
and identified gaps and shortage that should be a priority for virus
control. It is also important for countries to have a regional
monitoring program in addition to internal monitoring programs, as well
as to start a virus molecular care program.

Keywords: Influenza virus; H1N1; Bayesian phylogeographic; Iran



\textbf{Introduction}

Influenza is still a major cause of health disorders and mortality
worldwide and affects a large portion of the human population each year,
this potential could cause epidemics in humans, such as H1N1 virus
pandemic in 2009. In addition, many species of animals, including birds,
pigs, horses, and dogs, can be infected with influenza
viruses.\textsuperscript{12}

Influenza viruses belong to the Orthomyxoviridae family defined by
viruses that have a negative-sense, single-stranded, and fragmented RNA
genome. There are currently 18 different hemagglutinin subtypes (H1 to
H18) and 11 different neuraminidase subtypes (N1 to N11) for influenza A
viruses.\textsuperscript{3} Antigenic changes occur only in the proteins
of influenza virus neuraminidase and hemagglutinin, and hemagglutinin is
more important than neuraminidase because hemagglutinin is more
susceptible to such changes.

The history of the first influenza A (H1N1) pandemic in the 21st century
(March 2009) occurred 33 years after the last pandemic of the 20th
century (1976), followed by the detection of cases in the United States
and many other countries. With the spread of the disease to several
continents in April, the sixth phase of the pandemic was announced by
the World Health Organization.\textsuperscript{4} On the other hand, the
emergence and pandemic of influenza A (H1N1) virus with swine-origin
occurred so suddenly that apparently the pathogenic stages in
environment (first phase), pathogenicity in pigs (second phase),
transmission from pig to human (third phase), limited human-to-human
transmission in Mexico (fourth Phase), limited human outbreaks in the
Americas (fifth Phase), and widespread epidemics across the continent
(sixth Phase) occurred in less than three months.

With respect to viral epidemics that may emerge, molecular
epidemiological techniques have been useful tools in detecting the
source of epidemics and tracking the spread of regional or global
viruses. In this regard, phylogenetic methods, a kind of mathematical
modeling, provide new opportunities to study the evolutionary history of
pathogens and to reconstruct the spatio-temporal and demographic
dynamics of viral epidemics. Many viruses, such as the influenza virus,
evolve faster than normal transmission, and phylogenetic techniques as
an ideal and objective tool can be used for reconstructing
spatio-temporal dynamics and transmission history.

Phylogeography is the study of historical processes that may have shaped
the current geographical distribution of living species, such as
viruses. Nowadays, these studies are performed according to the
information obtained from the genealogy. Recent advances have made it
possible to integrate the theory of coalescent into phylogeography in
such a way that both demographic and spatial aspects of the epidemic are
inferred simultaneously. This information is used to track the patterns
of viral spread, which in turn can become effective intervention and
prevention strategies and can shed light on the main factors responsible
for the spread and transmission of the virus.\textsuperscript{5}

One of the limitations of the traditional epidemiological approaches is
their inability to estimate the path of the virus and identify the
estimated time and place of virus entry into a specific geographical
area based on available data. Bayesian phylogeographical approaches
using nucleotide sequences have made it possible to study the path of
the virus and the approximate time and place of virus entry into a
population along with other characteristics such as molecular dynamics
and so on. In this study, we investigate the above gaps using the
Bayesian phylogeographic approach for influenza virus H1N1 serotypes in
Iran and neighboring countries.

\textbf{Method}

We screened the NCBI Influenza Virus Resource and downloaded all HA and
NA nucleotide sequences of influenza H1N1 available up to December 25,
2020 from Iran and its neighboring countries (i.e., Pakistan,
Afghanistan, Armenia, Turkmenistan, Azerbaijan, Turkey and Iraq). We
captured sampling date and location of sequences by extracting
information deposited in the NCBI Influenza Virus Resource. In our final
genome sets, a total of 398 HA and 339 NA sequences remained after the
exclusion of identical sequences and sequences with unknown sampling
time and location. By using the ClustalW algorithm in MEGA v7.0,
multiple sequence alignment was performed and manually inspected. The
dataset was trimmed for phylogenetic analysis.\textsuperscript{6} The
initial maximum likelihood (ML) phylogenetic analysis was conducted
using Hasegawa- Kishino-Yano (HKY) and General Time Reversible (GTR)
nucleotide substitution models for HA and NA, respectively. The
best-fitting nucleotide substitution models were identified using an
online execution on the ATGC bioinformatics platform
(http://www.atgc-montpelier. fr/). Analysis was performed with 1000
bootstraps in MEGA v7.0.\textsuperscript{6}

To infer the evolutionary dynamic and time to the most recent common
ancestor (tMRCA) for the HA and NA sequences, Bayesian Markov chain
Monte Carlo (MCMC) method was performed using BEAST v2.5.241
package.\textsuperscript{7} In these analyses, HKY+G (for the HA
dataset) and GTR+G (for the NA dataset) substitution model, uncorrelated
lognormal relaxed clock model, and Bayesian skyline coalescent tree
priors were used.\textsuperscript{8} Four independent MCMC chains were
run for 25 million generations (sampling every 2,500 steps) and were
combined using the LogCombiner program v1.54.\textsuperscript{8}
Convergence was assessed based on the effective sampling size (ESS)
after a 10\% burn-in, using Tracer software v1.5. ESSs of 200 and above
were accepted. The maximum clade credibility tree was generated in the
TreeAnnotator program, while the initial 10\% of trees were discarded as
burn-in.\textsuperscript{7,9}The maximum clade credibility tree (MCC)
was visualized in the FigTree program v1.2.3.\textsuperscript{10}

Inferences about spatial dynamic and potential viral migration patterns
of H1N1 within Iran and between Iran and its neighboring countries were
made based on a discrete Bayesian phylogeographic model developed in
BEAST software v2.5.241.\textsuperscript{8} The symmetric substitution
model with the Bayesian Stochastic Search Variable Selection (BSSVS)
approach was performed in the SPREAD program v1.0.7.\textsuperscript{11}

To determine selection pressure acting on HA and NA lineages, we
estimated the ratio of non-synonymous (dN) to synonymous (dS)
substitutions per site (ratio dN/dS) for each lineage, using all the
sequences included in this study. Positively selected codons were
detected using the single likelihood ancestor counting (SLAC) and fixed
effects likelihood (FEL) methods with a significance level of 0.1, all
procedures are available in the HyPhy package and accessed through the
Datamonkey web server.\textsuperscript{12,13}

\textbf{Result}

The H1 phylogeographic tree showed two large independent clusters within
Iran, suggesting the initiation of two independent effective outbreaks
with different tMRCAs, one in the past years (1997) and the other in
recent years (2005). The first outbreak was initiated from the north
region of the country and most of time was circulated between the north
and northwest region within the country and established some small
introduction in the southwest region in the late years (2008). The
phylogeographic tree showed that the second initiation was introduced in
the north region and had concentrated circulation in the cities within
this region by 2013 and then, circulation of virus expanded to the west
region and continued to 2015, therefore based on our result inferred
cautiously there were small and concentrated epidemics which had
occurred in most parts of the country which came along until recently,
despite the rapid expansion and decline in the region, it has remained
stable (Figure 1). Along with the circulation of virus within the
country, the phylogeographic tree revealed that intercountry
transmission occurred in circulation between southwest region, Turkey
and Afghanistan and again back transmission to the north region in Iran
from 2007 to 2010, in addition, same back transmission was observed in
cities were located in the west region and close to the Turkey border
during 2013 to 2015. So, we could infer cautiously that, the virus has
entered the country many times in the form of multiple introductions and
spread, and according to our data, it did not have a single independent
source and the age of presence of the virus in Iran is older than
neighboring countries. Based on our genome set, lineages from different
parts of the country branched within the lineages from Tehran,
highlighting the role of Tehran as the epicenter of the outbreaks in the
country. After 2010, small and concentrated epidemics in other cities
have their origins in Tehran.

According to the above-mentioned, generally we concluded that probably
the virus has been circulating in Tehran with low frequency for a little
period and has gradually spread throughout the region and neighboring
countries in the following years in a single and sporadic cases. The
small genetic distance between the different branches of these clusters
in this period suggests rapid spread of the virus in this specific
geographical area during the narrow time (2007-2009) in Iran and
neighboring countries. Based on our genome set the virus was still
present in small numbers in some countries, such as Turkey, where the
virus was mainly circulating in comparison to other neighboring
countries.

The H1 phylogeographic tree based on different geographical regions was
constructed separately and showed that two independent clusters same as
the above results were created for our total sequences and
geographically suggested that the virus circulation started from north
and northwest to east and southwest of Iran over time, and then moved to
east and southeast in recent years (Figure 2), and this indicates the
correct goodness of fit of the model.

Results of the N1 phylogeographic tree were in line with the H1 tree,
which two independent clusters among sequences from Iran, Turkey, Iraq,
and Turkmenistan were observed, with the sequences related to Turkey
occupying the root of the tree (Figure 3). The phylogeographic tree
showed that the transmission and circulation pattern was like H1 tree,
and the northern region is the epicenter of this transmission which had
taken place bilaterally and had occurred between the north of the
country and Turkey. During a short time, the circulation of virus
involved the whole country (Figure 4).

It should be noted that, if there were more sequences from other
countries in our genome set, different results could be expected from
the model outputs.

The evolutionary rate for the HA and NA genes of the H1N1 viruses were
estimated at 4.01\selectlanguage{ngerman}×10\textsuperscript{-3} {[}95\% HPD: (2.82-5.40)
×10\textsuperscript{-3}{]} and 3.30×10\textsuperscript{-3} {[}95\% HPD:
(1.33-5.43) ×10\textsuperscript{-3}{]} substitutions/site/year,
respectively. The mean time of the most recent common ancestor of

H1N1 viruses was 1989 (95\% HPD: 1980-1994) for HA and NA as well.

The estimation of dN/dS ratio per site for each lineage was conducted.
After excluding the duplicated sequences, 210 sequences with 443 sites
for HA and 85 sequences with 91 sites for NA lineages were analyzed. The
SLAC analysis of HA lineages showed that 17 sites were under
negative/purifying selection while no positive/diversifying selection
were observed. The overall dN/dS for HA lineages was 0.403. For the NA
lineages, 14 negative/purifying selection sites and no
positive/diversifying selection were observed. The overall dN/dS for NA
lineages was 0.286. Based on the FEL analysis of HA lineages, 48 and 2
sites were under negative/purifying and positive/diversifying
selections, respectively. This was 24 and 1 selection sites for the NA
lineages, respectively. The results of Generic Algorithm Recombination
Detection (GARD) showed no evidence of recombination.

\textbf{Discussion}

In this study, the time and path of transmission of H1N1 serotype
influenza A viruses in Iran and neighboring countries have been
investigated by using Bayesian phylogeography analysis on the sequences
extracted from the gene bank. As of now several studies on geographical
phylodynamic of different influenza virus serotypes with different goals
and details have been developed and published around the
world.\textsuperscript{14,15}Based on our knowledge, this study is the
first study for Influenza in the field of Bayesian phylogeographical
analysis in Iran and the region.

The results of our study showed that based on the extracted sequences,
the age of emergence of H1N1 influenza virus serotype was older in Iran
compared to neighboring countries, and among the cities within the
country, Tehran had a key role and epicenter of transmission to other
cities. In the meanwhile, it should be noted that there were not enough
evidence diverse sequences from Iran and other possible countries of
virus transmission in our genome set.

The global transmission of virus during the pandemic can be explained by
the fact that and based on the existence agreements on previous reports,
started in April 2009 in Mexico, followed by North America. Expanding
transmission of the virus to Europe and its spread in the population of
European countries, in connection with the travel of people living in
European countries to Mexico or the United States one week before the
onset of clinical symptoms.\textsuperscript{4,16-18}Based on the results
of our study, the virus has been circulating in Tehran with low
frequency for some time and gradually it has spread throughout the
region and neighboring countries as sporadic event in the recent years.
Our results showed that after rapid inhibition, the virus was still
present in small numbers in some countries, such as Turkey. The results
of our phylodynamic reconstruction were in accordance with other
evidences that stated disease was initiated by the arrival of air
travelers from non-neighboring European countries, first by an Iranian
teenager living abroad in June and then by other travelers, gradually
coinciding with other foreign trips and return of pilgrims from Hajj
Umrah, the disease spread and was observed almost all over the country,
although the prevalence of the disease in some provinces, especially the
northwestern provinces and Tehran due to more population density was
higher than other centers in the country.\textsuperscript{19}

In general, the influenza epidemic caused by type A virus usually
occurred in a certain state, for example, the pandemic of influenza,
starts almost suddenly and reaches its maximum within 2-3 weeks, and
lasted for 5-6 weeks.\textsuperscript{4}The small genetic distance
between the different branches of these clusters in this period
indicated the high rate of spread of the virus, which reflected the
sudden onset and rapid inhibition of the epidemic in this period
(2007-2009) both in Iran and in other neighbor countries. The 2009
pandemic influenza virus is like seasonal influenza viruses in many
epidemiological features and when the pandemic is fully subsided and at
least after one year has passed, it is expected to follow the same trend
as other seasonal influenza viruses.

Therefore, due to the significant threat to public health caused by such
viruses, regular monitoring of H1N1 viruses in the country, especially
in entering point to the country, strengthening the social measures and
screening of newcomers and tourists from neighboring countries, should
be considered as impactful tools to fight against future
infections.\textsuperscript{20} It is also necessary for countries to
have a regional monitoring program in addition to internal monitoring
programs, because control of this disease would not be possible without
such a program. In addition, given the potential threat to the public
health of the H1N1 virus, it is also important to develop effective
measures like establishing a molecular surveillance program to prevent
epidemics and pandemics.

Our study showed that the estimated evolutionary rate for HA and NA
genomes for H1N1 serotype in our genome set from Iran and neighboring
countries is similar to that previously found in different countries in
Scotland, Argentina, Italy, China, India, Japan, South Korea, and
Israel.\textsuperscript{14,21,22}This finding validates the estimates of
the recent common ancestor in our study, and supports the validity of
our tree estimates and topology. Also presence of similar mutation rates
for HA and NA genes seems they were coevolving, and leads to minimizing
the possibility of emergence of new reassortments.\textsuperscript{23}

Based on our results we did not find any positive selection sites, but
other studies identified different number of positive selection sites
and these differences can be attributed to the differences in
significance levels and data sets used in the other
studies.\textsuperscript{24}

This study had some limitations such as, we could not study the
epidemiological parameters of the H1N1 virus in neighboring countries
such as Iraq, Armenia, Afghanistan, and the Persian Gulf countries in
depth due to the existence of limited sequences of these countries in
the gene bank. In addition, we could not directly estimate the full
extent of the evolution of the genome set because the time frame of this
data set was not large enough. Our models and time estimates need to be
further explored in future studies as new sequences from other countries
and wider time periods become available, allowing for a more
comprehensive assessment of the virus's evolutionary history.

In summary, our results suggested that the H1N1 serotype influenza virus
epidemic in Iran may have started much earlier than in other countries
surveyed in the region, and it was estimated that the date is earlier
than the identified years by molecular detection. Therefore, along with
such measures like resource management, diagnostic approaches, and
preparedness to fight against viruses that already were in place, we
need to initiate continuous monitoring, and screening of H1N1 serotype
influenza virus in the country, especially by implementation of
feasible, effective, and innovative measures at borderline for virus
control. It is also important for countries to have a regional
monitoring program in addition to internal monitoring programs, as well
as to start a virus molecular care program. In the future, with the
availability of new sequences from other countries and more open time
intervals, our model and timeline estimates need to be further explored.

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\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. Maximum clade credibility phylogenies for the hemagglutinin
gene of influenza A H1N1. The branches are colored according to the
location of their nodes. The scale bar at the bottom indicates the years
before the most recent sampling time (2019).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2. Significant locations of transmission of influenza H1N1 based
on HA nucleotide sequences\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3. Maximum clade credibility phylogenies for the neuraminidase
gene of influenza A H1N1. The branches are colored according to the
location of their nodes. The scale bar at the bottom indicates the years
before the most recent sampling time (2019).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 4. Significant locations of transmission of influenza H1N1 based
on NA nucleotide sequences\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure1/Figure1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure2/Figure2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure3/Figure3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure4/Figure4}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

