Abstract
Modeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.
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CITATION STYLE
Song, H.-S., Lee, N.-R., Kessell, A. K., McCullough, H. C., Park, S.-Y., Zhou, K., & Lee, D.-Y. (2024). Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation. MSystems, 9(5). https://doi.org/10.1128/msystems.01305-23
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