Abstract
Wastewater treatment plants play an important role in the emergence of antibiotic resistance. They provide a hot spot for exchange of resistance within and between species. Here, we analyse and quantify the genomic diversity of the indicator Escherichia coli in a German wastewater treatment plant and we relate it to isolates’ antibiotic resistance. Our results show a surprisingly large pan-genome, which mirrors how rich an environment a treatment plant is. We link the genomic analysis to a phenotypic resistance screen and pinpoint genomic hot spots, which correlate with a resistance phenotype. Besides well-known resistance genes, this forward genomics approach generates many novel genes, which correlated with resistance and which are partly completely unknown. A surprising overall finding of our analyses is that we do not see any difference in resistance and pan genome size between isolates taken from the inflow of the treatment plant and from the outflow. This means that while treatment plants reduce the amount of bacteria released into the environment, they do not reduce the potential for antibiotic resistance of these bacteria.
Highlights
In 1945, Alexander Fleming, the discoverer of Penicillin, warned of antibiotic resistance
That the E. coli core genome comprises around 1400–1500 genes, while the pan-genome may be of infinite size[11]
It is well known that wastewater treatment reduces the bacterial abundance, in addition a recent metagenomic study has shown that the bacterial community in wastewater is very different to the human gut community and that the number of detected genera is reduced in the wastewater[10]
Summary
In 1945, Alexander Fleming, the discoverer of Penicillin, warned of antibiotic resistance. At the heart of modern resistance development is a human-centered network of clinics, industry, private homes, farming, and wastewater. The current information on the genomic diversity of antibiotic resistant E. coli in wastewater is very limited. Our analysis reveals a surprisingly high genomic diversity of MDR E. coli in the wastewater with very flexible genomes harboring a high variation of virulence genes and resistance determinants. Using this diversity, we developed a computational approach to identify known, and novel genes correlating with resistance
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