Optimal quantification of contact inhibition in cell populations
Contact inhibition refers to a reduction in the rate of cell migration and/or cell proliferation in regions of high cell density. Under normal conditions, contact inhibition is associated with the proper functioning tissues, whereas abnormal regulation of contact inhibition is associated with pathol...
| Main Authors: | , , |
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| Format: | Journal article |
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Cell Press
2017
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| _version_ | 1826258734443134976 |
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| author | Warne, D Baker, R Simpson, M |
| author_facet | Warne, D Baker, R Simpson, M |
| author_sort | Warne, D |
| collection | OXFORD |
| description | Contact inhibition refers to a reduction in the rate of cell migration and/or cell proliferation in regions of high cell density. Under normal conditions, contact inhibition is associated with the proper functioning tissues, whereas abnormal regulation of contact inhibition is associated with pathological conditions, such as tumor spreading. Unfortunately, standard mathematical modeling practices mask the importance of parameters that control contact inhibition through scaling arguments. Furthermore, standard experimental protocols are insufficient to quantify the effects of contact inhibition because they focus on data describing early time, low-density dynamics only. Here we use the logistic growth equation as a caricature model of contact inhibition to make recommendations as to how to best mitigate these issues. Taking a Bayesian approach, we quantify the trade off between different features of experimental design and estimates of parameter uncertainty so that we can reformulate a standard cell proliferation assay to provide estimates of both the low-density intrinsic growth rate, λ, and the carrying capacity density, K, which is a measure of contact inhibition. |
| first_indexed | 2024-03-06T18:38:39Z |
| format | Journal article |
| id | oxford-uuid:0c26b49b-2b09-42e4-9e5b-b2f300c4c470 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T18:38:39Z |
| publishDate | 2017 |
| publisher | Cell Press |
| record_format | dspace |
| spelling | oxford-uuid:0c26b49b-2b09-42e4-9e5b-b2f300c4c4702022-03-26T09:33:22ZOptimal quantification of contact inhibition in cell populationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0c26b49b-2b09-42e4-9e5b-b2f300c4c470Symplectic Elements at OxfordCell Press2017Warne, DBaker, RSimpson, MContact inhibition refers to a reduction in the rate of cell migration and/or cell proliferation in regions of high cell density. Under normal conditions, contact inhibition is associated with the proper functioning tissues, whereas abnormal regulation of contact inhibition is associated with pathological conditions, such as tumor spreading. Unfortunately, standard mathematical modeling practices mask the importance of parameters that control contact inhibition through scaling arguments. Furthermore, standard experimental protocols are insufficient to quantify the effects of contact inhibition because they focus on data describing early time, low-density dynamics only. Here we use the logistic growth equation as a caricature model of contact inhibition to make recommendations as to how to best mitigate these issues. Taking a Bayesian approach, we quantify the trade off between different features of experimental design and estimates of parameter uncertainty so that we can reformulate a standard cell proliferation assay to provide estimates of both the low-density intrinsic growth rate, λ, and the carrying capacity density, K, which is a measure of contact inhibition. |
| spellingShingle | Warne, D Baker, R Simpson, M Optimal quantification of contact inhibition in cell populations |
| title | Optimal quantification of contact inhibition in cell populations |
| title_full | Optimal quantification of contact inhibition in cell populations |
| title_fullStr | Optimal quantification of contact inhibition in cell populations |
| title_full_unstemmed | Optimal quantification of contact inhibition in cell populations |
| title_short | Optimal quantification of contact inhibition in cell populations |
| title_sort | optimal quantification of contact inhibition in cell populations |
| work_keys_str_mv | AT warned optimalquantificationofcontactinhibitionincellpopulations AT bakerr optimalquantificationofcontactinhibitionincellpopulations AT simpsonm optimalquantificationofcontactinhibitionincellpopulations |