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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).

Publications

10 25 50

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Castro S B S D (2024) Robust heteroclinic cycles in pluridimensions in arXiv. (Submitted to the Journal of Nonlinear Science)

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Castro S B S D (2025) Visibility of heteroclinic networks in arXiv. (Submitted to SIAM Journal on Applied Dynamical Systems)

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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

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Hernández-Navarro L (2024) Slow spatial migration can help eradicate cooperative antimicrobial resistance in time-varying environments in arXiv. (Submitted to PLoS Computational Biology)

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Hernández-Navarro L (2023) Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance. in Journal of the Royal Society, Interface

 
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