Song Liyan, Yang Shu, Liu Hongjie, Xu Jing
Environmental Microbiology and Ecology Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Avenue, Shuitu High-Tech Park, Beibei, Chongqing, 400714, China.
Department of Geology and Geophysics, University of Utah, Salt Lake City, UT, 84112, USA.
Appl Microbiol Biotechnol. 2017 Jan;101(2):761-769. doi: 10.1007/s00253-016-7917-6. Epub 2016 Oct 21.
Little is known regarding how bacterial communities assemble at landfill, as well as how the environment shapes the composition of bacterial community. In this study, up to 42 refuse samples from a large-scale landfill in China were physicochemically and phylogenetically investigated. 16S ribosomal RNA (rRNA) gene-based Illumina MiSeq sequencing (nine samples) revealed that representatives of Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Firmicutes, and Bacteroidetes were dominant in the refuse samples, which was similar to a previous study on landfill leachate by using 454 pyrosequencing. Although 741 operational taxonomic units (OTUs) were detected across all nine samples, 6 of these OTUs were detected in all of the data sets, suggesting difference between bacterial community structures. Geographical differences between the samples, irrespective of depths, were revealed by a principal component analysis (PCA) based on the terminal restriction fragment length polymorphism (TRFLP) profiles of 42 refuse samples. Redundancy analysis (RDA) suggested that environmental heterogeneity (pH, landfilling ages, and depths) and the abundance of bacteria (represented by 16S rRNA gene copy numbers) were the main drivers shaping the bacterial community structure.
关于细菌群落如何在垃圾填埋场中组装，以及环境如何塑造细菌群落的组成，我们知之甚少。在本研究中，对来自中国一个大型垃圾填埋场的多达42个垃圾样品进行了物理化学和系统发育研究。基于16S核糖体RNA（rRNA）基因的Illumina MiSeq测序（九个样品）显示，α-变形菌纲、β-变形菌纲、γ-变形菌纲、厚壁菌门和拟杆菌门的代表在垃圾样品中占主导地位，这与之前一项使用454焦磷酸测序对垃圾渗滤液的研究结果相似。尽管在所有九个样品中检测到了741个操作分类单元（OTU），但其中6个OTU在所有数据集中均被检测到，这表明细菌群落结构存在差异。基于42个垃圾样品的末端限制性片段长度多态性（TRFLP）图谱的主成分分析（PCA）揭示了样品之间的地理差异，而与深度无关。冗余分析（RDA）表明，环境异质性（pH值、填埋年限和深度）和细菌丰度（以16S rRNA基因拷贝数表示）是塑造细菌群落结构的主要驱动因素。
