Periodic Reporting for period 1 - SynBiol-DynHet (Diversity in Synthetic Biological Systems)
Okres sprawozdawczy: 2015-09-01 do 2017-08-31
We address the impact of diversity in synthetic biological models. We focused on the impact of length and time scales in these systems, concerning two separate aspects:
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.
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 our ecological populations, we investigated public goods games, which are used to model the interaction between two types of species: one which produces a public good at a certain production cost to the benefit of the entire population, and another species which just makes use of this public good. These models have traditionally been used to understand the phenomenon of cooperation in ecological systems; here, we focused more specifically on what type of interactions or geometries can stabilise producers of the public good. We investigated this system on a patch structure, and found that if species interact locally and do not immediate respond to changes in the environment, producers can be stabilised. This stabilisation is due to the interplay of length and time scales (patch structure and response delay). The importance of this work is that it shows that these length and time scales can give unexpected results (in our case, a very unexpected stabilisation of producers in the high mobility limit, where they should normally die out), and thus merit more detailed investigation from both experiments and theory. Work performed in the final period of this project focused on how heterogeneity in these producers can additionally stabilse them further, and how different interaction topologies can change both producer stability and spatial spreading of producers in different ways.
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.
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.
The project has contributed towards a better understanding of interactions in microbial populations where a multitude of length and time scales are present. Our work on competing populations in antibiotic gradients is timely due to current experimental advances in the field of microfluidics, and a surge in investigating what type of drug treatments may alleviate the pressure on the population to become resistant or tolerant. Our work has highlighted that it is important to be aware of time scales during which the two species compete. It suggests that short antibiotic gradients may not contribute to the resistance pressure, but may be exploited, when the tolerant species is present in the system initially. In addition, our work on which pulse in a series of antibiotic pulses is most efficient in reducing a microbial population implies that sometimes further pulses or longer treatments are useless or even detrimental. Thus, our work thus indicates that antibiotic gradients may have important medical applications. However, since it is important for microbial experiments to verify whether our models are indeed applicable in more complicated systems (with more species being present, or given the way specific drugs impact specific bacteria), our work impacts mostly the biophysics community: we suggest that further detailed research is necessary, from both experiments, as well as theorists working on stochastic systems. Concerning populations interacting via a public good, our work conceptualised what type of models may lead to unexpecting behaviour. Thus, our research contributes to clarifying what type of public goods game models can yield interesting results, and thus may be interesting for experimental implementation. Our work thus impacts researchers from statistical physics, synthetic biological experiments and also nanoengineering. With both these projects, we show that well-designed microbial experiments in these systems are highly relevant and necessary so that we can better exploit these systems for both medical and engineering applications.