Axon growth regulation by a bistable molecular switch

Can repetitive mechanical motion cause structural damage to axons?

Biological structures have evolved to very efficiently generate, transmit, and withstand mechanical forces. These biological examples have inspired mechanical engineers for centuries and led to the development of critical insights and concepts. However, progress in mechanical engineering also raises new questions about biological structures. The past decades have seen the increasing study of failure of engineered structures due to repetitive loading, and its origin in processes such as materials fatigue. Repetitive loading is also experienced by some neurons, for example in the peripheral nervous system. This perspective, after briefly introducing the engineering concept of mechanical fatigue, aims to discuss the potential effects based on our knowledge of cellular responses to mechanical stresses. A particular focus of our discussion are the effects of mechanical stress on axons and their cytoskeletal structures. Furthermore, we highlight the difficulty of imaging these structures and the promise of new microscopy techniques. The identification of repair mechanisms and paradigms underlying long-term stability is an exciting and emerging topic in biology as well as a potential source of inspiration for engineers.

Nonlinear Growth Dynamics of Neuronal Cells Cultured on Directional Surfaces

During the development of the nervous system, neuronal cells extend axons and dendrites that form complex neuronal networks, which are essential for transmitting and processing information. Understanding the physical processes that underlie the formation of neuronal networks is essential for gaining a deeper insight into higher-order brain functions such as sensory processing, learning, and memory. In the process of creating networks, axons travel towards other recipient neurons, directed by a combination of internal and external cues that include genetic instructions, biochemical signals, as well as external mechanical and geometrical stimuli. Although there have been significant recent advances, the basic principles governing axonal growth, collective dynamics, and the development of neuronal networks remain poorly understood. In this paper, we present a detailed analysis of nonlinear dynamics for axonal growth on surfaces with periodic geometrical patterns. We show that axonal growth on these surfaces is described by nonlinear Langevin equations with speed-dependent deterministic terms and gaussian stochastic noise. This theoretical model yields a comprehensive description of axonal growth at both intermediate and long time scales (tens of hours after cell plating), and predicts key dynamical parameters, such as speed and angular correlation functions, axonal mean squared lengths, and diffusion (cell motility) coefficients. We use this model to perform simulations of axonal trajectories on the growth surfaces, in turn demonstrating very good agreement between simulated growth and the experimental results. These results provide important insights into the current understanding of the dynamical behavior of neurons, the self-wiring of the nervous system, as well as for designing innovative biomimetic neural network models.

Mechanics of axon growth and damage: A systematic review of computational models

Normal axon development depends on the action of mechanical forces both generated within the cytoskeleton and outside the cell, but forces of large magnitude or rate cause damage instead. Computational models aid scientists in studying the role of mechanical forces in axon growth and damage. These studies use simulations to evaluate how different sources of force generation within the cytoskeleton interact with each other to regulate axon elongation and retraction. Furthermore, mathematical models can help optimize externally applied tension to promote axon growth without causing damage. Finally, scientists also use simulations of axon damage to investigate how forces are distributed among different components of the axon and how the tissue surrounding an axon influences its susceptibility to injury. In this review, we discuss how computational studies complement experimental studies in the areas of axon growth, regeneration, and damage.

Force: A messenger of axon outgrowth

The axon is a sophisticated macromolecular machine composed of interrelated parts that transmit signals like spur gears transfer motion between parallel shafts. The growth cone is a fine sensor that integrates mechanical and chemical cues and transduces these signals through the generation of a traction force that pushes the tip and pulls the axon shaft forward. The axon shaft, in turn, senses this pulling force and transduces this signal in an orchestrated response, coordinating cytoskeleton remodeling and intercalated mass addition to sustain and support the advancing of the tip. Extensive research suggests that the direct application of active force is per se a powerful inducer of axon growth, potentially bypassing the contribution of the growth cone. This review provides a critical perspective on current knowledge of how the force is a messenger of axon growth and its mode of action for controlling navigation, including aspects that remain unclear. It also focuses on novel approaches and tools designed to mechanically manipulate axons, and discusses their implications in terms of potential novel therapies for re-wiring the nervous system.

A Stay in Friedrich Bonhoeffer's Lab in Tubingen in the Mid-eighties

The main focus of research for which Friedrich Bonhoeffer's work is known in the Neuroscience community was pioneer experiments on how axonal projections could organize into "maps", what mechanisms are involved in axon guidance and involve gradients of guiding molecules, and isolation of the first such molecules, e.g. RAGS (ephrin A5) and RGM (repulsive guidance molecule). Other papers have described in detail these contributions as well as Friedrich Bonhoeffer's personality. In the mid-eighties, I made a 2-year stay in his lab and initiated a line of research on development of binocular connections in Mammals, particularly the guidance of retinal fibers to one or the other side of the brain. In this paper I recall these circumstances as they pertain to Neuroscience as it stood at the time, and explain as best as I can how his lab was a conducive setting for the discoveries made there and how Friedrich Bonhoeffer acted for me as a scientist and a tutor.

A general hypothesis of multistable systems in pathophysiology

Despite intensive investigations numerous diseases remain etiologically puzzling and recalcitrant to treatments. A hypothesis is proposed here assuming that these difficulties are due to an unsuitable approach to the mechanisms of life, which is subjugated by an apparent complexity and fails to grasp the uniformity that lays behind. The stability of metabolism, despite the enormous complex of chemical reactions, suggests that reciprocal control is a prerequisite of life. Negative feedback loops have been known for a long time to maintain homeostasis, while more recently, different life processes involved in transitions or changes have been modeled by positive loops giving rise to bistable switches, also including various diseases. The present hypothesis makes a generalization, by assuming that any functional element of a biological system is involved in a positive or a negative feedback loop. Consequently, the hypothesis holds that the starting mechanism of any disease that affects a healthy human can be conceptually reduced to a bistable or multistationary loop system, thus providing a unifying model leading to the discovery of critical therapeutic targets.

A general theory of multistable systems in pathophysiology

Despite intensive investigations numerous diseases remain etiologically puzzling and recalcitrant to treatments. A theory is proposed here assuming that these difficulties are due to an unsuitable approach to the mechanisms of life, which is subjugated by an apparent complexity and fails to grasp the uniformity that lays behind. The stability of metabolism, despite the enormous complex of chemical reactions, suggests that reciprocal control is a prerequisite of life. Negative feedback loops have been known for a long time to maintain homeostasis, while more recently, different life processes involved in transitions or changes have been modeled by positive loops giving rise to bistable switches, also including various diseases. The present theory makes a generalization, by assuming that any functional element of a biological system is involved in a positive or a negative feedback loop. Consequently, the theory holds that the starting mechanism of any disease that affects a healthy human can be conceptually reduced to a bistable or multistationary loop system, thus providing a unifying model leading to the discovery of critical therapeutic targets.

A general hypothesis of multistable systems in pathophysiology

Despite intensive investigations numerous diseases remain etiologically puzzling and recalcitrant to treatments. A hypothesis is proposed here assuming that these difficulties are due to an unsuitable approach to the mechanisms of life, which is subjugated by an apparent complexity and fails to grasp the uniformity that lays behind. The stability of metabolism, despite the enormous complex of chemical reactions, suggests that reciprocal control is a prerequisite of life. Negative feedback loops have been known for a long time to maintain homeostasis, while more recently, different life processes involved in transitions or changes have been modeled by positive loops giving rise to bistable switches, also including various diseases. The present hypothesis makes a generalization, by assuming that any functional element of a biological system is involved in a positive or a negative feedback loop. Consequently, the hypothesis holds that the starting mechanism of any disease that affects a healthy human can be conceptually reduced to a bistable or multistationary loop system, thus providing a unifying model leading to the discovery of critical therapeutic targets.

With the Permission of Microtubules: An Updated Overview on Microtubule Function During Axon Pathfinding

During the establishment of neural circuitry axons often need to cover long distances to reach remote targets. The stereotyped navigation of these axons defines the connectivity between brain regions and cellular subtypes. This chemotrophic guidance process mostly relies on the spatio-temporal expression patterns of extracellular proteins and the selective expression of their receptors in projection neurons. Axon guidance is stimulated by guidance proteins and implemented by neuronal traction forces at the growth cones, which engage local cytoskeleton regulators and cell adhesion proteins. Different layers of guidance signaling regulation, such as the cleavage and processing of receptors, the expression of co-receptors and a wide variety of intracellular cascades downstream of receptors activation, have been progressively unveiled. Also, in the last decades, the regulation of microtubule (MT) assembly, stability and interactions with the submembranous actin network in the growth cone have emerged as crucial effector mechanisms in axon pathfinding. In this review, we will delve into the intracellular signaling cascades downstream of guidance receptors that converge on the MT cytoskeleton of the growing axon. In particular, we will focus on the microtubule-associated proteins (MAPs) network responsible of MT dynamics in the axon and growth cone. Complementarily, we will discuss new evidences that connect defects in MT scaffold proteins, MAPs or MT-based motors and axon misrouting during brain development.

BCNNM: A Framework for in silico Neural Tissue Development Modeling

Cerebral (“brain”) organoids are high-fidelity in vitro cellular models of the developing brain, which makes them one of the go-to methods to study isolated processes of tissue organization and its electrophysiological properties, allowing to collect invaluable data for in silico modeling neurodevelopmental processes. Complex computer models of biological systems supplement in vivo and in vitro experimentation and allow researchers to look at things that no laboratory study has access to, due to either technological or ethical limitations. In this paper, we present the Biological Cellular Neural Network Modeling (BCNNM) framework designed for building dynamic spatial models of neural tissue organization and basic stimulus dynamics. The BCNNM uses a convenient predicate description of sequences of biochemical reactions and can be used to run complex models of multi-layer neural network formation from a single initial stem cell. It involves processes such as proliferation of precursor cells and their differentiation into mature cell types, cell migration, axon and dendritic tree formation, axon pathfinding and synaptogenesis. The experiment described in this article demonstrates a creation of an in silico cerebral organoid-like structure, constituted of up to 1 million cells, which differentiate and self-organize into an interconnected system with four layers, where the spatial arrangement of layers and cells are consistent with the values of analogous parameters obtained from research on living tissues. Our in silico organoid contains axons and millions of synapses within and between the layers, and it comprises neurons with high density of connections (more than 10). In sum, the BCNNM is an easy-to-use and powerful framework for simulations of neural tissue development that provides a convenient way to design a variety of tractable in silico experiments.

Abl signaling directs growth of a pioneer axon in Drosophila by shaping the intrinsic fluctuations of actin

The fundamental problem in axon growth and guidance is understanding how cytoplasmic signaling modulates the cytoskeleton to produce directed growth cone motility. Live imaging of the TSM1 axon of the developing Drosophila wing has shown that the essential role of the core guidance signaling molecule, Abelson (Abl) tyrosine kinase, is to modulate the organization and spatial localization of actin in the advancing growth cone. Here, we dissect in detail the properties of that actin organization and its consequences for growth cone morphogenesis and motility. We show that advance of the actin mass in the distal axon drives the forward motion of the dynamic filopodial domain that defines the growth cone. We further show that Abl regulates both the width of the actin mass and its internal organization, spatially biasing the intrinsic fluctuations of actin to achieve net advance of the actin, and thus of the dynamic filopodial domain of the growth cone, while maintaining the essential coherence of the actin mass itself. These data suggest a model whereby guidance signaling systematically shapes the intrinsic, stochastic fluctuations of actin in the growth cone to produce axon growth and guidance.

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.