Experimental and computational models of neurite extension at a choice point in response to controlled diffusive gradients

Biofabrication of neural microphysiological systems using magnetic spheroid bioprinting

The high attrition rate of neuro-pharmaceuticals as they proceed to market necessitates the development of clinically-relevant in vitro neural microphysiological systems that can be utilized during the preclinical screening phase to assess the safety and efficacy of potential compounds. Historically, proposed models have adhered to two distinct approaches; those that are biologically relevant (e.g.-organoids, spheroids) or those that provide engineering control (e.g.-bioprinting, microfluidics). Separately, these approaches fail to fully recapitulate the complex hierarchical structure of the nervous system, limiting their clinical applications. Furthermore, the reliance on manual implementation present in many models fails to effectively scale up or satisfy the consistency standards required for widespread industry adoption. This work serves as a proof-of-concept for merging the two approaches to create a neural microphysiological system that overcomes their individual limitations. Spinal cord spheroids, fabricated using magnetic nanoparticles, are positioned in a three-dimensional hydrogel construct using magnetic bioprinting. Resulting constructs demonstrate both localized cell-cell interactions and long-distance projections that mimic in vivo structure. The use of magnetic nanoparticles for spheroid formation provides batch-to-batch consistency in size and shape and reduces the reliance on trained experimenters for accurate placing for culture. Taken together, this combination approach provides the first steps towards developing a simple approach for integrating spheroid, hydrogel culture, and bioprinting as an alternative to more specialized and expensive processes.

A Subtle Network Mediating Axon Guidance: Intrinsic Dynamic Structure of Growth Cone, Attractive and Repulsive Molecular Cues, and the Intermediate Role of Signaling Pathways

A fundamental feature of both early nervous system development and axon regeneration is the guidance of axonal projections to their targets in order to assemble neural circuits that control behavior. In the navigation process where the nerves grow toward their targets, the growth cones, which locate at the tips of axons, sense the environment surrounding them, including varies of attractive or repulsive molecular cues, then make directional decisions to adjust their navigation journey. The turning ability of a growth cone largely depends on its highly dynamic skeleton, where actin filaments and microtubules play a very important role in its motility. In this review, we summarize some possible mechanisms underlying growth cone motility, relevant molecular cues, and signaling pathways in axon guidance of previous studies and discuss some questions regarding directions for further studies.

Methods for fabrication and evaluation of a 3D microengineered model of myelinated peripheral nerve

OBJECTIVE

The cost and low success rates of the neurological drug development pipeline have diverted the pharmaceutical industry to 'nerve-on-a-chip' systems as preclinical models to streamline drug development. We present a novel micro-engineered 3D hydrogel platform for the culture of myelinated embryonic peripheral neural tissue to serve as an effective in vitro model for electrophysiological and histological analysis that could be adopted for preclinical testing.

APPROACH

Dorsal root ganglions (DRG) from 15 d old embryonic rats were cultured in 3D hydrogel platforms. The interaction between Schwann cells (SC) and neurons during axonal development and regeneration affects the direction of growth and the synthesis of myelin sheaths. Induction of myelination was performed with two approaches: the addition of exogenous SC and promoting migration of endogenous SC.

MAIN RESULTS

Histological analysis of the preparation utilizing exogenous SC showed aligned, highly fasciculated axonal growth with noticeable myelin sheaths around axons. Separately, electrophysiological testing of the preparation utilizing endogenous SC showed increased amplitude of the compound action potential and nerve conduction velocity in the presence of ascorbic acid (AA).

SIGNIFICANCE

This platform has immense potential to be a useful and translatable in vitro testing tool for drug discovery and myelination studies.

Model for Coordination of Microtubule and Actin Dynamics in Growth Cone Turning

In the developing nervous system, axons are guided to their synaptic targets by motile structures at the axon tip called growth cones, which reorganize their cytoskeleton in order to steer in response to chemotactic cues. Growth cone motility is mediated by an actin-adhesion “clutch” mechanism, in which mechanical attachment to a substrate, coupled with polarized actin growth, produces leading-edge protrusion. Several studies suggest that dynamic microtubules (MTs) in the growth cone periphery play an essential role in growth cone steering. It is not yet well-understood how the MT cytoskeleton and the dynamic actin-adhesion clutch system are coordinated to promote growth cone navigation. I introduce an experimentally motivated stochastic model of the dynamic reorganization of the growth cone cytoskeleton in response to external guidance cues. According to this model, asymmetric decoupling of MTs from actin retrograde flow leads to a local influx of MTs to the growth cone leading edge, and the leading-edge MT accumulation is amplified by positive feedback between MTs and the actin-adhesion clutch system. Local accumulation of MTs at the leading edge is hypothesized to increase actin adhesion to the substrate, which attenuates actin retrograde flow and promotes leading-edge protrusion. Growth cone alignment with the chemotactic gradient is predicted to be most effective for intermediate levels of sensitivity of the adhesion strength to the presence of leading-edge MTs. Quantitative predictions of the MT distribution and the local rate of retrograde actin flow will allow the hypothetical positive feedback mechanism to be experimentally tested.

Theoretical Models of Neural Development

Constructing a functioning nervous system requires the precise orchestration of a vast array of mechanical, molecular, and neural-activity-dependent cues. Theoretical models can play a vital role in helping to frame quantitative issues, reveal mathematical commonalities between apparently diverse systems, identify what is and what is not possible in principle, and test the abilities of specific mechanisms to explain the data. This review focuses on the progress that has been made over the last decade in our theoretical understanding of neural development.

Neural electrical activity and neural network growth

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization.