Exiguobacterium and Psychrobacter are bacterial genera with several cold-adapted species. These extremophiles are com- monly isolated from the same habitats in Earth’s cryosphere and have great ecological and biotechnological relevance. Thus, through comparative genomic analyses, it was possible to understand the functional diversity of these psychrotrophic and psychrophilic species and present new insights into the microbial adaptation to cold. The nucleotide identity between Exiguobacterium genomes was >90%. Three genomic islands were identiﬁed in the E. antarcticum B7 genome. These islands contained genes involved in ﬂagella biosynthesis and chemotaxis, as well as enzymes for carotenoid biosynthesis. Clustering of cold shock proteins by Ka/Ks ratio suggests the occurrence of a positive selection over these genes. Neighbor- joining clustering of complete genomes showed that the E. sibiricum was the most closely related to E. antarcticum.A total of 92 genes were shared between Exiguobacterium and Psychrobacter. A reduction in the genomic content of E. antarc- ticum B7 was observed. It presented the smallest genome size of its genus and a lower number of genes because of the loss of many gene families compared with the other genomes. In our study, eight genomes of Exiguobacterium and Psychrobacter were compared and analysed. Psychrobacter showed higher genomic plasticity and E. antarcticum B7 presented a large decrease in genomic content without changing its ability to grow in cold environments. Key words: Psychrobacter, Exiguobacterium, cold adaptation, psychrotrophic, comparative genomics, extremophiles. Introduction whereas Exiguobacterium was ﬁrst described by Collins et al. Several cold-adapted bacterial strains are taxonomically clas- (1983) with the microbiological characterization of the species siﬁed in the genera Exiguobacterium and Psychrobacter E. aurantiacum. (Vishnivetskaya et al. 2000; Rodrigues et al. 2006; Carneiro The genus Exiguobacterium is physiologically more diverse et al. 2012) and are commonly described in environmental than Psychrobacter, and it includes psychrotrophic, meso- studies using microbiological or molecular approaches philic, and moderate thermophilic bacterial species (Rodrigues et al. 2006, 2009; Yadav et al. 2015). Strains of (Vishnivetskaya and Kathariou 2005). Strains of these genera commonly colonize the same ecological niche, Exiguobacterium are commonly isolated from glacial ice, hot expressing genes that produce a cold-adaptive phenotype. springs, the rhizosphere of plants, permafrosts, and tropical Psychrobacter species have been isolated from the deep water and temperate soils (Rodrigues et al. 2006; Rodrigues and of the sea, permafrosts, Antarctic glacial ice, and sediment, Tiedje 2007; Carneiro et al. 2012). Exiguobacterium and among other habitats (Bowman et al. 1997; Shivaji et al. Psychrobacter are phylogenetically distant genera. Whereas 2005; Chaturvedi and Shivaji 2006; Moyer and Morita Exiguobacterium is classiﬁed in the phylum Firmicutes, class 2007; Shravage et al. 2007; Rodrigues et al. 2009). The genus Bacilli, and order Bacillales, Psychrobacter is classiﬁedinthe Psychrobacter was ﬁrst described by Juni and Heym (1986), phylum Proteobacteria, class Gammaproteobacteria,order The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Genome Biol. Evol. 10(3):731–741. doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 731 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Dias et al. GBE Pseudomonadales, family Moraxellaceae (https://www.name- sibiricum 255-15), CP015731.1 (Exiguobacterium sp. U13- sforlife.com/; last accessed January 20, 2017). Despite their 1), CP006866.1 (Exiguobacterium sp. MH3), CP000082.1 taxonomical classiﬁcation, both genera have developed mo- (Psychrobacter arcticus 273-4), CP014945.1 (Psychrobacter lecular mechanisms when they are grown in harsh conditions, alimentarius PAMC 27889), CP012678.1 (Psychrobacter ura- such as low temperature environments. tivorans R10.10B), and CP000323.1 (Psychrobacter cryohalo- The mechanisms of adaptation include the following: lentis K5). 1) increased enzymatic catalytic efﬁciency; 2) production of unsaturated branched-chain fatty acids to maintain mem- General Genomic Comparisons brane ﬂuidity; 3) expression of cold shock proteins that stabi- Initially, all genomes were compared with the genome of E. lize the bacterial cytosol at low temperatures; 4) uptake of antarcticum B7 by BLASTn, generating a ring on the software compatible solutes to maintain the cellular osmotic balance; BRIG v.0.95 (Alikhan et al. 2011). The GenBank ﬁle of E. and 5) carotenoid production (Barria et al. 2013; De Maayer antarcticum B7 was manually curated to highlight the main et al. 2014). Because of these metabolic peculiarities, psychro- genes involved in the cold adaptation processes. These genes philic and psychrotrophic bacteria have great biotechnological were indicated in the rings generated by the software, BRIG. appeal and are widely used in studies of biodegradation of Synteny between the genomes was analysed on the software hydrocarbons, antibiotics, and other environmental pollutants Artemis Comparison Tool (ACT) v.13.0.0 (Carver et al. 2005). (Jiang et al. 2014; Bajaj and Slingh 2015). Furthermore, these Genomic Islands (GIs) of E. antarcticum B7 were predicted by micro-organisms are of extreme importance to better under- GIPSy (Soares et al. 2016). Four types of islands were pre- stand the ecological and biogeochemical processes of the dicted: Resistance Island (RI), Pathogenicity Island (PAI), Earth’s cryosphere (Boetius et al. 2015). Symbiotic Island (SI), and Metabolic Island (MI). The thermo- With the advent of Next-Generation Sequencing (NGS) philic specie Exiguobacterium AT1b wasusedasreference. technologies in the last decade, the number of genomes avail- Genes within GIs were compared by BLASTn to the database able in databases has increased. In total, the GenBank data- of Predicted Genome Islands (Pre_GI) using an e-value of 1e- base has 42 genomes of Exiguobacterium, four of which are 05 to determine the main taxonomic hosts of the foreign completely assembled and belong to psychrotrophic or psy- genes. Pre_GI contains a sequence database of genes ac- chrophilic species. Psychrobacter contains 37 deposited quired by horizontal transfer for the Bacteria and Archaea genomes, four of which are completely assembled and be- domains (Pierneef et al. 2015). long to cold-adapted species. Several bioinformatics tools To determine the conservation of cold shock proteins have been developed to compare and analyse this large (CSPs), all sequences were extracted from GenBank ﬁles amount of genomic data. Our work presents the results of and a database was created using the script gb2fasta.py of a comparative genomic analysis performed with the genera the BlastGraph v.1.0 program package (Ye et al. 2013). This Exiguobacterium and Psychrobacter. The results obtained database was compared with itself by BLASTp using the pack- helped us understand and visualize the adaptive molecular age Blastall (Altschul et al. 1990). The resulting .xml ﬁle con- diversity of these two phylogenetically distant but ecologically taining the similarity scores was analysed in BlastGraph similar cold-adapted genera. software to construct a de Brujin graph where each node represents a protein sequence and the size of the edges rep- Materials and Methods resents the degree of similarity between these sequences (Ye et al. 2013). A neighbor-joining tree was calculated in MEGA7 Data Collection (Kumaretal. 2016) using the same data set described above We have carefully reviewed the 79 genomes of both genera for BlastGraph analyses. Sequences were aligned using deposited in GenBank and selected four genomes for each ClustalW before tree calculation. A total of 1,000 replicates genus to perform the comparative analysis. The selection was were calculated. To evaluate the selective pressure on CSP based on two criteria: 1) the “habitat” and “growth temper- genes, the sequences were analysed using the web applica- ature” information contained in the literature or BioSample tion Ka/Ks of the Norwegian Bioinformatics Platform (Siltberg data and 2) the completeness of the genomes. Only psychro- and Liberles 2002). trophic or psychrophilic species with genomes that were completely assembled were selected for analysis. The genome Clustering Analysis of Exiguobacterium antarcticum B7 was sequenced by our research group using a hybrid assembly methodology that To evaluate the functional and nucleotide similarity between used fragments and mate-paired libraries (Carneiro et al. strains of Exiguobacterium and Psychrobacter two approaches 2012). This genome was deposited under the accession num- were performed, both of which were based on clustering ber CP003063.1. The remaining seven genomes were methods. In the ﬁrst approach, a clustering based on the obtained from NCBI’s GenBank database and have the fol- neighbor-joining model was performed to compare the lowing accession numbers: CP001022.1 (Exiguobacterium DNA sequence of the genes from the core genome. 732 Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Genomic Architecture of the Two Cold-Adapted Genera Exiguobacterium and Psychrobacter GBE Table 1 General Characteristics of the Bacterial Species Organism Isolation Source Minimum Growth Genome Number GC Content Reference Temperature Size (bp) of CDSs (%) Exiguobacterium antarcticum B7 Ginger Lake, Antarctica 2 C 2,815,863 2,736 47.50 Carneiro et al. (2012) E. sibiricum 255-15 Permafrost, Siberia 10 C 3,034,136 3,107 47.68 Rodrigues et al. (2008) Exiguobacterium sp. MH3 Rhizosphere of a duckweed 4 C 3,164,195 3,160 47.20 Tang et al. (2013) strain, Lemna minor Exiguobacterium sp. U13-1 Lake Untersee, Antarctica – 3,208,634 3,178 47.10 Fomenkov et al. (2017) Psychrobacter arcticus 273-4 Kolyma, Siberia 10 C 2,650,701 2,130 42.8 Ayala-del-Rio et al. (2010) P. cryohalolentis K5 Kolyma Lowland, Russia 10 C 3,059,876 2,510 42.3 Unpublished data P.urativorans R10.10B Soil 20 C 2,802,354 2,359 42.2 Unpublished data P. alimentarius PAMC 27889 Rocky desert, Antarctica 10 C 3,332,539 2,678 42.9 Lee et al. (2016) Data not available in BioSample or literature. Thecoregenome and thedistancematrix werecalculated by the Exiguobacterium and Psychrobacter genomes was created PGAP v.1.11 (Zhao et al. 2012) using a coverage cutoff of using a script provided by the software package. This multi- 80% and identity of 50%. The output ﬁle 4.PanBased.NJ.tree fasta ﬁle was compared against itself by BLASTp using the was analysed in the software SplitsTree v.4.14.2 (Huson and blastall package. The distance matrix in .xml format was Bryant 2006) to obtain an unrooted tree. In the second ap- used as an input ﬁle for the software BlastGraph. A phyloge- proach, the whole nucleotide sequence of the genomes, in- netic tree was calculated using the UPGMA (Unweighted Pair cluding their plasmids, were compared all-against-all by Group Method with Arithmetic Mean) model and a bootstrap BLASTn using the software Gegenees v.2.2.1 (Agren et al. of 1,000 replicates. To determine the main biological subsys- 2012) with a fragment size of 200 bp and a step size of tems of the genomes, their complete sequence was submit- 100 bp. Fragments with identity values >30% were used to ted as a fasta ﬁle to the Rapid Annotation using Subsystem calculate the similarity scores. The result was presented as a Technology (RAST) server (Aziz et al. 2008). Subsystem clas- heat map with nucleotide similarity in percentage. The heat siﬁcation was evaluated, and the main pathways involved in map was subsequently analysed in the software SplitsTree cold adaptation were compared using the RAST server. v.4.14.2 to obtain an unrooted tree using the neighbor- joining model. Results and Discussion Comparative and Clustering Analysis Gene Distribution The eight selected genomes varied considerably in size, num- The gene distribution was analysed with the software PGAP ber of predicted genes, GC content, presence of plasmids, v.1.11 using the same parameters described in the section and other genotypic characteristics (table 1). As revealed by above. First, the pangenome calculation was performed sep- the rings of ﬁgure 1, a high nucleotide identity (between 90% arately for each genus to extract the information about the and 100%) within Exiguobacterium species was observed. core genome, accessory genes, singletons, and paralogous Compared with the Psychrobacter genomes, only seven genes. Subsequently, the pangenome was calculated using regions of E. antarcticum B7 showed an identity near all genomes from both genera. In the latter analyses, the 100%. Using the genome browser, it was possible to note PGAP output ﬁle, 1.Orthologs_Cluster.txt, and the PGAP in- that these conserved regions carried the rRNA gene clusters put ﬁle .pep containing the peptide sequence of all genomes (ﬁg. 1). A small number of genomic inversions were observed was used to extract the amino acid sequence of the core between the genomes of Exiguobacterium strains. On the genes by using a Perl script developed by our research group other hand, Psychrobacter genomes showed a larger number called getFastaFromOrthologs.pl. The core genes were classi- of inversions and larger inverted regions (ﬁg. 2). ﬁed into Gene Ontology (GO) categories using the software Exiguobacterium antarcticum B7 e E. sibiricum 255-15 are Blast2GO (Conesa et al. 2005). Venn diagrams and bar graphs the species with the highest structural similarity. Although were obtained in the R package. E. antarcticum B7 has the smallest genome of the genus, no large insertion/deletion regions could be observed in the Gene Gain and Loss Analysis synteny graph (ﬁg. 2). GIPSy was used to predict genomic islands in E. antarcti- The level of gain and loss of the gene families was analysed in cum B7. The prediction was based on commonly genomic thesoftwareBlastGraph v.1.0 (Ye et al. 2013). Initially, a features such as GC content; codon usage; presence of multifasta ﬁle containing all of the protein sequences from Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 733 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Dias et al. GBE FIG.1.—Circular map designed to compare the nucleotide identity of all genomes against Exiguobacterium antarcticum B7. The genomes were compared by BLASTn, and the percent identity between them was determined by the intensity of color in the circular rings. The innermost ring to the outermost in this ﬁgure is presented as follows: the GC content and CG skew of E. antarcticum B7, the genomes of E. sibiricum 255-15, Exiguobacterium sp. MH3, Exiguobacterium sp. U13-1, Psychrobacter arcticus 273-4, P. alimentarius PAMC 27889, P. cryohalolentis K5, and P. urativorans R10.10B, respectively. The three outermost rings comprise the location of the GIs (yellow arcs) and CDSs (red arcs) of E. antarcticum B7. The main genes involved in cold adaptation are indicated by circles colored according to the metabolic pathway. transposase genes; virulence, metabolism, antibiotic resis- genes encoding enzymes involved in the early stages of carot- tance, or symbiosis factors; ﬂanking tRNA genes; and absence enoid biosynthesis. A two-component system regulated by of the predicted islands in closely related species (Soares et al. a histidine kinase was also described within the island. In 2016). Two PAIs, threeRIs, and oneSI were detected (supple- EaPAI_2, EaRI_3 and EaSI_1 (genomic position: 2,459,471 up mentary table S1, Supplementary Material online). These to 2,469,289 bp), ﬁve of the ten CDSs detected were unchar- Genomic Islands (GIs) were tagged with the acronyms EaPAI acterized proteins. The other ﬁve CDSs were identiﬁed by com- (E. antarcticum Pathogenicity Island), EaRI, and EaSI, respec- putational homology as UDP-N-acetylglucosamine 2-epimerase tively. We did not found any evidence of horizontal gene (wecB), Uracil phosphoribosyltransferase (upp), Serine hydrox- ﬂow in the genomic region of the islands using the Pre_GI ymethyltransferase (glyA) and, once again, a two-component database. Interestingly, EaPAI_1 was predicted in the same lo- system (composed of a histidine kinase and a regulatory pro- cation as EaRI_2, as well as EaPAI_2 was predicted in the same tein). The gene wecB encodes an enzyme that catalyzes the location as EaRI_3 and Ea_SI_1 (supplementary table S1, synthesis of a bacterial capsule precursor which could explain Supplementary Material online). EaPAI_1 and EaRI_2 (genomic the prediction of this region as a putative pathogenicity island. position: 2,229,960 up to 2,257,989 bp) contain genes One of the main mechanisms of cold adaptation in species involved in ﬂagella biosynthesis and chemotaxis, as well as of the order Bacillales is the expression of the DesR-DesK 734 Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Genomic Architecture of the Two Cold-Adapted Genera Exiguobacterium and Psychrobacter GBE FIG.2.—Analysis of genomic synteny. Synteny plots were obtained using the Artemis Comparison Tool. Gray lines indicate the genome size of each bacterial strain. Red bars indicate the conserved genomic regions, and blue bars indicate regions of genomic inversion. To better visualize the structural correlation between genomes, a minimum cut-off of 150 for BLASTn scores was applied. Psychrobacter strains have a signiﬁcant number of inversions in their genomes. Exiguobacterium strains present a more conserved structural correlation. two-component system. During cold stress, a membrane sen- (ﬁg. 4). In addition, an intracluster analysis demonstrated that sor histidine kinase (DesK) activates a regulatory protein CSPs from both genera could be divided on three different (DesR) that in turn positively regulates the expression of fatty clades supported by high bootstrap values (ﬁg. 4). It is worth acid desaturase genes (des)(Aguilar et al. 2001). Fatty acid noting that E. antarcticum B7 and E. sibiricum 255 have six desaturase enzymes modify the chemical structure of mem- CSP genes each, while the other species have only three. This brane fatty acids in order to maintain membrane ﬂuidity. gene duplication could be an important mechanism of adap- Exiguobacterium antarcticum B7 contains twelve two- tation to cold environments. However, two of these CSPs of E. component systems throughout its genome. However, none antarcticum B7 (locus_tag: EaB7_2272 and EaB7_2747) were of them were near a fatty acid desaturase gene as described downregulated after 72 h of growth at 0 C(Dall’Agnol et al. for Bacillus subtilis (Aguilar et al. 2001). Additionally, all two- 2014) suggesting that these proteins are not necessary for component systems identiﬁed showed low similarity with the cold acclimation. Therefore, they possibly play different roles model system of B. subtilis identiﬁed by Aguilar et al. (2001) from those observed for the other CSPs. (BLASTp identity values were <50%). Two des genes were The clustering by K /K ratio (nonsynonymous and synon- a s identiﬁed in the genome of E. antarcticum and were upregu- ymous substitution rates) was used to evaluate the selective lated during cold stress (Dall’Agnol et al. 2014) suggesting pressure on these CSP genes. We noted that only CSPs that that desaturase enzymes are under regulatory control and were downregulated in cold temperatures showed very low as observed in B. subtillis, regulate chemical composition of Ka/Ks ratio (0.1255 and 0.3256) suggesting a purifying selec- membrane fatty acids. tion to conserve their protein sequence and function (supple- The extracted CSP sequences were compared all-against- mentary ﬁg. S1 and table S2, Supplementary Material online). all using the blastall package. A de Brujin graph was obtained Nonsynonimous substitutions were more prevalent (Ka/Ks ra- using BlastGraph (ﬁg. 3a) to visualize the sequences similarity tio>1) in the nodes 4 and 5 of the tree (supplementary ﬁg. S1 based on the reciprocal BLASTp values. Nodes of ﬁgure 3a and table S2, Supplementary Material online). These high represent the protein sequences, and the size of the edges values of Ka/Ks ratio clustered CSPs into three groups suggest- represents the degree of similarity (reciprocal BLASTp) be- ing that these groups are evolving at different rates. The dif- tween these sequences. No signiﬁcant differences were ob- ferential expression of CSP genes in cold temperatures is an served among CSPs from Exiguobacterium and Psychrobacter. indicative of distinct roles of these proteins. It is worth noting The CSPs of the thermophilic bacteria Exiguobacterium sp. that the gene clusters observed in UPGMA analysis are differ- AT1b also clustered together with all other proteins ent from what was observed in the Ka/Ks ratio analysis (ﬁg. 4 (ﬁg. 3a). Additional analysis was performed using the phe- and supplementary ﬁg. S1, Supplementary Material online). netic clustering method UPGMA. In this analysis, CSPs were For phylogenomic comparisons a dendogram was calcu- clustered into two groups according to the bacterial genera lated using the heat map of similarity generated by Gegenees Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 735 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Dias et al. GBE FIG.3.—De Bruijn graph of cold-shock proteins and clustering analysis of genomes. (a) A de Brujin graph clustering the sequences of CSPs (nodes) according to the results of the reciprocal BLASTp (edges). The comparison was conducted with the blastall package. The graph was designed in the BlastGraph program. (b) All-against-all comparison of the nucleotide genome sequences. The heat map represents the percent identity between the genomes. The tree was calculated in Gegenees software using the neighbor-joining model. observed dividing the two genera (3,919.75), thus evidencing the high phenetic distance between these taxa (supplemen- tary ﬁg. S2, Supplementary Material online). The values of split weight are drastically reduced within each genus clade. The branch length represented as a split weight shows the depth of the divergence between the taxa (supplementary ﬁg. S2, Supplementary Material online). Gene Distribution In our study, 2,276 genes were shared among the four species of Exiguobacterium (ﬁg. 5c), and 1,483 genes were shared among the four species of Psychrobacter (ﬁg. 5a). It was ob- served that only 92 genes were shared between strains of Exiguobacterium and Psychrobacter (ﬁg. 5e)(supplementary table S3, Supplementary Material online). One of the CSPs was identiﬁed among these core genes (EaB7_1549). Therefore, this is a highly conserved mechanism present in phylogenetically distant taxa. The core genes were subse- quently classiﬁed into GO terms (ﬁg. 6). CSPs were classiﬁed into the “response to stress” group of the GO Biological Processes (ﬁg. 6b). They have notorious importance to cold adaptation by maintaining cell viability through the stabiliza- FIG.4.—Phenetic clustering of CSP sequences using the UPGMA tion of the secondary structures of nucleic acids (Barria et al. method. The optimal tree with the sum of branch length¼ 1.74505027 is 2013). Recently, several other functions of CSPs were de- shown. The percentage of replicate trees in which the associated taxa scribed, such as their assistance in cellular osmotic balance, clustered together in the bootstrap test (1,000 replicates) are shown next to the branches. Analyses was conducted in MEGA7. protection against oxidative stress and starvation (Keto- Timonen et al. 2016). Four chaperone genes were also classiﬁed into the software (ﬁg. 3b). In the dendrogram, P. cryohalolentis and P. “response to stress” group of the GO Biological Processes, arcticus are the most closely related species sharing 49–59% including an ATP-dependent chaperone ClpB and chaperone of nucleotide similarity (ﬁg. 3b). Exiguobacterium antarcticum DnaK (ﬁg. 6b). Studies using the model bacterium Escherichia B7 and E. sibiricum 255-15 shared 38–40% of nucleotide coli have shown that ClpB is a translocase that acts in the similarity (ﬁg. 3b). The other Exiguobacterium genomes absence or presence of DnaK by assisting unfolded or mis- showed higher identity values (80.55–81.64%), although folded proteins in returning to their native structure (Li et al. they have been isolated from different ecological niches (ta- 2015). Despite their importance to cytosol stabilization, ble 1). Strains U131 and MH3 showed low identity with E. Dall’Agnol et al. (2014) showed that ClpB and DnaK of E. antarcticum (12.82% and 12.69%, respectively) and E. sibir- antarcticum B7 are downregulated under low temperatures. icum (13.01% and 12.77%) despite their classiﬁcation in the The most represented biological process among the core same genus. In addition, a high value of split weight was genes was “translation” (38 of the 93 proteins) (ﬁg. 6b). The 736 Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Genomic Architecture of the Two Cold-Adapted Genera Exiguobacterium and Psychrobacter GBE FIG.5.—Venn diagram and bar plots showing the results of the gene distribution calculated in PGAP. (a) Venn diagram with the number of genes shared among Psychrobacter urativorans R10.10B (red), P. cryohalolentis K5 (blue), P. arcticus 273-4 (green), and P. alimentarius PAMC 27889 (purple). (b) Bar plot showing the number of paralogous genes in each strain of Psychrobacter.(c) Venn diagram with the number of genes shared among Exiguobacterium sibiricum 255-15 (red), E. antarcticum B7 (blue), Exiguobacterium sp. MH3 (green), and Exiguobacterium sp. U13-1 (purple). (d) Bar plot showing the number of paralogous genes in each strain of Exiguobacterium.(e) Shared and singleton genes between the species of Exiguobacterium and Psychrobacter. L2 and L3 50 S ribosomal proteins are examples of gene prod- proteins were detected in E. antarcticum B7. Functional de- ucts that are involved in the translation process. The other termination of these hypothetical proteins is one of the main most represented biological processes were transmembrane bottlenecks in the postgenomic era. Bioinformatic approaches transport (9.8%), oxidation–reduction (8.2%), and cellular have been applied to the inference of protein function, such amino acid metabolism (6.2%) (ﬁg. 6b). Thus, much of the as protein–protein interaction networks and homology mod- shared genetic information among Exiguobacterium and eling (Galperin and Koonin 2004; Piovesan et al. 2015). Psychrobacter is composed of housekeeping genes. The main molecular functions described for the core genes were Gene Gain and Loss Analysis ATP binding (27%), structural constituent of ribosome (23%), transferase activity (22.6%), rRNA binding (17.6%), and In the neighbor-joining clustering presented in ﬁgure 7,it is metal ion binding (16.2%) (ﬁg. 6a). shown that E. antarcticum B7 has the lowest genetic content of Many paralogous genes were identiﬁed in all the strains. its genus, followed by E. sibiricum 255-15, Exiguobacterium sp. Psychrobacter cryohalolentis K5, P. alimentarius PAMC MH3, and Exiguobacterium sp. U13-1. The size of the genomes 27889, P. urativorans R10.10B, and P. arcticus 273-4 showed is indicated by the diameter of the circular graph. Additionally, 84, 75, 64, and 50 paralogous genes, respectively (ﬁg. 5b). E. antarcticum B7 is the only species among all genomes ana- Exiguobacterium sibiricum 255-15, Exiguobacterium sp. U13- lysed that lost more gene families than it gained (þ41/114) 1, Exiguobacterium sp.MH3,and E. antarcticum B7 showed (ﬁg. 7). All other species of both cold-adapted genera pre- 103, 88, 70, and 67 paralogous genes, respectively (ﬁg. 5d). sented an increase in the number of gene families compared Fatty acid desaturase proteins were found in the core genes of with their closest ancestor. Therefore, E. antarcticum B7 needs Exiguobacterium species but were absent in the shared genes less genetic information to grow under low temperatures of Psychrobacter. As previously mentioned, this enzyme is when compared with other species of the same genus. regulated by a two-component system, and is involved in The analysis of the subsystem categories performed with the insertion of double carbon bonds in fatty acid chains RAST showed a signiﬁcantly higher number of genes for the linkedtothe cell membrane (Los and Murata 1998; Psychrobacter species classiﬁed in the category “Cofactors, Sakamoto and Murata 2002). A total of 79 hypothetical vitamins, prosthetic groups, pigments” (table 2). The number Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 737 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Dias et al. GBE of genes for biotin biosynthesis were notoriously greater in genes involved in motility and chemotaxis. Genes of this sub- the Psychrobacter species. On the other hand, the system were not detected in the Psychrobacter genomes. This Exiguobacterium species showed a signiﬁcant number of observation is consistent with the lifestyle and ecological niche of each of the two bacterial genera. Exiguobacterium strains have peritrichous ﬂagella being commonly isolated from aquatic ecosystems. Conclusions Cold habitats comprise 20% of Earth’s surface (Fountain et al. 2012) and have been successfully colonized by species from all three domains of life. The importance of these com- munities ranges from their biotechnological applications (Feller 2013) to studies of astrobiology (Pikuta and Hoover 2003). In microbial ecology, several species have been isolated from the poles of our planet and many other psychrotrophic and psy- chrophilic species have been found in environments where cold is uncommon. In our study, we compared the genomes of eight cold-adapted species from Exiguobacterium and Psychrobacter genera. The genetic content of these two genera were quite dis- tinct both functionally and structurally. Nevertheless, one cold shock protein, which is considered essential for survival at low temperatures, were one of the few proteins shared between the genera. The genes coding for CSPs of E. antarcticum B7 were clustered into three groups that are apparently under- going positive selective pressure. The number of genes shared among the species of Psychrobacter is lower than that ob- FIG.6.—Molecular Functions and Biological Processes of gene served for Exiguobacterium, indicating a greater genomic ontology for the 93 genes shared among Exiguobacterium and plasticity of this ﬁrst genus. Interestingly, Psychrobacter has Psychrobacter species. Analysis was performed with Blast2GO software. a more restricted ecological distribution, whereas (a) Level 3 of the molecular functions. (b) Level 3 of the biological Exiguobacterium, with less genomic plasticity, is commonly processes. FIG.7.—Evidence of gene gain and loss using reciprocal BLASTp analysis. The dendrogram was obtained in the BlastGraph software. Bold numbers represent the percentage of bootstrap values. Numbers in each branch of the tree represent the number of gene families that were gained (þ)or lost () compared with their closest ancestor. The circular graph is a graphical representation of the gain/loss analysis. The green color represents the conserved families while the brown color represents the gained families. 738 Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Genomic Architecture of the Two Cold-Adapted Genera Exiguobacterium and Psychrobacter GBE Genome Biol. Evol. 10(3):731–741 doi:10.1093/gbe/evy029 Advance Access publication February 8, 2018 739 Downloaded from https://academic.oup.com/gbe/article-abstract/10/3/731/4846359 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Table 2 Percentage of Genes Distributed According to the Subsystem Category for Each Genome Subsystem Category Number of Features Exiguobacterium E. sibiricum Exiguobacterium Exiguobacterium Psychrobacter P. arcticus P. alimentarius P. urativorans antarcticum B7 255-15 sp. MH3 sp. U13-1 cryohalolentis K5 273-4 PAMC 27889 R10.10B Cofactors, vitamins, prosthetic groups, pigments 5.1% 5.3% 5% 5% 8.9% 8.5% 8.5% 8.5% Cell wall and capsule 3.4% 3.3% 2.8% 3.3% 4.7% 4.8% 4.1% 4.1% Virulence, disease, and defense 1.8% 1.7% 1.9% 1.9% 2.6% 2.2% 1.9% 1.9% Potassium metabolism 0.4% 0.4% 0.5% 0.5% 0.5% 0.6% 0.6% 0.6% Photosynthesis 0.1% 0% 0.1% 0.09% 0% 0% 0% 0% Miscellaneous 0.9% 0.8% 0.9% 0.9% 1.1% 0.8% 1% 1% Phages, prophages, transposable elements, plasmids 0.06% 0.09% 0.3% 0.06% 0% 0.5% 0.5% 0.5% Membrane transport 2.6% 0.02% 2.9% 2.9% 3.1% 2.9% 2.4% 2.4% Iron acquisition and metabolism 0.6% 0.7% 0.9% 0.8% 0.6% 0.2% 0.2% 0.2% RNA metabolism 4.5% 4.5% 4.3% 4.3% 6.5% 6.8% 6.7% 6.7% Nucleosides and nucleotides 3.9% 3.7% 3.6% 3.5% 3.5% 5.2% 3.3% 3.3% Protein metabolism 6.8% 5.8% 7.7% 7.5% 9.2% 9.5% 8.5% 8.5% Cell division and cell cycle 1.6% 1.4% 1.4% 1.4% 1.2% 1.3% 1.3% 1.3% Motility and chemotaxis 2.5% 2.3% 2.3% 2.3% 0% 0% 0% 0% Regulation and cell signaling 1.4% 1.6% 1.4% 1.6% 2.2% 1.8% 2.3% 2.3% Secondary metabolism 0.1% 0.1% 0.1% 0.1% 0.1% 0.2% 0.2% 0.2% DNA metabolism 2.2% 2.3% 2% 2% 3.9% 3.7% 3.1% 3.1% Fatty acids, lipids, and isoprenoids 4.1% 3.9% 3.9% 3.9% 5.3% 5.3% 4.7% 4.7% Nitrogen metabolism 0.4% 0.5% 0.4% 0.4% 0.6% 0.9% 0.6% 0.6% Dormancy and sporulation 0.4% 0.4% 0.4% 0.4% 0.07% 0% 0.1% 0.1% Respiration 1.6% 1.8% 1.5% 1.5% 4.2% 4.0% 4.2% 4.2% Stress response 2.8% 2.8% 2.6% 2.6% 3.6% 3.5% 3.4% 3.4% Metabolism of aromatic compounds 0.1% 0.1% 0.2% 0.2% 1.0% 0.3% 0.2% 0.2% Amino acids and derivatives 10.3% 9.8% 8.8% 8.8% 13.4% 11.1% 12.4% 12.4% Sulfur metabolism 0.3% 0.3% 0.3% 0.3% 0.8% 0.9% 0.9% 0.9% Phosphorous metabolism 1.4% 1.2% 1.1% 1.1% 1.1% 1.1% 1.3% 1.3% Carbohydrates 9.2% 10.5% 10.6% 10.5% 8.1% 8.1% 6.7% 6.7% NOTE.—Only the names of the strains are presented in the table. 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