数据驱动的病毒发现的机遇与挑战。

Opportunities and Challenges of Data-Driven Virus Discovery.

机构信息

Institute for Experimental Virology, TWINCORE Centre for Experimental and Clinical Infection Research, a Joint Venture between the Hannover Medical School (MHH) and the Helmholtz Centre for Infection Research (HZI), 30625 Hannover, Germany.

Division of Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.

出版信息

Biomolecules. 2022 Aug 4;12(8):1073. doi: 10.3390/biom12081073.

Abstract

Virus discovery has been fueled by new technologies ever since the first viruses were discovered at the end of the 19th century. Starting with mechanical devices that provided evidence for virus presence in sick hosts, virus discovery gradually transitioned into a sequence-based scientific discipline, which, nowadays, can characterize virus identity and explore viral diversity at an unprecedented resolution and depth. Sequencing technologies are now being used routinely and at ever-increasing scales, producing an avalanche of novel viral sequences found in a multitude of organisms and environments. In this perspective article, we argue that virus discovery has started to undergo another transformation prompted by the emergence of new approaches that are sequence data-centered and primarily computational, setting them apart from previous technology-driven innovations. The data-driven virus discovery approach is largely uncoupled from the collection and processing of biological samples, and exploits the availability of massive amounts of publicly and freely accessible data from sequencing archives. We discuss open challenges to be solved in order to unlock the full potential of data-driven virus discovery, and we highlight the benefits it can bring to classical (mostly molecular) virology and molecular biology in general.

摘要

自 19 世纪末首次发现病毒以来,新技术一直推动着病毒的发现。从最初在患病宿主中提供病毒存在证据的机械装置开始,病毒的发现逐渐发展成为一个基于序列的科学学科,如今可以以前所未有的分辨率和深度描述病毒的特征并探索病毒的多样性。测序技术现在已被常规使用,而且使用的规模也在不断扩大,从而产生了大量在多种生物体和环境中发现的新型病毒序列。在这篇观点文章中,我们认为,病毒的发现已经开始发生另一种转变,这是由新的方法引发的,这些方法以序列为中心,主要是基于计算的,与以前的技术驱动型创新有所区别。数据驱动的病毒发现方法在很大程度上与生物样本的收集和处理脱钩,并且利用了测序档案中大量公开和免费获取的数据。我们讨论了为了充分发挥数据驱动的病毒发现的潜力需要解决的开放性挑战,并强调了它可以为经典(主要是分子)病毒学和分子生物学带来的好处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e31/9406072/e374433f7a04/biomolecules-12-01073-g001.jpg

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