基于eDNA技术的白洋淀微型生物群落监测

传统形态学监测无法识别绝大多数微型生物,环境DNA(eDNA)宏条形码技术提供了一种新型高效的生物监测手段。以白洋淀为例,采用eDNA宏条形码测序技术,开展白洋淀微型生物群落监测,揭示了白洋淀微型生物群落组成、序列数、多样性等的时空分布,比较了eDNA技术和传统形态学方法对藻类的检出能力,分析了eDNA技术的灵敏度和还原力。结果表明:eDNA宏条形码技术检出白洋淀7个微型生物类群的4 569个OTU,分属于567个种,其中细菌(除蓝藻门)最多,原生动物次之,古细菌最少;时间上,白洋淀主要微型生物类群秋季生物多样性最高,夏季次之,微型生物类群的序列数、门与属水平的相对丰度也呈现出明显的季节特征。空间上,优势门类在各采样点的分布大致相似,Epsilonbacteraeota等部分相对丰度较少的门类分布明显不均衡;时间和空间变化均影响白洋淀微型生物群落的组成和分布,季节变化的影响更显著;eDNA比传统形态学方法具有更高的检出能力,二者联合使用更有利于全面获取微型生物组成信息。研究全面揭示了白洋淀微型生物群落信息,探索了eDNA宏条形码技术在北方湿地的应用,印证了该技术的高效性和灵敏度。

Microbial community monitoring in Baiyangdian Lake based on eDNA technology

A vast majority of microbes are unable to be monitored based on traditional morphological methods,which restricts its application; in contrast, environmental DNA(eDNA) metabarcoding provides a new and efficient biomonitoring method. In this study, the microbial communities in Baiyangdian Lake were examined by eDNA matabarcoding, and the spatiotemporal distribution of community composition, reads, and biodiversity of microbes in Baiyangdian Lake were identified. At the same time, algae detection ability was evaluated by comparing the eDNA and traditional morphological methods, and the sensitivity and flexibility of eDNA were analyzed. The results showed that:In Baiyangdian Lake, a total of 4 569 operational taxonomic units of seven microbial communities were detected based on eDNA matabarcoding and belonged to 567 species, of which bacteria(except Cyanobacteria) were the most abundant, followed by protozoa and the archaea were the least, respectively. In terms of time, the biodiversity of the main microbial communities in Baiyangdian Lake was the highest in autumn followed by that in summer, and the reads and relative abundance at the phylum or genus level of the microbial groups also showed obvious seasonal characteristics. Spatially, the distribution of dominant phyla at each sampling point was roughly similar,while the distribution of those relatively less abundant,such as Epsilonbacteraeota,was clearly unbalanced. The composition and distribution of microbial communities in Baiyangdian Lake were affected by temporal and spatial variations, and the effect of temporal variation was more significant. eDNA metabarcoding has a higher detection ability than traditional morphological methods, and the combination of these two methods is more conducive for acquiring comprehensive information to identify microbial components. The study reveals the composition of microbial communities in Baiyangdian Lake, explores the application of eDNA metabarcoding in northern wetlands, and demonstrates the high efficiency and sensitivity of eDNA technology.