The Nested Mobilome. Novel computational tools for understanding protein biology and evolution
Egorov, Artyom LU
(2026)
In Lund University, Faculty of Medicine Doctoral Dissertation Series
- Abstract
- Horizontal gene transfer (HGT) is a major driver of evolution and a key source of innovation in the microbial world. Mobile genetic elements (MGEs), such as plasmids and phages, often act as agents of HGT or as vehicles for cargo genes, some of which define the adaptive potential of the host organism in specific environments. These genes are involved in immunity, anti-immunity, virulence, and antimicrobial resistance. Often, horizontally acquired genes form islands (relatively large gene clusters) in the host genome, and these islands are frequently concentrated in so-called hotspot regions (for instance, due to the preferred integration site of MGEs, or because insertions in other positions would be deleterious). In addition, hotspot... (More)
- Horizontal gene transfer (HGT) is a major driver of evolution and a key source of innovation in the microbial world. Mobile genetic elements (MGEs), such as plasmids and phages, often act as agents of HGT or as vehicles for cargo genes, some of which define the adaptive potential of the host organism in specific environments. These genes are involved in immunity, anti-immunity, virulence, and antimicrobial resistance. Often, horizontally acquired genes form islands (relatively large gene clusters) in the host genome, and these islands are frequently concentrated in so-called hotspot regions (for instance, due to the preferred integration site of MGEs, or because insertions in other positions would be deleterious). In addition, hotspot positions of variability have a nested nature: while the host genome contains hotspot positions for MGE integration, the MGEs themselves also contain variable regions, characterised by high gene turnover or by the insertion of simpler MGE forms.
The observed co-occurrence of genes with similar functions on islands, as well as the tendency of islands with accessory genes of similar function to cluster at the same hotspot position, led to the formulation of the guilt by association and guilt by location principles. These principles facilitated functional prediction of unannotated proteins, or the “dark matter”, that makes up many of these MGE cargo gene families.
The central theme of this dissertation is the systematic annotation of hotspot regions and the development of a scalable algorithm for this problem. Through analysis of these regions across ~1.6M phage and plasmid sequences, I predicted genes potentially involved in immunity and anti-immunity, and some of these were validated experimentally. In addition, several side projects are highlighted throughout this thesis, including studies on the annotation of uORFs and their role in regulating antimicrobial resistance genes, the development of visualisation tools and web services. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4e9334d6-7c1e-4e2c-a3cf-9759ae841a9a
- author
- Egorov, Artyom
LU
- supervisor
-
- Gemma Atkinson LU
- Arne Elofsson LU
- opponent
-
- NIH Distinguished Investigator Koonin, Eugene V, National Institutes of Health, USA
- organization
- publishing date
- 2026
- type
- Thesis
- publication status
- published
- subject
- keywords
- HGT, MGEs, Hotspots, Immunity, Phages, uORFs
- in
- Lund University, Faculty of Medicine Doctoral Dissertation Series
- issue
- 2026:59
- pages
- 81 pages
- publisher
- Lund University, Faculty of Medicine
- defense location
- Belfragesalen, BMC D15, Klinikgatan 32 i Lund
- defense date
- 2026-04-27 13:00:00
- ISSN
- 1652-8220
- ISBN
- 978-91-8021-857-3
- language
- English
- LU publication?
- yes
- id
- 4e9334d6-7c1e-4e2c-a3cf-9759ae841a9a
- date added to LUP
- 2026-03-27 12:54:11
- date last changed
- 2026-04-02 09:06:11
@phdthesis{4e9334d6-7c1e-4e2c-a3cf-9759ae841a9a,
abstract = {{Horizontal gene transfer (HGT) is a major driver of evolution and a key source of innovation in the microbial world. Mobile genetic elements (MGEs), such as plasmids and phages, often act as agents of HGT or as vehicles for cargo genes, some of which define the adaptive potential of the host organism in specific environments. These genes are involved in immunity, anti-immunity, virulence, and antimicrobial resistance. Often, horizontally acquired genes form islands (relatively large gene clusters) in the host genome, and these islands are frequently concentrated in so-called hotspot regions (for instance, due to the preferred integration site of MGEs, or because insertions in other positions would be deleterious). In addition, hotspot positions of variability have a nested nature: while the host genome contains hotspot positions for MGE integration, the MGEs themselves also contain variable regions, characterised by high gene turnover or by the insertion of simpler MGE forms.<br/>The observed co-occurrence of genes with similar functions on islands, as well as the tendency of islands with accessory genes of similar function to cluster at the same hotspot position, led to the formulation of the guilt by association and guilt by location principles. These principles facilitated functional prediction of unannotated proteins, or the “dark matter”, that makes up many of these MGE cargo gene families.<br/>The central theme of this dissertation is the systematic annotation of hotspot regions and the development of a scalable algorithm for this problem. Through analysis of these regions across ~1.6M phage and plasmid sequences, I predicted genes potentially involved in immunity and anti-immunity, and some of these were validated experimentally. In addition, several side projects are highlighted throughout this thesis, including studies on the annotation of uORFs and their role in regulating antimicrobial resistance genes, the development of visualisation tools and web services.}},
author = {{Egorov, Artyom}},
isbn = {{978-91-8021-857-3}},
issn = {{1652-8220}},
keywords = {{HGT; MGEs; Hotspots; Immunity; Phages; uORFs}},
language = {{eng}},
number = {{2026:59}},
publisher = {{Lund University, Faculty of Medicine}},
school = {{Lund University}},
series = {{Lund University, Faculty of Medicine Doctoral Dissertation Series}},
title = {{The Nested Mobilome. Novel computational tools for understanding protein biology and evolution}},
year = {{2026}},
}