- Open Access
Complete genome sequence of Cellulophaga lytica type strain (LIM-21T)
- Amrita Pati1,
- Birte Abt2,
- Hazuki Teshima1, 3,
- Matt Nolan1,
- Alla Lapidus1,
- Susan Lucas1,
- Nancy Hammon1,
- Shweta Deshpande1,
- Jan-Fang Cheng1,
- Roxane Tapia1, 3,
- Cliff Han3,
- Lynne Goodwin1, 3,
- Sam Pitluck1,
- Konstantinos Liolios1,
- Ioanna Pagani1,
- Konstantinos Mavromatis1,
- Galina Ovchinikova1,
- Amy Chen4,
- Krishna Palaniappan4,
- Miriam Land1, 5,
- Loren Hauser1, 5,
- Cynthia D. Jeffries1, 5,
- John C. Detter1, 3,
- Evelyne-Marie Brambilla2,
- K. Palani Kannan2,
- Manfred Rohde6,
- Stefan Spring2,
- Markus Göker2,
- Tanja Woyke1,
- James Bristow1,
- Jonathan A. Eisen1, 7,
- Victor Markowitz4,
- Philip Hugenholtz1, 8,
- Nikos C. Kyrpides1,
- Hans-Peter Klenk2 and
- Natalia Ivanova1
© The Author(s) 2011
- Published: 29 April 2011
Cellulophaga lytica (Lewin 1969) Johansen et al. 1999 is the type species of the genus Cellulophaga which belongs to the family Flavobacteriaceae within the phylum ‘Bacteroidetes’ and was isolated from marine beach mud in Limon, Costa Rica. The species is of biotechnological interest because its members produce a wide range of extracellular enzymes capable of degrading proteins and polysaccharides. After the genome sequence of Cellulophaga algicola this is the second completed genome sequence of a member of the genus Cellulophaga. The 3,765,936 bp long genome with its 3,303 protein-coding and 55 RNA genes consists of one circular chromosome and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.
- motile by gliding
Strain LIM-21T (DSM 7489 = ATCC 23178 = JCM 8516) is the type strain of the species Cellulophaga lytica, which is the type species of the genus Cellulophaga . The genus currently consists of five more validly named species : C. algicola , C. baltica, C. fucicola , C. pacifica  and C. tyrosinoxydans . The species was first described in 1969 by Lewin as ‘Cytophaga lytica’ , and was subsequently transferred to the novel genus Cellulophaga as type strain C. lytica . The genus name is derived from the Neo-Latin word ‘cellulosum’ meaning ‘cellulose’ and the latinized Greek word ‘phagein’ meaning ‘to eat’, yielding the Neo-Latin word ‘Cellulophaga’ meaning ‘eater of cellulose’ . The species epithet is derived from the Neo-Latin word ‘lytica’ (loosening, dissolving) . Here we present a summary classification and a set of features for C. lytica strain LIM-21T, together with the description of the complete genomic sequencing and annotation.
A representative genomic 16S rRNA sequence of strain LIM-21T was compared using NCBI BLAST 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  and the relative frequencies, weighted by BLAST scores, of taxa and keywords (reduced to their stem ) were determined. The five most frequent genera were Cellulophaga (37.3%), Flavobacterium (8.5%), Cytophaga (6.3%), Aquimarina (5.8%) and Arenibacter (5.7%) (141 hits in total). Regarding the ten hits to sequences from members of the species, the average identity within HSPs was 99.0%, whereas the average coverage by HSPs was 93.3%. Regarding the eleven hits to sequences from other members of the genus, the average identity within HSPs was 94.0%, whereas the average coverage by HSPs was 93.1%. Among all other species, the one yielding the highest score was Cytophaga lytica (M62796), which corresponded to an identity of 99.2% and an HSP coverage of 96.9%. (Note that the Greengenes databases uses the INSDC (= EMBL/NCBI/DDBJ) annotation, which is not an authoritative source for nomenclature or classification). The highest-scoring environmental sequence was EU246790 (‘Identification microorganism Libya untreated Mediterranean sea water feed reverse osmosis plant isolate RSW1-4RSW1-4 str. RSW1-4’), which showed an identity of 100.0% and an HSP coverage of 96.2%. The five most frequent keywords within the labels of environmental samples which yielded hits were ‘sea’ (5.6%), ‘water’ (4.8%), ‘marin’ (3.6%), ‘sediment’ (3.1%) and ‘surfac’ (2.8%) (109 hits in total). The single most frequent keyword within the labels of environmental samples which yielded hits of a higher score than the highest scoring species was ‘feed, identif, libya, mediterranean, microorgan, osmosi, plant, revers, sea, untreat, water’ (9.1%) (1 hit in total).
Classification and general features of C. lytica LIM-21T according to the MIGS recommendations .
Species Cellulophaga lytica
Type strain LIM-21
motile by gliding
up to 8% NaCl
Limon, Costa Rica
Sample collection time
C. lytica is aerobic and chemoorganotrophic . The organism can degrade agar, alginate, gelatin and starch [24,25], but not casein, cellulose (filter paper), chitin, alginic acid, elastin or fibrinogen [1,25]. There are conflicting observations describing the ability of C. lytica to degrade carboxymethylcellulose (CMC). Whereas most authors [3,5,24,25] describe the hydrolysis of CMC, Nedashkovskaya et al. 2004  did not observe its degradation by C. lytica. Nitrate reduction and denitrification are negative . C. lytica is catalase  and oxidase positive . Acid is formed oxidatively from cellobiose, galactose, glucose, lactose, maltose and xylose . C. lytica is sensitive to oleandomycin, lincomycin and shows resistance to benzylpenicillin, carbencillin, gentamicin, kanamycin, neomycin, ampicillin, streptomycin and tetracycline .
The fatty acid profiles of four C. lytica strains were analyzed by Bowman in 2000 . The predominant cellular acids of these four analyzed C. lytica strains were branched-chain saturated and unsaturated fatty acids and straight-chain saturated and monounsaturated fatty acids, namely i-C15:0 (18.9%), i-C15:1ω10c (10.3%), i-C17:1ω7c (5.1%), C15:0 (9.3%), C16:1ω7c (9.0%), i-C15:0 3-OH (6.2%), i-C16:0 3-OH (5.2%) and i-C17:0 3-OH (20.8%) . The isoprenoid quinones of C. lytica were not determined, but for C. pacifica the presence of MK-6 as the major lipoquinone was described . Polar lipids have not been studied.
Genome project history
Genome sequencing project information
Three genomic libraries: one 454 pyrosequence standard library, one 454 PE library (8 kb insert size), one Illumina library
Illumina GAii, 454 GS FLX Titanium
1,605.2 × (Illumina); 22.9 × (pyrosequence)
Newbler version 2.5-internal-10Apr08, Velvet version 0.7.63, phrap version SPS-4.24
Gene calling method
Prodigal 1.4, GenePRIMP
Genbank Date of Release
February 28, 2011
NCBI project ID
Source material identifier
Tree of Life, GEBA
Growth conditions and DNA isolation
C. lytica LIM-21T, DSM 7489, was grown in DSMZ medium 514 (BACTO marine broth)  at 28°C. DNA was isolated from 0.5–1 g of cell paste using MasterPure Gram-positive DNA purification kit (Epicentre MGP04100) following the standard protocol as recommended by the manufacturer with modification st/DL for cell lysis as described in Wu et al. . DNA is available through the DNA Bank Network .
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 . Pyrosequencing reads were assembled using the Newbler assembler version 2.5-internal-10Apr08 (Roche). The initial Newbler assembly consisting of 28 contigs in one scaffold was converted into a phrap version SPS - 4.24  assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (3,907 Mb) was assembled with Velvet  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 156.1 Mb 454 draft data and all of the 454 paired end data. Newbler parameters are -consed -a 50 -l 350 -g -m -ml 20. The Phred/Phrap/Consed software package  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 , Dupfinisher , or sequencing cloned bridging PCR fragments with subcloning or transposon bombing (Epicentre Biotechnologies, Madison, WI). Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F.Chang, unpublished). A total of 238 additional reactions and two shatter libraries were necessary to close gaps and to raise the quality of the finished sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using a software Polisher developed at JGI . The error rate of the completed genome sequence is less than 1 in 100,000. Together, the combination of the Illumina and 454 sequencing platforms provided 1,628.1 × coverage of the genome. The final assembly contained 282,018 pyrosequence and 78,832,334 Illumina reads.
Genes were identified using Prodigal  as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline . 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 .
% of Total
Genome size (bp)
DNA coding region (bp)
DNA G+C content (bp)
Number of replicons
Genes with function prediction
Genes in paralog clusters
Genes assigned to COGs
Genes assigned Pfam domains
Genes with signal peptides
Genes with transmembrane helices
Number of genes associated with the general COG functional categories
Translation, ribosomal structure and biogenesis
RNA processing and modification
Replication, recombination and repair
Chromatin structure and dynamics
Cell cycle control, cell division, chromosome partitioning
Signal transduction mechanisms
Cell wall/membrane/envelope biogenesis
Intracellular trafficking, secretion, and vesicular transport
Posttranslational modification, protein turnover, chaperones
Energy production and conversion
Carbohydrate transport and metabolism
Amino acid transport and metabolism
Nucleotide transport and metabolism
Coenzyme transport and metabolism
Lipid transport and metabolism
Inorganic ion transport and metabolism
Secondary metabolites biosynthesis, transport and catabolism
General function prediction only
Not in COGs
A closer look at the genome sequence of strain LIM-21T revealed a set of genes which might be responsible for the yellow-orange color of C. lytica cells by encoding enzymes that are involved in the synthesis of carotenoids. Carotenoids are produced by the action of geranylgeranyl pyrophosphate synthase (Celly_1682), phytoene synthase (Celly_0459), phytoene desaturase (Celly_0458), lycopene cyclase (Celly_0462) and carotene hydroxylase (Celly_0461). Geranylgeranyl pyrophosphate synthases start the biosynthesis of carotenoids by combining farnesyl pyrophosphate with C5 isoprenoid units to C20-molecules, geranylgeranyl pyrophosphate. The phytoene synthase catalyzes the condensation of two geranylgeranyl pyrophosphate molecules followed by the removal of diphosphate and a proton shift leading to the formation of phytoene. Sequential desaturation steps are conducted by the phytoene desaturase followed by cyclization of the ends of the molecules catalyzed by the lycopene cyclase . This above mentioned set of genes was also found in the genome of C. algicola .
Strain LIM 21T produces a wide range of extracellular enzymes degrading proteins and polysaccharides. C. lytica, like the other members of the genus Cellulophaga, cannot hydrolyze filter paper or cellulose in its crystalline form, though they can hydrolyze the soluble cellulose derivative carboxymethylcellulose (CMC). The genome sequence of strain LIM 21T revealed the presence of three cellulases (Celly_0269, Celly_0304, Celly_0965), probably responsible for the hydrolysis of CMC. In addition two β-glucosidases (Celly_3249, Celly_1282) were identified in the genome, catalyzing the breakdown of the glycosidic β-1,4 bond between two glucose molecules in cellobiose. The deduced amino acid sequence of Celly_0304 shows 90% identity to the deduced sequence of the C. algicola cellulase coding gene Celly_0025. The identity of the deduced amino acid sequences of the cellulase encoding genes Celly_0269 and Celly_2753 is 65%. The neighborhoods of these two C. lytica cellulase genes have a similar structure like the respective genome regions in C. algicola, with orthologs belonging to different COG categories.
The LIM 21T genome contains 15 genes coding for sulfatases, which are located in close proximity to glycoside hydrolase genes suggesting that sulfated polysaccharides may be used as substrates. α-L-fucoidan could be a substrate, as three α-L-fucosidases (Celly_0440, Celly_0442, Celly_0449) are located in close proximity to nine sulfatases (Celly_0432, Celly_0425, Celly_0426, Celly_0436, Celly_0431, Celly_0433, Celly_0435, Celly_0438, Celly_0444). Sakai and colleagues report the existence of intracellular α-L-fucosidases and sulfatases, which enable ‘Fucophilus fucoidanolyticus’ to degrade fucoidan .
The above mentioned sulfatases and fucosidases containing region of C. lytica is similar to the recently described region of C. algicola with five α-L-fucosidases and three sulfatases . This fucoidan degrading ability could be also shared by Coraliomargarita akajimensis, as the annotation of the genome sequence revealed the existence of 49 sulfatases and 12 α-L-fucosidases .
The genomes of the two recently sequenced Cellulophaga type strains differ significantly in their size, C. lytica having 3.8 Mb and C. algicola 4.9 Mb and their number of pseudogenes, 19 (0.6%) and 122 (2.8%), respectively. Liu et al., 2004 have shown that pseudogenes in prokaryotes are not uncommon; the analysis of 64 genomes, including archaea, pathogen and nonpathogen bacteria, revealed an occurrence of pseudogenes of at least 1–5% of all gene-like sequences, with some genomes containing considerably higher amounts .
To estimate the overall similarity between the genomes of C. lytica and C. algicola the GGDC-Genome-to-Genome Distance Calculator [45,46] was used. The system calculates the distances by comparing the genomes to obtain HSPs (high-scoring segment pairs) and interfering distances from the set of formulas (1, HSP length / total length; 2, identities / HSP length; 3, identities / total length). The comparison of the genomes of C. lytica with C. algicola revealed that 25% of the average of both genome lengths are covered with HSPs. The identity within these HSPs was 82%, whereas the identity over the whole genome was only 20%. These results demonstrate that according to the whole genomes of C. lytica and C. algicola the similarity is not very high, although the comparison of 16S rRNA gene sequences showed only 7.7% differences.
In order to compare the C. lytica and C. algicola genomes, correlation values (Pearson coefficient) according to the similarity on the level of COG category, pfam, enzymes and TIGRfam were calculated. The highest correlation value (0.98) was reached on the level of pfam data; the correlation values on the basis of COG, enzyme and TIGRfam data were 0.88, 0.92 and 0.93, respectively. As a correlation value of 1 indicates the highest correlation, we can find a quite high correlation between the genomes of C. lytica and C. algicola at least considering the pfam data .
The comparison of the number of genes belonging to the different COG categories revealed no large differences in the genomes of C. lytica and C. algicola. A slightly higher fraction of genes belonging in the categories transcription (C. lytica 8.63%, C. algicola 6.85%), translation (C. lytica 7.34%, C. algicola 6.30%), amino acid metabolism (C. lytica 9.25%, C. algicola 8.19%), inorganic ion transport and metabolism (C. lytica 7.58%, C. algicola 6.85%) and posttranslational modification (C. lytica 4.72%, C. algicola 3.90%) were identified in C. lytica. The part of genes belonging to the following COG categories was slightly smaller in C. lytica than in C. algicola: carbohydrate metabolism (C. lytica 5.82%, C. algicola 6.77%), defense mechanisms (C. lytica 1.95%, C. algicola 2.48%), secondary metabolites biosynthesis (C. lytica 1.38%, C. algicola 2.05%).
We would like to gratefully acknowledge the help of Maren Schröder (DSMZ) for growing C. lytica cultures. This work was performed under the auspices of the US Department of Energy’s 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.
- Johansen JE, Nielsen P, Sjøholm C. Description of Cellulophaga báltica gen. nov., sp. nov. and Cellulophaga fucicola gen. nov., sp. nov. and reclassification of [Cytophaga] lytica to Cellulophaga lytica gen. nov., comb. nov. Int J Syst Bacteriol 1999; 49:1231–1240. PubMed doi:10.1099/00207713-49-3-1231View ArticlePubMedGoogle Scholar
- Euzéby JP. List of bacterial names with standing in nomenclature: A folder available on the Internet. Int J Syst Bacteriol 1997; 47:590–592. PubMed doi:10.1099/00207713-47-2-590View ArticlePubMedGoogle Scholar
- Bowman JP. Description of Cellulophaga algicola sp. nov., isolated from the surfaces of Antarctic algae, and reclassification of Cytophaga uliginosa (ZoBell and Upham 1944) Reichenbach 1989 as Cellulophaga uliginosa comb. nov. Int J Syst Evol Microbiol 2000; 50:1861–1868. PubMedView ArticlePubMedGoogle Scholar
- Nedashkovskaya OI, Suzuki M, Lysenko AM, Snauwaert C, Vancanneyt M, Swings J, Vysotskii MV, Mikhailov VV. Cellulophaga pacifica sp. nov. Int J Syst Evol Microbiol 2004; 54:609–613. PubMed doi:10.1099/ijs.0.02737-0View ArticlePubMedGoogle Scholar
- Kahng HY, Chung BS, Lee DH, Jung JS, Park JH, Joen CO. Cellulophaga tyrosinoxydans sp. nov., a tyrosinase producing bacterium isolated from seawater. Int J Syst Evol Microbiol 2009; 59:654–657. PubMed doi:10.1099/ijs.0.003210-0View ArticlePubMedGoogle Scholar
- Skerman VBD, McGowan V, Sneath PHA, eds. Approved Lists of Bacterial Names. [Approved Lists of Bacterial Names in IJSEM Online — Approved Lists of Bacterial Names Amended edition]. Int J Syst Bacteriol 1980; 30:225–420. doi:10.1099/00207713-30-1-225Google Scholar
- 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 doi:10.1128/AEM.03006-05PubMed CentralView ArticlePubMedGoogle Scholar
- Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137. doi:10.1108/eb046814View ArticleGoogle Scholar
- Lee C, Grasso C, Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics 2002; 18:452–464. PubMed doi:10.1093/bioinformatics/18.3.452View ArticlePubMedGoogle Scholar
- Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552. PubMedView ArticlePubMedGoogle Scholar
- Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML Web servers. Syst Biol 2008; 57:758–771. PubMed doi:10.1080/10635150802429642View ArticlePubMedGoogle Scholar
- 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. doi:10.1007/978-3-642-02008-7_13View ArticleGoogle Scholar
- Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM, Kyrpides NC. The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2010; 38:D346–D354. PubMed doi:10.1093/nar/gkp848PubMed CentralView ArticlePubMedGoogle Scholar
- Abt B, Lu M, Misra M, Han C, Nolan M, Lucas S, Hammon N, Deshpande S, Cheng JF, Tapia R, et al. Complete genome sequence of Cellulophaga algicola type strain (IC166T). Stand Genomic Sci 2011; 4:72–80. PubMed doi:10.4056/sigs.1543845PubMed CentralView ArticlePubMedGoogle Scholar
- 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 doi:10.1038/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
- 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 doi:10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
- Garrity GM, Holt JG. The Road Map to the Manual. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 119–169.View ArticleGoogle Scholar
- Ludwig W, Euzeby J, Whitman WG. Draft taxonomic outline of the Bacteroidetes, Planctomycetes, Chlamydiae, Spirochaetes, Fibrobacteres, Fusobacteria, Acidobacteria, Verrucomicrobia, Dictyoglomi, and Gemmatimonadetes. http://www.bergeys.org/outlines/Bergeys_Vol_4_Outline.pdf. Taxonomic Outline 2008
- Garrity GM, Holt J. Taxonomic outline of the Archaea and Bacteria. In: Bergey’s Manual of Systematic Bacteriology, 2nd ed. vol. 1. The Archaea, deeply branching and phototrophic bacteria. Garrity GM, Boone DR, Castenholz RW (eds). 2001; 155–166.Google Scholar
- Bernardet JF, Nakagawa Y, Holmes B. Proposed minimal standards for describing new taxa of the family F!avobacteriaceae and emended description of the family. Int J Syst Evol Microbiol 2002; 52:1049–1070. PubMed doi:10.1099/ijs.0.02136-0PubMedGoogle Scholar
- List Editor. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. List no. 41. Int J Syst Bacteriol 1992; 42:327–328. doi:10.1099/00207713-42-2-327Google Scholar
- Reichenbach H. Order 1. Cytophagales Leadbetter 1974, 99AL. In: Holt JG (ed), Bergey’s Manual of Systematic Bacteriology, First Edition, Volume 3, The Williams and Wilkins Co., Baltimore, 1989, p. 2011–2013.Google Scholar
- Bernardet JF, Segers P, Vancanneyt M, Berthe F, Kersters K, Vandamme P. Cutting a Gordian knot: emended classification and description of the genus Flavobacterium, emended description of the family Flavobacteriaceae, and proposal of Flavobacterium hydatis nom. nov. (Basonym, Cytophaga aquatilis Strohl and Tait 1978). Int J Syst Bacteriol 1996; 46:128–148. doi:10.1099/00207713-46-1-128View ArticleGoogle Scholar
- Lewin RA. A classification of flexibacteria. J Gen Microbiol 1969; 58:189–206. PubMedView ArticlePubMedGoogle Scholar
- Reichenbach H. Genus I. Cytophaga Winogradsky 1929, 577, (AL) emend. In: Staley JT, Bryant MP, Pfenning N, Holt JG (eds). Bergey’s manual of systematic bacteriology. Vol. 3. Baltimore, Md. Williams & Wilkins, 1989, pp. 2015–2050.Google Scholar
- BAuA. Classification of bacteria and archaea in risk groups. TRBA 2005; 466:84.Google Scholar
- 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. Nat Genet 2000; 25:25–29. PubMed doi:10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
- Lewin RA, Lounsbery DM. Isolation, Cultivation and Characterization of Flexibacteria. J Gen Microbiol 1969; 58:145–170. PubMedView ArticlePubMedGoogle Scholar
- Klenk HP, Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol 2010; 33:175–182. PubMed doi:10.1016/j.syapm.2010.03.003View ArticlePubMedGoogle Scholar
- 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 encyclopaedia of Bacteria and Archaea. Nature 2009; 462:1056–1060. PubMed doi:10.1038/nature08656PubMed CentralView ArticlePubMedGoogle Scholar
- List of growth media used at DSMZ: http://www.dsmz.de/microorganisms/media_list.php.
- 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. Biopreservation and Biobanking 2011; 9:51–55. doi:10.1089/bio.2010.0029View ArticlePubMedGoogle Scholar
- The DOE Joint Genome Institute. http://www.jgi.doe.gov
- Phrap and Phred for Windows. MacOS, Linux, and Unix. http://www.phrap.com
- Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829. PubMed doi:10.1101/gr.074492.107PubMed CentralView ArticlePubMedGoogle Scholar
- Han C, Chain P. 2006. Finishing repeat regions automatically with Dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology. Arabina HR, Valafar H (eds), CSREA Press. June 26–29, 2006: 141–146.Google Scholar
- 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
- 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 doi:10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
- 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 doi:10.1038/nmeth.1457View ArticlePubMedGoogle Scholar
- 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 doi:10.1093/bioinformatics/btp393View ArticlePubMedGoogle Scholar
- Sandmann G. Carotenoid biosynthesis and biotechnological application. Arch Biochem Biophys 2001; 385:4–12. PubMed doi:10.1006/abbi.2000.2170View ArticlePubMedGoogle Scholar
- Sakai T, Ishizuka K, Kato I. Isolation and characterization of fucoidan-degrading marine bacterium. Mar Biotechnol 2003; 5:409–416. PubMed doi:10.1007/s10126-002-0118-6View ArticlePubMedGoogle Scholar
- Mavromatis K, Abt B, Brambilla E, Lapidus A, Copeland A, Desphande S, Nolan M, Lucas S, Tice H, Cheng JF. Complete genome sequence of Coraliomargarita akajimensis type strain (04OKA010-24T). Stand Genomic Sci 2010; 2:290–299. PubMed doi:10.4056/sigs.952166PubMed CentralView ArticlePubMedGoogle Scholar
- Liu Y, Harrison PM, Kunin V, Gerstein M. Comprehensive analysis of pseudogenes in prokaryotes: widespread gene decay and failure of putative horizontally transferred genes. Genome Biol 2004; 5:R64. PubMed doi:10.1186/gb-2004-5-9-r64PubMed CentralView ArticlePubMedGoogle Scholar
- 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 doi:10.4056/sigs.531120PubMed CentralView ArticlePubMedGoogle Scholar
- 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 doi:10.4056/sigs.541628PubMed CentralView ArticlePubMedGoogle Scholar
- McBride MJ, Xie G, Martens EC, Lapidus A, Henrissat B, Rhodes RG, Goltsman E, Wang W, Xu J, Hunnicutt DW. Novel features of the polysaccharide-digesting gliding bacterium Flavobacterium johnsoniae as revealed by genome sequence analysis. Appl Environ Microbiol 2009; 75:6864–6875. PubMed doi:10.1128/AEM.01495-09PubMed CentralView ArticlePubMedGoogle Scholar