Statistical mechanics of phenotypic eco-evolution: from adaptive dynamics to complex diversification DOI Creative Commons
Matteo Sireci, Miguel A. Muñoz

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: July 23, 2023

The ecological and evolutionary dynamics of large sets individuals can be theoretically addressed using ideas tools from statistical mechanics. This strategy has been in the literature, both context population genetics –whose focus is genes or “genotypes”— adaptive dynamics, putting emphasis on traits “phenotypes”. Following this tradition, here we construct a framework allowing us to derive “macroscopic” equations rather general “microscopic” stochastic representing fundamental processes reproduction, mutation selection community individuals, each one characterized by its phenotypic features. Importantly, our setup, timescales are intertwined, which makes it particularly suitable describe microbial communities, timely topic utmost relevance. Our leads probabilistic description distribution space —even case arbitrarily populations— as encoded what call “generalized Crow-Kimura equation” replicator-mutator equation”. We discuss limits such an equation reduces (deterministic) theory “adaptive dynamics” (i.e. standard approach space. Moreover, emphasize aspects that beyond reach dynamics. In particular, working out, guiding example, simple model growing competing population, show resulting probability exhibit “dynamical phase transitions” changing unimodal bimodal —by means branching— multimodal, cascade branching events. Furthermore, formalism allows rationalize these cascades transitions parsimonious Landau’s transitions. Finally, extend account for finite populations illustrate possible consequences “demographic” effects. Altogether present extends and/or complements existing approaches evolutionary/adaptive paves way more systematic studies e.g. communities well future developments including theoretical analyses process perspective non-equilibrium

Language: Английский

A macroecological perspective on genetic diversity in the human gut microbiome DOI Creative Commons
William R. Shoemaker

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(7), P. e0288926 - e0288926

Published: July 21, 2023

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of genetic diversity that it harbors. Research efforts demonstrated considerable fraction within-host variation in is driven by ecological dynamics co-occurring strains belonging same species, suggesting an lens may provide insight into empirical patterns diversity. Indeed, model self-limiting growth and environmental noise known as Stochastic Logistic Model (SLM) was recently shown successfully predict temporal within single host. However, its ability across hosts be tested. In this manuscript I determine whether predictions SLM explain unrelated for 22 common microbial species. Specifically, stationary distribution explains allele frequencies predicts harboring given (i.e., prevalence) sites. The accuracy correlated with independent estimates strain structure, follow statistically similar forms due existence strain-level ecology.

Language: Английский

Citations

8
Smooth functional landscapes in microcosms DOI
Daniel R. Amor

Nature Ecology & Evolution, Journal Year: 2023, Volume and Issue: 7(11), P. 1754 - 1755

Published: Oct. 2, 2023

Language: Английский

Citations

1
Synthetic Ecosystems: From the Test Tube to the Biosphere DOI Creative Commons
Ricard V. Solé,

Victor Maull,

Daniel R. Amor

et al.

ACS Synthetic Biology, Journal Year: 2024, Volume and Issue: 13(12), P. 3812 - 3826

Published: Nov. 21, 2024

The study of ecosystems, both natural and artificial, has historically been mediated by population dynamics theories. In this framework, quantifying numbers related variables (associated with metabolism or biological-environmental interactions) plays a central role in measuring predicting system-level properties. As we move toward advanced technological engineering cells organisms, the possibility bioengineering ecosystems (from gut microbiome to wildlands) opens several questions that will require quantitative models find answers. Here, present comprehensive survey modeling approaches for managing three kinds synthetic sharing presence engineered strains. These include test tube examples hosting relatively low number interacting species, mesoscale closed (or ecospheres), macro-scale, ecosystems. potential outcomes ecosystem designs their limits be relevant different disciplines, including biomedical engineering, astrobiology, space exploration fighting climate change impacts on endangered We propose possible captures broad range scenarios tentative roadmap open problems further exploration.

Language: Английский

Citations

0
A macroecological perspective on genetic diversity in the human gut microbiome DOI Creative Commons
William R. Shoemaker

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: April 9, 2022

Abstract While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of genetic diversity that it harbors. Research efforts demonstrated considerable fraction within-host variation in is driven by ecological dynamics co-occurring strains belonging same species, suggesting an lens may provide insight into empirical patterns diversity. Indeed, model self-limiting growth and environmental noise known as Stochastic Logistic Model (SLM) was recently shown successfully predict temporal within single host. However, its ability across hosts be tested. In this manuscript I determine whether predictions SLM explain unrelated for 22 common microbial species. Specifically, stationary distribution explains allele frequencies predicts harboring given (i.e., prevalence) sites. The accuracy correlated with independent estimates strain structure, follow statistically similar forms due existence strain-level ecology.

Language: Английский

Citations

1
Statistical mechanics of phenotypic eco-evolution: from adaptive dynamics to complex diversification DOI Creative Commons
Matteo Sireci, Miguel A. Muñoz

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: July 23, 2023

The ecological and evolutionary dynamics of large sets individuals can be theoretically addressed using ideas tools from statistical mechanics. This strategy has been in the literature, both context population genetics –whose focus is genes or “genotypes”— adaptive dynamics, putting emphasis on traits “phenotypes”. Following this tradition, here we construct a framework allowing us to derive “macroscopic” equations rather general “microscopic” stochastic representing fundamental processes reproduction, mutation selection community individuals, each one characterized by its phenotypic features. Importantly, our setup, timescales are intertwined, which makes it particularly suitable describe microbial communities, timely topic utmost relevance. Our leads probabilistic description distribution space —even case arbitrarily populations— as encoded what call “generalized Crow-Kimura equation” replicator-mutator equation”. We discuss limits such an equation reduces (deterministic) theory “adaptive dynamics” (i.e. standard approach space. Moreover, emphasize aspects that beyond reach dynamics. In particular, working out, guiding example, simple model growing competing population, show resulting probability exhibit “dynamical phase transitions” changing unimodal bimodal —by means branching— multimodal, cascade branching events. Furthermore, formalism allows rationalize these cascades transitions parsimonious Landau’s transitions. Finally, extend account for finite populations illustrate possible consequences “demographic” effects. Altogether present extends and/or complements existing approaches evolutionary/adaptive paves way more systematic studies e.g. communities well future developments including theoretical analyses process perspective non-equilibrium

Language: Английский

Citations

0