Ciliates represent central nodes in freshwater planktonic food webs, and many species show pronounced seasonality, with short-lived maxima of a few dominant taxa while many being rare or ephemeral. These observations are primarily based on morphospecies counting methods, which, however, have limitations concerning the amount and volume of samples that can be processed. For high sampling frequencies at large scales, high throughput sequencing (HTS) of freshwater ciliates seems to be a promising tool. However, several studies reported large discrepancy between species abundance determinations by molecular compared to morphological means. Therefore, we compared ciliate DNA metabarcodes (V9 regions of the 18S rRNA gene) with morphospecies counts for a 3-year study (Lake Zurich, Switzerland; biweekly sampling, n = 74). In addition, we isolated, cultivated and sequenced the 18S rRNA gene of twelve selected ciliate species that served as seeds for HTS analyses. This workflow allowed for a detailed comparison of V9 data with microscopic analyses by quantitative protargol staining (QPS). The dynamics of V9 read abundances over the seasonal cycle corroborated well with morphospecies population patterns. Annual successions of rare and ephemeral species were more adequately characterized by V9 reads than by QPS. However, numbers of species specific sequence reads only partly reflected rank orders seen by counts. In contrast, biomass-based assemblage compositions showed higher similarity to V9 read numbers, probably indicating a relation between cell sizes and numbers / sizes of macronuclei (or 18S rRNA operons). Full-length 18S rRNA sequences of ciliates assigned to certain morphospecies are urgently needed for barcoding approaches as planktonic taxa are still poorly represented in public databases and the interpretation of HTS data depends on profound reference sequences. Through linking operational taxonomic units (OTUs) with known morphospecies, we can use the deep knowledge about the autecology of these species.

Network analyses of biological communities allow for identifying potential consequences of climate change on the resilience of ecosystems and their robustness to resist stressors. Using DNA metabarcoding datasets from a three-year-sampling (73 samples), we constructed the protistan plankton co-occurrence network of Lake Zurich, a model lake ecosystem subjected to climate change. Despite several documentations of dramatic lake warming in Lake Zurich, our study provides an unprecedented perspective by linking changes in biotic association patterns to climate stress. Water temperature belonged to the strongest environmental parameters splitting the data into two distinct seasonal networks (October–April; May–September). The expected ecological niche of phytoplankton, weakened through nutrient depletion because of permanent thermal stratification and through parasitic fungi, was occupied by the cyanobacterium Planktothrix rubescens and mixotrophic nanoflagellates. Instead of phytoplankton, bacteria and nanoflagellates were the main prey organisms associated with key predators (ciliates), which contrasts traditional views of biological associations in lake plankton. In a species extinction scenario, the warm season network emerged as more vulnerable than the cold season network, indicating a time-lagged effect of warmer winter temperatures on the communities. We conclude that climate stressors compromise lake ecosystem robustness and resilience through species replacement, richness differences, and succession as indicated by key network properties.

Ciliated protists (ciliates) are widely used for investigating evolution, mostly due to their successful radiation after their early evolutionary branching. In this study, we employed high-throughput sequencing technology to reveal the phylogenetic position of Synhymenia, as well as two classes Nassophorea and Phyllopharyngea, which have been a long-standing puzzle in the field of ciliate systematics and evolution. We obtained genomic and transcriptomic data from single cells of one synhymenian (Chilodontopsis depressa) and six other species of phyllopharyngeans (Chilodochona sp., Dysteria derouxi, Hartmannula sinica, Trithigmostoma cucullulus, Trochilia petrani, and Trochilia sp.). Phylogenomic analysis based on 157 orthologous genes comprising 173,835 amino acid residues revealed the affiliation of C. depressa within the class Phyllopharyngea, and the monophyly of Nassophorea, which strongly support the assignment of Synhymenia as a subclass within the class Phyllopharyngea. Comparative genomic analyses further revealed that C. depressa shares more orthologous genes with the class Nassophorea than with Phyllopharyngea, and the stop codon usage in C. depressa resembles that of Phyllopharyngea. Functional enrichment analysis demonstrated that biological pathways in C. depressa are more similar to Phyllopharyngea than Nassophorea. These results suggest that genomic and transcriptomic data can be used to provide insights into the evolutionary relationships within the “Nassophorea–Synhymenia–Phyllopharyngea” assemblage.

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding datasets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co‐occurrence networks constructed from time‐series metabarcoding datasets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate‐specific ^subnetworks resembled autecological species‐specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co‐occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate‐stressed ecosystems.