DMS-EPSRC Eco-Evolutionary Dynamics of Fluctuating Populations
Lead Research Organisation:
University of Leeds
Department Name: Applied Mathematics
Abstract
Understanding the origin of species diversity and the evolution of cooperation is a major scientific riddle that resonates with numerous societal concerns, like the rise of antimicrobial resistance or the loss of biodiversity, and is even relevant to epidemiology. Population dynamics traditionally ignores fluctuations and considers static and homogeneous environments. However, fluctuations arising from randomly occurring birth / death events (demographic noise) and the change of environmental conditions (environmental variability), together with the spatial dispersal of species, play a crucial role in understanding how the size and composition of a population jointly evolve in time, i.e. its eco-evolutionary dynamics. Here, we focus on the ubiquitous situation where the eco-evolutionary dynamics of fluctuating populations is shaped by the coupling of demographic noise and environmental variability.
The interdependence of environmental variability and demographic noise is poorly understood but of great importance in microbial communities, which are often subject to sudden and extreme environmental changes. In particular, modelling population of varying size and composition subject to changing external factors is crucial to understand the evolution of microbial antibiotic resistance. In fact, pharmacodynamics largely focuses on the deterministic description of large well-mixed bacterial populations, but fails to account crucial stochastic effects arising in small communities. When antibiotics reduce a large population to a very small one but fail to eradicate it, surviving cells may replicate and restore infections, and these survivors are likely to develop antibiotic resistance. Owing to the small population size, the details of the outcome are subject to large fluctuations.This important example clearly illustrates the need for theoretical advances to shed light on extinction and resistance scenarios in fluctuating environments.
This ambitious proposal has branched out from a series of previous smaller collaborative projects, see e.g. References [1,2,12], visits and a workshop (co-funded by the Leeds School of Mathematics and the EPSRC Network Plus). It is a timely opportunity to carry out a cutting-edge research programme, containing elements of adventure and whose central goal is to develop a suite of theoretical tools that will allow us to describe biologically relevant evolutionary models, and to make testable predictions in laboratory-controlled experiments. For this joint effort, crucially building on the team's unique complementary expertise, we will adopt a multidisciplinary approach combining various mathematical tools and will consider models of an increasing level of complexity. Many of the features of our theoretical models, such as switching environments, time-varying population sizes, public good production, etc. can be reproduced in laboratory experiments. This opens the door to a host of exciting possibilities to address theoretical questions of direct biological relevance, and to experimentally test various predictions of our theoretical models. We will explore these opportunities with our experimental biologist project partner (see Dr Jose Jimenez's letter of support).
The interdependence of environmental variability and demographic noise is poorly understood but of great importance in microbial communities, which are often subject to sudden and extreme environmental changes. In particular, modelling population of varying size and composition subject to changing external factors is crucial to understand the evolution of microbial antibiotic resistance. In fact, pharmacodynamics largely focuses on the deterministic description of large well-mixed bacterial populations, but fails to account crucial stochastic effects arising in small communities. When antibiotics reduce a large population to a very small one but fail to eradicate it, surviving cells may replicate and restore infections, and these survivors are likely to develop antibiotic resistance. Owing to the small population size, the details of the outcome are subject to large fluctuations.This important example clearly illustrates the need for theoretical advances to shed light on extinction and resistance scenarios in fluctuating environments.
This ambitious proposal has branched out from a series of previous smaller collaborative projects, see e.g. References [1,2,12], visits and a workshop (co-funded by the Leeds School of Mathematics and the EPSRC Network Plus). It is a timely opportunity to carry out a cutting-edge research programme, containing elements of adventure and whose central goal is to develop a suite of theoretical tools that will allow us to describe biologically relevant evolutionary models, and to make testable predictions in laboratory-controlled experiments. For this joint effort, crucially building on the team's unique complementary expertise, we will adopt a multidisciplinary approach combining various mathematical tools and will consider models of an increasing level of complexity. Many of the features of our theoretical models, such as switching environments, time-varying population sizes, public good production, etc. can be reproduced in laboratory experiments. This opens the door to a host of exciting possibilities to address theoretical questions of direct biological relevance, and to experimentally test various predictions of our theoretical models. We will explore these opportunities with our experimental biologist project partner (see Dr Jose Jimenez's letter of support).
Publications
Asker M
(2023)
Coexistence of Competing Microbial Strains under Twofold Environmental Variability and Demographic Fluctuations
in New Journal of Physics
Castro S B S D
(2024)
Robust heteroclinic cycles in pluridimensions
in arXiv. (Submitted to the Journal of Nonlinear Science)
Castro S B S D
(2025)
Visibility of heteroclinic networks
in arXiv. (Submitted to SIAM Journal on Applied Dynamical Systems)
Hernández-Navarro L
(2024)
Eco-evolutionary dynamics of cooperative antimicrobial resistance in a population of fluctuating volume and size
in Journal of Physics A: Mathematical and Theoretical
Hernández-Navarro L
(2024)
Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments
in arXiv. (Submitted to PLoS Computational Biology)
Hernández-Navarro L
(2023)
Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance.
in Journal of the Royal Society, Interface
Swailem M
(2024)
Computing macroscopic reaction rates in reaction-diffusion systems using Monte Carlo simulations.
in Physical review. E
Swailem M
(2023)
Lotka-Volterra predator-prey model with periodically varying carrying capacity.
in Physical review. E
Taitelbaum A
(2023)
Evolutionary dynamics in a varying environment: Continuous versus discrete noise
in Physical Review Research
| Description | We have demonstrated that the interdependence of environmental and chance (demographic) fluctuations can significantly impact microbial communities, notably the evolution of antimicrobial resistance. In particular, we have predicted and characterised a fluctuation-driven mechanism that can lead to the eradication of antimicrobial resistance in mathematical models inspired by lab-controlled (in vitro) set-ups. |
| Exploitation Route | Our modelling ideas and theoretical methods can be generalized to more realistic in vitro and in vivo settings, Moreover, our ideas and theoretical predictions need to be probed in lab-controlled experiments (work in progress), and in the future also in vivo and possibily in clinically-relevant conditions. This would require further continuous cross-disciplinary collaborations (mathematics, biology, medicine, ecology, physics). |
| Sectors | Environment Healthcare Manufacturing including Industrial Biotechology Pharmaceuticals and Medical Biotechnology |
| URL | https://eedfp.com/ |
| Description | Organisation of an international cross-disciplinary workshop: L24EEDs workshop on "Mathematical modelling of microbial communities: cooperation, dynamics, and resistance" |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Influenced training of practitioners or researchers |
| URL | https://eedfp.com/l24eeds-workshop/ |
| Description | DMS-EPSRC Eco-Evolutionary Dynamics of Fluctuating Populations |
| Amount | $300,000 (USD) |
| Funding ID | DMS-2128587 (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2128587&HistoricalAwards=false) |
| Organisation | Virginia Tech |
| Sector | Academic/University |
| Country | United States |
| Start | 07/2021 |
| End | 07/2024 |
| Title | Data set of the manuscript: Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance |
| Description | Dataset for 'Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance'. A full description of the data, methods, and interpretation may be found in the related publication. Computational data: raw results from stochastic simulations of our full model and of the effective Moran model at fixed total population. Scripts: codes to run the simulations (in Python), as well as codes to generate each of the 4+1 main and supplementary figures (in Matlab) from the computational data. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Dataset provides details about the simulation data and codes for all figures of the paper 'Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance' published in J. R. Soc. Interface 20, 20230393:1-13 (2023). These resources allow readers to replicate the results discussed in the paper, and illustrate the research findings. |
| URL | https://doi.org/10.5518/1360 |
| Title | Dataset for 'Coexistence of Competing Microbial Strains under Twofold Environmental Variability and Demographic Fluctuations' |
| Description | Dataset for 'Coexistence of Competing Microbial Strains under Twofold Environmental Variability and Demographic Fluctuations'. A full description of the data, methods, and interpretation may be found in the related publication. Computational data: raw results from stochastic simulations of our full model and of the effective Moran model at fixed total population. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Dataset provides details about the simulation data for all figures of the paper 'Coexistence of Competing Microbial Strains under Twofold Environmental Variability and Demographic Fluctuations' published in New J. Phys 25, 123010:1-18 (2023). |
| URL | https://archive.researchdata.leeds.ac.uk/1131/ |
| Title | Dataset for 'Eco-evolutionary dynamics of cooperative antimicrobial resistance in a population of fluctuating volume and size' |
| Description | Dataset for 'Eco-evolutionary dynamics of cooperative antimicrobial resistance in a population of fluctuating size and volume'. A full description of the data, methods, and interpretation may be found in the related publication. Computational data: raw results from stochastic simulations and theoretical predictions of our full model, in both the static and dynamic environment cases. Code: exact stochastic algorithm for simulating full model and .mat files for reading data. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Dataset provides details about the simulation data and codes for all figures of the paper "Eco-evolutionary dynamics of cooperative antimicrobial resistance in a population of fluctuating volume and size" currently published as e-print: arXiv:2312.14826 (submitted to the Journal of Physics A: Mathematical and Theoretical). These resources allow readers to replicate the results discussed in the paper, and illustrate the research findings. |
| URL | https://archive.researchdata.leeds.ac.uk/1209/ |
| Title | Dataset for 'Robust heteroclinic cycles in pluridimensions' |
| Description | The dataset was generated by solving the ordinary differential equations using the Python SciPy library solve_ivp: solve_ivp(dxdt, [0,tmax], initial_condition, method='RK45', rtol=1e-12, atol=1e-12, max_step=1.0) |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | The research dataset contains the data discussed in the paper https://arxiv.org/pdf/2412.12805 as well as the code used to produce the results. |
| URL | https://archive.researchdata.leeds.ac.uk/1355/ |
| Title | Supplementary data, code, and videos for "Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments" |
| Description | Supplementary codes, data and video resources in support of the manuscript "Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments" by L. Hernández-Navarro, K. Distefano, U.C. Täuber, and M. Mobilia (2024) posted on bioRxiv (https://doi.org/10.1101/2024.12.30.630406) and arXiv (https://doi.org/10.48550/arXiv.2501.01939) |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | The codes and data generated and used within the paper "Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments" by L. Hernández-Navarro, K. Distefano, U.C. Täuber, and M. Mobilia (2024) are available in the research dataset posted on the Open Science Framework repository (Lluis Hernandez-Navarro, Kenneth Distefano, Uwe C. Tauber, and Mauro Mobilia. 2024. Available resources are: supplementary data, codes, and videos for "Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments"). These resources allow readers to replicate the results discussed in the paper, and illustrate the research findings. |
| URL | https://osf.io/epb28/ |
| Description | Collaboration with Jimenez's group on DMS-EPSRC Eco-Evolutionary Dynamics of Fluctuating Populations |
| Organisation | Imperial College London |
| Department | Department of Life Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Mathematical, theoretical and computational modelling of eco-evolutionary dynamics of microbial communities, with a special focus on the evolution of the evolution of antimicrobial resistance. |
| Collaborator Contribution | Lab-controlled experiments to test our mathematical, theoretical and computational models for the evolution of the evolution of antimicrobial resistance. |
| Impact | No outputs as yet, as the collaboration is ongoing and developing. |
| Start Year | 2021 |
