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A hybrid computational model to predict chemotactic guidance of growth cones.

Roccasalvo IM, Micera S, Sergi PN - Sci Rep (2015)

Bottom Line: In this model, the key role of intracellular calcium was phenomenologically modelled through a non standard Gierer-Meinhardt system, as a crucial factor influencing the growth cone behaviour both in regular and complex conditions.The reliability of this approach was proven by using quantitative metrics, numerically supporting the similarity between in silico and biological results in regular conditions (control and attraction).Finally, the model was able to qualitatively predict emergent and counterintuitive phenomena resulting from complex boundary conditions.

View Article: PubMed Central - PubMed

Affiliation: The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.

ABSTRACT
The overall strategy used by growing axons to find their correct paths during the nervous system development is not yet completely understood. Indeed, some emergent and counterintuitive phenomena were recently described during axon pathfinding in presence of chemical gradients. Here, a novel computational model is presented together with its ability to reproduce both regular and counterintuitive axonal behaviours. In this model, the key role of intracellular calcium was phenomenologically modelled through a non standard Gierer-Meinhardt system, as a crucial factor influencing the growth cone behaviour both in regular and complex conditions. This model was able to explicitly reproduce neuritic paths accounting for the complex interplay between extracellular and intracellular environments, through the sensing capability of the growth cone. The reliability of this approach was proven by using quantitative metrics, numerically supporting the similarity between in silico and biological results in regular conditions (control and attraction). Finally, the model was able to qualitatively predict emergent and counterintuitive phenomena resulting from complex boundary conditions.

No MeSH data available.


Counterintuitive predictions.Left side: cartoons of different biological behaviours of GC in presence of attractive (blue) and repulsive (red) cues for different extracellular concentration of calcium ([Ca2+]e). Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. Right side: qualitative predictions of the model of the biological behaviours. Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. The traces of the growth cone trajectories (n = 3, for each case) are shown.
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f4: Counterintuitive predictions.Left side: cartoons of different biological behaviours of GC in presence of attractive (blue) and repulsive (red) cues for different extracellular concentration of calcium ([Ca2+]e). Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. Right side: qualitative predictions of the model of the biological behaviours. Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. The traces of the growth cone trajectories (n = 3, for each case) are shown.

Mentions: In silico axons were implemented within the multiphysics framework of CX3D to account for the global effect of attractive/repulsive chemical sources coupled with the different levels of [Ca2+]e39. The capability of the model to reproduce counterintuitive responses of biological axons was then tested. In Fig. 4, the observed biological behaviours are schematically represented on the left side of the panel, while in silico traces (n = 3, for each case) are shown on the right side.


A hybrid computational model to predict chemotactic guidance of growth cones.

Roccasalvo IM, Micera S, Sergi PN - Sci Rep (2015)

Counterintuitive predictions.Left side: cartoons of different biological behaviours of GC in presence of attractive (blue) and repulsive (red) cues for different extracellular concentration of calcium ([Ca2+]e). Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. Right side: qualitative predictions of the model of the biological behaviours. Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. The traces of the growth cone trajectories (n = 3, for each case) are shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4471899&req=5

f4: Counterintuitive predictions.Left side: cartoons of different biological behaviours of GC in presence of attractive (blue) and repulsive (red) cues for different extracellular concentration of calcium ([Ca2+]e). Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. Right side: qualitative predictions of the model of the biological behaviours. Upper panel: regular attraction towards an attractive cue. Upper-middle panel: counterintuitive behaviour, that is GC repulsion away from an attractive cue. Lower-middle panel: regular behaviour, that is GC repulsion away from a repulsive cue. Lower panel: counterintuitive behaviour, that is GC attraction towards a repulsive cue. The traces of the growth cone trajectories (n = 3, for each case) are shown.
Mentions: In silico axons were implemented within the multiphysics framework of CX3D to account for the global effect of attractive/repulsive chemical sources coupled with the different levels of [Ca2+]e39. The capability of the model to reproduce counterintuitive responses of biological axons was then tested. In Fig. 4, the observed biological behaviours are schematically represented on the left side of the panel, while in silico traces (n = 3, for each case) are shown on the right side.

Bottom Line: In this model, the key role of intracellular calcium was phenomenologically modelled through a non standard Gierer-Meinhardt system, as a crucial factor influencing the growth cone behaviour both in regular and complex conditions.The reliability of this approach was proven by using quantitative metrics, numerically supporting the similarity between in silico and biological results in regular conditions (control and attraction).Finally, the model was able to qualitatively predict emergent and counterintuitive phenomena resulting from complex boundary conditions.

View Article: PubMed Central - PubMed

Affiliation: The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.

ABSTRACT
The overall strategy used by growing axons to find their correct paths during the nervous system development is not yet completely understood. Indeed, some emergent and counterintuitive phenomena were recently described during axon pathfinding in presence of chemical gradients. Here, a novel computational model is presented together with its ability to reproduce both regular and counterintuitive axonal behaviours. In this model, the key role of intracellular calcium was phenomenologically modelled through a non standard Gierer-Meinhardt system, as a crucial factor influencing the growth cone behaviour both in regular and complex conditions. This model was able to explicitly reproduce neuritic paths accounting for the complex interplay between extracellular and intracellular environments, through the sensing capability of the growth cone. The reliability of this approach was proven by using quantitative metrics, numerically supporting the similarity between in silico and biological results in regular conditions (control and attraction). Finally, the model was able to qualitatively predict emergent and counterintuitive phenomena resulting from complex boundary conditions.

No MeSH data available.