RT Journal Article
SR Electronic
T1 Combining metabarcoding and morphological approaches to identify phytoplankton taxa associated with harmful algal blooms
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 816926
DO 10.1101/816926
A1 Svetlana Esenkulova
A1 Amy Tabata
A1 Ben J.G. Sutherland
A1 Nicola Haigh
A1 Christopher M. Pearce
A1 Kristina M. Miller
YR 2019
UL http://biorxiv.org/content/early/2019/10/24/816926.abstract
AB Impacts of harmful algal blooms (HABs) have increased in frequency, intensity, and geographical distribution in the last several decades. Detection methods to date largely depend on microscopic observations which require expertise and time-intensive processes. In this study, we apply microscopic observational methods, quantitative real-time polymerase chain reaction (qPCR), and metabarcoding with multiple markers (i.e. 16S, 18S-dinoflagellate and 18S-diatom, and large subunit (LSU) rDNA) on cultured (N=30) and field (N=24) samples containing suspected harmful algae (e.g., Alexandrium spp., Chattonella sp., Chrysochromulina spp., Dictyocha spp., Heterosigma akashiwo, Protoceratium reticulatum, Pseudochattonella verruculosa, Pseudo-nitzschia spp., and Pseudopedinella sp). Good detectability was found using previously published TaqMan assays for A. tamarense, H. akashiwo, and P. verruculosa. Overall, the multiple marker metabarcoding results were superior to the morphology-based method for detection and identification of harmful taxa, with the notable exception of taxa from the silicoflagellate group (e.g. Dictyocha spp.), which had better detection by morphology. Metabarcoding results depended greatly on the marker type applied, which highlights the value of a multiple-marker approach. The combined results of the 18S and the LSU markers closely corresponded with morphological identification of targeted species and provided the best overall taxonomic coverage and resolution. The most numerous unique taxa were identified using 18S-dinoflagellate amplicon (N=167) and the best resolution to species level occurred using LSU (N=60). This work is the first report of HAB species identification in Canada using a combination of morphological, metabarcoding, and qPCR approaches. These results emphasize the benefit of applying molecular techniques to detect HAB taxa and highlight the current necessity of using multiple markers for accurate detection of the diverse groups that cause HABs.