The impact of Traditional Chinese Medicine on mouse gut microbiota abundances and interactions based on Granger causality and pathway analysis - Zhang, Yi; Zhang, Dahan; Bai, Xiaogang; Chen, Yang; Qiu, Qinwei; Shang, Xiaoxiao; Deng, Yusheng; Yang, Hongyan; Fang, Xiaodong; Yang, Zhimin; Han, Lijuan (Frontiers in Microbiology, 2022)
Objectives Intestinal microbiota plays important roles in absorbing nutrients and defending pathogens, and is related to various diseases such as obesity, type 2 diabetes, hypertension, etc. As an alternative medicine, Traditional Chinese Medicine (TCM) has long been used in diseases treatment and health care, probably by mediating gut microbiota. However, the exact specific effects of TCM on abundances and interactions of microbiota are still unknown. Moreover, based on data of TCM ingredients and gut microorganism alterations, here we developed bioinformatics methods that help to decipher TCM impact on interactions of microbiota. Methods We use mouse model to understand dynamical alterations of 70 gut microorganisms upon 9 kinds of TCM treatments by time series data. Granger causality analysis is used to measure microorganism interactions. Moreover, novel “serial connection” and “diverging connection” models are used to suggest molecular mechanisms underlying the impact of TCM on gut microorganism interactions, based on microorganism gene product proteins, TCM chemical ingredients and KEGG reaction equations. Results Codonopsis pilosula (Dang shen), Cassia twig (Gui zhi), Radices saussureae (Mu xiang) and Sijunzi Decoction do not increase the abundance of any negative microorganisms. Most TCM decrease the abundance of Bifidobacterium_pseudolongum, suggesting Bifidobacterium_pseudolongum should be supplied during TCM treatment. Granger causality analysis indicated TCM treatment changes over half interactions between 70 microorganisms, “serial connection” and “diverging connection” models suggest interaction change may be related with reaction number connecting species protein and TCM ingredients. From the aspect of species diversity, TCM decocotion is better rather than single herb for health care. Sijunzi decoction only significantly increases the abundance of Bifidobacterium_pseudolongum, and never decreases any species abundance, but can improve alpha diversity with the lowest replacement speed. Conclusions Since most of the 9 kinds of TCMs are medicinal and edible plants, we expect the methods and results can optimize and integrate microbiota and TCMs in health care. Meanwhile, as a control study, these results can be combined with future disease case mouse model to find which species abundance variation are derived from disease.