Microbial Systematics and Evolutionary Microbiology
A yellow-colored bacterium with gliding motility, strain KIS68-18T, was isolated from a soil sample at Bijin Island in Tongyeong city, Republic of Korea. The cells were strictly aerobic, Gram-staining-negative, non-spore-forming, and rod-shaped. The strain grew at the range of 10–35°C (optimum, 25–30°C), pH 5.5–8.0 (optimum, 6.0–7.5), and 0–0.5% (w/v) NaCl. A phylogenetic analysis based on 16S rRNA gene sequences revealed that strain KIS68-18T was closely related to Chryseolinea serpens DSM 24574T (98.9%) and had low sequence similarities (below 92.6%) with other members of the family ‘Cytophagaceae’ in the phylum Bacteroidetes. The major respiratory quinone system was MK-7 and the predominant cellular fatty acids were C16:1ω5c (38.8%), iso-C15:0 (18.5%), and summed feature 3 (C16:1ω7c and/or C16:1ω6c, 10.6%). The polar lipids consisted of phosphatidylethanolamine, one unidentified phospholipid, three unidentified aminophospholipids, two unidentified aminolipids, and five unidentified lipids. The DNA G + C content was 50.9%. Based on the phylogenetic, physiological, and chemotaxonomic data, stain KIS68-18T represents a novel species of the genus Chryseolinea, for which the name Chryseolinea soli sp. nov. is proposed. The type strain of Chryseolinea soli is KIS68-18T (= KACC 17327T = NBRC 113100T).
Chryseolineastrain KIS68-18 novel species polyphasic taxonomy
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Kim, J.J., Alkawally, M., Brady, A.L., Rijpstra, W.I., Sinninghe Damste, J.S., and Dunfield, P.F. 2013. Chryseolinea serpens gen. nov., sp. nov., a member of the phylum Bacteroidetes isolated from soil. Int. J. Syst. Evol. Microbiol.63, 654–660.CrossRefGoogle Scholar
Kimura, M. 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol.16, 111–120.CrossRefGoogle Scholar
Kumar, S., Stecher, G., and Tamura, K. 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol.33, 1870–1874.CrossRefGoogle Scholar
Meier-Kolthoff, J.P., Auch, A.F., Klenk, H.P., and Goker, M. 2013. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics14, 60.CrossRefGoogle Scholar
Minnikin, D.E., O’Donnell, A.G., Goodfellow, M., Alderson, G., Athalye, M., Schaal, A., and Parlett, J.H. 1984. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J. Microbiol. Methods2, 233–241.CrossRefGoogle Scholar
Pruesse, E., Peplies, J., and Glockner, F.O. 2012. SINA: accurate highthroughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics28, 1823–1829.CrossRefGoogle Scholar
Sasser, M. 1990. Identification of bacteria by gas chromatography of cellular fatty acids. MIDI Technical Note 101. MIDI Inc. Newark, DE, USA.Google Scholar
Tatusova, T., DiCuccio, M., Badretdin, A., Chetvernin, V., Nawrocki, E.P., Zaslavsky, L., Lomsadze, A., Pruitt, K.D., Borodovsky, M., and Ostell, J. 2016. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res.44, 6614–6624.CrossRefGoogle Scholar
Yoon, S.H., Ha, S.M., Kwon, S., Lim, J., Kim, Y., Seo, H., and Chun, J. 2017a. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int. J. Syst. Evol. Microbiol.67, 1613–1617.CrossRefGoogle Scholar
Yoon, S.H., Ha, S.M., Lim, J., Kwon, S., and Chun, J. 2017b. A largescale evaluation of algorithms to calculate average nucleotide identity. Antonie van Leeuwenhoek110, 1281–1286.CrossRefGoogle Scholar