Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

 PMID:33619488  

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19.

Carly G K Ziegler | Vincent N Miao | Anna H Owings | Andrew W Navia | Ying Tang | Joshua D Bromley | Peter Lotfy | Meredith Sloan | Hannah Laird | Haley B Williams | Micayla George | Riley S Drake | Taylor Christian | Adam Parker | Campbell B Sindel | Molly W Burger | Yilianys Pride | Mohammad Hasan | George E Abraham | Michal Senitko | Tanya O Robinson | Alex K Shalek | Sarah C Glover | Bruce H Horwitz | Jose Ordovas-Montanes
bioRxiv : the preprint server for biology | 2021

Infection with SARS-CoV-2, the virus that causes COVID-19, can lead to severe lower respiratory illness including pneumonia and acute respiratory distress syndrome, which can result in profound morbidity and mortality. However, many infected individuals are either asymptomatic or have isolated upper respiratory symptoms, which suggests that the upper airways represent the initial site of viral infection, and that some individuals are able to largely constrain viral pathology to the nasal and oropharyngeal tissues. Which cell types in the human nasopharynx are the primary targets of SARS-CoV-2 infection, and how infection influences the cellular organization of the respiratory epithelium remains incompletely understood. Here, we present nasopharyngeal samples from a cohort of 35 individuals with COVID-19, representing a wide spectrum of disease states from ambulatory to critically ill, as well as 23 healthy and intubated patients without COVID-19. Using standard nasopharyngeal swabs, we collected viable cells and performed single-cell RNA-sequencing (scRNA-seq), simultaneously profiling both host and viral RNA. We find that following infection with SARS-CoV-2, the upper respiratory epithelium undergoes massive reorganization: secretory cells diversify and expand, and mature epithelial cells are preferentially lost. Further, we observe evidence for deuterosomal cell and immature ciliated cell expansion, potentially representing active repopulation of lost ciliated cells through coupled secretory cell differentiation. Epithelial cells from participants with mild/moderate COVID-19 show extensive induction of genes associated with anti-viral and type I interferon responses. In contrast, cells from participants with severe lower respiratory symptoms appear globally muted in their anti-viral capacity, despite substantially higher local inflammatory myeloid populations and equivalent nasal viral loads. This suggests an essential role for intrinsic, local epithelial immunity in curbing and constraining viral-induced pathology. Using a custom computational pipeline, we characterized cell-associated SARS-CoV-2 RNA and identified rare cells with RNA intermediates strongly suggestive of active replication. Both within and across individuals, we find remarkable diversity and heterogeneity among SARS-CoV-2 RNA+ host cells, including developing/immature and interferon-responsive ciliated cells, KRT13+ "hillock"-like cells, and unique subsets of secretory, goblet, and squamous cells. Finally, SARS-CoV-2 RNA+ cells, as compared to uninfected bystanders, are enriched for genes involved in susceptibility (e.g., CTSL , TMPRSS2 ) or response (e.g., MX1 , IFITM3 , EIF2AK2 ) to infection. Together, this work defines both protective and detrimental host responses to SARS-CoV-2, determines the direct viral targets of infection, and suggests that failed anti-viral epithelial immunity in the nasal mucosa may underlie the progression to severe COVID-19.

Pubmed ID: 33619488

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


BD FACSDiva Software (tool)

RRID:SCR_001456

A collection of tools for flow cytometer and application setup, data acquisition, and data analysis that help streamline flow cytometry workflows. It provides features to help users integrate flow systems into new application areas, including index sorting for stem cell and single-cell applications, as well as automation protocols for high-throughput and robotic laboratories.

View all literature mentions

circlize (tool)

RRID:SCR_002141

Software package that implements and enhances circular visualization in R. Due to natural born feature of R to draw statistical graphics, this package can provide more general and flexible way to visualize huge information in circular style.

View all literature mentions

Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

View all literature mentions

PRISM (tool)

RRID:SCR_005375

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

View all literature mentions

Systems Transcriptional Activity Reconstruction (tool)

RRID:SCR_005622

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

View all literature mentions

Thermo Fisher Scientific (tool)

RRID:SCR_008452

Commercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.

View all literature mentions

FlowJo (tool)

RRID:SCR_008520

Software for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.

View all literature mentions

BD Biosciences (tool)

RRID:SCR_013311

An Antibody supplier

View all literature mentions

ggplot2 (tool)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

View all literature mentions

bcl2fastq (tool)

RRID:SCR_015058

Conversion software that both demultiplexes data and converts BCL files generated by Illumina sequencing systems to standard FASTQ file formats for downstream analysis.

View all literature mentions

DESeq2 (tool)

RRID:SCR_015687

Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.

View all literature mentions

Drop-seq tools (tool)

RRID:SCR_018142

Software Java tools for analyzing Drop-seq data. Used to analyze gene expression from thousands of individual cells simultaneously. Analyzes mRNA transcripts while remembering origin cell transcript.

View all literature mentions

scVelo (tool)

RRID:SCR_018168

Software package for estimating and analyzing RNA velocities in single cells using dynamical modeling. RNA Velocity using dynamical modeling.

View all literature mentions

CellBender (tool)

RRID:SCR_025990

Software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing data. Deep generative model for noise removal in droplet-based single-cell RNA sequencing.

View all literature mentions

kraken2 (tool)

RRID:SCR_026838

Software tool as second version of Kraken taxonomic sequence classification system.

View all literature mentions