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Background:
Background:
Drug resistance is a growing threat across various organisms, including bacteria, fungi, and parasitic worms. Despite the extensive research in different disciplines, our understanding remains limited due to the vast differences between taxa.
Organisms differ, for instance, in their ploidy, lifestyle, and reproductive strategy. We know that all of these factors matter substantially for evolution - for example, biofilms shield bacteria from antibiotics, and sexual reproduction can shuffle allele combinations.
Approach:
Approach:
We will develop a model that combines the generality of the adaptation process, acting in all three studied taxa, with the specificity needed to model individual organisms. This will be achieved by developing tailored modules capturing specific properties of the process in each studied taxon. Individual modules can be combined and parameterized to model a wide range of species and evolutionary scenarios.
In particular, we will develop four types of modules: one for each studied aspect: genetics, lifestyle, and reproduction, and one additional module - environment. By altering the modules, for instance, by replacing a selfing module with a mating module, we will determine the effect of reproductive mode on resistance evolution.
Pharmacodynamics
Pharmacodynamics
Pharmacodynamic approach will allow us to determine the effect of drug on crucial population genetic parameters, such as replication and death rates. These are the subjects of evolution, with mutation affecting drug sensitivity of different strains.
Generating testable predictions
Generating testable predictions
We will use pharmacodynamic data to parametrize this modular model and investigate the role of important factors influencing drug resistance evolution in various taxa. In collaboration with experimental biologists, we will design simulations, propose hypotheses and generate concrete predictions that can be validated experimentally.
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