Complete genome sequence of Pseudomonas stutzeri strain RCH2 isolated from a Hexavalent Chromium [Cr(VI)] contaminated site
© The Author(s). 2017
Received: 21 June 2016
Accepted: 8 January 2017
Published: 8 February 2017
Hexavalent Chromium [Cr(VI)] is a widespread contaminant found in soil, sediment, and ground water in several DOE sites, including Hanford 100 H area. In order to stimulate microbially mediated reduction of Cr(VI) at this site, a poly-lactate hydrogen release compound was injected into the chromium contaminated aquifer. Targeted enrichment of dominant nitrate-reducing bacteria post injection resulted in the isolation of Pseudomonas stutzeri strain RCH2. P. stutzeri strain RCH2 was isolated using acetate as the electron donor and is a complete denitrifier. Experiments with anaerobic washed cell suspension of strain RCH2 revealed it could reduce Cr(VI) and Fe(III). The genome of strain RCH2 was sequenced using a combination of Illumina and 454 sequencing technologies and contained a circular chromosome of 4.6 Mb and three plasmids. Global genome comparisons of strain RCH2 with six other fully sequenced P. stutzeri strains revealed most genomic regions are conserved, however strain RCH2 has an additional 244 genes, some of which are involved in chemotaxis, Flp pilus biogenesis and pyruvate/2-oxogluturate complex formation.
KeywordsPseudomonas Nitrate reduction Chromium Hanford 100H
Hexavalent Cr(VI) is a highly toxic and mobile contaminant in the environment. At the DOE site in Hanford, WA, Cr(VI) concentrations reached as high as 50 ppm as a result of nuclear weapon production waste released into the groundwater and soil. In order to reduce Cr(VI) to non-toxic immobilized Cr(III), the bioremediative strategy at the site has been to stimulate indigenous microorganisms  by injecting environmentally safe, food quality polylactate ester Hydrogen Release Compound. The slow release electron donor induced biologically mediated reduction of Cr(VI) to Cr(III) by indigenous microorganisms, and as a result, Cr(IV) concentrations were reduced to below 50 ppb in all parts of the Hanford 100 H site . Some group of organisms including Pseudomonadaceae were enriched concomitant to decrease in Cr(VI) concentrations after HRC injection, and continued to remain high . Pseudomonas stutzeri strain RCH2, was isolated from a monitoring well post injection.
Pseudomonas spp. are well-characterized heterotrophs known to degrade several hydrocarbons [2–5], and reduce metals such as Cr(VI) [6–9]. They have commonly been detected in several DOE contaminated sites [10–13] including Uranium contaminated Oakridge Field Research Center [14, 15]. Prolific cultivation of Pseudomonas spp. from such unique contaminated environments is imperative in elucidating the metabolic potential, biochemical and physiological characteristics and the genetic determinants of key pathways of this ubiquitous group of bacteria in the environment. The genome sequence of RCH2 allows for detailed examination of this and closely related microbes in response to environmental perturbations at the genetic level, and provides a basis for investigating response, adaptation and evolution in presence of metal contaminants .
Classification and features
Enrichments were initiated in Minimal Fresh Water medium  with 10 mM acetate as the sole electron donor and 10 mM nitrate as the electron acceptor. All enrichments were incubated in the dark at 30 °C. Periodic transfers of positive enrichments as identified by microscopy or visual turbidity, were made into fresh media. After 5 such transfers, a pure culture of strain RCH2 was obtained by the agar shake tube method [18, 19]. For routine culturing, strain RCH2 was grown in MFW medium under anaerobic conditions, using either lactate or acetate as electron donor and nitrate as electron acceptor. All culturing was done in sealed serum vials with N2:CO2 gas (80:20) in the headspace, as the medium contained 30 mM bicarbonate buffer.
For initial genotyping, gDNA was extracted using the MoBio UltraClean Microbial DNA Isolation Kit (MoBio Inc, Carlsbad, CA). PCR amplification was carried out using universal bacterial 16S ribosomal RNA gene (16S rRNA) primers 1492R and 27 F in 50 μl reactions. The small subunit ribosomal RNA gene was sequenced by Sanger sequencing using universal primers 8 F and 1492R  at University of California, Berkeley sequencing facility. 16S rRNA sequence analysis places strain RCH2 in the family Pseudomonadaceae .
Genome sequencing information
Genome project history
Classification and general features of Pseudomonas stutzeri strain RCH2 according to the MIGS recommendations 
Terminal electron receptor
Cr(VI) contaminated aquifer
Optimal growth at 0.35% salinity
Benton County, Washington
Sample collection time
Centered on 46°38′51″N
Genome sequencing project information for Pseudomonas stutzeri strain RCH2
454 titanium standard library, 454 paired end library, Illumina GAii shotgun library
454-GS-FLX, Illumina GAii
Illumina GAii: 127.1x
Gene calling method
GenePrimp, Prodigal 1.4
Genbank Date of Release
September 6, 2011
Source Material Identifier
Chromium (VI) reduction, nitrate reduction
Growth conditions and genomic DNA preparation
P. stutzeri strain RCH2 was grown under anaerobic conditions at 37 °C in basal medium containing 20 mM lactate as the sole electron donor and carbon source and 10 mM nitrate as the terminal electron acceptor. Cells were harvested for DNA extraction when they reached mid-log phase of growth.
Genomic DNA was extracted from a 50 ml culture using the CTAB extraction method recommended by JGI, USA . JGI DNA mass standards were used to ascertain the quantity and quality of the extracted gDNA. JGI protocol for running the gel electrophoresis was followed.
Genome sequencing and assembly
The genome of P. stutzeri strain RCH2 was generated at the DOE JGI using a combination of Illumina  and 454 technologies . For this genome we constructed and sequenced an Illumina GAii shotgun library which generated 16,378,443 reads totaling 589.6 Mb, a 454 Titanium standard library which generated 255,080 reads and 2 paired end 454 libraries with an average insert size of 9 kb, and 19 kb which generated 582,773 reads totaling 216.3 Mb of 454 data. All general aspects of library construction and sequencing performed at the JGI . The initial draft assembly contained 32 contigs in 1 scaffold. The 454 Titanium standard data and the 454 paired end data were assembled together with Newbler, version 2.3. The Newbler consensus sequences were computationally shredded into 2 kb overlapping fake reads (shreds). Illumina sequencing data were assembled with VELVET, version 1.0.13 , and the consensus sequence were computationally shredded into 1.5 kb overlapping fake reads (shreds). We integrated the 454 Newbler consensus shreds, the Illumina VELVET consensus shreds and the read pairs in the 454 paired end library using parallel phrap, version SPS −4.24 (High Performance Software, LLC). The software Consed [39–41] was used in the following finishing process. Illumina data were used to correct potential base errors and increase consensus quality using the software Polisher developed at Joint Genome Institute (JGI) (Alla Lapidus, unpublished). Possible mis-assemblies were corrected using gap Resolution (Cliff Han, unpublished), Dupfinisher , or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR (J-F Cheng, unpublished) primer walks. A total of 68 additional reactions were necessary to close gaps and to raise the quality of the finished sequence. The total size of the genome is 4,600,489 bp and the final assembly is based on 148 Mb of 454 draft data which provides an average 32.2x coverage of the genome and 584.6 Mb of Illumina draft data which provides an average 127.1x coverage of the genome.
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, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. These data sources were combined to assert a product description for each predicted protein. Non-coding genes and miscellaneous features were predicted using tRNAscan-SE , RNAMMer , Rfam , TMHMM , and signalP .
Summary of genome: 1 chromosome and 3 plasmids
Genome statistics for Pseudomonas stutzeri strain RCH2
% of Total
Genome size (bp)
DNA coding (bp)
DNA G + C (bp)
Protein coding genes
Genes in internal clusters
Genes with function prediction
Genes assigned to COGs
Genes with Pfam domains
Genes with signal peptides
Genes with transmembrane helices
Number of genes associated with the general COG functional categories
% of totala
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 biogenesis
Intracellular trafficking and secretion
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
Insights from the genome sequence
We searched for regulatory interactions in P. stutzeri strain RCH2 using an automated conservative propagation procedure described earlier . By comparison with the RegPrecise database, this procedure identified 27 regulons in P. stutzeri RCH2 genome. Of those regulons, 11 contain genes for central carbon metabolism and utilization of various carbon sources. Other regulatory systems control metabolism of amino acids (MetR, PhhR), nitrogen (NtrC) and phosphonate (PhnF), biosynthesis of biotin (BirA), lipopolysaccharide (GlmR) and nucleotides (NrdR, RutR), metal homeostasis (CadR, CueR, Zur), DNA repair (LexA) and biogenesis of iron-sulfur clusters (IscR). At the same time, P. stutzeri strain RCH2 lacks several transcription factors conserved in various Gammaproteobacteria , like PdxR (regulator of pyridoxine biosynthesis), FabR (regulator of fatty acid biosynthesis) and SoxR (regulator of superoxide stress response).
Pseudomonas stutzeri strain RCH2 isolated from chromium-contaminated aquifer, is a complete denitrifier that can couple nitrate reduction to oxidation of several organic carbon. When supplemented with lactate, robust culture of strain RCH2 reduces Cr(VI) rapidly and this feature contributes to the versatility of this organism to survive in such chromium(VI) contaminated areas. The genome of strain RCH2 reveals differences when compared to closely related strains, and contains an additional 244 genes, mostly of unknown function. Clusters that are specific to strain RCH2 include chemotaxis and Flp pilus biogenesis and these clusters are absent from the five closely related strains examined. The genome sequence of strain RCH2 will assist in further research into the underlying mechanisms of adaption and persistence in metal and/or nitrate contaminated sites.
Department of Energy
Joint Genome Institute
National Center for Biotechnology Information (Bethesda, MD, USA)
Ribosomal Database Project (East Lansing, MI, USA)
The work conducted at Lawrence Berkeley National Lab by ENIGMA- Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Scientific Focus Area Program) and at the Joint Genome Institute was supported by the Office of Science, Office of Biological and Environmental Research, of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123. The work conducted by the U.S. Department of Energy Joint Genome Institute is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
RC isolated the organism and performed laboratory experiments. RC, HW and RW drafted the manuscript. RC, HW, PD, LG, AK, PN, RW, APA, TCH sequenced, assembled and annotated the genome. MZ and MA performed the SEM studies. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
- Faybishenko B, Hazen TC, Long PE, Brodie EL, Conrad ME, Hubbard SS, Christensen JN, Joyner D, Borglin SE, Chakraborty R, et al. In situ long-term reductive bioimmobilization of Cr(VI) in groundwater using hydrogen release compound. Environ Sci Technology. 2008;42(22):8478–85.View ArticleGoogle Scholar
- Barathi S, Vasudevan N. Utilization of petroleum hydrocarbons by Pseudomonas fluorescens isolated from a petroleum-contaminated soil. Environ Int. 2001;26(5–6):413–6.View ArticlePubMedGoogle Scholar
- Foght JM, Westlake DWS. Degradation of polycyclic aromatic-hydrocarbons and aromatic heterocycles by a Pseudomonas species. Can J Microbiol. 1988;34(10):1135–41.View ArticlePubMedGoogle Scholar
- Ramos JL, Duque E, Huertas MJ, Haidour A. Isolation and expansion of the catabolic potential of a Pseudomonas putida strain able to grow in the presence of high-concentrations of aromatic-hydrocarbons. J Bacteriol. 1995;177(14):3911–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Whyte LG, Bourbonniere L, Greer CW. Biodegradation of petroleum hydrocarbons by psychrotrophic Pseudomonas strains possessing both alkane (alk) and naphthalene (nah) catabolic pathways. Appl Environ Microb. 1997;63(9):3719–23.Google Scholar
- Han R, Geller JT, Yang L, Brodie EL, Chakraborty R, Larsen JT, Beller HR. Physiological and transcriptional studies of Cr(VI) reduction under aerobic and denitrifying conditions by an aquifer-derived Pseudomonad. Environ Sci Technology. 2010;44(19):7491–7.View ArticleGoogle Scholar
- Zawadzka AM, Crawford RL, Paszczynski AJ. Pyridine-2,6-bis(thiocarboxylic acid) produced by Pseudomonas stutzeri KC reduces chromium (VI) and precipitates mercury, cadmium, lead and arsenic. Biometals. 2007;20:145–8.
- Ishibashi Y, Cervantes C, Silver S. Chromium reduction in Pseudomonas putida. Appl Environ Microb. 1990;56(7):2268–70.Google Scholar
- Park CH, Keyhan M, Wielinga B, Fendorf S, Matin A. Purification to homogeneity and characterization of a novel Pseudomonas putida chromate reductase. Appl Environ Microb. 2000;66(5):1788–95.View ArticleGoogle Scholar
- Benyehuda G, Coombs J, Ward PL, Balkwill D, Barkay T. Metal resistance among aerobic chemoheterotrophic bacteria from the deep terrestrial subsurface. Can J Microbiol. 2003;49(2):151–6.View ArticlePubMedGoogle Scholar
- Brodie EL, Joyner DC, Faybishenko B, Conrad ME, Rios-Velazquez C, Malave J, Martinez R, Mork B, Willett A, Koenigsberg S, et al. Microbial community response to addition of polylactate compounds to stimulate hexavalent chromium reduction in groundwater. Chemosphere. 2011;85(4):660–5.View ArticlePubMedGoogle Scholar
- Jimenez L. Molecular analysis of deep-subsurface bacteria. Appl Environ Microb. 1990;56(7):2108–13.Google Scholar
- Liu P, Meagher RJ, Light YK, Yilmaz S, Chakraborty R, Arkin AP, Hazen TC, Singh AK. Microfluidic fluorescence in situ hybridization and flow cytometry (mu FlowFISH). Lab Chip. 2011;11(16):2673–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Cardenas E, Wu W-M, Leigh MB, Carley J, Carroll S, Gentry T, Luo J, Watson D, Gu B, Ginder-Vogel M, et al. Microbial communities in contaminated sediments, associated with bioremediation of uranium to submicromolar levels. Appl Environ Microb. 2008;74(12):3718–29.View ArticleGoogle Scholar
- Fields MW, Yan TF, Rhee SK, Carroll SL, Jardine PM, Watson DB, Criddle CS, Zhou JZ. Impacts on microbial communities and cultivable isolates from groundwater contaminated with high levels of nitric acid-uranium waste. FEMS Microbiol Ecol. 2005;53(3):417–28.View ArticlePubMedGoogle Scholar
- Han R, Qin L, Brown ST, Christensen JN, Beller HR. Differential isotopic fractionation during Cr(VI) reduction by an aquifer-derived bacterium under aerobic versus denitrifying conditions. Appl Environ Microbiol. 2012;78(7):2462–4.View ArticlePubMedPubMed CentralGoogle Scholar
- Coates JD, Achenbach LA. The microbiology of perchlorate reduction and its bioremediative application. In: Gu B, Coates JD, editors. PERCHLORATE: environmental ocurrence, interactions and treatment. New York: Springer; 2006. p. 279–95.View ArticleGoogle Scholar
- Bruce RA, Achenbach LA, Coates JD. Reduction of (per)chlorate by a novel organism isolated from paper mill waste. Environ Microbiol. 1999;1(4):319–29.View ArticlePubMedGoogle Scholar
- Coates JD, Cole KA, Chakraborty R, O’Connor SM, Achenbach LA. Diversity and ubiquity of bacteria capable of utilizing humic substances as electron donors for anaerobic respiration. Appl Environ Microb. 2002;68(5):2445–52.View ArticleGoogle Scholar
- Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23(21):2947–8.View ArticlePubMedGoogle Scholar
- Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Sun Y, Brown CT, Porras-Alfaro A, Kuske CR, Tiedje JM. Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res. 2014;42(D1):D633–42.View ArticlePubMedGoogle Scholar
- Gouy M, Guindon S, Gascuel O. SeaView version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol Biol Evol. 2010;27(2):221–4.View ArticlePubMedGoogle Scholar
- ElAnisimova M, Gascuel O. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Systematic Biol. 2006;55(4):539–52.View ArticleGoogle Scholar
- Pattanapipitpaisal P, Brown NL, Macaskie LE. Chromate reduction by Microbacterium liquefaciens immobilised in polyvinyl alcohol. Biotechnol Lett. 2001;23(1):61–5.View ArticleGoogle 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(5):541–7.View ArticlePubMedPubMed CentralGoogle 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 U S A. 1990;87(12):4576–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Garrity GM, Bell JA, Lilburn T. Phylum XIV. Proteobacteria phyl. nov. Bergey’s Manual Systematic Bacteriology. 2005;2(Part B):1.View ArticleGoogle Scholar
- Garrity GM, Bell JA, Lilburn T. Class III. Gammaproteobacteria class. nov. Bergey’s Manual Systematic Bacteriology. 2005;2(Part B):1.View ArticleGoogle Scholar
- Skerman VBD, McGowan V, Sneath PHA. Approved lists of bacterial names. Int J Syst Bacteriol. 1980;30:225–420.View ArticleGoogle Scholar
- Orla-Jensen S. The main lines of the natural bacterial system. J Bacteriol. 1921;6:263–73.PubMedPubMed CentralGoogle Scholar
- Winslow CEA, Broadhurst J, Buchanan RE, Krumwiede C, Rogers LA, Smith GH. The families and genera of the bacteria: preliminary report of the committee of the society of american bacteriologists on characterization and classification of bacterial types. J Bacteriol. 1917;2:505–66.PubMedPubMed CentralGoogle Scholar
- Migula W. Über ein neues system der bakterien. Arbeiten aus dem Bakteriologischen Institut der Technischen Hochschule zu Karlsruhe. 1894;1:235–8.Google Scholar
- Sijderius R. Dissertation: Heterotrophe bacterien, die thiosulfaat oxydeeren. University Amsterdam. 1946;1–146.
- 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(1):25–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Joint Genome Institute. http://www.jgi.doe.gov. Accessed 3 Jan 2016
- Bennett S. Solexa Ltd. Pharmacogenomics. 2004;5(4):433–8.View ArticlePubMedGoogle Scholar
- Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen ZT, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005;437(7057):376–80.PubMedPubMed CentralGoogle Scholar
- Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18(5):821–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Ewing B, Green P. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 1998;8(3):186–94.View ArticlePubMedGoogle Scholar
- Ewing B, Hillier L, Wendl MC, Green P. Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 1998;8(3):175–85.View ArticlePubMedGoogle Scholar
- Gordon D, Abajian C, Green P. Consed: a graphical tool for sequence finishing. Genome Rese. 1998;8(3):195–202.View ArticleGoogle Scholar
- Han CS, Chain P. Finishing repetitive regions automatically with dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology: June 26–29 2006. CSREA Press: 141–146.
- 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.View ArticlePubMedPubMed CentralGoogle 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(6):455–U462.View ArticlePubMedGoogle Scholar
- Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25(5):955–64.View ArticlePubMedPubMed CentralGoogle Scholar
- Lagesen K, Hallin P, Rodland EA, Staerfeldt HH, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007;35(9):3100–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Griffiths-Jones S, Bateman A, Marshall M, Khanna A, Eddy SR. Rfam: an RNA family database. Nucleic Acids Res. 2003;31(1):439–41.View ArticlePubMedPubMed CentralGoogle Scholar
- Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001;305(3):567–80.View ArticlePubMedGoogle Scholar
- Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol. 2004;340(4):783–95.View ArticlePubMedGoogle Scholar
- Novichkov PS, Kazakov AE, Ravcheev DA, Leyn SA, Kovaleva GY, Sutormin RA, Kazanov MD, Riehl W, Arkin AP, Dubchak I, et al. RegPrecise 3.0: a resource for genome-scale exploration of transcriptional regulation in bacteria. BMC Genomics. 2013;14:745.View ArticlePubMedPubMed CentralGoogle Scholar
- Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421.View ArticlePubMedPubMed CentralGoogle Scholar
- Alikhan N-F, Petty NK, Ben Zakour NL, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics. 2011;12.