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Watanabe, L.

Publications and source records attributed to Watanabe, L..

2 recordsLinked to original sources

Murine model of antibiotic-associated S. aureus gastrointestinal infections (SAGII) and colonization

BackgroundStaphylococcus aureus is an opportunistic pathogen that can both colonize the gastrointestinal tract and cause antibiotic associated diarrhea. MethodsTo develop a robust murine model for S. aureus gastrointestinal infection (SAGII) and colonization, mice were (a) treated with varying antibiotic regimes prior to infection, (b) infected with either a methicillin-sensitive S. aureus (MSSA) or a methicillin-resistant S. aureus (MRSA) strain, (c) challenged with different bacterial inocula, (d) tested for sexual dimorphism of SAGII virulence, and (e) tested for macronutrient effects on SAGII onset and virulence. ResultsWe found that antibiotic-treated male mice (but not female mice) were highly susceptible to even low inoculums of both an MSSA and an MRSA strains. Interestingly, male mice challenged with an MSSA strain showed more severe and more prolonged SAGII symptomatology than animals challenged with an MRSA strain. We also showed that for male mice a high-carbohydrate diet and a high-fat diet led to asymptomatic intestinal colonization followed by delayed SAGII sign onset. In contrast, male mice fed a high-protein diet started developing mild SAGII signs early but did not develop severe SAGII until two weeks post-challenge. Furthermore, only the high-protein diet sensitized female mice to SAGII, but their symptomatology remained less severe than in male mice. ConclusionsWe developed a robust murine model for antibiotic-associated S. aureus gastrointestinal infection and colonization. This model shows both sexual dimorphism and macronutrient preference for SAGII severity. Diet manipulation can also be used to establish S. aureus colonization of the GI tract.

microbiology↗

Dynamic Flux Balance Analysis Models in SBML

Computational models in systems biology and systems medicine are typically simulated using a single formalism such as ordinary differential equations (ODE). However, more complex models require the coupling of multiple formalisms since different biological phenomena are better described by different methods. For example, metabolism in steady state is often modeled using flux-balance analysis (FBA) whereas dynamic changes of model components are better described via ODEs. The coupling of FBA and ODE modeling formalisms results in dynamic FBA models. A major challenge is how to describe such hybrid models that couple multiple formalisms in a standardized way so that they can be exchanged between tools and simulated consistently in a reproducible manner. This paper presents a scheme for encoding and implementation of dynamic FBA models in the Systems Biology Markup Language (SBML), thereby enabling the exchange of multi-framework computational models between software tools. We demonstrate the feasibility of the approach using various example models and show that different tools are able to simulate the hybrid models and agree on the results. As part of this work, two independent implementations of a multi-framework simulation method for dynamic FBA have been developed supporting such models: iBioSim and sbmiutils.

bioinformatics↗