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单细胞RNA测序:揭示病毒与宿主相互作用的新型工具。

Single cell RNA-seq: a novel tool to unravel virus-host interplay.

作者信息

Jogi Harsh Rajeshbhai, Smaraki Nabaneeta, Nayak Sonali Sonejita, Rajawat Divya, Kamothi Dhaval J, Panigrahi Manjit

机构信息

Division of Veterinary Microbiology, Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India.

Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP 243122 India.

出版信息

Virusdisease. 2024 Mar;35(1):41-54. doi: 10.1007/s13337-024-00859-w. Epub 2024 Mar 9.

DOI:10.1007/s13337-024-00859-w
PMID:38817399
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11133279/
Abstract

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

摘要

在过去十年中,单细胞RNA测序(scRNA-seq)技术已成为一种至关重要的革命性工具,通过高分辨率评估来揭示细胞异质性。它避免了传统测序技术只能检测细胞群体平均表达水平的不足。在21世纪,出现了几种流行和大流行病毒。作为一种细胞内实体,病毒完全依赖宿主。当病毒倾向于从宿主细胞获取其复制和建立感染所需的因子时,就会产生复杂的病毒-宿主动态。作为一种主流工具,scRNA-seq能够通过全面的转录组分析来理解病毒-宿主相互作用。由于技术和方法的进步,该技术能够识别病毒基因组和宿主细胞反应的异质性。多组学方法分析方法的进一步发展以及可获取的scRNA-seq数据集的增加,将提高对病毒发病机制的理解,这有助于开发新的抗病毒治疗策略。