Ecological Modeling from Time-Series Inference: Insight into Dynamics and Stability of Intestinal Microbiota

By Richard R. Stein, V. Bucci, Nora C. Toussaint, C. Buffie, Gunnar Rätsch, Eric G. Pamer, Christopher Sander, João B. Xavier. PLoS Comput. Biol., 2013

621 citations recorded by the source corpus.

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka–Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli.

View Paper: https://www.semanticscholar.org/paper/27e44e21b24856f0fbb1e94827eac98238e996ef

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Citations in the corpus

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review (2014, background): “[103] extended the gLV equations by adding additional term describing the effect of environmental variations, i.”
Deciphering microbial interactions and detecting keystone species with co-occurrence networks (2014, background): “They have been applied as representations of microbial communities in diverse environments (Mounier et al., 2008; Rodriguez-Brito et al., 2010; Stein et al., 2013) as well as macroecological communities (Case, 2000).”
Numerical implementation of dynamical mean field theory for disordered systems: application to the Lotka–Volterra model of ecosystems (2019, background): “‖ The scaling with S of § Recent works on the inference of the interaction matrix from experiments have been carried out for the gut microbiome in [19, 20].”