Biology subjects

Rohwer, R. R.

Publications and source records attributed to Rohwer, R. R..

9 recordsLinked to original sources

bioRxiv2025

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses represent key ecological players in aquatic ecosystems, yet their evolutionary dynamics in response to environmental change remain poorly understood, particularly in freshwater environments. We leveraged an unprecedented 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1,512 high-quality giant virus metagenome-assembled genomes (GVMAGs), providing a unique framework to track viral genome evolution across decades. Viruses in the order Imitervirales dominated the Lake Mendota virome, exhibiting consistent presence across all seasons and years. We identified gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as drivers of genomic innovation in giant viruses. Co-occurrence network analysis between viral DNA polymerase B and eukaryotic 18S rRNA sequences revealed significantly increased virus-host associations following the 2009 invasion of a predatory zooplankton. Genome-wide single nucleotide polymorphism analysis demonstrated predominantly purifying selection across viral genes, but revealed a significant increase in positively selected genes post-invasion, including in functions related to host infection (such as protein translation). Comparative evolutionary analyses revealed that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, positioning them as evolutionary intermediates with bacterial-like genomic stability but virus-like adaptive capacity. By analyzing a vicennial (20-year) time series, we show that freshwater giant viruses employ sophisticated evolutionary strategies. They broaden their host range without abandoning established partners and maintain stable genomic backbones while rapidly adapting infection-related genes. These dynamics highlight their critical yet previously underappreciated role in freshwater ecosystem dynamics and resilience to environmental change.

microbiology↗

bioRxiv2024

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

BackgroundProtists, 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 worlds best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last twenty 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. ResultsBased 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. Further, 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. ConclusionsWe demonstrate that metagenomic sequence-based community analysis can complement existing eorts 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.

ecology↗

bioRxiv2024

Bacterial ecology and evolution converge on seasonal and decadal scales

Ecology and evolution are often viewed as distinct processes, which interact on contemporary time scales in microbiomes. To observe these processes in a natural system, we collected a two-decade, 471-sample freshwater lake time series, creating the longest metagenome dataset to date. Among 2,855 species-representative genomes, diverse species and strains followed cyclical seasonal patterns, and one in five species experienced decadal shifts in strain composition. The most globally abundant freshwater bacterium had constant species-level abundance, but environmental extremes appeared to trigger a shift in strain composition and positive selection of amino acid and nucleic acid metabolism genes. These genes identify organic nitrogen compounds as potential drivers of freshwater responses to global change. Seasonal and long-term strain dynamics could be regarded as ecological processes or equivalently as evolutionary change. Rather than as distinct processes that interact, we propose a conceptualization where ecology and evolution converge along a continuum to better describe change in diverse microbial communities.

evolutionary biology↗

bioRxiv2024

A 20-year time-series of a freshwater lake reveals seasonal dynamics and environmental drivers of viral diversity, ecology, and evolution

Long-term ecological studies are powerful tools to investigate microbiomes and ecosystem change but have mostly ignored viruses. Here, we leveraged a 20-year time-series of a freshwater lake to characterize 1.3 million viral genomes over time, seasonality, and environmental factors. We identified 578 auxiliary metabolic gene (AMG) clusters representing over 150,000 AMGs, the most abundant of which, including psbA for photosynthesis, pmoC for methane oxidation, and katG for hydrogen peroxide decomposition, were consistently represented in viruses across decades and seasons. We observed positive associations and niche differentiation between virus-host pairs during seasonal change including in keystone taxa, Cyanobacteria, methanotrophs, and Nanopelagicales. Environmental constraints, specifically inorganic carbon and ammonium influenced viral abundances over time, and highlighted roles of viruses in both "top-down" and "bottom-up" interactions. Key evolutionary processes shaping gene and genome-wide selection included favored fitness genes, reduced genomic heterogeneity, and dominant sub-populations carrying specific genes. Overall, our study advances understanding of diversity, ecological dynamics, and evolutionary trajectories of viruses in Earths microbiomes and ecosystems.

microbiology↗

bioRxiv2023

The aftermath of a trophic cascade: Increasedanoxia following species invasion of a eutrophiclake

Species invasions can disrupt aquatic ecosystems by re-wiring food webs. A trophic cascade triggered by the invasion of the predatory zooplankter spiny water flea (Bythotrephes cederstromii) resulted in increased phytoplankton due to decreased zooplankton grazing. Here, we show that increased phytoplankton biomass led to an increase in lake anoxia. The temporal and spatial extent of anoxia experienced a step change increase coincident with the invasion. Anoxia was driven by phytoplankton biomass and stratification changes, and anoxic factor increased by 10 days. In particular, anoxia established more quickly following spring stratification. A shift in spring phytoplankton phenology encompassed both abundance and community composition. Diatoms (Bacillaryophyta) drove the increase in spring phytoplankton biomass, but not all phytoplankton community members increased, shifting the community composition. We infer that increased phytoplankton biomass increased labile organic matter and drove hypolimnetic oxygen consumption. These results demonstrate how a species invasion can shift lake phenology and biogeochemistry. Scientific significance statementInvasive species can affect aquatic ecosystems, often by disrupting food webs. We investigated whether the invasive predatory zooplankton spiny water flea could additionally impact the biogeochemistry of a lake, specifically hypolimnetic anoxia dynamics. Using 24 years of observations spanning a spiny water flea invasion that triggered a food web-mediated increase in phytoplankton, we found that increased spring phytoplankton coincided with an earlier onset of anoxia, thereby drawing a connection between a species invasion and a shift in lake oxygen dynamics. Data availability statementAll data is publicly available through the Environmental Data Initiative via identifiers referenced in the methods. Scripts and data to reproduce the results are available on GitHub (https://github.com/robertladwig/spinyAnoxia) and in Rohwer et al. (2023). Author contributionsRRR and RL co-led the entire manuscript effort and contributed equally. RL and RRR came up with the research question and conducted the statistical and numerical analyses: RL analysed the anoxia dynamics and related water quality variables, RRR analysed the phytoplankton community dynamics. RL, RRR, and HAD created figures and visualizations. PCH, JW and JVZ provided essential feedback to the analyses and the discussion of ecosystem implications. RRR and RL co-wrote the paper.

ecology↗

bioRxiv2022

Species invasions shift microbial phenology in a two-decade freshwater time series

Invasive species impart abrupt changes on ecosystems, but their impacts on microbial communities are often overlooked. We paired a 20-year freshwater microbial community time series with zooplankton and phytoplankton counts, rich environmental data, and a 6-year cyanotoxin time series. We observed strong microbial phenological patterns that were disrupted by the invasions of spiny water flea (Bythotrephes cederstromii) and zebra mussels (Dreissena polymorpha). First, we detected shifts in Cyanobacteria phenology. After the spiny water flea invasion, Cyanobacteria dominance crept earlier into clearwater; and after the zebra mussel invasion, Cyanobacteria abundance crept even earlier into the diatom-dominated spring. During summer, the spiny water flea invasion sparked a cascade of shifting diversity where zooplankton diversity decreased and Cyanobacteria diversity increased. Second, we detected shifts in cyanotoxin phenology. After the zebra mussel invasion, microcystin increased in early summer and the duration of toxin production increased by over a month. Third, we observed shifts in heterotrophic bacteria phenology. The Bacteroidota phylum and members of the acI Nanopelagicales lineage were differentially more abundant. The proportion of the bacterial community that changed also differed by season; the spring and clearwater bacterial communities changed most following the spiny water flea invasion that lessened clearwater duration and intensity, while the diverse summer bacterial community changed least following the zebra mussel invasion despite the observed shifts in diversity and toxicity during summer. These long-term invasion-mediated shifts in microbial phenology demonstrate the interconnectedness of microbes with the broader food web, and their susceptibility to long-term environmental change. Significance StatementMicrobial communities are typically studied as part of the microbial loop, separately from the broader food web. Using a two-decade freshwater time series, we explored whether two species invasions that shifted the metazoan food web (spiny water flea and zebra mussels) also impacted the microbial communities. We looked for seasonal responses because the microbial communities had strong seasonal patterns. We discovered that Cyanobacteria increased early in the year, and Cyanobacteria diversity increased in the summer. Cyanotoxins also increased, along with the duration of toxin production. In the heterotrophic bacterial community, some organisms changed consistently within lineages and seasons while others diverged. These findings illustrate the importance of seasonal context, and highlight the interconnectedness of bacteria with the broader food web.

ecology↗

bioRxiv2022

Lake iTag measurements over nineteen years, introducing the limony dataset

How microbial communities change over time is key to understanding how ecosystems will respond to global change, and to answering fundamental questions about how microbial ecology and evolution unfold. However, our understanding of microbial change is limited by a lack of long-term observations. Using archived filters from freshwater Lake Mendota (WI, USA), we created a 20-year microbial time series that begins in year 2000, a decade before Illumina DNA sequencing hit the market. We characterized 1,023 samples and controls with 16S rRNA gene amplicon sequencing in the "limony" dataset, and 471 samples and controls with shotgun metagenome sequencing in the "TYMEFLIES" dataset. In addition to the raw sequencing data, we point users to associated data products: paired environmental data collected by the North Temperate Lakes Long-Term Ecological Research program (NTL-LTER), our R package to work with curated limony data, and metagenomic assemblies and metagenome-assembled genomes (MAGs) created from the TYMEFLIES dataset. The limony and TYMEFLIES datasets, along with their paired environmental data and reference genomes, are a unique and ready-to-use resource for diverse scientists including limnologists, ecologists, evolutionary biologists, bioinformaticians, modellers, and educators.

microbiology↗

bioRxiv2018

Connections between freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Metabolic processes at the microbial scale influence ecosystem functions because microbes are responsible for much of the carbon and nutrient cycling in freshwater. One approach to predict the metabolic capabilities of microbial communities is to search for functional marker genes in metagenomes. However, this approach does not provide context about co-occurrence with other metabolic traits within an organism or detailed taxonomy about those organisms. Here, we combine a functional marker gene analysis with metabolic pathway prediction of microbial population genomes (MAGs) assembled from metagenomic time series in eutrophic Lake Mendota and humic Trout Bog to identify how carbon and nutrient cycles are connected in freshwater. We found that phototrophy, carbon fixation, and nitrogen fixation pathways co-occurred in Cyanobacteria MAGs in Lake Mendota and in Chlorobiales MAGs in Trout Bog. Cyanobacteria MAGs also had strong temporal correlations to functional marker genes for nitrogen fixation in several years. Genes encoding steps in the nitrogen and sulfur cycles varied in abundance and taxonomy by lake, potentially reflecting the availability and composition of inorganic nutrients in these systems. We were also able to identify which populations contained the greatest density and diversity of genes encoding glycoside hydrolases. Populations with many glycoside hydrolases also encoded pathways for sugar degradation. By using both MAGs and marker genes, we were better able to link functions to specific taxonomic groups in our metagenomic time series, enabling a more detailed understanding of freshwater microbial carbon and nutrient cycling.

microbiology↗

bioRxiv2017

TaxAss: Leveraging Custom Databases Achieves Fine-Scale Taxonomic Resolution

Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater datasets using the comprehensive Silva database and the freshwater-specific FreshTrain database. TaxAss increased the percent of the dataset classified compared to using only Silva, especially at fine-resolution family-species taxa levels, while across the freshwater test-datasets classifications increased by as much as 11-40 percent of total reads. A similar increase in classifications was not observed in a control mouse gut dataset, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxa-levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxa levels incorrect classifications became significant. We validated TaxAss using simulated amplicon data with known taxonomy and found that 96-99% of test sequences were correctly classified at fine resolution. TaxAss splits a datasets sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source, and available at www.github.com/McMahonLab/TaxAss.\n\nIMPORTANCEMicrobial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon datasets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at phylum, class, and order level lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are dataset-dependent and cannot be compared between datasets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between datasets.

bioinformatics↗