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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Validation and Verification of Python based Neutron Spectrum Unfolding Software

To validate and verify the python-based code (PySL), designed to replicate the programs used by STAYSL for Beam Correction Factor (BCF) and Self-Shielding Factor (SHIELD), a series of tests were performed. To test BCF a python script was written to generate a random flux history file and both versions of the code processed the data. The test verified matching values up to at least one decimal place, approximately 10,000 tests where run and each one passed. Isotopes began to fail the tests once neutron saturation was reached. To verify this the total time of exposure was varied the isotopes that failed were compared to a list of their half-lives. The test process for SHIELD was very similar but, in this case, the code began by producing an input file with varying thickness and device type/environment for the SHIELD input. The failure condition for this test was if any of the data points for an isotope had a difference above 3%. Approximately 40 of these tests were run and there were only 3 isotopes that had reoccurring failures but only 2% of their points were above the 3% difference. A visual comparison was conducted by plotting the results from both programs. Although the test failed, the differences between their values were minuscule, and the self-shielding factor’s shape was preserved when plotted. Next steps for this project will be validating and verifying the python-based SigPhi code and then reproducing and testing the least squares unfolding performed by STAYSL.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Oak Ridge National Laboratory Pilot Demonstration of an Attestation and Anomaly Detection Framework using Distributed Ledger Technology for Power Grid Infrastructure

This report summarizes the design and pilot demonstration of a framework called Grid Guard that was created to provide increased data and device trustworthiness to electric grid devices by leveraging distributed ledger technology (DLT), specifically blockchain. Grid Guard contains a combination of core cryptographic methods such as the secure hash algorithm (SHA), and asymmetric cryptography, private permissioned blockchain, baselining configuration data, consensus algorithm (Raft) and the Hyperledger Fabric (HLF) framework. The system implements a low energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems such as substations, control centers and metering infrastructures. Blockchain is a distributed database structured that provides a practically unalterable (immutable) timeline of stored transactions. By relying on hashing and the Raft consensus algorithm, if an entity tries to illegitimately alter a record at one instance of the database the other ledger nodes are not altered. They work to cross-reference each other and easily locate any incorrectly added data and remove it. The bulk raw data is stored in an off-chain storage (outside of the blockchain ledger) and a hash of this baseline data is stored in the Blockchain ledger via hashing windows of time-series and configuration data, after aggregation and filtering. The bulk off-chain data repository is then considered to be trust-anchored using the hashes stored in the blockchain. To secure the electric grid testbed devices and data, device configuration baselines were compared to those baselines that had been previously stored in the ledger. Statistical baselines for device configurations, network communication patterns, and high-speed sensor data are calculated and then stored off-chain and hashes stored in the ledger. Measurements such as three-phase voltage and current, frequency, breaker status, protection scheme settings, network configuration settings (and other device configuration artifacts) and network traffic features (packet interarrival times) are compared every minute or other selected time windows. During phase 1 of the Grid Guard DLT project different DLT technologies were studies, and an assessment was performed on DLT technology vulnerabilities, uses, and key characteristics. DLT consensus protocols were studies (e.g., RAFT, named after Reliable, Replicated, Redundant, And Fault-Tolerant). Also, cryptography, public, private and permissioned or permissionless systems were assessed. Grid Guard implements a permissioned private DLT. Consensus algorithm selection and choice of DLT implementation depended heavily on the use-case. For this use-case, parameters were selected to measure performance and existing tools for assessment. Benchmarking was performed theoretically and practically. During phase 2 hashed transactions/blocks were inserted into the ledger every second. During phase 2 of the Grid Guard DLT project, a prototype framework was developed and demonstrated for attestation of critical substation devices and data using precision timing systems that use PTP and IRIG-B protocols) on a testbed of operational devices that emulated a distribution substation, control center, and power metering infrastructure using real Operational Technology (OT). The testbed includes OT devices such as protective relays, human machine interfaces (HMI), and power meters. To determine when to collect and compare system and network baselines, an initial examination of an anomaly detection capability to identify malicious manipulation of data streams was conducted. The resulting anomaly detection was demonstrated in a set of experiments and leveraged to trigger device artifact attestation checks. Attestation checks occur against device configuration baselines when compared with the immutable blockchain-stored baselines, which provided a cryptographically supported means by which to store baselines. The electrical substation-grid testbed was created to test the Grid Guard framework. The testbed emulates the operations of a portion of a power grid and SCADA systems as closely as possible. The testbed integrates real protocols, mainly IEC 61850 standard protocols, such as the Sampled Value (SV) and the GOOSE protocols. The testbed also supports DNP3 and other layer 2 and layer 3 protocols such as Telnet, SSH, SFTP/FTP and other proprietary protocols needed to connect to industrial control system equipment. The testbed emulates real power conditions using the OpalRT hardware-in-the-loop (HIL) device which can create fault situations that cannot be easily tested on real systems. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that electrical utilities commonly use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up – baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Evaluation and Validation Approaches for Simulation of Social Behavior: Challenges and Opportunities

While models of social systems have grown in scope to represent increasingly complex phenomena, efforts to validate these models against observations suffer from a number of challenges that include the lack of shared approaches, the use of single-dimensional evaluation criteria, and the difficulty in evaluating causal mechanisms. Moreover, current evaluation approaches suffer from sensitivity of the existing measurements to initial conditions and model assumptions, and failure to account for uncertainty. These effects lead to the lack of generalizability to new contexts, inability to replicate the validation approach for new models, and difficulties in interpretation of validation results. These challenges can be addressed by building a set of diverse and robust evaluation metrics and by developing best practices for comparative, reproducible validation of varied social simulation approaches against real-world data. Herein, we outline several best practices for data-drive model validation, such as defining evaluation strategies consistent with the intended use case and defining broad comparison criteria to highlight both model strengths and weaknesses. Leveraging common validation practices will enable robust analysis of simulation performance across diverse social scenarios and modeling approaches.

Saldanha, Emily G.↗
DOE OSTI2017

Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps

We call for the AD field to move beyond discrete biomarkers and utilize the full power of informatics and big data approaches to build and test personalized markers at a pathway and network level. While we have chosen AD as an example, the issues we propose are also highly relevant to other neurodegenerative disorders, such as vascular dementia or dementia with Lewy bodies, where even less is known about how various biomarkers interact. Indeed, the availability of rich biomarker data across a range of neurodegenerative disorders would enable more accurate pathology-based classification of such conditions (as opposed to the current predominantly clinical classifications). We further hypothesize that building dynamic network biomarkers and pathway crosstalk reference maps using the combined power of several protein/gene-level knowledge priors could accelerate discovery of disease-specific mechanisms and novel drug targets by enrichment with patient specific genetic information. Application of this methodology to large public AD datasets is needed to test our hypotheses and refine the methods. Subsequent replication in independent datasets and population studies as well as functional validation of mechanisms in laboratory models will be the next steps. Ultimately, it is our hope that such novel methods may yield further insights into both disease mechanisms as well as novel targets for biomarker development and drug discovery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Accelerating discoveries at DIII-D with the Integrated Research Infrastructure

DIII-D research is being accelerated by leveraging high performance computing (HPC) and data resources available through the National Energy Research Scientific Computing Center (NERSC) Superfacility initiative. As part of this initiative, a high-resolution, fully automated, whole discharge kinetic equilibrium reconstruction workflow was developed that runs at the NERSC for most DIII-D shots in under 20 min. This has eliminated a long-standing research barrier and opened the door to more sophisticated analyses, including plasma transport and stability. These capabilities would benefit from being automated and executed within the larger Department of Energy Advanced Scientific Computing Research program’s Integrated Research Infrastructure (IRI) framework. The goal of IRI is to empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. For transport, we are looking at producing flux matched profiles and also using particle tracing to predict fast ion heat deposition from neutral beam injection before a shot takes place. Our starting point for evaluating plasma stability focuses on the pedestal limits that must be navigated to achieve better confinement. This information is meant to help operators run more effective experiments, so it needs to be available rapidly inside the DIII-D control room. So far this has been achieved by ensuring the data is available with existing tools, but as more novel results are produced new visualization tools must be developed. In addition, all of the high-quality data we have generated has been collected into databases that can unlock even deeper insights. This has already been leveraged for model and code validation studies as well as for developing AI/ML surrogates. The workflows developed for this project are intended to serve as prototypes that can be replicated on other experiments and can be run to provide timely and essential information for ITER, as well as next stage fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Replicating Machine Learning Experiments in Materials Science

Transparency and reproducibility are important aspects of validation for Machine Learning (ML) models that are not fully understood and applies independently of the application domain.We offer a case study of reproducibility that highlights the challenges encountered when attempting to reproduce analyzes obtained with Machine Learning methods in materials informatics. Our study explores prediction results obtained with ML models and issues in training data serving as input. We discuss challenges related to theory-driven and numerical errors in training data, lack of reproducibility across platforms and versions, and effects of randomness when varying hyperparameters. In addition to model accuracy, a main metric of interest in the ML community, our results show that model sensitivity may be equally important for applying ML in domain applications such a materials science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

FIRST IMAGES FROM THE FOCUSING OPTICS X-RAY SOLAR IMAGER

The Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket payload flew for the first time on 2012 November 2, producing the first focused images of the Sun above 5 keV. To enable hard X-ray (HXR) imaging spectroscopy via direct focusing, FOXSI makes use of grazing-incidence replicated optics combined with fine-pitch solid-state detectors. On its first flight, FOXSI observed several targets that included active regions, the quiet Sun, and a GOES-class B2.7 microflare. This Letter provides an introduction to the FOXSI instrument and presents its first solar image. These data demonstrate the superiority in sensitivity and dynamic range that is achievable with a direct HXR imager with respect to previous, indirect imaging methods, and illustrate the technological readiness for a spaceborne mission to observe HXRs from solar flares via direct focusing optics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Citizen and machine learning-aided high-resolution mapping of urban heat exposure and stress

Abstract Through conversion of land cover to more built-up, impervious surfaces, cities create hotter environments than their surroundings for urban residents, with large differences expected between different parts of the city. Existing measurements of ambient air temperature and heat stress, however, are often insufficient to capture the intra-urban variability in heat exposure. This study provides a replicable method for modeling air temperature, humidity, and moist heat stress over the urban area of Chapel Hill while engaging citizens to collect high-temporal and spatially-resolved air temperature and humidity measurements. We use low-cost, consumer-grade sensors combined with satellite remote sensing data and machine learning to map urban air temperature and relative humidity over various land-cover classes to understand intra-urban spatial variability of ambient heat exposure at a relatively high resolution (10 m). Our findings show that individuals may be exposed to higher levels of air temperature and moist heat stress than weather station data suggest, and that the ambient heat exposure varies according to land cover type, with tree-covered land the coolest and built-up areas the warmest, and time of day, with higher air temperatures observed during the early afternoon. Combining our resulting dataset with sociodemographic data, policymakers and urban planners in Chapel Hill can use data output from this method to identify areas exposed to high temperature and moist heat stress as a first step to design effective mitigation measures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Results for the Fourth Quarter 2012 Tank 50 WAC Slurry Sample: Chemical and Radionuclide Contaminants

This report details the chemical and radionuclide contaminant results for the characterization of the 2012 Fourth Quarter sampling of Tank 50 for the Saltstone Waste Acceptance Criteria (WAC).1 Information from this characterization will be used by Waste Solidification Engineering (WSE) to support the transfer of low-level aqueous waste from Tank 50 to the Salt Feed Tank in the Saltstone Facility in Z-Area, where the waste will be immobilized. This information is also used to update the Tank 50 Waste Characterization System. The following conclusions are drawn from the analytical results provided in this report: The concentration of the reported chemical and radioactive contaminants were less than their respective WAC Limits and Targets, unless noted in this section. Norpar 13 and Isopar L have higher detection limits 5 compared with the Saltstone WAC 1 . The data provided in this report is based upon the concentrations in the sub-sample, and due to the limited solubility in aqueous solution, may not represent the concentrations of the analytes in Tank 50. Diisooctyl adipate (or diisooctyl hexanedioate) was measured at 1.30E+00 mg/L in one of two replicate measurements conducted on an at-depth sample. a The organic analysis of the at-depth sample was conducted at the request of SRR. 4 This analyte was below the detection limit in the surface sample. The low insoluble solids content increases the measurement uncertainty for insoluble species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Convergence of the Uncertainty Results

This paper describes the convergence of MELCOR Accident Consequence Code System, Version 2 (MACCS2) probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout scenario at the Peach Bottom Atomic Power Station. The consequence metrics evaluated are individual latent-cancer fatality (LCF) risk and individual early fatality risk. Consequence results are presented as conditional risk (i.e., assuming the accident occurs, risk per event) to individuals of the public as a result of the accident. In order to verify convergence for this uncertainty analysis, as recommended by the Nuclear Regulatory Commission’s Advisory Committee on Reactor Safeguards, a ‘high’ source term from the original population of Monte Carlo runs has been selected to be used for: (1) a study of the distribution of consequence results stemming solely from epistemic uncertainty in the MACCS2 parameters (i.e., separating the effect from the source term uncertainty), and (2) a comparison between Simple Random Sampling (SRS) and Latin Hypercube Sampling (LHS) in order to validate the original results obtained with LHS. Three replicates (each using a different random seed) of size 1,000 each using LHS and another set of three replicates of size 1,000 using SRS are analyzed. The results show that the LCF risk results are well converged with either LHS or SRS sampling. The early fatality risk results are less well converged at radial distances beyond 2 miles, and this is expected due to the sparse data (predominance of “zero” results).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Developing a Bubble Chamber Particle Discriminator Using Semi-Supervised Learning

The identification of non-signal events is a major hurdle to overcome for bubble chamber dark matter experiments such as PICO-60. The current practice of manually developing a discriminator function to eliminate background events is difficult when available calibration data is frequently impure and present only in small quantities. In this study, several different discriminator input/preprocessing formats and neural network architectures are applied to the task. First, they are optimized in a supervised learning context. Next, two novel semi-supervised learning algorithms are trained, and found to replicate the Acoustic Parameter (AP) discriminator previously used in PICO-60 with a mean of 97% accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Structure of the SPRY domain of the human RNA helicase DDX1, a putative interaction platform within a DEAD-box protein

The structure of the SPRY domain of the human RNA helicase DDX1 was determined at 2.0 Å resolution. The SPRY domain provides a putative protein–protein interaction platform within DDX1 that differs from other SPRY domains in its structure and conserved regions. The human RNA helicase DDX1 in the DEAD-box family plays an important role in RNA processing and has been associated with HIV-1 replication and tumour progression. Whereas previously described DEAD-box proteins have a structurally conserved core, DDX1 shows a unique structural feature: a large SPRY-domain insertion in its RecA-like consensus fold. SPRY domains are known to function as protein–protein interaction platforms. Here, the crystal structure of the SPRY domain of human DDX1 (hDSPRY) is reported at 2.0 Å resolution. The structure reveals two layers of concave, antiparallel β-sheets that stack onto each other and a third β-sheet beneath the β-sandwich. A comparison with SPRY-domain structures from other eukaryotic proteins showed that the general β-sandwich fold is conserved; however, differences were detected in the loop regions, which were identified in other SPRY domains to be essential for interaction with cognate partners. In contrast, in hDSPRY these loop regions are not strictly conserved across species. Interestingly, though, a conserved patch of positive surface charge is found that may replace the connecting loops as a protein–protein interaction surface. The data presented here comprise the first structural information on DDX1 and provide insights into the unique domain architecture of this DEAD-box protein. By providing the structure of a putative interaction domain of DDX1, this work will serve as a basis for further studies of the interaction network within the hetero-oligomeric complexes of DDX1 and of its recruitment to the HIV-1 Rev protein as a viral replication factor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

NGEE Arctic Plant Traits: Plant Community Composition, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

This dataset reports the characteristics of the dominant vegetation communities at the NGEE Arctic Kougarok field site, Kougarok Road Mile Marker 64 on the Seward Peninsula. Selected plots were surveyed from 18-23 July 2016. Environmental data (e.g., elevation, slope, soil moisture regime, disturbance type and degree, mean canopy height, etc.) were also recorded for each plot. Elevation measurements were updated 2020-08-18. All plant species (vascular plants, bryophytes and lichens) were recorded along with their percent cover in the plots as determined visually by the lead author. Plots were chosen subjectively in areas of homogeneous and representative vegetation and varied in size from 1-25 m2 depending on canopy structure and height. The site is an east-facing hillslope with vegetation that varies from the summit to the toeslope. The 30 total plots were selected as five replicate plots sampled from each of the six identified habitat types: 1) non-acidic mountain complex at the hillcrest, 2) dwarf-shrub lichen tundra on the shoulder, 3) alder shrublands predominantly on an elevational band across the backslope, 4) willow-birch tundra on the upper backslope, 5) tussock tundra on the footslope in inter-water tracks, and 6) tussock tundra mixed with willow-birch tundra or alder savanna in poor developed water tracks on the footslope. This dataset is comprised of two comma-separated (*.csv) files containing species and environmental data for the plant community composition plots. It also contains seven zipped folders of plot photographs, one map showing plot locations (*.pdf), one blank datasheet with the key to codes used in the field (*.pdf), select photos organized in a (*.pdf), and one User file (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome

Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism’s direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

HMGB1 mediates HAdV-7 infection-induced pulmonary inflammation in mice

Highlights: • HMGB1 was associated with HAdV-7-induced lung inflammation and pathology. • HMGB1 promoted HAdV-7 replication and bound to TLR-4, TLR-9, and RAGE receptors. • Receptor engagement by HMGB1 activated NF-κB, inducing inflammatory mediators. • Thus, HMGB1 could serve as a therapeutic target in HAdV-7 infection. Human adenovirus (HAdV) is a common respiratory pathogen in children, with no safe and effective treatment currently available. HAdV type 7 (HAdV-7), in particular, causes severe pediatric pneumonia with a high incidence of sequelae and mortality. Clinical data and animal experiments suggest that HAdV-7-induced pneumonia promotes cell necrosis, releasing a large number of inflammatory mediators. In recent years, the high mobility group box-1 (HMGB1) protein, released by necrotic cells, has been shown to play important roles in several viral infections. Here, we show that HMGB1 levels gradually increased in the media supernatants of HAdV-7 infected A549 cells, starting at 12 h post-infection. In vivo, HMGB1 levels in BALF and mRNA levels in lung tissues significantly increased after 3 days of HAdV-7 infection. Among the HMGB1 receptor genes, TLR-4 and TLR-9 expression increased, and so did the receptor for advanced glycation end-products (RAGE). Interestingly, NF-κB levels also increased concomitantly. Conversely, when HMGB1 was blocked, the pathological scores from lung tissues, inflammatory mediator levels, and viral copy number all were reduced significantly; in addition, HMGB1-related signaling pathway molecules, namely TLR-4, TLR-9, RAGE, and NF-κB were also reduced. We conclude that HMGB1 promotes HAdV-7 replication and signals through TLR-4, TLR-9, and RAGE receptors to activate NF-κB, stimulating the release of inflammatory mediators and contributing to adenoviral pathology. Thus, HMGB1 could be used as a therapeutic target in HAdV-7 infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TRIMe7-CypA, an alternative splicing isoform of TRIMCyp in rhesus macaque, negatively modulates TRIM5α activity

Highlights: • TRIMe7-CypA expresses in rhesus and pig-tailed, but not long-tailed macaques. • TRIMe7-CypA does not show the restriction to a HIV-GFP report virus in vitro. • It acts as a negative modulator to TRIM5α likely by competitive inhibition. - Abstract: The existence of innate, host-specific restriction factors is a major obstacle to the development of nonhuman primate models for AIDS studies, and TRIM5α is one of the most important of these restriction factors. In recent years, a TRIM5 chimeric gene that was retrotransposed by a cyclophilin A (CypA) cDNA was identified in certain macaque species. The TRIM5α-CypA fusion protein, TRIMCyp, which was expressed in these monkeys, had lost its restriction ability toward HIV-1. We previously found that TRIMe7-CypA, an alternative splicing isoform of the TRIMCyp transcripts, was expressed in pig-tailed and rhesus macaques but absent in long-tailed macaques. In this study, the anti-HIV-1 activity of TRIMe7-CypA in the rhesus macaque (RhTRIMe7-CypA) was investigated. The over-expression of RhTRIMe7-CypA in CrFK, HeLa and HEK293T cells did not restrict the infection or replication of an HIV-1-GFP reporter virus in these cells. As a positive control, rhesus (rh)TRIM5α strongly inhibited the reporter virus. Intriguingly, the anti-HIV-1 activity of RhTRIM5α was significantly reduced in a dose-dependent manner by the co-repression of RhTRIMe7-CypA. Our data indicate that although the RhTRIMe7-CypA isoform does not appear to restrict HIV-1, it may act as a negative modulator of TRIM family proteins, presumably by competitive inhibition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Accurate model annotation of a near-atomic resolution cryo-EM map

Electron cryomicroscopy (cryo-EM) has been used to determine the atomic coordinates (models) from density maps of biological assemblies. These models can be assessed by their overall fit to the experimental data and stereochemical information. However, these models do not annotate the actual density values of the atoms nor their positional uncertainty. Here, we introduce a computational procedure to derive an atomic model from a cryo- EM map with annotated metadata. The accuracy of such a model is validated by a faithful replication of the experimental cryo-EM map computed using the coordinates and associated metadata. The functional interpretation of any structural features in the model and its utilization for future studies can be made in the context of its measure of uncertainty. We applied this protocol to the 3.3-Å map of the mature P22 bacteriophage capsid, a large and complex macromolecular assembly. With this protocol, we identify and annotate previously undescribed molecular interactions between capsid subunits that are crucial to maintain stability in the absence of cementing proteins or cross-linking, as occur in other bacteriophages.

59 BASIC BIOLOGICAL SCIENCES↗