Assumptions on decision making and environment can yield multiple steady states in microbial community models
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Date
2023-06-22
Publication Type
Journal Article
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yes
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Abstract
Background
Microbial community simulations using genome scale metabolic networks (GSMs) are relevant for many application areas, such as the analysis of the human microbiome. Such simulations rely on assumptions about the culturing environment, affecting if the culture may reach a metabolically stationary state with constant microbial concentrations. They also require assumptions on decision making by the microbes: metabolic strategies can be in the interest of individual community members or of the whole community. However, the impact of such common assumptions on community simulation results has not been investigated systematically.
Results
Here, we investigate four combinations of assumptions, elucidate how they are applied in literature, provide novel mathematical formulations for their simulation, and show how the resulting predictions differ qualitatively. Our results stress that different assumption combinations give qualitatively different predictions on microbial coexistence by differential substrate utilization. This fundamental mechanism is critically under explored in the steady state GSM literature with its strong focus on coexistence states due to crossfeeding (division of labor). Furthermore, investigating a realistic synthetic community, where the two involved strains exhibit no growth in isolation, but grow as a community, we predict multiple modes of cooperation, even without an explicit cooperation mechanism.
Conclusions
Steady state GSM modelling of microbial communities relies both on assumed decision making principles and environmental assumptions. In principle, dynamic flux balance analysis addresses both. In practice, our methods that address the steady state directly may be preferable, especially if the community is expected to display multiple steady states.
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published
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Journal / series
Volume
24 (Supplement 1)
Pages / Article No.
262
Publisher
BioMed Central
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Subject
Microbial communities; Flux balance analysis; Game theory
Organisational unit
03699 - Stelling, Jörg / Stelling, Jörg
Notes
Funding
177164 - Intermicrobial and host-microbial interactions that determine the trajectory of mammalian microbial colorization in early life (SNF)