Flow-based cytometric analysis of cell cycle via simulated cell populations.
We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the "real" data to...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2010-04-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000741&type=printable |
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| _version_ | 1849695191216160768 |
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| author | M Rowan Brown Huw D Summers Paul Rees Paul J Smith Sally C Chappell Rachel J Errington |
| author_facet | M Rowan Brown Huw D Summers Paul Rees Paul J Smith Sally C Chappell Rachel J Errington |
| author_sort | M Rowan Brown |
| collection | DOAJ |
| description | We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the "real" data to initialise a computer simulation of the cell cycle that mimics the evolution of individual cells within a larger population and simulates the associated changes in fluorescence intensity of functional reporters. The model is based on stochastic formulations of cell cycle progression and cell division and uses evolutionary algorithms, allied to further experimental data sets, to optimise the system variables. At the population level, the in-silico cells provide the same statistical distributions of fluorescence as their real counterparts; in addition the model maintains information at the single cell level. The cell model is demonstrated in the analysis of cell cycle perturbation in human osteosarcoma tumour cells, using the topoisomerase II inhibitor, ICRF-193. The simulation gives a continuous temporal description of the pharmacodynamics between discrete experimental analysis points with a 24 hour interval; providing quantitative assessment of inter-mitotic time variation, drug interaction time constants and sub-population fractions within normal and polyploid cell cycles. Repeated simulations indicate a model accuracy of +/-5%. The development of a simulated cell model, initialized and calibrated by reference to experimental data, provides an analysis tool in which biological knowledge can be obtained directly via interrogation of the in-silico cell population. It is envisaged that this approach to the study of cell biology by simulating a virtual cell population pertinent to the data available can be applied to "generic" cell-based outputs including experimental data from imaging platforms. |
| format | Article |
| id | doaj-art-89b57d2875a24f99b7b41c0e43a3afad |
| institution | DOAJ |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2010-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-89b57d2875a24f99b7b41c0e43a3afad2025-08-20T03:19:50ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-04-0164e100074110.1371/journal.pcbi.1000741Flow-based cytometric analysis of cell cycle via simulated cell populations.M Rowan BrownHuw D SummersPaul ReesPaul J SmithSally C ChappellRachel J ErringtonWe present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the "real" data to initialise a computer simulation of the cell cycle that mimics the evolution of individual cells within a larger population and simulates the associated changes in fluorescence intensity of functional reporters. The model is based on stochastic formulations of cell cycle progression and cell division and uses evolutionary algorithms, allied to further experimental data sets, to optimise the system variables. At the population level, the in-silico cells provide the same statistical distributions of fluorescence as their real counterparts; in addition the model maintains information at the single cell level. The cell model is demonstrated in the analysis of cell cycle perturbation in human osteosarcoma tumour cells, using the topoisomerase II inhibitor, ICRF-193. The simulation gives a continuous temporal description of the pharmacodynamics between discrete experimental analysis points with a 24 hour interval; providing quantitative assessment of inter-mitotic time variation, drug interaction time constants and sub-population fractions within normal and polyploid cell cycles. Repeated simulations indicate a model accuracy of +/-5%. The development of a simulated cell model, initialized and calibrated by reference to experimental data, provides an analysis tool in which biological knowledge can be obtained directly via interrogation of the in-silico cell population. It is envisaged that this approach to the study of cell biology by simulating a virtual cell population pertinent to the data available can be applied to "generic" cell-based outputs including experimental data from imaging platforms.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000741&type=printable |
| spellingShingle | M Rowan Brown Huw D Summers Paul Rees Paul J Smith Sally C Chappell Rachel J Errington Flow-based cytometric analysis of cell cycle via simulated cell populations. PLoS Computational Biology |
| title | Flow-based cytometric analysis of cell cycle via simulated cell populations. |
| title_full | Flow-based cytometric analysis of cell cycle via simulated cell populations. |
| title_fullStr | Flow-based cytometric analysis of cell cycle via simulated cell populations. |
| title_full_unstemmed | Flow-based cytometric analysis of cell cycle via simulated cell populations. |
| title_short | Flow-based cytometric analysis of cell cycle via simulated cell populations. |
| title_sort | flow based cytometric analysis of cell cycle via simulated cell populations |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000741&type=printable |
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