Identification of the keystone species in non-alcoholic fatty liver disease by causal inference and dynamic intervention modeling

ObjectiveKeystone species are required for the integrity and stability of an ecological community, and therefore, are potential intervention targets for microbiome related diseases. DesignHere we describe an algorithm for the identification of keystone species from cross-sectional microbiome data of non-alcoholic fatty liver disease (NAFLD) based on causal inference theories and dynamic intervention modeling (DIM). ResultsEight keystone species in the gut of NAFLD, represented by P. loveana, A. indistinctus and D. pneumosintes, were identified by our algorithm, which could efficiently restore the microbial composition of the NAFLD toward a normal gut microbiome with 92.3% recovery. These keystone species regulate intestinal amino acids metabolism and acid-base environment to promote the growth of the butyrate-producing Lachnospiraceae and Ruminococcaceae species. ConclusionOur method may benefit microbiome studies in the broad fields of medicine, environmental science and microbiology. SUMMARYWhat is already known about this subject? O_LINon-alcoholic fatty liver disease (NAFLD) is a complex multifactorial disease whose pathogenesis remains unclear. C_LIO_LIDysbiosis in the gut microbiota affects the initiation and development of NAFLD, but the mechanisms is yet to be established. C_LIO_LIKeystone species represent excellent candidate targets for gut microbiome-based interventions, as they are defined as the species required for the integrity and stability of the ecological system. C_LI What are the new findings? O_LINAFLD showed significant dysbiosis in butyrate-producing Lachnospiraceae and Ruminococcaceae species. C_LIO_LIMicrobial interaction networks were constructed by the novel algorithm with causal inference. C_LIO_LIKeystone species were identified form microbial interaction networks through dynamic intervention modeling based on generalized Lotka-Volterra model. C_LIO_LIEight keystone species of NAFLD with the highest potential for restoring the microbial composition were identified. C_LI How might it impact on clinical practice in the foreseeable future? O_LIAn algorithm for the identification of keystone species from cross-sectional microbiome data based on causal inference theories and dynamic intervention modeling. C_LIO_LIEight keystone species in the gut of NAFLD, represented by P. loveana, A. indistinctus and D. pneumosintes, which could efficiently restore the microbial composition of the NAFLD toward a normal gut microbiome. C_LIO_LIOur method may benefit microbiome studies in the broad fields of medicine, environmental science and microbiology. C_LI