Research article Topical Sections

Effects of cell packing on chemoattractant distribution within a tissue

  • Received: 10 October 2017 Accepted: 22 January 2018 Published: 31 January 2018
  • Diffusible signals provide critical information to cells in biological systems, often in a concentration-dependent manner. In animal development, such signals can determine different cell fates or guide motile cells to their proper locations. It is well-known that migrating cells respond to graded chemoattractant cues by moving toward areas of higher concentrations. However, it is not clear how cell-dense animal tissues impact the distribution of chemoattractants in three dimensions. We leverage the simple architecture of the Drosophila egg chamber to explore this idea. In this context, sixteen large germline cells are packed together, enveloped by a somatic epithelium. A small set of epithelial cells, the border cells, form a motile cell cluster and respond to guidance signals by moving across the egg chamber during oogenesis. We created a geometrically-realistic model of the egg chamber and determined the distribution of the chemoattractants through that domain using a reaction-diffusion system. We used this information to determine reasonable biophysical parameters of chemoattractant that would facilitate gradient formation in the appropriate developmental time, and to explore the effects of different secretion locations in the egg chamber. Our model revealed several interesting features: The chemoattractant is more concentrated and the gradient sets up more quickly in a cell-packed space, and cell packing creates dips in the concentration and changes in gradient along the migratory path. We simulated migration with our calculated chemoattractant gradient and compared it to that with a constant gradient. We found that with our calculated gradient, migration was slower initially than in the constant gradient, which could be due to the exponential nature of the gradient or other variation in signal due to the heterogeneous domain. Given the many situations in which cell migration occurs in complex spatio-temporal environments, including development, immune response, and cancer metastasis, we believe modeling chemoattractant distribution in heterogeneous domains is widely relevant.

    Citation: Zachary Mekus, Jessica Cooley, Aaron George, Victoria Sabo, Morgan Strzegowski, Michelle Starz-Gaiano, Bradford E. Peercy. Effects of cell packing on chemoattractant distribution within a tissue[J]. AIMS Biophysics, 2018, 5(1): 1-21. doi: 10.3934/biophy.2018.1.1

    Related Papers:

  • Diffusible signals provide critical information to cells in biological systems, often in a concentration-dependent manner. In animal development, such signals can determine different cell fates or guide motile cells to their proper locations. It is well-known that migrating cells respond to graded chemoattractant cues by moving toward areas of higher concentrations. However, it is not clear how cell-dense animal tissues impact the distribution of chemoattractants in three dimensions. We leverage the simple architecture of the Drosophila egg chamber to explore this idea. In this context, sixteen large germline cells are packed together, enveloped by a somatic epithelium. A small set of epithelial cells, the border cells, form a motile cell cluster and respond to guidance signals by moving across the egg chamber during oogenesis. We created a geometrically-realistic model of the egg chamber and determined the distribution of the chemoattractants through that domain using a reaction-diffusion system. We used this information to determine reasonable biophysical parameters of chemoattractant that would facilitate gradient formation in the appropriate developmental time, and to explore the effects of different secretion locations in the egg chamber. Our model revealed several interesting features: The chemoattractant is more concentrated and the gradient sets up more quickly in a cell-packed space, and cell packing creates dips in the concentration and changes in gradient along the migratory path. We simulated migration with our calculated chemoattractant gradient and compared it to that with a constant gradient. We found that with our calculated gradient, migration was slower initially than in the constant gradient, which could be due to the exponential nature of the gradient or other variation in signal due to the heterogeneous domain. Given the many situations in which cell migration occurs in complex spatio-temporal environments, including development, immune response, and cancer metastasis, we believe modeling chemoattractant distribution in heterogeneous domains is widely relevant.


    加载中
    [1] Muller P, Schier AF (2011) Extracellular movement of signaling molecules. Dev Cell 21: 145–158. doi: 10.1016/j.devcel.2011.06.001
    [2] Briscoe J, Small S (2015) Morphogen rules: Design principles of gradient-mediated embryo patterning. Development 142: 3996–4009. doi: 10.1242/dev.129452
    [3] Kicheva A, Bollenbach T, Wartlick O, et al. (2012) Investigating the principles of morphogen gradient formation: From tissues to cells. Curr Opin Genet Dev 22: 527–532. doi: 10.1016/j.gde.2012.08.004
    [4] Janetopoulos C, Firtel RA (2008) Directional sensing during chemotaxis. FEBS Lett 582: 2075–2085. doi: 10.1016/j.febslet.2008.04.035
    [5] Roussos ET, Condeelis JS, Patsialou A (2011) Chemotaxis in cancer. Nat Rev Cancer 11: 573–587. doi: 10.1038/nrc3078
    [6] Cai D, Montell DJ (2014) Diverse and dynamic sources and sinks in gradient formation and directed migration. Curr Opin Cell Biol 30: 91–98. doi: 10.1016/j.ceb.2014.06.009
    [7] Haeger A, Wolf K, Zegers MM, et al. (2015) Collective cell migration: Guidance principles and hierarchies. Trends Cell Biol 25: 556–566. doi: 10.1016/j.tcb.2015.06.003
    [8] Danuser G, Allard J, Mogilner A (2013) Mathematical modeling of eukaryotic cell migration: Insights beyond experiments. Annu Rev Cell Dev Biol 29: 501–528. doi: 10.1146/annurev-cellbio-101512-122308
    [9] Barua D, Parent SE, Winklbauer R (2017) Mechanics of Fluid-Filled Interstitial Gaps. II. Gap Characteristics in Xenopus Embryonic Ectoderm. Biophys J 113: 923–936.
    [10] David R, Luu O, Damm EW, et al. (2014) Tissue cohesion and the mechanics of cell rearrangement. Development 141: 3672–3682. doi: 10.1242/dev.104315
    [11] Nicholson C, Hrabetova S (2017) Brain extracellular space: The final frontier of neuroscience. Biophys J.
    [12] Hudson AM, Cooley L (2014) Methods for studying oogenesis. Methods 68: 207–217. doi: 10.1016/j.ymeth.2014.01.005
    [13] Duhart JC, Parsons TT, Raftery LA (2017) The repertoire of epithelial morphogenesis on display: Progressive elaboration of Drosophila egg structure. Mech Develop.
    [14] Losick VP, Morris LX, Fox DT, et al. (2011) Drosophila stem cell niches: A decade of discovery suggests a unified view of stem cell regulation. Dev Cell 21: 159–171. doi: 10.1016/j.devcel.2011.06.018
    [15] Cheung LS, Schupbach T, Shvartsman SY (2011) Pattern formation by receptor tyrosine kinases: Analysis of the Gurken gradient in Drosophila oogenesis. Curr Opin Genet Dev 21: 719–725. doi: 10.1016/j.gde.2011.07.009
    [16] King RC (1970) Ovarian development in Drosophila melanogaster. Q Rev Biol 44: 487–495.
    [17] Montell DJ, Wan HY, Starz-Gaiano M (2012) Group choreography: Mechanisms orchestrating the collective movement of border cells. Nat Rev Mol Cell Biol 13: 631–645. doi: 10.1038/nrm3433
    [18] Saadin A, Starz-Gaiano M (2016) Circuitous genetic regulation governs a straightforward cell migration. Trends Genet 32: 660–673. doi: 10.1016/j.tig.2016.08.001
    [19] Duchek P, Somogyi K, Jekely G, et al. (2001) Guidance of cell migration by the Drosophila PDGF/VEGF receptor. Cell 107: 17–26. doi: 10.1016/S0092-8674(01)00502-5
    [20] McDonald JA, Pinheiro EM, Montell DJ (2003) PVF1, a PDGF/VEGF homolog, is sufficient to guide border cells and interacts genetically with Taiman. Development 130: 3469–3478. doi: 10.1242/dev.00574
    [21] Bianco A, Poukkula M, Cliffe A, et al. (2007) Two distinct modes of guidance signalling during collective migration of border cells. Nature 448: 362–365. doi: 10.1038/nature05965
    [22] Prasad M, Montell DJ (2007) Cellular and molecular mechanisms of border cell migration analyzed using time-lapse live-cell imaging. Dev Cell 12: 997–1005. doi: 10.1016/j.devcel.2007.03.021
    [23] Duchek P, Rorth P (2001) Guidance of cell migration by EGF receptor signaling during Drosophila oogenesis. Science 291: 131–133. doi: 10.1126/science.291.5501.131
    [24] McDonald JA, Pinheiro EM, Kadlec L, et al. (2006) Multiple EGFR ligands participate in guiding migrating border cells. Dev Biol 296: 94–103. doi: 10.1016/j.ydbio.2006.04.438
    [25] Wasserman JD, Freeman M (1998) An autoregulatory cascade of EGF receptor signaling patterns the Drosophila egg. Cell 95: 355–364. doi: 10.1016/S0092-8674(00)81767-5
    [26] Stonko DP, Manning L, Starz-Gaiano M, et al. (2015) A mathematical model of collective cell migration in a three-dimensional, heterogeneous environment. PLoS One 10: e0122799. doi: 10.1371/journal.pone.0122799
    [27] Cai D, Dai W, Prasad M, et al. (2016) Modeling and analysis of collective cell migration in an in vivo three-dimensional environment. Proc Natl Acad Sci USA 113: E2134–E2141. doi: 10.1073/pnas.1522656113
    [28] Yamao M, Naoki H, Ishii S (2011) Multi-cellular logistics of collective cell migration. PLoS One 6: e27950. doi: 10.1371/journal.pone.0027950
    [29] Manning LA, Weideman AM, Peercy BE, et al. (2015) Tissue landscape alters adjacent cell fates during Drosophila egg development. Nat Commun 6: 7356. doi: 10.1038/ncomms8356
    [30] Rorth P (2002) Initiating and guiding migration: Lessons from border cells. Trends Cell Biol 12: 325–331. doi: 10.1016/S0962-8924(02)02311-5
    [31] Grimm O, Coppey M, Wieschaus E (2010) Modelling the Bicoid gradient. Development 137: 2253–2264. doi: 10.1242/dev.032409
    [32] Muller P, Rogers KW, Yu SR, et al. (2013) Morphogen transport. Development 140: 1621–1638. doi: 10.1242/dev.083519
    [33] Kicheva A, Pantazis P, Bollenbach T, et al. (2007) Kinetics of morphogen gradient formation. Science 315: 521–525. doi: 10.1126/science.1135774
    [34] Zhou S, Lo WC, Suhalim JL, et al. (2012) Free extracellular diffusion creates the Dpp morphogen gradient of the Drosophila wing disc. Curr Biol 22: 668–675. doi: 10.1016/j.cub.2012.02.065
    [35] Wright VM, Vogt KL, Smythe E, et al. (2011) Differential activities of the Drosophila JAK/STAT pathway ligands Upd, Upd2 and Upd3. Cell Signal 23: 920–927. doi: 10.1016/j.cellsig.2011.01.020
    [36] Krall JA, Beyer EM, MacBeath G (2011) High- and low-affinity epidermal growth factor receptor-ligand interactions activate distinct signaling pathways. PLoS One 6: e15945. doi: 10.1371/journal.pone.0015945
    [37] Kong Q, Majeska RJ, Vazquez M (2011) Migration of connective tissue-derived cells is mediated by ultra-low concentration gradient fields of EGF. Exp Cell Res 317: 1491–1502. doi: 10.1016/j.yexcr.2011.04.003
    [38] Raja WK, Gligorijevic B, Wyckoff J, et al. (2010) A new chemotaxis device for cell migration studies. Integr Biol 2: 696–706. doi: 10.1039/c0ib00044b
    [39] Wang SJ, Saadi W, Lin F, et al. (2004) Differential effects of EGF gradient profiles on MDA-MB-231 breast cancer cell chemotaxis. Exp Cell Res 300: 180–189. doi: 10.1016/j.yexcr.2004.06.030
    [40] Kammermeyer KL, Wadsworth SC (1987) Expression of Drosophila epidermal growth factor receptor homologue in mitotic cell populations. Development 100: 201–210.
    [41] Iglesias PA, Devreotes PN (2012) Biased excitable networks: How cells direct motion in response to gradients. Curr Opin Cell Biol 24: 245–253. doi: 10.1016/j.ceb.2011.11.009
    [42] Prasad M, Jang AC, Starz-Gaiano M, et al. (2007) A protocol for culturing Drosophila melanogaster stage 9 egg chambers for live imaging. Nat Protoc 2: 2467–2473. doi: 10.1038/nprot.2007.363
    [43] Lusk JB, Lam VYW, Tolwinski NS (2017) Epidermal growth factor pathway signaling in Drosophila embryogenesis: Tools for understanding cancer. Cancers 9: 16. doi: 10.3390/cancers9020016
    [44] Stephens L, Milne L, Hawkins P (2008) Moving towards a better understanding of chemotaxis. Curr Biol 18: R485–R494. doi: 10.1016/j.cub.2008.04.048
    [45] Hughes-Alford SK, Lauffenburger DA (2012) Quantitative analysis of gradient sensing: Towards building predictive models of chemotaxis in cancer. Curr Opin Cell Biol 24: 284–291. doi: 10.1016/j.ceb.2012.01.001
    [46] Gregor T, Wieschaus EF, McGregor AP, et al. (2007) Stability and nuclear dynamics of the bicoid morphogen gradient. Cell 130: 141–152. doi: 10.1016/j.cell.2007.05.026
    [47] Venkiteswaran G, Lewellis SW, Wang J, et al. (2013) Generation and dynamics of an endogenous, self-generated signaling gradient across a migrating tissue. Cell 155: 674–687. doi: 10.1016/j.cell.2013.09.046
  • Reader Comments
  • © 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(5103) PDF downloads(1191) Cited by(2)

Article outline

Figures and Tables

Figures(9)  /  Tables(7)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog