bioRxivMicrobiologyPreprint
Systematic annotation of hyper-variability hotspots in phage genomes and plasmids
Artyom A. EgoroviD, Vasili HauryliukiD, Gemma Catherine AtkinsoniD
Abstract
Bacterial and bacteriophage genomes contain genomic regions of hyper-variability (diversity hotspots) caused by insertions of mobile genetic elements (MGEs), non-homologous recombination events and non-horizontal hypermutation. Accessory genes encoded in the diversity hotspots are involved in anti-MGE defence and counter-defence, virulence and antimicrobial resistance (AMR), thus playing key roles in interactions amongst phages, MGEs, bacteria and eukaryotic hosts. To date the majority of research has been focused on either individual hotspots or on relatively limited sets of hotspots in a small set of genomes, typically from a single species. A global understanding of hotspot diversity and dynamics still lacking. To address this gap, we developed iLund4u, an algorithm for the systematic annotation of hotspots across millions of sequences. Using a proteome composition approach, iLund4u detects proteome communities, annotates accessory proteins and identifies hotspots. By analysing 873K phage genomes and 696K plasmid sequences we identified 13.7K hotspots and 171K diverse protein families encoded there as cargo. Furthermore, iLund4u allows for protein search and proteome annotation functions versus a precomputed iLund4u database. In the protein search mode iLund4u identifies all hotspots that encode homologues of a query protein. In the proteome annotation mode iLund4u annotates hotspots by searching for communities of similar proteomes. Detailed documentation, user guide and the source code are available at the iLund4u home page: art-egorov.github.io/ilund4u.
- assay: proteomics
- research focus: cell type annotation
- research focus: database / resource
- approach: deep learning
- approach: statistical model
- Citations
- 10
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