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

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