APCTP
Design Principles of Cellular Networks APCTP Junior Research Groups
http://www.apctp.org/?JrgId=13
 
Group Introduction
Contact & Members
Research Focus
Publications
MEMOLOG
 
 
■ Research Focus


Endocrine cell network

The islets of Langerhans, embedded within the pancreas, play a crucial role in maintaining blood glucose levels constant by secreting the counter-regulatory hormones, insulin and glucagon. Glucose homeostasis is important for brain function. Persistent elevation of glucose levels is by definition diabetes, an increasingly common metabolic disease. The islet micro-organ consists mainly of endocrine α, β, and δ cells. Although these components are differentiated from the same progenitor, α and β cells play opposite roles: at low glucose levels, α cells secrete glucagon to increase glucose levels, while at high glucose levels, β cells secrete insulin to decrease glucose levels. It seems that two counter-regulatory components are sufficient to control (increase/decrease) glucose levels. The role of somatostatin-secreting δ cells for glucose homeostasis is still a mystery. Recent evidence suggests that the interactions between these endocrine cells play important roles for the control of glucose levels.

     Considering cellular interactions within a single islet, the spatial organization of α, β, and δ cells may have functional implications. Interestingly, different species have different architectures (cellular composition and arrangement) of islets for the glucose control. However, the islet size range (clusters of a few cells to several thousand cells) is similar across species having very different body sizes, suggesting the existence of an optimal islet size. In mice, β cells are located in the islet core, while non-β cells are located on the periphery. In contrast, human islets have more α cells (20-30% vs. 10-15% in mouse islets), and non-β cells are distributed throughout islets.

     Based on the previous research on cellular interactions and islet architectures, our group plans to develop a mathematical model of the cellular network of α, β, and δ cells, and find structure-function relations in the system design for controlling homeostasis.


Neural networks

The nervous and immune systems rely on cellular communications to a much larger extent than other physiological systems. Motivated by the study of neuronal connections, neural networks have been proposed to learn certain tasks. Recent studies have reported that neural networks in the brain are scale-free or small-world networks, as widely observed in biological and social networks. Hub neurons, that have a particularly large number of connections in a scale-free network, may play a role for an optimal integration of signals. Our group plans to examine adaptability of neural networks depending on their architecture.


Evolution of cellular networks

I turn now to the question: How can the endocrine and neural networks evolve to have such robust and adaptable functions? We may find the answer in the evolution of gene regulatory networks in which nodes represent genes, while weighted edges between nodes represent interactions between genes. Here the network design is encoded in a DNA sequence. Therefore, mutations in the DNA sequence result in the modification of gene regulatory networks. Note that while mutations occur in 1-dimensional sequences, phenotypes (networks) meet evolutionary pressure from environment, leading to natural selection of the random mutations based on their fitness to environment. To survive evolution, they must be robust (tolerant) to small changes in a given environment as well as evolvable to new environments. Our group plans to find the mechanism how cellular networks can develop to have these two features of robustness and evolvability.

 
 

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