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Multiple roles of the NF-B signaling pathway regulated by coupled negative feedback circuits

Dongsan Kim^*, Walter Kolch^, and Kwang-Hyun Cho^*,1

^* Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea;

Beatson Institute for Cancer Research, Cancer Research UK, Glasgow, UK; and

Integrative and Systems Biology, University of Glasgow, Glasgow, UK

¹ Correspondence: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea. E-mail: ckh{at}kaist.ac.kr

ABSTRACT

The NF-B signaling pathway can perform multiple functional roles depending on specific cellular environments and cell types. Even in the same cell clones, the pathway can show different kinetic and phenotypic properties. It is believed that the complex networks controlling the NF-B signaling pathway can generate these diverse and sometimes ambiguous phenomena. We noted, however, that the dynamics of NF-B signaling pathway is highly stochastic and that the NF-B signaling pathway contains multiple negative feedback circuits formed by IB isoform proteins, IB and IB in particular. Considering the topological similarity, their functional roles seem to be redundant, raising the question why different types of IB isoforms need to exist. From extensive stochastic simulations of the NF-B signaling pathway, we found that each IB isoform actually conducts a different regulatory role through its own negative feedback. Specifically, our data suggest that IB controls the dynamic patterns of nuclear NF-B, while IB induces cellular heterogeneity of the NF-B activities. These results may provide an answer to the question of how a single NF-B signaling pathway can perform multiple biological functions even in the same clonal populations.—Kim, D., Kolch, W., Cho, K.-H. Multiple roles of the NF-B signaling pathway regulated by coupled negative feedback circuits.

Key Words: heterogeneity • oscillations • stochastic simulations • systems biology • mathematical model • design principle