Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches

Nicola Tommasi,Andrea Ferrari,Paolo Biella,Andrea Galimberti,Massimo Labra

doi:10.3390/d13090437

Abstract

Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.

Highlights

The study of Plant—Pollinator interactions is pivotal to address both theoretical and applicative issues, with important implications in evolutionary studies, conservation biology, and agrifood security, and it is relevant for providing reliable policies of land-use management and mitigation of anthropogenic stressors [1,2,3,4].Traditionally, studies of Plant—Pollinator interactions have been carried out with direct field observations of animal foraging activity during flower visitation [5,6]
We investigated and summarized the criteria and the strategies adopted for filtering out the false positives and rare features or taxa, focusing on published studies on pollen DNA metabarcoding
The issue of removing false positives and rare taxa or features is quite neglected in the scientific literature in relation to the bioinformatic pipeline, the choices made when analysing a High-Throughput Sequencing (HTS) output could generate relevant effects on the community composition, species richness, and species interactions

Summary

Introduction

Studies of Plant—Pollinator interactions have been carried out with direct field observations of animal foraging activity during flower visitation [5,6]. To unveil Plant—Pollinator interactions, it is a valuable approach to classify the pollen grains carried on the pollinator’s body [7,8]. This pollen might be accidentally picked and carried by flower visitors when they touch plant reproductive structures. It can be actively collected and accumulated in specialized structures such as the scopa or the corbiculae in the case of some bee species. The identification of the transported pollen allows discovering of the foraging “history” of flower visitors prior to a sampling event

Methods

Discussion

Conclusion