Using metagenomic Hi-C data to discover broad host-range plasmids conferring antimicrobial resistance

Master thesis (2023)

Authors

E. Dorrestijn Electrical Engineering, Mathematics and Computer Science

Contributors

Thomas Abeel Pattern Recognition and Bioinformatics (mentor)
S. Pillay Pattern Recognition and Bioinformatics (graduation committee member)
Martin Skrodzki Computer Graphics and Visualisation (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Eljo Dorrestijn
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Published Date

23-06-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Horizontal gene transfer (HGT) trough plasmids is one of the main contributors to the rapid increase of antimicrobial resistance (AMR). Studying wastewater from wastewater treatment plants (WWTPs) allows us new insights into HGT as bacteria from different sources come together. Currently the analysis of HGT is limited, as plasmids cannot be linked to their host species with only metagenomic samples, however when combined with Hi-C sequencing data, sequences from the same cell can be linked together.
We developed a method that uses metagenomic Hi-C data to link bacterial genera together with detected plasmid consensus clusters and resistance genes. Using this method, we analysed datasets from two sources: activated sludge put into a reactor with an antibiotic pressure and a WWTP entrance. The activated sludge dataset was sequenced at two timepoints with an increasing antibiotic concentration. This allowed us to compare degrees of antibiotic resistance in different antibiotic pressures as well as detect broad host-range resistant plasmids. We detected an increase in acquired resistance in environments with a higher antibiotic pressure and detected a resistant plasmid in both locations, linked to both pathogenic as well as bacteria found in active sludge.

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