Opportunity Overview
Microbial communities evolve in volatile environments that often fluctuate between mild and harsh conditions, e.g. with sudden and radical changes in the concentration of toxins and nutrients. The resulting environmental variability greatly influences the population evolution, and the ability of species to cooperate and coexist. These are key characteristics of ecosystems that have direct applications in subjects of great societal concern, like the evolution of antimicrobial resistance (AMR). Drug resistance can often be viewed as a cooperative behaviour that is critically influenced by environmental and demographic fluctuations. Understanding how the coexistence of resistant and sensitive cells is affected by environmental changes and randomness variability are thus central questions in the effort of modelling the evolution of AMR.
While population dynamics is classically studied using differential equations in static environments, we will mathematically model the evolution of microbial communities subject to environmental and demographic fluctuations. Motivated by the application to the evolution of AMR, we will focus on models of competing species in the presence of varying toxin and/or nutrient concentrations. The main features of our modelling approach are the fluctuating size of populations, and eco-evolutionary coupling.
Objectives/methods:
By combining analytical techniques and simulations, we will study the eco-evolutionary dynamics of cooperative AMR in 1) well-mixed and 2) metapopulation settings.
1) The mechanism of AMR can often be regarded as a cooperative behaviour. Resistant cells may carry resistance plasmids expressing a "resistance enzyme" inactivating...
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Start FreeSolicitation Details
| Issuing agency | NERC |
|---|---|
| Country | United Kingdom |
| Category | Research Development |
| Published | September 30, 2024 |
| Procurement stage | Active solicitation |
| Response due | March 30, 2028 |
| Status | Open — accepting responses |
| Official source | View original notice |
| Last verified | September 21, 2026 |
Source: UK Research and Innovation (UKRI) — Open Government Licence v3.0.
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