Current Microbiology

, Volume 74, Issue 4, pp 515–521 | Cite as

Hymenobacter knuensis sp. nov., Isolated From River Water

  • Leonid N. Ten
  • Jae-Jin Lee
  • Yeon-Hee Lee
  • Su-Jin Park
  • Seung-Yeol Lee
  • Sangkyu Park
  • Dae Sung Lee
  • In-Kyu Kang
  • Myung Kyum Kim
  • Hee-Young JungEmail author


A Gram-stain-negative, non-motile, non-spore-forming, rod-shaped, aerobic bacterial strain, designated 16F7C-2T, was isolated from the Han River, South Korea, and was characterized taxonomically using a polyphasic approach. Comparative 16S rRNA gene sequence analysis showed that strain 16F7C-2T belonged to the family Cytophagaceae in the phylum Bacteroidetes and was most closely related to Hymenobacter algoricola VUG-A23aT (98.3%) and Hymenobacter fastidiosus VUG-A124T (97.7%). The G + C content of the genomic DNA of strain 16F7C-2T was 63.4 mol%. The detection of menaquinone MK-7 as the predominant respiratory quinone; a fatty acid profile with summed feature 3 (C16:1 ω7c/C16:1 ω6c; 19.5%), summed feature 4 (C17:1 iso I/C17:1 anteiso B; 15.9%), C15:0 iso (12.6%), C16:1 ω5c (10.5%), and C15:0 anteiso (10.4%) as the major components; and a polar lipid profile with phosphatidylethanolamine as the major component also supported the affiliation of strain 16F7C-2T to the genus Hymenobacter. The DNA–DNA relatedness between strain 16F7C-2T and H. algoricola JCM 17214T and H. fastidiosus JCM17224T were 45.2 ± 5.8 and 40.3 ± 2.9%, respectively, clearly showing that the isolate constitutes a new genospecies. Strain 16F7C-2T could be clearly differentiated from its closest neighbors on the basis of its phenotypic, genotypic, and chemotaxonomic features. Therefore, strain 16F7C-2T represents a novel species of the genus Hymenobacter, for which the name Hymenobacter knuensis sp. nov. is proposed. The type strain is 16F7C-2T (=KCTC 52538T = JCM 31814T).


Fatty Acid Profile Cellular Fatty Acid Isoprenoid Quinone Itaconate Major Polar Lipid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the Human Resource Training Program for Regional Innovation and Creativity through the Ministry of Education and National Research Foundation (NRF) of Korea (NRF-2014H1C1A1066929) and by the Brain Pool Program of 2016 (grant 162S-4-3-1727) through the Korean Federation of Science and Technology Societies (KOFST) funded by the Ministry of Science, ICT and Future Planning, Republic of Korea.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

284_2017_1216_MOESM1_ESM.docx (655 kb)
Supplementary material 1 (DOCX 655 KB)


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Leonid N. Ten
    • 1
  • Jae-Jin Lee
    • 1
  • Yeon-Hee Lee
    • 1
  • Su-Jin Park
    • 1
  • Seung-Yeol Lee
    • 1
  • Sangkyu Park
    • 1
  • Dae Sung Lee
    • 2
  • In-Kyu Kang
    • 3
  • Myung Kyum Kim
    • 4
  • Hee-Young Jung
    • 1
    • 5
    Email author
  1. 1.School of Applied BiosciencesKyungpook National UniversityDaeguRepublic of Korea
  2. 2.Department of Environmental EngineeringKyungpook National UniversityDaeguRepublic of Korea
  3. 3.Department of Horticultural ScienceKyungpook National UniversityDaeguRepublic of Korea
  4. 4.Department of Bio and Environmental TechnologySeoul Women’s UniversitySeoulRepublic of Korea
  5. 5.Institute of Plant MedicineKyungpook National UniversityDaeguRepublic of Korea

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