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At least 73 records · Page 4

Petroleum pollution changes microbial diversity and network complexity of soil profile in an oil refinery

Petroleum pollution resulting from spills and leakages in oil refinery areas has been a significant environmental concern for decades. Despite this, the effects of petroleum pollutants on soil microbial communities and their potential for pollutant biodegradation still required further investigation. In this study, we collected 75 soil samples from 0 to 5 m depths of 15 soil profiles in an abandoned refinery to analyze the effect of petroleum pollution on soil microbial diversity, community structure, and network co-occurrence patterns. Our results suggested soil microbial a-diversity decreased under high C10–C40 levels, coupled with significant changes in the community structure of soil profiles. However, soil microbial network complexity increased with petroleum pollution levels, suggesting more complex microbial potential interactions. A module specific for methane and methyl oxidation was also found under high C10–C40 levels of the soil profile, indicating stronger methanotrophic and methylotrophic metabolic activities at the heavily polluted soil profile. The increased network complexity observed may be due to more metabolic pathways and processes, as well as increased microbial interactions during these processes. These findings highlight the importance of considering both microbial diversity and network complexity in assessing the effects of petroleum pollution on soil ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Composition and physiological profiling of sprout-associated microbial communities

The native microfloras of various types of sprouts (alfalfa, clover, sunflower, mung bean, and broccoli sprouts) were examined to assess the relative effects of sprout type and inoculum factors (i.e., sprout-growing facility, seed lot, and inoculation with sprout-derived inocula) on the microbial community structure of sprouts. Sprouts were sonicated for 7 min or hand shaken with glass beads for 2 min to recover native microfloras from the surface, and the resulting suspensions were diluted and plated. The culturable fraction was characterized by the density (log CFU/g), richness (e.g., number of types of bacteria), and diversity (e.g., microbial richness and evenness) of colonies on tryptic soy agar plates incubated for 48 h at 30 degrees C. The relative similarity between sprout-associated microbial communities was assessed with the use of community-level physiological profiles (CLPPs) based on patterns of utilization of 95 separate carbon sources. Aerobic plate counts of 7.96 +/- 0.91 log CFU/g of sprout tissue (fresh weight) were observed, with no statistically significant differences in microbial cell density, richness, or diversity due to sprout type, sprout-growing facility, or seed lot. CLPP analyses revealed that the microbial communities associated with alfalfa and clover sprouts are more similar than those associated with the other sprout types tested. Variability among sprout types was more extensive than any differences between microbial communities associated with alfalfa and clover sprouts from different sprout-growing facilities and seed lots. These results indicate that the subsequent testing of biocontrol agents should focus on similar organisms for alfalfa and clover, but alternative types may be most suitable for the other sprout types tested. The inoculation of alfalfa sprouts with communities derived from various sprout types had a significant, source-independent effect on microbial community structure, indicating that the process of inoculation alters the dynamics of community development regardless of the types of organisms involved.

NASA Center KSC↗

Food Quality and Phytoplankton Community Composition in San Francisco Bay using Imaging Spectroscopy Data from the California HyspIRI Airborne Campaign

The San Francisco Bay (SFB) is the largest estuary on the west coast of the United States. It is an important transition zone between marine, freshwater, and inland terrestrial watersheds. The SFB is an important region for the cycling of nutrients and pollutants and it supports nurseries of ecologically and commercially important fisheries, including some threatened species. Phytoplankton community structure influences food web dynamics, and the taxonomy of the phytoplankton may be more important in determining primary food quality than environmental factors. As such, estimating food quality from phytoplankton community composition can be a robust tool to understand trophic transfer of energy. Recent work explores phytoplankton food quality in SFB through the use of microscopy and phytoplankton chemotaxonomy to evaluate how changes in phytoplankton composition may have influenced the recent trophic collapse of pelagic fishes in the northern part of the SFB. The objective of this study is to determine if the approach can also be applied to imaging spectroscopy data in order to quantify phytoplankton food quality from space. Imaging spectroscopy data of SFB from the Airborne VisibleInfrared Imaging Spectrometer (AVIRIS) was collected during the Hyperspectral Infrared (HyspIRI) Airborne Campaign in California (2013 2015) and used in this study. Estimates of ocean chlorophyll and phytoplankton community structure were determined using standard ocean chlorophyll algorithms and the PHYtoplankton Detection with Optics (PHYDOTax) algorithms. These were validated using in situ observations of phytoplankton composition using microscopic cell counts and phytoplankton chemotaxonomy from the US Geological Surveys ship surveys of the SFB. The findings from this study may inform the use of future high spectral resolution satellite sensors with the spatial resolution appropriate for coastal systems (e.g., HyspIRI) to assess food quality from space.

HyspIRI↗

Compositional changes of dissolved organic molecules along water flow and their influencing factors in the Three Gorges Reservoir

Molecular composition of dissolved organic matter (DOM) and its influencing factors in river reservoirs remains elusive. Here, molecular compositions of DOM, bacterial community structures, and water physiochemistry were investigated in the field and microcosm samples of the Three Gorges Reservoir (TGR). The results showed that DOM molecular compositions were significantly (R 2 = 0.245, p < 0.001) correlated with bacterial community structures in the studied field samples, suggesting that bacteria may actively interact with DOM molecules. In this study, the molecular compositions of DOM in the studied field samples were significantly (p < 0.05) affected by the distance between the sample sites and the Three Gorges Dam and by bacterial groups of Actinobacteria and Alphaproteobacteria, suggesting that both hydrological and bacterial processes may contribute to the variation in DOM molecular composition in the TGR water. Furthermore, microcosm experiments demonstrated that both microbial and abiotic processes may transform and/or produce DOM in the TGR, thereby affecting DOM molecular composition. Microbial process increased the average aromaticity index and decreased the carbon number of DOM molecules with increasing incubation duration; whereas average oxygen number, double bond equivalent, and oxidation state of carbon of DOM molecules increased during the first 14 days of incubation and began to decrease thereafter. Taken together, this study expands our understanding of the impact of microbial process on the DOM molecular composition in reservoir ecosystems, and has great implications for carbon cycling in major rivers.

58 GEOSCIENCES↗

Comparing the response of the indigenous microbial community to crude oil amendment in oxic versus hypoxic conditions

The Caspian Sea is the world’s largest landlocked saline lake which lies between Europe and Asia. This region is particularly known for its large-scale oil reserves, pipelines, and drilling activities, which have contributed to the environmental decline of this lake. In addition to pollution from the petroleum industry, drainage from various river basins brings an influx of residential, industrial, and agricultural effluents that induce eutrophication and hypoxic conditions in deeper, colder waters, creating an oxygen gradient. The temperature and oxygen stratification in this environment has presented a unique opportunity to investigate the potential of the biodegradative processes carried out by the indigenous microbial community. We believe these indigenous microbes possess different metabolic capabilities to degrade oil as they adapted to declining oxygen concentrations and temperatures with increasing depths over a prolonged period. Hence, community structure and composition will vary with depth. Microcosms were set up to observe the indigenous microbial reaction after a 60 ppm native crude oil amendment over 115 days. Surface water microcosms were incubated at 28ºC and aerated while deep water microcosms were incubated at 8ºC under anaerobic conditions. These two environmental conditions represent the temperature and oxygen extremes along the gradient and were selected as we try to simulate the indigenous community’s response to this oil contamination. DNA was extracted and amplified from these microcosms and sequenced. Bioinformatic analysis was performed to track changes in the abundance of taxa present and biodiversity over different time points to show the progression of community structure. All microcosms showed the presence of hydrocarbon-degrading phyla, whose presence is consistent with other reports from oil-enriched environments. However, distinct communities were observed in oxic versus hypoxic microcosms. Orders of Bacteria related to sulfate and nitrogen cycling were found in hypoxic microcosms, indicating a possible mechanism for the anaerobic biodegradation of crude oil. GC-MS analysis of initial and final microcosms also provided evidence of degradation of hydrocarbon fractions in both warm, oxic and cold, hypoxic conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Soil Metabolomics Predict Microbial Taxa as Biomarkers of Moisture Status in Soils from a Tidal Wetland

We present observations from a laboratory-controlled study on the impacts of extreme wetting and drying on a wetland soil microbiome. Our approach was to experimentally challenge the soil microbiome to understand impacts on anaerobic carbon cycling processes as the system transitions from dryness to saturation and vice-versa. Specifically, we tested for impacts on stress responses related to shifts from wet to drought conditions. We used a combination of high-resolution data for small organic chemical compounds (metabolites) and biological (community structure based on 16S rRNA gene sequencing) features. Using a robust correlation-independent data approach, we further tested the predictive power of soil metabolites for the presence or absence of taxa. Here, we demonstrate that taking an untargeted, multidimensional data approach to the interpretation of metabolomics has the potential to indicate the causative pathways selecting for the observed bacterial community structure in soils.

16S rRNA gene↗

Shifts in the swine nasal microbiota following Bordetella bronchiseptica challenge in a longitudinal study

Bordetella bronchiseptica is a widespread, highly infectious bacterial pathogen that causes respiratory disease in swine and increases the severity of respiratory infections caused by other viral or bacterial pathogens. However, the impact of B. bronchiseptica infection on the swine respiratory microbiota has not been thoroughly investigated. Here, we aim to assess the influence of B. bronchiseptica infection on the community structure and abundance of members of the swine nasal microbiota. To do so, the nasal microbiota of a non-infected control group and a group infected with B. bronchiseptica (BB group) were characterized prior to B. bronchiseptica strain KM22 challenge (day 0) and on selected days in the weeks following B. bronchiseptica challenge (days 1, 3, 7, 10, 14, 21, 36, and 42). Bordetella bronchiseptica was cultured from nasal samples of the BB group to assess nasal colonization. The results showed that B. bronchiseptica colonization did not persistently affect the nasal bacterial diversity of either of the treatment groups (alpha diversity). However, the bacterial community structures (beta diversity) of the two treatment groups significantly diverged on day 7 when peak colonization levels of B. bronchiseptica were detected. This divergence continued through the last sampling time point. In addition, Pasteurella, Pasteurellaceae (unclassified), Mycoplasma, Actinobacillus, Streptococcus, Escherichia-Shigella, and Prevotellaceae (unclassified) showed increased abundances in the BB group relative to the control group at various time points. This study revealed that B. bronchiseptica colonization can disturb the upper respiratory tract microbiota, and further research is warranted to assess how these disturbances can impact susceptibility to secondary infections by other respiratory pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗

Plant-Nitrifier Interactions in Topsoil and Subsoil

Plants can influence soil microbes through resource acquisition and interference competition, with consequences for ecosystem function such as nitrification. However, how plants alter soil conditions to influence nitrifiers and nitrification rates remains poorly understood, especially in the subsoil. Here, coupling the 15N isotopic pool dilution technique, high throughput sequencing and in situ soil O2 monitoring, we investigated how a deep-rooted perennial grass, miscanthus, versus an adjacent shallow-rooted turfgrass reference shapes nitrifier assembly and function along 1 m soil profiles. In topsoil, the suppression of ammonia (NH3) oxidizing archaea (AOA) and gross nitrification rates in miscanthus relative to the reference likely resulted from nitrifiers being outcompeted by plant roots and heterotrophic bacteria for ammonium (NH4+). The stronger tripartite competition under miscanthus may have been caused in part by the lower soil organic matter (SOM) content, which supported lower gross nitrogen (N) mineralization, the major soil process that produces NH4+. In contrast, below 10 cm soil depth, significantly greater gross nitrification rates were observed in miscanthus compared to the reference. This was likely driven by the significantly lower oxygen (O2) in miscanthus than reference subsoil, which selected against aerobic heterotrophic bacteria but in favor of AOA. Overall, we found that plants can regulate AOA community structure and function through different mechanisms in topsoil and subsoil, with suppression of nitrification in topsoil and enhancement of nitrification in subsoil.

Field Data↗

Habitat severity characteristics structure soil communities at regional and local spatial scales along the Antarctica Peninsula

Antarctic soils provide an excellent setting to test biogeographical patterns across spatial and environmental scales given their relatively simple communities and the dominance of physical factors that create strong environmental gradients. Additional urgency is given by the fact that their unique terrestrial communities are the subject of conservation efforts in a rapidly changing environment. We investigated relationships of soil community assembly and alpha and beta diversity with climatic and environmental parameters across regional and local scales in Maritime Antarctica. We sampled from a regional gradient of sites that differ in habitat severity, ranging from relatively favourable to harsher physicochemical conditions. At the regional scale, bacterial community characteristics and microarthropod abundance varied along this severity gradient, but most measures of fungal communities did not. Microarthropod and microbial communities differed in which soil and climate parameters were most influential, and the specific parameters that influenced each taxon differed across broad and fine spatial scales. This suggests that conservation efforts will need to focus on a large variety of habitat characteristics to successfully encompass diversity across taxa. Because beta diversity was the result of species turnover, conservation efforts also cannot focus on only the most biodiverse sites to effectively preserve all aspects of biodiversity.

54 ENVIRONMENTAL SCIENCES↗

Microbial communities and biogeochemical functioning across peatlands in the Athabasca Oil Sands region of Canada: Implications for reclamation and management

Abstract Peatlands play an important role in global biogeochemical cycles and are essential for multiple ecosystem functions. Understanding the environmental drivers of microbial functioning and community structure can provide insights to enable effective and evidence‐based management. However, it remains largely unknown how microbial diversity contributes to the functioning of belowground processes. Addressing this gap in knowledge will provide a better understanding of microbial‐mediated processes in peatlands that are undergoing restoration or reclamation. This study assessed the changes in microbial community diversity and structure as well as soil function by measuring microbial respiration on a range of substrates from three natural fen types found in the Athabasca Oil Sands region of Alberta, Canada (a poor fen, a hypersaline fen, and a tree‐rich fen) and a nearby constructed fen undergoing reclamation following open pit mining. Overall, substrate induced respiration was significantly higher in the constructed fen. Alpha diversity of fungi and prokaryotes was highest in the tree‐rich fen, and the composition of microbial communities was significantly different between fens. Both fungal and prokaryotic communities were strongly related to pore water pH and temperature, with plant richness also contributing to the shape of fungal communities. In summary, microbial community structure reflects the underlying differences in soil condition across different fens but plays essential roles in the ecological functions of soil. These findings provide a new outlook for the management of peatlands undergoing post‐mining reclamation. Future research on peatland reclamation should consider the dynamic interaction between communities and ecosystem functionality, for which this study forms a useful baseline.

54 ENVIRONMENTAL SCIENCES↗

Plankton energy flows using a global size-structured and trait-based model

Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Social network structure and the spread of complex contagions from a population genetics perspective

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

59 BASIC BIOLOGICAL SCIENCES↗

Microbes display broad diversity in cobamide preferences

ABSTRACT Cobamides, the vitamin B 12 (cobalamin) family of cofactors, are used by most organisms but produced by only a fraction of prokaryotes, and are thus considered key shared nutrients among microbes. Cobamides are structurally diverse, with multiple different cobamides found in most microbial communities. The ability to use different cobamides has been tested for several bacteria and microalgae, and nearly all show preferences for certain cobamides. This approach is limited by the commercial unavailability of cobamides other than cobalamin. Here, we have extracted and purified seven commercially unavailable cobamides to characterize bacterial cobamide preferences based on growth in specific cobamide-dependent conditions. The tested bacteria include engineered strains of Escherichia coli , Sinorhizobium meliloti , and Bacillus subtilis expressing native or heterologous cobamide-dependent enzymes, cultured under conditions that functionally isolate specific cobamide-dependent processes such as methionine synthesis. Comparison of these results to those of previous studies of diverse bacteria and microalgae revealed that a broad diversity of cobamide preferences exists not only across different organisms but also between different cobamide-dependent metabolic pathways within the same organism. The microbes differed in the cobamides that support growth most efficiently, cobamides that do not support growth, and the minimum cobamide concentrations required for growth. The latter differ by up to four orders of magnitude across organisms from different environments and by up to 20-fold between cobamide-dependent enzymes within the same organism. Given that cobamides are shared, required for use of specific growth substrates, and essential for central metabolism in certain organisms, cobamide preferences likely impact community structure and function. IMPORTANCE Nearly all bacteria are found in microbial communities with tens to thousands of other species. Molecular interactions such as metabolic cooperation and competition are key factors underlying community assembly and structure. Cobamides, the vitamin B 12 family of enzyme cofactors, are one such class of nutrients, produced by only a minority of prokaryotes but required by most microbes. A unique aspect of cobamides is their broad diversity, with nearly 20 structural forms identified in nature. Importantly, this structural diversity impacts growth as most bacteria that have been tested show preferences for specific cobamide forms. We measured cobamide-dependent growth in several model bacteria and compared the results to those of previous analyses of cobamide preference. We found that cobamide preferences vary widely across bacteria, showing the importance of characterizing these aspects of cobamide biology to understand the impact of cobamides on microbial communities.

Mok, Kenny C. (ORCID:0000000252276987)↗

Synthetic communities as a model for determining interactions between a biofertilizer chassis organism and native microbial consortia

Biofertilizers are critical for sustainable agriculture because they can replace ecologically disruptive chemical fertilizers while improving the trajectory of soil and plant health. However, for improving deployment, the persistence of biofertilizers within native soil consortia must be elucidated and enhanced. In this study we characterized a high-throughput, modular, and automation-friendly in vitro approach to screen for biofertilizer persistence within soil-derived consortia after co-cultivation with stable synthetic soil microbial communities (SynComs) obtained through a top-down cultivation process. Here, we profiled ~1200 SynComs isolated from various soil sources and cultivated in divergent media types, and we detected significant phylogenetic diversity (e.g. Shannon index >4) and richness (observed richness >400) across these communities. We observed high reproducibility in SynCom community structure from common soil and media types, which provided a testbed for assessing biofertilizer persistence within representative native consortia. Furthermore, we demonstrated that the screening method described herein can be coupled with microbial engineering to efficiently identify soil-derived SynComs in which an engineered biofertilizer organism (i.e. Bacillus subtilis) persists. Accordingly, we discovered that B. subtilis persisted in ~10% of SynComs that generally followed the diversity–invasion principle. Additionally, our approach enabled analysis of the ecological impact of B. subtilis inoculation on SynCom structure and profile alterations in community diversity and richness associated with the presence of a genetically modified model bacterium. Ultimately, this work has established a modular pipeline that could be integrated into a variety of microbiology/microbiome-relevant workflows or related applications that would benefit from assessment of the persistence of a specific organism of interest and its interaction with native consortia.

biofertilizers↗

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Metatranscriptomic analysis reveals dissimilarity in viral community activity between an ice-free and ice-covered winter in Lake Erie

Winter is a relatively under-studied season in freshwater ecology. The paucity of wintertime surveys has led to a lack of knowledge regarding microbial community activity during the winter in Lake Erie, a North American Great Lake. Viruses shape microbial communities and regulate biogeochemical cycles by acting as top-down controls, yet very few efforts have been made to examine active virus populations during the winter in Lake Erie. Furthermore, climate change-driven declines in seasonal ice cover have been shown to influence microbial community structure, but no studies have compared viral community activity between different ice cover conditions. We surveyed surface water metatranscriptomes for viral hallmark genes as a proxy for active virus populations and compared activity metrics between ice-covered and ice-free conditions from two sampled winters. Transcriptionally active viral communities were detected in both winters, spanning diverse phylogenetic clades of putative bacteriophage (Caudoviricetes), giant viruses (Nucleocytoviricota, or NCLDV), and RNA viruses (Orthornavirae). However, viral community activity metrics revealed pronounced differences between the ice-covered and ice-free winters. Viral community composition was distinct between winters and viral hallmark gene richness was reduced in the ice-covered relative to the ice-free conditions. In addition, the observed differences in viral communities correlated with microbial community activity metrics. Overall, these findings contribute to our understanding of the viral populations that are active during the winter in Lake Erie and suggest that viral community activity may be associated with ice cover extent.

59 BASIC BIOLOGICAL SCIENCES↗