MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Bucci, Vanni; Tzen, Belinda; Li, Ning; Simmons, Matt; Tanoue, Takeshi; Bogart, Elijah; Deng, Luxue; Yeliseyev, Vladimir; Delaney, Mary; Liu, Qing; Olle, Bernat; Stein, Richard; Honda, Kenya; Bry, Lynn; Gerber, Georg
• Is Part Of: Genome biology. Volume 17:Issue 1(2016)
• Page Start: 1
• Page End: 17
• Publication Date: 2016-12
• Subjects: Genomes -- Periodicals; Biology -- Periodicals; Molecular biology -- Periodicals; 572.8633
• DOI: 10.1186/s13059-016-0980-6
• Languages: English
• ISSNs: 1474-760X

Abstract

Abstract Predicting dynamics of host-microbial ecosystems is crucial for the rational design of bacteriotherapies. We present MDSINE, a suite of algorithms for inferring dynamical systems models from microbiome time-series data and predicting temporal behaviors. Using simulated data, we demonstrate that MDSINE significantly outperforms the existing inference method. We then show MDSINE's utility on two new gnotobiotic mice datasets, investigating infection withClostridium difficile and an immune-modulatory probiotic. Using these datasets, we demonstrate new capabilities, including accurate forecasting of microbial dynamics, prediction of stable sub-communities that inhibit pathogen growth, and identification of bacteria most crucial to community integrity in response to perturbations.