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Reported here is a coding-complete genome sequence of a SARS CoV-2 variant obtained from raw wastewater samples at the University of Tennessee—Knoxville campus. This sequence provides insight into SARS CoV-2 variants that circulate on large college campuses but remain mostly undetected.
Coronavirus disease 2019 (COVID-19) is an acute complex systemic disorder caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).While SARS-CoV-2 is known to cause significant pulmonary disease, various extrapulmonary manifestations of COVID-19 have also been reported. Growing evidence suggests that COVID-19 is associated with coagulopathy leading to micro and macrovascular complications. Although in patients with COVID-19, venous thromboembolic events are more frequent, arterial thrombosis also occurs at an increased rate. These often lead to acute life-threatening ischemia, which requires urgent diagnosis and treatment. We present case reports of two patients with an abnormal thrombus formation in the thoracic aorta who recently overcame COVID-19, which led to systemic embolism and splenic infarction. Ambulatory oral factor Xa inhibitor therapy led to aortic thrombosis resolution in both patients.
All lineages of SARS-CoV-2, the coronavirus responsible for the COVID-19 pandemic, contain mutations between amino acids 199 and 205 in the nucleocapsid (N) protein that are associated with increased infectivity. The effects of these mutations have been difficult to determine because N protein contributes to both viral replication and viral particle assembly during infection. Here, we used single-cycle infection and virus-like particle assays to show that N protein phosphorylation has opposing effects on viral assembly and genome replication. Ancestral SARS-CoV-2 N protein is densely phosphorylated, leading to higher levels of genome replication but 10-fold lower particle assembly compared to evolved variants with low N protein phosphorylation, such as Delta (N:R203M), Iota (N:S202R), and B.1.2 (N:P199L). A new open reading frame encoding a truncated N protein called N*, which occurs in the B.1.1 lineage and subsequent lineages of the Alpha, Gamma, and Omicron variants, supports high levels of both assembly and replication. Our findings help explain the enhanced fitness of viral variants of concern and a potential avenue for continued viral selection.
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
The in-situ soil moisture and thaw depth measurements provided in this dataset were collected coincident with airborne overflights of L-band synthetic aperture radar (SAR) instruments at the Teller, Kougarok, and Council study sites on the Seward Peninsula, Alaska. Overflights occurred on August 19, 2022. Soil moisture data at Teller and Kougarok was collected on August 19, and at Council on August 20. Thaw depth, soil pits, and any additional measurements were recorded on August 20 and 21. Field measurements and flights were conducted during the summer of 2022 as a collaboration between the National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE) Project’s Airborne SAR Campaign and the Next-Generation Ecosystem Experiments (NGEE) Arctic Project. This dataset includes a data file (*.csv), a data dictionary (*_dd.csv) and a file-level metadata (*_flmd.csv). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Boronic acid-modified polymers (BAMPs) can interact with glycoproteins and other glycosylated compounds through covalent binding of the boronic acid moieties to saccharide residues. As a first step toward evaluating the utility of BAMPs as SARS-CoV-2 antiviral agents, this COVID-19 rapid response LDRD was intended to examine the effect of BAMPs on SARS-CoV-2 spike glycoprotein and its subsequent binding with ACE2 receptor protein. Multiple different approaches were attempted in order to determine whether BAMPs based on poly(ethylene glycol) and poly(ethylenimine) bind the spike protein, but failed to produce a definitive answer. However, two different enzyme-linked immunosorbent assays clearly showed no discernable effect of boronic acid in inhibiting spike-ACE2 binding.
A stripmap Synthetic Aperture Radar (SAR) image is a long SAR image along some centerline, and formed from multiple synthetic apertures. At issue is that the centerline in the image actually corresponds to an arc on a round earth, and multiple strategies exist for fitting the image centerline to the round earth. Some of those strategies involve Rhumb lines, great circle paths, and great ellipse paths. Some are better than others in polar regions. Notions of parallel flight paths for the radar during data collection also require careful consideration of the geometry of a round earth.
SARS-CoV-2 replication involves the synthesis of two large proteins, which are inactive and harmless until the viral main protease enzyme (3CL M pro ) uses them as substrates, cleaving them into many smaller, functional products. Dr Andrey Kovalevsky and his team from Oak Ridge National Laboratory propose a design of novel inhibitors and the repurposing of clinical drugs developed to treat other diseases for the treatment of COVID-19. Finally, the team uses room temperature crystallography with X-rays and neutrons to guide structure-based and computer-assisted drug design and to assess the ability of drugs to inhibit the SARS-CoV-2 main protease, causing virus replication to stop.
Statistical and epidemiological data imply temperature sensitivity of the SARS-CoV2 coronavirus. However, the molecular level understanding of the virus structure at different temperature is still not clear. Spike protein is the outermost structural protein of the SARS-CoV-2 virus which interacts with the Angiotensin Converting Enzyme 2 (ACE2), a human receptor, and enters the respiratory system. In this study, we performed an all atom molecular dynamics simulation to study the effect of temperature on the structure of the Spike protein. After 200 ns of simulation at different temperatures, we came across some interesting phenomena exhibited by the protein. We found that the solvent exposed domain of Spike protein, namely S1, is more mobile than the transmembrane domain, S2. Structural studies implied the presence of several charged residues on the surface of N-terminal Domain of S1 which are optimally oriented at 10– 30°C. Bioinformatics analyses indicated that it is capable of binding to other human receptors and should not be disregarded. Additionally, we found that receptor binding motif (RBM), present on the receptor binding domain (RBD) of S1, begins to close around temperature of 40°C and attains a completely closed conformation at 50°C. We also found that the presence of glycan moieties did not influence the observed protein dynamics. Nevertheless, the closed conformation disables its ability to bind to ACE2, due to the burying of its receptor binding residues. Our results clearly show that there are active and inactive states of the protein at different temperatures. This would not only prove beneficial for understanding the fundamental nature of the virus, but would be also useful in the development of vaccines and therapeutics.
The scientific and public health communities responded to the COVID-19 pandemic with sample acquisition and genome sequencing on a scale that eclipsed all prior sequencing efforts. While this can only be characterized as a resounding success story that has cemented the use of genomics for epidemiological investigations for any future infectious disease outbreak, several retrospective studies are cataloging an array of lessons learned and issues that have yet to be addressed in order to realize the full potential of genomics as a routine biosurveillance tool. We have been both developing methods to accurately assess SARS-CoV-2 genomes from complex samples, and analyzing the large volumes of international data, both at the consensus level and the raw sequencing data. During the course of our investigations and similar to other groups, we have examined COVID-19 samples with signatures from multiple lineages of SARS-CoV-2 and will describe some of our findings during the development of a novel workflow that incorporates detection and reporting of potential co-infection within samples and also highlights any evidence of within-host recombination.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.
Stable subauroral red arcs (SAR arcs) were observed in both the northern and southern hemispheres on Sept. 28 to 30, 1967. For each pass the universal time and the longitude of the spacecraft as it crossed the magnetic equator are given. The SAR arc was noted to be worldwide in its extent and located on the same L shell in the northern and southern hemispheres. It appeared near L equals 3, moved equatorward to L equals 2.4, and later moved to, or reformed, near L equals 2.9. Its intensities were variable over the nearly two days of observations and, apparently influenced by the composition of the lower thermosphere, averaged 60 per cent greater in the northern hemisphere.
Observations from five separate experiments on the Isis 2 spacecraft are used to study the atmosphere/ionosphere during the magnetic storm of December 16-20, 1971. The data are most complete in the midlatitude region, permitting a study of the SAR arc (subauroral red arc) which developed during the night of December 17-18. Ion composition and temperature, electron temperature, electron-density height profiles from the spacecraft to the F region, and the intensity of the 6300-A oxygen emission are all presented for the region of interest. It is found that the H(+) concentration had sharp gradients near the SAR arc and that the plasma temperature was significantly enhanced over typical nighttime values, reaching nearly 7000 K at 1400 km on the field line which intersected the arc. A system of time-dependent equations for atmospheric/ionospheric composition and temperature is solved using boundary conditions which were selected so that the solutions are in agreement with the observations. From these solutions, an assessment is made of the influence of (1) the efflux of plasma from the ionosphere to the magnetosphere, (2) the decrease in O/N2 at the turbopause, (3) the increase in the loss coefficient as a result of an increase in the vibrational temperature of N2, and (4) the conduction of thermal energy into the ionosphere.
This paper describes a digital processing algorithm and its associated system design for producing images from Synthetic Aperture Radar (SAR) data. The proposed system uses the Fast Fourier Transform (FFT) approach to perform the two-dimensional correlation process. The range migration problem, which is often a major obstacle to efficient processing, can be alleviated by approximating the locus of echoes from a point target by several linear segments. SAR data corresponding to each segment is correlated separately, and the results are coherently summed to produce full-resolution images. This processing approach exhibits greatly improved computation efficiency relative to conventional digital processing methods.
Data digitization and thresholding are applied to two scenes - sea ice and fresh-water lakes - to define the possible uses of automatic picture processing of uncalibrated SAR L-band imagery. It is shown that certain types of features, those which have constant returns which are also very high or very low in intensity can be effectively studied using simple automatic picture processing techniques applied to uncalibrated radar data. In areas which are generally inaccessible or in which monitoring of the changes of some types of earth surfaces are required, the uncalibrated SAR data can provide valuable inputs for modeling and mapping purposes.
A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.
In order to predict the performance of a synthetic aperture radar for a wide variety of system and environmental parameters a computer simulation of the SAR system was developed. This model is a detailed description of the SAR imaging process on a pulse-by-pulse basis. The simulation is implemented as seven computer programs for a CDC Cyber 171 digital computer.
The application of modern LSI technology to the development of a time-domain azimuth correlator for SAR processing is discussed. General design requirements for azimuth correlators for missions such as SEASAT-A, Venus orbital imaging radar (VOIR), and shuttle imaging radar (SIR) are summarized. Several azimuth correlator architectures that are suitable for implementation using custom LSI devices are described. Technical factors pertaining to selection of appropriate LSI technologies are discussed, and the maturity of alternative technologies for spacecraft applications are reported in the context of expected space mission launch dates. The preliminary design of a custom LSI time-domain azimuth correlator device (ACD) being developed for use in future SAR processors is detailed.