ArticleFrontiers in microbiology2015
Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure.
Article in Frontiers in microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Synthetic Microbial Cocultivation for Targeted Production of Odd-Chain Carboxylates and Alcohols from Carbon Monoxide.Environmental science & technology · 2025Article
- A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry.Nature communications · 2025Article
- Effects of thermophilic and acidophilic microbial consortia on maize wet-milling steeping.Bioresources and bioprocessing · 2024Article
- Upgrading dilute ethanol to odd-chain carboxylic acids by a synthetic co-culture of Anaerotignum neopropionicum and Clostridium kluyveri.Biotechnology for biofuels and bioproducts · 2023Article
- A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures.Bioengineering (Basel, Switzerland) · 2023Article
- Systematizing Microbial Bioplastic Production for Developing Sustainable Bioeconomy: Metabolic Nexus Modeling, Economic and Environmental Technologies Assessment.Journal of polymers and the environment · 2023Review
- Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society, Interface · 2022Review
- Species abundance correlations carry limited information about microbial network interactions.PLoS computational biology · 2022Article
- NetCom: A Network-Based Tool for Predicting Metabolic Activities of Microbial Communities Based on Interpretation of Metagenomics Data.Microorganisms · 2021Article
- Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities.Genes · 2021Article
- Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data.Microorganisms · 2021Review
- Article
- Formation, characterization and modeling of emergent synthetic microbial communities.Computational and structural biotechnology journal · 2021Article
- Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence.PLoS computational biology · 2020Article
- Modeling a co-culture ofComputational and structural biotechnology journal · 2020Article
- From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes.Computational and structural biotechnology journal · 2020Review
- Modelling microbial communities using biochemical resource allocation analysis.Journal of the Royal Society, Interface · 2019Article
- Metabolic modelling of chronic wound microbiota predicts mutualistic interactions that drive community composition.Journal of applied microbiology · 2019Article
- Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges.Journal of industrial microbiology & biotechnology · 2019Review
- Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity.Frontiers in microbiology · 2019Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbial communities play important roles in health, industrial applications and earth's ecosystems. With current molecular techniques we can characterize these systems in unprecedented detail. However, such methods provide little mechanistic insight into how the genetic properties and the dynamic couplings between individual microorganisms give rise to their dynamic activities. Neither do they give insight into what we call "the community state", that is the fluxes and concentrations of nutrients within the community. This knowledge is a prerequisite for rational control and intervention in microbial communities. Therefore, the inference of the community structure from experimental data is a major current challenge. We will argue that this inference problem requires mathematical models that can integrate heterogeneous experimental data with existing knowledge. We propose that two types of models are needed. Firstly, mathematical models that integrate existing genomic, physiological, and physicochemical information with metagenomics data so as to maximize information content and predictive power. This can be achieved with the use of constraint-based genome-scale stoichiometric modeling of community metabolism which is ideally suited for this purpose. Next, we propose a simpler coarse-grained model, which is tailored to solve the inference problem from the experimental data. This model unambiguously relate to the more detailed genome-scale stoichiometric models which act as heterogeneous data integrators. The simpler inference models are, in our opinion, key to understanding microbial ecosystems, yet until now, have received remarkably little attention. This has led to the situation where the modeling of microbial communities, using only genome-scale models is currently more a computational, theoretical exercise than a method useful to the experimentalist.
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