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How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

Setty Y, Chen CC, Secrier M, Skoblov N, Kalamatianos D, Emmott S - BMC Syst Biol (2011)

Bottom Line: Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program.Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies.This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Science Laboratory, Microsoft Research, Cambridge, CB3 0FB, UK. yaki.setty@gmail.com

ABSTRACT

Background: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process.

Results: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration.

Conclusions: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

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DCX reduced activity experiment. A. In-silico migration in DCX-defective simulations. B. Histology of neuronal migration in the cortex of rats in DCX RNAi (reproduced with permission from [31]). C. Distribution of multipolar (blue) and bipolar (red) neurons over time (averaged over 10 different simulations). D. Zone occupancy as function of time (VZ/SVZ blue), IZ (green) and CP (red) (averaged over 10 different simulations).
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Figure 6: DCX reduced activity experiment. A. In-silico migration in DCX-defective simulations. B. Histology of neuronal migration in the cortex of rats in DCX RNAi (reproduced with permission from [31]). C. Distribution of multipolar (blue) and bipolar (red) neurons over time (averaged over 10 different simulations). D. Zone occupancy as function of time (VZ/SVZ blue), IZ (green) and CP (red) (averaged over 10 different simulations).

Mentions: DCX function is highly complex and implicates various mechanisms. One of its possible functions is that it acts as a motility regulator that increases glial guided migration [2,27-30]. DCX RNAi rats show disruptions in radial migration, forming a subcortical band consisting of multipolar neurons in the IZ [31,32]. In our model, DCX acts as a motility regulator that stimulates re-association with the glial fiber in multipolar neurons. When neuronal ability to activate DCX is reduced to the basal level, re-association of multipolar neurons with the glial fiber is less likely to occur. Consequently, in simulations, the bipolar migration stage was largely halted, neurons did not advance from the IZ to the CP and reduced accumulation in the CP occured. Simulations under reduced DCX activity displayed accumulation of multipolar neurons at the upper end of the IZ closer to the CP. A minority of the neurons reacted to the random basal activity level and adopted the bipolar state, allowing them to enter the CP (Figure 6A and the movie in Additional File 4). The emergent pattern in reduced DCX activity simulations is consistent with observations that DCX RNAi rats develop a subcortical band of multipolar neurons [1,31,32] (Figure 6B).


How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

Setty Y, Chen CC, Secrier M, Skoblov N, Kalamatianos D, Emmott S - BMC Syst Biol (2011)

DCX reduced activity experiment. A. In-silico migration in DCX-defective simulations. B. Histology of neuronal migration in the cortex of rats in DCX RNAi (reproduced with permission from [31]). C. Distribution of multipolar (blue) and bipolar (red) neurons over time (averaged over 10 different simulations). D. Zone occupancy as function of time (VZ/SVZ blue), IZ (green) and CP (red) (averaged over 10 different simulations).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3198702&req=5

Figure 6: DCX reduced activity experiment. A. In-silico migration in DCX-defective simulations. B. Histology of neuronal migration in the cortex of rats in DCX RNAi (reproduced with permission from [31]). C. Distribution of multipolar (blue) and bipolar (red) neurons over time (averaged over 10 different simulations). D. Zone occupancy as function of time (VZ/SVZ blue), IZ (green) and CP (red) (averaged over 10 different simulations).
Mentions: DCX function is highly complex and implicates various mechanisms. One of its possible functions is that it acts as a motility regulator that increases glial guided migration [2,27-30]. DCX RNAi rats show disruptions in radial migration, forming a subcortical band consisting of multipolar neurons in the IZ [31,32]. In our model, DCX acts as a motility regulator that stimulates re-association with the glial fiber in multipolar neurons. When neuronal ability to activate DCX is reduced to the basal level, re-association of multipolar neurons with the glial fiber is less likely to occur. Consequently, in simulations, the bipolar migration stage was largely halted, neurons did not advance from the IZ to the CP and reduced accumulation in the CP occured. Simulations under reduced DCX activity displayed accumulation of multipolar neurons at the upper end of the IZ closer to the CP. A minority of the neurons reacted to the random basal activity level and adopted the bipolar state, allowing them to enter the CP (Figure 6A and the movie in Additional File 4). The emergent pattern in reduced DCX activity simulations is consistent with observations that DCX RNAi rats develop a subcortical band of multipolar neurons [1,31,32] (Figure 6B).

Bottom Line: Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program.Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies.This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Science Laboratory, Microsoft Research, Cambridge, CB3 0FB, UK. yaki.setty@gmail.com

ABSTRACT

Background: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process.

Results: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration.

Conclusions: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

Show MeSH
Related in: MedlinePlus