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多标志物 DNA metabarcoding 从城市港口检测到一系列环境梯度。

Multi-marker DNA metabarcoding detects suites of environmental gradients from an urban harbour.

机构信息

Centre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Guelph, ON, N1G 2W1, Canada.

Whales Initiative, Ocean Wise Conservation Association, Victoria, BC, V8V 4Z9, Canada.

出版信息

Sci Rep. 2022 Jun 22;12(1):10556. doi: 10.1038/s41598-022-13262-6.

Abstract

There is increasing need for biodiversity monitoring, especially in places where potential anthropogenic disturbance may significantly impact ecosystem health. We employed a combination of traditional morphological and bulk macroinvertebrate metabarcoding analyses to benthic samples collected from Toronto Harbour (Ontario, Canada) to compare taxonomic and functional diversity of macroinvertebrates and their responses to environmental gradients. At the species rank, sites assessed using COI metabarcoding showed more variation than sites assessed using morphological methods. Depending on the assessment method, we detected gradients in magnesium (morphological taxa), ammonia (morphological taxa, COI sequence variants), pH (18S sequence variants) as well as gradients in contaminants such as metals (COI & 18S sequence variants) and organochlorines (COI sequence variants). Observed responses to contaminants such as aromatic hydrocarbons and metals align with known patchy distributions in harbour sediments. We determined that the morphological approach may limit the detection of macroinvertebrate responses to lake environmental conditions due to the effort needed to obtain fine level taxonomic assignments necessary to investigate responses. DNA metabarcoding, however, need not be limited to macroinvertebrates, can be automated, and taxonomic assignments are associated with a certain level of accuracy from sequence variants to named taxonomic groups. The capacity to detect change using a scalable approach such as metabarcoding is critical for addressing challenges associated with biodiversity monitoring and ecological investigations.

摘要

生物多样性监测的需求日益增长,尤其是在那些可能受到人为干扰的地方,这些干扰可能会对生态系统健康产生重大影响。我们采用传统的形态学和大型底栖动物宏条形码分析相结合的方法,对来自加拿大安大略省多伦多港的底栖样本进行了分析,以比较大型底栖动物的分类和功能多样性及其对环境梯度的响应。在物种等级上,使用 COI 宏条形码评估的地点比使用形态学方法评估的地点显示出更多的变化。根据评估方法的不同,我们检测到镁(形态分类群)、氨(形态分类群、COI 序列变体)、pH 值(18S 序列变体)的梯度,以及金属(COI 和 18S 序列变体)和有机氯(COI 序列变体)等污染物的梯度。观察到的对芳香烃和金属等污染物的反应与港口沉积物中已知的块状分布一致。我们确定,由于需要进行精细的分类学分配,形态学方法可能会限制对大型底栖动物对湖泊环境条件的反应的检测,这种分配对于调查反应是必要的。然而,宏条形码技术不一定局限于大型底栖动物,可以实现自动化,并且分类学分配与从序列变体到命名分类群的一定准确性相关。使用可扩展的方法(如宏条形码)检测变化的能力对于解决与生物多样性监测和生态调查相关的挑战至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1ad/9217803/973a523fb054/41598_2022_13262_Fig1_HTML.jpg

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