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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Defective Interfering Viral Particle Treatment Reduces Clinical Signs and Protects Hamsters from Lethal Nipah Virus Disease

Defective interfering particles (DIs) contain a considerably smaller genome than the parental virus but retain replication competency. As DIs can directly or indirectly alter propagation kinetics of the parental virus, they offer a novel approach to antiviral therapy, capitalizing on knowledge from natural infection. However, efforts to translate in vitro inhibition to in vivo screening models remain limited. We investigated the efficacy of virus-like particles containing DI genomes (therapeutic infectious particles [TIPs]) in the Syrian hamster model of lethal Nipah virus (NiV) disease. We found that coadministering a high dose of TIPs intraperitoneally with virus challenge improved clinical course and reduced lethality. To mimic natural exposure, we also evaluated lower-dose TIP delivery and virus challenge intranasally, finding equally efficacious reduction in disease severity and overall lethality. Eliminating TIP replicative capacity decreased efficacy, suggesting protection via direct inhibition. These data provide evidence that TIP-mediated treatment can confer protection against disease and lethal outcome in a robust animal NiV model, supporting further development of TIP treatment for NiV and other high-consequence pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The molecular basis of the neutralization breadth of the RBD-specific antibody CoV11

SARS-CoV-2, the virus behind the COVID-19 pandemic, has changed over time to the extent that the current virus is substantially different from what originally led to the pandemic in 2019–2020. Viral variants have modified the severity and transmissibility of the disease and continue do so. How much of this change is due to viral fitness versus a response to immune pressure is hard to define. One class of antibodies that continues to afford some level of protection from emerging variants are those that closely overlap the binding site for angiotensin-converting enzyme 2 (ACE2) on the receptor binding domain (RBD). Some members of this class that were identified early in the course of the pandemic arose from the VH 3-53 germline gene (IGHV3-53*01) and had short heavy chain complementarity-determining region 3s (CDR H3s). Here, we describe the molecular basis of the SARS-CoV-2 RBD recognition by the anti-RBD monoclonal antibody CoV11 isolated early in the COVID-19 pandemic and show how its unique mode of binding the RBD determines its neutralization breadth. CoV11 utilizes a heavy chain VH 3-53 and a light chain VK 3-20 germline sequence to bind to the RBD. Two of CoV11’s four heavy chain changes from the VH 3-53 germline sequence, $Thr^{28}_{FWRH1}$ to Ile and $Ser^{31}_{CDRH1}$ to Arg, and some unique features in its CDR H3 increase its affinity to the RBD, while the four light chain changes from the VK 3-20 germline sequence sit outside of the RBD binding site. Antibodies of this type can retain significant affinity and neutralization potency against variants of concern (VOCs) that have diverged significantly from original virus lineage such as the prevalent omicron variant. We also discuss the mechanism by which VH 3-53 encoded antibodies recognize spike antigen and show how minimal changes to their sequence, their choice of light chain, and their mode of binding influence their affinity and impact their neutralization breadth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Lipid-coated mesoporous silica nanoparticles for anti-viral applications via delivery of CRISPR-Cas9 ribonucleoproteins

Abstract Emerging and re-emerging viral pathogens present a unique challenge for anti-viral therapeutic development. Anti-viral approaches with high flexibility and rapid production times are essential for combating these high-pandemic risk viruses. CRISPR-Cas technologies have been extensively repurposed to treat a variety of diseases, with recent work expanding into potential applications against viral infections. However, delivery still presents a major challenge for these technologies. Lipid-coated mesoporous silica nanoparticles (LCMSNs) offer an attractive delivery vehicle for a variety of cargos due to their high biocompatibility, tractable synthesis, and amenability to chemical functionalization. Here, we report the use of LCMSNs to deliver CRISPR-Cas9 ribonucleoproteins (RNPs) that target the Niemann–Pick disease type C1 gene, an essential host factor required for entry of the high-pandemic risk pathogen Ebola virus, demonstrating an efficient reduction in viral infection. We further highlight successful in vivo delivery of the RNP-LCMSN platform to the mouse liver via systemic administration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Host cell and viral protease targets of human SERPINs identified by in silico docking

Serine protease inhibitors (SERPINs) are involved in various physiological processes and diseases, such as inflammation, cancer metastasis, and neurodegeneration. Their role in viral infections is poorly understood, as their expression patterns during infection and the range of proteases they target have yet to be fully characterized. Here, we show widespread expression of human SERPINs in response to respiratory virus infections, both in bronchioalveolar lavages from COVID-19 patients and in polarized human airway epithelial cultures. Using in silico docking of 10 SERPINs to 48 host proteases, we confirm known targets and predict new interactions. Protease activity assays validated selected interactions, confirming the newly predicted host targets for PAI-1 (SERPINE1) and PAI-2 (SERPINB2). PAI-1 inhibits cathepsin L, essential for SARS-CoV-2 maturation, and suppresses multi-cycle replication of both ancestral SARS-CoV-2 WA-1 and its variant Omicron BA.1. In addition, we identify PAI-2 as an antiviral SERPIN that reduces infectivity of human adenovirus 5 by directly inhibiting the adenoviral protease. Our study leverages in silico docking using full-length 3D protein structures to uncover new SERPIN targets, offering a range of candidate targets for therapeutic interventions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Pneumonia After Bacterial or Viral Infection Preceded or Followed by Radiation Exposure: A Reanalysis of Older Radiobiologic Data and Implications for Low-Dose Radiation Therapy for Coronavirus Disease 2019 Pneumonia

Currently, there are about 15 ongoing clinical studies on low dose radiation therapy for Coronavirus Disease 2019 pneumonia. One of the underlying assumptions is that irradiation of 0.5 to 1.5 Gy is effective at ameliorating viral pneumonia. We aimed to reanalyze all available experimental radiobiologic data to assess evidence for such amelioration.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Ticking off Lyme disease: OspA mRNA vaccine halts infection in mouse model

Lyme disease, a condition caused by Borrelia burgdorferi sensu lato and transmitted to humans via ticks, affects approximately 676,000 individuals annually in the United States and Western Europe.1 Currently, there is no approved Lyme vaccine available for human use. A promising study by Tahir et al., published in Molecular Therapy Nucleic Acids, investigated the efficacy of mRNA and subunit vaccines targeting Lyme disease.2 This research demonstrated complete protection from infection in a tick-fed mouse model using an outer surface protein A (OspA) mRNA vaccine. Although mRNA vaccines have shown success against viral pathogens, their clinical application against bacterial diseases has been limited.3 Thus, this study represents an important step toward developing an effective mRNA vaccine against Lyme disease.

He, Wei↗
DOE OSTI2022

An intranasal recombinant NDV-BRSV F opt vaccine is safe and reduces lesion severity in a colostrum-deprived calf model of RSV infection

Human respiratory syncytial virus (HRSV) is a major cause of severe lower respiratory tract disease in infants and the elderly, yet no safe, effective vaccine is commercially available. Closely related bovine RSV (BRSV) causes respiratory disease in young calves, with many similar features to those seen in HRSV. We previously showed that a Newcastle disease virus (NDV)-vectored vaccine expressing the F glycoprotein of HRSV reduced viral loads in lungs of mice and cotton rats and protected from HRSV. However, clinical signs and pathogenesis of disease in laboratory animals following HRSV infection differs from that observed in human infants. Thus, we examined whether a similar vaccine would protect neonatal calves from BRSV infection. Codon-optimized rNDV vaccine (rNDV-BRSV F opt ) was constructed and administered to colostrum-deprived calves. The rNDV-BRSV F opt vaccine was well-tolerated and there was no evidence of vaccine-enhanced disease in the upper airways or lungs of these calves compared to the non-vaccinated calves. We found two intranasal doses reduces severity of gross and microscopic lesions and decreases viral load in the lungs. Furthermore, serum neutralizing antibodies were generated in vaccinated calves. Finally, reduced lung CXC chemokine levels were observed in vaccinated calves after BRSV challenge. In summary, we have shown that rNDV-BRSV F opt vaccine is safe in colostrum-deprived calves, and is effective in reducing lung lesions, and decreasing viral load in upper respiratory tract and lungs after challenge.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

US National Institutes of Health Prioritization of SARS-CoV-2 Variants

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. Here, the group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada

West Nile virus is the most common mosquito borne disease in North America and the leading cause of viral encephalitis. West Nile virus is primarily transmitted between birds and mosquitoes while humans are incidental, dead-end hosts. Climate change may increase the risk of human infections as climatic variables have been shown to affect the mosquito life cycle, biting rate, incubation period of the disease in mosquitoes, and bird migration patterns. We develop a zero-inflated Poisson model to investigate how human West Nile virus case counts vary with respect to mosquito abundance and infection rates, bird abundance, and other environmental covariates. We use a Bayesian paradigm to fit our model to data from 2010–2019 in Ontario, Canada. Our results show mosquito infection rate, temperature, precipitation, and crow abundance are positively correlated with human cases while NDVI and robin abundance are negatively correlated with human cases. We find the inclusion of spatial random effects allows for more accurate predictions, particularly in years where cases are higher. Our model is able to accurately predict the magnitude and timing of yearly West Nile virus outbreaks and could be a valuable tool for public health officials to implement prevention strategies to mitigate these outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Rapid Computational Identification of Therapeutic Targets for Pathogens

Biological threats continue to persist and evolve as an important challenge to national security. There are multiple ways in which novel viral pathogens could emerge to pose a serious threat to human health. This project developed a pathogen target identification tool that can rapidly respond to a novel or emerging viral biological threat. A set of computational tools were developed that provide detailed information on the newly sequenced genes, their protein products and the drug target sites for the proteins that are best suited for biological countermeasure development. Three key innovations were developed in the project. 1) Development of a new extensive database of protein pocket structures with structure-based search algorithms to rapidly link novel protein targets with the complete collection of previously experimentally solved protein structures. 2) A novel clustering pipeline was introduced to group matching structures and associated small-molecule binding ligands into a consensus protein pocket with the associated small-molecule chemotypes predicted to fit in the pocket site. The matching experimentally solved structures were used to inform the value of different target sites. 3) Where there are viral protein targets with pockets structurally matched to similar human proteins, a biological knowledge graph, which links molecular interactions with human disease, was used to further assess the potential negative impact of a viral protein target with similarities to human proteins that could have important off target side effects. In total, the project produced a new resource for rapid and detailed assessment of promising targets for countermeasures, reflecting the ongoing wet lab, clinical, and computational data being collected. These capabilities will improve the ability to respond to a biological threat in multiple domains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes

Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10 –8 ) and three regions, 1q21.3 (MRPS21–PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10 –8 ) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Michaelis-like complex of SARS-CoV-2 main protease visualized by room-temperature X-ray crystallography

SARS-CoV-2 emerged at the end of 2019 to cause an unprecedented pandemic of the deadly respiratory disease COVID-19 that continues to date. The viral main protease (M pro ) is essential for SARS-CoV-2 replication and is therefore an important drug target. Understanding the catalytic mechanism of M pro , a cysteine protease with a catalytic site comprising the noncanonical Cys145–His41 dyad, can help in guiding drug design. Here, a 2.0 Å resolution room-temperature X-ray crystal structure is reported of a Michaelis-like complex of M pro harboring a single inactivating mutation C145A bound to the octapeptide Ac-SAVLQSGF-CONH 2 corresponding to the nsp4/nsp5 autocleavage site. The peptide substrate is unambiguously defined in subsites S5 to S3′ by strong electron density. Superposition of the Michaelis-like complex with the neutron structure of substrate-free M pro demonstrates that the catalytic site is inherently pre-organized for catalysis prior to substrate binding. Induced fit to the substrate is driven by P1 Gln binding in the predetermined subsite S1 and rearrangement of subsite S2 to accommodate P2 Leu. The Michaelis-like complex structure is ideal for in silico modeling of the SARS-CoV-2 M pro catalytic mechanism.

3CL protease↗
DOE OSTI2020

Laboratory Infection of Novel Akhmeta Virus in CAST/EiJ Mice

Akhmeta virus is a zoonotic Orthopoxvirus first identified in 2013 in the country of Georgia. Subsequent ecological investigations in Georgia have found evidence that this virus is widespread in its geographic distribution within the country and in its host-range, with rodents likely involved in its circulation in the wild. Yet, little is known about the pathogenicity of this virus in rodents. We conducted the first laboratory infection of Akhmeta virus in CAST/EiJ Mus musculus to further characterize this novel virus. We found a dose-dependent effect on mortality and weight loss (p < 0.05). Anti-orthopoxvirus antibodies were detected in the second- and third-highest dose groups (5 × 104 pfu and 3 × 102 pfu) at euthanasia by day 10, and day 14 post-infection, respectively. Anti-orthopoxvirus antibodies were not detected in the highest dose group (3 × 106 pfu), which were euthanized at day 7 post-infection and had high viral load in tissues, suggesting they succumbed to disease prior to mounting an effective immune response. In order of highest burden, viable virus was detected in the nostril, lung, tail, liver and spleen. All individuals tested in the highest dose groups were DNAemic. Akhmeta virus was highly pathogenic in CAST/EiJ Mus musculus, causing 100% mortality when ≥3 × 102 pfu was administered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Lassa Virus Replicon Particle Vaccine Protects Strain 13/N Guinea Pigs Against Challenge With Geographically and Genetically Diverse Viral Strains

Abstract Lassa virus (LASV) causes mild to severe hemorrhagic fever disease in humans. Strain 13/N guinea pigs are highly susceptible to infection with LASV strain Josiah (clade IV), providing a critical model system for therapeutics and vaccine development. To develop additional models of disease, we detail the clinical course in guinea pigs infected with 5 geographically and genetically diverse LASV strains. Two of the developed models (LASV clades II and III) were then used to evaluate efficacy of a virus replicon particle vaccine against heterologous LASV challenge, demonstrating complete protection against clinical disease after a single vaccination dose.

Immunology↗