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      Prediction of antibiotic resistance: time for a new preclinical paradigm?

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      Journal: Nature Reviews Microbiology
      Publisher: Springer Nature

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          Microbiological effects of sublethal levels of antibiotics.

          Dan Andersson, Diarmaid Hughes (2014)
          The widespread use of antibiotics results in the generation of antibiotic concentration gradients in humans, livestock and the environment. Thus, bacteria are frequently exposed to non-lethal (that is, subinhibitory) concentrations of drugs, and recent evidence suggests that this is likely to have an important role in the evolution of antibiotic resistance. In this Review, we discuss the ecology of antibiotics and the ability of subinhibitory concentrations to select for bacterial resistance. We also consider the effects of low-level drug exposure on bacterial physiology, including the generation of genetic and phenotypic variability, as well as the ability of antibiotics to function as signalling molecules. Together, these effects accelerate the emergence and spread of antibiotic-resistant bacteria among humans and animals.
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            Bacterial phylogeny structures soil resistomes across habitats

            Kevin J. Forsberg, Sanket Patel, Molly Gibson … (2014)
            Summary Ancient and diverse antibiotic resistance genes (ARGs) have previously been identified from soil 1–3 , including genes identical to those in human pathogens 4 . Despite the apparent overlap between soil and clinical resistomes 4–6 , factors influencing ARG composition in soil and their movement between genomes and habitats remain largely unknown 3 . General metagenome functions often correlate with the underlying structure of bacterial communities 7–12 . However, ARGs are hypothesized to be highly mobile 4,5,13 , prompting speculation that resistomes may not correlate with phylogenetic signatures or ecological divisions 13,14 . To investigate these relationships, we performed functional metagenomic selections for resistance to 18 antibiotics from 18 agricultural and grassland soils. The 2895 ARGs we discovered were predominantly novel, and represent all major resistance mechanisms 15 . We demonstrate that distinct soil types harbor distinct resistomes, and that nitrogen fertilizer amendments strongly influenced soil ARG content. Resistome composition also correlated with microbial phylogenetic and taxonomic structure, both across and within soil types. Consistent with this strong correlation, mobility elements syntenic with ARGs were rare in soil compared to sequenced pathogens, suggesting that ARGs in the soil may not transfer between bacteria as readily as is observed in the clinic. Together, our results indicate that bacterial community composition is the primary determinant of soil ARG content, challenging previous hypotheses that horizontal gene transfer effectively decouples resistomes from phylogeny 13,14 .
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              The biological cost of antibiotic resistance.

              Dan Andersson, Bruce R. Levin (1999)
              The frequency and rates of ascent and dissemination of antibiotic resistance in bacterial populations are anticipated to be directly related to the volume of antibiotic use and inversely related to the cost that resistance imposes on the fitness of bacteria. The data available from recent laboratory studies suggest that most, but not all, resistance-determining mutations and accessory elements engender some fitness cost, but those costs are likely to be ameliorated by subsequent evolution.
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                Author and article information

                Journal
                Title: Nature Reviews Microbiology
                Abbreviated Title: Nat Rev Micro
                Publisher: Springer Nature
                ISSN (Print): 1740-1526
                ISSN (Electronic): 1740-1534
                Publication date Created: July 31 2017
                Publication date (Print): July 31 2017
                Volume:
                Issue:
                Article
                DOI: 10.1038/nrmicro.2017.75
                PubMed ID: 28757648
                SO-VID: b88e03d6-9592-455c-9083-4fbd8c32d24b
                Copyright © © 2017
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