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Open Access

The antimicrobial resistance crisis: management through gene monitoring

Carolyn A. Michael, Ashley E. Franks, Maurizio Labbate
Published 9 November 2016.DOI: 10.1098/rsob.160236
Carolyn A. Michael
School of Life Sciences, University of Technology Sydney, Sydney 2007, Australia
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  • For correspondence: carolyn.michael@uts.edu.aucamcon@ozemail.com.au
Ashley E. Franks
Department of Physiology, Anatomy and Microbiology, School of Life Sciences, La Trobe University, Melbourne, Victoria, Australia
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Maurizio Labbate
School of Life Sciences, University of Technology Sydney, Sydney 2007, Australiaithree institute, University of Technology Sydney, Sydney 2007, Australia
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    Figure 1.

    Change in community gene frequency under selective pressure. The rate at which gene frequency rises within a microbial community is largely dependent upon the strength of the selective pressure. Where a selective pressure significantly impairs the reproductive success of a large proportion of the community, gene frequency rises rapidly even though overall community numbers may decrease (a). Conversely, where the impairment is less severe or else does not affect a large proportion of the community, this leads to a lower rate of increase (b). This latter effect, where the proportion of the population affected by a stressor decreases as the gene becomes more frequent, leads to gene frequency asymptotically approaching fixation (c).

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    Figure 2.

    Change of community gene frequency due to HGT and particularly natural transformation and recombination. The processes of HGT are stochastic. So, in the absence of selection to drive an increase in gene frequency the chance of an existing gene being excised from the host DNA and subsequently lost is the same as the gene frequency across the contributing community. Accordingly, where a gene is common in the community (a) it will become more so. Similarly, where a gene is rare (b), it will rapidly be lost from the community. The rate at which genes are lost or gained is also proportional to their frequency (c).

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    Figure 3.

    A hypothetical example of the changing geographical distribution of resistance genes. The changing spatial distribution of resistance genes can be used as an indicative measure of gene migration and hence the effectiveness of both stewardship and control programmes. Additionally, the availability of areas of low gene frequencies adjacent to areas of intense antimicrobial usage (a) may offer the ability to ‘dilute’ areas of high resistance gene frequency and so hasten the removal of resistance genes from the community. By applying geographical information system (GIS) or network analysis approaches to such information, correlations with environmental and socioeconomic variables may be drawn (b).

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    Figure 4.

    The overall change in community gene frequency with time. When the mechanisms that compete to change gene frequency within a community are considered together, it is clear that in order to rapidly reduce gene frequency (a), a low starting frequency (b) in the absence of selection is required. One way this may be achieved is to apply only a weak selective pressure (b) to the environment. Alternatively, early intervention to remove high selective pressures before a high gene frequency is achieved may be effective.

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November 2016

Open Biology: 6 (11)
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Keywords

antimicrobial resistance
horizontal gene transfer
evolution
crisis management
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The antimicrobial resistance crisis: management through gene monitoring
Carolyn A. Michael, Ashley E. Franks, Maurizio Labbate
Open Biol. 2016 6 160236; DOI: 10.1098/rsob.160236. Published 9 November 2016
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Research article:

The antimicrobial resistance crisis: management through gene monitoring

Carolyn A. Michael, Ashley E. Franks, Maurizio Labbate
Open Biol. 2016 6 160236; DOI: 10.1098/rsob.160236. Published 9 November 2016

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Article reuse

  • Article
    • Abstract
    • 1. Introduction
    • 2. Measuring evolution
    • 3. Implementation
    • 4. Stewardship of existing antimicrobials
    • 5. Limitations
    • 6. Discussion
    • 7. Conclusion
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