Open Access

Complete genome sequence of Thalassolituus oleivorans R6-15, an obligate hydrocarbonoclastic marine bacterium from the Arctic Ocean

Standards in Genomic Sciences20149:9030893

DOI: 10.4056/sigs.5229330

Published: 15 June 2014

Abstract

Strain R6-15 belongs to the genus Thalassolituus, in the family Oceanospirillaceae of Gammaproteobacteria. Representatives of this genus are known to be the obligate hydrocarbonoclastic marine bacteria. Thalassolituus oleivorans R6-15 is of special interest due to its dominance in the crude oil-degrading consortia enriched from the surface seawater of the Arctic Ocean. Here we describe the complete genome sequence and annotation of this strain, together with its phenotypic characteristics. The genome with size of 3,764,053 bp comprises one chromosome without any plasmids, and contains 3,372 protein-coding and 61 RNA genes, including 12 rRNA genes.

Keywords

Thalassolituus genome alkane-degrading surface seawater Arctic Ocean

Introduction

Thalassolituus spp. belong to the Oceanospirillaceae of Gammaproteobacteria. The genus was first described by Yakimov et al. (2004), and is currently composed of two type species, T. oleivorans and T. marinus [1,2]. Bacteria of this genus are known as obligate hydrocarbonoclastic marine bacteria [3]. Previous reports showed that Thalassolituus-related species were among the most dominant members of the petroleum hydrocarbon-enriched consortia at low temperature [47]. In addition to consortia enriched with oil, Thalassolituus spp. can be detected in variety of cold environments as well [810].

Strain R6-15 was isolated from the surface seawater of the Arctic Ocean after enriched with crude oil during the fourth Chinese National Arctic Research Expedition of the “Xulong” icebreaker in the summer of 2010. The 16S rRNA gene sequence shared 99.86% and 96.39% similarities with T. oleivorans MIL-1T and T. marinus IMCC1826T, respectively. Pyrosequencing results (16S rRNA gene V3 region) of fifteen oil-degrading consortia across the Arctic Ocean showed that the dominant member in most of the consortia shared identical sequence of this strain, comprising 8.4–99.6% of the total reads (not published).

Here, we described the complete genome sequence and annotation of strain T. oleivorans R6-15, and its phenotypic characteristics. Moreover, a brief comparison was made between strain R6-15 and the two type strains of the validly named species of this genus, in both phenotypic and genomic aspects.

Classification and features

T. oleivorans R6-15 is closely related with T. oleivorans MIL-1T (Figure 1, Table 1). The strain is aerobic, Gram-negative and motile by a single polar flagellum, exhibiting a characteristic morphology of a curved rod-shape cell (Figure 2). Strain R6-15 is able to utilize a restricted spectrum of carbon substrates for growth, including sodium acetate, Tween-40, Tween-80 and C12–C36 aliphatic hydrocarbons. Its growth temperature ranges from 4 to 32°C with optimum of 25°C.
Figure 1.

Phylogenetic tree highlighting the position of T. oleivorans strain R6-15 relative to other type and non-type strains with finished or non-contiguous finished genome sequences within the family Oceanospirillaceae. Accession numbers of 16S rRNA gene sequences are indicated in brackets. Sequences were aligned using DNAMAN version 6.0, and a neighbor-joining tree obtained using the maximum-likelihood method within the MEGA version 5.0 [11]. Numbers adjacent to the branches represent percentage bootstrap values based on 1,000 replicates.

Figure 2.

Transmission electron micrograph of T. oleivorans R6-15, using a JEM-1230 (JEOL) at an operating voltage of 120 kV. The scale bar represents 0.5 µm.

Table 1.

Classification and general features of T. oleivorans R6-15 according to the MIGS recommendations [12].

MIGS ID

Property

Term

Evidence codea

 

Current classification

Domain Bacteria

TAS [13]

 

Phylum Proteobacteria

TAS [14]

 

Class Gammaproteobacteria

TAS [1517]

 

Order Oceanospirillales

TAS [16,18]

 

Family Oceanospirillaceae

TAS [16,19]

 

Genus Thalassolituus

TAS [1]

 

Species Thalassolituus oleivorans

IDA

 

Gram stain

Negative

IDA

 

Cell shape

Curved rods

IDA

 

Motility

Motile

IDA

 

Sporulation

Non-sporulating

IDA

 

Temperature range

4–32°C

IDA

 

Optimum temperature

25°C

IDA

 

Carbon source

Sodium acetate, Tween-40, Tween-80, alkanes (C12-C36)

IDA

 

Energy source

Chemoorganotrophic

IDA

 

Terminal electron receptor

Oxygen

IDA

MIGS-6

Habitat

Surface seawater

IDA

MIGS-6.3

Salinity

0.5–5% NaCl (w/v)

IDA

MIGS-22

Oxygen

Aerobic

IDA

MIGS-15

Biotic relationship

Free-living

IDA

MIGS-14

Pathogenicity

Unknown

NAS

MIGS-4

Geographic location

Chukchi Sea, Arctic Ocean

IDA

MIGS-5

Sample collection time

July 2010

IDA

MIGS-4.1

Latitude

69°30.00′

IDA

MIGS-4.2

Longitude

-168°59.00′

IDA

MIGS-4.3

Depth

Surface seawater

IDA

MIGS-4.4

Altitude

Sea level

IDA

a) Evidence codes - IDA: Inferred from Direct Assay; TAS: Traceable Author Statement (i.e., a direct report exists in the literature); 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 [20]. If the evidence code is IDA, then the property should have been directly observed, for the purpose of this specific publication, for a live isolate by one of the authors, or an expert or reputable institution mentioned in the acknowledgements.

When compared to other Thalassolituus species, strain R6-15 differed from type strain MIL-1T [1] in catalase, urease and acid phosphatase, and in the utilization of n-alkane, pyruvic acid methyl ester, D-mannitol and D-sorbitol (Table 2). Differences were also observed with type strain IMCC1826T [2] in growth temperature range, catalase, nitrate reductase, urease and leucine arylamidase and the utilization of n-alkane, pyruvic acid methyl ester, β-Hydroxybutyric acid and D,L-Lactic acid (Table 2).
Table 2.

Differential phenotypic characteristics between T. oleivorans R6-15 and other Thalassolituus species.

Characteristic

1

2

3

Cell diameter (µm)

0.25–0.4 × 1.2–2.0

0.32–0.77 × 1.2–3.1

0.4–0.5 × 1.2–2.5

Salinity/Optimum (w/v)

0.5–5%/3%

0.5–5.7%/2.3%

0.5–5.0%/2.5%

Temperature range (°C)

4–32

4–30

15–42

Number of polar flagella

1

1–4

1

Production of

   

Catalase

+

+

Nitrate reductase

+

Urease

w

+

Acid phosphatase

+

+

Leucine arylamidase

+

+

Carbon source

   

Sodium acetate

+

+

na

n-alkane

C12-C36

C7-C20

C14 and C16

Pyruvic acid methyl ester

w

+

β-Hydroxybutyric acid

+

D,L-Lactic acid

+

D-Mannitol

+

D-Sorbitol

+

Geographic location

Chukchi Sea, Arctic Ocean

Harbor of Milazzo, Italy

Deokjeok island, Korea

Habitat

surface seawater

seawater/sediment

surface seawater

G+C content (mol%)

46.6

46.6

54.6

Strains: 1, T. oleivorans R6-15; 2, T. oleivorans MIL-1T; 3, T. marinus IMCC1826T. +: positive result, −: negative result, w: weak positive result, na: data not available.

Genome sequencing information

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position and dominance position in the crude oil-degrading consortia enriched from the surface seawater of the Arctic Ocean. The complete genome sequence was deposited in Genbank under accession number CP006829. Sequencing, finishing and annotation of the T. oleivorans R6-15 genome were performed by the Chinese National Human Genome Center (Shanghai). Table 3 presents the project information and its association with MIGS version 2.0 compliance [21].
Table 3.

Project information

MIGS ID

Property

Term

MIGS-31

Finishing quality

Finished

MIGS-28

Libraries used

one 454 pyrosequence standard library

MIGS-29

Sequencing platforms

454 GS FLX Titanium

MIGS-31.2

Fold coverage

21.1 ×

MIGS-30

Assemblers

Newbler version 2.7

MIGS-32

Gene calling method

NCBI PGAP pipeline

 

GenBank ID

CP006829

 

GenBank Date of Release

On publication

 

GOLD ID

Gi20060

 

Project relevance

Crude oil-degradation, biogeography

Growth conditions and DNA isolation

Strain R6-15 was grown aerobically in ONR7a medium [22] with sodium acetate as the sole carbon and energy source. The genomic DNA was extracted from the cell, concentrated and purified using the AxyPrep bacterial genomic DNA miniprep Kit (Axygen), as detailed in the manual for the instrument.

Genome sequencing and assembly

The genome was sequenced by using a massively parallel pyrosequencing technology (454 GS FLX) [23]. A total of 140,550 reads counting up to 78,223,504 bases were obtained, covered 21.1-folds of genome. The Newbler V2.7 [24] software package was used for sequence assembly and quality assessment. After assembling, 64 contigs ranging from 500 bp to 304,980 bp were obtained, and the relationship of the contigs was determined by multiplex PCR [25]. Gaps were then filled in by sequencing the PCR products using ABI 3730xl capillary sequencers. A total of 284 additional reactions were necessary to close gaps and to raise the quality of the finished sequence. Finally, the sequences were assembled using Phred, Phrap and Consed software packages [26], and low quality regions of the genome were re-sequenced. The final sequence accuracy was approximately 99.999%.

Genome annotation

The protein-coding genes, structural RNAs (5S, 16S, 23S), tRNAs and small non-coding RNAs were predicted and achieved by using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) server online [27]. The functional annotation of predicted ORFs was performed using RPS-BLAST [28] against the cluster of orthologous groups (COG) database [29] and Pfam database [30]. TMHMM program was used for gene prediction with transmembrane helices [31] and signalP program was used for prediction of genes with peptide signals [32].

Genome properties

The properties and the statistics of the genome are summarized in Table 4. The genome includes one circular chromosome of 3,764,053 bp (46.6% GC content). In total, 3,489 genes were predicted, 3,372 of which are protein-coding genes, and 61 RNAs; 56 pseudogenes were also identified. The majority of the protein-coding genes (67.07%) were assigned a putative function while the remaining ones were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 5 and Figure 3.
Figure 3.

Graphical map of the chromosome. From outside to the center: Genes on forward strand (color by COG categories), genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red), GC content, GC skew.

Table 4.

Genome statistics

Attribute

Value

% of Totala

Genome size (bp)

3,764,053

100.0

DNA coding region (bp)

3,315,444

88.08

DNA G+C content (bp)

1,753,947

46.60

Number of replicons

1

 

Extrachromosomal elements

0

 

Total genes

3,489

100.00

RNA genes

61

1.75

tRNA genes

48

1.38

rRNA operons

4

 

ncRNA genes

1

0.03

Protein-coding genes

3,372

96.65

Pseudo genes

56

1.61

Genes with function prediction

2,340

67.07

Genes in paralog clusters

1,051

30.12

Genes assigned to COGs

2,249

64.46

Genes assigned Pfam domains

2,576

73.83

Genes with signal peptides

338

9.69

Genes with transmembrane helices

775

22.21

aThe total is based on either the size of the genome in base pairs or on the total number of protein coding genes in the annotated genome.

Table 5.

Number of genes associated with the 25 general COG functional categories

Code

Value

%age

Description

J

182

7.11

Translation, ribosomal structure and biogenesis

A

1

0.04

RNA processing and modification

K

161

6.29

Transcription

L

132

5.16

Replication, recombination and repair

B

1

0.04

Chromatin structure and dynamics

D

32

1.25

Cell cycle control, cell division, chromosome partitioning

Y

0

0.00

Nuclear structure

V

28

1.09

Defense mechanisms

T

152

5.94

Signal transduction mechanisms

M

150

5.86

Cell wall/membrane/envelope biogenesis

N

85

3.32

Cell motility

Z

1

0.04

Cytoskeleton

W

0

0.00

Extracellular structures

U

83

3.24

Intracellular trafficking, secretion, and vesicular transport

O

127

4.96

Posttranslational modification, protein turnover, chaperones

C

143

5.59

Energy production and conversion

G

76

2.97

Carbohydrate transport and metabolism

E

187

7.30

Amino acid transport and metabolism

F

67

2.62

Nucleotide transport and metabolism

H

115

4.49

Coenzyme transport and metabolism

I

106

4.14

Lipid transport and metabolism

P

138

5.39

Inorganic ion transport and metabolism

Q

57

2.23

Secondary metabolites biosynthesis, transport and catabolism

R

329

12.85

General function prediction only

S

207

8.09

Function unknown

-

1240

35.54

Not in COGs

Insights from the genome sequence

Until now, only the genome sequence of the type strain T. oleivorans MIL-1T was available within the genus of Thalassolituus [9]. Here, we compared the genome of strain R6-15 with strain MIL-1T (Table 6). The genome of strain R6-15 is nearly 156 kb smaller in size than strain MIL-1T. The G+C content of strain R6-15 (46.6%) is similar with type strain MIL-1T (46.6%). The gene content of strain R6-15 is smaller than strain MIL-1T (3,489 vs 3,732).
Table 6.

Comparison of genomes between T. oleivorans R6-15 and T. oleivorans MIL-1T

Genome Name

Genome size (bp)

Gene count

Protein coding

Protein with function

Without function

Plasmid number

rRNA operons

T. oleivorans R6-15

3,764,053

3,489

3,372

2,340

1,032

0

4

T. oleivorans MIL-1T

3,920,328

3,732

3,603

2,038

1,565

0

4

Strain R6-15 shares 2,995 orthologous genes with type strain MIL-1T. The average percentage of nucleotide sequence identity is 96.92% between strain R6-15 and MIL-1T. In addition, DNA-DNA hybridization (DDH) estimate value between strain R6-15 and MIL-1T were calculated using the genome-to-genome distance calculator (GGDC2.0) [33,34]. The DDH estimate value between them was 84.5% ± 2.57, which were above the standard criteria (70%) [35]. Therefore, these results confirmed that strain R6-15 belonged to the species of Thalassolituus oleivorans.

Conclusion

Strain R6-15 is the first strain with the complete genome sequence of the genus Thalassolituus isolated from the Arctic Ocean. These genomic data will provide insights into the mechanisms of how this bacterium can thrive on the crude oil in the polar marine environments.

Notes

Declarations

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (41206158), the China Polar Environment Investigation and Estimate Project (2012–2015), and the Young Marine Science Foundation of SOA (2012142).

Authors’ Affiliations

(1)
Key Laboratory of Marine Genetic Resources, Third Institute of Oceanography, State Oceanic Administration
(2)
State Key Laboratory Breeding Base of Marine Genetic Resources
(3)
Key Laboratory of Marine Genetic Resources of Fujian Province
(4)
Life Science College, Xiamen University

References

  1. Yakimov MM, Giuliano L, Denaro R, Crisafi E, Chernikova TN, Abraham WR, Luensdorf H, Timmis KN, Golyshin PN. Thalassolituus oleivorans gen. nov., sp. nov., a novel marine bacterium that obligately utilizes hydrocarbons. Int J Syst Evol Microbiol 2004; 54:141–148. PubMed http://dx.doi.org/10.1099/ijs.0.02424-0View ArticlePubMedGoogle Scholar
  2. Choi A, Cho JC. Thalassolituus marinus sp. nov., a hydrocarbon-utilizing marine bacterium. Int J Syst Evol Microbiol 2013; 63:2234–2238. PubMed http://dx.doi.org/10.1099/ijs.0.046383-0View ArticlePubMedGoogle Scholar
  3. Yakimov MM, Timmis KN, Golyshin PN. Obligate oildegrading marine bacteria. Curr Opin Biotechnol 2007; 18:257–266. PubMed http://dx.doi.org/10.1016/jxopbio.2007.04.006View ArticlePubMedGoogle Scholar
  4. Yakimov MM, Denaro R, Genovese M, Cappello S, D’Auria G, Chernikova TN, Timmis KN, Golyshin PN, Giluliano L. Natural microbial diversity in superficial sediments of Milazzo Harbor (Sicily) and community successions during microcosm enrichment with various hydrocarbons. Environ Microbiol 2005; 7:1426–1441. PubMed http://dx.doi.org/10.1111/j.14625822.2005.00829.xView ArticlePubMedGoogle Scholar
  5. Coulon F, McKew BA, Osborn AM, McGenity TJ, Timmis KN. Effects of temperature and biostimulation on oil-degrading microbial communities in temperate estuarine waters. Environ Microbiol 2007; 9:177–186. PubMed http://dx.doi.org/10.1111/j.14622920.2006.01126.xView ArticlePubMedGoogle Scholar
  6. McKew BA, Coulon F, Osborn AM, Timmis KN, McGenity TJ. Determining the identity and roles of oil-metabolizing marine bacteria from the Thames estuary, UK. Environ Microbiol 2007; 9:165–176. PubMed http://dx.doi.org/10.1111/j.14622920.2006.01125.xView ArticlePubMedGoogle Scholar
  7. McKew BA, Coulon F, Yakimov MM, Denaro R, Genovese M, Smith CJ, Osborn AM, Timmis KN, McGenity TJ. Efficacy of intervention strategies for bioremediation of crude oil in marine systems and effects on indigenous hydrocarbonoclastic bacteria. Environ Microbiol 2007; 9:1562–1571. PubMed http://dx.doi.org/10.1111/j.1462-2920.2007.01277.xView ArticlePubMedGoogle Scholar
  8. Yakimov MM, Genovese M, Denaro R. Thalassolituus. Handbook of Hydrocarbon and Lipid Microbiology. Heidelberg: Springer-Verlag; 2010.Google Scholar
  9. Golyshin PN, Werner J, Chernikova TN, Tran H, Ferrer M, Yakimov MM, Teeling H, Golyshina OV, Consortium MS. Genome Sequence of Thalassolituus oleivorans MIL-1 (DSM 14913T). Genome Announc 2013;1(2).Google Scholar
  10. Hazen TC, Dubinsky EA, DeSantis TZ, Andersen GL, Piceno YM, Singh N, Jansson JK, Probst A, Borglin SE, Fortney JL, et al. Deep-sea oil plume enriches indigenous oil-degrading bacteria. Science 2010; 330:204–208. PubMed http://dx.doi.org/10.1126/science.1195979View ArticlePubMedGoogle Scholar
  11. 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; 28:2731–2739. PubMed http://dx.doi.org/10.1093/molbev/msr121PubMed CentralView ArticlePubMedGoogle Scholar
  12. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol 2008; 26:541–547. PubMed http://dx.doi.org/10.1038/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
  13. Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci USA 1990; 87:4576–4579. PubMed http://dx.doi.org/10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
  14. Garrity G, Bell J, Lilburn T. Phylum XIV. Proteobacteria phyl. nov. In: Garrity G, Brenner D, Krieg N, Staley J, editors. Bergey’s Manual of Systematic Bacteriology. Second ed. Volume 2, Part B. New York: Springer; 2005. p 1.View ArticleGoogle Scholar
  15. Garrity G, Bell J, Lilburn T. Class III. Gammaproteobacteria class nov. In: Garrity G, Brenner D, Krieg N, Staley J, editors. Bergey’s Manual of Systematic Bacteriology. Second ed. Volume 2, Part B. New York: Springer; 2005. p 1.View ArticleGoogle Scholar
  16. Validation of publication of new names and new combinations previously effectively published outside the IJSEM. List no. 106. Int J Syst Evol Microbiol 2005; 55:2235–2238. http://dx.doi.org/10.1099/ijs.0.64108-0
  17. Williams KP, Kelly DP. Proposal for a new class within the phylum Proteobacteria, Acidithiobacillia classis nov., with the type order Acidithiobacillales, and emended description of the class Gammaproteobacteria. Int J Syst Evol Microbiol 2013; 63:2901–2906. PubMed http://dx.doi.org/10.1099/ijs.0.049270-0View ArticlePubMedGoogle Scholar
  18. Garrity G, Bell J, Lilburn T. Order VIII. Oceanospirillales ord. nov. In: Garrity G, Brenner D, Krieg N, Staley J, editors. Bergey’s Manual of Systematic Bacteriology. Second ed. Volume 2, Part B. New York: Springer; 2005. p 270.View ArticleGoogle Scholar
  19. Garrity G, Bell J, Lilburn T. Family I. Oceanospirillaceae fam. nov. In: Garrity G, Brenner D, Krieg N, Staley J, editors. Bergey’s Manual of Systematic Bacteriology. Second ed. Volume 2, Part B. New York: Springer; 2005. p 271.Google Scholar
  20. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000; 25:25–29. PubMed http://dx.doi.org/10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
  21. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol 2008; 26:541–547. PubMed http://dx.doi.org/10.1038/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
  22. Dyksterhouse SE, Gray JP, Herwig RP, Lara JC, Staley JT. Cycloclasticus pugetii gen. nov., sp. nov., an aromatic hydrocarbon-degrading bacterium from marine sediments. Int J Syst Bacteriol 1995; 45:116–123. PubMed http://dx.doi.org/10.1099/00207713-45-1-116View ArticlePubMedGoogle Scholar
  23. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature 2005; 437:376–380. PubMedPubMed CentralPubMedGoogle Scholar
  24. The Newbler V2. 7. http://www.454.com/
  25. Tettelin H, Radune D, Kasif S, Khouri H, Salzberg SL. Optimized multiplex PCR: efficiently closing a whole-genome shotgun sequencing project. Genomics 1999; 62:500–507. PubMed http://dx.doi.org/10.1006/geno.1999.6048View ArticlePubMedGoogle Scholar
  26. Phred, Phrap and Consed software packages. http://www.genome.washington.edu
  27. Angiuoli SV, Gussman A, Klimke W, Cochrane G, Field D, Garrity G, Kodira CD, Kyrpides N, Madupu R, Markowitz V, et al. Toward an online repository of Standard Operating Procedures (SOPs) for (meta)genomic annotation. OMICS 2008; 12:137–141. PubMed http://dx.doi.org/10.1089/omi.2008.0017PubMed CentralView ArticlePubMedGoogle Scholar
  28. Marchler-Bauer A, Anderson JB, Derbyshire MK, DeWeese-Scott C, Gonzales NR, Gwadz M, Hao L, He S, Hurwitz DI, Jackson JD, et al. CDD: a conserved domain database for interactive domain family analysis. Nucleic Acids Res 2007; 35:D237–D240. PubMed http://dx.doi.org/10.1093/nar/gkl951PubMed CentralView ArticlePubMedGoogle Scholar
  29. 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; 28:33–36. PubMed http://dx.doi.org/10.1093/nar/28.1.33PubMed CentralView ArticlePubMedGoogle Scholar
  30. Sonnhammer EL, Eddy SR, Durbin R. Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins 1997; 28:405–420. PubMed http://dx.doi.org/10.1002/(SICI)1097-0134(199707)28:3<405::AID-PROT10=3.0.CO;2-LView ArticlePubMedGoogle Scholar
  31. Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol 2001; 305:567–580. PubMed http://dx.doi.org/10.1006/jmbi.2000.4315View ArticlePubMedGoogle Scholar
  32. Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol 2004; 340:783–795. PubMed http://dx.doi.org/10.1016/j.jmb.2004.05.028View ArticlePubMedGoogle Scholar
  33. Auch AF, Klenk HP, Goker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci 2010; 2:142–148. PubMed http://dx.doi.org/10.4056/sigs.541628PubMed CentralView ArticlePubMedGoogle Scholar
  34. Auch AF, von Jan M, Klenk HP, Goker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci 2010; 2:117–134. PubMed http://dx.doi.org/10.4056/sigs.531120PubMed CentralView ArticlePubMedGoogle Scholar
  35. Wayne LG, Brenner DJ, Colwell RR, Grimont PAD, Kandler O, Krichevsky MI, Moore LH, Moore WEC, Murray RGE, Stackebrandt E, et al. Report of the Ad Hoc Committee on Reconciliation of Approaches to Bacterial Systematics. Int J Syst Bacteriol 1987; 37:463–464. http://dx.doi.org/10.1099/00207713-37-4-463View ArticleGoogle Scholar

Copyright

© The Author(s) 2014