Large-scale screening of genomic data identifies novel mobile colistin resistance genes and reveals high over-representation in Pseudomonadota

Sammanfattning

The emergence of antibiotic-resistant bacteria is a health problem of great concern.Antibiotic resistance development is driven by selection pressure and the environment is believed to be the origin of most antibiotic resistance genes, from wherethey can mobilize into pathogens. In order to be prepared when novel antibioticresistance genes reach pathogens and prevent further transmission, early detectionand knowledge about the spread is of high importance. One specific type of antibiotic that is of high interest to characterize is colistin. Colistin is an antibioticthat targets gram-negative bacteria and is sometimes seen as the last alternative totreat dangerous infections caused by multi-drug resistance gram-negative bacteria.The emergence of mobile colistin resistance genes hence threatens the efficiency oftreating these types of infections. The aim of this thesis is to identify potential novelcolistin resistance genes and evaluate them in terms of gene mobility and phylogeny.In order to achieve this, a gene model optimized for colistin resistance genes hasbeen created with fARGene. This model was then used to screen large-scale bacterial genomic data for potential novel colistin resistance genes. The predicted geneswere analyzed in terms of mobility and phylogeny. This resulted in 680 257 predicted genes, over-represented in the class Gammaproteobacteria within the phylumPseudomonadota, that could be summarized into 1611 clusters. Out of these clusters, 104 showed signs of mobility, and many were closely related to the alreadyknown mobile colistin resistance genes. Additionally, 13 clusters comprising potential mobile novel colistin resistance genes that are present, or at risk of ending up,in pathogenic hosts could be identified.