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 to 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 non-biased and high through-put 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 (IPF). 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 RNA-seq 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.

中文翻译：

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从人类精密切割的肺切片中分离高产量和高质量的RNA，用于RNA测序和与较大患者群体的计算整合

作为研究肺生物学/疾病和筛选新疗法的模型，精确切割肺切片（PCLS）引起了越来越多的兴趣。特别地，与动物模型相比，源自人类组织的PCLS可以更好地概括肺生物学/疾病的某些方面。已经建立了几种用于PCLS的实验读数，但是要获得高产率和高质量的RNA用于下游分析仍然具有挑战性。对于利用下一代测序技术（例如RNA测序（RNA-seq））进行PCLS人类队列的无偏和高通量分析而言，这尤其成问题。在当前的研究中，我们提出了一种从少量组织中分离出高质量RNA的新颖方法，这些组织包括患病的人类组织，例如特发性肺纤维化（IPF）。我们表明，使用此方法分离的RNA具有足够的质量用于RT-qPCR和RNA-seq分析。此外，来自人PCLS的RNA-seq数据可用于多个已建立的计算管道，包括使用公开可用的单细胞RNA-seq数据对大量RNA-seq数据进行反卷积。使用Bisque进行的反卷积揭示了人类PCLS中的细胞群多样性，包括几种免疫细胞群，这些细胞群与已知存在且异常的人类疾病细胞群相关。