Development of a Data-mining System for Differential Profiling of Cell Glycoproteins Based on Lectin Microarray

Abstract

Cell-based regeneration therapies have great potential for application in new areas in clinical medicine, although some obstacles still remain to be overcome for a wide range of clinical applications. One major impediment is the difficulty in large-scale production of cells of interest with reproducibility. Current protocols of cell therapy require a time-consuming and laborious manual process. To solve this problem, we focused on the robotics of an automated and high-throughput cell culture system. Automated robotic cultivation of stem or progenitor cells in clinical trials has not been reported till date. The system AutoCulture® used in this study can automatically replace the culture medium, centrifuge cells, split cells, and take photographs for morphological assessment. We examined the feasibility of this system in a clinical setting. We observed similar characteristics by both the culture methods in terms of the growth rate, gene expression profile, cell surface profile by fluorescence-activated cell sorting, surface glycan profile, and genomic DNA stability. These results indicate that AutoCulture® is a feasible method for the cultivation of human cells for regenerative medicine. An automated cell-processing machine will play important roles in cell therapy and have widespread use from application in multicenter trials to provision of off-the-shelf cell products.