Sea-ice eukaryotes of the Gulf of Finland, Baltic Sea, and evidence for herbivory on weakly shade-adapted ice algae.

To determine community composition and physiological status of early spring sea-ice organisms, we collected sea-ice, slush and under-ice water samples from the Baltic Sea. We combined light microscopy, HPLC pigment analysis and pyrosequencing, and related the biomass and physiological status of sea-ice algae with the protistan community composition in a new way in the area. In terms of biomass, centric diatoms including a distinct Melosira arctica bloom in the upper intermediate section of the fast ice, dinoflagellates, euglenoids and the cyanobacterium Aphanizomenon sp. predominated in the sea-ice sections and unidentified flagellates in the slush. Based on pigment analyses, the ice-algal communities showed no adjusted photosynthetic pigment pools throughout the sea ice, and the bottom-ice communities were not shade-adapted. The sea ice included more characteristic phototrophic taxa (49%) than did slush (18%) and under-ice water (37%). Cercozoans and ciliates were the richest taxon groups, and the differences among the communities arose mainly from the various phagotrophic protistan taxa inhabiting the communities. The presence of pheophytin a coincided with an elevated ciliate biomass and read abundance in the drift ice and with a high Eurytemora affinis read abundance in the pack ice, indicating that ciliates and Eurytemora affinis were grazing on algae.

Bioinformatic Amplicon Read Processing Strategies Strongly Affect Eukaryotic Diversity and the Taxonomic Composition of Communities.

Amplicon read sequencing has revolutionized the field of microbial diversity studies. The technique has been developed for bacterial assemblages and has undergone rigorous testing with mock communities. However, due to the great complexity of eukaryotes and the numbers of different rDNA copies, analyzing eukaryotic diversity is more demanding than analyzing bacterial or mock communities, so studies are needed that test the methods of analyses on taxonomically diverse natural communities. In this study, we used 20 samples collected from the Baltic Sea ice, slush and under-ice water to investigate three program packages (UPARSE, mothur and QIIME) and 18 different bioinformatic strategies implemented in them. Our aim was to assess the impact of the initial steps of bioinformatic strategies on the results when analyzing natural eukaryotic communities. We found significant differences among the strategies in resulting read length, number of OTUs and estimates of diversity as well as clear differences in the taxonomic composition of communities. The differences arose mainly because of the variable number of chimeric reads that passed the pre-processing steps. Singleton removal and denoising substantially lowered the number of errors. Our study showed that the initial steps of the bioinformatic amplicon read processing strategies require careful consideration before applying them to eukaryotic communities.