Spatial Dynamics of Multistage Cell Lineages in Tissue Stratification

Chou, Ching-Shan; Lo, Wing-Cheong; Gokoffski, Kimberly K.; Zhang, Yongtao; Wan, Frederic Y. M.; Lander, Arthur D.; Calof, Anne L.; Nie, Qing

doi:10.1016/j.bpj.2010.09.034

Cited by 51 publications

(56 citation statements)

References 38 publications

(46 reference statements)

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“…We could determine the number of cells in each compartments at different time of development (from E11.5 to E15.5), but it is not yet technically possible to evaluate the flow of melanoblasts going from the dermis to epidermis. Other mathematical models have already been established to determine the proliferation features for cells in culture or in vivo (Chou et al, 2010;Di Garbo et al, 2010;Hyrien et al, 2010;Tabatabai et al, 2011;Tomasetti and Levy, 2010). However, none of them brings clear values of doubling times of their considered cells, as we do.…”

Section: Establishment Of the Melanocyte Lineagementioning

confidence: 87%

Biological and mathematical modeling of melanocyte development

et al. 2011

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SUMMARYWe aim to evaluate environmental and genetic effects on the expansion/proliferation of committed single cells during embryonic development, using melanoblasts as a paradigm to model this phenomenon. Melanoblasts are a specific type of cell that display extensive cellular proliferation during development. However, the events controlling melanoblast expansion are still poorly understood due to insufficient knowledge concerning their number and distribution in the various skin compartments. We show that melanoblast expansion is tightly controlled both spatially and temporally, with little variation between embryos. We established a mathematical model reflecting the main cellular mechanisms involved in melanoblast expansion, including proliferation and migration from the dermis to epidermis. In association with biological information, the model allows the calculation of doubling times for melanoblasts, revealing that dermal and epidermal melanoblasts have short but different doubling times. Moreover, the number of trunk founder melanoblasts at E8.5 was estimated to be 16, a population impossible to count by classical biological approaches. We also assessed the importance of the genetic background by studying gain-and lossof-function b-catenin mutants in the melanocyte lineage. We found that any alteration of b-catenin activity, whether positive or negative, reduced both dermal and epidermal melanoblast proliferation. Finally, we determined that the pool of dermal melanoblasts remains constant in wild-type and mutant embryos during development, implying that specific control mechanisms associated with cell division ensure half of the cells at each cell division to migrate from the dermis to the epidermis. Modeling melanoblast expansion revealed novel links between cell division, cell localization within the embryo and appropriate feedback control through b-catenin.

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Section: Establishment Of the Melanocyte Lineagementioning

confidence: 87%

Biological and mathematical modeling of melanocyte development

et al. 2011

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“…Such feedback can also drive the spatial stratification of epithelia (Chou et al 2010). Moreover, such studies show that in multistage lineages, the relative strengths of the different feedback loops determine which cell stage adopts stem or committed progenitor cell behaviors and suggest that feedback is the reason why stem and committed progenitor cell behaviors emerge in tissues.…”

Section: Introductionmentioning

confidence: 99%

Multispecies model of cell lineages and feedback control in solid tumors

Youssefpour

Lander

et al. 2012

Journal of Theoretical Biology

114

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We develop a multispecies continuum model to simulate the spatiotemporal dynamics of cell lineages in solid tumors. The model accounts for protein signaling factors produced by cells in lineages, and nutrients supplied by the microenvironment. Together, these regulate the rates of proliferation, self-renewal and differentiation of cells within the lineages, and control cell population sizes and distributions. Terminally differentiated cells release proteins (e.g., from the TGFβ superfamily) that feedback upon less differentiated cells in the lineage both to promote differentiation and decrease rates of proliferation (and self-renewal). Stem cells release a short-range factor that promotes self-renewal (e.g., representative of Wnt signaling factors), as well as a long-range inhibitor of this factor (e.g., representative of Wnt inhibitors such as Dkk and SFRPs). We find that the progression of the tumors and their response to treatment is controlled by the spatiotemporal dynamics of the signaling processes. The model predicts the development of spatiotemporal heterogeneous distributions of the feedback factors (Wnt, Dkk and TGFβ) and tumor cell populations with clusters of stem cells appearing at the tumor boundary, consistent with recent experiments. The nonlinear coupling between the heterogeneous expressions of growth factors and the heterogeneous distributions of cell populations at different lineage stages tends to create asymmetry in tumor shape that may sufficiently alter otherwise homeostatic feedback so as to favor escape from growth control. This occurs in a setting of invasive fingering, and enhanced aggressiveness after standard therapeutic interventions. We find, however, that combination therapy involving differentiation promoters and radiotherapy is very effective in eradicating such a tumor.

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“…These population dynamic models could include age structure (29), evolution (27,30), and stochasticity (30,31); and these models could also be applied to the regulation of cancer (32). Studies based on spatial modeling have found that diffusive and regulatory molecules involved in feedback mechanisms regulating the differentiation capabilities of the cells are important in maintaining the stem cell niche and shaping tissue stratification (33,34).…”

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confidence: 99%

Mathematical model of adult stem cell regeneration with cross-talk between genetic and epigenetic regulation

Lei

Levin

Nie

2014

Proc. Natl. Acad. Sci. U.S.A.

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Adult stem cells, which exist throughout the body, multiply by cell division to replenish dying cells or to promote regeneration to repair damaged tissues. To perform these functions during the lifetime of organs or tissues, stem cells need to maintain their populations in a faithful distribution of their epigenetic states, which are susceptible to stochastic fluctuations during each cell division, unexpected injury, and potential genetic mutations that occur during many cell divisions. However, it remains unclear how the three processes of differentiation, proliferation, and apoptosis in regulating stem cells collectively manage these challenging tasks. Here, without considering molecular details, we propose a genetic optimal control model for adult stem cell regeneration that includes the three fundamental processes, along with cell division and adaptation based on differential fitnesses of phenotypes. In the model, stem cells with a distribution of epigenetic states are required to maximize expected performance after each cell division. We show that heterogeneous proliferation that depends on the epigenetic states of stem cells can improve the maintenance of stem cell distributions to create balanced populations. A control strategy during each cell division leads to a feedback mechanism involving heterogeneous proliferation that can accelerate regeneration with less fluctuation in the stem cell population. When mutation is allowed, apoptosis evolves to maximize the performance during homeostasis after multiple cell divisions. The overall results highlight the importance of cross-talk between genetic and epigenetic regulation and the performance objectives during homeostasis in shaping a desirable heterogeneous distribution of stem cells in epigenetic states.fitness function | optimization | robustness | dynamic programming | systems biology

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Spatial Dynamics of Multistage Cell Lineages in Tissue Stratification

Cited by 51 publications

References 38 publications

Biological and mathematical modeling of melanocyte development

Biological and mathematical modeling of melanocyte development

Multispecies model of cell lineages and feedback control in solid tumors

Mathematical model of adult stem cell regeneration with cross-talk between genetic and epigenetic regulation

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