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Trypan blue as an affordable marker for automated live-dead cell analysis in image cytometry
Scanning ( IF 1.750 ) Pub Date : 2016-06-29 , DOI: 10.1002/sca.21335
Susanne Melzer 1 , Celio Siman Mafra Nunes 2 , Denise Coutinho Endringer 2 , Tadeu Uggere de Andrade 2 , Attila Tarnok 1 , Dominik Lenz 2
Affiliation  

The aim of the present study was to combine image cytometry and trypan blue (TB) exclusion staining for a reproducible high-throughput detection of dead cells, enabling TB as an inexpensive marker, to be affordable for many studies and creating the possibility to combine fluorochromes without or with less spectral overlap. Capillary blood was drawn from a healthy volunteer, red blood cells were lysed and leukocyte cell death was induced. Samples were stained with CD45-FITC, CD14-PE, TB and DAPI, and then analyzed using image cytometry (iCys). TB quenching control tests were performed using DAPI and CD45-FITC. Images were generated in .TIF and .JPEG format using iCys image cytometer. The images were analyzed using CellProfiler (CP) modules to optimize the analysis based on the aims of each phase of this study. CellProfiler Analyst (CPA) was used to classify cells throughout machine learning and to calculate sensibility of the classification. A sensitivity of 0.94 for dead cells and 0.99 for live cells was calculated using CPA. We did not see any quenching effects of the FITC staining. DAPI signal was reduced in the presence of TB. The results of the present study revealed that TB serves as a dead cell marker in an image cytometric analysis, being able to be combined with other fluorescence markers without loss of fluorescence intensity signal or overlapping emission spectrum. SCANNING 38:857-863, 2016. © 2016 Wiley Periodicals, Inc.

中文翻译:

台盼蓝作为一种经济实惠的标记物,用于图像细胞计数中的自动活死细胞分析

本研究的目的是将图像细胞计数和台盼蓝 (TB) 排除染色相结合,以进行可重复的高通量死细胞检测,使 TB 作为廉价标记物,对许多研究来说是负担得起的,并创造了结合荧光染料的可能性没有或有较少的光谱重叠。从健康志愿者抽取毛细血管血,裂解红细胞并诱导白细胞死亡。样品用 CD45-FITC、CD14-PE、TB 和 DAPI 染色,然后使用图像细胞术 (iCys) 进行分析。使用 DAPI 和 CD45-FITC 进行 TB 淬灭控制测试。使用 iCys 图像细胞仪以 .TIF 和 .JPEG 格式生成图像。使用 CellProfiler (CP) 模块分析图像,以根据本研究每个阶段的目标优化分析。CellProfiler Analyst (CPA) 用于在整个机器学习过程中对细胞进行分类并计算分类的敏感性。使用 CPA 计算出死细胞的灵敏度为 0.94,活细胞的灵敏度为 0.99。我们没有看到 FITC 染色的任何淬灭效应。存在 TB 时 DAPI 信号降低。本研究的结果表明,TB 在图像细胞计数分析中充当死细胞标记物,能够与其他荧光标记物结合而不会丢失荧光强度信号或重叠发射光谱。扫描 38:857-863, 2016. © 2016 Wiley Periodicals, Inc. 我们没有看到 FITC 染色的任何淬灭效应。存在 TB 时 DAPI 信号降低。本研究的结果表明,TB 在图像细胞计数分析中充当死细胞标记物,能够与其他荧光标记物结合而不会丢失荧光强度信号或重叠发射光谱。扫描 38:857-863, 2016. © 2016 Wiley Periodicals, Inc. 我们没有看到 FITC 染色的任何淬灭效应。存在 TB 时 DAPI 信号降低。本研究的结果表明,TB 在图像细胞计数分析中充当死细胞标记物,能够与其他荧光标记物结合而不会丢失荧光强度信号或重叠发射光谱。扫描 38:857-863, 2016. © 2016 Wiley Periodicals, Inc.
更新日期:2016-06-29
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