ArticleMicrobiology spectrum2024
TolRad, a model for predicting radiation tolerance using Pfam annotations, identifies novel radiosensitive bacterial species from reference genomes and MAGs.
Article in Microbiology spectrum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Decoding extremophiles: insights from bioinformatics, machine learning, and data-driven approaches.Briefings in bioinformatics · 2026Review
- Elucidating the interplay between intracellular manganese-iron-ratio and radiotolerance across all domains of life.FEMS microbes · 2026Article
- Quantitative morphological analysis ofApplied and environmental microbiology · 2024Article
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Authors and funding
4 authors.
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Abstract
The trait of ionizing radiation (IR) tolerance is variable between bacterium, with species succumbing to acute doses as low as 60 Gy and extremophiles able to survive doses exceeding 10,000 Gy. While survival screens have identified multiple highly radioresistant bacteria, such systemic searches have not been conducted for IR-sensitive bacteria. The taxonomy-level diversity of IR sensitivity is poorly understood, as are genetic elements that influence IR sensitivity. Using the protein domain (Pfam) frequencies from 61 bacterial species with experimentally determined IMPORTANCE: Bacterial species have vast genetic diversity, allowing for life in extreme environments and the conduction of complex chemistry. The ability to harness the full potential of bacterial diversity is hampered by the lack of high-throughput experimental or bioinformatic methods for characterizing bacterial traits. Here, we present a computational model that uses
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