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Inflammasome activation in infected macrophages drives COVID-19 pathology

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TLDR
In this paper , the authors showed that SARS-CoV-2 infection and replication in lung resident human macrophages is a critical driver of lung pathology, as inhibition of the NLRP3 inflammasome pathway reversed chronic lung pathology.
Abstract
Severe COVID-19 is characterized by persistent lung inflammation, inflammatory cytokine production, viral RNA and a sustained interferon (IFN) response, all of which are recapitulated and required for pathology in the SARS-CoV-2-infected MISTRG6-hACE2 humanized mouse model of COVID-19, which has a human immune system1-20. Blocking either viral replication with remdesivir21-23 or the downstream IFN-stimulated cascade with anti-IFNAR2 antibodies in vivo in the chronic stages of disease attenuates the overactive immune inflammatory response, especially inflammatory macrophages. Here we show that SARS-CoV-2 infection and replication in lung-resident human macrophages is a critical driver of disease. In response to infection mediated by CD16 and ACE2 receptors, human macrophages activate inflammasomes, release interleukin 1 (IL-1) and IL-18, and undergo pyroptosis, thereby contributing to the hyperinflammatory state of the lungs. Inflammasome activation and the accompanying inflammatory response are necessary for lung inflammation, as inhibition of the NLRP3 inflammasome pathway reverses chronic lung pathology. Notably, this blockade of inflammasome activation leads to the release of infectious virus by the infected macrophages. Thus, inflammasomes oppose host infection by SARS-CoV-2 through the production of inflammatory cytokines and suicide by pyroptosis to prevent a productive viral cycle.

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SARS-CoV-2 infection drives an inflammatory response in human adipose tissue through infection of adipocytes and macrophages

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Two Years into the COVID-19 Pandemic: Lessons Learned

TL;DR: An overview of the state of the art of knowledge gained in the last 2 years about the virus and COVID-19, including its origin and natural reservoir hosts, viral etiology, epidemiology, modes of transmission, clinical manifestations, pathophysiology, diagnosis, treatment, prevention, emerging variants, and vaccines, highlighting important differences from previously known highly pathogenic coronaviruses.
References
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Journal ArticleDOI

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
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STAR: ultrafast universal RNA-seq aligner

TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
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HTSeq—a Python framework to work with high-throughput sequencing data

TL;DR: This work presents HTSeq, a Python library to facilitate the rapid development of custom scripts for high-throughput sequencing data analysis, and presents htseq-count, a tool developed with HTSequ that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.
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Comprehensive Integration of Single-Cell Data.

TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
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