Scholarlink

<p>Viruses are key drivers of microbial ecology and&#xa0;evolution, yet their study is hindered due to challenges in culturing. Traditional gene-centric methods, which focus on a few hallmark genes like for capsids, miss much of the viral genome, leaving key viral proteins and functions undiscovered. Here, we introduce two powerful annotation-free metrics, V-score and V<sub>L</sub>-score, designed to quantify the “virus-likeness” of protein families and genomes and create an open-access searchable database, ‘V-Score-Search’. By applying V- and V<sub>L</sub>-scores to public protein databases, we link 19 − 59% of protein families with viruses representing a 5 − 8x increase over current estimates. These metrics outperform existing approaches, enabling high efficiency in detection of viral genomes, prophages, and host-derived auxiliary viral genes (AVGs) from fragmented sequences. Remarkably, we identify up to 17 times more AVGs dominated by non-metabolic proteins of unknown function. This innovation unlocks new insights into virus signatures and host interactions, with wide-ranging implications from genomics to biotechnology.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

V- and VL-scores unveil viral signatures and origins of protein families

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月28日

查看全文
  • Kun Zhou,
  • James C. Kosmopoulos,
  • Etan Dieppa Colón,
  • Peter John Badciong,
  • Karthik Anantharaman

摘要

Viruses are key drivers of microbial ecology and evolution, yet their study is hindered due to challenges in culturing. Traditional gene-centric methods, which focus on a few hallmark genes like for capsids, miss much of the viral genome, leaving key viral proteins and functions undiscovered. Here, we introduce two powerful annotation-free metrics, V-score and VL-score, designed to quantify the “virus-likeness” of protein families and genomes and create an open-access searchable database, ‘V-Score-Search’. By applying V- and VL-scores to public protein databases, we link 19 − 59% of protein families with viruses representing a 5 − 8x increase over current estimates. These metrics outperform existing approaches, enabling high efficiency in detection of viral genomes, prophages, and host-derived auxiliary viral genes (AVGs) from fragmented sequences. Remarkably, we identify up to 17 times more AVGs dominated by non-metabolic proteins of unknown function. This innovation unlocks new insights into virus signatures and host interactions, with wide-ranging implications from genomics to biotechnology.