Computational Biology Group／Intra-University Cooperative LaboratoriesKuroda Laboratory
(Systems Biology, BS)
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Professor KURODA Shinya
Our research is aimed to the understanding of the features of signaling pathways and examining them as a type of “channel”for communication to the extracellular environment. In particular,we first proposed the concept of“temporal information coding,”which embed information to the time pattern of molecular activation. Since information processing is performed through the molecular interactions too complex to understand with conventional methods we therefore create models that replicate the behavior of signaling pathway by the cooperation and feedback between simulation models and the actual measurements of cell behavior (Fig. 1).
- Research
keywords - Systems biology, trans-omics, metabolism, diabetes
Mechanisms of cell fate determination
Signal transduction networks including ERK elicit multiple cellular functions. One of the critical properties of the signal transduction system is that the same signaling net-works can code multiple cellular functions. We have recently found that the distinct temporal coding of ERK signaling networks regulate cell growth and differentiation in PC12 cells in response to EGF and NGF. We are currently trying to explore the decoding mechanism of distinct temporal patterns of ERK activation via downstream molecular networks.
Fig.2 Temporal coding of insulin action
Trans-omics of insullin action
We explored signal flows of insulin,an important hormone for metabolic homeostasis. We reconstructed the static signal flow of insulin based on time-series phosphoproteome and metabolome data together with multiple databases and found where an insulin signal flowed through a global transomic network. We analysed the dynamic signal flow using kinetic modelling together with model selection and model reduction, and found when specific phosphorylation and allosteric regulation selectively control temporal patterns of metabolites. Thus, we demonstrate a global landscape for the signal flow of insulin, which reveals the large-scale mechanism of metabolic homeostasis.
Sytems biology requires fundamental knowledge from a wide variety of fields, including the life sciences, physics, information science,and mathematics. We therefore do our best to maintain a multidisciplinary research staff with highly diverse backgrounds.
Fig.3 The large-scale trans-omic networks
