Computational discovery of antibiotic resistance genes and their horizontal transfer
Licentiate thesis, 2022

Antibiotic resistance is increasing among clinical infections and represents one of the most serious threats to public health. Pathogens often become resistant by acquiring mobile antibiotic resistance genes (ARGs) via horizontal gene transfer (HGT). To limit the spread of new ARGs, it is important that we identify emerging threats early, and that we improve our understanding of what drives the HGT of ARGs. The three papers encompassing this thesis aim to increase our knowledge about ARGs and their mobility. In paper I, computational screening of large genomic datasets was used to identify new resistance genes for macrolide antibiotics, and to clarify their evolution. A large diversity of new erm and mph genes was identified, including six new families of mobile ARGs carried by pathogens, that showed varied phylogenetic origins. Of the tested genes, 70% induced resistance in Escherichia coli. In paper II, we identified previously undiscovered mobile genes giving resistance to aminoglycoside antibiotics in pathogens, further demonstrating how computational methods can discover potential emerging ARGs. Close to one million bacterial genomes were screened for aac and aph genes, and the mobility of each predicted gene was evaluated. A total of 50 families of new mobile ARGs were identified in pathogens. When new ARGs were tested in E. coli. 86% were functional, with 39% giving clinical resistance. In paper III, the factors influencing the HGT of ARGs were investigated. Phylogenetic analysis was used to identify HGT events from a large set of ARGs. For each event, the genetic compatibility of the involved gene(s) and genomes, as well as the co-occurrence of donor and recipient in different environments, were computed and used as input to train random forest classifiers. The resulting models suggested that the most important factor for determining if a mobile ARG successfully undergoes horizontal transfer is the genetic compatibility between the gene and the recipient genome. The findings presented in this thesis increase our knowledge about new genes giving resistance to two important classes of antibiotics. Furthermore, the results provide new insights into the horizontal transfer of resistance genes.

phylogenetic analysis

Antibiotic resistance

horizontal gene transfer

computational screening

Pascal, Hörsalsvägen 1, Chalmers
Opponent: Associate Professor Thomas Nordahl Petersen, National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Denmark

Author

David Lund

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Lund D, Coertze R.D, Parras-Moltó M, Berglund F, Flach C-F, Johnning A, Larsson D.G.J, Kristiansson E. Computational screening reveals previously undiscovered aminoglycoside resistance genes in human pathogens

Lund D, Parras-Moltó M, Boström M, Inda-Díaz J.S, Benson L, Ebmeyer S, Larsson D.G.J, Johnning A, Kristiansson E. Factors influencing the horizontal gene transfer potential of antibiotic resistance genes

Driving Forces

Sustainable development

Areas of Advance

Health Engineering

Subject Categories

Microbiology

Bioinformatics (Computational Biology)

Medical Genetics

Bioinformatics and Systems Biology

Genetics

Publisher

Chalmers

Pascal, Hörsalsvägen 1, Chalmers

Opponent: Associate Professor Thomas Nordahl Petersen, National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Denmark

More information

Latest update

10/27/2023