ObjectivesThe intestinal microbiota is essential in absorbing nutrients and defending against pathogens and is associated with various diseases, including obesity, type 2 diabetes, and hypertension. As an alternative medicine, Traditional Chinese Medicine (TCM) has long been used in disease treatment and healthcare, partly because it may mediate gut microbiota. However, the specific effects of TCM on the abundance and interactions of microbiota remain unknown. Moreover, using TCM ingredients and data detailing changes in the abundance of gut microorganisms, we developed bioinformatic methods that decipher the impact of TCM on microorganism interactions. MethodsThe dynamics of gut microorganisms affected by TCM treatments is explored using a mouse model, which provided the abundance of 70 microorganisms over time. The Granger causality analysis was used to measure microorganism interactions. Novel "serial connection" and "diverging connection" models were used to identify molecular mechanisms underlying the impact of TCM on gut microorganism interactions, based on microorganism proteins, TCM chemical ingredients, and KEGG reaction equations. ResultsCodonopsis pilosula (Dangshen), Cassia twig (Gui Zhi), Radices saussureae (Mu Xiang), and Sijunzi Decoction did not cause an increase in the abundance of harmful microorganisms. Most TCMs decreased the abundance of Bifidobacterium pseudolongum, suggesting a Bifidobacterium pseudolongum supplement should be used during TCM treatment. The Granger causality analysis indicated that TCM treatment changes more than half the interactions between the 70 microorganisms, and "serial connection" and "diverging connection" models suggested that changes in interactions may be related to the reaction number connecting species proteins and TCM ingredients. From a species diversity perspective, a TCM decoction is better than a single herb for healthcare. The Sijunzi Decoction only significantly increased the abundance of Bifidobacterium pseudolongum and did not cause a decrease in the abundance of other species but was found to improve the alpha diversity with the lowest replacement rate. ConclusionsBecause most of the nine TCMs are medicinal and edible plants, we expect the methods and results presented can be used to optimize and integrate microbiota and TCMs into healthcare processes. Moreover, as a control study, these results can be combined with future disease mouse models to link variations in species abundance with particular diseases.