Isolation of high-yield and -quality RNA from human precision-cut lung slices for RNA-sequencing and computational integration with larger patient cohorts

Abstract

Precision-cut lung slices (PCLS) have gained increasing interest as a model to study lung biology/disease and screening novel therapeutics. In particular, PCLS derived from human tissue can better recapitulate some aspects of lung biology/disease as compared with animal models. Several experimental readouts have been established for use with PCLS, but obtaining high-yield and -quality RNA for downstream analysis has remained challenging. This is particularly problematic for utilizing the power of next-generation sequencing techniques, such as RNA-sequencing (RNA-seq), for nonbiased and high-throughput analysis of PCLS human cohorts. In the current study, we present a novel approach for isolating high-quality RNA from a small amount of tissue, including diseased human tissue, such as idiopathic pulmonary fibrosis. We show that the RNA isolated using this method has sufficient quality for RT-qPCR and RNA-seq analysis. Furthermore, the RNA-seq data from human PCLS could be used in several established computational pipelines, including deconvolution of bulk RNA-seq data using publicly available single-cell RNAseq data. Deconvolution using Bisque revealed a diversity of cell populations in human PCLS, including several immune cell populations, which correlated with cell populations known to be present and aberrant in human disease.