Research Interests
Studying biological systems based on heterogeneity
Biological systems consist of heterogeneity, and they work based on the heterogeneity. For example, distributions of the number of molecules or cells in the systems determine the states of higher biological organization-from cells and tissues up to organisms. I am interested in visualizing the distributions and network in them (e.g., cell-cell network) by accurate system-wide measurements with single molecule, single base, and/or single cell resolution. This approach may provide significant insights in also medical science and diseases since, for example, at the onset of a disease, homeostasis is not destroyed simultaneously in an entire population of cells, but instead starts at the single cell level. Highly sensitive measurements of these phenomena may contribute to an early diagnosis, which may provide preventive care for the patients. Moreover, finding differences between individuals by accurate measurements will contribute to the personalization of care.
In our laboratory, the first aim is usually to develop new techniques to "see" something unknown, in order to understand biological systems as described. Secondly, we often collaborate with biologists and/or medical scientists to contribute to medical sciences and our understanding of diseases. Concretely, we have been focusing on counting copy number of RNA molecules genome-wide in a digital manner, and on identifying each cell and counting the number of cells by determining genomic DNA sequences at the single cell and single base resolution.
Our targets are organoids, immune cells, microbiota, and others.
I had been working on single molecule observation of molecular motors by optical microscopy, and have jumped into genomics research field. Based on these experiences,
we are making a new platform which enables to combine imaging and sequencing. Using this system,
we are studying, e.g., the coordination dynamics between cell division and differentiation which are essential process for multi cellular organisms.
Shiroguchi lab（RIKEN HP)
Project
Integration of bio-imaging, sequencing, and machine learning (DECODE project)
Organoids, stem cells
Cell-Cell interaction
Molecular barcodes for digital quantification of nucleic acid molecules