Determining Plant – Leaf Miner – Parasitoid Interactions: A DNA Barcoding Approach

A major challenge in network ecology is to describe the full-range of species interactions in a community to create highly-resolved food-webs. We developed a molecular approach based on DNA full barcoding and mini-barcoding to describe difficult to observe plant – leaf miner – parasitoid interactions, consisting of animals commonly regarded as agricultural pests and their natural enemies. We tested the ability of universal primers to amplify the remaining DNA inside leaf miner mines after the emergence of the insect. We compared the results of a) morphological identification of adult specimens; b) identification based on the shape of the mines; c) the COI Mini-barcode (130 bp) and d) the COI full barcode (658 bp) fragments to accurately identify the leaf-miner species. We used the molecular approach to build and analyse a tri-partite ecological network of plant – leaf miner – parasitoid interactions. We were able to detect the DNA of leaf-mining insects within their feeding mines on a range of host plants using mini-barcoding primers: 6% for the leaves collected empty and 33% success after we observed the emergence of the leaf miner. We suggest that the low amplification success of leaf mines collected empty was mainly due to the time since the adult emerged and discuss methodological improvements. Nevertheless our approach provided new species-interaction data for the ecological network. We found that the 130 bp fragment is variable enough to identify all the species included in this study. Both COI fragments reveal that some leaf miner species could be composed of cryptic species. The network built using the molecular approach was more accurate in describing tri-partite interactions compared with traditional approaches based on morphological criteria.网络生态学（network ecology）的核心挑战之一，在于对群落内物种间的全部相互作用进行系统性描述，以构建高解析度食物网。本研究开发了一种基于DNA全条形码（full barcoding）与微型条形码（mini-barcoding）的分子方法，用于解析难以直接观测的植物-潜叶昆虫（leaf miner）-拟寄生者（parasitoid）相互作用体系，该体系包含通常被视为农业害虫的物种及其天敌。我们测试了通用引物在昆虫羽化后，对潜叶昆虫取食斑内残留DNA的扩增能力。我们以精准鉴定潜叶昆虫物种为目标，对比了四类鉴定方法的结果：a) 成虫标本的形态学鉴定；b) 基于潜叶斑形态的鉴定；c) 细胞色素C氧化酶亚基I（cytochrome c oxidase subunit I, COI）微型条形码（130 bp）片段鉴定；以及d) COI全条形码（658 bp）片段鉴定。我们利用该分子方法构建并分析了植物-潜叶昆虫-拟寄生者相互作用的三重生态网络。借助微型条形码引物，我们可在多种寄主植物的潜叶斑中检测到潜叶昆虫的DNA：对于采集时已无成虫的叶片，检测成功率为6%；而在观测到昆虫羽化后采集的样本中，检测成功率达33%。我们推测，空潜叶斑样本的低扩增成功率主要源于成虫羽化后的时间间隔，并对实验方法的优化方向展开了讨论。尽管如此，本研究的分子方法仍为生态网络研究提供了全新的物种相互作用数据。我们发现，130 bp的COI微型条形码片段具有足够的序列变异性，可准确鉴定本研究涉及的所有物种。两类COI条形码片段均显示，部分潜叶昆虫物种实际由隐存种（cryptic species）构成。相较于基于形态学标准的传统研究方法，利用本分子方法构建的生态网络，在描述三重相互作用时具备更高的准确性。