Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: Schemes of cytoneme-mediated cell signaling based on experimental evidence : (A) Type 1: Receiving cells emit cytonemes to collect the morphogen from producing cells. (B) Type 2: Producing cells emit cytonemes to deliver the morphogen to receiving cells. (C) Type 3: Both producing and receiving cells emit cytonemes to deliver and collet the morphogen respectively. (D) Frame of reference used to develop the mathematical equations. (E) Schematic representation of the cytoneme triangular dynamics. (F) Schematic representation of the cytoneme trapezoidal dynamics.

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques:

Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: (A) Wing imaginal disc cytonemes protruding from A (top left) and from P (top right) compartment cells marked with Ihog-RFP. Bottom panels show 3D reconstructions of a confocal Z-stack taken at the basal side of the tissue showing cytonemes protruding and from A (bottom left) and P (bottom right) compartment cells. (B) A confocal Z-stack taken from the apical to basal side of the abdominal histoblast epithelium with the A compartment marked with life-actin-RFP (red) and the P compartment marked with CD8GFP (green). (C) In vivo temporal sequence of abdominal histoblast cytonemes taken at one-minute intervals. Top image sequences show both A and P compartment labelled cytonemes (A in red, P in green), middle image sequences show a single channel of A compartment cytonemes, and bottom image sequences show the single channel of P compartment cytonemes. (D) Statistical violin plots of cytoneme length distribution in the A (blue) and the P (green) compartments in wing disc (left) and abdominal histoblast nest (right). Scale bars: 15μm.

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques: In Vivo, Sequencing

Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: (A) Confocal sections of Drosophila epithelia labeled with Hh : GFP BAC and EnhancerPtcRed . Top: abdominal histoblast nest. Bottom: imaginal wing disc. (B) Quantified data of the Hh gradient in both epithelia: wing disc (green) and abdominal histoblast nest (blue). (C) Comparison between the wing disc experimental gradient (green) and the predicted gradient estimated by our cytoneme model (blue). (D) Comparison between the abdominal histoblast nest experimental gradient (green) and the predicted gradient estimated by cytoneme model (blue). (E) Comparison between the wing disc experimental gradient (green) and the predicted gradients applying different models: cytoneme model (blue) and diffusion-degradation model (black). (F) Comparison between the abdominal histoblast experimental gradient (green) and the predicted gradients applying different models: cytoneme model (blue) and diffusion-degradation model with different diffusion coefficient (red 3 times smaller than black). Scale bars: 30μm.

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques: Labeling, Comparison, Diffusion-based Assay

Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: Reference simulation in red, simulations after modifying a specific parameter in blue (graded light to dark depends on the value) and experimental data in green. X) Left. Morphogen distribution for different cases, normalized to the maximum value of the reference case, along receiving cells including the expected variability per cell row (error bars). Right. Study of the number of contacts in the first row of receiving cells x 0 , normalized to the average value of the reference case: top, violin plots of 2000 simulations per case; bottom, green-color-coded matrix of p-values for the violin distributions. X’) Coefficient of variation per case in the first row of receiving cells x 0 (left). Green-color-coded matrix of p-values for violin distributions (right). X”) Distribution of contacts normalized to their maximum value to compare changes in gradient shape along receiving cells (left). Coefficient of the normalized distributions to study the scaling along receiving cells (right). (A) Simulations for different cell size/cytoneme length ratios (ϕ = 2.5 to 3.5 each 0.2 μm (blue), ϕ = 3 μm (red)). (B) Simulations for different number of producing cells rows involved in the signaling (Np = 1 to 14 (blue), Np = 15 (red)). (C) Simulations for different number of cytonemes per cell (ncyt = 1 to 3 (blue), ncyt = 4 (red)).

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques:

Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: Reference case in red, simulations after modifying a feature in blue and experimental data in green. X) Left. Morphogen distribution along receiving cells for different cases, normalized to the maximum value of the reference case, showing the expected variability per cell row (error bars). Right. Study of the number of contacts in the first row of receiving cells x 0 , normalized to the average value of the reference case. Top, violin plots of 2000 simulations per case. Bottom, green-color-coded matrix of p-values for the violin distributions. X’) Coefficient of variation per case in the first row of receiving cells x 0 (left). Green-color-coded matrix of p-values for violin distributions (right). X´´) Distribution of contacts normalized to their maximum value to compare changes in gradient shape along receiving cells (left). Coefficient of the normalized distributions to study the scaling along receiving cells (right). (A) Simulations for different cytoneme signaling type (type 3 in red and type1-2 in blue). (B) Simulations for different contact functions (type ψ ( μ ) in red and type ψ ( μ , x ) in blue). (C) Simulations of the hypothetical case of multiple contacts between cytonemes along the overlapping surface (single contact in blue, multiple contacts in red). (D) Simulations for different probability of contact ( μ = 40% to 80% each 20% in blue, μ = 100% in red).

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques:

Journal: PLoS Computational Biology

Article Title: Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling

doi: 10.1371/journal.pcbi.1009245

Figure Lengend Snippet: (A) Representative image of FRAP experiments in abdominal histoblast nests in which the signal is eliminated after photobleaching over a specific ROI. (B) Hh ( Hh : GFP BAC ) gradient profile shortly before bleaching in black and Hh signal recovery over time coded in a hot colormap; each step corresponds to 45 seconds. (C) Ptc ( EnhancerPtcRed ) expression profile shortly before bleaching in black and ptc signal recovery over time coded in a hot colormap, each step is 45 seconds. D) In silico signal evolution predicted for abdominal histoblast nests. E) A graphical comparison every 3 minutes between in silico simulations and experimental data. F) Simulations for cytonemes contacting while growing with a different proportion of triangular/trapezoidal cytoneme dynamics (10% triangles in light blue, 50% triangles in red, 90% triangles in dark blue). Scale bars: 15μm.

Article Snippet: Cytomorph was generated implementing the cytoneme model in Matlab language (MatlabR2015a).

Techniques: Expressing, In Silico, Comparison