Global epistasis and the emergence of function in microbial consortia

Cell, Год журнала: 2024, Номер 187(12), С. 3108 - 3119.e30

Опубликована: Май 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.

Язык: Английский

---

Universal abundance fluctuations across microbial communities, tropical forests, and urban populations

Proceedings of the National Academy of Sciences, Год журнала: 2023, Номер 120(44)

Опубликована: Окт. 24, 2023

The growth of complex populations, such as microbial communities, forests, and cities, occurs over vastly different spatial temporal scales. Although research in fields has developed detailed, system-specific models to understand each individual system, a unified analysis populations is lacking; an could deepen our understanding system facilitate cross-pollination tools insights across fields. Here, we use shared framework analyze time-series data the human gut microbiome, tropical forest, urban employment. We demonstrate that single, three-parameter model stochastic population dynamics can reproduce empirical distributions abundances fluctuations all three datasets. parameters characterizing species measure its mean abundance, deterministic stability, stochasticity. Our reveals that, despite vast differences scale, systems occupy similar region parameter space when time measured generations. In other words, although observed these may appear different, this difference primarily due physical timescales associated with system. Further, show distribution abundance described by just two derive two-parameter functional form for improve risk estimation forecasting.

Язык: Английский

---

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes

Proceedings of the National Academy of Sciences, Год журнала: 2023, Номер 120(48)

Опубликована: Ноя. 22, 2023

Microbiome engineering offers the potential to leverage microbial communities improve outcomes in human health, agriculture, and climate. To translate this into reality, it is crucial reliably predict community composition function. But a brute force approach cataloging function hindered by combinatorial explosion number of ways we can combine species. An alternative parameterize using simplified, mechanistic models, then extrapolate these models beyond where have sampled. approaches remain data-hungry, as well requiring an priori specification what kinds mechanisms are included which omitted. Here, resolve both issues introducing mechanism-agnostic predicting compositions functions limited data. The critical step identification sparse representation landscape. We sparsity functions, drawing from techniques compressive sensing. validate on silico data, generated theoretical model. By sampling just ∼ 1% all possible communities, accurately out sample. demonstrate real-world application our applying four experimental datasets showing that recover interpretable, accurate predictions highly

Язык: Английский

---

Pulsed, continuous or somewhere in between? Resource dynamics matter in the optimisation of microbial communities

The ISME Journal, Год журнала: 2023, Номер 17(4), С. 641 - 644

Опубликована: Янв. 24, 2023

Abstract The optimisation of synthetic and natural microbial communities has vast potential for emerging applications in medicine, agriculture industry. Realising this goal is contingent on a close correlation between theory, experiments, the real world. Although temporal pattern resource supply can play major role community assembly, dynamics are commonly treated inconsistently theoretical experimental research. Here we explore how composition varies under continuous supply, typical approaches, versus pulsed experiments. Using simulations classical competition models, show that diverges rapidly two regimes, with almost zero overlap once pulsing interval stretches beyond just four hours. implication growing field regime must be tailored to being optimised. As such, argue should considered both constraint design novel as tuning mechanism pre-existing like those found human gut.

Язык: Английский

---

The Nonlinear Dynamics and Chaos Control of Pricing Games in Group Robot Systems

Entropy, Год журнала: 2025, Номер 27(2), С. 164 - 164

Опубликована: Фев. 4, 2025

System stability control in resource allocation is a critical issue group robot systems. Against this backdrop, study investigates the nonlinear dynamics and chaotic phenomena that arise during pricing games among finitely rational robots proposes strategies to mitigate behaviors. A system model business for are developed based on market mechanism mapping, of formulated as second-order discrete using game theory. Numerical simulations reveal small perturbations parameters, such adjustment speed, product demand coefficients, substitution can induce To address these phenomena, method combining state feedback parameter proposed. This approach dynamically tunes intensity via M, thereby delaying bifurcations suppressing It ensures distribution eigenvalues satisfies conditions, allowing over unstable periodic orbits period-doubling bifurcations. Simulation results demonstrate proposed effectively delays stabilizes attractors. The system's Nash equilibrium significantly improved, range expanded. These findings provide essential theoretical foundations practical guidance design application

Язык: Английский

---

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

Current Opinion in Microbiology, Год журнала: 2025, Номер 83, С. 102580 - 102580

Опубликована: Янв. 22, 2025

Язык: Английский

---

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

Frontiers in Synthetic Biology, Год журнала: 2025, Номер 3

Опубликована: Март 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.

Язык: Английский

---

Functional convergence in slow-growing microbial communities arises from thermodynamic constraints

The ISME Journal, Год журнала: 2023, Номер 17(9), С. 1482 - 1494

Опубликована: Июнь 28, 2023

The dynamics of microbial communities is complex, determined by competition for metabolic substrates and cross-feeding byproducts. Species in the community grow harvesting energy from chemical reactions that transform to products. In many anoxic environments, these are close thermodynamic equilibrium growth slow. To understand structure energy-limited we developed a consumer-resource model incorporating energetic constraints on an interconnected network. central element product inhibition, meaning may be limited not only depletion but also accumulation We demonstrate additional cause convergence function network-independent species composition biochemical details-providing possible explanation despite taxonomic variation observed natural industrial environments. Furthermore, discovered network governed principle maximum free dissipation. Our results predict decrease functional faster growing communities, which validate analyzing experimental data anaerobic digesters. Overall, work demonstrates how universal principles constrain metabolism explain communities.

Язык: Английский

---

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Апрель 13, 2023

Microbiome engineering offers the potential to lever-age microbial communities improve outcomes in human health, agriculture, and climate. To translate this into reality, it is crucial reliably predict community composition function. But a brute force approach cataloguing function hindered by combinatorial explosion number of ways we can combine species. An alternative parameterize using simplified, mechanistic models, then extrapolate these models beyond where have sampled. approaches remain data-hungry, as well requiring an priori specification what kinds mechanism are included which omitted. Here, resolve both issues introducing new, mechanism-agnostic predicting compositions functions limited data. The critical step discovery sparse representation landscape. We leverage sparsity functions, drawing from techniques compressive sensing. validate on silico data, generated theoretical model. By sampling just ∼ 1% all possible communities, accurately out sample. demonstrate real-world application our applying four experimental datasets, showing that recover interpretable, accurate predictions highly

Язык: Английский

---

The Architecture of Theory and Data in Microbiome Design: towards an S-matrix for microbiomes

Опубликована: Авг. 9, 2024

Designing microbiomes for applications in health, bioengineering, and sustainability is intrinsically linked to a fundamental theoretical understanding of the rules governing microbial community assembly. Microbial ecologists have used range mathematical models understand, predict, control microbiomes, ranging from mechanistic models, putting populations their interactions as focus, purely statistical approaches, searching patterns empirical experimental data. We review success limitations these modeling approaches when designing novel especially guided by (inevitably) incomplete Although successful at predicting generic assembly, phenomenological tend fall short precision needed design implement specific functionality microbiome. argue that effectively with optimal functions diverse environments, should combine data-driven techniques models---a middle, third way using theory inform design.

Язык: Английский

---