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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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Lis1 reduced activity experiment. A. In-silico migration in Lis1-defective simulations. B. Histology of neuronal migration in the cortex of a Lis1 RNAi in mice (reproduced with permission from [24]). 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 4: Lis1 reduced activity experiment. A. In-silico migration in Lis1-defective simulations. B. Histology of neuronal migration in the cortex of a Lis1 RNAi in mice (reproduced with permission from [24]). 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: In simulations under reduced Lis1 activity, neuroblasts, once proliferated from the mother progenitor glial cell, entered the multipolar stage shortly after proliferation and dissociated from the glial fiber, rather than progressing normally along the fiber. Thus, reduced Lis1 activity shortens the duration over which neuroblasts remain associated with the glial fiber, and hastens multipolar migration. Consequently, the neuron population accumulated at the SVZ/VZ and the lower IZ and rarely migrated to the CP (Figure 4A and the movie in Additional File 2). This migration pattern that emerged in Lis1 reduced activity simulations concurs with the morphology observed in Lis1 RNAi in mice [21] in which neurons accumulate at the lower parts of the brain section closer to the VZ/SVZ (Figure 4B).


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)

Lis1 reduced activity experiment. A. In-silico migration in Lis1-defective simulations. B. Histology of neuronal migration in the cortex of a Lis1 RNAi in mice (reproduced with permission from [24]). 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 4: Lis1 reduced activity experiment. A. In-silico migration in Lis1-defective simulations. B. Histology of neuronal migration in the cortex of a Lis1 RNAi in mice (reproduced with permission from [24]). 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: In simulations under reduced Lis1 activity, neuroblasts, once proliferated from the mother progenitor glial cell, entered the multipolar stage shortly after proliferation and dissociated from the glial fiber, rather than progressing normally along the fiber. Thus, reduced Lis1 activity shortens the duration over which neuroblasts remain associated with the glial fiber, and hastens multipolar migration. Consequently, the neuron population accumulated at the SVZ/VZ and the lower IZ and rarely migrated to the CP (Figure 4A and the movie in Additional File 2). This migration pattern that emerged in Lis1 reduced activity simulations concurs with the morphology observed in Lis1 RNAi in mice [21] in which neurons accumulate at the lower parts of the brain section closer to the VZ/SVZ (Figure 4B).

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