An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments
Abstract Background Every biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts of cell fate for the sake of throughpu...
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| Format: | Article |
| Language: | English |
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BMC
2019-05-01
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| Series: | BMC Cancer |
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| Online Access: | http://link.springer.com/article/10.1186/s12885-019-5694-1 |
| _version_ | 1818299026479513600 |
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| author | Vasanth S. Murali Bo-Jui Chang Reto Fiolka Gaudenz Danuser Murat Can Cobanoglu Erik S. Welf |
| author_facet | Vasanth S. Murali Bo-Jui Chang Reto Fiolka Gaudenz Danuser Murat Can Cobanoglu Erik S. Welf |
| author_sort | Vasanth S. Murali |
| collection | DOAJ |
| description | Abstract Background Every biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts of cell fate for the sake of throughput. Methods Here we describe a methodology to quantify proliferation and viability of single cells in 3D culture conditions by leveraging automated microscopy and image analysis to facilitate reliable and high-throughput measurements. We detail experimental conditions that can be adjusted to increase either throughput or robustness of the assay, and we provide a stand alone image analysis program for users who wish to implement this 3D drug screening assay in high throughput. Results We demonstrate this approach by evaluating a combination of RAF and MEK inhibitors on melanoma cells, showing that cells cultured in 3D collagen-based matrices are more sensitive than cells grown in 2D culture, and that cell proliferation is much more sensitive than cell viability. We also find that cells grown in 3D cultured spheroids exhibit equivalent sensitivity to single cells grown in 3D collagen, suggesting that for the case of melanoma, a 3D single cell model may be equally effective for drug identification as 3D spheroids models. The single cell resolution of this approach enables stratification of heterogeneous populations of cells into differentially responsive subtypes upon drug treatment, which we demonstrate by determining the effect of RAK/MEK inhibition on melanoma cells co-cultured with fibroblasts. Furthermore, we show that spheroids grown from single cells exhibit dramatic heterogeneity to drug response, suggesting that heritable drug resistance can arise stochastically in single cells but be retained by subsequent generations. Conclusion In summary, image-based analysis renders cell fate detection robust, sensitive, and high-throughput, enabling cell fate evaluation of single cells in more complex microenvironmental conditions. |
| first_indexed | 2024-12-13T04:44:41Z |
| format | Article |
| id | doaj.art-ce01fffca20842278247ccf00a0ded08 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-12-13T04:44:41Z |
| publishDate | 2019-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-ce01fffca20842278247ccf00a0ded082022-12-21T23:59:11ZengBMCBMC Cancer1471-24072019-05-0119111710.1186/s12885-019-5694-1An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironmentsVasanth S. Murali0Bo-Jui Chang1Reto Fiolka2Gaudenz Danuser3Murat Can Cobanoglu4Erik S. Welf5Department of Cell Biology, UT Southwestern Medical CenterDepartment of Cell Biology, UT Southwestern Medical CenterDepartment of Cell Biology, UT Southwestern Medical CenterDepartment of Cell Biology, UT Southwestern Medical CenterLyda Hill Department of Bioinformatics, UT Southwestern Medical CenterDepartment of Cell Biology, UT Southwestern Medical CenterAbstract Background Every biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts of cell fate for the sake of throughput. Methods Here we describe a methodology to quantify proliferation and viability of single cells in 3D culture conditions by leveraging automated microscopy and image analysis to facilitate reliable and high-throughput measurements. We detail experimental conditions that can be adjusted to increase either throughput or robustness of the assay, and we provide a stand alone image analysis program for users who wish to implement this 3D drug screening assay in high throughput. Results We demonstrate this approach by evaluating a combination of RAF and MEK inhibitors on melanoma cells, showing that cells cultured in 3D collagen-based matrices are more sensitive than cells grown in 2D culture, and that cell proliferation is much more sensitive than cell viability. We also find that cells grown in 3D cultured spheroids exhibit equivalent sensitivity to single cells grown in 3D collagen, suggesting that for the case of melanoma, a 3D single cell model may be equally effective for drug identification as 3D spheroids models. The single cell resolution of this approach enables stratification of heterogeneous populations of cells into differentially responsive subtypes upon drug treatment, which we demonstrate by determining the effect of RAK/MEK inhibition on melanoma cells co-cultured with fibroblasts. Furthermore, we show that spheroids grown from single cells exhibit dramatic heterogeneity to drug response, suggesting that heritable drug resistance can arise stochastically in single cells but be retained by subsequent generations. Conclusion In summary, image-based analysis renders cell fate detection robust, sensitive, and high-throughput, enabling cell fate evaluation of single cells in more complex microenvironmental conditions.http://link.springer.com/article/10.1186/s12885-019-5694-1Drug screenHigh throughputImage analysisSpheroidOrganoidCell fate |
| spellingShingle | Vasanth S. Murali Bo-Jui Chang Reto Fiolka Gaudenz Danuser Murat Can Cobanoglu Erik S. Welf An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments BMC Cancer Drug screen High throughput Image analysis Spheroid Organoid Cell fate |
| title | An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments |
| title_full | An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments |
| title_fullStr | An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments |
| title_full_unstemmed | An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments |
| title_short | An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments |
| title_sort | image based assay to quantify changes in proliferation and viability upon drug treatment in 3d microenvironments |
| topic | Drug screen High throughput Image analysis Spheroid Organoid Cell fate |
| url | http://link.springer.com/article/10.1186/s12885-019-5694-1 |
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