Open Access

Genome sequence of the Leisingera aquimarina type strain (DSM 24565T), a member of the marine Roseobacter clade rich in extrachromosomal elements

  • Thomas Riedel1,
  • Hazuki Teshima2,
  • Jörn Petersen3,
  • Anne Fiebig3,
  • Karen Davenport2,
  • Hajnalka Daligault2,
  • Tracy Erkkila2,
  • Wei Gu2,
  • Christine Munk2,
  • Yan Xu2,
  • Amy Chen4,
  • Amrita Pati5,
  • Natalia Ivanova5,
  • Lynne A. Goodwin2, 5,
  • Patrick Chain2,
  • John C. Detter2, 5,
  • Manfred Rohde1,
  • Sabine Gronow3,
  • Nikos C. Kyrpides5,
  • Tanja Woyke5,
  • Markus Göker3Email author,
  • Thorsten Brinkhoff6 and
  • Hans-Peter Klenk3
Standards in Genomic Sciences20138:8030389

DOI: 10.4056/sigs.3858183

Published: 30 July 2013

Abstract

Leisingera aquimarina Vandecandelaere et al. 2008 is a member of the genomically well characterized Roseobacter clade within the family Rhodobacteraceae. Representatives of the marine Roseobacter clade are metabolically versatile and involved in carbon fixation and biogeochemical processes. They form a physiologically heterogeneous group, found predominantly in coastal or polar waters, especially in symbiosis with algae, in microbial mats, in sediments or associated with invertebrates. Here we describe the features of L. aquimarina DSM 24565T together with the permanent-draft genome sequence and annotation. The 5,344,253 bp long genome consists of one chromosome and an unusually high number of seven extrachromosomal elements and contains 5,129 protein-coding and 89 RNA genes. It was sequenced as part of the DOE Joint Genome Institute Community Sequencing Program 2010 and of the activities of the Transregional Collaborative Research Centre 51 funded by the German Research Foundation (DFG).

Keywords

marine biofilm ovoid-shaped halotolerant heterotrophic quorum sensing plasmid thiosulfate oxidation carbon monoxide utilization Rhodobacteraceae Alphaproteobacteria

Introduction

Strain R-26159T (= DSM 24565T = LMG 24366T = CCUG 55860T) is the type strain of the species Leisingera aquimarina [1], one of the three species currently with a validly published name in the genus Leisingera; the other ones are the type species L. methylohalidivorans [1,2] and L. nanhaiensis [3]. The genus Leisingera is a member of the widespread Roseobacter clade, present in various marine habitats [4]. Strain R-26159T was isolated from a marine electroactive biofilm grown on a stainless-steel cathode, which was exposed to natural seawater at the ISMAR-CNR Marine Station within the harbor of Genova (Italy) [1]. The genus Leisingera was named after Thomas Leisinger for his work on the bacterial methyl halide metabolism [2]; the species epithet aquimarina refers to the Neolatin adjective marinus, from the sea, from seawater. PubMed records do not currently indicate any follow-up research with strain R-26159T after the initial description of L. aquimarina [1].

Here we present a summary classification and a set of features for L. aquimarina DSM 24565T, together with the description of the genomic sequencing and annotation.

Classification and features of the organism 16S rRNA analysis

A representative genomic 16S rRNA gene sequence of L. aquimarina DSM 24565T was compared using NCBI BLAST [5,6] under default settings (e.g., considering only the high-scoring segment pairs (HSPs) from the best 250 hits) with the most recent release of the Greengenes database [7] and the relative frequencies of taxa and keywords (reduced to their stem [8]) were determined, weighted by BLAST scores. The most frequently occurring genera were Phaeobacter (31.4%), Ruegeria (25.9%), Silicibacter (16.1%), Roseobacter (14.4%) and Nautella (3.9%) (127 hits in total). Regarding the four hits to sequences from other members of the genus, the average identity within HSPs was 99.4%, whereas the average coverage by HSPs was 99.3%. Among all other species, the one yielding the highest score was Leisingera methylohalidivorans (NR_025637), which corresponded to an identity of 99.2% and an HSP coverage of 100.0%. (Note that the Greengenes database uses the INSDC (= EMBL/NCBI/DDBJ) annotation, which is not an authoritative source for nomenclature or classification.) The highest-scoring environmental sequence was FJ202534 (Greengenes short name ‘and White Plague Disease-Induced Changes Caribbean Coral Montastraea faveolata kept aquarium 23 days clone SGUS1024’), which showed an identity of 97.8% and an HSP coverage of 100.0%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were ‘coral’ (4.7%), ‘caribbean’ (3.8%), ‘faveolata’ (3.5%), ‘chang’ (3.4%) and ‘white’ (3.3%) (117 hits in total). Environmental samples which yielded hits of a higher score than the highest scoring species were not found, which might indicate that the species is rarely found in the environment.

Figure 1 shows the phylogenetic neighborhood of L. aquimarina in a 16S rRNA gene based tree. The sequences of the four identical 16S rRNA gene copies in the genome do not differ from the previously published 16S rRNA gene sequence AM900415.
Figure 1.

Phylogenetic tree highlighting the position of L. aquimarina relative to the type strains of the other species within the genus Leisingera and the neighboring genera Phaeobacter and Ruegeria. The tree was inferred from 1,383 aligned characters [9,10] of the 16S rRNA gene sequence under the maximum likelihood (ML) criterion [11]. Rooting was done initially using the midpoint method [12] and then checked for its agreement with the current classification (Table 1). The branches are scaled in terms of the expected number of substitutions per site. Numbers adjacent to the branches are support values from 1,000 ML bootstrap replicates [13] (left) and from 1,000 maximum-parsimony bootstrap replicates [14] (right) if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [15] are labeled with one asterisk, those also listed as ‘Complete and Published’ with two asterisks [16,17]. The genomes of P. caeruleus [18] and P. arcticus [19] are reported in this issue.

Morphology and physiology

Cells of strain R-26159T are Gram-negative, ovoid (1 × 1.4 µm) and contain a single polar flagellum (not visible in Figure 2), which is used for motility. Poly-β-hydroxybutyrate is present in inclusion bodies. Colonies are dark beige-pink in color, round and 1–2 mm in diameter after 3 days incubation on marine agar (MA). Growth occurs after 2 days incubation at 20 °C on MA, but not on Reasoner’ 2A agar (R2A), Nutrient agar (NA), Trypticase-Soy agar (TSA) or Peptone-Yeast Extract-Glucose agar (PYG). The temperature range for growth is 4–37°C whereas no growth occurs at 40°C or higher. The salinity range for growth is 1–7% NaCl. The pH range for growth is 5.5–9.0 with an optimum between 6.5–8. Growth occurs on betaine (1 mM) as a sole carbon source, but not on L-methionine (10 mM). Cells are catalase- and oxidase-positive. Degradation of gelatin is weakly positive but cells do not degrade tyrosine, DNA, starch, casein, chitin, aesculin or Tween 80. The strain shows leucine arylamidase activity; weak alkaline phosphatase, esterase lipase (C8) and naphthol-AS-BI phosphohydrolase activities. No activity is detected for esterase (C4), valine arylamidase, acid phosphatase, α-galactosidase, β-glucuronidase, α-glucosidase, β-glucosidase, N-acetyl-β-glucosaminidase, α-mannosidase, lipase (C14), cystine arylamidase, trypsin, α-chymotrypsin, arginine dihydrolase, urease or α-fucosidase. Nitrate is not reduced to nitrite or nitrogen. Indole is not produced and glucose is not fermented. Cells do not assimilate D-glucose, L-arabinose, D-mannose, D-mannitol, N-acetylglucosamine, maltose, potassium gluconate, capric acid, adipic acid, malate, citrate or phenylacetic acid. Cells are susceptible to cefoxitin (30 mg), erythromycin (15 mg), tetracycline (30 mg) and streptomycin (25 mg), but resistant to vancomycin (30 mg), trimethoprim (1.25 mg), clindamycin (2 mg) and gentamicin (30 mg) (all data from [1]).
Figure 2.

Scanning electron micrograph of L. aquimarina DSM 24565T.

The utilization of carbon compounds by L. aquimarina DSM 24565T grown at 20°C was also determined for this study using Generation-III microplates in an OmniLog phenotyping device (BIOLOG Inc., Hayward, CA, USA). The microplates were inoculated at 28°C with a cell suspension at a cell density of 95–96% turbidity and dye IF-A. Further additives were vitamin, micronutrient and sea-salt solutions. The exported measurement data were further analyzed with the opm package for R [31,32], using its functionality for statistically estimating parameters from the respiration curves and translating them into negative, ambiguous, and positive reactions. The strain was studied in two independent biological replicates, and reactions with a different behavior between the two repetitions were regarded as ambiguous. At 28°C the strain reacted poorly, with positive reactions only for 1% NaCl, 4% NaCl and lithium chloride. This is in accordance with the comparatively low median of the temperature range of the strain [1].

Chemotaxonomy

The principal cellular fatty acids of strain R-26159T are mono-unsaturated straight chain acids: C18:1 ω7c (71.6%), C14:1 iso E (11.6%), C14:1 2-OH (4.2%), C16:0 2-OH (4.2%), C16:0 (3.5%), an unknown fatty acid of equivalent chain-length 11.799 (2.7%), C12:0 3-OH (2.1%) as well as C10:0 3-OH (2.0%) [28]. Remaining fatty acids were detected in very small fractions only (<1.0%) [1]. The same predominant fatty acids were also found in other members of the Phaeobacter-Leisingera cluster [2,28,33].
Table 1.

Classification and general features of L. aquimarina DSM 24565T according to the MIGS recommendations [20].

MIGS ID

Property

Term

Evidence code

 

Classification

Domain Bacteria

TAS [21]

 

Phylum Proteobacteria

TAS [22]

 

Class Alphaproteobacteria

TAS [23,24]

 

Order Rhodobacterales

TAS [24,25]

 

Family Rhodobacteraceae

TAS [24,26]

 

Genus Leisingera

TAS [27,28]

 

Species Leisingera aquimarina

TAS [1]

MIGS-7

Subspecific genetic lineage (strain)

R-26159T

TAS [1]

MIGS-12

Reference for biomaterial

Vandecandelaere et al. 2008

TAS [1]

 

Current classification

  
 

Gram stain

Negative

TAS [1]

 

Cell shape

Ovoid-shaped

TAS [1]

 

Motility

Motile

TAS [1]

 

Sporulation

Not reported

 
 

Temperature range

Mesophile (4–37°C)

TAS [1]

 

Optimum temperature

20°C

NAS

 

Salinity

Halophile, 1–7% NaCl (w/v)

TAS [1]

MIGS-22

Relationship to oxygen

aerobic

TAS [1]

 

Carbon source

Yeast extract, peptone, betaine

TAS [1]

MIGS-6

Habitat

Seawater, biofilm

TAS [1]

MIGS-6.2

pH

6.5–8.0

TAS [1]

MIGS-15

Biotic relationship

Free living

TAS [1]

 

Biosafety level

1

TAS [27]

MIGS-23.1

Isolation

Marine biofilm on stainless steel cathode

TAS [1]

MIGS-4

Geographic location

ISMAR-CNR Marine Station, Genoa harbor, Italy

TAS [1]

MIGS-4.1

Latitude

+44.41

TAS [1]

MIGS-4.2

Longitude

+8.92

TAS [1]

MIGS-4.3

Depth

Not reported

 

Evidence codes - 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). Evidence codes are from the Gene Ontology project [28].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of the DOE Joint Genome Institute Community Sequencing Program 2010, CSP 441: “Whole genome type strain sequences of the genera Phaeobacter and Leisingera - a monophyletic group of highly physiologically diverse organisms”. The genome project is deposited in the GenomesOnLine Database [15] and the complete genome sequence was submitted to GenBank. Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI). A summary of the project information is shown in Table 2.
Table 2.

Genome sequencing project information

MIGS ID

Property

Term

MIGS-31

Finishing quality

Improved high quality draft

MIGS-28

Libraries used

Two genomic libraries: Illumina standard (short PE), Illumina CLIP (long PE)

MIGS-29

Sequencing platforms

Illumina HiSeq 2000, PacBio

MIGS-31.2

Sequencing coverage

699 × Illumina; unknown × PacBio

MIGS-30

Assemblers

Allpath version 39750, Velvet 1.1.05, phrap version SPS - 4.24

MIGS-32

Gene calling method

Prodigal 1.4, GenePRIMP

 

INSDC ID

pending

 

GenBank Date of Release

pending

 

GOLD ID

Gi10856

 

NCBI project ID

81653

 

Database: IMG

2521172617

MIGS-13

Source material identifier

DSM 24565T

 

Project relevance

Tree of Life, carbon cycle, sulfur cycle, environmental

Growth conditions and DNA isolation

A culture of L. aquimarina DSM 24565T was grown in the DSMZ medium 514 (BACTO Marine Broth) [34] at 20°C. Genomic DNA was isolated from 0.5–1 g of cell paste using Jetflex Genomic DNA Purification Kit (GENOMED 600100) following the standard protocol provided by the manufacturer but modified by the use of additional 20 µl proteinase K and 40 minute incubation. DNA is available through the DNA Bank Network [35].

Genome sequencing and assembly

The draft genome was generated using Illumina data [36]. For this genome, we constructed and sequenced an Illumina short-insert paired-end library with an average insert size of 270 bp which generated 13,668,574 reads and an Illumina long-insert paired-end library with an average insert size of 8047.58 +/− 2682.23 bp which generated 11,512,166 reads totaling 3,777 Mbp of Illumina data (Feng Chen, unpublished). All general aspects of library construction and sequencing can be found at the JGI web site [37]. The initial draft assembly contained 64 contigs in 18 scaffold(s). The initial draft data was assembled with Allpaths [39] and the consensus was computationally shredded into 10 kbp overlapping fake reads (shreds). The Illumina draft data was also assembled with Velvet [39], and the consensus sequences were computationally shredded into 1.5 kbp overlapping fake reads (shreds). The Illumina draft data was assembled again with Velvet using the shreds from the first Velvet assembly to guide the next assembly. The consensus from the second Velvet assembly was shredded into 1.5 kbp overlapping fake reads. The fake reads from the Allpaths assembly and both Velvet assemblies and a subset of the Illumina CLIP paired-end reads were assembled using parallel phrap (High Performance Software, LLC) [40]. Possible mis-assemblies were corrected with manual editing in Consed [37,39,40]. Gap closure was accomplished using repeat resolution software (Wei Gu, unpublished), and sequencing of bridging PCR fragments with PacBio (Cliff Han, unpublished) technologies. A total of 57 PCR PacBio consensus sequences were completed to close gaps and to raise the quality of the final sequence. The final assembly is based on 3,777 Mbp of Illumina draft data, which provides an average 699 × coverage of the genome.

Genome annotation

Genes were identified using Prodigal [41] as part of the JGI genome annotation pipeline [42], followed by a round of manual curation using the JGI GenePRIMP pipeline [43]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGR-Fam, Pfam, PRIAM, KEGG, COG, and InterPro databases. Additional gene prediction analysis and functional annotation was performed within the Integrated Microbial Genomes - Expert Review (IMG-ER) platform [44].

Genome properties

The genome statistics are provided in Table 3 and Figure 3. The genome consists of a 4.25 Mbp chromosome and seven extrachromosomal elements of 6.2 to 248.9 kbp length with a G+C content of 61.4%. Of the 5,218 genes predicted, 5,129 were protein-coding genes, and 89 RNAs. The majority of the protein-coding genes (80.4%) 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 4.
Figure 3.

Graphical map of the chromosome. From bottom to the top: Genes on forward strand (colored by COG categories), Genes on reverse strand (colored by COG categories), RNA genes (tRNAs green, rRNAs red, other RNAs black), GC content (black), GC skew (purple/olive).

Table 3.

Genome Statistics

Attribute

Value

% of Total

Genome size (bp)

5,344,253

100.00

DNA coding region (bp)

4,678,916

87.55

DNA G+C content (bp)

3,278,568

61.35

Number of scaffolds

8

 

Extrachromosomal elements

7

 

Total genes

5,218

100.00

RNA genes

89

1.71

rRNA operons

4

 

tRNA genes

61

1.17

Protein-coding genes

5,129

98.29

Genes with function prediction (proteins)

4,196

80.41

Genes in paralog clusters

4,110

78.77

Genes assigned to COGs

3,955

75.80

Genes assigned Pfam domains

4,253

81.51

Genes with signal peptides

419

8.03

Genes with transmembrane helices

1,037

19.87

CRISPR repeats

0

 
Table 4.

Number of genes associated with the general COG functional categories

Code

value

%age

Description

J

175

4.0

Translation, ribosomal structure and biogenesis

A

1

0.0

RNA processing and modification

K

365

8.4

Transcription

L

296

6.8

Replication, recombination and repair

B

2

0.1

Chromatin structure and dynamics

D

43

1.0

Cell cycle control, cell division, chromosome partitioning

Y

0

0.0

Nuclear structure

V

53

1.2

Defense mechanisms

T

182

4.2

Signal transduction mechanisms

M

221

5.1

Cell wall/membrane/envelope biogenesis

N

55

1.3

Cell motility

Z

2

0.1

Cytoskeleton

W

0

0.0

Extracellular structures

U

75

1.7

Intracellular trafficking and secretion, and vesicular transport

O

157

3.6

Posttranslational modification, protein turnover, chaperones

C

273

6.3

Energy production and conversion

G

168

3.9

Carbohydrate transport and metabolism

E

550

12.6

Amino acid transport and metabolism

F

95

2.2

Nucleotide transport and metabolism

H

188

4.3

Coenzyme transport and metabolism

I

172

4.0

Lipid transport and metabolism

P

220

5.1

Inorganic ion transport and metabolism

Q

152

3.5

Secondary metabolites biosynthesis, transport and catabolism

R

513

11.8

General function prediction only

S

393

9.0

Function unknown

-

1,263

24.2

Not in COGs

Insights into the genome

Genome sequencing of Leisingera aquimarina DSM 24565T reveals the presence of seven plasmids with sizes between 6 kb and 249 kb (Table 5). The circular conformation of the chromosome and the two smallest extrachromosomal elements has been experimentally validated. The six larger plasmids contain characteristic replication modules [45] of the RepABC-, DnaA-like, RepA- and RepB-type comprising a replicase as well as the parAB partitioning operon [46]. The respective replicases that mediate the initiation of replication are designated according to the established plasmid classification scheme [47]. The different numbering of e.g. the replicases RepC-8, RepC-13 and RepC-14 from RepABC-type plasmids corresponds to specific plasmid compatibility groups that are required for a stable coexistence of the replicons within the same cell [48]. The cryptic 6 kb plasmid pAqui_G6 contains a solitary RepA-II type replicase without a partitioning module, but replicon maintenance in the daughter cells is probably ensured by its postsegregational killing system (PSK) consisting of a typical operon with two small genes encoding a stable toxin and an unstable antitoxin [49]. PSK systems are also located on pAqui_C182 and pAqui_F126 (Tab. 6).
Table 5.

General genomic features of the chromosome and extrachromosomal replicons from Leisingera aquimarina strain DSM 24565T.

Replicon

Scaffold

Replicase

Length (bp)

GC (%)

Topology

No. Genes#

Chromosome

1

DnaA

4,250,010

61

circular

4245

pAqui_A249

2

RepC-14

248,908

59

linear*

238

pAqui_B243

3

RepC-13

242,809

61

linear*

231

pAqui_C182

4

RepC-8

182,150

63

linear*

159

pAqui_D148

5

RepB-I

148,175

63

linear*

121

pAqui_E140

6

RepA-I

140,244

62

linear*

109

pAqui_F126

7

DnaA-like I

125,793

62

circular

105

pAqui_G6

8

RepA-II

6,164

58

circular

10

*Circularity not experimentally validated;

#deduced from automatic annotation.

Table 6.

Integrated Microbial Genome (IMG) locus tags of L. aquimarina DSM 24565T genes for the initiation of replication, toxin/antitoxin modules and two representatives of type IV secretion systems (T4SS) that are required for conjugation. The locus tags are accentuated in blue1,2,3.

 

Replication Initiation

Plasmid Stability

Type IV Secretion

Replicon

Replicase

Locus Tag

Toxin

Antitoxin

VirB4

VirD4

Chromosome

DnaA

Aqui_0952

-

-

Aqui_3705

Aqui_37203

pAqui_A249

RepC-14

Aqui_4671

-

-

Aqui_46852

Aqui_45983

pAqui_B243

RepC-13

Aqui_4931

-

-

-

-

pAqui_C182

RepC-8

Aqui_5105

Aqui_5145

Aqui_5144

-

-

pAqui_D148

RepB-I

Aqui_4343

-

-

-

-

pAqui_E140

RepA-I

Aqui_4076

-

-

-

-

pAqui_F126

DnaA-like I

Aqui_4459

Aqui_4464

Aqui_4465

  

pAqui_G6

RepA-II1

Aqui_5224

Aqui_5228

Aqui_5229

-

-

1solitary replicase without partitioning module;

2traC gene of F factor conjugation system;

3presence of adjacent DNA relaxase VirD2.

The locus tags of all replicases, plasmid stability modules and the large virB4 and virD4 genes of type IV secretion systems are presented in Table 6. A characteristic T4SS comprising the relaxase VirD2 and the coupling protein VirD4 as well as the complete virB gene cluster for the transmembrane channel is located on the chromosome [50]. Its functional role is unclear, but very closely related T4SS are detected on plasmids of e.g. Dinoroseobacter shibae DSM 16493T [51], Leisingera nanhaiensis DSM 24252T and Phaeobacter caeruleus DSM 24564T [52]. Furthermore, the largest plasmid pAqui_A249 contains the complete F factor conjugation transfer (tra) region with 20 genes (Aqui_4678 to Aqui_4697). It exhibits only weak homology with the typical type IV secretion system of the Roseobacter clade, which is represented by the chromosomal counterpart, but it resembles the F sex factor of Escherichia coli that is the paradigm for bacterial conjugation [53].

The 243 kb RepABC-13 type plasmid pAqui_B243 is predominated by seven ABC-transporters. Even more conspicuous is the presence of a couple of pentose phosphate pathway genes including an operon of genes of the Entner-Doudoroff pathway (Aqui_4914 to Aqui_4917; EC 1.1.1.49; EC 4.2.1.12; EC 4.1.2.14; EC 5.3.1.9) that is generally used in Roseobacters to convert D-fructose-6-phosphate to D-glyceraldehyde-3-phosphate [54]. The exclusive missing gene within this operon is the chromosome encoded 6-phosphogluconolactonase (Aqui_2983; EC 3.1.1.31). The presence of a glycolytic 6-phosphofructokinase (PFK; Aqui_4950; EC 2.7.1.11) is a genetic novelty in this group of marine bacteria, because the current opinion was that “the typical pfk gene is absent from all sequenced Roseobacter clade genomes and glucose is hence probably catabolized via the Entner-Doudoroff pathway and not via classical glycolysis” [55]. However, the putative functionality of the Embden-Meyerhoff-Parnas pathway (glycolysis) has to be validated e.g. via pulse-chase experiments with 13C labeled glucose [56]. Finally, the plasmid pAqui_B243 contains the phosphoenolpyruvate synthase (Aqui_4951; EC 2.7.1.11) that is required together with the chromosomal phosphoenolpyruvate carboxylase (Aqui_0364; EC 4.1.1.31) for prokaryotic CO2 fixation and the formation of oxaloacetate from pyruvate.

The 148 kb RepB-I type plasmid pAqui_D148 contains a complete rhamnose operon [50] and many genes that are required for polysaccharide biosynthesis. This extrachromosomal replicon also harbors two siderophore synthetase genes (Aqui_4320; Aqui_4321), two outer membrane receptors for Fe-transport (Aqui_4319; Aqui_4360) and genes of a putative ABC-type Fe3+ siderophore transport system (Aqui_4361 to Aqui_4364).

The 140 kb RepA-I type plasmid pAqui_E140 is largely predominated by glycosyltransferases, polysaccharide biosynthesis as well as cell-wall biogenesis genes, and it contains an operon for GDP-mannose metabolism (Aqui_5058 to Aqui_5055).

The 126 kb DnaA-like I replicon pAqui_F126 contains a large type VI secretion system (T6SS) with a size of about 30 kb. The role of this export system that has been first described in the context of bacterial pathogenesis, but recent findings indicate a more general physiological role in defense against eukaryotic cells and other bacteria in the environment [57]. Homologous T6S systems are present on the DnaA-like I plasmids of Leisingera methylohalidivorans DSM 14336T (pMeth_A285) and Phaeobacter caeruleus DSM 24564T (pCaer_C109) as well as the RepC-8 type plasmid of Phaeobacter daeponensis DSM23529T (pDaep_A276).

Genome analysis of strain L. aquimarina DSM 24565T revealed further the presence of genes encoding LuxI as well as LuxR homologues, which are involved in quorum sensing (QS), an already known feature of several members of the Roseobacter clade [58]. QS is a bacterial communication system used by many bacterial species to coordinate special behaviors based on bacterial population density [58]. Whereas two genes encode a N-acyl-L-homoserine lactone synthase (LuxI, Aqui_0074, Aqui_4264), some genes were identified to encode LuxR homologues (response and transcriptional regulators, e.g., Aqui_0075 and Aqui_3114).

Furthermore, several genes forming a putative operon are involved in the oxidation of (e.g., Aqui_3422 to Aqui_3426) indicating the oxidation of thiosulfate into sulfate to produce energy. Additionally genes for carbon monoxide utilization (Aqui_2391 and Aqui_2392, Aqui_2518, Aqui_2520, Aqui_3522, Aqui_5216 and Aqui_5217) were observed.

Interestingly, also a gene encoding a sensor of blue light using FAD (BLUF, Aqui_2375) was detected, indicating possible blue-light depending signal transduction.

As indicated by the 16S rRNA gene sequence analysis (Figure 1), the classification of some Leisingera and Phaeobacter species might need to be reconsidered. We conducted a preliminary phylogenomic analysis with GGDC [5961] applied to the genome of L. aquimarina DSM 24565T and the draft genomes of the type strains of the other Leisingera and Phaeobacter species. The results shown in Table 7 indicate that the DNA-DNA hybridization (DDH) similarities calculated in silico of L. aquimarina to Phaeobacter caeruleus and P. daeponensis species are higher than those to L. nanhaiensis, confirming the 16S rRNA gene sequence analysis. Thus a taxonomic revision of L. aquimarina might be warranted.
Table 7.

DDH similarities between L. aquimarina DSM 24565T and the other Leisingera and Phaeobacter species (with genome-sequenced type strains)

Reference species

formula 1

formula 2

formula 3

L. nanhaiensis (2512047090)

14.50±3.11

19.20±2.28

14.70±2.65

L. methylohalidivorans (2512564009)

52.40±3.47

32.40±2.46

47.00±3.03

P. arcticus (2516653081)

16.60±3.25

20.70±2.32

16.50±2.75

P. caeruleus (2512047087)

45.90±3.41

28.40±2.44

40.60±3.01

P. daeponensis (2516493020)

47.30±3.42

27.90±2.43

41.30±3.01

P. gallaeciensis (AOQA01000000)

17.90±3.31

21.50±2.34

17.60±2.80

P. inhibens (2516653078)

18.30±3.33

20.80±2.33

17.90±2.82

DDH similarities were calculated in silico with the GGDC server version 2.0 [57]. The standard deviations indicate the inherent uncertainty in estimating DDH values from intergenomic distances based on models derived from empirical test data sets (which are always limited in size); see [56] for details. The distance formulas are explained in [56]. The numbers in parentheses are IMG object IDs (GenBank accession number in the case of P. gallaeciensis) identifying the underlying genome sequences.

Declarations

Acknowledgements

The authors would like to gratefully acknowledge the assistance of Iliana Schröder for growing L. aquamarina cultures and Evelyne-Marie Brambilla for DNA extraction and quality control (both at the DSMZ). The work conducted by the U.S. Department of Energy Joint Genome Institute was supported by the Office of Science of the U.S. Department of Energy under contract No. DE-AC02-05CH11231; the work conducted by the members of the Roseobacter consortium was supported by the German Research Foundation (DFG) Transregio-SFB 51. We also thank the European Commission which supported phenotyping via the Microme project 222886 within the Framework 7 program.

Authors’ Affiliations

(1)
HZI - Helmholtz Centre for Infection Research
(2)
Bioscience Division, Los Alamos National Laboratory
(3)
Leibniz Institute, DSMZ - German Collection of Microorganisms and Cell Cultures
(4)
Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory
(5)
DOE Joint Genome Institute
(6)
Institute for Chemistry and Biology of the Marine Environment (ICBM)

References

  1. Vandecandelaere I, Segaert E, Mollica A, Faimali M, Vandamme P. Leisingera aquimarina sp. nov., isolated form a marine electroactive biofilm, and emended descriptions of Leisingera methylohalidivorans Schaefer et al. 2002, Phaeobacter daeponensis Yoon et al. 2007 and Phaeobacter inhibens Martens et al. 2006. Int J Syst Evol Microbiol 2008; 58:2788–2793. PubMed http://dx.doi.org/10.1099/ijs.0.65844-0View ArticlePubMedGoogle Scholar
  2. Schaefer JK, Goodwin KD, McDonald IR, Murrell JC, Oremland RS. Leisingera methylohalidivorans gen. nov., sp. nov., a marine methylotroph that grows on methyl bromide. Int J Syst Evol Microbiol 2002; 52:851–859. PubMed http://dx.doi.org/10.1099/ijs.0.01960-0PubMedGoogle Scholar
  3. Sun F, Wang B, Liu X, Lai Q, Du Y, Li G, Luo J, Shao Z. Leisingera nanhaiensis sp. nov., isolated from marine sediment. Int J Syst Evol Microbiol 2010; 60:275–280. PubMed http://dx.doi.org/10.1099/ijs.0.010439-0View ArticlePubMedGoogle Scholar
  4. Buchan A, Gonzalez JM, Moran MA. Overview of the marine Roseobacter lineage. Appl Environ Microbiol 2005; 71:5665–5677. PubMed http://dx.doi.org/10.1128/AEM.71.10.5665-5677.2005PubMed CentralView ArticlePubMedGoogle Scholar
  5. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410. PubMedView ArticlePubMedGoogle Scholar
  6. Korf I, Yandell M, Bedell J. BLAST, O’Reilly, Sebastopol, 2003.Google Scholar
  7. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Appl Environ Microbiol 2006; 72:5069–5072. PubMed http://dx.doi.org/10.1128/AEM.03006-05PubMed CentralView ArticlePubMedGoogle Scholar
  8. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.View ArticleGoogle Scholar
  9. Lee C, Grasso C, Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics 2002; 18:452–464. PubMed http://dx.doi.org/10.1093/bioinformatics/18.3.452View ArticlePubMedGoogle Scholar
  10. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552. PubMed http://dx.doi.org/10.1093/oxfordjournals.molbev.a 026334View ArticlePubMedGoogle Scholar
  11. Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web-servers. Syst Biol 2008; 57:758–771. PubMed http://dx.doi.org/10.1080/10635150802429642View ArticlePubMedGoogle Scholar
  12. Hess PN, De Moraes Russo CA. An empirical test of the midpoint rooting method. Biol J Linn Soc Lond 2007; 92:669–674. http://dx.doi.org/10.1111/j.10958312.2007.00864.xView ArticleGoogle Scholar
  13. Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME, Stamatakis A. How Many Bootstrap Replicates Are Necessary? Lect Notes Comput Sci 2009; 5541:184–200. http://dx.doi.org/10.1007/978-3-642-02008-7_13View ArticleGoogle Scholar
  14. Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods), Version 4.0 b10. Sinauer Associates, Sunderland, 2002.Google Scholar
  15. Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, Markowitz VM, Kyrpides NC. The GenomesOnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2012; 40:D571–D579. PubMed http://dx.doi.org/10.1093/nar/gkr1100PubMed CentralView ArticlePubMedGoogle Scholar
  16. Ruiz-Ponte C, Cilia V, Lambert C, Nicolas JL. Roseobacter gallaciensis sp. nov., a marine bacterium isolated from rearings and collectors of the scallop Pecten maximus. Int J Syst Bacteriol 1998; 48:537–542. PubMed http://dx.doi.org/10.1099/00207713-48-2-537View ArticlePubMedGoogle Scholar
  17. Moran MA, Buchan A, Gonzalez JM, Heidelbarg JF, Witman WB, Kiene JR, Henriksen JR, King GM, Belas R, Fuqua C, et al. Genome sequence of Silicibacter pomeroyi reveals adaptation to the marine environment. Nature 2004; 432:910–913. PubMed http://dx.doi.org/10.1038/nature03170View ArticlePubMedGoogle Scholar
  18. Beyersmann PG, Chertkov O, Petersen J, Fiebig A, Chen A, Pati A, Ivanova N, Lapidus A, Goodwin LA, Chain P, et al. Genome sequence of Phaeobacter caeruleustype strain (DSM 24564T), a surface-associated member of the marine Roseobacter clade. Stand Genomic Sci 2013; (this issue).
  19. Freese HM, Dalingault H, Petersen J, Pradella S, Davenport K, Teshima H, Chen A, Pati A, Ivanova N, Goodwin LA, et al. Genome sequence of the plasmid and phage-gene rich marine Phaeobacter arcticus type strain (DSM 23566T). Stand Genomic Sci 2013; (this issue).
  20. 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
  21. Woese CR, Kandler O, Weelis ML. Towards a natural system of organisms. Proposal for the domains Archaea and Bacteria. Proc Natl Acad Sci USA 1990; 87:4576–4579. PubMed http://dx.doi.org/10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
  22. Garrity GM, Bell JA, Lilburn T. Phylum XIV. Proteobacteria phyl nov. In: Brenner DJ, Krieg NR, Stanley JT, Garrity GM (eds), Bergey’s Manual of Sytematic Bacteriology, second edition. Vol. 2 (The Proteobacteria), part B (The Gammaproteobacteria), Springer, New York, 2005, p. 1.View ArticleGoogle Scholar
  23. Garrity GM, Bell JA, Lilburn T. Class I. Alphaproteobacteria class. nov. In: Brenner DJ, Krieg NR, Stanley JT, Garrity GM (eds), Bergey’s Manual of Sytematic Bacteriology, second edition. Vol. 2 (The Proteobacteria), part C (The Alpha-, Beta-, Delta-, and Epsilonproteobacteria), Springer, New York, 2005, p. 1.View ArticleGoogle Scholar
  24. Validation list No. 107. List of new names and new combinations previously effectively, but not validly, published. Int J Syst Evol Microbiol 2006; 56:1–6. PubMed http://dx.doi.org/10.1099/ijs.0.64188-0
  25. Garrity GM, Bell JA, Lilburn T. Order III. Rhodobacterales ord. nov. In: Brenner DJ, Krieg NR, Staley JT, Garrity GM (eds), Bergey’s Manual of Systematic Bacteriology, second edition. vol. 2 (The Proteobacteria), part C (The Alpha-, Beta-, Delta-, and Epsilonproteobacteria), Springer, New York, 2005, p. 161.Google Scholar
  26. Garrity GM, Bell JA, Lilburn T. Family I. Rhodobacteraceae fam. nov. In: Brenner DJ, Krieg NR, Staley JT, Garrity GM (eds), Bergey’s Manual of Systematic Bacteriology, second edition. vol. 2 (The Proteobacteria), part C (The Alpha-, Beta-, Delta-, and Epsilonproteobacteria), Springer, New York, 2005Google Scholar
  27. Schaefer JK, Goodwin KD, McDonald IR, Murrell JC, Oremland RS. Leisingera methylohalidivorans gen. nov., sp. nov., a marine methylotroph that grows on methyl bromide. Int J Syst Evol Microbiol 2002; 52:851–859. PubMed http://dx.doi.org/10.1099/ijs.0.01960-0PubMedGoogle Scholar
  28. Martens T, Heidorn T, Pukall R, Simon M, Tindall BJ, Brinkhoff T. Reclassification of Roseobacter gallaeciensis Ruiz-Ponte et al. 1998 as Phaeobacter gallaeciensis gen. nov., comb. nov., description of Phaeobacter inhibens sp. nov., reclassification of Ruegeria algicola (Lafay et al. 1995) Uchino et al. 1999 as Marinovum algicola gen. nov., comb. nov., and emended descriptions of the genera Roseobacter, Ruegeria and Leisingera. Int J Syst Evol Microbiol 2006; 56:1293–1304. PubMed http://dx.doi.org/10.1099/ijs.0.63724-0View ArticlePubMedGoogle Scholar
  29. BAuA. Classification of Bacteria and Archaea in risk groups. TRBA 2010; 466:93.Google Scholar
  30. 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
  31. Vaas LAI, Sikorski J, Michael V, Göker M, Klenk HP. Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics. PLoS ONE 2012; 7:e34846. PubMed http://dx.doi.org/10.1371/journal.pone.0034846PubMed CentralView ArticlePubMedGoogle Scholar
  32. Vaas LAI, Sikorski J, Hofer B, Fiebig A, Buddruhs N, Klenk HP, Göker M. opm: An R package for analyzing OmniLog Phenotype Microarray data. Bioinformatics 2013; 29:1823–1824. PubMed http://dx.doi.org/10.1093/bioinformatics/btt291View ArticlePubMedGoogle Scholar
  33. Yoon JH, Kang SJ, Lee SY, Oh TK. Phaeobacter daeponensis sp. nov., isolated from a tidal flat of the Yellow Sea in Korea. Int J Syst Evol Microbiol 2007; 57:856–861. PubMed http://dx.doi.org/10.1099/ijs.0.64779-0View ArticlePubMedGoogle Scholar
  34. List of growth media used at the DSMZ: http://www.dmsz.de/catalogues/cataloque-microorganisms/culture-technology/list-of-media-for-microorganisms.html.
  35. Gemeinholzer B, Dröge G, Zetzsche H, Haszprunar G, Klenk HP, Güntsch A, Berendsohn WG, Wägele JW. The DNA Bank Network: the start from a German initiative. Biopreserv Biobank 2011; 9:51–55. http://dx.doi.org/10.1089/bio.2010.0029View ArticlePubMedGoogle Scholar
  36. Bennett S. Solexa Ltd. Pharmacogenomics 2004; 5:433–438. PubMed http://dx.doi.org/10.1517/14622416.5.4.433View ArticlePubMedGoogle Scholar
  37. The DOE Joint Genome Institute. www.jgi.doe.gov
  38. Butler J, MacCallum I, Kleber M, Shlyakhter IA, Belmonte MK, Lander ES, Nusbaum C, Jaffe DB. ALLPATHS: de novo assembly of whole-genome shotgun microreads. Genome Res 2008; 18:810–820. PubMed http://dx.doi.org/10.1101/gr.7337908PubMed CentralView ArticlePubMedGoogle Scholar
  39. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829. PubMed http://dx.doi.org/10.1101/gr.074492.107PubMed CentralView ArticlePubMedGoogle Scholar
  40. Phrap and Phred for Windows. MacOS, Linux, and Unix. http://www.phrap.com
  41. Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
  42. Mavromatis K, Ivanova NN, Chen IM, Szeto E, Markowitz VM, Kyrpides NC. The DOE-JGI Standard operating procedure for the annotations of microbial genomes. Stand Genomic Sci 2009; 1:63–67. PubMed http://dx.doi.org/10.4056/sigs.632PubMed CentralView ArticlePubMedGoogle Scholar
  43. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods 2010; 7:455–457. PubMed http://dx.doi.org/10.1038/nmeth.1457View ArticlePubMedGoogle Scholar
  44. Markowitz VM, Ivanova NN, Chen IMA, Chu K, Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics 2009; 25:2271–2278. PubMed http://dx.doi.org/10.1093/bioinformatics/btp393View ArticlePubMedGoogle Scholar
  45. del Solar G, Giraldo R, Ruiz-Echevarria MJ, Espinosa M, Diaz-Orejes R. Replication and control of circular bacterial plasmids. Microbiol Mol Biol Rev 1998; 62:434–464. PubMedPubMed CentralPubMedGoogle Scholar
  46. Petersen J, Brinkmann H, Berger M, Brinkhoff T, Päuker O, Pradella S. Origin and evolution of a novel DnaA-like plasmid replication type in Rhodobacterales. Mol Biol Evol 2011; 28:1229–1240. PubMed http://dx.doi.org/10.1093/molbev/msq310View ArticlePubMedGoogle Scholar
  47. Petersen J. Phylogeny and compatibility: plasmid classification in the genomics era. Arch Microbiol 2011; 193:313–321. PubMedPubMedGoogle Scholar
  48. Petersen J, Brinkmann H, Pradella S. Diversity and evolution of repABC type plasmids in Rhodobacterales. Environ Microbiol 2009; 11:2627–2638. PubMed http://dx.doi.org/10.1111/j.1462-2920.2009.01987.xView ArticlePubMedGoogle Scholar
  49. Zielenkiewicz U, Ceglowski P. Mechanisms of plasmid stable maintenance with special focus on plasmid addiction systems. Acta Biochim Pol 2001; 48:1003–1023. PubMedPubMedGoogle Scholar
  50. Giraud MF, Naismith JH. The rhamnose pathway. Curr Opin Struct Biol 2000; 10:687–696. PubMed http://dx.doi.org/10.1016/S0959-440X(00)00145-7View ArticlePubMedGoogle Scholar
  51. Wagner-Döbler I, Ballhausen B, Berger M, Brinkhoff T, Buchholz I, Bunk B, Cypionka H, Daniel R, Drepper D, Gerdts G, et al. The complete genome sequence of the algal symbiont Dinoroseobacter shibae: a hitchhiker’s guide to life in the sea. ISME J 2010; 4:61–77. PubMed http://dx.doi.org/10.1038/ismej.2009.94View ArticlePubMedGoogle Scholar
  52. Petersen J, Frank O, Göker M, Pradella S. Extrachromosomal, extraordinary and essential-the plasmids of the Roseobacter clade. Appl Microbiol Biotechnol 2013; 97:2805–2815. PubMed http://dx.doi.org/10.1007/s00253-013-4746-8View ArticlePubMedGoogle Scholar
  53. Lawley TD, Klimke WA, Gubbins MJ, Frost LS. F factor conjugation is a true type IV secretion system. FEMS Microbiol Lett 2003; 224:1–15. PubMed http://dx.doi.org/10.1016/S0378-1097(03)00430-0View ArticlePubMedGoogle Scholar
  54. Zech H, Thole S, Schreiber K, Kalhöfer D, Voget S, Brinkhoff T, Simon M, Schomburg D, Rabus R. Growth phase-dependent global protein and metabolite profiles of Phaeobacter gallaeciensis strain DSM 17395, a member of the marine Roseobacter-clade. Proteomics 2009; 9:3677–3697. PubMed http://dx.doi.org/10.1002/pmic.200900120View ArticlePubMedGoogle Scholar
  55. Petersen J, Brinkmann H, Bunk B, Michael V, Päuker O, Pradella S. Think pink: photosynthesis, plasmids and the Roseobacter clade. Environ Microbiol 2012; 14:2661–2672. PubMed http://dx.doi.org/10.1111/j.1462-2920.2012.02806.xView ArticlePubMedGoogle Scholar
  56. Fürch T, Preusse M, Tomasch J, Zech H, Wagner-Döbler I, Rabus R, Wittmann C. Metabolic fluxes in the central carbon metabolism of Dinoroseobacter shibae and Phaeobacter gallaeciensis, two members of the marine Roseobacter clade. BMC Microbiol 2009; 9:209. PubMed http://dx.doi.org/10.1186/1471-2180-9-209PubMed CentralView ArticlePubMedGoogle Scholar
  57. Schwarz S, Hood RD, Mougous JD. What is type VI secretion doing in all those bugs? Trends Microbiol 2010; 18:531–537. PubMed http://dx.doi.org/10.1016/j.tim.2010.09.001PubMed CentralView ArticlePubMedGoogle Scholar
  58. Wagner-Döbler I, Thiel V, Eberl L, Allgaier M, Bodor A, Meyer S, Ebner S, Hennig A, Pukall R, Schulz S. Discovery of complex mixtures of novel long-chain quorum sensing signals in free-living and host-associated marine alphaproteobacteria. ChemBioChem 2005; 6:2195–2206. PubMed http://dx.doi.org/10.1002/cbic.200500189View ArticlePubMedGoogle Scholar
  59. Auch AF, Von Jan M, Klenk HP, Göker 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
  60. Auch AF, Klenk HP, Göker 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
  61. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60. PubMed http://dx.doi.org/10.1186/1471-2105-14-60PubMed CentralView ArticlePubMedGoogle Scholar

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