Sample Non-destructive Cell Evaluation Technology

Intracellular proteins and metabolites emit autofluorescence of various wavelengths and intensities. The autofluorescence pattern, which is formed by the synthesis of respective autofluorescence, functions as a "fingerprint" that expresses the properties of each cell. In the CRIF method,¹ the information on cell position and morphology is obtained by reflection microscopy,^2,3 and cellular autofluorescence information is obtained by confocal laser microscopy. Then, by performing image analysis for each cell, the CRIF systematically and comprehensively extracts autofluorescence information for each cell, and reconstructs the information as an autofluorescence pattern. Thus, a "cell's fingerprint" that identifies each cell can be obtained. Moreover, it has been clarified that the application of the "cells' fingerprints" to various types of machine learning enables the construction of a machine learning model that reflects each cell's underlying characteristics in the autofluorescence pattern, and also enables high-accuracy identification of cell types and prediction of the metabolic state. As this method uses the autofluorescence emitted by cells, no special treatment, such as the introduction of fluorescent protein-expressing genes or staining, is required. In other words, the properties of intact living cells can be analyzed. Conventional methods using fluorescent protein labeling require complicated gene manipulation to track specific cells and monitor gene expression. On the other hand, the CRIF method is expected to identify cells with the targeted properties in an extremely simple manner. Moreover, due to the use of a confocal platform, this method can be applied to the analysis of a three-dimensional space, enabling the evaluation of the properties of cells that constitute three-dimensional structures, such as colonies and biofilms. Thus, by linking the information on the cell to spatial information, this method is expected to contribute to the discovery of new knowledge.

Strengths in the Industrial Arena

Since the CRIF method is a simple method that can analyze the properties of intact living cells at the single cell level, it is considered to be a key technology that improves the efficiency of the cell property evaluation, which is essential for cell breeding technologies in various fields, such as microorganisms, plants and animals, stem cell differentiation induction technologies, and technologies for the synthesis of artificial cells. By actively communicating with various research institutions and companies, we aim to establish the CRIF as a highly versatile technology so that it can be used in a wide variety of fields from basic research in various fields to applied research on, for example, regenerative medicine, in the future.