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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transmission risk of Oropouche fever across the Americas

Abstract Background Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. Methods To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. Results Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. Conclusions Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

ToF-SIMS spectral data analysis of Paenibacillus sp. 300A biofilms and planktonic cells

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.

Biofilms↗
DOE OSTI2021

Arabidopsis thaliana zinc accumulation in leaf trichomes is correlated with zinc concentration in leaves

Zinc (Zn) is a key micronutrient for plants and animals, and understanding Zn homeostasis in plants can improve both agriculture and human health. While root Zn transporters in plant model species have been characterized in detail, comparatively little is known about shoot processes controlling Zn concentrations and spatial distribution. Previous work showed that Zn hyperaccumulator species such as Arabidopsis halleri accumulate Zn and other metals in leaf trichomes. To date there is no systematic study regarding Zn accumulation in the trichomes of the non-accumulating, genetic model species A. thaliana. Here, we used Synchrotron X-Ray Fluorescence mapping to show that Zn accumulates at the base of trichomes of A. thaliana. Using transgenic and natural accessions of A thaliana that vary in bulk leaf Zn concentration, we demonstrate that higher leaf Zn increases total Zn found at the base of trichome cells. Our data indicates that Zn accumulation in trichomes is a function of the Zn status of the plant, and provides the basis for future studies on a genetically tractable plant species to understand the molecular steps involved in Zn spatial distribution in leaves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Heterogeneous Distribution of Erucic Acid in Brassica napus Seeds

Brassica napus (B. napus) is the world's most widely grown temperate oilseed crop. Although breeding for human consumption has led to removal of erucic acid from refined canola oils, there is renewed interest in the industrial uses of erucic acid derived from B. napus, and there is a rich germplasm available for use. Here, low- and high-erucic acid accessions of B. napus seeds were examined for the distribution of erucic acid-containing lipids and the gene transcripts encoding the enzymes involved in pathways for its incorporation into triacylglycerols (TAGs) across the major tissues of the seeds. In general, the results indicate that a heterogeneous distribution of erucic acid across B. napus seed tissues was contributed by two isoforms (out of six) of FATTY ACYL COA ELONGASE (FAE1) and a combination of phospholipid:diacylglycerol acyltransferase (PDAT)- and diacylglycerol acyltransferase (DGAT)-mediated incorporation of erucic acid into TAGs in cotyledonary tissues. An absence of the expression of these two FAE1 isoforms accounted for the absence of erucic acid in the TAGs of the lowerucic accession.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ToF-SIMS spectral analysis of Shewanella oneidensis MR-1 biofilms

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many powerful features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution, mass resolution, and mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Shewanella oneidensis MR-1 isolated from freshwater lake sediment in New York state. The MR-1 strain is known to have metal and sulfur reducing properties and it can be used for bioremediation and wastewater treatment. There is a current need to identify small molecules and fragments produced from bacterial biofilms, especially those from extracellular polymeric substance (EPS). Static ToF-SIMS spectra of MR-1 were obtained using an IONTOF TOF.SIMS V instrument equipped with a 25 keV Bi$^+_3$ metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids, fatty acids, flavonoids, and quinolones to other naturally occurring organic compounds. It is anticipated that the mass spectral identification of key peaks will assist detection of metabolites, EPS molecules like polysaccharides, and biologically relevant small organic molecules using ToF-SIMS in future surface and interface research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Engineering microbial consortia with rationally designed cellular interactions

Synthetic microbial consortia represent a frontier of synthetic biology that promises versatile engineering of cellular functions. They are primarily developed through the design and construction of cellular interactions that coordinate individual dynamics and generate collective behaviors. Here we review recent advances in the engineering of synthetic communities through cellular-interaction programming. We first examine fundamental building blocks for intercellular communication and unidirectional positive and negative interactions. Here, we then recap the assembly of the building blocks for creating bidirectional interactions in two-species ecosystems, which is followed by the discussion of engineering toward complex communities with increasing species numbers, under spatial contexts, and via model-guided design. We conclude by summarizing major challenges and future opportunities of engineered microbial ecosystems.

42 ENGINEERING↗
DOE OSTI2025

Spatial Glycomics and Kidney Disease

Glycans are critical for the kidney's physiological and pathological cellular functions, and our ability to reveal their spatial distributions within tissues has helped us reveal how these carbohydrate moieties are involved in many of these processes. This review discusses the role of different types of glycans in kidney biology and disease, common approaches used for glycan imaging, and how glycan imaging has helped us better understand kidney pathology. Here, we mainly focus on emerging methods using mass spectrometry imaging (MSI) because this technology is untargeted and provides complete information on glycan composition compared to the other methods, such as lectin and metabolite labeling, which are targeted and often inform only on the specific part of a glycan structure. We especially focus on protein N-glycosylation, as this is one of the most common post-translational modifications, and these moieties play a vital role in renal structure and function. The recent advancements in MSI of N-glycans we reviewed have provided new insights into the pathophysiology of the kidney and paved the way for clinical application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Phase II Final Technical Report: Dynamic Gamma-ray Imaging for In Vivo Tracking of Microelement Transport Across Plant-Microbial Systems

The Department of Energy Office of Biological and Environmental Research (DOE BER) Mesoscale to Molecules Bioimaging Technology Program aims to develop new imaging and measurement technology to enable in situ and dynamic imaging across a range of spatial and temporal scales. Various imaging modalities are required to span the complete spatiotemporal landscape for bioenergy and environmental bioimaging needs. The high-resolution gamma-ray spectroscopy, imaging, and sensitivity of new high-purity germanium (HPGe) instruments provide a unique opportunity to complement and enhance these research goals. The HPGe-based Gamma-ray Imager for Plant Research (GIPR) developed here provides non-invasive, in vivo measurements to dynamically track the uptake and distribution of multiple gamma-emitting radioactive elements simultaneously as they move from the soil microbiome into living plants. The hand portable GIPR utilizes commercially available radioisotopes to provide spatial and temporal imaging of plant microelement exchange for the broader scientific community.

Kiser, Matthew↗
DOE OSTI2026

Regional specialization in prefrontal cortex manifests in the reliability of task progression codes

The brain has the remarkable ability to guide the performance of complex tasks. Distinct prefrontal cortical areas make specific contributions to this ability, with the orbitofrontal cortex (OFC) critical for processing information related to trial outcomes and the dorsomedial prefrontal cortex (dmPFC) critical for sustained effort and selecting the right action at the right time. Yet, in both areas, neural activity represents both outcome- and action-related quantities. How similar neural representations support different functions remains unclear. Here, we compared OFC and dmPFC activity in rats performing a spatial alternation task. We show that, in contrast to other task-related variables, task progression is represented in both areas, but with distinct patterns of across-trial reliability that match each area’s previously documented functional specialization. Our results indicate that the engagement of reliable, task-phase-specific activity patterns differs across prefrontal regions in a manner well suited to engage different computations at different times.

Biological and medical sciences↗
DOE OSTI2023

Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition

Deep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in early visual cortex, images were preprocessed with three different spatial frequency (SF) channels, before they were fed to a layer of spiking neurons whose synaptic weights were updated using spike-timing-dependent-plasticity. We investigate how the quality of the represented objects changes under different SF bands and WTA-I schemes. We demonstrate that a network of 200 spiking neurons tuned to three SFs can efficiently represent objects with as little as 15 spikes per neuron. Furthermore, studying how core object recognition may be implemented using biologically plausible learning rules in SNNs may not only further our understanding of the brain, but also lead to novel and efficient artificial vision systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Growth modeling to evaluate alternative cultivation strategies to enhance national microalgal biomass production

In this paper, we present a model-based assessment of alternative cultivation strategies on algal biomass production within the conterminous United States. Our assessment focuses on two basic cultivation strategies: 1) seasonal rotation of three representative freshwater algal strains that are well suited for warm weather, cold weather, and all-season diverse weather conditions, respectively; and 2) variation between three open pond water depths (15cm, 20cm, and 25cm). The enhanced Biomass Assessment Tool (BAT) is applied on a site-specific, hourly basis at 5,832 North American Land Data Assimilation System Phase 2 1/8° meteorological model grid cells over a 30-year period (1980-2009) to evaluate the operational strategies. Recognizing that resource management decisions may also consider scales beyond the individual site, we also conduct a regional assessment of focused on 7 representative climate zones in the conterminous United States. Results demonstrate that the spatial variability of algal productivity is largely affected by the strain-specific growth response to light and temperature that vary significantly by climate zone and latitude. Therefore, with a limited set of alternative cultivation strategies, the BAT identified the best performing combination of cultivation strategies on a site-specific basis that considerably enhances national annual biomass productivity. Specifically, the appropriate choice of seasonal strain rotation is able to significantly dampen climate-driven seasonal and spatial variability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Impact of crowding on the diversity of expanding populations

Crowding effects critically impact the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide, they push each other apart, remodeling the structure and extent of the population’s range. Recent work has shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes, which controls the fate of new variants as long as they are rare, remains unclear. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria–Delbrück fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically “pushed out” of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone-size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power law for low-frequency clones. Our model predicts that the distribution depends on a single parameter—the characteristic growth layer thickness—and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of an Experimental Approach to Achieve Spatially Resolved Plant Root-Associated Metaproteomics Using an Agar-Plate System

Plant–microbe interactions in the rhizosphere play a vital role in plant health and productivity. The composition and function of root-associated microbiomes is strongly influenced by their surrounding environment, which is often customized by their host. How microbiomes change with respect to space and time across plant roots remains poorly understood, and methodologies that facilitate spatiotemporal metaproteomic studies of root-associated microbiomes are yet to be realized. Here, we developed a method that provides spatially resolved metaproteome measurements along plant roots embedded in agar-plate culture systems, which have long been used to study plants. Spatially defined agar “plugs” of interest were excised and subsequently processed using a novel peptide extraction method prior to metaproteomics, which was used to infer both microbial community composition and function. As a proof-of-principle, a previously studied 10-member community constructed from a Populus root system was grown in an agar plate with a 3-week-old Populus trichocarpa plant. Metaproteomics was performed across two time points (24 and 48 h) for three distinct locations (root base, root tip, and a region distant from the root). The spatial resolution of these measurements provides evidence that microbiome composition and expression changes across the plant root interface. Interrogation of the individual microbial proteomes revealed functional profiles related to their behavioral associations with the plant root, in which chemotaxis and augmented metabolism likely supported predominance of the most abundant member. This study demonstrated a novel peptide extraction method for studying plant agar-plate culture systems, which was previously unsuitable for (meta)proteomic measurements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Imaging beyond the surface region: Probing hidden materials via atomic force microscopy

Probing material properties at surfaces down to the single-particle scale of atoms and molecules has been achieved, but high-resolution subsurface imaging remains a nanometrology challenge due to electromagnetic and acoustic dispersion and diffraction. The atomically sharp probe used in scanning probe microscopy (SPM) has broken these limits at surfaces. Subsurface imaging is possible under certain physical, chemical, electrical, and thermal gradients present in the material. Of all the SPM techniques, atomic force microscopy has entertained unique opportunities for nondestructive and label-free measurements. Here, we explore the physics of the subsurface imaging problem and the emerging solutions that offer exceptional potential for visualization. We discuss materials science, electronics, biology, polymer and composite sciences, and emerging quantum sensing and quantum bio-imaging applications. The perspectives and prospects of subsurface techniques are presented to stimulate further work toward enabling noninvasive high spatial and spectral resolution investigation of materials including meta- and quantum materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Employing bacterial microcompartments to create privileged redox pools for biofuel production (Final report: Accomplishments)

Over the award period we made progress on all three objectives. We completed our goal of understanding the impact of cofactor recycling on pathway performance for a propanediol-related pathway (Objective 1) and coupled this data with kinetic metabolic models developed in Objective 3, resulting in several products (4 published research articles, 1 review and 3 other research manuscripts in preparation). We completed half of Objective 2 but found the pathway was incompatible with compartmentalization, which is an important but unexpected result. The details are relayed in the following sections, grouped by objective and task as applicable.

09 BIOMASS FUELS↗
DOE OSTI2020

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

How deep should we go to understand roots at the top of the world?

Harsh environmental conditions and the short summers of northern, high-latitude biomes impose unique constraints on the plants that live in the arctic tundra and the boreal forest. To escape the harsh aboveground environment, plants in these habitats often allocate a large portion of their biomass belowground to facilitate nutrient acquisition. In turn, the proximity of living plant roots to vast stores of sequestered soil carbon in these biomes means that shifts in rooting depth distribution and the size of the root–soil interface could significantly contribute to ongoing climate change. Indeed, plant ‘priming’ of rhizosphere decomposition via root exudation, particularly from shallowly distributed roots, can lead to losses of carbon from tundra soils. While we have a hard-won understanding of the distribution of plant communities across the arctic tundra and the boreal forest from direct field observations scaled to the landscape level using climate-informed mapping techniques (i.e. the Circumpolar Arctic Vegetation Map (CAVM); Walker et al. , 2005), these vegetation maps are only the tip of the iceberg (Iversen et al. , 2015). Root form and function remain hidden beneath the land surface. In an article recently published in New Phytologist , Blume-Werry et al. (2023, 10.1111/nph.18998) asked whether rooting depth distribution, and ensuing carbon emissions, could be inferred from commonly used vegetation mapping classifications across the pan-Arctic. An important question to guide our understanding, mapping, and prediction of belowground characteristics and ecosystem feedbacks at the top of the world. Unfortunately, they found that the answer was ‘not quite’. While rooting depth distribution varied demonstrably, in turn causing substantial changes in modeled carbon emissions via rhizosphere ‘priming’, variation across rooting depth profiles did not correspond with vegetation mapping classes. If we are unable to predict belowground rooting depth distributions across large spatial scales by leveraging aboveground vegetation community distributions, how then should belowground researchers proceed?

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Spatial scales of competition and a growth–motility trade-off interact to determine bacterial coexistence

The coexistence of competing species is a long-lasting puzzle in evolutionary ecology research. Despite abundant experimental evidence showing that the opportunity for coexistence decreases as niche overlap increases between species, bacterial species and strains competing for the same resources are commonly found across diverse spatially heterogeneous habitats. We thus hypothesized that the spatial scale of competition may play a key role in determining bacterial coexistence, and interact with other mechanisms that promote coexistence, including a growth–motility trade-off. To test this hypothesis, we let two Pseudomonas putida strains compete at local and regional scales by inoculating them either in a mixed droplet or in separate droplets in the same Petri dish, respectively. We also created conditions that allow the bacterial strains to disperse across abiotic or fungal hyphae networks. We found that competition at the local scale led to competitive exclusion while regional competition promoted coexistence. When competing in the presence of dispersal networks, the growth–motility trade-off promoted coexistence only when the strains were inoculated in separate droplets. Our results provide a mechanism by which existing laboratory data suggesting competitive exclusion at a local scale is reconciled with the widespread coexistence of competing bacterial strains in complex natural environments with dispersal.

59 BASIC BIOLOGICAL SCIENCES↗