Global epistasis and the emergence of function in microbial consortia

Cell, Journal Year: 2024, Volume and Issue: 187(12), P. 3108 - 3119.e30

Published: May 21, 2024

The many functions of microbial communities emerge from a complex web interactions between organisms and their environment. This poses significant obstacle to engineering consortia, hindering our ability harness the potential microorganisms for biotechnological applications. In this study, we demonstrate that collective effect ecological microbes in community can be captured by simple statistical models predict how adding new species will affect its function. These predictive mirror patterns global epistasis reported genetics, they quantitatively interpreted terms pairwise members. Our results illuminate an unexplored path predicting function consortia composition, paving way optimizing desirable properties bringing tasks biological at genetic, organismal, scales under same quantitative formalism.

Language: Английский

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Competition for shared resources increases dependence on initial population size during coalescence of gut microbial communities

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(11)

Published: March 10, 2025

The long-term success of introduced populations depends on both their initial size and ability to compete against existing residents, but it remains unclear how these factors collectively shape colonization dynamics. Here, we investigate population (propagule) shapes the outcome community coalescence by systematically mixing eight pairs in vitro microbial communities at ratios that vary over six orders magnitude, compare our results neutral ecological theory. Although composition resulting cocultures deviated substantially from expectations, each coculture contained species whose relative abundance depended propagule even after ~40 generations growth. Using a consumer–resource model, show this dose-dependent can arise when resident have high niche overlap consume shared resources similar rates. Strain isolates displayed longer-lasting dose dependence into diverse than pairwise cocultures, consistent with model’s prediction should larger, more persistent effects communities. Our model also successfully predicted resource-utilization profiles, as inferred growth spent media untargeted metabolomics, would stronger coculture. This work demonstrates transient, dynamics emerge resource competition exert outcomes coalescence.

Language: Английский

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Emergent predictability in microbial ecosystems

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

Published: March 29, 2024

Microbial ecosystems carry out essential functions for global climate, human health, and industry. These complex communities exhibit a surprising amount of functionally relevant diversity at all levels taxonomic resolution, presenting significant challenge most modeling frameworks. A long-standing hope theoretical ecology is that some patterns might persist despite community complexity – or perhaps even emerge because it. deeper understanding such “emergent simplicity” could enable new approaches predicting the behaviors in nature. However, examples described so far afford limited predictive power, as they focused on reproducibility rather than prediction. Here, we propose an information-theoretic framework defining, nuancing quantifying emergent simplicity empirical data based ability simple models to predict community-level functional properties. Applying this two published datasets, demonstrate majority properties measured across both experiments robust evidence predictability: surprisingly, richness increases, compositional descriptions become more predictive. We show behavior not typical within standard frameworks ecology, argue improving our control natural microbial will require shift focus: away from , towards prediction ecosystems.

Language: Английский

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Assembly Graph as the Rosetta Stone of Ecological Assembly

Environmental Microbiology, Journal Year: 2025, Volume and Issue: 27(1)

Published: Jan. 1, 2025

Ecological assembly-the process of ecological community formation through species introductions-has recently seen exciting theoretical advancements across dynamical, informational, and probabilistic approaches. However, these theories often remain inaccessible to non-theoreticians, they lack a unifying lens. Here, I introduce the assembly graph as an integrative tool connect emerging theories. The visually represents dynamics, where nodes symbolise combinations edges represent transitions driven by introductions. Through lens graphs, review how processes reduce uncertainty in random arrivals (informational approach), identify graphical properties that guarantee coexistence examine class dynamical models constrain topology graphs (dynamical quantify transition probabilities with incomplete information (probabilistic approach). To facilitate empirical testing, also methods decompose complex into smaller, measurable components, well computational tools for deriving graphs. In sum, this math-light progress aims catalyse research towards predictive understanding assembly.

Language: Английский

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Towards synthetic ecology: strategies for the optimization of microbial community functions

Frontiers in Synthetic Biology, Journal Year: 2025, Volume and Issue: 3

Published: March 18, 2025

Microbial communities are able to carry out myriad functions of biotechnological interest, ranging from the degradation industrial waste synthesis valuable chemical products. Over past years, several strategies have emerged for design microbial and optimization their functions. Here we provide an accessible overview these strategies. We highlight how principles synthetic biology, originally devised engineering individual organisms sub-organismal units (e.g., enzymes), influenced development field ecology. With this, aim encourage readers critically evaluate insights biology should guide our approach community-level engineering.

Language: Английский

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Hypergraph reconstruction from dynamics

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 19, 2025

Abstract A plethora of methods have been developed in the past two decades to infer underlying network structure an interconnected system from its collective dynamics. However, capable inferring nonpairwise interactions are only starting appear. Here, we develop inference algorithm based on sparse identification nonlinear dynamics (SINDy) reconstruct hypergraphs and simplicial complexes time-series data. Our model-free method does not require information about node or coupling functions, making it applicable complex systems that do a reliable mathematical description. We first benchmark new synthetic data generated Kuramoto Lorenz then use effective connectivity brain resting-state EEG data, which reveals significant contributions non-pairwise shaping macroscopic

Language: Английский

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High fecal indicator bacteria in temperate headwater streams at baseflow: implications for management and public health

Water Research X, Journal Year: 2025, Volume and Issue: unknown, P. 100347 - 100347

Published: April 1, 2025

Language: Английский

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The architecture of theory and data in microbiome design: towards an S-matrix for microbiomes

Current Opinion in Microbiology, Journal Year: 2025, Volume and Issue: 83, P. 102580 - 102580

Published: Jan. 22, 2025

Language: Английский

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The sparse macroecology of microbiology

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(5)

Published: Jan. 22, 2024

Micro-nano plastics originating from the prevalent usage of have raised increasingly alarming concerns worldwide. However, there remains a fundamental knowledge gap in nanoplastics because lack effective analytical ...Plastics are now omnipresent our daily lives. The existence microplastics (1 µm to 5 mm length) and possibly even (<1 μm) has recently health concerns. In particular, believed be more toxic since their ...

Language: Английский

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An evolution-based framework for describing human gut bacteria

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

Published: Dec. 5, 2023

Abstract The human gut microbiome contains many bacterial strains of the same species (‘strain-level variants’). Describing in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to genetic complexity strain-level variation. Here, we measured patterns co-evolution across >7,000 spanning tree-of-life. Using these as prior for studying hundreds commensal that isolated, sequenced, and metabolically profiled revealed widespread structure beneath phylogenetic level species. Defining by their co-evolutionary signatures enabled predicting metabolic phenotypes engineering consortia from strain genome content alone. Our findings demonstrate relevant organization variation motivate new schema describing based on evolutionary history. One Sentence Summary statistical model captures history provides insight into biology.

Language: Английский

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