Endothelial cells show surprising cell rearrangement behaviour during angiogenic sprouting; however, the underlying mechanisms and functional importance remain unclear. By combining computational modelling with experimentation, we identify that Notch/VEGFR-regulated differential dynamics of VE-cadherin junctions drive functional endothelial cell rearrangements during sprouting. We propose that continual flux in Notch signalling levels in individual cells results in differential VE-cadherin turnover and junctional-cortex protrusions, which powers differential cell movement. In cultured endothelial cells, Notch signalling quantitatively reduced junctional VE-cadherin mobility. In simulations, only differential adhesion dynamics generated long-range position changes, required for tip cell competition and stalk cell intercalation. Simulation and quantitative image analysis on VE-cadherin junctional patterning in vivo identified that differential VE-cadherin mobility is lost under pathological high VEGF conditions, in retinopathy and tumour vessels. Our results provide a mechanistic concept for how cells rearrange during normal sprouting and how rearrangement switches to generate abnormal vessels in pathologies.
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This work was supported by Cancer Research UK, the Lister Institute of Preventive Medicine, the Leducq transatlantic Network ARTEMIS and the ERC starting grant REshape (311719). C.F. is supported by a Marie Curie FP7 people initiative Fellowship. R.B. is supported by a HFSP fellowship. AP was financially supported by EPSRC grant EP/I031758/1. G.C. and D.V. were supported by funds from the Deutsche Forschungsgemeinschaft (SFB629) and the Max-Planck-Society. L.C.W. and S.W. are supported by grants from the Knut and Alice Wallenberg Foundation and from the Association for International Cancer Research. We thank B. Cruys (KU Leuven) and C. Lewis (MIT) for comments on the manuscript. We thank R. Chaleil for his support and maintenance of the high-performance computing system.
The authors declare no competing financial interests.
Integrated supplementary information
Quantification of inhibited/active VE-cadherin patterning in mouse retinas (a) Representative confocal microscopy images of VE-cadherin antibody staining from P22 retinal blood vessels. Inserts show higher magnification of selected regions from vascular sprouts. In the mature retina, VE-cadherin staining shows a homogenous patterning in all different blood vessels, with linear lines without signs of VE-cadherin endocytosis or serrate junctions. (b) NICD GOF retinas show a reduction in patches of VE-cadherin stainings classified as active and Dll4 Fc Ab retinas show the opposite, with a shift towards patches classified as active. 6 samples analysed across three separate retinas in each case (mean and s.d.). (c) VEGFR-1 injected retinas show a clear reduction in active VE-cadherin patch classifications. 6 samples analysed across three separate retinas in each case (mean and s.d.) (d–e) representative patches from the classification software showing a striking difference between VE-cadherin junctional profiles of NICD GOF retinas (d) and Dll4-Ab retinas (e). Colour bar indicates min to max pixel intensity (images were 32-bit), which was the same across both samples.
Automatic feature detection of objects validates the hand-classification of retinal vasculature as unbiased. Patch classifications 1 to 6 (highly active to highly inhibited) shown numbered along the x-axis. For each experimental setup every patch classified was assessed using the automatic feature detection software we developed (se Methods section for details) to quantify the VE-cadherin staining, in each hand-classified patch, in terms of the number of: large objects (junction segments), small objects (vesicles), line serratedness (high score = more serrated) and line straightness (high score = more straight). Mean and s.d. shown, n = 6 images from 3 retinas for each. Consistently across retinas patched we see a trend where patches classified as highly active contain more big and small objects (disjointed junctional segments and vesicles) and junction lines are less straight/more serrated than in those patches classified as inhibited. Highly inhibited patches consistently contain less vesicles and straighter lines. As the trends here match the original hand-classification definitions of active and inhibited patches this validates that hand classification was performed in an unbiased manner. Were a biased approach used, and a user hand classified patches without ensuring that patches have the required VE-cadherin patterning for that class, then we would expect to see no correlating trend between these classifications and feature detection quantification.
Sensitivity of rearrangement behaviour and tip cell competition to changes in Temperature (T) in the CPM and the differential adhesion threshold (η) in M1. (a) Varying T in a wt:wt vessel. (b–e) Using 1:9 wt:VEGFR-2 + /− chimera with best match mechanism M1(A)M2(A), results averaged over 50 runs for each parameter setting short and long range sensitivity to T was investigated. (b, c) Short range sensitivity analysis, T = 0 to 25 in increments of 5. If T = 0 the het contribution to the tip is at its lowest (28%) compared to 52% measured in this chimera setting in vitro, suggesting noise helps the hets to maintain the tip against the wt for longer in this chimera. (d, e) Long range sensitivity analysis, T = 0 to 100 in increments of 50. If noise levels are increased (T = 50, 100) hets now over contribute to the tip and jostling times are highly increased, which increases the apparent overtakes observed with the Artificial Lars method. However, reigning tip cell leaders are close to zero indicating that the hets over contribute to the tip due to ineffectual jostling rather than ‘clear overtakes’—defined as position interchanges where the new leader remains at the tip for at least 30 mins. Optimal setting used in main simulations, T = 10 shown as vertical dotted line. In vitro het contribution to the tip (52%) shown as horizontal dotted line. (f, g) Sensitivity to changes in M1 (η) using a 1:9 wt:VEGFR-2 + /− simulated chimera, averaged over 50 runs for each parameter setting. η determines the threshold of VEGFR-2 activity level per cell that determines a cell to be classified as ‘weakly adhesive’ otherwise it is strongly adhesive. If η = 0 any activity through VEGFR-2, no matter how small, will cause the cell to be weakly adhesive. As η increases so does the amount of activity through VEGFR-2 required for a cell to be classified as weakly adhesive, affecting the balance of differential adhesion and rearrangement behaviour. Dotted vertical lines show optimised value. Horizontal dotted line show in vitro het contribution to the tip measurement. Mean and s.e.m. shown.
Sensitivity of cell rearrangement and tip cell overtaking behaviour to changes in relative strength (S) of the two mechanisms and to the filopodia extension regime used to model VEGFR-2 heterozygosity. (a–e) Cells simulated in a wt:wt vessel with the different mechanism variants, results averaged over 50 runs varying S, mean and s.e.m shown. All values plotted on left y-axis except jostling time, plotted on right y-axis. Dotted line shows the optimal value (75%) across all variants, which gives maximised overtaking behaviour (Artificial Lars and Reginer frequencies) whilst minimising jostling and still matching the approximate 4hr overtaking rate. This value was then used in all further simulations. (f–m) Tip cell competition dynamics over time in simulation with variants of VEGFR-2 heterozygous modelling. (f–i) Case 1: filopodia extension is driven by the ratio of a memAgents current active VEGFR-2 level proportional to the full amount possible in a wt cell. (j–m) Case 2: filopodia dynamics are driven by the ratio of a memAgents current active VEGFR-2 level proportional to the current cells own maximum VEGFR-2 expression level, so halved for het cells. (f, h, j, l) cell number of current tip cell over time as observed by Artificial Lars method in 6 different runs (each colour is one run). (g, i, k, m) mutant status of tip cell as observed by Artificial Lars method in 6 different runs (each colour is one run) 0 = wt, 1 = het. In each graph one run is highlighted (blue thick line) to aid comparison between cases.
Identifying that differential adhesion is required to drive long-range positional interchange of active cells. (a, b, c) The average (+ /− sem) amount of time each cell spends at the tip given its initial position, averaged over 50 simulations. (a) Cells are initialised in the positions shown. (b) The M1 adhesion variants simulated in a wt:wt sprout show a significant difference in cells initialised further back in the sprout (cell 1 and 2 are furthest from the tip) ability to reach the tip meaning that cells further back are not driving forward as reliably, even if they are selected as active cells by notch signalling. Kruskal Wallis test shows initial position significantly affects tip cell occupancy except with differential adhesion (excluding cell 10, which starts as the tip and has a bias in all cases to occupy the tip for longer periods): All Weak: p = 2.0841e − 9, Differential adhesion: p = 0.4962, All Strong: p = 1.8087e − 5. (c) In a 1:9 wt: VEGFR-2 + /− chimera with cell 1 designated as the only wt cell in each run. It is clear only differential adhesion can match the experimental data, where the wt cell contributes to the tip 50% of the time even when initialised in the furthest position on every run. The lack of intercalation in the uniform adhesion regimes (M1ii and M1iii) show only a very short time spent at the tip. (d) To investigate if the short time wt cells occupy the tip with uniform adhesion is due to a delay in reaching the position or because they reach it quickly but then are jostled away we measured the first time the wt cell (initialised at the rear, cell 1 in a 1:9 wt:VEGFR-2 + /− chimera) reaches the tip with the Artificial Lars observation method. Averaged over 100 h of simulations, giving n = 22, 77, 25, 35, 69, 24 for columns left to right). All significances found to be P < 0.0001 unpaired t-test. (e, f) Kymographs of cell position changes in the x axis (toward the tip, × increases) over one simulation of the 1:9 wt:VEGFR-2 + /− chimera with the wt cell initialised at the rear (wt cells positional changes shown as the thick black). See also Supplementary Videos 1–5.
Original confocal images of the heat mapped pathological vessels. Glioblastoma vessels from Fig. 8(c, d). (a, c) vascular detection using mTmG Pdgfb-iCre mice. (b, d) Endogenous VE-cadherin antibody staining. Both vessels, even the one classified as mostly inhibited (c, d and Fig. 8d), are currently angiogenic as there are many filopodia evident. This observation reinforces the prediction that actively growing vessels could experience waves and phases of synchronous inhibition and halting of rearrangement. e, f) show vessels from the OIR experiments corresponding to the heat map in Fig. 8(e). (e) Vascular detection using isolectin staining (f) Endogenous VE-cadherin antibody staining in the OIR retina.
Screenshots from a simulation showing how the spring-agent mesh, defined in continuous space is snapped to the 3D integer grid for fast agent-rule updates. (1) Springs and Agents in mesh only (junction springs purple). (2) Triangulated mesh surface shown in black, See 1 for details. (3–5) Node agents snapped to the integer grid in the spring mesh (black cubes). Spring agents which sit between nodes, along springs of filopodia (light grey cubes). Surface agents (dark grey cubes) are created on the integer grid anywhere that the triangulated mesh surface passes through that does not already contain a node agent from the same cell, ensuring full coverage in 3D integer space of the otherwise continuous mesh surface for fast agent rule updates. (6–10) Section of 1–4 showing only first 2 layers in the integer grid for greater clarity. Integer grid delineated by green lines.
Flow diagram of the Cellular Potts Module as adapted and included in the memAgent-spring model.
Supplementary Information (PDF 4226 kb)
Simulation of a wt:wt vessel representing 13 h of sprouting with the best matching mechanism combination M1(A)M2(A), differential adhesion and Notch driven polarised movement (related to Fig. 3).
Cells are shown in different colours to show individual cell behaviour and movement more clearly. Different clear leaders emerge and overtake to become the new tip cell, with periods of battling of two cells in between. Cells at the rear of the vessel initially can be seen to move right to the front. (MPG 8312 kb)
Simulation of a wt:wt vessel representing 9hrs of sprouting, with mechanism M1(B)M2(A), where all cells are strongly adhesive but also performing Notch driven polarised movement (related to Fig. 3).
Cells are shown in different colours to show individual cell behaviour and movement more clearly. The dark blue cell is actually at the tip for the entire simulation but s constantly jostled and battled with by two neighbours. The cells stay close to their initial position throughout the run. (MPG 5636 kb)
Simulation of a wt:wt vessel representing 13 h of sprouting with combination M1(C)M2(A), where all cells are weakly adhesive combined with Notch driven polarised movement (related to Fig. 3).
Cells are shown in different colours to show individual cell behaviour and movement more clearly. No clear leaders or overtakes are seen, instead the front is a constant battling ground. The competition between M1 and M2 is evident, the weakly adhesive junctions score the highest energy penalty so every elongation event through M2 is followed by a rounding up of cells to counter the rise in energy that this elongation causes. Semi stable states are visible where the cells reach a conformation with all cells having short straight junctions, but M2 moves push it out of these and high levels of jostling occur to re-find this short junction energy minima. Cells do not move far from their original position. (MPG 8328 kb)
DAPT simulated treatment on a wt:wt vessel with mechanism M1(A)M2(A) differential adhesion and Notch driven polarised movement, representing 9 h of sprouting time (related to Fig. 3).
DAPT has now knocked out any differential nature to the mechanisms and the vessel shows jostling behaviour similar to that seen in Videos 2 and 3 with the non-differential adhesion regimes. There are no clear overtakes of new tip cells as seen in the normal wt:wt case in Video 1. Instead the same dominant green cell remains at the tip with almost constant battling with two other neighbours. (MPG 5014 kb)
A 1:9 wt:VEGFR-2 + /− chimera, het cells shown in green, wt in black with the M1(A)M2(A) mechanism with differential adhesion and Notch driven polarised movement (related to Fig. 3).
The wt cell is initialised at the furthest point in the sprout but it is shown to travel right to the tip to take the lead. (MPG 7914 kb)
A 1:9 wt:VEGFR-2 + /− chimera, het cells shown in green, wt in black with the non-matching M1(B)M2(A) mechanism where all cells are strongly adhesive plus Notch driven polarised movement (related to Fig. 3).
The wt cell is initialised at the furthest point in the sprout as in Video 4, but without differential adhesion, M1 and M2 compete, so even though the cell should be strongly competitive, the high energy cost of M2 elongation moves to push it towards the tip, means M1 pushes the cell back and shortens its junctions. The wt cell only makes it half way before being jostled back. (MPG 6862 kb)
p-VEGFR-2 dynamics in a wt:wt vessel with mechanism M1(A)M2(A) differential adhesion and Notch driven polarised movement (related to Fig. 3).
Green-purple intensity represents the pVEGR-2 level (high to low) and also indicates the actively moving cells (green cells are more actively moving). As the cells rearrange, the location and activity of these cells changes. An active cell may move forward, meet another active cell, and both become inhibited, whilst new active cells spring up as regions of all inhibited cells are transiently created during the rearrangements. This shows that though an alternating salt and pepper pattern of active/inhibited cell neighbours is evident, there are also phases when highly active cells neighbour each other, while they are battling and other times when the whole sprout can appear inhibited as a new pattern is developing. The actual junctions shapes are straighter when cells are inhibited (purple) compared to more complex dynamic shapes when the cells are actively jostling forward. (MPG 5456 kb)
Three-dimensional rotation of maximum projection of entire z-stack confocal microscopy images from eGFP-tagged VE-cadherin (green). It is possible to clearly observe differential adherens junction patterns in individual cells, with some having highly active junctions and endocytic vesicles, while others presented a more regular linear shape (inhibited). (MOV 4496 kb)
Three-dimensional rotation of maximum projection of entire z-stack confocal microscopy images from eGFP-tagged VE-cadherin (green). Most of endothelial cells present vesicular and serrated irregular patterning of adherens junctions in DAPT-treated embryoid bodies, with scarce straight-line junctional profiles. (MOV 6820 kb)
Time-lapse of a DMSO-treated DsRed (wt): VE-cadherin-eGFP embryoid body vascular sprout (related to Fig. 5).
Time-lapse confocal microscopy of a vascular sprout from embryoid bodies generated from 1:1 mix of DsRed (red) and VE-cadherin-eGFP (green) expressing ES cells. In this video is possible to observe the dynamic behaviour of single cells (DsRed) shuffling in the vascular sprout, and the endothelial cell junctions dynamics (green) during cell shuffling. Note that over time there are changes with regions going from a highly active VE-cadherin state to a more stable VE-cadherin (linear junctions). Cells undergoing shuffling present stronger VE-cadherin expression. (AVI 3232 kb)
Three-dimensional rotation of maximum projection of entire z-stack confocal microscopy images from eGFP-tagged (green) VE-cadherin embryoid bodies (green) counterstained with anti-Pecam1 (grey) and anti-Dll4 (red) antibodies, and nuclear staining (Dapi, blue). Dll4-positive cells show more irregular and vesicular VE-cadherin pattern compared to Dll4-negative cells. Some Dll4-vesicles are co-positive for VE-cadherin. (MOV 6137 kb)
Oscillating rearrangement under pathologically high VEGF levels in a wt vessel with differential Mechanism M1(A)M2(A) (related to Fig. 3).
Colour indicates individual cells. In the active phase all cells gain complex junctional shapes and act like a DAPT treated vessel. The inhibited phase shows cells have straighter junctions and barely move. (MPG 7722 kb)
Oscillating p-VEGFR-2 levels under pathologically high VEGF levels in a wt vessel with differential Mechanism M1(A)M2(A) (related to Fig. 3).
Colour indicates p-VEGFR-2 level (equivalent to endocytosed VE-cadherin internal signal) green = high, purple = low. (MPG 6732 kb)
Time-lapse confocal microscopy of a vascular sprout from embryoid bodies generated from 1:1 mix of DsRed (red) and YFP (green) expressing ES cells. The video depicts a sprouting tip cell aborting its invasion and integrating the immediate vessel segment, shuffling forward and conquering a new tip position in the nearby vascular sprout. This demonstrates the multifunctional behaviour of cells low in Notch as tip cells and shufflers in the sprout. (AVI 1337 kb)
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Bentley, K., Franco, C., Philippides, A. et al. The role of differential VE-cadherin dynamics in cell rearrangement during angiogenesis. Nat Cell Biol 16, 309–321 (2014). https://doi.org/10.1038/ncb2926
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