Quantitative experimental characterization and mathematical modeling of mixed culture dynamics

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Traditional laboratory methods rely on pure cultures for strain characterization, limiting the ability to apply findings to mixed species environments. This limitation stems from insufficient understanding of interaction mechanisms within communities and their external environments. For instance, competition can be direct, through interference, or indirect, via resource competition, such as sharing substrates. To study mixed cultures effectively, monitoring population dynamics and quantifying cell numbers and metabolites is essential. Despite theoretical models addressing mixed culture dynamics, practical studies in laboratories have been scarce due to the lack of cell quantification methods and protocols for defined mixed cultivations. Consequently, quantitative data validating these models, especially involving more than two species, is limited. Research on bacterial population dynamics with absolute cell counts exceeding two species is particularly rare. This work aims to establish a methodology for the quantitative analysis of a mixed bacterial culture comprising at least three species, focusing on identifying interactions among species with unknown growth characteristics. A novel approach was employed, comparing experimental results with model simulations using selected strains from the CF context as a model mixed culture.