PhaTYP：使用BERT预测噬菌体的生活方式
PhaTYP: Predicting the lifestyle for bacteriophages using BERT
摘要：
感染细菌的噬菌体有两种不同的生活方式：毒性和温和性。预测细菌的生活方式有助于破译它们与细菌宿主的相互作用，有助于细菌在噬菌体治疗等领域的应用。由于实验方法注释的生活方式，无法跟上快速积累的测序的生活方式，计算方法预测的生活方式已成为一个有吸引力的替代。尽管有一些有希望的结果，但由于有限的已知注释和从宏基因组数据组装的测序噬菌体重叠群的绝对量，计算生活方式预测仍然很困难。特别是，大多数现有的工具不能精确地预测短重叠群的生活方式。在这项工作中，我们开发了PhaTYP（Phage TYPe预测工具），以提高短重叠群上生活方式预测的准确性。我们设计了两个不同的训练任务，自我监督和微调任务，以克服生活方式预测的困难。我们对PhaTYP与四种最先进的方法进行了严格的测试和比较：DeePhage，PHYSIDE，PhagePred和BACPHLIP。实验结果表明，PhaTYP优于所有这些方法，并在短重叠群上实现更稳定的性能。此外，我们证明了PhaTYP用于分析人类新生儿肠道数据的噬菌体生活方式的实用性。该应用表明PhaTYP是研究宏基因组数据中微生物的有用手段，有助于扩展我们对微生物群落的理解。
英文摘要：
Bacteriophages (or phages), which infect bacteria, have two distinct lifestyles: virulent and temperate. Predicting the lifestyle of phages helps decipher their interactions with their bacterial hosts, aiding phages' applications in fields such as phage therapy. Because experimental methods for annotating the lifestyle of phages cannot keep pace with the fast accumulation of sequenced phages, computational method for predicting phages' lifestyles has become an attractive alternative. Despite some promising results, computational lifestyle prediction remains difficult because of the limited known annotations and the sheer amount of sequenced phage contigs assembled from metagenomic data. In particular, most of the existing tools cannot precisely predict phages' lifestyles for short contigs. In this work, we develop PhaTYP (Phage TYPe prediction tool) to improve the accuracy of lifestyle prediction on short contigs. We design two different training tasks, self-supervised and fine-tuning tasks, to overcome lifestyle prediction difficulties. We rigorously tested and compared PhaTYP with four state-of-the-art methods: DeePhage, PHACTS, PhagePred, and BACPHLIP. The experimental results show that PhaTYP outperforms all these methods and achieves more stable performance on short contigs. In addition, we demonstrated the utility of PhaTYP for analyzing the phage lifestyle on human neonates' gut data. This application shows that PhaTYP is a useful means for studying phages in metagenomic data and helps extend our understanding of microbial communities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
