In vivo antiviral host transcriptional response to SARS-CoV-2 by viral load, sex, and age
Authors: Vikas Peddu
Francesca Bovier
Pavitra Roychoudhury
Hong Xie
Matteo Porotto
Lasata Shrestha
Pei-Yong Shi
Megan C Mears
Anne Moscona
Dennis A Bente
Keith R Jerome
Meei-Li Huang
Nicole A P Lieberman
Alexander L Greninger
Maria N Cajimat
Journal: PLoS Biology (2020)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: SARS-CoV-2; host response; gene expression; antiviral factors; Th1 chemokines
Affiliations: Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington, United States of America., Galveston National Laboratory, University of Texas Medical Branch, Galveston, Texas, United States of America., Department of Experimental Pathology, University of Texas Medical Branch, Galveston, Texas, United States of America., Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, Texas, United States of America., Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America., Center for Host-Pathogen Interaction, Columbia University Medical Center, New York, New York, United States of America., Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America., Department of Pediatrics, Columbia University Medical Center, New York, New York, United States of America., Department of Microbiology & Immunology, Columbia University Medical Center, New York, New York, United States of America., Department of Physiology & Cellular Biophysics, Columbia University Medical Center, New York, New York, United States of America., Department of Experimental Medicine, University of Campania "Luigi Vanvitelli," Caserta, Italy.

Abstract:  Despite limited genomic diversity, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown a wide range of clinical manifestations in different patient populations. The mechanisms behind these host differences are still unclear. Here, we examined host response gene expression across infection status, viral load, age, and sex among shotgun RNA sequencing profiles of nasopharyngeal (NP) swabs from 430 individuals with PCR-confirmed SARS-CoV-2 and 54 negative controls. SARS-CoV-2 induced a strong antiviral response with up-regulation of antiviral factors such as OAS1-3 and IFIT1-3 and T helper type 1 (Th1) chemokines CXCL9/10/11, as well as a reduction in transcription of ribosomal proteins. SARS-CoV-2 culture in human airway epithelial (HAE) cultures replicated the in vivo antiviral host response 7 days post infection, with no induction of interferon-stimulated genes after 3 days. Patient-matched longitudinal specimens (mean elapsed time = 6.3 days) demonstrated reduction in interferon-induced transcription, recovery of transcription of ribosomal proteins, and initiation of wound healing and humoral immune responses. Expression of interferon-responsive genes, including ACE2, increased as a function of viral load, while transcripts for B cell-specific proteins and neutrophil chemokines were elevated in patients with lower viral load. Older individuals had reduced expression of the Th1 chemokines CXCL9/10/11 and their cognate receptor CXCR3, as well as CD8A and granzyme B, suggesting deficiencies in trafficking and/or function of cytotoxic T cells and natural killer (NK) cells. Relative to females, males had reduced B cell-specific and NK cell-specific transcripts and an increase in inhibitors of nuclear factor kappa-B (NF-κB) signaling, possibly inappropriately throttling antiviral responses. Collectively, our data demonstrate that host responses to SARS-CoV-2 are dependent on viral load and infection time course, with observed differences due to age and sex that may contribute to disease severity. 

Retracted: No

PubPeer comments:
 Cq values are used for Sars-CoV-2 quantification. Cq values can not be used as stand alone values, qPCR is a semi-quantitative technique. Furthermore, the largest issue is that 2 different techniques are used for extraction, and this is not taken into account (2 different volumes, 2 different kits). The latter and other sources of variability (including swabbing, storage, ...) make that the divisions based on Cq values might be off. Why not confirm the PCR data with the RNA seq data? The virus should be found back in there as well. ,