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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Atypical Divergence of SARS-CoV-2 Orf8 from Orf7a within the Coronavirus Lineage Suggests Potential Stealthy Viral Strategies in Immune Evasion

Orf8, one of the most puzzling genes in the SARS lineage of coronaviruses, marks a unique and striking difference in genome organization between SARS-CoV-2 and SARS-CoV-1. Here, using sequence comparisons, we unequivocally reveal the distant sequence similarities between SARS-CoV-2 Orf8 with its SARS-CoV-1 counterparts and the X4-like genes of coronaviruses, including its highly divergent “paralog” gene Orf7a, whose product is a potential immune antagonist of known structure. Supervised sequence space walks unravel identity levels that drop below 10% and yet exhibit subtle conservation patterns in this novel superfamily, characterized by an immunoglobulin-like beta sandwich topology. We document the high accuracy of the sequence space walk process in detail and characterize the subgroups of the superfamily in sequence space by systematic annotation of gene and taxon groups. While SARS-CoV-1 Orf7a and Orf8 genes are most similar to bat virus sequences, their SARS-CoV-2 counterparts are closer to pangolin virus homologs, reflecting the fine structure of conservation patterns within the SARS-CoV-2 genomes. The divergence between Orf7a and Orf8 is exceptionally idiosyncratic, since Orf7a is more constrained, whereas Orf8 is subject to rampant change, a peculiar feature that may be related to hitherto-unknown viral infection strategies. Despite their common origin, the Orf7a and Orf8 protein families exhibit different modes of evolutionary trajectories within the coronavirus lineage, which might be partly attributable to their complex interactions with the mammalian host cell, reflected by a multitude of functional associations of Orf8 in SARS-CoV-2 compared to a very small number of interactions discovered for Orf7a.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Integration of SARS-CoV-2 testing and genomic sequencing into influenza sentinel surveillance in Uganda, January to December 2022

The Uganda Virus Research Institute, National Influenza Center laboratory integrated SARS-CoV-2 polymerase chain reaction testing and genomic sequencing into the influenza surveillance program that was established in 2007. A total of 7,698 nasopharyngeal/oropharyngeal (NP/OP) swab samples were collected and analyzed from ILI/SARI sentinel sites across the country from January to December 2022. All samples were tested for influenza and SARS-CoV-2. Of these, 252 (3.3%), 162 (2.1%), and 589 (7.7%) were positive for influenza A, influenza B, and SARS-CoV-2, respectively. Out of 414 influenza-positive samples, 122 (29.5%) were AH1pdm09, 130 (31.4%) were AH3, and 162 (39.1%) were B-Victoria. All SARS-CoV-2 sequenced samples were of the Omicron variant, with subvariants of concern known to evade the immune system being detected, such as BQ.1 and XBB.2. Other SARS-CoV-2 positive samples collected from other health centers in the community outside the surveillance sites were included into SARS-CoV-2 genomic sequencing with similar patterns with respect to variants. In all, the ILI/SARI surveillance system has shown to be an efficient, cost-effective, and sustainable program, providing a ready platform to monitor the circulation of SARS-CoV-2 in communities at the national level while remaining vigilant for the persistent threat of influenza. The integration of SARS-CoV-2 detection and genomic surveillance into the influenza surveillance program will strengthen the laboratory response capacity, as well as facilitate the timely release of SARS-CoV-2 genomic information to be used to complement the multiple response strategies for COVID-19 pandemic mitigation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Design Thinking for the Applied Sciences: Developing a Novel Approach to Encourage the Use of Synthetic Aperture Radar (SAR) and Open Source Tools for Forest Monitoring

Earth observations from Synthetic Aperture Radar, or SAR, have yet to be fully leveraged for forest monitoring applications. While SAR sensors are uniquely able to capture components of forest structure over optical imagery, especially in cloud-heavy regions, there is a shortage of freely-available applied training materials and related case studies. With the wealth of available datasets from Sentinel-1 and other missions, such as ALOS-Palsar open historical archive, and in preparation for upcoming opendata policy SAR missions (e.g. NISAR and BIOMASS), the applied forestry community would benefit from increased access to relevant, understandable SAR training materials. This work documents lessons learned and best practices for creating EO capacity building/training materials gleaned from the SAR Handbook project. Strategies for increasing legibility for both print and online applications, illustration and editing guidelines for original and modified figures, and the development of quick-reference guides will be shared. Additionally, the conception and use of companion “explainer” videos, using cartoon characters and humor to outline relevant SAR concepts will be explored. Preliminary results indicate the SAR Handbook and supplemental project materials are already having an impact in training sessions. Increased uptake of SAR technologies in SERVIR Hub regions, where Hubs are leading follow-on SAR trainings, has also been noted. In addition, a review of download statistics from the SERVIR global website indicates widespread worldwide access. We conclude similar holistic approaches integrating design concepts into future content development would help increase uptake of EO applications by the earth science community.

Kucera, Leah M.↗
DOE OSTI2020

Co-notch and independent windowing to mitigate interference in SAR-based imagery

Various technologies for mitigating distortion in coherent image products generated from SAR data are described herein. Synthetic aperture radar (SAR) datasets generated based upon SAR returns from first and second passes of a SAR platform over a scene are received. The SAR datasets can be co-notched at matching sample indices to improve coherence of SAR images generated from the datasets. Windowed SAR data is generated by applying independent windows to subsets of each of the datasets to reduce sidelobe levels of their image impulse responses. Coherent image products are generated based upon the windowed SAR data, wherein an image quality of the coherent image products is improved as compared to coherent image products generated based upon the SAR datasets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Structure of SARS-CoV-2 ORF8, a rapidly evolving immune evasion protein

The molecular basis for the severity and rapid spread of the COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely unknown. ORF8 is a rapidly evolving accessory protein that has been proposed to interfere with immune responses. The crystal structure of SARS-CoV-2 ORF8 was determined at 2.04-Å resolution by X-ray crystallography. The structure reveals a ~60-residue core similar to SARS-CoV-2 ORF7a, with the addition of two dimerization interfaces unique to SARS-CoV-2 ORF8. A covalent disulfide-linked dimer is formed through an N-terminal sequence specific to SARS-CoV-2, while a separate noncovalent interface is formed by another SARS-CoV-2-specific sequence, 73 YIDI 76 . Together, the presence of these interfaces shows how SARS-CoV-2 ORF8 can form unique large-scale assemblies not possible for SARS-CoV, potentially mediating unique immune suppression and evasion activities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Identifying key determinants and dynamics of SARS-CoV-2/ACE2 tight interaction

SARS-CoV-2 virus, the causative agent of Covid-19, has fired up a global pandemic. The virus interacts with the human receptor angiotensin-converting enzyme 2 (ACE2) for an invasion via receptor binding domain (RBD) on its spike protein. To provide a deeper understanding of this interaction, we performed microsecond simulations of the RBD-ACE2 complex for SARS-CoV-2 and compared it with the closely related SARS-CoV discovered in 2003. We show residues in the RBD of SARS-CoV-2 that were mutated from SARS-CoV, collectively help make the RBD anchor much stronger to the N-terminal part of ACE2 than the corresponding residues on RBD of SARS-CoV. This would result in a reduced dissociation rate of SARS-CoV-2 from human receptor protein compared to SARS-CoV. The phenomenon was consistently observed in simulations beyond 500 ns and was reproducible across different force fields. Altogether, our study adds more insight into the critical dynamics of the key residues at the virus spike and human receptor binding interface and potentially aids the development of diagnostics and therapeutics to combat the pandemic efficiently.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2013

Validation of Forested Inundation Extent Revealed by L-Band Polarimetric and Interferometric SAR Data

UAVSAR, NASA's airborne Synthetic Aperture Radar (SAR), conducted an extended observational campaign in Central and South America in March 2013, primarily related to volcanic deformations along the Andean Mountain Range but also including a large number of flights studying other scientific phenomena. During this campaign, the L-Band SAR collected data over the Napo River in Ecuador. The objectives of this experiment were to acquire polarimetric and interferometric L-Band SAR data over an inundated tropical forest in Ecuador simultaneously with on-the-ground field work ascertaining the extent of inundation, and to then derive from this data a quantitative estimate for the error in the SAR-derived inundation extent. In this paper, we will first describe the processing and preliminary analysis of the SAR data. The polarimetric SAR data will be classified by land cover and inundation state. The interferometric SAR data will be used to identify those areas where change in inundation extent occurred, and to measure the change in water level between two observations separated by a week. Second, we will describe the collection of the field estimates of inundation, and have preliminary comparisons of inundation extent measured in the field field versus that estimated from the SAR data.

Synthetic Aperture Radar (SAR),↗
DOE OSTI2020

SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed

Wastewater-based epidemiology may be useful for informing public health response to viral diseases like COVID-19 caused by SARS-CoV-2. Here, we quantified SARS-CoV-2 RNA in wastewater influent and primary settled solids in two wastewater treatment plants to inform the preanalytical and analytical approaches and to assess whether influent or solids harbored more viral targets. The primary settled solids samples resulted in higher SARS-CoV-2 detection frequencies than the corresponding influent samples. Likewise, SARS-CoV-2 RNA was more readily detected in solids using one-step digital droplet (dd)RT-PCR than with two-step RT-QPCR and two-step ddRT-PCR, likely owing to reduced inhibition with the one-step ddRT-PCR assay. We subsequently analyzed a longitudinal time series of 89 settled solids samples from a single plant for SARS-CoV-2 RNA as well as coronavirus recovery (bovine coronavirus) and fecal strength (pepper mild mottle virus) controls. SARS-CoV-2 RNA targets N1 and N2 concentrations correlated positively and significantly with COVID-19 clinically confirmed case counts in the sewershed. Together, the results demonstrate that measuring SARS-CoV-2 RNA concentrations in settled solids may be a more sensitive approach than measuring SARS-CoV-2 in influent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

Research & Experimental Medicine↗
NASA NTRS1983

SAR calibration: A technology review

Various potential applications of amplitude-calibrated SAR systems are briefly described, along with an estimate of calibration performance requirements. A review of the basic SAR calibration problem is given. For background purposes and to establish consistent definition of terms, various conventional SAR performance parameters are reviewed along with three additional parameters which are directly related to calibrated SAR systems. Techniques for calibrating a SAR are described. Included in the results presented are: calibration philosophy and procedures; review of the calibration signal generator technology development with results describing both the development of instrumentation and internal calibration measurements for two SAR systems; summary of analysis and measurements required to determine optimum retroreflector design and configuration for use as a reference for the absolute calibration of a SAR system; and summary of techniques for in-flight measurements of SAR antenna response.

Larson, R. W.↗
NASA NTRS1993

Cross-calibration between airborne SAR sensors

As Synthetic Aperture Radar (SAR) system performance and experience in SAR signature evaluation increase, quantitative analysis becomes more and more important. Such analyses require an absolute radiometric calibration of the complete SAR system. To keep the expenditure on calibration of future multichannel and multisensor remote sensing systems (e.g., X-SAR/SIR-C) within a tolerable level, data from different tracks and different sensors (channels) must be cross calibrated. The 1989 joint E-SAR/DC-8 SAR calibration campaign gave a first opportunity for such an experiment, including cross sensor and cross track calibration. A basic requirement for successful cross calibration is the stability of the SAR systems. The calibration parameters derived from different tracks and the polarimetric properties of the uncalibrated data are used to describe this stability. Quality criteria for a successful cross calibration are the agreement of alpha degree values and the consistency of radar cross sections of equally sized corner reflectors. Channel imbalance and cross talk provide additional quality in case of the polarimetric DC-8 SAR.

Zink, Manfred↗
NASA NTRS2018

Design Principles for Smallsat SARs

Synthetic Aperture Radar (SAR) is by now a mature remote sensing technique to obtain spatially-resolved radar measurements of terrain. Currently, SAR image data are readily available from an ever-expanding multitude of SAR satellites in Earth orbit. Many spaceborne SAR systems currently in use or planned for the near-term are multifunctional: their designs tend to maximize the menu of image modes available to the end user. They also follow fairly conventional design principles, laid down decades ago, that lead almost inevitably to large antennas and even larger spacecraft. This raises the question: how does one go about designing a SAR system that fits in a Smallsat (<200 kg) form factor? The design principles for Smallsat SARs outlined in this paper have been developed over a twenty-year period in architecting Earth-orbiting SARs such as NASA/JPL’s NISAR and ESA’s Biomass mission, as well as planetary SAR mission concepts. Example mission concepts following this approach will be presented at the end of the paper. These include an S-Band Smallsat geodetic constellation to measure surface deformation, as called for by the 2018 National Academy Decadal Survey for Earth Observation from Space. Another example is a Ka-band cubesat-sized system designed to detect changes on Earth’s surface.

Freeman, Anthony↗
NASA NTRS2019

Early Lessons on Combining Lidar and Multi‑baseline SAR Measurements for Forest Structure Characterization

The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements pro-vided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established frame-work for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns.

Matteo Pardini↗
NASA NTRSDate not supplied

Evaluating SAR Radiometric Terrain Correction products: Optimal products for applied users

Operational applications for Synthetic Aperture Radar (SAR) are under development around the world, driven by the free-and-open access of SAR C-band observations that Sentinel-1 of Copernicus has been providing since 2014. Groups like SERVIR, a joint initiative between NASA and USAID, are at the forefront of remote sensing applied uses, and have made many significant contributions to lower the barrier to access, process, and apply SAR for ecosystem services. A takeaway from the SERVIR experience in using SAR is the need to use the appropriate SAR polarimetric product. Radiometric Terrain Correction (RTC) is a key entry-level product for multiple applications that range from ecosystems to hazards. Many software packages exist to create RTC products from SLC or GRD-type Level-1 SAR data, some of which were released only recently, e.g. Interferometric SAR Computing Environment (ISCE) added an RTC module in April 2020. In addition, new versions of open source softwares are expected to address known issues from previous versions, such as Sentinel-1 Toolbox from the European Space Agency (SNAP-7). Despite the growing availability of RTC software solutions, little work has been done to identify differences between RTC products from different softwares. And to address the question, which open-source software produces the most accurate RTC product? This work evaluates Sentinel-1 RTC products created with three different softwares and approaches, including SNAP-7, ISCE-2, and a pseudo RTC product derived from GEE. The GAMMA-derived RTC product, a known optimal RTC and implemented by Alaska Satellite Facility (ASF), is used as a reference. Time series stacks over ten different sites representing varied terrain and ecosystems are evaluated. Products are evaluated for geolocation quality, absolute radiometric calibration, and for the fidelity of the radiometric terrain flattening. The results provide direct guidance and recommendations about the quality of the RTC products obtained from open source methods. This understanding is key to develop operational applications that rely on SAR Sentinel-1 data that need affordable and scalable solutions.

Africa Flores-Anderson↗
DOE OSTI2020

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Bistatic SAR: Proof of Concept.

Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

Yocky, David A.↗
NASA NTRS1981

Multisensor analysis of hydrologic features with emphasis on the Seasat SAR

Synthetic aperture radar (SAR) imagery of the Wind River Range area in Wyoming is compared with visible and near-infrared imagery of the same area. Data from the Seasat L-Band SAR and an aircraft X-Band SAR are compared with Landsat Return Beam Vidicon (RBV) visible data and near-infrared aerial photography and topographic maps of the same area. It is noted that visible and near-infrared data provide more information than the SAR data when conditions are the most favorable. The SAR penetrates clouds and snow, however, and data can be acquired day or night. Drainage density detail is good on SAR imagery because individual streams show up well owing to riparian vegetation; this causes higher radar reflections which result from the 'rough' surface which vegetation creates. In the winter image, the X-Band radar data show high returns because of cracks on the lake ice surfaces. High returns can also be seen in the L-Band SAR imagery of the lakes due to ripples on the surface induced by wind. It is concluded that the use of multispectral data would optimize analysis of hydrologic features.

Foster, J. L.↗