Ultra high content image analysis and phenotype profiling of 3D cultured micro-tissues.

Ultra high content image analysis and phenotype profiling of 3D cultured micro-tissues.
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DOI:
10.1371/journal.pone.0109688
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Meerman JH
Meerman JH
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Di Z;Klop MJ;Rogkoti VM;Le Dévédec SE;van de Water B;Verbeek FJ;Price LS;Meerman JH

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In many situations, 3D cell cultures mimic the natural organization of tissues more closely than 2D cultures. Conventional methods for phenotyping such 3D cultures use either single or multiple simple parameters based on morphology and fluorescence staining intensity. However, due to their simplicity many details are not taken into account which limits system-level study of phenotype characteristics. Here, we have developed a new image analysis platform to automatically profile 3D cell phenotypes with 598 parameters including morphology, topology, and texture parameters such as wavelet and image moments. As proof of concept, we analyzed mouse breast cancer cells (4T1 cells) in a 384-well plate format following exposure to a diverse set of compounds at different concentrations. The result showed concentration dependent phenotypic trajectories for different biologically active compounds that could be used to classify compounds based on their biological target. To demonstrate the wider applicability of our method, we analyzed the phenotypes of a collection of 44 human breast cancer cell lines cultured in 3D and showed that our method correctly distinguished basal-A, basal-B, luminal and ERBB2+ cell lines in a supervised nearest neighbor classification method.
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