Integrative Metabolic Modelling of Bacterial Systems in Microbiome Contexts: From Genomes to Community Functions

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Microbiomes".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 1158

Special Issue Editor


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Guest Editor
Department of Science, Roma Tre University, Rome, Italy
Interests: microbiome; metabolic modelling; bioinformatics

Special Issue Information

Dear Colleagues,

The rapid growth of multi-omics and metagenomic data is transforming our understanding of microbiomes across natural, clinical, and industrial environments. In this evolving landscape, metabolic modelling of individual bacterial strains and microbial communities has become a key tool for linking genomic potential to ecological and functional roles. This Special Issue invites original research articles and reviews that explore the integration of genome-scale metabolic models (GEMs) within microbiome research. We particularly welcome studies focused on the reconstruction of metabolic networks, phenotype prediction, simulation of interspecies interactions, and the rational design of synthetic consortia. Contributions that combine experimental data, computational approaches, artificial intelligence, or automated genome annotation and pathway prediction tools are highly encouraged. Topics of interest include, but are not limited to, metabolic modelling of bacteria isolated from complex environments (e.g., soil, gut, marine ecosystems); integrated approaches for model construction from metagenomes and MAGs (metagenome-assembled genomes); computational exploration of cross-feeding and trophic interactions within microbial communities; experimental validation of in silico predictions in natural or synthetic microbiomes; development of bioinformatics tools to automate metabolic modelling in microbiome studies.

Dr. Arianna Basile
Guest Editor

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Keywords

  • microbiome
  • multi-omics
  • microbial communities
  • metabolic modelling
  • bioinformatics tools

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Published Papers (1 paper)

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Review

25 pages, 762 KB  
Review
From Single Organisms to Communities: Modeling Methanotrophs and Their Satellites
by Maryam A. Esembaeva, Ekaterina V. Melikhova, Vladislav A. Kachnov and Mikhail A. Kulyashov
Microorganisms 2026, 14(1), 3; https://doi.org/10.3390/microorganisms14010003 - 19 Dec 2025
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Abstract
Aerobic methanotrophs mediate methane oxidation contributing to a major biological sink that limits CH4 release to the atmosphere in oxygenated environments and serve as promising platforms for biotechnological applications. In natural and engineered environments, these bacteria rarely exist in isolation but form [...] Read more.
Aerobic methanotrophs mediate methane oxidation contributing to a major biological sink that limits CH4 release to the atmosphere in oxygenated environments and serve as promising platforms for biotechnological applications. In natural and engineered environments, these bacteria rarely exist in isolation but form stable associations with heterotrophic satellites that utilize methanotrophic metabolites, remove inhibitory intermediates, and provide essential growth factors. Such interactions enhance methane oxidation efficiency and community stability, yet the metabolic mechanisms underlying them remain poorly resolved. This review summarizes current knowledge on both natural and synthetic aerobic methanotrophic consortia, focusing on the composition, functions, and biotechnological relevance of satellite microorganisms. We systematically examine available mathematical frameworks—from ecological and statistical models to genome-scale metabolic reconstructions and dynamic flux balance analysis—applied to methanotrophs and their satellites. Our analysis reveals that while genome-scale metabolic models have been developed for model heterotrophic species, only a few correspond to experimentally identified methanotroph satellites, and community-level reconstructions remain limited. The lack of curated and experimentally validated models restricts the predictive power of current approaches. Addressing these limitations will require not only targeted reconstruction of satellite metabolism, but also the combined use of complementary computational methods followed by experimental verification. Such an integrative strategy will be essential for understanding methanotrophic community organization and function and, more broadly, other microbial consortia with complex metabolic interactions. Addressing these limitations through targeted reconstruction of satellite metabolism and integration of existing models will be key to advancing quantitative understanding of methanotrophic community organization and function. Full article
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