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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Readthrough of ACTN3 577X nonsense mutation produces full-length α-actinin-3 protein

Highlights: • ACTN3 577X gene expression is suppressed in mammalian cells. • Inhibition of nonsense-mediated mRNA decay (NMD) enhances 577X gene expression. • Aminoglycosides induce readthrough of the 577X codon. • NMD inhibition potentiates aminoglycoside-induced readthrough of the 577X gene. The ACTN3 gene encodes α-actinin-3 protein, which stabilizes the contractile apparatus at the Z-line in skeletal muscle cell fast fibers. A nonsense mutation of the arginine (R) at the codon for amino acid 577 of the ACTN3 gene generates a premature termination codon (PTC) and produces the R577X polymorphism in humans (X specifies translational termination). The ACTN3 577X genotype abolishes α-actinin-3 protein production due to targeted degradation of the mutant transcript by the cellular nonsense-mediated mRNA decay (NMD) system, which requires mRNA splicing. In humans, α-actinin-3 deficiency can decrease sprinting and power performance as well as skeletal muscle mass and strength. Here we investigated whether suppression of the in-frame PTC induced by treatment with the aminoglycosides gentamicin and G418 that promote termination codon readthrough could allow production of full-length α-actinin-3 protein from ACTN3 577X. We constructed expression plasmids encoding mature mRNA that lacks introns or pre-mRNA, which carries introns for the ACTN3 577X gene (X and X{sub pre}, respectively) and transfected the constructs into HEK293 cells. Similar constructs for the ACTN3 577R gene were used as controls. HEK293 cells carrying the X gene, but not the X{sub pre} gene, expressed exogenous truncated α-actinin-3 protein, indicating NMD-mediated suppression of exogenous X{sub pre} expression. Cells treated with aminoglycosides produced exogenous full-length α-actinin-3 protein in X-transfected cells, but not in X{sub pre}-transfected cells. The NMD inhibitor caffeine prevented suppression of X{sub pre} expression and thereby induced production of full-length α-actinin-3 protein in the presence of aminoglycoside. Together these results indicate that the ACTN3 R577X polymorphism could be a novel target for readthrough therapy, which may affect athletic and muscle performance in humans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Profiling of bioactive lipids in different dendritic cell subsets using an improved multiplex quantitative LC-MS/MS method

Highlights: • We improved a LC-MS/MS method to measure many mediators simultaneously. • Conventional DCs produce inflammatory lipids (leukotrienes) preferentially. • RA-DCs produce PGI{sub 2}, PGE{sub 2}, and TXA{sub 2} preferentially. Lipids are an energy source and key components of the cell membrane; however, they are also bioactive mediators of physiological and pathophysiological phenomena. Quantification of bioactive lipids is not easy because they have diverse chemical properties and are present in trace amounts. Here, we improved a multiplex method of quantifying bioactive lipids, thereby enabling measurement of 90 compounds simultaneously. We then used this system to quantify bioactive lipids produced by two subsets of dendritic cells (DCs): all-trans retinoic acid-treated DCs (RA-DCs) (a type of tolerogenic DC (tDC)) and conventional DCs (cDCs). We found that cDCs produced inflammatory lipid mediators such as leukotrienes, whereas RA-DCs produced anti-inflammatory lipid mediators such as prostaglandin I{sub 2}. Consistent with this, cDCs expressed larger amounts of mRNA encoding 5-lipoxygenase and LTA{sub 4} hydrolase (both responsible for leukotriene biosynthesis) and RA-DCs produced larger amounts of mRNA encoding prostaglandin I{sub 2} synthase. Taken together, the results suggest that the method is useful for clarifying the roles of bioactive lipids during immune responses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Synthesis and detoxification of nitric oxide in the plant beneficial rhizobacterium Bacillus amyloliquefaciens SQR9 and its effect on biofilm formation

Nitric oxide (NO) is an important gas signal that regulates many biological processes, and due to the high nitrogen recycling activity in the rhizosphere, NO is an important signaling molecule in this region. Thus, an understanding of the effect of NO on the rhizomicrobiome, especially on plant beneficial rhizobacteria, is important for the use of these bacteria in agriculture. In this study, the effect of exogenous NO on the beneficial rhizobacterium Bacillus amyloliquefaciens SQR9 was investigated. The results showed that low concentrations of NO increased the ability of the strain SQR9 to form biofilms, while high concentrations of NO inhibited the growth of this bacterium. The SQR9 gene yflM encodes nitric oxide synthase (NOS), which is used to synthesize NO, while the gene ykvO encodes a sepiapterin reductase that is used to synthesize tetrahydrobiopterin, the coenzyme of NOS. Isothermal titration calorimetry and high-performance liquid chromatography analyses demonstrated an interaction between YkvO and NADPH. SQR9 has two hmp genes, although only one was observed to be responsible for NO detoxification through oxidization. This study revealed the effect of NO on plant beneficial rhizobacterium and assessed the ability of this strain to adapt to exogenous NO, which will help to improve the application of this strain in agricultural production.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Characterization of diterpene synthase genes in the wild rice species Oryza brachyatha provides evolutionary insight into rice phytoalexin biosynthesis

Highlights: • Diterpene-type phtyoalexin oryzalexins are only found in Oryza sativa. • Copalyl diphosphate synthase (CPS) and kaurene synthase-like in turn make diterpenes. • A distant wild rice species O. brachyantha has different CPS activity to O. sativa. • CPS activity type determines the range of diterpene-type phytoalexins produced. • syn-CPS acquisition was necessary for evolution of oryzalexin S production in rice. Cultivated rice (Oryza sativa; Os) produces a variety of labdane-related diterpenoids; not only phytohormone gibberellins (GAs) but also phytoalexins for defense including phytocassanes, momilactones and oryzalexins. Their carbon skeleton diterpenes are constructed from geranylgeranyl diphosphate via ent-copalyl diphosphate (ent-CDP) or its diastereomer syn-CDP. These two-step reactions are successively catalyzed by homologs of the two diterpene synthases, ent-CDP synthase (ent-CPS) and ent-kaurene synthase (KS) that are responsible for the biosynthesis of GAs; e.g. OsCPS4 and OsKSL8 that are involved in the biosynthesis of oryzalexin S, a rice phytoalexin. Oryza brachyantha (Ob) is the most distant wild rice species from Os among the Oryza genus. We previously reported that the Ob genome contains ObCPS{sub 1}1g, ObKSL8-a, ObKSL8-b and ObKSL8-c for specialized metabolism at a locus similar to the OsKSL8 locus on chromosome 11. These Ob genes are closely related to OsCPS4 and OsKSL8, respectively. We herein characterize the diterpene synthase genes in Ob, using functional analyses and expression analysis. Recombinant OsKSL8 and ObKSL8-a showed the same in vitro function when syn-CDP or normal-CDP were used as substrates. Nonetheless, our results suggest that Ob produces normal-CDP-related diterpenoid phytoalexins, presumably via ObKSL8-a, while Os produces a syn-CDP-related phytoalexin, oryzalexin S, via OsKSL8. This difference must be due to the kinds of CPS that are present in each species; Os has OsCPS4 encoding syn-CPS, while Ob has ObCPS{sub 1}1g encoding normal-CPS. Thus, we propose the evolutionary history underlying oryzalexin S biosynthesis: the gain of a syn-CPS was a critical event allowing the biosynthesis of oryzalexin S.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Tissue-specific variation in 5-terminal exons of mouse Anoctamin 1 transcript induces N-terminal variation of its protein via alternative translational start sites

Anoctamin 1 (encoded by the Ano1 gene) is a Ca{sup 2+}-activated Cl{sup −} channel critical to many physiological functions. It has been speculated that Ano1 expression is regulated in a tissue-dependent manner via alternative promoters. However, variation in the 5-end sequence of mouse Ano1 (mAno1) and its tissue-dependent regulation are poorly understood. We identified a novel 5-terminal exon (designated exon 1a) of mAno1 instead of the known 5-terminal exon (exon 0) using 5-rapid amplification of cDNA ends (RACE) analysis. Unexpectedly, the novel 5-end variant mAno1{sub Ex1a} was abundantly expressed in many tissues including the salivary and mammary glands, rectum, lung, trachea and prostate. In contrast, the known variant mAno1{sub Ex0} predominated only in male reproductive tissues such as the epididymis and testis. In a heterologous expression system, mAno1{sub Ex0} encoded a longer protein than mAno1{sub Ex1a}, and this long isoform was abolished by a mutation in the exon 0 start codon. Moreover, the mAno1{sub Ex0}-specific N-terminal sequence was immunohistochemically detected in epididymis but not in salivary gland. Our data suggest that mAno1 expression is regulated via alternative promoters, and its transcriptional variation results in variation of the N-terminal sequence of the Ano1 protein due to the alternative translation initiation sites. These tissue-specific variations might contribute to the regulation of mAno1 expression and activity according to the physiological function of each tissue.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Global regulatory function of the low oxygen-induced transcriptional regulator LoiA in Salmonella Typhimurium revealed by RNA sequencing

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a major intestinal pathogen that can infect both humans and a variety of animals. LoiA, a novel virulence-regulating protein encoded in Salmonella pathogenicity island (SPI)-14, has been shown to be induced under low oxygen conditions and contribute to S. Typhimurium invasion into intestinal epithetical cells by activating the SPI-1 invasion genes. However, the global regulatory network of LoiA remains unknown. Here, we used high-throughput RNA sequencing (RNA-seq) technology to investigate the regulatory function of LoiA in S. Typhimurium under low oxygen conditions. A total of 1250 genes were differentially expressed between the loiA mutant and the wild-type strain; 413 genes were up-regulated and 837 were down-regulated. SPI-1 gene expression was down-regulated in the loiA mutant, consistent with previous results. SPI-2 gene expression was not affected by deletion of loiA; the expression of most genes involved in flagellar basal body and hook biosynthesis was up-regulated in the loiA mutant, while the expression of genes associated with flagellin, motility, and chemotaxis was down-regulated; the expression of lon, encoding an ATP-dependent protease, was up-regulated in the mutant. This study indicates that LoiA regulates a variety of virulence-associated genes in S. Typhimurium. The negative regulation of Lon protease by LoiA indicates that LoiA can regulates several virulence-associated genes in S. Typhimurium via the Lon protease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Evolutionary conservation of transferrin genomic organization and expression characterization in seven freshwater turtles

Highlights: • Transferrin have evolutionary conservation in genomic organization in freshwater turtles. • Transferrin have evolutionary conservation in expression characterization in freshwater turtles. • 12 positive selected sites were detected in freshwater turtles which were mainly located on the surface of Tf proteins. Serum transferrin (tf), encoding an iron-binding glycoprotein, has been revealed to play important roles in iron transportation and immune response, and it also has been demonstrated to be valuable for phylogenetic analysis in vertebrates. However, the evolutionary conservation, expression profiles and positive selection of transferrin genes among freshwater turtle species remain largely unclear. Here, the genomic DNA and coding sequences of transferrin genes were cloned and characterized in seven freshwater turtles including Mauremys mutica, Mauremys sinensis, Cyclemys dentate, Mauremyssi reevesi, Heosemys grandis, Trachemys scripta and Chrysemys picta. The isolated coding sequences of turtles' tf genes were 2118 bp or 2121 bp, encoding 706 or 707 amino acids. The predicted Tf proteins of turtles share high identities with M. mutica Tf, up to 91%–98% and the M. mutica Tf has the highest identity (91%) in amino acid with the Chelomia mydas Tf, the moderate with other reptiles' Tfs (65%–59%), chicken (58%), and Human Tf (∼55%), and the lowest with zebrafish Tf (41%). Additionally, tf genes were consistently composed of 17 exons and 16 introns with the same splicing sites in introns in all the turtles examined. Moreover, 12 positive selected sites were detected in these turtles’ Tf and mainly distributed on the surface of transferrin protein. Importantly, it was found that transferrin genes in all turtles examined were predominantly expressed in adult liver via real-time quantitative PCR. The molecular characterizations and expression profiles of transferrin would shed new insights into understanding the conversations and divergences of transferrin genes in turtles, even in vertebrates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Seismicity-constrained fault detection and characterization with a multitask machine learning model

Geological fault detection and characterization are crucial for understanding subsurface dynamics across scales. While methods for fault delineation based on either seismicity location analysis or seismic image reflector discontinuity are well-established, a systematic approach that integrates both data types remains absent. We develop a novel machine learning model that unifies seismic reflector images and seismicity location information to automatically identify geological faults and characterize their geometrical properties. The model encodes a seismic image and a seismicity location image separately, and fuses the encoded features with a spatial-channel attention fusion module to improve the learning of important features in both inputs. We design an automated strategy to generate high-quality synthetic training data and labels. To improve the realism of the seismicity location image, we include random seismicity noise and missing seismicity location associated with some of the faults. We validate the model’s efficacy and accuracy using synthetic data examples and two field data examples. Moreover, we show that fine-tuning the trained model with a small, domain-specific dataset enhances its fidelity for field data applications. The results demonstrate that integrating seismicity location and seismic images into a unified framework allows the end-to-end neural network to achieve higher fidelity and accuracy in delineating subsurface faults and their geometrical properties compared with image-only fault detection methods. Our approach offers an adaptive data-driven tool for geological fault characterization and seismic hazard mitigation, bridging the gap between seismicity location and image-based fault detection methods.

58 GEOSCIENCES↗
DOE OSTI2023

Mining metatranscriptomes reveals a vast world of viroid-like circular RNAs

Viroids and viroid-like covalently closed circular (ccc) RNAs are minimal replicators that typically encode no proteins and hijack cellular enzymes for replication. The extent and diversity of viroid-like agents are poorly understood. We developed a computational pipeline to identify viroid-like cccRNAs and applied it to 5,131 metatranscriptomes and 1,344 plant transcriptomes. The search yielded 11,378 viroid-like cccRNAs spanning 4,409 species-level clusters, a 5-fold increase compared to the previously identified viroid-like elements. Within this diverse collection, we discovered numerous putative viroids, satellite RNAs, retrozymes, and ribozy-like viruses. Diverse ribozyme combinations and unusual ribozymes within the cccRNAs were identified. Self-cleaving ribozymes were identified in ambiviruses, some mito-like viruses and capsid-encoding satellite virus-like cccRNAs. The broad presence of viroid-like cccRNAs in diverse transcriptomes and ecosystems implies that their host range is far broader than currently known, and matches to CRISPR spacers suggest that some cccRNAs replicate in prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗
DOE OSTI2018

An atomistic building block description of C-S-H - Towards a realistic C-S-H model

Understanding the atomistic structure of Calcium silicate hydrate (C-S-H), the main product of cement hydration, is of paramount importance to better formulate sustainable cement. The existing atomistic models are not in total agreement with experimental results and fail to explain the nanosized nature of C-S-H. Here, we present a new approach for describing the complexity of these structures at the molecular level, enabling a detailed comparison of C-S-H models. The new methodology encodes a full, large scale atomistic C-S-H structure by a simple, readable string of characters, similar to the way the base sequence in DNA encodes a vast range of different proteins. We then use the methodology to assess 14 Å tobermorite-defect structures and their stabilities using DFT and classical molecular dynamics. Finally we highlight how the model may be extended to develop reliable atomistic C-S-H models for a range of Ca/Si ratios and conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Virion glycosylation influences mycobacteriophage immune recognition

Glycosylation of eukaryotic virus particles is common and influences their uptake, trafficking, and immune recognition. In contrast, glycosylation of bacteriophage particles has not been reported; phage virions typically do not enter the cytoplasm upon infection, and they do not generally inhabit eukaryotic systems. We show here that several genomically distinct phages of Mycobacteria are modified with glycans attached to the C terminus of capsid and tail tube protein subunits. These O-linked glycans influence antibody production and recognition, shielding viral particles from antibody binding and reducing production of neutralizing antibodies. Glycosylation is mediated by phage-encoded glycosyltransferases, and genomic analysis suggests that they are relatively common among mycobacteriophages. Putative glycosyltransferases are also encoded by some Gordonia and Streptomyces phages, but there is little evidence of glycosylation among the broader phage population. The immune response to glycosylated phage virions in mice suggests that glycosylation may be an advantageous property for phage therapy of Mycobacterium infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗
DOE OSTI2022

Co-optimized machine-learned manifold models for large eddy simulation of turbulent combustion

Many modeling approaches in large eddy simulation (LES) of turbulent combustion employ a projection of the thermochemical state onto a low-dimensional manifold within state space to reduce the number of transported variables and hence computational cost. Flamelet-generated manifolds (FGM) is an example of a well-established, physics-based approach, but increasingly, principal component analysis (PCA) is being used as a data-driven method for generating manifold models. For both approaches, the nonlinear relationship between the location on the predefined manifold and the outputs of interest, such as reaction rates, can be tabulated or encoded in a neural network. This work proposes a new approach for manifold modeling that extends these existing approaches. A modified neural network structure simultaneously encodes the definition of the manifold variables, the nonlinear mapping, and the subfilter closure for LES. This allows all three of these aspects of the model to be co-optimized, generating a model from any source of combustion thermochemical state data. The manifold parameterizing variables are constrained to be linear combinations of species, as in FGM and PCA-based models, to aid in interpretability and implementation. For LES, subfilter variances of the manifold variables are also included as inputs. Two types of a priori analysis are performed to evaluate the new approach. In the first, the model is trained on data from one-dimensional premixed flames. In this case, the approach recovers the behavior of flamelet-based manifold approaches, and in fact slightly improves performance by identifying an optimized progress variable. The approach is also applied to data from direct numerical simulations of spherical ignition kernels in isotropic turbulence. For any specified manifold dimensionality, the new approach provides substantially lower prediction errors than a PCA-based model developed from the same data set. Additionally, the LES formulation of the new approach can provide accurate predictions for filtered reaction rates across a variety of filter widths.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An orphan gene BOOSTER enhances photosynthetic efficiency and plant productivity

Organelle-to-nucleus DNA transfer is an ongoing process playing an important role in the evolution of eukaryotic life. Here, genome-wide association studies (GWAS) of non-photochemical quenching parameters in 743 Populus trichocarpa accessions identified a nuclear-encoded genomic region associated with variation in photosynthesis under fluctuating light. The identified gene, BOOSTER (BSTR), comprises three exons, two with apparent endophytic origin and the third containing a large fragment of plastid-encoded Rubisco large subunit. Higher expression of BSTR facilitated anterograde signaling between nucleus and plastid, which corresponded to enhanced expression of Rubisco, increased photosynthesis, and up to 35% greater plant height and 88% biomass in poplar accessions under field conditions. Overexpression of BSTR in Populus tremula × P. alba achieved up to a 200% in plant height. Similarly, Arabidopsis plants heterologously expressing BSTR gained up to 200% in biomass and up to 50% increase in seed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Functional activity and functional gene diversity of a Cu-contaminated soil remediated by aided phytostabilization using compost, dolomitic limestone and a mixed tree stand

Trace elements (TEs) availability, biochemical activity and functional gene diversity was studied in a Cu-contaminated soil, revegetated for six years with a mixed stand of willow, black poplar, and false indigo-bush, and amended or not with compost plus dolomitic limestone (OMDL). The OMDL amendment significantly reduced Cu and As availability and soil toxicity, and increased the biochemical activity and microbial functional diversity assessed with the GEOCHIP technique, as compared to the unamended soil (Unt). The OMDL soil showed significantly higher abundance of 25 functional genes involved in decomposition organic compounds, and 11, 3 and 11 functional genes involved in the N, P and S biogeochemical cycles. Functional gene abundance was positively correlated with nutrient contents but negatively correlated with Cu availability and soil toxicity. The abundance of microbial functional genes encoding for resistance to various TEs also increased, possibly due to the microbial proliferation and lower Cu exposure in the presence of high total soil Cu concentration. Genes encoding for antibiotic resistance due to the co-occurrence of TEs and antibiotic resistant genes on genetic mobile elements. Finally, overall, phytomanagement confirmed its potential to restore the biological fertility and diversity of a severely Cu-contaminated soil, but the increase of TEs and antibiotic resistant gene abundances deserve attention in future studies.

54 ENVIRONMENTAL SCIENCES↗