Laboratory of Signal Transduction
Our research interest is on fundamental theories and concepts of eukaryotic cells. For this purpose, we use the budding yeast Saccharomyces cerevisiae as a model organism, using bioimaging technology and cell biology techniques. Multivariate analysis with morphological data provided high-dimensional phenotypic information of all individual mutant strains of the budding yeast. Comprehensive analysis of mutant strains revealed new genetic dogmas, discovered close relationships between gene function and morphological phenotype, elucidated new gene functions, classified mutant strains by clustering based on the morphological information. We have conducted target prediction and identification of compounds. We are also interested in the mechanism of autophagy, which is an intracellular degradation system, by combining bioimaging technology and cell biological analysis methods, taking advantage of the characteristics of model eukaryotic cells.
The research projects currently underway are as follows.
(1) Mechanism of autophagy
We are conducting research on autophagy using S. cerevisiae as a model system of eukaryotic cells. The interesting phenomenon is that the process of autophagosome formation proceeds with a very characteristic and dynamic membrane formation. Considering the physiological significance of autophagy, the important question to ask is what is decomposed by autophagy. We study these issues using morphological methods such as optical microscopes and electron microscopes.
(2) Identification of drug targets using morphological profiling
We are developing drug discovery tools using S. cerevisiae. Specifically, we recently developed the morphological profiling technique useful to predict intracellular target of the compounds. We perform (1) target prediction of new antifungal agents and (2) identification of mode of action of new antifungal agents.
(3) Genome editing of sake yeast
Using the genome editing technology of CRISPR-Cas9, we are breeding sake yeast based on preexisting evidence. By investigating changes in cell morphology during breeding, we are also studying whether cell morphology can provide useful information during breeding.
(4) Monitoring and control of fermentation using morphological information
Yeast produces many fermented products such as ethanol and has been widely used in the fermentation industry. There is a great demand to understand the state of yeast cells during the fermentation process. Therefore, we are proposing to monitor the activity of yeast cells by analyzing the yeast morphology. We are also developing a new AI-based technique to forecast and control the fermenting products based on the morphology data.
(5) Analysis of yeast cell morphology using intelligent image active cell sorting (iIACS)
iIACS is a flow cytometer that sorts cells based on image information, which was developed in the Goda Laboratory of the Graduate School of Science in 2018. Using iIACS, we are researching whether high-throughput morphological analysis of yeast can be performed using this iIACS. Ultimately, we are aiming to create a new yeast using morphological information, which is named “Super Yeast 2020 Project”.
(6) Study of the mechanism of haploinsufficiency
Haploinsufficiency is a phenomenon in which a deletion mutation in the heterozygous diploid results in obvious phenotype. We are currently studying the property of the haploinsufficient genes in morphology as well as the conditions under which haploinsufficiency is likely to occur.
(7) Comprehensive analysis of morphological phenotypes using an image analysis program
To understand biological system as the network of logical and informational process, one of the invaluable tools is genetics. Global analysis of the yeast mutant phenotypes can provide relationships between knockout of the gene and function in the network. We developed CalMorph image analysis system useful to examine high-dimensional quantitative phenotypes under the fluorescence microscope.
Our goal is to place all yeast genes and their corresponding products on a functional network based on phenotyping.