Skip to main content

Complete genome sequence of the moderately thermophilic mineral-sulfide-oxidizing firmicute Sulfobacillus acidophilus type strain (NALT)

Abstract

Sulfobacillus acidophilus Norris et al. 1996 is a member of the genus Sulfobacillus which comprises five species of the order Clostridiales. Sulfobacillus species are of interest for comparison to other sulfur and iron oxidizers and also have biomining applications. This is the first completed genome sequence of a type strain of the genus Sulfobacillus, and the second published genome of a member of the species S. acidophilus. The genome, which consists of one chromosome and one plasmid with a total size of 3,557,831 bp harbors 3,626 protein-coding and 69 RNA genes, and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Introduction

The genus Sulfobacillus currently consists of five species [1], all of which are mildly thermophilic or thermotolerant acidophiles [2]. Sulfobacilli grow mixotrophically by oxidizing ferrous iron, sulfur, and mineral sulfides in the presence of yeast extract or other organic compounds [3]. Some can also grow autotrophically [2,3]. The strains that have been tested are capable of anaerobic growth using Fe+3 as an electron acceptor [2,4]. The genus Sulfobacillus, along with the genus Thermaerobacter, have only tentatively been assigned to a family, “Clostridiales Family XVII incertae sedis”. This group may form a deep branch within the phylum Firmicutes or may constitute a new phylum [5]. Strain NALT (= DSM 10332 = ATCC 700253) is the type strain of the species Sulfobacillus acidophilus. The genus name was derived from the Latin words ‘sulfur’ and ‘bacillus’ meaning ‘small sulfur-oxidizing rod’ [6]. The species epithet is derived from the Neo-Latin words ‘acidum’, acid, and ‘philus’, loving, meaning acid-loving [3]. The first genome from a member of the species S. acidophilus, strain TPY, which was isolated from a hydrothermal vent in the Pacific Ocean, was recently sequenced by Li et al. [7]. Here we present a summary classification and a set of features for S. acidophilum strain NALT, together with the description of the complete genomic sequencing and annotation.

Classification and features

A representative genomic 16S rRNA sequence of S. acidophilus NALT was compared using NCBI BLAST [8,9] 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 [10] and the relative frequencies of taxa and keywords (reduced to their stem [11]) were determined, weighted by BLAST scores. The most frequently occurring genera were Sulfobacillus (81.9%), Thermaerobacter (8.0%), Laceyella (2.8%), ‘Gloeobacter’ (2.1%) and ‘Synechococcus’ (2.0%) (76 hits in total). Regarding the six hits to sequences from members of the species, the average identity within HSPs was 98.9%, whereas the average coverage by HSPs was 97.2%. Regarding the 23 hits to sequences from other members of the genus, the average identity within HSPs was 93.1%, whereas the average coverage by HSPs was 81.2%. Among all other species, the one yielding the highest score was “Sulfobacillus yellowstonensis” (AY007665), which corresponded to an identity of 99.4% and an HSP coverage of 97.0%. (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 HQ730681 (‘Microbial Anaerobic Sediments Tinto River: Natural Acid and Heavy Metals Content extreme acid clone SN1 2009 12D’), which showed an identity of 94.5% and an HSP coverage of 99.0%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were ‘acid’ (4.8%), ‘soil’ (4.5%), ‘hydrotherm’ (3.7%), ‘microbi’ (3.7%) and ‘mine’ (3.0%) (172 hits in total). These keywords correspond well to the environment from which strain NALT was isolated. Environmental samples that yielded hits of a higher score than the highest scoring species were not found.

Figure 1 shows the phylogenetic neighborhood of S. acidophilus NALT in a 16S rRNA based tree. The sequences of the five 16S rRNA gene copies in the genome differ from each other by up to eight nucleotides, and differ by up to four nucleotides from the previously published 16S rRNA sequence (AB089842), which contains two ambiguous base calls.

Figure 1.
figure 1

Phylogenetic tree highlighting the position of S. acidophilus relative to the type strains of the other species within the genus Sulfobacillus. The tree was inferred from 1,422 aligned characters [12,13] of the 16S rRNA gene sequence under the maximum likelihood (ML) criterion [14]. The comparatively closely related genus Symbiobacterium [15] was included for rooting the tree. The branches are scaled in terms of the expected number of substitutions per site. Numbers adjacent to the branches, if any, are support values from 1,000 ML bootstrap replicates [16] (left) and from 1,000 maximum parsimony bootstrap replicates [17] (right) if larger than 60% (i.e., there were none). Lineages with type strain genome sequencing projects registered in GOLD [18] are labeled with one asterisk, those also listed as ‘Complete and Published’ with two asterisks [19].

Cells of S. acidophilus NALT are rods 3.0–5.0 µm in length and 0.5–0.8 µm in width (Table 1 and Figure 2) [3]. Cells are Gram-positive and form spherical endospores [3]. Flagella were not observed [3]. Strain NALT was found to grow between 28°C and 62°C with an optimum at 48°C [35]. The upper and lower temperatures for growth were not determined but were predicted to be 10°C and 62°C [35]. The pH range for growth was 1.6–2.3 with an optimum at 1.8 [35]. Three strains of S. acidophilus have been found to be facultative anaerobes that are able to use Fe+3 as an electron acceptor under anaerobic conditions [4]; but strain NALT was not tested in this study. Strain NALT can grow autotrophically or mixotrophically by oxidizing Fe+2, sulfur, or mineral sulfides or heterotrophically on yeast extract [3]. S. acidophilus and other sulfobacilli have potential applications in biomining. Strain NALT increased the leaching of numerous mineral sulfides [35], however, its sensitivity to low concentrations of metals may limit its usefulness in biomining [35].

Figure 2.
figure 2

Scanning electron micrograph of S. acidophilus NALT

Table 1. Classification and general features of S. acidophilus NALT according to the MIGS recommendations [20] and the NamesforLife database [21].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [38], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [39]. The genome project is deposited in the Genomes OnLine Database [18] 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

Growth conditions and DNA isolation

S. acidophilus strain NALT, DSM 10332, was grown in DSMZ medium 709 (Acidomicrobium medium) [40] at 45°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/LALM for cell lysis as described in Wu et al. 2009 [39]. DNA is available through the DNA Bank Network [41].

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 [42]. Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 104 contigs in three scaffolds was converted into a phrap [43] assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (599.7 Mb) were assembled with Velvet [44] 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 143.7 Mb of 454 draft data and all of the 454 paired-end data. Newbler parameters were -consed -a 50 -l 350 -g -m -ml 20. The Phred/Phrap/Consed software package [43] 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 (C. Han, unpublished), Dupfinisher [45], or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, PCR and Bubble PCR primer walks (J.-F. Chang, unpublished). A total of 640 additional reactions and eight 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 the software Polisher developed at JGI [46]. 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 219.6 × coverage of the genome. The final assembly contained 612,059 pyrosequence and 16,626,072 Illumina reads.

Genome annotation

Genes were identified using Prodigal [47] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [48]. 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 [49].

Genome properties

The genome consists of one circular chromosome of 3,472,898 bp and one circular plasmid of 84,933 bp length with an overall G+C content of 56.8% (Table 3 and Figures 3 and 4). Based on coverage of 454 paired ends, the plasmid may be inserted into the chromosome in about half of the population. Of the 3,695 genes predicted, 3,626 are protein-coding genes, and 69 are RNAs; 155 pseudogenes were also identified. The majority of the protein-coding genes (68.3%) 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.
figure 3

Graphical map of the chromosome. From outside to the 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, GC skew.

Figure 4.
figure 4

Graphical map of the plasmid. From outside to the 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, GC skew.

Table 3. Genome Statistics
Table 4. Number of genes associated with the general COG functional categories

Insights into the genome sequence

Comparative genomics

While the sequencing of the genome described in this paper was underway, Li et al. from the Third Institute of Oceanography, Xiamen, China published the complete genome sequence of strain TPY [7]. The two genomes differ in size by less than 7,000 bp. Here, we take the opportunity to compare the completed genome sequences from these two stains, NALT and TPY, both belonging to S. acidophilus. While the biological material for the type stain, NALT, is publicly available from the DSMZ open collection for postgenomic analyses, no source of the biological material (MIGS-13 criterion, see Table 2) of strain TPY was provided by Li et al. [7].

To estimate the overall similarity between the genomes of strains NALT and TPY (Genbank accession number: CP002901), the GGDC-Genome-to-Genome Distance Calculator [50,51] was used. The system calculates the distances by comparing the genomes to obtain HSPs (high-scoring segment pairs) and interfering distances from three formulae (HSP length / total length; identities / HSP length; identities / total length). The comparison of the genomes of strains NALT and TPY revealed that 99.65% of the average of the genome lengths are covered with HSPs. The identity within these HSPs was 99.01%, whereas the identity over the whole genome (counting regions not covered by HSPs as non-identical) was 98.67%. The inferred digital DNA-DNA hybridization values for the two strains are 96.47% (formula 1 in [51]), 86.08% (formula 2 in [51]) and 97.05% (formula 3 in [51]), respectively. These results clearly demonstrate that according to the whole genome sequences of strains NALT and TPY, the similarity is very high, supporting the membership of both strains in the same species.

The comparison of the number of genes belonging to the different COG categories revealed few differences between the genomes of strains NALT and TPY. Strain NALT has 2,740 genes with COGs assigned, while strain TPY has 2,700. We analyzed the differences in COG assignment between the two strains and found that in almost all cases they could be explained by differences in the gene calls or pseudogene assignment, i.e. in one genome two parts of a pseudogene were called as two separate genes, while in the other genome they were combined into one pseudogene. The only clear case of a difference in gene content between the two strains is the presence of a transposable element consisting of two genes (Sulac_1668, Sulac_1669) disrupting a subunit of a potassium transporter (Sulac_1667) in strain NALT. There were also cases where a gene in one strain was split into two genes in the other strain. For example, Sulac_2178 corresponds to TPY_1983 and TPY1984, and Sulac_0347 corresponds to TPY_0381 and TPY_0382. In both cases the differences are due to a single base indel.

A dot plot showed that there are large blocks of synteny between the two genomes with some rearrangements (data not shown). The genes found on the plasmid in strain NALT are found in two regions of the chromosome in strain TPY. Sulac_3528-3555 corresponds to TPY_0524-0552, while Sulac_3556-3626 corresponds to TPY_2310-2244. This suggests that in strain TPY, the plasmid was inserted into the chromosome and then split into two pieces.

We analyzed CRISPR repeats with the CRISPR Recognition Tool [52] and found major differences between the two strains. They both have two regions of CRISPR repeats, but the strain TPY repeat regions have 8 and 9 repeats while the strain NALT repeat regions have 27 and 43 repeats. All of the spacers in the TPY repeat regions are found in NALT, but NALT has many additional spacers. This agrees with previous results suggesting that CRISPRs evolve quickly, and differences can be found in closely related strains [53].

References

  1. 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 http://dx.doi.org/10.1099/00207713-47-2-590

    Article  PubMed  Google Scholar 

  2. Johnson DB, Joulian C, d’Hugues P, Hallberg KB. Sulfobacillus benefaciens sp. nov., an acidophilic facultative anaerobic Firmicute isolated from mineral bioleaching operations. Extremophiles 2008; 12:789–798. PubMed http://dx.doi.org/10.1007/s00792-008-0184-4

    Article  CAS  PubMed  Google Scholar 

  3. Norris PR, Clark DA, Owen JP, Waterhouse S. Characteristics of Sulfobacillus acidophilus sp. nov. and other moderately thermophilic mineral-sulphide-oxidizing bacteria. Microbiology 1996; 142:775–783. PubMed http://dx.doi.org/10.1099/00221287-142-4-775

    Article  CAS  PubMed  Google Scholar 

  4. Bridge TAM, Johnson DB. Reduction of soluble iron and reductive dissolution of ferric iron-containing minerals by moderately thermophilic iron-oxidizing bacteria. Appl Environ Microbiol 1998; 64:2181–2186. PubMed

    PubMed Central  CAS  PubMed  Google Scholar 

  5. Ludwig W, Schleifer KH, Whitman WB. Revised road map to the phylum Firmicutes. In: Bergey’s Manual of Systematic Bacteriology, 2nd ed., vol. 3. De Vos P, Garrity G, Jones D, Krieg NR, Ludwig W, Rainey FA, Schleifer KH, Whitman WB (eds). 2009. Springer-Verlag, New York. pp. 1–13.

    Google Scholar 

  6. Golovacheva RS, Karavaiko GI. Sulfobacillus, a new genus of thermophilic sporulating bacteria. Mikrobiologiia 1978; 47:815–822. PubMed

    CAS  PubMed  Google Scholar 

  7. Li B, Chen Y, Liu Q, Hu S, Chen X. Complete genome analysis of Sulfobacillus acidophilus strain TPY isolated from a hydrothermal vent in the Pacific Ocean. J Bacteriol 2011; 193:5555–5556. PubMed http://dx.doi.org/10.1128/JB.05684-11

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Altschul SF, Gish W, Miller W, Myers E, Lipman D. Basic local alignment search tool. J Mol Biol 1990; 215:403–410. PubMed

    Article  CAS  PubMed  Google Scholar 

  9. Korf I, Yandell M, Bedell J. BLAST, O’Reilly, Sebastopol, 2003.

    Google Scholar 

  10. 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.03006-05

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.

    Article  Google Scholar 

  12. 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/18.3.452

    Article  CAS  PubMed  Google Scholar 

  13. 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.a026334

    Article  CAS  PubMed  Google Scholar 

  14. 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/10.1080/10635150802429642

    Article  PubMed  Google Scholar 

  15. Yarza P, Ludwig W, Euzéby J, Amann R, Schleifer KH, Glöckner FO, Rossello-Mora R. Update of the All-Species Living Tree Project based on 16S and 23S rRNA sequence analyses. Syst Appl Microbiol 2010; 33:291–299. PubMed http://dx.doi.org/10.1016/j.syapm.2010.08.001

    Article  CAS  PubMed  Google Scholar 

  16. 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_13

    Article  CAS  Google Scholar 

  17. Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods), Version 4.0 b10. Sinauer Associates, Sunderland, 2002.

    Google Scholar 

  18. 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/gkr1100

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Ueda K, Yamashita A, Ishikawa J, Shimada M, Watsuji TO, Morimura K, Ikeda H, Hattori M, Beppu T. Genome sequence of Symbiobacterium thermophilum, an uncultivatable bacterium that depends on microbial commensalism. Nucleic Acids Res 2004; 32:4937–4944. PubMed http://dx.doi.org/10.1093/nar/gkh830

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol 2008; 26:541–547. PubMed http://dx.doi.org/10.1038/nbt1360

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today 2010; 37:9.

    Google Scholar 

  22. 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 http://dx.doi.org/10.1073/pnas.87.12.4576

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Gibbons NE, Murray RGE. Proposals Concerning the Higher Taxa of Bacteria. Int J Syst Bacteriol 1978; 28:1–6. http://dx.doi.org/10.1099/00207713-28-1-1

    Article  Google Scholar 

  24. 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.

    Chapter  Google Scholar 

  25. Murray RGE. The Higher Taxa, or, a Place for Everything…? In: Holt JG (ed), Bergey’s Manual of Systematic Bacteriology, First Edition, Volume 1, The Williams and Wilkins Co., Baltimore, 1984, p. 31–34.

    Google Scholar 

  26. List Editor. List of new names and new combinations previously effectively, but not validly, published. List no. 132. Int J Syst Evol Microbiol 2010; 60:469–472. http://dx.doi.org/10.1099/ijs.0.022855-0

  27. 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.

    Google Scholar 

  28. Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol 1980; 30:225–420. http://dx.doi.org/10.1099/00207713-30-1-225

    Article  Google Scholar 

  29. Prévot AR. In: Hauderoy P, Ehringer G, Guillot G, Magrou. J., Prévot AR, Rosset D, Urbain A (eds), Dictionnaire des Bactéries Pathogènes, Second Edition, Masson et Cie, Paris, 1953, p. 1–692.

    Google Scholar 

  30. da Costa MS, Rainey FA. Family II. Alicyclobacillaceae 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, 2009, p. 229.

    Google Scholar 

  31. List Editor. Validation List no. 36. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol 1991; 41:178–179. http://dx.doi.org/10.1099/00207713-41-1-178

  32. Golovacheva RS, Karavaiko GI. Sulfobacillus, a new genus of thermophilic sporulating bacteria. Mikrobiologiia 1978; 47:815–822. PubMed

    CAS  PubMed  Google Scholar 

  33. Johnson DB, Joulian C, d’Hugues P, Hallberg KB. Sulfobacillus benefaciens sp. nov., an acidophilic facultative anaerobic Firmicute isolated from mineral bioleaching operations. Extremophiles 2008; 12:789–798. PubMed http://dx.doi.org/10.1007/s00792-008-0184-4

    Article  CAS  PubMed  Google Scholar 

  34. List Editor. Validation List no. 59. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol 1996; 46:1189–1190. http://dx.doi.org/10.1099/00207713-46-4-1189

  35. Watling HR, Perrot FA, Shiers DW. Comparison of selected characteristics of Sulfobacillus species and review of their occurrence in acidic and bioleaching environments. Hydrometallurgy 2008; 93:57–65. http://dx.doi.org/10.1016/j.hydromet.2008.03.001

    Article  CAS  Google Scholar 

  36. BAuA. Classification of Bacteria and Archaea in risk groups. TRBA 466. p. 227. Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, Germany. 2010.

    Google Scholar 

  37. 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 http://dx.doi.org/10.1038/75556

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. 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.2010.03.003

    Article  CAS  PubMed  Google Scholar 

  39. 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 http://dx.doi.org/10.1038/nature08656

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. List of growth media used at DSMZ: http://www.dsmz.de/catalogues/catalogue-microorganisms/culture-technology/list-of-media-for-microorganisms.html.

  41. 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.2010.0029

    Article  PubMed  Google Scholar 

  42. JGI website. http://www.jgi.doe.gov.

  43. The Phred/Phrap/Consed software package. http://www.phrap.com.

  44. 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.074492.107

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  45. 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.

  46. 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 

  47. Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119

    Article  PubMed Central  PubMed  Google Scholar 

  48. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods 2010; 7:455–457. PubMed http://dx.doi.org/10.1038/nmeth.1457

    Article  CAS  PubMed  Google Scholar 

  49. 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/btp393

    Article  CAS  PubMed  Google Scholar 

  50. Auch AF, Von Jan M, Klenk HP, Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci 2010; 2:117–134. PubMed http://dx.doi.org/10.4056/sigs.531120

    Article  PubMed Central  PubMed  Google Scholar 

  51. Auch AF, Klenk HP, Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci 2010; 2:142–148. PubMed http://dx.doi.org/10.4056/sigs.541628

    Article  PubMed Central  PubMed  Google Scholar 

  52. Bland C, Ramsey TL, Sabree F, Lowe M, Brown K, Kyrpides NC, Hugenholtz P. CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinformatics 2007; 8:209. PubMed http://dx.doi.org/10.1186/1471-2105-8-209

    Article  PubMed Central  PubMed  Google Scholar 

  53. Tyson GW, Banfield JF. Rapidly evolving CRISPRs implicated in acquired resistance of microorganisms to viruses. Environ Microbiol 2008; 10:200–207. PubMed

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to gratefully acknowledge the help of Gabriele Gehrich-Schröter for growing S. acidophilus cultures and Susanne Schneider for DNA extraction (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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hans-Peter Klenk.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article

Anderson, I., Chertkov, O., Chen, A. et al. Complete genome sequence of the moderately thermophilic mineral-sulfide-oxidizing firmicute Sulfobacillus acidophilus type strain (NALT). Stand in Genomic Sci 6, 293–303 (2012). https://doi.org/10.4056/sigs.2736042

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.4056/sigs.2736042

Keywords