Abstract
We present a novel methodology to construct a Boolean dynamic model from time series metagenomic information and integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic underpinnings for microbial interactions. We apply this in the context of a critical health issue: clindamycin antibiotic treatment and opportunistic Clostridium difficile infection. Our model recapitulates known dynamics of clindamycin antibiotic treatment and C. difficile infection and predicts therapeutic probiotic interventions to suppress C. difficile infection. Genome-scale metabolic network reconstructions reveal metabolic differences between community members and are used to explore the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of our computational model, that B. intestinihominis can in fact slow C. difficile growth.
Highlights
Human health is inseparably connected to the billions of microbes that live in and on us
The community of bacteria that live in our intestines is important to normal intestinal function, and destruction of this community has a causative role in diseases including obesity, diabetes, and even neurological disorders
Clostridum difficile is an opportunistic pathogenic bacterium that causes potentially life-threatening intestinal inflammation and diarrhea and frequently occurs after antibiotic treatment, which wipes out the normal intestinal bacterial community
Summary
Human health is inseparably connected to the billions of microbes that live in and on us. Microbial community composition often persists for years without significant change [5]. The generally accepted paradigm is that antibiotic treatment (or some other perturbation) significantly disrupts the microbial community structure in the gut, which creates a void that C. difficile will subsequently fill [7,8,9,10]. Such infections occur in roughly 600,000 people in the United States each year (this number is on the rise), with an associated mortality rate of 2.3% [11]. An altered gut flora has further been identified as a causal factor in obesity, diabetes, some cancers and behavioral disorders [12,13,14,15,16,17]
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