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一种高度多重化和敏感的 RNA-seq 方案,用于同时分析宿主和病原体转录组。

A highly multiplexed and sensitive RNA-seq protocol for simultaneous analysis of host and pathogen transcriptomes.

机构信息

Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

出版信息

Nat Protoc. 2016 Aug;11(8):1477-91. doi: 10.1038/nprot.2016.090. Epub 2016 Jul 21.

Abstract

The ability to simultaneously characterize the bacterial and host expression programs during infection would facilitate a comprehensive understanding of pathogen-host interactions. Although RNA sequencing (RNA-seq) has greatly advanced our ability to study the transcriptomes of prokaryotes and eukaryotes separately, limitations in existing protocols for the generation and analysis of RNA-seq data have hindered simultaneous profiling of host and bacterial pathogen transcripts from the same sample. Here we provide a detailed protocol for simultaneous analysis of host and bacterial transcripts by RNA-seq. Importantly, this protocol details the steps required for efficient host and bacteria lysis, barcoding of samples, technical advances in sample preparation for low-yield sample inputs and a computational pipeline for analysis of both mammalian and microbial reads from mixed host-pathogen RNA-seq data. Sample preparation takes 3 d from cultured cells to pooled libraries. Data analysis takes an additional day. Compared with previous methods, the protocol detailed here provides a sensitive, facile and generalizable approach that is suitable for large-scale studies and will enable the field to obtain in-depth analysis of host-pathogen interactions in infection models.

摘要

同时描述感染过程中细菌和宿主的表达程序的能力将有助于全面了解病原体-宿主的相互作用。尽管 RNA 测序 (RNA-seq) 极大地提高了我们分别研究原核生物和真核生物转录组的能力,但现有 RNA-seq 数据生成和分析协议的局限性阻碍了从同一样本中同时分析宿主和细菌病原体的转录本。在这里,我们提供了一个通过 RNA-seq 同时分析宿主和细菌转录本的详细方案。重要的是,该方案详细介绍了从同一样本中同时分析宿主和细菌转录本所需的步骤,包括宿主和细菌的有效裂解、样本的条形码标记、针对低产量样本输入的样品制备技术的改进,以及用于分析混合宿主-病原体 RNA-seq 数据中哺乳动物和微生物读段的计算流程。从培养细胞到混合文库的样品制备需要 3 天。数据分析需要额外的一天。与以前的方法相比,这里详细介绍的方案提供了一种灵敏、简便和可推广的方法,适用于大规模研究,并将使该领域能够对感染模型中的宿主-病原体相互作用进行深入分析。

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