ArticlePLoS computational biology2023
Ecological landscapes guide the assembly of optimal microbial communities.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Novel artificial selection method improves function of simulated microbial communities.PLoS computational biology · 2026Article
- A foundation model for microbial growth dynamics.bioRxiv : the preprint server for biology · 2025Article
- The Nonlinear Dynamics and Chaos Control of Pricing Games in Group Robot Systems.Entropy (Basel, Switzerland) · 2025Article
- Deterministic succession patterns in the rumen and fecal microbiome associate with host metabolic shifts in peripartum dairy cattle.GigaScience · 2025Article
- Synthetic communities as a model for determining interactions between a biofertilizer chassis organism and native microbial consortia.The ISME journal · 2025Article
- Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Universal abundance fluctuations across microbial communities, tropical forests, and urban populations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Functional convergence in slow-growing microbial communities arises from thermodynamic constraints.The ISME journal · 2023Article
- Pulsed, continuous or somewhere in between? Resource dynamics matter in the optimisation of microbial communities.The ISME journal · 2023Article
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Authors and funding
2 authors.
Funding
Abstract
Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.