Increasing marine trophic web knowledge through DNA analyses of fish stomach content: a step towards an Ecosystem Based Approach to fisheries research

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-scaled 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 analysed 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.

多物种与生态系统模型是落地基于生态系统的渔业管理方法的核心依托，此类模型亟需涵盖海洋生物间营养相互作用（含随时间演变的动态变化）的海量详实数据。DNA宏条形码技术(DNA metabarcoding)能够同时对数百份样本中的群落开展分类学鉴定，有望大幅提速大规模胃容物数据的采集工作。但要实现DNA宏条形码技术的常规化应用，仍需攻克多项技术瓶颈：诸如采样流程可能较为繁琐、易检测到高比例的捕食者自身DNA，且无法提供可靠的丰度估算结果。本研究开发了一款DNA宏条形码检测方法，用于解析5种具有重要商业价值的鱼类的食性，该方法可便捷地整合至常规采样流程中。该方法无需解剖胃部并提取胃容物，即可加快分析进程；同时通过使用封闭引物(Blocking Primers)避免扩增捕食者自身的DNA序列。经模拟样本与真实胃组织样本的测试验证，该方法已被证实效果显著，能够有效区分由捕食者生态特征或猎物可获得性差异引发的食性变化。此外，本研究将该实验方案应用于此前已通过目视法分析过的鲭鱼胃部样本，证实DNA宏条形码技术可弥补目视分析的局限，检测出目视法遗漏的猎物类群。最后，本文探讨了基于DNA宏条形码技术的数据如何助力营养相互作用相关数据的采集工作。本研究进一步彰显了DNA宏条形码技术在鱼类营养相互作用研究与监测中的应用潜力，为其纳入常规监测计划提供了实践基础，这对于推行基于生态系统的渔业管理方法至关重要。