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Potential impacts of aquatic pollutants: sub-clinical antibiotic concentrations induce genome changes and promote antibiotic resistance.

Chow L, Waldron L, Gillings MR - Front Microbiol (2015)

Bottom Line: These changes were observed in as few as five passages, despite the fact that the protocols used sample less than 0.3% of the genome, in turn suggesting much more widespread alterations to sequence and genome architecture.Experimental lines also displayed variant colony morphologies.The final MICs were significantly higher in some experimental lineages of P. protegens, suggesting that 1/10 the MIC induces de-novo mutation events that generate resistance phenotypes.

View Article: PubMed Central - PubMed

Affiliation: Emma Veritas Laboratory, Department of Biological Sciences, Macquarie University Sydney, NSW, Australia.

ABSTRACT
Antibiotics are disseminated into aquatic environments via human waste streams and agricultural run-off. Here they can persist at low, but biologically relevant, concentrations. Antibiotic pollution establishes a selection gradient for resistance and may also raise the frequency of events that generate resistance: point mutations; recombination; and lateral gene transfer. This study examined the response of bacteria to sub-inhibitory levels of antibiotics. Pseudomonas aeruginosa and Pseudomonas protegens were exposed kanamycin, tetracycline or ciprofloxacin at 1/10 the minimal inhibitory concentration (MIC) in a serial streaking experiment over 40 passages. Significant changes in rep-PCR fingerprints were noted in both species when exposed to sub-inhibitory antibiotic concentrations. These changes were observed in as few as five passages, despite the fact that the protocols used sample less than 0.3% of the genome, in turn suggesting much more widespread alterations to sequence and genome architecture. Experimental lines also displayed variant colony morphologies. The final MICs were significantly higher in some experimental lineages of P. protegens, suggesting that 1/10 the MIC induces de-novo mutation events that generate resistance phenotypes. The implications of these results are clear: exposure of the environmental microbiome to antibiotic pollution will induce similar changes, including generating newly resistant species that may be of significant concern for human health.

No MeSH data available.


Related in: MedlinePlus

Similarity co-efficient (F) of BOX patterns from experimental lines at generation 40 [F = 2Nxy/(Nx + Ny)] compared to control lines. Dots represent the averge F-statistic of three samples from each line and each box contains nine lines for each treatment. Scores below 1.0 indicate consistent polymorphisms in BOX-PCR patterns.
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Figure 3: Similarity co-efficient (F) of BOX patterns from experimental lines at generation 40 [F = 2Nxy/(Nx + Ny)] compared to control lines. Dots represent the averge F-statistic of three samples from each line and each box contains nine lines for each treatment. Scores below 1.0 indicate consistent polymorphisms in BOX-PCR patterns.

Mentions: To determine the degree of polymorphism amongst the individual experiments, F statistics were calculated. A scatter plot of the F-statistics shows that control lines maintained a uniform BOX-PCR pattern across all three bacterial isolates (PA14, PF-5, and PF-5A) for the 40 generations of the experiment (Figure 3). Amongst the lineages treated with sub-inhibitory antibiotic concentrations, only the kanamycin treatment of PA14 maintained a stable BOX-PCR pattern. All other treatments generated polymorphic banding patterns in at least some of the replicates. The approximate degree to which polymorphisms were generated was in the order of Kan < Tet < Cipro (Figure 3).


Potential impacts of aquatic pollutants: sub-clinical antibiotic concentrations induce genome changes and promote antibiotic resistance.

Chow L, Waldron L, Gillings MR - Front Microbiol (2015)

Similarity co-efficient (F) of BOX patterns from experimental lines at generation 40 [F = 2Nxy/(Nx + Ny)] compared to control lines. Dots represent the averge F-statistic of three samples from each line and each box contains nine lines for each treatment. Scores below 1.0 indicate consistent polymorphisms in BOX-PCR patterns.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525061&req=5

Figure 3: Similarity co-efficient (F) of BOX patterns from experimental lines at generation 40 [F = 2Nxy/(Nx + Ny)] compared to control lines. Dots represent the averge F-statistic of three samples from each line and each box contains nine lines for each treatment. Scores below 1.0 indicate consistent polymorphisms in BOX-PCR patterns.
Mentions: To determine the degree of polymorphism amongst the individual experiments, F statistics were calculated. A scatter plot of the F-statistics shows that control lines maintained a uniform BOX-PCR pattern across all three bacterial isolates (PA14, PF-5, and PF-5A) for the 40 generations of the experiment (Figure 3). Amongst the lineages treated with sub-inhibitory antibiotic concentrations, only the kanamycin treatment of PA14 maintained a stable BOX-PCR pattern. All other treatments generated polymorphic banding patterns in at least some of the replicates. The approximate degree to which polymorphisms were generated was in the order of Kan < Tet < Cipro (Figure 3).

Bottom Line: These changes were observed in as few as five passages, despite the fact that the protocols used sample less than 0.3% of the genome, in turn suggesting much more widespread alterations to sequence and genome architecture.Experimental lines also displayed variant colony morphologies.The final MICs were significantly higher in some experimental lineages of P. protegens, suggesting that 1/10 the MIC induces de-novo mutation events that generate resistance phenotypes.

View Article: PubMed Central - PubMed

Affiliation: Emma Veritas Laboratory, Department of Biological Sciences, Macquarie University Sydney, NSW, Australia.

ABSTRACT
Antibiotics are disseminated into aquatic environments via human waste streams and agricultural run-off. Here they can persist at low, but biologically relevant, concentrations. Antibiotic pollution establishes a selection gradient for resistance and may also raise the frequency of events that generate resistance: point mutations; recombination; and lateral gene transfer. This study examined the response of bacteria to sub-inhibitory levels of antibiotics. Pseudomonas aeruginosa and Pseudomonas protegens were exposed kanamycin, tetracycline or ciprofloxacin at 1/10 the minimal inhibitory concentration (MIC) in a serial streaking experiment over 40 passages. Significant changes in rep-PCR fingerprints were noted in both species when exposed to sub-inhibitory antibiotic concentrations. These changes were observed in as few as five passages, despite the fact that the protocols used sample less than 0.3% of the genome, in turn suggesting much more widespread alterations to sequence and genome architecture. Experimental lines also displayed variant colony morphologies. The final MICs were significantly higher in some experimental lineages of P. protegens, suggesting that 1/10 the MIC induces de-novo mutation events that generate resistance phenotypes. The implications of these results are clear: exposure of the environmental microbiome to antibiotic pollution will induce similar changes, including generating newly resistant species that may be of significant concern for human health.

No MeSH data available.


Related in: MedlinePlus