Transcriptome analysis of chemically polarised rat macrophages: in search of target genes for ARDS therapy

Acute respiratory distress syndrome (ARDS) is a severe clinical manifestation of an acute lung injury (ALI), which is characterized by poor oxygenation and non-compliant or "stiff" lungs. Modern guidelines for the treatment of ARDS include only symptomatic therapy: ventilator support, prone positioning, sedation and medications to prevent movement, diuretic medication for excess liquid removing, extracorporeal membrane oxygenation (ECMO). Lack of the pathogenic ARDS treatment contributed to the actualization of the search for new therapeutic approaches. Cell therapy is one of such approaches which are now of great interest in the ARDS therapy. Macrophages are known to play a key role in the pathogenesis of ARDS. Depending on the stage of the disease, macrophages exhibiting pro-inflammatory (M1) and anti-inflammatory (M2) states. It has been suggested that the utilisation of M2 macrophages in the early stages of the disease may contribute to a positive disease outcome. The aim of this study was to induce an anti-inflammatory phenotype of macrophages by knockdown of genes selected on the basis of transcriptome analysis of chemically polarised macrophages. Intact rat macrophages were obtained by differentiating CD43-positive rat blood monocytes for 7 days in the presence of MCSF. Lipopolysaccharide endotoxin (LPS) was added at 7 days of culturing to induce a pro-inflammatory phenotype (M1). A mixture of interleukins IL4 and IL10 was used to activate cells via an alternative anti-inflammatory pathway. Samples were lysed in Extract RNA isolation solution (Evrogen, Russia). Preparation of libraries for sequencing was performed using TruSeq RNA Sample Prep Kit v2 according to the manufacturer's recommendations. Raw data were processed using Nextflow nf-core/rnaseq bioinformatic analysis to compare the control and one of the experimental groups. Candidate genes whose decreased expression level would potentially lead to an anti-inflammatory phenotype of macrophages were selected based on transcriptome analysis data.