Data-driven insights on the dissemination of antibiotic resistance genes
Doktorsavhandling, 2025
antibiotic resistance
phylogenetic analysis
hidden Markov model
microbiome
random forest
horizontal gene transfer
Författare
David Lund
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Extensive screening reveals previously undiscovered aminoglycoside resistance genes in human pathogens
Communications Biology,;Vol. 6(2023)
Artikel i vetenskaplig tidskrift
Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes
Microbiome,;Vol. 11(2023)p. 44-
Artikel i vetenskaplig tidskrift
Lund, D., Johnning, A., Holmström, M., Varghaei, L., Inda-Díaz, J. S., Bengtsson-Palme, J., Kristiansson, E. Community-promoted antibiotic resistance genes show increased dissemination among pathogens.
Parras-Moltó, M., Lund, D., Ebmeyer, S., Larsson, D. G. J., Johnning, A., Kristiansson, E. The transfer of antibiotic resistance genes between evolutionarily distant bacteria.
Genetic compatibility and ecological connectivity drive the dissemination of antibiotic resistance genes
Nature Communications,;Vol. 16(2025)
Artikel i vetenskaplig tidskrift
Lund, D., Axillus, S., Larsson, D. G. J., Johnning, A., Kristiansson, E. Can we predict the spread of emerging antibiotic resistance genes?
This thesis applies computational methods to analyze the presence and spread of resistance genes in different environments. Our results reveal a vast number of previously unknown resistance genes in different environments. We also show that the human gut and wastewater environments are connected to the spread of antibiotic resistance genes, and that this process is influenced by the genetic similarity between bacteria. Finally, we show that machine learning can potentially be used to anticipate the spread of new resistance genes. Together, our results provide new knowledge that can inform strategies to combat the spread of antibiotic resistance.
Nya resistensgener mot antibiotika och deras spridning i miljön
Vetenskapsrådet (VR) (2019-03482), 2020-01-01 -- 2023-12-31.
Ämneskategorier (SSIF 2025)
Bioinformatik och beräkningsbiologi
ISBN
978-91-8103-222-2
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5680
Utgivare
Chalmers
Pascal, Chalmers tvärgata 3, Göteborg
Opponent: Professor Sofia Kirke Forslund-Startceva, Max Delbrük Center, Berlin