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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sequencing and analysis of 131 SARS-CoV-2 isolates in previously sampled and unsampled regions of Jordan from 2020 to 2023

The Hashemite Kingdom of Jordan remains an understudied country for next generation sequencing analysis of SARS-CoV-2 genomes collected during the 2019 pandemic. Here we provide 131 additional reference genomes collected between 2020–2023 from SARS-CoV-2-positive patients across Jordan. Phylogenetic analysis supports existing pandemic narratives of changing clade dominance over time and adds genomes in novel Jordanian locations and timepoints to make Jordan SARS-CoV-2 databases more comprehensive. Samples from the less-sequenced cities of Ajloun, Jaresh, Karak, and Madaba identified previously unreported lineages while Amman, Irbid, and Zarqa have existing sequencing efforts bolstered. Despite many incomplete patient records and a relatively small sample size, we observe interesting symptom patterns that support existing global and Jordanian pandemic narratives. We note how in-country COVID-19 pandemic genomic studies showcase Jordan’s efforts to expand next generation sequencing capabilities, especially through the leveraging of EDGE COVID-19, a bioinformatics platform for performing rapid, batched analysis of SARS-CoV-2 sequencing that streamlines sample processing prepared from a network of hospital locations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Phylodynamics of SARS-CoV-2 Lineages B.1.1.7, B.1.1.529 and B.1.617.2 in Nigeria Suggests Divergent Evolutionary Trajectories

Background: The early months of the COVID-19 pandemic were characterized by high transmission rates and mortality, compounded by the emergence of multiple SARS-CoV-2 lineages, including Variants of Concern (VOCs). This study investigates the phylodynamic and spatio-temporal trends of VOCs during the peak of the pandemic in Nigeria. Methods: Whole-genome sequencing (WGS) data from three major VOCs circulating in Nigeria, B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.1.529 (Omicron), were analyzed using tools such as Nextclade, R Studio v 4.2.3, and BEAST X v 10.5.0. The spatial distribution, evolutionary history, viral ancestral introductions, and geographic dispersal patterns were characterized. Results: Three major lineages following WHO nomenclature were identified: Alpha, Delta, and Omicron. The Delta variant exhibited the widest geographic spread, detected in 14 states, while the Alpha variant was the least distributed, identified in only eight states but present across most epidemiological weeks studied. Evolutionary rates varied slightly, with Alpha exhibiting the slowest rate (2.66 × 10 −4 substitutions/site/year). Viral population analyses showed distinct patterns: Omicron sustained elevated population growth over time, while Delta declined after initial expansion. The earliest Times to Most Recent Common Ancestor (TMRCA) were consistent with the earliest outbreaks of SARS-CoV-2 globally. Geographic transmission analysis indicated a predominant coastal-to-inland spread for all variants, with Omicron showing the most diffuse dispersal, highlighting commercial routes as significant drivers of viral diffusion. Conclusion: The SARS-CoV-2 epidemic in Nigeria was characterized by multiple variant introductions and a dominant coastal-to-inland spread, emphasizing that despite lockdown measures, commercial trade routes played a critical role in viral dissemination. These findings provide insights into pandemic control strategies and future outbreak preparedness.

Nigeria↗
DOE OSTI2025

Development of an ultrahigh affinity, trimeric ACE2 biologic as a universal SARS-CoV-2 antagonist

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 pandemic, utilizes membrane-bound, angiotensin-converting enzyme II (ACE2) for internalization and infection. We describe the development of a biologic that takes advantage of the proximity of the N-terminus of bound ACE2 to the three-fold symmetry axis of the spike protein to create an ultrapotent, trivalent ACE2 entry antagonist. Distinct disulfide bonds were added to enhance serum stability and a single point mutation was introduced to eliminate enzymatic activity. Through surface plasmon resonance, pseudovirus neutralization assays, and single-particle cryo-electron microscopy, we show this antagonist binds to and inhibits SARS-CoV-2 variants. We further show the antagonist binds to and inhibits a 2003 SARS-CoV-1 strain. Collectively, structural insight has allowed us to design a universal trivalent antagonist against all variants of SARS-CoV-2 tested, suggesting it will be active against the emergence of future mutants.

Gonzales, Juliet (ORCID:0000000327219566)↗
DOE OSTI2025

A 1-year study on SARS-CoV-2 variant shifts in wastewater using dPCR: comparison with clinical and GISAID data

Wastewater testing can be used to monitor SARS-CoV-2 infections in communities. Data from PCR-based wastewater testing are usually available to public health authorities within 5–7 days after excreta and other body fluids enter the sewer. While PCR-based methods can accurately detect and quantify SARS-CoV-2, sequencing-based methods are usually required to distinguish between variants, delaying the results and adding cost to the process. We developed and assessed a novel, customizable digital PCR (dPCR)-based genotyping method for SARS-CoV-2 variant detection in wastewater, which is more cost-effective, faster, and more accessible than sequencing. This approach was applied to more than 1,400 wastewater samples

Wilton, Rose↗
DOE OSTI2026

Nicotine-Inspired, De Novo-Designed SARS-CoV-2 Main Protease Inhibitors Reveal Unique Chemistry for Covalently Conjugating Both Cysteine and Histidine Residues in the Catalytic Dyad

Anecdotal reports about smokers with low SARS-CoV-2 infection rates prompted a search for nicotine and its pyrolysis products as SARS-CoV-2 main protease (M Pro ) inhibitors. From this search, 3-vinylpyridine was discovered as a weak binder for the M Pro S1 subsite and was used subsequently as a de novo starting point for covalent inhibitor design that quickly yielded a highly potent inhibitor, SR-A-174, with an IC 50 value of 60 nM. Representing a novel class of M Pro inhibitors, SR-A-174 features an N,N -diaryl-α,α-dichloroacetamide scaffold that facilitated rapid exploration of alternative covalent warheads and various N-substituents, leading to the identification of multiple inhibitors with potent antiviral activity. Eight such M Pro inhibitor structures were determined, all demonstrating covalent binding to catalytic Cys145 of M Pro . In six determined structures, binding is dominated by the covalent bond plus van der Waals contacts, which contrasts with the extensive hydrogen bond networks formed with peptidomimetic inhibitors such as nirmatrelvir. Strikingly, two N,N -diaryl-α,α-dichloroacetamide inhibitors exhibit an unprecedented dual covalent modification mode of the catalytic dyad, forming bonds to both Cys145 and His41 with a concomitant loss of both chlorides and displacing the inhibitors from the S1 subsite. This dyad-targeting reactivity suggests a novel route for bioconjugation of both cysteine and histidine.

SARS-CoV-2↗
DOE OSTI2026

A funnel approach to enable analyses of epitope-specific human CD4 T cells specific for influenza and SARS-CoV-2

Protection against pathogens relies heavily on the adaptive immune response, whose key regulators are CD4 T cells. CD4 T cells, notable for their complex repertoire and functional potential, can most easily be dissected by identifying, quantifying, characterizing, and isolating epitope-specific cells. In the study reported here, we present a systematic and unbiased strategy that has enabled the identification of highly immunogenic peptide epitopes derived from influenza virus and SARS-CoV-2, presented by human HLA-DR proteins. Coupling the use of HLA-DR transgenic mice with infection and vaccination and highly sensitive epitope-specific cytokine ELISpot assays, we have narrowed the potential epitopes from 450 to 600 peptides to 5–15 peptides for each allele by an iterative process of elimination and selection, which we have termed a funnel approach. These epitopes have been validated in HLA-DR-typed human CD4 T cells directly ex vivo and enabled the derivation and implementation of HLA-DR peptide tetramers. Tetramer staining of human PBMCs enriched for CD4 T memory populations from healthy adult subjects, highlighted this approach as a sensitive and specific method for identifying novel epitopes, and subsequent CD4 T-cell responses to human viral infections.

CD4 T cell↗
DOE OSTI2025

Phosphorylation toggles the SARS-CoV-2 nucleocapsid protein between two membrane-associated condensate states

Abstract The Nucleocapsid protein (N) of SARS-CoV-2 plays a critical role in the viral lifecycle by regulating RNA replication and by packaging the viral genome. N and RNA phase separate to form condensates that may be important for these functions. Both functions occur at membrane surfaces, but how N toggles between these two membrane-associated functional states is unclear. Here, we reveal that phosphorylation switches how N condensates interact with membranes, in part by modulating condensate material properties. Our studies also show that phosphorylation alters N’s interaction with viral membrane proteins. We gain mechanistic insight through structural analysis and molecular simulations, which suggest phosphorylation induces a conformational change in N that softens condensate material properties. Together, our findings identify membrane association as a key feature of N condensates and provide mechanistic insights into the regulatory role of phosphorylation. Understanding this mechanism suggests potential therapeutic targets for COVID infection.

Science & Technology - Other Topics↗
DOE OSTI2026

Cleavage at the nsp5–nsp6 site of SARS-CoV-2 main protease intermediate precursor is faster from a monomer than a dimer form

Our previous studies of severe acute respiratory syndrome coronavirus 2 main protease (MPro) precursor monomer indicate that the initial N-terminal nonstructural protein (nsp)4/nsp5 cleavage occurs intramolecularly, with a small fraction of the active site loop equilibrium being in the active state. To understand the influence of dimer formation of MPro upon N-terminal cleavage on the subsequent C-terminal nsp5/nsp6 intermolecular cleavage kinetics, the stepwise processing of a monomeric, inactive precursor containing the native terminal cleavage sites of MPro (MBP- (−6) MPro C145A(+3) -GB1-6H, 86.2 kDa) by mature WT MPro (MPro WT ) was investigated. Differential scanning fluorimetry and analytical ultracentrifugation measurements of various MPro constructs suggest that the C145A mutation decreases the dimer dissociation constant (K dimer ) by ∼26-fold, relative to WT C145 and H41A. The monomeric precursor’s nsp4–nsp5 site appears to saturate MProWT’s active sites and cleave faster, followed by a slower first-order cleavage at the C-terminal site. No detectable product resulting from the C-terminal cleavage is observed until most of the N-terminal cleavage is complete. The initial intermediate product (termed MPro C145A-IP ) is a homodimer with an estimated K dimer of <0.05 μM. In contrast, the first-order kinetics observed for the cleavage of the monomeric form of the intermediate product is at least 300 times faster than that of the dimer form. Room-temperature X-ray structure of the MPro C145A-IP –ensitrelvir complex is like that of the MPro WT –ensitrelvir complex and reveals a dynamic C-terminal region including MPro residues 302 to 306. These results are interpreted from the point of view of a mechanism in which nsp5–nsp6 cleavage may occur from a monomeric intermediate, and dimer formation restricts this cleavage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Circadian immunometabolic states impart a temporal response to SARS-CoV-2 spike proteins in mammalian macrophages

Circadian rhythms, the 24-hour cycles that tune organismal physiology to the daily rhythms of light and dark, optimally organize cellular processes such as metabolism and mitochondrial function. In mammals, macrophage functions are regulated by these 24-hour circadian rhythms such that the immunometabolic response is coordinated across the day, consolidating macrophage physiology into temporally distinct phases to time the cellular immune response. However, while it is known that there are time-of-day specific responses to stress in a macrophage, little has been done to determine if circadian regulation coordinates the response of a macrophage to real-world pathogens. Importantly, key proteins in the response to viral infection have been found to be under circadian control, and time of day of application is known to affect the efficacy of vaccinations, including in the case of the COVID-19 virus. Therefore, to investigate if the circadian regulation of macrophage physiology imparted a time-of-day response to viral exposure, we exposed primary mouse and human macrophages to the SARS-CoV-1 and CoV-2 spike proteins at different times over the circadian day. To establish a time-of-day effect, we performed a multi-omics analysis and in vitro tissue culture assays examining macrophage responses over circadian time. We found that, conserved across the species, the timing of spike protein exposure dictated two distinct temporal responses which were characterized by hallmarks of immunometabolic suppression and modest inflammatory activation. However, these responses were primarily influenced by central metabolic and mitochondrial changes and not by classical immune activation.

Circadian Biology↗
DOE OSTI2025

S -Adenosylhomocysteine Analogs Selectively Suppress Pan-Coronavirus Replication by Inhibition of nsp14 Methyltransferase

To address the ongoing threat of SARS-CoV-2 and potential emergence of novel coronaviruses, we employed a comprehensive strategy to identify and synthesize inhibitors of coronavirus methyltransferases with chemical analogs of S-adenosylhomocysteine (SAH). Two analogs, designated 4h and 4p, inhibit both mouse hepatitis virus and SARS-CoV-2 replication. Compound 4p was the most potent with half-maximal inhibition of biochemical activity at 0.2 μM and antiviral activity at ∼20 μM. This compound also has low cytotoxicity and preferentially inhibits nsp14 over nsp16 and human methyltransferases. Furthermore, molecular docking based on a newly determined crystal structure of the apo nsp16−nsp10 complex predicts that 4p occupies both the Sadenosylmethione and Gppp binding pockets of nsp14 and nsp16. Selectivity of 4p for nsp14 is likely due to the enhanced structural stability of the nsp14 binding pocket relative to nsp16. These findings highlight SAH analogs as scaffolds for pan-coronavirus therapeutics and underscore the value of structure-guided design in antiviral drug discovery.

Coronavirus↗
DOE OSTI2026

Iterative ML and Experiments for Emerging VOCs

SAND2026-17074O Iterative ML and Experiments for Emerging VOCs is a tool that analyzes and predicts the behaviors of SARS-CoV-2 variants. It processes experimental data on ACE2 (the receptor for the SARS-CoV-2 virus that allows it to infect the cell) and antibody binding using machine learning models, including neural networks, to forecast ACE2 interactions and variant expression. The tool employs transfer learning and global epistasis modeling, integrating public datasets with proprietary data to enhance prediction accuracy. Additionally, it fits concentration-response curves to determine dissociation constants and generates visualizations to support research findings, thereby aiding in the identification of new antibodies for emerging variants of concern. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sheffield, Thomas [Sandia National Lab. (SNL-NM), ↗
DOE OSTI2026

Directed evolution of a stem-helix–targeting antibody enables MERS-CoV cross-neutralization through enhanced binding affinity

Broadly neutralizing antibodies (bnAbs) targeting conserved regions of the betacoronavirus spike are important for pan-betacoronavirus protection and pandemic preparedness. Here, we report the isolation of a human monoclonal antibody, CC65.1, from a SARS-CoV-2 convalescent donor that targets the conserved S2 stem helix region. CC65.1 neutralizes various sarbecoviruses, including SARS-CoV-2, and binds to the MERS-CoV spike but lacks MERS-CoV-neutralizing activity due to insufficient binding affinity. We utilized directed evolution to enhance the binding affinity of CC65.1 for the MERS-CoV S2 stem helix, yielding engineered antibody variants with newly acquired MERS-CoV-neutralizing activity. High-resolution structural analysis reveals key paratope mutations that enhance binding and stabilize epitope engagement. Our findings demonstrate the potential of in vitro affinity maturation to expand the neutralization breadth of stem-helix-targeting antibodies across divergent betacoronaviruses. This work supports the development of engineered bnAbs for broadly protective betacoronavirus countermeasures and provides a strategy for achieving cross-lineage neutralization.

Zhou, Panpan↗
DOE OSTI2025

A split luciferase system for studying coronavirus Mpro dimerization in vitro and in living cells

The main protease enzyme (Mpro) of coronaviruses cleaves the viral polyprotein into functional units essential for virus replication. Prior work has demonstrated that Mpro functions as a homodimer. However, studies on the mechanism of dimerization have been challenging because the purified protease is mostly dimeric, dimerization-defective mutants lack proteolytic activity, and robust cell-based assays have yet to be reported. To enable work on Mpro dimerization, we have developed a quantitative luciferase-based SARS-CoV-2 (SARS2) Mpro biosensor that accurately reports protein dimerization in living cells and, upon purification, also in vitro. Co-transfection of cells with a construct expressing Mpro fused to the 18 kDa LargeBiT of luciferase (LgBiT) and a second construct with Mpro fused to the 1 kDa SmallBiT of luciferase (SmBiT) results in a reconstitution of luciferase activity in a dose-dependent manner that requires conserved residues within the dimerization interface. Proteolytic activity is dispensable for dimerization and, uniquely, a C145A catalytically inactive mutant exhibits enhanced dimerization signal likely due to lower cytotoxicity. Mpro enzymes from multiple different coronaviruses also dimerize in this system, indicating mechanistic conservation. Interestingly, this dimerization biosensor also provides a quantitative read-out of inhibitor-facilitated dimerization. Covalent SARS2 Mpro inhibitors such as nirmatrelvir cause a 3- to 5-fold increase in luciferase activity. Together with corroborating structural, biophysical, and molecular dynamics experiments, our studies support a model in which covalent Mpro inhibitors such as nirmatrelvir simultaneously block catalytic activity and induce allosteric stabilization of the dimeric complex.

SARS-CoV-2 main protease (Mpro/3CLpro)↗
DOE OSTI2026

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Heterogeneous estimations of non-pharmaceutical mitigation behavior during the COVID-19 pandemic

The COVID-19 pandemic highlighted the importance of human behavior in mitigating the spread of disease. Nonetheless, human behavior is often overlooked in models of disease spread, particularly by underutilizing real-world data. We address this by estimating probabilities that individuals engage in behaviors that influence SARS-CoV-2 transmission risk during the COVID-19 pandemic, between September 2020 and June 2022. These behaviors include wearing a mask, using public transportation, spending time with others, avoiding contact with others, and going to work. Our estimates account for the age and sex of individuals and are generated for every county in the United States. We utilized multiple open-source datasets and United States Census data to produce these estimates. Multiple datasets were used for validation, showing our estimates demonstrated comparable accuracy and robustness. Our estimates aid in understanding human behavior dynamics during the COVID-19 pandemic and could be used to inform monthly or longer-term behavior in simulations of COVID-19. Moreover, the methods presented can be applied to other behaviors and features for future simulations of infectious disease.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗