A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids
Abstract Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approa...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2020-12-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.15252/msb.20209798 |
| _version_ | 1797288032520372224 |
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| author | Vito RT Zanotelli Matthias Leutenegger Xiao‐Kang Lun Fanny Georgi Natalie de Souza Bernd Bodenmiller |
| author_facet | Vito RT Zanotelli Matthias Leutenegger Xiao‐Kang Lun Fanny Georgi Natalie de Souza Bernd Bodenmiller |
| author_sort | Vito RT Zanotelli |
| collection | DOAJ |
| description | Abstract Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell‐intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems‐level studies of single‐cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell‐intrinsic and cell‐extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies. |
| first_indexed | 2024-03-07T18:43:25Z |
| format | Article |
| id | doaj.art-577f6dc37c6a41c6a2fe8bda0a9e1fce |
| institution | Directory Open Access Journal |
| issn | 1744-4292 |
| language | English |
| last_indexed | 2024-03-07T18:43:25Z |
| publishDate | 2020-12-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj.art-577f6dc37c6a41c6a2fe8bda0a9e1fce2024-03-02T03:22:11ZengSpringer NatureMolecular Systems Biology1744-42922020-12-011612n/an/a10.15252/msb.20209798A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroidsVito RT Zanotelli0Matthias Leutenegger1Xiao‐Kang Lun2Fanny Georgi3Natalie de Souza4Bernd Bodenmiller5Department of Quantitative Biomedicine University of Zurich Zürich SwitzerlandDepartment of Molecular Life Sciences University of Zurich Zürich SwitzerlandLife Science Zürich Graduate School ETH Zürich and University of Zürich Zürich SwitzerlandLife Science Zürich Graduate School ETH Zürich and University of Zürich Zürich SwitzerlandDepartment of Quantitative Biomedicine University of Zurich Zürich SwitzerlandDepartment of Quantitative Biomedicine University of Zurich Zürich SwitzerlandAbstract Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell‐intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems‐level studies of single‐cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell‐intrinsic and cell‐extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies.https://doi.org/10.15252/msb.20209798high‐throughput assaymultiplexed imagingspatial signalingspatial variancetissue organization |
| spellingShingle | Vito RT Zanotelli Matthias Leutenegger Xiao‐Kang Lun Fanny Georgi Natalie de Souza Bernd Bodenmiller A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids Molecular Systems Biology high‐throughput assay multiplexed imaging spatial signaling spatial variance tissue organization |
| title | A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids |
| title_full | A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids |
| title_fullStr | A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids |
| title_full_unstemmed | A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids |
| title_short | A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids |
| title_sort | quantitative analysis of the interplay of environment neighborhood and cell state in 3d spheroids |
| topic | high‐throughput assay multiplexed imaging spatial signaling spatial variance tissue organization |
| url | https://doi.org/10.15252/msb.20209798 |
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