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Current Microbiology

, Volume 65, Issue 5, pp 568–574 | Cite as

Roseibacterium beibuensis sp. nov., a Novel Member of Roseobacter Clade Isolated from Beibu Gulf in the South China Sea

  • Yujiao Mao
  • Jingjing Wei
  • Qiang Zheng
  • Na Xiao
  • Qipei Li
  • Yingnan Fu
  • Yanan Wang
  • Nianzhi Jiao
Article

Abstract

A novel aerobic, bacteriochlorophyll-containing bacteria strain JLT1202rT was isolated from Beibu Gulf in the South China Sea. Cells were gram-negative, non-motile, and short-ovoid to rod-shaped with two narrower poles. Strain JLT1202rT formed circular, opaque, wine-red colonies, and grew optimally at 3–4 % NaCl, pH 7.5–8.0 and 28–30 °C. The strain was catalase, oxidase, ONPG, gelatin, and Voges–Proskauer test positive. In vivo absorption spectrum of bacteriochlorophyll a presented two peaks at 800 and 877 nm. The predominant cellular fatty acid was C18:1 ω7c and significant amounts of C16:0, C18:0, C10:0 3-OH, C16:0 2-OH, and 11-methyl C18:1 ω7c were present. Strain JLT1202rT contained Q-10 as the major respiratory quinone and the genomic DNA G+C content was 76.3 mol%. Phylogenetic analysis based on 16S rRNA gene sequences of various species with validly published names showed that strain JLT1202rT fell within the genus Roseibacterium, family Rhodobacteraceae, sharing the highest similarity with Roseibacterium elongatum OCh 323T (97.9 % similarity), followed by Dinoroseobacter shibae DFL 12T (95.4 % similarity). The phylogenetic distance of pufM genes between strain JLT1202rT and R. elongatum OCh 323T was 9.4 %, suggesting that strain JLT1202rT was distinct from the only strain of the genus Roseibacterium. Based on the variabilities of phylogenetic and phenotypic characteristics, strain JLT1202rT stands for a novel species of the genus Roseibacterium and the name R. beibuensis sp. nov. is proposed with JLT1202rT as the type strain (=JCM 18015T = CGMCC 1.10994T).

Keywords

PHAs Cellular Fatty Acid Bacteriochlorophyll Bacterial Community Diversity Roseobacter Clade 
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.

Notes

Acknowledgments

The authors would like to thank Professor Xiaojun Yan, Marine Biotechnology Laboratory, Ningbo University for his valuable help. This study was supported by the 973 Program (2011CB808800), the NSFC Project (91028001), the SOA Project (201105021) and the 863 Program (2012AA092003).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Yujiao Mao
    • 1
  • Jingjing Wei
    • 1
  • Qiang Zheng
    • 1
  • Na Xiao
    • 1
  • Qipei Li
    • 1
  • Yingnan Fu
    • 1
  • Yanan Wang
    • 1
    • 2
  • Nianzhi Jiao
    • 1
  1. 1.State Key Laboratory of Marine Environmental ScienceXiamen UniversityXiamenPeople’s Republic China
  2. 2.Key Laboratory of Microbial Engineering at the Institute of BiologyHenan Academy of SciencesZhengzhouPeople’s Republic China

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