收集人、大猪、小猪、大鼠、小鼠以及鸡五个不同个体的粪便样品,每个个体取两个平行样,提取总DNA;PCR扩增,获得16S rRNA V6标签片段;Illumina测序;经BIPES以及QIIME分析并比较菌群结构及多样性.研究结果发现,不同物种之间肠道菌群差异较大.五类物种肠道菌群均以厚壁菌门、拟杆菌门、以及变形菌门为主,但鸡的厚壁菌门显著减少,而变形菌门显著增加.从α多样性角度来看,猪肠道菌群种属丰富度及Shannon指数均显著高于人及鸡肠道菌群.从β多样性角度,尽管不同人之间的肠道菌群相似度较低,但不同物种之间相比较,小猪与大鼠肠道菌群与人相似性高于小鼠和鸡肠道菌群.与人类相比,小猪的肠道微生物组最相近,而鸡的肠道菌群相似度最低.

Low cost and high throughput capacity are major advantages of using next generation sequencing (NGS) techniques to determine metagenomic 16S rRNA tag sequences. These methods have significantly changed our view of microorganisms in the fields of human health and environmental science. However, DNA extraction using commercial kits has shortcomings of high cost and time constraint. In the present study, we evaluated the determination of fecal microbiomes using a direct boiling method compared with 5 different commercial extraction methods, e.g., Qiagen and MO BIO kits. Principal coordinate analysis (PCoA) using UniFrac distances and clustering showed that direct boiling of a wide range of feces concentrations gave a similar pattern of bacterial communities as those obtained from most of the commercial kits, with the exception of the MO BIO method. Fecal concentration by boiling method affected the estimation of α-diversity indices, otherwise results were generally comparable between boiling and commercial methods. The operational taxonomic units (OTUs) determined through direct boiling showed highly consistent frequencies with those determined through most of the commercial methods. Even those for the MO BIO kit were also obtained by the direct boiling method with high confidence. The present study suggested that direct boiling could be used to determine the fecal microbiome and using this method would significantly reduce the cost and improve the efficiency of the sample preparation for studying gut microbiome diversity.

The microbial community plays an essential role in the high productivity in mangrove wetlands. A proper understanding of the spatial variations of microbial communities will provide clues about the underline mechanisms that structure microbial groups and the isolation of bacterial strains of interest. In the present study, the diversity and composition of the bacterial community in sediments collected from four locations, namely mudflat, edge, bulk, and rhizosphere, within the Mai Po Ramsar Wetland in Hong Kong, SAR, China were compared using the barcoded Illumina paired-end sequencing technique. Rarefaction results showed that the bulk sediment inside the mature mangrove forest had the highest bacterial α-diversity, while the mudflat sediment without vegetation had the lowest. The comparison of β-diversity using principal component analysis and principal coordinate analysis with UniFrac metrics both showed that the spatial effects on bacterial communities were significant. All sediment samples could be clustered into two major groups, inner (bulk and rhizosphere sediments collected inside the mangrove forest) and outer mangrove sediments (the sediments collected at the mudflat and the edge of the mangrove forest). With the linear discriminate analysis scores larger than 3, four phyla, namely Actinobacteria, Acidobacteria, Nitrospirae, and Verrucomicrobia, were enriched in the nutrient-rich inner mangrove sediments, while abundances of Proteobacteria and Deferribacterias were higher in outer mangrove sediments. The rhizosphere effect of mangrove plants was also significant, which had a lower α-diversity, a higher amount of Nitrospirae, and a lower abundance of Proteobacteria than the bulk sediment nearby.

ABSTRACT Sediment, a special realm in aquatic environments, has high microbial diversity. While there are numerous reports about the microbial community in marine sediment, freshwater and intertidal sediment communities have been overlooked. The present study determined millions of Illumina reads for a comparison of bacterial communities in freshwater, intertidal wetland, and marine sediments along Pearl River, China, using a technically consistent approach. Our results show that both taxon richness and evenness were the highest in freshwater sediment, medium in intertidal sediment, and lowest in marine sediment. The high number of sequences allowed the determination of a wide variety of bacterial lineages in all sediments for reliable statistical analyses. Principal component analysis showed that the three types of communities could be well separated from phylum to operational taxonomy unit (OTU) levels, and the OTUs from abundant to rare showed satisfactory resolutions. Statistical analysis (LEfSe) demonstrated that the freshwater sediment was enriched with Acidobacteria , Nitrospira , Verrucomicrobia , Alphaproteobacteria , and Betaproteobacteria . The intertidal sediment had a unique community with diverse primary producers (such as Chloroflexi , Bacillariophyta , Gammaproteobacteria , and Epsilonproteobacteria ) as well as saprophytic microbes (such as Actinomycetales , Bacteroidetes , and Firmicutes ). The marine sediment had a higher abundance of Gammaproteobacteria and Deltaproteobacteria , which were mainly involved in sulfate reduction in anaerobic conditions. These results are helpful for a systematic understanding of bacterial communities in natural sediment environments.

Clustering 16S/18S rRNA amplicon sequences into operational taxonomic units (OTUs) is a critical step for the bioinformatic analysis of microbial diversity. Here, we report a pipeline for selecting OTUs with a relatively low computational demand and a high degree of accuracy. This pipeline is referred to as two-stage clustering (TSC) because it divides tags into two groups according to their abundance and clusters them sequentially. The more abundant group is clustered using a hierarchical algorithm similar to that in ESPRIT, which has a high degree of accuracy but is computationally costly for large datasets. The rarer group, which includes the majority of tags, is then heuristically clustered to improve efficiency. To further improve the computational efficiency and accuracy, two preclustering steps are implemented. To maintain clustering accuracy, all tags are grouped into an OTU depending on their pairwise Needleman-Wunsch distance. This method not only improved the computational efficiency but also mitigated the spurious OTU estimation from ‘noise’ sequences. In addition, OTUs clustered using TSC showed comparable or improved performance in beta-diversity comparisons compared to existing OTU selection methods. This study suggests that the distribution of sequencing datasets is a useful property for improving the computational efficiency and increasing the clustering accuracy of the high-throughput sequencing of PCR amplicons. The software and user guide are freely available at http://hwzhoulab.smu.edu.cn/paperdata/.