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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An Improved Top-Down Mass Spectrometry Characterization of Chlamydomonas reinhardtii Histones and Their Post-translational Modifications

We present an updated analysis of the linker and core histone proteins and their proteoforms in the green microalga Chlamydomonas reinhardtii by top-down mass spectrometry (TDMS). The combination of high-resolution liquid chromatographic separation, robust fragmentation high, mass spectral resolution, the application of a custom search algorithm, and extensive manual analysis enabled the characterization of 86 proteoforms across all four core histones H2A, H2B, H3 and H4, and the linker histone H1. All canonical H2A paralogs, which vary in their C-termini, were identified, along with an unreported non-canonical variant that had both high levels of acetylation and C-terminal truncations. Similarly, a majority of the canonical H2B paralogs were identified, along with a smaller non-canonical variant, H2B.v, that was highly acetylated. Histone H4 exhibited a novel acetylation profile that differs significantly from that found in other organisms. A majority of H3 was monomethylated at K4, while a small fraction of H3 was trimethylated at K4 and also highly acetylated.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomistic simulations of the Escherichia coli ribosome provide selection criteria for translationally active substrates

As genetic code expansion advances beyond l-α-amino acids to backbone modifications and new polymerization chemistries, delineating what substrates the ribosome can accommodate remains a challenge. The Escherichia coli ribosome tolerates non-l-α-amino acids in vitro, but few structural insights that explain how are available, and the boundary conditions for efficient bond formation are so far unknown. Here we determine a high-resolution cryogenic electron microscopy structure of the E. coli ribosome containing α-amino acid monomers and use metadynamics simulations to define energy surface minima and understand incorporation efficiencies. Reactive monomers across diverse structural classes favour a conformational space where the aminoacyl-tRNA nucleophile is <4 Å from the peptidyl-tRNA carbonyl with a Bürgi–Dunitz angle of 76–115°. Monomers with free energy minima that fall outside this conformational space do not react efficiently. This insight should accelerate the in vivo and in vitro ribosomal synthesis of sequence-defined, non-peptide heterooligomers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A broken translational symmetry state in an infinite-layer nickelate

A defining signature of strongly correlated electronic systems is a rich phase diagram, which consists of multiple broken symmetries, such as magnetism, superconductivity, and charge order. In the recently discovered nickelate superconductors a large antiferromagnetic exchange energy has been reported, which implies the existence of strong electronic correlations. However, signatures of a broken-symmetry state other than superconductivity have not yet been observed. Here, we observe charge ordering in infinite-layer nickelates La 1-x Sr x NiO 2 using resonant x-ray scattering. The parent compound orders along the Ni-O bond direction with an incommensurate wave vector, distinct from the stripe order observed in other nickelates that propagates along a direction 45º to the Ni-O bond. The resonance profile we measure indicates that ordering originates from the nickelate layers and induces a parasitic charge modulation of lanthanum electrons. After doping, the charge order diminishes and its wave vector shifts toward commensurate, indicating that strong electronic correlations are likely to be responsible for the ordered state. Our results suggest that the existence of charge order and its potential interplay with antiferromagnetic fluctuations and superconductivity are important themes in nickel-based superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advances in bioelectronics: Materials, devices, and translational applications

Modern electronics and materials science are bringing revolutionary advances to biointerface design and are shattering the limits of what is possible in the areas of biomedical diagnostics and sensing, neuroscience, and prosthetics. Furthermore, this special issue highlights the rapid progress in all areas of bioelectronics and includes contributions that explore the interfaces between electronics, materials science, and other engineering disciplines, as well as biochemistry, biophysics, and general biology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Ab initio translationally invariant nucleon-nucleus optical potentials

We combine the ab initio symmetry-adapted no-core shell model (SA-NCSM) with the single-particle Green's function approach to construct optical potentials rooted in first principles. Specifically, we show that total cross sections and phase shifts for neutron elastic scattering from a 4 He target with projectile energies between 0.5 and 10 MeV closely reproduce the experiment. In addition, we discuss an important new development that resolves a long-standing issue with spurious center-of-mass motion in the Green's function formalism for many-body approaches. Furthermore, the new development opens a path for first-principle predictions of cross sections for elastic scattering of single-nucleon projectiles, nucleon capture, and deuteron breakup reactions, feasible for a broad range of open-shell spherical and deformed nuclei in the SA-NCSM approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Microbial inputs at the litter layer translate climate into altered organic matter properties

Plant litter chemistry is altered during decomposition but it remains unknown if these alterations, and thus the composition of residual litter, will change in response to climate. Selective microbial mineralization of litter components and the accumulation of microbial necromass can drive litter compositional change, but the extent to which these mechanisms respond to climate remains poorly understood. We addressed this knowledge gap by studying needle litter decomposition along a boreal forest climate transect. Specifically, we investigated how the composition and/or metabolism of the decomposer community varies with climate, and if that variation is associated with distinct modifications of litter chemistry during decomposition. We analyzed the composition of microbial phospholipid fatty acids (PLFA) in the litter layer and measured natural abundance δ 13 CPLFA values as an integrated measure of microbial metabolisms. Changes in litter chemistry and δ 13 C values were measured in litterbag experiments conducted at each transect site. A warmer climate was associated with higher litter nitrogen concentrations as well as altered microbial community structure (lower fungi:bacteria ratios) and microbial metabolism (higher δ 13 CPLFA). Litter in warmer transect regions accumulated less aliphatic-C (lipids, waxes) and retained more O-alkyl-C (carbohydrates), consistent with enhanced 13 C-enrichment in residual litter, than in colder regions. These results suggest that chemical changes during litter decomposition will change with climate, driven primarily by indirect climate effects (e.g. greater nitrogen availability and decreased fungi:bacteria ratios) rather than direct temperature effects. A positive correlation between microbial biomass δ 13 C values and 13 C-enrichment during decomposition suggests that change in litter chemistry is driven more by distinct microbial necromass inputs than differences in the selective removal of litter components. Our study highlights the role that microbial inputs during early litter decomposition can play in shaping surface litter contribution to soil organic matter as it responds to climate warming effects such as greater nitrogen availability.

13C↗
DOE OSTI2022

SNF1-related protein kinase 1 represses Arabidopsis growth through post-translational modification of E2Fa in response to energy stress

Cellular sugar starvation and/or energy deprivation serves as an important signaling cue for the live cells to trigger the necessary stress adaptation response. When exposed to cellular energy stress (ES) conditions, the plants reconfigure metabolic pathways and rebalance energy status while restricting vegetative organ growth. Despite the vital importance of this ES-induced growth restriction, the regulatory mechanism underlying the response remains largely elusive in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

CALCIUM‐DEPENDENT PROTEIN KINASE32 regulates cellulose biosynthesis through post‐translational modification of cellulose synthase

Summary Cellulose is an essential component of plant cell walls and an economically important source of food, paper, textiles, and biofuel. Despite its economic and biological significance, the regulation of cellulose biosynthesis is poorly understood. Phosphorylation and dephosphorylation of cellulose synthases (CESAs) were shown to impact the direction and velocity of cellulose synthase complexes (CSCs). However, the protein kinases that phosphorylate CESAs are largely unknown. We conducted research in Arabidopsis thaliana to reveal protein kinases that phosphorylate CESAs. In this study, we used yeast two‐hybrid, protein biochemistry, genetics, and live‐cell imaging to reveal the role of calcium‐dependent protein kinase32 (CPK32) in the regulation of cellulose biosynthesis in A. thaliana . We identified CPK32 using CESA3 as a bait in a yeast two‐hybrid assay. We showed that CPK32 phosphorylates CESA3 while it interacts with both CESA1 and CESA3. Overexpressing functionally defective CPK32 variant and phospho‐dead mutation of CESA3 led to decreased motility of CSCs and reduced crystalline cellulose content in etiolated seedlings. Deregulation of CPKs impacted the stability of CSCs. We uncovered a new function of CPKs that regulates cellulose biosynthesis and a novel mechanism by which phosphorylation regulates the stability of CSCs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Soybean ( Glycine max ) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics

Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.

54 ENVIRONMENTAL SCIENCES↗