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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Portable Unit for Metabolic Analysis

The Portable Unit for Metabolic Analysis (PUMA) is an instrument that measures several quantities indicative of human metabolic function. Specifically, this instrument makes time-resolved measurements of temperature, pressure, flow, and the partial pressures of oxygen and carbon dioxide in breath during both inhalation and exhalation. Portable instruments for measuring these quantities have been commercially available, but the response times of those instruments are too long to enable temporal resolution of phenomena on the time scales of human respiration cycles. In contrast, the response time of the PUMA is significantly shorter than characteristic times of human respiration phenomena, making it possible to analyze varying metabolic parameters, not only on sequential breath cycles but also at successive phases of inhalation and exhalation within the same breath cycle. In operation, the PUMA is positioned to sample breath near the subject s mouth. Commercial off-the-shelf sensors are used for three of the measurements: a miniature pressure transducer for pressure, a thermistor for temperature, and an ultrasonic sensor for flow. Sensors developed at Glenn Research Center are used for measuring the partial pressures of oxygen and carbon dioxide: The carbon dioxide sensor exploits the relatively strong absorption of infrared light by carbon dioxide. Light from an infrared source passes through the stream of inhaled or exhaled gas and is focused on an infrared- sensitive photodetector. The oxygen sensor exploits the effect of oxygen in quenching the fluorescence of ruthenium-doped organic molecules in a dye on the tip of an optical fiber. A blue laser diode is used to excite the fluorescence, and the optical fiber carries the fluorescent light to a photodiode, the temporal variation of the output of which bears a known relationship with the rate of quenching of fluorescence and, hence, with the partial pressure of oxygen. The outputs of the sensors are digitized, preprocessed by a small onboard computer, and then sent wirelessly to a desktop computer, where the collected data are analyzed and displayed. In addition to the raw data on temperature, pressure, flow, and mole fractions of oxygen and carbon dioxide, the display can include volumetric oxygen consumption, volumetric carbon dioxide production, respiratory equivalent ratio, and volumetric flow rate of exhaled gas.

Dietrich, Daniel L.↗
NASA NTRS2010

Testing and Results of Human Metabolic Simulation Utilizing Ultrasonic Nebulizer Technology for Water Vapor Generation

Life support technology must be evaluated thoroughly before ever being implemented into a functioning design. A major concern during that evaluation is safety. The ability to mimic human metabolic loads allows test engineers to evaluate the effectiveness of new technologies without risking injury to any actual humans. The main function of most life support technologies is the removal of carbon dioxide (CO2) and water (H2O) vapor. As such any good human metabolic simulator (HMS) will mimic the human body s ability to produce these items. Introducing CO2 into a test chamber is a very straightforward process with few unknowns so the focus of this particular new HMS design was on the much more complicated process of introducing known quantities of H2O vapor on command. Past iterations of the HMS have utilized steam which is very hard to keep in vapor phase while transporting and injecting into a test chamber. Also steam adds large quantities of heat to any test chamber, well beyond what an actual human does. For the new HMS an alternative approach to water vapor generation was designed utilizing ultrasonic nebulizers as a method for creating water vapor. Ultrasonic technology allows water to be vibrated into extremely tiny pieces (2-5 microns) and evaporate without requiring additional heating. Doing this process inside the test chamber itself allows H2O vapor generation without the unwanted heat and the challenging process of transporting water vapor. This paper presents the design details as well as results of all initial and final acceptance system testing. Testing of the system was performed at a range of known human metabolic rates in both sea-level and reduced pressure environments. This multitude of test points fully defines the systems capabilities as they relate to actual environmental systems testing.

Stubbe, Matthew↗
NASA NTRS2011

Changes in Liver Metabolic Gene Expression from Radiation Exposure

Radiation exposure is one of the unique physiological challenges of human spaceflight that is not encountered on earth. While radiation exposure is known to impart physiological stresses and alter normal function, it is unclear how it specifically affects drug metabolism. A major concern is that the actions of medications used in spaceflight may deviate from the expectations formed from terrestrial use. This concern was investigated at the molecular level by analyzing how gamma radiation exposure affected gene expression in the livers of mice. Three different doses of radiation were administered and after various intervals of recovery time, gene expression was measured with RT-qPCR screening arrays for drug metabolism and DNA repair. After examining the results of 192 genes total from each of 72 mice, 65 genes were found to be significantly affected by at least one of the doses of radiation. In general, the genes affected are involved in the metabolism of drugs with lipid or steroid hormone-like structures, as well as the maintenance of redox homeostasis and repair of DNA damage.

Peters, C. P.↗
NASA NTRS2012

Changes in Liver Metabolic Gene Expression from Radiation Exposure

Increased exposure to radiation is one physiological stressor associated with spaceflight. While known to alter normal physiological function, how radiation affects metabolism of administered medications is unclear. Crew health could be affected if the actions of medications used in spaceflight deviated from expectations formed during terrestrial medication use. Three different doses of gamma radiation (50 mGy - 6.05 Gy) and a sham were administered to groups of 6 mice each, and after various intervals of recovery time, liver gene expression was measured with RT-qPCR arrays for drug metabolism and DNA repair enzymes. Results indicated approx.65 genes of the 190 tested were significantly affected by at least one of the radiation doses. Many of the affected genes are involved in the metabolism of drugs with hydrophobic or steroid-like structures, maintenance of redox homeostasis and repair of DNA damage. Most affected genes returned to near control expression levels by 7 days post-treatment. With 6 Gy exposure, metallothionein expression was 132-fold more than control at the 4 hr time point, and fell at each later time point (11-fold at 24 hrs, and 8-fold at 7 days). In contrast, Cyp17a1 showed a 4-fold elevation at 4 hrs after exposure and remained constant for 7 days.

Peters, C. P.↗
NASA NTRS2012

Changes in Liver Metabolic Gene Expression after Radiation Exposure

The health of the liver, especially the rate of its metabolic enzymes, determines the concentration of circulating drugs as well as the duration of their efficacy. Most pharmaceuticals are metabolized by the liver, and clinically-used medication doses are given with normal liver function in mind. A drug overdose can result in the case of a liver that is damaged and removing pharmaceuticals from the circulation at a rate slower than normal. Alternatively, if liver function is elevated and removing drugs from the system more quickly than usual, it would be as if too little drug had been given for effective treatment. Because of the importance of the liver in drug metabolism, we want to understand any effects of spaceflight on the enzymes of the liver. Exposure to cosmic radiation is one aspect of spaceflight that can be modeled in ground experiments.

Peters, C. P.↗
NASA NTRS2016

Metabolic Potential and Activity in Fluids of the Coast Range Ophiolite Microbial Observatory, California, USA

Metabolic potential and activity associated with hydrogen and carbon monoxide were characterized in fluids sampled from the the Coast Range Ophiolite Microbial Observatory (CROMO). CROMO consists of two clusters of science-dedicated wells drilled to varying depths up to 35m in the actively serpentinizing, Jurassic-age Coast Range Ophiolite of Northern California, along with a suite of pre-existing monitoring wells at the same site. Consistent with the fluid chemistry observed in other serpentinizing systems, CROMO fluids are highly alkaline, with pH up to 12.5, high in methane, with concentrations up 1600 micromolar, and low in dissolved inorganic carbon (DIC), with concentrations of 10's to 100's of micromolar. CROMO is conspicuous for fluid H2 concentrations that are consistently sub-micromolar, orders of magnitude lower than is typical of other systems. However, higher H2 concentrations (10's -100's of micromolar) at an earlier stage of fluid chemical evolution are predicted by, or consistent with: thermodynamic models for fluid chemistry based on parent rock composition equivalent to local peridotite and with water:rock ratio constrained by observed pH; the presence of magnetite at several wt% in CROMO drill cores; and concentrations of formate and carbon monoxide that would require elevated H2 if formed in equilibrium with H2 and DIC. Calculated Gibbs energy changes for reaction of H2 and CO in each of several metabolisms, across the range of fluid composition encompassed by the CROMO wells, range from bioenergetically feasible (capable of driving ATP synthesis) to thermodynamically unfavorable. Active consumption relative to killed controls was observed for both CO and H2 during incubation of fluids from the pre-existing monitoring wells; in incubations of freshly cored solids, consumption was only observed in one sample set (corresponding to the lowest pH) out of three. The specific metabolisms by which H2 and CO are consumed remain to be determined.

Hydrogen↗
NASA NTRS2019

Exobiology Through the Lens of Constraint-Based Metabolic Modeling

A focus of many astrobiology questions resides on the interplay between biochemistry and geochemistry. This biotic-abiotic interface is intimately connected to habitability. Computational systems biology provides a paradigm to characterize this interface. Here we describe the application of constraint-based metabolic modeling to characterize photosynthetic microorganisms inhabiting a modern analog to the Earth’s primordial ocean. Biochemistry is captured in a metabolic network that is converted to a mathematical model. Geochemistry results in constraints that limit the capabilities of the metabolic network. The combination of the two within a single framework can elucidate the co-evolution of life and the environment.

Broddrick, Jared T.↗
DOE OSTI2021

Application of the Metabolic Modeling Pipeline in KBase to Categorize Reactions, Predict Essential Genes, and Predict Pathways in an Isolate Genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

Allen, Benjamin↗
DOE OSTI2020

Towards the Reconstruction of Integrated Genome-Scale Models of Metabolism and Gene Expression

The reconstruction of integrated genome-scale models of metabolism and gene expression has been a challenge for a while now. In fact, various methods that allow integrating reconstructions of Transcriptional Regulatory Networks, gene expression data or both into Genome-Scale Metabolic Models have been proposed. Several of these methods are surveyed in this article, which allowed identifying their strengths and weaknesses concerning the reconstruction of integrated models for multiple prokaryotic organisms. Additionally, the main resources of regulatory information were also surveyed, as the existence of novel sources of regulatory information and gene expression data may contribute for the improvement of methodologies referred herein.

Databases of regulatory information↗
DOE OSTI2026

Elucidation of odd-chain dicarboxylate metabolism in Acinetobacter baylyi and application to polyethylene upcycling

Polyethylene (PE) is a versatile polymer, but its end-of-life management is challenging due to its recalcitrant structure. We present a promising approach combining chemical degradation and bio-upcycling to convert postconsumer PE waste into a value-added bioproduct. Specifically, PE was degraded into acetic acid and C 4 –C 7 dicarboxylic acids by nitric acid. We then elucidated the catabolic pathways for glutarate (C 5 ) and pimelate (C 7 ) in the nonmodel bacterium Acinetobacter baylyi ADP1 through RNA sequencing, phenotyping, and enzymatic assays. Whole-genome sequencing of evolved isolates also identified a crucial IclR family transcriptional regulator, DcaS, which acts as a repressor of dicarboxylate metabolism. The reverse-engineered strain exhibited enhanced substrate utilization compared to the wild-type strain. Using rational metabolic engineering, the PE deconstruction products were bioconverted into the valuable chemical lycopene, highlighting the potential of this microbial chassis to produce value-added bioproducts from postconsumer PE waste, thus promoting a circular economy for plastics.

metabolic engineering↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Diversification of JAZ‐MYC signaling function in immune metabolism

Summary Jasmonate (JA) re‐programs metabolism to confer resistance to diverse environmental threats. Jasmonate stimulates the degradation of JASMONATE ZIM‐DOMAIN (JAZ) proteins that repress the activity of MYC transcription factors. In Arabidopsis thaliana , MYC and JAZ are encoded by 4 and 13 genes, respectively. The extent to which expansion of the MYC and JAZ families has contributed to functional diversification of JA responses is not well understood. Here, we investigated the role of MYC and JAZ paralogs in controlling the production of defense compounds derived from aromatic amino acids (AAAs). Analysis of loss‐of‐function and dominant myc mutations identified MYC3 and MYC4 as the major regulators of JA‐induced tryptophan metabolism. We developed a JAZ family‐based, forward genetics approach to screen randomized jaz polymutants for allelic combinations that enhance tryptophan biosynthetic capacity. We found that mutants defective in all members ( JAZ1/2/5/6 ) of JAZ group I over‐accumulate AAA‐derived defense compounds, constitutively express marker genes for the JA–ethylene branch of immunity and are more resistant to necrotrophic pathogens but not insect herbivores. In defining JAZ and MYC paralogs that regulate the production of amino‐acid‐derived defense compounds, our results provide insight into the specificity of JA signaling in immunity.

jasmonate↗
DOE OSTI2022

Nitrogen Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. So we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change ( Δ r G ′ o ) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings ( https://github.com/maranasgroup/dGPredictor ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Editorial: Selective Controls on Microbial Energy Metabolisms: From the Microscale to the Macroscale

A mechanistic and predictive understanding of the genotypic and phenotypic controls on microbial element cycling remains a grand challenge in microbiology. While the composition and concentration of carbon sources, electron donors, and electron acceptors are known to influence microbial community structure by selecting for microbial sub-populations with distinct catabolic and respiratory pathways, selective inhibitors and trace nutrient availability modulate the activity of metabolic enzymes. This in turn influences the distribution of microbial sub-populations with distinct metabolic and respiratory traits, which are then structured by complex multi-dimensional environmental gradients that influence the composition, gene content and element cycling activity of microbiomes. While some parameters are known to select for different respiratory activities (e.g., lanthanides as essential nutrients for methanotrophs, molybdate as a specific inhibitor of sulfate reduction, carbon:nitrogen ratio and concentration as a control on the end-products of nitrate respiration), there are others to discover, and demonstrating how selective parameters operate and mediate element cycling across scales requires multi-disciplinary research in both the lab and field.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

iNovo479: Metabolic Modeling Provides a Roadmap to Optimize Bioproduct Yield from Deconstructed Lignin Aromatics by Novosphingobium aromaticivorans

Lignin is an abundant renewable source of aromatics and precursors for the production of other organic chemicals. However, lignin is a heterogeneous polymer, so the mixture of aromatics released during its depolymerization can make its conversion to chemicals challenging. Microbes are a potential solution to this challenge, as some can catabolize multiple aromatic substrates into one product. Novosphingobium aromaticivorans has this ability, and its use as a bacterial chassis for lignin valorization could be improved by the ability to predict product yields based on thermodynamic and metabolic inputs. In this work, we built a genome-scale metabolic model of N. aromaticivorans, iNovo479, to guide the engineering of strains for aromatic conversion into products. iNovo479 predicted product yields from single or multiple aromatics, and the impact of combinations of aromatic and non-aromatic substrates on product yields. We show that enzyme reactions from other organisms can be added to iNovo479 to predict the feasibility and profitability of producing additional products by engineered strains. Thus, we conclude that iNovo479 can help guide the design of bacteria to convert lignin aromatics into valuable chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone

Abstract The plant‐sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2‐pyrone synthase gene from Gerbera hybrida ( GhPS ) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl‐CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP‐citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl‐CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12‐ ACL1‐ACC1 using fed‐batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources.

2‐pyrone synthase↗
DOE OSTI2021

Spatiotemporal distribution of chemical signatures exhibited by Myxococcus xanthus in response to metabolic conditions

Myxococcus xanthus is a common soil bacterium with a complex life cycle, which is known for production of secondary metabolites. However, little is known about the effects of nutrient availability on M. xanthus metabolite production. In this study, we utilize confocal Raman microscopy (CRM) to examine the spatiotemporal distribution of chemical signatures secreted by M. xanthus and their response to varied nutrient availability. Here, ten distinct spectral features are observed by CRM from M. xanthus grown on nutrient-rich medium. However, when M. xanthus is constrained to grow under nutrient-limited conditions, by starving it of casitone, it develops fruiting bodies, and the accompanying Raman microspectra are dramatically altered. The reduced metabolic state engendered by the absence of casitone in the medium is associated with reduced, or completely eliminated, features at 1140 cm –1 , 1560 cm –1 , and 1648 cm –1 . In their place, a feature at 1537 cm –1 is observed, this feature being tentatively assigned to a transitional phase important for cellular adaptation to varying environmental conditions. In addition, correlating principal component analysis heat maps with optical images illustrates how fruiting bodies in the center co-exist with motile cells at the colony edge. While the metabolites responsible for these Raman features are not completely identified, three M. xanthus peaks at 1004, 1151, and 1510 cm –1 are consistent with the production of lycopene. Thus, a combination of CRM imaging and PCA enables the spatial mapping of spectral signatures of secreted factors from M. xanthus and their correlation with metabolic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗