Fmicb 10 00053

ORIGINAL RESEARCH
published: 06 February 2019

doi: 10.3389/fmicb.2019.00053
Comparative Genomic Analyses

Reveal Core-Genome-Wide Genes
Under Positive Selection and Major
Regulatory Hubs in Outlier Strains of
Pseudomonas aeruginosa
Utkarsh Sood 1,2 , Princy Hira 1 , Roshan Kumar 1,2,3 , Abhay Bajaj 1,4 ,
Desiraju Lakshmi Narsimha Rao 5 , Rup Lal 1,2* and Mallikarjun Shakarad 1*
1
Department of Zoology, University of Delhi, New Delhi, India, 2 PhiXGen Private Limited, Gurugram, India, 3 Department
of Veterinary & Biomedical Sciences, South Dakota State University, Brookings, SD, United States, 4 National Centre for
Microbial Resource, National Centre for Cell Science, Pune, India, 5 ICAR-Indian Institute of Soil Science, Bhopal, India
Edited by:
Vasco Ariston
Genomic information for outlier strains of Pseudomonas aeruginosa is exiguous when
De Carvalho Azevedo, compared with classical strains. We sequenced and constructed the complete genome
Universidade Federal de Minas
of an environmental strain CR1 of P. aeruginosa and performed the comparative genomic
Gerais, Brazil
analysis. It clustered with the outlier group, hence we scaled up the analyses to understand
Reviewed by:
Vasvi Chaudhry, the differences in environmental and clinical outlier strains. We identified eight new regions
University of Tübingen, Germany of genomic plasticity and a plasmid pCR1 with a VirB/D4 complex followed by trimeric
Marcus Vinicius Canário Viana,
Universidade Federal do Pará, Brazil
auto-transporter that can induce virulence phenotype in the genome of strain CR1.
*Correspondence:
Virulence genotype analysis revealed that strain CR1 lacked hemolytic phospholipase C
Rup Lal and D, three genes for LPS biosynthesis and had reduced antibiotic resistance genes
ruplal@gmail.com
when compared with clinical strains. Genes belonging to proteases, bacterial exporters
Mallikarjun Shakarad
beelab.ms@gmail.com and DNA stabilization were found to be under strong positive selection, thus facilitating
pathogenicity and survival of the outliers. The outliers had the complete operon for the
Specialty section:
production of vibrioferrin, a siderophore present in plant growth promoting bacteria. The
This article was submitted to
Evolutionary and Genomic competence to acquire multidrug resistance and new virulence factors makes these
Microbiology, strains a potential threat. However, we identified major regulatory hubs that can be used
a section of the journal
Frontiers in Microbiology
as drug targets against both the classical and outlier groups.
Received: 21 November 2018 Keywords: Pseudomonas aeruginosa, outliers, environmental genomics, drug targets, positive selection
Accepted: 14 January 2019
Published: 06 February 2019
Citation: INTRODUCTION
Sood U, Hira P, Kumar R, Bajaj A,
Rao DLN, Lal R and Shakarad M Pseudomonas aeruginosa is one of the major opportunistic pathogens that has been isolated
(2019) Comparative Genomic from a wide range of ecological niches including soil, water and clinical samples (Stover et al.,
Analyses Reveal Core-Genome-Wide
2000). This opportunistic pathogen is prototypical “multidrug-resistant” (MDR) with intrinsically
Genes Under Positive Selection
and Major Regulatory Hubs in Outlier
advanced antibiotic resistance gene clusters (Lambert, 2002; Livermore, 2002). Some of the strains
Strains of Pseudomonas aeruginosa. of P. aeruginosa have been associated with serious illnesses mainly imparting nosocomial infections
Front. Microbiol. 10:53. (ventilator-associated pneumonia) and various sepsis syndromes (Planquette et al., 2013; Philippart
doi: 10.3389/fmicb.2019.00053 et al., 2015). The pathogenicity of P. aeruginosa is attributed to the presence of prominent virulence
Frontiers in Microbiology | www.frontiersin.org 1 February 2019 | Volume 10 | Article 53

Sood et al. Genome Analysis of P. aeruginosa Outlier Strains
factors that consist of proteases, pili, flagella, quorum sensing interaction on the core genome of both the groups was used
proteins, exotoxin A and type III secretion system (T3SS) to identify major regulators that can be targeted as drug
(Lyczak et al., 2000). Amongst these, the T3SS- also called targets.
injectosome is responsible for the injection of toxins into
the eukaryotic host cell and thus majorly determines the
degree of pathogenicity (Cornelis, 2006). Therefore, strains MATERIALS AND METHODS
lacking T3SS were thought to be less pathogenic due to
the absence of injectosome machinery and its effector toxins Genome Sequencing and Assembly
(ExoS, ExoT, ExoU, and ExoY) that play a prominent role The Pseudomonas strain CR1 used in the study is an isolate from
in acute as well as chronic infections (Hauser, 2009). These the rhizosphere of chili crop grown with high inputs of chemical
T3SS deficient strains are termed as outlier strains and they fertilizers and pesticides at Guntur, Andhra Pradesh, India
form a distinct phylogenetic clade represented by strain PA7 (Supplementary Table S1). The DNA was extracted using Cetyl
(Roy et al., 2010); and were shown to have diverged early Trimethyl Ammonium Bromide (CTAB) extraction method
from the classical strains of P. aeruginosa (Gomila et al., (Wilson, 1987) and sequenced using Single Molecule Real Time
2015). The outliers counteract T3SS deficiency by adopting sequencing (SMRT, Pacific Biosciences) at the Quebec Innovation
novel virulence factors and attaining multidrug resistance, Centre McGill University, Canada. The 16S rRNA sequence
thus making them difficult to treat using antibiotics (Roy homology of the strain revealed its identity as Pseudomonas
et al., 2010; Huber et al., 2016). An outlier clinical isolate of aeruginosa.
P. aeruginosa strain CLJ1 was reported to induce hemorrhagic A total of 73,250 subreads of average length 10,488 bp
pneumonia, mainly due to the presence of a two-partner secreted were obtained from Pac Bio RS II with 20 kb library
Exolysin (ExlA) with membrane lytic activity (Elsen et al., (Pacific Biosciences, Menlo Park, CA, United States). The
2014). The two genes encoding this lytic toxin are present reads were assembled into 2 contigs, using the HGAP2
on a region of genomic plasticity (RGP) that is associated algorithm (Chin et al., 2013) in SMRT Analysis 2.1 (Pacific
with outlier P. aeruginosa (Huber et al., 2016; Reboud et al., Biosciences).
2016). Although strains of P. aeruginosa are ubiquitous and
there are more than 1500 assemblies present for classical Selection and Annotation of Genomes
strains, only a handful of draft genomes (n = 12) (Boukerb for Comparative Analysis
et al., 2015; Kos et al., 2015; Mai-Prochnow et al., 2015; van For comparative genomic analysis, complete genomes of 50
Belkum et al., 2015) are present in the genome database for P. aeruginosa strains (including the complete genome of PA7)
outlier strains (either clinical isolates or with unknown origin), were retrieved from the Pseudomonas Genome Database (Winsor
with a single complete genome of strain PA7 (Roy et al., et al., 2016) (Supplementary Table S2, data accessed on
2010). 14.07.2016). Further to increase the resolution, 15 draft genomes
In this study, a new outlier strain CR1 of P. aeruginosa, reported as the closest neighbor by RAST neighbor score were
an isolate from the rhizosphere of chili crop was genomically also included in the analysis. Preliminary analysis revealed that
characterized (Supplementary Table S1). Its complete genome the strain CR1 was a member of the outlier PA7 clade. Therefore,
was sequenced and compared with other outliers of clinical and we included all the draft genomes of outlier strains (n = 12)
unknown origin. Virulence factors in association with acquired of P. aeruginosa available till 14.07.2016. The genomes were
resistance play a significant role in inducing pathogenicity, annotated by RAST server 2.0 (Aziz et al., 2008) and Glimmer-
therefore the genes associated with virulence and antibiotic 3 (Delcher et al., 2007) was used for predicting genes. The 12
resistance were analyzed in this environmental isolate. Here, draft genome of outliers and two complete genomes of strain CR1
we also report the presence of a plasmid pCR1 from strain and PA7 were taken for genomic comparison among outliers. The
CR1 which is not present in the genome of any of the draft genomes were checked for completeness by analyzing the
outlier strains. The plasmid had VirB/D4 type IV secretion presence of 107 essential copy genes using the Comprehensive
system in association with trimeric autotransporter adhesin Microbial Resource as a database, where 107 Hidden Markov
protein having similarity with yadA like adhesin that can models (HMMs) of essential copy genes were analyzed in all
impart a pathogenic potential to CR1 (Christie, 2001; Linke phylogenetic outlier strains (Dupont et al., 2012).
et al., 2006; Basso et al., 2017). Like other outliers, CR1 lacks Further, the 14 outlier strains were annotated for RNAs and
T3SS which majorly confers pathogenicity. The probability tRNAs using RNAmmer (Lagesen et al., 2007) and ARAGORN,
of these strains to be a pathogen was also assessed based (Laslett and Canback, 2004), respectively. The CRISPR elements
on the number of pathogenic protein families present in within the outlier strains were analyzed using CRISPR finder
the genome. Differences in the core and pan-genes of the server (Grissa et al., 2007). The Phage genomic content was
two groups were determined. Core genome-wide genes under determined using PHAST (Zhou et al., 2011). The sequence
positive selection were determined for identifying the genes type (ST) was also predicted for the strains clustered in
under strong positive selection that can provide advantageous outlier clade using MLST 1.8 tool (Larsen et al., 2012).
variants to the outlier genomes. The ability of these strains to The whole genome sequence of strain CR1 was deposited to
gain virulence factors and acquired antibiotic resistance require PubMLST server (Jolley et al., 2018) for assigning new ST.
new drug targets to be identified. Therefore, protein–protein The DNA-DNA hybridization values were also calculated to

delineate at sub-species level using the Genome to Genome v 1.1.3 pipeline (Supplementary File S1) (Hongo et al.,
Distance Calculator (GGDC v 2.1) for the outliers (Auch et al., 2015). The genes in the orthologous group were detected
2010a,b). for recombination signals and removed using PhiPack (Bruen
and Bruen, 2005). For all genes tested for positive selection,
Phylogenomics Analysis the false discovery rate (FDR) was controlled using the BY
All Pseudomonas strains (n = 78) were subjected to method (Benjamini and Yekutieli, 2001) and the significance
phylogenetic/phylogenomic analysis using four different level was set to 10%. The rates of synonymous and non-
methods viz. Mummer based Average Nucleotide Identity synonymous substitutions were estimated using site-model
(ANIm), PhyloPhlAn (Segata et al., 2013), phylogeny based on of the codeml program in the PAML v4.8 package (Yang,
SNPs within the core genome using Harvest suite (Treangen et al., 2007). trimAl (Capella-Gutiérrez et al., 2009) was used for
2014) and pangenome consensus matrix using get_homologues alignment trimming. A phylogenetic tree for each gene was
(Contreras-Moreira and Vinuesa, 2013). The ANIm values were built using the maximum-likelihood approach implemented by
calculated for each pair of genomes using pyani1 module based PhyML v3.0 (Guindon and Gascuel, 2003). The search for
on the Mummer algorithm at default parameters. Thereafter, positive selection in codeml is done by comparing the log-
a dual dendrogram based on ANIm values, was constructed likelihood values of codon evolution models that do not allow
in R (R Development Core Team, 2015). Further, to obtain a sites with positive selection (M1a, M7, and M8a) with the
consensus tree topology, amino acid sequences predicted by values obtained from the more general nested models that
Glimmer-3 were used for phylogenomic reconstruction using also allow for site classes with positive selection occurrence
PhyloPhlAn. PhyloPhlAn locates 400 ubiquitous bacterial genes (M2 and M8, respectively). The p-values are calculated as
by sequence alignment in amino acid space, then builds a tree by 21l (twice the difference in the likelihood of the two nested
concatenating the most discriminative positions in each gene into models evaluated) based on the χ2 distribution with 2◦
a single long sequence and applying FastTree (Price et al., 2009), of freedom for nested models M1a/M2 and M7/M8 and
and RaxML (Stamatakis, 2014) to construct phylogenetic tree 1◦ of freedom for nested models M8a/M8. This being a
based on maximum likelihood with 1000 bootstrap replicates. multiple testing scenario, corrected q-values from the list
Unrooted maximum likelihood (100 bootstraps) tree of 78 of p-values obtained for all groups evaluated using the
P. aeruginosa genomes based on SNPs within the core genome given nested model pair were determined (Hongo et al.,
was defined using Parsnp tool of the Harvest suite. 2015).
Pangenome matrix was also used to construct the dendrogram
for closely related P. aeruginosa strains in order to obtain better Core and Pan-Genome Analysis
resolution of phylogenetic clades. The consensus pangenome To decipher the core genome content of the outlier strains, the
matrix was generated using the intersection of pan-genes get_homologues pipeline was used with OrthoMCL (OMCL) at
predicted by COG and OMCL algorithms using get_homologues. 75% query coverage as well as sequence similarity (Contreras-
This matrix was then used to construct a parsimony tree using Moreira and Vinuesa, 2013). The pan-genome was obtained
PARS program from the PHYLIP suite to deduce the phylogeny using OrthoMCL methods and at default parameters (with t = 0).
implied in this matrix. The core and pan-genomic contents were determined for all the
Pseudomonas strains (n = 78), classical (n = 64), and outliers
Determination of Regions of Genome (n = 14) separately. The pangenome for 78 strains was used to
Plasticity (RGP) find out the genes exclusively present in all the outliers (n = 14)
The strain CR1 was analyzed for regions of genomic that were absent in all the classical strains (n = 64). The core
plasticity (RGP) using the standard genome subtractive and pangenome for all groups were annotated against the COG
approach on pairwise genome comparisons with reference database by rpsblast (e-value 0.001) using WebMGA server (Wu
genomes of PAO1, UCBPP-PA14, and PA7. The criteria to S. et al., 2011).
characterize and discriminate RGPs from other features in a
genome were based on the following: atypical composition,
Functional Annotations of the Outlier
presence of tRNA- that serves as insertion sites, presence
of insertion sequence (IS) elements and direct repeats Strains
(DR) flanking RGPs, presence of integrase and transposase To determine the functional variability across the 14 outlier
(Langille et al., 2010; Che et al., 2014). These RGP were genomes in the PA7 clade, the comparative genomic analysis
then plotted in genome map using CG view (Grant and was performed based on proteins and metabolic pathways. The
Stothard, 2008) in the circular map of the chromosome 1 ORFs were predicted using Glimmer-3 and annotated by KAAS
(Figure 1A). (KEGG Automatic Annotation Server) (Moriya et al., 2007) using
Bi-directional Best Hit (BBH) algorithm. Further, the metabolic
Orthologs Under Positive Selection pathways were reconstructed for the outlier genomes using
The orthologs were predicted using OrthoMCL v1.4 using – MinPath (Minimal set of Pathways) (Ye and Doak, 2009) to
mode 1. The orthologous groups were then added to POTION obtain the minimal set of pathways. COG categories were also
assigned to the proteome of all the outlier strains by rpsblast (e-
1
https://github.com/widdowquinn/pyani value 0.001) against the COG database using WebMGA server.

FIGURE 1 | General genomic attributes of Pseudomonas aeruginosa CR1. (A) Circular map of chromosome 1 of CR1 strain. From outside to inside Ring 1: COG
categories of ORFs in the positive strand. Ring 2: COG categories of ORFs in the negative strand. Ring 3: Regions of Genomic plasticity starting from zero bp mark
in a clockwise direction. Ring 4: BLASTn alignment (expected threshold = 1e-220) between CR1 and previously sequenced outlier PA7 (teal); Ring 5: PAO1 (aqua);
Ring 6: UCBPP-PA14 (orange). Rings 7 and 8: GC content and GC skew, respectively. (B) Circular map of plasmid pCR1. From outside to inside Rings 1, 2, 3, and 4
depicts COG categories of ORFs of the positive strand, genes on positive strand, genes on negative strand and COG categories of ORFs of negative strand,
respectively. Rings 5 and 6 represents GC content and GC skew, respectively.

The matrix thus generated was plotted as a heatmap with dual making a link from a node having degree kn to another node
dendrogram in R. of degree k0 n . Then, the average neighborhood connectivity of
nodes with connectivity kn is given by Cn (kn ) = 6 k 0 n k0 n P
Pathogenic Potential, Resistance Profile (k0 n | kn ) ∼ kn −α (Girvan and Newman, 2002) following a power
law scaling behavior with α < 1 for most of the real networks
and Virulence Factors of Outlier Strains
(Maslov and Sneppen, 2002). If Cn (kn ) is an increasing function
The genomic data of all the outlier strains were annotated
of kn (for negative values of α), then the topology of the network
for pathogenic protein families using PathogenFinder and the
shows assortative mixing (Almaas, 2007) where nodes with a
probability of being a pathogen was calculated using the whole
high number of edges per node (high-degree nodes) have an
genome data (Cosentino et al., 2013). Resfinder (Kleinheinz et al.,
affinity to connect to other high-degree nodes in the network.
2014) was used to determine the acquired resistance genes in the
However, with positive values for α is the signature of the network
outliers. Virulence factor database (VFDB) (Chen et al., 2005) was
having a hierarchical structure, where low-degree nodes tend to
used for deciphering bacterial virulence factors.
connect high-degree hubs (Almaas, 2007) and few high-degree
hubs present in the network try to control the low-degree nodes.
Protein–Protein Interactions
For determining the major key regulatory proteins that are
specific to particular clade and can act as potential drug targets RESULTS AND DISCUSSION
in the classical and outlier strains, the interactome of the core
genes was analyzed. The protein–protein interaction (PPI) model Genomic Features Among Outliers
was constructed using STRING Database v10.5 (Szklarczyk et al., The sequences obtained for the strain CR1 were assembled into
2017). Pseudomonas aeruginosa was selected as the reference two replicons of sizes 6,138,025 bp (Chr 1) and 61,310 bp
organism for PPI construction. The core genes of both the groups (pCR1). In order to circularize both the replicons, the ends of
were used as input and queried against P. aeruginosa PPIs present the assembled contigs were mapped using BLASTn (Altschul
in the STRING database. The PPI networks were visualized using et al., 1990). An overlapping region of 19,971 bp in case of
Cytoscape Version 3.3.0 (Shannon et al., 2003). Network analyzer the chromosome and 14,506 bp in the plasmid were detected
plugin was used for determining the statistical and functional and removed. The chromosome and plasmid were found to be
significance of the PPI networks, calculated using different 6,118,054 and 46,804 bp, respectively, making a total genome size
parameters such as the probability of degree distribution, average of 6,164,858 bp (6.16 Mbp) (Figures 1A,B). CR1 and PA7 had
clustering coefficient and average neighborhood connectivity as the complete set of 107 essential marker genes and all the draft
described in previous studies (Albert and Barabasi, 2002; Gupta genomes were more than 96–98% complete based on essential
et al., 2016; Kumar et al., 2017). marker gene approach.
The average genome size of P. aeruginosa outliers was
Statistical Analyses of the Network 6,539,166 bp ± 233906 bp, with strain AZPAE14941 showing
The degree of probability distribution, P(k), of a network defined the maximum size (6,881,480 bp) and minimum in strain CR1
by P(k) = nk/N, which is the ratio of the number of nodes having (6,164,858 bp) (Supplementary Figure S1). The present results
a k degree in the network (nk) to the size of the network (N), was show that the genome size of strain CR1 is smallest among the
used to capture the network structure, identification of hubs, and outlier strains, primarily due to the lack of type I restriction-
modular organization of the network. The constructed network modification system and mercury resistance cluster (RGP63 and
obeyed the power law, P(k) ∼k−γ , indicating the scale-free nature RGP79). In contrast to PA7 (Roy et al., 2010) three RGPs (RGP4,
of the network, where γ is an order parameter that identified RGP78, and RGP79) having characteristic phage signatures and
the different topological structure of a scale-free network. The a putative integrated plasmid (RGP75) were also absent in CR1.
clustering coefficient C(k), which is defined by C (k) = 2E/[k Out of the 18 RGP reported exclusive to PA7 (Roy et al.,
(k − 1)] is the ratio of the number of edges E of the node having 2010), 13 were present in CR1. As the missing regions mostly
a k degree with neighbors to the total possible number of such coded for resistance to antibiotics and phage-related elements
edges, [k (k − 1)]/2 which is a measure of the topological structure it can be reasonably ascertained that resistance is acquired by
of the network (Watts and Strogatz, 1998). The average clustering the organism under stress in a clinical setup that is missing
coefficient C(k) identifies overall organization of formation of in the environmental strains. A similar scenario was observed
clusters in the network. Similar to P(k), C(k) may depend on in the genome of an environmental isolate of classical clade-
network size and characterizes various properties of the network: strain M18 (6,327,754 bp) that was closely related to clinical
(i) for scale-free and random networks where C(k) is independent strain LESB58 (6,601,757 bp) but had a smaller genome and
of k, C(k) ∼ constant, and (ii) for hierarchical networks where was more susceptible to several antimicrobial agents (Wu D. Q.
C(k) follows power-law scaling behavior, C(k) ∼ kβ with β ∼ 1. et al., 2011). Based on this, it can be hypothesized that CR1
The neighborhood connectivity of a node is the number of type genomes are the progenitors of PA7 type genomes and
neighbors connected to it and characterizes the correlation might have acquired multi drug resistance probably in a hospital
pattern of connectivity of interacting nodes in the network. environment or hospital waste disposal site. Our hypothesis gains
This connectivity correlation would be measured by defining support from the fact that an outlier strain CLJ3 that was resistant
a conditional probability P(k0 n |kn ) which is the probability of to antibiotics was isolated after antibiotic administration from

the same patient from which CLJ1 was isolated (Elsen et al., formation in P. aeruginosa (Wood and Wood, 2016) was also
2014). This, strengthens the view that the environment shapes the detected. pCR1 showed an overall identity (Iden) of 97% with
genomic content of an organism (Kumar et al., 2017). Among a query coverage (QC) of 76% with a newly sequenced plasmid
all the outliers, only strain CR1 possessed a plasmid of size p14057 having KPC resistance (BLASTn; NCBI NR database).
46,804 bp with GC content of 59.2% and approximately 45% It also contained VirB/D4 type IV secretion system (T4SS)
of ORFs in the plasmid coded for hypothetical proteins. The gene cluster (B7D75_29180-29240), showing similarity with the
presence of plasmid within the strain CR1 suggested horizontal T4SS present on the chromosome of P. savastanoi (QC: 83%
gene transfer (HGT) mediated acquisition as none of the outliers and Iden.: 100%; Accession: FN645745.1) and to T4SS on the
reported in the literature possessed any plasmids. Further, the plasmid of P. syringae B76 (QC: 65% and Iden: 68%; Accession:
percentage GC content of the plasmid (59.2%) is well below the JQ418525.1). VirB/D4 type T4SS mediates the transfer of
average GC content (66.5%) of outliers’ genome and members of DNA-protein complexes and other proteins like virulence factors
classical strains of P. aeruginosa (Mathee et al., 2008) suggesting to the host cell by conjugation (Fronzes et al., 2009; Wallden
its extra-chromosomal origin. et al., 2010). The putative relaxase (B7D75_28990) on pCR1
Outlier strains (n = 14) possessed a wide variety of CRISPR in association with the T4SS system might be responsible for
elements, with a maximum number of CRISPR arrays (n = 5) rolling circle replication-mediated conjugation (Chandler et al.,
in case of CR1 and AZPAE14901 (Table 1). The presence 2013) in strain CR1. Notably, this plasmid had no identity to the
of a large number of CRISPR elements suggested that these conjugative integrated pKLC102 region (RGP75) of the strain
outliers perhaps were vulnerable to bacteriophage attacks that PA7. Additionally, a conjugal transfer protein (B7D75_29255)
led to the incorporation of CRISPR elements. Eleven outlier having yadA like anchor protein domain (LPXTG motif) similar
strains showed phage protein signatures from Pseudomonas to the putative adhesin on the plasmid of strain PA3448 isolated
phage Pf1 (NC_001331), Pseudomonas phage YMC11/02/R656 from blood of human (QC: 100%, Iden.: 74%; Accession No:
(NC_028657) and 8 strains showed the presence of phage OGX61696.1) was found in pCR1. This protein belongs to
proteins from Pseudomonas phage F116 (NC_006552). The the class of trimeric autotransporters adhesins (TAAs) and is
abundance of these phage proteins within the outliers suggested characterized as a virulence factor by BLASTp based on similarity
the common phage pool for the P. aeruginosa outlier strains. with VFDB protein dataset, increasing the capability of adhesion
However, a prophage region showing similarity to proteins to both biotic and abiotic surfaces and auto-aggregation leading
(Supplementary Table S3) of various phages that are known to biofilm formation (Linke et al., 2006). The genes for antibiotic
to infect bacteria associated with soil or environmental samples resistance often reported from clinical P. aeruginosa plasmids
were found only in CR1 strain indicative of its environmental were absent.
origin.
For differentiating these outliers based on their genetic
background and deciphering the sequence type, a combination Consensus Phylogenomic Clustering of
of DNA sequences of housekeeping alleles acs-5, aro-8, gua- Outliers
3, mut-5, nuo-1, pps-11, and trp-3, and their whole genome To demarcate the outlier strains of P. aeruginosa, the
data was used2 . Amongst the outliers (n = 14), 11 were phylogenetic and phylogenomic analyses were performed
assigned known sequence type and it was found that strain by using 400 conserved marker genes, ANIm, core genome
CR1, AZPAE14941, and EML528 corresponds to an unknown alignment, and pan-genome gene presence/absence matrix. All
sequence type (Table 1), highlighting a possibility of novel the analyses revealed three clades with representative genomes
sequence type for these three outlier strains. Subsequently, strain of PAO1, UCBPP-PA14, and PA7. It corresponded with the
CR1 and EML528 were assigned new sequence types, while no phylogeny obtained by Freschi et al., 2015. CR1 was the member
sequence type was assigned to AZPAE14941 due to its allele of the PA7 clade with members that are completely devoid of
profile being incomplete (Table 1). type III secretion system. Strains in the outlier clade shared
nearly 94% identity with the classical strains whereas, within the
Conjugative Plasmid pCR1 clade, the percentage identity increased up to 98–99%, suggesting
The genes encoded by pCR1 had no significant sequence the higher similarity in outliers’ genomic repertoire. A similar
similarity with the genomic sequence of the outliers making trend of clustering was observed in the phylogeny based on
the genes encoded by pCR1 specific to strain CR1. Although 400 ubiquitous conserved bacterial genes, pan-genome matrix
it had 45% hypothetical proteins, pCR1 had all proteins using maximum likelihood method (Guindon and Gascuel,
required for replication (B7D75_29005), plasmid maintenance 2003) (Figure 2 and Supplementary Figures S2, S3) and
(ParA: B7D75_28995, ParB: B7D75_29000 KikA protein: unrooted tree based on core genome alignment (Supplementary
B7D75_29260) and conjugation (TraL: B7D75_29275, Figure S4). This confirmed the high level of genomic relatedness
T4SS B7D75_29180-29235) (Figure 1B) that made up the among the classical strains and outliers yet reflecting the two
plasmid backbone. Additionally, a HigB/A toxin/antitoxin groups to be different. The results from our analyses suggest
(TA) (B7D75_29125/B7D75_29130) system that is shown to that the whole genome-based phylogeny methods should
influence the virulence factors pyochelin, pyocyanin, and biofilm be used for delineating the closely related strains which are
found to be 100% similar on the basis of 16S rRNA gene
2
https://pubmlst.org/paeruginosa/ sequence.

Sood et al.
TABLE 1 | General genomic attributes of 14 outlier strains of P. aeruginosa: ANIm values were calculated between CR1 and other outliers.
Strain Origin Genome Number of Genes Sequence tRNAs rRNAs GC CRISPR Prophage Complete- ANIm (%) DDH∗ (%) Reference
(Country) size contigs type (5S, 16S, content arrays regions ness
23S) (%) (Genes/%)
PA7 Burn wound 6588339 1 6302 1195 75 4,4,4 66.5 3 4 107 (100) 98.97 91.1 Roy et al., 2010
Frontiers in Microbiology | www.frontiersin.org

(Argentina)
CR1 Rhizosphere 6164858 2 5838 3198 76 4,4,4 66.8 5 2 107 (100) 100 100 This study
(India)
ATCC 9027 Otitis 6362326 80 6121 2230 69 1,1,1 66.6 1 2 106 (99.06) 99.33 93.9 Mai-Prochnow
(Australia) et al., 2015
AZPAE14901 Abcess/Pus 6881448 232 6709 2212 63 1,1,1 66.2 5 2 105 (98.13) 99.32 86.6 Kos et al., 2015
(India)
AZPAE14941 Peritoneal 6881480 183 6722 Not 66 2,1,1 66.0 3 2 105 (98.13) 98.94 85.7 Kos et al., 2015
(Hong Kong) Assigned
AZPAE15042 Urinary 6636169 143 6470 2211 69 1,1,1 66.3 3 1 105 (98.13) 99.36 90.7 Kos et al., 2015
(Germany)
7
EML528 Unknown 6365411 53 6064 3043 70 2,1,1 66.6 4 1 107 (100) 98.95 91.7 Boukerb et al.,
(Germany) 2015
EML545 Unknown 6442089 64 6142 2228 68 3,3,3 66.6 3 2 107 (100) 99.37 94.0 Boukerb et al.,
(Germany) 2015
EML548 Unknown 6333473 120 6088 2230 73 4,4,4 66.6 1 2 103 (96.26) 99.34 93.8 Boukerb et al.,
(Germany) 2015
WH-SGI-V- Clinical 6757340 102 6532 2023 67 7,1,1 66.4 3 5 107 (100) 98.90 89.6 van Belkum
07055 (United States) et al., 2015
WH-SGI-V- Clinical 6336003 87 6066 1195 68 6,1,1 66.7 2 3 105 (98.13) 98.96 93.8 van Belkum
07370 (France) et al., 2015
∗ GGDC server was used to calculate genome to genome distance among outliers.
February 2019 | Volume 10 | Article 53

Genome Analysis of P. aeruginosa Outlier Strains
FIGURE 2 | Phylogenetic analysis of P. aeruginosa strains using pan-genome matrix. The consensus pan-genome matrix was generated using the intersection of
pan genes predicted by COG and OMCL algorithms to construct a parsimony tree using PARS from the PHYLIP. Three major clusters represented by PAO1 (Blue),
UCBPP-PA14 (Green), and PA7 (Maroon) were observed. The outlier clade represented by PA7 was split into 2 clades one with a representative genome of PA7
(Maroon) and second by strain CR1 (red).
The dendrograms based on ANI, tree based on core-genome WH-SGI-V-07064. Based on the genetic divergence, we propose
alignment and pangenome matrix provided better resolution of two sub-clades within the outliers.
phylogenetic distance among the clades as these strains differed
on the basis of the pan-genomic content and SNPs in the Regions of Genomic Plasticity (RGP) in
core genome alignment and in case of 400 conserved genes, Strain CR1
the resolution was less due to high sequence identity among Previous studies have shown the presence of various regions of
the 400 marker genes (98–99%). Based on this the outlier genomic plasticity (RGP) within P. aeruginosa strains (Mathee
clade was distinctly represented by two sub-clades one with et al., 2008; Roy et al., 2010; Jani et al., 2016). As the genome of
the representative complete genome of CR1 with draft genomes strain CR1 is nearly 99% similar to PA7, there were large regions
of strains ATCC9027, EML548, EML545, AZPAE14901, and of DNA that were 100% similar (Supplementary Figure S5).
AZPAE15042 and the second clade had PA7 as the representative At the time of analysis 87 RGPs (numbered 1 to 97) had
with the genomes of EML528, AZPAE14941, WH-SGI-V-07055, been reported in P. aeruginosa strains (Klockgether et al., 2011;
WH-SGI-V-07618, WH-SGI-V-07072, WH-SGI-V-07370, and Boukerb et al., 2016). Out of the 87 RGPs, 32 were missing

in strain CR1 and it harbored eight new RGPs which were for galactonate metabolism from the non-Pseudomonas origin.
added to already known 87 RGPs (numbered RGP98-RGP105; Genes involved in D-gluconate, ketogluconate metabolism and
Supplementary Table S4). Although the sequence similarity of choline degradation that were absent in PA7 were present in
strain CR1 and PA7 based on ANIm was 98.97%, strain CR1 RGP103. The ORFs in this region had 87–93% similarity with
harbored 11 prominent regions (eight new RGPs and differences P. citronellis, indicative of HGT. Furthermore, the RGP104 region
in three already known RGPs) having features not reported had an arginine/agmatine antiporter that has a major role in
earlier. Two previously known regions (RGP5 and RGP72) had maintaining the internal pH of the cell and also found in enteric
particular ORFs in strain CR1 which were absent in strain PAO1, pathogenic bacteria (Fang et al., 2010). All these regions are
UCBPP-PA14, and PA7. The third region, RGP58 was found important in maintaining the osmotic balance of cell, protect it
to be missing in PA7 but was present in CR1. The entire list against reactive oxygen species (ROS) and provide continuous
of RGPs has been compiled (Supplementary Table S4) and the energy to the cell by supplying intermediates for the Entner-
strain-specific features of CR1 have been listed (Table 2 and Doudoroff (ED) pathway and prevent starvation (Buch et al.,
Supplementary Figure S6). Replacements islands were identified 2008; Ghasempur et al., 2014). RGP100 contained genes for type
in RGP9, RGP31, RGP60, and RGP68 that had the strain-specific I secretion system (T1SS) and RGP58 coded for type VI secretion
genes for flagellin glycosylation, O-antigen gene cluster, pilA system proteins that can impart a pathogenic potential to strain
gene, and pyoverdine synthesis gene cluster, respectively. RGP63 CR1 (Hood et al., 2010; Thomas et al., 2014). BLASTn analysis
and RGP64 had homologous ORF disrupted by insertion in revealed that ORFs in this region had a non-Pseudomonas origin.
strain CR1. The ORFs included in the RGPs were identified and ORFs in replacement island RGP31 had genes for O-antigen
numbered as per the NCBI locus tag for strain CR1 (B7D75) and biosynthesis protein that is known to be the most variable
PA7 (PSPA7). The flanking loci (conserved) of each RGP called component of the LPS (Steimle et al., 2016). It showed only 66%
anchors in strains PAO1 and UCBPP-PA14 were also identified identity (QC: 55%; e-value: 1e-105) to its homolog present in
as listed in Supplementary Table S4. PA7 and was more closely related to strain NCMG1179 (QC:
These regions of genomic plasticity as observed in strain 99%; identity: 98%). Regions like RGP99, RGP98, and RGP101
CR1 might provide various strain specific advantages to the carrying transposases, partitioning proteins, and phage proteins
organism. For instance, RGP72 in strain CR1 harbored genes could help in recombination and efficient transposition of the
TABLE 2 | Details to RGPs found in strain CR1: number of ORFs, GC content, tRNA, integrase and transposase genes, major annotation, similarity/origin, and putative
functions.
GI (RGP) Size (bp) %G+C tRNA Integrase Transposase Major annotations Similarity Putative functions
RGP98 4,694 55.86 No No Yes Mobile Genetic Elements, Helicase and Transposition of genetic
Helicase, Bacterial Partitioning proteins elements
Partitioning Protein have origins from
Bordetella and
Acidhalobacter
RGP99 41,377 64.21 Yes Yes No Phage-related proteins, Major hits from Recombination
Hypothetical proteins Stenotrophomonas (presence of attL and
Phage S1 attR sites)
RGP100 7,638 64.68 No No No Type I secretion protein Non-Pseudomonas TISS (pathogenic
(TolC), ABC Transporters, aeruginosa origin potential)
ATP-binding proteins,
haemolysin D, YceK/YidQ
family proteins
RGP101 7,313 51.21 No Yes No Hypothetical proteins Classical strains of Hypothetical proteins
P. aeruginosa
RGP102 11,296 66.10 No No No Hypothetical proteins Non-Pseudomonas Unknown
origin; Burkholderia and
Xylella
RGP103 14,440 65.93 Yes Yes No Formaldehyde activating Pseudomonas Aldehyde
enzyme, aldehyde citronellolis Detoxification;
dehydrogenase; D -gluconate and
aldo/keto reductase, ketogluconate
Gluconate dehydratase. metabolism
RGP104 12,652 58.79 Yes No No Amino acid permease, Origin from classical Acid
arginine/agmatine strains of P. aeruginosa tolerance/resistance
antiporter,
SAM-dependent
methyltransferase
RGP105 4,251 60.50 No No No rhiA, rhiB genes, Origin from soil Rhizosphere expressed
transcriptional regulators inhabiting bacteria like genes
Rhizobium

genetic elements across the genus. RGP105 had genes coding for transporters, DNA replication-stabilization, and hypothetical
rhizosphere expressed (rhi) gene operon which has been linked proteins with unknown function in the P. aeruginosa outlier
with plant-microbe interactions in Rhizobium leguminosarum genomes were under positive selection (Table 3). A carbohydrate
(Giordano, 2015), thus supporting the environmental origin in binding protein with metzincin protease and transglutaminase
CR1 strain. Rhizosphere expressed genes were absent in all the cysteine protease may have a role in biofilm formation and
clinical genomes. dispersal (Passmore et al., 2015; Rybtke et al., 2015). Epoxide
hydrolase that has been shown to decrease mucociliary transport
Genome-Scale Positive Selection and restrict bacterial clearance from the lung (Hvorecny et al.,
Detection 2018) was observed as undergoing positive Darwinian selection.
A total of 5457 orthologous groups were analyzed for gene In addition to these, Metallo-β-lactamase that can degrade
undergoing positive selection, after filtering 128 genes that β-lactam antibiotics (Palzkill, 2013) and peptidase M48 with
were identified to exhibit significant evidence for homologous dual nature of chaperone and metalloprotease that are believed
recombination (FDR < 10%). Among these, 20 genes were to mediate tissue penetration and infection (Maredia et al.,
found to be subjected to strong selection pressure (Table 3) with 2012) were also positively selected. Further, oprD porin was
ω > 1 (ω equal to the ratio of dN to dS for amino acid sites also found to be under positive selection, and it has been
under positive selection). Genes coding for proteases, bacterial shown to carry mutations in classical strains of P. aeruginosa
TABLE 3 | The list of genes under positive natural selection [ω represents the value of dN/dS, p-value: probability value; q-value: false discovery rate (FDR < 10%)].
Gene Function Cluster name ω p-value q-value
Proteases and hydrolases

Carbohydrate-binding protein with metzincin Protease secreted by biofilm of ORTHOMCL2836 29.07471 0 0.000844
domain (B7D75_11240) P. aeruginosa
Epoxide hydrolase (B7D75_07235) Virulence factor; hydrolysis of ORTHOMCL5445 30.65061 0 0.000576
CFTR in lungs
Transglutaminase cysteine protease Role in biofilm formation and ORTHOMCL2866 23.91616 0.000006 0.004772
(B7D75_11075) dispersal
Metallo β-lactamase fold metallo-hydrolase Degrade beta-lactam ORTHOMCL4367 21.31702 0.000023 0.010209
(B7D75_21135) antibiotics
Outer membrane porin, OprD family Mutation in oprD mechanism ORTHOMCL2807 18.80725 0.000082 0.028645
(B7D75_11385) for carbapenem resistance
Peptidase M48 (B7D75_26190) Chaperone and ORTHOMCL1727 17.31162 0.000174 0.045382
metalloprotease
Bacterial transporters
LysE family translocator (B7D75_10555) Lysine exporter ORTHOMCL2297 21.92155 0.000017 0.00845
Hydrogen peroxide inducible genes activator Expression of hydrogen ORTHOMCL481 25.94273 0.000002 0.002425
(LysR family) (B7D75_26850) peroxide-inducible genes
High affinity sulfate family inorganic anion Sulfate transporter ORTHOMCL1053 22.29005 0.000014 0.00845
transporter (B7D75_00150)
Branched-chain amino acid transport system II Transport system for ORTHOMCL3746 17.34394 0.000171 0.045382
carrier protein (B7D75_16930) branched-chain amino acids
(BCAAs; Ile, Leu, and Val)
Amino acid permease (B7D75_21325) Amino acid transporters ORTHOMCL4632 17.92312 0.000128 0.039327
Type IV pilus secretin PilQ (B7D75_26155) Involved in type IV pilus ORTHOMCL1798 20.61727 0.000033 0.013371
formation, competence for
transformation, type III
secretion, and type II secretion
ProQ activator of osmoprotectant transporter Transport betaine and other ORTHOMCL2663 18.45609 0.000098 0.032009
ProP (B7D75_12075) osmoprotectants
DNA stabilization and replication
Nuclease SbcCD subunit C (B7D75_21985) Double stranded exo- and ORTHOMCL4686 24.01605 0.000006 0.004772
endonuclease
ATP-dependent DNA helicase (B7D75_08610) DNA replication ORTHOMCL2136 21.94135 0.000017 0.00845
Error-prone DNA polymerase (B7D75_21945) DNA replication ORTHOMCL4522 17.55637 0.000154 0.044617
Hypothetical protein
hmga2e, putative (B7D75_11510) Unknown ORTHOMCL2780 21.86925 0.000018 0.00845
Hypothetical protein (B7D75_05465) Unknown ORTHOMCL1549 38.14207 0 0.000027
Hypothetical protein (B7D75_14605) Unknown ORTHOMCL3251 27.56469 0.000001 0.001347
Terminase (B7D75_05835) Viral terminase ORTHOMCL6048 20.30993 0.000039 0.014478

and has been regarded as a mosaic gene (Lynch et al., outliers, the accessory genes encoding proteins involved in
1987; Pirnay et al., 2002) that plays a role in antibiotic replication, recombination and repair, cell cycle control, cell
resistance against carbapenems due to its reduced uptake (Li division, chromosome partitioning and intracellular trafficking
et al., 2012). Various transporters like lysine exporter, sulfate (p-value < 0.001 and FDR < 0.03) were more in number
transporter, amino acid permease, and transporter for branched- as compared to the core genes (Figure 4A). Replication,
chain amino acids were also positively selected (Table 3). recombination and repair, and cell motility categories had more
They provide a continuous supply of amino acids to the genes in accessory and core categories, respectively, in both
cell and prevent starvation (Tralau et al., 2007). Although the outlier and classical groups. This can be attributed to the
these transporters are important for maintaining adequate fact that these outlier and classical strains are from diverse
nutrient levels, the branched-chain amino acids (BCAA) are niches and therefore possessed a large number of accessory
an important link between the metabolic state of the cell and genes for maintaining replication and cell division in various
virulence in Staphylococcus aureus by acting as co-repressors environments, at the same time, maintained a core set of
of global transcriptional regulators (Kaiser et al., 2015). These genes required for motility. We also found three genes of
proteases and transporters have a dual role in survival and the replication gene category to be under positive selection
pathogenicity of these outliers and can play a key role in which can be a major cause of generation of advantageous
shaping the pathogenic potential of these strains in the course of variants for the population and make these organisms ubiquitous.
evolution. However, the COG categories responsible for functions like
amino acid metabolism, translation, ribosomal structure and
Core-Pan-Genome Dynamics and biogenesis, energy production and conversion (p-value < 0.001
Functional Analysis FDR < 0.03), post-translational modification, protein turnover,
To examine the core-pan dynamics, we made three groups: signal transduction mechanisms, nucleotide transport and
outliers (n = 14), classical strains (n = 64), and all strains (n = 78). metabolism, and cell wall biogenesis were significantly (p-
The groups were analyzed for their core genome content using value < 0.05 FDR < 0.05) more enriched in the core genes of the
OrthoMCL with 75% query coverage and sequence similarity and outliers while a higher number of accessory genes were found in
pangenome at default parameters in get_homologues and plotted almost all the COG categories of the classical strains (Figure 4B).
with Tettelin fit (Figure 3) (Tettelin et al., 2005). The analysis The high abundance of gene categories in the core of the outlier
revealed a core genome size of 4,708 genes and 10,429 non- genome (n = 14) reflected that they are metabolically similar
redundant pangenes within 14 outlier genomes. This was further amongst themselves but distinct from the classical strains.
followed by the analysis for core and pan-genome of classical Although 6276 more pangenes were present in classical
strains (n = 64). The core and pan-genome size in case of 64 strains, comparison of the pangenes in 64 classical and 14 outlier
classical strains were 3199 and 16705 genes, respectively, and strains revealed 136 genes that were exclusively present in the
as soon as 14 outliers were added, the core genome shrank to outliers. Most of these genes were hypothetical. COG annotation
2885 genes while the pangenome increased to 19736 genes, clearly revealed 78 genes which belonged mainly to transcription,
signifying the expansion of pangenome. The frequency of core energy production and conversion, amino acid transport and
and accessory genes between outliers and classical strains were metabolism and secondary metabolites biosynthesis, transport
compared using the Chi-square test of independence, and were and catabolism. These in our opinion contributed to the
found to be significant [χ2 (1) = 51.63, p < 0.001]. Further, the outlier specific genes and hence their presence could be an
outlier genomes were more similar than the classical strains as important parameter to characterize the outliers’ clade. All
reflected by the high prevalence of core genes in them (44.60%) the outliers had the D-Araf biosynthetic pathway, but it
vis-a-vis classical strains (19.15%). The core genome size in was also present in Exl-A positive strain CF_PA39 (Huber
outliers was estimated using Tettelin fit under the assumption of et al., 2016). From the 136 genes we found the complete
64 genomes (g = 64) for outlier group. This suggested that the cluster for enzymes involved in L-Ectoine degradation viz.
core genome in case of hypothetical 64 outlier genomes (using the doeA (B7D75_20030; ectoine hydrolase; EC 3.5.4.44), doeB
equation in Figure 3B) would be ∼4700 genes. This supports the (B7D75_20035; N2-acetyl-L-2,4-diaminobutanoate deacetylase;
observation that all the 14 genomes are highly identical to each EC 3.5.1.125), and doeC (B7D75_09470; aspartate-semialdehyde
other and the majority of the genes are conserved as core genes dehydrogenase; EC 1.2.1.M5). Many environmental isolates use
and adding more genomes will not decrease the core genome ectoine as a growth substrate (Schwibbert et al., 2011) that also
size drastically. On the contrary, there was a decline (9.82%) serves as key osmoprotectant (Yu et al., 2017). In addition to
in the core genes and increase (15.35%) in the pangenes of the this, we found a region specific to all the outliers with genes
classical strains when all the genomes (n = 78) were subjected to L-Proline/Glycine betaine transporter (ProP) (B7D75_13890),
analysis supporting the fact that these two groups are significantly nitrilase (B7D75_13895), cytochrome c (B7D75_13900) and
different. cytochrome d1 nitrite reductase (B7D75_13905) that help
The core and accessory genes in both the groups were bacteria to cope with osmotic stress in environment (Chen
annotated for COG (Clusters of Orthologous Groups of proteins) and Beattie, 2008), catalyzes the hydrolysis of nitriles to
functional categories. The distribution of COG functional carboxylic acid and ammonia without formation of free amides,
categories was remarkably different between core genes and and have roles in hormone synthesis, nutrient assimilation
accessory genes. In comparison to the core genome in 14 and detoxification of exogenous and endogenous nitriles

FIGURE 3 | Estimation of core and pan-genome of P. aeruginosa strains with Tettelin fit (blue: pangenome; red: core-genome). (A,B) Represents the estimate of the
pan and core genome of 14 outlier strains; (C,D) represents the estimate of core and pan-genome of 64 P. aeruginosa strains included in the current study and (E,F)
represents estimate of the core and pan-genome curves for 78 genomes. The x-axis represents the number of genomes (g) while the y-axis represents the core
genome and pan-genome size (number of genes). The equation for estimating pan and core-genome size according to Tettelin fit are given with the respected
graphs.

FIGURE 4 | Comparative functional analysis based on COG categories between core and accessory genes in (A) outlier strains (n = 14) and (B) classical strains
(n = 64). COG-based binning of core genes and accessory genes. The abscissa denotes different COG functional categories. The ordinate denotes the number of
genes in each COG category. Four COG functional categories (RNA processing and modification, Chromatin structure and dynamics, Extracellular structures, and
Cytoskeleton) including only one or without homologs in the COG collection are not displayed. Significant enrichment of gene occurrence in the individual category is
marked by asterisks (∗ p < 0.05, ∗∗ p < 0.001; FDR < 10% Chi-square test).

(Howden and Preston, 2009; Raczynska et al., 2011). All these an outlier strain from the classical strains. Our analysis to
characteristics were specific to outliers and were absent in the identify outlier specific genes from the core-genes which
classical strains of P. aeruginosa. In addition to being the group- were present in all the 14 outliers and absent from 64
specific genes for the outliers, the presence of these genes also classical strains also confirmed that all the 14 outliers had
pointed out that the outliers as a group are very distinct in their the fused phzA1 and phzB1 (B7D75_03695). Strain CR1
functional attributes and possess many genes which confer an and PA7 were found to harbor complete operons phzB1-
advantage in surviving under environmental stress. phzG1 (B7D75_03695-03670); phzA2-phzG2 (B7D75_15445-
For deciphering the functional disparities in outliers, the 15415), phzM (B7D75_03705), and phzS gene (B7D75_03660)
genomes (n = 14) were annotated using KEGG orthology but lacked phzH. The fused gene does not alter phenazine
and subjected to pathway reconstruction by MinPath. The production, and strain CR1 produced the characteristic blue
functional analysis revealed the differential abundance color pigment in the culture broth which is indicative of
of genes encoding Type IV secretion system, nucleotide the production of pyocyanin. Further, all the outliers barring
sugars metabolism, ABC transporters and pathways linked EML528 had the complete operon pvsA-pvsE (B7D75_14020-
to energy production and metabolism based on the minimal B7D75_14040) and vibrioferrin receptor pvuA (B7D75_14015)
set of pathways (Figure 5A). This observational difference that are required for the production of vibrioferrin, a siderophore;
suggests different metabolic preferences of P. aeruginosa outlier which was also reported in agriculturally important Azotobacter
strains. Further, T3SS was completely missing- suggesting vinelandii and was previously reported only in marine bacteria
the genotypic validation for outliers as they were reported (Baars et al., 2016). This may in part explain why the CR1
not to harbor T3SS (Roy et al., 2010). Interestingly, the strain has been known to have the ability to promote the
analysis based on minimal pathways clearly indicated growth of plants (data not presented here). The entire cluster
that CR1 was in the clade of PA7; thus suggesting that of vibrioferrin was absent in classical strains like PAO1 and
common complete metabolic pathways exist in both the UCBPP-PA14. Recently vibrioferrin has been reported in P. fragi
strains. However, the clustering in case of COG categories (Stanborough et al., 2017) but so far vibrioferrin production
generated a topology similar to the phylogenetic analysis has not been reported in P. aeruginosa. This indicates that all
where the two genomes were present in different sub-clades the outliers possess extra siderophore producing genes that are
(Figure 5B). absent in classical strains. This suggests the acquisition of this
gene cluster by horizontal gene transfer from other strains of
Virulence Genotype Pseudomonas spp. and other bacteria in soil. The genes for
All the outlier strains (n = 14) were found to be highly pyoverdine were also present in all strains. PA7 is known to
identical (98.5–99.5%). CR1 strain possessed all the genes produce type II pyoverdine and has the characteristic 966-bp
required for flagella formation, type IV pili biosynthesis, coding region that contained an esterase/lipase protein domain
type IV pili twitching motility, alginate biosynthesis and (PSPA7_2860) in strain CR1 (B7D75_13235) (Smith et al., 2005).
regulation but lacked a toxA gene similar to PA7. It also However, the ferripyoverdine receptor (fpvA) was of the type
harbored the exlA (B7D75_20920) and exlB (B7D75_20915) IIb in all strains. Interestingly strain CR1 lacked both hemolytic
required for the formation of exolysin A. Apart from the phospholipase C (plcH) and phospholipase D (pldA). Rest all
similarity in the genetic repertoire of most of the flagellar factors for quorum sensing systems, regulation by GacS/GacA
assembly genes, strain CR1 possessed flaB gene (B7D75_19585) two-component systems and hydrogen cyanide production
instead of flaC gene (PSPA7_4279). These two genes have showed complete synteny to all the complete genomes of
higher similarity at their N-terminus and comparatively lesser P. aeruginosa.
similarity at the C-terminus with an overall query coverage The probability of being a pathogen depicting the pathogenic
and percentage similarity of 85 and 63%, respectively. Three potential of the outliers was in the range of 62–68% among
more outlier strains viz., EML545, WH-SGI-V-07055, and the 14 strains, lowest being for ATCC9027 and EML548 and
WH-SGI-V-07618 had the same genotype and rest of the highest for PA7, WH-SGI-V-07072, and WH-SGI-V-07370. The
outliers had flaC gene as in strain PA7 indicating this locus to pathogenicity potential of strain CR1 (66.0%) was significantly
be distinct in comparison to other genes required for flagella higher [χ2 (1) = 10.24, p < 0.005]. The number of pathogenic
biosynthesis. Recently flaC locus from Campylobacterales was families annotated in the genome was highest in strain PA7 with
reported to have a high intrinsic property to activate the innate input proteome coverage 15.72% and 757 pathogenic families
immune response (Faber et al., 2016). Genes coding for LPS-O and lowest in case of strain ATCC9027 (Table 4). The principal
antigen in CR1 lacks three genes UDP-N-acetylglucosamine 2- component analysis that is used to visualize genetic distance and
epimerase (EC 5.1.3.14; PSPA7_1971), UDP-glucose 4-epimerase relatedness were performed using four parameters (probability of
(EC 5.1.3.2; PSPA7_1984), and Undecaprenyl-phosphate being a pathogen, input proteome coverage, matched pathogenic
N-acetylglucosaminyl 1-phosphate transferase (EC 2.7.8-; family and matched non-pathogenic families) among the 14
PSPA7_1985) that can lead to strain-specific lipopolysaccharide genomes. The PCA bi-plot (Figure 6) clearly showed that
in the cell wall of CR1 strain. strain PA7, WH-SGI-V-07370, WH-SGI-V-07064, and WH-
Phenazines are key virulence factors that are characteristic SGI-V-07072 formed a distinct compact cluster, separate from
of P. aeruginosa. Outliers (n = 14) had fused phzA1 with other strains indicating them to be more pathogenic than
phzB1 and this can be used as a marker gene to distinguish other outlier strains. Interestingly even among the outliers,

FIGURE 5 | Functional analysis of Pseudomonas outlier strains. (A) The amino acid sequences of all the 14 genomes were assigned KO number by KAAS server.
The protein families were then mapped for a minimal set of pathways using a parsimony approach. The heat map was constructed based on most abundant top 50
subsystems using Pearson correlation. (B) The ORF’s were mapped against the COG database using rpsblast. For both the heatmaps rows are centered; unit
variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage.

TABLE 4 | Pathogenic potential of the 14 outlier strains.
Strain Probability Input proteome coverage Matched pathogenic Matched not pathogenic
(%) families families
ATCC9027 0.617 5.61 238 92

EML548 0.615 5.68 239 93
CR1 0.660 5.51 244 69
AZPAE14901 0.638 5.15 248 82
EML545 0.656 5.42 249 71
AZPAE15042 0.639 5.45 252 83
EML528 0.640 8.75 383 125
AZPAE14941 0.653 7.84 387 115
WH-SGI-V-07618 0.663 7.92 395 107
WH-SGI-V-07055 0.661 8.04 395 109
WH-SGI-V-07072 0.675 15.35 719 179
WH-SGI-V-07064 0.674 15.51 721 180
WH-SGI-V-07370 0.676 14.92 730 180
PA7 0.672 15.72 757 191
Principal component analysis was performed on the four factors viz. The probability of being a pathogen, number of pathogenic families, input proteome coverage for
pathogenic family and matched non-pathogenic families.
FIGURE 6 | PCA analysis on pathogenic potential of P. aeruginosa outlier strains. The PCA- analysis was performed on the four parameters namely number of
pathogenic and non-pathogenic families annotated, probability of being a pathogen and input proteome percentage among the 14 strains. PA7 along with
WH-SGI-V-07370, WH-SGI-V-07064, and WH-SGI-V-07072 clustered in a different quadrant from the other strains showing high pathogenicity.
CR1 clustered in the group of less virulent strains represented Insights into the pathogenic protein families clearly indicated
by strain ATCC9027 possibly due to its non-clinical origin that these strains were less pathogenic when compared to the
and less pathogenic proteins. Although pathogenicity is context strains of classical clade having a higher probability of being a
dependent and strains of PA7 clade have been shown to be pathogen in the range of 70.8–76.4% (Supplementary Table S5)
avirulent in mammalian infection models but were pathogenic but have a significant number of pathogenic families in their
in invertebrate and plant infection models (Hilker et al., 2015). genomes.

FIGURE 7 | Protein–Protein Interaction network of (A) Core genes of outlier strains (n = 14) and (B) Core genes of classical strains (n = 64). The circles represent
protein hubs and line represent edges. The radius of major regulatory hubs decreases as the number of interactions decreases. The topological properties of these
networks depicting the correlation coefficient values (r 2 ). (C) Node degree distribution, (D) average clustering coefficient, (E) average neighborhood connectivity. All
these properties follow the power distribution and show the nature of the scale-free network and hierarchical organization.
Antibiotic Resistance of Outlier Strains phenicol resistance, and sulphonamide resistance. Interestingly,
Resfinder-v2.1 predicted the presence of acquired resistance all the strains (n = 14) including strain CR1 possessed complete
genes for β-lactam resistance, aminoglycoside resistance, genetic repertoire (blaOXA-50 (B7D75_28665), blaPAO

(B7D75_04145) genes with all the associated regulators and multi-drug resistant strain PA7 had these mutations. Strain CR1
activators) required for β-lactam resistance providing evidence along with the remaining 10 strains showed susceptible genotype
for pan -β-lactam resistance development in P. aeruginosa for Fluoroquinolones.
(Moya et al., 2012). Further, all outliers (n = 14) harbored All the genomes had intact mexABOprM (B7D75_02135-
aph(3’)-IIb (B7D75_04095) that confers resistance to several 02140-02145), mexCDOprJ (B7D75_23705-23700-23695),
important aminoglycoside antibiotics, including kanamycin A mexEFOprN (B7D75_12715-12710-12705) and its regulator
and B, neomycin B and C, butirosin and seldomycin F5 (Zeng mexT (B7D75_12720). CR1 had the mexXYOprA with oprA
and Jin, 2003). The genes reported imparting chloramphenicol (B7D75_14890) gene linked to mexXY (B7D75_14880-14885)
resistance were searched in the genome of CR1 strain. CR1 had as in the genome of PA7. The multidrug efflux system was
catA gene (B7D75_19145) but had frameshift in the catB7 gene ubiquitously present in all the genomes. The analysis revealed
(B7D75_21755), and cmx was exclusive to PA7 as a gene in that majority of outlier strains including CR1 possessed a
RGP75 (Roy et al., 2010). catB7 is an effector of chloramphenicol reduced number of acquired resistant genes and is susceptible to
resistance (White et al., 1999). Only WH-SGI-V-07072 and a certain antibiotic(s), however, strains PA7, WH-SGI-V-07072,
WH-SGI-V-07370 along with PA7 showed the presence of strA, and WH-SGI-V-07370 were most pathogenic and resistant to
strB, sul1 genes for aminoglycoside and sulphonamide resistance. majority of the antibiotics.
Further, aadB (200 -aminoglycoside nucleotidyltransferase) was
identified only in the genomes of WH-SGI-V-07072 and WH- Protein–Protein Interactions
SGI-V-07370 and was not present in any other genome including The core amino acid sequences of the classical (n = 3199)
the complete genomes of CR1 and PA7. and outlier (n = 4708) genomes were used for constructing
PA7 has been exclusively known to possess amikacin resistance complex PPI network using STRING Database v10.5 (Szklarczyk
due to the presence of AAC4 gene and its product is an AAC et al., 2017). The outlier strains showed five major hubs namely
(60 )-II constituted in the RGP75, but our analysis revealed that gltB (glutamate synthase), PA1400 (pyruvate carboxylase), polA
the gene is not exclusive to PA7 and these are also present (DNA polymerase I), gacS (histidine kinase) and guaA (GMP
in strain WH-SGI-V-07055. The genes exclusive to PA7 were synthase) whereas the classical strains had gltB, dnaK (chaperone
aph(6)-Ic aph(30 )-IIa in addition to cmx gene. Interestingly, protein), guaB (inosine 50 -monophosphate dehydrogenase),
strains CR1, ATCC9027, AZPAE14901, AZPAE15042, EML545, hemE (uroporphyrin decarboxylase) and rpoA (DNA-directed
and EML548 lack the arnBCAD operon (present in PA7, PAO1 RNA polymerase) as the major regulatory hubs. gltB emerged
and UCBPP-PA14 and remaining outliers) required for resistance to be the major regulator having the highest degree (d) in
to polymyxin B and cationic antimicrobial peptides. outliers (d = 239) as well as the classical strains (d = 127);
Point mutations in gyrA (Thr83Ile) and parC (Ser87Leu) whereas, rest of the regulatory hubs were unique for both
known to be associated with Fluoroquinolone (FQ) resistance the groups (Figure 7 and Table 5). The difference in the
were checked by aligning both these genes among the 14 strains. degree of association in both the groups can be attributed
Strains WH-SGI-V-07064, WH-SGI-V-07072 and the known to higher overall nucleotide relatedness among outlier strains
TABLE 5 | Major regulatory hubs from the core genome of an outlier and classical strains.
Regulatory Degree Protein Function

hub
Outliers
gltB 239 Glutamate synthase Provides glutamate for the glutamine synthetase reaction, absent in animals
PA1400 221 Pyruvate carboxylase Irreversible carboxylation of pyruvate to form oxaloacetate (OAA)
polA 171 DNA polymerase I Prokaryotic DNA replication
gacS 159 Histidine kinase Play a role in signal transduction across the cellular membrane.
guaA 146 GMP synthase Converts xanthosine monophosphate to guanosine monophosphate in the de novo
synthesis of purine nucleotides,
Classical
gltB 127 Glutamate synthase Provides glutamate for the glutamine synthetase reaction, absent in animals
dnaK 67 Chaperone protein DnaK is also involved in chromosomal DNA replication, possibly through an analogous
interaction with the DnaA
guaB 57 Inosine 50 -monophosphate dehydrogenase Purine biosynthetic enzyme; catalyzes the nicotinamide adenine dinucleotide
(NAD+)-dependent oxidation of inosine monophosphate (IMP) to xanthosine
monophosphate (XMP)
hemE 57 Uroporphyrin decarboxylase Catalyzes the decarboxylation of four acetate groups of uroporphyrinogen-III to yield
coproporphyrinogen-III
rpoA 55 DNA-directed RNA polymerase Essential for life; significant role in transcription
Hubs with their degree of association, the protein encoded and the function performed by these proteins. gltB was the major regulator in both the groups and four group
specific regulatory hubs.

than between the members of the outlier and classical clades. outliers can be distinguished into 2 sub-clades one represented
Outliers had more genes in the core genome and therefore by CR1 having increased antibiotic susceptibility and other
gltB had a higher degree of association in outlier PPI network. by strain PA7 having multidrug-resistant phenotypes. The
The gene gltB that codes for glutamate synthase [NADPH] genomes of the outliers were significantly more conserved
large chain (EC 1.4.1.13), engaged in L-glutamate biosynthesis than that of the classical clinical strains due to the high
via GLT pathway (Pahel et al., 1978), which is itself part prevalence of core genes thus strengthening the fact that
of amino acid biosynthesis has a role in the formation of the two groups are significantly different. Outlier strains had
enzymes involved in nitrogen assimilation (Janssen et al., 1981) genes normally found in soil-dwelling bacteria like ectoine
and enhancing the yield of exotoxin A (Somerville et al., degradation, plant-induced nitrilase in their pangenome that
1999). Further, two studies have shown that the gltB gene in were absent in the classical strains. Although the outliers are
concert with glutamine synthase (glnA) is a potential target considered as the strain of same species, they show major
for drug development (Mowbray et al., 2014; Murima et al., ambiguities in virulence factors, antibiotic resistance pattern,
2014). Interestingly, all the five hubs in case of outliers were and protein regulatory hubs when compared with classical
connected to each other in sequential order according to the strains.
degree of interactions. However, in the classical strains, there
was no interaction between gltB and the second prominent
regulator dnaK which itself interacted with the next three hubs DATA AVAILABILITY
(Figure 7). Therefore, gltB can be regarded as the master of the
proteome network with dnaK also playing an important role The complete genome sequence of chromosome and
as it is the second most prominent regulatory hub (d = 67). plasmid of CR1 were deposited into the GenBank database
Thus, targeting both these genes gltB and dnaK) can have a with Accession number CP020560.1 and CP020561.2.
better impact against their pathogenesis (Chiappori et al., 2015). The genome of CR1 was also submitted to PubMLST
Therefore, in classical strains, a combination of drugs targeting database with organism id 6661 for assigning new sequence
both these regulatory hubs can prove to be more effective against type.
multi-drug resistance. Similarly, the remaining major regulatory
(Figure 7) protein hubs of the outliers can also be targeted as
drug targets. Although these are considered as strains of the
AUTHOR CONTRIBUTIONS
same species, the regulatory hub differs with gltB to be the major US, MS, and RL planned the study. DR provided the strain. US
regulator. and PH did the experimental work for genomic DNA isolation
The network followed a power scaling behavior as the and quantification. US, PH, RK, and AB did the computational
degree exponent γ were 0.60 and 0.75, and the value was less analysis. All authors were involved in the writing and improving
than 2 (Barabasi and Oltvai, 2004) signifying the emergence of the manuscript.
of hierarchical modules and/or communities (Ravasz et al.,
2002). Few highly connected hubs were connected to many
low degree hubs indicating the regulatory power of the hubs FUNDING
over these nodes. Further, the average clustering coefficient and
average neighborhood connectivity were calculated and it also This work was supported by grants from the All India Network
followed power scaling law with β values of 0.36 and 0.78 Project on Soil Biodiversity-Biofertilizers by Indian Council of
and α values of 0.71 and 0.75 in outlier and classical strains, Agricultural Research (ICAR) and Department of Biotechnology
respectively, confirming that the network was hierarchical and (DBT), New Delhi.
the hub proteins in each network are indicative of the key
molecules for habitat adaptation in each genome of the respective
groups. ACKNOWLEDGMENTS
US, PH, RK, and AB gratefully acknowledge the University
CONCLUSION Grants Commission (UGC), Council for Scientific and Industrial
Research (CSIR), DBT and UGC-DS Kothari Scheme for
Represented by very few genomic sequences, clinical strains providing research fellowship.
of P. aeruginosa outlier group have shown to harbor novel
virulence factors. We report here a non-clinical outlier strain
CR1 characterized by a reduced genome size lacking few SUPPLEMENTARY MATERIAL
virulent factors found in clinical strains, the presence of a
The Supplementary Material for this article can be found online
new type I secretion system from the non-Pseudomonas origin
at: https://www.frontiersin.org/articles/10.3389/fmicb.2019.
in RGP100 and a plasmid bearing trimeric autotransporter
00053/full#supplementary-material
linked with VirB/D4 type IV secretion system. CR1 strain
has genes responsible for siderophore production that is FIGURE S1 | 3-D scatterplot of genome size (x-axis), number of coding
important in plants ability to acquire iron. We observed that sequences (y-axis) and DDH values (z-axis) among 14 outlier strains.

FIGURE S2 | Heatmap with dual dendrogram based on the average nucleotide FIGURE S6 | Representation of new RGPs (RGP98-105) of CR1 against the type
identity. The strains were compared using ANIm (mummer based) at default strain PA7. (A) RGP98, (B) RGP99, (C) RGP100, (D) RGP101, (E) RGP102, (F)
parameters. The matrix was then was plotted as a dual dendrogram in R (R RGP103, (G) RGP104, (H) RGP105.
Development Core Team, 2015).
TABLE S1 | Soil properties of the isolation source of CR1 (rhizosphere soil of chili
FIGURE S3 | Phylogeny based on 400 conserved marker genes using the plantation).
maximum likelihood method. Azotobacter vinelandii CA6 was taken as
outgroup. TABLE S2 | Details of all the 78 strains of P. aeruginosa.
FIGURE S4 | Phylogenetic tree of 78 P. aeruginosa genomes based on SNPs TABLE S3 | Annotation of environmental phage exclusive to CR1 as predicted by
within the core genome was defined using Parsnp tool of the Harvest PHAST server.
suite. TABLE S4 | Complete list of regions of genomic plasticity in P. aeruginosa.
FIGURE S5 | Circos representation of the whole genome alignment in strain CR1 TABLE S5 | Pathogenic potential of classical strains predicted by PathogenFinder.
and PA7 with a window size of 10 kb. Colors of arcs depict the orientation of the
blocks (green: positive strand; red: negative strand). FILE S1 | Configuration file used in POTION pipeline.
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ORIGINAL RESEARCH

published: 06 February 2019

Comparative Genomic Analyses

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Gene Function Cluster name ω p-value q-value

Proteases and hydrolases

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TABLE 4 | Pathogenic potential of the 14 outlier strains.

ATCC9027 0.617 5.61 238 92

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Regulatory Degree Protein Function

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