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Biologie

在计算机中 宿主-病原体相互作用过程中circRNA的鉴定和表征

Published: October 21, 2022
doi:
10.3791/64565
, , ,
1Institute of Biological Sciences, Faculty of Science,Universiti Malaya, 2Centre for Research in Biotechnology for Agriculture (CEBAR),Universiti Malaya

Summary

此处提交的协议解释了从研究宿主-病原体相互作用的RNA测序转录组数据中预测和功能表征circRNA所需的完整 计算机 管道。

Abstract

环状RNA（circRNA）是一类通过反向剪接 形成的 非编码RNA。这些circRNA主要因其作为各种生物过程的调节剂的作用而被研究。值得注意的是，新出现的证据表明，宿主circRNA在感染病原体（例如流感和冠状病毒）时可以差异表达（DE），这表明circRNA在调节宿主先天免疫反应方面发挥作用。然而，关于 circRNA 在致病性感染中的作用的研究受到进行必要的生物信息学分析以从 RNA 测序 （RNA-seq） 数据中识别 DE circRNA 所需的知识和技能的限制。在任何验证之前，circRNA的生物信息学预测和鉴定至关重要，并且使用昂贵且耗时的湿实验室技术进行功能研究。为了解决这个问题，本文提供了使用RNA-seq数据对circRNA进行 计算机 预测和表征的分步方案。该协议可分为四个步骤：1）通过CIRIquant管道 预测 和定量DE circRNA;2）通过circBase 进行 注释和DE circRNA的表征;3）通过Circr流水线预测CircRNA-miRNA相互作用;4）使用基因本体（GO）和京都基因和基因组百科全书（KEGG）对circRNA亲本基因进行功能富集分析。该管道将有助于推动未来的 体外 和 体内 研究，以进一步揭示circRNA在宿主 – 病原体相互作用中的作用。

Introduction

宿主-病原体相互作用代表了病原体和宿主生物之间的复杂相互作用，它触发了宿主的先天免疫反应，最终导致入侵病原体的去除1，2。在致病性感染期间，许多宿主免疫基因受到调节以抑制病原体的复制和释放。例如，对致病性感染进行调节的常见干扰素刺激基因（ISG）包括ADAR1，IFIT1，IFIT2，IFIT3，ISG20，RIG-I和OASL3，4。除了蛋白质编码基因外，研究还报告说，非编码RNA，如长非编码RNA（lncRNA），microRNA（miRNA）和环状RNA（circRNA）也在致病性感染期间发挥作用并同时受到调节5，6，7。与主要将蛋白质编码为功能分子的蛋白质编码基因相反，已知非编码RNA（ncRNA）在转录和转录后水平上充当基因的调节因子。然而，与蛋白质编码基因相比，涉及非编码RNA（特别是circRNA）参与调节宿主免疫基因的研究并没有很好的报道。

CircRNA的广泛特征是其共价闭合的连续环结构，该结构是通过称为反向剪接8的非规范剪接过程产生的。与同源线性RNA的剪接过程不同，反向剪接过程涉及下游供体位点与上游受体位点的连接，形成圆形结构。目前，已经提出了三种不同的circRNA生物发生的反向剪接机制。这些是RNA结合蛋白（RBP）介导的环化9，10，内含子配对驱动的环化11和lariat驱动的环化12，13，14。鉴于circRNA以环状结构端到端连接，它们往往对正常的核酸外切酶消化具有天然抵抗力，因此被认为比线性对应物更稳定15。circRNA表现出的另一个共同特征包括宿主16中的细胞或组织类型特异性表达。

正如其独特的结构和细胞或组织特异性表达所暗示的那样，circRNA已被发现在细胞中发挥重要的生物学功能。迄今为止，circRNA的突出功能之一是它们作为microRNA（miRNA）海绵的作用17，18。circRNA的这种调节作用是通过circRNA核苷酸与miRNA种子区域的互补结合而发生的。这种circRNA-miRNA相互作用抑制了miRNA对靶mRNA的正常调节功能，从而调节基因19，20的表达。此外，circRNA还已知通过与RNA结合蛋白（RBP）相互作用并形成RNA-蛋白质复合物来调节基因表达21。虽然circRNA被归类为非编码RNA，但也有证据表明circRNA可以作为蛋白质翻译的模板22，23，24。

最近，circRNA已被证明在调节宿主 – 病原体相互作用中起着关键作用，特别是在宿主和病毒之间。通常，宿主circRNA被认为有助于调节宿主的免疫反应以消除入侵的病原体。促进宿主免疫反应的circRNA的一个例子是circRNA_0082633，由Guo等人报道25。这种circRNA增强了A549细胞内的I型干扰素（IFN）信号传导，有助于抑制流感病毒复制25。此外，Qu等人还报道了一种名为circRNA AIVR的人内含子circRNA，它通过调节CREB结合蛋白（CREBBP）的表达来促进免疫，CREBBP是IFN-β26，27的信号换能器。然而，已知在感染时促进疾病发病机制的circRNA也存在。例如，Yu等人最近报道了从含有2A基因的GATA锌指结构域剪接而成的circRNA通过抑制宿主细胞自噬28在促进H1N1病毒复制中所起的作用。

为了有效地研究circRNA，通常实施全基因组circRNA预测算法，然后在进行任何功能研究之前对预测的circRNA候选物进行 计算机 表征。这种预测和表征circRNA的生物信息学方法成本更低，时间效率更高。它有助于完善要进行功能研究的候选者的数量，并可能导致新的发现。在这里，我们提供了一个详细的基于生物信息学的协议，用于宿主 – 病原体相互作用过程中circRNA 的计算机鉴定， 表征和功能注释。该协议包括从RNA测序数据集中鉴定和定量circRNA，通过circBase 进行 注释，以及根据circRNA类型，重叠基因的数量和预测的circRNA-miRNA相互作用来表征circRNA候选者。本研究还通过基因本体（GO）和京都基因和基因组百科全书（KEGG）富集分析提供了circRNA亲本基因的功能注释。

Protocol

在该协议中，从基因表达综合（GEO）数据库中下载并使用由甲型流感病毒感染的人巨噬细胞制备的去识别核糖体RNA（rRNA）耗尽RNA-seq库数据集。 图1总结了从circRNA的预测到功能表征的整个生物信息学管道。以下各节将进一步解释管道的每个部分。 1. 数据分析前的准备、下载和设置 注意：本研究中使用的所有软件包都是免?…

Representative Results

上一节中列出的协议已经过修改和配置，以适应 Linux 操作系统系统。主要原因是大多数涉及 circRNA 分析的模块库和包只能在 Linux 平台上工作。在该分析中，从GEO数据库42下载了从GEO数据库42 中制备的由甲型流感病毒感染的人巨噬细胞制备的去识别核糖体RNA（rRNA）耗尽RNA-seq文库数据集，并用于生成具有代表性的结果。 环形RNA预测和定量本分?…

Discussion

为了说明该协议的实用性，以来自甲型流感病毒感染的人巨噬细胞的RNA-seq为例。研究了在宿主-病原体相互作用中充当潜在miRNA海绵的circRNA及其在宿主内的GO和KEGG功能富集。尽管网上有各种各样的circRNA工具，但它们中的每一个都是一个独立的软件包，不会相互交互。在这里，我们汇总了circRNA预测和定量，circRNA功能富集，circRNA-miRNA相互作用预测和ceRNA网络构建所需的一些工具。这种简化的方案节?…

Divulgations

The authors have nothing to disclose.

Acknowledgements

作者要感谢Tan KeEn和Cameron Bracken博士对这份手稿的批判性评论。这项工作得到了基础研究资助计划（FRGS/1/2020/SKK0/UM/02/15）和马来亚大学高影响力研究资助计划（UM.C/625/1/HIR/MOE/CHAN/02/07）。

Materials

Bedtools GitHub https://github.com/arq5x/bedtools2/ Referring to section 4.1.2. Needed for Circr.
BWA Burrows-Wheeler Aligner http://bio-bwa.sourceforge.net/ Referring to section 2.1.1 and 2.1.2. Needed to run CIRIquant, and to index the genome
Circr GitHub https://github.com/bicciatolab/Circr Referring to section 4. Use to predict the miRNA binding sites
CIRIquant GitHub https://github.com/bioinfo-biols/CIRIquant Referring to section 2.1.3. To predict circRNAs
Clusterprofiler GitHub https://github.com/YuLab-SMU/clusterProfiler Referring to section 7. For GO and KEGG functional enrichment
CPU Intel  Intel(R) Xeon(R) CPU E5-2620 V2 @ 2.10 GHz   Cores: 6-core CPU Memory: 65 GB Graphics card: NVIDIA GK107GL (QUADRO K2000)  Specifications used to run this entire protocol.
Cytoscape Cytoscape https://cytoscape.org/download.html Referring to section 5.2. Needed to plot ceRNA network
FastQC Babraham Bioinformatics https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ Referring to section 1.2.1. Quality checking on Fastq files
HISAT2 http://daehwankimlab.github.io/hisat2/ Referring to section 2.1.1 and 2.1.2. Needed to run CIRIquant, and to index the genome
Linux Ubuntu 20.04.5 LTS (Focal Fossa) https://releases.ubuntu.com/focal/ Needed to run the entire protocol. Other Ubuntu versions may still be valid to carry out the protocol.
miRanda http://www.microrna.org/microrna/getDownloads.do Referring to section 4.1.2. Needed for Circr
Pybedtools pybedtools 0.8.2 https://pypi.org/project/pybedtools/ Needed for BED file genomic manipulation
Python Python 2.7 and 3.6 or abover https://www.python.org/downloads/ To run necessary library modules
R The Comprehensive R Archive Network https://cran.r-project.org/ To manipulate dataframes
RNAhybrid BiBiServ https://bibiserv.cebitec.uni-bielefeld.de/rnahybrid Referring to section 4.1.2. Needed for Circr
RStudio RStudio https://www.rstudio.com/ A workspace to run R
samtools  SAMtools http://www.htslib.org/ Referring to section 2.1.2. Needed to run CIRIquant
StringTie Johns Hopkins University: Center for Computational Biology http://ccb.jhu.edu/software/stringtie/index.shtml Referring to section 2.1.2. Needed to run CIRIquant
TargetScan GitHub https://github.com/nsoranzo/targetscan Referring to section 4.1.2. Needed for Circr
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Tags

Keywords: CircRNAHost-pathogen InteractionsIn Silico IdentificationCharacterizationBioinformaticsRNA-seq AnalysisDifferential Expression AnalysisCiriquantPrepDE.pyCiri DE ReplicateLinuxProgrammingProtocolWorkflow
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Ealam Selvan, M., Lim, K. S., Teo, C. H., Lim, Y. In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions. J. Vis. Exp. (188), e64565, doi:10.3791/64565 (2022).
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