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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sulfate adenylyl transferase kinetics and mechanisms of metabolic inhibitors of microbial sulfate respiration

Abstract Sulfate analog oxyanions that function as selective metabolic inhibitors of dissimilatory sulfate reducing microorganisms (SRM) are widely used in ecological studies and industrial applications. As such, it is important to understand the mode of action and mechanisms of tolerance or adaptation to these compounds. Different oxyanions vary widely in their inhibitory potency and mechanism of inhibition, but current evidence suggests that the sulfate adenylyl transferase/ATP sulfurylase (Sat) enzyme is an important target. We heterologously expressed and purified the Sat from the model SRM, Desulfovibrio alaskensis G20. With this enzyme we determined the turnover kinetics (kcat, KM) for alternative substrates (molybdate, selenate, arsenate, monofluorophosphate, and chromate) and inhibition constants (KI) for competitive inhibitors (perchlorate, chlorate, and nitrate). These measurements enable the first quantitative comparisons of these compounds as substrates or inhibitors of a purified Sat from a respiratory sulfate reducer. We compare predicted half-maximal inhibitory concentrations (IC50) based on Sat kinetics with measured IC50 values against D. alaskensis G20 growth and discuss our results in light of known mechanisms of sensitivity or resistance to oxyanions. This analysis helps with the interpretation of recent adaptive laboratory evolution studies and illustrates the value of interpreting gene–microbe–environment interactions through the lens of enzyme kinetics.

Carlson, Hans K. (ORCID:0000000215835313)↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2024

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗
DOE OSTI2026

From microbial diversity to functional potential using dimensionality reduction

The high dimensionality of microbial diversity data from ‘omics observations can be reduced using Machine Learning, with many recent studies showcasing ML utility for exploratory ecological feature finding and process prediction. Here, we compare the Self Organizing Map (SOM) dimensionality reduction method to the well-documented sample-based Principal Coordinate Analysis (PCoA) and taxa-based Weighted Gene Correlation Network Analysis (WGCNA) using near daily 16S rRNA gene amplicon sequencing data from the 2019 to 2020 MOSAiC International Arctic Drift Expedition. We then map k-means clustering outputs from each method to available metagenomes, extracting functionally distinct seasonal microbial ecotypes in the surface Arctic Ocean. Our results indicate the SOM method better represented expected seasonal transitions and identified a greater number of metabolically distinct functional groups than the more traditional PCoA ordination. Ultimately, we identified four community ecotypes with distinct taxonomic and functional cut-offs driven by seasonality, water mass, and substrate turnover, highlighting the importance of succession in functional diversity for the central Arctic Ocean. These results reinforce ML dimensionality reduction as a meaningful translator in the mining of historical amplicon datasets to address modern mechanistic questions and potentially provide ’omics informed ecotype diversity to leverage in mechanistic biogeochemical models.

Arctic Ocean↗
DOE OSTI2025

From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing

Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.

Petzold, Christopher J↗
DOE OSTI2020

Metagenomic Alterations in Gut Microbiota Precede and Predict Onset of Colitis in the IL10 Gene-Deficient Murine Model

SUMMARY. Currently, predictive markers for the development andcourse of inflammatory bowel diseases (IBD) are not available. This study supports the notion that gut microbiome metagenomic profiles could be developed into a useful tool to assess risk and manage human IBD. BACKGROUND & AIMS: Inflammatory bowel diseases (IBD) are chronic inflammatory disorders where predictive bio-markers for the disease development and clinical course are sorely needed for development of prevention and early intervention strategies that can be implemented to improve clinical outcomes. Since gut microbiome alterations can reflect and/or contribute to impending host health changes, we examined whether gut microbiota metagenomic profiles would provide more robust measures for predicting disease outcomes in colitis-prone hosts. METHODS: Using the interleukin (IL) 10 gene-deficient (IL10KO) murine model where early life dysbiosis from antibiotic (cefoperozone [CPZ]) treated dams vertically transferred to pups increases risk for colitis later in life, we investigated temporal metagenomic profiles in the gut microbiota of post-weaning offspring and determined their relationship to even-tual clinical outcomes. RESULTS: Compared to controls, offspring acquiring maternalCPZ-induced dysbiosis exhibited a restructuring of intestinal microbial membership in both bacteriome and mycobiome that was associated with alterations in specific functional subsystems. Furthermore, among IL10 KO offspring fromCPZ-treated dams, several functional subsystems, particularly nitrogen metabolism, diverged between mice that developed spontaneous colitis (CPZ-colitis) versus those that did not (CPZ-no-colitis) at a time point prior to eventual clinical outcome. CONCLUSIONS: Our findings provide support that functional metagenomic profiling of gut microbes has potential and promise meriting further study for development of tools to assess risk and manage human IBD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in Escherichia coli

Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

FriendlyNets

FriendlyNets provides a method for assessing the promotion/inhibition effect on a microbe of a microbial community using a network of community interactions. At its core, FriendlyNets judges how much a network promotes or inhibits one of its nodes. It does this by assuming a set of dynamical systems represented by the network and using the resulting dynamics. FriendlyNets is also packaged with functions for generating a network from a set of genome-scale metabolic models (commonly called GSMs or GEMs) by simulating pairwise growth.

Brunner, James↗
DOE OSTI2024

Godzilla mineral dust and La Soufrière volcanic ash fallout immediately stimulate marine microbial phosphate uptake

During the “Godzilla” dust storm of June 2020, unusually high fluxes of mineral dust traveled across the Atlantic from the Sahara Desert, reaching the Caribbean Basin, Gulf Coast, and southeastern United States. Additionally, an eruption of the La Soufrière volcano on St. Vincent in April 2021 generated substantial ashfall in the southeastern Caribbean. While many studies have analyzed mineral dust’s ability to relieve nutrient limitation of phosphorus (P) in the P-stressed North Atlantic, less is known about the impact of extreme events and other natural aerosols on fluxes of P into seawater and from seawater into marine microbial cells. We quantified P and iron (Fe) content in mineral dust from the Godzilla dust storm and volcanic ash from the La Soufrière eruption collected at Ragged Point, Barbados. We also performed seawater incubations to assess the marine microbial response to aerosol deposition. Using environmentally-relevant concentrations of atmospheric particles for within the ocean’s mixed layer allowed us to draw realistic conclusions about how these deposition events impacted P cycling in situ. Volcanic ash has lower P content than mineral dust, and P in volcanic ash is far less soluble (~1%) than assumed in current atmospheric deposition models. Adding mineral dust and the volcanic ash leachate in concentrations representing different deposition scenarios increased soluble reactive phosphorus (SRP) concentrations in coastal seawater by ~7-32 nM. Phosphate uptake rate was stimulated in coastal seawater after either mineral dust or volcanic ash deposition at aerosol concentrations relevant to the Godzilla dust event, with ash eliciting the fastest uptake rate. Furthermore, high concentrations of both the mineral dust and volcanic ash led to slightly elevated alkaline phosphatase activity (APA) compared to the relevant controls, indicating higher potential for use of dissolved organic phosphorus (DOP) as a P source. Quantifying these aerosols’ impacts on P cycling is a significant step towards achieving a better understanding of their potential roles in relieving nutrient limitation and fueling the biological carbon pump.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Results of the Micro-12 Flight Experiment: Effects of Microgravity on Shewanella oneidensis MR-1

The Micro-12 flight experiment was launched on SpaceX-15 and completed during berthing on the International Space Station. The goal of this experiment was to understand the effects of spaceflight and microgravity on the physiology of the model exoelectrogen Shewanella oneidensis MR-1. BioServe Fluid Processing Apparatus (FPA) and Group Activation Pack (GAP) hardware systems were used for both flight and ground control tests. Under spaceflight conditions, extracellular electron transfer (EET) rates were found to be significantly increased on insoluble substrates, while biofilm development appeared to be unchanged under the conditions tested; these processes are critical for microbial-assisted bioelectrochemical systems. Additionally, RNAseq analysis, proteomic profiling, and competitive mutant fitness profiling were performed to gain further understanding of microbial physiology under EET-respiring conditions during spaceflight. Overall, the results of the Micro-12 project support the idea that Shewanella oneidensis MR-1, in particular, and exoelectrogens in general could be useful chassis organisms for synthetic biology applications using microbial bioelectrochemical systems. These findings will assist bioengineering and synthetic biology development efforts harnessing the unique capabilities of exoelectrogens for life support and in situ resource utilization.

Dougherty, Michael↗
NASA NTRSDate not supplied

NASA GeneLab: Open Science for Life in Space

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 350 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab Sequencing Lab. The GLDS contains rich metadata about each experiment and has integrated radiation dosimetry data from experiments flown on the Space Shuttle, International Space Station, and Free Flying spacecrafts. With the increasing amount and complexity of omics data being generated, GeneLab utilizes community-defined, common models for metadata and terminology so that omics data and results are discoverable and reliably reproducible. GeneLab uses the ISA-Tab specification and semantic model for organizing and representing omics metadata. In addition to metadata standards, data files must be open-source file or common exchange formats to ensure accessibility and usability by all users. To ease data ingestion and transfer, the web-based submission tool allows PIs a user-friendly user interface to curate, organize, and publish their space relevant omics data. In the more recent years, data curation and submission portal has incorporated the FAIR principles making data findable, accessible, interoperable, and reusable. To increase reusability of data, GeneLab has implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 200 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. To train the next generation of scientists, NASA offers training programs such as GeneLab 4 High School (GL4HS) and GeneLab 4 Universities. NLM Curation at a Scale Workshop 2022 | NASA GeneLab (GL4U) to teach students bioinformatics and computational biology methods to analyze omics data. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

GeneLab↗
DOE OSTI2022

Long-term nitrogen deposition enhances microbial capacities in soil carbon stabilization but reduces network complexity

Background: Anthropogenic activities have increased the inputs of atmospheric reactive nitrogen (N) into terrestrial ecosystems, affecting soil carbon stability and microbial communities. Previous studies have primarily examined the effects of nitrogen deposition on microbial taxonomy, enzymatic activities, and functional processes. Here, we examined various functional traits of soil microbial communities and how these traits are interrelated in a Mediterranean type grassland administrated with 14 years of 7 g m –2 year –1 of N amendment, based on estimated atmospheric N deposition in areas within California, USA, by the end of the twenty-first century. Results: Soil microbial communities were significantly altered by N deposition. Consistent with higher aboveground plant biomass and litter, fast-growing bacteria, assessed by abundance-weighted average rRNA operon copy number, were favored in N deposited soils. The relative abundances of genes associated with labile carbon (C) degradation (e.g., amyA and cda) were also increased. In contrast, the relative abundances of functional genes associated with the degradation of more recalcitrant C (e.g., mannanase and chitinase) were either unchanged or decreased. Compared with the ambient control, N deposition significantly reduced network complexity, such as average degree and connectedness. The network for N deposited samples contained only genes associated with C degradation, suggesting that C degradation genes became more intensely connected under N deposition. Conclusions: We propose a conceptual model to summarize the mechanisms of how changes in above- and belowground ecosystems by long-term N deposition collectively lead to more soil C accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling

Rice paddies significantly contribute to atmospheric methane (CH 4 ). Here, we show that two independent rice genotypes overexpressing genes for PLANT PEPTIDES CONTAINING SULFATED TYROSINE (PSY) reduce cumulative CH 4 emissions by 38% (PSY1) and 58% (PSY2) over 70 days of growth compared with controls. Genome-resolved metatranscriptomic data from PSY rhizosphere soils reveal lower ratios of gene activities for (mostly hydrogenotrophic) CH 4 production versus consumption, decreased activity of H 2 -producing genes, and increased activity of bacterial H 2 oxidation pathways. Metabolic modeling using metagenomic and metabolomic data predicts elevated H 2 oxidation and suppressed H 2 production in the PSY rhizosphere. Assembled genomes of rhizosphere H 2 -oxidizing bacteria are enriched in genes utilizing gluconeogenic acids compared with H 2 -producing counterparts, and their activities are likely stimulated by elevated levels of gluconeogenic acids, primarily amino acids, in PSY root exudates. Overall, our study indicates that decreased CH 4 emissions are due to a lower amount of H 2 available for hydrogenotrophic methanogenesis and provides a powerful strategy to mitigate CH 4 emissions from increasingly widespread rice cultivation.

Biological and medical sciences↗
DOE OSTI2022

Low 13 C- 13 C abundances in abiotic ethane

Distinguishing biotic compounds from abiotic ones is important in resource geology, biogeochemistry, and the search for life in the universe. Stable isotopes have traditionally been used to discriminate the origins of organic materials, with particular focus on hydrocarbons. However, despite extensive efforts, unequivocal distinction of abiotic hydrocarbons remains challenging. Recent development of clumped-isotope analysis provides more robust information because it is independent of the stable isotopic composition of the starting material. Here, we report data from a 13 C- 13 C clumped-isotope analysis of ethane and demonstrate that the abiotically-synthesized ethane shows distinctively low 13 C- 13 C abundances compared to thermogenic ethane. A collision frequency model predicts the observed low 13 C- 13 C abundances (anti-clumping) in ethane produced from methyl radical recombination. In contrast, thermogenic ethane presumably exhibits near stochastic 13 C- 13 C distribution inherited from the biological precursor, which undergoes C-C bond cleavage/recombination during metabolism. Further, we find an exceptionally high 13 C- 13 C signature in ethane remaining after microbial oxidation. In summary, the approach distinguishes between thermogenic, microbially altered, and abiotic hydrocarbons. The 13 C- 13 C signature can provide an important step forward for discrimination of the origin of organic molecules on Earth and in extra-terrestrial environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

A Historical Search for the Occurrence of Habitable Ground Ice at the Phoenix Landing Site

A numerical model of the thermal history of Martian ground ice at the approximate location of the planned Phoenix landing site has been developed and used to identify instances of relatively warm ground ice over the last 10 Ma. Many terrestrial organisms are adapted to life at or below the freezing temperature of water, and we will use the approximate doubling time of terrestrial microbial populations as a function of temperature, is used as a metric against which to assess the "habitability" of Martian ground ice.

Zent, Aaron P.↗
DOE OSTI2021

Bringing function to structure: Root–soil interactions shaping phosphatase activity throughout a soil profile in Puerto Rico

Abstract Large areas of highly productive tropical forests occur on weathered soils with low concentrations of available phosphorus (P). In such forests, root and microbial production of acid phosphatase enzymes capable of mineralizing organic phosphorus is considered vital to increasing available P for plant uptake. We measured both root and soil phosphatase throughout depth and alongside a variety of root and soil factors to better understand the potential of roots and soil biota to increase P availability and to constrain estimates of the biochemical mineralization within ecosystem models. We measured soil phosphatase down to 1 m, root phosphatase to 30 cm, and collected data on fine‐root mass density, specific root length, soil P, bulk density, and soil texture using soil cores in four tropical forests within the Luquillo Experimental Forest in Puerto Rico. We found that soil phosphatase decreased with soil depth, but not root phosphatase. Furthermore, when both soil and root phosphatase were expressed per soil volume, soil phosphatase was 100‐fold higher that root phosphatase. Both root and soil factors influenced soil and root phosphatase. Soil phosphatase increased with fine‐root mass density and organic P, which together explained over 50% of the variation in soil phosphatase. Over 80% of the variation in root phosphatase per unit root mass was attributed to specific root length (positive correlation) and available (resin) P (negative correlation). Synthesis : Fine‐root traits and soil P data are necessary to understand and represent soil and root phosphatase activity throughout the soil column and across sites with different soil conditions and tree species. These findings can be used to parameterize or benchmark estimates of biochemical mineralization in ecosystem models that contain fine‐root biomass and soil P distributions throughout depth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Seismic refraction tracks porosity generation and possible CO 2 production at depth under a headwater catchment

Significance To understand groundwater in weathered bedrock aquifers, we explore (bio)geochemical reactions using geophysical measurements. The result leads to a conceptual model for the three-dimensional distribution of geochemical alteration in the subsurface—well beyond the typical approach of inferring (bio)geochemical reactions in the subsurface from pits, boreholes, and outcrops. With this geophysical technique we discovered the prevalence of gas beneath the water table at this site. This geophysical viewing of the subsurface highlights patterns of water movement, reactions of clays, and microbial and abiotic gas-producing reactions recorded in the subsurface and thus illuminates storage, flow, and reactions of groundwater in bedrock systems. Protecting the groundwater resource beneath our feet will rely on such enhanced capacities to see into the subsurface.

58 GEOSCIENCES↗
NASA NTRS1993

Origins of species: acquired genomes and individuality

Entire genomes with their accompanying protein synthetic systems are transferred throughout the biosphere primarily as bacteria and protists which become symbionts as they irreversibly integrate into pre-existing organisms to form more complex individuals. Individualization is stabilized by simultaneous transmission of once-separate heterologous genetic systems. The origin of new species is hypothesized to correlate with the acquisition, integration and subsequent inheritance of such acquired microbial genomes. These processes were recognized by Mereschkovsky ("Symbiogenesis" in Russian, 1909) and by Wallin ("Symbionticism", see p. 181, this issue).

NASA Discipline Exobiology↗