Comparison of Cell Arrays and Multi-Well Plates in Microscopy-Based Screening.

Q2 Biochemistry, Genetics and Molecular Biology
High-Throughput Pub Date : 2018-05-15 DOI:10.3390/ht7020013
Ann-Kristin Becker, Holger Erfle, Manuel Gunkel, Nina Beil, Lars Kaderali, Vytaute Starkuviene
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引用次数: 3

Abstract

Multi-well plates and cell arrays enable microscopy-based screening assays in which many samples can be analysed in parallel. Each of the formats possesses its own strengths and weaknesses, but reference comparisons between these platforms and their application rationale is lacking. We aim to fill this gap by comparing two RNA interference (RNAi)-mediated fluorescence microscopy-based assays, namely epidermal growth factor (EGF) internalization and cell cycle progression, on both platforms. Quantitative analysis revealed that both platforms enabled the generation of data with the appearance of the expected phenotypes significantly distinct from the negative controls. The measurements of cell cycle progression were less variable in multi-well plates. The result can largely be attributed to higher cell numbers resulting in less data variability when dealing with the assay generating phenotypic cell subpopulations. The EGF internalization assay with a uniform phenotype over nearly the whole cell population performed better on cell arrays than in multi-well plates. The result was achieved by scoring five times less cells on cell arrays than in multi-well plates, indicating the efficiency of the cell array format. Our data indicate that the choice of the screening platform primarily depends on the type of the cellular assay to achieve a maximum data quality and screen efficiency.

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细胞阵列和多孔板在显微镜筛选中的比较。
多孔板和细胞阵列使显微镜为基础的筛选分析,其中许多样品可以并行分析。每种格式都有自己的优点和缺点,但是缺乏这些平台及其应用程序基本原理之间的参考比较。我们的目标是通过比较两种RNA干扰(RNAi)介导的基于荧光显微镜的检测,即表皮生长因子(EGF)内化和细胞周期进展,在两个平台上填补这一空白。定量分析显示,这两个平台都能够产生与阴性对照显著不同的预期表型外观的数据。在多孔板中,细胞周期进程的测量变化较小。结果可以在很大程度上归因于较高的细胞数量导致较少的数据变异性,当处理产生表型细胞亚群的分析。在几乎整个细胞群中具有统一表型的EGF内化试验在细胞阵列上比在多孔板上表现得更好。该结果是通过在细胞阵列上比在多孔板上少记录五倍的细胞来实现的,这表明细胞阵列格式的效率。我们的数据表明,筛选平台的选择主要取决于细胞分析的类型,以实现最大的数据质量和筛选效率。
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
High-Throughput
High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
9 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
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