Identification of the positively selected genes governing host-pathogen arm race in Vibrio sp. through comparative genomics approach

Biojournal of Science and TechnologyBiojournal of Science and TechnologyBiojournal of Science and TechnologyBiojournal of Science and Technology
Research Article
Identification of the positively selected genes governing host
pathogen arm race in Vibrio sp. through comparative genomics
approach
Atai Rabby1
, Sajib Chakraborty
Shahjalal Soad1
, Kaniz Fatima Chanda
1
Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka
2
Department of EEE, University of Melbourne, National ICT Australia, Victoria
*Corresponding author
Sajib Chakraborty
Assistant Professor, Department of Biochemistry and Molecular Biology, Faculty of Biological Sciences, University
of Dhaka, Dhaka-1000, Bangladesh. Email:
Published: 24-07-2015
Biojournal of Science and Technology
Academic Editor: Dr. Md. Shahidul Islam
This is an Open Access article distributed under
(http://creativecommons.org/licenses/by/4.0
reproduction in any medium, provided the origina
Abstract
Bacterial evolution is due to the adaptive nature of the core bacterial genomes that plays critical role in
diversification, fitness and adaptation of the species to different environment and host. Since Vibrio
cholerae represents an appropriate model orga
driven factors shaping the microbial genome structure and function, the current study aims to identify
genes that are under these strong forces in V. cholerae. Here, we employed a comparative genomic
approach to identify genes that are under positive selection in ten strains of Vibrio sp. including four
pathogenic V. cholerae strains. From the available genome sequence data, a total of 422 orthologous
genes were identified by reciprocal BLAST best
and tree comparison method. These 422 genes, representing the core genome of Vibrio sp., constituted the
dataset to be analyzed for evolutionary selections. The analysis of natural selection, based on M
Likelihood method on synonymous and non
the bacterial core genomes are mostly under purifying selection with a few positively selected regions.
However, our finding also reveals that positiv
range of different genes encompassing diverse functional pathways including cell surface proteins (e.g.
outer membrane-specific lipoprotein transporter/assembly proteins etc.), cell motility proteins
flagellar motor switch proteins, flagellar hook and assembly proteins), nutrient acquisition (e.g. amino
acid, carbohydrate and phosphate ABC transporters), DNA repair and transcription related proteins.
Interestingly, these positively selected gene
and fitness in gastrointestinal environment. Therefore, the collective evidences of these positively
selected genes spanning several pathways raise the possibility of their involvement in evolu
races with other bacteria, phages, and/or the host immune system. This finding points to the natural
selections which is the responsible factor for the diversification of Vibrio genus.
Keywords: positive selection, V
Biojournal of Science and TechnologyBiojournal of Science and TechnologyBiojournal of Science and TechnologyBiojournal of Science and Technology
Identification of the positively selected genes governing host
, Sajib Chakraborty1*
, Atiqur Rahman1
, Shamma Shakila Rahman
Kaniz Fatima Chanda1
, Rajib Chakravorty2
Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka-1000, Bangladesh.
Department of EEE, University of Melbourne, National ICT Australia, Victoria 3010, Australia
. Email: schak.du@gmail.com
Received: 01-06-201
Biojournal of Science and Technology Vol.2:2015 Accepted: 29-06-201
Dr. Md. Shahidul Islam Article no: m140008
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
http://creativecommons.org/licenses/by/4.0 ), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
cholerae represents an appropriate model organism for studying the interplay of environment and host
genes that are under these strong forces in V. cholerae. Here, we employed a comparative genomic
genes were identified by reciprocal BLAST best-hit method, recombination breakpoint frequency analysis
dataset to be analyzed for evolutionary selections. The analysis of natural selection, based on M
Likelihood method on synonymous and non-synonymous substitution rate, confirms the hypothesis that
However, our finding also reveals that positively selected sites in the Vibrio genome occur in a wide
specific lipoprotein transporter/assembly proteins etc.), cell motility proteins
Interestingly, these positively selected gene products are directly involved with host-pathogen interactions
selected genes spanning several pathways raise the possibility of their involvement in evolu
selections which is the responsible factor for the diversification of Vibrio genus.
Vibrio cholerae, genome wide selection, molecular
Identification of the positively selected genes governing host-
Shakila Rahman1
,
1000, Bangladesh.
3010, Australia
2015
2015
m140008
the terms of the Creative Commons Attribution License
), which permits unrestricted use, distribution, and
nism for studying the interplay of environment and host
genes that are under these strong forces in V. cholerae. Here, we employed a comparative genomics
t method, recombination breakpoint frequency analysis
dataset to be analyzed for evolutionary selections. The analysis of natural selection, based on Maximum
synonymous substitution rate, confirms the hypothesis that
ely selected sites in the Vibrio genome occur in a wide
specific lipoprotein transporter/assembly proteins etc.), cell motility proteins (e.g.
pathogen interactions
selected genes spanning several pathways raise the possibility of their involvement in evolutionary arms
molecular evolution

ISSN 2410-9754 Vol:1, 2014
@2014, GNP Biojournal of Science and Technology P a g e | 1
INTRODUCTION
Host-pathogen interactions and environmental
settings are evolutionary forces that confer the
adaptation of bacterial genomes (Petersen et al.
2007). The growing number of sequenced bacterial
genomes coupled with the comparative genomics
techniques provides the solid platform to
investigate the nature of the genome-shaping
natural selection process in bacteria. Particularly,
the genes under positive selection have drawn
much of the attention since these genes correlate
with the functional adaptations in response to
environmental settings and host selection pressure.
A number of studies have been conducted to
elucidate the positively selected genes in different
bacterial genomes including pathogenic
Escherichia coli (Chen et al. 2006, Petersen et al.
2007), Campylobacter sp. (Lefebure and Stanhope
2009) and Burkholderia pseudomallei (Nandi et al.
2010). Here, we attempted to investigate the
positively selected genes in V. cholerae in genome
wide manner. The extensive studies on V. cholerae
in terms of natural habitat, pathogenicity as well as
it’s interactions with host along with the
availability of genome sequences for a number of
different strains of V. cholerae have made it as an
appropriate model organism for studying the
interplay of environment and host driven factors
that tend to alter the microbial genome structure
and functions. In this study, we aimed to identify
the genes under positive selection in V. cholerae
genome as a trace of ongoing interplay of
environment and host driven factors with bacterial
genome.
V. cholerae is a gram negative
gammaproteobacteria. Some of its strains are
pathogenic and responsible for one of the most
prominent life threatening disease, cholera. The
evolution of V. cholerae genes throughout its entire
genome will give us insights regarding its
pathogenicity and host-pathogen interaction
patterns.
V. cholerae lives both in aquatic environment as
well as human gut and also infected by
Vibriophages. Thus, evolutionary pressures are
constantly acting on the genome. Studies have
shown that multiple quorum-sensing circuits
function in parallel to control virulence and
biofilm formation in V. cholerae.(Hammer and
Bassler 2003) Motility of Vibrio group is mediated
by a virulent factor which has also been
established previously.(BERRY 1975) These data
indicates to the possible targets for natural
selections as the host will try to mimic the
virulence factors and the protein products of the
selected genes come to direct or indirect host-
pathogen interactions. Comparative genomics data
is ideal for identifying genes that are affected by
selection pressure (Chen et al. 2006).
Here, we scanned positive selection in genome
wide manure by employing a comparative
genomics approach. By comparing the genes and
their corresponding proteins of different
organisms, the rate of synonymous and non-
synonymous substitution (pressure of selection)
could be identified. The statistics used to identify
positive selection in these studies is the ratio of
non-synonymous to synonymous substitution rate,
ω (dN/dS).(Hurst 2002, Yang and Bielawski 2000)
Our particular interest was in identifying positive
selection because it provides evidence for adaptive
changes in function. Moreover, we further aimed
to investigate the selection pressure on different
functional pathways of V. cholerae and to perform
clustering statistics to find out highly selected
genes that have evolved only in V. cholerae
genome (species-specific evolution).
METHODS AND MATERIALS
Construction of primary data files with
orthologous DNA sequences
Genome sequences of four V. cholerae strains and
six other Vibrio sp. were retrieved from the NCBI
FTP server (ftp://ftp.ncbi.nih.gov). All protein
coding annotated gene sequences within ten
selected species were blasted using reciprocal blast
best hit method (Moreno-Hagelsieb and Latimer
2008) (Table-1). The hits with an E-value cut off of
10-6
and minimum query coverage was set to 75%

ISSN 2410-9754 Vol:1, 2014
to be considered as positives and subsequently
selected for further analysis. A meta-database was
constructed by incorporating the positive hits
representing the annotated genes from ten selected
genomes (Table-1), excluding hypothetical,
putative and predicted genes. When more than one
gene sequence from a particular genome was
found (gene duplication events could possibly
account for such phenomena), only one sequence
was chosen based on their query coverage and E-
value. A total of 886 homologous gene sets from
10 Vibrio sp. were obtained as primary datasets.
Bioedit tool was used for local blast and meta-
database construction during homologous gene
search (Hall 1999). The evolutionary relationship
among the Vibrio sp. was established by analyzing
16srRNA phylogenetic tree (Figure 1).
Table-1: List of Vibrio Strains used in the
analysis
Starin RefSeq Accession
V. cholerae O395 NC_009456, NC_009457
V. cholerae O1 NC_002505, NC_002506
V. cholerae MJ NC_012667, NC_012668
V. cholerae M66 NC_012578, NC_012580
V. splendidus LGP32 NC_011744, NC_011753
V. vulnificus CMCP6 NC_004459, NC_004460
V. vulnificus YJ016 NC_005128, NC_005139,
NC_005140
V. fischeri ES114 NC_006840, NC_006841
V. harveyi ATCC NC_009777, NC_009783
V. parahaemolyticus
RIMD
NC_004603, NC_004605
Detection of Paralogous and Xenologous genes
Since the presence of paralogous and xenologous
genes in the primary dataset could potentially
interfere with the detection of positive selection,
recombination branch point test was used to detect
the recombination and gene duplication events
using Recombination detection program
(RDPversion3).(Martin and Rybicki 2000) In brief,
RDP3 examines nucleotide sequence alignments
and attempts to identify recombination breakpoints
using ten published recombination detection
algorithms, including RDP, geneconv and
chimaera that we employed in this
analysis.(Martin and Rybicki 2000, Padidam et al.
1999, Posada and Crandall 2001) The genes
showing evidence of significant recombination in
all three methods (P≤ 0.01) were considered as
paralogue and removed from further analyses.
Comparative phylogenetic method was used to
detect horizontally transferred genes. In short, 16s
rRNA tree was compared with species tree using T-
Rex tool (Li et al. 2005). Genes showing
significant evidence (bootstrap score) of Lateral
gene transfer were removed from further
analysis(Boc and Makarenkov 2003). After
removing paralogoues and xenologoues, remaining
genes were classified according to their COG
categories found in NCBI genome annotation
Report(Tatusov et al. 2000).
Figure 1. Species Tree of Vibrio cholerae Using
16s rRNA Sequence Alignment. Sequence of 16s
rRNA of O395 strain was retrieved from NCBI
nucleotide database by data mining, then the
sequence was used in to find closely related
species. 10 closely related strains were under a
single common ancestor were found and selected
for analysis.
Test for Positive selection
Ten selected Vibrio spps. were distributed into
three different groups according to their host and
habitat -Group I: all species, Group II: All V.

ISSN 2410-9754 Vol:1, 2014
cholerae (VC) –M66, 0395, O1 and MJ, Group III:
all non-cholerae Vibrio sp. (Supplementary Table
1). For each group a total of 422 orthologous gene
sets were subjected to BLASTx and their
corresponding amino acid sequence alignments
were used to create the codon wise alignment of
each orthologous gene by online tools: Revtrans
1.4 and Pal2Nal (Suyama et al. 2006, Wernersson
and Pedersen 2003). HyPhy as implemented in
MEGA 5.03 software package was used to detect
codon wise nonsynonymous/synonymous
substitution ratio (ω) (Tamura et al. 2011). Briefly,
it involves the estimation of synonymous (S) and
nonsyonymous (N) sites using the joint Maximum
Likelihood reconstructions of ancestral states
under a Muse-Gaut model (Muse and Gaut 1994)
of codon substitution and Felsenstein 1981 model
(Felsenstein 1981) of nucleotide substitution. A
positive value for the test statistic indicates an
overabundance of nonsynonymous substitutions.
The probability of rejecting the null hypothesis of
neutral evolution was also calculated (Kosakovsky
Pond and Frost 2005, Suzuki and Gojobori 1999)
and the P-value less than 0.05 were considered
significant. Additionally, the normalized dN-dS
values were also obtained using the total number
of substitutions in the alignment (measured in
expected substitutions per site). The entire
orthologous gene sets and their corresponding
codon alignments of other two groups were used to
determine dN/dS ratio (ω) in each group.
GO enrichment score
GO enrichment score was calculated to identify the
enriched GO terms in the positively selected genes
in all four groups. To calculate enrichment score
target list of positively genes was compared to the
background set of 422 orthologous gene set via a
standard approach that utilize hypergeometric
distribution.(Sealfon et al. 2006) GO enrichment
score was calculated by using the following
equation
ܲ‫ܺ(ܾ݋ݎ‬ ≥ ܾ) = ‫;ܾ(ܶܥܪ‬ ܰ, ‫,ܤ‬ ݊)
= ෍
ቀ
݊
݅
ቁ ቀ
ܰ − ݊
‫ܤ‬ − ݅
ቁ
ቀ
ܰ
‫ܤ‬
ቁ
௠௜௡(௡,ே)
௜ୀ଴
Given a total number of genes N, with B of these
genes associated with a particular GO term and n
of these genes in the target set, then the probability
that b or more genes from the target set are
associated with the given GO term is given by the
hyper geometric tail.
RESULT
Identifying highly selected genes using K-means
unsupervised clustering method
Genes were classified as high, moderate and low
using K-means unsupervised clustering method (J.
A. Hartigan 1979, Kimura 1983, MacQueen 1967)
according to their number of positively selected
codons. 92 genes were found belonging to ‘high
positive selection’ category as they harbor
relatively high percentages of positively selected
sites (%PS). When compared with the %PS of
House-keeping genes, these 92 genes showed
significant higher substitution rate (Supplementary
Figure 1) suggesting that the genes with higher rate
of selection are truly under influence of natural
selection. These highly positively selected 92
genes were found belonging to 14 COG categories
among the total 18 COG categories representing
the core genome (Figure 2).
Core genome is largely under purifying selection
while only a small portion is under positive
selection.
Positive selection reflecting the traces of adaptive
evolutionary process is determined by calculating
the ration (ω) between nonsynonymous (dN) and
synonymous (dS) codon substitution rates. The
ratio ω (dN/dS) > 1 refers to positive selection
whereas ω=1 indicates purifying selection.
There are three types of evolutionary selection
process in terms of codon substitution: positive
selection, purifying selection and neutral selection
(Hahn 2008, Montoya-Burgos 2011, Yang and

ISSN 2410-9754 Vol:1, 2014
Bielawski 2000). Individual codons were analyzed
in each of the 422 genes to observe the frequency
distribution of these orthologous genes under the
three types of selection process. For majority of
the genes 75%-90% codons were found to be
under purifying selection (Figure 3a). In case of
neutral selection most number of genes harbor
10%-35% of neutrally selected codons (Figure 3b)
whereas highest number of genes were found with
only 4%-10% positively selected codons (Figure
3c). The highest percentage of positively selected
codons was found to be 38%. These data suggested
that purifying selection is the most favorable
selection process, probably due to the codon
adaptation or random mutation events (Kimura
1983). However, positive selection occurring only
in a minor portion of gene is specific and reflects
reminiscent of evolutionary pressure.
Figure 2. Classification of Orthologous genes according to COG category. NCBI COG database was used
to identify the COG category of every gene included as orthologous. All of the Vibrio cholerae genes were
fallen into eighteen categories.
Eight Cluster of Orthologous Genes(COG)
pathway categories are enriched with highly
selected genes.
422 genes were found as orthologous representing
the core genome of the ten selected Vibrio sp.
These genes were then classified into 18 categories
according to their COG annotation as found in
NCBI genome annotation Report (Tatusov et al.
2000). Distribution of these orthologous genes into
different functional pathways is shown in a pie
chart (Figure 2). Eight categories, namely- 1)
amino acid transport and metabolism 2) translation
and ribosomal biogenesis 3) carbohydrate transport
and metabolism 4) energy production and
conversion 5) DNA replication/recombination and
repair 6) nucleotide transport and metabolism 7)
transcription and 8) coenzyme metabolism,
comprise 70% of the core genome where the first
two categories (amino acid transport and
metabolism, and transcription and ribosomal
biogenesis) with highest number of genes
representing 13% and 12% of the core genome
respectively. Among the remaining categories cell
motility and secretion (5%), Inorganic ion
transport (4%) and Cell envelope and biogenesis
(4%) were prominent.

ISSN 2410-9754 Vol:1, 2014
There are three types of evolutionary selection
process in terms of codon substitution: positive
selection, purifying selection and neutral selection
(Hahn 2008, Montoya-Burgos 2011, Yang and
Bielawski 2000). Individual codons were analyzed
in each of the 422 genes to observe the frequency
distribution of these orthologous genes under the
three types of selection process. For majority of
the genes 75%-90% codons were found to be
under purifying selection (Figure 3a). In case of
neutral selection most number of genes harbor
10%-35% of neutrally selected codons (Figure 3b)
whereas highest number of genes were found with
only 4%-10% positively selected codons (Figure
3c). The highest percentage of positively selected
codons was found to be 38%. These data suggested
that purifying selection is the most favorable
selection process, probably due to the codon
adaptation or random mutation events (Kimura
1983). However, positive selection occurring only
in a minor portion of gene is specific and reflects
reminiscent of evolutionary pressure.
Eight Cluster of Orthologous Genes(COG)
pathway categories are enriched with highly
selected genes.
422 genes were found as orthologous representing
the core genome of the ten selected Vibrio sp.
These genes were then classified into 18 categories
according to their COG annotation as found in
NCBI genome annotation Report (Tatusov et al.
2000). Distribution of these orthologous genes into
different functional pathways is shown in a pie
chart (Figure 2). Eight categories, namely- 1)
amino acid transport and metabolism 2) translation
and ribosomal biogenesis 3) carbohydrate transport
and metabolism 4) energy production and
conversion 5) DNA replication/recombination and
repair 6) nucleotide transport and metabolism 7)
transcription and 8) coenzyme metabolism,
comprise 70% of the core genome where the first
two categories (amino acid transport and
metabolism, and transcription and ribosomal
biogenesis) with highest number of genes
representing 13% and 12% of the core genome
respectively. Among the remaining categories cell
motility and secretion (5%), Inorganic ion
transport (4%) and Cell envelope and biogenesis
(4%) were prominent.
Figure 3. Frequency distribution of genes under
three different type of codon selection.
Percentage of codons under positive, purifying and
neutral selection were calculated and bar
diagrams were build to indentify the distribution of
genes under these selection process. Red, Green
and blue bars are indicating Positive selection,
Purifying selection and Neutral selection
respectively.
GO enrichment score provided the most
important pathway to look insights for codon wise
selection
To identify the functional gene categories enriched
with 92 positively selected genes a GO enrichment
scoring approach described by Eden et al
published in BMC bioinformatics, 2009 was
applied. In order to calculate enrichment score, GO

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@2014, GNP
categories of all of the 422 genes of core genome
were used as a background dataset and an equation
described by Sealfon et. al. was used. The
pathways were then ranked based on the P
and GO enrichment scores. Six functional
pathways showing low P- value and higher G
enrichment score were considered as pathways
with highly enriched positively selected genes
(Figure 4). These categories are 1) cell motility and
secretion 2) intracellular trafficking 3) post
translational modifications 4) inorganic ion
transport and metabolism 5) signal transduction
mechanism and 6) cell division and chromosome
partitioning. Remaining other twelve categories
harbor mostly low and moderately selected genes
therefore not included in the analysis.
To understand the functional constraints’
genes of flagellar assembly, functional domains
were indentified with their corresponding protein
sequence by InterProScan Sequence Search online
tool.(Mulder and Apweiler 2007) Positions of
these domains and motifs were indentified in the
codon alignments with their corresponding
selection rate (Figure 5). In few cases the domains
are in between high selection rate (i.e. flgE, flgH,
flgD, fliF) suggesting slow evolution of these
functional domains. Therefore, it seemed that
though the genes for flagellar assembly are in
strong evolutionary pressure but their function is
essential for the survival of Vibrio cholerae
However, it is one of the limitations for
computational substitution approach that we
cannot always correlate function of the gene the
corresponding codon substitutions.
Identifying Vibrio cholerae specific positively
selected genes using data map
In order to investigate the positively selected genes
those played critical role in determining the fitness
only selected in the Vibrio choler
different groups described earlier and indicated in
Figure 1 were assessed for their orthologous genes
using dN/dS ratio. These three groups are
Group I: All ten Vibrio species 2) Group II:
cholerae only 3) Group III: Non-cholerae
f the 422 genes of core genome
were used as a background dataset and an equation
was used. The
pathways were then ranked based on the P- values
and GO enrichment scores. Six functional
value and higher GO
enrichment score were considered as pathways
with highly enriched positively selected genes
(Figure 4). These categories are 1) cell motility and
secretion 2) intracellular trafficking 3) post-
translational modifications 4) inorganic ion
tabolism 5) signal transduction
mechanism and 6) cell division and chromosome
partitioning. Remaining other twelve categories
harbor mostly low and moderately selected genes
therefore not included in the analysis.
To understand the functional constraints’ on the
genes of flagellar assembly, functional domains
were indentified with their corresponding protein
sequence by InterProScan Sequence Search online
tool.(Mulder and Apweiler 2007) Positions of
these domains and motifs were indentified in the
ignments with their corresponding
selection rate (Figure 5). In few cases the domains
are in between high selection rate (i.e. flgE, flgH,
flgD, fliF) suggesting slow evolution of these
functional domains. Therefore, it seemed that
gellar assembly are in
strong evolutionary pressure but their function is
Vibrio cholerae.
However, it is one of the limitations for
computational substitution approach that we
cannot always correlate function of the gene the
Identifying Vibrio cholerae specific positively
In order to investigate the positively selected genes
those played critical role in determining the fitness
Vibrio cholerae sp., three
different groups described earlier and indicated in
Figure 1 were assessed for their orthologous genes
using dN/dS ratio. These three groups are – 1)
species 2) Group II: Vibrio
cholerae Vibrio
sp. The aim of the classification was to determine
the genes that were under positive selection only in
Vibrio sp. By excluding the positively selected
genes found within Vibrio cholereae and and non
cholerae Vibrio species from the core positively
selected gene set harboring 92 genes, we can
identify the genes that undergone selection
pressure during speciation of Vibrio cholerae
Using the classification status of these three groups
a data-map was built and the genes that were found
to be under high positive selection in group I but
not in group II and III were included as positive.
49 genes were found through the analysis (Table
2), where 12 of these genes were associated with
the six GO categories that were enriched with
highly selected genes. Three selected genes in
flagellar assembly namely FlgE, FliF and MotB
were found to be critical for speciation
cholerae from Vibrio co-ancestor.
Figure 4: GO enrichment score of different
pathways of Vibrio cholerae according to COG
categories. A GO enrichment score were
calculated using the described algorithm and
assigned for each category. Pathways or COG
categories with higher enrichment score and lowe
P-value were thought to be evolving with higher
selection rate.
Vol:1, 2014
Science and Technology P a g e | 6
sp. The aim of the classification was to determine
the genes that were under positive selection only in
Vibrio sp. By excluding the positively selected
genes found within Vibrio cholereae and and non-
cholerae Vibrio species from the core positively
selected gene set harboring 92 genes, we can
identify the genes that undergone selection
Vibrio cholerae.
Using the classification status of these three groups
map was built and the genes that were found
der high positive selection in group I but
not in group II and III were included as positive.
49 genes were found through the analysis (Table
2), where 12 of these genes were associated with
the six GO categories that were enriched with
es. Three selected genes in
flagellar assembly namely FlgE, FliF and MotB
were found to be critical for speciation Vibrio
ancestor.
: GO enrichment score of different
pathways of Vibrio cholerae according to COG
A GO enrichment score were
calculated using the described algorithm and
assigned for each category. Pathways or COG
categories with higher enrichment score and lower
value were thought to be evolving with higher

ISSN 2410-9754 Vol:1, 2014
Figure 5. Individual substitution rate of codons
with their corresponding domain position.
Corresponding protein sequence of codon
alignment were used in INTERPRO scanner to find
out their domains with positions. The labeling of
the domains used in this figure is following :- (1)
Bacterial flagellin N-terminal helical
region[Flagellin_N (PF00669)] (2) Flagellin hook
IN motif [Flagellin_IN (PF07196)] (3) Bacterial
flagellin C-terminal helical region [Flagellin_C
(PF00700)] (4) Flg_bb_rod (PF00460) (5)
Flagellar basal body protein FlaE(PF07559) (6)
Flagellar basal body rod FlgEFG protein C-
terminal (7) FlgEFG_subfam(TIGR03506) (8)
Flagellar hook protein flgE superfamily (9)
flgK_ends( TIGR02492) (10) Flagellar basal body
rod FlgEFG protein C-terminal [Flg_bbr_C
(PF06429) ] (11) Phase 1 flagellin
superfamily(SSF64518) (12) Surface presentation
of antigens (SPOA) (13)
PROKAR_LIPOPROTEIN (PS51257) (14) FlgH
(PF02107) (15) Membrane MotB of proton-
channel complex MotA/MotB [MotB_plug
(PF13677)] (16) OmpA domain [OmpA
(PF00691)] (17) Secretory protein of YscJ/FliF
family[YscJ_FliF (PF01514)] (18) Flagellar M-
ring protein C-terminal [YscJ_FliF_C (PF08345)]
(19) FlgD Tudor-like domain(PF13861) (20)
Flagellar hook capping protein - N-terminal
region (PF03963) (21) FlgD Ig-like
domain(PF13860)(20) Flagellar hook capping
protein - N-terminal region (PF03963) (22) Cache
domain [Cache_1 (PF02743)](23) HAMP
(PF00672,PS50885,SM00304) (23) HAMP
(PF00672, PS50885, SM00304) (24) Methyl-
accepting chemotaxis protein (MCP) signalling
domain [MCPsignal (PF00015)] (25) Vibrio
chemotaxis protein N terminus [MCP_N
(PF05581)] (26) Methyl-accepting chemotaxis-
like domains (chemotaxis sensory transducer) [
MA (SM00283) ] (27) Flagella basal body rod
protein superfamily (IPR006300).
DISCUSSION
A total of 92 genes were found under high positive
selection out of the core genome of selected Vibrio
sp. consisting of 424 orthologous genes. GO
enrichment analysis showed that six pathways
composed of 78 orthologous genes from the core
genome are particularly enriched with highly
positively selected genes. 31 genes highly
positively selected genes belong to these GO
categories out of 78 genes. Among the GO
categories ‘Cell motility and secretion’ is the most
enriched with high positively selected genes
followed by intracellular trafficking as shown by
the enrichment score and P value. Out of 20
orthologous genes belonging to Cell motility
pathway ten genes were found to be under high
positive selection.
Ten high positively selected genes out total 20
orthologous genes associated with Cell motility
facilitates this category to emerge as the most
enriched one with a log(P) value of -26. When the

ISSN 2410-9754 Vol:1, 2014
positively selected genes of the three different
groups (Group I: all sp, Group II: Only VC strain,
Group III: Non cholerae Vibrio sp) were compared
41 genes out of the 92 genes were found to only
31 positively selected genes of the six pathways
(Supplementary Table 2) and 46 highly selected
genes only in Vibrio cholerae species (Table 2)
were found in this study. The selected genes are
from different categories, performed various
functions and lies in the different portions of the
genome. Thus it is concluded that positive
selection in Vibrio cholerae species is a genome
wide phenomena. A possible explanation for this
nearly genome-wide positive selection pressure, as
well as its even distribution across the functional
elements of the genome, may be the result of an
evolutionary arms race, or macro-evolutionary
version of the Red Queen Hypothesis, between
competing species within the mammalian and/or
vertebrate gastrointestinal tract.(Clay and Kover
1996) This habitat is known to harbor vast species
diversity (Frank and Pace 2008, Ley et al. 2008),
and thus competition will constantly exist between
species for resources. According to the Red Queen
Hypothesis, species involved in competition for
resources can maintain their fitness relative to
other competing species only by improving their
specific fitness, and this could ultimately lead to
extensive levels of positive selection signature
across the genome (Clay and Kover 1996,
Lefebure and Stanhope 2009). Every gene that has
been found as Orthologous was annotated
according to NCBI COG database and 18
pathways had been found containing all
Orthologous genes of Vibrio cholerae O395. After
estimating dN/dS for each orthologous gene sets,
92 genes of 16 different pathways were found to be
highly selected and six pathways were found to be
highly selected in vibrio genome (Figure 3). These
pathways are (1) Intracellular trafficking and
secretion (2) Posttranslational modification,
protein turnover, chaperones (3) Cell motility and
secretion (4) Signal transduction mechanisms (5)
Inorganic ion transport and metabolism and (6)
Cell division and chromosome partitioning.
Table 2. Genes that showed evidence of Positive selection
Gene Symbol % PS€
COG¥
GO Term
MotA/TolQ/E
xbbB
14.19 COG0811U Intracellular trafficking and secretion
VC0395_007
0
14.02 COG0840NT Signal Transduction
mshH 12.39 COG2200T Signal Transduction
VC0395_A18
07
11.86 COG2217P Inorganic ion transport and metabolism
FkpA 11.72 COG0545O Post-translational modification, protein turnover, chaperone
functions
CcmF 11.18 COG1138O Post-translational modification, protein turnover, chaperone
functions
FliN 10.85 COG1886NU Cell motility and secretion
Tig 10.49 COG0544O Post-translational modification, protein turnover, chaperone
functions
flgB 9.92 COG1815N Cell motility and secretion
PstS 9.89 COG0226P Inorganic ion transport and metabolism
MotB* 9.77 COG1360N Cell motility and secretion
FlaA 9.33 COG1344N Cell motility and secretion
flgE* 9.26 COG1749N Cell motility and secretion

ISSN 2410-9754 Vol:1, 2014
flgD 8.94 COG1843N Cell motility and secretion
glnE 8.9 COG1391OT Signal Transduction
FexB 8.49 COG0642T Signal Transduction
SppA* 8.28 COG0616OU Post-translational modification, protein turnover, chaperone
functions
ptsP* 8.17 COG3605T Signal Transduction
metN* 8.14 COG1135P Inorganic ion transport and metabolism
SmpB* 8.07 COG0691O Post-translational modification, protein turnover, chaperone
functions
mukB* 8.02 COG3096D Cell division and chromosome partitioning
SecF* 7.94 COG0341U Intracellular trafficing and secretion
flgK 7.85 COG1256N Cell motility and secretion
lepB* 7.72 COG0681U Intracellular trafficing and secretion
HscB 7.6 COG1076O Post-translational modification, protein turnover, chaperone
functions
VC0395_055
7
7.45 COG0229O Post-translational modification, protein turnover, chaperone
functions
ftsZ* 7.42 COG0206D Cell division and chromosome partitioning
cysJ* 7.37 COG0369P Inorganic ion transport and metabolism
FliF* 7.34 COG1766N Cell motility and secretion
metQ 7.06 COG1464P Inorganic ion transport and metabolism
flgH 7.00 COG2063N Cell motility and secretion
Note: COG categories were retrieved from table of Protein Details for Vibrio cholerae O395 using NCBI
whole genome search. ( * Genes that are selected only in Vibrio cholerae genomes; €
%PS : Percentage of
Positively Selected sites; ¥
COG : Cluster of Orthologous genes )
However, the most interesting observation came
out from our study is the positive selection event
of cell motility and secretion pathway. Evidently
genes involved in flagellar assembly are under
severe influence of natural adaptation in vibrio
genome as they play roles in different bacterial
process. Besides motility, flagella are also involved
in chemotaxis and signaling mechanism. It is the
outer membrane portion and directly interacts with
host during adherence with intestinal epithelial
cells. (Attridge and Rowley 1983) It was
hypothesized earlier that, as motility is one of the
important virulent factor for Vibrio cholerae thus
host will try to mimic the activity of this system
and proteins associated with motility will be
important target for natural selection. Our study
clearly reveals that the whole flagellar assembly is
under strong evolutionary pressure and gene
associated with this system is evolving together
with different selection rate (Figure 6).
CONCLUSION
There is a possibility that we have missed some
genes during this process as many of them were
discarded due to the recombination event or
evidence for Horizontal transfer. False positive or
false negative results were no assessed here with
alternative approach as we considered substitution
rate of every codon site and finally the percentage
of positively selected sites. Although highly
selected genes were compared with house-keeping
genes for their selection rate, which clearly
indicates the validity of our method but still there
is a chance that we have missed some genes or
included some false positives genes as positively
selected genes.
Among 18 COG categories only six were found to

ISSN 2410-9754
@2014, GNP
be under severe influence of evolutionary pressure.
In brief, genes that are selected in vibrio genome
are mostly involved in motility, chemotaxis, ion or
nutrition transport, signaling, protein modification,
multiplication of cell and intracellular trafficking.
All these evidence suggest that genes that come
with direct host-pathogen interaction, involved
with nutritional status or environmental adaptation
Figure 6. Genes involved in Flagellar Assembly.
corresponding genes. Genes highlighted with Red
Both inner membrane and outer membrane proteins coding genes are evolving with higher selection rate.
be under severe influence of evolutionary pressure.
at are selected in vibrio genome
are mostly involved in motility, chemotaxis, ion or
nutrition transport, signaling, protein modification,
multiplication of cell and intracellular trafficking.
All these evidence suggest that genes that come
pathogen interaction, involved
with nutritional status or environmental adaptation
are under evolutionary pressure and shows high
rate of natural selection. The results also clearly
support Red Queen hypothesis.
We also concluded that in Vibrio Spp. N
selection is a genome wide phenomena and
purifying selection is the dominant selection
Process.
Genes involved in Flagellar Assembly. A flagellar proteins assembly is shown here with their
ighted with Red and Yellow is highly & moderately selected
Vol:1, 2014
Science and Technology P a g e | 10
are under evolutionary pressure and shows high
rate of natural selection. The results also clearly
support Red Queen hypothesis.
We also concluded that in Vibrio Spp. Natural
selection is a genome wide phenomena and
purifying selection is the dominant selection
A flagellar proteins assembly is shown here with their
highly & moderately selected respectively.

ISSN 2410-9754 Vol:1, 2014
ACKNOWLEDGEMENT
We thank Mahmuda Khatun and Hadisur Rahman
for their help during data mining.
REFERENCE
1. Attridge SR, Rowley D. 1983. The Role of the
Flagellum in the Adherence of Vibrio cholerae.
Journal of Infectious Diseases 147: 864-872.
2. BERRY MNGALJ. 1975. Motility as a
Virulence Factor for Vibrio cholerae.
INFECTiON AND IMMUNITY 11: 890-897.
3. Boc A, Makarenkov V. 2003. New Efficient
Algorithm for Detection of Horizontal Gene
Transfer Events. Pages 190-201 in Benson G,
Page RM, eds. Algorithms in Bioinformatics,
vol. 2812 Springer Berlin Heidelberg.
4. Chen SL, et al. 2006. Identification of genes
subject to positive selection in uropathogenic
strains of Escherichia coli: a comparative
genomics approach. Proc Natl Acad Sci U S A
103: 5977-5982.
5. Clay K, Kover PX. 1996. The Red Queen
Hypothesis and plant/pathogen interactions.
Annu Rev Phytopathol 34: 29-50.
6. Felsenstein J. 1981. Evolutionary trees from
DNA sequences: a maximum likelihood
approach. J Mol Evol 17: 368-376.
7. Frank DN, Pace NR. 2008. Gastrointestinal
microbiology enters the metagenomics era.
Curr Opin Gastroenterol 24: 4-10.
8. Hahn MW. 2008. Toward a selection theory of
molecular evolution. Evolution 62: 255-265.
9. Hall TA. 1999. BioEdit: a user-friendly
biological sequence alignment editor and
analysis program for Windows 95/98/NT.
Nucleic Acids Symposium Series 41: 95-98.
10. Hammer BK, Bassler BL. 2003. Quorum
sensing controls biofilm formation in Vibrio
cholerae. Mol Microbiol 50: 101-104.
11. Hurst LD. 2002. The Ka/Ks ratio: diagnosing
the form of sequence evolution. Trends Genet
18: 486.
12. J. A. Hartigan MAW. 1979. A K-Means
Clustering Algorithm. Applied Statistics 28:
100--108.
13. Kimura M. 1983. The neutral theory of
molecular evolution. Cambridge: Cambridge
University Press.
14. Kosakovsky Pond SL, Frost SD. 2005. Not so
different after all: a comparison of methods for
detecting amino acid sites under selection. Mol
Biol Evol 22: 1208-1222.
15. Lefebure T, Stanhope MJ. 2009. Pervasive,
genome-wide positive selection leading to
functional divergence in the bacterial genus
Campylobacter. Genome Res 19: 1224-1232.
16. Ley RE, et al. 2008. Evolution of mammals
and their gut microbes. Science 320: 1647-
1651.
17. Li Z, Wang L, Zhong Y. 2005. Detecting
horizontal gene transfer with T-REX and
RHOM programs. Brief Bioinform 6: 394-401.
18. MacQueen JB. 1967. Some Methods for
Classification and Analysis of MultiVariate
Observations. Pages 281-297 in Cam LML,
Neyman J, eds. Proc. of the fifth Berkeley
Symposium on Mathematical Statistics and
Probability: University of California Press.
19. Martin D, Rybicki E. 2000. RDP: detection of
recombination amongst aligned sequences.
Bioinformatics 16: 562-563.
20. Montoya-Burgos JI. 2011. Patterns of Positive
Selection and Neutral Evolution in the Protein-
Coding Genes of <italic>Tetraodon</italic>
and <italic>Takifugu</italic>. PLoS ONE 6:
e24800.
21. Moreno-Hagelsieb G, Latimer K. 2008.
Choosing BLAST options for better detection
of orthologs as reciprocal best hits.
Bioinformatics 24: 319-324.
22. Mulder N, Apweiler R. 2007. InterPro and
InterProScan: tools for protein sequence
classification and comparison. Methods Mol
Biol 396: 59-70.
23. Muse SV, Gaut BS. 1994. A likelihood
approach for comparing synonymous and
nonsynonymous nucleotide substitution rates,
with application to the chloroplast genome.
Mol Biol Evol 11: 715-724.
24. Nandi T, et al. 2010. A genomic survey of

ISSN 2410-9754 Vol:1, 2014
positive selection in Burkholderia
pseudomallei provides insights into the
evolution of accidental virulence. PLoS Pathog
6: e1000845.
25. Padidam M, Sawyer S, Fauquet CM. 1999.
Possible emergence of new geminiviruses by
frequent recombination. Virology 265: 218-
225.
26. Petersen L, Bollback JP, Dimmic M, Hubisz
M, Nielsen R. 2007. Genes under positive
selection in Escherichia coli. Genome Res 17:
1336-1343.
27. Posada D, Crandall KA. 2001. Evaluation of
methods for detecting recombination from
DNA sequences: computer simulations. Proc
Natl Acad Sci U S A 98: 13757-13762.
28. Sealfon RS, Hibbs MA, Huttenhower C,
Myers CL, Troyanskaya OG. 2006. GOLEM:
an interactive graph-based gene-ontology
navigation and analysis tool. BMC
Bioinformatics 7: 443.
29. Suyama M, Torrents D, Bork P. 2006.
PAL2NAL: robust conversion of protein
sequence alignments into the corresponding
codon alignments. Nucleic Acids Res 34:
W609-612.
30. Suzuki Y, Gojobori T. 1999. A method for
detecting positive selection at single amino
acid sites. Mol Biol Evol 16: 1315-1328.
31. Tamura K, Peterson D, Peterson N, Stecher G,
Nei M, Kumar S. 2011. MEGA5: molecular
evolutionary genetics analysis using maximum
likelihood, evolutionary distance, and
maximum parsimony methods. Mol Biol Evol
28: 2731-2739.
32. Tatusov RL, Galperin MY, Natale DA, Koonin
EV. 2000. The COG database: a tool for
genome-scale analysis of protein functions and
evolution. Nucleic Acids Research 28: 33-36.
33. Wernersson R, Pedersen AG. 2003. RevTrans:
Multiple alignment of coding DNA from
aligned amino acid sequences. Nucleic Acids
Res 31: 3537-3539.
34. Yang Z, Bielawski JP. 2000. Statistical
methods for detecting molecular adaptation.
Trends Ecol Evol 15: 496-503.

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