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微生物群落多样性数学表征方法及其在污水处理系统研究中的应用
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国家水体污染控制与治理科技重大专项(2017ZX07402002)


Mathematic methods for the evaluation of microbial diversity and their applications in the research on wastewater treatment systems
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    摘要:

    微生物群落在调节全球气候、人类健康和工业生物技术应用中扮演着重要角色。定量表征微生物群落多样性是认识微生物群落基本特征、动态变化和功能的前提。本文介绍了常用的α多样性指数,包括物种数目、Shannon-Weaver指数、Simpson多样性指数和Hill多样性指数;并介绍了其他多样性评估方法及其原理,包括能够评价样本对微生物群落各物种覆盖程度的稀释性曲线和Good’s coverage指数,以及能估算群落多样性的Chao1、ACE指数和基于物种丰度分布曲线的模型方法;并以最大规模的生物技术应用——污水处理厂为例,介绍了这些方法在认识微生物群落多样性中的应用。现有研究表明:所检测到的城市污水处理厂中微生物群落的物种数目和Shannon-Weaver指数随检测方法解析通量(样本大小)的增加而增大;但现有方法仍无法反映城市污水处理厂微生物群落的真实多样性。基于特定的物种丰度分布曲线对DNA样本数据进行模拟和重建,结果表明对群落物种数目的评估存在较大的不确定性;Shannon-Weaver指数,特别是Simpson多样性指数等受低丰度物种影响较小,可以准确计算,是评价和比较微生物群落分类学多样性的好手段。改进模型拟合方法和加大取样深度能提高微生物群落物种数目的评估精度。此外,认识微生物群落其他方面的多样性如系统发育多样性和功能多样性,也对认识微生物生态特征具有重要意义。

    Abstract:

    Microbial communities play central roles in global climate regulation, human health and industrial biotechnology. The quantification of microbial diversity is important for the understanding of ecological characteristics of communities, their dynamics and functions. Herein, we introduced the commonly used alpha-diversity indices, including richness, Shannon-Weaver index, Simpson diversity indices and Hill’s diversity number. Also, we summarized diversity evaluation ways which are used in estimating the coverage of molecular methods (e.g., rarefaction curve and good’s coverage) and community richness (e.g., Chao1 and ACE indices and taxa abundance distribution curve). Then we showed the application of mathematic methods in the research on microbial diversity by taking wastewater treatment plant (WWTP) as an example which is the largest application of bioprocess engineering. Current investigations showed that taxa richness and Shannon diversity of activated sludge microbial communities in full-scale WWTPs increased with the increase in sampling sizes of different methods. However, the disparity between sample size and community size is a common problem in microbial investigations. By reconstructing microbial communities using DNA sampling data based on certain taxa abundance distribution curves, diversity of the communities was evaluated. It was shown that microbial richness was characterized with large uncertainty. Shannon diversity, and especially Simpson diversity indices which are weakly dependent on low-abundance taxa could be estimated accurately. They are good tools to evaluate and compare microbial taxonomic diversity. Developing novel modeling approaches and advances in sequencing technology can improve the accuracy of microbial richness evaluation. In addition, clarifying phylogenetic and functional diversity of microbial communities are also of substantial importance for the understanding of microbial ecology.

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夏瑜,何绪文,文湘华. 微生物群落多样性数学表征方法及其在污水处理系统研究中的应用[J]. 微生物学通报, 2018, 45(8): 1778-1786

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  • 在线发布日期: 2018-08-03
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