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Modelling antibiotic resistance in microbes

The intensive use and misuse of antibiotics has built-up resistance in most human pathogens against antibiotics. An EU-funded project has generated knowledge to predict the rate and future path of resistance evolution to mitigate this worrying phenomenon.
Modelling antibiotic resistance in microbes
The 'Predicting antibiotic resistance' (PAR) project has developed quantitative models to capture the complex dynamics of microbial resistance. The relevant values were then validated using in vitro and in vivo models.

Key issues addressed by PAR were the formation and emergence of resistant bacteria, mechanism of pathogen survival and persistence as well as their transmission.

PAR researchers identified the resistance genes, the resistome, in Pseudomonas aeruginosa. The effect of these mutations were studied in several species of Mycobacterium tuberculosis to assess the different phenotypic changes.

Project work also demonstrated that many antibiotics, including b-lactam antibiotics, can promote mutagenesis in Escherichia coli, for example. Of particular concern is the fact that some antibiotics may affect bacterial resistance generation at sub-minimum inhibitory concentration (MIC). Findings from a dabbling duck model using E. coli suggest that extremely low antibiotic concentrations in the environment can maintain the resistant bacteria.

Results of particular interest concern a highly problematic resistance gene, NDM-1, that has recently spread globally at an alarming rate. PAR investigations show that this gene has a high expression and recombination rate as well as associations with certain plasmids. This is a community-acquired infection closely linked to poor sanitation in East Asia and often spread by tourism and medical tourism. Of high political impact, these studies led the Indian government to draw up an antibiotic prescription and control policy for the first time.

PAR researchers demonstrated that for commercially available antibiotics (e.g. fusidic acid and mecillinam), resistance development and compensatory evolution is generally slower for drugs with multiple targets.

Dissemination initiatives included 4 major research planning meetings, 135 peer-reviewed publications, over 200 conference presentations and book chapters. In addition, results have been presented and discussed in several other forums, the EU, European Medicines Agency (EMEA) and within the industry.

The results produced in the project have generated great interest from the public health sector, physicians, environmental agencies, agricultural organisations and media. Project outcomes also have significant implications for improving our understanding of molecular evolution, bacterial physiology and preventing antibiotic resistance.

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