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  • Short genome report
  • Open Access

Complete genome sequence of Salinicoccus halodurans H3B36, isolated from the Qaidam Basin in China

Standards in Genomic Sciences201510:116

  • Received: 19 June 2015
  • Accepted: 4 September 2015
  • Published:


Salinicoccus halodurans H3B36 is a moderately halophilic bacterium isolated from a sediment sample of Qaidam Basin at 3.2 m vertical depth. Strain H3B36 accumulate N α-acetyl-α-lysine as compatible solute against salinity and heat stresses and may have potential applications in industrial biotechnology. In this study, we sequenced the genome of strain H3B36 using single molecule, real-time sequencing technology on a PacBio RS II instrument. The complete genome of strain H3B36 was 2,778,379 bp and contained 2,853 protein-coding genes, 12 rRNA genes, and 61 tRNA genes with 58 tandem repeats, six minisatellite DNA sequences, 11 genome islands, and no CRISPR repeat region. Further analysis of epigenetic modifications revealed the presence of 11,000 m4C-type modified bases, 7,545 m6A-type modified bases, and 89,064 other modified bases. The data on the genome of this strain may provide an insight into the metabolism of N α-acetyl-α-lysine.


  • Qaidam Basin
  • Moderately halophilic
  • Salinicoccus halodurans strain
  • Staphylococcaceae
  • Genome sequencing


Moderately halophilic bacteria are a group of halophilic microorganisms that grow optimally in media containing between 3 % and 15 % (w/v) NaCl. These bacteria exhibit strong salt tolerance and are widely distributed in different high-salt habitats, such as hypersaline soils and lakes, solar salterns, and salted foods [1, 2]. To cope with the hyperosmotic conditions, these microorganisms accumulate large quantities of inorganic ions, such as K+ and Cl, or a particular group of organic osmolytes [3, 4], such as sugars (trehalose and sucrose), sugar derivatives (glucosylglycerol and mannosylglycerate), polyols (glycerol and arabitol), phosphodiesters (di-myo-inositol phosphate), amino acids (proline, α-glutamate, and β-glutamate), and derivatives (betaine and ectoine) [58]. In strain H3B36, which was isolated from subsurface saline soil (3.2-m depth) in Qaidam Basin in the Qinghai province, China, we detected a special compound, N α-acetyl-α-lysine, that acts as an organic osmolyte and thermolyte (authors’ unpublished observation). The amount of N α-acetyl-α-lysine in the cell was increased and could be accumulated to a high level when strain H3B36 was subjected to salt stress or heat stress. Unlike other compatible solutes, N α-acetyl-α-lysine has only been found to date in Salinibacter ruber to date, and the molecular mechanisms through which this compound is synthesized and stored are unclear [9, 10].

Based on analysis of the 16S rRNA gene sequence, this strain is most closely related to Salinicoccus halodurans W24T (= CGMCC 1.6501T = DSM 19336T ) [11]. The genus Salinicoccus , which was first described by Ventosa et al. [12, 13], belongs to the family Staphylococcaceae . To date, 16 validly named species of Salinicoccus have been identified; however, only six genome sequences are available. All species of the genus Salinicoccus are defined as moderately halophilic bacteria. These organisms may have potential applications in various fields, including as additives in the food industry; for production of polymer compounds, enzymes, and stress protectants; and in environmental protection and biodegradation [1419].

To obtain insights into the metabolic pathway of N α-acetyl-α-lysine and explore the genome of the Salinicoccus spp, we performed complete genome sequence analysis and annotation of Salinicoccus halodurans H3B36.

Organism information

Classification and features

Strain H3B36 (Table 1) was isolated from a subsurface saline soil sample (3.2 m depth) from the Qaidam Basin of China by enriching in liquid medium at 37 °C and then plating on agar medium until single colonies were obtained. The 16S rRNA gene sequence of strain H3B36 and other available 16S rRNA gene sequences of closely related species collected from the EzTaxon-e database were used to construct a phylogenetic tree (Fig. 1) [20]. CLUSTAL_X was used to generate alignments [21]. After trimming, the alignments were converted to the MEGA format, and a phylogenetic tree was constructed. The evolutionary history was inferred using the maximum likelihood method based on the Kimura 2-parameter model within MEGA software version 5.10 [22, 23]. Taxonomic analysis showed that strain H3B36 was most closely related to Salinicoccus halodurans W24 T with 99.9 % 16S rRNA gene sequence identity, and as such, strain H3B36 was classified as a strain of Salinicoccus halodurans .
Table 1

Classification and general features of Salinicoccus halodurans H3B36 according to the MIGS recommendations [44]




Evidence codea



Domain Bacteria

TAS [45]


Phylum Firmicutes

TAS [46]


Class Bacilli

TAS [47, 48]


Order Bacillales

TAS [49, 50]


Family Staphylococcaceae

TAS [48, 51]


Genus Salinicoccus

TAS [12, 13]


Species Salinicoccus halodurans

TAS [11]


Strain H3B36



Gram stain


TAS [11]


Cell shape






TAS [11]




TAS [11]


Temperature range

4-42 °C



Optimum temperature

28-30 °C



pH range; Optimum

5.5-9.0; 7.5



Carbon source





subsurface saline soil (3.2 m depth)



Salinity range;

2-18 % NaCl (w/v)



Oxygen requirement




Biotic relationship








Geographic location

China: Qaidam basin



Sample collection





37.06 N




94.73 E




2674 m


aEvidence codes- IDA inferred from direct assay, TAS traceable author statement, NAS non-traceable author statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project [29]

Fig. 1
Fig. 1

Phylogenetic tree based on the 16S rRNA gene showing the position of Salinicoccus halodurans H3B36 relative to other species in the genus Salinicoccus. Staphylococcus aureus was used as an outgroup. The analysis involved 18 nucleotide sequences, and there were a total of 1394 positions in the final dataset. GenBank accession numbers for the sequences of each strain are indicated in parentheses. The maximum likelihood algorithm based on the Kimura 2-parameter model was used to construct the phylogenetic consensus tree. All positions containing missing data and gaps were eliminated. Numbers next to the branches represent the bootstrap values obtained by repeating the analysis 1000 times, and values of less than 70 % are not shown at the nodes. The tree is drawn to scale, with branch lengths indicating the number of substitutions per site

The cell morphology of strain H3B36 was determined using scanning electron microscopy (Fig. 2). Microscopically, cells of strain H3B36 were spherical and measured approximately 0.9 μm in diameter. Cells occurred singly or in pairs, tetrads, or irregular clumps at early growth stages. Colonies on GMH agar medium were white, opaque, circular, and slight convex. Cells were able to grow at a temperature range from 4 to 42 °C, with optimum growth observed around 30 °C in GMH medium. Analysis of growth in GMH medium with different NaCl concentrations, the strain grew well when NaCl ranged from 2 to 18 % (w/v) and could not grow in medium without NaCl or with NaCl at concentrations of more than 20 % (w/v). Optimal growth occurred between 4 % and 6 % (w/v) NaCl.
Fig. 2
Fig. 2

Scanning electron micrographs of Salinicoccus halodurans H3B36 using field-emission scanning electron microscopy (Hitachi SU8010, Japan)

Genome sequencing information

Genome project history

Salinicoccus halodurans H3B36 was selected for genome sequencing because we observed the presence of a unique compatible solute for protection and potential industrial applications. The complete genome sequence has been deposited in GenBank under the accession number CP011366. Sequencing, annotation, and analysis were performed at WUHAN Institute of Biotechnology, China. The project information and its association with MIGS version 2.0 are shown in Table 2.
Table 2

Genome sequencing project information





Finishing quality



Libraries used



Sequencing platforms

PacBio RS II

MIGS 31.2

Fold coverage




HGAP2.2.0 workflow


Gene calling method



Locus Tag



GenBank ID



GenBank Date of Release

May 11, 2015





BioProject ID



Source Material Identifier

Strain H3B36


Project relevance

Environmental and biotechnological

Growth conditions and genomic DNA preparation

Salinicoccus halodurans H3B36 was grown aerobically in GMH medium containing 5 g/L casamino acid, 5 g/L yeast extract, 4 g/L MgSO4 · 7H2O, 2 g/L KCl, 0.036 g/L FeSO4 · 7H2O, 0.36 mg/L MnCl2 · 7H2O, and 60 g/L NaCl, at pH 7.0 (titrated with 1 M NaOH). Genomic DNA from freshly grown cells harvested in the exponential growth phase was extracted using the QIAGEN Genomic DNA Buffer Set and QIAGEN Genomic-tip 100/G according to the manufacturer’s protocols. The prepared DNA was evaluated on a 0.75 % agarose gel to verify the integrity of the molecular weight fragments. Qualification and quantification of the prepared DNA sample was measured with a NanoDrop instrument (Thermo Scientific, Wilmington, MA, USA) and Qubit (Life Technologies, Grand Island, NY, USA) to confirm the suitability of the DNA sample for high-throughput next-generation sequencing.

Genome sequencing and assembly

The genome of Salinicoccus halodurans H3B36 was sequenced using third-generation sequencing technology on a PacBio RS II instrument. The analysis produced a total of 573,153,827 bp, and 54,457 post-filter reads with a mean length of 10,524 bp were obtained. The Hierarchical Genome Assembly Processing pipeline, version 2.2.0, was used to assemble the genome [2426]. Long reads were selected as the seed sequences for constructing preassemblies, and the other short reads were mapped to the seeds using BLASTR software for alignment, which corrected the errors in the long reads and thus increased the accuracy rating of bases more than 99 %. Based on this analysis, we obtained 95.7 M high-quality reads with an average length of 12,910 bp. Using the overlap-layout-consensus (OLC) algorithms to debug the parameters, we adopted Celera assembler software for assembly. To improve the assembly, the raw data were mapped to the assembled reference sequence to remove any fine-scale errors using Quiver software. Low-depth contigs were then removed, and the rest of the contigs were connected using Minumus2 software. Finally, the data were assembled de novo to one final 2,778,378-bp complete contig with 212 × depth of coverage.

Genome annotation

The RAST Prokaryotic Genome Annotation Server was used to predict protein-coding open reading frames, tRNAs, and structural RNA genes [27]. The Cluster of Orthologous Groups, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Swiss-Prot, and Non-Redundant Protein databases were used to annotate the predicted genes [2832]. Pfam databases were used to predicted genes with conserved domains [33]. Transmembrane helices and signal peptides were identified using TMHMM and SignalP, version4.1, respectively [34, 35]. Tandem Repeat Finder software was used to predict tandem repeat sequences, and Misa software was used to find the minisatellite DNA sequences [36]. Genome islands were analyzed using IslandViewer software, which integrates three software programs (IslandPick, SIGI-HMM, and IslandPath-DIMOB) and combines the Virulence Factor and Antibiotic Resistance Gene databases [37, 38]. In addition, the CRISPR motif was identified using CRISPR II software [39]. Analysis of the raw data was performed to identify loci having epigenetic modifications (i.e., m4C, m6A, and other modification) due to the dynamic characteristics of the raw data [40, 41]. The Restriction Enzyme Database was used to identify the genes involved in the restriction modification system [42].

Genome properties

The complete genome sequence of Salinicoccus halodurans H3B36 was found to be 2,778,378 bp and had a G + C content of 44.54 %. No plasmids were found. RAST predicted 2,853 coding sequences, 61 tRNA genes, and 16 structural RNA genes. The predicted CDSs represented 88.79 % of the total genome sequence, with an average length of 864.72 bp. Genome analysis showed that the genome of strain H3B36 contained 58 tandem repeats, six minisatellite DNA sequences, and 11 genome islands. Further analysis of epigenetic modifications revealed 11,000 m4C-type modified bases, 7,545 m6A-type modified bases, and 89,064 other modified bases in the genome. Furthermore, several restriction modification genes were found, with eight belonging to the type I system, three belonging to the type II system, and one belonging to the type IV system. The genome statistics and gene distributions into COG functional categories are presented in Tables 3 and 4, respectively. The circular representation of the bacterial genome was drawn using CGview software (Fig. 3) [43].
Table 3

Genome statistics



% of Total

Genome size (bp)



DNA coding (bp)



DNA G + C (bp)



DNA scaffolds



Total genes



Protein coding genes



RNA genes



Pseudo genes



Genes in internal clusters



Genes with function prediction



Genes assigned to COGs



Genes with Pfam domains



Genes with signal peptides



Genes with transmembrane helices



CRISPR repeats



a N/D, not determined

Table 4

Number of genes associated COG functional categories of Salinicoccus halodurans H3B36



% age





Translation, ribosomal structure and biogenesis




RNA processing and modification








Replication, recombination and repair




Chromatin structure and dynamics




Cell cycle control, Cell division, chromosome partitioning




Defense mechanisms




Signal transduction mechanisms




Cell wall/membrane biogenesis




Cell motility




Intracellular trafficking and secretion




Posttranslational modification, protein turnover, chaperones




Energy production and conversion




Carbohydrate transport and metabolism




Amino acid transport and metabolism




Nucleotide transport and metabolism




Coenzyme transport and metabolism




Lipid transport and metabolism




Inorganic ion transport and metabolism




Secondary metabolites biosynthesis, transport and catabolism




General function prediction only




Function unknown




Not in COGs

The total is based on the total number of protein coding genes in the annotated genome

Fig. 3
Fig. 3

Circular chromosome map of Salinicoccus halodurans H3B36. From inner to outer: 1, GC skew (GC Skew is calculated using a sliding window, as (G – C) / (G + C), with the value plotted as the deviation from the average GC skew of the entire sequence); 2, GC content (plotted using a sliding window, as the deviation from the average GC content of the entire sequence); 3, tRNA/rRNA; 4 and 5, CDS (colored according to COG function categories, where 4 is the reverse strand and 5 is the forward strand); 6 and 7, m4C and m6A sites in CDS/rRNA/tRNA (6 is the reverse strand and 7 is the forward strand); and 8, m4C and m6A sites in intergene regions

Insights from the genome sequence

Genome analysis showed that Salinicoccus halodurans H3B36 contained many genes related to the stress response, such as choline and betaine transporters, glycerol uptake facilitator protein, cold-shock protein, chaperones proteins, and others. These genes allowed the strain to cope with different environmental stresses. Experimentation and additional analysis of these genes may help to elucidate the mechanisms mediating the stress response and facilitate the development of Salinicoccus halodurans H3B36 for use in industry applications. In addition, several genes encoding hydrolases, including amylase (1), protease (19), pullulanase (2), lipase (3), phosphoesterase (5), and glucosidase (4), were identified in the genome. Hydrolases are highly valuable resources for some specific industrial processes, and hydrolases from various extremophiles may have many advantages [14, 19]. These results indicated that Salinicoccus halodurans H3B36 might have the potential for application in industrial biotechnology as a producer of miscellaneous hydrolases.

N α-acetyl-α-lysine was found play a key role in protecting Salinicoccus halodurans H3B36 cells under different stresses (unpublished observation by Kai Jiang, Yanfen Xue and Yanhe Ma). Genome annotations showed that lysine may be synthesized through the acetyl-dependent diaminopimelic acid pathway in Salinicoccus halodurans H3B36. One 8-kb gene cluster containing eight genes was predicted to be involved in N α-acetyl-α-lysine biosynthesis. Six genes in the cluster map to enzymes in the acetyl-dependent diaminopimelic acid pathway, including the genes encoding aspartokinase, aspartate-semialdehyde dehydrogenase, dihydrodipicolinate synthase, dihydrodipicolinate reductase, 2,3,4,5-tetrahydropyridine-2,6-dicarboxylate N-acetyltransferase and diaminopimelate decarboxylase. N α-acetyl-α-lysine is a derivative of lysine, so this gene cluster may participate in the synthesis of N α-acetyl-α-lysine. Further studies are required to verify this assumption and identify the metabolic pathway mediating N α-acetyl-α-lysine biosynthesis in Salinicoccus halodurans H3B36.


This is the first report describing the genome sequence of Salinicoccus halodurans . The genome size of Salinicoccus halodurans H3B36 (2.78 M) is larger than the other sequenced members of genus Salinicoccus including Salinicoccus sp. SV-16 (2.59 M), Salinicoccus luteus DSM 17002T (2.55 M), Salinicoccus albus DSM 19776T (2.64 M), Salinicoccus carnicancri CrmT (2.67 M), and Salinicoccus roseus W12 (2.56 M). Salinicoccus halodurans H3B36 has a G + C content (44.5 %) higher than Salinicoccus albus DSM 19776T but lower than those of Salinicoccus carnicancri CrmT, Salinicoccus sp. SV-16, Salinicoccus luteus DSM 17002T , and Salinicoccus roseus strain W12 (47.9 %, 48.7 %, 49.1 % and 50.0 %, respectively). Further comparative genomic study shows that the N α-acetyl-α-lysine related gene cluster is also found in other sequenced members of genus Salinicoccus . The gene cluster in Salinicoccus sp. SV-16, Salinicoccus luteus DSM 17002T , Salinicoccus carnicancri CrmT, and Salinicoccus roseus W12 containing eight genes are similar to that in Salinicoccus halodurans H3B36. Salinicoccus albus DSM 19776T has a slight discrepancy, which lacks aspartokinase in its gene cluster. The genome of Salinicoccus halodurans H3B36 provides important insights into our understanding of the metabolism of N α-acetyl-α-lysine. Furthermore, the sequence of Salinicoccus halodurans H3B36 provides useful information and may contribute to facilitate applications of genus Salinicoccus in industrial biotechnology.



The Hierarchical Genome Assembly Processing


Rapid Annotation using Subsystem Technology



This work was supported by the Ministry of Sciences and Technology of China (grant nos. 2011CBA00800, 2013CBA733900, 2012AA022100, and 2011AA02A206).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

State Key Laboratory of Microbial Resources and National Engineering Laboratory for Industrial Enzymes, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China


  1. Kushner DJ, Kamekura M. Physiology of halophilic eubacteria. In: Rodriguez-Valera F, editor. Halophilic bacteria. Boca Ratón: CRC Press; 1988. p. 109–40.Google Scholar
  2. Ventosa A. Taxonomy of moderately halophilic heterotrophic eubacteria. In: Rodriguez-Valera F, editor. Halophilic bacteria. Boca Ratón: CRC Press; 1988. p. 71–84.Google Scholar
  3. Galinski EA, Trüper HG. Microbial behaviour in salt-stressed ecosystems. FEMS Microbiol Rev. 1994;15:95–108.View ArticleGoogle Scholar
  4. Roberts MF. Organic compatible solutes of halotolerant and halophilic microorganisms. Saline Systems. 2005;1:5.PubMed CentralView ArticlePubMedGoogle Scholar
  5. Severin J, Wohlfarth A, Galinski EA. The predominant role of recently discovered tetrahydropyrimidines for the osmoadaptation of halophilic eubacteria. J Gen Microbiol. 1992;138:1629–38.View ArticleGoogle Scholar
  6. da Costa MS, Santos H, Galinski EA. An overview of the role and diversity of compatible solutes in Bacteria and Archaea. Adv Biochem Eng Biotechnol. 1998;61:117–53.PubMedGoogle Scholar
  7. Oren A. Microbial life at high salt concentrations: phylogenetic and metabolic diversity. Saline Systems. 2008;4:2.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Klahn S, Hagemann M. Compatible solute biosynthesis in cyanobacteria. Environ Microbiol. 2011;13:551–62.View ArticlePubMedGoogle Scholar
  9. Oren A, Heldal M, Norland S, Galinski EA. Intracellular ion and organic solute concentrations of the extremely halophilic bacterium Salinibacter ruber. Extremophiles. 2002;6:491–8.View ArticlePubMedGoogle Scholar
  10. Antón J, Oren A, Benlloch S, Rodríquez-Valera F, Amann R, Rosselló-Mora R. Salinibacter ruber gen. nov., sp. nov., a novel, extremely halophilic member of the Bacteria from saltern crystallizer ponds. Int J Syst Evol Microbiol. 2002;52:485–91.View ArticlePubMedGoogle Scholar
  11. Wang XW, Xue YF, Yuan SQ, Zhou C, Ma YH. Salinicoccus halodurans sp. nov., a moderate halophile from saline soil in China. Int J Syst Evol Microbiol. 2008;58:1537–41.View ArticlePubMedGoogle Scholar
  12. Validation List no. 34. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol. 1990;40:320–321.
  13. Ventosa A, Márquez MC, Ruizberraquero MC, Kocur M. Salinicoccus roseus gen. nov, sp. Nov, a new moderately halophilic gram-positive coccus. Syst Appl Microbiol. 1990;13:29–33.View ArticleGoogle Scholar
  14. Margesin R, Schinner F. Potential of halotolerant and halophilic microorganisms for biotechnology. Extremophiles. 2001;5:73–83.View ArticlePubMedGoogle Scholar
  15. Tokunaga H, Ishibashi M, Arakawa T, Tokunaga M. Highly efficient renaturation of beta-lactamase isolated from moderately halophilic bacteria. Febs Letters. 2004;558:7–12.View ArticlePubMedGoogle Scholar
  16. Le Borgne S, Paniagua D, Vazquez-Duhalt R. Biodegradation of organic pollutants by halophilic bacteria and archaea. J Mol Microbiol Biotechnol. 2008;15:74–92.View ArticlePubMedGoogle Scholar
  17. Harishchandra RK, Wulff S, Lentzen G, Neuhaus T, Galla HJ. The effect of compatible solute ectoines on the structural organization of lipid monolayer and bilayer membranes. Biophys Chem. 2010;150:37–46.View ArticlePubMedGoogle Scholar
  18. Lentzen G, Schwarz T. Extremolytes: Natural compounds from extremophiles for versatile applications. Appl Microbiol Biotechnol. 2006;72:623–34.View ArticlePubMedGoogle Scholar
  19. Ventosa A, Nieto JJ. Biotechnological applications and potentialities of halophilic microorganisms. World J Microbiol Biotechnol. 1995;11:85–94.View ArticlePubMedGoogle Scholar
  20. Kim OS, Cho YJ, Lee K, Yoon SH, Kim M, Na H, et al. Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. Int J Syst Evol Microbiol. 2012;62:716–21.View ArticlePubMedGoogle Scholar
  21. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–80.PubMed CentralView ArticlePubMedGoogle Scholar
  22. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol. 1981;17:368–76.View ArticlePubMedGoogle Scholar
  23. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Mol Biol Evol. 2011;128:2731–9.View ArticleGoogle Scholar
  24. Chin CS, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods. 2013;10:563–9.View ArticlePubMedGoogle Scholar
  25. Chaisson MJ, Tesler G. Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics. 2012;13(1):238.PubMed CentralView ArticlePubMedGoogle Scholar
  26. Miller JR, Delcher AL, Koren S, Venter E, Walenz BP, Brownley A, et al. Aggressive assembly of pyrosequencing reads with mates. Bioinformatics. 2008;24(24):2818–24.PubMed CentralView ArticlePubMedGoogle Scholar
  27. 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(1):75.PubMed CentralView ArticlePubMedGoogle Scholar
  28. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28:33–6.PubMed CentralView ArticlePubMedGoogle Scholar
  29. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nat Genet. 2000;25:25–9.PubMed CentralView ArticlePubMedGoogle Scholar
  30. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32 suppl 1:D277–80.PubMed CentralView ArticlePubMedGoogle Scholar
  31. Magrane M, Consortium U. UniProt Knowledgebase: a hub of integrated protein data. Database J. Biol Databases Curation. 2011; 2011: bar009.Google Scholar
  32. Pruitt KD, Tatusova T, Brown GR, Maglott DR. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Res. 2012;40:D130–5.PubMed CentralView ArticlePubMedGoogle Scholar
  33. Finn RD, Mistry J, Tate J, Coggill P, Heger A, Pollington JE, et al. The Pfam protein families database. Nucleic Acids Res. 2010;38:D211–22.PubMed CentralView ArticlePubMedGoogle Scholar
  34. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001;305:567–80.View ArticlePubMedGoogle Scholar
  35. Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6.View ArticlePubMedGoogle Scholar
  36. Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573–80.PubMed CentralView ArticlePubMedGoogle Scholar
  37. Langille MGI, Brinkman FSL. IslandViewer: an integrated interface for computational identification and visualization of genomic islands. Bioinformatics. 2009;25(5):664–5.PubMed CentralView ArticlePubMedGoogle Scholar
  38. Juhas M, van der Meer JR, Gaillard M, Harding RM, Hood DW, Crook DW. Genomic islands: tools of bacterial horizontal gene transfer and evolution. FEMS Microbiol Rev. 2009;33(2):376–93.PubMed CentralView ArticlePubMedGoogle Scholar
  39. Grissa I, Vergnaud G, Pourcel C. The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformatics. 2007;8(1):172.PubMed CentralView ArticlePubMedGoogle Scholar
  40. Flusberg BA, Webster DR, Lee JH, Travers KJ, Olivares EC, Clark TA, et al. Direct detection of DNA methylation during single-molecule, real-time sequencing. Nat Methods. 2010;7(6):461–U72.PubMed CentralView ArticlePubMedGoogle Scholar
  41. Davis BM, Chao MC, Waldor MK. Entering the era of bacterial epigenomics with single molecule real time DNA sequencing. Curr Opin Microbiol. 2013;16(2):192–8.PubMed CentralView ArticlePubMedGoogle Scholar
  42. Roberts RJ, Vincze T, Posfai J, Macelis D. REBASE-a database for DNA restriction and modification: enzymes, genes and genomes. Nucleic Acids Res. 2015;43:D298–9.PubMed CentralView ArticlePubMedGoogle Scholar
  43. Stothard P, Wishart DS. Circular genome visualization and exploration using CGView. Bioinformatics. 2005;21(4):537–9.View ArticlePubMedGoogle Scholar
  44. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26:541–7.PubMed CentralView ArticlePubMedGoogle Scholar
  45. Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87:4576–9.PubMed CentralView ArticlePubMedGoogle Scholar
  46. Gibbons NE, Murray RGE. Proposals concerning the higher taxa of bacteria. Int J Syst Bacteriol. 1978;28:1–6.View ArticleGoogle Scholar
  47. Murray RGE. The Higher Taxa, or, a Place for Everything…? Bergey's Manual of Systematic Bacteriology. 1984;1:31–4.Google Scholar
  48. Validation List 132. List of new names and new combinations previously effectively, but not validly, published. Int J Syst Evol Microbiol. 2010;60:469–472.Google Scholar
  49. Hauderoy P, Ehringer G, Guillot G, Magrou J, Prévot AR, Rossetti D, et al. Dictionnaire des Bactéries Pathogènes. 2nd ed. Paris: Masson et Cie; 1953.
  50. Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol. 1980;30:225–420.View ArticleGoogle Scholar
  51. Schleifer KH, Bell JA. Family VIII. Staphylococcaceae fam. nov. In: De Vos P, Garrity G, Jones D, Krieg NR, Ludwig W, Rainey FA, et al., editors. Bergey's Manual of Systematic Bacteriology. New York: Springer; 2009. p. 392.Google Scholar


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