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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 307 records · Page 17

Implied alignment: a synapomorphy-based multiple-sequence alignment method and its use in cladogram search

A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Non-NASA Center↗

The use of additive and subtractive approaches to examine the nuclear localization sequence of the polyomavirus major capsid protein VP1

A nuclear localization signal (NLS) has been identified in the N-terminal (Ala1-Pro-Lys-Arg-Lys-Ser-Gly-Val-Ser-Lys-Cys11) amino acid sequence of the polyomavirus major capsid protein VP1. The importance of this amino acid sequence for nuclear transport of VP1 protein was demonstrated by a genetic "subtractive" study using the constructs pSG5VP1 (full-length VP1) and pSG5 delta 5'VP1 (truncated VP1, lacking amino acids Ala1-Cys11). These constructs were used to transfect COS-7 cells, and expression and intracellular localization of the VP1 protein was visualized by indirect immunofluorescence. These studies revealed that the full-length VP1 was expressed and localized in the nucleus, while the truncated VP1 protein was localized in the cytoplasm and not transported to the nucleus. These findings were substantiated by an "additive" approach using FITC-labeled conjugates of synthetic peptides homologous to the NLS of VP1 cross-linked to bovine serum albumin or immunoglobulin G. Both conjugates localized in the nucleus after microinjection into the cytoplasm of 3T6 cells. The importance of individual amino acids found in the basic sequence (Lys3-Arg-Lys5) of the NLS was also investigated. This was accomplished by synthesizing three additional peptides in which lysine-3 was substituted with threonine, arginine-4 was substituted with threonine, or lysine-5 was substituted with threonine. It was found that lysine-3 was crucial for nuclear transport, since substitution of this amino acid with threonine prevented nuclear localization of the microinjected, FITC-labeled conjugate.

Non-NASA Center↗

Comparative sequence analyses on the 16S rRNA (rDNA) of Bacillus acidocaldarius, Bacillus acidoterrestris, and Bacillus cycloheptanicus and proposal for creation of a new genus, Alicyclobacillus gen. nov

Comparative 16S rRNA (rDNA) sequence analyses performed on the thermophilic Bacillus species Bacillus acidocaldarius, Bacillus acidoterrestris, and Bacillus cycloheptanicus revealed that these organisms are sufficiently different from the traditional Bacillus species to warrant reclassification in a new genus, Alicyclobacillus gen. nov. An analysis of 16S rRNA sequences established that these three thermoacidophiles cluster in a group that differs markedly from both the obligately thermophilic organisms Bacillus stearothermophilus and the facultatively thermophilic organism Bacillus coagulans, as well as many other common mesophilic and thermophilic Bacillus species. The thermoacidophilic Bacillus species B. acidocaldarius, B. acidoterrestris, and B. cycloheptanicus also are unique in that they possess omega-alicylic fatty acid as the major natural membranous lipid component, which is a rare phenotype that has not been found in any other Bacillus species characterized to date. This phenotype, along with the 16S rRNA sequence data, suggests that these thermoacidophiles are biochemically and genetically unique and supports the proposal that they should be reclassified in the new genus Alicyclobacillus.

Non-NASA Center↗

Tuning the Mechanical Properties of Crosslinked Copolymers via Sequence and Solvent‐Selective Swelling for Vat Photopolymerization

Block copolymers (BCPs) offer distinct advantages for vat photopolymerization by enabling mechanically programmable network structures through microphase-separated morphologies that can be kinetically trapped during curing, yielding properties unattainable in homogeneous resins. However, the respective roles of repeat-unit sequence and solvent environment, together with their interplay in directing network formation and mechanical performance, remain unclear. Here, we synthesize a series of CO 2 -based polycarbonate copolymers comprising a crosslinkable glassy poly(vinyl cyclohexene carbonate) (PVCHC, A block) and a non-crosslinkable soft poly(propylene carbonate) (PPC, B block). The polymer sequence is systematically varied (ABA, BAB, and statistical), and solvent choice controls block-selective swelling to jointly control gelation behavior, microphase morphology, and mechanical response through changes in the accessibility and local environment of photocrosslinkable vinyl groups during network formation, as revealed by photorheology and small angle x-ray scattering. By tuning polymer sequence and curing solvent, we transform nominally identical formulations from brittle to highly ductile materials, achieving a three-orders-of-magnitude range in toughness (0.003 to 9.1 MJ m −3 ). These results establish clear structure–processing–property relationships and identify polymer sequence and selective solvation as powerful strategies for programming both printability and performance of block copolymer resins for additive manufacturing.

additive manufacturing↗

Uncovering Sequence and Structural Characteristics of Fungal Expansin‐Related Proteins With Potential to Drive Substrate Targeting

Expansins loosen plant cell wall networks through disrupting non-covalent bonds between cellulose microfibrils and matrix polysaccharides. Whereas expansins were first discovered in plants, expansin-related proteins have since been identified in bacteria and fungi. The biological function of microbial expansins remains unclear; however, several studies have shown distinct binding preferences toward different structural polysaccharides. Earlier studies of bacterial expansin-related proteins uncovered sequence and structural features that correlate to substrate binding. Herein, 20 fungal expansin-related sequences were recombinantly produced in Komagataella phaffii, and the purified proteins were compared in terms of substrate binding to cellulosic and chitinous substrates. The impact of pH on the zeta potential of prioritized substrates was also measured, and Principal Component Analysis was performed to uncover correlations between protein characteristics (e.g., pI, hydrophobicity, surface charge distribution) and measured substrate binding preferences. Whereas acidic proteins with a predicted pI less than 5.0 preferentially bound to chitin, basic proteins with pI greater than 8.0 preferentially bound to xylan and xylan-containing fiber. Similar to many cellulases, binding to cellulose was correlated to relatively high aromatic amino acid content in the protein sequence and presence of a carbohydrate binding module (CBM), which in the case of expansins is a C-terminal CBM63. Whereas overall sequence characteristics could be correlated to substrate binding preference, the identity of amino acids occupying conserved positions that impact protein activity was better correlated with loosenin versus expansin classifications.

chitin↗

Parameterization of generic positive sequence models to represent behavior of inverter based resources in low short circuit scenarios

The connection of large inverter based resources (IBR) in transmission systems is often located geographically and electrically far away from load centers. This, coupled with the displacement of synchronous machine plants, results in a reduction of the network short circuit strength at the point of connection. Under these conditions, state-of-the-art positive sequence simulation platforms and models can have difficulties maintaining numerical stability and/or providing an accurate representation of IBR plant dynamic behavior. As a result, computationally heavy time domain electromagnetic transient (EMT) simulations may be required to evaluate these systems. In this paper, a recently developed improved generic positive sequence model is parameterized to provide a representation of IBR behavior in low short circuit networks. Further, comparisons against generic and detailed EMT models demonstrate the suitability of the improved positive sequence model to study practical stability issues experienced with presently in-service plants. Such a model can provide some of the accuracy of an EMT representation with a much lower computational burden. The performance of the positive sequence model is validated against the behavior shown by both open white box and closed black box EMT domain models from around the world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Keratinophilic fungi: Specialized fungal communities in a desert ecosystem identified using cultured-based and Illumina sequencing approaches

Soil fungi in desert ecosystems are adapted to harsh environmental conditions such as high soil surface temperatures and limited organic matter and water. Given limited carbon inputs from plant material, heterotrophic fungi likely use unconventional sources of carbon in these systems. A baiting method was used to culture keratinophilic fungi from biocrust and rhizosphere soils in an arid grassland in Utah, USA. Fungi were baited using llama and sheep wool, horsehair, and snakeskin on two media, and pure cultures were identified using ITS and LSU rRNA sequences. One hundred-eighteen fungal colonies were grown, representing a total of 32 Operational Taxonomic Units (OTUs) at 97 % similarity. Cultures were dominated by the phylum Ascomycota (88 %) followed by Mucoromycota (8.6 %) and Basidiomycota (3.4 %). The orders Pleosporales, Eurotiales, Hypocreales, and Sordariales were commonly isolated, with the dominant taxa Alternaria (27 %), Aspergillus (22 %), Fusarium (11 %), and Chaetomium (8%). Thirty percent of the fungi isolated have the capacity to degrade keratin in vitro using a keratin azure assay, with Penicillium showing the highest degradation followed by Geomyces, Alternaria, and Fusarium. Although keratin degraders can be infectious, dermatophytes associated with skin infections were not isolated in culture or detected in Illumina sequencing. Illumina sequencing was used to determine general patterns in seasonal variation and habitat preference of keratinophiles. Alternaria was the most abundant genus with >70 % of the sequences. The combination of Illumina data with culture-dependent approaches facilitated the characterization of a specialized community and confirmed the low abundance of dermatophytes in this arid site.

59 BASIC BIOLOGICAL SCIENCES↗

Exploration of Tertiary Structure in Sequence-Defined Polymers Using Molecular Dynamics Simulations

Peptoids are a class of sequence-defined biomimetic polymers with peptide-like backbones and side chains located on backbone nitrogens rather than alpha carbons. These materials demonstrate a strong ability for precise control of single-chain structure, multiunit self-assembly, and macromolecular assembly through careful tuning of sequence due to the diversity of available side chains, although the driving forces behind these assemblies are often not understood. Prior experimental work has shown that linked 15mer peptoids can mimic the protein helical hairpin structure by leveraging the chirality-inducing nature of bulky side chains and hydrophobicity, but there are still gaps in our understanding of the relationship between sequence, stability, and particular secondary or tertiary structure. Here, we present a molecular dynamics (MD) study on the folding behavior of these polymers into hairpins, discussing the differences in structure from sequences with various characteristics in water and acetonitrile, and then compare the handedness preference of common helical motifs between solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical Nanomaterials Assembled from Peptoids and Other Sequence-Defined Synthetic Polymers

In nature, the self-assembly of sequence-specific biopolymers into hierarchical structures plays an essential role in the construction of functional biomaterials. To develop synthetic materials that can mimic and surpass the function of these natural counterparts, various sequence-defined bio- and biomimetic polymers have been developed and exploited as building blocks for hierarchical self-assembly. This review summarizes the recent advances in the molecular self-assembly of hierarchical nanomaterials based on peptoids (or poly-N-substituted glycines) and other sequence-defined synthetic polymers. Modern techniques to monitor the assembly mechanisms and characterize the physicochemical properties of these self-assembly systems are highlighted. In addition, discussions about their potential applications in biomedical sciences and renewable energy are also included. Furthermore, this review aims to highlight essential features of sequence-defined synthetic polymers (e.g., high stability and protein-like high-information content) and how these unique features enable the construction of robust biomimetic functional materials with high programmability and predictability, with an emphasis on peptoids and their self-assembled nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protein sequence design with a learned potential

The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.

59 BASIC BIOLOGICAL SCIENCES↗

Large language models generate functional protein sequences across diverse families

Deep-learning language models have shown promise in various biotechnological applications, including protein design and engineering. Here, in this paper, we describe ProGen, a language model that can generate protein sequences with a predictable function across large protein families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. The model was trained on 280 million protein sequences from >19,000 families and is augmented with control tags specifying protein properties. ProGen can be further fine-tuned to curated sequences and tags to improve controllable generation performance of proteins from families with sufficient homologous samples. Artificial proteins fine-tuned to five distinct lysozyme families showed similar catalytic efficiencies as natural lysozymes, with sequence identity to natural proteins as low as 31.4%. ProGen is readily adapted to diverse protein families, as we demonstrate with chorismate mutase and malate dehydrogenase.

59 BASIC BIOLOGICAL SCIENCES↗

DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning

Deep learning methods that achieved great success in predicting intrachain residue-residue contacts have been applied to predict interchain contacts between proteins. However, these methods require multiple sequence alignments (MSAs) of a pair of interacting proteins (dimers) as input, which are often difficult to obtain because there are not many known protein complexes available to generate MSAs of sufficient depth for a pair of proteins. In recognizing that multiple sequence alignments of a monomer that forms homomultimers contain the co-evolutionary signals of both intrachain and interchain residue pairs in contact, we applied DNCON2 (a deep learning-based protein intrachain residue-residue contact predictor) to predict both intrachain and interchain contacts for homomultimers using multiple sequence alignment (MSA) and other co-evolutionary features of a single monomer followed by discrimination of interchain and intrachain contacts according to the tertiary structure of the monomer. We name this tool DNCON2_Inter. Allowing true-positive predictions within two residue shifts, the best average precision was obtained for the Top-L/10 predictions of 22.9% for homodimers and 17.0% for higher-order homomultimers. In some instances, especially where interchain contact densities are high, DNCON2_Inter predicted interchain contacts with 100% precision. We also developed Con_Complex, a complex structure reconstruction tool that uses predicted contacts to produce the structure of the complex. Using Con_Complex, we show that the predicted contacts can be used to accurately construct the structure of some complexes. Our experiment demonstrates that monomeric multiple sequence alignments can be used with deep learning to predict interchain contacts of homomeric proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Full genome sequence for the African swine fever virus outbreak in the Dominican Republic in 1980

African swine fever is a lethal disease of domestic pigs, geographically expanding as a pandemic, that is affecting countries across Eurasia and severely damaging their swine production industry. After more than 40 years of being absent in the Western hemisphere, in 2020 ASF reappeared in the Dominican Republic and Haiti. The recent outbreak strain in the Dominican Republic has been identified as a genotype II ASFV a derivative of the ASF strain circulating in Asia and Europe. However, to date no full-length genome sequence from either the 1978–1980 Here we report the complete genome sequence of an African swine fever virus (ASFV) (DR-1980) that was previously isolated from blood collected in 1980 from the Dominican Republic at the end of the last outbreak, before culling of all swine on the island of Hispaniola and stored in the Plum Island Animal Disease Center ASFV repository. A contig representing the full-length genome (183,687 base pairs) was de novo assembled into a single contig using both Nanopore and Illumina sequences. DR-1980 was determined to belong to genotype I and, as determined by full genome comparison, a close relative to the sequenced Sardinia viruses that were causing outbreaks at this time.

60 APPLIED LIFE SCIENCES↗

Basin-scale study of CO 2 storage in stacked sequence of geological formations

Commercial scale decarbonization through carbon capture and storage may likely involve many CO 2 storage projects located in close proximity. The close proximity could raise concerns over caprock integrity associated with reservoir pressure buildup and interference among adjacent projects. Commercial-scale injection will also require large prospective CO 2 storage resource and high injectivity in the targeted storage formations. To accommodate the need for both large resource and high injectivity, project operators could consider injecting CO 2 into a stacked sequence of formations. This analysis investigates the benefits of injecting CO 2 into a vertically stacked sequence of saline formations, over injecting the same amount of CO 2 into a single saline formation, in addressing these challenges. Our analysis shows that injecting into the stacked sequence mitigates the extent of pressure buildup among the stacked formations, while still achieving the same or greater target CO 2 storage volumes. Among cases modeled, the resulting pressure buildup front is most reduced when each storage site distributes injection volumes over several wells, each of which injects a portion of the total CO 2 mass across the stacked sequence. This favorable case not only results in the smallest CO 2 aerial footprint, but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 46% compared to the single-formation storage), the result of which is crucial to maintain caprock integrity. This analysis provides insights into required decision-making when considering multi-project deployment in a shared basin.

42 ENGINEERING↗

Sequence-dependent self-assembly of supramolecular nanofibers in periodic dynamic block copolymers

Block copolymers (BCPs) can spontaneously self-assemble into various nanostructured morphologies which enable their diverse applications in selective membranes, polymer electrolytes, and optoelectronics. To expand the range of nanostructures accessible to block copolymers, we designed dynamic block copolymers (DBCPs) that combine the phase separation of traditional block copolymers with the supramolecular self-assembly of periodic dynamic polymers. We demonstrate that DBCPs synthesized with a periodic block sequence self-assemble into high aspect ratio supramolecular nanofibers with well-ordered PEG and PDMS domains, in contrast to those synthesized with a random sequence which do not form nanofibers but have disordered morphologies. The periodicity of the block sequence ensures regular placement of dynamic bonds along the polymer chain, which enables stacking of the hydrogen bonding units into ordered 1D supramolecular nanofibers and delays the onset of terminal flow by up to 60 °C compared to the random block sequence. The hierarchically assembled supramolecular nanofibers display complex mechanical and thermal phase behavior arising from the interplay between phase separation of the dissimilar polymer backbones and supramolecular interactions between dynamic bonds. Despite identical bulk composition, the periodic DBCPs demonstrate ionic conductivity values over two orders of magnitude higher than their random counterparts due to the formation of well-ordered, interconnected, high aspect ratio ion-transporting PEG domains. In conclusion, these results highlight the potential for DBCPs as an emerging material platform to achieve advanced, self-assembled nanostructured morphologies.

36 MATERIALS SCIENCE↗

Pseudouridine synthase 7 is an opportunistic enzyme that binds and modifies substrates with diverse sequences and structures

Pseudouridine (Ψ) is a ubiquitous RNA modification incorporated by pseudouridine synthase (Pus) enzymes into hundreds of noncoding and protein-coding RNA substrates. Here, in this study, we determined the contributions of substrate structure and protein sequence to binding and catalysis by pseudouridine synthase 7 (Pus7), one of the principal messenger RNA (mRNA) modifying enzymes. Pus7 is distinct among the eukaryotic Pus proteins because it modifies a wider variety of substrates and shares limited homology with other Pus family members. We solved the crystal structure of Saccharomyces cerevisiae Pus7, detailing the architecture of the eukaryotic-specific insertions thought to be responsible for the expanded substrate scope of Pus7. Additionally, we identified an insertion domain in the protein that fine-tunes Pus7 activity both in vitro and in cells. These data demonstrate that Pus7 preferentially binds substrates possessing the previously identified UGUAR (R = purine) consensus sequence and that RNA secondary structure is not a strong requirement for Pus7-binding. In contrast, the rate constants and extent of Ψ incorporation are more influenced by RNA structure, with Pus7 modifying UGUAR sequences in less-structured contexts more efficiently both in vitro and in cells. Although less-structured substrates were preferred, Pus7 fully modified every transfer RNA, mRNA, and nonnatural RNA containing the consensus recognition sequence that we tested. Our findings suggest that Pus7 is a promiscuous enzyme and lead us to propose that factors beyond inherent enzyme properties (e.g., enzyme localization, RNA structure, and competition with other RNA-binding proteins) largely dictate Pus7 substrate selection.

59 BASIC BIOLOGICAL SCIENCES↗

The dark side of galaxy stellar populations – II. The dependence of star-formation histories on halo mass and on the scatter of the main sequence

Nearby galaxies are the end result of their cosmological evolution, which is predicted to be influenced by the growth of their host dark matter haloes. This co-evolution potentially leaves signatures in present-day observed galaxy properties, which might be essential to further understand how the growth and properties of galaxies are connected to those of their host haloes. In this work, we study the evolutionary histories of nearby galaxies both in terms of their host haloes and the scatter of the star-forming main sequence by investigating their time-resolved stellar populations using absorption optical spectra drawn from the Sloan Digital Sky Survey. We find that galaxy star-formation histories depend on the masses of their host haloes, and hence they shape the evolution of the star-forming main sequence over cosmic time. Additionally, we also find that the scatter around the z = 0 star-forming main sequence is not (entirely) stochastic, as galaxies with currently different star-formation rates have experienced, on average, different star-formation histories. Furthermore, our findings suggest that dark matter haloes might play a key role in modulating the evolution of star formation in galaxies, and thus of the main sequence, and further demonstrate that galaxies at different evolutionary stages contribute to the observed scatter of this relation.

79 ASTRONOMY AND ASTROPHYSICS↗

Effects of stratification on overshooting and waves atop the convective core of M ⊙ main-sequence stars

As a massive star evolves along the main sequence, its core contracts, leaving behind a stable stratification in helium. We simulate two-dimensional convection in the core at three different stages of evolution of a $5\,\mathrm{ M}_{\odot }$ star, with three different stratifications in helium atop the core. We study the propagation of internal gravity waves in the stably stratified envelope, along with the overshooting length of convective plumes above the convective boundary. We find that the stratification in helium in evolved stars hinders radial motions and effectively shields the radiative envelope against plume penetration. This prevents convective overshooting from being an efficient mixing process in the radiative envelope. In addition, internal gravity waves are less excited in evolved models compared to the zero-age-main-sequence model, and are also more damped in the stratified region above the core. As a result, the wave power is several orders of magnitude lower in mid- and terminal-main-sequence models compared to zero-age-main-sequence stars.

79 ASTRONOMY AND ASTROPHYSICS↗