five

Identifying modulators of inflammation in an in vitro airway epithelial inflammation model using an arrayed CRISPRi screen

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP517585
下载链接
链接失效反馈
官方服务:
资源简介:
To study modulators of inflammatory airway disease, we developed an in vitro bronchial epithelial cell model system based on the BEAS-2B cell line exposed to lipopolysaccharide (LPS) and diesel exhaust particles (DEP). Combined LPS and DEP exposure triggered a molecular inflammatory phenotype, including elevated TSLP and IL-8 mRNA expression, similar to that observed in airway epithelial cells from asthma patients. In this model, we performed high-throughput perturbation of 24 mRNA and long non-coding (lncRNA) target genes through an arrayed CRISPR-interference screen, followed by shallow RNA-sequencing to identify modulators of inflammation. Perturbation of individual targets had a significant impact on the BEAS-2B DEP/LPS transcriptome. Some mRNA targets reversed the DEP/LPS gene expression signature upon knockdown and could serve as candidate therapeutic targets. Perturbation of other target genes however further amplified the pro-inflammatory signature and thus may have an anti-inflammatory role in these cells. In conclusion, we present a novel in vitro model system for airway inflammation that exhibited an inflammatory profile relevant for asthmatic patients, and demonstrate the feasibility to perform high-throughput target perturbation and molecular phenotyping by integrating CRISPR-interference and shallow RNA-sequencing. Overall design: High throughput perturbation of 24 mRNA and long non-coding (lncRNA) target genes through an arrayed CRISPR-interference screen, followed by shallow RNA-sequencing to identify modulators of inflammation
创建时间:
2024-09-15
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作