A new framework to study the impact of antimicrobials on the within-host dynamics of bacterial infections.

The treatment and complete cure of bacterial infections can be difficult. Some infections that are not completely eliminated from the tissues can relapse especially in immunodeficient adults and children or can become chronic and be transmitted between infected individuals for long times. Pathogens that persist asymptomaticatically in chickens, pigs and cattle and are transmissible to humans through the food chain still cause great concern.
Difficulties in treatment and eradication of bacterial infections of animals and man can often be ascribed to suboptimal exploitation of the therapeutic potential offered by current drug treatments, a direct consequence of our superficial knowledge of how antibiotics affect the infection process inside the body of an animal. Although we understand how antibiotics act on bacteria in test-tube conditions we still do not fully comprehend the action of drugs in the whole animal in relation to the location and growth of the pathogens in the tissues. The emergence of new multi-drug-resistant bacterial strains is a grave emergency and a compounding factor in the current difficulties in tackling bacterial diseases and we are losing many of our first-line antimicrobials, with very few new drugs currently in the pipeline.
We will create and use a new framework that integrates the simultaneous tracking of multiple bacterial subpopulations in the body and the monitoring of the pharmacological properties of antibiotics that have different sites and modes of action and are broadly representative of commonly used drugs. Our research will also be supported by mathematical modelling of the impact of these drugs on the in vivo infection process. The work will be able to generate biological and mathematical knowledge on the reciprocal impacts of pathogen behaviour and the sites and modes of action of antibiotics in isolation and in combination treatments. The work will enable optimisation of treatment regimens with currently available drugs and will inform the criteria behind a more rational development and selection of new antibiotics.

We will exploit the tractability, relevance and broad applicability of the murine model of Salmonella infections to understand and quantify the effects of different antibiotics on the dynamics of growth, spread, persistence and relapse of bacterial infections, in vivo, in order to optimize and rationalise the treatment of infectious diseases.

We will develop a novel framework based on a coherent multidisciplinary strategy that integrates experimental biology and mathematical modelling, with the support of pharmacokinetic-pharmacodynamic (PK/PD) testing and modelling. We will compare and contrast the effects of four antibiotics, each representative of a mode of action and belonging to different classes of commonly used drugs. We shall use: i) gentamicin which poorly penetrates phagocytes; ii) ciprofloxacin which efficiently penetrates inside cells; iii) ampicillin which acts only on replicating bacteria; iv) chloramphenicol which is bacteriostatic.
We shall monitor the reciprocal impact of pathogen behaviour and antimicrobial treatment by high-resolution in vivo analysis of numerical and spatial fluctuations of molecularly tagged Salmonella subpopulations within infected tissues.
The work will explore: a) the relationship between bacterial location, growth, death and spread in vivo and the action of antimicrobials; b) the effect of bactericidal vs bacteriostatic drugs on infection dynamics; c) the basis, in terms of host-pathogen infection dynamics, of the establishment of persistent infections post-antimicrobial treatment and subsequent relapse; d) the applicability of modelling frameworks to predict the effects of combined multidrug treatments and to select the most efficient combinations of drugs.
The work will create translatable conceptual advances as well as mathematical and PK/PD models to rationally tailor drug development, choice and optimised treatment regimens to the biological features of infection processes.

Who will benefit from the research?
The research will have an immediate impact on the broad academic scientific community and those sectors of industry currently engaged in research on the development and selection of antimicrobial compounds. Scientists will rapidly benefit from the availability of knowledge and approaches that will be developed and validated during the programme of work and that can be extended to a large number of animal and microbial species. The approaches generated by the research will be broadly applicable to many infections and therefore the work is likely to generate fruitful collaboration networks that have the potential to bring industry and academia together.
The research will be of benefit for the general public and will impact on human and animal health due to its high impact on a more rational and cost effective usage of antimicrobials ultimately also leading towards reductions in the development and spread of antimicrobial resistance.

How will they benefit from this research?
The research will combine different disciplines to create a general platform for the assessment of the in vivo efficacy of medical treatments. This will immediately provide a rigorous way of understanding the intricate relationships between pathogen behavior in vivo and the activity of antimicrobial drugs. The work will provide those conceptual advancements necessary to understand the reasons between the pitfalls of some of the current treatments and will provide the medical profession with tools to design more targeted treatment strategies. In doing so, the work will contribute to counteract the loss of efficacy of current antimicrobial treatments and the progressive increase of antimicrobial resistance, both recognised major threats for humankind.
The research will have a clear and immediate impact on the development and use of mathematical models for the optimization of antimicrobial treatments as a resource for the academic community and industry. The models will be able to generate predictions on the impact of targeted pharmacological therapies on bacterial infections. This will initiate a process that has the potential to lead to increased usage of predictive models by academia and industry and eventually by the medical profession leading to cost effective pathways to antimicrobial usage through strict scientific criteria and not through empirical approaches.
The use of more targeted treatment regimes and the design of shorter treatment schedules, for example via the use of synergistic multidrug treatments, will eventually impact on the overall reduction in the use of antibiotics. This will represent a cost benefit for society and reduce the development of drug resistance.
The work will impact on the development of more rigorous ways to linking antibiotic efficacy with pharmacodynamics/pharmacokinetics and in vivo pathogen behavior; this will inform what is required from new drugs to be of the highest efficacy in different disease manifestations (e.g. acute or chronic/persistent infections). This will impact on drug selection and therefore the proposed work will constitute a resource for those in academia and industry who are involved in drug discovery.