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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Microscale spatial distribution and soil organic matter persistence in top and subsoil

The spatial distribution of organic substrates and microscale soil heterogeneity significantly influence organic matter (OM) persistence as constraints on OM accessibility to microorganisms. However, it is unclear how changes in OM spatial heterogeneity driven by factors such as soil depth affect the relative importance of substrate spatial distribution on OM persistence. This work evaluated the decomposition and persistence of 13 C and 15 N labeled water-extractable OM inputs over 50 days as either hotspot (i.e., pelleted in 1–2 mm-size pieces) or distributed (i.e., added as OM < 0.07 μm suspended in water) forms in topsoil (0–0.2 m) and subsoil (0.8–0.9 m) samples of an Andisol. We observed greater persistence of added C in the subsoil with distributed OM inputs relative to hotspot OM, indicated by a 17% reduction in cumulative mineralization of the added C and a 10% higher conversion to mineral-associated OM. A lower substrate availability potentially reduced mineralization due to OM dispersion throughout the soil. NanoSIMS (nanoscale secondary ion mass spectrometry) analysis identified organo-mineral associations on cross-sectioned aggregate interiors in the subsoil. On the other hand, in the topsoil, we did not observe significant differences in the persistence of OM, suggesting that the large amounts of particulate OM already present in the soil outweighed the influence of added OM spatial distribution. Here, we demonstrated under laboratory conditions that the spatial distribution of fresh OM input alone significantly affected the decomposition and persistence of OM inputs in the subsoil. On the other hand, spatial distribution seems to play a lower role in topsoils rich in particulate OM. The divergence in the influence of OM spatial distribution between the top and subsoil is likely driven by differences in soil mineralogy and OM composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Anaerobic Dynamic Membrane Bioreactor Development to Facilitate Organic Waste Conversion to Medium-Chain Carboxylic Acids and Their Downstream Recovery

Platform chemicals such as medium-chain carboxylic acids (MCCAs) can be produced from organic waste streams via chain elongation in anaerobic mixed-culture bioreactors. A product recovery system is needed to collect MCCAs from the bioreactor effluent. Membrane-based liquid–liquid extraction, the most commonly used product recovery approach, requires suspended solids removal from the bioreactor effluent to avoid membrane fouling. An anaerobic dynamic membrane bioreactor (AnDMBR) was developed to evaluate MCCA production from brewery and prefermented food waste and to produce a permeate with low suspended solids to facilitate downstream product recovery. The AnDMBR employed an inexpensive stainless-steel mesh as the support material for the development of a biofilm or dynamic membrane, which was responsible for solids–liquid separation. The AnDMBR produced a permeate quality with an average total suspended solids (TSS) concentration of 0.12 g L –1 , while the average bioreactor TSS concentration was two orders of magnitude higher (21.6 g L –1 ). A maximum solids removal efficiency of ≥99% was achieved and good permeate quality was sustained for over 200 days without fouling control or cleaning the support material. In addition to solids–liquid separation, the dynamic membrane was responsible for a substantial fraction of the biological activity of the AnDMBR. The relative activity of Clostridiales, as determined by 16S rRNA sequencing, correlated with MCCA production and was higher in the dynamic membrane (20.0 ± 4.9%) than in the suspended biomass (5.2 ± 2.7%) in the bioreactor. This observation was consistent with MCCA production data as the permeate MCCA concentrations were significantly (p = 8.2 × 10 –5 ) higher than that in the bioreactor, suggesting that the dynamic membrane biofilm contributed to chain elongation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A bacterial toolkit for plants

Here, we highlight efforts to engineer microorganisms and their plant hosts to address the challenges of sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Salivary microbiome composition changes after bariatric surgery

Recent studies show that the salivary microbiome in subjects with obesity differ from those without obesity, but the mechanism of interaction between the salivary microbiome composition and body weight is unclear. Herein we investigate this relation by analyzing saliva samples from 35 adult patients with obesity undergoing bariatric surgery. Our aim was to describe salivary microbiome changes during body weight loss on an individual-specific level, and to elucidate the effect of bariatric surgery on the salivary microbiome which has not been studied before. Analysis of samples collected before and 1 day after surgery, as well as 3 and 12 months after surgery, showed that the salivary microbiome changed in all study participants, but these changes were heterogeneous. In the majority of participants proportions of Gemella species, Granulicatella elegans, Porphyromonas pasteri, Prevotella nanceiensis and Streptococcus oralis decreased, while Veillonella species, Megasphaera micronuciformis and Prevotella saliva increased. Nevertheless, we found participants deviating from this general trend which suggests that a variety of individual-specific factors influence the salivary microbiome composition more effectively than the body weight dynamics alone. The observed microbiome alternations could be related to dietary changes. Therefore, further studies should focus on association with altered taste preferences and potential oral health consequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metagenomic features of bioburden serve as outcome indicators in combat extremity wounds

Abstract Battlefield injury management requires specialized care, and wound infection is a frequent complication. Challenges related to characterizing relevant pathogens further complicates treatment. Applying metagenomics to wounds offers a comprehensive path toward assessing microbial genomic fingerprints and could indicate prognostic variables for future decision support tools. Wound specimens from combat-injured U.S. service members, obtained during surgical debridements before delayed wound closure, were subjected to whole metagenome analysis and targeted enrichment of antimicrobial resistance genes. Results did not indicate a singular, common microbial metagenomic profile for wound failure, instead reflecting a complex microenvironment with varying bioburden diversity across outcomes. Genus-level Pseudomonas detection was associated with wound failure at all surgeries. A logistic regression model was fit to the presence and absence of antimicrobial resistance classes to assess associations with nosocomial pathogens. A. baumannii detection was associated with detection of genomic signatures for resistance to trimethoprim, aminoglycosides, bacitracin, and polymyxin. Machine learning classifiers were applied to identify wound and microbial variables associated with outcome. Feature importance rankings averaged across models indicated the variables with the largest effects on predicting wound outcome, including an increase in P. putida sequence reads. These results describe the microbial genomic determinants in combat wound bioburden and demonstrate metagenomic investigation as a comprehensive tool for providing information toward aiding treatment of combat-related injuries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exabiome: Advancing Microbial Science through Exascale Computing

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Temporal dynamics of free‐living nitrogen fixation in the switchgrass rhizosphere

Abstract Free‐living nitrogen fixation (FLNF) represents an important terrestrial N source and is gaining interest for its potential to contribute plant available N to bioenergy cropping systems. Switchgrass, a cellulosic bioenergy crop, may be particularly reliant on FLNF when grown on low N systems, like marginal lands. However, the potential contributions of FLNF to switchgrass as well as the controls on this process are not well understood. In this study, we evaluated drivers of FLNF rates and N‐fixing microbial (diazotrophic) community composition in field‐grown switchgrass systems over two growing seasons with high temporal sampling. We found that climate variables are strong drivers of FLNF rates in switchgrass systems, compared to other environmental and biological factors including soil nutrients and diazotrophic community composition. Increased soil moisture availability generally promoted FLNF rates, but extreme rainfall events were detrimental. These climate‐related responses suggest a potential for loss of FLNF‐derived N contributions under projected climate shifts. We found a significant, but weak correlation between diazotrophic community composition and FLNF rates. We also observed a significant shift in the diazotrophic community composition between 2017 and 2018 and similarly measured a significant difference in FLNF rates between growing seasons. Lastly, we found that seasonal FLNF N contributions, based on measurement with high temporal resolution, has the potential to meet up to 80% of switchgrass N demands suggesting that FLNF measurements extrapolated from fewer time points or locations may underestimate these potential N contributions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗
DOE OSTI2020

Best Practices for Successfully Writing and Publishing a Genome Announcement in Microbiology Resource Announcements

Microbiology Resource Announcements (MRA) provides peer-reviewed announcements of scientific resources for the microbial research community. We describe the best practices for writing an announcement that ensures that these publications are truly useful resources. Adhering to these best practices can lead to successful publication without the need for extensive revisions.

Dunning Hotopp, Julie C.↗
DOE OSTI2026

Metagenomes and metagenome-assembled genomes from a nutrient removal plant at Los Angeles County Sanitation Districts (LACSD) that transitioned from high to low dissolved oxygen

Operating biological nutrient removal (BNR) wastewater treatment plants with low dissolved oxygen (DO) conditions can reduce energy costs. We report on five metagenomes and 492 metagenome-assembled genomes (MAGs) obtained from samples collected at the Pomona water reclamation plant before and after a DO reduction from 3.5 to 0.7 mg/L.

dissolved oxygen↗
DOE OSTI2022

Comparing western (Megascops kennicottii) and whiskered (M. trichopsis) screech-owl microbiomes in southern Arizona using a novel 16S rRNA sequencing method

Microbiomes are essential to a host’s physiology and health. Despite the overall importance of microbiomes to animal health, they remain understudied in wildlife. Microbiomes function as physical barriers to invading pathogens, and changes in the diversity or composition of microbes within a host may disrupt this barrier. In order to use microbiomes in wildlife ecology, knowledge of the natural variation within and among species is essential. We compare the diversity and composition of two avian species that share the same habitat and niche in our study area, the western screech-owl (Megascops kennicottii) and the whiskered screech-owl (M. trichopsis). We used a targeted 16S sequencing method to improve the taxonomic resolution of microbiomes. We found similar measures of alpha diversity between species and sample types (cloacal samples vs. fecal samples). However, there were significant differences in bacterial species richness among nestlings from different nest boxes, and the composition differed between the two bird species and among nestlings from different nest boxes. Western screech-owls had more variation in alpha diversity and composition and had fewer bacterial species in their core microbiome than whiskered screech-owls. Siblings are likely to yield similar findings for microbiomes; thus, sampling nestlings from different nests may be most informative for monitoring population-level changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Enabling depth resolved temporal resolved soil microbial sampling with novel vadose zone diffusion sampler

To address the difficulty in Earth system science in making time-course measurements of molecular signatures in soil biochemistry, we developed a soil stake system to sample and replace a defined soil analog medium, connected through hydraulic connectivity via perforated casings and modular inserts. We deployed these stakes to a site in Prosser, WA and measured microbial colonization of sterile sand-clay inserts enriched with N-acetyl-glucosamine at different depths over spring and summer. DNA and RNA analyses revealed distinct microbial recruitment and activity patterns. Inserts showed lower microbial diversity but higher abundance of Proteobacteriota and Bacteriota compared to native soils, alongside seasonal shifts in taxonomic and functional profiles. The soil stake system offers a novel approach for studying microbial dynamics across temporal and spatial scales.

58 GEOSCIENCES↗
DOE OSTI2020

SPRUCE Soil Metabolome Responses to Whole Ecosystem Warming in SPRUCE Experimental Plots Beginning in 2016

This dataset reports a suite of complementary environmental geochemical analyses of peat extracts and porewater samples from SPRUCE experimental plots across a range of whole ecosystem warming (WEW) temperature treatments beginning in 2016. Results of peat extract analyses include NMR and GC-MS analyses of central metabolites, liquid chromatography mass spectra (LC-MS) analyses of lipids, and quantitative proteomics. Porewater was analyzed by FTICR-MS for secondary metabolites, and for carbon dioxide (CO2), methane (CH4) concentrations, stable isotope composition, and the differential solubility corrected CO2:CH4 ratio. This dataset contains six files in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development and Validation of a Process Model and Open-Source Process Simulator for Microalgae-Based Tertiary Phosphorus Recovery

Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, the lack of validated mechanistic models and their implementation in process simulators have limited the adoption of this technology. In this study, an updated lumped pathway metabolic model (Phototrophic-Mixotrophic Process Model, PM 2 ), including both photoautotrophic and heterotrophic metabolisms of microalgae, was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design and simulation platform – for robust simulation under uncertainty. A global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experimental data and 45 days of continuous online monitoring data from a full-scale (568 m 3 ·d -1 ) microalgae-based tertiary wastewater treatment plant (EcoRecover process). In particular, along with dynamic influent composition, temperature and light intensity data with diel variation were provided as model inputs to reflect the microalgal behavior under day-night cycling. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L -1 , while also capturing the general trends of state variables according to nutrient availability.

Lumped pathway metabolic model↗