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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Functional Meta-Analysis of the Proteomic Responses of Arabidopsis Seedlings to the Spaceflight Environment Reveals Multi-Dimensional Sources of Variability across Spaceflight Experiments

The human quest for sustainable habitation of extraterrestrial environments necessitates a robust understanding of life’s adaptability to the unique conditions of spaceflight. This study provides a comprehensive proteomic dissection of the Arabidopsis plant’s responses to the spaceflight environment through a meta-analysis of proteomics data from four separate spaceflight experiments conducted on the International Space Station (ISS) in different hardware configurations. Raw proteomics LC/MS spectra were analyzed for differential expression in MaxQuant and Perseus software. The analysis of dissimilarities among the datasets reveals the multidimensional nature of plant proteomic responses to spaceflight, impacted by variables such as spaceflight hardware, seedling age, lighting conditions, and proteomic quantification techniques. By contrasting datasets that varied in light exposure, we elucidated proteins involved in photomorphogenesis and skotomorphogenesis in plant spaceflight responses. Additionally, with data from an onboard 1 g control experiment, we isolated proteins that specifically respond to the microgravity environment and those that respond to other spaceflight conditions. This study identified proteins and associated metabolic pathways that are consistently impacted across the datasets. Notably, these shared proteins were associated with critical metabolic functions, including carbon metabolism, glycolysis, gluconeogenesis, and amino acid biosynthesis, underscoring their potential significance in Arabidopsis’ spaceflight adaptation mechanisms and informing strategies for successful space farming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A Structural, Functional, and Computational Analysis of BshA, the First Enzyme in the Bacillithiol Biosynthesis Pathway

Bacillithiol is a compound produced by several Gram-positive bacterial species, including the human pathogens Staphylococcus aureus and Bacillus anthracis. It is involved in maintaining cellular redox balance as well as the destruction of reactive oxygen species and harmful xenobiotic agents, including the antibiotic fosfomycin. BshA, BshB, and BshC are the enzymes involved in bacillithiol biosynthesis. BshA is a retaining glycosyltransferase responsible for the first committed step in bacillithiol production, namely the addition of N-acetylglucosamine to l-malate. Retaining glycosyltransferases like BshA are proposed to utilize an S N i-like reaction mechanism in which leaving group departure and nucleophilic attack occur on the same face of the hexose. However, significant questions regarding the details of how BshA and similar enzymes accommodate their substrates and facilitate catalysis persist. Here we report X-ray crystallographic structures of BshA from Bacillus subtilis 168 bound with UMP and/or GlcNAc-mal at resolutions of 2.15 and 2.02 Å, respectively. These ligand-bound structures, along with our functional and computational studies, provide clearer insight into how BshA and other retaining GT-B glycosyltransferases operate, corroborating the substrate-assisted, S N i-like reaction mechanism. In conclusion, the analyses presented herein can serve as the basis for the design of inhibitors capable of preventing bacillithiol production and, subsequently, help combat resistance to fosfomycin in various pathogenic Gram-positive microorganisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Final Report Systems Level Analysis of the Function and Adaptive Responses of Methanogenic Consortia

The purpose of this research was to determine whether the syntrophic microbial associations that are central to the functioning of methane-producing terrestrial wetlands can be predictively modeled with coupled multi-species genome-scale metabolic models. Such models are important because methane is an important greenhouse gas and there is a need to predictively model how the methane-producing microbial communities will respond to environmental perturbations, such as global climate change. The research discovered that the most prodigious methane-producing microorganisms on earth participate in a previously unrecognized form of energy exchange. The methane-producers Methanosaeta and Methanosarcina forge biological electrical connections with other microbes in order to obtain electrons to reduce carbon dioxide to methane. This direct interspecies electron transfer (DIET) was demonstrated in complex microbial communities as well as in defined co-cultures. For example, metatranscriptomic analysis of gene expression in both natural communities and defined co-cultures demonstrated that Methanosaeta species highly expressed genes for the enzymes for the reduction of carbon dioxide to methane. Furthermore, Methanosaeta’s electron-donating partners highly expressed genes for the biological electrical connections known as microbial nanowires. A series of studies involving transcriptomics, genome resequencing, and analysis of the metabolism of a series of strains with targeted gene deletions, further elucidated the mechanisms and energetics of DIET in methane-producing co-cultures, as well as in a co-culture of Geobacter metallireducens and Geobacter sulfurreducens, which provided a system for studying DIET with two genetically tractable partners. Genome-scale modeling of DIET in the G. metallireducens/G. sulfurreducens co-culture suggested that DIET provides more energy to the electron-donating partner that electron exchange via interspecies hydrogen transfer, but that the performance of DIET may be strongly influenced by environmental factors. These studies have significantly modified conceptual models for carbon and electron flow in methane-producing environments and have developed a computational framework for predictive modeling the influence of environmental perturbations on methane-producing microbial communities. The results have important implications for modeling the response of methane-producing microbial communities to climate change as well as for the bioenergy strategy of converting wastes and biomass to methane.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

SAAF: SANS data Analysis using Analytical Functions

The recently completed Extended Q-Range Small Angle Scattering Diffractometer (EQ-SANS) has put the focus on its software needs with renewed urgency. In a series of efforts, we aim at providing a complete set of software solutions on the EQ-SANS instrument. These programs include initial data processing, data correction and reduction, analytical model fitting to the scattering data, Monte Carlo simulation for structure determination, and virtual instrument simulation for experiment planning. SAAF is one such program for analytical data modeling. It takes the reduced EQ-SANS data and allows users to fit the data to analytical models. These models are easy to write. They can either be user written, or from the pre-supplied model library.

Data Analysis↗
DOE OSTI2018

CaFe 2 O 4 oxygen carrier characterization during the partial oxidation of coal in the chemical looping gasification application

The calcium ferrite (CaFe 2 O 4 ) oxygen carrier characterization during chemical looping coal gasification was conducted using X-ray diffraction and Raman spectroscopic analysis. Density functional theory (DFT) analysis and experimental data were used to elucidate the mechanism for the selective oxidation of coal char. The Raman spectroscopic analyses indicated that the initial reduction of CaFe 2 O 4 were at the Fe (8) O 6 and Fe (7) O 6 octahedral sites which are related to the morphological changes at the [4 0 0] and [2 1 2] crystal planes. After the initial reduction, the Raman spectroscopic data indicated the remaining oxygen from Fe-O sites containing Ca (e.g. Fe–O–Ca) participated in the reduction reaction. Deep reduction of the CaFe 2 O 4 led to the removal of oxygen from the Fe–O–Ca bonds, indicated by the decrease in Raman intensities of the corresponding species, and the appearance of the CaO and Fe 0 . The oxygen ion diffusion controlling regime was due to the oxygen transfer occurring at the Fe octahedral sites. Furthermore, these results indicated calcium functions to control both the movement of oxygen ions through the solid and the rate of carbon oxidation in coal char leading to the selective oxidation to produce CO, the desirable product of the chemical looping gasification application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A geometric approach for computing tolerance bounds for elastic functional data

We design an approach for constructing tolerance bounds for functional data with random warping variability. In particular, we define a generative, probabilistic model for the amplitude and phase components of such observations, which parsimoniously characterizes variability in the baseline data. Based on the proposed model, we define two different types of tolerance bounds that are able to measure both types of variability, and as a result, identify when the data has gone beyond the bounds of amplitude and/or phase. The first functional tolerance bounds are computed via a bootstrap procedure on the geometric space of amplitude and phase functions. The second functional tolerance bounds utilize functional Principal Component Analysis to construct a tolerance factor. Our report is motivated by two main applications: process control and disease monitoring. The problem of statistical analysis and modeling of functional data in process control is important in determining when a production has moved beyond a baseline. Moreover, in biomedical applications, doctors use long, approximately periodic signals (such as the electrocardiogram) to diagnose and monitor diseases. In this context, it is desirable to identify abnormalities in these signals. We additionally consider a simulated example to assess our approach and compare it to two existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Identification of succinic semialdehyde reductases from Geobacter: expression, purification, crystallization, preliminary functional, and crystallographic analysis

Succinic semialdehyde reductase (SSAR) is an important enzyme involved in {gamma}-aminobutyrate (GABA) metabolism. By converting succinic semialdehyde (SSA) to {gamma}-hydroxybutyrate (GHB), the SSAR facilitates an alternative pathway for GABA degradation. In this study, we identified SSARs from Geobacter sulfurreducens and Geobacter metallireducens (GsSSAR and GmSSAR, respectively). The enzymes were over-expressed in Escherichia coli and purified to near homogeneity. Both GsSSAR and GmSSAR showed the activity of reducing SSA using nicotinamide adenine dinucleotide phosphate as a co-factor. The oligomeric sizes of GsSSAR and GmSSAR, as determined by analytical size exclusion chromatography, suggest that the enzymes presumably exist as tetramers in solution. The recombinant GsSSAR and GmSSAR crystallized in the presence of NADP{sup +}, and the resulting crystals diffracted to 1.89 {angstrom} (GsSSAR) and 2.25 {angstrom} (GmSSAR) resolution. The GsSSAR and GmSSAR crystals belong to the space groups P2{sub 1}22{sub 1} (a = 99.61 {angstrom}, b = 147.49 {angstrom}, c = 182.47 {angstrom}) and P1 (a = 75.97 {angstrom}, b = 79.14 {angstrom}, c = 95.47 {angstrom}, {alpha} = 82.15{sup o}, {beta} = 88.80{sup o}, {gamma} = 87.66{sup o}), respectively. Preliminary crystallographic data analysis suggests the presence of eight protein monomers in the asymmetric units for both GsSSAR and GmSSAR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Transcriptomic analysis of metabolic function in the giant kelp, Macrocystis pyrifera , across depth and season

To increase knowledge of transcript diversity for the giant kelp, Macrocystis pyrifera, and assess gene expression across naturally occurring depth gradients in light, temperature and nutrients, we sequenced four cDNA libraries created from blades collected at the sea surface and at 18 m depth during the winter and summer. Comparative genomics cluster analyses revealed novel gene families (clusters) in existing brown alga expressed sequence tag data compared with other related algal groups, a pattern also seen with the addition of M. pyrifera sequences. Assembly of 228 Mbp of sequence generated c. 9000 isotigs and c. 12 000 open reading frames. Annotations were assigned using families of hidden Markov models for c. 11% of open reading frames; M. pyrifera had highest similarity to other members of the Phaeophyceae, namely Ectocarpus siliculosus and Laminaria digitata. Quantitative polymerase chain reaction of transcript targets verified depth-related differences in gene expression; stress response and light-harvesting transcripts, especially members of the LI818 (also known as LHCSR) family, showed high expression in the surface compared with 18 m depth, while some nitrogen acquisition transcripts (e.g. nitrite reductase) were upregulated at depth compared with the surface, supporting a conceptual biological model of depth-dependent physiology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

A Theoretical Analysis: Physical Unclonable Functions and The Software Protection Problem

Physical Unclonable Functions (PUFs) or Physical One Way Functions (P-OWFs) are physical systems whose responses to input stimuli (i.e., challenges) are easy to measure (within reasonable error bounds) but hard to clone. This property of unclonability is due to the accepted hardness of replicating the multitude of uncontrollable manufacturing characteristics and makes PUFs useful in solving problems such as device authentication, software protection, licensing, and certified execution. In this paper, we focus on the effectiveness of PUFs for software protection and show that traditional non-computational (black-box) PUFs cannot solve the problem against real world adversaries in offline settings. Our contributions are the following: We provide two real world adversary models (weak and strong variants) and present definitions for security against the adversaries. We continue by proposing schemes secure against the weak adversary and show that no scheme is secure against a strong adversary without the use of trusted hardware. Finally, we present a protection scheme secure against strong adversaries based on trusted hardware.

97 MATHEMATICS AND COMPUTING↗