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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
DOE OSTI2023

Virus‐Based Pyroelectricity

Abstract The first observation of heat‐induced electrical potential generation on a virus and its detection through pyroelectricity are presented. Specifically, the authors investigate the pyroelectric properties of the M13 phage, which possesses inherent dipole structures derived from the noncentrosymmetric arrangement of the major coat protein (pVIII) with an α‐helical conformation. Unidirectional polarization of the phage is achieved through genetic engineering of the tail protein (pIII) and template‐assisted self‐assembly techniques. By modifying the pVIII proteins with varying numbers of glutamate residues, the structure‐dependent tunable pyroelectric properties of the phage are explored. The most polarized phage exhibits a pyroelectric coefficient of 0.13 µC m −2 °C −1 . Computational modeling and circular dichroism (CD) spectroscopy analysis confirm that the unfolding of α‐helices within the pVIII proteins leads to changes in phage polarization upon heating. Moreover, the phage is genetically modified to enable its pyroelectric function in diverse chemical environments. This phage‐based approach not only provides valuable insights into bio‐pyroelectricity but also opens up new opportunities for the detection of various viral particles. Furthermore, it holds great potential for the development of novel biomaterials for future applications in biosensors and bioelectric materials.

Kim, Han↗
DOE OSTI2020

Metabolic Pathway Engineering

Modern microbial and enzyme engineering and their advancement are increasingly dependent on the marriage of a wide range of sophisticated technologies. For students entering the field of biotechnology, the outlook is indeed daunting. Expertise at levels beyond that of simple familiarity will be needed to conduct competitive research. It goes without saying that to be competitive, all new researchers in this field will need basic preparation in molecular biology, biochemistry, and genetics. Further, experience working with concepts and experimental tools in enzyme biochemistry and kinetics, gene editing, computational metabolic pathway modeling, experimental pathway flux analysis, and computational clustering tools to process complex data sets will be vital for success. We speculate that most biotechnology researchers in early career at this time will build teams of collaborators to address these disparate science fields rather than attempt to become experts in one lab.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2024

High phenotypic and genotypic plasticity among strains of the mushroom-forming fungus Schizophyllum commune

Schizophyllum commune is a mushroom-forming fungus notable for its distinctive fruiting bodies with split gills. It is used as a model organism to study mushroom development, lignocellulose degradation and mating type loci. It is a hypervariable species with considerable genetic and phenotypic diversity between the strains. In this study, we systematically phenotyped 16 dikaryotic strains for aspects of mushroom development and 18 monokaryotic strains for lignocellulose degradation. There was considerable heterogeneity among the strains regarding these phenotypes. The majority of the strains developed mushrooms with varying morphologies, although some strains only grew vegetatively under the tested conditions. Growth on various carbon sources showed strain-specific profiles. The genomes of seven monokaryotic strains were sequenced and analyzed together with six previously published genome sequences. Moreover, the related species Schizophyllum fasciatum was sequenced. Although there was considerable genetic variation between the genome assemblies, the genes related to mushroom formation and lignocellulose degradation were well conserved. These sequenced genomes, in combination with the high phenotypic diversity, will provide a solid basis for functional genomics analyses of the strains of S. commune.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Engineering quorum-sensing circuits in Synechococcus elongatus PCC 7942 towards self-inducible systems

Despite significant potential for cyanobacteria as sustainable bioproduction chases, there are limited examples of scaled cyanobacterial bioproduction. In part, this is because most cyanobacterial species are poorly adapted to bioreactor cultivation conditions and lack features that facilitate biomass growth and harvesting at scale. We explored quorum sensing (QS) pathways derived from heterotrophic microbes as a method for autoinduction of gene expression circuits coordinated to population density in cyanobacteria. Here, we integrated genetic modules designed to produce and detect the diffusible QS signal, acyl-homoserine lactones (AHLs), in the cyanobacterial model, Synechococcus elongatus PCC 7942 (S. elongatus). We demonstrate that S. elongatus heterologously produces sufficient AHL signals to activate gene expression in a dose-dependent and population density-responsive manner. A hybrid combination of AHL synthesis enzyme from Vibrio fischeri (Lux system) with the transcription factor receiver from Pseudomonas aeruginosa (Las system) provides an ideal activation ratio and mitigates toxicity observed with some AHL systems. As a proof of concept, we coupled the QS pathway to the expression of a cell division inhibitory gene, cdv3, facilitating late-phase cell elongation, cell sedimentation, and improved biomass recovery. Our findings provide a foundation for the development of auto-induction systems leverageable to improve cyanobacterial biotechnology applications.

Acyl homoserine lactones (AHL)↗
DOE OSTI2024

Programmed cell death regulator BAP2 is required for IRE1-mediated unfolded protein response in Arabidopsis

Environmental and physiological situations can challenge the balance between protein synthesis and folding capacity of the endoplasmic reticulum (ER) and cause ER stress, a potentially lethal condition. The unfolded protein response (UPR) restores ER homeostasis or actuates programmed cell death (PCD) when ER stress is unresolved. The cell fate determination mechanisms of the UPR are not well understood, especially in plants. Here, we integrate genetics and ER stress profiling with natural variation and quantitative trait locus analysis of 350 natural accessions of the model species Arabidopsis thaliana . Our analyses implicate a single nucleotide polymorphism to the loss of function of the general PCD regulator BON-ASSOCIATED PROTEIN2 (BAP2) in UPR outcomes. We establish that ER stress-induced BAP2 expression is antagonistically regulated by the UPR master regulator, inositol-requiring enzyme 1 (IRE1), and that BAP2 controls adaptive UPR amplitude in ER stress and ignites pro-death mechanisms in conditions of UPR insufficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modeling and Optimization of Zeolites for Contaminant Removal from Coal Combustion Impoundment Leachates

Coal Combustion Residual (CCR) landfills in the U.S. can lead to elevated contaminant concentrations in groundwater and runoff, particularly of arsenic, boron, and selenium. Zeolites can be readily synthesized from materials contained within the coal combustion ash impoundments and can be cation-exchanged to enhance adsorption capacity, selectivity, and reactivity. However, the optimization of zeolites becomes a daunting task when accounting for the variety of Si:Al ratios, the species of extra-framework cations present, and the zeolite pore structure. Molecular simulations provide methods to study and guide the design of zeolites for the sorption of contaminants from aqueous solution. In this work, models that predict the sorption of arsenic, boron, and selenium from water using cation-exchanged zeolites. Because of the lack of experimental adsorption data for these species of contaminants, models were parametrized to reproduce the results of first-principles calculations and then used to predict sorption for zeolites for a dataset containing 6000 combinations of zeolites and sorption conditions. Machine learning was used to train a model to predict sorption for materials in this database based on the results of the molecular simulations. Next, a genetic algorithm was used to optimize zeolites for the removal of each contaminant from aqueous solution for individual impoundment sites based on contaminant concentrations reported by the Electric Power Research Institute.

Findley, John↗
DOE OSTI2023

eYGFPuv-Assisted Transgenic Selection in Populus deltoides WV94 and Multiplex Genome Editing in Protoplasts of P. trichocarpa × P. deltoides Clone ‘52-225’

Although CRISPR/Cas-based genome editing has been widely used for plant genetic engineering, its application in the genetic improvement of trees has been limited, partly because of challenges in Agrobacterium-mediated transformation. As an important model for poplar genomics and biotechnology research, eastern cottonwood (Populus deltoides) clone WV94 can be transformed by A. tumefaciens, but several challenges remain unresolved, including the relatively low transformation efficiency and the relatively high rate of false positives from antibiotic-based selection of transgenic events. Moreover, the efficacy of CRISPR-Cas system has not been explored in P. deltoides yet. Here, we first optimized the protocol for Agrobacterium-mediated stable transformation in P. deltoides WV94 and applied a UV-visible reporter called eYGFPuv in transformation. Our results showed that the transgenic events in the early stage of transformation could be easily recognized and counted in a non-invasive manner to narrow down the number of regenerated shoots for further molecular characterization (at the DNA or mRNA level) using PCR. We found that approximately 8.7% of explants regenerated transgenic shoots with green fluorescence within two months. Next, we examined the efficacy of multiplex CRISPR-based genome editing in the protoplasts derived from P. deltoides WV94 and hybrid poplar clone ‘52-225’ (P. trichocarpa × P. deltoides clone ‘52-225’). The two constructs expressing the Trex2-Cas9 system resulted in mutation efficiency ranging from 31% to 57% in hybrid poplar clone 52-225, but no editing events were observed in P. deltoides WV94 transient assay. The eYGFPuv-assisted plant transformation and genome editing approach demonstrated in this study has great potential for accelerating the genome editing-based breeding process in poplar and other non-model plants species and point to the need for additional CRISPR work in P. deltoides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimization of a Lightweight Floating Offshore Wind Turbine with Water Ballast Motion Mitigation Technology

Floating offshore wind turbines are a promising technology for addressing energy needs by utilizing wind resources offshore. The current state of the art is based on heavy, expensive platforms to survive the ocean environment. Typical design techniques do not involve optimization because of the computationally expensive time domain solvers used to model motions and loads in the ocean environment. However, this design uses an efficient frequency domain solver with a genetic algorithm to rapidly optimize the design of a novel floating wind turbine concept. The concept utilizes a liquid ballast mass to mitigate motions on a lightweight post-tensioned concrete platform. The simple cruciform-shaped design of the platform made of post-tensioned concrete is less expensive than steel, reducing the raw material and manufacturing cost. The use of ballast water to behave as a tuned mass damper allows a smaller platform to achieve the same motions as a much larger platform, thus reducing the mass and cost. The optimization techniques applied with these design innovations resulted in a design with a levelized cost of energy of USD 0.0753/kWh, roughly half the cost of the current state of the art.

Ramsay, William↗
DOE OSTI2024

Optimizing the location and configuration of disaster resilience hubs under transportation and electric power network failures

Natural disasters often result in failures of transportation network components and blackouts that imperil the wellbeing of vulnerable populations. In response to these events, resilience hubs have been proposed as a pre-disaster planning strategy to improve access to critical services. This paper introduces an optimization-based approach to locate and configure electric power-generating resilience hubs considering the possibility of failures in transportation and electric power systems. The model's objective is to identify hub locations and configurations that maximize transportation accessibility to the hubs and maximize the satisfaction of basic energy needs through hub-generated electric power. Besides a budget constraint, the model accounts for limits on the levels of hub energy generation vis-à-vis community energy demands, and on the transportation network distance of communities to hubs. Three heuristics are presented for the proposed planning problem. The first heuristic is a genetic algorithm (GA) with problem-specific solution generation procedures. The other two heuristics implement greedy search techniques. Numerical experiments were conducted, using data from rural Puerto Rico, to illustrate the application of the proposed model and heuristics, and examine their performance. In the numerical experiments, the GA heuristic found better solutions than the greedy heuristics. Additionally, design solutions consisting of spatially dispersed hubs with low energy generation capacity were better than solutions with spatially concentrated high-capacity hubs. Lastly, across a wide range of hub demand scenarios, only a small number of candidate hub locations consistently ranked among the best locations for establishing a hub.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Widespread misregulation of inter-species hybrid transcriptomes due to sex-specific and sex-chromosome regulatory evolution

When gene regulatory networks diverge between species, their dysfunctional expression in inter-species hybrid individuals can create genetic incompatibilities that generate the developmental defects responsible for intrinsic post-zygotic reproductive isolation. Both cis- and trans-acting regulatory divergence can be hastened by directional selection through adaptation, sexual selection, and inter-sexual conflict, in addition to cryptic evolution under stabilizing selection. Dysfunctional sex-biased gene expression, in particular, may provide an important source of sexually-dimorphic genetic incompatibilities. Here, we characterize and compare male and female/hermaphrodite transcriptome profiles for sibling nematode species Caenorhabditis briggsae and C. nigoni, along with allele-specific expression in their F 1 hybrids, to deconvolve features of expression divergence and regulatory dysfunction. Despite evidence of widespread stabilizing selection on gene expression, misexpression of sex-biased genes pervades F 1 hybrids of both sexes. This finding implicates greater fragility of male genetic networks to produce dysfunctional organismal phenotypes. Spermatogenesis genes are especially prone to high divergence in both expression and coding sequences, consistent with a “faster male” model for Haldane’s rule and elevated sterility of hybrid males. Moreover, underdominant expression pervades male-biased genes compared to female-biased and sex-neutral genes and an excess of cis-trans compensatory regulatory divergence for X-linked genes underscores a “large-X effect” for hybrid male expression dysfunction. Extensive regulatory divergence in sex determination pathway genes likely contributes to demasculinization of XX hybrids. The evolution of genetic incompatibilities due to regulatory versus coding sequence divergence, however, are expected to arise in an uncorrelated fashion. This study identifies important differences between the sexes in how regulatory networks diverge to contribute to sex-biases in how genetic incompatibilities manifest during the speciation process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genome-wide Association Study Identifies Candidate Loci with Major Contributions to the Genetic Control of Pod Morphological Traits in Snap Bean

Snap beans are cultivars of common bean (Phaseolus vulgaris) that are cultivated for their fleshy immature pods that exhibit a wide diversity of pod shapes and sizes. The genetic basis of the snap bean pod shape is complex and involves the interaction of multiple genes. This study used a snap bean diversity panel composed of heirloom and improved cultivars used in North America and genome-wide association studies (GWAS) to investigate the genetic basis of pod morphological characteristics, including length, width, height, width/height ratio, and coefficients of variation (CVs). The GWAS detected multiple genomic regions associated with each pod trait, with a total of 20 quantitative trait loci (QTLs) for pod length, 9 for pod width, 14 for pod height, and 10 for pod width/height ratio. Regarding theCVof each pod trait, genome-wide association analyses detected six QTL for lengthCVs, five for widthCVs, 15 for heightCVs, and six for width/height ratioCVs. Thirteen regions in seven chromosomes were associated with two or more pod traits. Eighteen QTLs for pod traits in this study colocated with previously reported QTLs for pod and seed traits. The QTL intervals encompass gene models with homologues in other species that are involved in the control of developmental processes. These results capture the complex nature of the genetic control of snap bean pod traits and confirm the significance of genomic regions harboring overlapping QTLs identified in this and other studies. The phenotypic expression of pod traits in snap bean appears to be under the control of a few genomic regions with a strong effect with additional contributions of multiple small-effect regions. Validation of the function of the candidate genes identified in associated regions will contribute to our understanding of legume pod development.

Agriculture↗
DOE OSTI2022

WormBase in 2022—data, processes, and tools for analyzing Caenorhabditis elegans

WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Revising the Role of Cortical Cytoskeleton during Secretion: Actin and Myosin XI Function in Vesicle Tethering

In plants, secretion of cell wall components and membrane proteins plays a fundamental role in growth and development as well as survival in diverse environments. Exocytosis, as the last step of the secretory trafficking pathway, is a highly ordered and precisely controlled process involving tethering, docking, and fusion of vesicles at the plasma membrane (PM) for cargo delivery. Although the exocytic process and machinery are well characterized in yeast and animal models, the molecular players and specific molecular events that underpin late stages of exocytosis in plant cells remain largely unknown. Here, by using the delivery of functional, fluorescent-tagged cellulose synthase (CESA) complexes (CSCs) to the PM as a model system for secretion, as well as single-particle tracking in living cells, we describe a quantitative approach for measuring the frequency of vesicle tethering events. Genetic and pharmacological inhibition of cytoskeletal function, reveal that the initial vesicle tethering step of exocytosis is dependent on actin and myosin XI. In contrast, treatments with the microtubule inhibitor, oryzalin, did not significantly affect vesicle tethering or fusion during CSC exocytosis but caused a minor increase in transient or aborted tethering events. With data from this new quantitative approach and improved spatiotemporal resolution of single particle events during secretion, we generate a revised model for the role of the cortical cytoskeleton in CSC trafficking.

Zhang, Weiwei↗
DOE OSTI2024

Assembly and Repair of Photosystem II in Chlamydomonas reinhardtii

Oxygenic photosynthetic organisms use Photosystem II (PSII) to oxidize water and reduce plastoquinone. Here, we review the mechanisms by which PSII is assembled and turned over in the model green alga Chlamydomonas reinhardtii. This species has been used to make key discoveries in PSII research due to its metabolic flexibility and amenability to genetic approaches. PSII subunits originate from both nuclear and chloroplastic gene products in Chlamydomonas. Nuclear-encoded PSII subunits are transported into the chloroplast and chloroplast-encoded PSII subunits are translated by a coordinated mechanism. Active PSII dimers are built from discrete reaction center complexes in a process facilitated by assembly factors. The phosphorylation of core subunits affects supercomplex formation and localization within the thylakoid network. Proteolysis primarily targets the D1 subunit, which when replaced, allows PSII to be reactivated and completes a repair cycle. While PSII has been extensively studied using Chlamydomonas as a model species, important questions remain about its assembly and repair which are presented here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Engineering of non-model eukaryotes for bioenergy and biochemical production

The prospect of leveraging naturally occurring phenotypes to overcome bottlenecks constraining the bioeconomy has marshalled increased exploration of nonconventional organisms. This review discusses the status of non-model eukaryotic species in bioproduction, the evaluation criteria for effectively matching a candidate host to a biosynthetic process, and the genetic engineering tools needed for host domestication. Here, we present breakthroughs in genome editing and heterologous pathway design, delving into innovative spatiotemporal modulation strategies that potentiate more refined engineering capabilities. We cover current understanding of genetic instability and its ramifications for industrial scale-up, highlighting key factors and possible remedies. Finally, we propose future opportunities to expand the current collection of available hosts and provide guidance to benefit the broader bioeconomy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Thermodynamic analysis and optimization of supercritical carbon dioxide Brayton cycles for use with low-grade geothermal heat sources

The transcritical carbon dioxide Rankine cycle has emerged as an alternative for power generation in low-grade heat applications. However, the low heat rejection temperatures required for condensing the carbon dioxide is almost prohibitive for many locations. A simple solution is the adoption of a supercritical carbon dioxide Brayton cycle which does not need such low temperature heat sinks. This power cycle has been poorly studied previously in low-grade heat applications. Therefore, with the aim of determining the performance and feasibility of the supercritical carbon dioxide Brayton cycle from thermodynamic viewpoint, using a low-grade geothermal heat source, this paper presents a comparative thermodynamic analysis between four different supercritical carbon dioxide Brayton cycles. For this purpose, detailed models were developed and solved by coupling the thermodynamic model with the thermal-hydraulic model of a Printed Circuit Heat Exchanger. Subsequently, simulations of a base case, a parametric analysis, and an optimization using Genetic Algorithms, were carried out. Results show that there is a combination of operating conditions that maximizes the electrical output of the system. Besides, some values of the minimum pressure of the cycles can increase substantially the precooler cooling water pumping power. At the optimum design point, using a 20 kg/s geothermal brine stream at 150 °C as heat source with a minimum allowable reinjection temperature of 70 °C, the Intercooled Recuperated Brayton Cycle achieved the highest electric power output, energy and exergy efficiencies, obtaining values of 779.99 kW, 11.51%, and 52.49%, respectively. The other feasible alternatives were the Recuperated Brayton Cycle, the Simple Brayton Cycle and the Intercooled Brayton Cycle, ranked, in that order.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering

Abstract CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

59 BASIC BIOLOGICAL SCIENCES↗