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Cell mixing induced by myc is required for competitive tissue invasion and destruction

Abstract

Cell–cell intercalation is used in several developmental processes to shape the normal body plan1. There is no clear evidence that intercalation is involved in pathologies. Here we use the proto-oncogene myc to study a process analogous to early phase of tumour expansion: myc-induced cell competition2,3,4,5,6,7. Cell competition is a conserved mechanism5,6,8,9 driving the elimination of slow-proliferating cells (so-called ‘losers’) by faster-proliferating neighbours (so-called ‘winners’) through apoptosis10 and is important in preventing developmental malformations and maintain tissue fitness11. Here we show, using long-term live imaging of myc-driven competition in the Drosophila pupal notum and in the wing imaginal disc, that the probability of elimination of loser cells correlates with the surface of contact shared with winners. As such, modifying loser–winner interface morphology can modulate the strength of competition. We further show that elimination of loser clones requires winner–loser cell mixing through cell–cell intercalation. Cell mixing is driven by differential growth and the high tension at winner–winner interfaces relative to winner–loser and loser–loser interfaces, which leads to a preferential stabilization of winner–loser contacts and reduction of clone compactness over time. Differences in tension are generated by a relative difference in F-actin levels between loser and winner junctions, induced by differential levels of the membrane lipid phosphatidylinositol (3,4,5)-trisphosphate. Our results establish the first link between cell–cell intercalation induced by a proto-oncogene and how it promotes invasiveness and destruction of healthy tissues.

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Figure 1: Loser elimination correlates with the surface shared with winners.
Figure 2: Winner–loser mixing is induced by junction remodelling and cell–cell intercalation.
Figure 3: Differences in PIP3 induce loser–winner mixing.
Figure 4: Filamentous actin and tension modulation are responsible for winner–loser mixing.

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References

  1. Walck-Shannon, E. & Hardin, J. Cell intercalation from top to bottom. Nature Rev. Mol. Cell Biol. 15, 34–48 (2014)

    Article  CAS  Google Scholar 

  2. Morata, G. & Ripoll, P. Minutes: mutants of Drosophila autonomously affecting cell division rate. Dev. Biol. 42, 211–221 (1975)

    Article  CAS  PubMed  Google Scholar 

  3. de la Cova, C., Abril, M., Bellosta, P., Gallant, P. & Johnston, L. A. Drosophila myc regulates organ size by inducing cell competition. Cell 117, 107–116 (2004)

    Article  CAS  PubMed  Google Scholar 

  4. Moreno, E. & Basler, K. dMyc transforms cells into super-competitors. Cell 117, 117–129 (2004)

    Article  CAS  PubMed  Google Scholar 

  5. Sancho, M. et al. Competitive interactions eliminate unfit embryonic stem cells at the onset of differentiation. Dev. Cell 26, 19–30 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Claveria, C., Giovinazzo, G., Sierra, R. & Torres, M. Myc-driven endogenous cell competition in the early mammalian embryo. Nature 500, 39–44 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  7. Levayer, R. & Moreno, E. Mechanisms of cell competition: themes and variations. J. Cell Biol. 200, 689–698 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tamori, Y. et al. Involvement of Lgl and Mahjong/VprBP in cell competition. PLoS Biol. 8, e1000422 (2010)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Martins, V. C. et al. Cell competition is a tumour suppressor mechanism in the thymus. Nature 509, 465–470 (2014)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Moreno, E., Basler, K. & Morata, G. Cells compete for decapentaplegic survival factor to prevent apoptosis in Drosophila wing development. Nature 416, 755–759 (2002)

    Article  ADS  CAS  PubMed  Google Scholar 

  11. Merino, M. M. et al. Elimination of unfit cells maintains tissue health and prolongs lifespan. Cell 160, 461–476 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Rhiner, C. et al. Flower forms an extracellular code that reveals the fitness of a cell to its neighbors in Drosophila . Dev. Cell 18, 985–998 (2010)

    Article  CAS  PubMed  Google Scholar 

  13. Lecuit, T., Lenne, P. F. & Munro, E. Force generation, transmission, and integration during cell and tissue morphogenesis. Annu. Rev. Cell Dev. Biol. 27, 157–184 (2011)

    Article  CAS  PubMed  Google Scholar 

  14. Simpson, P. & Morata, G. Differential mitotic rates and patterns of growth in compartments in the Drosophila wing. Dev. Biol. 85, 299–308 (1981)

    Article  CAS  PubMed  Google Scholar 

  15. Landsberg, K. P. et al. Increased cell bond tension governs cell sorting at the Drosophila anteroposterior compartment boundary. Curr. Biol. 19, 1950–1955 (2009)

    Article  CAS  PubMed  Google Scholar 

  16. Simpson, P. Parameters of cell competition in the compartments of the wing disc of Drosophila . Dev. Biol. 69, 182–193 (1979)

    Article  CAS  PubMed  Google Scholar 

  17. Li, W., Kale, A. & Baker, N. E. Oriented cell division as a response to cell death and cell competition. Curr. Biol. 19, 1821–1826 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bardet, P. L. et al. PTEN controls junction lengthening and stability during cell rearrangement in epithelial tissue. Dev. Cell 25, 534–546 (2013)

    Article  CAS  PubMed  Google Scholar 

  19. Andersen, D. S., Colombani, J. & Leopold, P. Coordination of organ growth: principles and outstanding questions from the world of insects. Trends Cell Biol. 23, 336–344 (2013)

    Article  CAS  PubMed  Google Scholar 

  20. Britton, J. S., Lockwood, W. K., Li, L., Cohen, S. M. & Edgar, B. A. Drosophila’s insulin/PI3-kinase pathway coordinates cellular metabolism with nutritional conditions. Dev. Cell 2, 239–249 (2002)

    Article  CAS  PubMed  Google Scholar 

  21. Legoff, L., Rouault, H. & Lecuit, T. A global pattern of mechanical stress polarizes cell divisions and cell shape in the growing Drosophila wing disc. Development 140, 4051–4059 (2013)

    Article  CAS  PubMed  Google Scholar 

  22. Mao, Y. et al. Differential proliferation rates generate patterns of mechanical tension that orient tissue growth. EMBO J. 32, 2790–2803 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Kolsch, V., Charest, P. G. & Firtel, R. A. The regulation of cell motility and chemotaxis by phospholipid signaling. J. Cell Sci. 121, 551–559 (2008)

    Article  CAS  PubMed  Google Scholar 

  24. Bosveld, F. et al. Mechanical control of morphogenesis by Fat/Dachsous/Four-jointed planar cell polarity pathway. Science 336, 724–727 (2012)

    Article  ADS  CAS  PubMed  Google Scholar 

  25. Sansores-Garcia, L. et al. Modulating F-actin organization induces organ growth by affecting the Hippo pathway. EMBO J. 30, 2325–2335 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Rauzi, M., Verant, P., Lecuit, T. & Lenne, P. F. Nature and anisotropy of cortical forces orienting Drosophila tissue morphogenesis. Nature Cell Biol. 10, 1401–1410 (2008)

    Article  CAS  PubMed  Google Scholar 

  27. Brodland, G. W. & Veldhuis, J. H. The mechanics of metastasis: insights from a computational model. PLoS ONE 7, e44281 (2012)

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  28. Parisi, F. & Vidal, M. Epithelial delamination and migration: lessons from Drosophila . Cell Adhes. Migr. 5, 366–372 (2011)

    Article  Google Scholar 

  29. Leung, C. T. & Brugge, J. S. Outgrowth of single oncogene-expressing cells from suppressive epithelial environments. Nature 482, 410–413 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Butcher, D. T., Alliston, T. & Weaver, V. M. A tense situation: forcing tumour progression. Nature Rev. Cancer 9, 108–122 (2009)

    Article  CAS  PubMed  Google Scholar 

  31. Oda, H. & Tsukita, S. Real-time imaging of cell-cell adherens junctions reveals that Drosophila mesoderm invagination begins with two phases of apical constriction of cells. J. Cell Sci. 114, 493–501 (2001)

    Article  CAS  PubMed  Google Scholar 

  32. Merino, M. M., Rhiner, C., Portela, M. & Moreno, E. “Fitness fingerprints” mediate physiological culling of unwanted neurons in Drosophila . Curr Biol. 23, 1300–1309 (2013)

    Article  CAS  PubMed  Google Scholar 

  33. Pacquelet, A. & Rorth, P. Regulatory mechanisms required for DE-cadherin function in cell migration and other types of adhesion. J. Cell Biol. 170, 803–812 (2005)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Corrigall, D., Walther, R. F., Rodriguez, L., Fichelson, P. & Pichaud, F. Hedgehog signaling is a principal inducer of myosin-II-driven cell ingression in Drosophila epithelia. Dev. Cell 13, 730–742 (2007)

    Article  CAS  PubMed  Google Scholar 

  35. Moreno, E., Yan, M. & Basler, K. Evolution of TNF signaling mechanisms: JNK-dependent apoptosis triggered by Eiger, the Drosophila homolog of the TNF superfamily. Curr Biol. 12, 1263–1268 (2002)

    Article  CAS  PubMed  Google Scholar 

  36. Ford, D. et al. Alteration of Drosophila life span using conditional, tissue-specific expression of transgenes triggered by doxycyline or RU486/Mifepristone. Exp. Gerontol. 42, 483–497 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Tanimoto, H., Itoh, S., ten Dijke, P. & Tabata, T. Hedgehog creates a gradient of DPP activity in Drosophila wing imaginal discs. Mol. Cell 5, 59–71 (2000)

    Article  CAS  PubMed  Google Scholar 

  38. Zhang, H. et al. Deletion of Drosophila insulin-like peptides causes growth defects and metabolic abnormalities. Proc. Natl Acad. Sci. USA 106, 19617–19622 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. Rauzi, M., Lenne, P. F. & Lecuit, T. Planar polarized actomyosin contractile flows control epithelial junction remodelling. Nature 468, 1110–1114 (2010)

    Article  ADS  CAS  PubMed  Google Scholar 

  40. Homem, C. C. & Peifer, M. Diaphanous regulates myosin and adherens junctions to control cell contractility and protrusive behavior during morphogenesis. Development 135, 1005–1018 (2008)

    Article  CAS  PubMed  Google Scholar 

  41. Huang, J., Zhou, W., Dong, W., Watson, A. M. & Hong, Y. Directed, efficient, and versatile modifications of the Drosophila genome by genomic engineering. Proc. Natl Acad. Sci. USA 106, 8284–8289 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  42. Royou, A., Field, C., Sisson, J. C., Sullivan, W. & Karess, R. Reassessing the role and dynamics of nonmuscle myosin II during furrow formation in early Drosophila embryos. Mol. Biol. Cell 15, 838–850 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Bellaiche, Y., Gho, M., Kaltschmidt, J. A., Brand, A. H. & Schweisguth, F. Frizzled regulates localization of cell-fate determinants and mitotic spindle rotation during asymmetric cell division. Nature Cell Biol. 3, 50–57 (2001)

    Article  CAS  PubMed  Google Scholar 

  44. Grosshans, J. et al. RhoGEF2 and the formin Dia control the formation of the furrow canal by directed actin assembly during Drosophila cellularisation. Development 132, 1009–1020 (2005)

    Article  CAS  PubMed  Google Scholar 

  45. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nature Methods 9, 676–682 (2012)

    Article  CAS  PubMed  Google Scholar 

  46. Marinari, E. et al. Live-cell delamination counterbalances epithelial growth to limit tissue overcrowding. Nature 484, 542–545 (2012)

    Article  ADS  CAS  PubMed  Google Scholar 

  47. Aigouy, B. et al. Cell flow reorients the axis of planar polarity in the wing epithelium of Drosophila . Cell 142, 773–786 (2010)

    Article  CAS  PubMed  Google Scholar 

  48. Martin, F. A., Herrera, S. C. & Morata, G. Cell competition, growth and size control in the Drosophila wing imaginal disc. Development 136, 3747–3756 (2009)

    Article  CAS  PubMed  Google Scholar 

  49. Burkel, B. M., von Dassow, G. & Bement, W. M. Versatile fluorescent probes for actin filaments based on the actin-binding domain of utrophin. Cell Motil. Cytoskeleton 64, 822–832 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sacan, A., Ferhatosmanoglu, H. & Coskun, H. CellTrack: an open-source software for cell tracking and motility analysis. Bioinformatics 24, 1647–1649 (2008)

    Article  CAS  PubMed  Google Scholar 

  51. Igaki, T. et al. Eiger, a TNF superfamily ligand that triggers the Drosophila JNK pathway. EMBO J. 21, 3009–3018 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Zhang, C. et al. An intergenic regulatory region mediates Drosophila Myc-induced apoptosis and blocks tissue hyperplasia. Oncogene 34, 2385–2397 (2014)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Bubb, M. R., Spector, I., Beyer, B. B. & Fosen, K. M. Effects of jasplakinolide on the kinetics of actin polymerization. An explanation for certain in vivo observations. J. Biol. Chem. 275, 5163–5170 (2000)

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank members of the Moreno laboratory for reading this manuscript. We also thank M. Bergen for help on E-cad fluorescence recovery after photobleaching (FRAP) data collection. We are also very grateful to Y. Bellaïche, O. Baumann, J. Grossahns, H. Jasper, T. Lecuit, L. Legoff, G. Morata, H. Stocker, R. Sousa-Nunes, the Bloomington stock center and the Developmental Studies Hybridoma Bank for sharing stocks and reagents, to B. Aigouy for the Packing analyser software and the Center for Microscopy and Image Analysis (University of Zurich) for sharing equipment. R.L. was supported by an EMBO long-term fellowship (ALTF 366-2012) and a Human Frontier post-doctoral fellowship (LT000178/2013). Work in our laboratory is funded by the European Research Council, the Swiss National Science Foundation, the Josef Steiner Cancer Research Foundation and the Swiss Cancer League.

Author information

Authors and Affiliations

Authors

Contributions

R.L. and E.M. designed the experiments. R.L. performed and analysed the experiments. B.H. generated fwe knockout and fweloseA::mcherry knock-in flies. R.L. and E.M. wrote the manuscript.

Corresponding author

Correspondence to Eduardo Moreno.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Loser elimination also correlates with the shared perimeter with winners in the wing disc.

a, Left: selective plane z-projection of an ex vivo cultured wing disc expressing ubi-Ecad::GFP with loser clones (RFP, purple, WT in tub-myc) 36 h ACI, representative of ten videos. Numerals 1, 2, 3 correspond to the clones shown on the right. Right: snapshots showing the delamination of loser cells and one event of clone splitting preceding cell elimination (3). Scale bars, 5 µm. b, Distribution of the proportion of junctional perimeter of loser cells shared with winners in eliminated cells 1 h before delamination (top) (0 = cell in the centre of the clone, 1 = isolated cell surrounded by winners) and in all the loser cells at t0 (bottom). c, Probability of loser cell elimination for a given surface of contact shared with winners in WT loser cells in tub-dmyc. Statistical tests are Fisher’s exact tests performed with the point 0–0.25 (*P < 0.05; ****P < 10−4). Error bars, 95% confidence interval.

Extended Data Figure 2 Contact-dependent death is triggered downstream of flower.

The transmembrane protein Flower is a central regulator of competition12. The fwelose isoforms (loseA and loseB) are induced downstream of several competition contexts and their expression is necessary for loser elimination and sufficient to drive cell elimination when contacting WT cells12. The contact-dependent communication could occur upstream of fwe (for instance by modifying the levels of induction of fwelose ) or downstream of fwe induction. Several pieces of evidence indicate that it occurs downstream of fwe induction. First, cell death also correlated with shared apical perimeter in clones homogenously expressing fweloseA (Fig. 1c, red curve). Second, using a knock-in fusion fweloseA::mcherry (Extended Data Fig. 2a), we could show that fwelose induction did not correlate with the surface of contact shared with winners (Extended Data Fig. 2b, c) as previously suggested by in situ experiments for fwelose (ref. 12). Finally, the probability of elimination of clones overexpressing fwelose is proportional to the relative differences in fwelose levels inside and outside the clones (Extended Data Fig. 2d, e). Altogether, this suggested a model where cells can compute the relative differences of fwelose levels with all their neighbours through an unknown molecular mechanism. a, Schematic of the modified fwe locus (left) and the resulting messenger RNA of the three isoforms (right). Orange rectangles are exons. The 5′ and 3′ untranslated regions are shown in purple. Exon 5 is specific to each isoform. The red box shows the localization of the mCherry tag at the end of the exon 5 of fweloseA . Note that the vector backbone was conserved in the knock-in line (white, AmpR). b, Two examples of selective plane z-projection of ex vivo cultured wing discs expressing fweloseA::mcherry KI in WT clone in tub-dmyc background (purple) 36 h ACI representative of 12 discs. The clone contour is shown in purple (right). Scale bars, 10 µm. The intensity profile of the white dotted line is shown below. Bottom right, a lateral view of fweloseA::mcherry and its accumulation in the apico-lateral region. c, Scatter plot of fweloseA::mcherry membrane intensity in loser cells in wing disc (WT in tub-myc, y axis) against the proportion of perimeter shared with winner cells (x axis). One dot represents one cell. Pearson correlation coefficient = −0.24. d, UAS-fweloseB::HA clones (GFP) in wing discs 72 h ACI with different concentrations of RU486 in the food media. The expression of fweloseB in clones is the sum of act-G4 flip out driver (constant) and the hormone-sensitive Gal4 (Gal4 switch, expression proportional to the RU486 concentration) while fweloseB is only driven by the Gal4 switch outside the clone. GFP panels were acquired with the same parameters and are shown with the same contrasts. From left to right, discs representative of 43, 28 and 23 discs. Scale bars, 100 µm. e, Average proportion of the wing pouch surface covered by clones (left, purple histogram) and average GFP intensity ratio inside/outside clones (right, green curve, log scale) 72 h ACI. Error bars, s.e.m. Statistical tests are Mann–Whitney tests performed for wing pouch coverage. f, UAS-fweloseB::HA clones (GFP) in wing discs 72 h ACI in a control (left, UAS-lacZ, representative of 19 discs) or upon overexpression of active MRLC (UAS-sqhE20E21, right, representative of 11 discs). Scale bars, 100 µm. g, Average proportion of the wing pouch surface covered by clones 72 h ACI. Error bars, s.e.m. Statistical test is a Mann–Whitney test.

Extended Data Figure 3 E-cad and active MRLC rescue losers only through the change of winner–loser surface of contact.

a, Supercompetition assay in the wing disc 24 h, 48 h and 72 h ACI (purple: loser cells) in normal competition (loser cells overexpressing β-gal), upon limitation of cell mixing (UAS-ecad and UAS-sqhE20E21, a constitutively active MRLC) and in WT clones in WT background (no competition). Left: schematic of the expected effect on clone shape; black line thickness is the strength of cell–cell adhesion, red lines show actomyosin network. Middle: example of wing discs at different time ACI; scale bars = 100 µm. See Extended Data Fig. 3b for the number of discs scanned for each condition. Right: close-up views of clones overexpressing E-cad (top) and active MRLC (bottom). Active MRLC induces apical actin accumulation and partial apical constriction. Scale bars, 5 µm. b, c, Density of loser clones (b) and averaged loser clone size (c) at 24, 48 and 72 h ACI in the wing pouch. Error bars, s.e.m.; n is the number of wing discs (b) or the number of clones (c). Statistical tests are Mann–Whitney tests performed with the control competition (in green, UAS-βgal in tub-dmyc) or with control without competition (in orange, WT in WT). NS, P > 0.05; *P < 0.05; **P < 10−2; ***P < 10−3. Note that we did not find significant differences of clone size at 72 h as the few clones remaining for the control competition were at the periphery of the wing disc where competition is less effective. d, E-cad and active MRLC do not have a cell autonomous effect on growth. Left: wing discs showing WT clones (act<y<gal4, UAS-mcd8::GFP, purple) overexpressing β-gal, E-cad or sqhE20E21 (active MRLC) 48 h ACI, representative of 56, 13 and 17 discs, respectively. The insets show the clones marked with an asterisk. Scale bars, 100 µm. Right: average clone surface, n = number of clones, error bars are s.e.m. NS, P > 0.05, Mann–Whitney tests. e, E-cad and active MRLC do not prevent genetically induced apoptosis. Left: adult eye of a WT fly (oregonR), and flies with abnormal eye morphology due to induction of JNK-dependent death in the eyes (eye-specific gal4, GMR-gal4 and UAS-eiger, the fly orthologue of TNF35,51) expressing β-gal (control), diap1 (apoptosis inhibition), E-cad or sqhE20E21 (active MRLC), representative of 30, 34, 37, 29 and 29 adults, respectively. Right: averaged eye surface in pixels (a.u., arbitrary units); n = number of flies; error bars, s.e.m. P values, Mann–Whitney tests. f, E-cad and active MRLC do not modify the probability of loser death for a given surface of contact with winners. Probability of loser cell elimination in the pupal notum for a given surface of contact shared with winners in myc-dependent competition (purple, from Fig. 1d), in WT cells in WT background (control, dotted green, from Fig. 1d), or in losers overexpressing E-cad (dotted red) or active MRLC (sqh-E20E21, dotted pink). Statistical tests are Fisher’s exact tests performed with myc-dependent competition (purple) (NS, P > 0.05). Error bars, 95% confidence intervals.

Extended Data Figure 4 Clone fragmentation does not correlate with clone size.

a, Twin clones 48 h ACI marked with two copies of GFP (green) and absence of β-gal or two copies of β-gal (red) and absence of GFP (FRT40A ubi-nlsGFP/FRT40A bcat-βgal). Left: non-fragmented clones. Middle and right: fragmented clones (the GFP sibling clone is used as a reference) with clone cells separated by a single cell (middle) or more than one cell (right). b, Proportion of fragmented clones 48 h ACI in WT GFP clones in WT background (blue, from Fig. 2d) quantified with the one cell distance criteria. Same quantification in FRT40A ubi-nlsGFP/FRT40A bcat-βgal where 2×βgal clones were counted as split when clone cells were separated by a single cell and were associated with a continuous group of sibling 2×GFP cells. This quantification showed no differences with the WT GFP clones in WT background, demonstrating that our method does not produce false positive results. However, it slightly underestimates the total number of fragmented clones (compare with ‘all’, where every split 2×βgal clone is counted); n = number of clones. Statistical tests are Fisher’s exact tests performed with WT GFP clones in WT background (blue). c, Wing discs 48 h ACI in control (WT in WT) and in supercompetition assay with loser cells expressing β-gal, UAS-ecad, UAS-sqhE20E21, UAS-diap1 (an endogenous apoptosis inhibitor) or UAS-p35 (a bacterial caspase 3 inhibitor) and fwelose RNAi; or after induction of winner clones (UAS-p35, UAS-myc in WT, p35 is necessary to block the cell autonomous death induced by high myc overexpression52, and WT in M/+ where WT clones have no GFP). White arrowheads show fragmented clones. Insets show close-up view of representative clones (see Fig. 2d for number of clones analysed). Scale bars, 100 µm. d, Scatter plot showing the proportion of fragmented clone (y axis) against the average size of clone (x axis) 48 h ACI for all the different genotypes used in this study (see legend). One dot represents one fragmentation assay. There is no correlation between clone size and clone splitting. Pearson correlation coefficient = 0.14. Note also that without the outlier point (UAS-pten RNAi in WT) the correlation is close to 0 (correlation coefficient = −0.036).

Extended Data Figure 5 Clone fragmentation is driven by winner–loser mixing.

a, Left: schematic showing loser cells (WT, purple) and winner cells (tub-dmyc, green). Orange junctions are junctions shared by a winner and a loser cell (winner–loser junctions). Dark green junctions are the winner–winner junctions (sharing one vertex with a loser cell) and dark purple are the loser–loser junctions (sharing one vertex with a winner cell) used for the analysis. Right: proportion of junctions undergoing a single remodelling event over 10 h in the notum. P values, Fisher’s exact tests. b, Probability to undergo additional junction remodelling after a first remodelling event. n = number of junctions. P values, Fisher’s exact tests. This suggests that winner–loser junctions undergoing first remodelling events have a higher probability of reverting to the initial topology. c, Left: snapshots of WT cells and tub-dmyc cells in the notum (no clone) at t0. Purple junctions disappear after 10 h while green junctions remain unchanged (see Supplementary Video 8, representative of three and four videos, respectively). Scale bars, 10 µm. Right: proportion of junction disappearing after 10 h. P values, Fisher’s exact tests. d, Examples of clones in the notum at t0 and 10 h later for various genotypes. E-cad::GFP is in green and UAS–RFP in purple. The white dotted lines show clone contours. See Extended Data Fig. 5e for the number of clones analysed for each. Scale bars, 10 µm. e, Fold change of clone compactness after 10 h in the notum (see Methods). One dot represents one clone. The bars are averages. P values, Mann–Whitney tests performed with WT in WT (green) or WT in tub-dmyc (purple) (NS, P > 0.05; *P < 0.05; **P < 10−2; ***P < 10−3; ****P < 10−4).

Extended Data Figure 6 Differential PIP3 drives clone splitting.

a, b, The z-projection of tGPH (PIP3, green and pseudocolour) in the pupal notum in clones (RFP, purple) overexpressing a dominant negative of PI3K (UAS-pi3kDN (a), representative of 14 clones) or upon downregulation of PTEN (UAS-pten RNAi (b), representative of 10 clones). White dotted lines show clone boundaries. Scale bars, 10 µm. c, The z-projection of a phospho-Akt staining (green) in wing disc overexpressing fweloseA::HA in the posterior compartment (purple, eng-G4, representative of 16 discs). Scale bar, 100 µm. d, phosphor-Akt in WT clones (no GFP) surrounded by M/+ cells (representative of 21 discs). White arrows point to some WT clones. Scale bar, 100 µm. e, The z-projections of phospho-Akt (green), GFP (magenta) in wing discs after removal of one additional copy of myc in the posterior compartment and 24 h of starvation (hh-gal4, UAS-flp × tub>dmyc>gal4, UAS–GFP, representative of ten discs). Scale bar, 100 µm. f, The z-projection of tGPH (PIP3) in loser clones (supercompetition assay, purple are losers) in the pupal notum after 48 h of starvation. Representative of 28 clones. Scale bars, 10 µm. g, Quantification of the mean junction membrane intensity of tGPH in winner–winner, loser–loser and winner–loser junctions in the notum; n = number of junctions. Error bars, s.e.m. P values, Mann–Whitney tests. h, Wing discs with loser cells (supercompetition assay) 48 h ACI after 24 h of starvation, or upon removal of one copy of Drosophila insulin-like peptides (Dilp1 to Dilp5). Insets show representative clones of 650 and 471 clones, respectively. Scale bars, 100 µm. i, Proportion of fragmented clones; n = number of clones. Statistical tests are Fisher’s exact tests performed with WT (in blue, WT in WT) or control competition (in green, UAS-βgal in tub-dmyc). NS, P > 0.05; *P < 0.05; **P < 10−2. WT in WT and WT in tub-dmyc come from Fig. 2d. This result suggests that losers and winners have differential abilities in processing and responding to extracellular insulin. j, Wing discs showing UAS-βgal clones (loser, purple) in tub-dmyc background 72 h ACI with or without 24 h of starvation, representative of 32 and 36 discs. Scale bars, 100 µm. k, Average density of loser clones (left) and average proportion of the wing pouch covered with GFP-positive cells (right) 72 h ACI. Error bars, s.e.m. P values, Mann–Whitney tests.

Extended Data Figure 7 Akt is not sufficient to explain winner–loser mixing, and E-cad, myosin II and Dachs do not show visible defects in loser clones.

a, Wing discs showing clones upon downregulation of Akt (UAS-akt RNAi, left) or upregulation of Akt (UAS-akt, right) 48 h ACI. Insets show close-up views of a representative clone in each condition for 203 and 169 clones, respectively. Scale bars, 100 µm. b, Proportion of fragmented clones. WT in WT comes from Fig. 2d. UAS-pi3kDN in WT and UAS-pten RNAi in WT come from Fig. 3d, e. n = number of clones. Statistical tests are Fisher’s exact tests performed with WT (in blue, WT in WT) or as indicated by the dotted lines. NS, P > 0.05; *P < 0.05; **P < 10−2; ***P < 10−3. c, The z-projection of endo-Ecad::GFP (knock-in line) in the pupal notum. Loser clones are marked with RFP (WT in tub-dmyc background, representative of 30 clones and 3 nota). White line marks the clone contour. Scale bar, 10 µm. d, Average normalized intensity recovery curves of endo-Ecad::GFP after photobleaching in loser–loser junctions (WT in tub-dmyc, purple) and in winner–winner junctions (tub-dmyc) in the notum. Error bars, s.e.m. e, The z-projection of MRLC::GFP (endogenous promoter, spaghetti-squashed, sqh) in the pupal notum. Loser clones are marked with RFP (WT in tub-dmyc background, representative of 30 clones and 5 nota). White line marks the clone contour. Scale bar, 10 µm. Note that utABD::GFP (as shown in Fig. 4a) is under the control of the same promoter, thus the actin reduction in losers is not due to a reduction of sqh promoter activity. f, The z-projection of Dachs::GFP (endogenous promoter) in the pupal notum. Loser clones are marked with RFP (WT in tub-dmyc background, representative of 17 clones and 2 nota). White line marks the clone contour. Scale bar, 10 µm.

Extended Data Figure 8 F-actin turnover/polymerization rate is reduced in loser junctions.

The utABD::GFP has been previously used to assess actin dynamics39,49. This is further demonstrated by the experiment described in a and b. a, Ex vivo cultured wing discs in control media (DMSO 0.2%) or in media containing 2 µM jasplakilonide, an inhibitor or actin turnover53. White rectangles are the bleached zones. White dotted line is that used for the kymographs shown on the right; t = 0 s (white dotted line on kymographs) is the time of bleaching. Images representative of 25 FRAP experiments for each condition. Scale bars, 5 µm. b, Averaged normalized recovery curves of utABD::GFP intensity after photobleaching in control and jasplakinolide-treated wing discs. Error bars, s.e.m. c, Averaged utABD::GFP normalized intensity recovery curves in loser–loser junctions (purple), winner–winner junctions (green) and winner–loser junctions (orange) after photobleaching (WT losers in tub-dmyc) in the notum. Error bars, s.e.m. d, Distribution of the characteristic times of utABD::GFP intensity recovery in winner–winner, loser–loser and winner–loser junctions. P values, Mann–Whitney tests. e, Top, schematic of the FRAP experiments; two ROIs are bleached simultaneously in the same winner cell (tub-dmyc) sharing contacts with a loser cell (WT). Grey square, winner–loser bleached junction; black square, winner–winner bleached junction. Bottom, confocal image in the pupal notum 48 h ACI of utABD::GFP in a supercompetition assay (purple cells, losers). Scale bar, 5 µm. Squares show the simultaneously bleached regions (1, winner–winner junction; 2, winner–loser junction); the white dotted line is the line used for the kymograph shown on the right, representative of 41 FRAP experiments. f, Distribution of the fold change of the characteristic time of intensity recovery in the winner–winner junction compared with a winner–loser junction of the same cell ((τw–wτw–l)/τw–w). One dot represents one cell. The bar is the average. The statistical test is a one-sample t-test with 0 as reference value.

Extended Data Figure 9 Filamentous actin defects are necessary and sufficient to drive clone fragmentation.

a, The z-projection of phalloidin (green) and GFP (magenta) in a wing disc containing WT clones (no GFP) in M/+ background representative of 20 discs. Top inset shows phalloidin signal for two WT clones (white lines). Right: close-up views of cell shape in two WT clones. Scale bar, 100 µm. b, Wing discs 48 h ACI upon silencing of Arp3 (arp3 RNAi) in WT background, in supercompetition assay with loser cells expressing Arp3::GFP, silencing of Dia (dia RNAi) in WT background, and in supercompetition assay with loser cells expressing Dia::GFP. Discs correspond to experiments quantified in Fig. 4d; control WT and control supercompetition assays are the same as in Fig. 2d. White arrowheads show fragmented clones. Insets show close-up view of a representative clone in each condition out of 108, 174, 259 and 233 clones analysed, respectively. Scale bars, 100 µm. c, Wing disc 48 h ACI. The clones without GFP are homozygous mutant for diaphanous (dia5 , hypomorphic allele40), the sibling WT clones have two copies of GFP. Four close-up views of fragmented mutant clones are shown on the right, representative of 132 clones analysed. The proportion of fragmented clones is 39.3%, counting every fragmented clone (including patches separated by more than one cell). Scale bar, 100 µm. d, Top: representative wing discs during supercompetition 72 ACI in loser cells (purple, GFP) overexpressing β-gal (control, representative of 24 discs) or Dia::GFP (representative of 26 discs). Scale bar, 100 µm. Bottom: quantification of the mean loser clone density and the average proportion of the wing pouch surface covered by loser clones. *P < 0.05; **P < 10−2; Mann–Whitney test. Error bars, s.e.m. e, Level of expression of expanded (exp-lacZ), a downstream target of Yki/YAP, in two representative examples of clones overexpressing Dia::GFP (hs-flp22, act<y<gal4; UAS–GFP × UAS-dia::GFP) 72 h ACI (representative of 31 clones out of 16 wing discs). White lines show the contour of the clones. Scale bars, 5 µm.

Extended Data Figure 10 PIP3 acts upstream of actin defects.

Starvation was sufficient to abolish differences in F-actin between compartments expressing different levels of myc (Extended Data Fig. 10a), whereas overexpression of fweloseA in the posterior compartment did not modify F-actin (Extended Data Fig. 10b). Moreover, PIP3 downregulation in a full compartment was sufficient to downregulate actin (Extended Data Fig. 10c) and junctional Dia (Extended Data Fig. 10d). Finally, overexpression of Dia significantly reduced the number of fragmented clones upon downgregulation of PIP3, whereas knocking down Dia and increasing PIP3 impaired the rescue of loser fragmentation (Extended Data Figure 10e, f, P = 0.017 and 0.003, respectively). Altogether, we concluded that actin defects are driven by the modulation of PIP3 in loser cells. a, The z-projections of utABD::GFP (green, F-actin) and RFP (magenta) in wing discs after removal of one additional copy of myc in the posterior compartment (hh-gal4, UAS-flp × tub>dmyc>gal4, UAS–RFP, left, representative of 20 discs) and after 24 h of starvation (right, representative of 9 discs out of 10). Scale bars, 100 µm. b, The z-projection of utABD::GFP (green, F-actin) in a wing disc overexpressing fweloseA::HA in the posterior compartment (purple, eng-G4, representative of 20 discs). Scale bar, 100 µm. c, Stainings of utABD::GFP and phalloidin in control wing discs (hh-gal4 alone, representative of 18 discs) and upon reduction of PIP3 in the posterior compartment using hh-gal4 and UAS-pi3kDN (see top scheme: A, anterior; P, posterior; D, dorsal; V, ventral, representative of 11 discs). The posterior compartment is at the right side of the Patched (Ptc) stripe marked in blue. Scale bars, 100 µm. Bottom: averaged normalized intensity line profiles along the antero-posterior axis for utABD::GFP (green and yellow) and Ptc (blue). Position 0 corresponds to the maximum inflexion of Ptc intensity peak (right side of the stripe); n = number of wing discs. Error bars, s.e.m. d, Dia staining in control (hh-gal4 alone, representative of 18 discs) and upon reduction of PIP3 in the posterior compartment using hh-gal4 and UAS-pi3kDN (representative of 18 discs). Scale bars, 100 µm. Bottom: averaged normalized intensity line profile taken along the antero-posterior axis for Dia (green and yellow) and Ptc (blue); n = number of wing discs. Error bars, s.e.m. e, Wing discs 48 h ACI showing clones (hs-flp22; act<y<gal4; UAS–GFP purple) in WT background overexpressing a dominant negative form of PI3K (UAS-pi3kDN) and dia::GFP, or loser clones in tub-dmyc background overexpressing a constitutively active form of PI3K (pi3kCA) and dia RNAi. The white arrowhead shows a fragmented clone. Insets show close-up views of a representative clone out of 112 and 86 clones, respectively. Scale bars, 100 µm. f, Proportion of fragmented clones. Blue bars are act<y<Gal4 clones in WT background; green bars are loser clones in tub-dmyc background. WT in WT and UAS-βgal in tub-dmyc (supercompetition assay) come from Fig. 2d. UAS-pi3kDN in WT and pi3kCA in tub-dmyc come from Fig. 3d, e; n = number of clones. Statistical tests are Fisher’s exact tests performed with WT in WT (in blue) or UAS-βgal in tub-dmyc (in green) or as indicated by the black dotted lines. NS, P > 0.05; *P < 0.05; ***P < 10−3; ****P < 10−4.

Supplementary information

Supplementary Information

This file contains a Supplementary Discussion and additional references. (PDF 104 kb)

Live imaging of loser cells (wt in tub-dmyc)

ubi-Ecad.::GFP (green, left) and UAS-mcd8::RFP (purple, wt loser cells in tub-dmyc background) in the pupal notum. White arrows point to delaminating cells (48h after clone induction, 20h after pupation). Note that the blurred signal moving in the background are out of focus macrophages. Scale bar=10μm. (MOV 5138 kb)

Live imaging of wt cells (wt in wt)

ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, wt cells in wt background) in the pupal notum. White arrows point to delaminating cells. Scale bar=10μm. (MOV 9620 kb)

Live imaging of loser cell elimination (wt in tub-dmyc) in a wing disc

Three examples of clones expressing ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, wt loser cells in tub-dmyc background) in ex-vivo cultured wing disc. The first frames show the full wing disc and the localisation of the clones. Movies stop when the clones get out of frame. Scale bar=5μm. (MOV 3464 kb)

Live imaging of loser cells upon inhibition of apoptosis (UAS-diap1 in tub-dmyc)

ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, UAS-diap1 loser cells in tub-dmyc background) in the pupal notum. White arrows point to spontaneous delamination occurring outside the clone. Note the absence of delamination in the clone. Scale bar=10μm. (MOV 13279 kb)

Live imaging of cells overexpressing fewloseA

ubi-Ecad.::GFP (green, and gray) and UAS-RFP (purple, UAS-fewloseA cells in wt background) in the pupal notum. White arrows point to loser delaminating cells. The first frames show the localisation of the clone (light blue). The RFP is not shown at later time point as it was rapidly bleached. Scale bar=10μm. (MOV 4972 kb)

Live imaging of loser cells upon silencing of fewlose (UAS-fwelose RNAi in tub-dmyc)

ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, UAS-fwelose RNAi loser cells in tub-dmyc background) in the pupal notum. White arrows point to delaminating cells. Scale bar=10μm. (MOV 11269 kb)

Junction remodelling and cell intercalation at loser clone boundaries

Two examples of persistent junction remodelling in the pupal notum leading to clone splitting (left) or to the loss of a loser/loser junction (right). ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, wt loser cells in tub-dmyc background). The initial junction topology is shown in blue, the final topology is shown in orange. Scale bar=10μm. (MOV 1466 kb)

Junction remodelling in wt and tub-dmyc nota

ubi-Ecad.::GFP in a wt pupal notum (left) or in a tub-dmyc notum (right). Purple junctions are disappearing junctions, green junctions are cell-cell interfaces still present after 10h. Scale bar=10μm. (MOV 11804 kb)

F-actin dynamics in loser (wt in tub-dmyc) and winner junctions

FRAPs of junctional sqh-utABD.::GFP in a loser-loser (left), a winner-winner (middle) or a winner-loser (right) junction in the pupal notum (wt loser cells in tub-dmyc). White circles show the bleached ROI. Scale bar=5μm. (MOV 3427 kb)

Junction ablation in winner and loser junctions

Junction relaxation after laser ablation in the pupal notum 48h after clone induction. Scale bars=2µm. First raw: supercompetition assay, winner-winner (left), loser-loser (middle) and winner-loser (right) junctions. ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, wt cells in tub-dmyc background). Second raw: Downregulation of PIP3 in clones. wt-wt (left), pi3kDN-pi3kDN (middle) and wt-pi3kDN (right) junctions. ubi-Ecad.::GFP (green) and UAS-RFP (purple, UAS-pi3kDN cells in wt background). Third raw: loser cells overexpressing Dia::GFP, winner-winner (left), loser-loser (middle) and winner-loser (right) junctions. ubi-Ecad.::GFP (gray) and UAS-diaGFP (gray, junction and cytoplasmic signal, UAS-dia::GFP cells in tub-dmyc background). Fourth raw: Loser cells after starvation, winner-winner (left), loser-loser (middle) and winner-loser (right) junctions. ubi-Ecad.::GFP (green) and UAS-mcd8::RFP (purple, wt cells in tub-dmyc background) in the pupal notum 48h after clone induction and 48h starvation. Note that the frame rate is different for this movie. Due to low signals, we also used a Kalman filter for a better display. (MOV 1073 kb)

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Levayer, R., Hauert, B. & Moreno, E. Cell mixing induced by myc is required for competitive tissue invasion and destruction. Nature 524, 476–480 (2015). https://doi.org/10.1038/nature14684

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