School of Materials Science and Engineering, Georgia Institute of Technology, 30332, USA.
Lab Chip. 2017 Aug 8;17(16):2861-2872. doi: 10.1039/c7lc00451f.
Studying cell behavior within 3D material niches is key to understanding cell biology in health and diseases, and developing biomaterials for regenerative medicine applications. Current approaches to studying these cell-material niches have low throughput and can only analyze a few replicates per experiment resulting in reduced measurement assurance and analytical power. Here, we report 3D material cytometry (3DMaC), a novel high-throughput method based on microfabricated, shape-specific 3D cell-material niches and imaging cytometry. 3DMaC achieves rapid and highly multiplexed analyses of very high replicate numbers ("n" of 10-10) of 3D biomaterial constructs. 3DMaC overcomes current limitations of low "n", low-throughput, and "noisy" assays, to provide rapid and simultaneous analyses of potentially hundreds of parameters in 3D biomaterial cultures. The method is demonstrated here for a set of 85 000 events containing twelve distinct cell-biomaterial micro-niches along with robust, customized computational methods for high-throughput analytics with potentially unprecedented statistical power.
研究 3D 材料龛内的细胞行为对于理解健康和疾病中的细胞生物学以及开发用于再生医学应用的生物材料至关重要。目前研究这些细胞-材料龛的方法通量低,每个实验只能分析几个重复,导致测量保证和分析能力降低。在这里,我们报告了 3D 材料细胞计量术(3DMaC),这是一种基于微加工、形状特异性 3D 细胞-材料龛和成像细胞计量术的新型高通量方法。3DMaC 实现了非常高的重复数(“n”为 10-10)的 3D 生物材料构建体的快速和高度多重分析。3DMaC 克服了当前低“n”、低通量和“嘈杂”测定的限制,为 3D 生物材料培养物中的潜在数百个参数提供了快速和同时的分析。该方法在这里针对一组包含十二个不同细胞-生物材料微龛的 85,000 个事件进行了演示,同时还提供了强大的、定制的高通量分析计算方法,具有潜在的前所未有的统计能力。