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Devadhasan A, Kolodny O, Carja O. Competition for resources can reshape the evolutionary properties of spatial structure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.13.589370. [PMID: 38659847 PMCID: PMC11042312 DOI: 10.1101/2024.04.13.589370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Many evolving ecosystems have spatial structures that can be conceptualized as networks, with nodes representing individuals or homogeneous subpopulations and links the patterns of interaction and replacement between them. Prior models of evolution on networks do not take ecological niche differences and eco-evolutionary interplay into account. Here, we combine a resource competition model with evolutionary graph theory to study how heterogeneous topological structure shapes evolutionary dynamics under global frequency-dependent ecological interactions. We find that the addition of ecological competition for resources can produce a reversal of roles between amplifier and suppressor networks for deleterious mutants entering the population. Moreover, we show that this effect is a non-linear function of ecological niche overlap and discuss intuition for the observed dynamics using simulations and analytical approximations.
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Affiliation(s)
- Anush Devadhasan
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Oren Kolodny
- Department of Ecology, Evolution, and Behavior, E. Silberman Institute of Life Sciences, The Hebrew University of Jerusalem
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
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2
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Goldman DA, Xue KS, Parrott AB, Jeeda RR, Franzese LR, Lopez JG, Vila JCC, Petrov DA, Good BH, Relman DA, Huang KC. Competition for shared resources increases dependence on initial population size during coalescence of gut microbial communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.569120. [PMID: 38076867 PMCID: PMC10705444 DOI: 10.1101/2023.11.29.569120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
The long-term success of introduced populations depends on their initial size and ability to compete against existing residents, but it remains unclear how these factors collectively shape colonization. Here, we investigate how initial population (propagule) size and resource competition interact during community coalescence by systematically mixing eight pairs of in vitro microbial communities at ratios that vary over six orders of magnitude, and we compare our results to a neutral ecological model. Although the composition of the resulting co-cultures deviated substantially from neutral expectations, each co-culture contained species whose relative abundance depended on propagule size even after ~40 generations of growth. Using a consumer-resource model, we show that this dose-dependent colonization can arise when resident and introduced species have high niche overlap and consume shared resources at similar rates. This model predicts that propagule size will have larger, longer-lasting effects in diverse communities in which niche overlap is higher, and we experimentally confirm that strain isolates show stronger dose dependence when introduced into diverse communities than in pairwise co-culture. This work shows how neutral-like colonization dynamics can emerge from non-neutral resource competition and have lasting effects on the outcomes of community coalescence.
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Affiliation(s)
- Doran A. Goldman
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Katherine S. Xue
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Autumn B. Parrott
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Rashi R. Jeeda
- Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Lauryn R. Franzese
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Jaime G. Lopez
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Jean C. C. Vila
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Dmitri A. Petrov
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Benjamin H. Good
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - David A. Relman
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA
| | - Kerwyn Casey Huang
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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3
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. ARXIV 2023:arXiv:2304.10694v3. [PMID: 37131883 PMCID: PMC10153352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R * and species coexistence cones. Here, we extend these arguments by constructing a novel geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically-stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, Massachusetts 02215, USA
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4
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. Phys Rev E 2023; 108:044409. [PMID: 37978666 DOI: 10.1103/physreve.108.044409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/29/2023] [Indexed: 11/19/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R^{*} and species coexistence cones. Here, we extend these arguments by constructing a geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, Massachusetts 02215, USA
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5
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Jops K, O'Dwyer JP. Life history complementarity and the maintenance of biodiversity. Nature 2023:10.1038/s41586-023-06154-w. [PMID: 37286601 DOI: 10.1038/s41586-023-06154-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 05/02/2023] [Indexed: 06/09/2023]
Abstract
Life history, the schedule of when and how fast organisms grow, die and reproduce, is a critical axis along which species differ from each other1-4. In parallel, competition is a fundamental mechanism that determines the potential for species coexistence5-8. Previous models of stochastic competition have demonstrated that large numbers of species can persist over long timescales, even when competing for a single common resource9-12, but how life history differences between species increase or decrease the possibility of coexistence and, conversely, whether competition constrains what combinations of life history strategies complement each other remain open questions. Here we show that specific combinations of life history strategy optimize the persistence times of species competing for a single resource before one species overtakes its competitors. This suggests that co-occurring species would tend to have such complementary life history strategies, which we demonstrate using empirical data for perennial plants.
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Affiliation(s)
- Kenneth Jops
- Department of Plant Biology, University of Illinois, Urbana, IL, USA.
| | - James P O'Dwyer
- Department of Plant Biology, University of Illinois, Urbana, IL, USA.
- Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana, IL, USA.
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6
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.21.537832. [PMID: 37131730 PMCID: PMC10153274 DOI: 10.1101/2023.04.21.537832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze Consumer Resource Models (CRMs) using geometric arguments. This has led to broadly applicable principles such as Tilman's R* and species coexistence cones. Here, we extend these arguments by constructing a novel geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species coexistence and enumerate ecologically-stable steady states and transitions between them. Collectively, these results constitute a qualitatively new way of understanding the role of species traits in shaping ecosystems within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, MA 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, MA 02215, USA
- Biological Design Center, Boston University, Boston, MA 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, MA 02215, USA
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7
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Gibbs T, Zhang Y, Miller ZR, O’Dwyer JP. Stability criteria for the consumption and exchange of essential resources. PLoS Comput Biol 2022; 18:e1010521. [PMID: 36074781 PMCID: PMC9488833 DOI: 10.1371/journal.pcbi.1010521] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 09/20/2022] [Accepted: 08/29/2022] [Indexed: 11/18/2022] Open
Abstract
Models of consumer effects on a shared resource environment have helped clarify how the interplay of consumer traits and resource supply impact stable coexistence. Recent models generalize this picture to include the exchange of resources alongside resource competition. These models exemplify the fact that although consumers shape the resource environment, the outcome of consumer interactions is context-dependent: such models can have either stable or unstable equilibria, depending on the resource supply. However, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig’s law, where species require and deplete multiple resources, but each consumer’s growth rate is only limited by a single one of these resources. Resources that are taken up but not incorporated into new biomass are leaked back into the environment, possibly transformed by intracellular reactions, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns derived analytically apply to a broader class of network structures and resource inflow profiles, including cases where multiple species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when resource limitation and exchange are modeled directly.
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Affiliation(s)
- Theo Gibbs
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- * E-mail:
| | - Yifan Zhang
- Department of Plant Biology, University of Illinois, Urbana, Illinois, United States of America
| | - Zachary R. Miller
- Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America
| | - James P. O’Dwyer
- Department of Plant Biology, University of Illinois, Urbana, Illinois, United States of America
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8
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van den Berg NI, Machado D, Santos S, Rocha I, Chacón J, Harcombe W, Mitri S, Patil KR. Ecological modelling approaches for predicting emergent properties in microbial communities. Nat Ecol Evol 2022; 6:855-865. [PMID: 35577982 PMCID: PMC7613029 DOI: 10.1038/s41559-022-01746-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 03/23/2022] [Indexed: 12/20/2022]
Abstract
Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.
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Affiliation(s)
| | - Daniel Machado
- Department of Biotechnology and Food Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sophia Santos
- Centre of Biological Engineering, University of Minho, Braga, Portugal
| | - Isabel Rocha
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
| | - Jeremy Chacón
- Ecology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA
| | - William Harcombe
- Ecology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA
| | - Sara Mitri
- Département de Microbiologie Fondamentale, University of Lausanne, Lausanne, Switzerland
| | - Kiran R Patil
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.
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9
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Estrela S, Vila JCC, Lu N, Bajić D, Rebolleda-Gómez M, Chang CY, Goldford JE, Sanchez-Gorostiaga A, Sánchez Á. Functional attractors in microbial community assembly. Cell Syst 2022; 13:29-42.e7. [PMID: 34653368 PMCID: PMC8800145 DOI: 10.1016/j.cels.2021.09.011] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Revised: 06/02/2021] [Accepted: 09/21/2021] [Indexed: 01/21/2023]
Abstract
For microbiome biology to become a more predictive science, we must identify which descriptive features of microbial communities are reproducible and predictable, which are not, and why. We address this question by experimentally studying parallelism and convergence in microbial community assembly in replicate glucose-limited habitats. Here, we show that the previously observed family-level convergence in these habitats reflects a reproducible metabolic organization, where the ratio of the dominant metabolic groups can be explained from a simple resource-partitioning model. In turn, taxonomic divergence among replicate communities arises from multistability in population dynamics. Multistability can also lead to alternative functional states in closed ecosystems but not in metacommunities. Our findings empirically illustrate how the evolutionary conservation of quantitative metabolic traits, multistability, and the inherent stochasticity of population dynamics, may all conspire to generate the patterns of reproducibility and variability at different levels of organization that are commonplace in microbial community assembly.
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Affiliation(s)
- Sylvie Estrela
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA.
| | - Jean C C Vila
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Nanxi Lu
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Djordje Bajić
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Maria Rebolleda-Gómez
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Chang-Yu Chang
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Joshua E Goldford
- Physics of Living Systems, Massachusetts Institute of Technology, Boston, MA 02139, USA
| | - Alicia Sanchez-Gorostiaga
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA; Department of Microbial Biotechnology, Centro Nacional de Biotecnología, CSIC, UAM Cantoblanco, 28049 Madrid, Spain
| | - Álvaro Sánchez
- Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA.
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10
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Liu R, Liu G. Complex dynamics of a stochastic uni-directional consumer-resource mutualism system. ECOLOGICAL COMPLEXITY 2021. [DOI: 10.1016/j.ecocom.2021.100965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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11
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Gupta D, Garlaschi S, Suweis S, Azaele S, Maritan A. Effective Resource Competition Model for Species Coexistence. PHYSICAL REVIEW LETTERS 2021; 127:208101. [PMID: 34860037 DOI: 10.1103/physrevlett.127.208101] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 07/26/2021] [Accepted: 10/06/2021] [Indexed: 06/13/2023]
Abstract
Local coexistence of species in large ecosystems is traditionally explained within the broad framework of niche theory. However, its rationale hardly justifies rich biodiversity observed in nearly homogeneous environments. Here we consider a consumer-resource model in which a coarse-graining procedure accounts for a variety of ecological mechanisms and leads to effective spatial effects which favor species coexistence. Herein, we provide conditions for several species to live in an environment with very few resources. In fact, the model displays two different phases depending on whether the number of surviving species is larger or smaller than the number of resources. We obtain conditions whereby a species can successfully colonize a pool of coexisting species. Finally, we analytically compute the distribution of the population sizes of coexisting species. Numerical simulations as well as empirical distributions of population sizes support our analytical findings.
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Affiliation(s)
- Deepak Gupta
- Dipartimento di Fisica e Astronomia Galileo Galilei, Università degli Studi di Padova, via Marzolo 8, 35131 Padova, Italy
- Department of Physics, Simon Fraser University, Burnaby, British Columbia V5A1S6, Canada
| | - Stefano Garlaschi
- Dipartimento di Fisica e Astronomia Galileo Galilei, Università degli Studi di Padova, via Marzolo 8, 35131 Padova, Italy
| | - Samir Suweis
- Dipartimento di Fisica e Astronomia Galileo Galilei, Università degli Studi di Padova, via Marzolo 8, 35131 Padova, Italy
| | - Sandro Azaele
- Dipartimento di Fisica e Astronomia Galileo Galilei, Università degli Studi di Padova, via Marzolo 8, 35131 Padova, Italy
| | - Amos Maritan
- Dipartimento di Fisica e Astronomia Galileo Galilei, Università degli Studi di Padova, via Marzolo 8, 35131 Padova, Italy
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12
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Estrela S, Sánchez Á, Rebolleda-Gómez M. Multi-Replicated Enrichment Communities as a Model System in Microbial Ecology. Front Microbiol 2021; 12:657467. [PMID: 33897672 PMCID: PMC8062719 DOI: 10.3389/fmicb.2021.657467] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/15/2021] [Indexed: 12/21/2022] Open
Abstract
Recent advances in robotics and affordable genomic sequencing technologies have made it possible to establish and quantitatively track the assembly of enrichment communities in high-throughput. By conducting community assembly experiments in up to thousands of synthetic habitats, where the extrinsic sources of variation among replicates can be controlled, we can now study the reproducibility and predictability of microbial community assembly at different levels of organization, and its relationship with nutrient composition and other ecological drivers. Through a dialog with mathematical models, high-throughput enrichment communities are bringing us closer to the goal of developing a quantitative predictive theory of microbial community assembly. In this short review, we present an overview of recent research on this growing field, highlighting the connection between theory and experiments and suggesting directions for future work.
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Affiliation(s)
- Sylvie Estrela
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, United States
| | - Álvaro Sánchez
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, United States
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