Axon guidance

Axons often follow very precise paths in the nervous system, and how they manage to find their way so accurately is an area of ongoing research.

[1] A combination of genetic and biochemical methods (see below) has led to the discovery of several important classes of axon guidance molecules and their receptors:[2] In addition, many other classes of extracellular molecules are used by growth cones to navigate properly: Growing axons rely on a variety of guidance cues in deciding upon a growth pathway.

The growth cones of extending axons process these cues in an intricate system of signal interpretation and integration, in order to ensure appropriate guidance.

For instance, in Xenopus retinotectal connection systems, the pioneer axons of retinal ganglion cells originate from the dorsal part of the eye.

[7] Studies in zebrafish retina showed that inhibiting neural differentiation of early retinal progenitors prevents axons from exiting the eye.

[12] These findings indicate that transitory cell populations can serve an important guidance role even though they have no function in the mature nervous system.

The earliest descriptions of the axonal growth cone were made by the Spanish neurobiologist Santiago Ramón y Cajal in the late 19th century.

In genetic model organisms like mice, zebrafish, nematodes, and fruit flies, scientists can generate mutations and see whether and how they cause axons to make errors in navigation.

Embryos of these species are easy to obtain and, unlike mammals, develop externally and are easily accessible to experimental manipulation.

However, after crossing (contralaterally), the same growth cone must become repelled or lose attraction to the midline and reinterpret the environment to locate the correct target tissue.

[15] In the spinal cord of vertebrates, commissural neurons from the dorsal regions project downward toward the ventral floor plate.

Explanted neurons grown in culture would respond to exogenously supplied Slit according to whether or not they had contacted floor plate tissue.

The neurobiologist Roger Sperry proposed a prescient model for topographic mapping mediated by what he called molecular "tags."

Meanwhile, in the target of the retinal cells (the optic tectum), Ephrin ligands are organized in a similar gradient: high posterior to low anterior.

Researchers used the chick to biochemically purify components from the tectum that showed specific activity against retinal axons in culture.

Most axon guidance receptors activate signal transduction cascades that ultimately lead to reorganization of the cytoskeleton and adhesive properties of the growth cone, which together underlie the motility of all cells.

In fact, commissural axon growth responses have been shown to be attracted, repressed, or silenced in the presence of Netrin activated DCC receptor.

The ability for axons to navigate and adjust responses to various extracellular cues, at long distances from the cell body, has prompted investigators to look at the intrinsic properties of growth cones.

Recent studies reveal that guidance cues can influence spatiotemporal changes in axons by modulating the local translation and degradation of proteins in growth cones.

In fact, in retinal ganglion cells (RGCs) with soma severed axons, growth cones continue to track and innervate the tectum of Xenopus embryos.

[20] To accommodate this activity, growth cones are believed to pool mRNAs that code for receptors and intracellular signaling proteins involved in cytoskeleton remodeling.

[21] In Xenopus retinotectal projection systems, the expression of these proteins has been shown to be influenced by guidance cues and the subsequent activation of local translation machinery.

[24] As a result, studies suggest that local protein expression is a convenient mechanism to explain the rapid, dynamic, and autonomous nature of growth cone advancement in response to guidance molecules.

The connectome, or the braingraph, can be constructed from diffusion MRI data: the vertices of the graph correspond to anatomically labelled brain areas, and two such vertices, say u and v, are connected by an edge if the tractography phase of the data processing finds an axonal fiber that connects the two areas, corresponding to u and v. Numerous braingraphs, computed from the Human Connectome Project can be downloaded from the http://braingraph.org site.

The surprising observation is that the appearance of the edges is far from random: it resembles a growing, complex structure, like a tree or a shrub (visualized on this animation on YouTube.