Cooperative growth in microbial communities is a driver of multistability

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: June 3, 2024

Abstract Microbial communities often exhibit more than one possible stable composition for the same set of external conditions. In human microbiome, these persistent changes in species and abundance are associated with health disease states, but drivers alternative states remain unclear. Here we experimentally demonstrate that a cross-kingdom community, composed six relevant to respiratory tract, displays four each dominated by different species. pairwise coculture, observe widespread bistability among pairs, providing natural origin multistability full community. contrast common association between antagonism, experiments reveal many positive interactions within community members. We find multiple display cooperative growth, modeling predicts this could drive observed as well non-canonical outcomes. A biochemical screening reveals glutamate either reduces or eliminates cooperativity growth several species, confirm such supplementation extent across pairs Our findings provide mechanistic explanation how rather competitive can underlie microbial communities.

Language: Английский

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Modeling tumors as complex ecosystems

iScience, Journal Year: 2024, Volume and Issue: 27(9), P. 110699 - 110699

Published: Aug. 10, 2024

Many cancers resist therapeutic intervention. This is fundamentally related to intratumor heterogeneity: multiple cell populations, each with different phenotypic signatures, coexist within a tumor and its metastases. Like species in an ecosystem, cancer populations are intertwined complex network of ecological interactions. Most mathematical models ecology, however, cannot account for such diversity or predict consequences. Here, we propose that the generalized Lotka-Volterra model (GLV), standard tool describe species-rich communities, provides suitable framework ecology heterogeneous tumors. We develop GLV growth discuss how emerging properties provide new understanding disease. potential extensions their application plasticity, cancer-immune interactions, metastatic growth. Our work outlines set questions road map further research ecology.

Language: Английский

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A Non‐Equilibrium Species Distribution Model Reveals Unprecedented Depth of Time Lag Responses to Past Environmental Change Trajectories

Ecology Letters, Journal Year: 2025, Volume and Issue: 28(1)

Published: Jan. 1, 2025

ABSTRACT Previous studies have demonstrated legacy effects of current species distributions to past environmental conditions, but the temporal extent such time lag dynamics remains unknown. Here, we developed a non‐equilibrium Species Distribution Modelling (SDM) approach quantifying that must be taken into account capture 95% effect given series conditions has on distribution species. We applied this 92 European forest birds in response trajectories change cover and climate. found SDMs outperformed traditional for Non‐equilibrium suggest unprecedented long‐lasting global changes (average ranged from 9 231 years). This framework can help relax equilibrium hypothesis improve future predictions biodiversity redistribution changes.

Language: Английский

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Imbalance in gut microbial interactions as a marker of health and disease

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

Imbalances in the human gut microbiome (dysbioses) are linked to multiple diseases but remain poorly understood. Current biomarkers identify dysbiosis inconsistent and fail capture ecological mechanisms differentiating healthy from diseased microbiomes. We propose a general biomarker, inspired by phenomenology observed gut-microbiome theoretical model introduced here. The emergent communities show complex interaction networks two distinct collective states, corresponding dysbiotic Our robust metric for dysbiosis, quantifying balance between cooperation competition, differentiates these states both simulated real datasets across diverse diseases. Moreover, it reveals that results shift toward greater community. further correlates with disease progression, highlighting its potential as diagnostic tool.

Language: Английский

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Alternative cliques of coexisting species in complex ecosystems

Journal of Physics Complexity, Journal Year: 2024, Volume and Issue: 5(2), P. 025022 - 025022

Published: May 24, 2024

Abstract The possibility that some ecosystems can exist in alternative stable states has profound implications for ecosystem conservation and restoration. Current ecological theory on multistability mostly relies few-species dynamical models, which are intrinsically related to specific non-linear dynamics. Recent theoretical advances, however, have shown multiple ‘cliques’—small subsets of coexisting species—can be present species-rich models even under linear interactions. Yet, the mechanisms governing appearence characteristics these cliques remain largely unexplored. In work, we investigate generalized Lotka–Volterra model with mathematical computational techniques. Our findings reveal simple probabilistic constraints explain appearence, properties stability cliques. work contributes understanding complex communities.

Language: Английский

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A simple model of population dynamics with beneficial and harmful interaction networks for empirical applications.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 18, 2024

Abstract Population dynamic models can forecast changes in the abundances of multiple interconnected species, which makes them potentially powerful tools for managing ecological communities, yet they remain largely under-utilised applied settings. High data requirements and ability to only model a narrow range interactions and/or trophic levels together limits their usefulness when faced with complex data-poor systems, where beneficial (e.g. mutualism) harmful competition) may operate simultaneously within between species. We present population dynamics that describe wide interaction outcomes simple, unified structure. Species growth rates are constrained by maximum rate parameter prevents risk explosions even case mutualism. defined two, not mutually-exclusive matrices effects respectively, providing potential net effect one species another switch from as density increases. This recreates classic two-species mutualistic, competitive, predator-prey scenarios, allowing us types same equation. The parameter, theoretically based intrinsic constraints on reproduction, be parameterised sources including natural history, historical data, breeding programs. illustrate this study threatened two interacting predators. new is generaliseable communities. Its structure lowers whilst remaining intuitive biologically realistic, making it an accessible option predicting community-wide contexts sparse uncertain.

Language: Английский

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Unpacking sublinear growth: diversity, stability and coexistence

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 4, 2024

How can many species coexist in natural ecosystems remains a fundamental question ecology. Theory suggests that competition for space and resources should maintain the number of coexisting far below staggering diversity commonly found nature. A recent model finds that, when sublinear growth rates are coupled with competition, stabilize community dynamics. This, turn, is suggested to explain coexistence ecosystems. In this brief note we clarify why (SG) does not solve long standing paradox coexistence. This because SG emerges from an unrealistic property, which per-capita rate diverges at low abundance, preventing ever going extinct. When infinite abundance reconciled more realistic assumptions, recovers expected paradox: increasing leads competitive exclusion extinctions.

Language: Английский

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Unpacking sublinear growth: diversity, stability and coexistence

Oikos, Journal Year: 2024, Volume and Issue: 2025(1)

Published: Dec. 4, 2024

How can so many species coexist in natural ecosystems remains a fundamental question ecology. Classical models suggest that competition for space and resources should maintain the number of coexisting far below staggering diversity commonly found nature. To overcome this paradox, theoretical studies have long highlighted mechanisms favour coexistence, from distribution interaction strengths between to shape population growth functions. In particular, family mathematical finds that, when sublinear (SG) rates are coupled with species, stabilize community dynamics. This could SG may explain stable coexistence ecosystems. Here we clarify why do not solve paradox coexistence. is because, model, emerges an unrealistic property, which per capita tend infinity at low abundance, preventing ever going extinct due competitive exclusion. Infinite abundance be regularized by assuming minimal threshold, goes or follows non‐infinite curves. When done, model recovers classical result: increasing pool leads exclusion extinctions.

Language: Английский

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The interplay of facilitation and competition drives the emergence of multistability in dryland plant communities

Ecology, Journal Year: 2024, Volume and Issue: 105(8)

Published: July 2, 2024

Within communities, species are wrapped in a set of feedbacks with each other and their environment. When such strong enough they can generate alternative stable states. So far, research on states has mostly focused systems small number limited diversity interaction types. Here, we analyze spatial model plant community dynamics stressed ecosystems as drylands, where is characterized by strategy, the different interact through facilitation competition for space resources, water. We identify three types multistability emerging from interplay facilitation. Under low-stress levels, communities organize groups coexisting species, maintained space, ("cliques"). higher stress positive feedback lead to dominance single facilitating ("mutual exclusion states"). At highest left system coexists desert state. By linking ecology theory using ecosystems, our study contributes highlight importance loops stability ecological communities.

Language: Английский

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A method for in silico exploration of potential Glioblastoma Multiforme attractors using single-cell RNA sequencing

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 9, 2024

We presented a method to find potential cancer attractors using single-cell RNA sequencing (scRNA-seq) data. tested our in Glioblastoma Multiforme (GBM) dataset, an aggressive brain tumor presenting high heterogeneity. Using the attractor concept, we argued that GBM's underlying dynamics could partially explain observed heterogeneity, with dataset covering representative region around attractor. Exploratory data analysis revealed promising cellular clusters within 3-dimensional marker space. approximated clusters’ centroid as stable states and each cluster covariance matrix defining confidence regions. To investigate presence of inside regions, constructed GBM gene regulatory network, defined model for dynamics, prepared framework parameter estimation. An exploration hyperparameter space allowed us sample time series intending simulate myriad variations microenvironment. obtained different densities across expression parameters displaying multistability clusters. Although used methodological approach studying GBM, would like highlight its generality other types cancer. Therefore, this report contributes advance simulation opens avenues therapeutic targets.

Language: Английский

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