Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake

Abstract

Background: Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world's best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria.

Results: Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota.

Conclusions: We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction. Video Abstract.

Keywords: Community ecology; Metagenomics; Protistan ecology; rRNA.

Fig. 1

Phylogenetic tree of 18S rRNA gene sequences extracted from Lake Mendota metagenomes over the 20-year time series. Colored, filled circular points on the tree indicate novel sequences extracted from the Mendota metagenomes, while smaller black circles denote a representative set of previously published sequences. The outer heatmap represents the mean Z-score of extracted sequence during each of the seasons of the year, and bars show the number of samples the 18S rRNA gene was found in

Fig. 2

Evidence of seasonal variability of SSU rRNA genes. A The abundance of major taxa of protists and metazoans in Lake Mendota by season. Circles are colored by the season of the year and sized according to total abundance via CPM_contig for that month. B Alpha diversity as assessed by extracting OTUs with TPM of 100 or greater. Distributions of alpha diversity are shown for both eukaryotes and bacteria for each month of the year in the time series. C Proportion of total observed taxa present in each season of the dataset for (left) bacteria and (right) eukaryotes

Fig. 3

Shift in diversity and abundance of microbial eukaryotes and other relevant eukaryotic taxa after the spiny water flea invasion. A Phylum breakdown of OTUs that did or did not show statistically significant increases in CPM_contig before and after 2010. The majority of statistically significant increases were from OTUs annotated as clade Alveolata (including phyla Ciliophora, Apicomplexa, and Dinoflagellata). B Difference in mean CPM_contig after the invasion for OTUs and mean CPM_contig before the invasion of the spiny water flea, grouped and colored by the statistical significance of the change in abundance

Fig. 4

Abundances of Alveolates in the Lake Mendota time series. A Phylogenetic tree showing all alveolate (clade Alveolata) sequences (square tip points) alongside their NCBI RefSeq closest blast matches (small circles), highlighted by their taxonomic class. The green circle at the bottom of the tree is a clade of Ochrophyta used as an outgroup. B Extracted 18S rRNA gene sequences are labeled with a “*” if they changed significantly in abundance according to the procedure described in the text. C The number of 18S rRNA genes from all samples that fell into the cluster (97% sequence identity) in the phylogenetic tree. Ciliates of class Spirotrichea tended to be most highly abundant in the dataset. D Distribution of days that had positive Z-scores in abundance for each Alveolate phylum for each year of the dataset. In the later years of the dataset, dinoflagellates in particular had a higher proportion of total sampling days that had elevated abundance relative to the mean. E Alpha diversity (number of OTUs) present relative to total extracted for each alveolate class in each year of the dataset. Classes Nassophorea, Litostomatea, and Heterotrichea were universally more commonly present in the latter half of the dataset (2010–2019) and in particular in 2012–2018. Lines drawn on top of the boxplots and point show the overall trend (black) and colored trends in relative alpha diversity for the three taxonomic classes for which alpha diversity trends were significant

Fig. 5

Changing community profile of metazoans in Lake Mendota. A Phylogenetic tree showing genus-level taxonomic assignment of each metazoan 97% OTU. Shapes indicate sample origin and are colored based on order-level taxonomic assignments of the respective genus. Squares correspond to references extracted from companion metagenomes for Daphnia (water flea) and Bythotrephes (spiny water flea; references for each generated using enriched metagenomes from Lake Mendota). Tree is rooted at the phylum Ochrophyta. B Stars (“*”) denote significant abundance increases of rRNA clustered OTUs after 2010. C Difference in average Z-score of abundance of metagenomic rRNA before and after the spiny water flea invasion by year and season. The x-axis corresponds to Z-score, and points are colored by season. D Time series seasonal Z-scores for taxa numbered in panel (B). E Mapped abundances of each of the 18S rRNA genes extracted from the companion metagenomes for Bythotrephes and Daphnia

Fig. 6

Network analysis over 20-year time series of metagenomes suggests stable connections between eukaryotes and bacteria. Circles correspond to significant, strong correlations between taxa listed on the x- and y-axes and are both colored and sized according to the correlation coefficient. Only correlations with a significant Benjamini-Hochberg-corrected p-value and a correlation coefficient of greater than or equal to 0.50 are included visually. The color corresponds to whether the x-axis partner is bacterial or eukaryotic, and shading indicates specific phylum. Self-correlations are excluded when the small subunit rRNA gene sequences were the same

Fig. 7

Metagenome-assembled genomes recovered from Lake Mendota span a wide range of eukaryotic taxa. A Phylogenetic tree of extracted MAGs using concatenated alignment of BUSCO genes alongside reference genomes from the corresponding phyla. Only MAGs which contained a sufficient number of BUSCO genes (see the “Methods”) were included. Unfilled and labeled circles correspond to MAGs extracted from the Lake Mendota time series. B Lollipop plot showing completeness of each MAG via EukCC (connected point) and the percentage consensus of the phylum-level taxonomic annotation provided by EUKulele (colored asterisk (*)). C Abundance of the most abundant metagenome-assembled genomes extracted from within each taxonomic group across the metagenomic time series, expressed in CPM_contig; each point is an estimated abundance for one MAG at one timepoint