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Abstract

The present study aimed to determine the taxonomic positions of strains designated R-5-52-3, R-5-33-5-1-2, R-5-48-2 and R-5-51-4 isolated from hot spring water samples. Cells of these strains were Gram-stain-negative, non-motile and rod-shaped. The strains shared highest 16S rRNA gene sequence similarity with KCTC 32020 (95.1%). Growth occurred at 28–55 °C, at pH 6–8 and with up to 3 % (w/v) NaCl. DNA fingerprinting, biochemical, phylogenetic and 16S rRNA gene sequence analyses suggested that R-5-52-3, R-5-33-5-1-2, R-5-48-2 and R-5-51-4 were different strains but belonged to the same species. Hence, R-5-52-3 was chosen for further analysis and R-5-33-5-1-2, R-5-48-2 and R-5-51-4 were considered as additional strains of this species. R-5-52-3 possessed Q-8 as the only quinone and iso-C, iso-C, C and iso-C as major fatty acids. The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, unidentified polar lipids and two unidentified phospholipids. The genomic G+C content was 71.6 mol%. Heat shock proteins (e.g. Hsp20, GroEL, DnaK and Clp ATPases) were noted in the R-5-52-3 genome, which could suggest its protection in the hot spring environment. Pan-genome analysis showed the number of singleton gene clusters among members varied. Average nucleotide identity (ANI) values between R-5-52-3, YIM 77520 and KCTC 32020 were 80.1–85.8 %, which were below the cut-off level (95–96 %) recommended as the ANI criterion for interspecies identity. Thus, based on the above results, strain R-5-52-3 represents a novel species of the genus , for which the name sp. nov. is proposed. The type strain is R-5-52-3 (=KCTC 72061=CGMCC 1.16678).

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2020-01-02
2020-01-24
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References

  1. Garrity GM, Bell JA, Lilburn T, Phylum XIV. Proteobacteria phyl. nov. class III. Gammaproteobacteria class. nov In Brenner DJ, Krieg NR, Staley JT, Garrity GM. (editors) Bergey’s Manual of Systematic Bacteriology2, 2nd ed. New York: Springer; 2005; p 1
    [Google Scholar]
  2. Moon CD, Young W, Maclean PH, Cookson AL, Bermingham EN. Metagenomic insights into the roles of Proteobacteria in the gastrointestinal microbiomes of healthy dogs and cats. Microbiologyopen 2018;7: e00677 [CrossRef]
    [Google Scholar]
  3. TT Y, Zhou EM, Yin YR, Yao JC, Ming H et al. Vulcaniibacterium tengchongense gen. nov., sp. nov. isolated from a geothermally heated soil sample, and reclassification of Lysobacter thermophilus Wei, et al. 2012 as Vulcaniibacterium thermophilum comb. nov. Antonie Van Leeuwenhoek2013: 369– 376
    [Google Scholar]
  4. Parte AC. LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. Int J Syst Evol Microbiol 2018;68: 1825– 1829 [CrossRef]
    [Google Scholar]
  5. Li W-J, Xu P, Schumann P, Zhang Y-Q, Pukall R et al. Georgenia ruanii sp. nov., a novel actinobacterium isolated from forest soil in Yunnan (China), and emended description of the genus Georgenia. Int J Syst Evol Microbiol 2007;57: 1424– 1428 [CrossRef]
    [Google Scholar]
  6. Dong Z-Y, Narsing Rao MP, Wang H-F, Fang B-Z, Liu Y-H et al. Transcriptomic analysis of two endophytes involved in enhancing salt stress ability of Arabidopsis thaliana. Sci Total Environ 2019;686: 107– 117 [CrossRef]
    [Google Scholar]
  7. 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]
    [Google Scholar]
  8. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987;4: 406– 425
    [Google Scholar]
  9. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981;17: 368– 376 [CrossRef]
    [Google Scholar]
  10. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 2016;33: 1870– 1874 [CrossRef]
    [Google Scholar]
  11. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 1997;25: 4876– 4882 [CrossRef]
    [Google Scholar]
  12. Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 1980;16: 111– 120 [CrossRef]
    [Google Scholar]
  13. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 1985;39: 783– 791 [CrossRef]
    [Google Scholar]
  14. Fujino Y, Kawatsu R, Inagaki F, Umeda A, Yokoyama T et al. Thermus thermophilus TMY isolated from silica scale taken from a geothermal power plant. J Appl Microbiol 2008;104: 70– 78 [CrossRef]
    [Google Scholar]
  15. Kim M, Oh H-S, Park S-C, Chun J. Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int J Syst Evol Microbiol 2014;64: 346– 351 [CrossRef]
    [Google Scholar]
  16. 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]
    [Google Scholar]
  17. Luo R, Liu B, Xie Y, Li Z, Huang W et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 2012;1: 18 [CrossRef]
    [Google Scholar]
  18. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 2015;25: 1043– 1055 [CrossRef]
    [Google Scholar]
  19. Eren AM, ÖC E, Quince C, Vineis JH, Morrison HG et al. Anvi'o: an advanced analysis and visualization platform for 'omics data. PeerJ 2015;8: e1319
    [Google Scholar]
  20. Edgar RC. Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004;32: 1792– 1797 [CrossRef]
    [Google Scholar]
  21. Price MN, Dehal PS, Arkin AP. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 2009;26: 1641– 1650 [CrossRef]
    [Google Scholar]
  22. Letunic I, Bork P. Interactive tree of life (iTOL) V4: recent updates and new developments. Nucleic Acids Res 2019;47: W256– W259 [CrossRef]
    [Google Scholar]
  23. Delcher A, Harmon D, Kasif S, White O, Salzberg SL. Improved microbial gene identification with GLIMMER. Nucleic Acids Res 1999;27: 4636– 4641 [CrossRef]
    [Google Scholar]
  24. Tatusov RL, Koonin EV, Lipman DJ. A genomic perspective on protein families. Science 1997;278: 631– 637 [CrossRef]
    [Google Scholar]
  25. Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B et al. The COG database: an updated version includes eukaryotes. BMC Bioinformatics 2003;4: 41 [CrossRef]
    [Google Scholar]
  26. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res 2007;35: W182– W185 [CrossRef]
    [Google Scholar]
  27. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 1997;25: 955– 964 [CrossRef]
    [Google Scholar]
  28. Lagesen K, Hallin P, Rødland EA, Staerfeldt H-H, Rognes T et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res 2007;35: 3100– 3108 [CrossRef]
    [Google Scholar]
  29. Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using diamond. Nat Methods 2015;12: 59– 60 [CrossRef]
    [Google Scholar]
  30. van Dongen S, Abreu-Goodger C. Using MCL to extract clusters from networks. Methods Mol Biol 2012;804: 281– 295 [CrossRef]
    [Google Scholar]
  31. 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]
    [Google Scholar]
  32. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M et al. Versatile and open software for comparing large genomes. Genome Biol 2004;5: R12– 2483 [CrossRef]
    [Google Scholar]
  33. Richter M, Rosselló-Móra R, Oliver Glöckner F, Peplies J. JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. Bioinformatics 2016;32: 929– 931 [CrossRef]
    [Google Scholar]
  34. DC L, Yang F, Lu B, Chen DF, Yang WJ. Thermotolerance and molecular chaperone function of the small heat shock protein HSP20 from hyperthermophilic archaeon, Sulfolobus solfataricus P2. Cell Stress Chaperones 2012;17: 103– 108
    [Google Scholar]
  35. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci U S A 2009;106: 19126– 19131 [CrossRef]
    [Google Scholar]
  36. Xu P et al. Naxibacter alkalitolerans gen. nov., sp. nov., a novel member of the family 'Oxalobacteraceae' isolated from China. Int J Syst Evol Microbiol 2005;55: 1149– 1153 [CrossRef]
    [Google Scholar]
  37. Kovacs N. Identification of Pseudomonas pyocyanea by the oxidase reaction. Nature 1956;178: 703– 704 [CrossRef]
    [Google Scholar]
  38. Gonzalez C, Gutierrez C, Ramirez C. Halobacterium vallismortis sp. nov. An amylolytic and carbohydrate-metabolizing, extremely halophilic bacterium. Can J Microbiol 1978;24: 710– 715 [CrossRef]
    [Google Scholar]
  39. Fautz E, Reichenbach H. A simple test for flexirubin-type pigments. FEMS Microbiol Lett 1980;8: 87– 91 [CrossRef]
    [Google Scholar]
  40. Venil CK, Khasim AR, Aruldass CA, Ahmad WA. Microencapsulation of flexirubin-type pigment by spray drying: characterization and antioxidant activity. Int Biodeterior Biodegradation 2016;113: 350– 356 [CrossRef]
    [Google Scholar]
  41. Venil CK, Zakaria ZA, Ahmad WA. Optimization of culture conditions for flexirubin production by Chryseobacterium artocarpi CECT 8497 using response surface methodology. Acta Biochim Pol 2015;62: 185– 190 [CrossRef]
    [Google Scholar]
  42. Collins MD, Pirouz T, Goodfellow M, Minnikin DE. Distribution of menaquinones in actinomycetes and corynebacteria. J Gen Microbiol 1977;100: 221– 230 [CrossRef]
    [Google Scholar]
  43. Kroppenstedt RM. Separation of bacterial menaquinones by HPLC using reverse phase (RP18) and a silver loaded ion exchanger as stationary phases. J Liq Chromatogr 1982;5: 2359– 2367 [CrossRef]
    [Google Scholar]
  44. Minnikin DE, Collins MD, Goodfellow M. Fatty Acid and Polar Lipid Composition in the Classification of Cellulomonas, Oerskovia and Related Taxa. J Appl Bacteriol 1979;47: 87– 95 [CrossRef]
    [Google Scholar]
  45. Collins MD, Jones D. Lipids in the classification and identification of coryneform bacteria containing peptidoglycans based on 2, 4-diaminobutyric acid. J Appl Bacteriol 1980;48: 459– 470 [CrossRef]
    [Google Scholar]
  46. Sasser M. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI Technical Note 101. Newark: Microbial ID, Inc; 1990
    [Google Scholar]
  47. Wei D-Q, Yu T-T, Yao J-C, Zhou E-M, Song Z-Q et al. Lysobacter thermophilus sp. nov., isolated from a geothermal soil sample in Tengchong, south-west China. Antonie van Leeuwenhoek 2012;102: 643– 651 [CrossRef]
    [Google Scholar]
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