LysoPhD: predicting functional prophages in bacterial genomes from high-throughput sequencing
| Autor: | Niu Qi, Ying Xu, Shuai Cheng Li, Shaoliang Peng, Xiang-Li-Lan Zhang, Xie Xiangcheng, Yi-Gang Tong |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
Contig Bacterial genome size Computational biology Gene Annotation 010501 environmental sciences Biology biology.organism_classification 01 natural sciences Genome DNA sequencing Deep sequencing Bacteriophage 03 medical and health sciences Prophage 030304 developmental biology 0105 earth and related environmental sciences |
| Zdroj: | BIBM |
| DOI: | 10.1109/bibm47256.2019.8983280 |
| Popis: | Motivation: When a temperate bacteriophage (phage) integrates into the chromosome of its host or to remain as latent episomal DNA, the prophage plays an important role in bacterial virulence acquisition and increase. With the recent release of thousands of bacterial high throughput sequencing data, there has been a growing interest in analyzing the impact of interdependency between a prophage and its host. One of the essential tasks is to acquire and identify the complete sequence of the prophage, i.e., the functional prophages. However, no existing tools can identify functional prophages from bacterial genomes. A few tools can predict putative prophage in bacterial genomes, but they are unable to distinguish functional prophages from defective prophages. To reduce the cost and to relieve the tedious biological experiments for functional prophage analysis, computational methods for predicting functional prophages based on bacterial high-throughput sequencing data would be an effective alternation. Results: This paper presents a method, LysoPhD, the first tool to predict functional prophage sequences using bacterial HTS data automatically and accurately. The main idea is to obtain whole genome of functional prophages from the bacterial genome based on phage gene annotation and reads-mediated contig connection. LysoPhD obtains whole genome sequences of functional prophages based on improved models. The obtained the sequences are verified by wet lab experiments. Specifically, LysoPhD is applied to a set of staphylococcus HTS data in the case studies. Ten functional prophages are predicted from 72 staphylococcus isolates. The 72 bacterial strains are then induced with Mitomycin C and subsequent deep sequencing verified of the 10 functional prophages. This shows that LysoPhD is a sensitive and accurate program for functional prophage prediction. |
| Databáze: | OpenAIRE |
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