Open Access

Complete genome sequence of Mahella australiensis type strain (50-1 BONT)

  • Johannes Sikorski
  • , Hazuki Teshima,
  • , Matt Nolan
  • , Susan Lucas
  • , Nancy Hammon
  • , Shweta Deshpande
  • , Jan-Fang Cheng
  • , Sam Pitluck
  • , Konstantinos Liolios
  • , Ioanna Pagani
  • , Natalia Ivanova
  • , Marcel Huntemann
  • , Konstantinos Mavromatis
  • , Galina Ovchinikova
  • , Amrita Pati
  • , Roxanne Tapia,
  • , Cliff Han,
  • , Lynne Goodwin,
  • , Amy Chen
  • , Krishna Palaniappan
  • , Miriam Land,
  • , Loren Hauser,
  • , Olivier D. Ngatchou-Djao
  • , Manfred Rohde
  • , Rüdiger Pukall
  • , Stefan Spring
  • , Birte Abt
  • , Markus Göker
  • , John C. Detter,
  • , Tanja Woyke
  • , James Bristow
  • , Victor Markowitz
  • , Philip Hugenholtz,
  • , Jonathan A. Eisen,
  • , Nikos C. Kyrpides
  • , Hans-Peter Klenk
  • and Alla Lapidus
Corresponding author

DOI: 10.4056/sigs.1864526

Received: 30 June 2011

Published: 01 July 2011


Mahella australiensis Bonilla Salinas et al. 2004 is the type species of the genus Mahella, which belongs to the family Thermoanaerobacteraceae. The species is of interest because it differs from other known anaerobic spore-forming bacteria in its G+C content, and in certain phenotypic traits, such as carbon source utilization and relationship to temperature. Moreover, it has been discussed that this species might be an indigenous member of petroleum and oil reservoirs. This is the first completed genome sequence of a member of the genus Mahella and the ninth completed type strain genome sequence from the family Thermoanaerobacteraceae. The 3,135,972 bp long genome with its 2,974 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.


strictly anaerobicmotilespore-formingGram-positivemoderately thermophilicchemoorganotrophicThermoanaerobacteraceaeGEBA


Strain 50-1 BONT (= DSM 15567 = CIP 107919) is the type strain of Mahella australiensis, and the type and only species of the monotypic genus Mahella [1,2]. The genus name is derived from the Neo-Latin word Mahella (named in honor of the American microbiologist R. A. Mah, for his important contribution to the taxonomy of anaerobes) [2]. The species epithet is derived from the Neo-Latin word australiensis (related to Australia) [1]. Strain 50-1 BONT was isolated from the Riverslea Oil Field in the Bowen-Surat basin in Queensland, eastern Australia [1]. No further isolates have been reported for M. australiensis. Here we present a summary classification and a set of features for M. australiensis 50-1 BONT, together with the description of the complete genomic sequencing and annotation.

Classification and features

A representative genomic 16S rRNA sequence of M. australiensis 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 [3] and the relative frequencies, weighted by BLAST scores, of taxa and keywords (reduced to their stem [4] were determined. The three most frequent genera were Clostridium (76.6%), Mahella (18.5%) and Pelotomaculum (4.8%) (36 hits in total). Regarding the two hits to sequences from members of the species, the average identity within HSPs was 99.9%, whereas the average coverage by HSPs was 100.0%. Among all other species, the one yielding the highest score was Pelotomaculum isophthalicicum, which corresponded to an identity of 88.5% and a HSP coverage of 49.0%. (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 DQ378192 ('oil-polluted soil clone F28 Pitesti'), which showed an identity of 98.5% and a HSP coverage of 98.0%. The five most frequent keywords within the labels of environmental samples which yielded hits were 'microbi' (3.7%), 'anaerob' (2.9%), 'digest' (2.2%), 'soil' (2.0%) and 'thermophil' (1.7%) (213 hits in total). The five most frequent keywords within the labels of environmental samples which yielded hits of a higher score than the highest scoring species were 'microbi' (4.4%), 'anaerob' (3.3%), 'digest' (3.2%), 'soil' (2.6%) and 'condit, denitrification-induc, paddi, popul, respons, rice' (1.9%) (123 hits in total). These keywords reflect some of the ecological and physiological properties reported for strain 50-1 BONT in the original description [1].

Figure 1 shows the phylogenetic neighborhood of M. australiensis 50-1 BONT in a 16S rRNA based tree. The sequences of the three 16S rRNA gene copies in the genome differ from each other by up to two nucleotides, and differ by up to four nucleotides from the previously published 16S rRNA sequence (AY331143).

Figure 1

Phylogenetic tree highlighting the position of M. australiensis strain 50-1 BONT relative to the other type strains within the order Thermoanaerobacterales. The tree was inferred from 1,275 aligned characters [5,6] of the 16S rRNA gene sequence under the maximum likelihood criterion [7] and rooted in accordance with the current taxonomy. The branches are scaled in terms of the expected number of substitutions per site. Numbers to the right of bifurcations are support values from 950 bootstrap replicates [8] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [9] are labeled with one asterisk, those registered as 'Complete and Published' with two asterisks [10,11]. Apparently, even the best BLAST hits show a low degree of similarity to M. australiensis (see above), in agreement with the isolated position of the species in the latest version of the 16S rRNA phylogeny from the All-Species-Living-Tree Project [12]. The species selection for Figure 1 was based on the current taxonomic classification (Table 1).

The cells of strain 50-1 BONT are generally rod-shaped with a size of 3–20 x 0.5 µm (Figure 2). They occur singly or in pairs [1]. Strain 50-1 BONT stains Gram-positive and is spore-forming (Table1). The organism is described to be motile by peritrichous flagella, with a mean of four flagella per cell [1] (not visible in Figure 2). Strain 50-1 BONT was found to be a strictly anaerobic chemoorganotroph which requires 0.1% NaCl for optimal growth [1], but is also able to grow in the presence of up to 4% NaCl [1]. The organism can use a wide range of carbohydrates as carbon and energy sources, including arabinose, cellobiose, fructose, galactose, glucose, mannose, sucrose, xylose and yeast extract [1]. Lactate, formate, ethanol, acetate, H2, and CO2 are the end products of the glucose metabolism [1]. The temperature range for growth is between 30°C and 60°C, with the optimum at 50°C [1]. Mesothermophilia distinguishes M. australiensis from its closest relatives, such as the members if the genus Thermoanaerobacterium [1]. After seven days of incubation at 50°C, round colonies (1–2 mm diameter) were found in roll tubes [1]. The pH range for growth is between 5.5 and 8.8, with an optimum at pH 7.5 [1]. Strain 50-1 BONT was not able to reduce thiosulfate or to hydrolyze starch [1]. Moreover, it does not use elemental sulfur, sulfate, sulfite, nitrate or nitrite as electron acceptors [1]. The generation time of the strain 50-1 BONT was 11 h [1].

Figure 2

Scanning electron micrograph of M. australiensis 50-1 BONT

Table 1

Classification and general features of M. australiensis 50-1 BONT according to the MIGS recommendations [13] and the NamesforLife database [14].




   Evidence code

   Current classification

   Domain Bacteria

   TAS [15]

   Phylum Firmicutes

   TAS [16,17]

   Class Clostridia

   TAS [18,19]

   Order Thermoanaerobacterales

   TAS [18,20]

   Family Thermoanaerobacteraceae

   TAS [18,21]

   Genus Mahella

   TAS [1]

   Species Mahella australiensis

   TAS [1]

   Type strain 50-1 BON

   TAS [1]

   Gram stain


   TAS [1]

   Cell shape


   TAS [1]


   motile by peritrichous flagella

   TAS [1]


   swollen sporangia, terminal spores

   TAS [1]

   Temperature range


   TAS [1]

   Optimum temperature


   TAS [1]


   0.1%-4% NaCl

   TAS [1]


   Oxygen requirement

   strictly anaerobic

   TAS [1]

   Carbon source

   arabinose, cellobiose, fructose, galactose,    glucose, mannose, sucrose, xylose and yeast extract

   TAS [1]

   Energy metabolism


   TAS [1]



   oil fields

   TAS [1]


   Biotic relationship





   not reported

   Biosafety level


   TAS [22]


   oil well in Queensland

   TAS [1]


   Geographic location

   Riverslea Oil Field in the Bowen-Surat basin, Queensland, Australia

   TAS [1]


   Sample collection time





   roughly -27.32




   roughly 148.72




   not reported



   not reported

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 [23]. If the evidence code is IDA, the property was directly observed by one of the authors or an expert mentioned in the acknowledgements.


No chemotaxonomic information is currently available for the strain 50-1 BONT.

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [24], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [25]. The genome project is deposited in the Genome On Line Database [9] 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

    Three genomic libraries: one 454 pyrosequence standard library,    one 454 PE library (10 kb insert size), one Illumina library


    Sequencing platforms

    Illumina GAii, 454 GS FLX Titanium


    Sequencing coverage

    52.1 × Illumina; 35.9 × pyrosequence



    Newbler version 2.3, Velvet, phrap


    Gene calling method

    Prodigal 1.4, GenePRIMP



    Genbank Date of Release

    May 13, 2011



    NCBI project ID


    Database: IMG-GEBA



    Source material identifier

    DSM 15567

    Project relevance

    Tree of Life, GEBA

Growth conditions and DNA isolation

M. australiensis 50-1 BONT, DSM 15567, was grown anaerobically in DSMZ medium 339 (Wilkins-Chalgreen anaerobe broth, Oxoid CM 643) [26] at 50°C. DNA was isolated from 0.5-1 g of cell paste using Jetflex Genomic DNA Purification Kit (GENOMED 600100) following the standard protocol as recommended by the manufacturer. Cell lysis was enhanced by adding 20 µl proteinase K for two hours at 58°C. DNA is available through the DNA Bank Network [27].

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 [28]. Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 40 contigs in one scaffold was converted into a phrap [29] assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (444 Mb) was assembled with Velvet [30] 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 108.4 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 [29] 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 [28], Dupfinisher, or sequencing cloned bridging PCR fragments with subcloning [31]. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F. Chang, unpublished). A total of 279 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 [32]. 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 88.0 × coverage of the genome. The final assembly contained 364,783 pyrosequence and 4,541,603 Illumina reads.

Genome annotation

Genes were identified using Prodigal [33] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [34]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) non-redundant 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 [35].

Genome properties

The genome consists of a 3,135,972 bp long chromosome with a G+C content of 43.5% (Table 3 and Figure 3). Of the 3,033 genes predicted, 2,974 were protein-coding genes, and 59 RNAs; 104 pseudogenes were also identified. The majority of the protein-coding genes (70.4%) were assigned with 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.

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 chromosome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red, 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/envelope biogenesis




    Cell motility








    Extracellular structures




    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




    Function unknown




    Not in COGs

Insights from the genome sequence

Comparative genomics

Lacking an available genome sequence of the closest relative of M. australiensis, (Thermoanaerobacterium thermosulfurogenes, Figure 1), the following comparative analyses were done with Thermoanaerobacterium thermosaccharolyticum (GenBank CP002171), the closest related organism with a publicly available genome. While the two genomes are similar in size (M. australiensis 3.1 Mb, 2,974 genes; T. thermosaccharolyticum 2.8 Mb, 2,757 genes), they differ significantly in their G+C content (43% vs. 34%). An estimate of the overall similarity between M. australiensis, T. thermosaccharolyticum and Caldicellulosiruptor saccharolyticus [11] (GenBank EKD00000000.1, as an equidistant outgroup, Figure 1), was generated with the GGDC-Genome-to-Genome Distance Calculator [36,37]. This system calculates the distances by comparing the genomes to obtain HSPs (high-scoring segment pairs) and inferring distances from the set of formulae (1, HSP length / total length; 2, identities / HSP length; 3, identities / total length). Table 5 shows the results of the pair wise comparison between the three genomes.

Table 5

Pairwise comparison of M. australiensis, T. thermosaccharolyticum and C. saccharolyticus using the GGDC-Calculator.

   HSP length /   total length [%]

   identities /   HSP length [%]

   identities /   total length [%]

M. australiensis

   T. thermosaccharolyticum




M. australiensis

   C. saccharolyticus




C. saccharolyticus

   T. thermosaccharolyticum




The fraction of shared genes in the three genomes is shown in a Venn diagram (Figure 4). The numbers of pairwise shared genes were calculated with the phylogenetic profiler function of the IMG ER platform [35]. The homologous genes within the genomes were detected with a maximum E-value of 10-5 and a minimum identity of 30%. About half of all the genes in the genomes (1,313 genes) are shared among the three genomes, with equivalent numbers of genes (265 to 327) shared pairwise to the exclusion of the third genome or occurring in only one genome (866 to 1,069). Within the 1,069 unique genes of M. australiensis that have no detectable homologs in the genomes of T. thermosaccharolyticum and C. saccharolyticus (under the sequence similarity thresholds used for the comparison) the 16 genes encoding xylose isomerases appear to be noteworthy; for seven of these isomerase genes no homologs were detected in the other two genomes; only nine genes were identified in C. saccharolyticus, and five in T. thermosaccharolyticum. The high number of xylose isomerise genes suggests a strong utilization of pentoses by M. australiensis. It is already known that several members of the order Thermoanaerobacterales are capable of xylose metabolism [38]. In addition, a number of extracellular solute-binding proteins were found in the genome of M. australiensis. These proteins belong to a high affinity transport system, which is involved in active transport of solutes across the cytoplasmic membrane. The M. australiensis genome contains 54 genes coding for solute-binding proteins belonging to family 1, whereas in C. saccharolyticus and T. thermosaccharolyticum contain only 16 and 13 solute-binding protein family 1 coding genes, respectively.

Figure 4

Venn diagram depicting the intersections of protein sets (total number of derived protein sequences in parentheses) of M. australiensis, T. thermosaccharolyticum and C. saccharolyticus.

T. thermosaccharolyticum probably transports sugars via a phosphotransferase system (PTS). A total of 29 genes coding for proteins belonging to the PTS specific for different sugars were found in the genome of T. thermosaccharolyticum. The PTS of Thermoanaerobacter tengcongensis was recently studied in detail [39], with 22 proteins identified as participants in the PTS. In contrast, no genes coding for PTS proteins were identified in the genome of M. australiensis, and only one fructose specific PEP-dependent PTS gene was reported in C. saccharolyticus [11]. In conclusion, the number and distribution of these transport mechanisms seems to be highly variable within the Thermoanaerobacteraceae.



We would like to gratefully acknowledge the help of Katja Steenblock for growing M. australiensis 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.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


  1. Bonilla Salinas MB, Fardeau ML, Thomas P, Cayol JL, Patel BKC and Ollivier B. Mahella australiensis gen. nov., sp. nov., a moderately thermophilic anaerobic bacterium isolated from an Australian oil well. Int J Syst Evol Microbiol. 2004; 54:2169-2173 View ArticlePubMed
  2. Euzéby JP. List of bacterial names with standing in nomenclature: A folder available on the Internet. Int J Syst Bacteriol. 1997; 47:590-592 View ArticlePubMed
  3. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie E, Keller K, Huber T, Dalevi D, Hu P and Andersen G. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006; 72:5069-5072 View ArticlePubMed
  4. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems. 1980; 14:130-137.
  5. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000; 17:540-552PubMed
  6. Lee C, Grasso C and Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics. 2002; 18:452-464 View ArticlePubMed
  7. Stamatakis A, Hoover P and Rougemont J. A rapid bootstrap algorithm for the RAxML web servers. Syst Biol. 2008; 57:758-771 View ArticlePubMed
  8. 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
  9. 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
  10. Pitluck S, Yasawong M, Munk C, Nolan M, Lapidus A, Lucas S, Glavina Del Rio T, Tice H, Cheng JF and Bruce D. Complete genome sequence of Thermosediminibacter oceani type strain (JW/IW-1228PT). Stand Genomic Sci. 2010; 3:108-116 View ArticlePubMed
  11. van de Werken HJ, Verhaart MR, VanFossen AL, Willquist K, Lewis DL, Nichols JD, Goorissen HP, Mongodin EF, Nelson KE and van Niel EW. Hydrogenomics of the extremely thermophilic bacterium Caldicellulosiruptor saccharolyticus. Appl Environ Microbiol. 2008; 74:6720-6729 View ArticlePubMed
  12. Yarza P, Ludwig W, Euzéby J, Amman R, Schleifer KH, Glöckner FO and Rosselló-Mora R. Updates of the All-Species Living Tree Project based on 16S and 23S rRNA sequence analyses. Syst Appl Microbiol. 2010; 33:291-299 View ArticlePubMed
  13. 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
  14. Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today. 2010; 37:9
  15. 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
  16. 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.
  17. Gibbons NE and Murray RGE. Proposals concerning the higher taxa of Bacteria. Int J Syst Bacteriol. 1978; 28:1-6 View Article
  18. Validation list 132. List of new names and new combinations previously effectively, but not validly, published. Int J Syst Evol Microbiol. 2010; 60:469-472 View Article
  19. Rainey FA. Class II. Clostridia class nov. In: De Vos P, Garrity G, Jones D, Krieg NR, Ludwig W, Rainey FA, Schleifer KH, Whitman WB (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 3, Springer-Verlag, New York, 2009, p. 736.
  20. Wiegel J. 2009. Order III. Thermoanaerobacterales ord. nov. In: De Vos P, Garrity G, Jones D, Krieg NR, Ludwig W, Rainey FA, Schleifer KH, Whitman WB (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 3, Springer-Verlag, New York, p. 1224.
  21. Wiegel J. 2009. Family I. Thermoanaerobacteraceae fam. nov. In: De Vos P, Garrity G, Jones D, Krieg NR, Ludwig W, Rainey FA, Schleifer KH, Whitman WB (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 3, Springer-Verlag, New York, p. 1225.
  22. BAuA. Classification of Bacteria and Archaea in risk groups. TRBA. 2010; 466:123
  23. 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
  24. 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
  25. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, Kunin V, Goodwin L, Wu M and Tindall BJ. A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature. 2009; 462:1056-1060 View ArticlePubMed
  26. List of growth media used at DSMZ: Web Site
  27. Gemeinholzer B, Dröge G, Zetzsche H, Haszprunar G, Klenk HP, Güntsch A, Berendsohn WG and Wägele JW. The DNA Bank Network: the start from a German initiative. Biopreservation and Biobanking. 2011; 9:51-55 View Article
  28. JGI website. Web Site
  29. The Phred/Phrap/Consed software package. Web Site
  30. 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
  31. Han C, Chain P. Finishing repeat regions automatically with Dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology. Arabnia HR, Valafar H (eds), CSREA Press. June 26-29, 2006: 141-146.
  32. 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
  33. 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
  34. 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
  35. 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
  36. Auch AF, von Jan M, Klenk HP and 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 View ArticlePubMed
  37. Auch AF, Klenk HP and Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci. 2010; 2:142-148 View ArticlePubMed
  38. Uffen RL. Xylan degradation: a glimpse at microbial diversity. J Ind Microbiol Biotechnol. 1997; 19:1-6 View Article
  39. Navdaeva V, Zurbriggen A, Waltersperger S, Schneider P, Oberholzer AE, Bähler P, Bächler C, Grieder A, Baumann U and Erni B. Phosphoenolpyruvate: Sugar phosphotransferase system from the hyperthermophilic Thermoanaerobacter tengcongensis. Biochemistry. 2011; 50:1184-1193 View ArticlePubMed