Polyploidy and community structure
Polyploidy and community structure
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DOI：
10.1038/nmicrobiol.2016.261
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发表时间：
2017-01
影响因子：
28.3
通讯作者：
J. Soppa
中科院分区：
文献类型：
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作者：
J. Soppa
群落结构分析在微生物学的各个领域都发挥着重要作用，例如微生物生态学、微生物组表征和种群动态分析以及生物反应器的优化。近年来，专注于使用标记基因分析微生物种群群落结构的论文数量急剧增加。群落结构的分析通常应用标记基因频率的量化。到目前为止，最广泛使用的基因是 16S rRNA 基因，但也使用替代基因，例如 amoA 基因（用于氨氧化剂）或 nifH 基因（用于固氮生物）。尽管传统上使用标记基因的 PCR 扩增和 PCR 产物的测序，但近年来，下一代测序方法已成为最先进的技术。标记基因频率分析的基本假设是每个读数都源自一个细胞，因此标记基因频率反映了所研究群体中不同分类单元的分数。已经讨论了损害这一基本假设的几个因素；例如，DNA 分离偏差、扩增偏差、测序偏差和统计偏差，以及使用复杂的统计程序或分析已知组成的对照模拟群落等解决方案已被提出1-3。已确定的另一个问题是不同原核生物中 rRNA 操纵子的数量不同，可以低至 1 个拷贝，也可以高达 15 个拷贝4。作为一种解决方案，使用系统发育信息预测可能的 rRNA 拷贝数的生物信息学方法已经被开发出来。然而，另一个因素影响了使用标记基因频率来分析成分
Community structure analyses are instrumental in various fields of microbiology, such as microbial ecology, and for the characterization of microbiomes and the analysis of population dynamics, as well as for the optimization of bioreactors. The number of papers concentrating on the analysis of community structures of microbial populations using marker genes has increased dramatically in recent years. Analyses of community structures typically apply the quantification of marker gene frequencies. By far, the most widely used gene is the 16S rRNA gene, but alternative genes, such as the amoA gene (for ammonia oxidizers) or the nifH gene (for nitrogen-fixing organisms), are also used. Although traditionally, PCR amplification of marker genes and sequencing of the PCR products have been used, in recent years, next-generation sequencing approaches have become state of the art.The basic assumption underlying the analyses of marker gene frequencies is that each read originates from one cell, and thus that marker gene frequencies mirror the fractions of different taxa in the population under investigation. Several factors have been discussed that compromise this basic assumption; for example, DNA isolation bias, amplification bias, sequencing bias and statistical bias, and solutions such as using sophisticated statistical programs or the analysis of control mock communities of known composition have been proposed1–3. Another problem that has been identified is the varying number of rRNA operons in different prokaryotes, which can be as low as 1 copy or as high as 15 copies4. As a solution, bioinformatic methods that predict the probable rRNA copy number using phylogenetic information have been developed. However, another factor compromising the use of marker gene frequencies to analyse the composition