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The purpose of this experiment was to evaluate the host epigenetic response to Influenza A (H5N1) viral infection from human lung adenocarcinoma cells (Calu-3) high throughput sequencing (ChIP-Seq) sample data. Host-associated viral downloads contain one or more primary host-pathogen experimental study metadata design workbooks (supporting metadata only).
Plant root-associated microbial symbionts comprise the plant rhizobiome. These microbes function in provisioning nutrients and water to their hosts, impacting plant health and disease. The plant microbiome is shaped by plant species, plant genotype, soil and environmental conditions, but the contributions of these variables are hard to disentangle from each other in natural systems. We used bioassay common garden experiments to decouple plant genotype and soil property impacts on fungal and bacterial community structure in the Populus rhizobiome. High throughput amplification and sequencing of 16S, ITS, 28S and 18S rDNA was accomplished through 454 pyrosequencing. Co-association patterns of fungal and bacterial taxa were assessed with 16S and ITS datasets. Community bipartite fungal-bacterial networks and PERMANOVA results attribute significant difference in fungal or bacterial communities to soil origin, soil chemical properties and plant genotype. Indicator species analysis identified a common set of root bacteria as well as endophytic and ectomycorrhizal fungi associated with Populus in different soils. However, no single taxon, or consortium of microbes, was indicative of a particular Populus genotype. Fungal-bacterial networks were over-represented in arbuscular mycorrhizal, endophytic, and ectomycorrhizal fungi, as well as bacteria belonging to the orders Rhizobiales, Chitinophagales, Cytophagales, and Burkholderiales. These results demonstrate the importance of soil and plant genotype on fungal-bacterial networks in the belowground plant microbiome.
Three different types of plasmas have been investigated using both experimental and theoretical methods. The first type of plasma is dense, highly ionized, governed by magnetohydrodynamics, and highly dynamic. This plasma is relevant to solar coronal loops, astrophysical jets, and other situations where strong magnetic forces act on the plasma. A well-diagnosed laboratory experiment creates a magnetohydrodynamically driven highly collimated plasma jet. This jet undergoes a kink instability such that it rapidly develops a corkscrew shape. The kink causes lateral acceleration of the jet, and this lateral acceleration drives a Rayleigh-Taylor instability that in turn chokes the current flowing in the jet and causes a magnetic reconnection. The magnetic reconnection causes electron and ion heating as well as emission of whistler waves. This entire sequence of events has been observed, measured in detail, and related to theoretical models. The second type of plasma is a transient rf-produced plasma used as a seed plasma for the magnetohydrodynamic experiments described above. Detailed atomic physics ionization processes have been investigated and modeled. The third type of plasma that has been studied is a dusty plasma where the dust particles are spontaneously growing ice grains. The rapid growth of the ice grains to large size and their highly ordered alignment has been investigated as well as collective motion of the ice grains, including well-defined flows on the surface of nested toroids. In addition to the experimental work described above, several related theoretical models have been developed, most notably a model showing how a complex interaction between gravity and magnetic fields on extremely weakly ionized plasma in an accretion disk provides an electric power source that can drive astrophysical jets associated with the accretion disk. Eighteen papers reporting this work have been published in a wide variety of journals.
Deoxynucleotide triphosphohydrolases (dNTPases) play a critical role in cellular survival and DNA replication through the proper maintenance of cellular dNTP pools. While the vast majority of these enzymes display broad activity toward canonical dNTPs, such as the dNTPase SAMHD1 that blocks reverse transcription of retroviruses in macrophages by maintaining dNTP pools at low levels, Escherichia coli ( Ec )-dGTPase is the only known enzyme that specifically hydrolyzes dGTP. However, the mechanism behind dGTP selectivity is unclear. Here we present the free-, ligand (dGTP)- and inhibitor (GTP)-bound structures of hexameric Ec- dGTPase, including an X-ray free-electron laser structure of the free Ec- -dGTPase enzyme to 3.2 Å. To obtain this structure, we developed a method that applied UV-fluorescence microscopy, video analysis, and highly automated goniometer-based instrumentation to map and rapidly position individual crystals randomly located on fixed target holders, resulting in the highest indexing rates observed for a serial femtosecond crystallography experiment. Our structures show a highly dynamic active site where conformational changes are coupled to substrate (dGTP), but not inhibitor binding, since GTP locks dGTPase in its apo- form. Moreover, despite no sequence homology, Ec- dGTPase and SAMHD1 share similar active-site and HD motif architectures; however, Ec- dGTPase residues at the end of the substrate-binding pocket mimic Watson–Crick interactions providing guanine base specificity, while a 7-Å cleft separates SAMHD1 residues from dNTP bases, abolishing nucleotide-type discrimination. Furthermore, the structures shed light on the mechanism by which long distance binding (25 Å) of single-stranded DNA in an allosteric site primes the active site by conformationally “opening” a tyrosine gate allowing enhanced substrate binding.
This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".
DNATrax (DNA Tagged Reagents for Aerosol eXperiments) was developed to provide a safe simulant for understanding the transport and dispersion of pathogens. Specifically, it was developed as a safe surrogate for the Bacillus anthrasis spore bioagent, since most naturally occurring spores are not safe for public release. As DNA-tagged sugar particles, DNATrax aerosols are safe for public release. Scientists can add unique DNA barcode sequences to the sugar particles to produce a wide variety of test particles that can be easily differentiated, making it possible to release and test them simultaneously. The unique barcodes also eliminate the need to conduct decontamination between tests, dramatically reducing the cost and time to run experiments. Additionally, the surrogate offers a high-sensitivity detection method to understand key public health issues. We conducted both lab-based and largescale field studies using DNATrax to validate its capabilities for use as a pathogen surrogate. We have demonstrated the ability to produce DNATrax in a range of sizes, adjusting the microparticles to simulate different sized pathogens with ability to create unique sequences of DNA bases, enabling them to create a nearly unlimited variety of test particles.
The India National Gas Hydrate Program Expedition 02 (NGHP-02) discovered gas hydrate at high saturation in sand reservoirs at several sites in the deepwater Bay of Bengal. To assess the potential response of those deposits to scientific depressurization experiments, comprehensive geologic models were constructed to enable numerical simulation for two sites. Both sites (NGHP-02-09 and NGHP-02-16) feature thick sequences of thinly-interbedded reservoir and non-reservoir facies at sub-seafloor depths less than 300m and sub-sea depths of 2400m or more. These settings pose significant challenges to current modeling capabilities. First, the thinly-interbedded reservoir architecture complicates the determination of basic reservoir parameters from both log and core data due to measurement resolution issues. Secondly, the fine scale variation in sediment properties imparts great contrasts in key parameters over very short distances, creating high gradients at multiple scales and varying orientations that necessitate careful design of high-definition simulation grids. Thirdly, the deposits include internal sources of water, as well as a range of complex boundary conditions, including variable permeability within the overlying mud-rich “seals,” that complicate reservoir depressurization. Lastly, because of the unique combination of great water depth and relatively shallow sub-seafloor depth: models designed to maximize the dissociation rate impose large pressure drawdowns on relatively low-strength sediments. This condition renders the proper evaluation and integration of the geomechanical response to hydrate dissociation critical. In this report, we review the history of gas hydrate reservoir simulation, discuss methods for creating geologic input models, and summarize the key findings and implications of the collaborative NGHP-02 numerical simulation effort. Together, the studies confirm the viability of the modeled accumulations for scientific testing and identify key challenges related to the selection of specific test sites and the design of test wells.
Probing the fast dynamics of surface sites using NMR spectroscopy is highly challenging owing to the sites’ high dilution and the difficulties often associated with isotopic enrichment. Intra-CH 2 1 H- 1 H dipolar couplings are ideal probes of motions given that they only involve 1 H’s and the tensor has a well-defined size and orientation. Here, we introduce a frequency-selective variant of the double-quantum sideband method to measure like-spin 1 H- 1 H dipolar coupling constants. The experiment dramatically reduces the instrument time required to measure dynamically-averaged intra-CH 2 dipolar couplings. We demonstrate the performance of the sequence using silica-supported silanes as model highly-mobile surface species.
Desalination of high salinity solutions has been studied using a novel experimental technique and a theoretical model. Neutron imaging has been employed to visualize lithium ions in mesoporous carbon materials, which are used as electrodes in capacitive deionization for water desalination. Experiments were conducted with a flow-through capacitive deionization cell designed for neutron imaging and with lithium chloride ( 6 LiCl) as the electrolyte. Sequences of neutron images have been obtained at a relatively high concentration of lithium chloride ( 6 LiCl) solution to provide information on the transport of ions within the electrodes. A new model that computes the individual ionic concentration profiles inside mesoporous carbon electrodes has been used to simulate the capacitive deionization process. Modifications have also been introduced into the simulation model to calculate results at high electrolyte concentrations. Experimental data and simulation results provide insight into why capacitive deionization is not effective for desalination of high ionic-strength solutions. The combination of experimental information, obtained through neutron imaging, with the theoretical model will help in the design of capacitive deionization devices, which can improve the process for high ionic-strength solutions.
Abstract A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformational changes, a subset of which are functionally important. Techniques for capturing the continuous conformational changes underlying function are essential for further progress. Here, we present chemically-detailed conformational movies of biological function, extracted data-analytically from experimental single-particle cryo-electron microscopy (cryo-EM) snapshots of ryanodine receptor type 1 (RyR1), a calcium-activated calcium channel engaged in the binding of ligands. The functional motions differ substantially from those inferred from static structures in the nature of conformationally active structural domains, the sequence and extent of conformational motions, and the way allosteric signals are transduced within and between domains. Our approach highlights the importance of combining experiment, advanced data analysis, and molecular simulations.
Premise of research. Plants in natural and agricultural systems are influenced in myriad ways by their microbial communities, particularly by providing goods and services that change plant functional traits. Microbes are considered an influential part of the environmental context that change plant trait expression, but often, microbe-mediated effects are contingent on local resources, such as nitrogen. Here, we ask how microbes and nitrogen affect belowground functional traits and patterns of phenotypic selection. Methodology. We performed a fully factorial greenhouse experiment with switchgrass (Panicum virgatum), manipulating microbial community composition and nitrogen availability. We measured plant performance and belowground functional traits and performed 16S amplicon sequencing of the root-associated microbial communities. We looked for correlations between microbial taxa and root functional traits, and we performed phenotypic selection analysis on five belowground functional traits to determine how traits affect plant relative performance across biotic and abiotic contexts. Pivotal results. All belowground plant functional traits except root tissue density were affected by adding nitrogen. We found that a microbial taxon (amplicon sequence variant [ASV]) in the genus Micromonospora correlated with shorter root lengths. We also found strong positive selection for longer roots regardless of the abiotic or biotic environment. In contrast, selection favored lower root-to-shoot ratios in high-nitrogen conditions, and selection on root tissue density was highest in treatments that had high nitrogen levels and perturbed microbial communities. Conclusions. We did not detect microbial effects on the expression of plant traits (ecological effects); however, patterns of phenotypic selection (evolutionary effects) on root tissue density differed depending on the biotic and abiotic environment. Additionally, we detected strong selection for increased root length across treatments; we also found that one ASV correlated with decreased root length, indicating potential conflict between root microbiome components and plant fitness. Future work would be to include microbial taxa in phenotypic selection analysis and to conduct manipulations of the microbes correlated with functional traits to determine causality.
Radiation shielding modeling involves a wide range of applications, such as power reactors, critical experiments, portable sources, linear accelerators, and fusion systems. Particle energy ranges vary from thermal energies to fast energy spectra. MAVRIC, as the radiation shielding sequence of the SCALE code system [1] developed and maintained by Oak Ridge National Laboratory, is capable of modeling both neutron and photon interactions in matter and is widely used by the US Nuclear Regulatory Commission, Department of Energy, the National Nuclear Security Administration, and radiation shielding practitioners all around the world. Although most applications don’t involve highly energetic photons that can cause photonuclear reactions and create coupled chains of high energy, ionized electrons and bremsstrahlung radiation within a material medium, when present, these reactions can have a significant impact upon the downstream particle fluxes from incident photons above 20 MeV. For example, linear accelerators used for medical isotope production are examples of applications in which high-energetic photons are generated and used for driving or controlling other components of a complex facility. Radiation shielding analyses of such a facility would require accounting for any and all significant sources of radiation. Unfortunately, MAVRIC included no data and methods to model either photonuclear reactions or the bremsstrahlung photons until this work, which enabled accounting for both. Photonuclear reaction cross sections were imported from the Evaluated Nuclear Data File libraries, and corresponding methods were implemented in the SCALE code system; see Section 2 for how the nuclear data are imported and used. Bremsstrahlung photons were modeled by assuming thick-target approximation whereby all generated electrons and positrons due to photon interactions are assumed to be absorbed within the same material in which they were born, yielding a quick particle transport simulation method by using fast lookup tables for generating subsequent gammas; see Section 4 for details. A suite of verification models was used to test implemented methods and associated data. Tests yielded satisfactory results for the new features. Enhancements will be released as part of the next major SCALE release (v7.0), which is anticipated to be deployed in 2025, with beta releases available in the interim.
In this project, we applied our labeling pipeline to Arabidopsis and sorghum by feeding tissues with isotopically labeled versions of commercially available amino acids to identify all metabolite features that incorporate the label. In sorghum, we fed five accessions, sampled across the diversity of sorghum, to identify the precursor-of-origin for metabolites that vary between accessions as well as those that may be missing from a single reference genotype. This provided us with precursor-of-origin annotation for thousands of unknown metabolites. We then used GWA to map genes responsible for the synthesis of precursor-of-origin classified metabolites. For sorghum leaf and root ducible metabolites, we performed untargeted metabolomics on leaf and root tissues from 300 diverse genotyped sorghum inbred lines. The amino acid precursor-of-origin metabolite library were then used to identify the corresponding metabolites in the GWA data sets and to identify novel gene-metabolite associations. Finally, we utilized existing and newly generated sequenced EMS mutants of sorghum to validate the predicted gene-metabolite relationships that our labelling analysis identified. In parallel, we conducted similar feeding experiments in Arabidopsis to categorize metabolites based on precursor-of-origin, identify those that vary across our existing Arabidopsis metabolite GWA dataset, and identify genes required for the synthesis of each metabolite. To provide an independent test of gene annotation and pathway involvement, we tested the GWA gene-metabolite associations in Arabidopsis by analyzing the metabolic phenotypes of gene knockouts. Genes of particular interest from both sorghum and Arabidopsis were studied in detail by directly measuring the activity of the corresponding enzymes following heterologous expression. In summary, this work classified as-yet-unknown amino acid-derived metabolites and identified genes involved in their production generated through “omics” technologies. This information was used to validate gene function and identify new metabolism in Arabidopsis and sorghum.
“A picture tells a thousand words”—this is a concept that captivates everyone, from the casual observer to the experimental physics scientist. To bring this concept to light in support of Stockpile Stewardship subcritical experiments executed at the Nevada National Security Site (NNSS), we have developed a new diagnostic tool to investigate the behavior of materials under high-explosive dynamic shock conditions. For the Leda subcritical experiment executed in August, 2014, a single line-of-sight imaging system was designed and fielded as a stretch diagnostic goal for National Security Technologies, LLC (NSTec). For the Lyra series, beginning with the Orpheus experiment in September 2015, a newly created dynamic stereo surface imaging (DSSI) capability was deployed. The DSSI diagnostic records a high-speed image sequence that allows scientists to peer inside an imploding hydrodynamic test article with stereoscopic imaging.
<ul><li>Re-designed ambient experimental apparatus constructed and operational</li><li>Finalized design of elevated experiments w/ LSU</li><li>Shakedown reveals that current sensors do not respond to changes in gas content</li><li>Designing surrogate sensor(s) w/ LSU</li><li>Implemented a sequence anomaly detection algorithm to identify kicks</li></ul>
Plsp1 is a type I signal peptidase that is responsible for removing the targeting signal peptide from passenger proteins upon their delivery to the thylakoid lumen. Plsp1 is itself a resident of the thylakoid membrane, with a single membrane anchor and the catalytic domain facing the lumen. Work to uncover the targeting mechanism for this protein has been underway in the Inoue lab from the previous DOE funding period has established that Plsp1 is targeted at the thylakoid by the Sec1 translocase, and that it passes through a high molecular weight intermediate in the stroma en route to the thylakoid membrane. During this funding period we have demonstrated by MS/MS of immunoprecipitated samples that the high molecular weight complex containing Plsp1 in the stroma contains primarily the α1 and β1 forms of Cpn60 in approximately equal amounts. Mixing experiments with overexpressed purified proteins have reproduced the Cpn60/Plsp1 complex. Surprisingly, the co-chaperonins Cpn10 and Cpn20 were not detected in the immunoprecipitated sample, even though they are able to bind to the Cpn60/Plsp1 complex formed in mixing experiments. We have further confirmed that the addition of purified stromal cpSecA1 results in a decrease in the amount of Plsp1 successfully incorporated into the thylakoid membrane. We are currently working on experiments to describe the conditions for the handoff between Cpn60 and cpSec1 in the stroma prior to membrane targeting. The structure of Plsp1 can be inferred by threading its sequence onto the structure of its E. coli homologue LepB to contain a single membrane anchor followed by a soluble structure consisting of ten β strands. In the last DOE funding period it was determined that the transmembrane domain not only acts as the membrane anchor, but probably mediates the interaction with cpSecA1. We have now determined that the binding to Cpn60 is likely mediated by β strands 1 and 2. What is the mechanism and significance of oxidative folding of Plsp1? It was found during the last DOE funding period that Plsp1 purified after overexpression in E. coli loses its peptidase activity upon reduction of its conserved cysteines. We have now determined that Plsp1 undergoes a measurable conformational change upon reduction, both by monitoring susceptibility to protease and by native tryptophan fluorescence. We have also shown that Plsp1 is at least partly, and likely completely, oxidized in the thylakoid lumen. While these results were not unexpected, experiments on Plsp1 in vivo were completely surprising. We have known for years (from work conducted with prior DOE funding) that a Plsp1 knockout is embryo lethal. Accordingly, given that reduction of the isolated protein inactivates it, we expected that plants in which one or both of the cysteine pair were mutated would also lead to a severe mutant phenotype. This was not observed, and in fact, these mutants complemented fully the plsp1 plants. This lead to the hypothesis that either association with an interacting protein or with the membrane preserves Plsp1structure even when the disulfides are reduced. Work performed in the last DOE funding cycle revealed that Pgrl1, a protein reportedly involved in cyclic electron flow, interacts stably with Plsp1. However, the Plsp1 cysteine-less mutants are still able to compliment the plsp1 mutant even in the pgrl1 knockout mutant background. We have also found that in vitro activity of Plsl1 is not abolished by reduction in thylakoids that have been permeabilized by low concentrations of detergent, whereas the activity of fully extracted protein is. This points to membrane association as the condition important to activity, and by extension, structure preservation. We are presently working to isolate Plsp1 in a lipid nanodisk to test this hypothesis.
Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap . In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at .
By means of molecular dynamics (MD) simulations, we demonstrate that porous graphene can efficiently separate gases according to their molecular sizes. The flux sequence from the classical MD simulation is H{sub 2}>CO{sub 2}≫N{sub 2}>Ar>CH{sub 4}, which generally follows the trend in the kinetic diameters. This trend is also confirmed from the fluxes based on the computed free energy barriers for gas permeation using the umbrella sampling method and kinetic theory of gases. Both brute-force MD simulations and free-energy calcualtions lead to the flux trend consistent with experiments. Case studies of two compositions of CO{sub 2}/N{sub 2} mixtures further demonstrate the separation capability of nanoporous graphene. - Graphical abstract: Classical molecular dynamics simulations show the flux trend of H{sub 2}>CO{sub 2}≫N{sub 2}>Ar>CH{sub 4} for their permeation through a porous graphene, in excellent agreement with a recent experiment. - Highlights: • Classical MD simulations show the flux trend of H{sub 2}>CO{sub 2}≫N{sub 2}>Ar>CH{sub 4} for their permeation through a porous graphene. • Free energy calculations yield permeation barriers for those gases. • Selectivities for several gas pairs are estimated from the free-energy barriers and the kinetic theory of gases. • The selectivity trend is in excellent agreement with a recent experiment.