AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Sukarrieta, Spain.
IKERBASQUE - Basque Foundation for Science, Bilbao, Spain.
J Fish Biol. 2024 Aug;105(2):431-443. doi: 10.1111/jfb.15754. Epub 2024 May 10.
Multispecies and ecosystem models, which are key for the implementation of ecosystem-based approaches to fisheries management, require extensive data on the trophic interactions between marine organisms, including changes over time. DNA metabarcoding, by allowing the simultaneous taxonomic identification of the community present in hundreds of samples, could be used for speeding up large-scale stomach content data collection. Yet, for DNA metabarcoding to be routinely implemented, technical challenges should be addressed, such as the potentially complicated sampling logistics, the detection of a high proportion of predator DNA, and the inability to provide reliable abundance estimations. Here, we present a DNA metabarcoding assay developed to examine the diet of five commercially important fish, which can be feasibly incorporated into routinary samplings. The method is devised to speed up the analysis process by avoiding the stomach dissection and content extraction steps, while preventing the amplification of predator DNA by using blocking primers. Tested in mock samples and in real stomach samples, the method has proven effective and shows great effectiveness discerning diet variations due to predator ecology or prey availability. Additionally, by applying our protocol to mackerel stomachs previously analyzed by visual inspection, we showcase how DNA metabarcoding could complement visually based data by detecting overlooked prey by the visual approach. We finally discuss how DNA metabarcoding-based data can contribute to trophic data collection. Our work reinforces the potential of DNA metabarcoding for the study and monitoring of fish trophic interactions and provides a basis for its incorporation into routine monitoring programs, which will be critical for the implementation of ecosystem-based approaches to fisheries management.
多物种和生态系统模型是实施基于生态系统的渔业管理方法的关键,这些模型需要大量关于海洋生物之间营养相互作用的信息,包括随时间的变化。DNA 代谢组学可以同时对数百个样本中的群落进行分类鉴定,从而加速大规模的胃内容物数据收集。然而,为了使 DNA 代谢组学常规化,需要解决技术挑战,例如潜在的复杂采样物流、高比例捕食者 DNA 的检测以及无法提供可靠丰度估计的问题。在这里,我们提出了一种开发的 DNA 代谢组学分析方法,用于研究五种商业上重要的鱼类的饮食,该方法可以方便地纳入常规采样。该方法旨在通过避免胃解剖和内容物提取步骤来加速分析过程,同时通过使用阻断引物来防止捕食者 DNA 的扩增。在模拟样本和真实胃样本中的测试表明,该方法有效且能有效辨别由于捕食者生态或猎物供应而导致的饮食变化。此外,通过将我们的方案应用于先前通过目视检查分析的鲭鱼胃样本,我们展示了 DNA 代谢组学如何通过检测目视方法忽略的猎物来补充基于目视的数据。我们最后讨论了基于 DNA 代谢组学的数据如何有助于营养数据收集。我们的工作增强了 DNA 代谢组学在研究和监测鱼类营养相互作用方面的潜力,并为其纳入常规监测计划提供了基础,这对于实施基于生态系统的渔业管理方法至关重要。