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A report on 30 unrecorded bacteria species in Korea belonging to the classes Betaproteobacteria and Gammaproteobacteria in 2021

  • Yunjeong Lee (Department of Microbiology, Chung-Ang University College of Medicine) ;
  • Jung-Hoon Yoon (Department of Food Science and Biotechnology, Sungkyunkwan University) ;
  • Myung Kyum Kim (Department of Bio and Environmental Technology, College of Natural Science, Seoul Women's University) ;
  • Kiseong Joh (Department of Bioscience and Biotechnology, Hankuk University of Foreign Studies) ;
  • Seung Bum Kim (Department of Microbiology and Molecular Biology, Chungnam National University) ;
  • Che-Ok Jeon (Department of Life Science, Chung-Ang University) ;
  • Chang-Jun Cha (Department of Systems Biotechnology, Chung-Ang University) ;
  • Wan-Taek Im (Department of Biotechnology, Hankyong National University) ;
  • Wonyong Kim (Department of Microbiology, Chung-Ang University College of Medicine)
  • Received : 2022.11.15
  • Accepted : 2023.04.17
  • Published : 2023.08.31

Abstract

A total of 30 bacterial strains were identified in the classes Betaproteobacteria and Gammaproteobacteria in the study of prokaryotic species in Korea. These strains were isolated from a variety of environmental sources, including soil, tidal flat, mud, wetland, pine cone, seaweed, sea sediment, and brackish water. Phylogenetic analysis showed that isolates were identified based on high 16S rRNA gene sequence similarities (≥98.7%) with the predefined bacterial type species. In this study, we present data on previously unreported species from Korea, including 10 species from three families of one order in the class Betaproteobacteria and 20 species from 12 families of nine order in the class Gammaproteobacteria. Morphological, biochemical characteristics, isolation sources, and NIBR deposit numbers are provided in the description sections.

Keywords

Acknowledgement

This work was supported by the project on survey of indigenous species of Korea of the National Institute of Biological Resources (NIBR) under the Ministry of Environment(MOE).

References

  1. Felsenstein, J. 1981. Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal Molecular Evolution 17(6):368-376. https://doi.org/10.1007/BF01734359
  2. Felsenstein, J. 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39(4):783-791. https://doi.org/10.2307/2408678
  3. Fitch, W.M. and E. Margoliash. 1967. Construction of phylogenetic trees. Science 155(3760):279-284. https://doi.org/10.1126/science.155.3760.279
  4. Kersters, K., P. de Vos, M. Gillis, J. Swings, P. Vandamme and E. Stackebrandt. 2006. Introduction to the proteobacteria. The Prokaryotes, Springer, New York. pp. 3-37.
  5. Kim, O.S., Y.J. Cho, K. Lee, S.H. Yoon, M. Kim, H. Na, S.C. Park, Y.S. Jeon, J.H. Lee, H. Yi, S. Won and J. Chun 2012. Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. International Journal of Systematic and Evolutionary Microbiology 62(Pt3):716-721. https://doi.org/10.1099/ijs.0.038075-0
  6. Kimura, M.A. 1980. Simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 16(2):111120.
  7. Kumar, S., G. Stecher and K. Tamura. 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology Evolution 33(7):18701874.
  8. Lane, D.J. 1991. 16S/23S RNA sequencing. In: E. Stackebrandt and M. Goodfellow (eds). Nucleic Acid Techniques in Bacterial Systematics. John Wiley & Sons Ltd., London. pp. 115-175.
  9. Oren, A. and G.M. Garrity. 2021. Valid publication of the names of forty-two phyla of prokaryotes. Int J Syst Evol Microbiol. 71:005056.
  10. Saitou, N. and M. Nei. 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology Evolution 4(4):406-425.
  11. Thompson, J.D., T.J. Gibson, F. Plewniak, F. Jeanmougin and D.G. Higgins. 1997. The CLUSTAL_X Windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research 25(24):4876-4882. https://doi.org/10.1093/nar/25.24.4876