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78 records · Page 5

Dispersal, habitat filtering, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography

Abstract Wetlands store 20–30% of the world’s soil carbon, and identifying the microbial controls on these carbon reserves is essential to predicting feedbacks to climate change. Although viral infections likely play important roles in wetland ecosystem dynamics, we lack a basic understanding of wetland viral ecology. Here 63 viral size-fraction metagenomes (viromes) and paired total metagenomes were generated from three time points in 2021 at seven fresh- and saltwater wetlands in the California Bodega Marine Reserve. We recovered 12,826 viral population genomic sequences (vOTUs), only 4.4% of which were detected at the same field site two years prior, indicating a small degree of population stability or recurrence. Viral communities differed most significantly among the seven wetland sites and were also structured by habitat (plant community composition and salinity). Read mapping to a new version of our reference database, PIGEONv2.0 (515,763 vOTUs), revealed 196 vOTUs present over large geographic distances, often reflecting shared habitat characteristics. Wetland vOTU microdiversity was significantly lower locally than globally and lower within than between time points, indicating greater divergence with increasing spatiotemporal distance. Viruses tended to have broad predicted host ranges via CRISPR spacer linkages to metagenome-assembled genomes, and increased SNP frequencies in CRISPR-targeted major tail protein genes suggest potential viral eco-evolutionary dynamics in response to both immune targeting and changes in host cell receptors involved in viral attachment. Together, these results highlight the importance of dispersal, environmental selection, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography.

Environmental Sciences & Ecology↗

The Switchgrass Microbiome: A Review of Structure, Function, and Taxonomic Distribution

Switchgrass (Panicum virgatum L.) has been championed as a promising bioenergy crop due to its high productivity across a wide environmental range. The switchgrass microbiome—including bacteria, archaea, fungi, and other microbiota inhabiting soil and plant tissues—can influence plant function substantially. We conducted a review of the literature investigating switchgrass microbiome structure, key functional roles, and taxa isolated from field-grown plants. Although site conditions and plant compartment (i.e., location within shoots, roots, or root-influenced soil) appear to be the strongest drivers of switchgrass microbiome structure, the microbiome is also shaped by climate, season, and host genotype. Studies comparing across plant species show that the switchgrass microbiome is more similar to the microbiomes of other perennial plants than to the microbiomes of annual plants. Members of the switchgrass microbiome confer several benefits to their host. Most notably, mycorrhizal fungi can increase plant biomass many-fold, associative nitrogen-fixing bacteria can provide a substantial portion of the plant’s nitrogen demand, and fungal endophytes can improve plant tolerance to drought. Although the fungi and bacteria cultured from switchgrass represent only a portion of the microbiome, these serve as a valuable resource for researchers interested in investigating functional outcomes of the switchgrass microbiome. We highlight areas where additional research is necessary for a more comprehensive understanding of switchgrass microbiome structure, function, and potential to enhance sustainable bioenergy production. Key gaps include the role of understudied organisms (e.g., viruses, microeukaryotes, and nonmycorrhizal fungi), multitrophic relationships, mechanisms underpinning switchgrass–microbiome interactions, and field-scale validation of experimental findings.

54 ENVIRONMENTAL SCIENCES↗

A Genomic Catalogue of Earth’s Microbiomes - Introductory KBase Narrative

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled unprecedented insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this powerful approach to over 10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, human- and animal-host associated microbiomes, engineered environments, and natural and agricultural soils to capture extant microbial metabolic and functional potential. We present a comprehensive catalogue of 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units (OTUs), spanning 135 phyla, which expand the known phylogenetic diversity of Bacteria and Archaea by 44%. We also demonstrate the utility of this collection for secondary metabolite biosynthetic potential and predicting host-virus linkage, which can provide a view into the global distribution of lysogenic viruses. This resource underscores the value of leveraging genome-centric approaches to reveal genomic properties of uncultivated microbes that impact on ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Increasing Mosquito Abundance Under Global Warming

Mosquitoes are a key virus vector that poses significant health threats globally, affecting 700 million individuals and causing 1 million deaths annually. Accurately predicting mosquito abundance and dispersion remains a challenge. Complex interactions between mosquito dynamics and various environmental factors, notably hydrology, contribute to this challenge. Existing models typically focus on precipitation and temperature and often overlook further impacts of hydrological variables within mosquito modeling. In this study, we developed an artificial intelligence‐based model for mosquito dynamics, explicitly accounting for different hydrological variables, such as precipitation, soil moisture and streamflow. Using Toronto, Canada, as a case study, we identified causal relationships between changes in mosquito populations, hydrological factors, vegetation (e.g., leaf area index), and climate variables (e.g., daylight length, precipitation, and temperature). We embedded these relationships into a Long Short‐Term Memory (LSTM) Neural Network Model capable of accurately detecting mosquito dynamics across annual, seasonal, and monthly time scales. The LSTM is able to explain, on average, approximately 40% of the variance in the observed mosquito abundance data. Using the calibrated model, we predicted that the summer season mosquito abundance would increase by ∼16% and ∼19% under an intermediate greenhouse emission scenario, Shared Socioeconomic Pathway (SSP) 2–4.5, and a high greenhouse emission scenario, SSP5‐8.5, respectively. We expect that this model can serve as a valuable tool and inform science‐based decisions affecting mosquito dynamics and public health. It can also build a foundation for future risk analysis at the regional and larger scales.

54 ENVIRONMENTAL SCIENCES↗

A genomic catalog of Earth’s microbiomes

Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial Community Analysis & Functional Evaluation in Soils

The overall objective of this proposal was to develop technologies to alter the composition and function of important members of microbial communities. In particular, the overall objective of the microbial community editing portion of the proposal focuses on developing foundational tools and understanding required to predict, alter and design grass rhizosphere communities impacting DOE missions. Specifically, the project is centered on the Microbial Community Analysis & Functional Evaluation in Soils (m-CAFES) to manipulate microbial consortia associated with plants of interest for the bioenergy sector, under the presumption that bacterial communities can be manipulated to enhance plant health. For tasks of specific interest to us, we are focusing on developing novel Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) based technologies (primarily focusing on Aim 1) and their delivery modalities (notably subaim 1.2) to edit specific bacterial genomes of interest to enhance their functionalities, and programmably ablate specific undesirable members of bacterial communities for plant health. We are focusing on engineering bacteriophages (bacterial viruses, for subaim 1.2) to carry programmable CRISPR-Cas systems (subaim 1.1) to target (ablate) or alter (edit) genomes of interest. This will enable us to carry out microbial perturbations that will impact community composition and function and ultimately plant growth and health, to enable the next phase of the project by deploying them in situ (subaims 1.3 and 1.4).

59 BASIC BIOLOGICAL SCIENCES↗