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Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients
Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method th...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205692/ https://www.ncbi.nlm.nih.gov/pubmed/32479746 http://dx.doi.org/10.1016/j.cell.2020.05.006 |
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author | Bost, Pierre Giladi, Amir Liu, Yang Bendjelal, Yanis Xu, Gang David, Eyal Blecher-Gonen, Ronnie Cohen, Merav Medaglia, Chiara Li, Hanjie Deczkowska, Aleksandra Zhang, Shuye Schwikowski, Benno Zhang, Zheng Amit, Ido |
author_facet | Bost, Pierre Giladi, Amir Liu, Yang Bendjelal, Yanis Xu, Gang David, Eyal Blecher-Gonen, Ronnie Cohen, Merav Medaglia, Chiara Li, Hanjie Deczkowska, Aleksandra Zhang, Shuye Schwikowski, Benno Zhang, Zheng Amit, Ido |
author_sort | Bost, Pierre |
collection | PubMed |
description | Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped single-cell RNA sequencing (scRNA-seq) data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the sensitivity and specificity of Viral-Track to systematically detect viruses from multiple models of infection, including hepatitis B virus, in an unsupervised manner. Applying Viral-Track to bronchoalveloar-lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the virus on the immune system of severe patients compared to mild cases. Viral-Track detects an unexpected co-infection of the human metapneumovirus, present mainly in monocytes perturbed in type-I interferon (IFN)-signaling. Viral-Track provides a robust technology for dissecting the mechanisms of viral-infection and pathology. |
format | Online Article Text |
id | pubmed-7205692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72056922020-05-08 Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients Bost, Pierre Giladi, Amir Liu, Yang Bendjelal, Yanis Xu, Gang David, Eyal Blecher-Gonen, Ronnie Cohen, Merav Medaglia, Chiara Li, Hanjie Deczkowska, Aleksandra Zhang, Shuye Schwikowski, Benno Zhang, Zheng Amit, Ido Cell Article Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped single-cell RNA sequencing (scRNA-seq) data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the sensitivity and specificity of Viral-Track to systematically detect viruses from multiple models of infection, including hepatitis B virus, in an unsupervised manner. Applying Viral-Track to bronchoalveloar-lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the virus on the immune system of severe patients compared to mild cases. Viral-Track detects an unexpected co-infection of the human metapneumovirus, present mainly in monocytes perturbed in type-I interferon (IFN)-signaling. Viral-Track provides a robust technology for dissecting the mechanisms of viral-infection and pathology. Elsevier Inc. 2020-06-25 2020-05-08 /pmc/articles/PMC7205692/ /pubmed/32479746 http://dx.doi.org/10.1016/j.cell.2020.05.006 Text en © 2020 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Bost, Pierre Giladi, Amir Liu, Yang Bendjelal, Yanis Xu, Gang David, Eyal Blecher-Gonen, Ronnie Cohen, Merav Medaglia, Chiara Li, Hanjie Deczkowska, Aleksandra Zhang, Shuye Schwikowski, Benno Zhang, Zheng Amit, Ido Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title | Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title_full | Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title_fullStr | Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title_full_unstemmed | Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title_short | Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients |
title_sort | host-viral infection maps reveal signatures of severe covid-19 patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205692/ https://www.ncbi.nlm.nih.gov/pubmed/32479746 http://dx.doi.org/10.1016/j.cell.2020.05.006 |
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