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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DeepNeo: a webserver for predicting immunogenic neoantigens

Abstract Non-self epitopes, whether originated from foreign substances or somatic mutations, trigger immune responses when presented by major histocompatibility complex (MHC) molecules and recognized by T cells. Identification of immunogenically active neoepitopes has significant implications in cancer and virus medicine. However, current methods are mostly limited to predicting physical binding of mutant peptides and MHCs. We previously developed a deep-learning based model, DeepNeo, to identify immunogenic neoepitopes by capturing the structural properties of peptide-MHC pairs with T cell reactivity. Here, we upgraded our DeepNeo model with up-to-date training data. The upgraded model (DeepNeo-v2) was improved in evaluation metrics and showed prediction score distribution that better fits known neoantigen behavior. The immunogenic neoantigen prediction can be conducted at https://deepneo.net.

Kim, Jeong Yeon↗
DOE OSTI2020

Distinguishing Potassium Channel Resting State Conformations in Live Cells with Environment-Sensitive Fluorescence

Ion channels are polymorphic membrane proteins whose high-resolution structures offer images of individual conformations, giving us starting points for identifying the complex and transient allosteric changes that give rise to channel physiology. Here, we report live-cell imaging of voltage-dependent structural changes of voltage-gated Kv2.1 channels using peptidyl tarantula toxins labeled with an environment-sensitive fluorophore, whose spectral shifts enable identification of voltage-dependent conformation changes in the resting voltage sensing domain (VSD) of the channel. We synthesize a new environment-sensitive, far-red fluorophore, julolidine phenoxazone (JP) azide, and conjugate it to tarantula toxin GxTX to characterize Kv2.1 VSD allostery during membrane depolarization. JP has an inherent response to the polarity of its immediate surroundings, offering site-specific structural insight into each channel conformation. Using voltage-clamp spectroscopy to collect emission spectra as a function of membrane potential, we find that they vary with toxin labeling site, the presence of Kv2 channels, and changes in membrane potential. With a high-affinity conjugate in which the fluorophore itself interacts closely with the channel, the emission shift midpoint is 50 mV more negative than the Kv2.1 gating current midpoint. This suggests that substantial conformational changes at the toxin-channel interface are associated with early gating charge transitions and these are not concerted with VSD motions at more depolarized potentials. These fluorescent probes enable study of conformational changes that can be correlated with electrophysiology, putting channel structures and models into a context of live-cell membranes and physiological states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MassIVE MSV000095714

Proteomic analysis reveals translation-related proteins are significantly altered in response to stabilized G4s. Identification of the importance of translation factors in overcoming G4s led to the question of how E. coli cells generally respond to chemicals that stabilize such structures. As a first step in addressing this question, a proteomic analysis was carried out to measure the quantitative effects of NMM on the levels of individual proteins in E. coli. Protein levels from early log-phase cultures of delta-tolC and delta-tolC tufA::kan strains grown in the presence or absence of NMM were measured to assess how reduced EF- Tu levels and NMM impacted expression.

Bottom-up proteomics↗
DOE OSTI2018

Identification of an algal xylan synthase indicates that there is functional orthology between algal and plant cell wall biosynthesis

Summary Insights into the evolution of plant cell walls have important implications for comprehending these diverse and abundant biological structures. In order to understand the evolving structure–function relationships of the plant cell wall, it is imperative to trace the origin of its different components. The present study is focused on plant 1,4‐β‐xylan, tracing its evolutionary origin by genome and transcriptome mining followed by phylogenetic analysis, utilizing a large selection of plants and algae. It substantiates the findings by heterologous expression and biochemical characterization of a charophyte alga xylan synthase. Of the 12 known gene classes involved in 1,4‐β‐xylan formation, XYS 1/ IRX 10 in plants, IRX 7, IRX 8, IRX 9, IRX 14 and GUX occurred for the first time in charophyte algae. An XYS 1/ IRX 10 ortholog from Klebsormidium flaccidum , designated K. flaccidum XYLAN SYNTHASE ‐1 ( Kf XYS 1), possesses 1,4‐β‐xylan synthase activity, and 1,4‐β‐xylan occurs in the K. flaccidum cell wall. These data suggest that plant 1,4‐β‐xylan originated in charophytes and shed light on the origin of one of the key cell wall innovations to occur in charophyte algae, facilitating terrestrialization and emergence of polysaccharide‐based plant cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Application of electron backscatter diffraction techniques to quantify effects of aging on sub-grain and spatial heterogeneity in NMC cathodes

Identification and evaluation of structural heterogeneity in spent cathode materials is crucial to developing appropriate remediation strategies for novel recycling processes. Native heterogeneities may be exacerbated during the cell's operational lifetime, as sub-particle-scale variations induce anisotropic expansion and contraction upon cycling. Structural transformations resulting from repeated cycling and calendar aging predominantly occur at the secondary particle surface and at the grain boundaries (GBs) between primary particles. However, the diffusion and stress build up around and across GBs are poorly understood. In this study, electron backscatter diffraction (EBSD) is employed to track sub-grain lattice structure across a statistically relevant number of Li(Ni0.33Mn0.33Co0.33)O2 (NMC-111) particles. Specifically, differences in lattice misorientation – measured as the deviation from the grain's average orientation – are tracked as a function of position within the electrode (near current collector, middle, and near separator) and as a function of electrochemical cycling. Further, a novel method of structural analysis is developed, offering insight into sub-grain diffusion behavior by comparing lattice misorientation near the grain boundary versus in the grain bulk. The present results suggest that electrode-scale spatial heterogeneity in lattice structure is induced by initial manufacturing conditions, and that radial gradients in lattice misorientation evolve at the primary particle scale with repeated electrochemical cycling.

25 ENERGY STORAGE↗
DOE OSTI2024

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

3D cell mapping↗
DOE OSTI2018

Identification of a Structural Element in HIV-1 Gag Required for Virus Particle Assembly and Maturation

ABSTRACT Late in the HIV-1 replication cycle, the viral structural protein Gag is targeted to virus assembly sites at the plasma membrane of infected cells. The capsid (CA) domain of Gag plays a critical role in the formation of the hexameric Gag lattice in the immature virion, and, during particle release, CA is cleaved from the Gag precursor by the viral protease and forms the conical core of the mature virion. A highly conserved Pro-Pro-Ile-Pro (PPIP) motif (CA residues 122 to 125) [PPIP(122–125)] in a loop connecting CA helices 6 and 7 resides at a 3-fold axis formed by neighboring hexamers in the immature Gag lattice. In this study, we characterized the role of this PPIP(122–125) loop in HIV-1 assembly and maturation. While mutations P123A and P125A were relatively well tolerated, mutation of P122 and I124 significantly impaired virus release, caused Gag processing defects, and abolished infectivity. X-ray crystallography indicated that the P122A and I124A mutations induce subtle changes in the structure of the mature CA lattice which were permissive for in vitro assembly of CA tubes. Transmission electron microscopy and cryo-electron tomography demonstrated that the P122A and I124A mutations induce severe structural defects in the immature Gag lattice and abrogate conical core formation. Propagation of the P122A and I124A mutants in T-cell lines led to the selection of compensatory mutations within CA. Our findings demonstrate that the CA PPIP(122–125) loop comprises a structural element critical for the formation of the immature Gag lattice. IMPORTANCE Capsid (CA) plays multiple roles in the HIV-1 replication cycle. CA-CA domain interactions are responsible for multimerization of the Gag polyprotein at virus assembly sites, and in the mature virion, CA monomers assemble into a conical core that encapsidates the viral RNA genome. Multiple CA regions that contribute to the assembly and release of HIV-1 particles have been mapped and investigated. Here, we identified and characterized a Pro-rich loop in CA that is important for the formation of the immature Gag lattice. Changes in this region disrupt viral production and abrogate the formation of infectious, mature virions. Propagation of the mutants in culture led to the selection of second-site compensatory mutations within CA. These results expand our knowledge of the assembly and maturation steps in the viral replication cycle and may be relevant for development of antiviral drugs targeting CA.

Novikova, Mariia↗
DOE OSTI2022

Single-Cell Metabolomics with Rapid Determination of Chemical Formulas from Isotopic Fine Structures

Metabolomic measurements can provide functional readouts of cellular states and phenotypes. Here, we present a protocol for single-cell metabolomics that permits direct untargeted detection of a broad number of metabolites under ambient conditions, without the need for sample processing, and with high confidence in the discovery and identification of the molecular formulas for detected metabolites. This protocol describes combining fiber-based laser ablation electrospray ionization (f-LAESI) with a 21 Tesla Fourier transform ion cyclotron resonance mass spectrometer (21T-FTICR-MS) to obtain high confidence molecular formula information about detected metabolites. The f-LAESI source utilizes mid-infrared laser ablation through a sharp optical fiber tip, affording direct ambient analysis of cells without the need for sample processing. Using the 21T-FTICR-MS as a mass analyzer enabled measurement of the isotopic fine structure (IFS) for numerous metabolites simultaneously from single cells, and the IFSs were in turn computationally processed to rapidly determine the corresponding elemental compositions. This metabolomics technique complements other single cell omics measurement methods, helping to resolve complex molecular interactions that take place within cells unattainable from single cell transcriptomic and proteomics methods.

mass spectrometry, FTICR, FTMS, ultrahigh mass res↗
DOE OSTI2022

In situ visualization of multicomponents coevolution in a battery pouch cell

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

25 ENERGY STORAGE↗
DOE OSTI2019

Comparative Structural and Antigenic Characterization of Genetically Distinct Flavobacterium psychrophilum O-Polysaccharides

Little is known about the underlying basis of serotype specificity among strains of Flavobacterium psychrophilum , the agent of rainbow trout fry syndrome and bacterial cold-water disease. The identification of different heat-stable O-serotypes among strains of this gram-negative pathogen does, however, suggest structural variations in the O-polysaccharide (O-PS) moiety of cell surface lipopolysaccharide (LPS). A trisaccharide composed of L-rhamnose (L-Rha), 2-acetamido-2-deoxy-L-fucose (L-FucNAc) and 2-acetamido-4-R-2,4-dideoxy-D-quinovose (D-Qui2NAc4NR), where R represents a dihydroxyhexanamido derivative, was previously identified as the repeating unit of Fp CSF259-93 O-PS. Interestingly, the O-PS gene cluster of this strain and that of Fp 950106-1/1, which belongs to a different O-serotype, are identical except for wzy, which encodes the putative polymerase that links trisaccharide repeats into O-PS chains. We have now found from results of glycosyl composition analysis and high-resolution nuclear magnetic resonance, that the linkage of D-Qui2NAc4NR to L-Rha, which is α1-2 for Fp CSF259-93 versus β1-3 for Fp 950106-1/1, is the only structural difference between O-PS from these strains. The corresponding difference in O-serotype specificity was established from the reactions of rabbit and trout anti-F. psychrophilum antibody with purified O-PS and LPS. Moreover, LPS-based differences in antigenicity were noted between strains with O-PS loci identical to those of Fp CSF259-93 or Fp 950106-1/1, except for the genes predicted to direct synthesis of different R-groups in Qui2NAc4NR. The findings provide a framework for defining the genetic basis of O-PS structure and antigenicity and suggest that the repertoire of F. psychrophilum O-serotypes extends beyond what is presently recognized from serological studies of this important fish pathogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Transforming our understanding of chloroplast-associated genes through comprehensive characterization of protein localizations and protein-protein interactions

Bioenergy crops are a renewable source of fuels and are a critical base for building a carbon-neutral economy. Rational engineering of bioenergy crops has the potential to enhance the yields. However, our ability to engineer plants is limited because the functions of most genes remain unknown. Systematic characterization of gene function in plants thus has the potential to greatly accelerate bioenergy research. Here, we focus on the chloroplast, an underexplored energy-producing organelle that is a hallmark of plants. The chloroplast is one of the promising targets of biofuel crop engineering efforts because of its central role in photosynthesis, metabolism, and intracellular signaling. However, the protein composition of the chloroplast and the functions of most of its proteins remain poorly characterized. At the core of this project, we sought to comprehensively determine the localization of chloroplast-associated proteins and generate a spatially defined protein-protein interaction network for chloroplast. For this purpose, we used the leading model alga Chlamydomonas reinhardtii, which greatly increased experimental speed and throughput. We illustrated the value of our findings to land plants by determining the localization of Arabidopsis thaliana land plant homologs of the Chlamydomonas proteins. Altogether, we were successful in determining the localization of 1,034 chloroplast-associated proteins in Chlamydomonas. The localizations provide numerous insights into the spatial organization of chloroplasts and how they function to support photosynthesis. The localization patterns of distinct proteins revealed new chloroplast structures and revealed new spatial organization inside the chloroplast. We also identified new components of known chloroplast structures, such as the chloroplast envelope, nucleoid, plastoglobuli, and pyrenoid. We identified these new components by investigating the interacting partners of known proteins. Many proteins localized in both the chloroplast and other cellular structures, thereby hinting at new functions and communication between cellular structures. We also applied machine learning on the atlas to generate predictions for the location of all of the proteins in Chlamydomonas. This enabled us to assign putative functions to many uncharacterized proteins based on their cellular location. Altogether, this research establishes a rich resource that opens new avenues of investigation and guides future work in deciphering and manipulating chloroplast function. Next, we developed an extensive protein-protein interaction network for the chloroplast by performing affinity purification-mass spectrometry on ~1,150 tagged chloroplast-associated proteins, the first such large-scale study in any photosynthetic organism. This dataset reveals 4,694 high-confidence protein-protein interactions, offering insights into the functions of thousands of conserved poorly-characterized chloroplast proteins. This systematic identification of protein-protein interactions in the chloroplast also provides multiple exciting new research directions and a detailed blueprint of the chloroplast's operation. This research lays the groundwork to decipher the inner workings of the chloroplast, the cell structure at the heart of photosynthesis. The spatial atlas and protein-protein interactions reveal chloroplast organizational features that would not have been accessible with traditional approaches. The localization mapping, insights into the function, and research materials generated further provide a rich resource for the research community to advance the understanding of how the chloroplast is organized to enable engineering of enhanced photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Crystallographic Characterization of Sodium Ions in a Bacterial Leucine/Sodium Symporter

Na + is the most abundant ion in living organisms and plays essential roles in regulating nutrient uptake, muscle contraction, and neurotransmission. The identification of Na + in protein structures is crucial for gaining a deeper understanding of protein function in a physiological context. LeuT, a bacterial homolog of the neurotransmitter:sodium symporter family, uses the Na + gradient to power the uptake of amino acids into cells and has been used as a paradigm for the study of Na + -dependent transport systems. We have devised a low-energy multi-crystal approach for characterizing low-Z (Z ≤ 20) anomalous scattering ions such as Na + , Mg 2+ , K + , and Ca 2+ by combining Bijvoet-difference Fourier syntheses for ion detection and f” refinements for ion speciation. Using the approach, we experimentally identify two Na + bound near the central leucine binding site in LeuT. Using LeuT microcrystals, we also demonstrate that Na + may be depleted to study conformational changes in the LeuT transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification of a secretory heme‐binding protein from Nocardia seriolae involved in cell apoptosis

Abstract According to the whole‐genome bioinformatics analysis, a heme‐binding protein from Nocardia seriolae (HBP) was found. HBP was predicted to be a bacterial secretory protein, located at mitochondrial membrane in eukaryotic cells and have a similar protein structure with the heme‐binding protein of Mycobacterium tuberculosis , Rv0203. In this study, HBP was found to be a secretory protein and co‐localized with mitochondria in FHM cells. Quantitative analysis of mitochondrial membrane potential value, caspase‐3 activity, and transcription level of apoptosis‐related genes suggested that overexpression of HBP protein can induce cell apoptosis. In conclusion, HBP was a secretory protein which may target to mitochondria and involve in cell apoptosis in host cells. This research will promote the function study of HBP and deepen the comprehension of the virulence factors and pathogenic mechanisms of N. seriolae .

Wen, Yiming↗
DOE OSTI2022

Ferroelectric Ordering in Nanosized PbTiO 3

The insight into the three-dimensional configuration of ferroelectric ordering in ferroelectric nanomaterials is motivated by the application of the development of functional nanodevices and the structural designing. However, the atomic deciphering of the spatial distribution of ordered structure remains challenging for the limitation of dimension and probing techniques. Here, in this paper, a neutron pair distribution function (nPDF) was utilized to analyze the spontaneous polarization distribution of zero-dimensional PbTiO 3 nanoparticles in three dimensions, via the application of reverse Monte Carlo (RMC) modeling. The comprehensive identification with transmission electron microscopy verified the linear characteristics of polarization along the c-axis in the main body, while electric polarization distribution on the surface was enhanced abnormally. In addition, the correlation of dipole vectors extending to three unit cells below the surface is retained. This work shows an application of the micro/macroscale information to effectively decode the polarization structure of nanoferroelectrics, providing new views of designing nanoferroelectric devices.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Estimation of dynamic rotor loads for the rotor systems research aircraft: Methodology development and validation

The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.

Duval, R. W.↗
DOE OSTI2019

Discovery of a Novel Chemotype of Histone Lysine Methyltransferase EHMT1/2 (GLP/G9a) Inhibitors: Rational Design, Synthesis, Biological Evaluation, and Co-crystal Structure

Since the discovery of compound BIX01294 over 10 years ago, only a very limited number of nonquinazoline inhibitors of H3K9-specific methyltransferases G9a and G9a-like protein (GLP) have been reported. In this paper, we report the identification of a novel chemotype for G9a/GLP inhibitors, based on the underinvestigated 2-alkyl-5-aminoand 2-aryl-5-amino-substituted 3$H$-benzo[$e$][1,4]diazepine scaffold. Our research efforts resulted in the identification 12a (EML741), which not only maintained the high in vitro and cellular potency of its quinazoline counterpart, but also displayed improved inhibitory potency against DNA methyltransferase 1, improved selectivity against other methyltransferases, low cell toxicity, and improved apparent permeability values in both parallel artificial membrane permeability assay (PAMPA) and blood–brain barrier-specific PAMPA, and therefore might potentially be a better candidate for animal studies. Finally, the co-crystal structure of GLP in complex with 12a provides the basis for the further development of benzodiazepine-based G9a/GLP inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗