Assessing the relevance of DNA metabarcoding compared to morphological identification for lake phytoplankton monitoring

Abstract

Phytoplankton is a key biological group used to assess the ecological status of lakes. The classical monitoring approach relies on microscopic identification and counting of phytoplankton species, which is time-consuming and requires high taxonomic expertise. High-throughput sequencing, combined with metabarcoding, has recently demonstrated its potential as an alternative approach for plankton surveys. Several studies have confirmed the relevance of the diatom metabarcoding approach to calculate biotic indices based on species ecology. However, phytoplankton communities have not yet benefited from such validation. Here, by comparing the results obtained with the two methods (molecular and microscopic counting), we evaluated the relevance of metabarcoding approach for phytoplankton monitoring by considering different metrics: alpha diversity, taxonomic composition, community structure and a phytoplankton biotic index used to assess the trophic level of lakes. For this purpose, 55 samples were collected in four large alpine lakes (Aiguebelette, Annecy, Bourget, Geneva) during the year 2021. For each sample, a metabarcoding analysis based on two genetic markers (16S and 23S rRNA) was performed, in addition to the microscopic count. Regarding the trophic level of lakes, significant differences were found between index values obtained with the two approaches. The main hypothesis toexplain these differences comes from the incompleteness, particularly at the species level