Applying pollen DNA metabarcoding to the study of plant–pollinator interactions

Abstract

Premise of the study:To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer-scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks.Methods:We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases.Results:We successfully built a proof-of-concept quantitative pollination network using pollen metabarcoding.Discussion:Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant–pollinator interactions.

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

“…First and perhaps foremost, pollen metabarcoding data currently cannot be treated as if they are quantitative, given the lack of consistent relationship between sequence counts and pollen grain proportions. This does not mean that quantitative results can never be generated by metabarcoding; for example, samples which are assessed for the presence/absence of plant species can be aggregated to generate proportions of samples with particular plant species present, which can be useful for pollination network studies among other study types (Bell, Fowler, et al., ). Second, it is standard procedure to use negative controls for PCR‐based methods.…”

“…Small-scale studies have demonstrated proof of concept, and the field has advanced significantly over the past few years. Pollen DNA (meta)barcoding has been applied to airborne allergen monitoring (Kraaijeveld et al, 2015), plant-pollinator interactions (Bell, Fowler et al, 2017;Galimberti et al, 2014;Keller et al, 2015;Richardson, Lin, Quijia, et al, 2015a;Richardson, Lin, Sponsler, et al, 2015Sickel et al, 2015 and quality control of honey (Hawkins et al, 2015;Valentini, Miquel, & Taberlet, 2010;de Vere et al, 2017). Its potential has also been recognized for examining changes in plant communities over time (Suyama et al 1996;Parducci, Suyama, Lascoux, & Bennett, 2005, Parducci et al, 2017, and in forensics .…”

“…Visual identification is also slow if there are a large number of samples to be examined. These disadvantages may be overcome through the use of DNA barcoding and metabarcoding methods, which could unlock the potential of pollen as a biomarker for a wide range of applications (Bell, Burgess, Okamoto, Aranda, & Brosi, 2016;Bell, de Vere, et al, 2016;Bell, Fowler, et al, 2017).…”

Environmental DNA metabarcoding of wild flowers reveals diverse communities of terrestrial arthropods

“…This includes extracting DNA from sources such as bulk samples or insect soups (Arribas, Andújar, Hopkins, Shepherd, & Vogler, 2016;Elbrecht et al, 2016;Hajibabaei, Shokralla, Zhou, Singer, & Baird, 2011;Yu et al, 2012), empty leaf mines (Derocles, Evans, Nichols, Evans, & Lunt, 2015), spider webs (Blake, McKeown, Bushell, & Shaw, 2016;Xu, Yen, Bowman, & Turner, 2015), pitcher plant fluid (Bittleston, Baker, Strominger, Pringle, & Pierce, 2015), environmental samples like soil and water (environmental DNA [eDNA]) (Taberlet, Coissac, Hajibabaei, & Rieseberg, 2012;Thomsen et al, 2012;Thomsen & Willerslev, 2015;Zinger et al, 2018), host plant and predatory diet identification from insect DNA extracts (Jurado-Rivera, Vogler, Reid, Petitpierre, & Gómez-Zurita, 2009;Paula et al, 2016), and predator scat from bats (Bohmann et al, 2011;Vesterinen, Lilley, Laine, & Wahlberg, 2013). Recently, also DNA from pollen attached to insects has been used for retrieving information on plant-pollinator interactions (Bell et al, 2017;Pornon et al, 2016). Many of such recent studies rely on DNA metabarcoding-high-throughput sequencing of PCR amplicons using generic primers (Taberlet, Bonin, Zinger, & Coissac, 2018;Taberlet et al, 2012).…”

Genome‐skimming provides accurate quantification for pollen mixtures

“…Furthermore, rare species are prone to being overlooked in subsampling and microscopic examination. Alternatively, molecular identifications such as metabarcoding have seen increasing applications in bulk pollen characterizations (Bell et al, 2016(Bell et al, , 2017Cornman, Otto, Iwanowicz, & Pettis, 2015;Danner, Molitor, Schiele, Härtel, & Steffan-Dewenter, 2016;Galimberti et al, 2014;Kamo et al, 2018;Keller et al, 2015;Pornon et al, 2016;Richardson et al, 2015). Metabarcoding employs high-throughput sequencing (HTS) in analysing pooled amplicons obtained from mixed taxa (Cristescu, 2014;Ji et al, 2013).…”