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A frequency-dependent decoding mechanism for axonal length sensing.

Bressloff PC, Karamched BR - Front Cell Neurosci (2015)

Bottom Line: We have recently developed a mathematical model of axonal length sensing in which a system of delay differential equations describe a chemical signaling network.If the protein output were thresholded, then this could provide a mechanism for axonal length control.We analyze the robustness of such a mechanism in the presence of intrinsic noise due to finite copy numbers within the gene network.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Utah Salt Lake City, UT, USA.

ABSTRACT
We have recently developed a mathematical model of axonal length sensing in which a system of delay differential equations describe a chemical signaling network. We showed that chemical oscillations emerge due to delayed negative feedback via a Hopf bifurcation, resulting in a frequency that is a monotonically decreasing function of axonal length. In this paper, we explore how frequency-encoding of axonal length can be decoded by a frequency-modulated gene network. If the protein output were thresholded, then this could provide a mechanism for axonal length control. We analyze the robustness of such a mechanism in the presence of intrinsic noise due to finite copy numbers within the gene network.

No MeSH data available.


Schematic diagram of the bidirectional motor-transport mechanism for axonal length sensing hypothesized by Rishal et al. (2012). A kinesin-based anterograde signal activates a dynein-based retrograde signal that itself represses the anterograde signal via negative feedback. The frequency of the resulting oscillatory retrograde signal decreases with axonal growth.
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Figure 1: Schematic diagram of the bidirectional motor-transport mechanism for axonal length sensing hypothesized by Rishal et al. (2012). A kinesin-based anterograde signal activates a dynein-based retrograde signal that itself represses the anterograde signal via negative feedback. The frequency of the resulting oscillatory retrograde signal decreases with axonal growth.

Mentions: Recently, a mechanism for axonal length sensing based on bidirectional motor transport was proposed by Rishal et al. (2012), which is distinct from the aforementioned mechanisms. A schematic illustration of the motor-based model is shown in Figure 1. A signal is produced at the cell body and is subsequently carried by kinesin motors to the tip of the growing axon, where it activates the production of another chemical signal. The latter is transported by dynein motors back to the cell body, where it inhibits the production of the original chemical signal via negative feedback. Once the axon grows past some critical length, the amount of inhibitory chemical signal located at the cell body begins to oscillate with a frequency that decreases as axonal length increases. If axonal growth is correlated with this frequency, then spatial information regarding length of the axon can be communicated to the cell body, where frequency-dependent activation of transcription factors could regulate axonal growth (Cai et al., 2008). Computer simulations of this mechanism provided results that are consistent with what was proposed in Rishal et al. (2012). An important prediction of these simulations is that reducing either anterograde or retrograde signals by partial knockdown of kinesin or dynein motor activity should increase axonal length. This prediction has been confirmed experimentally in peripheral sensory neurons (Rishal et al., 2012). Note that a previous model of Kam et al. (2009) is inconsistent with the experimental data. The earlier model assumes that the unidirectional transport of a retrograde signal by dynein motors maintains axonal growth until the signal at the cell body becomes too weak due to a constant rate of signal loss en route. In this case, the partial knockdown of motor activity would lead to shorter axons. Hence the experimental results provide circumstantial evidence for frequency-encoded axonal length.


A frequency-dependent decoding mechanism for axonal length sensing.

Bressloff PC, Karamched BR - Front Cell Neurosci (2015)

Schematic diagram of the bidirectional motor-transport mechanism for axonal length sensing hypothesized by Rishal et al. (2012). A kinesin-based anterograde signal activates a dynein-based retrograde signal that itself represses the anterograde signal via negative feedback. The frequency of the resulting oscillatory retrograde signal decreases with axonal growth.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508512&req=5

Figure 1: Schematic diagram of the bidirectional motor-transport mechanism for axonal length sensing hypothesized by Rishal et al. (2012). A kinesin-based anterograde signal activates a dynein-based retrograde signal that itself represses the anterograde signal via negative feedback. The frequency of the resulting oscillatory retrograde signal decreases with axonal growth.
Mentions: Recently, a mechanism for axonal length sensing based on bidirectional motor transport was proposed by Rishal et al. (2012), which is distinct from the aforementioned mechanisms. A schematic illustration of the motor-based model is shown in Figure 1. A signal is produced at the cell body and is subsequently carried by kinesin motors to the tip of the growing axon, where it activates the production of another chemical signal. The latter is transported by dynein motors back to the cell body, where it inhibits the production of the original chemical signal via negative feedback. Once the axon grows past some critical length, the amount of inhibitory chemical signal located at the cell body begins to oscillate with a frequency that decreases as axonal length increases. If axonal growth is correlated with this frequency, then spatial information regarding length of the axon can be communicated to the cell body, where frequency-dependent activation of transcription factors could regulate axonal growth (Cai et al., 2008). Computer simulations of this mechanism provided results that are consistent with what was proposed in Rishal et al. (2012). An important prediction of these simulations is that reducing either anterograde or retrograde signals by partial knockdown of kinesin or dynein motor activity should increase axonal length. This prediction has been confirmed experimentally in peripheral sensory neurons (Rishal et al., 2012). Note that a previous model of Kam et al. (2009) is inconsistent with the experimental data. The earlier model assumes that the unidirectional transport of a retrograde signal by dynein motors maintains axonal growth until the signal at the cell body becomes too weak due to a constant rate of signal loss en route. In this case, the partial knockdown of motor activity would lead to shorter axons. Hence the experimental results provide circumstantial evidence for frequency-encoded axonal length.

Bottom Line: We have recently developed a mathematical model of axonal length sensing in which a system of delay differential equations describe a chemical signaling network.If the protein output were thresholded, then this could provide a mechanism for axonal length control.We analyze the robustness of such a mechanism in the presence of intrinsic noise due to finite copy numbers within the gene network.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Utah Salt Lake City, UT, USA.

ABSTRACT
We have recently developed a mathematical model of axonal length sensing in which a system of delay differential equations describe a chemical signaling network. We showed that chemical oscillations emerge due to delayed negative feedback via a Hopf bifurcation, resulting in a frequency that is a monotonically decreasing function of axonal length. In this paper, we explore how frequency-encoding of axonal length can be decoded by a frequency-modulated gene network. If the protein output were thresholded, then this could provide a mechanism for axonal length control. We analyze the robustness of such a mechanism in the presence of intrinsic noise due to finite copy numbers within the gene network.

No MeSH data available.