调节SARS-CoV-2感染的宿主编码microrna的全基因组分析

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Christina L Rootes, Karla J Cowley, Aaron M Brice, Henry G Beetham, Rasan Mohamed Sathiqu, Kaylene J Simpson, Cameron R Stewart
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引用次数: 0

摘要

病毒利用细胞机制完成它们的复制周期。进一步了解这一过程有助于深入了解病毒复制的机制和抗病毒治疗的潜在靶点。全基因组CRISPR筛选已经确定了在SARS-COV-2感染过程中重要的细胞通路,包括囊泡交通、脂质稳态和PI3K信号传导。对影响SARS-CoV-2感染的宿主编码microRNAs (miRNAs)进行功能基因组学驱动分析,将为进一步了解宿主-病原体界面提供公正和发现驱动的见解。在这里,我们展示了在生物安全水平(BSL)-4实验室中使用高通量机器人技术、高含量成像和新型数据分析管道进行的全基因组互补miRNA模拟和抑制剂筛选的结果。该数据集已经确定了SARS-CoV-2复制的miRNA启动子和抑制剂,可用于研究人员进一步探索针对SARS-CoV-2的治疗靶点和影响COVID发病机制的宿主因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genome-wide analysis of host-encoded microRNAs modulating SARS-CoV-2 infection.

Viruses exploit cellular machinery to complete their replication cycle. Furthering our understanding of this process provides insight into the mechanism of virus replication and potential targets for antiviral therapeutics. Genome-wide CRISPR screens have identified cellular pathways important in the SARS-COV-2 infection process, including vesicular traffic, lipid homeostasis and PI3K signalling. Functional genomics-driven analysis of host-encoded microRNAs (miRNAs) impacting SARS-CoV-2 infection would provide further unbiased and discovery-driven insight into the host-pathogen interface. Here we present findings from genome-wide complementary miRNA mimic and inhibitor screens performed in a bio-safety level (BSL)-4 laboratory using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines. This dataset has identified both miRNA promoters and inhibitors of SARS-CoV-2 replication which may be used by researchers to further explore therapeutic targets against SARS-CoV-2 and the host factors influencing COVID pathogenesis.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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