Molecular Medicine and Cell Biology
Outline of Research and Education
The cellular membrane is the essential component of cells that distinguishes the inside and the outside of cells. While the membrane receives all of the stimulus affecting the cells, how it behaves is not well understood. Our lab focuses on the membrane-binding proteins connecting the membrane to the intracellular signaling for varieties of cellular functions including proliferation and morphological changes, using biochemical, cell biological, biophysical, and information techniques. The roles of lipid composition of the membrane, including the saturation or unsaturation of fatty acids, are examined using the membrane-binding proteins.
Major Research Topics
Elucidating cell-shape dependent intracellular signaling
The intracellular signaling cascade became understood by observing molecule-molecule interactions. However, the spatial organization of these signaling cascades had not been studied so well. We found the BAR domain superfamily proteins that remodel membrane shape and then, presumably, dictate the intracellular signaling cascades. Thus, the important questions are how the BAR domain superfamily proteins are regulated, and how they assemble the downstream molecules.
Searching for new membrane binding proteins
Given the importance of membrane lipids as essential components of cells, we suppose there are many lipid-binding molecules that have not been clarified. We are searching for novel lipid-binding proteins using a variety of methods.
The importance of fatty acids in the membrane.
Another point for understanding the cellular membrane is the importance of fatty-acid tails of lipids. Although the importance of saturated or unsaturated lipids in nutrients is well-known, the mechanism of importance is not understood in molecular levels in cell biology. We will examine how fatty acids are important in intracellular signaling including that for cancer, using the proteins listed above.
Information science for cell biology
Image analysis using deep learning enables the recognition of the features stipulated by researchers. Such image analysis will reveal previously unrecognized features of protein localization for cellular morphology and will relate the cell morphology to cellular functions.
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