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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Protonation-state-Coupled Conformational Dynamics in Reaction Mechanisms of Channel and Pump Rhodopsins

Channel and pump rhodopsins use energy from light absorbed by a covalently bound retinal chromophore to transport ions across membranes of microbial cells. Ion transfer steps, including proton transfer, can couple to changes in protein conformational dynamics and water positions. Although general principles of how microbial rhodopsins function are largely understood, key issues pertaining to reaction mechanisms remain unclear. Here, we compare the protonation-coupled dynamics of pump and channelrhodopsins, highlighting the roles that water dynamics, protein electrostatics and protein flexibility can have in ion transport mechanisms. We discuss observations supporting important functional roles of inter- and intra-helical carboxylate/hydroxyl hydrogen-bonding motifs. Specifically, we use the proton pump bacteriorhodopsin, the sodium pump KR2, channelrhodopsins and Anabaena sensory rhodopsin. We outline the usefulness of theoretic biophysics approaches to the study of retinal proteins, challenges in studying the hydrogen-bond dynamics of rhodopsin active sites, and implications for conformational coupling in membrane transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Seasonality and longer-term development generate temporal dynamics in the Populus microbiome

ABSTRACT Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change. IMPORTANCE Microbiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Isoflavone supplementation, via red clover hay, alters the rumen microbial community and promotes weight gain of steers grazing mixed grass pastures

Biochanin A, an isoflavone present in the pasture legume red clover (Trifloium pratense L.), alters fermentation in the rumen of cattle and other ruminants. Biochanin A inhibits hyperammonia-producing bacteria and promotes cellulolytic bacteria and fiber catalysis in vitro and ex vivo. Consequently, biochanin A supplementation improves weight gain in grazing steers. Red clover contains biologically active isoflavones that may act synergistically. Therefore, the objective was to evaluate the effect of two levels of red clover hay on growth performance and the microbial community in growing steers grazing mixed grass pastures. A grazing experiment was conducted over 2 early growing seasons (2016 and 2017) with 36 cross-bred steers and twelve rumen-fistulated, growing Holstein steers for evaluation of average daily gain and rumen microbiota, respectively. Steers were blocked by body weight and assigned to pastures with one of four treatments: 1) pasture only, 2) pasture + dry distillers’ grains (DDG), 3) pasture + DDG + low level of red clover hay (~15% red clover diet), or 4) pasture + DDG + high level of red clover hay (~30% red clover diet). DDG were added to treatments to meet protein requirements and to balance total protein supplementation between treatments. All supplementation strategies (DDG ± red clover hay) increased average daily gains in comparison to pasture-only controls (P < 0.05), with a low level of red clover supplementation being the most effective (+0.17 kg d-1 > DDG only controls; P < 0.05). Similarly, hyper-ammonia-producing bacteria inhibition (10–100-fold; P < 0.05), fiber catalysis (+10–25%; P < 0.05) and short chain fatty acid concentrations were greatest with the low red clover supplement (+~25%; P < 0.05). These results provide evidence that lower levels or red clover supplementation may be optimal for maximizing overall microbial community function and animal performance in grazing steers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Success Through Synergy (STS): Increasing Cultivation Yield and Stability with Rationally Designed Consortia

Consortia of functionally diverse microbial assemblages hold potential to enhance the production of microalgae for biofuels and bioproducts. In laboratory experiments, increases in algal yield have been achieved through the amendment of algal cultures with growth-promoting bacteria, as well as the rational design of algal-algal consortia (i.e., combining strains with complementary traits). Despite this evidence, commercial systems typically rely on monocultures because of the technical challenges that multi-taxa cultures impose. In this project, we aimed to generate algae-bacteria and algae-algae consortia in the lab and test the performance of these consortia against monoculture counterparts in the field. We also aimed to generate toolkits that could be used by the scientific community and algal farmers to advance the cultivation of consortia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

IA-TmG.1.0

As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Frequent precipitation regime soil (rain-fed and tile-drained agriculture) was collected from Iowa State University’s Comparison of Biofuel Systems (COBS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

KS-TmG.1.0

As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Intermediate precipitation regime soil (rain-fed and irrigated agriculture) was collected from Konza Prairie Biological Station (KPBS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

WA-TmG.1.0

As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Soil samples were collected from Washington State University’s Irrigated Agriculture Research and Extension Center (IAREC) in Prosser, WA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica . The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

trait-based modeling↗
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Environmental Consequences of an Emerging Biosphere

It seems feasible to detect biological signatures ("biosignatures") in other planetary systems using the tools of astronomy. There are at least two types of biosignatures; spectral and/or polarization features created by biological products, and electromagnetic signals created by technology. The latter example of a biosignature requires SETI-like searches. This presentation addresses only spectral signatures of biological products and properties of habitable planets. Spectral biosignatures are indeed promising targets for near-term exploration. They can arise from organic constituents (e.g., vegetation) and/or inorganic products (e.g., atmospheric O2). Features originating from a planet's surface are likely to be localized in specific regions, whereas gaseous biosignatures can become globally distributed by atmospheric circulation. Biosignatures should be most abundant within environments that are, or once were, habitable. We currently believe that habitable environments necessarily provide Liquid water and biochemically useful energy. However, we do not yet fully comprehend the diversity of features that might arise within these environments that are non-biological in origin, yet mimic biosignatures. For example, atmospheres reflect the events leading to their origins as well as a host of ongoing planetary processes that might include biological activity. We are persuaded that abundant atmospheric oxygen in an environment with abundant liquid water constitutes definitive evidence of life. However, our own early biosphere thrived for more than a billion years in the absence of abundant atmospheric oxygen. The production of other, more reduced, gaseous biomarkers of "young" and/or anaerobic biospheres has not been systematically studied. Biological gas production is strongly controlled by the structure and function of microbial ecosystems. Investigations of microbial ecosystems that are close analogs of ancient communities offer multiple benefits. Such studies can interpret the production of the most important biomarker gases, while simultaneously helping us to understand the formidable array of ecological processes that guided early biological evolution. Astrobiologists must recognize those aspects of biosignatures that truly reflect the most fundamental, and therefore universal, properties of life. We must learn how the environment can modify biosignatures, and how technology can enable an array of biosignatures to be detected remotely within realistic budgetary constraints

DesMarais, David J.↗
DOE OSTI2014

Phylogeny and phylogeography of functional genes shared among seven terrestrial subsurface metagenomes reveal N-cycling and microbial evolutionary relationships

Comparative studies on community phylogenetics and phylogeography of microorganisms living in extreme environments are rare. Terrestrial subsurface habitats are valuable for studying microbial biogeographical patterns due to their isolation and the restricted dispersal mechanisms. Since the taxonomic identity of a microorganism does not always correspond well with its functional role in a particular community, the use of taxonomic assignments or patterns may give limited inference on how microbial functions are affected by historical, geographical and environmental factors. With seven metagenomic libraries generated from fracture water samples collected from five South African mines, this study was carried out to (1) screen for ubiquitous functions or pathways of biogeochemical cycling of CH 4 , S, and N; (2) to characterize the biodiversity represented by the common functional genes; (3) to investigate the subsurface biogeography as revealed by this subset of genes; and (4) to explore the possibility of using metagenomic data for evolutionary study. The ubiquitous functional genes are NarV, NPD, PAPS reductase, NifH, NifD, NifK, NifE, and NifN genes. Although these eight common functional genes were taxonomically and phylogenetically diverse and distinct from each other, the dissimilarity between samples did not correlate strongly with geographical or environmental parameters or residence time of the water. Por genes homologous to those of Thermodesulfovibrio yellowstonii detected in all metagenomes were deep lineages of Nitrospirae, suggesting that subsurface habitats have preserved ancestral genetic signatures that inform the study of the origin and evolution of prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Community Structure and Function of High-Temperature Chlorophototrophic Microbial Mats Inhabiting Diverse Geothermal Environments

Six phototrophic microbial mat communities from different geothermal springs (YNP) were studied using metagenome sequencing and geochemical analyses. The primary goals of this work were to determine differences in community composition of high-temperature phototrophic mats distributed across the Yellowstone geothermal ecosystem, and to identify metabolic attributes of predominant organisms present in these communities that may correlate with environmental attributes important in niche differentiation. Random shotgun metagenome sequences from six phototrophic communities (average ~53 Mbp/site) were subjected to multiple taxonomic, phylogenetic, and functional analyses. All methods, including G + C content distribution, MEGAN analyses, and oligonucleotide frequency based clustering, provided strong support for the dominant community members present in each site. Cyanobacteria were only observed in non-sulfidic sites; de novo assemblies were obtained for Synechococcus-like populations at Chocolate Pots (CP_7) and Fischerella-like populations at White Creek (WC_6). Chloroflexi-like sequences (esp. Roseiflexus and/or Chloroflexus spp.) were observed in all six samples and contained genes involved in bacteriochlorophyll biosynthesis and the 3-hydroxypropionate carbon fixation pathway. Other major sequence assemblies were obtained for a Chlorobiales population from CP_7 (proposed family Thermochlorobacteriaceae), and an anoxygenic, sulfur-oxidizing Thermochromatium-like (Gamma-proteobacteria) population from Bath Lake Vista Annex (BLVA_20). Additional sequence coverage is necessary to establish more complete assemblies of other novel bacteria in these sites (e.g., Bacteroidetes and Firmicutes); however, current assemblies suggested that several of these organisms play important roles in heterotrophic and fermentative metabolisms. Definitive linkages were established between several of the dominant phylotypes present in these habitats and important functional processes such as photosynthesis, carbon fixation, sulfur oxidation, and fermentation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Efficient α, β-motif finder for identification of phenotype-related functional modules

Background: Microbial communities in their natural environments exhibit phenotypes that can directly cause particular diseases, convert biomass or wastewater to energy, or degrade various environmental contaminants. Understanding how these communities realize specific phenotypic traits (e.g., carbon fixation, hydrogen production) is critical for addressing health, bioremediation, or bioenergy problems. Results: In this paper, we describe a graph-theoretical method for in silico prediction of the cellular subsystems that are related to the expression of a target phenotype. The proposed (a, b)-motif finder approach allows for identification of these phenotype-related subsystems that, in addition to metabolic subsystems, could include their regulators, sensors, transporters, and even uncharacterized proteins. By comparing dozens of genome-scale networks of functionally associated proteins, our method efficiently identifies those statistically significant functional modules that are in at least a networks of phenotype-expressing organisms but appear in no more than b networks of organisms that do not exhibit the target phenotype. It has been shown via various experiments that the enumerated modules are indeed related to phenotype-expression when tested with different target phenotypes like hydrogen production, motility, aerobic respiration, and acid-tolerance. Conclusion: Thus, we have proposed a methodology that can identify potential statistically significant phenotyperelated functional modules. The functional module is modeled as an (a, b)-clique, where a and b are two criteria introduced in this work. We also propose a novel network model, called the two-typed, divided network. The new network model and the criteria make the problem tractable even while very large networks are being compared. The code can be downloaded from http://www.freescience.org/cs/ABClique/

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗