1887

Abstract

Two Gram-stain-negative, Fe(III)-reducing, facultatively anaerobic, motile via a single polar flagellum, rod-shaped bacterial strains, designated IMCC35001 and IMCC35002, were isolated from tidal flat sediment and seawater, respectively. Results of 16S rRNA gene sequence analysis showed that IMCC35001 and IMCC35002 shared 96.6 % sequence similarity and were most closely related to FUT3661 (98.6 %) and Asr22-7 (96.8 %), respectively. Draft genome sequences of IMCC35001 and IMCC35002 revealed 4.0 and 4.8 Mbp of genome size with 61.0 and 51.8 mol% of DNA G+C content, respectively. Average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between the two strains were 73.1 and 19.8 %, respectively, indicating that they are separate species. The two genomes showed ≤84.4 % ANI and ≤27.8 % dDDH to other species of the genus , suggesting that the two strains each represent novel species. The two strains contained both menaquinone (MK-7) and ubiquinones (Q-7 and Q-8). Major fatty acids of strain IMCC35001 were iso-C, C 9, C 8 and C and those of strain IMCC35002 were C 9, C and summed feature 3 (C 7 and/or C 6). Major polar lipids in both strains were phosphatidylethanolamine, phosphatidylglycerol, unidentified phospholipid, unidentified aminophospholipid and unidentified lipids. The two strains reduced Fe(III) citrate, Fe(III) oxyhydroxide, Mn(IV) oxide and sodium selenate but did not reduce sodium sulfate. They were also differentiated by several phenotypic characteristics. Based on the polyphasic taxonomic data, IMCC35001 and IMCC35002 were considered to represent each novel species in the genus , for which the names sp. nov. (IMCC35001=KACC 21161=NBRC 113699) and (IMCC35002=KACC 21162=NBRC 113700) sp. nov. are proposed.

Funding
This study was supported by the:
  • Juchan Hwang , Ministry of Oceans and Fisheries , (Award 20180430)
Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.004359
2020-07-31
2020-08-06
Loading full text...

Full text loading...

/deliver/fulltext/ijsem/10.1099/ijsem.0.004359/ijsem004359.html?itemId=/content/journal/ijsem/10.1099/ijsem.0.004359&mimeType=html&fmt=ahah

References

  1. Lovley DR. Dissimilatory Fe(III) and Mn(IV) reduction. Microbiol Rev 1991; 55:259–287 [CrossRef][PubMed]
    [Google Scholar]
  2. Lovley DR. Dissimilatory metal reduction. Annu Rev Microbiol 1993; 47:263–290 [CrossRef][PubMed]
    [Google Scholar]
  3. Li X, Hou L, Liu M, Zheng Y, Yin G et al. Evidence of nitrogen loss from anaerobic ammonium oxidation coupled with ferric iron reduction in an intertidal wetland. Environ Sci Technol 2015; 49:11560–11568 [CrossRef][PubMed]
    [Google Scholar]
  4. Rosselló-Mora RA, Ludwig W, Kämpfer P, Amann R, Schleifer K-H et al. Ferrimonas balearica gen. nov., spec. nov., a New Marine Facultative Fe(III)-reducing Bacterium. Syst Appl Microbiol 1995; 18:196–202 [CrossRef]
    [Google Scholar]
  5. Rahman MM, Cha C-J. Ferrimonas gelatinilytica sp. nov., isolated from tidal flat sediment. Int J Syst Evol Microbiol 2013; 63:4309–4314 [CrossRef][PubMed]
    [Google Scholar]
  6. Ji S, Zhao R, Li Z, Li B, Shi X et al. Ferrimonas sediminum sp. nov., isolated from coastal sediment of an amphioxus breeding zone. Int J Syst Evol Microbiol 2013; 63:977–981 [CrossRef][PubMed]
    [Google Scholar]
  7. Nakagawa T, Iino T, Suzuki K-I, Harayama S. Ferrimonas futtsuensis sp. nov. and Ferrimonas kyonanensis sp. nov., selenate-reducing bacteria belonging to the Gammaproteobacteria isolated from Tokyo Bay. Int J Syst Evol Microbiol 2006; 56:2639–2645 [CrossRef][PubMed]
    [Google Scholar]
  8. Yim KJ, Lee M, Lee H-W, Kim K-N, Yang H-M et al. Ferrimonas pelagia sp. nov., isolated from seawater. Int J Syst Evol Microbiol 2013; 63:3175–3179 [CrossRef][PubMed]
    [Google Scholar]
  9. Katsuta A, Adachi K, Matsuda S, Shizuri Y, Kasai H. Ferrimonas marina sp. nov. Int J Syst Evol Microbiol 2005; 55:1851–1855 [CrossRef][PubMed]
    [Google Scholar]
  10. Campbell S, Harada RM, Li QX. Ferrimonas senticii sp. nov., a novel gammaproteobacterium isolated from the mucus of a puffer fish caught in Kaneohe Bay, Hawai'i. Int J Syst Evol Microbiol 2007; 57:2670–2673 [CrossRef][PubMed]
    [Google Scholar]
  11. Yoon S-H, Ha S-M, Kwon S, Lim J, Kim Y et al. Introducing EzBioCloud: a taxonomically United database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol 2017; 67:1613–1617 [CrossRef][PubMed]
    [Google Scholar]
  12. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 1991; 173:697–703 [CrossRef][PubMed]
    [Google Scholar]
  13. Pruesse E, Peplies J, Glöckner FO. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 2012; 28:1823–1829 [CrossRef][PubMed]
    [Google Scholar]
  14. Ludwig W, Strunk O, Westram R, Richter L, Meier H et al. ARB: a software environment for sequence data. Nucleic Acids Res 2004; 32:1363–1371 [CrossRef][PubMed]
    [Google Scholar]
  15. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981; 17:368–376 [CrossRef][PubMed]
    [Google Scholar]
  16. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987; 4:406–425 [CrossRef][PubMed]
    [Google Scholar]
  17. Rzhetsky A, Nei M. Theoretical Foundation of the minimum-evolution method of phylogenetic inference. Mol Biol Evol 1993; 10:1073–1095 [CrossRef][PubMed]
    [Google Scholar]
  18. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018; 35:1547–1549 [CrossRef][PubMed]
    [Google Scholar]
  19. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 1985; 39:783–791 [CrossRef][PubMed]
    [Google Scholar]
  20. Stackebrandt E, Goebel BM. Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Evol Microbiol 1994; 44:846–849 [CrossRef]
    [Google Scholar]
  21. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [CrossRef][PubMed]
    [Google Scholar]
  22. Yoon S-H, Ha S-min, Lim J, Kwon S, Chun J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie van Leeuwenhoek 2017; 110:1281–1286 [CrossRef]
    [Google Scholar]
  23. Meier-Kolthoff JP, Auch AF, Klenk H-P, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60 [CrossRef][PubMed]
    [Google Scholar]
  24. Na S-I, Kim YO, Yoon S-H, Ha S-M, Baek I et al. UBCG: up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction. J Microbiol 2018; 56:280–285 [CrossRef][PubMed]
    [Google Scholar]
  25. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [CrossRef][PubMed]
    [Google Scholar]
  26. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 2016; 428:726–731 [CrossRef][PubMed]
    [Google Scholar]
  27. Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M et al. KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics 2020; 36:2251–2252 [CrossRef]
    [Google Scholar]
  28. Marchler-Bauer A, Zheng C, Chitsaz F, Derbyshire MK, Geer LY et al. CDD: conserved domains and protein three-dimensional structure. Nucleic Acids Res 2013; 41:D348–D352 [CrossRef][PubMed]
    [Google Scholar]
  29. Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P et al. DNA–DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 2007; 57:81–91 [CrossRef][PubMed]
    [Google Scholar]
  30. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci USA 2009; 106:19126–19131 [CrossRef][PubMed]
    [Google Scholar]
  31. Chun J, Oren A, Ventosa A, Christensen H, Arahal DR et al. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol 2018; 68:461–466 [CrossRef][PubMed]
    [Google Scholar]
  32. Garber AI, Nealson KH, Okamoto A, McAllister SM, Chan CS et al. FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genome and metagenome assemblies. Front Microbiol 2020; 11:37 [CrossRef][PubMed]
    [Google Scholar]
  33. Wolfe AJ, Berg HC. Migration of bacteria in semisolid agar. Proc Natl Acad Sci USA 1989; 86:6973–6977 [CrossRef][PubMed]
    [Google Scholar]
  34. Hach C. Water Analysis Handbook Loveland, Colorado, USA: 2002 pp 61–62
    [Google Scholar]
  35. Sasser M. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI Technical Note 101. Newark: DE: MIDI Inc; 1990
    [Google Scholar]
  36. Minnikin DE, O'Donnell AG, Goodfellow M, Alderson G, Athalye M et al. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J Microbiol Methods 1984; 2:233–241 [CrossRef]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/ijsem.0.004359
Loading
/content/journal/ijsem/10.1099/ijsem.0.004359
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error