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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Inventory of Composable Elements (ICE) v6.0.0

The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.

Plahar, Hector↗
DOE OSTI2018

Structures of chaperone-substrate complexes docked onto the export gate in a type III secretion system

The flagellum and the injectisome enable bacterial locomotion and pathogenesis, respectively. These nanomachines assemble and function using a type III secretion system (T3SS). Exported proteins are delivered to the export apparatus by dedicated cytoplasmic chaperones for their transport through the membrane. The structural and mechanistic basis of this process is poorly understood. Here we report the structures of two ternary complexes among flagellar chaperones (FliT and FliS), protein substrates (the filament-capping FliD and flagellin FliC), and the export gate platform protein FlhA. The substrates do not interact directly with FlhA; however, they are required to induce a binding-competent conformation to the chaperone that exposes the recognition motif featuring a highly conserved sequence recognized by FlhA. The structural data reveal the recognition signal in a class of T3SS proteins and provide new insight into the assembly of key protein complexes at the export gate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Crystal structure of the CoV-Y domain of SARS-CoV-2 nonstructural protein 3

Abstract Replication of the coronavirus genome starts with the formation of viral RNA-containing double-membrane vesicles (DMV) following viral entry into the host cell. The multi-domain nonstructural protein 3 (nsp3) is the largest protein encoded by the known coronavirus genome and serves as a central component of the viral replication and transcription machinery. Previous studies demonstrated that the highly-conserved C-terminal region of nsp3 is essential for subcellular membrane rearrangement, yet the underlying mechanisms remain elusive. Here we report the crystal structure of the CoV-Y domain, the most C-terminal domain of the SARS-CoV-2 nsp3, at 2.4 Å-resolution. CoV-Y adopts a previously uncharacterized V-shaped fold featuring three distinct subdomains. Sequence alignment and structure prediction suggest that this fold is likely shared by the CoV-Y domains from closely related nsp3 homologs. NMR-based fragment screening combined with molecular docking identifies surface cavities in CoV-Y for interaction with potential ligands and other nsps. These studies provide the first structural view on a complete nsp3 CoV-Y domain, and the molecular framework for understanding the architecture, assembly and function of the nsp3 C-terminal domains in coronavirus replication. Our work illuminates nsp3 as a potential target for therapeutic interventions to aid in the on-going battle against the COVID-19 pandemic and diseases caused by other coronaviruses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Crystal structure of a putative 3-hydroxypimelyl-CoA dehydrogenase, Hcd1, from Syntrophus aciditrophicus strain SB at 1.78 Å resolution

Syntrophus aciditrophicus strain SB is a model syntroph that degrades benzoate and alicyclic acids. Here, the structure of a putative 3-hydroxypimelyl-CoA dehydrogenase from S. aciditrophicus strain SB (SaHcd1) was resolved at 1.78 Å resolution. SaHcd1 contains sequence motifs and structural features that belong to the short-chain dehydrogenase/reductase (SDR) family of NADPH-dependent oxidoreductases. SaHcd1 is proposed to concomitantly reduce NAD + or NADP + to NADH or NADPH, respectively, while converting 3-hydroxypimelyl-CoA to 3-oxopimeyl-CoA. Further enzymatic studies are needed to confirm the function of SaHcd1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Operator Action Time Evaluation of Emergency Water Injection Strategy for Extreme SGTR Accidents

In terms of severe accidents caused by earthquakes or tsunamis that are beyond expectation, a special safety inspection for operating plants, following the Fukushima accident, has been conducted by the government of Korea to verify that nation's nuclear power plants have been adequately designed to respond to extreme accidents. The inspection results show that Korean nuclear power plants in operation have no imminent risk for an expected maximum potential earthquake or coastal flooding based on the up-to-date investigation. However, there is a need to implement long- and short-term safety improvements in order to secure the level of safety for natural beyond-design-basis events. One of the measures to increase the mitigation capability during extreme accidents is installing the injection flow paths to provide emergency cooling water of extemal sources using fire engines to the steam generators (SGs) or reactor cooling system (RCS). An emergency cooling water system consists of a fixed pipe connected from the RCS or SGs to the outside of the containment. A standby valve is installed on the pipe. Following the occurrence of an extreme accident, movable equipment (for example, a fire truck hose) can be connected to the pipe hole at the opening of the isolation valve. The emergency cooling water injection strategy was not taken into account for the steam generator tube rupture (SGTR) accident management strategy of the OPR-1000. Therefore, it is necessary to develop some guidelines or strategies to cope with an extreme SGTR scenarios using the newly installed injection flow paths and fire engines. As long as the fission products released from the core during severe accidents are kept inside the containment, there may be several ways to reduce the radionuclide release into the environment, for example, by using plant safety features. The containment bypass sequences, however, allow the fission products to be released into the environment or directly to the auxiliary building. The SGTR accidents, which are one of the containment bypass sequences, have shown during various probabilistic safety assessments (PSAs) to be contributors to plant risk, mainly because of their potential for causing a release outside containment. This paper is intended to be an investigation of the characteristics of accident progressions and assessments for the mitigative effectiveness of the external cooling water injection strategies during extreme SGTR accidents in a typical OPR-1000 plant. Analyses were performed using a MAAP computer code version 5.03. The MAAP code is a system-level computer code capable of conducting integral analyses of potential severe accident progressions in nuclear power plants, whose main purpose is to support a level 2 PSA or severe accident management strategy developments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Apollo: Democratizing genome annotation

Genome annotation is the process of identifying the location and function of a genome's encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, we present Apollo, an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform. Some of Apollo's newer user interface features include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

luoyunan/ECNet: First release

ECNet (evolutionary context-integrated neural network) is a deep learning model that guides protein engineering by predicting protein fitness from the sequence. It integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe.

Luo, Yunan↗
DOE OSTI2020

Fine Structures in the Main Sequence Revealed by Gaia Data Release 2

The Hertzsprung–Russell diagram (HRD) is fully examined using the Fourier analysis. This work shows more stars are above the gap in the lower main sequence than below it, and this implies that stars spend more time above the gap while they undergo variability associated with the {sup 3}He instability. The enhanced HRD also shows the width of the gap is not linear and depends on the G{sub BP}−G{sub RP} color up until G{sub BP}−G{sub RP}=2.7. Beyond this color limit, the gap is hardly seen. Besides, a new low density region is revealed for the first time centered at M {sub G} ≈ 10.7 and G {sub BP} − G {sub RP} ≈ 2.8, which is below the lower right corner of the gap. This work also shows that the main sequence appears to have fine stripes where stellar densities are relatively low or high compared to their adjacent regions on the main sequence. These stripes can be seen throughout the main sequence of stars redder than G {sub BP} − G {sub RP} = 0.8 and are not limited to any specific color or spectral type. Slopes of these features are different from the main sequence, but are pretty consistent throughout the main sequence, with a few exceptions. We are perplexed by these new features, but the complexities of stellar atmospheric features and opacities of dwarfs may have caused these patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Unified rational protein engineering with sequence-based deep representation learning

Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach predicts the stability of natural and de novo designed proteins, and the quantitative function of molecularly diverse mutants, competitively with the state-of-the-art methods. UniRep further enables two orders of magnitude efficiency improvement in a protein engineering task. Lastly, UniRep is a versatile summary of fundamental protein features that can be applied across protein engineering informatics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

RCSB Protein Data Bank 1D3D module: displaying positional features on macromolecular assemblies

Mapping positional features from one-dimensional (1D) sequences onto three-dimensional (3D) structures of biological macromolecules is a powerful tool to show geometric patterns of biochemical annotations and provide a better understanding of the mechanisms underpinning protein and nucleic acid function at the atomic level. We present a new library designed to display fully customizable interactive views between 1D positional features of protein and/or nucleic acid sequences and their 3D structures as isolated chains or components of macromolecular assemblies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Whole-genome demography of COVID-19 virus during its pandemic period and on “panvalent” vaccine design

With over 16 million submitted genomic sequences, the SARS-CoV-2 (SC2) virus, the cause of the most recent worldwide COVID-19 pandemic, has become the most sequenced genome of all known viruses, revealing, for example, a vast number of expanding viral lineages. Since the pandemic phase appears to be over, we performed a retrospective re-examination of the demographic grouping pattern and their genomic characteristics during the entire pandemic period up to the peak of the last pandemic wave. For our study, we extracted from the NCBI only unique viral sequences and converted each sequence data to a relational vector, indicating the presence/absence of each variational event compared to a “reference” sequence. Our study revealed several genomic features that are unexpected or different from those of previous studies. For example, approximately 44,000 variants with unique sequences emerged during the pandemic period; they group into only four major viral-genomic groups and each has a set of mostly unique highly-conserved variant-genotypes (HCVGs); and a small set from the first (“ancestral”) group was inherited by the three (“descendant”) groups, suggesting that HCVGs in the next group may be predictable from the current group(s). Such a concept may be potentially important in designing “panvalent” vaccines against the current and future waves of viral infections.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Introduction: Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aquatic environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogencoevolution. Methods: We developed and refined methods to sample and sequence cyanobacteria, cyanophages, and measured features of their abiotic environment. Results: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol from this exploratory effort included a combination of in-line and single vacuum flask filtrations, which reduced filtration processing time by over threefold in some cases compared to other tested methods, such as a fully in-line sequence or in-site filtrations. We successfully extracted an average of approximately 400–1200 ng for all filter fractions, with some variations between kits. Discussion: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons.

Salish Sea↗
DOE OSTI2022

Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning

ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Chimeric Fatty Acyl-Acyl Carrier Protein Thioesterases Provide Mechanistic Insight into Enzyme Specificity and Expression

Medium-chain fatty acids are commodity chemicals. Increasing and modifying the activity of thioesterases (TEs) on medium-chain fatty acyl-acyl carrier protein (acyl-ACP) esters may enable a high-yield microbial production of these molecules. The plant Cuphea palustris harbors two distinct TEs: C. palustris FatB1 ( Cp FatB1) (C 8 specificity, lower activity) and Cp FatB2 (C 14 specificity, higher activity) with 78% sequence identity. We combined structural features from these two enzymes to create several chimeric TEs, some of which showed nonnatural fatty acid production as measured by an enzymatic assay and gas chromatography-mass spectrometry (GC-MS). Substantially, chimera 4 exhibited an increased C 8 fatty acid production in correlation with improved microbial expression. This chimera led us to identify Cp FatB2-specific amino acids between positions 219 and 272 that lead to higher protein levels. Chimera 7 produced a broad range of fatty acids and appeared to combine a fatty acid binding pocket with long-chain specificity and an ACP interaction site that may activate fatty acid extrusion. Using homology modeling and in silico docking with ACP, we identified a “positive patch” within amino acids 162 to 218, which may direct the ACP interaction and regulate access to short-chain fatty acids. On the basis of this modeling, we transplanted putative ACP interaction sequences from Cp FatB1 into Cp FatB2 and created a chimeric thioesterase that produced medium-chain as well as long-chain fatty acids. Hence, the engineering of chimeric enzymes and characterizing their microbial activity and chain-length specificity suggested mechanistic insights into TE functions and also generated thioesterases with potentially useful properties. These observations may inform a rational engineering of TEs to allow alkyl chain length control. IMPORTANCE: Medium-chain fatty acids are important commodity chemicals. These molecules are used as plastic precursors and in shampoos and other detergents and could be used as biofuel precursors if production economics were favorable. Hydrocarbon-based liquid fuels must be optimized to have a desired boiling point, low freezing point, low viscosity, and other physical characteristics. Furthermore, the solubility and harshness of detergents and the flexibility of plastic polymers can be modulated. The length and distribution of the carbon chains in the hydrophobic tails determine these properties. The biological synthesis of cell membranes and fatty acids produces chains of primarily 16 to 18 carbons, which give rise to current biofuels. The ultimate goal of the work presented here is to engineer metabolic pathways to produce designer molecules with the correct number of carbons in a chain, so that such molecules could be used directly as specialty commodity chemicals or as fuels after minimal processing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox—called seqNMF—with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral data sets. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Abstract Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli , use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia lipolytica . A negative selection screen in the absence of non-homologous end-joining, the dominant DNA repair mechanism, was used to generate single guide RNA (sgRNA) activity profiles for both SpCas9 and LbCas12a. This genome-wide data served as input to a deep learning algorithm, DeepGuide, that is able to accurately predict guide activity. DeepGuide uses unsupervised learning to obtain a compressed representation of the genome, followed by supervised learning to map sgRNA sequence, genomic context, and epigenetic features with guide activity. Experimental validation, both genome-wide and with a subset of selected genes, confirms DeepGuide’s ability to accurately predict high activity sgRNAs. DeepGuide provides an organism specific predictor of CRISPR guide activity that with retraining could be applied to other fungal species, prokaryotes, and other non-conventional organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exploring a new definition of the green valley and its implications

ABSTRACT The distribution of galaxies on a colour–magnitude diagram reveals a bimodality, featuring a passively evolving red sequence and a star-forming blue cloud. The region between these two, the green valley (GV), represents a fundamental transition where quenching processes operate. We exploit an alternative definition of the GV using the 4000 Å break strength, an indicator that is more resilient than colour to dust attenuation. We compare and contrast our GV definition with the traditional one, based on dust-corrected colour, making use of data from the Sloan Digital Sky Survey. Our GV selection – that does not need a dust correction and thus does not carry the inherent systematics – reveals very similar trends regarding nebular activity (star formation, AGN, quiescence) to the standard dust-corrected 0.1(g − r). By use of high-SNR stacked spectra of the quiescent GV subsample, we derive the simple stellar population (SSP) age difference across the GV, a rough proxy of the quenching time-scale (Δt). We obtain an increasing trend with velocity dispersion (σ), from Δt ∼ 1.5 Gyr at σ = 100 km s−1, up to 3.5 Gyr at σ = 200 km s−1, followed by a rapid decrease in the most massive GV galaxies (Δt ∼ 1 Gyr at σ = 250 km s−1), suggesting two different modes of quenching, or the presence of an additional channel (rejuvenation).

Angthopo, James↗