Nucleic Acids ResearchMicrobiologyPeer-reviewed journal article
Exploring the diversity of anti-defense systems across prokaryotes, phages, and mobile genetic elements
Florian TessoniD, Erin D. HuitingiD, Linlin WeiiD, Jie Ren, Matthew Johnson, Rémi PlaneliD, Jean CuryiD, Yue FengiD, Joseph Bondy‐DenomyiD, Aude G. BernheimiD
Abstract
The co-evolution of prokaryotes, phages, and mobile genetic elements (MGEs) over the past billions of years has driven the emergence and diversification of defense and anti-defense systems alike. Anti-defense proteins have diverse functional domains, sequences, and are typically small, creating a challenge to detect anti-defense homologs across the prokaryotic genomes. To date, no tools comprehensively annotate anti-defense proteins within a desired genome or MGE. Here, we developed "AntiDefenseFinder" - a free open-source tool and web service that detects 156 anti-defense systems (of one or more proteins) in any genomic sequence. Using this dataset, we identified 47,981 anti-defense systems distributed across prokaryotes, phage, and MGEs. We found that some genes co-localize in "anti-defense islands", including E. coli T4 and Lambda phages, although many are standalone. Out of the 112 systems detected in bacteria, 100 systems localize only or preferentially in prophages, plasmids, phage satellites, integrons, and integrative and conjugative elements. However, over 80% of anti-Pycsar protein 1 (Apyc1) resides in non-mobile regions of bacteria. Evolutionary and functional analyses revealed that Apyc1 likely originated in bacteria to regulate cNMP signaling, but was co-opted multiple times by phages to overcome cNMP-utilizing defenses. With the AntiDefenseFinder tool, we hope to facilitate the identification of the full repertoire of anti-defense systems in MGEs, the discovery of new protein functions, and a deeper understanding of host-pathogen arms race.
- organism: bacteria (other)
- organism: virus
- assay: proteomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: protein folding & dynamics
- research focus: host-pathogen & immune response
- approach: deep learning
- approach: statistical model
- Citations
- 85
- FWCI
- 13.11
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Systematic and quantitative view of the antiviral arsenal of prokaryotes
F. Tesson, A. Herve, … A. Bernheim·bioRxiv·Sep 2, 2021
- Mapping the landscape of anti-phage defense mechanisms in the E. coli pangenome
C. Vassallo, C. Doering, … M. T. Laub·bioRxiv·May 12, 2022
- An expanding arsenal of immune systems that protect bacteria from phages
A. Millman, S. Melamed, … R. Sorek·bioRxiv·May 11, 2022
- Genomic characterization of the antiviral arsenal of Actinobacteria
H. Georjon, F. Tesson, … A. Bernheim·bioRxiv·Mar 30, 2023
- Genomic landscape of antiviral defense systems in prokaryotes and phages
Jinquan Li, Jiazheng Gu, … Meng Li·bioRxiv·Oct 26, 2024
- Leveraging defense system modularity to discover anti-phage systems
Liu yanqiu, Tan keyi, … Wenyuan Han·bioRxiv·Dec 8, 2025