Abstract：
Environmental DNA metabarcoding is gaining momentum as a time and cost-effective tool for biomonitoring and environmental impact assessment. Yet, its use as a replacement for the conventional marine benthic monitoring based on morphological analysis of macrofauna is still challenging. Here we propose to study the meiofauna, which is much better represented in sediment DNA samples. We focus on nematodes, which are the most numerous and diverse group of meiofauna. Our aim is to assess the potential of nematode metabarcoding to monitor impacts associated with offshore oil platform activities. To achieve this goal, we used nematode-optimized marker (18S V1V2-Nema) and universal eukaryotic marker (18S V9) region to analyse 252 sediment DNA samples collected near three offshore oil platforms in the North Sea. For both markers, we analysed changes in alpha and beta diversity in relation to distance from the platforms and environmental variables. We also defined three impact classes based on selected environmental variables that are associated with oil extraction activities and used random forest classifiers to compare the predictive performance of both datasets. Our results show that alpha- and beta-diversity of nematodes varies with the increasing distance from the platforms. The variables directly related to platform activity, such as Ba and THC, strongly influence the nematode community. The nematode metabarcoding data provide more robust predictive models than eukaryotic data. Furthermore, the nematode community appears more stable in time and space, as illustrated by the overlap of nematode datasets obtained from the same platform three years apart. A significative negative correlation between distance and Shannon diversity also advocates for higher performance of the V1V2-Nema over the V9. Overall, these results suggest that the sensitivity of nematodes is higher compared to the eukaryotic community. Hence, nematode metabarcoding has the potential to become an effective tool for benthic monitoring in marine environment.
摘要：
环境DNA元编码作为生物监测和环境影响评估的时间和成本效益高的工具正在获得动力。然而，它作为基于大型动物形态分析的传统海洋底栖监测的替代品仍然具有挑战性。在这里，我们建议研究小型动物，这在沉积物DNA样本中表现得更好。我们专注于线虫，是最多、最多样化的动物群。我们的目标是评估线虫代谢编码的潜力，以监测与海上石油平台活动相关的影响。为了实现这一目标,我们使用线虫优化标记（18SV1V2-Nema）和通用真核标记（18SV9）区域来分析在北海三个海上石油平台附近收集的252个沉积物DNA样品。对于这两个标记，我们分析了α和β多样性的变化与平台距离和环境变量的关系。我们还根据与石油开采活动相关的选定环境变量定义了三个影响类别，并使用随机森林分类器来比较两个数据集的预测性能。我们的结果表明，线虫的α和β多样性随距平台的距离增加而变化。与平台活动直接相关的变量，例如Ba和THC，强烈影响线虫群落。线虫元编码数据提供比真核数据更可靠的预测模型。此外，线虫群落在时间和空间上显得更加稳定，从同一平台获得的线虫数据集的重叠间隔三年。距离和香农多样性之间的显着负相关也主张V1V2-Nema比V9具有更高的性能。总的来说,这些结果表明，与真核生物群落相比，线虫的敏感性更高。因此，线虫代谢编码有可能成为海洋环境底栖监测的有效工具。
