Exploring the microbial resistome in river sediments exposed to extraordinary high levels of antibiotics
Poster (konferens), 2010

The rapid development and propagation of antibiotic resistance in pathogenic and opportunistic bacteria is a major threat to public health worldwide. The phenomenon has been widely studied in the clinical setting, but comparatively little is known about the prevalence and diversity of antibiotic resistance in communities of environmental bacteria, often referred to as the environmental resistome. As the external environment may function as a reservoir of resistance genes to human pathogens, we are interested in how environmental bacteria are affected by antibiotic pollution. We have previously isolated microbial DNA from river sediments taken up- and downstream from a water treatment plant that processes waste water from several pharmaceutical plants producing antibiotics. In a previous study, we used deep sequencing to identify unprecedented frequencies of known resistance genes to several classes of antibiotics in these samples. In this study, we aim to functionally characterize the resistome in a more open and exploratory way by screening genomic DNA libraries transformed into sensitive hosts. To generate the libraries, several experimental strategies were explored, including mechanical shearing and enzymatic digestion of the isolated DNA followed by blunt- or sticky end cloning into different plasmids, subsequently transformed into sensitive E. coli. Pros and cons of the different strategies will be discussed along with preliminary results of the screening against selected antibiotics.


antibiotic resistance


antibiotic contamination


Anders Janzon

Göteborgs universitet

Carolin Rutgersson

Göteborgs universitet

Erik Kristiansson

Göteborgs universitet

Edward R.B. Moore

Göteborgs universitet

D. G. Joakim Larsson

Göteborgs universitet

35th FEBS Congress: Molecules of Life


Biologisk systematik

Biokemi och molekylärbiologi

Annan biologi

Farmakologi och toxikologi


Bioinformatik och systembiologi



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