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Updated: Sep 13, 2025

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Published on: June 11, 2015
Pangenome-scale annotation of mycobacteriophages for dissecting phage-host interactions based on a sequence
Xiao Guo1, Zheng-Guo He1,2
1College of Life Science and Technology, Guangxi University, Nanning, China.
Abstract:
With the increasing severity of bacterial drug resistance, there is a growing need for phages with well-defined genetic backgrounds to combat drug-resistant infections. Mycobacteriophages constitute the largest genome-sequenced phage group; however, the vast majority of these phage proteins have not yet been effectively annotated. In this study, we employed a structure-based similarity search approach to improve protein annotation. Through the application of this approach to 240,754 proteins from 2,169 mycobacteriophage genomes, we increased the protein annotation rate from 34% to 52.11%. Additionally, we identified a series of predicted counter-defense proteins, including anti-CRISPR proteins and antitoxins, and inferred the potential interaction network of phage-encoded proteins involved in replication, transcription, and translation with host-associated molecular machinery. This study addresses a substantial gap in the current knowledge of the potential function of phage proteins and provides key insights into the interactions between mycobacteriophages and their hosts.IMPORTANCEMycobacteriophages constitute the largest group of phages with sequenced genomes. However, a significant portion of these phage proteins have not yet been effectively annotated, seriously hindering our understanding of the basic biological processes of phage-host interactions and their practical applications. This study utilized a structure-based similarity search approach to enhance phage protein annotation. This approach led to the identification of novel predicted protein folds, structural domain fusion phenomena, and putative new enzymes. Additionally, the study identified a series of phage-encoded proteins that may play a role in hijacking host-associated replication, transcription, and translation processes, providing insights into the molecular mechanisms underlying mycobacteriophage interactions with host machinery. This study addresses a critical knowledge gap regarding the potential function of phage proteins and provides key insights into the interactions between mycobacteriophages and their hosts.
Insights
This study enhanced mycobacteriophage protein annotation using structure-based searches, increasing the rate from 34% to 52.11%. It identified novel protein functions and interactions crucial for combating drug-resistant bacteria.
Area of Science:
- * Genomics and Bioinformatics
- * Microbiology and Virology
Background:
- * Mycobacteriophages represent the largest group of phages with sequenced genomes.
- * A significant portion of mycobacteriophage proteins remain unannotated, limiting understanding of phage-host interactions.
- * Bacterial drug resistance necessitates phages with well-defined genetic backgrounds for therapeutic applications.
Purpose of the Study:
- * To improve the annotation rate of mycobacteriophage proteins using a structure-based similarity search approach.
- * To identify novel protein functions, structural features, and potential counter-defense mechanisms in mycobacteriophages.
- * To elucidate the molecular interactions between mycobacteriophages and their host machinery.
Main Methods:
- * Applied a structure-based similarity search to 240,754 proteins from 2,169 mycobacteriophage genomes.
- * Analyzed identified proteins for novel folds, domain fusions, and enzymatic activity.
- * Inferred interaction networks of phage-encoded proteins with host replication, transcription, and translation machinery.
Main Results:
- * Increased the mycobacteriophage protein annotation rate from 34% to 52.11%.
- * Identified novel predicted protein folds, structural domain fusions, and putative new enzymes.
- * Discovered predicted counter-defense proteins (e.g., anti-CRISPR, antitoxins) and potential host machinery interaction networks.
Conclusions:
- * The structure-based approach significantly enhances mycobacteriophage protein annotation, addressing a critical knowledge gap.
- * This improved annotation provides key insights into mycobacteriophage biology and phage-host interactions.
- * Findings contribute to the development of phages as therapeutic agents against drug-resistant infections.
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