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通过对聚合酶链式反应(PCR)扩增的16S核糖体RNA(rRNA)基因进行双梯度变性梯度凝胶电泳,分析海草床沉积物中的细菌群落。

Analysis of bacterial communities in seagrass bed sediments by double-gradient denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA genes.

作者信息

James J B, Sherman T D, Devereux R

机构信息

Office of Research and Development, US Environmental Protection Agency, NHEERL-Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, FL 32561, USA.

出版信息

Microb Ecol. 2006 Nov;52(4):655-61. doi: 10.1007/s00248-006-9075-3. Epub 2006 Jun 10.

Abstract

Bacterial communities associated with seagrass bed sediments are not well studied. The work presented here investigated several factors and their impact on bacterial community diversity, including the presence or absence of vegetation, depth into sediment, and season. Double-gradient denaturing gradient gel electrophoresis (DG-DGGE) was used to generate banding patterns from the amplification products of 16S rRNA genes in 1-cm sediment depth fractions. Bioinformatics software and other statistical analyses were used to generate similarity scores between sections. Jackknife analyses of these similarity coefficients were used to group banding patterns by depth into sediment, presence or absence of vegetation, and by season. The effects of season and vegetation were strong and consistent, leading to correct grouping of banding patterns. The effects of depth were not consistent enough to correctly group banding patterns using this technique. While it is not argued that bacterial communities in sediment are not influenced by depth in sediment, this study suggests that the differences are too fine and inconsistent to be resolved using 1-cm depth fractions and DG-DGGE. The effects of vegetation and season on bacterial communities in sediment were more consistent than the effects of depth in sediment, suggesting they exert stronger controls on microbial community structure.

摘要

与海草床沉积物相关的细菌群落尚未得到充分研究。本文所开展的工作调查了几个因素及其对细菌群落多样性的影响,包括有无植被、沉积物深度以及季节。采用双梯度变性梯度凝胶电泳(DG-DGGE)从1厘米沉积物深度分层中16S rRNA基因的扩增产物生成条带模式。利用生物信息学软件和其他统计分析来生成各部分之间的相似性得分。对这些相似系数进行刀切法分析,以便按沉积物深度、有无植被以及季节对条带模式进行分组。季节和植被的影响强烈且一致,能使条带模式得到正确分组。深度的影响不够一致,无法用该技术对条带模式进行正确分组。虽然并非认为沉积物中的细菌群落不受沉积物深度的影响,但本研究表明,差异过于细微且不一致,无法用1厘米深度分层和DG-DGGE来分辨。植被和季节对沉积物中细菌群落的影响比沉积物深度的影响更为一致,表明它们对微生物群落结构施加了更强的控制。

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