Droplet Microarray Based on Superhydrophobic-Superhydrophilic Patterns for Single Cell Analysis.

Microarrays Pub Date : 2016-12-09 DOI:10.3390/microarrays5040028

Gabriella E Jogia, Tina Tronser, Anna A Popova, Pavel A Levkin

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引用次数: 27

Abstract

Single-cell analysis provides fundamental information on individual cell response to different environmental cues and is a growing interest in cancer and stem cell research. However, current existing methods are still facing challenges in performing such analysis in a high-throughput manner whilst being cost-effective. Here we established the Droplet Microarray (DMA) as a miniaturized screening platform for high-throughput single-cell analysis. Using the method of limited dilution and varying cell density and seeding time, we optimized the distribution of single cells on the DMA. We established culturing conditions for single cells in individual droplets on DMA obtaining the survival of nearly 100% of single cells and doubling time of single cells comparable with that of cells cultured in bulk cell population using conventional methods. Our results demonstrate that the DMA is a suitable platform for single-cell analysis, which carries a number of advantages compared with existing technologies allowing for treatment, staining and spot-to-spot analysis of single cells over time using conventional analysis methods such as microscopy.

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基于超疏水-超亲水模式的微滴芯片单细胞分析。

单细胞分析提供了个体细胞对不同环境信号反应的基本信息，在癌症和干细胞研究中越来越受到关注。然而，目前现有的方法仍然面临着以高通量方式进行此类分析同时具有成本效益的挑战。在这里，我们建立了微滴阵列(DMA)作为高通量单细胞分析的小型筛选平台。采用有限稀释、改变细胞密度和播种时间的方法，优化了单细胞在DMA上的分布。我们在DMA上建立了单个液滴中单细胞的培养条件，获得了接近100%的单细胞存活率，单细胞的培养时间与传统方法在大细胞群中培养的细胞相当。我们的研究结果表明，DMA是一个适合单细胞分析的平台，与现有技术相比，它具有许多优势，可以使用传统的分析方法(如显微镜)对单细胞进行处理、染色和点对点分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Microarrays

自引率

0.00%

发文量

审稿时长

11 weeks

期刊介绍： High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.