- Research article
- Open Access
Pan-genome dynamics of Pseudomonas gene complements enriched across hexachlorocyclohexane dumpsite
© Sharma et al.; licensee BioMed Central. 2015
- Received: 24 September 2014
- Accepted: 25 March 2015
- Published: 18 April 2015
Phylogenetic heterogeneity across Pseudomonas genus is complemented by its diverse genome architecture enriched by accessory genetic elements (plasmids, transposons, and integrons) conferring resistance across this genus. Here, we sequenced a stress tolerant genotype i.e. Pseudomonas sp. strain RL isolated from a hexachlorocyclohexane (HCH) contaminated pond (45 mg of total HCH g−1 sediment) and further compared its gene repertoire with 17 reference ecotypes belonging to P. stutzeri, P. mendocina, P. aeruginosa, P. psychrotolerans and P. denitrificans, representing metabolically diverse ecosystems (i.e. marine, clinical, and soil/sludge). Metagenomic data from HCH contaminated pond sediment and similar HCH contaminated sites were further used to analyze the pan-genome dynamics of Pseudomonas genotypes enriched across increasing HCH gradient.
Although strain RL demonstrated clear species demarcation (ANI ≤ 80.03%) from the rest of its phylogenetic relatives, it was found to be closest to P. stutzeri clade which was further complemented functionally. Comparative functional analysis elucidated strain specific enrichment of metabolic pathways like α-linoleic acid degradation and carbazole degradation in Pseudomonas sp. strain RL and P. stutzeri XLDN-R, respectively. Composition based methods (%codon bias and %G + C difference) further highlighted the significance of horizontal gene transfer (HGT) in evolution of nitrogen metabolism, two-component system (TCS) and methionine metabolism across the Pseudomonas genomes used in this study. An intact mobile class-I integron (3,552 bp) with a captured gene cassette encoding for dihydrofolate reductase (dhfra1) was detected in strain RL, distinctly demarcated from other integron harboring species (i.e. P. aeruginosa, P. stutzeri, and P. putida). Mobility of this integron was confirmed by its association with Tnp21-like transposon (95% identity) suggesting stress specific mobilization across HCH contaminated sites. Metagenomics data from pond sediment and recently surveyed HCH adulterated soils revealed the in situ enrichment of integron associated transposase gene (TnpA6100) across increasing HCH contamination (0.7 to 450 mg HCH g−1 of soil).
Unlocking the potential of comparative genomics supplemented with metagenomics, we have attempted to resolve the environment and strain specific demarcations across 18 Pseudomonas gene complements. Pan-genome analyses of these strains indicate at astoundingly diverse metabolic strategies and provide genetic basis for the cosmopolitan existence of this taxon.
- Comparative genomics
- Horizontal gene transfer
- Selective pressures
Pseudomonas represents ubiquitous taxon defined by Gram negative, rod-shaped -γ Proteobacteria, having an enormous metabolic versatility to inhabit varied stressed environments . Till date, genus Pseudomonas encompasses 218 authentically pronounced species  including various niche-specialist genotypes e.g. P. aeruginosa , P. stutzeri , and P. putida . Pseudomonas genotypes are characterized by extensive genetic heterogeneity acted upon by selective pressures through mobile genetic elements (MGEs) that confer catabolic potential to degrade variety of xenobiotic compounds such as antibiotics, biocides, and heavy metals .
Over the last two decades, comparative genomics has emerged as a powerful tool to demarcate between functionally important genetic elements (i.e. core-genome) and niche specific adaptive genes on genomic islands (i.e. flexible-genome) . However, impedance to the comparative genomics approach is the inability to demonstrate results at community (population) level which can be circumvented using metagenome data to reveal complex community interactions. Genome size variations among pseudomonads (ranging from 3.7 Mbp for P. stutzeri  to 7.1 Mbp for P. aeruginosa ) and their relatively higher in situ abundance across stressed environments  make them a potential candidate for studying micro-evolutionary events that occur at population level.
Microbial biogeography of HCH contaminated environments has been elucidated using both culture-dependent [9-15] and culture-independent [8,16] studies. Recent metagenomic surveys have revealed that higher HCH contamination (450 mg HCH g−1) results in enrichment of sphingomonads and pseudomonads precisely . Competence among sphingomonads to tolerate and/or degrade HCH has been attributed to the acquisition of lin genes and studied in details in the past [17-21]. But the genetic mechanism behind co-existence of pseudomonads under HCH stress is still unknown. Here, we have sequenced a HCH tolerant Pseudomonas strain i.e. Pseudomonas sp. strain RL isolated from HCH contaminated pond sediment. Detailed comparative genomic analysis with its reference ecotypes (n = 17) combined with in situ population level genetic information (metagenomics), was performed to highlight the niche specific gene repertoire of strain RL. We further reported a mobile class-I integron (3,552 bp) in strain RL with a captured gene cassette encoding for dihydrofolate reductase (dhfra1) gene, associated with a Tnp21-like transposon. Integrons though have been attributed to the acquisition of antibiotic resistant genes since 1980’s but till date their occurrence in Pseudomonas spp. has been rare and precisely limited to P. aeruginosa, P. putida, and P. stutzeri . Environmental sequence data from the HCH contaminated pond sediment (45 mg HCH g−1) together with previous metagenomic survey of HCH contaminated dumpsite (450 mg HCH g−1) and adjoining agricultural soils (0.07 mg HCH g−1)  were also used to reveal the metagenomic recruitment of this integron unit. Our results highlighted the in situ genetic predominance of the integron associated TnpA6100 gene (IS6100 related transposase) across increasing HCH contamination. Remarkably higher in situ abundance of this transposase particularly at the HCH contaminated site emphasizes at the transposon driven HGT among in situ cohorts, hence contributing towards the overall fitness of the inhabiting Pseudomonas community .
Site selection and physiochemical analysis
Field experiment was performed in September of 2011 at HCH contaminated pond located in the vicinity of lindane production unit (28°54′ N, 81° 09′ E) at Chinhat, Lucknow, India. Four random sediment samples, 50 g each were collected from the selected site, transported on ice (4 °C) and stored at −80°C until further processing. Physicochemical analysis of the samples was performed using X-Ray diffraction (XRD) , followed by estimation of HCH concentration using previously described method . Briefly, 1 g of each sample was extracted in solvent (hexane/acetone; 1:1) by sonication and the extract was dried to subsequently yield HCH residues. The dried extract was then dissolved in 2 ml ethyl acetate. Further, the concentration of HCH isomers was estimated based on calibration against external standards of HCH isomers (α-, β-, γ-, δ- HCH) by Gas Chromatograph (GC-17A, Shimadzu, Japan) equipped with electron capture 63Ni detector and a 30 m REX-50 column (Restek, USA). Gas chromatography data for HCH concentration from another HCH dumpsite survey  was also used for comparative evaluation.
Strain isolation and genome sequencing
Sediment sample (1 g) from HCH contaminated pond was suspended in 5 ml sterile 1× PBS (137 mM NaCl, 1.3 mM KCl, 3.2 mM Na2HPO4, 0.5 mM KH2PO4, pH 7.4), serially diluted and plated on Luria-Bertani (LB) agar plates with Nystatin (100 U/ml) . Yellow pigmented colonies were avoided with an aim to isolate Pseudomonas strains and not the previously well characterized sphingomonads [9-15,27]. A black pigment producing colony, within 9 days of incubation at 28°C, was picked and purified by repeated streaking on LB agar. Purified bacterial colony was cultured in LB broth; bacterial cells were harvested by brief centrifugations followed by isolation of genomic DNA using CTAB method . Identification of isolated Pseudomonas sp. strain RL was confirmed by 16S rRNA gene amplification and sequencing. Total genomic DNA samples were further processed for whole genome sequencing using DNA sample preparation kit (Illumina Inc., San Diego, CA, USA). Paired-end reads were generated using Illumina HiSeq 2000 (n = 6,255,556, 2 kb paired-end library) and 454 GS FLX titanium platforms (n = 1,01,139, 2 kb single-read library) at Beijing Genome Institute, BGI, Shenzhen, Guangdong, China. Whole genome reads were quality filtered using quality measures such as minimum quality score = Q20, minimum read length = 90 bp (Illumina) and 350 bp (Pyrosequencing) without ambiguous bases.
de-novo genome assembly and annotation
Raw sequence reads obtained for strain RL were assembled into contigs using Velvet_1.2.03 assembler  set at parameters: insert length = 2 kb, standard deviation of insert length = 100 bp, expected coverage = 20 and minimum contig length = 500 bp. After finalizing the de-novo assembly, contigs were checked for the misassembled and low coverage regions. Quality filtered contigs were further extended using paired-end criterion based method. Final assembly was checked for the percentage completeness using single copy genes i.e. thirty-one protein encoding phylogenetic marker genes (dnaG, frr, infC, nusA, pgk, pyrG, rplA, rplB, rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, rpoB, rpsB, rpsC, rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB, and tsf)  and 107 genes by Dupont et al., (2012) . The genome revealed presence of all the 31/31 and 103/107 genes suggesting its near complete status for further whole genome based analysis. ORFs were predicted from contigs using FragGeneScan 1.16  followed by KAAS (KEGG Automatic Annotation Server) assignment of KEGG ortholog (KO) identifiers to the query genes by BLASTP against the KEGG GENES database . For comparative genome analysis, sequence data was used for Pseudomonas genotypes (n = 18, including strain RL) from NCBI (ftp://ftp.ncbi.nlm.nih.gov/genomes/Bacteria/). Summary of the genomes used in this study and their selection criterion is provided in a separate section below under the title ‘Summary of reference genomes and metagenomes’. Metabolic pathways were reconstructed and filtered using MinPath (Minimal set of Pathways)  for all the Pseudomonas genomes i.e. Pseudomonas sp. strain RL and its 17 reference genotypes. Protein family reconstruction was estimated against Pfam  and KEGG databases  using HMMER  and BLASTP, respectively. The strains were further investigated for presence of integron by BLASTN against INTEGRALL 1.2 database . This was followed by a local BLASTN search against a manually curated database pertaining to class-I integrons from Pseudomonas genus .
Phylogenetic status of strain RL was determined using 400 conserved bacterial marker genes  and representative whole genome sequences from 40 diverse Pseudomonas species as available in NCBI database (http://www.ncbi.nlm.nih.gov/genome/browse/representative/). In addition to using one representative strain from each of 40 species, 10 supplementary strains (sub-species) from P. aeruginosa (n = 4), P. stutzeri (n = 4), and P. mendocina (n = 2) were also included in the dataset for being assigned as exclusive 10 closest phylogenetic neighbors by RAST whole genome based functional score . A phylogenetic tree was hence constructed using maximum likelihood (ML) methodology on the basis of protein coding bacterial conserved gene (400) sequences  determined for Pseudomonas sp. RL and 50 other Pseudomonas strains with Azotobacter vinelandii being the outgroup. Azotobacter vinelandii CA was used as outgroup considering its adjacency with pseudomonads (being the sister taxon) but definitely an outlier for the in-group as an independent genus [41,42]. For further studying the sub-species demarcation patterns, pairwise average nucleotide identity (ANI)  calculations were performed for explicitly strain RL and its 17 closely related reference genotypes as observed from the clade topology of 400 genes based phylogenetic tree. These 18 Pseudomonas strains were then used for further comprehensive comparative genomic analysis.
Identification of orthologous segments and detection of positively selected proteins
Orthologous segments were determined using Murasaki  and OSfinder v1.4 (Orthologous-Segment Finder)  for all 18 Pseudomonas genomes. Short homologous regions called anchors were determined between the genomes using Murasaki at 28 and 36, weight and length of seed patterns, respectively. Positions of the anchors (as determined by Murasaki) were fed to OSfinder (1000 minimum orthologous segment length cut-off) that discriminated orthologous anchors from non-orthologous anchors using Hidden Markov Model (HMM). To further supplement the above analysis pairwise orthologous gene identification was performed using reciprocal smallest distance (RSD) algorithm  set at E-value and divergence cut-off of 1e-15 and 0.5, respectively. Using whole genome based synteny information (minimum length = 5 kb) a circos  plot was constructed to identify the most syntenous genomes among all (n = 18).
For identification of proteins being selected positively, dN/dS ratio was calculated in pairwise manner for the set of orthologous proteins which were further aligned using CLUSTAL W algorithm . Nucleotide sequences of these alignments were then aligned codon by codon, using the PAL2NAL script . The dN/dS ratio for each pair of proteins was hence calculated using Yn00 module of the PAML package . Protein pairs with > 30% length difference were excluded from further analysis. To focus on the time-independent attribute of natural selection, dN/dS ratios were plotted against dS values .
Identification of HGTs and MGIs (Metagenomic Islands)
Genomic islands (GIs) profile was generated using SIGI-HMM  at sensitivity value of 0.7 to determine transition probabilities at the gene level. For this purpose the %codon bias and % G + C difference was calculated across 2 kb window size for strain RL and its 17 phylogenetic neighbors (Additional file 1: Table S1). GIs were then annotated using BLASTX (E-value = 10−5) against COG  and KEGG database  for putative HGTs. Metagenomic reads were mapped over the 18 Pseudomonas genomes using GASSST (Global Alignment Short Sequence Search Tool)  at 80% sequence similarity cut-off and enabled reverse complement search. Metagenomic mapping included both whole-genome and genome-specific markers (GSMs) binning using k-mer based GSMers . Metagenomic reads were hence tilled against the reference genomes (n = 18) and GSMs with a view to understand mechanism generating variability reflected by the metagenomic islands and their subsequent potential adaptations in the stressed environments. Further, metagenomic islands were predicted explicitly across strain RL genome using method previously reported by Sangwan et al., (2014)  to understand HCH stress specific enrichment as well as vestigiality of genes pertinent to strain RL.
All the statistical computations used in this study were performed in R . For comparative functional analysis, Principal Component Analysis (PCA) was performed on 131 variables (denoting the metabolic pathways) and 18 factors denoting the genomes. This was followed by hierarchical clustering on the first two dimensions of PCA using Euclidean metric and ward as method. Top 50 variables (metabolic pathways) were also plotted at 0.8% relative abundance and 0.6% variance cut-off. Species-specific abundance was analyzed with respect to HCH stress gradient via non-metric multidimensional scaling (NMDS) using the Vegan package  in R. NMDS analysis was also used to determine the inter-species genetic variance with respect to variable genome size, %G + C difference, %codon bias, HGT proteins and MGEs. Fisher’s exact t-test was performed using sequential Bonnferroni corrections  with adjusted P-values < 0.001, for all pairwise trait comparisons of Pseudomonas genomes used in this study.
Summary of reference genomes and metagenomes
Strain RL, a HCH non-degrader, was isolated from HCH contaminated pond and was further used along with its 17 reference genotypes in comparative analysis to understand evolutionary dynamics under varied habitat specific selective pressures. For assigning phylogenomic status to strain RL, whole genome sequences from 40 representative Pseudomonas species were used as available in NCBI database (http://www.ncbi.nlm.nih.gov/genome/browse/representative/). Additionally, 10 strains (sub-species) were also used belonging to P. aeruginosa (n = 4), P. stutzeri (n = 4), and P. mendocina (n = 2) for being 10 closest phylogenetic neighbors to strain RL predicted by RAST whole genome based functional scores. Involvement of multiple strains for these species further enabled us to study intra-species functional demarcations across them. Pseudomonas sp. TKP  and P. aeruginosa MTB1  were also included owing to their similar ecotype status as strain RL i.e. isolated from HCH contaminated soils from Japan. Phylogenomic reconstruction hence was performed using 400 conserved bacterial marker genes  and 50 Pseudomonas strains which revealed 16 Pseudomonas strains as phylogenetic neighbors to strain RL. These strains were used for further detailed comparative genomic analysis along with Pseudomonas sp. TKP which was included for inhabiting similar HCH stress (as strain RL) although an outlier from related reference genotypes as per the phylogenetic tree. Hence, these 17 Pseudomonas genomes were referred to as reference ecotypes/phylogenetic neighbors of strain RL. Sequence data was obtained for the Pseudomonas genomes from NCBI Genome database: Pseudomonas sp. TKP [GenBank:NC_023064.1], P. mendocina ymp [GenBank:NC_009439.1] P. mendocina DLHK [GenBank:NZ_ALKM00000000.1], P. mendocina NK-01 [GenBank:NC_015410.1], P. aeruginosa 9BR [GenBank:NZ_AFXI00000000.1], P. aeruginosa 19BR [GenBank:NZ_AFXJ00000000.1], P. aeruginosa 213BR [GenBank:NZ_AFXK00000000], P. aeruginosa DK2 [GenBank:NC_ 018080.1], P. aeruginosa MTB-1 [GenBank:NC_023019.1], P. stutzeri T13 [GenBank:NZ_ALJB01000000.1], P. stutzeri XLDN-R [GenBank:NZ_AKYE00000000.1], P. stutzeri CCUG 29243 [GenBank:NC_018028.1], P. stutzeri ATCC 14405 [GenBank:NZ_AGSL00000000.1], P. stutzeri A1501 [GenBank:NC_009434.1], P. psychrotolerans L19 [GenBank:NZ_AHBD00000000.1], P. luteola XLDN4-9 [GenBank:NZ_ALAT00000000.1] and P. denitrificans ATCC 13867 [GenBank:NC_020829.1].
HCH contaminated soil metagenomes were also used in this study for the metagenomic recruitment of Pseudomonas strains (n = 18) for understanding the extent of flexible genotype maintained across in situ cohorts under the selective pressure of HCH contamination. We used metagenomic reads [SRP 047092 under NCBI Short Read Archive] from the HCH contaminated pond sediment which is also the source of isolation for strain RL, along with metagenomic reads from a previous HCH metagenomic survey ; HCH dumpsite [MG-RAST ID: 4461840.3], soil that was 1 Km away [MG-RAST ID: 4461013.3] and 5 Km [MG-RAST ID: 4461011.3] away from HCH dumpsite.
Physicochemical analysis of HCH contaminated pond sediment and soil samples
EC (dS m −1 )
Organic Carbon (%)
Available P (kg ha −1 )
Available K (kg ha −1 )
Available N (kg ha −1 )
ΣHCH (mg g −1 )
General features of Pseudomonas genomes
General genome features of Pseudomonas sp. RL and its 17 reference genotypes
Genome size (in bp)
%G + C
Presence of integron associated integrase
No. of annotated proteins
Habitat and accession numbers for genome sequences
Pseudomonas sp. RL
HCH dumpsite, India (JBOY00000000)
P. aeruginosa 19BR
Present (99%, E = 0.0)
MDR strain (clinical) (NZ_AFXJ00000000.1)
P. aeruginosa 213BR
Present (99%, E = 0.0)
MDR strain (clinical) (NZ_AFXK00000000)
P. aeruginosa 9BR
Present (99%, E = 0.0)
MDR strain (clinical) (NZ_AFXI00000000.1)
P. aeruginosa DK2
Cystic fibrosis patient (clinical) (NC_ 018080.1)
P. aeruginosa MTB-1
HCH contaminated soil, Japan (NC_023019.1)
P. stutzeri ATCC 14405
Polluted marine isolate, denitrifying bacterium (NZ_AGSL00000000.1)
P. stutzeri CCUG 29243
Polluted marine isolate, naphthalene degrading (NC_018028.1)
P. stutzeri XLDN-R
Soil, carbazole degrading (NZ_AKYE00000000.1)
P. stutzeri T13
Present (99%, E = 0.0)
P. stutzeri A1501
P. mendocina ymp
Yucca mountain sediment, high level nuclear respository (NC_009439.1)
Pseudomonas mendocina DLHK
Bioreactor, denitrifying bacteria (NZ_ALKM00000000.1)
Pseudomonas mendocina NK-01
Farmland soil, China (NC_015410.1)
Pseudomonas psychrotolerans L19
50 percent copper alloy coin (NZ_AHBD00000000.1)
Pseudomonas luteola XLDN4-9
Pseudomonas denitrificans ATCC 13867
Not found (NC_020829.1)
Pseudomonas sp. TKP
HCH contaminated soil, Japan (NC_023064.1)
We used a set of 400 conserved bacterial marker genes to determine the phylogenetic status of strain RL. A phylogenetic tree was constructed using maximum likelihood methodology revealing prominently three major groups neighboring strain RL, including P. stutzeri, P. aeruginosa, and P. mendocina (Figure 1A). Strain RL fell within the cluster including P. stutzeri group though delineated at species level (ANI ≤ 80.03%). Above strain RL, a larger cluster was observed containing two sub-groups of P. aeruginosa and P. mendocina along with presence of individual representative strains for P. denitrificans (ATCC 13867), P. luteola (XLDN4-9), and P. psychrotolerans (L19) (Figure 1A). Comparing the intra-species phylogenetic topology of two major groups of P. aeruginosa and P. stutzeri, P. aeruginosa genomes were found to form a tight monophyletic clade in contrast to largely divergent P. stutzeri group (Figure 1A). These results were in good agreement with ANI analysis, where pairwise ANI values for P. aeruginosa members (n = 5; 19BR, 213BR, 9BR, DK2, MTB1) were greater than 99% suggesting these strains to be sub-species (Figure 1B) . However, two sub-groups were identified for P. stutzeri clade, first with P. stutzeri CCUG 29243 and ATCC 14405, and second containing P. stutzeri A1501, T13 and XLDN-R (Figure 1A). This distinct deviation could be accredited to the ecotype status resulting from the niche specific adaptations, as P. stutzeri ATCC 14405 and CCUG 29243 both are marine isolates [66,67] however, A1501, T13, and XLDN-R, are well-known soil/sludge dwellers [68,69]. ANI values for P. stutzeri group (≤88.2%) were also not in accordance with species demarcation value of 95-96%  indicating towards intra species level divergence (Figure 1B). P. mendocina ymp along with other P. mendocina strains was placed outside both P. aeruginosa (ANI ≤ 79.98%) and P. stutzeri (ANI ≤ 79.97%) groups (Figure 1B). P. denitrificans ATCC 13867 (ANI ≤ 82.08%), P. luteola XLDN4-9 (ANI ≤ 76.42), and P. psychrotolerans L19 (ANI ≤ 79.01) were revealed to be organized in the same major clade alongside P. aeruginosa and P. mendocina but as separate nodes demonstrating species delineation supported by ANI values as well (Figure 1A, B).
Structure and characterization of integron
The gene cassette inserted between 5′-CS and 3′-CS was found to be encoding dihydrofolate reductase (dhfra1) (447 bp) gene which confers trimethoprim resistance (Figure 3A). A 115 bp long 59-be (base element) was found downstream of dhfrA1 gene containing 2 short stretches of complete conservation designated as L (left) and R (right)  (Figure 3C). Each of these sites was found to be made up of a pair of inversely oriented intI binding domains known as 1 L, 2 L, 1R, and 2R separated by spacers (Figure 3C). We determined a 7 bp long 1 L (GGTTAAC) and 8 bp long 2 L site (GCAGCAAC), separated by a 5 bp spacer. Similarly, a 7 bp long 1R (GTTAAGG) and 2R site (GCTGTGC) were also determined with a 5 bp long spacer. 2 L and 2R sites were found to be separated by a 39 bp sequence consistent with dhfra1 associated 59-be. Alignment of 59-be elements associated with different classes of dhfr gene i.e. dhfrA1, dhfrA5, dhfrA7, dhfrA12, dhfrA14, dhfrB1, dhfrB2, and dhfrB3 revealed that 1 L, 2 L, 2R sites were identical to those associated with dhfrA1 gene but 1R site showed a minor change in this case. 1R site in strain RL was identified to be i.e. GTTAA’GG’ (7 bp) instead of GTTAA’CC’ (Figure 3C). The alignment also revealed that the last 3 residues (‘AAC’) in 1 L site and first 3 residues (‘GTT’) in 1R site are completely conserved (Figure 3C). The intI facilitated recombination is documented to be restricted between the G and TT region in 1R of the 59-be , which was found to be completely intact in RL’s integron unit. Integrons though have been found in different genera but very few have been reported in Pseudomonas spp.  and rarer is the dhfrA1 gene association with class I integron.
Finally, detailed comparison of integron unit of strain RL with its phylogenetic neighbors revealed presence of an intact integron in P. aeruginosa 19BR and 213BR though no association with transposon (Additional file 2: Figure S1) was observed. However, in case of P. stutzeri T13, a mobile integron linked with transposon was determined that has yet to capture gene cassette (Additional file 2: Figure S1).
Environment specific activation of class-I integron revealed through metagenomics
Evidence for the mobility of integrons is their association with transposons, insertion sequences (ISs) or conjugative plasmids . Elaborate study of the reconstructed integron elucidated presence of conserved 5′-CS and 3′-CS sites and a gene captured in between, which indicated at the separation event of these elements. In this study, we confirmed the presence of class-I integron (3,552 bp) in RL on a Tnp21-like transposon (BLASTN; 95%, E-value = 0.0) (Figure 3B). The transposon (Tn) module was found to be present upstream (100 bp) in the beginning of the integron. The module consisted of ORFs encoding for resolvase specific sites i.e. res I (9 bp), res Ii (27 bp), res III (32 bp), and TnpR (615 bp) and TnpA (2,967 bp) and was found to be flanked by IR (invert repeat sequences) on both sides (Figure 3B). This was then followed by a complete integron adjoined by a TnpA6100 element at its 3′ end, indicating its potential to perform active gene transfer events.
Comparative metabolic capabilities
KEGG based metabolic pathway reconstruction was used to compare the functional repertoire of Pseudomonas genomes (n = 18, Table 2). The central metabolic pathways such as glycolysis and pentose phosphate pathway in strain RL were in sync with those reported in its phylogenetic neighbors (n = 17). However, in contrast to all of the Pseudomonas genomes used in this study strain RL revealed unique presence of α-linoleic acid degradation pathway. Although, multiple Pseudomonas species (e.g. fluorescens, putida, alcaligenes) have been reported to degrade the fatty acid derivatives, its implicit presence in RL indicates at its differential capacity to use α-linoleic acid as carbon source . Similarly, when compared to the other genomes (n = 17), P. stutzeri XLDN-R was found to exclusively possess the carbazole degradation pathway which was further supported by the fact that this particular strain was isolated from soil for its differential ability to utilize carbazole as sole source of both carbon and nitrogen . 3-chloroacrylic acid degradation pathway was found uniquely in P. stutzeri CCUG 29243 indicating at its capability of using 3-chloroacrylic acid as carbon source . In addition, toluene & xylene degradation potential was found to be an exclusive metabolic feature of P. stutzeri CCUG 29243 genome, which further highlighted towards its bioremediation potential against toluene contamination .
Pairwise functional comparisons (pathways) performed across P. aeruginosa (n = 5) and P. stutzeri (n = 5) strains revealed the genetic predominance of 2,4-dichlorobenzoate degradation and ether-lipid metabolism in P. aeruginosa strains. Presence of 2,4-dichlorobenzoate degradation pathway supported the existence of an efficient enzyme system for chlorobenzoate degradation already established for P. aeruginosa strains . In contrast to P. stutzeri strains the P. aeruginosa strains were also found to possess the streptomycin degradation pathway highlighting its genetic potential of being a persistent opportunistic pathogen i.e. extra-ordinary capability to inactivate multiple aminoglyocosides including streptomycin . As reported in a previous study, caprolactam degradation  and D-alanine catabolism pathways are the distinct features of P. aeruginosa strains. Interestingly, P. aeruginosa strains can preferentially catabolize D-alanine over other carbon sources to promote the production of extra-cellular virulence factors . This preferential acquisition of multiple functional traits (pathways) in P. aeruginosa strains in contrast to other pseudomonads reveals the persistent evolutionary processes undertaken to evolve as a metropolitan pathogen .
KEGG metabolic pathway based analysis further revealed several lifestyle specific preferences (secretion systems) across pseudomonad genomes (n = 18). As for an example, P. aeruginosa strains (known human pathogens), were revealed to possess the complete genetic repertoire for Type III (T3SS) (13/15 KOs) and Type IV (T4SS) secretion systems (10/12 KOs). Presence of type III and IV secretion systems clearly indicates at the pivotal metabolic role of secretion systems in P. aeruginosa strains (clinical superbugs) in both secretion and injection of virulence factors into the host environments . However, P. stutzeri strains (nonpathogenic; KOs = 0) were completely devoid of genes related to Type III and IV secretion system. Interestingly, several intra-species (niche-specific) metabolic adaptations were also revealed between the P. stutzeri ecotypes i.e. marine and soil/sediment isolates. Marine inhabitants i.e. ATCC 14405, CCUG 29243 in contrast to other stutzeri strains (soil dwellers) were found to lack genes involved in fluorobenzoate degradation  and zeatin biosynthesis pathways, which already have been established as the characteristic features of soil dwelling pseudomonads e.g. zeatin helps in inter-cell communication with plants .
Detailed functional analysis was performed explicitly between HCH tolerant pseudomonads i.e. strain RL, TKP and P. aeruginosa MTB1. Association of lin genes with HCH degradation has already been studied in detail in sphingomonads [17-20,85-89]. In contrast to sphingomonads, both the upper (linA, linB, linC) and lower pathway genes (linDER, linKLMN, linGHIJ, and linF) required for γ-HCH degradation  were absent among these HCH inhabitants (pseudomonads). To rule out the altercations conferred by low sequence coverage and assembly we established the complete absence of lin genes by comparing both contigs (validated by paired end criterion) and ORFs (contigs = BLASTX and ORFs = BLASTP) against the reference lin gene database . In addition, the quality filtered raw sequence reads were mapped using bwa-0.5.9  and BLASTN against the CDS sequences of lin gene database with a minimum coverage cut-off = 100X . Higher in situ abundance and confirmed absence of HCH degradation pathway genes in these Pseudomonas genomes pointed towards the presence of a yet unknown metabolic way to cope up with such high HCH concentrations (45 mg HCH g−1 of soil). Therefore, we further focused our effort to analyze the orthologous segments between these three genomes i.e. RL, TKP, and MTB1. The detailed annotation of 1.3 Mb of orthologous segment from these HCH-tolerating Pseudomonas genotypes revealed (Additional file 3: Table S2) the presence of bacterial chemotaxis, two-component system, flagellar assembly proteins, and Type II secretion system along with the central metabolic pathways like TCA, glycolysis, ubiquinone synthesis, and amino acid biosynthesis. Although, we didn’t observe any novel mechanism of HCH tolerance across orthologous segments, the orthologous delineation of chemosensory two-component system (pilG, pilH, cheB, cheY, fleR, phoB, and gacA) across RL, TKP and MTB1 highlighted towards the importance of this system in genetically adapting against HCH stress (Additional file 3: Table S2).
Identification of orthologues and proteins under positive selection
We used a two-step based approach for the identification of orthologous proteins across all 18 Pseudomonas genomes. First step i.e. whole genome based multiple alignments using Murasaki  and OSfinder v1.4 , revealed protein families including but not limited to; two-component system, DNA replication associated proteins, ribosomal subunit forming proteins, recombinase, bacterioferritins, flagella associated proteins, electron-transferring dehydrogenases, cell division proteins, transcription repair proteins as core features across pseudomonad genomes (Additional file 4: Table S5).
In second step i.e. pairwise protein profile comparison, the RSD analysis  was performed between RL and its phylogenetic neighbors (n = 17). RSD analysis predicted maximum of 851 orthologous proteins for P. stutzeri ATCC 14405 and minimum of 598 proteins for P. mendocina DLHK, with maximum likelihood distance estimate > 2 (Table 2). A common set of pairwise orthologous proteins were further implemented for dN/dS analysis to identify the positively selected functions. In order to study the inter-species evolutionary dynamics, orthologs were also identified between P. stutzeri and P. aeruginosa genomes. Both the groups (10 strains (5 each of aeruginosa and stutzeri)) shared a total of 681 orthologs (442 unique KO entries) which included functional pathways like pilus assembly, septum site determination, DNA replication, ribosomal assembly, multiple sugar transport, recombination, flagellar assembly, transcriptional regulation, membrane proteins and chemotaxis (Additional file 5: Table S6).
In addition, a genome-wide synteny analysis (window size cut-off = 5 kb) was also performed for 18 genomes, which highlighted (Figure 5B) the higher levels of genome wide synteny between P. aeruginosa genomes (19BR, 213BR, 9BR, DK2, MTB1) i.e. larger (>5 kb) conserved blocks, in contrast to P. stutzeri genomes. However, strain RL and rest of the genomes showed very rare synteny events especially P. psychrotolerans L19 exhibiting virtually no syntenous regions at 5 kb window size, which was hence removed from the plot (Figure 5B).
Interestingly, majority of these positively selected protein pairs (dN/dS > 1) have already been known to play important metabolic functions across pseudomonads genotypes. For instance, Pseudomonas strains are well known to utilize nitrate for both growth and to generate proton motive force (for mobility) using nitrate reductase which is initiated by uptake of nitrate via ABC transporters . Similarly, flagellar biosynthesis and chemotaxis response regulator proteins work together as a unit aiding pseudomonads in both colonization and virulence . Citrate transporter was found to be uniquely favored in P. stutzeri T13, which is established to help Pseudomonas strains (e.g. P. aeruginosa) in iron uptake via its iron-chelating activity as a siderophore . Ton-B transporters were also revealed to be under positive selection in strain T13 which again helps in iron uptake, indicating at the persistent evolution of iron uptake system . Integrase (recombinase) was also found to be under positive selection in strain TKP (HCH tolerant) which once again supports the role of integrase in enhancing genome plasticity under stressed conditions such as HCH contamination . This also stands true for the positive selection of SOS regulon in P. mendocina ymp which was isolated from a nuclear waste repository characterized by enormous heavy metal stress . Similarly, MinC was also found to be under positive selection which along with ATPase MinD is implied to be involved in regulating the cell growth of Pseudomonas putida under phenol induced stress . Magnesium transporter was discovered to be under positive selection in strain MTB1, which is known to inhibit the T3SS, hence attenuating the virulence capability and also in transporting magnesium . Overall, our pairwise dN/dS results indicate at the continuous genetic evolution in order to improve the genetic fitness of this taxon across stressed environments.
Genome wide identification and annotation of HGT events
Potential HGT candidate genes were identified across 18 Pseudomonas genomes using %codon bias and %G + C difference analysis, implemented in SIGI-HMM program . A maximum of 603 and minimum of 103 HGT proteins were predicted for P. aeruginosa 9BR and P. denitrificans ATCC 13867, respectively. The potential HGT candidates were then assigned KO numbers using KAAS, majority (>65%) of which were annotated to be the uncharacterized proteins without any assigned KO entries. Pathways were further mapped to individual proteins (with assigned KOs) using MinPath  (Additional file 3: Table S3). We found that RL and P. stutzeri A1501 revealed presence of an uncharacterized protein yhgF (K06959) potentially imported in their genomes through lateral gene transfer. P. mendocina ymp and P. stutzeri CCUG 29243 revealed methionine metabolism and one carbon pool by folate pathway to have been acquired via HGT (Additional file 3: Table S3). P. stutzeri ATCC 14405, P. stutzeri XLDN-R, and P. stutzeri T13 exhibited lateral acquisition of genes involved in nitrogen metabolism and TCS pathway (Additional file 3: Table S3). Interestingly, erratic incidence of nitrogen fixing genes in Pseudomonas spp. has always raised debate in the past and HGT has been postulated as one of the main reasons behind their acquisition  (Additional file 3: Table S3). Our results suggested that the evolution of the TCS via HGT helps microbial community to respond to niche-specific signals and ecogenetically adapt against stress .
Metagenomic demarcations across pseudomonad gene complements
Global alignment based mapping of 5 metagenomic datasets  against Pseudomonas genomes (n = 18) revealed (Additional file 1: Table S1) maximum mapping for strain RL i.e. HCH dumpsite = 6,473, 1 Km = 3,855 and 5 Km = 2,161. However, for HCH contaminated pond soil metagenome, strain TKP showed maximum reads mapping (n = 3,44,108) followed by strain RL (n = 2,92,290). P. aeruginosa 213BR, 19BR along with rest of the Pseudomonas genomes used in this study showed negligible metagenomic mapping (Additional file 1: Table S1). On the other hand, metagenomic mapping of GSMs  against 18 reference genomes revealed maximum mapping for strain RL i.e. 1,425 reads from HCH contaminated pond metagenome dataset, which is absolutely pertinent because pond is the site of isolation of the strain RL. Our results validated GSM mapping to be more specific (species/strain) as compared to whole genome based metagenome mapping. Detailed results for metagenomic binning of reads for individual genome are provided in (Additional file 1: Table S1). NMDS ordination plots were used to determine the effect of HCH stress on the in situ abundance of these Pseudomonas cohorts (Figure 2) revealing strain TKP and RL to be the most enriched at the HCH dumpsite with maximum HCH contamination (450 mg HCH g−1) emphasizing the role of HCH stress in shaping up the genotypic heterogeneity.
Furthermore, pond sediment metagenome reads were mapped against Pseudomonas sp. RL genome to identify the environment specific metagenomic islands (MGIs). MGIs were then annotated (Additional file 3: Table S4) as continuous stretches of gaps in the metagenome recruitment plots. MGI annotations revealed that the metabolic functions such as divalent heavy metal cations, homoserine kinase, PIN domain of the 5′-3′ exonuclease, putative GTP-binding protein EngB, cytochrome, thiol-disulfide interchange protein, spermidine/putrescine ABC transporter ATP binding domain, are absent in the in situ cohorts of the strain RL. Detailed annotation results are provided in the supporting information i.e. Additional file 3: Table S4.
It has been reported that spermidine transporter demonstrates an important role in signal modulation of Type III secretory system . Absence of both spermidine ABC transporter and type III secretory system in Pseudomonas sp. RL at the HCH contaminated pond clearly indicates their vestigiality under HCH stress. Similarly, GTP binding protein EngB is reported to be necessary for normal septation and its disruption leads to extensive filamentation. Interestingly, various pseudomonads e.g. P. putida and P. aeruginosa; are known to exert filamentous phenotype acquiring higher resistance towards various metabolic stress conditions . As for an example, antibiotics stress has been reported to increase the filamentous growth in P. aeruginosa . Our results here suggest that filamentous phenotype is favored across HCH stress. Molybdopterin co factor is required by enzymes for carbon, nitrogen and sulphur metabolism. However, its absence can be compensated by iron or other metal ions acting as cofactors via activating alternative nitrogenase or sulphur metabolism pathway. Besides above mentioned proteins, minimal genome at this site revealed the absence of flagellar basal body L-ring protein, flagellar rod assembly proteins, and flagellar basal body P-ring proteins (Additional file 3: Table S4). Interestingly, one of the MGIs was annotated to be N-acetyl neuramic acid synthetase (NcuB) which has been reported to be pathogenicity determinant in Pseudomonas species . Our MGI analysis implies that virulence determinant factors such as NcuB, Type-III secretory system, spermidine transporter, and flagella-associated genes are inactive under HCH stress. This further highlights that virulence in Pseudomonas is a part of genetic adaptation course whereby it can reduce its virulence potential as a result of niche-specific selection . Therefore, here we suggest that HCH stress might be causing the attenuation of virulence determining factors to acquire various habitat-specific metabolic traits. Although this is just a preliminary hypothesis and further research can yield valuable information on survival strategies of Pseudomonas at such stressed environment.
Environment specific selective pressures have always been the apex driving force in the modulation of microbial genomes’ stability . Genus Pseudomonas encompasses metabolically versatile and ecologically significant bacterial genotypes inhabiting all major natural environments . Here, we have exploited the promising field of comparative genomics supplemented with community genomics to resolve the niche specific demarcations across 18 ecologically diverse Pseudomonas genotypes.
Various phylogenetic tools have been employed in the past for identification of Bacillus, Clostridium and Pseudomonas species based on 16S rRNA genes [106-108], However, here, we have used the conserved marker genes sequences (proteins = 400) supported by ANI for taxonomic assignment of strain RL. While 16S rRNA gene sequences are readily available, counting on one single gene lacks phylogenetic resolution . Conserved gene based phylogenomic reconstruction revealed P. aeruginosa group to be phylogenetically as well as functionally conserved in contrast to P. stutzeri group which was found to deviate with ecotype status variations. Strain RL was found to deviate phylogenetically at species level from its reference genotypes (ANI value ≤ 80.03%). Further, while comparing the metabolic potential, strain-specific enrichment was discovered for α-linoleic acid degradation pathway and carbazole degradation in Pseudomonas sp. strain RL and P. stutzeri XLDN-R, respectively. We further reported (Figure 3) a mobile class-I integron (3,552 bp) in RL with intact 5’-CS (1,150 bp) and 3′-CS (1,200 bp) and dhfrA1 (447 bp) as captured gene. Characterization of the integron further revealed presence of promoter sequence (Pc) upstream of the gene cassette highlighting its significance as an active natural expression vector. Metagenomic recruitment of the integron unit of RL on HCH contaminated metagenome datasets revealed (Figure 4) concentrated mapping for IS6100 associated transposase-TnpA6100 gene, which indicated active transfer of DNA within or between genomes specifically at dumpsite (Figure 4). Higher abundance of integron mediated TnpA6100 can be attributed to the stress response by the bacterial community inhabiting the HCH contaminated sites, although the exact mechanism still remains unclear. Furthermore, MGIs were annotated to reveal vestigiality/loss of virulence determinants at the HCH dumpsite with respect to strain RL suggesting diminution of virulence factors at the expense of acquiring micro-habitat specific traits under stress.
Availability of supporting data
The Whole Genome Shotgun project for Pseudomonas sp. strain RL genome sequence has been deposited at DDBJ/EMBL/GenBank under the accession JBOY00000000. The phylogenetic data for the study has been deposited in Dryad (http://datadryad.org/) with doi:10.5061/dryad.nd154.
The authors acknowledge funds from Government of India under project, National Bureau of Agriculturally Important Microorganisms (NBAIM) AMASS/2006-07/NBAIM/CIR, Department of Biotechnology (DBT) under project BT/PR3301/BCE/08/875/2011 and All India Network Project on Soil Biodiversity-Biofertilizers (ICAR) XIth Plan (12-A/2007-1A II). AS, NS, VN and PK gratefully acknowledge National Bureau of Agriculturally Important Microorganisms (NBAIM), Council for Scientific and Industrial Research (CSIR) and University Grants Commission (UGC) for providing research fellowships.
- Spiers AJ, Buckling A, Rainey PB. The causes of Pseudomonas diversity. Microbiology. 2000;146:2345–50.PubMedGoogle Scholar
- Euzéby JP. List of bacterial names with standing in nomenclature: a folder available on the internet. Int J Sys Evol Microbiol. 1997;47:590–2.Google Scholar
- Schmidt KD, Tümmler B, Römling U. Comparative genome mapping of Pseudomonas aeruginosa PAO with P. aeruginosa C, which belongs to a major clone in cystic fibrosis patients and aquatic habitats. J Bacteriol. 1996;178:85–93.PubMed CentralPubMedGoogle Scholar
- Ginard M, Lalucat J, Tummler B, Romling U. Genome organization of Pseudomonas stutzeri and resulting taxonomic and evolutionary considerations. Int J Syst Bacteriol. 1997;47:132–43.PubMedGoogle Scholar
- Marugg JD, Van Spanje M, Hoekstra WPM, Schippers B, Weisbeek PJ. Isolation and analysis of genes involved in siderophore biosynthesis in plant-growth-stimulating Pseudomonas putida WCS358. J Bacteriol. 1985;164:563–70.PubMed CentralPubMedGoogle Scholar
- Livermore DM. Multiple mechanisms of antimicrobial resistance in Pseudomonas aeruginosa: our worst nightmare? Clin Infect Dis. 2002;34:634–40.PubMedGoogle Scholar
- Tettelin H, Riley D, Cattuto C, Medim D. Comparative genomics: the bacterial pan-genome. Curr Opin Microbiol. 2008;11:472–7.PubMedGoogle Scholar
- Sangwan N, Lata P, Dwivedi V, Singh A, Niharika N, Kaur J, et al. Comparative metagenomic analysis of soil microbial communities across three hexachlorocyclohexane contamination levels. PLoS One. 2012;7, e46219.PubMed CentralPubMedGoogle Scholar
- Singh AK, Garg N, Sangwan N, Negi V, Kumar R, Vikram S, et al. Pontibacter ramchanderi sp. nov., isolated from hexachlorocyclohexane (HCH) contaminated pond sediment located in the vicinity of a lindane production unit. Int J Syst Evol Microbiol. 2013;63:2829–34.PubMedGoogle Scholar
- Kaur J, Kaur J, Niharika N, Lal R. Sphingomonas laterariae sp. nov., isolated from a hexachlorocyclohexane-contaminated dump site. Int J Syst Evol Microbiol. 2012;62:2891–6.PubMedGoogle Scholar
- Niharika N, Jindal S, Kaur J, Lal R. Sphingomonas indica sp. nov., isolated from hexachlorocyclohexane (HCH)-contaminated soil. Int J Syst Evol Microbiol. 2012;62:2997–3002.PubMedGoogle Scholar
- Malhotra J, Anand S, Jindal S, Rajagopal R, Lal R. Acinetobacter indicus sp. nov., isolated from a hexachlorocyclohexane dump site. Int J Syst Evol Microbiol. 2012;62:2883–90.PubMedGoogle Scholar
- Dwivedi V, Niharika N, Lal R. Pontibacter lucknowensis sp. nov., isolated from a hexachlorocyclohexane dump site. Int J Syst Evol Microbiol. 2013;63:309–13.PubMedGoogle Scholar
- Lata P, Lal D, Lal R. Flavobacterium ummariense sp. nov., isolated from hexachlorocyclohexane-contaminated soil, and emended description of Flavobacterium ceti Vela et al. 2007. Int J Syst Evol Microbiol. 2012;62:2674–9.PubMedGoogle Scholar
- Anand S, Bala K, Saxena A, Schumann P, Lal R. Microbacterium amylolyticum sp. nov., isolated from soil from an industrial waste site. Int J Syst Evol Microbiol. 2012;62:2114–20.PubMedGoogle Scholar
- Sangwan N, Verma H, Kumar R, Negi V, Lax S, Khurana P, et al. Reconstructing an ancestral genotype of two hexachlorocyclohexane degrading Sphingobium species using metagenomic sequence data. ISME J. 2014;8:398–408.PubMed CentralPubMedGoogle Scholar
- Lal R, Pandey G, Sharma P, Kumari K, Malhotra S, Pandey R, et al. Biochemistry of microbial degradation of hexachlorocyclohexane and prospects for bioremediation. Microbiol Mol Biol Rev. 2010;74:58–80.PubMed CentralPubMedGoogle Scholar
- Kumari R, Subudhi S, Suar M, Dhingra G, Raina V, Dogra C, et al. Cloning and characterization of lin genes responsible for the degradation of hexachlorocyclohexane isomers by Sphingomonas paucimobilis strain B90. Appl Environ Microbiol. 2002;68:6021–8.PubMed CentralPubMedGoogle Scholar
- Nagata Y, Natsui S, Endo R, Ohtsubo Y, Ichikawa N, Ankai A, et al. Genomic organization and genomic structural rearrangements of Sphingobium japonicum UT26, an archetypal -hexachlorocyclohexane-degrading bacterium. Enzyme Microb Technol. 2011;49:499–508.PubMedGoogle Scholar
- Sharma P, Raina V, Kumari R, Malhotra S, Dogra D, Kumari H, et al. Haloalkane dehalogenase LinB is responsible for β- and δ-hexachlorocyclohexane in Sphingobium indicum B90A. Appl Environ Microbiol. 2006;72:5720–7.PubMed CentralPubMedGoogle Scholar
- Verma H, Kumar R, Oldach P, Sangwan N, Khurana JP, Gilbert JA, et al. Comparative genomic analysis of nine Sphingobium strains: Insights into their Evolution and Hexachlorocyclohexane (HCH) Degradation Pathway. BMC Genomics. 2014;15:1014.PubMed CentralPubMedGoogle Scholar
- Ndi OL, Barton MD. Resistance determinants of Pseudomonas species from aquaculture in Australia. J Aquac Res Dev. 2012;3:119.Google Scholar
- Brazelton WJ, Baross JA. Abundant transposases encoded by the metagenome of a hydrothermal chimney biofilm. ISME J. 2009;3:1420–4.PubMedGoogle Scholar
- Dahl TW, Ruhl M, Hammarlund EU, Canfield DU, Rosing MT, Bjerrum CJ. Tracing euxinia by molybdenum concentrations in sediments using handheld X-ray fluorescence spectroscopy (HHXRF). Chem Geol. 2013;360–361:241–51.Google Scholar
- Jit S, Dadhwal M, Kumari H, Jindal S, Kaur J, Lata P, et al. Evaluation of hexachlorocyclohexane contamination from the last lindane production plant operating in India. Environ Sci Pollut Res Int. 2011;18:586–97.PubMedGoogle Scholar
- Vanbroekhoven K, Ryngaert A, Bastiaens L, Wattiau P, Vanacenneyt M, Swings J, et al. Streptomycin as a selective agent to facilitate recovery and isolation of introduced and indigenous Sphingomonas from environmental samples. Environ Microbiol. 2004;6:1123–36.PubMedGoogle Scholar
- Jindal S, Dua A, Lal R. Sphingopyxis indica sp. nov., isolated from a high dose point hexachlorocyclohexane (HCH)-contaminated dumpsite. Int J Syst Evol Microbiol. 2013;63:2186–91.PubMedGoogle Scholar
- Doyle JJ, Doyle JL. Isolation of plant DNA from fresh tissue. Focus. 1990;12:13–5.Google Scholar
- Zerbino DR, Birney E. Velvet: Algorithms for de novo short read assembly using de Bruijin graphs. Genome Res. 2008;18:821–9.PubMed CentralPubMedGoogle Scholar
- Martin W, Scott AJ. Phylogenomic analysis of bacterial and archaeal sequences with AMPHORA2. Bioinformatics. 2012;28:1033–4.Google Scholar
- Dupont CL, Rusch DB, Yooseph S, Lombardo MJ, Richter RA, Valas R, et al. Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage. ISME J. 2012;6:1186–99.PubMed CentralPubMedGoogle Scholar
- Rho M, Tang H, Ye Y. FragGeneScan: predicting genes in short and error- prone reads. Nucleic Acid Res. 2010;38, e191.PubMed CentralPubMedGoogle Scholar
- Moriya Y, Itoh M, Okuda S, Yoshizawa A, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007;35:182–5.Google Scholar
- Ye Y, Doak TG. A parsimony approach to biological pathway reconstruction/inference for genomes and metagenomes. PLoS Comput Biol. 2009;5, e1000465.PubMed CentralPubMedGoogle Scholar
- Punta M, Coggill PC, Eberhardt RY, Mistry J, Tate J, Boursnell C, et al. The Pfam protein families database. Nucleic Acids Res. 2012;40(Database Issue):D290–301.PubMed CentralPubMedGoogle Scholar
- Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32(Database Issue):D277–80.PubMed CentralPubMedGoogle Scholar
- Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011;39(Web Server issue):W29–37.PubMed CentralPubMedGoogle Scholar
- Moura A, Soares M, Pereira C, Leitão N, Henriques I, Correia A. INTEGRALL: a database and search engine for integrons, integrases and gene cassettes. Bioinformatics. 2009;25:1096–8.PubMedGoogle Scholar
- Segata N, Börnigen D, Morgan XC, Huttenhower C. PhyloPhlAn is a new method for improved phylogenetic and taxonomic placement of microbes. Nat Commun. 2013;4:2304.PubMed CentralPubMedGoogle Scholar
- Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75–90.PubMed CentralPubMedGoogle Scholar
- A-Rong L, Yan-Zhou Z, Hui-Jie Q, Wei-Feng S, Murphy RW, Chao-Dong Z. Outgroup selection in tree construction: a case study of the family Halictidae (Hymenoptera: Apoidea). Acta Entomologica Sinica. 2010;53:192–201.Google Scholar
- Özen AI, Ussery DW. Defining the Pseudomonas genus: where do we draw the line with Azotobacter? Microb Ecol. 2012;63:239–48.PubMed CentralPubMedGoogle Scholar
- Konstantinidis KT, Tiedje JM. Genomic insights that advance the species definition for prokaryotes. Proc Natl Acad Sci U S A. 2005;102:2567–72.PubMed CentralPubMedGoogle Scholar
- Popendorf K, Tsuyoshi H, Osana Y, Sakakibara Y. Murasaki: a fast, parallelizable algorithm to find anchors from multiple genomes. PLoS One. 2010;5, e12651.PubMed CentralPubMedGoogle Scholar
- Hachiya T, Osana Y, Popendorf K, Sakakibara Y. Accurate identification of orthologous segments among multiple genomes. Bioinformatics. 2009;25:853–60.PubMedGoogle Scholar
- Wall DP, DeLuca T. Ortholog detection using the Reciprocal Smallest Distance Algorithm. Methods Mol Biol. 2007;396:95–110.PubMedGoogle Scholar
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45.PubMed CentralPubMedGoogle Scholar
- Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gaps penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–80.PubMed CentralPubMedGoogle Scholar
- Suyama M, Torrents D, Bork P. PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res. 2006;34(Web Server Issue):W609–612.PubMed CentralPubMedGoogle Scholar
- Yang Z. PAML 4: Phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24:1586–91.PubMedGoogle Scholar
- Rocha EPC, Smith JM, Hurst LD, Holden MT, Cooper JE, Smith NH, et al. Comparisons of dN/dS are time dependent for closely related bacterial genomes. J Theor Biol. 2006;239:226–35.PubMedGoogle Scholar
- Waack S, Keller O, Asper R, Brodag T, Damm C, Fricke WF, et al. Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models. BMC Bioinformatics. 2006;7:142–54.PubMed CentralPubMedGoogle Scholar
- Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, Koonin EV, et al. The COG database: an updated version includes eukaryotes. BMC Bioinformatics. 2003;4:41.PubMed CentralPubMedGoogle Scholar
- Rizk G, Lavenier D. GASSST: global alignment short sequence search tool. Bioinformatics. 2010;26:2534–40.PubMed CentralPubMedGoogle Scholar
- Qichao T, He Z, Zhou J. Strain/species identification in metagenomes using genome specific markers. Nucleic Acids Res. 2014;doi:10.1093/nar/gku138.Google Scholar
- R Development Core Team. R: A language and environment for statistical computing. ienna, Austria: R Foundation for Statistical Computing; 2011.Google Scholar
- Oksanen J, Blanchet FG, Kindt R, Legendre P, O’Hara RG, Simpson GL, et al. vegan: Community Ecology Package. R package version 1.17-0. http://cran.r-project.org/web/packages/vegan/. 2010
- Sokal RR, Rohlf FJ. Biometry: the principles and practice of statistics in biological research. 4th ed. New York: W. H. Freeman and Co; 2012. p. 937.Google Scholar
- Ohtsubo Y, Kishida K, Sato T, Tabata M, Kawasumi T, Ogura Y, et al. Complete genome sequence of Pseudomonas sp. Strain TKP, isolated from a -Hexachlorocyclohexane-degrading mixed culture. Genome Announc. 2014;2:e01241–13.PubMed CentralPubMedGoogle Scholar
- Ohtsubo Y, Sato T, Kishida K, Tabata M, Ogura Y, Hayashi T, et al. Complete genome sequence of Pseudomonas aeruginosa MTB-1, isolated from a microbial community enriched by the technical formulation of Hexachlorocyclohexane. Genome Announc. 2013;2:e01130–13.Google Scholar
- Walker A, Jurado-Exposito M, Bending GD, Smith VJ. Spatial variability in the degradation rate of isoproturon in soil. Environ Pollut. 2001;111:407–15.PubMedGoogle Scholar
- Mwangi K, Boga HI, Muigai AW, Kiiyuikia C, Tsanuo MK. Degradation of dichlorodiphenyltrichloroethane (DDT) by bacterial isolates from cultivated and uncultivated soil. Afr J Microbiol Res. 2010;4:185–96.Google Scholar
- NTP (National Toxicology Program). Report on Carcinogens, Thirteenth Edition. Research Triangle Park, NC: U.S: Department of Health and Human Services, Public Health Service; 2014.Google Scholar
- Botzman M, Margalit H. Variation in global codon usage bias among prokaryotic organisms is associated with their lifestyles. Genome Biol. 2011;12:R109.PubMed CentralPubMedGoogle Scholar
- Richter M, Rossello’-Mo’ra R. R Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci USA. 2009;106:19126–31.PubMed CentralPubMedGoogle Scholar
- Peña A, Busquets A, Gomila M, Bosch R, Nogalesa B, García-Valdésa E, et al. Draft genome of Pseudomonas stutzeri strain ZoBell (CCUG 16156), a marine isolate and model organism for denitrification studies. J Bacteriol. 2012;194:1277–8.PubMed CentralPubMedGoogle Scholar
- Brunet-Galmésa I, Busquetsa A, Peñaa A, Gomilab M, BalbinaNogalesa B, García-Valdésa E, et al. Complete genome sequence of the naphthalene-degrading bacterium Pseudomonas stutzeri AN10 (CCUG 29243). J Bacteriol. 2012;194:6642–3.Google Scholar
- Li A, Gai Z, Cui D, Ma F, Yang J, Zhang X, et al. Genome sequence of a highly efficient aerobic denitrifying bacterium, Pseudomonas stutzeri T13. J Bacteriol. 2012;194:5720.PubMed CentralPubMedGoogle Scholar
- Liu X, Gai Z, Tao F, Yu H, Tang H, Xu P. Genome sequences of Pseudomonas luteola XLDN4-9 and Pseudomonas stutzeri XLDN-R, two efficient carbazole-degrading strains. J Bacteriol. 2012;194:5701–2.PubMed CentralPubMedGoogle Scholar
- Stokes HW, Hall RM. A novel family of potentially mobile DNA elements encoding site-specific gene-integration functions: integrons. Mol Microbiol. 1989;3:1669–83.PubMedGoogle Scholar
- Collis CM, Hall RM. Gene cassettes from the insert region of integrons are excised as covalently closed circles. Mol Microbiol. 1992;6:2875–85.PubMedGoogle Scholar
- Stokes HW, O’Gorman DB, Recchia GD, Parsekhian M, Hall RM. Structure and function of 59-base element recombination sites associated with mobile gene cassettes. Mol Microbiol. 1997;26:731–45.PubMedGoogle Scholar
- Mazel D. Integrons: agents of bacterial evolution. Nat Rev Microbiol. 2006;4:608–20.PubMedGoogle Scholar
- Matzke NJ, Shih PM, Kerfeld CA. Bayesian analysis of congruence of core genes in Prochlorococcus and Synechococcus and implications on Horizontal Gene Transfer. PLoS One. 2014;9, e85103.PubMed CentralPubMedGoogle Scholar
- Kuo TM, Nakamura LK. Diversity of oleic acid, ricinoleic acid and linoleic acid conversions among Pseudomonas aeruginosa strains. Curr Microbiol. 2004;49:261–6.PubMedGoogle Scholar
- Poelarends GJ, Wilkens M, Larkin MJ, Elsas JD, Janssen DB. Degradation of 1,3-dichloropropene by Pseudomonas cichorii 170. Appl Env Microbiol. 1998;64:2931–6.Google Scholar
- Martino CD, López NI, Iustman LJR. Isolation and characterization of benzene, toluene and xylene degrading Pseudomonas sp. selected as candidates for bioremediation. Int Biodeter Biodegr. 2012;67:15e20.Google Scholar
- Romanov V, Hausinger RP. Pseudomonas aeruginosa 142 uses a three-component ortho halobenzoate 1,2-dioxygenase for metabolism of 2,4-Dichloro- and 2-Chlorobenzoate. J Bacteriol. 1994;176:3368–74.PubMed CentralPubMedGoogle Scholar
- Poole K. Aminoglycoside resistance in Pseudomonas aeruginosa. Antimicrob Agents Chemother. 2005;49:479–87.PubMed CentralPubMedGoogle Scholar
- Esikova T, Ponamoreva O, Baskunov B, Tarand S, Boronin A. Transformation of low-molecular linear caprolactam oligomers by caprolactam degrading bacteria. J Chem Technol Biotechnol. 2012;87:1284–90.Google Scholar
- Boulette ML, Baynham PJ, Jorth PA, Kukavica-Ibrulj I, Longoria A, Barrera K, et al. Characterization of alanine catabolism in Pseudomonas aeruginosa and its importance for proliferation in vivo. J Bacteriol. 2009;191:6329–34.PubMed CentralPubMedGoogle Scholar
- Ma Q, Zhai Y, Schneider JC, Ramseier TM, Saier Jr MH. Protein secretion systems of Pseudomonas aeruginosa and P fluorescens. Biochim Biophys Acta. 2003;1611:223–33.PubMedGoogle Scholar
- Song B, Palleroni NJ, Häggblom MM. Isolation and characterization of diverse halobenzoate-degrading denitrifying bacteria from soils and sediments. Appl Environ Microbiol. 2000;66:3446–53.PubMed CentralPubMedGoogle Scholar
- Koenig RL, Morris RO, Polacco JC. tRNA is the source of low-level trans-Zeatin production in Methylobacterium spp. J Bacteriol. 2002;184:1832–42.PubMed CentralPubMedGoogle Scholar
- Anand S, Sangwan N, Lata P, Kaur J, Dua A, Singh AK, et al. Genome sequence of Sphingobium indicum B90A, a hexachlorocyclohexane-degrading bacterium. J Bacteriol. 2012;194:4471–2.PubMed CentralPubMedGoogle Scholar
- Kumar Singh A, Sangwan N, Sharma A, Gupta V, Khurana JP, Lal R. Draft genome sequence of Sphingobium quisquiliarum strain P25T, a novel hexachlorocylohexane (HCH)-degrading bacterium isolated from an HCH dumpsite. Genome Announc. 2013;1:e00717–13.PubMed CentralPubMedGoogle Scholar
- Mukherjee U, Kumar R, Mahato NK, Khurana JP, Lal R. Draft genome sequence of Sphingobium sp. strain HDIPO4, an avid degrader of hexachlorocyclohexane. Genome Announc. 2013;1:e00749–13.PubMed CentralPubMedGoogle Scholar
- Kaur J, Verma H, Tripathi C, Khurana JP, Lal R. Draft genome sequence of a hexachlorocyclohexane-degrading bacterium, Sphingobium baderi strain LL03T. Genome Announc. 2013;1:e00751–13.PubMed CentralPubMedGoogle Scholar
- Kohli P, Dua A, Sangwan N, Oldach P, Khurana JP, Lal R. Draft genome sequence of Sphingobium ummariense strain RL-3, a hexachlorocyclohexane-degrading bacterium. Genome Announc. 2013;1:e00956–13.PubMed CentralPubMedGoogle Scholar
- Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics. 2009;25:1754–60.PubMed CentralPubMedGoogle Scholar
- Rediers H, Vanderleyden J, De Mot R. Nitrate respiration in Pseudomonas stutzeri A15 and its involvement in rice and wheat root colonization. Microbiol Res. 2009;164:461–8.PubMedGoogle Scholar
- Robleto EA, López-Hernández I, Silby MW, Levy SB. Genetic Analysis of the AdnA regulon in Pseudomonas fluorescens: nonessential role of flagella in adhesion to sand and biofilm formation. J Bacteriol. 2003;185:453–60.PubMed CentralPubMedGoogle Scholar
- Marshall B, Stintzi A, Gilmour C, Meyer J-M, Poole K. Citrate-mediated iron uptake in Pseudomonas aeruginosa: involvement of the citrate-inducible FecA receptor and the FeoB ferrous iron transporter. Microbiol. 2009;155:305–15.Google Scholar
- Mirus O, Strauss S, Nicolaisen K, von Haeseler A, Schleiff E. TonB-dependent transporters and their occurrence in cyanobacteria. BMC Biol. 2009;7:68.PubMed CentralPubMedGoogle Scholar
- Baharoglu Z, Krin E, Mazel D. Connecting environment and genome plasticity in the characterization of transformation-induced SOS regulation and carbon catabolite control of the Vibrio cholerae integron integrase. J Bacteriol. 2012;194:1659–67.PubMed CentralPubMedGoogle Scholar
- Santos PM, Benndorf D, Sá-Correia I. Insights into Pseudomonas putida KT2440 response to phenol-induced stress by quantitative proteomics. Proteomics. 2004;4:2640–52.PubMedGoogle Scholar
- Anderson GG, Yahr TL, Lovewell RR, O’Toole GA. The Pseudomonas aeruginosa magnesium transporter MgtE inhibits transcription of the Type III Secretion System. Infect Immun. 2010;78:1239–49.PubMed CentralPubMedGoogle Scholar
- Vermeiren H, Willems A, Schoofs G, de Mot R, Keijers V, Hai W, et al. The rice inoculant strain Alcaligenes faecalis A15 is a nitrogen-fixing Pseudomonas stutzeri. Syst Appl Microbiol. 1999;22:215–24.PubMedGoogle Scholar
- Alm E, Huang K, Arkin A. The evolution of Two-Component Systems in bacteria reveals different strategies for niche adaptation. PLoS Comput Biol. 2006;2, e143.PubMed CentralPubMedGoogle Scholar
- Zhou L, Wang J, Zhang L-H. Modulation of bacterial Type III secretion system by a spermidine transporter dependent signaling pathway. PLoS One. 2007;2, e1291.PubMed CentralPubMedGoogle Scholar
- Crabbé A, Leroy B, Wattiez R, Aertsen A, Leys N, Cornelis P, et al. Differential proteomics and physiology of Pseudomonas putida KT2440 under filament-inducing conditions. BMC Microbiol. 2012;12:282.PubMed CentralPubMedGoogle Scholar
- Hammer MC, Baltch AL, Smith RP, Conroy JV, Bishop M, Michelsen PP, et al. Human granulocyte activity against moxalactam-induced filamentous forms of P. aeruginosa. Antimicrob Agents Chemother. 1988;32:1565.PubMed CentralPubMedGoogle Scholar
- Liao X, Hancock RE. Cloning and characterization of the Pseudomonas aeruginosa pbpB gene encoding Penicillin-Binding Protein 3. Antimicrob Agents Chemother. 1995;39:1871–4.PubMed CentralPubMedGoogle Scholar
- Lore NI, Cigana C, Fino ID, Riva C, Juhas M, Schwager S, et al. Cystic Fibrosis-Niche adaptation of Pseudomonas aeruginosa reduces virulence in multiple infection hosts. PLoS One. 2012;7, e35648.PubMed CentralPubMedGoogle Scholar
- Boto L, Martinez JL. Ecological and temporal constraints in the evolution of bacterial genomes. Genes. 2011;2:804–28.PubMed CentralPubMedGoogle Scholar
- Kalia VC, Mukherjee T, Bhushan A, Joshi J, Shankar P, Huma N. Analysis of the unexplored features of rrs (16S rDNA) of the genus Clostridium. BMC Genomics. 2011;12, e18.Google Scholar
- Porwal S, Lal S, Cheema S, Kalia VC. Phylogeny in aid of the present and novel microbial lineages: diversity in Bacillus. PLoS One. 2009;4, e44.Google Scholar
- Bhushan A, Joshi J, Shankar P, Kushwah J, Raju SC, Purohit HJ, et al. Development of genomic tools for the identification of certain Pseudomonas up to species level. Indian J Microbiol. 2013;53:253–63.PubMed CentralPubMedGoogle Scholar
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