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• W2993676783 abstract "The generalized Lotka-Volterra (gLV) equations are a mathematical proxy for ecological dynamics. We focus on a gLV model of the gut microbiome, in which the evolution of the gut microbial state is determined in part by pairwise inter-species interaction parameters that encode environmentally-mediated resource competition between microbes. We develop an in silico method that controls the steady-state outcome of the system by adjusting these interaction parameters. This approach is confined to a bistable region of the gLV model. The two steady states of interest are idealized as either a healthy or diseased steady state of the gut microbiome. In this method, a dimensionality reduction technique called steady-state reduction (SSR) is first used to generate a two-dimensional (2D) gLV model that approximates the high-dimensional dynamics on the 2D subspace spanned by the two steady states. Then a bifurcation analysis of the 2D model analytically determines parameter modifications that drive a disease-prone initial condition to the healthy steady state. This parameter modification of the reduced 2D model guides parameter modifications of the original high-dimensional model, resulting in a change of steady-state outcome in the high-dimensional model. This control method, called SPARC (SSR-guided parameter change), bypasses the computational challenge of directly determining parameter modifications in the original high-dimensional system. SPARC could guide the development of indirect bacteriotherapies, which seek to change microbial compositions by deliberately modifying gut environmental variables such as gut acidity or macronutrient availability." @default.
• W2993676783 created "2019-12-13" @default.
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• W2993676783 date "2020-05-06" @default.
• W2993676783 modified "2023-10-14" @default.
• W2993676783 title "Control of ecological outcomes through deliberate parameter changes in a model of the gut microbiome" @default.
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• W2993676783 doi "https://doi.org/10.1103/physreve.101.052402" @default.
• W2993676783 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32575322" @default.
• W2993676783 hasPublicationYear "2020" @default.
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