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DeepPL: A deep-learning-based tool for the prediction of bacteriophage lifecycle
Yujie Zhang1, Mark Mao2, Robert Zhang2
1Produce Safety and Microbiology Research Unit, U.S. Department of Agriculture, Agricultural Research Service, Western Regional Research Center, Albany, California, United States of America.
Plos Computational Biology
|October 17, 2024
Summary
DeepPL, a new tool using natural language processing, accurately predicts bacteriophage (phage) lifecycles from nucleotide sequences. This method offers a reliable alternative to traditional experiments for phage research and metagenomics.
Area of Science:
- Virology
- Bioinformatics
- Computational Biology
Background:
- Bacteriophages (phages) exhibit distinct lifecycles: lytic (host lysis) and lysogenic (genome integration).
- Accurate phage lifecycle identification is vital for developing phage-based applications.
- Traditional biological experiments for determining phage lifecycles are complex and time-consuming.
Purpose of the Study:
- To develop and evaluate DeepPL, a novel natural language processing (NLP)-based tool for predicting phage lifecycles.
- To assess DeepPL's performance using nucleotide sequences, comparing it to existing prediction algorithms.
- To explore DeepPL's utility in viral metagenomic research.
Main Methods:
- Development of DeepPL, an NLP-based tool utilizing nucleotide sequences for phage lifecycle prediction.
- Performance evaluation using established datasets, including isolated and verified phages.
- Testing DeepPL on a mock phage community metagenomic dataset generated by next-generation sequencing.
Main Results:
- DeepPL achieved high accuracy (94.65%), sensitivity (92.24%), and specificity (95.91%) in general lifecycle prediction.
- DeepPL demonstrated 100% accuracy for previously isolated and biologically verified phages.
- In metagenomic analysis, DeepPL showed 100% accuracy on complete phage genomes and 71.14%-100% on phage contigs.
Conclusions:
- DeepPL provides a reliable and accurate method for predicting bacteriophage lifecycles directly from nucleotide sequences.
- The tool's high performance suggests its applicability in both fundamental phage research and complex metagenomic studies.
- DeepPL offers a significant advancement over traditional experimental methods for phage lifecycle determination.
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