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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Protist diversity and community complexity in the rhizosphere of switchgrass are dynamic as plants develop

Abstract Background Despite their widespread distribution and ecological importance, protists remain one of the least understood components of the soil and rhizosphere microbiome. Knowledge of the roles that protists play in stimulating organic matter decomposition and shaping microbiome dynamics continues to grow, but there remains a need to understand the extent to which biological and environmental factors mediate protist community assembly and dynamics. We hypothesize that protists communities are filtered by the influence of plants on their rhizosphere biological and physicochemical environment, resulting in patterns of protist diversity and composition that mirror previously observed diversity and successional dynamics in rhizosphere bacterial communities. Results We analyzed protist communities associated with the rhizosphere and bulk soil of switchgrass (SG) plants ( Panicum virgatum ) at different phenological stages, grown in two marginal soils as part of a large-scale field experiment. Our results reveal that the diversity of protists is lower in rhizosphere than bulk soils, and that temporal variations depend on soil properties but are less pronounced in rhizosphere soil. Patterns of significantly prevalent protists groups in the rhizosphere suggest that most protists play varied ecological roles across plant growth stages and that some plant pathogenic protists and protists with omnivorous diets reoccur over time in the rhizosphere. We found that protist co-occurrence network dynamics are more complex in the rhizosphere compared to bulk soil. A phylogenetic bin-based null model analysis showed that protists’ community assembly in our study sites is mainly controlled by homogenous selection and dispersal limitation, with stronger selection in rhizosphere than bulk soil as SG grew and senesced. Conclusions We demonstrate that environmental filtering is a dominant determinant of overall protist community properties and that at the rhizosphere level, plant control on the physical and biological environment is a critical driver of protist community composition and dynamics. Since protists are key contributors to plant nutrient availability and bacterial community composition and abundance, mapping and understanding their patterns in rhizosphere soil is foundational to understanding the ecology of the root-microbe-soil system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Microbial life in 25-m-deep boreholes in ancient permafrost illuminated by metagenomics

This study describes the composition and potential metabolic adaptation of microbial communities in northeastern Siberia, a repository of the oldest permafrost in the Northern Hemisphere. Samples of contrasting depth (1.75 to 25.1 m below surface), age (from ~ 10 kyr to 1.1 Myr) and salinity (from low 0.1–0.2 ppt and brackish 0.3–1.3 ppt to saline 6.1 ppt) were collected from freshwater permafrost (FP) of borehole AL1_15 on the Alazeya River, and coastal brackish permafrost (BP) overlying marine permafrost (MP) of borehole CH1_17 on the East Siberian Sea coast. To avoid the limited view provided with culturing work, we used 16S rRNA gene sequencing to show that the biodiversity decreased dramatically with permafrost age. Nonmetric multidimensional scaling (NMDS) analysis placed the samples into three groups: FP and BP together (10–100 kyr old), MP (105–120 kyr old), and FP (> 900 kyr old). Younger FP/BP deposits were distinguished by the presence of Acidobacteriota, Bacteroidota, Chloroflexota_A, and Gemmatimonadota, older FP deposits had a higher proportion of Gammaproteobacteria, and older MP deposits had much more uncultured groups within Asgardarchaeota, Crenarchaeota, Chloroflexota, Patescibacteria, and unassigned archaea. The 60 recovered metagenome-assembled genomes and un-binned metagenomic assemblies suggested that despite the large taxonomic differences between samples, they all had a wide range of taxa capable of fermentation coupled to nitrate utilization, with the exception of sulfur reduction present only in old MP deposits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Abstract Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Deep-ultraviolet ptychographic pocket-scope (DART): mesoscale lensless molecular imaging with label-free spectroscopic contrast

The mesoscale characterization of biological specimens has traditionally required compromises between resolution, field-of-view, depth-of-field, and molecular specificity, with most approaches relying on external labels. Here we present the Deep-ultrAviolet ptychogRaphic pockeT-scope (DART), a handheld platform that transforms label-free molecular imaging through intrinsic deep-ultraviolet spectroscopic contrast. By leveraging biomolecules’ natural absorption fingerprints and combining them with lensless ptychographic microscopy, DART resolves down to 308-nm linewidths across centimeter-scale areas while maintaining millimeter-scale depth-of-field. The system’s virtual error-bin methodology effectively eliminates artifacts from limited temporal coherence and other optical imperfections, enabling high-fidelity molecular imaging without lenses. Through differential spectroscopic imaging at deep-ultraviolet wavelengths, DART quantitatively maps nucleic acid and protein distributions with femtogram sensitivity, providing an intrinsic basis for explainable virtual staining. We demonstrate DART’s capabilities through imaging of tissue sections, cytopathology specimens, blood cells, and neural populations, revealing detailed molecular contrast without external labels. The combination of high-resolution molecular mapping and broad mesoscale imaging in a portable platform opens new possibilities from rapid clinical diagnostics, tissue analysis, to biological characterization in space exploration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Estimating SHmax azimuth with P sources and vertical geophones: Use P-P reflection amplitudes or use SV-P reflection times?

We compared two methods for extracting the azimuth of maximum horizontal stress (SHmax) from 3D land-based seismic data generated by a P source and recorded with vertical geophones. In the first method, we used the direct-SV mode that is produced by all land-based P sources. P sources generate SV illumination that radiates in all azimuth directions from a source station and creates SV-P reflections that are recorded by vertical geophones. Unless stratigraphy has steep dip, SV-P raypaths recorded by vertical geophones are the reverse of P-SV raypaths recorded by horizontal geophones. Thus, SV-P data provide the same S-wave sensitivity to stress fields as popular P-SV data do. In the second method, we retrieved P-P reflections and then performed an amplitude-variation-with-azimuth (AVA) analysis of the amplitude-gradient behavior of P-P reflection wavelets. We did this analysis in narrow azimuth corridors to determine the gradient of reflection-wavelet amplitudes as a function of azimuth. This P-P AVA amplitude-gradient method has been of great interest in the reflection seismology community since it was introduced in the late 1990s. Each of these methods, AVA analysis of the gradient of P-P reflection amplitudes and azimuth-dependent arrival times of SV-P reflections, can be used to determine the azimuth of SHmax stress. We compare the results of the two methods with ground truth measurements of SHmax azimuth at a CO 2 sequestration site in the Michigan Basin. SHmax azimuths were determined from P-P and SV-P data at three major boundaries at depths of approximately 3500 ft (1067 m), 5500 ft (1676 m), and 7500 ft (2286 m). Two estimates of SHmax azimuth (one using SV-P data and one using P-P data) were made at each stacking bin inside a 24 mi 2 (62 km 2 ) image space. The result was approximately 98,000 estimates of SHmax azimuth across each of these three boundaries for each of these two prediction strategies. Histogram displays of PP AVA gradient estimates had peaks at correct azimuths of SHmax at all three depths, but the spread of the distributions widened with depth and split into two peaks at the deepest boundary. In contrast, each histogram of SHmax azimuth predicted by azimuth-dependent SV-P traveltimes had a single, definitive peak that was positioned at the correct SHmax azimuth at all three boundary depths.

Geochemistry & Geophysics↗
DOE OSTI2021

A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool

Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Compressive characterization of biphoton frequency spectra

Frequency-bin qudits constitute a promising tool for quantum information processing. Here we use compressive sensing to characterize the spectral correlations of entangled photon pairs in a quantum frequency comb, obtaining a 26-fold reduction in measurement time compared to raster scanning.

Simmerman, Emma↗
DOE OSTI2022

Bell state analyzer for spectrally distinct photons

We demonstrate a Bell state analyzer that operates directly on frequency mismatch. Based on electro-optic modulators and Fourier-transform pulse shapers, our quantum frequency processor design implements interleaved Hadamard gates in discrete frequency modes. Experimental tests on entangled-photon inputs reveal fidelities of ∼ <#comment/> 98 % <#comment/> for discriminating between the | Ψ <#comment/> + ⟩ <#comment/> and | Ψ <#comment/> − <#comment/> ⟩ <#comment/> frequency-bin Bell states. Our approach resolves the tension between wavelength-multiplexed state transport and high-fidelity Bell state measurements, which typically require spectral indistinguishability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

CMOS photonic integrated source of broadband polarization-entangled photons

We showcase a fully on-chip CMOS-fabricated silicon photonic integrated circuit employing a bidirectionally pumped microring and polarization splitter-rotators tailored for the generation of broadband (>9 THz), high-fidelity (90–98%) polarization-entangled photons. Spanning the optical C+L-band and producing over 116 frequency-bin pairs on a 38.4-GHz-spaced grid, this source is ideal for flex-grid wavelength-multiplexed entanglement distribution in multiuser networks.

42 ENGINEERING↗
DOE OSTI2020

Genomic Dissection of Anthracnose ( Colletotrichum sublineolum ) Resistance Response in Sorghum Differential Line SC112-14

Sorghum production is expanding to warmer and more humid regions where its production is being limited by multiple fungal pathogens. Anthracnose, caused by Colletotrichum sublineolum , is one of the major diseases in these regions, where it can cause yield losses of both grain and biomass. In this study, 114 recombinant inbred lines (RILs) derived from resistant sorghum line SC112-14 were evaluated at four distinct geographic locations in the United States for response to anthracnose. A genome scan using a high-density linkage map of 3,838 single nucleotide polymorphisms (SNPs) detected two loci at 5.25 and 1.18 Mb on chromosomes 5 and 6, respectively, that explain up to 59% and 44% of the observed phenotypic variation. A bin-mapping approach using a subset of 31 highly informative RILs was employed to determine the disease response to inoculation with ten anthracnose pathotypes in the greenhouse. A genome scan showed that the 5.25 Mb region on chromosome 5 is associated with a resistance response to nine pathotypes. Five SNP markers were developed and used to fine map the locus on chromosome 5 by evaluating 1,500 segregating F 2:3 progenies. Based on the genotypic and phenotypic analyses of 11 recombinants, the locus was narrowed down to a 470-kb genomic region. Following a genome-wide association study based on 574 accessions previously phenotyped and genotyped, the resistance locus was delimited to a 34-kb genomic interval with five candidate genes. All five candidate genes encode proteins associated with plant immune systems, suggesting they may act in synergy in the resistance response.

Genetics & Heredity↗
DOE OSTI2022

Modeled Hourly Tidal Current Velocities, Directions, and Heights from May 1 - September 1, 2005 at Two Points Near East Forelands and Tyonek in Cook Inlet, Alaska

This dataset includes modeled tidal current velocities, direction and depth at two locations in East and North Forelands (60.716, -151.434 and 61.024, -151.157) near Nikiski and Tyonek, respectively, in Cook Inlet, Alaska. Data from two grid cells were provided by the Pacific Northwest National Laboratory based on a tidal hydrodynamic model that characterized the tidal stream resources in Cook Inlet for a period from May 1 to September 1, 2005 (Wang and Yang 2020). The model grid size had a horizontal spatial resolution of 100 m at East Forelands and 200 m at Tyonek; mean sea level (MSL) depth was 47.9 m and 23.7 m at each respective site, and there were 10 depth bins that ranged in size with the tide from 4.3-5.2 m and 1.9-2.8 m, respectively (Wang and Yang 2020).

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Flux Histograms for 2017 Analysis

Flux for 2017 Analysis histograms for FHC and RHC:- The fluxes are integrated over the fiducial volume limited by -176 < X <177, -172 < Y < 179 and 25 < Z < 1150 cm. The fluxes are PPFX corrected, and both, the hadron production and focusing systematics are included (see docs 23441 and 17608 for more details).- These fluxes have been made with the official FHC (RHC) ND MC CAFAna files using the function DeriveFlux from CAFAna/XSec/Flux.*.- The root files have two types of histograms: flux_N and fractional_uncertainty_N, where N is the neutrino type. The entries are normalized by 10^6 POT, m2 and the bin width.- The text files contain tables of the flux normalized by 10^6 POT and m2.- The fractional uncertainties are made by the hadron production and beam focusing uncertainties added in quadrature. This corresponds to the sigma fraction respect to the central value and it meant to be used to make an uncertainty band (the covariance matrix is not included yet).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characterization of Soil and Rock Magnetic Properties along Multiple Hillslope Transects at Teller Road Site, Seward Peninsula, Alaska, 2018 and 2023

The magnetometer data was collected in multiple directions across the watershed hillslope at the NGEE Arctic Teller Road site at mile marker 27 (TL_MM27) on the Seward Peninsula, Alaska over multiple years in March 2018 and April 2023. The magnetic data were collected using a Geometrics Inc. G-858 gradiometer and G-857 base station in 2018 and the G-864 gradiometer and G857 base station in 2023. The data was collected (in all instances) by towing the gradiometer behind a snow machine around the watershed with the two sensors in a vertical profile with constant spacing during the continuous survey in that specific year. Magnetic total field measurements were collected by gradiometer and base station, and the data processing was performed in Geometrics MagMap2000 software. The processing steps were limited to removal of data spikes (despiking), reading dropouts, and correction/removal of bad GPS points. All offsets between sensors and GPS are stated within the data files and metadata, alongwith the processed and raw data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).In this data submission there are two sets of raw magnetic data (.bin and .stn for 2018 and base for 2023; raw rover mag for 2023 is in .csv) inside two .zip files that identify the year the mag data was collected. The data are proprietary format to Geometrics and can be opened and processed with MagMap2000 which can be downloaded for free at Geometrics website. There are also two processed data files *.csv for each year and two metadata files *.csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (August 2015)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken August 29, 2015 at a location (KB1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples from a deep soil pit were collected from 0 to 234 cm depth below surface at discrete depths every ~10-20 cm for microbial analyses. 13 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores).This dataset includes a zip file of 2216 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (June to October 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken at three time points from June 12, 2019 to October 23,2019 at a location (PTT1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples were collected from 60 to 180 cm below surface every 30cm for microbial analyses through metagenomic sequencing. 15 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 780 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (May to September 2017)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken roughly every month in the period May 18 to September 13 in 2017 at a location (Pit2) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were taken with a hand-auger and separated into 5-20 cm segments based on soil horizonation down to 150 cm depth below surface. Each segment was subsampled for microbial analyses. Corresponding 16S rRNA gene amplicon data is available at the NCBI Single Read Archive (SRA) Database BioProject ID PRJNA626616, and soil geochemistry data at doi:10.15485/1631972. 40 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 6993 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs generated from the Wind River Basin (WRB). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes measured at 3 depths during snowmelt period in East River, CO (March, May, and June, September 2017)

Snowmelt is a critical biogeochemical period that accounts for large nitrogen (N) export events from high-elevation watersheds. Soil microbial populations bloom and immobilize N during snowmelt, yet the population size crashes in spring, which releases a pulse of soil N. We sought to discover the N sources fueling this microbial bloom and determine the fate of N following microbial die-off. Here, focusing on the snowmelt period within a headwater catchment of the Upper Colorado River Basin (East River, CO), we deployed strain-resolved metagenomics to identify the metabolic pathways and processes that mobilize soil N during and after snowmelt. Soil metagenome samples were taken from 6 snowpits from 3 depths (0-5cm, 5-15cm, >15cm) at 4 time points during snowmelt period (March 2017, May 2017, and June 2017, September 2017) generating 48 metagenomes. We reconstructed 474 metagenome-assembled genomes (MAGs) across all metagenomes.All 48 metagenomes were sequenced at JGI and raw data can be found under JGI (Joint Genome Institute) GOLD Study Gs0135149. Metagenome assemblies from IMG under the same study were used for genome binning. This dataset (1) a zip file of 474 MAGs (as fasta files, Gs0135149_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0135149.kml), (4) metagenome metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (metagenomes.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗