TREM-2 is a sensor and activator of T cell response in SARS-CoV-2 infection

Wu, Yongjian; Wang, Manni; Yin, Huan; Ming, Siqi; Li, Xingyu; Jiang, Guanmin; Liu, Ye; Wang, Pei‐Hui; Zhou, Guangde; Liu, Lei; Gong, Sitang; Zhou, Haibo; Shan, Hong; Huang, Xi

doi:10.1126/sciadv.abi6802

Cited by 29 publications

(18 citation statements)

References 74 publications

(118 reference statements)

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“…Hence TREM-2 may be involved in lung localised CD4 + T cells in COVID-19 patients. TREM-2 expression on both CD4 + and CD8 + T cells was correlated to TCR dependent markers including CD134 (OX-40), CD137, CD69 and CD25 (197). This implies that TREM-2 plays critical role in T cell activation and differentiation in SARS-CoV-2 pneumonia.…”

Section: Local Immune Response In Covid-19 Pneumoniamentioning

confidence: 84%

“…In severe COVID-19 disease the soluble mediators IL6, IL1b, CXCL8 and CXCL10 are expressed in a TREM-2 dependent manner by macrophages (196). Other studies have demonstrated that TREM-2 is constitutively expressed on T cells during SARS-CoV-2 infection leading to rise in IL-2, IFN-g, IL-1B and IL-4 thereby being a key mediator in T cell immunity and inflammation (197). TREM-2 expression was higher in peripheral blood and lung infiltrating CD4 + and CD8 + T cells of severe and non-severe COVID 19 patients than healthy donors.…”

Section: Local Immune Response In Covid-19 Pneumoniamentioning

confidence: 99%

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Frontline workers: Mediators of mucosal immunity in community acquired pneumonia and COVID-19

et al. 2022

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The current COVID-19 pandemic has highlighted a need to further understand lung mucosal immunity to reduce the burden of community acquired pneumonia, including that caused by the SARS-CoV-2 virus. Local mucosal immunity provides the first line of defence against respiratory pathogens, however very little is known about the mechanisms involved, with a majority of literature on respiratory infections based on the examination of peripheral blood. The mortality for severe community acquired pneumonia has been rising annually, even prior to the current pandemic, highlighting a significant need to increase knowledge, understanding and research in this field. In this review we profile key mediators of lung mucosal immunity, the dysfunction that occurs in the diseased lung microenvironment including the imbalance of inflammatory mediators and dysbiosis of the local microbiome. A greater understanding of lung tissue-based immunity may lead to improved diagnostic and prognostic procedures and novel treatment strategies aimed at reducing the disease burden of community acquired pneumonia, avoiding the systemic manifestations of infection and excess morbidity and mortality.

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Section: Local Immune Response In Covid-19 Pneumoniamentioning

confidence: 84%

Section: Local Immune Response In Covid-19 Pneumoniamentioning

confidence: 99%

Frontline workers: Mediators of mucosal immunity in community acquired pneumonia and COVID-19

et al. 2022

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“…A modified distribution of the ZAP70 kinase on the plasma membrane of T-cells contributes to the signal transduction and amplification of the TCR [84] . Interestingly, CD3/ZAP70 protein has been shown to interact with TREM-2 in the T-cells of patients infected with SARS-CoV-2 [85] .…”

Section: Discussionmentioning

confidence: 99%

Transcriptomics secondary analysis of severe human infection with SARS-CoV-2 identifies gene expression changes and predicts three transcriptional biomarkers in leukocytes

Clancy

Hoffmann

Pickett

2023

Computational and Structural Biotechnology Journal

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“…A modified distribution of the ZAP70 kinase on the plasma membrane of T-cells contributes to the signal transduction and amplification of the TCR [48]. Interestingly, CD3/ZAP70 protein has been shown to interact with TREM-2 in the T-cells of patients infected with SARS-CoV-2 [49]. The ASPH and C5orf30 genes, which were identified as significant DEGs in our study, have been identified previously as markers of severe infection [50].…”

Section: Discussionmentioning

confidence: 99%

Transcriptomics Meta-Analysis Predicts Two Robust Human Biomarkers for Severe Infection with SARS-CoV-2

Clancy

Hoffmann

Pickett

2022

Preprint

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Defining the human factors associated with severe vs mild SARS-CoV-2 infection has become of increasing interest. Mining large numbers of public gene expression datasets is an effective way to identify genes that contribute to a given phenotype. Combining RNA-sequencing data with the associated clinical metadata describing disease severity can enable earlier identification of patients who are at higher risk of developing severe COVID-19 disease. We consequently identified 356 public RNA-seq human transcriptome samples from the Gene Expression Omnibus database that had disease severity metadata. We then subjected these samples to a robust RNA-seq data processing workflow to quantify gene expression in each patient. This process involved using Salmon to map the reads to the reference transcriptomes, edgeR to calculate significant differential expression levels, and gene ontology enrichment using Camera. We then applied a machine learning algorithm to the read counts data to identify features that best differentiated samples based on COVID-19 severity phenotype. Ultimately, we produced a ranked list of genes based on their Gini importance values that includes GIMAP7 and S1PR2, which are associated with immunity and inflammation (respectively). Our results show that these two genes can potentially predict people with severe COVID-19 at up to ~90% accuracy. We expect that our findings can help contribute to the development of improved prognostics for severe COVID-19.

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TREM-2 is a sensor and activator of T cell response in SARS-CoV-2 infection

Abstract: TREM-2 recognizes SARS-CoV-2 membrane protein and activates CD3ζ/ZAP70/STAT1 signal pathway to induce antiviral T H 1 response.

Cited by 29 publications

References 74 publications

Frontline workers: Mediators of mucosal immunity in community acquired pneumonia and COVID-19

Frontline workers: Mediators of mucosal immunity in community acquired pneumonia and COVID-19

Transcriptomics secondary analysis of severe human infection with SARS-CoV-2 identifies gene expression changes and predicts three transcriptional biomarkers in leukocytes

Transcriptomics Meta-Analysis Predicts Two Robust Human Biomarkers for Severe Infection with SARS-CoV-2

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