Open Access

Complete genome sequence of Desulfarculus baarsii type strain (2st14T)

  • Hui Sun
  • , Stefan Spring
  • , Alla Lapidus
  • , Karen Davenport,
  • , Tijana Glavina Del Rio
  • , Hope Tice
  • , Matt Nolan
  • , Alex Copeland
  • , Jan-Fang Cheng
  • , Susan Lucas
  • , Roxanne Tapia,
  • , Lynne Goodwin,
  • , Sam Pitluck
  • , Natalia Ivanova
  • , Ionna Pagani
  • , Konstantinos Mavromatis
  • , Galina Ovchinnikova
  • , Amrita Pati
  • , Amy Chen
  • , Krishna Palaniappan
  • , Loren Hauser,
  • , Yun-Juan Chang,
  • , Cynthia D. Jeffries,
  • , John C. Detter,
  • , Cliff Han,
  • , Manfred Rohde
  • , Evelyne Brambilla
  • , Markus Göker
  • , Tanja Woyke
  • , Jim Bristow
  • , Jonathan A. Eisen,
  • , Victor Markowitz
  • , Philip Hugenholtz
  • , Nikos C Kyrpides
  • , Hans-Peter Klenk
  • and Miriam Land,
Corresponding author

DOI: 10.4056/sigs.1243258

Received: 20 November 2010

Published: 31 December 2010


Desulfarculus baarsii (Widdel 1981) Kuever et al. 2006 is the type and only species of the genus Desulfarculus, which represents the family Desulfarculaceae and the order Desulfarculales. This species is a mesophilic sulfate-reducing bacterium with the capability to oxidize acetate and fatty acids of up to 18 carbon atoms completely to CO2. The acetyl-CoA/CODH (Wood-Ljungdahl) pathway is used by this species for the complete oxidation of carbon sources and autotrophic growth on formate. The type strain 2st14T was isolated from a ditch sediment collected near the University of Konstanz, Germany. This is the first completed genome sequence of a member of the order Desulfarculales. The 3,655,731 bp long single replicon genome with its 3,303 protein-coding and 52 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.


obligate anaerobicsulfate reductionWood-Ljungdahl pathwayfreshwater sedimentDeltaproteobacteriaDesulfarculaceaeGEBA


Most sulfate reducing bacteria, available in pure culture, oxidize organic electron donors incompletely to acetate, whereas species that oxidize acetate and other carbon compounds completely to CO2, using sulfate as an electron acceptor, are less frequently isolated. Sulfate reducers with the latter type of metabolism are of special interest, because it is assumed that they are dominant in anoxic marine sediments [1]. Sulfate reducing prokaryotes with the ability to mineralize organic compounds to CO2 are phylogenetically dispersed and can be found within the Proteobacteria, Firmicutes and Euryarchaeota. At the time of writing, representatives of this type of metabolism, for which a completely sequenced genome exists include Desulfobacterium autotrophicum [2], Desulfotomaculum acetoxidans [3] and Archaeoglobus fulgidus [4]. In the present work, the complete genome sequence of Desulfarculus baarsii a completely oxidizing sulfate reducing bacterium representing the order Desulfarculales within the Deltaproteobacteria, was determined. The original description of D. baarsii was based on strain 1st1 (= “Göttingen”) [5], which was probably subsequently lost and replaced by the designated type strain 2st14T (= “Konstanz”) [6]. Strain 2st14T (= DSM 2075 = ATCC 33931 = LMG 7858) was enriched from anoxic mud from a ditch near the University of Konstanz, Germany, in a medium supplemented with stearate and sulfate and subsequently isolated in an anaerobic agar dilution series with formate plus sulfate [7,8]. D. baarsii strain 2st14T is the first member of the family Desulfarculaceae within the order Desulfarculales with a sequenced genome. The presented sequence data will enable interesting genome comparisons with other sulfate reducing bacteria of the class Deltaproteobacteria.

Classification and features

The species D. baarsii represents a separate lineage within the Deltaproteobacteria which is only distantly related to most other members of this class. The closest relatives based on 16S rRNA gene sequence similarity values are the type strains of Desulfomonile tiedjei (87.6% sequence identity) and Desulfomonile liminaris (87.2%), both belonging to the family Syntrophaceae within the order Syntrophobacterales [9]. The most similar cloned 16S rRNA gene, EUB-42 [10] shared only 95.5% sequence similarity with D. baarsii and was retrieved from anaerobic sludge. Strain 2st14T represents the only strain of this species available from a culture collection, thus far. Currently available data from cultivation independent studies (environmental screening and genomic surveys) did not surpass 86% sequence similarity, indicating that members of this species are restricted to distinct habitats which are currently undersampled in most environments or are in low abundance, (status October 2010). The single genomic 16S rRNA sequence of strain 2st14T was compared using BLAST with the most resent release of the Greengenes database [11] and the relative frequencies of taxa and keywords, weighted by BLAST scores, were determined. The five most frequent genera were Desulfovibrio (43.3%), Syntrophobacter (14.4%), Desulfomonile (11.8%), Desulfarculus (9.6%) and Desulfatibacillum (7.5%). The species yielding the highest score was D. baarsii. The five most frequent keywords within the labels of environmental samples which yielded hits were 'sediment' (4.5%), 'microbial' (4.5%), 'lake' (1.7%), 'depth' (1.7%) and 'sea' (1.6%). Environmental samples which yielded hits of a higher score than the highest scoring species were not found.

Figure 1 shows the phylogenetic neighborhood of D. baarsii 2st14T in a 16S rRNA based tree. The sequence of the single 16S rRNA gene in the genome differs by one nucleotide from the previously published 16S rRNA gene sequence generated from DSM 2075 (AF418174) which contains five ambiguous base calls. Genbank entry M34403 from 1989 is also annotated as 16S rRNA sequence of strain 2st14T, but differs in 45 positions (3.2%) from the actual sequence. This difference probably reflects more the progress in sequencing technology than biological differences.

Figure 1

Phylogenetic tree highlighting the position of D. baarsii relative to the other type strains of related genera within the class Deltaproteobacteria. The tree was inferred from 1,465 aligned characters [12,13] of the 16S rRNA gene sequence under the maximum likelihood criterion [14] and rooted in accordance with the current taxonomy. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 1,000 bootstrap replicates [15] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [16] are shown in blue, published genomes [17] and INSDC accession CP000478 for Syntrophobacter fumaroxidans in bold.

The cells of D. baarsii 2st14T are vibrioid, Gram-negative and 0.5-0.7 by 1.5–4 µm in size (Figure 2, Table 1). Motility is conferred by a single polar flagellum (not visible in Figure 2) [5]. The temperature range for growth is 20-39°C with an optimum around 35°C. The pH range for growth is 6.5–8.2, with an optimum at 7.3. The strain grows optimally in the presence of 7–20 g/l NaCl and 1.2–3g/l MgCl2 × 6 H2O, but growth is nearly as rapid at lower concentrations [7]. D. baarsii strain 2st14T is a strictly anaerobic, non-fermentative, chemoorganotrophic sulfate-reducer that oxidizes organic substrates completely to CO2. Sulfate, sulfite and thiosulfate serve as terminal electron acceptors and are reduced to H2S, but sulfur, fumarate and nitrate cannot be utilized. The following compounds are utilized as electron donors and carbon sources: formate, acetate, propionate, butyrate, iso-butyrate, 2-methylbutyrate, valerate, iso-valerate, and higher fatty acids up to 18 carbon atoms. Growth on formate does not require an additional organic carbon source [5,7]. A high activity of carbon monoxide dehydrogenase is observed in D. baarsii, indicating the operation of the anaerobic C1-pathway (Wood-Ljungdahl pathway) for formate assimilation and CO2 fixation or complete oxidation of acetyl-CoA [27].

Figure 2

Scanning electron micrograph of D. baarsii 2st14T

Table 1

Classification and general features of D. baarsii strain 2st14T in according to the MIGS recommendations [18].




   Evidence code

   Current classification

    Domain Bacteria

   TAS [19]

    Phylum Proteobacteria

   TAS [20]

    Class Deltaproteobacteria

   TAS [21,22]

    Order Desulfarculales

   TAS [21,23]

    Family Desulfarculaceae

   TAS [7,21,23, 24]

    Genus Desulfarculus

   TAS [7,21]

    Species Desulfarculus baarsii

   TAS [6,7,21]

    Type strain 2st14

   TAS [6]

   Gram stain


   TAS [5]

   Cell shape


   TAS [5]


    motile (single polar flagellum)

   TAS [5]



   TAS [5]

   Temperature range


   TAS [5]

   Optimum temperature


   TAS [5]


    optimum growth at 7–20 g/l NaCl

   TAS [5,7]


   Oxygen requirement

    strictly anaerobic

   TAS [5]

   Carbon source

    CO2, formate, acetate, propionate, butyrate,    higher fatty acids

   TAS [5]

   Energy source

    formate, acetate, propionate, butyrate,    higher fatty acids

   TAS [5]



    anoxic freshwater or brackish sediments

   TAS [5]


   Biotic relationship

    free living





   TAS [25]

   Biosafety level


   TAS [25]


    mud from a ditch

   TAS [7]


   Geographic location

    Konstanz, Germany

   TAS [7]


   Sample collection time

    1981 or before



   Latitude   Longitude

    47.7    9.2




    not reported



    about 406 m


Evidence codes - IDA: Inferred from Direct Assay (first time in publication); TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from of the Gene Ontology project [26]. If the evidence code is IDA, then the property was directly observed by one of the authors or an expert mentioned in the acknowledgements.

The oxygen detoxification system of D. baarsii was analyzed in some detail. It could be shown that a genomic region encoding a putative rubredoxin oxidoreductase (rbo) and rubredoxin (rub) of D. baarsii is able to suppress deleterious effects of reactive oxygen species (ROS) in Escherichia coli mutants lacking superoxide dismutase [28]. The cloned genes were identified in the whole genome sequence as Deba_2049 (rub) and Deba_2050 (rbo) and found in close proximity to a gene encoding rubrerythrin (Deba_2051), which is supposed to play an important role in the oxygen tolerance of anaerobic bacteria [29]. The product of the recombinant rbo gene of D. baarsii was later further characterized and designated as desulfoferrodoxin (Dfx), because no evidence for a rubredoxin oxidoreductase could be demonstrated. Instead, a function as superoxide reductase was proposed [30].


The cellular fatty acid pattern of D. baarsii strain 2st14T is dominated by saturated straight chain fatty acids (43.0% C14:0, 9.9% C16:0, and 2.3% C18:0), followed by saturated iso- and anteiso-branched fatty acids (21.3% i-C14:0, 12.3% ai-C15:0, and 2.8% i-C15:0). Occurrence of the dimethylacetal (DMA) derivates C15:0 DMA (1.8%) and i-C15:0 DMA (0.6%) represents a distinctive trait of this strain, because these compounds are rarely found in Desulfovibrio species [31]. A comparison of the fatty acid profiles of D. baarsii and various Gram-negative sulfate-reducers by cluster analysis indicated a separate position of D. baarsii [31], corroborating the distinct phylogenetic position of the species as shown based on the 16S rRNA sequence analysis (Figure 1). Unfortunately, besides the cellular fatty acid composition no further chemotaxonomic data are available for this species.

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [32], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [33]. The genome project is deposited in the Genome OnLine Database [16] and the complete genome sequence is deposited in 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.





    Finishing quality



    Libraries used

    Two 454 pyrosequence libraries, standard and pairs end (13 kb insert size)     and one Illumina standard library


    Sequencing platforms

    454 Titanium, Illumina GAii


    Sequencing coverage

    43.1 × 454 Titanium; 73.2 × Illumina



    Newbler, Velvet, phrap


    Gene calling method




    GenBank Date of Release

    August 6, 2010



    NCBI project ID


    Database: IMG-GEBA



    Source material identifier

    DSM 2075

    Project relevance


Growth conditions and DNA isolation

D. baarsii, strain 2st14T, DSM 2075, was grown anaerobically in DSMZ medium 208 (Desulfovibrio baarsii medium) [34] at 37°C. DNA was isolated from 0.5-1 g of cell paste using Jetflex Genomic DNA Purification Kit (GENOMED 600100) following the manufacturer’s instructions, but with 30 min incubation at 58°C with an additional 10 µl proteinase K for cell lysis.

Genome sequencing and assembly

The genome of 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 [35]. Pyrosequencing reads were assembled using the Newbler assembler version 2.1-PreRelease-4-28-2009-gcc-3.4.6-threads (Roche). The initial Newbler assembly consisted of 42 contigs in two scaffolds and was converted into a phrap assembly by making fake reads from the consensus, collecting the read pairs in the 454 paired end library. Illumina GAii sequencing data (267.7Mb) were assembled with Velvet [36] 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 157.7 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 [37] was used for sequence assembly and quality assessment in the following finishing process: After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with gapResolution [35], Dupfinisher, or sequencing cloned bridging PCR fragments with subcloning or transposon bombing (Epicentre Biotechnologies, Madison, WI) [38]. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F.Chang, unpublished). A total of 344 additional reactions 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 [39]. 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 116.3 × coverage of the genome. Final assembly contained 431,804 pyrosequence and 7,436,430 Illumina reads.

Genome annotation

Genes were identified using Prodigal [40] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [41]. 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 platform [42].

Genome properties

The genome is 3,655,731 bp long and comprises one main circular chromosome with an overall GC content of 65.7% (Table 3 and Figure 3). Of the 3,355 genes predicted, 3,303 were protein-coding genes, and 52 RNAs; 26 pseudogenes were also identified. The majority of the protein-coding genes (73.4%) were assigned a putative function while those remaining were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 4.

Table 3

Genome Statistics



   % of Total

Genome size (bp)



DNA coding region (bp)



DNA G+C content (bp)



Number of replicons


Extrachromosomal elements


Total genes



RNA genes



rRNA operons


Protein-coding genes



Pseudo genes



Genes with function prediction



Genes in paralog clusters



Genes assigned to COGs



Genes assigned Pfam domains



Genes with signal peptides



Genes with transmembrane helices



CRISPR repeats


Figure 3

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

Table 4

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




    Nuclear structure




    Defense mechanisms




    Signal transduction mechanisms




    Cell wall/membrane biogenesis




    Cell motility








    Extracellular structures




    Intracellular trafficking and 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




    Function unknown




    Not in COGs



We would like to gratefully acknowledge the help of Maren Schröder (DSMZ) for growing cultures of D. baarsii. 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. German Research Foundation (DFG) supported DSMZ under INST 599/1-2.


  1. Jørgensen BB. Mineralization of organic matter in the sea bed - the role of sulphate reduction. Nature. 1982; 296:643-645 View Article
  2. Strittmatter AW, Liesegang H, Rabus R, Decker I, Amann J, Sönke A, Henna A, Fricke WF, Martinez-Arias R and Bartels D. Genome sequence of Desulfobacterium autotrophicum HRM2, a marine sulfate reducer oxidizing organic carbon completely to carbon dioxide. Environ Microbiol. 2009; 11:1038-1055 View ArticlePubMed
  3. Spring S, Lapidus A, Schröder M, Gleim D, Sims D, Meincke L, Glavina Del Rio T, Tice H, Copeland A and Cheng JF. Complete genome sequence of Desulfotomaculum acetoxidans type strain (5575T). Stand Genomic Sci. 2009; 1:242-253 View Article
  4. Klenk HP, Clayton RA, Tomb JF, White O, Nelson KE, Ketchum KA, Dodson RJ, Gwinn M, Hickey EK and Peterson JD. The complete genome sequence of the hyperthermophilic, sulphate-reducing archaeon Archaeoglobus fulgidus. Nature. 1997; 390:364-370 View ArticlePubMed
  5. Widdel F. Anaerober Abbau von Fettsäuren und Benzoesäure durch neu isolierte Arten Sulfat-reduzierender Bakterien. Dissertation. Georg-August-Universität zu Göttingen, Göttingen 1980.
  6. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. Validation List no. 7. Int J Syst Bacteriol. 1981; 31:382-383 View Article
  7. Kuever J, Rainey FA, Widdel F. Genus I. Desulfarculus gen. nov. In: DJ Brenner, NR Krieg, JT Staley and GM Garrity (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. 1004-1005.
  8. Jansen K, Thauer RK, Widdel F and Fuchs G. Carbon assimilation pathways in sulfate reducing bacteria. Formate, carbondioxide, carbon monoxide, and acetate by Desulfovibrio baarsii. Arch Microbiol. 1984; 138:257-262 View Article
  9. Chun J, Lee JH, Jung Y, Kim M, Kim S, Kim BK and Lim YW. EzTaxon: a web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences. Int J Syst Evol Microbiol. 2007; 57:2259-2261 View ArticlePubMed
  10. Xu K, Liu H, Li X, Chen J and Wang A. Typical methanogenic inhibitors can considerably alter bacterial populations and affect the intereaction between fatty acid degraders and homoacetogens. Appl Microbiol Biotechnol. 2010; 87:2267-2279 View ArticlePubMed
  11. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P and Andersen GL. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006; 72:5069-5072 View ArticlePubMed
  12. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000; 17:540-552PubMed
  13. Lee C, Grasso C and Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics. 2002; 18:452-464 View ArticlePubMed
  14. Stamatakis A, Hoover P and Rougemont J. A rapid bootstrap algorithm for the RAxML Web servers. Syst Biol. 2008; 57:758-771 View ArticlePubMed
  15. Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME and Stamatakis A. How many bootstrap replicates are necessary? Lect Notes Comput Sci. 2009; 5541:184-200 View Article
  16. Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM and Kyrpides NC. The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res. 2009; 38:D346-D354 View ArticlePubMed
  17. McInerney MJ, Rohlin L, Mouttaki H, Kim U, Krupp RS, Rios-Hernandez L, Sieber J, Struchtemeyer CG, Bhattacharyya A, Campbell JW and Gunsalus RP. The genome of Syntrophus aciditrophus: life at the thermodynamic limit of microbial growth. Proc Natl Acad Sci USA. 2007; 104:7600-7605 View ArticlePubMed
  18. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ and Angiuoli SV. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008; 26:541-547 View ArticlePubMed
  19. Woese CR, Kandler O and 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 View ArticlePubMed
  20. 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.
  21. . 107. List of new names and new combinations previously effectively, but not validly, published. Int J Syst Evol Microbiol. 2006; 56:1-6 View ArticlePubMed
  22. Kuever J, Rainey FA, Widdel F. Class IV. Deltaproteobacteria class. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 2, Part C, Springer, New York, 2005, p. 922.
  23. Kuever J, Rainey FA, Widdel F. Order IV. Desulfarcales ord. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 2, Part C, Springer, New York, 2005, p. 1003.
  24. Kuever J, Rainey FA, Widdel F. Family I. Desulfarculaceae fam. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 2, Part C, Springer, New York, 2005, p. 1003.
  25. Classification of bacteria and archaea in risk groups. TRBA 466.Web Site
  26. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS and Eppig JT. Gene ontology: tool for the unification of biology. Nat Genet. 2000; 25:25-29 View ArticlePubMed
  27. Schauder R, Eikmanns B, Thauer RK, Widdel F and Fuchs G. Acetate oxidation to CO2 in anaerobic bacteria via a novel pathway not involving reactions of the citric acid cycle. Arch Microbiol. 1986; 145:162-172 View Article
  28. Pianzzola MJ, Soubes M and Touati D. Overproduction of the rbo gene product from Desulfovibrio species suppresses all deleterious effects of lack of superoxide dismutase in Escherichia coli. J Bacteriol. 1996; 178:6736-6742PubMed
  29. Lumppio HL, Shenvi NV, Summers AO, Voordouw G and Kurtz DM. Rubrerythrin and rubredoxin oxidoreductase in Desulfovibrio vulgaris: a novel oxidative stress protection system. J Bacteriol. 2001; 183:101-108 View ArticlePubMed
  30. Lombard M, Fontecave M, Touati D and Niviere V. Reaction of the desulfoferrodoxin from Desulfoarculus baarsii with superoxide anion. Evidence for a superoxide reductase activity. J Biol Chem. 2000; 275:115-121 View ArticlePubMed
  31. Vainshtein M, Hippe H and Kroppenstedt RM. Cellular fatty acid composition of Desulfovibrio species and its use in classification of sulfate-reducing bacteria. Syst Appl Microbiol. 1992; 15:554-566
  32. Klenk HP and Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol. 2010; 33:175-182 View ArticlePubMed
  33. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova N, Kunin V, Goodwin L, Wu M and Tindall BJ. A phylogeny-driven genomic encyclopedia of Bacteria and Archaea. Nature. 2009; 462:1056-1060 View ArticlePubMed
  34. List of growth media used at DSMZ: Web Site
  35. DOE Joint Genome Institute. Web Site
  36. Zerbino DR and Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008; 18:821-829 View ArticlePubMed
  37. Phrap and Phred for Windows, MacOS, Linux, and Unix. Web Site
  38. Sims D, Brettin T, Detter JC, Han C, Lapidus A, Copeland A, Glavina Del Rio T, Nolan M, Chen F and Lucas S. Complete genome sequence of Kytococcus sedentarius type strain (541T). Stand Genomic Sci. 2009; 1:12-20 View Article
  39. 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.
  40. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW and Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010; 11:119 View ArticlePubMed
  41. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A and Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods. 2010; 7:455-457 View ArticlePubMed
  42. Markowitz VM, Ivanova NN, Chen IMA, Chu K and Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics. 2009; 25:2271-2278 View ArticlePubMed