Dataset Information

An anti-influenza combined therapy assessed by single cell RNA-sequencing.

ABSTRACT: Influenza makes millions of people ill every year, placing a large burden on the healthcare system and the economy. To develop a treatment against influenza, we combined virucidal sialylated cyclodextrins with interferon lambda and demonstrated, in human airway epithelia, that the two compounds inhibit the replication of a clinical H1N1 strain more efficiently when administered together rather than alone. We investigated the mechanism of action of the combined treatment by single cell RNA-sequencing analysis and found that both the single and combined treatments impair viral replication to different extents across distinct epithelial cell types. We showed that each cell type comprises multiple sub-types, whose proportions are altered by H1N1 infection, and assessed the ability of the treatments to restore them. To the best of our knowledge this is the first study investigating the effectiveness of an antiviral therapy against influenza virus by single cell transcriptomic studies.

SUBMITTER: Medaglia C

PROVIDER: S-EPMC9549038 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An anti-influenza combined therapy assessed by single cell RNA-sequencing.

Medaglia Chiara C Kolpakov Ilya I Zwygart Arnaud Charles-Antoine AC Zhu Yong Y Constant Samuel S Huang Song S Cagno Valeria V Dermitzakis Emmanouil T ET Stellacci Francesco F Xenarios Ioannis I Tapparel Caroline C

Communications biology 20221010 1

Influenza makes millions of people ill every year, placing a large burden on the healthcare system and the economy. To develop a treatment against influenza, we combined virucidal sialylated cyclodextrins with interferon lambda and demonstrated, in human airway epithelia, that the two compounds inhibit the replication of a clinical H1N1 strain more efficiently when administered together rather than alone. We investigated the mechanism of action of the combined treatment by single cell RNA-sequen ...[more]

PMID: 36216966

Similar Datasets

Project description:BackgroundUlcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response. Single-cell RNA sequencing (scRNA-seq) can be used to rapidly obtain the precise gene expression patterns of thousands of cells in the intestine, analyze the characteristics of cells with the same phenotype, and provide new insights into the growth and development of intestinal organs, the clonal evolution of cells, and immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases.AimTo identify clinical phenotypes and biomarkers that can predict the response of UC patients to specific therapeutic drugs and thus aid the diagnosis and treatment of UC.MethodsUsing the Gene Expression Omnibus (GEO) database, we analyzed peripheral blood cell subtypes of patients with UC by scRNA-seq combined with bulk RNA sequencing (RNA-seq) to reveal the core genes of UC. We then combined weighted gene correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis to reveal diagnostic markers of UC.ResultsAfter processing the scRNA-seq data, we obtained data from approximately 24340 cells and identified 17 cell types. Through intercellular communication analysis, we selected monocyte marker genes as the candidate gene set for the prediction model. Construction of a WGCNA coexpression network identified RhoB, cathepsin D (CTSD) and zyxin (ZYX) as core genes. Immune infiltration analysis showed that these three core genes were strongly correlated with immune cells. Functional enrichment analysis showed that the differentially expressed genes were closely related to immune and inflammatory responses, which are associated with many challenges in the diagnosis and treatment of UC.ConclusionThrough scRNA-seq analysis, LASSO diagnostic model building and WGCNA, we identified RhoB, CTSD and ZYX as core genes of UC that are closely related to monocyte infiltration that may serve as diagnostic markers and molecular targets for UC therapeutic intervention.

Dataset Information

An anti-influenza combined therapy assessed by single cell RNA-sequencing.

Publications

An anti-influenza combined therapy assessed by single cell RNA-sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets