Monitoring bloom-forming Aphanizomenon using environmental DNA metabarcoding: Method development, validation, and field application

湖泊生态系统 河流生态系统 失语症 环境DNA 生物 生态系统 生态学 遗传学 生物多样性 鱼腥藻 蓝藻 细菌
作者
Dexiang Sun,Shiguo Li,Wei Xiong,Xun Du,Kun Qiao,Aibin Zhan
出处
期刊:Journal of Environmental Sciences-china [Elsevier BV]
卷期号:150: 477-489
标识
DOI:10.1016/j.jes.2024.02.007
摘要

Harmful algal blooms (HABs) have emerged as a critical global environmental and ecological concern. Timely and accurate monitoring of the prevalent bloom-forming genera is crucial for HAB management. Conventional microscope-based methods are time-consuming, labor-intensive, and specialized expertise-dependent, often making them impractical for large-scale surveillance. Molecular methods, such as metabarcoding, provide efficient technical solutions; however, the lack of competent PCR primers and further field validation present obstacles to their wide use. Here, we successfully developed Aphanizomenon-specific primers and validated the application of environmental DNA (eDNA) metabarcoding for field-based monitoring of Aphanizomenon in 37 sites across lentic and lotic freshwater ecosystems in Beijing. The sensitivity and specificity tests of newly developed primers demonstrated high performance - comprehensive recovery of biodiversity in Aphanizomenon communities and high ratios (>95%) of Aphanizomenon sequences in datasets. We observed significant correlations between the sequence abundance derived from eDNA metabarcoding and the total cell density determined through microscopic identification across all the sampling sites, both in the spring (r = 0.8086, p < 0.0001) and summer (r = 0.7902, p < 0.0001), thus validating the utility of eDNA metabarcoding based on the newly developed primers for monitoring in the field. Further, we identified key environmental variables that were primary drivers responsible for the spatiotemporal distribution of Aphanizomenon abundance. These variables included temperature, total nitrogen, and dissolved oxygen in lentic ecosystems, and total phosphorus in lotic ecosystems. The method developed and validated here offers an accurate, efficient, and high-throughput tool for the monitoring of Aphanizomenon blooms in freshwater ecosystems.
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