| Literature DB >> 34278591 |
Teng Wang1, Andrea Weiss1, Yuanchi Ha1, Lingchong You1,2,3.
Abstract
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.Entities:
Keywords: coarse-grained model; horizontal gene transfer; machine learning; microbial communities; mobile genetic elements; next generation sequencing; plasmid persistence
Mesh:
Year: 2021 PMID: 34278591 PMCID: PMC8822872 DOI: 10.1002/bies.202100084
Source DB: PubMed Journal: Bioessays ISSN: 0265-9247 Impact factor: 4.653