Search for: All records

Invasive species impart abrupt changes on ecosystems, but their impacts on microbial communities are often overlooked. We paired a 20 y freshwater microbial community time series with zooplankton and phytoplankton counts, rich environmental data, and a 6 y cyanotoxin time series. We observed strong microbial phenological patterns that were disrupted by the invasions of spiny water flea ( Bythotrephes cederströmii ) 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 differed by season; spring and clearwater communities changed most following the spiny water flea invasion that lessened clearwater intensity, while summer communities changed least following the zebra mussel invasion despite the shifts in Cyanobacteria diversity and toxicity. A modeling framework identified the invasions as primary drivers of the observed phenological changes. 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. 

The Lake Mendota Microbial Observatory collects routine water physical and chemical measurements alongside their microbial samples. This dataset includes measurements of water temperature, dissolved oxygen, pH, and conductivity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld probes. Data from 2006-2014 was compiled from multiple sources and includes only water temperature and dissolved oxygen. Data from 2014-2019 is from the same probe, a YSI Pro Plus instrument, and also includes pH and specific conductance. Routine microbial observatory sampling continues into the present. 

The Lake Mendota Microbial Observatory collects routine water clarity measurements alongside their microbial samples. This dataset includes measurements of water clarity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld Secchi discs. When multiple personnel performed the Secchi disc measurements, the average and standard deviation are reported. To take the Secchi depth, sunglasses are removed and the disc is lowered on the shaded side of the boat. The Secchi depth is the average between where the Secchi disc disappears while lowering it and where it reappears while raising it. Routine microbial observatory sampling continues into the present. 

Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Ultraviolet-visible (UV-vis) spectroscopy is an analytical technique commonly used to assess the composition of dissolved organic matter in water samples. Here, we present spectra from Lake Mendota samples collected from June - November in 2017 at the surface of Lake Mendota as well as at specific depths within the water column. All samples were collected near the NTL-LTER research buoy. Absorbance values are listed for wavelengths 200 - 800 nm for each sample. 

Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) allows for the characterization of dissolved organic matter at the molecular level. The water sample was collected near the NTL-LTER research buoy on Lake Mendota. Formula assignments were made to raw mass to charge ratios detected in the mass spectrum using a custom processing script and resulting in a list of chemical formulas making up the DOM sample. 

ABSTRACT Natural microbial communities consist of closely related taxa that may exhibit phenotypic differences and inhabit distinct niches. However, connecting genetic diversity to ecological properties remains a challenge in microbial ecology due to the lack of pure cultures across the microbial tree of life. “ Candidatus Accumulibacter phosphatis” (Accumulibacter) is a polyphosphate-accumulating organism that contributes to the enhanced biological phosphorus removal (EBPR) biotechnological process for removing excess phosphorus from wastewater and preventing eutrophication from downstream receiving waters. Distinct Accumulibacter clades often coexist in full-scale wastewater treatment plants and laboratory-scale enrichment bioreactors and have been hypothesized to inhabit distinct ecological niches. However, since individual strains of the Accumulibacter lineage have not been isolated in pure culture to date, these predictions have been made solely on genome-based comparisons and enrichments with varying strain compositions. Here, we used genome-resolved metagenomics and metatranscriptomics to explore the activity of coexisting Accumulibacter strains in an engineered bioreactor environment. We obtained four high-quality genomes of Accumulibacter strains that were present in the bioreactor ecosystem, one of which is a completely contiguous draft genome scaffolded with long Nanopore reads. We identified core and accessory genes to investigate how gene expression patterns differed among the dominating strains. Using this approach, we were able to identify putative pathways and functions that may confer distinct functions to Accumulibacter strains and provide key functional insights into this biotechnologically significant microbial lineage. IMPORTANCE “ Candidatus Accumulibacter phosphatis” is a model polyphosphate-accumulating organism that has been studied using genome-resolved metagenomics, metatranscriptomics, and metaproteomics to understand the EBPR process. Within the Accumulibacter lineage, several similar but diverging clades are defined by the shared sequence identity of the polyphosphate kinase ( ppk1 ) locus. These clades are predicted to have key functional differences in acetate uptake rates, phage defense mechanisms, and nitrogen-cycling capabilities. However, such hypotheses have largely been made based on gene content comparisons of sequenced Accumulibacter genomes, some of which were obtained from different systems. Here, we performed time series genome-resolved metatranscriptomics to explore gene expression patterns of coexisting Accumulibacter clades in the same bioreactor ecosystem. Our work provides an approach for elucidating ecologically relevant functions based on gene expression patterns between closely related microbial populations. 

ABSTRACT Nitrite-oxidizing bacteria belonging to the genus Nitrospira mediate a key step in nitrification and play important roles in the biogeochemical nitrogen cycle and wastewater treatment. While these organisms have recently been shown to exhibit metabolic flexibility beyond their chemolithoautotrophic lifestyle, including the use of simple organic compounds to fuel their energy metabolism, the metabolic networks controlling their autotrophic and mixotrophic growth remain poorly understood. Here, we reconstructed a genome-scale metabolic model for Nitrospira moscoviensis ( i Nmo686) and used flux balance analysis to evaluate the metabolic networks controlling autotrophic and formatotrophic growth on nitrite and formate, respectively. Subsequently, proteomic analysis and [ 13 C]bicarbonate and [ 13 C]formate tracer experiments coupled to metabolomic analysis were performed to experimentally validate model predictions. Our findings corroborate that N. moscoviensis uses the reductive tricarboxylic acid cycle for CO 2 fixation, and we also show that N. moscoviensis can indirectly use formate as a carbon source by oxidizing it first to CO 2 followed by reassimilation, rather than direct incorporation via the reductive glycine pathway. Our study offers the first measurements of Nitrospira ’s in vivo central carbon metabolism and provides a quantitative tool that can be used for understanding and predicting their metabolic processes. IMPORTANCE Nitrospira spp. are globally abundant nitrifying bacteria in soil and aquatic ecosystems and in wastewater treatment plants, where they control the oxidation of nitrite to nitrate. Despite their critical contribution to nitrogen cycling across diverse environments, detailed understanding of their metabolic network and prediction of their function under different environmental conditions remains a major challenge. Here, we provide the first constraint-based metabolic model of Nitrospira moscoviensis representing the ubiquitous Nitrospira lineage II and subsequently validate this model using proteomics and 13 C-tracers combined with intracellular metabolomic analysis. The resulting genome-scale model will serve as a knowledge base of Nitrospira metabolism and lays the foundation for quantitative systems biology studies of these globally important nitrite-oxidizing bacteria. 

Abstract Temperate phages are viruses of bacteria that can establish two types of infection: a lysogenic infection in which the virus replicates with the host cell without producing virions, and a lytic infection where the host cell is eventually destroyed, and new virions are released. While both lytic and lysogenic infections are routinely observed in the environment, the ecological and evolutionary processes regulating these viral dynamics are still not well understood, especially for uncultivated virus-host pairs. Here, we characterized the long-term dynamics of uncultivated viruses infecting green sulfur bacteria (GSB) in a model freshwater lake (Trout Bog Lake, TBL). As no GSB virus has been formally described yet, we first used two complementary approaches to identify new GSB viruses from TBL; one in vitro based on flow cytometry cell sorting, the other in silico based on CRISPR spacer sequences. We then took advantage of existing TBL metagenomes covering the 2005–2018 period to examine the interactions between GSB and their viruses across years and seasons. From our data, GSB populations in TBL were constantly associated with at least 2-8 viruses each, including both lytic and temperate phages. The dominant GSB population in particular was consistently associated with two prophages with a nearly 100% infection rate for >10 years. We illustrate with a theoretical model that such an interaction can be stable given a low, but persistent, level of prophage induction in low-diversity host populations. Overall, our data suggest that lytic and lysogenic viruses can readily co-infect the same host population, and that host strain-level diversity might be an important factor controlling virus-host dynamics including lytic/lysogeny switch. 

ABSTRACT Metagenome-assembled genomes (MAGs) expand our understanding of microbial diversity, evolution, and ecology. Concerns have been raised on how sequencing, assembly, binning, and quality assessment tools may result in MAGs that do not reflect single populations in nature. Here, we reflect on another issue, i.e., how to handle highly similar MAGs assembled from independent data sets. Obtaining multiple genomic representatives for a species is highly valuable, as it allows for population genomic analyses; however, when retaining genomes of closely related populations, it complicates MAG quality assessment and abundance inferences. We show that (i) published data sets contain a large fraction of MAGs sharing >99% average nucleotide identity, (ii) different software packages and parameters used to resolve this redundancy remove very different numbers of MAGs, and (iii) the removal of closely related genomes leads to losses of population-specific auxiliary genes. Finally, we highlight some approaches that can infer strain-specific dynamics across a sample series without dereplication. 

Methylmercury (MeHg) production is controlled by the bioavailability of inorganic divalent mercury (Hg(II)_i) and Hg‐methylation capacity of the microbial community (conferred by thehgcABgene cluster). However, the relative importance of these factors and their interaction in the environment remain poorly understood. Here, metagenomic sequencing and a full‐factorial MeHg formation experiment were conducted across a wetland sulfate gradient with different microbial communities and pore water chemistries. From this experiment, the relative importance of each factor on MeHg formation was isolated. Hg(II)_ibioavailability correlated with the dissolved organic matter composition, while the microbial Hg‐methylation capacity correlated with the abundance ofhgcAgenes. MeHg formation responded synergistically to both factors. Notably,hgcAsequences were from diverse taxonomic groups, none of which contained genes for dissimilatory sulfate reduction. This work expands our understanding of the geochemical and microbial constraints on MeHg formation in situ and provides an experimental framework for further mechanistic studies.