Comparison of networks formed with mixed cells and cells with average properties.

<p><b>A</b>, <b>F</b>, and <b>K</b> morphologies for mixed tip (red) and stalk (gray) cells (<i>F</i>_tip = 0.5). <b>B</b>, <b>G</b>, and <b>L</b> morphologies for averaged cells (<i>F</i>_tip = 0.5). <b>C</b>-<b>E</b>, <b>H</b>-<b>J</b>, and <b>M</b>-<b>O</b> morphometrics for a range of tip cell fractions for both the control and mixed model. The morphometrics were calculated for 50 simulations at 10 000 MCS (error bars represent the standard deviation). p-values were obtained with a Welch’s t-test for the null hypothesis that the mean of mixed model and the control model are identical.</p

Effects of reducing tip cell chemoattractant sensitivity for varying NICD thresholds.

<p>Morphospace of the final morphologies (10 000 MCS) with varying tip cell chemoattractant sensitivities (<i>χ</i>(tip)) and NICD thresholds (Θ_NICD).</p

Parameter values for the angiogenesis and tip cell selection model.

<p>Underlined parameters are varied in the screen for tip cell behavior.</p

Overview of the angiogenesis model and the parameter search.

<p><b>A</b> Time-lapse of angiogenesis model behavior <b>B</b> For each parameter P that is tested in the parameter search a morphospace is created to compare the different parameter values for different tip cell fractions. <b>C</b> Each morphology is studied in detail to see if the sprout tips are occupied by tip cells (red). <b>D</b> Each row of morphologies is studied to find rows in which the morphologies differ, indicating that network formation depends on the tip cell fraction.</p

Effects of Apelin or APJ silencing in spheroid sprouting assays.

<p><b>A</b>-<b>F</b> Microscopy images of the WT and CD34- spheroids in VEGF-enriched collage after 24 hours. <b>G</b>-<b>H</b> Number of sprouts, relative to siNT treatment, after 24 hours for spheroids with mixed cells and CD34- spheroids. These metrics are the mean of the normalized, average number of sprouts of each replicate with the error bars depicting standard deviation. The * denotes <i>p</i> < 0.05, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159478#sec011" target="_blank">Materials and Methods</a> for details of the normalization and statistical analysis. <b>I</b>-<b>L</b> Example morphologies formed in the computational angiogenesis model (750 MCS); <b>(I-J)</b> model including tip cells (<i>θ</i>_<i>NICD</i> = 0.2, in absence (<b>I</b>) and in presence (<b>J</b>) of chemoattractant inhibition; <b>(K-L)</b> model with reduced tip cell number (<i>θ</i>_<i>NICD</i> = 0) in presence (<b>K</b>) and in absence (<b>M</b>) of chemoattractant inhibition. <b>M</b> Number of sprouts after 750 MCS for <i>n</i> = 20 simulations; error bars show the standard deviation; asterisks denote <i>p</i> < 0.05 for p-values obtained with Welch’s t-test in comparison with controls (no inhibition).</p

Effects of different tip and stalk cell properties on network morphology.

<p><b>A</b>-<b>F</b> Trends of compactness (black rectangles) and number of lacunae (blue circles) calculated with the morphologies at 10 000 MCS. For each data point 10 morphologies were analyzed and the error bars represent the standard deviation. p-values were obtained with a Welch’s t-test for the null hypothesis that the mean of the sample is identical to that of a reference with the nominal parameters listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159478#pone.0159478.t001" target="_blank">Table 1</a>. For <b>B</b> this reference is the data for tip cell fraction 1 and for all other graphs this is the data for tip cell fraction 0. <b>G</b>-<b>L</b> Morphologies after 10 000 MCS for each tested parameter value with <i>F</i>_tip = 0.2.</p

Effects of tip cell selection on network formation.

<p><b>A</b>-<b>F</b> Networks formed with varying fractions of predefined tip cells (<i>F</i>_tip) with <i>χ</i>(tip) = 400 at 10 000 MCS. <b>G</b>-<b>L</b> Networks formed with the tip cell selection model for varying NICD thresholds (Θ_NICD) at 10 000 MCS. <b>M</b> Standard deviation of lacuna area in a network after 10 000 MCS. <b>N</b>-<b>Q</b> Close up of the evolution of a network with 20% predefined tip cells (marked area in <b>B</b>). <b>R</b>-<b>T</b> Comparison of the morphometrics for networks formed with predefined and selected tip cells with reduced chemoattractant sensitivity (<i>χ</i>(tip) = 400) and network at 10 000 MCS. For the simulations with tip cell selection, the average tip cell fraction was calculated for each NICD threshold. For all plots (<b>M</b> and <b>R</b>-<b>T</b>) the values were averaged over 50 simulations and error bars depict the standard deviation.</p

Differences in cell properties can enable cells of one type to occupy sprout tips.

<p>The percentage of sprout tips occupied by at least one tip cell was calculated at 10 000 MCS and averaged over 50 simulations (error bars depict the standard deviation). In each simulation 20% of the cells were predefined as tip cells. For each simulation one tip cell parameter was changed, except for the control experiment where the nominal parameters were used for both tip and stalk cells. p-values were obtained with a one sided Welch’s t-test for the null hypothesis that the number of tip cells at the sprout tips is not larger than in the control simulation.</p

The CD34⁺ fraction of HMEC-1 cultures contains the VEGF-induced angiogenic sprouting activity.

<p>(A, left panel) Representative images of spheroids that were generated from HMEC-1 were either unsorted or FACS-sorted, based on CD34 cell surface expression (CD34^- and CD34⁺ populations). Spheroids were embedded in collagen gel supplemented with (<b>+</b>) or without (-) VEGF. Scale bar = 200 μm. (A, right panel) Flow cytometry dot plot demonstrating gating for HMEC-1 sorting based on CD34 expression. (B) The number of sprouts per spheroid and the mean sprout length were quantified using Image J. Error bars represent standard deviation. *Significantly different from unstimulated control (VEGF-) with P < 0.05.</p

Effect of CD34 silencing on sprouting, cell migration and invasion.

<p>(A, left panel) Representative images of spheroids that were generated from HMEC-1 transfected with either a non-targeting siRNA (siNT) or siCD34 and subsequently embedded in collagen gel in the presence or absence of VEGF-A. (A, right panel) Spheroids were analyzed at 24 h after embedding and the number of sprouts per spheroid and average sprout length were quantified using Image J. Results were expressed relative to values of siNT transfected cells without VEGF. (B, left panel) siNT- and siCD34-transfected HMEC-1 were grown until confluent. Scratches were made using a pipette tip and images were taken at 0 and 6 h after scratching. (B, right panel) The percentage of width of the scratch filled with cells was quantified over time. (C, left panel) Representative images of HMEC-1 transfected with siNT or siCD34, located at the lower side of the Boyden filter after invasion through Matrigel visualized by DNA staining (i,iii) or Giemsa (ii,iv) staining at 20 h after seeding. (C, right panel) Cells invading the Matrigel were quantified by counting the number of nuclei per microscopic field. Error bars represent standard deviation, except for Fig 3C (right panel) where they represent 95% confidence interval; *Significantly different from siNT control with P < 0.05.</p