Open Access

Genome sequence of Frateuria aurantia type strain (Kondô 67T), a xanthomonade isolated from Lilium auratium Lindl.

  • Iain Anderson1,
  • Huzuki Teshima1, 2,
  • Matt Nolan1,
  • Alla Lapidus3, 4,
  • Hope Tice1,
  • Tijana Glavina Del Rio1,
  • Jan-Fang Cheng1,
  • Cliff Han1, 2,
  • Roxanne Tapia1, 2,
  • Lynne A. Goodwin1, 2,
  • Sam Pitluck1,
  • Konstantinos Liolios1,
  • Konstantinos Mavromatis1,
  • Ioanna Pagani1,
  • Natalia Ivanova1,
  • Natalia Mikhailova1,
  • Amrita Pati1,
  • Amy Chen5,
  • Krishna Palaniappan5,
  • Miriam Land6,
  • Manfred Rohde7,
  • Elke Lang8,
  • John C. Detter1, 2,
  • Markus Göker8,
  • Tanja Woyke1,
  • James Bristow1,
  • Jonathan A. Eisen1, 9,
  • Victor Markowitz5,
  • Philip Hugenholtz1, 10,
  • Nikos C. Kyrpides1 and
  • Hans-Peter Klenk8Email author
Standards in Genomic Sciences20139:9010083

https://doi.org/10.4056/sigs.4338002

Published: 16 October 2013

Abstract

Frateuria aurantia (ex Kondô and Ameyama 1958) Swings et al. 1980 is a member of the bispecific genus Frateuria in the family Xanthomonadaceae, which is already heavily targeted for non-type strain genome sequencing. Strain Kondô 67T was initially (1958) identified as a member of ‘Acetobacter aurantius’, a name that was not considered for the approved list. Kondô 67T was therefore later designated as the type strain of the newly proposed acetogenic species Frateuria aurantia. The strain is of interest because of its triterpenoids (hopane family). F. aurantia Kondô 67T is the first member of the genus Frateura whose genome sequence has been deciphered, and here we describe the features of this organism, together with the complete genome sequence and annotation. The 3,603,458-bp long chromosome with its 3,200 protein-coding and 88 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Keywords

strictly aerobicmotilerod-shapedacetogenicmesophilicAcetobacter aurantius Xanthomonadaceae GEBA

Introduction

Strain Kondô 67T, also known as G-6T and as IFO 3245T (= DSM 6220 = ATCC 33424 = NBRC 3245) is the type strain of the species Frateuria aurantia [1], the type species in the bispecific genus Frateuria [1]. Kondô 67T was originally isolated from Lilium auratum Lindl and classified as a member of ‘Acetobacter aurantius’ from which it was reclassified 22 years later as the type strain of the type species of Frateuria [1]. The genus was named after the Belgian microbiologist Joseph Frateur (1903-1974) [1]; the species epithet is derived from the Neo-Latin adjective aurantia, referring to the gold-yellow color of the strain on MYP agar [1]. Strain Kondô 67T was characterized as ‘acetogenic’ [2] and as containing triterpenoids of the hopane family [3]. Here we present a summary classification and a set of features for F. aurantia Kondô 67T, together with the description of the genomic sequencing and annotation.

Classification and features

A representative genomic 16S rRNA gene sequence of strain Kondô 67T was compared using NCBI BLAST [4,5] 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 [6] and the relative frequencies of taxa and keywords (reduced to their stem [7]) were determined, weighted by BLAST scores. The most frequently occurring genera were Dyella (34.3%), Rhodanobacter (24.0%), Frateuria (19.6%), Luteibacter (11.9%) and ‘Luteibactor’ (3.7%) (105 hits in total). Regarding the eleven hits to sequences from members of the species, the average identity within HSPs was 99.6%, whereas the average coverage by HSPs was 100.0%. Among all other species, the one yielding the highest score was Dyella ginsengisoli (EF191354), which corresponded to an identity of 98.2% and an HSP coverage of 99.0%. (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 HM556321 (‘insect herbivore microbiome plant biomass-degrading capacity Atta colombica colony N11 fungus garden top clone TIBW663’), which showed an identity of 99.7% and an HSP coverage of 97.2%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were ‘soil’ (5.9%), ‘sediment’ (2.5%), ‘microbi’ (1.8%), ‘enrich’ (1.5%) and ‘vent’ (1.3%) (145 hits in total). The most frequently occurring keyword within the labels of those environmental samples which yielded hits of a higher score than the highest scoring species was ‘atta, biomass-degrad, capac, colombica, coloni, fungu, garden, herbivor, insect, microbiom, plant, top’ (8.3%) (6 hits in total), reflecting some of the known features of the strain’s origin.

Figure 1 shows the phylogenetic neighborhood of F. aurantia in a 16S rRNA based tree. The sequences of the four identical 16S rRNA gene copies in the genome differ by one nucleotide from the previously published 16S rRNA sequence (AB091194).
Figure 1.

Phylogenetic tree highlighting the position of F. aurantia relative to the type strains of the other species within the family Xanthomonadaceae. The tree was inferred from 1,431 aligned characters [8,9] of the 16S rRNA gene sequence under the maximum likelihood (ML) criterion [10]. Rooting was done initially using the midpoint method [11] 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 750 ML bootstrap replicates [12] (left) and from 1,000 maximum-parsimony bootstrap replicates [13] (right) if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [14] are labeled with one asterisk, those also listed as ‘Complete and Published’ with two asterisks.

F. aurantia Kondô 67T cells stain Gram-negative [1], were straight rod shaped, 0.5–0.7 µm in width and 0.7–3.5 µm in length (Figure 2) [1] and motile via polar flagella [1] (not visible in Figure 2). Cells occur singly or in pairs, rarely in filaments [1]. Cultures grow in dark, glistening, flat colonies with a soluble brown pigment [1]. They are oxidase positive and catalase negative [1]; physiological features and antibiotic susceptibilities were reported in great detail in [1]. Cells grow well at pH 3.6 and 34°C [1].
Figure 2.

Scanning electron micrograph of F. aurantia Kondô 67T

Chemotaxonomy

Besides trace amounts of diploptene and rearranged compounds like fern-7-ene [3], the main lipids isolated from DSM 6220T are iso-branched fatty acids and triterpenoids of the hopane family, such as bacteriohopanetetrol and derived hopanoid. The organism also produces ubiquinone Q8 [27].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [28], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [29]. The genome project is deposited in the Genomes On Line Database [14] and the complete genome sequence is deposited in GenBank. Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI) using state of the art sequencing technology [30]. A summary of the project information is shown in Table 2.
Table 1.

Classification and general features of F. aurantia Kondô 67T according to the MIGS recommendations [15] (published by the Genome Standards Consortium [16]) and NamesforLife [17].

MIGS ID

Property

Term

Evidence code

 

Current classification

Domain Bacteria

TAS [18]

 

Phylum Proteobacteria

TAs [19]

 

Class Gammaproteobacteria

TAS [20,21]

 

Order Xanthomonadales

TAS [20,22]

 

Family Xanthomonadaceae

TAS [20,22]

 

Genus Frateuria

TAS [1,23]

 

Species Frateuria aurantia

TAS [1]

 

Type strain Kondô 67 = G-6 = IFO 3245

TAS [1]

 

Gram stain

negative

TAS [1]

 

Cell shape

rod-shaped, mostly strait

TAS [1]

 

Motility

motile

TAS [1]

 

Sporulation

not reported

 
 

Temperature range

mesophile

TAS [1]

 

Optimum temperature

30–C

TAS [1]

 

Salinity

0.2–2% NaCl (w/v)

TAS [1]

MIGS-22

Oxygen requirement

aerobe

TAS [1]

 

Carbon source

glucose, yeast extract, mannitol, peptone

TAS [1]

 

Energy metabolism

organoheterotroph

TAS [1]

MIGS-6

Habitat

Lilium auratum

TAS [1]

MIGS-15

Biotic relationship

host-associated

TAS [1]

MIGS-14

Pathogenicity

none

NAS

 

Biosafety level

1

TAS [24]

MIGS-23.1

Isolation

from Lilium auratum Lindl

TAS [25]

MIGS-4

Geographic location

Kawasaki, Japan

TAS [1]

MIGS-5

Sample collection time

1958 or before

TAS [25]

MIGS-4.1

Latitude

35.50

TAS [1]

MIGS-4.2

Longitude

139.77

TAS [1]

MIGS-4.3

Depth

not reported

 

MIGS-4.4

Altitude

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 [26].

Table 2.

Genome sequencing project information

MIGS ID

Property

Term

MIGS-31

Finishing quality

Finished

MIGS-28

Libraries used

Two genomic libraries: one 454 PE library (7.5 kb insert size), one Illumina library

MIGS-29

Sequencing platforms

Illumina GAii, 454 GS FLX Titanium

MIGS-31.2

Sequencing coverage

537.4 × Illumina; 8.6 × pyrosequence

MIGS-30

Assemblers

Newbler version 2.3-PreRelease-6/30/2009, Velvet 1.0.13, phrap version SPS - 4.24

MIGS-32

Gene calling method

Prodigal

 

INSDC ID

CP003350

 

GenBank Date of Release

June 14, 2012

 

GOLD ID

Gc02155

 

NCBI project ID

64505

 

Database: IMG

2509601034

MIGS-13

Source material identifier

DSM 6220

 

Project relevance

Tree of Life, GEBA

Growth conditions and DNA isolation

F. aurantia strain Kondô 67T, DSM 6220, was grown in DSMZ medium 360 (YPM medium) [31] at 30°C. DNA was isolated from 0.5–1 g of cell paste using standard procedures at the DSMZ DNA laboratory and quality control processes requested by the sequencing center (JGI). DNA is available through the DNA Bank Network [32].

Genome sequencing and assembly

The genome was sequenced using a combination of Illumina and 454 sequencing platforms. All general aspects of library construction and sequencing can be found at the JGI website [33]. Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 36 contigs in one scaffold was converted into a phrap [34] assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (2,074.3 Mb) was assembled with Velvet [35] and the consensus sequences were shredded into 1.5 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 63.7Mb 454 draft data. Newbler parameters are -consed -a 50 -l 350 -g -m -ml 20. The Phred/Phrap/Consed software package [34] was used for sequence assembly and quality assessment in the subsequent finishing process. After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with gapResolution [33], Dupfinisher [36], or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F. Chang, unpublished). A total of 43 additional reactions and one shatter library were necessary to close gaps and to raise the quality of the final sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using a software Polisher developed at JGI [37]. The error rate of the final genome sequence is less than 1 in 100,000.

Together, the combination of the Illumina and 454 sequencing platforms provided 546.0 × coverage of the genome. The final assembly contained 163,130 pyrosequence and 25,455,174 Illumina reads.

Genome annotation

Genes were identified using Prodigal [38] as part of the DOE-JGI [39] genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [40]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) non-redundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. These data sources were combined to assert a product description for each predicted protein. Additional gene prediction analysis and functional annotation were performed within the Integrated Microbial Genomes - Expert Review (IMG-ER) platform [41].

Genome properties

The genome consists of a 3,603,458 bp long circular chromosome with a G+C content of 63.4% (Table 3 and Figure 3). Of the 3,288 genes predicted, 3,200 were protein-coding genes, and 88 RNAs; 99 pseudogenes were also identified. The majority of the protein-coding genes (79.6%) 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 outside to center: 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)

3,603,458

100.00%

DNA coding region (bp)

3,189,580

88.51%

DNA G+C content (bp)

2,284,441

63.40%

Number of replicons

1

 

Extrachromosomal elements

0

 

Total genes

3,288

100.00%

RNA genes

88

2.68%

rRNA operons

4

 

tRNA genes

73

2.22%

Protein-coding genes

3,200

97.32%

Pseudo genes

99

3.01%

Genes with function prediction (proteins)

2,616

79.56%

Genes in paralog clusters

1,350

41.06%

Genes assigned to COGs

2,610

79.38%

Genes assigned Pfam domains

2,724

82.85%

Genes with signal peptides

313

9.52%

Genes with transmembrane helices

722

21.96%

CRISPR repeats

1

 
Table 4.

Number of genes associated with the general COG functional categories

Code

value

%age

Description

J

167

5.7

Translation, ribosomal structure and biogenesis

A

1

0.0

RNA processing and modification

K

192

6.6

Transcription

L

145

5.0

Replication, recombination and repair

B

1

0.0

Chromatin structure and dynamics

D

30

1.0

Cell cycle control, cell division, chromosome partitioning

Y

0

0.0

Nuclear structure

V

56

1.9

Defense mechanisms

T

129

4.4

Signal transduction mechanisms

M

214

7.3

Cell wall/membrane biogenesis

N

92

3.1

Cell motility

Z

0

0.0

Cytoskeleton

W

0

0.0

Extracellular structures

U

112

3.8

Intracellular trafficking and secretion, and vesicular transport

O

133

4.5

Posttranslational modification, protein turnover, chaperones

C

186

6.4

Energy production and conversion

G

170

5.8

Carbohydrate transport and metabolism

E

209

7.1

Amino acid transport and metabolism

F

68

2.3

Nucleotide transport and metabolism

H

143

4.9

Coenzyme transport and metabolism

I

101

3.5

Lipid transport and metabolism

P

146

5.0

Inorganic ion transport and metabolism

Q

63

2.2

Secondary metabolites biosynthesis, transport and catabolism

R

323

11.0

General function prediction only

S

246

8.4

Function unknown

-

678

20.6

Not in COGs

Notes

Declarations

Acknowledgements

We would like to gratefully acknowledge the help of Markus Kopitz for growing F. aurantia cultures and Susanne Schneider for DNA extractions and quality control (both at DSMZ). This work was performed under the auspices of the US Department of Energy Office of Science, Biological and Environmental Research Program, and by the University of California, Lawrence Berkeley National Laboratory under contract No. DE-AC02-05CH11231, Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344, and Los Alamos National Laboratory under contract No. DE-AC02-06NA25396, UT-Battelle and Oak Ridge National Laboratory under contract DE-AC05-00OR22725, as well as German Research Foundation (DFG) INST 599/1-2 and in part by the Russian Ministry of Science Mega-grant no.11.G34.31.0068; SJ O’Brien Principal Investigator.

Authors’ Affiliations

(1)
DOE Joint Genome Institute
(2)
Bioscience Division, Los Alamos National Laboratory
(3)
Theodosius Dobzhansky Center for Genome Bionformatics, St. Petersburg State University
(4)
Algorithmic Biology Lab, St. Petersburg Academic University
(5)
Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory
(6)
Oak Ridge National Laboratory
(7)
HZI - Helmholtz Centre for Infection Research
(8)
Leibniz Institute, DSMZ - German Collection of Microorganisms and Cell Cultures
(9)
University of California Davis Genome Center
(10)
Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland

References

  1. Swings J, Gillis M, Kersters K, De Vos P, Gosselé F, de Ley J. Frateuria, a new genus for “Acetobacter aurantius”. Int J Syst Bacteriol 1980; 30:547–556. http://dx.doi.org/10.1099/00207713-30-3-547View ArticleGoogle Scholar
  2. Johnson DB, Rolfe S, Hallberg KB, Iversen E. Isolation and phylogenetic characterization of acidophilic microorganisms indigenous to acidic drainage waters at an abandoned Norwegian copper mine. Environ Microbiol 2001; 3:630–637. PubMed http://dx.doi.org/10.1046/j.1462-2920.2001.00234.xView ArticlePubMedGoogle Scholar
  3. Joyeux C, Fouchard S, Llopiz P, Neunlist S. Influence of the temperature and the growth phase on the hopanoids and fatty acids content of Frateuria aurantia (DSMZ 6220). FEMS Microbiol Ecol 2004; 47:371–379. PubMed http://dx.doi.org/10.1016/S0168-6496(03)00302-7View ArticlePubMedGoogle Scholar
  4. 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
  5. Korf I, Yandell M, Bedell J. BLAST, O’Reilly, Sebastopol, 2003.Google Scholar
  6. 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
  7. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.View ArticleGoogle Scholar
  8. 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
  9. 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.a026334View ArticlePubMedGoogle Scholar
  10. 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
  11. 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.1095-8312.2007.00864.xView ArticleGoogle Scholar
  12. 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
  13. Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods), Version 4.0 b10. Sinauer Associates, Sunderland, 2002.Google Scholar
  14. Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, Markowitz VM, Kyrpides NC. The Genomes OnLine 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
  15. 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
  16. Field D, Amaral-Zettler L, Cochrane G, Cole JR, Dawyndt P, Garrity GM, Gilbert J, Glöckner FO, Hirschman L, Karsch-Mzrachi I, et al. PLoS Biol 2011; 9:e1001088. PubMed http://dx.doi.org/10.1371/journal.pbio.1001088PubMed CentralView ArticlePubMedGoogle Scholar
  17. Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today 2010; 37:9.Google Scholar
  18. Woese CR, Kandler O, Wheelis 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
  19. Garrity GM, Bell JA, Lilburn T. Phylum XIV. Proteobacteria phyl. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 1.View ArticleGoogle Scholar
  20. 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
  21. Garrity GM, Bell JA, Lilburn T. Class III. Gammaproteobacteria class. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 1.View ArticleGoogle Scholar
  22. Saddler GS, Bradbury JF. Order III. Xanthomonadales ord. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 63.View ArticleGoogle Scholar
  23. Zhang JY, Liu XY, Liu SJ. Frateuria terrea sp. nov., isolated from forest soil, and emended description of the genus Frateuria. Int J Syst Evol Microbiol 2011; 61:443–447. PubMed http://dx.doi.Org/10.1099/ijs.0.021618-0View ArticlePubMedGoogle Scholar
  24. BAuA. 2010, Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466, p. 89.
  25. Kondô K, Ameyama M. Carbohydrate metabolism by Acetobacter species. I. Oxidative activity for various carbohydrates. Bull Agric Chem Soc Jpn 1958; 22:369–372. http://dx.doi.org/10.1271/bbb1924.22.369View ArticleGoogle Scholar
  26. 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
  27. Yamada Y, Okada Y, Kondô K. Isolation and characterization of “polarly flaggelated intermediate strains” in acetic bacteria. J Gen Appl Microbiol 1976; 22:237–245. http://dx.doi.org/10.2323/jgam.22.237View ArticleGoogle Scholar
  28. Klenk HP, Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol 2010; 33:175–182. PubMed http://dx.doi.org/10.1016/j.syapm.2010.03.003View ArticlePubMedGoogle Scholar
  29. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, Kunin V, Goodwin L, Wu M, Tindall BJ, et al. A phylogeny-driven Genomic Encyclopedia of Bacteria and Archaea. Nature 2009; 462:1056–1060. PubMed http://dx.doi.org/10.1038/nature08656PubMed CentralView ArticlePubMedGoogle Scholar
  30. Mavromatis K, Land ML, Brettin TS, Quest DJ, Copeland A, Clum A, Goodwin L, Woyke T, Lapidus A, Klenk HP, et al. The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation. PLoS ONE 2012; 7:e48837. PubMed http://dx.doi.org/10.1371/journal.pone.0048837PubMed CentralView ArticlePubMedGoogle Scholar
  31. List of growth media used at DSMZ: http://www.dsmz.de/catalogues/catalogue-microorganisms/culture-technology/list-of-media-for-microorganisms.html.
  32. 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
  33. The DOE Joint Genome Institute. www.jgi.doe.gov
  34. Phrap and Phred for Windows. MacOS, Linux, and Unix. www.phrap.com
  35. 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
  36. Han C, Chain P. Finishing repeat regions automatically with Dupfinisher. In: Proceedings of the 2006 international conference on bioinformatics & computational biology. Arabnia HR, Valafar H (eds), CSREA Press. June 26–29, 2006: 141–146.Google Scholar
  37. Lapidus A, LaButti K, Foster B, Lowry S, Trong S, Goltsman E. POLISHER: An effective tool for using ultra short reads in microbial genome assembly and finishing. AGBT, Marco Island, FL, 2008.Google Scholar
  38. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal Prokaryotic Dynamic Programming Genefinding Algorithm. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
  39. 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
  40. Pati A, Ivanova N, Mikhailova N, Ovchinikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: A Gene Prediction Improvement Pipeline for microbial genomes. Nat Methods 2010; 7:455–457. PubMed http://dx.doi.org/10.1038/nmeth.1457View ArticlePubMedGoogle Scholar
  41. 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

Copyright

© The Author(s) 2013