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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2022

Magnitude-squared Coherence: A Powerful Tool for Disentangling Doppler Planet Discoveries from Stellar Activity

Abstract If Doppler searches for Earth-mass, habitable planets are to succeed, observers must be able to identify and model out stellar activity signals. Here we demonstrate how to diagnose activity signals by calculating the magnitude-squared coherence C ˆ xy 2 ( f ) between an activity-indicator time series x t and the radial-velocity (RV) time series y t . Since planets only cause modulation in RV, not in activity indicators, a high value of C ˆ xy 2 ( f ) indicates that the signal at frequency f has a stellar origin. We use Welch’s method to measure coherence between activity indicators and RVs in archival observations of GJ 581, α Cen B, and GJ 3998. High RV-H α coherence at the frequency of GJ 3998 b and high RV-S index coherence at the frequency of GJ 3998c, indicate that the planets may actually be stellar signals. We also replicate previous results showing that GJ 581 d and g are rotation harmonics and demonstrate that α Cen B has activity signals that are not associated with rotation. Welch’s power spectrum estimates have cleaner spectral windows than Lomb–Scargle periodograms, improving our ability to estimate rotation periods. We find that the rotation period of GJ 581 is 132 days, with no evidence of differential rotation. Welch’s method may yield unacceptably large bias for data sets with N < 75 observations and works best on data sets with N > 100. Tapering the time-domain data can reduce the bias of the Welch’s power spectrum estimator, but observers should not apply tapers to data sets with extremely uneven observing cadence. A software package for calculating magnitude-squared coherence and Welch’s power spectrum estimates is available on github.

Dodson-Robinson, Sarah E. (ORCID:0000000287964974)↗
DOE OSTI2014

A firmware-defined digital direct-sampling NMR spectrometer for condensed matter physics

We report on the design and implementation of a new digital, broad-band nuclear magnetic resonance (NMR) spectrometer suitable for probing condensed matter. The spectrometer uses direct sampling in both transmission and reception. It relies on a single, commercially-available signal processing device with a user-accessible field-programmable gate array (FPGA). Its functions are defined exclusively by the FPGA firmware and the application software. Besides allowing for fast replication, flexibility, and extensibility, our software-based solution preserves the option to reuse the components for other projects. The device operates up to 400 MHz without, and up to 800 MHz with undersampling, respectively. Digital down-conversion with ±10 MHz passband is provided on the receiver side. The system supports high repetition rates and has virtually no intrinsic dead time. We describe briefly how the spectrometer integrates into the experimental setup and present test data which demonstrates that its performance is competitive with that of conventional designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Computational Prediction of Infrasound Arrival Times and Directions from Stationary and Moving Impulsive Sources

This report addresses the need to predict infrasound signal arrival times and back azimuths at monitoring stations, enabling more focused and efficient searches within recorded waveform data. The primary challenge is estimating expected signal arrival windows for stationary and moving acoustic sources, such as chemical explosions, volcanic eruptions, meteoroids, and spacecraft re-entry events. To address this challenge, a reproducible methodology is described that uses simplified propagation speeds for boundary layer, tropospheric, stratospheric, and thermospheric atmospheric waveguides. While the Python source code itself is not freely available, this document provides detailed, step-by-step instructions, and equations enabling users to replicate and adapt the method independently. The method reliably predicts signal arrival intervals and back azimuths, thereby supporting rapid detection and accurate interpretation of infrasound events. Results demonstrate that this method effectively identifies plausible signal arrival intervals and directions, facilitating faster event detection and more reliable interpretation. This methodology directly supports atmospheric monitoring, planetary defense, and forensic analysis of explosive atmospheric events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2015

RNA helicase MOV10 functions as a co-factor of HIV-1 Rev to facilitate Rev/RRE-dependent nuclear export of viral mRNAs

Human immunodeficiency virus type 1 (HIV-1) exploits multiple host factors during its replication. The REV/RRE-dependent nuclear export of unspliced/partially spliced viral transcripts needs the assistance of host proteins. Recent studies have shown that MOV10 overexpression inhibited HIV-1 replication at various steps. However, the endogenous MOV10 was required in certain step(s) of HIV-1 replication. In this report, we found that MOV10 potently enhances the nuclear export of viral mRNAs and subsequently increases the expression of Gag protein and other late products through affecting the Rev/RRE axis. The co-immunoprecipitation analysis indicated that MOV10 interacts with Rev in an RNA-independent manner. The DEAG-box of MOV10 was required for the enhancement of Rev/RRE-dependent nuclear export and the DEAG-box mutant showed a dominant-negative activity. Our data propose that HIV-1 utilizes the anti-viral factor MOV10 to function as a co-factor of Rev and demonstrate the complicated effects of MOV10 on HIV-1 life cycle. - Highlights: • MOV10 can function as a co-factor of HIV-1 Rev. • MOV10 facilitates Rev/RRE-dependent transport of viral mRNAs. • MOV10 interacts with Rev in an RNA-independent manner. • The DEAG-box of MOV10 is required for the enhancement of Rev/RRE-dependent export.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The width of the lateral element of the synaptonemal complex is determined by a multilayered organization of its components

The synaptonemal complex (SC) is a proteinaceous structure that holds the homologous chromosomes in close proximity while they exchange genetic material in a process known as meiotic recombination. This meiotic recombination leads to genetic variability in sexually reproducing organisms. The ultrastructure of the SC is studied by electron microscopy and it is observed as a tripartite structure. Two lateral elements (LE) separated by a central region (CR) confer its classical tripartite organization. The LEs are the anchoring platform for the replicated homologous chromosomes to properly exchange genetic material with one another. An accurate assembly of the LE is indispensable for the proper completion of meiosis. Ultrastructural studies suggested that the LE is organized as a multilayered unit. However, no validation of this model has been previously provided. In this ultrastructural study, by using mice with different genetic backgrounds that affect the LE width, we provide further evidence that support a multilayered organization of the LE. Additionally, we provide data suggesting additional roles of the different cohesin complex components in the structure of the LEs of the SC. - Highlights: • The lateral element of the synaptonemal complex is a multilayered structure. • The width of the lateral element in synaptonemal complex-null mice is different. • Two cohesin complex cores plus one axial element form a wild-type lateral element. • The layers of the lateral element can be analyzed in different null mice models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks

Microbiomes from every environment contain a myriad of uncultivated archaeal and bacterial viruses, but studying these viruses is hampered by the lack of a universal, scalable taxonomic framework. We present vConTACT v.2.0, a network-based application utilizing whole genome gene-sharing profiles for virus taxonomy that integrates distance-based hierarchical clustering and confidence scores for all taxonomic predictions. We report near-identical (96%) replication of existing genus-level viral taxonomy assignments from the International Committee on Taxonomy of Viruses for National Center for Biotechnology Information virus RefSeq. Application of vConTACT v.2.0 to 1,364 previously unclassified viruses deposited in virus RefSeq as reference genomes produced automatic, high-confidence genus assignments for 820 of the 1,364. We applied vConTACT v.2.0 to analyze 15,280 Global Ocean Virome genome fragments and were able to provide taxonomic assignments for 31% of these data, which shows that our algorithm is scalable to very large metagenomic datasets. Finally, our taxonomy tool can be automated and applied to metagenomes from any environment for virus classification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Comprehensive evaluation and parametric sensitivity of interatomic potential models for diffusion kinetics of Cr 2 O 3 in molecular dynamics

While molecular dynamics (MD) has proven to be a promising approach to investigate the diffusion properties, the grand challenge resides in evaluating potential model parameters to accurately replicate experimentally measured properties. The Buckingham potential model with Columbic interaction is widely employed in MD simulations of chromia (Cr 2 O 3 ) systems, as it allows for reasonable computational cost and accuracy. However, considering the well-known limitation of classical potential models in simultaneous reproduction of various physical phenomena, further comprehensive evaluation of the potential is required for calculation of diffusion properties. In this study, we benchmark the performance of three different Buckingham models with the experimental data by calculating structural, thermodynamic, and mechanical properties of defect-free Cr 2 O 3 , and diffusion properties of Cr 2 O 3 with vacancy defects. Available Buckingham models display limited accuracies, consolidating the necessity of retraining the potential parameters for all properties impacting the diffusion dynamics. Oversimplification in parameterization procedures is suggested to impede the universal performance in property reproduction. Furthermore, this research also demonstrates effective guidelines for choosing a proper parameter set of current Buckingham potential for MD simulation with Cr 2 O 3 depending on properties and for potential reparameterization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics

SARS-CoV-2 depends on -1 programmed ribosomal frameshifting (-1 PRF) to express proteins essential for its replication. The RNA pseudoknot stimulating -1 PRF is thus an attractive drug target. However, the structural models of this pseudoknot obtained from cryo-EM and crystallography differ in some important features, leaving the pseudoknot structure unclear. We measured the solution structure of the pseudoknot using small-angle X-ray scattering (SAXS). The measured profile did not agree with profiles computed from the previously solved structures. Beginning with each of these solved structures, we used the SAXS data to direct all atom molecular dynamics (MD) simulations to improve the agreement in profiles. In all cases, this refinement resulted in a bent conformation that more closely resembled the cryo-EM structures than the crystal structure. Applying the same approach to a point mutant abolishing -1 PRF revealed a notably more bent structure with reoriented helices. This work clarifies the dynamic structures of the SARS-CoV-2 pseudoknot in solution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations

This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers' privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.001% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Gamma-ray Measurements from Neutron Pulsed Die-Away Experiments

Pulsed-neutron die-away experiments are a promising experimental method that complement criticality benchmarks for nuclear data validation. The experiments have several advantages that include compatibility with non-fissile material, low benchmark uncertainties, and high sensitivity to absorption and scattering cross sections. When validating thermal neutron scattering laws, small targets are desirable for their large sensitivity to the scattering cross section and angular distribution. Unfortunately, room return or scattering from a shielding box limits the use of the very small targets needed to maximize sensitivity to thermal scattering laws. To address this problem, we propose changing the observable of the experiment from leaked thermal neutrons to γ-rays produced by (n, γ) reactions in the target. If feasible, this change allows removal of the shielding box, achieving higher sensitivity to thermal neutron scattering laws. This study focuses on replicating benchmark pulsed-neutron die-away experiments with γ-rays. We compare the integral parameters with γ-rays to those obtained with neutrons. We also discuss experimental design choices such as detector placement, shielding, and the presence of Cd. The results show the integral parameter with γ-rays is sensitive to detector location with respect to the target when Cd shielding is present. In addition, while Pb shielding around the γ-ray detectors do not seem to affect the integral parameter, the presence of Cd shielding does and adds background γ-rays to the die-away curves making it difficult to calculate the integral parameter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A species’ response to spatial climatic variation does not predict its response to climate change

The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

2D-DIC Challenge MATLAB Analysis Code v. 1.0

This code replicates the analysis completed in the published article (see reference below) for the 2D-DIC Challenge (https://sem.org/dic-challenge/), conducted under the auspices of the Society for Experimental Mechanics (SEM). The purpose of the DIC Challenge is to provide a set of vetted and standard images, which all users and developers of Digital Image Correlation (DIC) software can use -DIC Challenge results from Sample 14 and Sample 15 of the DIC-Challenge images, and computes various statistics on the data, such as the noise, bias, and spatial resolution. P.L. Reu, E. Toussaint, E. Jones, H.A. Bruck, M. Iadicola, R. Balcaen, D.Z. Turner, T. Siebert, P. Lava, M. Simonsen (2018) Exp. Mech. 58(7):1067-1099, https://doi.org/10.1007/s11340-017-0349-0.

Jones, Elizabeth↗
DOE OSTI2015

Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States

Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO 2 and NO x over the past 16 years (1995–2010) across the United States (US), their impacts on anthropogenic aerosol loading over North America, and subsequent impacts on regional radiation budgets. In particular, this study attempts to determine the consequences of the changes in tropospheric aerosol burden arising from substantial reductions in emissions of SO 2 and NO x associated with control measures under the Clean Air Act (CAA) especially on trends in solar radiation. Extensive analyses conducted by Gan et al. (2014a) utilizing observations (e.g., SURFRAD, CASTNET, IMPROVE, and ARM) over the past 16 years (1995–2010) indicate a shortwave (SW) radiation (both all-sky and clear-sky) "brightening" in the US. The relationship of the radiation brightening trend with decreases in the aerosol burden is less apparent in the western US. One of the main reasons for this is that the emission controls under the CAA were aimed primarily at reducing pollutants in areas violating national air quality standards, most of which were located in the eastern US, while the relatively less populated areas in the western US were less polluted at the beginning of this study period. Comparisons of model results with observations of aerosol optical depth (AOD), aerosol concentration, and radiation demonstrate that the coupled WRF–CMAQ model is capable of replicating the trends well even though it tends to underestimate the AOD. In particular, the sulfate concentration predictions were well matched with the observations. The discrepancies found in the clear-sky diffuse SW radiation are likely due to several factors such as the potential increase of ice particles associated with increasing air traffic, the definition of "clear-sky" in the radiation retrieval methodology, and aerosol semi-direct and/or indirect effects which cannot be readily isolated from the observed data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The gammaherpesviral TATA-box-binding protein directly interacts with the CTD of host RNA Pol II to direct late gene transcription

β- and γ-herpesviruses include the oncogenic human viruses Kaposi’s sarcoma-associated virus (KSHV) and Epstein-Barr virus (EBV), and human cytomegalovirus (HCMV), which is a significant cause of congenital disease. Near the end of their replication cycle, these viruses transcribe their late genes in a manner distinct from host transcription. Late gene transcription requires six virally encoded proteins, one of which is a functional mimic of host TATA-box-binding protein (TBP) that is also involved in recruitment of RNA polymerase II (Pol II) via unknown mechanisms. Here, we applied biochemical protein interaction studies together with electron microscopy-based imaging of a reconstituted human preinitiation complex to define the mechanism underlying Pol II recruitment. These data revealed that the herpesviral TBP, encoded by ORF24 in KSHV, makes a direct protein-protein contact with the C-terminal domain of host RNA polymerase II (Pol II), which is a unique feature that functionally distinguishes viral from cellular TBP. The interaction is mediated by the N-terminal domain (NTD) of ORF24 through a conserved motif that is shared in its β- and γ-herpesvirus homologs. Thus, these herpesviruses employ an unprecedented strategy in eukaryotic transcription, wherein promoter recognition and polymerase recruitment are facilitated by a single transcriptional activator with functionally distinct domains.

59 BASIC BIOLOGICAL SCIENCES↗