A robust approach to estimate relative phytoplankton cell abundance from metagenomes
J. J. Pierella Karlusich, E. Pelletier, L. Zinger, F. Lombard, A. Zingone, S. Colin, J. M. Gasol, R. Dorrell, E. Scalco, S. G. Acinas, P. Wincker, C. de Vargas, C. Bowler
Abstract
Phytoplankton account for >45% of global primary production, and have an enormous impact on aquatic food webs and on the entire Earth System. Their members are found among prokaryotes (cyanobacteria) and multiple eukaryotic lineages containing chloroplasts. Phytoplankton communities are generally studied by PCR amplification of bacterial (16S), nuclear (18S) or chloroplastic (16S) rRNA marker genes from DNA extracted from environmental samples. However, our appreciation of phytoplankton abundance or biomass is limited by PCR-amplification biases, rRNA gene copy number variations across taxa, and the fact that rRNA genes do not provide insights into metabolic traits such as photosynthesis. In addition, rRNA marker genes fail to capture both cyanobacteria and photosynthetic eukaryotes simultaneously. Here, we targeted the photosynthetic gene psbO from metagenomes to circumvent these limitations: the method is PCR-free, and the gene is universally and exclusively present in photosynthetic prokaryotes and eukaryotes, mainly in one copy per genome. We applied and validated this new strategy with the Tara Oceans datasets, and showed improved correlations with flow cytometry and microscopy than when based on rRNA genes. Furthermore, we revealed unexpected features of the ecology of these organisms, such as the high abundance of picocyanobacterial aggregates and symbionts in the ocean, and the decrease in relative abundance of phototrophs towards the larger size classes of marine dinoflagellates. To facilitate the incorporation of psbO in molecular-based surveys, we compiled a curated database of >18,000 unique sequences. Overall, psbO appears to be a promising new gene marker for molecular-based evaluations of entire phytoplankton communities.
02 /Specification & Classification
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