ArticlePLoS computational biology2014
Emergent biosynthetic capacity in simple microbial communities.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
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- COmmunity and Single Microbe Optimisation System (COSMOS).NPJ systems biology and applications · 2025Article
- GEM-based computational modeling for exploring metabolic interactions in a microbial community.PLoS computational biology · 2024Article
- Predicting microbial interactions with approaches based on flux balance analysis: an evaluation.BMC bioinformatics · 2024Article
- Plant Growth-Promoting Bacteria of Soil: Designing of Consortia Beneficial for Crop Production.Microorganisms · 2023Review
- Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta.PLoS biology · 2023Article
- Competition for nutrients increases invasion resistance during assembly of microbial communities.Molecular ecology · 2022Article
- A compendium of predicted growths and derived symbiotic relationships between 803 gut microbes in 13 different diets.Current research in microbial sciences · 2022Article
- Metaproteomics reveals methyltransferases implicated in dichloromethane and glycine betaine fermentation by 'Frontiers in microbiology · 2022Article
- Deciphering metabolism, one microbe at a time.Nature · 2021Article
- Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021Review
- Article
- Modelling microbial communities: Harnessing consortia for biotechnological applications.Computational and structural biotechnology journal · 2021Review
- Observational
- Multi-faceted approaches to discovering and predicting microbial nutritional interactions.Current opinion in biotechnology · 2020Review
- Therapeutic microbes to tackle disease.Nature · 2020Article
- μBialSim: Constraint-Based Dynamic Simulation of Complex Microbiomes.Frontiers in bioengineering and biotechnology · 2020Article
- Defining and Evaluating Microbial Contributions to Metabolite Variation in Microbiome-Metabolome Association Studies.mSystems · 2019Article
- AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data.BMC bioinformatics · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Microbes have an astonishing capacity to transform their environments. Yet, the metabolic capacity of a single species is limited and the vast majority of microorganisms form complex communities and join forces to exhibit capabilities far exceeding those achieved by any single species. Such enhanced metabolic capacities represent a promising route to many medical, environmental, and industrial applications and call for the development of a predictive, systems-level understanding of synergistic microbial capacity. Here we present a comprehensive computational framework, integrating high-quality metabolic models of multiple species, temporal dynamics, and flux variability analysis, to study the metabolic capacity and dynamics of simple two-species microbial ecosystems. We specifically focus on detecting emergent biosynthetic capacity--instances in which a community growing on some medium produces and secretes metabolites that are not secreted by any member species when growing in isolation on that same medium. Using this framework to model a large collection of two-species communities on multiple media, we demonstrate that emergent biosynthetic capacity is highly prevalent. We identify commonly observed emergent metabolites and metabolic reprogramming patterns, characterizing typical mechanisms of emergent capacity. We further find that emergent secretion tends to occur in two waves, the first as soon as the two organisms are introduced, and the second when the medium is depleted and nutrients become limited. Finally, aiming to identify global community determinants of emergent capacity, we find a marked association between the level of emergent biosynthetic capacity and the functional/phylogenetic distance between community members. Specifically, we demonstrate a "Goldilocks" principle, where high levels of emergent capacity are observed when the species comprising the community are functionally neither too close, nor too distant. Taken together, our results demonstrate the potential to design and engineer synthetic communities capable of novel metabolic activities and point to promising future directions in environmental and clinical bioengineering.
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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.