Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA.
Bioessays. 2021 Sep;43(9):e2100084. doi: 10.1002/bies.202100084. Epub 2021 Jul 18.
Plasmids are a major type of mobile genetic elements (MGEs) that mediate horizontal gene transfer. The stable maintenance of plasmids plays a critical role in the functions and survival for microbial populations. However, predicting and controlling plasmid persistence and abundance in complex microbial communities remain challenging. Computationally, this challenge arises from the combinatorial explosion associated with the conventional modeling framework. Recently, a plasmid-centric framework (PCF) has been developed to overcome this computational bottleneck. This framework enables the derivation of a simple metric, the persistence potential, to predict plasmid persistence and abundance. Here, we discuss how PCF can be extended to account for plasmid interactions. We also discuss how such model-guided predictions of plasmid fates can benefit from the development of new experimental tools and data-driven computational methods.
质粒是一种主要的移动遗传元件 (MGE)，介导水平基因转移。质粒的稳定维持对于微生物种群的功能和生存起着至关重要的作用。然而，预测和控制复杂微生物群落中质粒的持久性和丰度仍然具有挑战性。在计算方面，这一挑战源于与传统建模框架相关的组合爆炸。最近，开发了一种以质粒为中心的框架 (PCF) 来克服这一计算瓶颈。该框架能够推导出一个简单的度量标准，即持久性潜力，用于预测质粒的持久性和丰度。在这里，我们讨论如何扩展 PCF 以考虑质粒相互作用。我们还讨论了如何从新的实验工具和数据驱动的计算方法的发展中受益于质粒命运的模型指导预测。
