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比较显微镜检查和 DNA 代谢组学技术在识别数百个湖泊中的蓝藻群落。

Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes.

机构信息

Department of Biology, McGill University, Montreal, Quebec, Canada; Interuniversity Research Group in Limnology (GRIL), Quebec, Canada.

Interuniversity Research Group in Limnology (GRIL), Quebec, Canada; Department of Biology, Concordia University, Montreal, Quebec, Canada.

出版信息

Harmful Algae. 2022 Mar;113:102187. doi: 10.1016/j.hal.2022.102187. Epub 2022 Feb 3.

Abstract

Accurately identifying the species present in an ecosystem is vital to lake managers and successful bioassessment programs. This is particularly important when monitoring cyanobacteria, as numerous taxa produce toxins and can have major negative impacts on aquatic ecosystems. Increasingly, DNA-based techniques such as metabarcoding are being used for measuring aquatic biodiversity, as they could accelerate processing time, decrease costs and reduce some of the biases associated with traditional light microscopy. Despite the continuing use of traditional microscopy and the growing use of DNA metabarcoding to identify cyanobacteria assemblages, methodological comparisons between the two approaches have rarely been reported from a wide suite of lake types. Here, we compare planktonic cyanobacteria assemblages generated by inverted light microscopy and DNA metabarcoding from a 379-lake dataset spanning a longitudinal and trophic gradient. We found moderate levels of congruence between methods at the broadest taxonomic levels (i.e., Order, RV=0.40, p < 0.0001). This comparison revealed distinct cyanobacteria communities from lakes of different trophic states, with Microcystis, Aphanizomenon and Dolichospermum dominating with both methods in eutrophic and hypereutrophic sites. This finding supports the use of either method when monitoring eutrophication in lake surface waters. The biggest difference between the two methods was the detection of picocyanobacteria, which are typically underestimated by light microscopy. This reveals that the communities generated by each method currently are complementary as opposed to identical and promotes a combined-method strategy when monitoring a range of trophic systems. For example, microscopy can provide measures of cyanobacteria biomass, which are critical data in managing lakes. Going forward, we believe that molecular genetic methods will be increasingly adopted as reference databases are routinely updated with more representative sequences and will improve as cyanobacteria taxonomy is resolved with the increase in available genetic information.

摘要

准确识别生态系统中存在的物种对湖泊管理者和成功的生物评估计划至关重要。在监测蓝藻时,这一点尤为重要,因为许多蓝藻属会产生毒素,并对水生生态系统造成重大负面影响。越来越多的基于 DNA 的技术,如 metabarcoding,正被用于测量水生生物多样性,因为它们可以加速处理时间、降低成本,并减少与传统显微镜相关的一些偏差。尽管传统显微镜仍在继续使用,并且 DNA metabarcoding 越来越多地用于识别蓝藻组合,但从广泛的湖泊类型来看,这两种方法之间的方法比较很少有报道。在这里,我们比较了通过倒置显微镜和 DNA metabarcoding 从跨越纵向和营养梯度的 379 个湖泊数据集生成的浮游蓝藻组合。我们发现,在最广泛的分类学水平(即目,RV=0.40,p<0.0001)上,两种方法之间存在中等程度的一致性。这种比较揭示了不同营养状态湖泊的独特蓝藻群落,微囊藻、鱼腥藻和束丝藻在富营养化和超富营养化地区用这两种方法都占主导地位。这一发现支持在监测湖泊地表水富营养化时使用这两种方法中的任何一种。这两种方法之间最大的区别是对微微型蓝藻的检测,这些蓝藻通常被显微镜低估。这表明,这两种方法所产生的群落目前是互补的,而不是相同的,并在监测一系列营养系统时促进了联合方法策略。例如,显微镜可以提供蓝藻生物量的测量,这是管理湖泊的关键数据。展望未来,我们相信随着参考数据库定期更新更具代表性的序列,以及随着可用遗传信息的增加解决蓝藻分类学问题,分子遗传方法将越来越被采用。

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