Molecular characterization of the planktonic microorganisms in water of two mountain brackish lakes.

来自 PUBMED

作者:

Zeng JDeng LJLou KZhang TYang HMShi YWLin Q

展开

摘要:

The prokaryotic diversity in two brackish lakes (Sayram Lake and Chaiwopu Lake) was investigated by constructing bacterial and archaeal clone libraries of 16S rRNA genes. Bacterial clones from Sayram Lake were classified into six phyla (Proteobacteria, Verrucomicrobia, Bacteroidetes, Planctomycetes, Acidobacteria, Actinobacteria). Of these, Proteobacteria and Verrucomicrobia were the most dominant, representing 50.4 and 16.8% of the clone library, respectively. Sequences related to Proteobacteria (58.1%), Cyanobacteria (17.2%), Bacteroidetes (15%), Verrucomicrobia (4.3%), Actinobacteria (3.2%) constituted over 97% of the bacterial clone library from Chaiwopu Lake. In addition, 58.8% (Sayram Lake) and 48% (Chaiwopu Lake) of bacterial clones showed high sequence identity to pure cultures. The composition of Archaea was obviously different between the two lakes. Only the Crenarchaeota phylum was found in the Sayram Lake, whereas Archaeal sequences from Chaiwopu Lake were classified into three phyla: Crenarchaeota (5.8%), Thaumarchaeota (81.2%), and Euryarchaeota (13%). Among the archaeal sequences, 94.2% were highly related to cultivable species of the genus Nitrosopumilus, Methanoculleus, and Methanobacterium. These results showed a high diversity of potential cultivable heterotrophic bacteria in Sayram Lake and Chaiwopu Lake. Chaiwopu Lake was a source of potentially novel, cultivable archaea.

收起

展开

DOI:

10.1002/jobm.201300187

被引量:

5

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(792)

参考文献(0)

引证文献(5)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读