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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 433 records · Page 24

Quantum simulation of boson-related Hamiltonians: techniques, effective Hamiltonian construction, and error analysis

Elementary quantum mechanics proposes that a closed physical system consistently evolves in a reversible manner. However, control and readout necessitate the coupling of the quantum system to the external environment, subjecting it to relaxation and decoherence. Consequently, system-environment interactions are indispensable for simulating physically significant theories. A broad spectrum of physical systems in condensed-matter and high-energy physics, vibrational spectroscopy, and circuit and cavity QED necessitates the incorporation of bosonic degrees of freedom, such as phonons, photons, and gluons, into optimized fermion algorithms for near-future quantum simulations. In particular, when a quantum system is surrounded by an external environment, its basic physics can usually be simplified to a spin or fermionic system interacting with bosonic modes. Nevertheless, troublesome factors such as the magnitude of the bosonic degrees of freedom typically complicate the direct quantum simulation of these interacting models, necessitating the consideration of a comprehensive plan. This strategy should specifically include a suitable fermion/boson-to-qubit mapping scheme to encode sufficiently large yet manageable bosonic modes, and a method for truncating and/or downfolding the Hamiltonian to the defined subspace for performing an approximate but highly accurate simulation, guided by rigorous error analysis. In this pedagogical tutorial review, we aim to provide such an exhaustive strategy, focusing on encoding and simulating certain bosonic-related model Hamiltonians, inclusive of their static properties and time evolutions. Specifically, we emphasize two aspects: (1) the discussion of recently developed quantum algorithms for these interacting models and the construction of effective Hamiltonians, and (2) a detailed analysis regarding a tightened error bound for truncating the bosonic modes for a class of fermion-boson interacting Hamiltonians.

bosonic Hamiltonian↗

Diverse mechanisms of metaeffector activity in an intracellular bacterial pathogen, Legionella pneumophila

Abstract Pathogens deliver complex arsenals of translocated effector proteins to host cells during infection, but the extent to which these proteins are regulated once inside the eukaryotic cell remains poorly defined. Among all bacterial pathogens, Legionella pneumophila maintains the largest known set of translocated substrates, delivering over 300 proteins to the host cell via its Type IVB , Icm/Dot translocation system. Backed by a few notable examples of effector–effector regulation in L. pneumophila , we sought to define the extent of this phenomenon through a systematic analysis of effector–effector functional interaction. We used Saccharomyces cerevisiae , an established proxy for the eukaryotic host, to query > 108,000 pairwise genetic interactions between two compatible expression libraries of ~330 L. pneumophila‐ translocated substrates. While capturing all known examples of effector–effector suppression, we identify fourteen novel translocated substrates that suppress the activity of other bacterial effectors and one pair with synergistic activities. In at least nine instances, this regulation is direct—a hallmark of an emerging class of proteins called metaeffectors, or “effectors of effectors”. Through detailed structural and functional analysis, we show that metaeffector activity derives from a diverse range of mechanisms, shapes evolution, and can be used to reveal important aspects of each cognate effector's function. Metaeffectors, along with other, indirect, forms of effector–effector modulation, may be a common feature of many intracellular pathogens—with unrealized potential to inform our understanding of how pathogens regulate their interactions with the host cell.

59 BASIC BIOLOGICAL SCIENCES↗

Seasonal changes in the drivers of water physico-chemistry variability of a small freshwater tidal river

Where rivers meet the sea, tides can exert a physical and chemical influence on the lower reaches of a river. How tidal dynamics in these tidal river reaches interact with upstream hydrological drivers such as storm rainfall, which ultimately determines the quantity and composition of material transferred from watersheds to estuaries, is currently unknown. We monitored a small freshwater tidal river in the Pacific Northwest, USA in high resolution over one year to evaluate the relative importance of tides versus upstream hydrological flows (i.e., base flow and precipitation events) on basic physico-chemical parameters (pH, dissolved oxygen, turbidity, specific conductivity, and temperature), and how these interactions relate to the downstream estuary. Tidal variability and diurnal cycles (i.e. solar radiation) dominated water physico-chemical variability in the summer, but the influence of these drivers was overshadowed by storm-driven sharp pulses in river physico-chemistry during the remainder of the year. Within such events, we found incidences of counterclockwise hysteresis of pH, counterclockwise hysteresis of dissolved oxygen, and clockwise hysteresis of turbidity, although systematic trends were not observed across events. The dominance of storm rainfall in the river’s physico-chemistry dynamics, and similar pulses of decreased pH observed in adjacent estuarine waters, suggest that the linkage between tidal streams and the broader system is variable throughout the year. High-frequency monitoring of tidal river biogeochemistry is therefore crucial to enable the assessment of how the relative strength of these drivers may change with future sea level rise and altered precipitation patterns to modulate biogeochemical dynamics across the land-ocean-atmosphere continuum.

aquatic↗

Neutron spin echo shows pHLIP is capable of retarding membrane thickness fluctuations

In this study, cell membranes are responsible for a range of biological processes that require interactions between lipids and proteins. While the effects of lipids on proteins are becoming better understood, our knowledge of how protein conformational changes influence membrane dynamics remains rudimentary. Here, we performed experiments and computer simulations to study the dynamic response of a lipid membrane to changes in the conformational state of pH-low insertion peptide (pHLIP), which transitions from a surface-associated (SA) state at neutral or basic pH to a transmembrane (TM) α-helix under acidic conditions. Our results show that TM-pHLIP significantly slows down membrane thickness fluctuations due to an increase in effective membrane viscosity. Our findings suggest a possible membrane regulatory mechanism, where the TM helix affects lipid chain conformations, and subsequently alters membrane fluctuations and viscosity.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the roles of microbes in facilitating plant adaptation to climate change

Plants benefit from their close association with soil microbes which assist in their response to abiotic and biotic stressors. Yet much of what we know about plant stress responses is based on studies where the microbial partners were uncontrolled and unknown. Under climate change, the soil microbial community will also be sensitive to and respond to abiotic and biotic stressors. Thus, facilitating plant adaptation to climate change will require a systems-based approach that accounts for the multi-dimensional nature of plant–microbe–environment interactions. In this perspective, we highlight some of the key factors influencing plant–microbe interactions under stress as well as new tools to facilitate the controlled study of their molecular complexity, such as fabricated ecosystems and synthetic communities. When paired with genomic and biochemical methods, these tools provide researchers with more precision, reproducibility, and manipulability for exploring plant–microbe–environment interactions under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

A tutorial on radio frequency sheath physics for magnetically confined fusion devices

Radio frequency (RF) sheaths occur under a wide variety of conditions when RF waves, material surfaces and plasma coexist. RF sheaths are of special importance in describing the interaction of ion cyclotron range of frequency (ICRF) waves with the boundary plasma in tokamaks, stellarators and other magnetic confinement devices. In this article the basic physics of RF sheaths is discussed in the context of magnetic fusion research. Techniques for modelling RF sheaths, their interaction with RF wave fields and the resulting consequences are highlighted. The article is intended as a guide for the early-career ICRF researcher, but it may equally well serve to provide an overview of basic RF sheath concepts and modelling directions for any interested fusion scientist.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized , and so name our tool MetConSIN: Met abolically Con textualized S pecies I nteraction N etworks.

59 BASIC BIOLOGICAL SCIENCES↗

Gene-environment interactions due to quantile-specific heritability of triglyceride and VLDL concentrations

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., triglycerides) is high or low relative to its distribution in the population. Quantile-specific offspring-parent regression slopes (β OP ) were estimated by quantile regression for 6227 offspring-parent pairs. Quantile-specific heritability (h 2 ), estimated by 2β OP /(1 + $\Gamma$ spouse ), decreased 0.0047 ± 0.0007 (P = 2.9 × 10 -14 ) for each one-percent decrement in fasting triglyceride concentrations, i.e., h 2 ± SE were: 0.428 ± 0.059, 0.230 ± 0.030, 0.111 ± 0.015, 0.050 ± 0.016, and 0.033 ± 0.010 at the 90th, 75th, 50th, 25th, and 10th percentiles of the triglyceride distribution, respectively. Consistent with quantile-dependent expressivity, 11 drug studies report smaller genotype differences at lower (post-treatment) than higher (pre-treatment) triglyceride concentrations. This meant genotype-specific triglyceride changes could not move in parallel when triglycerides were decreased pharmacologically, so that subtracting pre-treatment from post-treatment triglyceride levels necessarily created a greater triglyceride decrease for the genotype with a higher pre-treatment value (purported precision-medicine genetic markers). In addition, sixty-five purported gene-environment interactions were found to be potentially attributable to triglyceride's quantile-dependent expressivity, including gene-adiposity (APOA5, APOB, APOE, GCKR, IRS-1, LPL, MTHFR, PCSK9, PNPLA3, PPARγ2), gene-exercise (APOA1, APOA2, LPL), gene-diet (APOA5, APOE, INSIG2, LPL, MYB, NXPH1, PER2, TNFA), gene-alcohol (ALDH2, APOA5, APOC3, CETP, LPL), gene-smoking (APOC3, CYBA, LPL, USF1), gene-pregnancy (LPL), and gene-insulin resistance interactions (APOE, LPL).

59 BASIC BIOLOGICAL SCIENCES↗

Bacterial Community Assembly, Succession, and Metabolic Function during Outdoor Cultivation of Microchloropsis salina

Outdoor cultivation of microalgae has promising potential for renewable bioenergy, but there is a knowledge gap on the structure and function of the algal microbiome that coinhabits these ecosystems. Here, we describe the assembly mechanisms, taxonomic structure, and metabolic potential of bacteria associated with Microchloropsis salina cultivated outdoors. Open mesocosms were inoculated with algal cultures that were either free of bacteria or coincubated with one of two different strains of alga-associated bacteria and were sampled across five time points taken over multiple harvesting rounds of a 40-day experiment. Using quantitative analyses of metagenome-assembled genomes (MAGs), we tracked bacterial community compositional abundance and taxon-specific functional capacity involved in algal-bacterial interactions. One of the inoculated bacteria (Alteromonas sp.) persisted and dispersed across mesocosms, whereas the other inoculated strain (Phaeobacter gallaeciensis) disappeared by day 17 while a taxonomically similar but functionally distinct Phaeobacter strain became established. The inoculated strains were less abundant than 6 numerically dominant newly recruited taxa with functional capacities for mutualistic or saprophytic lifestyles, suggesting a generalist approach to persistence. This includes a highly abundant unclassified Rhodobacteraceae species that fluctuated between 25% and 77% of the total community. Overall, we did not find evidence for priority effects exerted by the distinct inoculum conditions; all mesocosms converged with similar microbial community compositions by the end of the experiment. Instead, we infer that the 15 total populations were retained due to host selection, as they showed high metabolic potential for algal-bacterial interactions such as recycling alga-produced carbon and nitrogen and production of vitamins and secondary metabolites associated with algal growth and senescence, including B vitamins, tropodithietic acid, and roseobacticides.

rhodobacteraceae↗

Plant stimulation of soil microbial community succession: how sequential expression mediates soil carbon stabilization and turnover

It is now understood that most plant C is utilized or transformed by soil microorganisms en route to stabilization. Hence the composition of microbial communities that mediate decomposition and transformation of root C is critical, as are the metabolic capabilities of these communities. The change in composition and function of the C-transforming microbial communities over time in effect defines the biological component of soil C stabilization. Our research was designed to test 2 general hypotheses; the first two hypotheses are discussed first; H1: Root-exudate interactions with soil microbial populations results in the expression of enzymatic capacities for macromolecular, complex carbon decomposition; and H2: Microbial communities surrounding roots undergo taxonomic succession linked to functional gene activities as roots grow, mature, and decompose in soil. Over the term of the project we made significant progress in 1) quantifying the temporal pattern of root interactions with the soil decomposing community and 2) characterizing the role of root exudates in mediating these interactions.

54 ENVIRONMENTAL SCIENCES↗

Computer systems for annotation of single molecule fragments

There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Campylobacter jejuni Demonstrates Conserved Proteomic and Transcriptomic Responses When Co-cultured With Human INT 407 and Caco-2 Epithelial Cells

Major foodborne bacterial pathogens, such as Campylobacter jejuni , have devised complex strategies to establish and foster intestinal infections. For more than two decades, researchers have used immortalized cell lines derived from human intestinal tissue to dissect C. jejuni -host cell interactions. Known from these studies is that C. jejuni virulence is multifactorial, requiring a coordinated response to produce virulence factors that facilitate host cell interactions. This study was initiated to identify C. jejuni proteins that contribute to adaptation to the host cell environment and cellular invasion. We demonstrated that C. jejuni responds to INT 407 and Caco-2 cells in a similar fashion at the cellular and molecular levels. Active protein synthesis was found to be required for C. jejuni to maximally invade these host cells. Proteomic and transcriptomic approaches were then used to define the protein and gene expression profiles of C. jejuni co-cultured with cells. By focusing on those genes showing increased expression by C. jejuni when co-cultured with epithelial cells, we discovered that C. jejuni quickly adapts to co-culture with epithelial cells by synthesizing gene products that enable it to acquire specific amino acids for growth, scavenge for inorganic molecules including iron, resist reactive oxygen/nitrogen species, and promote host cell interactions. Based on these findings, we selected a subset of the genes involved in chemotaxis and the regulation of flagellar assembly and generated C. jejuni deletion mutants for phenotypic analysis. Binding and internalization assays revealed significant differences in the interaction of C. jejuni chemotaxis and flagellar regulatory mutants. The identification of genes involved in C. jejuni adaptation to culture with host cells provides new insights into the infection process.

59 BASIC BIOLOGICAL SCIENCES↗

Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge

Elucidating protein–ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein–ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein–ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein–ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein–ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein–ligand interactions on cryo-EM data using prior structural information.

59 BASIC BIOLOGICAL SCIENCES↗

Protein–Protein Interaction Regulates the Direction of Catalysis and Electron Transfer in a Redox Enzyme Complex

Protein-protein complexes are fundamental to life where they are key to processes ranging from central metabolism to cell signaling. Transient protein-protein interactions generally underpin the electron-transfer (ET) pathways of respiration.1 One of the many well-characterized examples of a transient ET complex is that between cytochrome c and cytochrome c oxidase.2-5 The interaction between these partner proteins is weak and dynamic. This ensures the frequent exchange of partner proteins as required to support electron flux in cases where the sole function of one of the proteins is to shuttle electrons between redox partners.1 While it is generally assumed that such transient protein-protein interactions are specific, for Paracoccus denitrificans it has recently been shown that seven proteins in a respiratory network interact in a seemingly ill-defined manner. This results in an intricate electron-transfer network that may be better suited to successful colonization of habitats with changing resources.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Reveals Missing Edges and Putative Interaction Mechanisms in Microbial Ecosystem Networks

Different organisms in a microbial community may drastically affect each other’s growth phenotypes, significantly affecting the community dynamics, with important implications for human and environmental health. Novel culturing methods and the decreasing costs of sequencing will gradually enable high-throughput measurements of pairwise interactions in systematic coculturing studies. However, a thorough characterization of all interactions that occur within a microbial community is greatly limited both by the combinatorial complexity of possible assortments and by the limited biological insight that interaction measurements typically provide without laborious specific follow-ups. Here, we show how a simple and flexible formal representation of microbial pairs can be used for the classification of interactions via machine learning. The approach we propose predicts with high accuracy the outcome of yet-to-be performed experiments and generates testable hypotheses about the mechanisms of specific interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating the role of acidic, basic, and polar amino acids and dipeptides on a molecular electrocatalyst for H 2 oxidation

Amino acids and peptides have been shown to have a significant influence on the H2 production and oxidation reactivity of Ni(P R 2 N R’ 2 ) 2 , where P R 2 N R’ 2 = 1,5-diaza-3,7-diphosphacyclooctane, R is either phenyl (Ph) or cyclohexyl (Cy), and R’ is either an amino acid or peptide. Most recently, the Ni(P Cy 2 Naminoacid 2 ) 2 complexes (CyAA) have shown enhanced H 2 oxidation rates, water solubility, and in the case of arginine (CyArg) and phenylalanine (CyPhe), electrocatalytic reversibility. Both the backbone –COOH and side chain interactions were shown to be critical to catalytic performance. Here we further investigate the roles of the outer coordination sphere by evaluating amino acids with acidic, basic, and hydrophilic side chains, as well as dipeptides which combine multiple successful features from previous complexes. Six new complexes were prepared, three containing single amino acids: aspartic acid (CyAsp), lysine (CyLys), and serine (CySer) and three containing dipeptides: glycine-phenylalanine (Cy(GlyPhe)), phenylalanine-glycine (Cy(PheGly)), and aspartic acid-phenylananine (Cy(AspPhe)). The resulting catalytic performance demonstrates that complexes need both interactions between side chain and –COOH groups for fast, efficient catalysis. The fastest of all of the catalysts, Cy(AspPhe), had both of these features, while the other dipeptide complexes with an amide replacing the -COOH were both slower; however, the amide group was demonstrated to participate in the proton pathway when side chain interactions are present to position it. Both the hydrophilic and basic side chains, notably lacking in side chain interactions, significantly increased the overpotential, with only modest increases in TOF. Of all of the complexes, only CyAsp was reversible at room temperature, and only in water, the first of these complexes to demonstrate room temperature reversibility in water. These results continue to provide and solidify design rules for controlling reactivity and efficiency of Ni(P 2 N 2 ) 2 complexes with the outer coordination sphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Five PMI Isolates from Populus Deltoides and Populus Trichocarpa

Five bacterial isolates were isolated from the roots of poplar trees (Populus deltoides and P. trichocarpa), which are model organisms and a main focus of the Plant-Microbe Interfaces (PMI) project at ORNL. These strains belong to genera are not well represented and give a more complete view of the microbial community and bacterial interactions with poplar trees. These strains will support future studies and contribute to the broader PMI goal of understanding microbe-microbe and plant-microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Cross-Feedings, Competition, and Positive and Negative Synergies in a Four-Species Synthetic Community for Anaerobic Degradation of Cellulose to Methane

A synthetic community was designed using four microbial species that together performed distinct key metabolic processes in the anaerobic degradation of cellulose to methane and CO 2 . The microorganisms exhibited expected interactions, such as cross-feeding of acetate from a cellulolytic bacterium to an acetoclastic methanogen and competition of H 2 between a sulfate reducing bacterium and a hydrogenotrophic methanogen.

59 BASIC BIOLOGICAL SCIENCES↗