Periodic Reporting for period 1 - SynBiol-DynHet (Diversity in Synthetic Biological Systems)
Periodo di rendicontazione: 2015-09-01 al 2017-08-31
First, microbial systems can be used as model systems for ecological questions, concerning, for example, the interactions or geometries which can support biodiversity or cooperative behaviour in ecological populations. Such populations are structured such that different types of interactions happen on different length and time scales (eg within smaller habitats, or with time delays). Such structured habitats occur increasingly in the environment, for example due to climate change. Microbial model systems provide a toolbox where the impact of specific inter-species interactions or geometries can be investigated by engineering well-defined and tunable experimental conditions. We address these interactions and geometries theoretically, in order to potentially guide experiments towards systems where biodiversity or cooperation may be particularly threatened, or well-established. In doing so, we draw from and develop methods of statistical physics, as these methods can elucidate what types of behaviours among interactive species may be more general.
Second, microbial systems themselves need to be better understood, so that one can, for example, improve drug treatments when these species occur during an infection. This is particularly important in the face of the growing threat of increasing antibiotic resistance. In addition to resistance, bacteria can also become tolerant towards an antibiotic drug via a phenotypic switch. It is important to understand what types of antibiotic drug treatments may be able reduce the pressure of the species to become resistant or tolerant. In experimental systems, the impact of different types of drug treatments on a small, controllable set of species can be investigated. Thus, the theoretical work performed in the course of this project addresses the impact of temporal antibiotic gradients on a bacterial population of two species, where we assumed one species to be more tolerant to the antibiotics.
Concerning microbial populations, we studied a theoretical model system for bacteria under the influence of antibiotics. Here, we investigated how the competition between one more and one less tolerant or resistant bacterial population could be exploited in order to maximally reduce the population size in an antibiotic drug gradient. We assumed that the more tolerant species only got affected by the high-stress environment of the antibiotic treatment (high drug concentration), while the less tolerant species also got affected during treatment with low concentrations. We found that there exist timescales over which the low-stress regime is as effective as the high-stress regime. We also investigated the impact of multiple antibiotic pulses on our model population, and found that depending on the low-stress and high-stress durations within an antibiotic pulse, the bacterial population can get maximally reduced during the first pulse already. This work thus highlights the need for precise microbial experiments, targeting this competition, in order to investigate to what extent the predictions of this model – and similar models also used in public health policy – are applicable to real situations, where more species or an immune system may be present.
Both projects set the stage for further research, which we have already started with the funding of this fellowship. Concerning interacting ecological populations in systems where multiple length and time scales are present, we are currently finishing work on spatial spreading, which is also important to nanoengineering research with DNA-segments, where similar dynamics can occur. Concerning microbial populations and antibiotics, we are currently investigating the extinction dynamics of these populations more closely, also in connection with experiments.