There is now considerable evidence of the importance of mechanical cues in neuronal development and regeneration. Motivated by the difference in the mechanical properties of the tissue environment between the peripheral (PNS) and central (CNS) nervous systems, we compare substrate-stiffness-dependent outgrowth and traction forces from PNS (dorsal root ganglion (DRG)) and CNS (hippocampal) neurons. We show that neurites from DRG neurons display maximal outgrowth on substrates with a Young's modulus of ∼1000 Pa, whereas hippocampal neurite outgrowth is independent of substrate stiffness. Using traction force microscopy, we also find a substantial difference in growth cone traction force generation, with DRG growth cones exerting severalfold larger forces compared with hippocampal growth cones. The traction forces generated by DRG and hippocampal growth cones both increase with increasing stiffness, and DRG growth cones growing on substrates with a Young's modulus of 1000 Pa strengthen considerably after 18-30 h. Finally, we find that retrograde actin flow is almost three times faster in hippocampal growth cones than in DRG. Moreover, the density of paxillin puncta is significantly lower in hippocampal growth cones, suggesting that stronger substrate coupling of the DRG cytoskeleton is responsible for the remarkable difference in traction force generation. These findings reveal a differential adaptation of cytoskeletal dynamics to substrate stiffness in growth cones of different neuronal types, and highlight the potential importance of the mechanical properties of the cellular environment for neuronal navigation during embryonic development and nerve regeneration.

Axonal chemotaxis is believed to be important in wiring up the developing and regenerating nervous system, but little is known about how axons actually respond to molecular gradients. We report a new quantitative assay that allows the long-term response of axons to gradients of known and controllable shape to be examined in a three-dimensional gel. Using this assay, we show that axons may be nature's most-sensitive gradient detectors, but this sensitivity exists only within a narrow range of ligand concentrations. This assay should also be applicable to other biological processes that are controlled by molecular gradients, such as cell migration and morphogenesis.

Axon guidance by molecular gradients plays a crucial role in wiring up the nervous system. However, the mechanisms axons use to detect gradients are largely unknown. We first develop a Bayesian ''ideal observer'' analysis of gradient detection by axons, based on the hypothesis that a principal constraint on gradient detection is intrinsic receptor binding noise. Second, from this model, we derive an equation predicting how the degree of response of an axon to a gradient should vary with gradient steepness and absolute concentration. Third, we confirm this prediction quantitatively by performing the first systematic experimental analysis of how axonal response varies with both these quantities. These experiments demonstrate a degree of sensitivity much higher than previously reported for any chemotacting system. Together, these results reveal both the quantitative constraints that must be satisfied for effective axonal guidance and the computational principles that may be used by the underlying signal transduction pathways, and allow predictions for the degree of response of axons to gradients in a wide variety of in vivo and in vitro settings.axon guidance ͉ chemotaxis ͉ growth cone ͉ nerve growth factor ͉ nerve regeneration E ndogenous chemical gradients are a key source of information used by developing axons when wiring up the nervous system. Furthermore, artificially generated gradients are a potential therapy for restoring connectivity after neural injury. Many of the molecular gradients that direct axons in the developing nervous system have recently been identified, together with some of the signaling pathways through which they operate (1-8). However, our understanding of the mechanisms by which axons actually detect gradients remains qualitative. This limits our ability to predict both the response of axons when gradients are perturbed and the optimal parameters for promoting regrowth after injury.To be guided by a gradient, axons must be able to detect small spatial variations in receptor binding. This requires integrating signals from spatially distributed receptors to make a decision as to the direction of the gradient. Resources within the growth cone can then be marshaled appropriately by this information, for instance, via the production of steep gradients of intracellular signaling molecules (8). Although there is evidence for a role for gradients of molecules such as Ca 2ϩ in this latter step (9, 10), very little is known about the computations required to accurately make the initial decision.What constrains the ability of an axon to make a decision regarding gradient direction? Both experimental and computational work addressing chemotaxis in related systems such as bacteria, leukocytes, and Dictyostelium has identified the fundamental role of noise in limiting gradient perception. Noise can arise from low numbers of ligand molecules, from the stochastic nature of receptor binding, and from intracellular signaling pathways (11-16). Such constraints must also apply to axonal gradient sensing (17...

A new method for producing molecular gradients of arbitrary shape in thin three dimensional gels is described. Patterns are produced on the surface of the gel by printing with a micropump that dispenses small droplets of solution at controlled rates. The molecules in the solution rapidly diffuse into the gel and create a smooth concentration profile that is independent of depth. The pattern is relatively stable for long times, and its evolution can be accurately described by finite element modeling of the diffusion equation. As a demonstration of the method, direct measurements of protein gradients are performed by quantitative fluorescence microscopy. A complementary technique for measuring diffusion coefficients is also presented. This rapid, flexible, contactless approach to gradient generation is ideally suited for cell culture experiments to investigate the role of gradients of diffusible substances in processes such as chemotaxis, morphogenesis, and pattern formation, as well as for high-throughput screening of system responses to a wide range of chemical concentrations.

No abstract