Adjusting the range of cell-cell communication enables fine-tuning of cell fate patterns from checkerboard to engulfing.
Cell differentiation
Mathematical modeling
Pattern formation
Statistical mechanics
Journal
Journal of mathematical biology
ISSN: 1432-1416
Titre abrégé: J Math Biol
Pays: Germany
ID NLM: 7502105
Informations de publication
Date de publication:
07 09 2023
07 09 2023
Historique:
received:
03
08
2022
accepted:
25
06
2023
revised:
20
06
2023
medline:
11
9
2023
pubmed:
8
9
2023
entrez:
7
9
2023
Statut:
epublish
Résumé
During development, spatio-temporal patterns ranging from checkerboard to engulfing occur with precise proportions of the respective cell fates. Key developmental regulators are intracellular transcriptional interactions and intercellular signaling. We present an analytically tractable mathematical model based on signaling that reliably generates different cell type patterns with specified proportions. Employing statistical mechanics, We derived a cell fate decision model for two cell types. A detailed steady state analysis on the resulting dynamical system yielded necessary conditions to generate spatially heterogeneous patterns. This allows the cell type proportions to be controlled by a single model parameter. Cell-cell communication is realized by local and global signaling mechanisms. These result in different cell type patterns. A nearest neighbor signal yields checkerboard patterns. Increasing the signal dispersion, cell fate clusters and an engulfing pattern can be generated. Altogether, the presented model allows us to reliably generate heterogeneous cell type patterns of different kinds as well as desired proportions.
Identifiants
pubmed: 37679573
doi: 10.1007/s00285-023-01959-9
pii: 10.1007/s00285-023-01959-9
pmc: PMC10485129
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
54Informations de copyright
© 2023. The Author(s).
Références
Bessonnard S, De Mot L, Gonze D, Barriol M, Dennis C, Goldbeter A, Dupont G, Chazaud C (2014) Gata6, Nanog and Erk signaling control cell fate in the inner cell mass through a tristable regulatory network. Development 141(19):3637–3648. https://doi.org/10.1242/dev.109678
doi: 10.1242/dev.109678
Binder BJ, Simpson MJ (2013) Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions. Phys Rev E 88:022705. https://doi.org/10.1103/PhysRevE.88.022705
doi: 10.1103/PhysRevE.88.022705
Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Phillips R (2005) Transcriptional regulation by the numbers: models. Curr Opin Genet Dev 15(2):116–124. https://doi.org/10.1016/j.gde.2005.02.007
doi: 10.1016/j.gde.2005.02.007
Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Kuhlman T, Phillips R (2005) Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev 15(2):125–135. https://doi.org/10.1016/j.gde.2005.02.006
doi: 10.1016/j.gde.2005.02.006
Chen JS, Gumbayan AM, Zeller RW, Mahaffy JM (2014) An expanded notch-delta model exhibiting long-range patterning and incorporating MicroRNA regulation. PLOS Comput Biol 10(6):1003655. https://doi.org/10.1371/journal.pcbi.1003655
doi: 10.1371/journal.pcbi.1003655
Cherry JL, Adler FR (2000) How to make a biological switch. J Theor Biol 203(2):117–133. https://doi.org/10.1006/jtbi.2000.1068
doi: 10.1006/jtbi.2000.1068
Cohen M, Georgiou M, Stevenson NL, Miodownik M, Baum B (2010) Dynamic filopodia transmit intermittent delta-notch signaling to drive pattern refinement during lateral inhibition. Dev Cell 19(1):78–89. https://doi.org/10.1016/j.devcel.2010.06.006
doi: 10.1016/j.devcel.2010.06.006
Collier JR, Monk NAM, Maini PK, Lewis JH (1996) Pattern formation by lateral inhibition with feedback: a mathematical model of delta-notch intercellular signalling. J Theor Biol 183(4):429–446. https://doi.org/10.1006/jtbi.1996.0233
doi: 10.1006/jtbi.1996.0233
de Joussineau C, Soulé J, Martin M, Anguille C, Montcourrier P, Alexandre D (2003) Delta-promoted filopodia mediate long-range lateral inhibition in Drosophila. Nature 426(6966):555–559. https://doi.org/10.1038/nature02157
doi: 10.1038/nature02157
Dirk R, Fischer JL, Schardt S, Ankenbrand MJ, Fischer SC (2022) Recognition and reconstruction of cell differentiation patterns with deep learning. arXiv. https://doi.org/10.48550/ARXIV.2212.10058 . arXiv:2212.10058
Emily M, François O (2007) A statistical approach to estimating the strength of cell-cell interactions under the differential adhesion hypothesis. Theor Biol Med Model 4:37. https://doi.org/10.1186/1742-4682-4-37
doi: 10.1186/1742-4682-4-37
Fiorentino J, Scialdone A (2022) The role of cell geometry and cell-cell communication in gradient sensing. PLOS Comput Biol 18(3):1–22. https://doi.org/10.1371/journal.pcbi.1009552
doi: 10.1371/journal.pcbi.1009552
Garcia HG, Kondev J, Orme N, Theriot JA, Phillips R (2011) Thermodynamics of biological processes. Methods Enzymol 492:27–59. https://doi.org/10.1016/B978-0-12-381268-1.00014-8
doi: 10.1016/B978-0-12-381268-1.00014-8
Gerland U, Moroz JD, Hwa T (2002) Physical constraints and functional characteristics of transcription factor-DNA interaction. Proc Natl Acad Sci 99(19):12015–12020. https://doi.org/10.1073/pnas.192693599
doi: 10.1073/pnas.192693599
Gilbert SF (2014) Developmental Biology/Scott F. Gilbert., 10th edn. Sinauer Associates, Sunderland, Mass
Hawley J, Manning C, Biga V, Glendinning P, Papalopulu N (2022) Dynamic switching of lateral inhibition spatial patterns. J R Soc Interface 19(193):20220339. https://doi.org/10.1098/rsif.2022.0339
doi: 10.1098/rsif.2022.0339
Heitzler P, Simpson P (1991) The choice of cell fate in the epidermis of drosophila. Cell 64(6):1083–1092. https://doi.org/10.1016/0092-8674(91)90263-X
doi: 10.1016/0092-8674(91)90263-X
Huang S, Guo Y-P, May G, Enver T (2007) Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Dev Biol 305(2):695–713. https://doi.org/10.1016/j.ydbio.2007.02.036
doi: 10.1016/j.ydbio.2007.02.036
Liebisch T, Drusko A, Mathew B, Stelzer EHK, Fischer SC, Matthäus F (2020) Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach. Sci Rep 10(1):22405. https://doi.org/10.1038/s41598-020-80141-3
doi: 10.1038/s41598-020-80141-3
Mathew B, Muñoz-Descalzo S, Corujo-Simon E, Schröter C, Stelzer EHK, Fischer SC (2019) Mouse ICM organoids reveal three-dimensional cell fate clustering. Biophys J 116(1):127–141. https://doi.org/10.1016/j.bpj.2018.11.011
doi: 10.1016/j.bpj.2018.11.011
Mitsui K, Tokuzawa Y, Itoh H, Segawa K, Murakami M, Takahashi K, Maruyama M, Maeda M, Yamanaka S (2003) The homeoprotein Nanog is required for maintenance of pluripotency in mouse epiblast and es cells. Cell 113(5):631–642. https://doi.org/10.1016/S0092-8674(03)00393-3
doi: 10.1016/S0092-8674(03)00393-3
Morris SA, Teo RTY, Li H, Robson P, Glover DM, Zernicka-Goetz M (2010) Origin and formation of the first two distinct cell types of the inner cell mass in the mouse embryo. Proc Natl Acad Sci USA 107(14):6364–6369. https://doi.org/10.1073/pnas.0915063107
doi: 10.1073/pnas.0915063107
Morris SA, Graham SJL, Jedrusik A, Zernicka-Goetz M (2013) The differential response to Fgf signalling in cells internalized at different times influences lineage segregation in preimplantation mouse embryos. Open Biol 3(11):130104. https://doi.org/10.1098/rsob.130104
doi: 10.1098/rsob.130104
Mot LD, Gonze D, Bessonnard S, Chazaud C, Goldbeter A, Dupont G (2016) Cell fate specification based on tristability in the inner cell mass of mouse blastocysts. Biophys J 110(3):710–722. https://doi.org/10.1016/j.bpj.2015.12.020
doi: 10.1016/j.bpj.2015.12.020
Nichols J, Silva J, Roode M, Smith A (2009) Suppression of Erk signalling promotes ground state pluripotency in the mouse embryo. Development 136(19):3215–3222. https://doi.org/10.1242/dev.038893
doi: 10.1242/dev.038893
Nissen SB, Perera M, Gonzalez JM, Morgani SM, Jensen MH, Sneppen K, Brickman JM, Trusina A (2017) Four simple rules that are sufficient to generate the mammalian blastocyst. PLOS Biol 15(7):1–30. https://doi.org/10.1371/journal.pbio.2000737
doi: 10.1371/journal.pbio.2000737
Płusa B, Piliszek A (2020) Common principles of early mammalian embryo self-organisation. Development 147(14):dev183079. https://doi.org/10.1242/dev.183079
Raina D, Bahadori A, Stanoev A, Protzek M, Koseska A, Schröter C (2021) Cell-cell communication through FGF4 generates and maintains robust proportions of differentiated cell types in embryonic stem cells. Development. https://doi.org/10.1242/dev.199926
doi: 10.1242/dev.199926
Revell C, Blumenfeld R, Chalut KJ (2019) Force-based three-dimensional model predicts mechanical drivers of cell sorting. Proc R Soc B Biol Sci 286(1895):20182495. https://doi.org/10.1098/rspb.2018.2495
doi: 10.1098/rspb.2018.2495
Saiz N, Williams KM, Seshan VE, Hadjantonakis A-K (2016) Asynchronous fate decisions by single cells collectively ensure consistent lineage composition in the mouse blastocyst. Nat Commun 7(1):13463. https://doi.org/10.1038/ncomms13463
doi: 10.1038/ncomms13463
Saiz N, Mora-Bitria L, Rahman S, George H, Herder JP, Garcia-Ojalvo J, Hadjantonakis A-K (2020) Growth-factor-mediated coupling between lineage size and cell fate choice underlies robustness of mammalian development. eLife 9:56079. https://doi.org/10.7554/eLife.56079
Schmitz A, Fischer SC, Mattheyer C, Pampaloni F, Stelzer EHK (2017) Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids. Sci Rep 7(1):43693. https://doi.org/10.1038/srep43693
doi: 10.1038/srep43693
Schrode N, Saiz N, Di Talia S, Hadjantonakis A-K (2014) Gata6 levels modulate primitive endoderm cell fate choice and timing in the mouse blastocyst. Dev cell 29(4):454–467. https://doi.org/10.1016/j.devcel.2014.04.011
doi: 10.1016/j.devcel.2014.04.011
Schröter C, Rué P, Mackenzie JP, Martinez Arias A (2015) FGF/MAPK signaling sets the switching threshold of a bistable circuit controlling cell fate decisions in embryonic stem cells. Development 142(24):4205–4216. https://doi.org/10.1242/dev.127530
doi: 10.1242/dev.127530
Stanoev A, Schröter C, Koseska A (2021) Robustness and timing of cellular differentiation through population-based symmetry breaking. Development 148(3):dev197608. https://doi.org/10.1242/dev.197608
Sternberg PW (1993) Falling off the knife edge. Curr Biol 3(11):763–765. https://doi.org/10.1016/0960-9822(93)90025-J
doi: 10.1016/0960-9822(93)90025-J
Torii KU (2012) Two-dimensional spatial patterning in developmental systems. Trends Cell Biol 22(8):438–446
doi: 10.1016/j.tcb.2012.06.002
Tosenberger A, Gonze D, Bessonnard S, Cohen-Tannoudji M, Chazaud C, Dupont G (2017) A multiscale model of early cell lineage specification including cell division. NPJ Syst Biol Appl 3(1):16. https://doi.org/10.1038/s41540-017-0017-0
doi: 10.1038/s41540-017-0017-0
White DE, Kinney MA, McDevitt TC, Kemp ML (2013) Spatial pattern dynamics of 3d stem cell loss of pluripotency via rules-based computational modeling. PLOS Comput Biol 9(3):1–12. https://doi.org/10.1371/journal.pcbi.1002952
doi: 10.1371/journal.pcbi.1002952
Yamanaka Y, Lanner F, Rossant J (2010) FGF signal-dependent segregation of primitive endoderm and epiblast in the mouse blastocyst. Development 137(5):715–724. https://doi.org/10.1242/dev.043471
doi: 10.1242/dev.043471