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Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure.
Rando, Halie M; MacLean, Adam L; Lee, Alexandra J; Lordan, Ronan; Ray, Sandipan; Bansal, Vikas; Skelly, Ashwin N; Sell, Elizabeth; Dziak, John J; Shinholster, Lamonica; D'Agostino McGowan, Lucy; Ben Guebila, Marouen; Wellhausen, Nils; Knyazev, Sergey; Boca, Simina M; Capone, Stephen; Qi, Yanjun; Park, YoSon; Mai, David; Sun, Yuchen; Boerckel, Joel D; Brueffer, Christian; Byrd, James Brian; Kamil, Jeremy P; Wang, Jinhui; Velazquez, Ryan; Szeto, Gregory L; Barton, John P; Goel, Rishi Raj; Mangul, Serghei; Lubiana, Tiago; Gitter, Anthony; Greene, Casey S.
  • Rando HM; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • MacLean AL; Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, USA.
  • Lee AJ; Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, USA.
  • Lordan R; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.
  • Ray S; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Bansal V; Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Skelly AN; Department of Biotechnology, Indian Institute of Technology Hyderabad, Sangareddy, Telangana, India.
  • Sell E; Biomedical Data Science and Machine Learning Group, German Center for Neurodegenerative Diseases, Tübingen, Germany.
  • Dziak JJ; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Shinholster L; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • D'Agostino McGowan L; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Ben Guebila M; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, Pennsylvania, USA.
  • Wellhausen N; Mercer University, Macon, Georgia, USA.
  • Knyazev S; Department of Mathematics and Statistics, Wake Forest Universitygrid.241167.7, Winston-Salem, North Carolina, USA.
  • Boca SM; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.
  • Capone S; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Qi Y; Georgia State University, Atlanta, Georgia, USA.
  • Park Y; Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC, USA.
  • Mai D; Early Biometrics & Statistical Innovation, Data Science & Artificial Intelligence, R & D, AstraZeneca, Gaithersburg, Maryland, USA.
  • Sun Y; St. George's University School of Medicine, St. George's, Grenada.
  • Boerckel JD; Department of Computer Science, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
  • Brueffer C; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Byrd JB; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Kamil JP; Department of Computer Science, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
  • Wang J; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Velazquez R; Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Szeto GL; Department of Clinical Sciences, Lund University, Lund, Sweden.
  • Barton JP; University of Michigan School of Medicine, Ann Arbor, Michigan, USA.
  • Goel RR; Department of Microbiology and Immunology, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA.
  • Mangul S; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Lubiana T; Azimuth1, McLean, Virginia, USA.
  • Gitter A; Department of Physics and Astronomy, University of California-Riverside, Riverside, California, USA.
  • Greene CS; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
mSystems ; 6(5): e0009521, 2021 10 26.
Article in English | MEDLINE | ID: covidwho-1483995
ABSTRACT
The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the genomic content of coronaviruses, which specifies the virus's structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system's protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the structure, phylogeny, and pathogenesis of the virus therefore helps to guide interpretation of the broader impacts of the virus on the human body and on human populations. For this reason, an in-depth exploration of viral mechanisms is critical to a robust understanding of SARS-CoV-2 and, potentially, future emergent human CoVs (HCoVs).
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid / Variants Language: English Journal: MSystems Year: 2021 Document Type: Article Affiliation country: MSystems.00095-21

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid / Variants Language: English Journal: MSystems Year: 2021 Document Type: Article Affiliation country: MSystems.00095-21