Search NASA⌕ Search

SEARCH · Search NASA

Results for “BIOLOGY”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response

Motivation: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems such as protein complexes, metabolic reactions, and signal transduction pathways. Hypergraphs are generalizations of graphs that naturally model multi-way interactions in data, and we therefore seek to understand how they can more faithfully identify, and potentially predict, complex relationships in genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges are differentially expressed genes and vertices represent conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Our results demonstrate the utility of using hypergraphs to represent complex biological systems, and highlight potentially interesting biological results about host response to highly pathogenic viruses.

systems biology, hypergraph, viral infection, biol↗
DOE OSTI2020

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Mass spectrometry-based proteomics for system-level characterization of biological responses to engineered nanomaterials

The widespread applications of engineered nanomaterials or nanotechnology make the characterization of biological responses to nanomaterials as an important area of research. The applications of omics-based approaches such as mass spectrometry-based proteomics have revealed new insights into the cellular responses upon exposure to nanomaterials, including how nanomaterials interact and alter cellular pathways. For instance, a redox-dependent response is often associated with exposure of nanomaterials, which leads to the generation of reactive oxygen species. In this review, we discuss the general quantitative proteomics approaches, with an emphasis on redox proteomics and their applications for characterizing the biological responses to nanomaterials.

Zhang, Tong↗
DOE OSTI2016

Rupturing of Biological Spores As a Source of Secondary Particles in Amazonia

Airborne biological particles, such as fungal spores and pollen, are ubiquitous in the Earth’s atmosphere and play an important role in the atmospheric environment and climate, impacting air quality, cloud formation, and the Earth’s radiation budget. The atmospheric transformations of airborne biological spores at elevated relative humidity remain poorly understood and their climatic role is uncertain. Using an environmental scanning electron microscope (ESEM), we observed rupturing of Amazonian fungal spores and subsequent release of nanometer to submicron size fragments after exposure to high humidity. We find that fungal fragments contain elements of inorganic salts (e.g., Na and Cl). They are hygroscopic in nature with a growth factor up to 2.3 at 96% relative humidity, thus they may potentially influence cloud formation. Due to their hygroscopic growth, light scattering cross sections of the fragments are enhanced by up to a factor of 10. Furthermore, rupturing of fungal spores at high humidity may explain the bursting events of nanoparticles and may provide insight into new particle formation in Amazonia.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Chapter 8. Hybrid Biological–Inorganic Systems for CO 2 Conversion to Fuels

The biological reduction of CO 2 into organic carbon is integral to the formation and maintenance of all life on earth. An urgent need to mitigate the effects of CO 2 on our atmosphere has provided an imperative to exploit biological CO 2 fixation for the conversion of CO2 into valuable and energy rich fuels. Photosynthesis uses only sunlight, water, and CO2 as starting materials to form all biomass.

CO2 Conversion to Fuels↗
DOE OSTI2017

Grand Challenges for Biological and Environmental Research: Progress and Future Vision. A Report from the Biological and Environmental Research Advisory Committee

The Biological and Environmental Research (BER) program within the U.S. Department of Energy (DOE) Office of Science supports research focusing on the interconnections between energy production and the living environment. This fundamental research, conducted at universities, DOE national laboratories, and research institutions across the country, explores organisms and ecosystems that can influence the U.S. energy system and advances understanding of the relationships between energy and environment from local to global scales. Research within BER can be categorized into biological systems and Earth and environmental systems. Biological systems research seeks to characterize and predictively understand microbial and plant systems using genomic science, computational analyses, and experimental approaches. Foundational knowledge of the structure and function of these systems underpins the ability to leverage natural processes for energy production, including the sustainable development of biofuels and other bioproducts. Earth and environmental systems research seeks to characterize and predictively understand feedbacks between Earth and energy systems and includes studies on atmospheric physics and chemistry, ecosystem ecology and biogeochemistry, and development and validation of Earth system models extending from regional to global scales. To promote world-class research in these areas, BER supports user facilities that enable observation and measurement of atmospheric, biological, and biogeochemical processes using the latest technologies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Ultra-High Resolution Elemental/Isotopic Mass Spectrometry (m/?m> 1,000,000): Coupling of the Liquid Sampling-Atmospheric Pressure Glow Discharge with an Orbitrap Mass Spectrometer for Applications in Biological Chemistry and Environmental Analysis

Many fundamental questions of astrophysics, biochemistry, and geology rely on the ability to accurately and precisely measure the mass and abundance of isotopes. Taken a step further, the capacity to perform such measurements on intact molecules provides insights into processes in diverse biological systems. Described here is the coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma, with a commercially available ThermoScientific Fusion Lumos mass spectrometer. Demonstrated for the first time is the ionization and isotopically-resolved fingerprinting of a long-postulated, but never mass-spectrometrically observed, bi-metallic complex Hg:Se-cysteine. Such a complex has been implicated as having a role in observations of Hg detoxification by selenoproteins/amino acids. Demonstrated as well is the ability to mass spectrometrically-resolve the geochronologically important isobaric 87Sr and 87Rb species (?m ~ 0.3 mDa, mass resolution m/?m ? 1,700,000). The mass difference in this case reflects the beta-decay of the 87Rb to the stable Sr isotope. These two demonstrations highlight what may be a significant change in bioinorganic and atomic mass spectrometry, with impact expected across a broad spectrum of the physical, biological and geological sciences.

Hoegg, Edward D.↗
DOE OSTI2021

Resonant X-ray scattering of biological assemblies

Understanding the relationship between structure and function for biological assemblies can guide identification of new therapeutics, design of biomaterials, and development of biotechnological processes. Resonant X-ray scattering provides a chemically-specific approach to characterize complex biological structures based on anomalous or resonant scattering from a specific element or chemical moiety. Anomalous or resonant diffraction can provide structural details with high atomic resolution, while resonant X-ray scattering can provide structural details with lower resolution through tender or soft X-rays. Furthermore, we review applications, challenges, and opportunities for resonant X-ray scattering in the field of structural biology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Gold core/ceria shell-based redox active nanozyme mimicking the biological multienzyme complex phenomenon

Catalytically active individual gold (Au) and cerium oxide (CeO2) nanoparticles are well known to exhibit specific enzyme-like activities, such as natural catalase, oxidase, superoxide dismutase, and peroxidase enzymes. These activities have been maneuvered to design several biological applications such as immunoassays, glucose detection, radiation and free radical protection and tissue engineering. A functional nanozyme depicting multienzyme like properties that functions as a synthetic super enzyme has eluded the researchers in the nanoscience community for past decade. In current report, we have designed a functional multienzyme in the form of Gold (core)-CeO2 (shell) nanoparticles (Au@CeO2 CSNPs) exhibiting excellent peroxidase, catalase and superoxide dismutase enzyme-like activities that are controlled simply by tuning the pH. The reaction kinetic parameters reveal that the peroxidase-like activity of this core shell nanozyme is comparable to natural HRP enzyme. Unlike peroxidase-like activity exhibited by other nanomaterials, Au@CeO2 CSNPs showed decrease in hydroxyl radical formation, suggesting that the bio catalytic reactions are performed by efficient electron transfers. A significant enzyme-like activity of this core shell nanoparticle was conserved at extreme pH (2 – 11) and temperatures (up to 90 °C), clearly suggesting the superiority over natural enzymes. Further, the utility of peroxidase-like activity of this core shell nanoparticles was extended for the detection of glucose, which showed a linear range of detection between (100 µM – 1 mM). It is hypothesized that the proximity of the redox potentials of Au+/Au and Ce (III)/Ce (IV) may result in a redox couple promoting the multienzyme activity of core shell nanoparticles. Au@CeO2 CSNPs may open new directions for development of single platform sensors in multiple biosensing applications.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Cellulose–hemicellulose interactions at elevated temperatures increase cellulose recalcitrance to biological conversion

It has been previously shown that cellulose-lignin droplets’ strong interactions, resulting from lignin coalescence and redisposition on cellulose surface during thermochemical pretreatments, increase cellulose recalcitrance to biological conversion, especially at commercially viable low enzyme loadings. However, information on the impact of cellulose–hemicellulose interactions on cellulose recalcitrance following relevant pretreatment conditions are scarce. Here, to investigate the effects of plausible hemicellulose precipitation and re-association with cellulose on cellulose conversion, different pretreatments were applied to pure Avicel® PH101 cellulose alone and Avicel mixed with model hemicellulose compounds followed by enzymatic hydrolysis of resulting solids at both low and high enzyme loadings. Solids produced by pretreatment of Avicel mixed with hemicelluloses (AMH) were found to contain about 2 to 14.6% of exogenous, precipitated hemicelluloses and showed a remarkably much lower digestibility (up to 60%) than their respective controls. However, the exogenous hemicellulosic residues that associated with Avicel following high temperature pretreatments resulted in greater losses in cellulose conversion than those formed at low temperatures, suggesting that temperature plays a strong role in the strength of cellulose–hemicellulose association. Molecular dynamics simulations of hemicellulosic xylan and cellulose were found to further support this temperature effect as the xylan–cellulose interactions were found to substantially increase at elevated temperatures. Furthermore, exogenous, precipitated hemicelluloses in pretreated AMH solids resulted in a larger drop in cellulose conversion than the delignified lignocellulosic biomass containing comparably much higher natural hemicellulose amounts. In conclusion, increased cellulase loadings or supplementation of cellulase with xylanases enhanced cellulose conversion for most pretreated AMH solids; however, this approach was less effective for solids containing mannan polysaccharides, suggesting stronger association of cellulose with (hetero) mannans or lack of enzymes in the mixture required to hydrolyze such polysaccharides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Biomass Recalcitrance in Willow Under Two Biological Conversion Paradigms: Enzymatic Hydrolysis and Anaerobic Digestion

Biomass recalcitrance, the inherent resistance of plants towards deconstruction, negatively affects the viability of biorefineries. This trait is not only dictated by the properties of the biomass but also by the conversion system used and its interactions with specific features of the biomass. Here, biomass recalcitrance to anaerobic digestion (AD) was assessed using a biomethanation potential (BMP) assay. Plant material (n = 94) was selected from a large population of natural Salix viminalis accessions, previously evaluated for biomass recalcitrance using hydrothermal pretreatment-enzymatic hydrolysis. Correlations between yields from the two biological conversion systems were evaluated, as well as the influence of biomass compositional features, analyzed by pyrolysis-molecular beam mass spectrometry (py-MBMS), and other biomass physical properties on conversion performance. BMP values averaged 198.0 Nml CH 4 /g biomass after 94 days, ranging from 28.6 to 245.9. S lignin and carbohydrate-derived spectral features were positively correlated with performance under both systems, whereas G lignin, p-coumaric acid, and ferulic acid-derived ions were negatively correlated with yields and rates. Most spectral features were more strongly correlated with enzymatic hydrolysis yields compared to methane production. For early-stage methane production and rate, recalcitrance factors were similar compared to enzymatic hydrolysis, with weaker correlations observed at later timepoints. The results suggest that although variation in methane potential was considerably lower than enzymatic hydrolysis yields, a reduced recalcitrance under this system will still be of importance to improve early conversion rates. Spectral features of low methane-producing samples indicate the presence of inhibitory substances, warranting further study.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Context Dependence of Biological Circuits

It has been an ongoing scientific debate whether biological parameters are conserved across experimental setups with different media, pH values, and other experimental conditions. Our work explores this question using Bayesian probability as a rigorous framework to assess the biological context of parameters in a model of the cell growth controller in You et al. When this growth controller is uninduced, the E. coli cell population grows to carrying capacity; however, when the circuit is induced, the cell population growth is regulated to remain well below carrying capacity. This growth control controller regulates the E. coli cell population by cell to cell communication using the signaling molecule AHL and by cell death using the bacterial toxin CcdB. To evaluate the context dependence of parameters such as the cell growth rate, the carrying capacity, the AHL degradation rate, the leakiness of AHL, the leakiness of toxin CcdB, and the IPTG induction factor, we collect experimental data from the growth control circuit in two different media, at two different pH values, and with several induction levels. We define a set of possible context dependencies that describe how these parameters may differ with the experimental conditions and we develop mathematical models of the growth controller across the different experimental contexts. We then determine whether these parameters are shared across experimental contexts or whether they are context dependent. For each of these possible context dependencies, we use Bayesian inference to assess its plausibility and to estimate the parameters of the growth controller. Ultimately, we find that there is significant experimental context dependence in this circuit. Furthermore, we also find that the estimated parameter values are sensitive to our assumption of a context relationship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants

Upon sensing developmental or environmental cues, epigenetic regulators transform the chromatin landscape of a network of genes to modulate their expression and dictate adequate cellular and organismal responses. Knowledge of the specific biological processes and genomic loci controlled by each epigenetic regulator will greatly advance our understanding of epigenetic regulation in plants. To facilitate hypothesis generation and testing in this domain, we present EpiNet, an extensive gene regulatory network (GRN) featuring epigenetic regulators. EpiNet was enabled by (i) curated knowledge of epigenetic regulators involved in DNA methylation, histone modification, chromatin remodeling, and siRNA pathways; and (ii) a machine-learning network inference approach powered by a wealth of public transcriptome datasets. We applied GENIE3, a machine-learning network inference approach, to mine public Arabidopsis transcriptomes and construct tissue-specific GRNs with both epigenetic regulators and transcription factors as predictors. The resultant GRNs, named EpiNet, can now be intersected with individual transcriptomic studies on biological processes of interest to identify the most influential epigenetic regulators, as well as predicted gene targets of the epigenetic regulators. We demonstrate the validity of this approach using case studies of shoot and root apical meristem development.

root apical meristem↗