Collaborative Research: Deciphering the Genetic Diversity of Viruses through Gene Networks

噬菌体是感染细菌的病毒，可以对细菌种群产生深远的影响。这些病毒是地球上大多数生态系统中最丰富和最多样化的成员，在每一个支持生命的环境中都有发现。新分离的噬菌体样本的大多数DNA序列与当前数据库中包含的任何序列几乎没有相似之处。这意味着通过寻找相似序列来识别新样本并不是一个有效的策略。因此，找到不同的方法来表征这些病毒是至关重要的，这将有助于我们了解它们作为微生物群落成员的关键作用。这项研究将开发一种新的基于网络的病毒分类方法，从而为探索病毒生态学开辟新的途径，并为进化研究提供基因组数据。这种新方法将重新定义如何表示病毒的遗传多样性，使以比目前更高的分辨率直接分析复杂的病毒群落成为可能。此外，该项目将把来自计算科学和生物科学的学生联合起来，创建能够开展这项研究的跨学科团队，这种培训将在课堂和实验室进行。该项目将为病毒宏基因组的研究开发一个新的图形框架，特别旨在将新的病毒序列置于病毒遗传多样性的全球背景下。由于病毒基因组是随着时间的推移从多个来源获得的基因的嵌合体，因此采用“以基因为中心”而不是“以基因组为中心”的方法对病毒组中的序列进行分类。除了捕获病毒基因组的组合结构外，该方法对来自不同数据集的基因组和组态大小的变化具有鲁棒性。通过新算法和指标的发展，数据中的进化和生态信号将被整合，以告知网络的结构。该网络还将用于测试由数据驱动的假设，特别是病毒宿主范围的信号。有关该项目的更多信息，请访问PI的实验室网站http://www.putonti-lab.com。

Bacteriophages are viruses that infect bacteria and can have a profound impact on bacterial populations. These viruses are the most abundant and diverse members of most ecosystems on Earth, having been found in every environment that supports life. The majority of the DNA sequences of newly isolated bacteriophage samples bears little or no resemblance to any sequences contained within current databases. This means that identifying new samples by looking for similar sequences is not an effective strategy. It is therefore crucial to find different approaches to characterize these viruses, which will then help is understand the critical roles that they have as members of microbial communities. This research will develop a new network-based approach for classifying viruses, thereby opening new avenues for exploring virus ecology as well as providing genomic data for evolutionary studies. This new approach will redefine how the genetic diversity of viruses is represented, making possible direct analyses of complex viral communities at higher resolution than is currently possible. Furthermore, the project will unite students from the computational and biological sciences, creating interdisciplinary teams able to carry out this research, with this training taking both in the classroom and laboratory.The project will develop a new graphical framework for the investigation of viral metagenomes, specifically aimed at putting novel viral sequences into a global context of viral genetic diversity. Because virus genomes are mosaics of genes acquired over time from multiple sources, a 'gene-centric' rather than a 'genome-centric' approach to classify the sequences in viromes is taken. In addition to capturing the combinatorial structure of virus genomes, this approach is robust to variation in genome and contig size that can arise from diverse datasets. Through the development of novel algorithms and metrics, evolutionary and ecological signals in the data will be integrated to inform the network's structure. The network will also be used to test hypotheses driven from the data, in particular the signals of viral host-range. For more information about the project visit the PI's lab website at http://www.putonti-lab.com.